GM crops: global socio-economic andenvironmental impacts 1996-2020

Graham Brookes
PG Economics Ltd, UK
Dorchester, UK https://www.pgeconomics.co.uk/ October 2022

GM crop impact: 1996-2020

Table of contents
Foreword........................................................................................................................................................7
Executive summary and conclusions .........................................................................................................8
1 Introduction ..............................................................................................................................................18
1.1 Objectives ..........................................................................................................................................18
1.2 Methodology .....................................................................................................................................18
1.3 Structure of report ............................................................................................................................19
2 Global context of GM crops....................................................................................................................20
2.1 Global plantings ...............................................................................................................................20
2.2 Plantings by crop and trait ..............................................................................................................20
2.2.1 By crop ........................................................................................................................................20
2.2.2 By trait ........................................................................................................................................222.2.3 By country ..................................................................................................................................22
3 The farm level economic impact of GM crops 1996-2020 ...................................................................25
3.1 Herbicide tolerant crops ..................................................................................................................27
3.1.1 GM HT soybeans.......................................................................................................................28
3.1.2 Insect resistant soybeans ..........................................................................................................41
3.1.3 Herbicide tolerant maize ..........................................................................................................41
3.1.4 Herbicide tolerant cotton .........................................................................................................47
3.1.5 Herbicide tolerant canola .........................................................................................................49
3.1.6 GM herbicide tolerant (GM HT) sugar beet ..........................................................................55
3.2 Insect resistant crops ........................................................................................................................58
3.2.1 GM insect resistant43F (GM IR) maize ..................................................................................58
3.2.2 Insect resistant (Bt) cotton (GM IR) ........................................................................................66
3.3 Other GM crops ................................................................................................................................75
3.3.1 Maize/corn rootworm resistance ............................................................................................75
3.3.2 Virus resistant papaya ..............................................................................................................76
3.3.3 Virus resistant squash ..............................................................................................................77
3.3.4 Drought tolerant maize ............................................................................................................77
3.3.5 Insect resistant brinjal ...............................................................................................................77
3.3.6 Other crops ................................................................................................................................78
3.4 Indirect (non-pecuniary) farm level economic impacts ..............................................................79
3.5 Production effects of the technology .............................................................................................81
4 The environmental impact of GM crops...............................................................................................83
4.1 Use of insecticides and herbicides .................................................................................................83
4.1.1 GM herbicide tolerant (to glyphosate) soybeans (GM HT) .................................................90
4.1.2 GM herbicide tolerant (to glyphosate) and insect resistant soybeans (Intacta) ..............102
4.1.3 GM Herbicide tolerant (GM HT) maize ...............................................................................103
4.1.4 GM HT Herbicide tolerant (GM HT) cotton........................................................................110
4.1.5 GM Herbicide tolerant (GM HT) canola ..............................................................................117
4.1.6 GM HT sugar beet...................................................................................................................120
4.1.7 GM IR maize ............................................................................................................................121
4.1.8 GM insect resistant (GM IR) cotton ......................................................................................127
4.1.9 Other environmental impacts - development of herbicide resistant weeds and weed
shifts ...................................................................................................................................................133
4.2 Soil carbon sequestration ..............................................................................................................134©PG Economics Ltd 20222

GM crop impact: 1996-2020

4.2.1 Tractor fuel use ........................................................................................................................135
4.2.2 Soil carbon sequestration .......................................................................................................138
4.2.3 Herbicide tolerance and conservation tillage ......................................................................141
4.2.4 Herbicide tolerant soybeans ..................................................................................................142
4.2.5 Herbicide tolerant maize ........................................................................................................152
4.2.6 Herbicide tolerant canola .......................................................................................................156
4.2.7 Herbicide tolerant cotton .......................................................................................................158
4.2.8 Insect resistant cotton .............................................................................................................158
4.2.9 Insect resistant maize..............................................................................................................159
4.2.10 Insect resistant soybeans ......................................................................................................160
4.2.11 Intensification of crop production ......................................................................................160
4.2.12
Summary of carbon sequestration impact ..................................................................161
Appendix 1: Base yields used where GM technology delivers a positive yield gain ......................165
Appendix 2: Impacts, assumptions, rationale and sources for all trait/country combinations .....166
Appendix 3: Additional information relating to the environmental impact: example comparisons.....................................................................................................................................................................182
Appendix 4: The Environmental Impact Quotient (EIQ): a method to measure the environmental
impact of pesticides ..................................................................................................................................188
Appendix 5 Soil carbon sequestration key literature...........................................................................192
Appendix 6: Additional carbon sequestration impact data ................................................................200
References ..................................................................................................................................................204

Table of tables
Table 1. Additional crop production arising from positive yield effects of GM crops .....................12
Table 2: Carbon storage/sequestration from reduced fuel use with GM crops 1996-2020 ...............16
Table 3: Context of carbon sequestration impact 2020: car equivalents ..............................................16
Table 4: GM share of crop plantings in 2018 by country (% of total plantings) .................................24
Table 5: Farm level income impact of using GM HT soybeans in Brazil 1997-2020 ..........................33
Table 6: Farm level income impact of using herbicide tolerant soybeans in Romania 1999-2006 ...37
Table 7: Farm level income impact of using GM HT soybeans in Mexico 2004-2016 .......................38
Table 8: Farm level income impact of using GM HT soybeans in Bolivia 2005-2020 ........................39
Table 9: Main impacts of insect resistant soybeans 2013/14 to 2020/21 ...............................................41
Table 10: Summary of cumulative farm level impact of using GM HT cotton: other countries: .....49
Table 11: Farm level income impact of using GM HT canola in Australia 2008-2020 ($US) ............54
Table 12: Farm level income impact of using GM IR maize in Portugal 2020 ....................................63
Table 13: Farm level income impact of using GM IR maize in Brazil 2008-2020 ...............................63
Table 14: Farm level income impact of using GM IR cotton in China 1997-2020...............................67
Table 15: Values of non-pecuniary benefits associated with GM crops in the US .............................80
Table 16: Additional crop production arising from positive yield effects of GM crops (million
tonnes) .................................................................................................................................................81
Table 17: Average (%) yield gains GM IR cotton and maize 1996-2020 ..............................................82
Table 18: Average ai use and field EIQs for conventional soybeans 2006-2018 to deliver equal
efficacy to GM HT soybeans .............................................................................................................94
Table 19: National level changes in herbicide ai use and field EIQ values for GM HT soybeans in
Canada 1997-2018 ..............................................................................................................................96©PG Economics Ltd 20223

GM crop impact: 1996-2020

Table 20: National level changes in herbicide ai use and field EIQ values for GM HT soybeans in
Brazil 1997-2020..................................................................................................................................97
Table 21: Average ai use and field EIQs for conventional maize 2007-2018 to deliver equal efficacy
to GM HT maize ...............................................................................................................................105
Table 22: Average ai use and field EIQs for conventional cotton 2006-2020 to deliver equal
efficacy to GM HT cotton ................................................................................................................113
Table 23: Comparison of insecticide ai use and field EIQ values for conventional, Ingard andBollgard II cotton in Australia ........................................................................................................130
Table 24: Estimated reduction in fuel use from adoption of conservation tillage (litres/ha) .........136
Table 25: US soybean: tractor fuel consumption by tillage method (litres/ha) ................................136
Table 26: Total farm diesel fuel consumption estimate (litres/ha) .....................................................137
Table 27: COMET-Planner: carbon sequestration by conservation practice (average) ...................138
Table 28: Summary of the potential of maize and soybeans cultivation systems to reduce net
emissions or sequester carbon (kg of carbon/ha/year) ................................................................139
Table 29: Carbon storage/sequestration from reduced fuel use with GM crops 1996-2020 ...........162
Table 30: Context of carbon sequestration impact 2020: car equivalents ..........................................163

Table of figures
Figure 1: Global GM crop farm income benefits 2020: baseline total $18.8 billion ..............................9
Figure 2: Cumulative global GM crop farm income benefits 1996-2020: baseline total $261.3 billion................................................................................................................................................................9
Figure 3: Cumulative global GM crop farm income benefits 1996-2020 by country: baseline total$261.3 billion .......................................................................................................................................10
Figure 4: Global GM crop farm income benefits 2020 by country: baseline total $18.8 billion ........10
Figure 5: Average return on investment per extra $ spent on GM traited-seed 1996-2020 $/ha......11
Figure 6: Share of aggregate active ingredient usage (reductions) by trait 1996-2020 (baseline total
748.6 million kg) .................................................................................................................................14
Figure 7: Share of aggregate EIQ changes (improvements) by trait 1996-2020 ..................................14
Figure 8: GM crop plantings 2020 by crop (base area of the four GM crops: 185.6 million ha) .......20
Figure 9: 2020: share of GM crops in global plantings of key crops (ha) ............................................21
Figure 10: Global GM crop plantings by crop 1996-2020 (ha) ..............................................................21
Figure 11: Global GM crop plantings by main trait and crop: 2020.....................................................22
Figure 12: Global GM crop plantings 2020 by country ..........................................................................23
Figure 13: Farm level savings of using GM HT soybeans (first generation) in the US 1996-2020($/ha) ....................................................................................................................................................29
Figure 14: Average farm income gain from using 2nd generation GM HT soybeans in the US 19962020 ($/ha) ...........................................................................................................................................30
Figure 15: Average farm income gain from GM HT soybeans in Argentina 1996-2020 ($/ha) ........32
Figure 16: National farm income benefit from using GM HT soybeans in Paraguay and Uruguay
1999-2020 (million $) ..........................................................................................................................34
Figure 17: Farm level income impact of using GM HT soybeans (first generation) in Canada 19972020 ($/ha) ...........................................................................................................................................35
Figure 18: Farm level income impact of using GM HT soybeans in South Africa 2001-2020 ($/ha)..............................................................................................................................................................36
Figure 19: Global farm level income benefits derived from using GM HT soybeans 1996-2020(million $) ............................................................................................................................................40©PG Economics Ltd 20224

GM crop impact: 1996-2020

Figure 20: Farm income impact of using GM HT maize in the US 1997-2020 (million $).................42
Figure 21: Farm level income impact of using GM HT maize in Canada 1999-2020 ($/ha) .............43
Figure 22: Farm level income impact of using GM HT maize in Philippines 2006-2020 ($/ha) .......45
Figure 23: Farm level income impact of using GM HT maize in Colombia 2009-2020 ($/ha) ..........46
Figure 24: Farm level income impact of using GM HT cotton in the US 1997-2020 ($/ha) ...............48
Figure 25: Farm level income impact of using GM HT canola in Canada 1996-2020 ($/ha).............51
Figure 26: National farm income impact: GM HT canola in the US 1999-2020 (million $)...............52
Figure 27: Farm level income impact of using GM HT sugar beet in the US 2007-2020 ($/ha)........57
Figure 28: Farm level income impact of using GM IR maize in the US 1996-2020 ($/ha) .................59
Figure 29: Farm income impact: GM IR maize in Canada 1996-2020 ($/ha) .......................................60
Figure 30: Farm level income impact of using GM IR maize in South Africa 2000-2020 ($/ha).......61
Figure 31: Farm level income impact of using GM IR maize in Spain 1998-2020 ($/ha) ...................62
Figure 32: Farm level income impact of using GM IR maize in Philippines 2003-2020 ($/ha) .........64
Figure 33: Farm level income impact of using GM IR cotton in the US 1996-2020 ($/ha).................66
Figure 34: Farm level income impact of using GM IR cotton in Australia 1996-2020 ($/ha) ............68
Figure 35: National farm income impact: GM IR cotton in Argentina 1998-2020 (million $) ..........69
Figure 36: Farm level income impact of using GM IR cotton in Mexico 1996-2020...........................70
Figure 37: Farm income impact: GM IR cotton in South Africa 1998-2020 ($/ha)..............................71
Figure 38: Farm level income impact of using GM IR cotton in India 2002-2020 ($/ha) ...................72
Figure 39: Farm level income impact of using GM IR cotton in Brazil 2006-2020 ($/ha) ..................73
Figure 40: Farm level income impact of using GM IR CRW control maize in the US 2003-2020($/ha) ....................................................................................................................................................76
Figure 41: Non-pecuniary benefits derived by US farmers 1996-2020 by trait ($ million) ...............81
Figure 42: Average herbicide usage on soybeans in the US 1996-2020 (kg/ha)..................................91
Figure 43: Average herbicide usage on soybeans in the US 1996-2020 (EIQ/ha) ...............................91
Figure 44: A comparison of the average EIQ/ha for conventional and GM HT soybeans in the US
1996-2020 .............................................................................................................................................93
Figure 45: A comparison of the average EIQ/ha for weed control systems used in conventional
soybeans that delivers equal efficacy to weed control systems in GM HT soybeans in the US
2006-2020 .............................................................................................................................................95
Figure 46: Reduction in herbicide use and the environmental load from using GM HT soybeans in
all adopting countries 1996-2020....................................................................................................102
Figure 47: Average herbicide usage on maize in the US 1996-2020 (kg/ha) .....................................103
Figure 48: Average herbicide usage on maize in the US 1996-2020 (EIQ/ha) ...................................104
Figure 49: A comparison of the average EIQ/ha for conventional and GM HT maize in the US
1996-2020 ...........................................................................................................................................105
Figure 50: A comparison of the average EIQ/ha for weed control systems used in conventionalmaize that delivers equal efficacy to weed control systems in GM HT maize in the US 20072020 ....................................................................................................................................................106
Figure 51: Reduction in herbicide use and the environmental load from using GM HT maize in
adopting countries 1997-2020 .........................................................................................................110
Figure 52: Average herbicide usage on cotton in the US 1997-2019 (kg/ha) .....................................111
Figure 53: Average herbicide usage on cotton in the US 1997-2019 (EIQ/ha) ..................................111
Figure 54: A comparison of the average EIQ/ha for conventional and GM HT cotton in the US
1997-2020 ...........................................................................................................................................112
Figure 55: A comparison of the average EIQ/ha for weed control systems used in conventional
cotton that delivers equal efficacy to weed control systems in GM HT maize in the US 20072020 ....................................................................................................................................................114©PG Economics Ltd 20225

GM crop impact: 1996-2020

Figure 56: Reduction in herbicide use and the environmental load from using GM HT cotton in
the US, Australia, Argentina, Colombia and South Africa 1997-2020 ......................................117
Figure 57: Average active ingredient differences conventional versus GM HT canola US 1999-2020............................................................................................................................................................118
Figure 58: Average EIQ/ha differences conventional versus GM HT canola US 1999-2020 ..........118
Figure 59: Reduction in herbicide use and the environmental load from using GM HT canola in
the US, Canada and Australia 1996-2020 ......................................................................................120
Figure 60: Average insecticide use on maize 1996-2020 (kg active ingredient/ha) ..........................122
Figure 61: Reduction in insecticide use and the environmental load from using GM IR maize in
adopting countries 1996-2020 .........................................................................................................127
Figure 62: Average cotton insecticide usage: 1996-2020 (average active ingredient use: kg/ha) ...129
Figure 63: Reduction in insecticide use and the environmental load from using GM IR cotton in
adopting countries 1996-2020 .........................................................................................................132
Figure 64: US soybean: crop area by tillage practices 1996-2020 (hectares)......................................142
Figure 65: US GM HT soybeans by tillage 1996-2020 (million ha) .....................................................143
Figure 66: US soybeans permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg) ................................................................................144
Figure 67: US soybeans - potential additional carbon dioxide sequestered 1996-2020 (million kg)............................................................................................................................................................145
Figure 68: Argentina soybeans tillage practices 1996-2020 (million ha)............................................145
Figure 69: Argentina GM HT soybeans by tillage practice 1996-2020 (million ha) .........................146
Figure 70: Argentina soybeans permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg) ................................................................................147
Figure 71: Argentina soybeans - potential additional carbon dioxide sequestered 1996-2020(million kg) .......................................................................................................................................148
Figure 72: Brazil soybeans tillage practices 1996-2020 (million ha) ...................................................149
Figure 73: Brazil soybeans permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg) ................................................................................150
Figure 74: Brazil soybeans - potential additional carbon dioxide sequestered 1996-2020 (millionkg) ......................................................................................................................................................151
Figure 75: US maize: crop area by tillage practices 1996-2020 (million ha) ......................................153
Figure 76: US GM HT maize by tillage 1996-2020 (million ha) ..........................................................153
Figure 77: US maize permanent reduction in carbon dioxide emissions resulting from a reduction
in fuel use 1996-2020 (million kg) ..................................................................................................154
Figure 78: US maize - potential additional carbon dioxide sequestered 1996-2020 (million kg) ...155
Figure 79: Canadian canola permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1997-2020 (million kg) ................................................................................157
Figure 80: Canadian canola - potential additional carbon dioxide sequestered 1997-2020 (millionkg) ......................................................................................................................................................158
Figure 81: Permanent reduction in global tractor fuel consumption and carbon dioxide emissions
resulting from the cultivation of GM IR cotton (1996-2020) ......................................................159©PG Economics Ltd 20226

GM crop impact: 1996-2020

Foreword
This paper is intended for use by a wide range of people with interests in agriculture across theworld – farmers, farmer organisations, industry associations, inter-professional bodies, input
suppliers, users of agricultural products, government departments, international organisations,non-governmental organisations, politicians, academics, researchers, students and interested
citizens.
The material contained in the paper, which is the 15th annual report on the global economic andenvironmental impact of genetically modified (GM) crops, aims to provide insights into thereasons why so many farmers around the world have adopted crop biotechnology and continue
to use it in their production systems since the technology first became available on a widespreadcommercial basis in the mid-1990s.
The paper draws, and is largely based on, the considerable body of consistent peer reviewed
literature available that has examined the economic and other reasons behind farm level crop
biotechnology adoption, together with the environmental impacts associated with the changes 1.
The work contained in this paper has been submitted and accepted for publication in the peer
reviewed publication GM Crops and Food. The length of this paper, at over 200 pages, is toolong for acceptance for publication as a single document in peer reviewed journals. Therefore,
the author submitted three papers focusing separately on the economic impacts, theenvironmental impacts associated with pesticide use change and the environmental impacts
associated with carbon dioxide emissions. The economic impact paper is available in volume 13,2022-issue 1, p 171-195. http://doi.org/10.1080/21645698.2022.2105626. The environmental impact
associated with pesticide use paper is DOI: 10.1080/21645698.2022.2118497 and the environmental
impact associated with carbon emissions paper is DOI: 10.1080/21645698.2022.2118495. These
two later papers will be published in the next edition of the journal but are available on thejournal’s website under current research (this status recorded in early October 2022). All papers
are available on open access. These papers follow on from numerous previous peer reviewed
papers by the author on the subject of crop biotechnology impact 2.

1

Data from other sources, including industry, is used where no other sources of (representative) data are

available. All sources and assumptions used are detailed in the paper
For example, the last global impact report covering the years 1996-2018 can be found in the GM Crops
journal. The environmental impact paper is available at GM Crops & Food, 11:4, 215-240, DOI:
10.1080/21645698.2020.1773198. The economic impact paper is GM Crops & Food, 11:4, 242-261, DOI:
10.1080/21645698.2020.1779574. See also www.pgeconomics.co.uk for a full list of these peer review papers
2©PG Economics Ltd 20227

GM crop impact: 1996-2020

Executive summary and conclusions
This report presents the findings of research into the global socio-economic and environmental
impact of genetically modified (GM) crops in the twenty-five years since they were firstcommercially planted on a significant area. It focuses on the farm level economic effects, theproduction effects, the environmental impact resulting from changes in the use of insecticides
and herbicides, and the contribution towards reducing greenhouse gas (GHG) emissions.
Farm income effects 3
GM technology has had a significant positive impact on farm income derived from a combinationof enhanced productivity and efficiency gains (Figure 1 and Figure 2). In 2020, the direct global
farm income benefit from GM crops was $18.8 billion. This is equivalent to having added 5.9% to
the value of global production of the four main crops of soybeans, maize, canola and cotton.
Since 1996, farm incomes have increased by $261.3 billion.
The largest gains in farm income in 2020 have arisen in the maize sector, largely from yield gains.
The $3.7 billion additional income generated by GM insect resistant (GM IR) maize in 2020 has
been equivalent to adding 6.3% to the value of the crop in the GM crop growing countries, or
adding, the equivalent of 2.8% to the $133 billion value of the global maize crop in 2020.
Cumulatively since 1996, GM IR technology has added $67.8 billion to the income of global maize
farmers.
Substantial gains have also arisen in the cotton sector through a combination of higher yields andlower costs. In 2020, cotton farm income levels in the GM adopting countries increased by $3.94
billion and since 1996, the sector has benefited from an additional $73.11 billion. The 2020 income
gains are equivalent to adding 12.1% to the value of the cotton crop in these countries, or 12% to
the $32.7 billion value of total global cotton production. This is a substantial increase in value
added terms for two categories of cotton seed technology.
Significant increases to farm incomes have also resulted in the soybean and canola sectors. The
GM herbicide tolerant (HT) technology in soybeans has boosted farm incomes by $5.64 billion in
2020, and since 1996 has delivered $74.65 billion of extra farm income. The adoption of ‘Intacta’soybeans (combining HT and IR traits) in South America since 2013 also provided $16 billion of
additional farm income. In the canola sector (largely North American) an additional $8.2 billion
has been generated (1996-2020).

3

See section 3 for details©PG Economics Ltd 20228

GM crop impact: 1996-2020

Figure 1: Global GM crop farm income benefits 2020: baseline total $18.8 billion
HT canola, 3.3%

Others, 0.7%

HT cotton, 0.7%
IR cotton, 20.2%

HT soy, 30.0%

HT corn, 8.3%

Intacta soy, 17.2%
IR Corn, 19.6%
Notes: Others = HT sugar beet, Virus resistant papaya and squash, drought tolerant maize and IR brinjal

Figure 2: Cumulative global GM crop farm income benefits 1996-2020: baseline total $261.3
billionHT cotton, 1.0%

HT canola, 3.1%

Others, 0.5%
HT soy, 28.6%

IR cotton, 27.0%

Intacta soy, 6.1%
HT corn, 7.7%
IR Corn, 25.9%
Notes: Others = HT sugar beet, Virus resistant papaya and squash, drought tolerant maize and IR brinjal

Figure 3 and Figure 4 summarise farm income impacts in key GM crop adopting countries. These
highlight the important farm income benefit arising from GM HT soybeans in South America(Argentina, Bolivia, Brazil, Paraguay and Uruguay), GM IR cotton in China and India and therange GM crop adoption in the US. Figure 4, in particular (the increasing share of ‘other©PG Economics Ltd 20229

GM crop impact: 1996-2020

countries’) also illustrates the growing level of farm income benefits being obtained in countries
that were later adopters of GM crop technology such as Pakistan, the Philippines and Colombia.
Figure 3: Cumulative global GM crop farm income benefits 1996-2020 by country: baseline
total $261.3 billion
Australia, 0.6%

Other countries,
5.7%

Canada, 3.9%
Africa, 1.2%

US, 42.5%

India, 10.5%

Argentina, 12.9%

China, 10.1%
Brazil, 12.7%
Figure 4: Global GM crop farm income benefits 2020 by country: baseline total $18.8 billion
Australia, 0.4%
Other countries, 4.0%

Canada, 5.1%

Africa, 1.5%
India, 8.1%
US, 39.1%

Argentina, 15.1%

China, 8.4%
Brazil, 18.3%

In terms of the division of the economic benefits obtained by farmers in developing countries
relative to farmers in developed countries, in 2020, 55% of the farm income benefits have been
earned by developing country farmers. The vast majority of these income gains for developing©PG Economics Ltd 202210

GM crop impact: 1996-2020

country farmers have been from GM IR cotton and GM HT soybeans 4. Over the twenty-fiveyears, 1996-2020, the cumulative farm income gain derived by developing country farmers was
52% ($136.6 billion).
Examining the cost farmers pay for accessing GM technology, the average cost to farmers (19962020) was equal to 27% of the total technology gains (inclusive of farm income gains plus cost of
the technology payable to the seed supply chain 5). In terms of investment, this means that foreach extra dollar invested in GM crop seeds (relative to conventional seed costs), farmers gained
an average $3.76 in extra income. In developing countries, the average return was $5.22 for eachextra dollar invested in GM crop seed and in developed countries the average return was $3.00(Figure 5).
For farmers in developing countries the total cost was equal to 19% of total technology gains,whilst for farmers in developed countries the cost was 33% of the total technology gains.
Although, circumstances vary between countries, the higher share of total technology gains
accounted for by farm income gains in developing countries, relative to the farm income share indeveloped countries, reflects factors such as weaker provision and enforcement of intellectual
property rights in developing countries and the higher average level of farm income gain on a perhectare basis derived by developing country farmers relative to developed country farmers.
Figure 5: Average return on investment per extra $ spent on GM traited-seed 1996-2020 $/ha
6.00
5.22
5.00
3.76

4.00

3.00

3.00
2.00
1.00
-

Average return on investment: all Average return on investment:
adopting countries
developed countries

Average return on investment:
developing countries

Seventy-two per cent of the total income gain over the 25-year period derives from higher yields
and second crop soybean gains with 28% from lower costs (mostly from lower pest and weed
control costs). The balance of the income gain arising from yield/production gains relative to cost
4

The authors acknowledge that the classification of different countries into developing or developed country

status affects the distribution of benefits between these two categories of country. The definition used in thispaper is consistent with the definition used by James (2014)5

The cost of the technology accrues to the seed supply chain including sellers of seed to farmers, seedmultipliers, plant breeders, distributors and the GM technology providers©PG Economics Ltd 202211

GM crop impact: 1996-2020

savings is changing as second-generation GM crops are increasingly adopted. Thus in 2020 the
split of total income gain came 91% from yield/production gains and 9% from cost savings.
Production effects of the technology
Based on the yield impacts used in the direct farm income benefit calculations above and taking
account of the second soybean crop facilitation in South America, GM crops have added
important volumes to global production of maize, cotton, canola and soybeans since 1996 (Table
1).
The GM IR traits, used in maize and cotton, have accounted for 91.1% of the additional maize
production and 98.2% of the additional cotton production. Positive yield impacts from the use ofthis technology have occurred in all user countries, except for GM IR cotton in Australia where
the levels of Heliothis sp (boll and bud worm pests) pest control previously obtained withintensive insecticide use were very good. The main benefit and reason for adoption of thistechnology in Australia has arisen from significant cost savings and the associated environmental
gains from reduced insecticide use, when compared to average yields derived from crops using
conventional technology (such as application of insecticides and seed treatments). The average
yield impact across the total area planted to these traits over the 25 years since 1996 has been
+17.7% for maize and +14.5% for cotton.
As indicated earlier, the primary impact of GM HT technology has been to provide more costeffective (less expensive) and easier weed control, as opposed to improving yields, the improved
weed control has, nevertheless, delivered higher yields in some countries. The main source ofadditional production from this technology has been via the facilitation of no tillage production
systems, shortening the production cycle and how it has enabled many farmers in South America
to plant a crop of soybeans immediately after a wheat crop in the same growing season. Thissecond crop, additional to traditional soybean production, has added 222.7 million tonnes toglobal soybean production between 1996 and 2020 with Intacta soybeans adding a further 44.4
million tonnes since 2013. The remaining additional GM-related soybean production has comefrom the second generation of GM HT soybeans grown in North American countries since 2008
and where the GM HT technology has enabled farmers to obtain higher yield via improved levels
of weed control.
Table 1. Additional crop production arising from positive yield effects of GM crops (million
tonnes)
1996-2020
Soybeans
330.35Maize
594.58
Cotton37.01
Canola
15.77
Sugar beet
1.87
Note: Sugar beet, US and Canada only (from 2008)

2020
33.48
47.9
2.26
1.00
0.15

The widespread use of GM crop technology has also contributed to changing agriculture’s land
footprint by allowing farmers to grow more on existing land used for agricultural purposes,
reducing the pressure to bring in new land into cultivation. For example, if world agriculture
wanted to maintain global production of the four main crops in which GM seed technology has
been widely used levels at 2020 levels, but without using the GM technology, this would require©PG Economics Ltd 202212

GM crop impact: 1996-2020

farmers to plant an additional 11.6 million ha of soybeans, 8.5 million ha of maize, 2.8 million haof cotton and 0.5 million ha of canola, an area (23.4 million ha in total) equivalent to the combined
agricultural area of Philippines and Vietnam. This fits well with the land sharing and sparing
approach, that the science and evidence (see for example Balmford, 2021) shows is the best way
to deliver a more sustainable global agriculture.
Environmental impact from changes in insecticide and herbicide use 6
To examine this impact, the study has analysed active ingredient use and utilised the indicator
known as the Environmental Impact Quotient (EIQ) to assess the broader impact on theenvironment (plus impact on animal and human health). The EIQ distils the various
environmental and health impacts of individual pesticides in different GM and conventional
production systems into a single ‘field value per hectare’ and draws on key toxicity andenvironmental exposure data related to individual products. It therefore provides a bettermeasure to contrast and compare the impact of various pesticides on the environment andhuman health than weight of active ingredient alone. Readers should, however, note that the EIQ
is an indicator only (primarily of toxicity) and does not take into account all environmental issues
and impacts. In the analysis of GM HT production, we have assumed that the conventional
alternative delivers the same level of weed control as occurs in the GM HT production system.
GM traits have contributed to a significant reduction in the environmental impact associated with
insecticide and herbicide use on the areas devoted to GM crops (Figure 6 and Figure 7). Since
1996, the use of pesticides on the GM crop area was reduced by 748.6 million kg of active
ingredient (a 7.2% reduction), and the environmental impact associated with herbicide andinsecticide use on these crops, as measured by the EIQ indicator, fell by17.3%.
The largest share of this was accounted for by GM IR cotton (45%) followed by GM HT maize(30%: Figure 6). In terms of the environmental impact associated with herbicide and insecticide
use on these crops, as measured by the EIQ indicator, this improved by 17.3%, with the largest
share of these improvements delivered by GM IR cotton (about 40% of the total), followed by GM
HT soybeans (26%).
At the country level, US farms have seen the largest environmental benefits, with a 322 million kg
reduction in pesticide active ingredient use (43% of the total). This is not surprising given that US
farmers were first to make widespread use of GM crop technology, and for many years, the GM
adoption levels in all four US crops have been in excess of 80%, and insecticide/herbicide use has,in the past been, the primary method of weed and pest control. Important environmental
benefits have also occurred in China and India from the adoption of GM IR cotton, with areduction in insecticide active ingredient use of over 304 million kg (1996-2020).

6

See section 4.1©PG Economics Ltd 202213

GM crop impact: 1996-2020

Figure 6: Share of aggregate active ingredient usage (reductions) by trait 1996-2020 (baseline
total 748.6 million kg)
GM HT sugar beet,
0.1%

GM IR soybeans, 3.2%GM HT soy, 0.4%

GM HT maize, 29.9%

GM IR cotton, 45.3%

GM HT canola, 4.6%
GM HT cotton, 5.2%
GM IR maize, 11.4%

Figure 7: Share of aggregate EIQ changes (improvements) by trait 1996-2020
GM HT sugar beet,
0.1%
GM IR soybeans, 5.5%

GM HT soy, 26.3%

GM IR cotton, 39.6%

GM HT maize, 13.2%

GM HT canola, 2.0%
GMHT
cotton,1.4%
GM IR maize, 11.8%

It should, however, be noted that in some regions where GM HT crops have been widely grown,some farmers have relied too much on the use of glyphosate to manage weeds in GM HT crops
and this has contributed to the development of weed resistance. There are currently 56 weeds
recognised as exhibiting resistance to glyphosate worldwide, of which several are not associatedwith glyphosate tolerant crops (www.weedscience.org). For example, there are currently 17
weeds recognised in the US as exhibiting resistance to glyphosate, of which two are notassociated with glyphosate tolerant crops. In the US, the affected area is currently within a rangeof 60%-80% of the total area annually devoted to maize, cotton, canola, soybeans and sugar beet(the crops in which GM HT technology is used).

©PG Economics Ltd 202214

GM crop impact: 1996-2020

Where farmers are faced with the existence of weeds resistant to glyphosate in GM HT crops,
they are advised to include other herbicides (with different and complementary modes of action)in combination with glyphosate and, in some cases, to adopt cultural practices such as ploughingin their integrated weed management systems. These changes in weed management practices
have been evident from the changes in herbicide usage patterns discussed above and reflect thebroader agenda of developing more integrated weed control strategies across all forms ofcropping systems (not just GM HT) to minimise and slow down the potential for weeds
developing resistance to whatever form of weed control is practiced. In addition, GM HT crops
tolerant to other herbicides (often stacked with glyphosate) have become available from 2016 insome countries. At the macro level, these changes have influenced the mix, total amount, costand overall profile of herbicides applied to GM HT crops in the last 15 years.
Relative to the conventional alternative, the environmental profile of GM HT crop use has,nevertheless, continued to offer important advantages and in most cases, provides an improved
environmental profile compared to the conventional alternative (as measured by the EIQ
indicator).
Impact on greenhouse gas (GHG) emissions 7
The scope for GM crops contributing to lower levels of GHG emissions comes from two principal
sources:a) Reduced fuel use
The fuel savings arising from making fewer insecticide applications with the use of GM IR crop
technology in maize, cotton and soybeans and the switch from conventional tillage (CT) to
reduced/no tillage (RT/NT 8) systems facilitated by GM HT crops, have delivered permanentsavings in carbon dioxide emissions. Over the period 1996 to 2020, the cumulative permanent
reduction in fuel use has been about 39,147 million kg of carbon dioxide, arising from reduced
fuel use of 14,662 million litres. In terms of car equivalents, this is equal to taking 25.9 million
cars off the road for a year (Table 2).
The largest fuel use-related reductions in carbon dioxide emissions have come from the adoptionof GM HT technology and how it has facilitated a switch to RT/NT production systems with their
reduced soil cultivation practices. This accounted for 92% of the fuel and carbon dioxide savingsin the period 1996-2020, within which GM HT soybeans accounted for the largest contribution(68% of the total savings). These savings have been greatest in South America.
In 2020, the fuel related savings were 2,330 million kg of carbon dioxide, arising from reduced
fuel use of 948 million litres. These savings are equivalent to taking 1.68 million cars off the roadfor one year.

7

See section 4.2

No-till (NT) farming means that ground is hardly disturbed at planting (not ploughed), while reduced
tillage (RT) means that ground is disturbed less than it would be with traditional tillage systems. For
example, under a NT farming system, soybean seeds are planted through the organic material that is left
over from a previous crop such as maize, cotton or wheat. Full definitions are given in section 4.2.2
8©PG Economics Ltd 202215

GM crop impact: 1996-2020

Table 2: Carbon storage/sequestration from reduced fuel use with GM crops 1996-2020
Crop/trait/country

Fuel saving(million litres)

Permanent carbon
dioxide savings arisingfrom reduced fuel use(million kg of carbon
dioxide)Permanent fuel savings:
as average family car
equivalents removed
from the road for a year(‘000s)HT soybeans
Argentina
4,433
11,837
7,844
Brazil
2,749
7,341
4,865
Bolivia, Paraguay, Uruguay
899
2,401
1,591
US
1,687
4,503
2,984
Canada255
681
451
HT maize
US
2,257
6,027
3,994
Canada121
323
214
HT canola
Canada: GM HT canola
1,067
2,848
1,887
IR maize
Brazil369
984
652
US/Canada/Spain/South
Africa91
243
161
IR cotton – global
285
760
504
IR soybeans – SouthAmerica
449
1,199
795
Total
14,662
39,14725,942
Notes:
1. Assumption: an average family car in 2020 produces 123.4 grams of carbon dioxide per km. A car
does an average of 12,231 km/year and therefore produces 1,509 kg of carbon dioxide/year
2. GM IR cotton. India, Pakistan, Myanmar and China excluded because insecticides assumed to be
applied by hand, using back pack sprayersb) Additional soil carbon storage/sequestration
There has been significant sequestration (storage) of soil carbon (and therefore lower emissions ofcarbon dioxide) resulting from the widespread adoption and maintenance of ‘no-till’ (NT) and‘reduced-till’ (RT) farming systems in North and South America. This has been facilitated by theuse of GM HT crop technology.
Based on the areas of GM HT crops using RT/NT production systems in North and SouthAmerica in 2020, we estimate that an extra 5,750 million kg of soil carbon has been sequestered in2020. This is equivalent to 21,101 million kg of carbon dioxide that has not been released into theglobal atmosphere. In terms of removing vehicles from the road, these savings are equivalent totaking 14 million cars off the road for one year (Table 3).

Table 3: Context of carbon sequestration impact 2020: car equivalents
Crop/trait/country

Additional carbon
stored in soil
(million kg ofcarbon)©PG Economics Ltd 2022

16

Potential
additional soil
carbonsequestration
savings (million

Soil carbon
sequestration savings: asaverage family car
equivalents removedGM crop impact: 1996-2020

kg of carbon
dioxide)from the road for a year(‘000s)

1,832.5
1,485.0
490.7
110.9
62.9

6,725.2
5,450.1
1,800.8
407.0
230.7

4,445.8
3,611.0
1,193.1
269.6
152.9

1,481.6
15.6

5,437.6
57.4

3,602.7
38.0

270.4

992.4

657.5

0
0
0
0
5,749.6000021,101.1000013,980.7

HT soybeans
Argentina
BrazilBolivia, Paraguay, Uruguay
US
CanadaHT maize
US
CanadaHT canola
Canada: GM HT canola
IR maize
BrazilUS/Canada/Spain/South Africa
IR cotton – global
IR soybeans – South America
Total

If the annual estimates of soil carbon sequestration are aggregated over the 1996-2020 period,
then the additional amount of soil carbon sequestered since 1996 has been equivalent to 344,044
million kg of carbon dioxide that has not been released into the global atmosphere, equivalent totaking about 228 million cars off the road over this period. Readers should, however, note that
this estimate is likely to significantly overstate the true soil carbon sequestration benefits from theadoption of RT/NT systems over this 25 year period because some of the additional soil carbon
sequestration gains from RT/NT systems will have been lost from some subsequent ploughing ofland in these crops and production systems.
Overall, it is not possible to confidently estimate cumulative soil sequestration gains that take
into account reversions to conventional tillage because of a lack of data.
Returning to the 2020 analysis of carbon emission savings from both sources of fuel related
savings and soil carbon storage, aggregating these benefits results in the total carbon dioxidesavings in 2020 being equal to about 23,631 million kg, equivalent to taking 15.6 million cars off
the road for a year. This is equal to 49% of registered cars in the UK.

©PG Economics Ltd 202217

GM crop impact: 1996-2020

1 Introduction
This study 9 examines the socio-economic impact on farm income and environmental impacts
arising from pesticide usage and greenhouse gas (GHG) emissions, of crop biotechnology, over
the twenty-five years, 1996-2020 10. It also quantifies the production impact of the technology on
the key crops where it has been used.

1.1 Objectives
The principal objective of the study was to identify the global socio-economic and environmental
impact of genetically modified (GM) crops over the first twenty-five years of widespreadcommercial production.
More specifically, the report examines the following impacts:
Socio-economic impacts on:• Cropping systems: risks of crop losses, use of inputs, crop yields and rotations;• Farm profitability: costs of production, revenue and gross margin profitability;• Indirect (non-pecuniary) impacts of the technology;• Production effects.
Environmental impacts associated with:• Insecticide and herbicide use, including use of the environmental impact measure, theEnvironmental Impact Quotient (EIQ) 11;• Greenhouse gas (GHG) emissions.

1.2 Methodology
The report has been compiled based largely on desk research and analysis. A detailed literature
review 12 has been undertaken to identify relevant data. Primary data for impacts of commercial
cultivation were not available for every crop, in every year and for each country, but all
representative, previous research has been utilised. The findings of this research have been usedas the basis for the analysis presented 13, although where relevant, we have undertaken primary
analysis from base data (eg, calculation of the environmental impacts). More specific information
about assumptions used and their origins are provided in each of the sections of the report.
9

The authors acknowledge that funding towards the researching of this paper was provided by Bayer Crop

Science. The material presented in this paper is, however, the independent view of the authors – it is astandard condition for all work undertaken by PG Economics that all reports are independently andobjectively compiled without influence from funding sponsors
10This study updates earlier studies first produced in 2005 and updated regularly, covering the first nine thensubsequent years of GM crop adoption globally. Readers should, however, note that some data presented inthis report are not directly comparable with data presented in the earlier papers because the current paper
takes into account the availability of new data and analysis (including revisions to data applicable to earlier
years)
11

Based on Kovach J et al (1992 & annually updated) – see section 4.1 and Appendix 4

12

See References

13

Where several pieces of research of relevance to one subject (eg, the impact of using a biotech trait on theyield of a crop) have been identified, the findings used have been largely based on the average©PG Economics Ltd 202218

GM crop impact: 1996-2020

1.3 Structure of report
The report is structured as follows:••••

Section one: introduction;
Section two: overview of biotech crop plantings by trait and country;
Section three: farm level profitability impacts by trait and country, intangible (nonpecuniary) benefits and production impact;
Section four: environmental impacts covering impact of changes in herbicide andinsecticide use and contributions to reducing GHG emissions.

©PG Economics Ltd 2022

19

GM crop impact: 1996-2020

2 Global context of GM crops
This section provides a broad overview of the global development of GM crops over the twentyfive years, 1996-2020.

2.1 Global plantings
Although the first commercial GM crops were planted in 1994 (tomatoes), 1996 was the first year
in which a significant area of crops containing GM traits were planted (1.66 million hectares).
Since then there has been a dramatic increase in plantings and by 2020, the global planted area
was 185.6 million hectares (ha).
In terms of the share of the main crops in which GM traits have been commercialised (soybeans,maize/corn, cotton and canola), GM traits accounted for 47.4% of the global plantings to thesefour crops in 2020.

2.2 Plantings by crop and trait
2.2.1 By crop
Almost all of the global GM crop area derives from soybeans, maize/corn, cotton and canola(Figure 8) 14. In 2020, GM soybeans accounted for the largest share (50%), followed by maize/corn(33%), cotton (12%) and canola (5%).
Figure 8: GM crop plantings 2020 by crop (base area of the four GM crops: 185.6 million ha)
Cotton12%Canola5%

Soybeans
50%

Corn
33%

Sources: Various including ISAAA, Canola Council of Canada, CropLife Canada, USDA, CSIRO, ArgenBio,
National Ministries of Agriculture (Mexico, Philippines, Spain, Vietnam), Grains South Africa

14

In 2020, there were also additional GM crop plantings of papaya (187 hectares), squash (1,000 hectares),sugar beet (462,300 ha), alfalfa (about 1.26 million ha) and potatoes (1,780 ha) in the US. There were also 9,000
hectares of papaya in China, 17,000 ha of sugar beet in Canada and 6,309 ha of insect resistant brinjal in
Bangladesh©PG Economics Ltd 2022

20

GM crop impact: 1996-2020

In terms of the share of total global plantings to these four crops, GM traits accounted for the
majority of soybean plantings (72%) in 2020. For the other three main crops, the GM shares were
31% for maize, 76% for cotton and 27% for canola (Figure 9).
Figure 9: 2020: share of GM crops in global plantings of key crops (ha)
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Soybeans

Corn

CottonCanolaConventional

36,022,348

137,972,155

7,378,481

25,381,462

GM area

91,857,652

60,767,845

23,151,519

9,318,538

Sources: Various including ISAAA, Canola Council of Canada, CropLife Canada, USDA, CSIRO, ArgenBio,
National Ministries of Agriculture (Mexico, Philippines, Spain, Vietnam), Grains South Africa

The trend in plantings to GM crops (by crop) since 1996 is shown in Figure 10.
Figure 10: Global GM crop plantings by crop 1996-2020 (ha)100,000,000
90,000,000
80,000,000
70,000,000
60,000,000
50,000,000
40,000,000
30,000,000
20,000,000
10,000,000
01996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Soybeans

Maize

CottonCanolaSources: Various including ISAAA, Canola Council of Canada, CropLife Canada, USDA, CSIRO, ArgenBio,
National Ministries of Agriculture (Mexico, Philippines, Spain, Vietnam), Grains South Africa©PG Economics Ltd 202221

GM crop impact: 1996-2020

2.2.2 By trait
Figure 11 summarises the breakdown of the main GM traits planted globally in 2020. GM
herbicide tolerant (HT) soybeans dominate, accounting for 33.6% of the total, followed byherbicide tolerant (HT) and insect resistant (IR: largely Bt) maize, IR soybeans (also containing
HT technology) and IR cotton with respective shares of 21%, 20.9%, 10.8% and 8.3% 15.
Figure 11: Global GM crop plantings by main trait and crop: 2020
HT sugar beet
0.2%
Ht canola
3.4%

IR soybeans
10.8%

IR cotton
8.3%

Ht soy33.6%

HT corn
21.0%
IR corn
20.9%

Ht cotton
1.9%

Sources: Various including ISAAA, Canola Council of Canada, CropLife Canada, USDA, CSIRO, ArgenBio,
National Ministries of Agriculture (Mexico, Philippines, Spain, Vietnam), Grains South Africa

2.2.3 By country
The US had the largest share of global GM crop plantings in 2020 (36%), followed by Brazil (30%).
The other main countries planting GM crops were Argentina, India, Canada and China (Figure
12).

15

The reader should note that the total plantings by trait produces a higher global planted area (273.4 millionha) than the global area by crop (185.6 million ha) because of the planting of some crops containing the stacked
traits of herbicide tolerance and insect resistance©PG Economics Ltd 2022

22

GM crop impact: 1996-2020

Figure 12: Global GM crop plantings 2020 by country
India
7%

Others7%

US36%

Argentina
12%

China
2%
Canada6%

Brazil30%

Sources: Various including ISAAA, Canola Council of Canada, CropLife Canada, USDA, CSIRO, ArgenBio,
National Ministries of Agriculture (Mexico, Philippines, Spain, Vietnam), Grains South Africa

In terms of the GM share of production in the main adopting countries, Table 4 shows that, in
2020, the technology accounted for important shares of total production of the four main crops, inseveral countries. More specifically:
•

•

•

•

•

US: was one of the first countries to adopt the technology in 1996 for traits in soybeans,maize and cotton, and from 1999 in canola, hence the very high adoption levels thathave continued to 2020. All of the US sugar beet crop also used GM HT technology in
2020;
Canada and Argentina: like the US were early adopters, with the technology now
dominating production in the three crops of soybeans, maize and canola in Canada, andmaize, cotton and soybeans in Argentina;
South Africa: was the first and, remains the primary African country to embrace thetechnology, which was first used commercially in 2000. The technology is widely usedin the important crops of maize and soybeans, and now accounts for all of the cotton
crop (16,200 ha in 2020);
Australia: was an early adopter of GM technology in cotton (1996), with GM traits now
accounting for almost all cotton production. Extension of the technology to other crops
did, however, not occur until 2008 when HT canola was allowed in some Australianstates;In Asia, seven countries used GM crops in 2020. China was the first Asian country to
use the technology commercially back in 1997 when GM IR technology was first used.
This technology rapidly expanded to about two thirds of the total crop within five years
and accounted for 95% of the crop in 2020. GM virus resistant papaya has also beenused in China since 2008. In India, IR cotton was first adopted in 2002, and its use
increased rapidly in subsequent years, so that in 2020 this technology continues to©PG Economics Ltd 202223

GM crop impact: 1996-2020•

dominate total cotton production (94% of the total). IR cotton is also grown in Pakistan
and Myanmar. In the Philippines, IR maize was first used commercially in 2003, withHT maize also adopted from 2006. Vietnam adopted IR/HT maize in 2015 and 10% of
the crop used seed containing this technology in 2020. Lastly, virus resistant brinjal has
been grown in Bangladesh since 2014;
In South America, there are interesting country examples where the adoption of GM
technology in one country resulted in a spread of the technology, initially illegally,
across borders into countries which were first reluctant to legalise the use of thetechnology. GM HT soybeans were first grown illegally in the southernmost states ofBrazil in 1997, a year after legal adoption in Argentina. It was not until 2003 that theBrazilian government legalised the commercial growing of GM HT soybeans, whenmore than 10% of the country’s soybean crop had been using the technology illegally (in2002). Since then, GM technology use has extended to cotton in 2006 and maize in 2008.
A similar process of widespread illegal adoption of GM HT soybeans occurred in
Paraguay and Bolivia before the respective governments authorised the planting ofsoybean crops using this GM trait. Intacta soybeans (insect resistant and herbicide
tolerant) have been grown in Brazil, Paraguay, Argentina and Uruguay since 2013.

Table 4: GM share of crop plantings in 2020 by country (% of total plantings)
Soybeans
Maize
CottonCanola
US
94
92
96
97
Canada86
90
N/a89
Argentina
97
99
100
N/a
South Africa
95
90
100
N/a
Australia
N/a
N/a
100
25
China
N/a
N/a
95
N/a
Philippines
N/a
27
N/a
N/a
Paraguay
99
72
100
N/a
Brazil96
93
88
N/a
Uruguay
99
90
N/a
N/a
India
N/a
N/a
94
N/a
Colombia
N/a
58
56
N/a
Mexico
Nil
N/a
97
N/a
Bolivia
97
N/a
N/a
N/a
Vietnam
N/a
10
N/a
N/a
Pakistan
N/a
N/a
95
N/a
Myanmar
N/a
N/a
89
N/a
Notes: N/a = not applicable. Colombia maize % adoption relates to commercial maize area only, excluding
subsistence maize crop

©PG Economics Ltd 202224

GM crop impact: 1996-2020

3 The farm level economic impact of GM crops 19962020
This section examines the farm level economic impact of growing GM crops and covers thefollowing main issues:
•
•
•
•
•

•

Impact on crop yields;
Effect on key costs of production, notably seed cost and crop protection expenditure;
Impact on other costs such as fuel and labour;
Effect on profitability;
Other impacts such as crop quality, scope for planting a second crop in a season andimpacts that are often referred to as intangible impacts such as convenience, risk
management and husbandry flexibility;
Production effects.

The analysis is based on an extensive examination of existing farm level impact data for GM
crops. Whilst primary data for impacts of commercial cultivation were not available for every
crop, in every year and for each country, a substantial body of representative research andanalysis is available and this has been used as the basis for the analysis presented.
As the economic performance and impact of this technology at the farm level varies widely, both
between and within regions/countries (as applies to any technology used in agriculture), themeasurement of performance and impact is considered on a case by case basis in terms of crop andtrait combinations. The analysis presented is based on the average performance and impact
recorded in different crops by the studies reviewed; the average performance being the mostcommon way in which the identified literature has reported impact. Where several pieces of
relevant research (eg, on the impact of using a GM trait on the yield of a crop in one country in aparticular year) have been identified, the findings used have been largely based on the average ofthese findings.
This approach may overstate or understate the real impact of GM technology for some trait, cropand country combinations, especially in cases where the technology has provided yieldenhancements. However, as impact data for every trait, crop, location and year is not available,
the authors have had to extrapolate available impact data from identified studies for years forwhich no data are available. It is acknowledged that this represents a potential methodologicalweakness of the research. To reduce the possibilities of over/understating impact, the analysis:•

16

Directly applies impacts identified from the literature to the years that have been studied.
As a result, the impacts used vary in many cases according to the findings of literature
covering different years 16. Hence, the analysis takes into account variation in the impactof the technology on yield according to its effectiveness in dealing with (annual)fluctuations in pest and weed infestation levels as identified by research;

Examples where such data is available include the impact of GM (IR cotton: in India (see Bennett et al (2004),

IMRB (2006) and IMRB (2007)), in Mexico (see Traxler et al (2001) and Monsanto Mexico (annual reports to
the Mexican government)) and in the US (see Sankala & Blumenthal (2003 and 2006), Mullins & Hudson(2004))©PG Economics Ltd 202225

GM crop impact: 1996-2020

•

•

•

Uses current farm level crop prices and bases any yield impacts on (adjusted – see below)
current average yields. In this way some degree of dynamic has been introduced into theanalysis that would, otherwise, be missing if constant prices and average yields identified
in year-specific studies had been used;
Includes some changes and updates to the impact assumptions identified in the literature
based on consultation with local sources (analysts, industry representatives) so as tobetter reflect prevailing/changing conditions (eg, pest and weed pressure, cost oftechnology);
Adjusts downwards the average base yield (in cases where GM technology has been
identified as having delivered yield improvements) on which the yield enhancement has
been applied. In this way, the impact on total production is not overstated (seeAppendix 1 for examples).

Appendix 2 also provides details of the impacts, assumptions applied and sources.
Other aspects of the methodology used to estimate the impact on direct farm income are as
follows:•••

Impact is quantified at the trait and crop level, including where stacked traits areavailable to farmers. Where stacked traits have been used, the individual trait
components were analysed separately to ensure estimates of all traits were calculated;
All values presented are nominal for the year shown and the base currency used is the
US dollar. All financial impacts in other currencies have been converted to US dollars at
prevailing annual average exchange rates for each year;
The analysis focuses on changes in farm income in each year arising from impact of GM
technology on yields, key costs of production (notably seed cost and crop protection
expenditure, but also impact on costs such as fuel and labour 17), crop quality (eg,
improvements in quality arising from less pest damage or lower levels of weed
impurities which result in price premia being obtained from buyers) and the scope forfacilitating the planting of a second crop in a season (eg, second crop soybeans inArgentina following wheat that would, in the absence of the GM HT seed, probably nothave been planted). Thus, the farm income effect measured is essentially a gross margin
impact (impact on gross revenue, less variable costs of production) rather than a full net
cost of production assessment. Through the inclusion of yield impacts and theapplication of actual (average) farm prices for each year, the analysis also indirectly takes
into account the possible impact of biotech crop adoption on global crop supply andworld prices.

The section also examines some of the more intangible (more difficult to quantify) economic
impacts of GM technology. The literature in this area is much more limited and in terms ofaiming to quantify these impacts, largely restricted to the US-specific studies. The findings of this17

Where available – information and analysis on these costs is more limited than the impacts on seed and crop

protection costs because only a few of the papers reviewed have included consideration of such costs. In mostcases the analysis relates to impact of crop protection and seed cost only

©PG Economics Ltd 2022

26

GM crop impact: 1996-2020

research are summarised 18 and extrapolated to the cumulative biotech crop planted areas in the
US over the period 1996-2020.
Lastly, the paper includes estimates of the production impacts of GM technology at the croplevel. These have been aggregated to provide the reader with a global perspective of the broader
production impact of the technology. These impacts derive from the yield impacts (where
identified), but also from the facilitation of additional cropping within a season (notably in
relation to soybeans in South America).
The section is structured on a trait and country basis highlighting the key farm level impacts.

3.1 Herbicide tolerant crops
GM HT crops were amongst the first to be widely grown, with most largely tolerant to theherbicide active ingredient glyphosate. The main economic impact of this technology has been toprovide more cost effective (less expensive) and easier weed control for farmers. Nevertheless,some users of this technology have also derived higher yields from better weed control (relative
to weed control obtained from conventional technology). As detailed in the following subsections, the impact varies by country and year, and is due to several factors. These include thechanging costs of different weed control systems used in GM HT versus conventional (non-GM)
crops, which may include different/alternative herbicides and/or other forms of weed control (eg,hand or mechanical weeding), the mix and amounts of herbicides applied, the cost farmers pay
for accessing the GM HT technology and levels of weed problems faced by farmers. In turn,there are a number of important and changing variables affecting the mix and cost of different
weed control systems used:
•

•

18

The mix and amounts of herbicides used are affected by price and availability ofherbicides. Herbicides used include both ‘older’ products that are no longer protected bypatents and newer ‘patent-protected’ chemistry, with availability affected by commercial
decisions of suppliers to market or withdraw products from markets and regulation (eg,changes to approval processes and the imposition of restrictions/bans). Prices also varyby year and country;
The amount farmers pay for use of the technology varies by country and year. Pricing oftechnology (all forms of seed and crop protection technology, not just GM technology)
varies according to the level of benefit that farmers are likely to derive from it. In
addition, it is influenced by intellectual property rights (patent protection, plant breeders’rights and rules relating to use of farm-saved seed). In countries with weaker intellectual
property rights, the cost of the technology tends to be lower than in countries where there
are stronger rights. Also, the HT technology available in 2020 is, in some countries, notthe same as the technology available in the early years of adoption. In the first 15-20
years of widespread use of GM HT crop technology, crops tolerant to glyphosate
dominated. In 2020, some farmers, notably in North America, now have the option ofusing seed tolerant to glyphosate plus other active ingredients like glufosinate, 2 4 D anddicamba. These forms of ‘stacked’ tolerances are typically more expensive than the single
herbicide tolerance traits of the early years of use;

Notably relating to the US - Marra and Piggott (2006)©PG Economics Ltd 202227

GM crop impact: 1996-2020•

Where GM HT crops tolerant to glyphosate have been widely grown for a number ofyears, some incidence of weed resistance to glyphosate has occurred and resistance has
become a major concern in some regions. Detailed discussion of this issue is presented in
section 4 (environmental impacts). From a farm economic perspective, this resulted ingrowers of GM HT crops increasingly including other herbicides (with different andcomplementary modes of action) in combination with glyphosate in their weed
management systems. In addition, in the last 4-5 years, the increasing array of new GM
HT technology referred to above has entered the market offering farmers (notably in the
US and Canada in 2020) crops that are tolerant to other herbicide active ingredientstypically in combination with tolerance to glyphosate (and sometimes offering tolerance
to three active ingredients). At the macro level, these changes have influenced the mix,
total amount, cost and overall profile of herbicides applied to GM HT crops. It has also
resulted in the weed control costs associated with growing GM HT crops generally being
higher in 2020 than in the early 2000s. However, relative to the conventional alternative,
GM HT crops have continued to offer important economic advantages for most users,
either in the form of lower costs of production or higher yields (arising from better weed
control). An important contributory factor to this (maintenance of cost saving advantage
of GM HT systems versus conventional alternatives) is that many of the herbicides usedin conventional production systems also face significant weed resistance issues
themselves (in the mid-1990s this was one of the reasons why glyphosate tolerantsoybeans were rapidly adopted, as glyphosate provided good control of these weeds).

These points are further illustrated in the analysis below.

3.1.1 GM HT soybeans
3.1.1.1 The US
First generation GM HT soybeans
In 2020, 94% (33.3 million ha) of the total US soybean crop was planted to seed with GM HT
traits. Of this, 3.8 million ha (11% of the total GM HT crop) were first generation GM HT
soybeans. The farm level impact of using this technology since 1996 is summarised in Figure 13.
The key features are as follows:••

The primary impact has been to reduce the cost of weed control, with the annual savings
being within a range of between $25/ha and $85/ha (based on a comparison of
conventional herbicide regimes that are required to deliver a comparable level of weed
control to the GM HT soybean system). Of note are the periods immediately after 2000,
when glyphosate was no longer patent protected in the US, resulting in increased
availability of alternative (generic) and cheaper glyphosate and the period between 2008
and 2010, when there was a significant increase in the global price of glyphosate relative
to increases in the price of other herbicides (commonly used on conventional soybeans).
In addition, the problem of weed species becoming resistant to glyphosate and to otherherbicides used in soybean production (both GM HT and conventional) during the last 20
years has influenced the mix, volume; cost and overall profile of herbicides applied toboth forms of production;
Against the background of underlying improvements in average yield levels over the
1996-2020 period (via improvements in plant breeding, including the adoption of second-©PG Economics Ltd 202228

GM crop impact: 1996-2020•

generation HT soybeans – see below), the specific yield impact of the first generation of
GM HT technology has been neutral 19;
The annual total national farm income benefit from using the technology rose from $5
million in 1996 to $1.42 billion in 2007. Since then the aggregate farm income gains havefluctuated and eventually declined as the total area planted to this trait has fallen in linewith increased adoption of second-generation GM HT soybeans (see below). In 2020, thetotal income gain from first generation HT soybeans was $58.8 million. The cumulative
farm income benefit over the 1996-2020 period (in nominal terms) was $14.06 billion.

Figure 13: Farm level savings of using GM HT soybeans (first generation) in the US 1996-2020($/ha)
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0

Impact on margins after deduction of cost of technology

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0

Impact on weed control costs

Sources and notes:
1. Impact data 1996-1997 based on Marra et al (2002), 1998-2000 based on Carpenter and Gianessi(1999) and 2001-2007 based on Sankala & Blumenthal (2003 & 2006), Johnson and Strom (2008).
2008 onwards own calculations based on commonly used weed control programmes and current(each year) prices of herbicides. The weed control systems, usage levels and prices are drawn froma combination of extension services and Kynetec annual farmer (survey) data
2. The higher values for the cost savings in 2001 onwards reflect the methodology used by Sankala &Blumenthal, which was to examine the conventional herbicide regime that would be required todeliver the same level of weed control in a low/reduced till system to that delivered from the GM
HT no/reduced till soybean system. This is a more robust methodology than some of the more
simplistic alternatives used elsewhere. In earlier years the cost savings were based on comparisons19

Some early studies of the impact of GM HT soybeans in the US suggested that GM HT soybeans produced

lower yields than conventional soybean varieties. Where this may have occurred, it applied only in earlyyears of adoption, when the technology was not present in all leading varieties suitable for all of the main
growing regions of the US. By 1998/99 the technology was available in leading varieties and no statisticallysignificant average yield differences have been found between GM (first generation) and conventional
soybean varieties©PG Economics Ltd 202229

GM crop impact: 1996-2020

between GM HT soy growers and/or conventional herbicide regimes that were commonplace prior
to commercialisation in the mid-1990s when conventional tillage systems were more important

Second generation GM HT soybeans
A second generation of GM HT soybeans became available to commercial soybean growers in the
US in 2009. It was planted on 27.6 million ha in 2020 (83% of the total crop). The technology
offered the same tolerance to glyphosate as the first generation (and the same cost saving) but
with higher yielding potential. Pre-launch trials of the technology suggested that average yields
would increase by between +7% and +11%. Only limited seed was initially available for planting
in 2009 and the trait was not available in many of the leading (best performing) varieties. As aresult, reports of first year performance 20 were varied when compared with the first generation of
GM HT soybeans (which was available in all leading varieties), with some farmers reporting no
improvement in yield relative to first generation GM HT soybeans whilst others found significant
improvements in yield, of up to +10%. In 2010, when the trait was available in many more of theleading varieties, farmer feedback to the seed/technology providers reported average yield
improvements of about +5%. In subsequent years, the average yield gains reported were higher
in the range of +9% to +11% relative to first generation GM HT and conventional soybean crops.
Applying these yield gains plus the same cost saving assumptions as applied to first generation
GM HT soybeans, but with a seed premium of between $50/ha and $67/ha (average $55.5/ha until
2018 but having fallen to +$30/ha in 2020), the net impact on farm income in 2020, inclusive ofyield gain, was +$112/ha (Figure 14). Aggregated to the national level this was equal to an
improvement in farm income of $3.1 billion in 2020 and cumulatively since 2009, the total farmincome gain has been $22.8 billion.
Figure 14: Average farm income gain from using 2nd generation GM HT soybeans in the US
1996-2020 ($/ha)
180.00161.08160.00145.28140.00129.37120.00111.26110.0296.33

100.00107.67104.57107.65112.48

72.87

80.00
60.00
40.00

40.85

20.00
-

20

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

The authors are not aware of any survey-based assessment of performance in 2009

©PG Economics Ltd 2022

30

2019

2020

GM crop impact: 1996-2020

3.1.1.2 Argentina
As in the US, first generation GM HT soybeans were planted commercially from 1996. Since
then, use of the technology has increased rapidly and almost all soybeans grown in Argentina are
GM HT (97.1%) in 2020. The impact on farm income has been substantial, with farmers deriving
important cost saving and farm income benefits both similar and additional to those obtained in
the US (Figure 15). More specifically:
•
•

•

•

•

•

21

The impact on yield has been neutral (ie, no positive or negative yield impact);
The cost of the technology to Argentine farmers has been substantially lower than in the
US (about $1/ha-$4/ha compared to $15/ha-$57/ha in the US) mainly because the maintechnology provider (Monsanto) was not able to obtain patent protection for thetechnology in Argentina. As such, Argentine farmers have been free to save and use GM
HT first generation seed without paying any technology fees or royalties (on farm-savedseed) for many years;
The savings from reduced expenditure on herbicides, fewer spray runs and machinery
use have been in the range of $14-$33/ha. Net income gains have been in the range of$14/ha-$30/ha;
The net income gain from use of the GM HT technology at a national level was $227
million in 2020. Since 1996, the cumulative benefit (in nominal terms) has been $7.5
billion;An additional farm income benefit that many Argentine soybean growers have derived
comes from the additional scope for second cropping of soybeans. This has arisen
because of the simplicity, ease and weed management flexibility provided by the (GM)technology which has been an important factor facilitating the use of no and reduced
tillage production systems. In turn the adoption of low/no tillage production systems has
reduced the time required for harvesting and drilling subsequent crops and hence has
enabled many Argentine farmers to cultivate two crops (wheat followed by soybeans) in
one season. Thirty-two per cent of the total Argentine soybean crop was second crop in2020 21, compared to 8% in 1996. Based on the additional gross margin income derived
from second crop soybeans (see Appendix 2), this has contributed a further boost tonational soybean farm income of $1.4 billion in 2020 and $16.6 billion cumulatively since
1996;
The total farm income benefit inclusive of the second cropping was $1.65 million in 2020
and $24.1 billion cumulatively between 1996 and 2020.

The second crop share was 5.3 million ha in 2020

©PG Economics Ltd 202231

GM crop impact: 1996-2020

Figure 15: Average farm income gain from GM HT soybeans in Argentina 1996-2020 ($/ha)
35.00
30.00
25.00
20.00
15.00
10.00
5.00

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00

Sources and notes:
1. The primary source of information for impact on the costs of production is Qaim & Traxler (2002 &2005). This has been updated in recent years to reflect changes in typical weed control practices,herbicide prices and weed control practices
2. All values for prices and costs denominated in Argentine pesos have been converted to US dollars
at the annual average exchange rate in each year
3. Additional information is available in Appendix 2
4. The net savings to costs understate the total gains in recent years because 70%-80% of GM HT
plantings have been to farm-saved seed on which no seed premium was payable (relative to the $3$4/ha premium charged for new seed)
5. From 2013/14, second generation GM soybeans (tolerant to glyphosate and insect resistant)soybeans became available. The area planted to single trait (GM HT) soybeans has therefore
subsequently declined as increasing numbers of farmers plant the stacked (HT and IR) soybeans

3.1.1.3 Brazil
GM HT soybeans were probably first planted in Brazil in 1997. Since then, the area planted has
increased to 96% of the total crop in 2020 22.
The impact of using GM HT soybeans has been similar to that identified in the US and Argentina.
The net savings on herbicide costs have been larger in Brazil, due to higher average costs of weed
control. Hence, the average cost savings arising from a combination of reduced herbicide use,
fewer spray runs, labour and machinery savings, were between $20/ha and $81/ha in the period
2003 to 2020 (Table 5). The net cost saving after deduction of the technology fee (assumed to be$8.8/ha in 2020) has been between $9/ha and $44/ha in recent years. At a national level, theadoption of GM HT soybeans increased farm income levels by $424.4 million in 2020.
Cumulatively over the period 1997 to 2020, farm incomes have risen by $9.08 billion (in nominal
terms).

22

Until 2003 all plantings were technically illegal©PG Economics Ltd 202232

GM crop impact: 1996-2020

Table 5: Farm level income impact of using GM HT soybeans in Brazil 1997-2020
Year

Cost savings ($/ha)

Net cost saving after inclusionof technology cost ($/ha)
35.19
38.51
35.15
31.71
42.71
36.39
68.00
61.66
57.23
61.32
8.74
44.44
27.68
37.8
20.76
20.75
30.14
30.23
19.67
32.60
38.30
33.28
31.12
32.68

Impact on farm income at anational level ($ millions)
3.8
20.5
43.5
43.7
58.7
66.7
214.7
320.9
534.6
730.6
116.3
591.9
448.4
694.1
426.2
511.1
766.7
724.9
364.6
502.2
603.2
444.5
390.9
424.4

1997
38.8
1998
42.12
1999
38.76
2000
65.32
2001
46.32
2002
40.00
2003
77.00
2004
76.66
2005
73.39
2006
81.09
2007
29.85
2008
64.07
2009
47.93
2010
57.28
2011
45.57
2012
32.27
2013
42.2
2014
41.28
2015
26.79
2016
40.05
2017
42.48
2018
42.04
2019
39.88
2020
41.44
Sources and notes:
1. Impact data based on 2004 comparison data from the Parana Department of Agriculture (2004)
Cost of production comparison: biotech and conventional soybeans, in USDA GAIN report BR4629
of 11 November 2004. www.fas.usad.gov/gainfiles/200411/146118108.pdf for the period to 2006.
From 2007 based on Galvao (2009, 2010, 2012, 2013, 2014, 2015), Kleffmann herbicide usage dataand own analysis
2. Cost of the technology from 2003 is based on the royalty payments officially levied by thetechnology providers. For years up to 2002, the cost of technology is based on costs of buying newseed in Argentina (the source of the seed). This probably overstates the real cost of the technology
and understates the cost savings
3. All values for prices and costs denominated in Brazilian Real have been converted to US dollars at
the annual average exchange rate in each year
4. From 2013/14, second generation GM soybeans (tolerant to glyphosate and insect resistant)soybeans became available. The area planted to single trait (GM HT) soybeans has therefore
subsequently declined as increasing numbers of farmers plant the stacked (HT and IR) soybeans

3.1.1.4 Paraguay and Uruguay
GM HT soybeans have been grown since 1999 and 2000 respectively in Paraguay and Uruguay.
In 2020, they accounted for 98% of total soybean plantings in both countries 23. Using the original
farm level impact data derived from Argentine research (on conventional alternatives) and23

As in Argentina, the majority of plantings are to farm saved or uncertified seed

©PG Economics Ltd 2022

33

GM crop impact: 1996-2020

applying this to production in these two countries together with subsequent updating of GM HT
production that reflects changes in herbicide usage and cost data (sources AMIS
Global/Kleffmann) 24, Figure 16 summarises the national farm level income benefits that havebeen derived from using the technology.
In 2020, the respective national farm income gains were $27 million in Paraguay ($127.1 million
including second crop benefits) and $17.1 million in Uruguay. Cumulatively, the farm income
gains for the period 1999-2020 have been $1.66 billion in Paraguay and $271.8 million in Uruguay.
Figure 16: National farm income benefit from using GM HT soybeans in Paraguay and
Uruguay 1999-2020 (million $)160.00140.00120.00100.00Million $
80.00
60.00
40.00
20.00
0.00

1999

2001

2003

2005

2007

Paraguay

2009

2011

2013

2015

2017

2019

Uruguay

Note: First year of adoption: Paraguay 1999, Uruguay 2000

3.1.1.5 CanadaFirst generation GM HT soybeans
GM HT soybeans were first planted in Canada in 1997. In 2020, the share of total plantings
accounted for by first generation GM HT soybeans was 7% (0.14 million ha).
At the farm level, the main impacts of use have been similar to the impacts in the US. The
average reduction in weed control costs has been within a range of $42/ha and $80/ha and theaverage farm income benefit (after deduction for the extra cost of the seed technology) has been
within a range of $14/ha-$41/ha (Figure 17).
At the national level, the increase in farm income was $4.3 million in 2020 and since 1997, thecumulative increase in farm income has been $232.3 million (in nominal terms).

24

Qaim & Traxler (2002 & 2005). The authors are not aware of any specific impact research having been

conducted and published in Paraguay or Uruguay. Cost of herbicide data for recent years has been updated
to reflect price and weed control practice changes in these countries (source: based on AMIS
Global/Kleffmann/Kynetec)©PG Economics Ltd 2022

34

GM crop impact: 1996-2020

Figure 17: Farm level income impact of using GM HT soybeans (first generation) in Canada
1997-2020 ($/ha)
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0

Wedd cost savings

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

-

Impact on farm income after deduction of cost of technology

Sources and notes:
1. Impact data based on George Morris Centre Report 2004 and updated in recent years to reflectchanges in herbicide prices and weed control practices
2. Original values for prices and costs denominated in Canadian dollars have been converted to US
dollars at the annual average exchange rate in each year

Second generation GM HT soybeans
As in the US, 2009 was the first year of commercial availability of second-generation GM HT
soybeans. Seed containing this trait was planted on 1.62 million ha in 2020, equal to 79% of thetotal crop. In the absence of Canadian-specific impact data, we have applied the same cost oftechnology and yield impact assumptions as used in the analysis of impact in the US. On thisbasis, the net impact on farm income was +$132.3/ha in 2020, with an aggregate increase in farmincome of +$213.8 million. Since 2009, the total farm income gain has been $1.3 billion.

3.1.1.6 South Africa
The first year GM HT soybeans were planted commercially in South Africa was 2001. In 2020,
786,000 hectares (95%) of total soybean plantings were to varieties containing the GM HT trait. In
terms of impact at the farm level, the average reduction in weed control costs has been within arange of $9/ha and $36/ha. After deduction of the cost of the technology, the average farmincome gain has been within a range of 40.5/ha and £13/ha (Figure 18). At the national level, theincrease in farm income was $11.3 million in 2020. Cumulatively the farm income gain since 2001
has been $68.3 million 25.

25This possibly understates the beneficial impact because it does not take into consideration any savings fromreduced labour for hand weeding for some farms©PG Economics Ltd 202235

GM crop impact: 1996-2020

Figure 18: Farm level income impact of using GM HT soybeans in South Africa 2001-2020($/ha)
16.00
13.36

14.00

11.89

12.00
9.11 9.12

10.00
8.00
6.00

8.70

7.93

6.97
5.69

5.56

5.17 5.01

7.94

15.09
14.42

11.73

8.72

4.51

4.00
1.95

1.77

2.00

0.54

0.00

Sources and notes:
1. Impact data, based on Kleffmann herbicide usage data, own analysis, Gouse (2014) and MonsantoSouth Africa
2. All values for prices and costs denominated in South African Rand have been converted to US
dollars at the annual average exchange rate in each year
3. The average cost of the technology in South Africa is very low (on a per hectare basis) at no morethan $2-$3/ha. This reflects the high level of farm-saved seed typically used ((80%-85% of the crop)on which no seed premium (for the technology) is payable

3.1.1.7 Romania
Farmers in Romania have not been permitted to plant GM HT soybeans since the country joined
the EU at the start of 2007 (the EU regulatory authorities have not completed the process ofevaluating past applications for the approval for planting GM HT soybeans and currently there isno ongoing application for approval for planting first generation GM HT soybeans in the EU).
The impact data presented below therefore covers the period 1999-2006.
The growing of GM HT soybeans in Romania had resulted in substantially greater net farmincome gains per hectare than any of the other countries using the technology:•

Yield gains of an average of 31% 26 have been recorded. This yield gain has arisen fromthe substantial improvements in weed control 27. In recent years, as fields have been

26

Source: Brookes (2005)

27

Weed infestation levels, particularly of difficult to control weeds such as Johnson grass, have been very highin Romania. This is largely a legacy of the economic transition during the 1990s which resulted in very low
levels of farm income, abandonment of land and very low levels of weed control. As a result, the weed bankdeveloped substantially and has subsequently been very difficult to control, until the GM HT soybean systembecame available (glyphosate has been the key to controlling difficult weeds like Johnson grass)©PG Economics Ltd 202236

GM crop impact: 1996-2020

•

•
•

•

cleaned of problem weeds, the average yield gains have decreased and were reported at+13% in 2006 28;
The cost of the technology to farmers in Romania tended to be higher than othercountries, with seed being sold in conjunction with the herbicide. For example, in the
2002-2006 period, the average cost of seed and herbicide per hectare was $120/ha to$130/ha. This relatively high cost, however, did not deter adoption of the technology
because of the major yield gains, improvements in the quality of soybeans produced(less weed material in the beans sold to crushers which resulted in price premia being
obtained 29) and cost savings derived;
The average net increase in gross margin in 2006 was $59/ha (an average of $104/ha overthe eight years of commercial use: Table 6);
At the national level, the increase in farm income amounted to $7.6 million in 2006.
Cumulatively in the period 1999-2006 the increase in farm income was $44.6 million (innominal terms);
The yield gains in 2006 were equivalent to a 9% increase in national production 30 (theannual average increase in production over the eight years was equal to 10.1%).

Table 6: Farm level income impact of using herbicide tolerant soybeans in Romania 1999-2006
Year

Cost saving($/ha)

Cost savings netof cost oftechnology ($/ha)

Net increasein grossmargin ($/ha)

Impact on farmincome at anational level ($millions)

Increase innational farmincome as % offarm level valueof national
production
4.0
8.2
10.3
14.6
12.7
13.7
12.2
9.3

1999
162.082.08
105.181.63
2000
140.30
-19.7
89.14
3.21
2001
147.33-0.67
107.171.93
2002
167.8032.8
157.41
5.19
2003
206.7076.7
219.01
8.76
2004
63.33
8.81
135.86
9.51
2005
64.54
9.10
76.16
6.69
2006
64.99
9.10
58.79
7.64
Sources and notes:
1. Impact data (sources: Brookes (2005) and Monsanto Romania (2008)). Average yield increase 31%
applied to all years to 2003 and reduced to +25% 2004, +19% 2005 and +13% 2006. Average
improvement in price premia from high quality 2% applied to years 1999-2004
2. All values for prices and costs denominated in Romanian Lei have been converted to US dollars at
the annual average exchange rate in each year
3. Technology cost includes cost of herbicides
4. The technology was not permitted to be planted from 2007 – due to Romania joining the EU

28

Source: Farmer survey conducted in 2006 on behalf of Monsanto Romania

29

Industry sources report that price premia for cleaner crops were no longer payable by crushers from 2005

and hence this element has been discontinued in the subsequent analysis
30

Derived by calculating the yield gains made on the GM HT area and comparing this increase in production

relative to total soybean production©PG Economics Ltd 202237

GM crop impact: 1996-2020

3.1.1.8 Mexico
GM HT soybeans were first planted commercially in Mexico in 1997 on a trial basis and wereallowed ‘unrestricted’ from 2012. However, adoption levels have typically remained below 10%of the total crop and 2016 was the last year when GM HT soybeans were planted (2,810 ha - out of
total plantings of 211,000 ha). Since 2016 there have been no plantings, due to the permission forplanting having been revoked by the Mexican regulatory authorities. Therefore, the impact
analysis presented below relates to the period to 2016.
The main impacts of use derived from a combination of yield increase (a range of +2% to +13%,
varying on a yearly basis) from better weed control and (herbicide) cost savings. However, as the
GM HT trait was only made available in a limited number of varieties, and, more importantly, it
was not available in leading/latest varieties, the average yield of the varieties containing the GM
HT trait have tended to lag behind the yields obtained from the leading varieties (despite
improvements in weed control) since 2014 (the recorded average yield difference between the
GM HT soybeans and conventional alternatives has been between -1% and -2% post 2014). As aresult, the average farm income impact over the period of all adoption (inclusive of the pilot
planting years from 2004) has been within a range of -$3/ha in the most recent years of adoption
to +$89/ha in the early years of adoption when positive yield gains and weed control cost savings
were obtainable. In 2016, the last year of adoption, the net income effect was marginally positive(+$6/ha), as the cost savings associated with lower weed control with the GM HT soybeans were
marginally higher than the revenue loss from a lower average yield of -1.8% (Table 7).
Table 7: Farm level income impact of using GM HT soybeans in Mexico 2004-2016
Year

Cost savings after
Net cost saving/increase in gross
Impact on farm income at a
inclusion of seedmargin (inclusive of technology
national level ($ millions)premium ($/ha)cost & yield gain: $/ha)
2004
49.44
82.34
1.18
2005
51.20
89.41
0.94
2006
51.20
72.98
0.51
2007
51.05
66.84
0.33
2008
33.05
54.13
0.54
2009
-12.79
59.55
1.01
2010
-12.84
9.29
0.19
2011
-12.25
12.71
0.19
2012
-12.32
23.42
0.15
2013
14.33
87.86
1.0
2014
18.81
0.08
0.01
2015
0.56
-3.03
-0.05
2016
22.61
5.96
0.02
Sources and notes:
1. Impact data based on Monsanto, 2005, 2007, 2008, 2009, 2010, 2013, 2014, 2015, 2016. Reportes final
del programa Soya Solución Faena en Chiapas. Monsanto Comercial
2. All values for prices and costs denominated in Mexican pesos have been converted to US dollars at
the annual average exchange rate in each year
3. Negative yields in 2014-2016 reflect a combination of drought in the main regions where GM HT
soybeans are grown and the trait not being available in some leading varieties©PG Economics Ltd 202238

GM crop impact: 1996-2020

3.1.1.9 Bolivia
GM HT soybeans were officially permitted for planting in 2009, although ‘illegal’ plantings had
occurred for several years beforehand. For the purposes of analysis in this section, impacts havebeen calculated back to 2005, when an estimated 0.3 million ha of soybeans used GM HT
technology. In 2020, 1.35 million ha (97% of total crop) used GM HT technology.
The main impacts of the technology 31 have been (Table 8):
•

•

•
•

An increase in yield arising from improved yield control. The research work conductedby Fernandez et al (2009) estimated a 30% yield difference between GM HT andconventional soybeans; although some of the yield gain reflected the use of poor-quality
conventional seed by some farmers. In our analysis, we have used a more conservative
yield gain of +15% (based on industry views);
GM HT soybeans are assumed to trade at a price discount to conventional soybeans of
2.7%, reflecting the higher price set for conventional soybeans by the Bolivian
government in 2020;
The cost of the technology to farmers has been $3.3/ha and the cost savings equal to$9.3/ha, resulting in a change of +$6/ha to the overall cost of production;
In 2020, the average farm income gain from using GM HT soybeans was $28.6/ha,
resulting in a total farm income gain of $38.6 million. Cumulatively since 2005, the total
farm income gain is estimated at $957.1 million.

Table 8: Farm level income impact of using GM HT soybeans in Bolivia 2005-2020
Year

Net cost saving/increase in gross margin
Impact on farm income at a national level ($(inclusive of technology cost & yield
millions)
gain: $/ha)
2005
39.73
12.08
2006
36.60
15.55
2007
44.40
19.45
2008
79.97
36.27
2009
89.91
59.61
2010
103.1380.15
2011
106.68105.692012
109.60105.22
2013
102.7593.81
2014
101.01
107.31
2015
84.08
86.09
2016
52.11
53.58
2017
42.05
53.56
2018
35.14
44.76
2019
33.80
44.59
2020
28.62
38.59
Sources and notes:
1. Impact data based on Fernandez et al (2009). Average yield gain assumed +15%, cost of technology$3.32/ha31

Based on Fernandez et al (2009)©PG Economics Ltd 202239

GM crop impact: 1996-2020

3.1.1.10 Summary of global economic impact
In global terms, the farm level impact of using GM HT technology in soybeans (excluding Intacta:
see section 3.1.2) was $4.12 billion in 2020 (Figure 19). If the second crop benefits arising inArgentina are included the total is $5.64 billion. Cumulatively since 1996, the farm income
benefit has been (in nominal terms) $57 billion ($74.65 billion if second crop gains in Argentina
and Paraguay are included).
In terms of the total value of global soybean production in 2020, the additional farm income(inclusive of Argentine second crop gains) generated by the technology is equal to a value-added
equivalent of 5.6%.
These economic benefits should be placed within the context of a significant increase in the levelof soybean production in the main GM adopting countries since 1996 (more than a doubling in
the area planted in the leading soybean producing countries of the US, Brazil and Argentina).
These economic benefits mostly derive from cost savings although farmers in Mexico, Bolivia andRomania also obtained yield gains (from significant improvements in weed control levels relative
to levels applicable prior to the introduction of the technology). In addition, the availability of
second-generation GM HT soybeans in North America since 2009 is also delivering yield gains. If
it is also assumed that all of the second crop soybean gains are effectively additional productionthat would not otherwise have occurred without the GM HT technology (the GM HT technology
facilitated major expansion of second crop soybeans in Argentina and to a lesser extent inParaguay), then these gains are de facto 'yield' gains. Under this assumption, of the total
cumulative farm income gains from using GM HT soybeans, $43 billion (58%) is due to yieldgains/second crop benefits and the balance, 42%, is due to cost savings.
Figure 19: Global farm level income benefits derived from using GM HT soybeans 1996-2020(million $)
4,500
4,000

million $

3,500
3,000
2,500
2,000
1,500
1,000
500
0

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
Direct benefits
Arg and Para 2nd crop

©PG Economics Ltd 202240

GM crop impact: 1996-2020

3.1.2 Insect resistant soybeans
Second generation GM soybeans comprising both HT and IR traits (Intacta) were available tofarmers in four South American countries for the first time in 2013-14. A summary of the
adoption and key features of impact over the eight-year period to 2020-21 is shown in Table 9.
The total farm income gain recorded on a cumulative total usage area of 155.8 million ha was$16.05 billion.
Table 9: Main impacts of insect resistant soybeans 2013/14 to 2020/21
Cumulative
area planted(‘000 ha)Average yieldgain (%)

Average costof technology(seedpremium)($/ha)
36.84
26.25
37.22
29.63

Average farmincome gain($/ha)

Aggregate
farm income
gain (million$)

Brazil123,141+9.4
107.2013,200.7
Argentina
20,869+7.2
73.56
1,535.0
Paraguay
9,454
+13.4
121.39
1,147.6
Uruguay
2,367
+7.3
70.68
167.3
Total
9.3
16,050Notes:
1. Impact data based on pre-commercial trials in 2011 and 2013 and post production farm surveys(post market monitoring: Monsanto/Bayer)
2. Impact on cost of production includes herbicide cost savings, as indicated in section 3.1.1 for first
generation HT soybeans plus insecticide use savings of about $12/ha in Brazil, $11/ha in Argentina,$40/ha in Paraguay and $14/ha in Uruguay

3.1.3 Herbicide tolerant maize
3.1.3.1 The US
Herbicide tolerant maize 32 has been used commercially in the US since 1997 and in 2020 was
planted on 89% of the total US maize crop. The impact of using this technology at the farm levelis summarised in Figure 20. As with herbicide tolerant soybeans, the main benefit has been to
reduce costs, and hence improve profitability levels. The average cost of the technology (seedpremium over the period 1996-2020 has been $24.38/ha ($24.82/ha in 2020) and the average weed
control cost savings equal to $56.98/ha ($57.48/ha in 2020). Average profitability has therefore
improved by $30.98/ha over the 1996-2020 period ($32.61/ha in 2020). The net gain to farmincome in 2020 was $968.4 million and cumulatively, since 1997, the farm income benefit has been
$12.74 billion.

32

Tolerant to glufosinate ammonium or to glyphosate (or both herbicides), although cultivars tolerant toglyphosate have accounted for the majority of plantings. Also, corn varieties tolerant to these two herbicides
plus tolerance to 2 4 D from 2017

©PG Economics Ltd 2022

41

GM crop impact: 1996-2020

Figure 20: Farm income impact of using GM HT maize in the US 1997-2020 ($/ha)
50.0

46.7

45.0
36.1

40.0
35.0

25.3

30.0 25.1
25.3
25.0

33.2

25.2

25.1
25.1
25.1
25.0 23.9

38.9
36.2

38.8

33.5
32.1

32.6

25.9
20.3

20.0

14.2

15.0

17.9
16.1 16.5

10.0
5.0
0.0
1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

2019

Source and notes: Impact analysis based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 &2006), Johnson & Strom (2008) and updated from 2008 to reflect changes in herbicide prices and typical
weed control programmes

3.1.3.2 Canada
In Canada, GM HT maize was first planted commercially in 1999. In 2020, the proportion of total
plantings accounted for by varieties containing a GM HT trait was 98%. As in the US, the main
benefit has been to reduce costs and to improve profitability levels (Figure 21). Average annual
profitability has improved by $12.4/ha over the period 1999-2020, based on weed control savingsof $42/ha less the average additional cost of the technology over this period of $29.69/ha. In 2020,
the average farm income gain was $14.1/ha (seed premium $31.61/ha) resulting in an aggregate
increase in farm income of $19.4 million. Since 1999 the farm income benefit has been $225.4
million.

©PG Economics Ltd 202242

GM crop impact: 1996-2020

Figure 21: Farm level income impact of using GM HT maize in Canada 1999-2020 ($/ha)
25.0

23.5
20.0

20.0

16.6
14.7

15.0

14.6
14.0

17.9

15.6
13.9

12.5

14.4 14.1

13.0
10.1

9.5

10.0

9.2

9.5
8.6

9.0

8.9

6.6

6.1
5.0

0.0

Source and notes: Impact analysis based on data from Ontario Ministry of Agriculture, Kleffmann/Kynetec
herbicide usage data and Monsanto/Bayer Canada

3.1.3.3 Argentina
GM HT maize was first planted commercially in Argentina in 2004, and in 2020, varieties
containing a GM HT trait were planted on 6.27 million ha (98% of the total maize area). It has
been adopted in two distinct types of area, the majority (80%) in the traditional ‘corn production
belt’ and 20% in newer maize-growing regions, which have traditionally been known as moremarginal areas that surround the ‘Corn Belt’. Initially the HT trait was available as a single trait
in seed only and there was limited take up until stacked traited seed, containing both the HT and
IR trait became available in 2007. Following this there was more rapid adoption, so that in 2020,
when 92% of the total crop used varieties containing an HT trait, 96% of this seed was stacked
seed.
In relation to impact on farm income, this can be examined from two perspectives; as a single GM
HT trait and as a stacked trait. This differential nature of impact largely reflects the locations inwhich the different (single or stacked-traited seed) has tended to be used:
Single GM HT traited seed
• In all regions the average cost of the technology has been $16.8/ha over the period 20042020;• In the ‘Corn Belt’ area, use of the single trait technology has resulted in an average 3%
yield improvement via improved weed control. In the more marginal areas, the yield
impact has been much more significant (+22%) as farmers have been able to significantly
improve weed control levels;• The average farm income gain arising from the combination of higher yields and reduced
weed control costs, for the 2004-2020 period has been $97.48/ha;©PG Economics Ltd 202243

GM crop impact: 1996-2020

In 2020, the additional farm income at a national level, from using single traited GM HT
technology, was +$35.4 million, and cumulatively since 2004, the income gain has been
$443.1 million.
Stacked-traited GM HT seed
• The average yield gain identified since adoption has been +15.75% 33. Given the average
yield impact identified for the early years of adoption of the single traited GM IR maize
was +5.5% (see section 3.2.7), our analysis has applied this level of impact to the GM IR
component of the study (section 3.2.7), with the balance attributed to the GM HT trait.
Hence, for the purposes of this analysis, the assumed yield effect of the GM HT trait on
the area planted to GM stacked maize seed is +10.25%;• The average cost of the technology (seed premium) applied to GM HT component for theperiod 2007-2020 has been $18/ha, with the impact on costs of production (other thanseed) assumed to be the same as for single-traited seed;• Based on these assumptions, the net impact on farm income in 2020 was +$102.37/ha,
giving an aggregated national level farm income gain of $551.7 million. Cumulatively
since 2007, the farm income gain has been $4.56 billion.
•

3.1.3.4 South Africa
Herbicide tolerant maize has been grown commercially in South Africa since 2003, and in 2020,
2.16 million hectares out of total plantings of 2.6 million hectares used this trait. Farmers using
the technology have found small net savings in the cost of production (ie, the cost saving fromreduced expenditure on herbicides has been greater than the cost of the technology), with theaverage net farm income gain for the period 2003 to 2020 having been $5/ha (based on an average
cost of technology of $13.5/ha and an average wed control cost reduction of $18.5/ha. In 2020, thenet farm income gain was +$1/ha. At the national level, this is equivalent to a net gain of $2.44
million in 2020 and since 2003, the cumulative income gain has been $102.6 million. Readers
should note that these cost savings do not take into consideration any labour cost saving that may
arise from reduced need for hand weeding. For example, Regier G et al (2013) identified amongst
small farmers in KwaZulu-Natal, savings of over $80/ha from reduced requirement for hand
weeding with the adoption of GM HT maize. It should also be noted that Gouse et al (2012)
found that small farmers (who account for about 5% of total maize production) obtained yieldgains of between +3% and +8% when using this technology relative to conventional maize
growing in which hand weeding was the primary form of weed control practice.

3.1.3.5 Philippines
GM HT maize was first grown commercially in 2006, and in 2020 was planted on 686,000
hectares. The technology has provided higher yields from improved weed control compared toconventionally grown maize using a combination of herbicides and/or hand weeding methods.
In the first two years of adoption, (based on industry sources) this was estimated to be +15% for
the limited number of early adopters. A more detailed analysis by Gonsales et al (2009) drawn
from a larger ‘population’ of adopters, identified an average yield gain of +5%. Over the period
2006-2020, the average cost of the technology (seed premium) has been $39.1/ha ($40.2/ha in2020), which compared to the average reduction in weed control costs of $29.75/ha, resulted in a

33

Based on farm level feedback/surveys to the technology providers©PG Economics Ltd 2022

44

GM crop impact: 1996-2020

net increase in total costs of production of about $9.35/ha 34. Nevertheless, the average impact on
income has been +$28.9/ha due to the higher yields. In 2020, the average net farm income gainfrom using GM HT maize was +$23.34/ha (Figure 22), which at the national level was equal to+$16 million. Cumulatively, since 2006, the total farm income gain has been $237.9 million.
Figure 22: Farm level income impact of using GM HT maize in Philippines 2006-2020 ($/ha)
60.00

54.47

52.52

50.00

45.74
39.39 37.93

40.00
31.56
30.00

20.34

20.00

23.07

26.78 27.24

26.92
21.46 20.99

19.95

23.34

10.00
0.00

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Source and notes: Impact analysis based on data from Gonsales et al (2009), Kleffmann herbicide usage data
and Monsanto/Bayer Philippines

3.1.3.6 Brazil
2020 was the eleventh year in which GM HT maize was planted in Brazil (on 83% of the total
crop: 16.5 million ha). The technology is estimated to have delivered an average yield gain from
improved weed control of 3.5%. The average cost of production has decreased marginally (by$2.5/ha), as the cost of the technology (seed premium: $22.92/ha) has been marginally higher than
the savings from lower weed control costs of $16.9/ha). In net farm income terms, inclusive ofyield gain, the average farm income gain has been $21.6/ha. At the national level, the cumulative
farm income gain has been $2.3 billion (2009-2020).

3.1.3.7 Colombia
GM HT maize was first planted in Colombia in 2009 and in 2020, 109,000 ha (58% of thecommercial total crop) used this technology (in the form of stacked traited seed, with GM IR
technology).
Analysis of its impact is drawn from Brookes (2020), which also draws on a study by Mendez etal (2011) and surveys of maize growers in 2015 and 2017 by Celeres. These analyses examined
the impact for the stacked traited seed but for the purposes of this analysis of the HT trait, all of
the positive yield impact has been assumed to be attributed to the IR trait (presented in section
3.2.1.8 below).
34

Based on own analysis of industry data and Kleffmann/AMIS Global pesticide usage data

©PG Economics Ltd 202245

GM crop impact: 1996-2020

In terms of impact of costs of production, the GM HT part is estimated to have had a net positive
impact on profitability of about $7.8/ha in 2020 (seed premium of $18.4/ha, counterbalanced byweed control cost savings of $26.2/ha: Figure 23). At the national level, the average farm income
gain for the period 2009-2020 has been $13.85/ha (average seed premium of $20.88/ha,
counterbalanced by weed control cost savings of $34.73/ha). The aggregate total income gain in2020 was $0.85 million, with the cumulative gain since 2009 having been $11.18 million.
Figure 23: Farm level income impact of using GM HT maize in Colombia 2009-2020 ($/ha)
50.00
45.00
40.00

37.71

40.17

40.33

41.21

44.04
39.62

36.99
32.76

35.00
30.00

29.71
26.18

23.64

25.00
20.00

32.98

31.89

15.53

16.54

16.61

17.09

19.22

16.58
12.35

15.00

11.48

10.00

9.82

8.84

7.79

2018

2019

2020

5.00
0.00

2009

2010

2011

2012

Weed control cost saving

2013

2014

2015

2016

2017

Farm income impact after deduction of cost of technology

Sources: Derived from Brookes (2020), Mendez et al (2011) and Celeres 2015, 2017

3.1.3.8 Uruguay
Maize farmers in Uruguay gained access to GM HT maize technology in 2011 (via stacked traitedseed) and 90% of the country’s 143,000 ha crop used this technology in 2020. Whilst the authors
are not aware of any studies examining the impact of GM HT maize in Uruguay, applying impact
and cost assumptions based on the neighbouring Argentina, suggests that if only cost of
production changes are assumed (all yield gains are associated with better pest control and none
attributed to improved weed control), then the average seed premium for this technology of$16.17/ha is greater than the average weed control saving of $13.37/ha, resulting in a net loss of$2.8/ha. This is equal to a net loss of about $2.5 million at the national level since 2011. However,
all of the GM maize seed used by farmers is stacked containing the insect resistant and herbicide
tolerant traits and has delivered an average yield gain of +5.5%. Taken in this context, the use of
the technology will have delivered overall improvements in farm income and for quantificationof this, readers should refer to section 3.2.10 for further information on the performance of theinsect resistant maize traited seed.

3.1.3.9 Paraguay
GM HT technology was used for the first time in 2013 in Paraguay, and in 2020, 66% of thecountry’s maize crop (471,740 ha) used seed containing this trait. Based on an average seedpremium of $13.9/ha (source: industry) and an estimated average herbicide cost saving of©PG Economics Ltd 202246

GM crop impact: 1996-2020$15.3/ha (sources: industry and AMIS Global 2013 and 2015), the average farm income gain has
been $2.4/ha (2020 $3.4/ha). At the national level, this was equal to about $0.17 million in 2020
and a cumulative gain of $7.32 million since 2013.

3.1.3.10 Vietnam
GM HT maize was first planted commercially in 2015, and in 2020 was planted on 92,000 ha (9.7%of the total crop). Analysis by Brookes (2017), shows that a yield gain of over 12% has been
identified from the 2015 (first year) trials of the stacked (HT and IR) maize. Further analysis by
Brookes and Dinh (2021) identified an average yield gain for the stacked traited seed of +15.22%.
In this analysis we have assumed that 5% of this yield gain has arisen from improved weed
control (the remaining 10.22% yield gain attributed to the insect pest resistance trait), coupledwith an attributed cost of (HT) technology of $17.12/ha, the average farm income gain over the six
years of adoption has been $72.81/ha. At the national level, this equates to an aggregate net farmincome gain of $23.04 million (2015-2020).

3.1.3.11 Summary of global economic impact
In global terms, the farm level economic impact of using GM HT technology in maize was $1.55
billion in 2020 (62% of which was in the US). Cumulatively since 1997, the farm income benefit
has been (in nominal terms) $20.2 billion. Of this, 61% has been due to cost savings and 39% toyield gains (from improved weed control relative to the level of weed control achieved by
farmers using conventional technology).
The additional farm income generated by the technology is equal to a value-added equivalent of
1.2% of global maize production.

3.1.4 Herbicide tolerant cotton
3.1.4.1 The US
GM HT cotton was first grown commercially in the US in 1997 and in 2020 was planted on 91% of
total cotton plantings 35. The farm income impact of using GM HT cotton is summarised in Figure
24. The primary benefit has been to reduce weed control costs, and hence improve profitability
levels. Over the period to 2020, the average farm income gain has been $16.2/ha. In 2020, the net
income gain was $6.1/ha. Overall, the aggregate net direct farm income impact in 2020 was $19
million (this does not take into consideration any non-pecuniary benefits associated withadoption of the technology: see section 3.4). Cumulatively since 1997 there has been a net farmincome benefit from using the technology of $1.17 billion.

35

Although there have been GM HT cultivars tolerant to glyphosate and glufosinate, glyphosate tolerant

cultivars have dominated©PG Economics Ltd 202247

GM crop impact: 1996-2020

Figure 24: Farm level income impact of using GM HT cotton in the US 1997-2020 ($/ha)
120.00100.00
80.00
60.00
40.00
20.00

Weed control cost savings

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0.00

Farm income impact after deduction of cost of technology

Source and notes:
1.

Early years analysis based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006)
and Johnson & Strom (2008). Post 2008 based on own analysis using data from Kynetec, USDA andextension services

2.

Average cost of technology 1997-2020: $58.1/ha. The significant decrease in net farm income gains
post 2004 largely reflects the availability (and wide adoption) of second-generation HT cotton
which was more expensive than the early traits.

3.1.4.2 Other countries
Australia, Argentina, South Africa, Mexico, Colombia and Brazil are the other countries where
GM HT cotton is grown commercially; from 2000 in Australia, 2001 in South Africa, 2002 in
Argentina, 2005 in Mexico, 2006 in Colombia and 2009 in Brazil. In 2020, 100% (280,000 ha), 100%
16,175 ha), 100% (450,000 ha), 97% (145,500 ha), 56% (4,865 ha) and 81% (1,12,600 ha) respectivelyof the total Australian, Argentine, South African, Mexican, Colombian and Brazilian cotton crops
were planted to GM HT cultivars.
We are not aware of any published research into the impact of GM HT cotton in South Africa,
Argentina, Mexico or Colombia, although in Colombia there is published research (Brookes(2020)) that draws on analysis of the impact of stacked-traited cotton (that combines IR and HT
traits). In Australia, although research has been conducted into the impact of using GM HT
cotton (eg, Doyle et al (2003)) this does not provide quantification of the impact 36. Our analysis

36

This largely survey-based research observed a wide variation of impact with yield and income gains widelyreported for many farmers©PG Economics Ltd 202248

GM crop impact: 1996-2020

summarised below in Table 10 is primarily ‘own analysis’ that draws on the limited publishedanalysis and industry source estimates 37:
Table 10: Summary of cumulative farm level impact of using GM HT cotton: other countries:
Country

Average yield
impact (%)

Average costof technology($/ha)

Average
impact on
farm income($/ha)

Aggregate
farm income
gain (‘000$)+62.53

Averagereduction in
weed control
costs before
deduction oftechnology
cost ($/ha)-90.76Australia(2000-2020)
Argentina(2002-2020)
South Africa(2001-2016)
Mexico (20062020)
Colombia(2006-2020)
Brazil (20092020)

Nil+28.23+145.4+1.6+21.44-26.12+43.39+238.4Nil+16.66-48.61+31.95+8.31+14+51.42-29.10+297.51+546.7+3.5+73.00-90.43+63.72+18.89+1.6+30.83-42.76+53.15+397.3

3.1.4.3 Summary of global economic impact
Across the seven countries using GM HT cotton in 2020, the total farm income impact derived
from using GM HT cotton was +$134.8 million. Cumulatively since 1997, there have been net
farm income gains of $2.53 billion. Of this, 58% has been due to cost savings and 42% to yieldgains (from improved weed control relative to the level of weed control achieved using
conventional technology).

3.1.5 Herbicide tolerant canola
3.1.5.1 Canada
Canada was the first country to commercially use GM HT canola in 1996. Since then the area
planted to varieties containing GM HT traits has increased significantly, and in 2020 was 97% of
the total crop (8.05 million ha of GM HT crop).
The farm level impact of using GM HT canola in Canada since 1996 is summarised in Figure 25.
The key features are as follows:•37

The primary impact in the early years of adoption was increased yields of almost 11%(eg, in 2002 this yield increase was equivalent to an increase in total Canadian canola

Sources: Monsanto Australia, Argentina, South Africa & Mexico, including Annual reports by Monsanto to

the Mexican government (as part of post market monitoring). Also, Kleffmann herbicide usage data in eachcountry and analysis by Galvão (2010-2015) for Brazil©PG Economics Ltd 202249

GM crop impact: 1996-2020

•

•

•

38

production of nearly 7%). In addition, a higher price was achieved from crushers
through supplying cleaner crops (lower levels of weed impurities). With thedevelopment of hybrid varieties using conventional technology, the yield advantage of
GM HT canola relative to conventional alternatives 38 has been eroded. As a result, ouranalysis has applied the yield advantage of +10.7%, associated with the GM HT
technology in its early years of adoption (source: Canola Council study of 2001), to 2003.
From 2004 the yield gain has been based on differences between average annual variety
trial results for ‘Clearfield’ (conventional herbicide tolerant varieties) and biotech
alternatives (see notes to Figure 25 for details). The biotech alternatives have also beendifferentiated into glyphosate tolerant and glufosinate tolerant. The quality premia
associated with cleaner crops (see above) has not been included in the analysis from 2004;
Cost of production (excluding the cost of the technology) has fallen, mainly throughreduced expenditure on herbicides and some savings in fuel and labour. These savings
have annually been between $20/ha and $43/ha. The cost of the technology to 2003 was,however, marginally higher than these savings resulting in a net increase in costs of $3/ha
to $5/ha. On the basis of comparing GM HT canola with ‘Clearfield’ HT canola (from2004), there has, however been a net cost saving of $5/ha and $32/ha;
The overall impact on profitability (inclusive of yield improvements and higher quality)
has been an increase of between $21/ha and $48/ha, up to 2003. On the basis ofcomparing GM HT canola with ‘Clearfield’ HT canola (from 2004), the net increase inprofitability has been between $23/ha and $81/ha;
The annual total national farm income benefit from using the technology has risen from
$6 million in 1996 to $568.9 million in 2020. The cumulative farm income benefit over the
1996-2020 period (in nominal terms) was $7.57 billion.

The main one of which is ‘Clearfield’ conventionally derived herbicide tolerant varieties. Also, hybrid

canola now accounts for the majority of plantings (including some GM hybrids) with the hybrid vigour
delivered by conventional breeding techniques (even in the GM HT (to glyphosate) varieties)©PG Economics Ltd 202250

GM crop impact: 1996-2020

Figure 25: Farm level income impact of using GM HT canola in Canada 1996-2020 ($/ha)
90.00
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00
-10.00Weed control cost savings
Net impact on costs after deduction of cost of technology
Farm income impact inclusive of yield gain

Sources and notes:
1. Impact data based on Canola Council study (2001) to 2003 and Gusta M et al (2009). Includes a
10.7% yield improvement and a 1.27% increase in the price premium earned (cleaner crop withlower levels of weed impurities) until 2003. After 2004 the yield gain has been based on differences
between average annual variety trial results for ‘Clearfield’ and biotech alternatives. The biotech
alternatives have also been differentiated into glyphosate tolerant and glufosinate tolerant. This
resulted in; for GM glyphosate tolerant varieties no yield difference for 2004, 2005, 2008 and 2010,+4% 2006 and 2007, +1.67% 2009, +1.6% 2011, +1.5% 2012, +3.1% 2013, +3.4% 2014, +4.3% 2015, +2.6%
2016, +2.5% 2017, +2.9% 2018, +4.3% 2019 and +2% 2020. For GM glufosinate tolerant varieties, theyield differences were +12% 2004 and 2008, +19% 2005, +10% 2006 and 2007, +11.8% 2009, +10.9%
2010, +4.6% 2011, +4.8% 2012, +10.1% 2013, +11% 2014, +11.6% 2015, +7.3% 2016, +7.5% 2017, +9.5%
2018, +2.6% 2019 and +7.4% 2020
2. Negative values denote a net increase in the cost of production (ie, the cost of the technology was
greater than the other cost (eg, on herbicides) reductions)
3. All values for prices and costs denominated in Canadian dollars have been converted to US dollars
at the annual average exchange rate in each year
4. Values presented are the weighted average changes – with weighting based on the proportion of
the crop area planted to seed containing either glyphosate or glufosinate tolerant varieties

3.1. 5.2 The US
GM HT canola has been planted on a commercial basis in the US since 1999. In 2020, 95% of the
US canola crop was GM HT (688,230 ha).
The farm level impact has been similar to the impact identified in Canada. More specifically:•

Average yields increased by about 6% in the initial years of adoption. As in Canada (seesection 3.1.5.1) the availability of high yielding hybrid conventional varieties has erodedsome of this yield gain relative to conventional alternatives. As a result, the positive
yield impacts post 2004 have been applied on the same basis as in Canada (comparison
with ‘Clearfield’);©PG Economics Ltd 2022

51

GM crop impact: 1996-2020

•

•

•

The cost of the technology has been $12/ha-$17/ha for glufosinate tolerant varieties and$12/ha-$33/ha for glyphosate tolerant varieties. Cost savings (before inclusion of thetechnology costs) have been $1/ha-$45/ha ($11.2/ha in 2020) for glufosinate tolerant
canola and $19-$79/ha for glyphosate tolerant canola ($24/ha 2020);
The net impact on gross margins has been between +$22/ha and +$90/ha ($50.55/ha in2020) for glufosinate tolerant canola, and between +$23/ha and +$61/ha for glyphosate
tolerant canola ($21.54/ha in 2020);
At the national level the total farm income benefit in 2020 was $30.2 million (Figure 26)
and the cumulative benefit since 1999 has been $460 million.

Figure 26: National farm income impact: GM HT canola in the US 1999-2020 (million $)
35.0
30.0

26.8

26.5
22.9
20.2

25.0
Million $

31.1

31.1

18.918.1

20.0

12.8

15.0

17.2

30.2

27.6

21.322.2

24.5
22.4
22.3
21.2

16.0

11.211.4

10.0
5.0

4.1

0.0
1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

2019

Source and notes: Impact analysis based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 &2006), Johnson & Strom (2008) and updated from 2008 to reflect changes in herbicide prices and weed
control practices. Decrease in total farm income impact 2002-2004 is due to decline in total plantings ofcanola in the US (from 612,000 in 2002 to 316,000 ha in 2004). Positive yield impact applied in the same way
as Canada from 2004 – see section 3.1.5.1

3.1.5.3 Australia
GM HT canola was first planted for commercial use in 2008. In 2020, GM HT canola was planted
on 562,500 ha. All of these plantings had tolerance to the herbicide glyphosate.
The main source of data on impact of this technology comes originally from a farm survey-based
analysis of impact of the glyphosate tolerant canola, commissioned by Monsanto amongst 92 of
the 108 farmers using this technology in 2008/09. Key findings from this survey were as follows:•

The technology was made available in both open pollinated and hybrid varieties, withthe open pollinated varieties representing the cheaper end of the seed market, wherecompetition was mainly with open pollinated varieties containing herbicide tolerance(derived conventionally) to herbicides in the triazine (TT) group. The hybrid varieties
containing glyphosate tolerance competed with non-herbicide tolerant conventional
hybrid varieties and herbicide tolerant ‘Clearfield’ hybrids (tolerant to the imidazolinone©PG Economics Ltd 202252

GM crop impact: 1996-2020

•

•

•

group of herbicides), although, where used in 2008, all of the 33 farmers in the survey
using GM HT hybrids did so mainly in competition and comparison with ‘Clearfield’varieties;
The GM HT open pollinated varieties sold to farmers at a premium of about $Aus3/ha(about $2.5 US/ha) relative to the TT varieties. The GM HT hybrids sold at a seedpremium of about $Aus 9/ha ($7.55 US/ha) compared to ‘Clearfield’ hybrids. In addition,
farmers using the GM HT technology paid a ‘technology’ fee in two parts; one part was aset fee of $Aus500 per farm plus a second part based on output - $Aus 10.2/tonne of
output of canola. On the basis that there were 108 farmers using GM HT (glyphosate
tolerant) technology in 2008, the average ‘up front’ fee paid for the technology was$Aus5.62/ha. On the basis of average yields obtained for the two main types of GM HT
seed used, those using open pollinated varieties paid Aus $11.83/ha (basis average yieldof 1.16 tonnes/ha) and those using GM HT hybrids paid $Aus12.95/ha (basis: average
yield of 1.27 tonnes/ha). Therefore, the total seed premium and technology fee paid byfarmers for the GM HT technology in 2008/09 was $Aus20.45/ha ($17.16 US/ha) for open
pollinated varieties and $Aus 27.57/ha ($23.13 US/ha) for hybrid varieties. After taking
into consideration the seed premium/technology fees, the GM HT system was marginallymore expensive by $Aus 3/ha ($2.5 US/ha) and Aus $4/ha (US $3.36/ha) respectively forweed control than the TT and ‘Clearfield’ varieties;
The GM HT varieties delivered higher average yields than their conventionalcounterparts: +22.11% compared to the TT varieties and +4.96% compared to the‘Clearfield’ varieties. In addition, the GM HT varieties produced higher oil contents of+2% and +1.8% respectively compared to TT and ‘Clearfield’ varieties;
The average reduction in weed control costs from using the GM HT system (excluding
seed premium/technology fee) was $Aus 17/ha for open pollinated varieties (competingwith TT varieties) and $Aus 24/ha for hybrids (competing with ‘Clearfield’ varieties).

In the analysis summarised in Table 11, we have applied these research findings to the total GM
HT crop area on a weighted basis in which the results of GM HT open pollinated varieties thatcompete with TT varieties were applied to 64% of the total area in 2009 and 32% in 2010 and thebalance of area used the results from the GM HT hybrids competing with ‘Clearfield’ varieties.
This weighting reflects the distribution of farms in the survey. From 2011, yield differences
identified in Hudson D and Richards R (2014) were used (a yield gain of about 14% relative toopen pollinated triazine tolerant varieties and a yield reduction of about 0.2% relative toClearfield hybrid canola again based on estimates of open pollination/hybrid seed sales). In
addition, the seed premia have been adjusted to reflect changes that have occurred post 2008
(mostly reflecting the end part royalty part of the premia that is yield dependant). Cost
differences between the different canola production systems were also updated from 2011 basedon the findings of Hudson and Richards (2014) and changes in herbicide prices. The findings
show an average farm income gain of US $38.2/ha and a total farm income gain of $25.1 million in2020 (Table 11). Cumulatively since 2008, the total farm income gain has been $156.8 million.
It is noted that the share of GM HT canola has risen to only 25% of the total canola seed market
and this suggests that the economic performance of GM HT canola relative to some of themainstream alternative production systems and seed types is not offering sufficient enoughadvantage to encourage wider take up of the technology. The recent analysis by Hudson andRichards (2014) provides insights into the impacts of the technology and shows that GM HT
canola offers greatest economic advantage relative to TT canola and where farmers are faced with©PG Economics Ltd 202253

GM crop impact: 1996-2020

weeds that are resistant to a number of non-glyphosate herbicides (eg, annual ryegrass (Lolium
rigidum) and wild radish (Raphanus raphanistrum)). Relative to ‘Clearfield’ canola andconventional canola (that contains no HT traits, whether GM-derived or not), GM HT canola isreported to offer little yield gain and the cost savings associated with reduced herbicide costs
have tended to be more than offset by the cost of the technology. These factors may have been
one of the main reasons for changes in the pricing of the GM HT technology introduced in 2012
which resulted in some reduction in the total seed premia level.
Table 11: Farm level income impact of using GM HT canola in Australia 2008-2020 ($US)
Year

Average costsaving ($/ha)

Average cost savings
Average net increase
Increase in farm(net after cost ofin gross margins
income at a national
technology: $/ha)($/ha)
level (‘000 $)
2008
19.18
-20.76
96.87
978
2009
20.13
-21.08
95.14
3,919
2010
21.90
-10.13
57.27
7,635
2011
27.07
-5.97
29.74
4,138
2012
27.13
+5.41
44.77
8,105
2013
11.29
-1.26
67.94
15,108
2014
10.54
-1.18
45.59
17,332
2015
8.79
-0.98
37.73
17,193
2016
8.69
-0.97
34.66
15,516
2017
8.96
-1.0
28.29
13,907
2018
8.74
-0.98
27.14
13,538
2019
8.13
-0.91
26.15
14,907
2020
7.97
-0.89
44.55
25,562
Source derived from and based on Monsanto survey of licence holders 2008
Notes:
1. The average values shown are weighted averages
2. Other weighted average values derived include: yield +21.1% 2008, +20.9% 2009, +15.8% 2010,+7.6% 2011 and 2012, +11% 2013-2015, +8% 2016-20. Quality (price) premium of 2.1% applied on
the basis of this level of increase in average oil content. In 2010, because of a non-GM canola pricepremium of 7%, the net impact on price was to apply a price discount of -4.9%. In 2011 because ofa non-GM canola price premium of 7%, the net impact on price was to apply a price discount of 2.9%. Since 2012, the price discount applied is -2%

3.1.5.4 Summary of global economic impact
In global terms, the farm level impact of using GM HT technology in canola in Canada, the US
and Australia was $624.1 million in 2020. Cumulatively since 1996, the farm income benefit has
been (in nominal terms) $8.18 billion. Within this, 75% has been due to yield gains and thebalance (25%) has been from cost savings.
In terms of the total value of canola production in these three countries in 2020, the additionalfarm income generated by the technology is equal to a value-added equivalent of 5.9%. Relative
to the value of global canola production in 2020, the farm income benefit added the equivalent of
1.8%.

©PG Economics Ltd 2022

54

GM crop impact: 1996-2020

3.1.6 GM herbicide tolerant (GM HT) sugar beet
3.1.6.1 US
GM HT sugar beet was first grown commercially in the US in 2007. In 2020, 462,280 hectares of
GM HT sugar beet were planted, equal to all of the US crop.
Impact of the technology in 2007 and 2008 has been identified as follows:a)

Yield: analysis by Kniss (2008) covering a limited number of farms in Wyoming (2007)
identified positive yield impacts of +8.8% in terms of additional root yield (from better
weed control) and +12.6% in terms of sugar content relative to conventional crops (ie, theGM HT crop had about a 3.8% higher sugar content, which amounts to a 12.8% total
sucrose gain relative to conventional sugar beet once the root yield gain was taken into
consideration). In contrast, Khan (2008) found similar yields reported between
conventional and GM HT sugar beet in the Red River Valley region (North Dakota) andMichigan. These contrasting results probably reflect a combination of factors including:
•

•

•

b)

The sugar beet growing regions in Wyoming can probably be classified as high weed
problem areas and, as such, are regions where obtaining effective weed control isdifficult using conventional technology (timing of application is key to weed control
in sugar beet, with optimal time for application being when weeds are small). Also,
some weeds (eg, Kochia) are resistant to some of the commonly used ALS inhibitor
herbicides like chlorsulfuron. The availability of GM HT sugar beet with its greater
flexibility on application timing has therefore potentially delivered important yieldgains for such growers;
The GM HT trait was not available in all leading varieties suitable in all growing
regions in 2008, hence the yield benefits referred to above from better weed control
have to some extent been counterbalanced by only being available in poorer
performing germplasm in states like Michigan and North Dakota (notably not being
available in 2008 in leading varieties with rhizomania resistance). It should be notedthat the authors of the research cited in this section both perceive that yield benefits
from using GM HT sugar beet will be a common feature of the technology in mostregions once the technology is available in leading varieties;
2008 was reported to have been, in the leading sugar beet growing states, areasonable year for controlling weeds through conventional technology (ie, it waspossible to get good levels of weed control through timely applications), hence thesimilar performance reported between the two systems.

Costs of production• Kniss’s work in Wyoming identified weed control costs (comprising herbicides,
application, cultivation and hand labour) for conventional beet of $437/ha compared
to $84/ha for the GM HT system. After taking into consideration the $131/ha seedpremium/technology fee for the GM HT trait, the net cost differences between thetwo systems was $222/ha in favour of the GM HT system. Kniss did, however,acknowledge that the conventional costs associated with this sample were highrelative to most producers (reflecting application of maximum dose rates for©PG Economics Ltd 2022

55

GM crop impact: 1996-2020•

herbicides and use of hand labour), with a more typical range of conventional weed
control costs being between $171/ha and $319/ha (average $245/ha);Khan’s analysis puts the typical weed control costs in the Red River region of North
Dakota to be about $227/ha for conventional compared to $91/ha for GM HT sugar
beet. After taking into consideration the seed premium/technology fee (assumed by
Khan to be $158/ha 39 ), the total weed control costs were $249/ha for the GM HT
system, $22/ha higher than the conventional system. Despite this net increase inaverage costs of production, most growers in this region used (and planned tocontinue using), the GM HT system because of the convenience and weed control
flexibility benefits associated with it (which research by Marra and Piggot (2006): seesection 3.4, estimated in the maize, soybean and cotton sectors to be valued at
between $12/ha and $25/ha to US farmers). It is also likely that Khan’s analysis may
understate the total cost savings from using the technology by not taking into
account savings on application costs and labour for hand weeding.

For the purposes of our analysis we have drawn on both these pieces of work and sought toupdate the impact assumptions based on experience post 2008. We are not aware of any
published yield impact studies. Discussions with independent sugar beet analysts and industry
representatives confirm that the early findings of research studies have been realised, with thetechnology delivering important yield improvements in some regions (those with difficult tocontrol weeds, as identified by Kniss) but not so in other regions. The yield assumptions appliedin the analysis below (Figure 27) therefore continue to be based on the findings of the original
two papers by Kniss and Khan. In relation to the seed premium and weed control costs, thesehave been updated to reflect changes in seed prices/premia, herbicide usage patterns andherbicide prices. This shows a net farm income gain in 2020 of $73.6 million to US sugar beetfarmers (average gain per hectare of $129.6/ha). Cumulatively, the farm income gain, since 2007
has been $733.4 million.

39

Differences in the seed premium assumed by the different analysts reflect slightly different assumptions on

seed rates used by farmers (the technology premium being charged per bag of seed)©PG Economics Ltd 2022

56

GM crop impact: 1996-2020

Figure 27: Farm level income impact of using GM HT sugar beet in the US 2007-2020 ($/ha)
400.00350.00300.00250.00200.00150.00100.0050.00
0.00-50.002007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

-100.00
Weed control cost savings
Net impact on costs after deducting cost of technology
Farm income impact including yield effectSources derived from and based on Kniss (2008), Khan (2008), Jon Joseph Q et al (2010), Stachler J et al (2011)
and Kynetec
Notes:
1. The yield gains identified by Kniss have been applied to the 2007 GM HT plantings in total and to
the estimated GM HT plantings in the states of Idaho, Wyoming, Nebraska and Colorado, where
penetration of plantings in 2008 was 85% (these states account for 26% of the total GM HT crop in2008), and which are perceived to be regions of above average weed problems. For all otherregions, no yield gain is assumed. For 2008 onwards, this equates to a net average yield gain of+3.4% (2008-2020)
2. The seed premium of $131/ha, average costs of weed control respectively for conventional and GM
HT systems of $245/ha and $84/ha, from Kniss, were applied to the crop in Idaho, Wyoming,
Nebraska and Colorado. The seed premium of $158/ha, weed control costs of $227/ha and $249/ha
respectively for conventional and GM HT sugar beet, identified by Khan, were applied to all otherregions using the technology. The resulting average values for seed premium/cost of technology
was $152.16/ha 2008 and $151.08/ha 2009 and 2010. Based on industry and extension service datafor 2011, a seed premium of $148/ha has been used for subsequent years

3.1.6.2 Canada
GM HT sugar beet has also been used in the small Canadian sugar beet sector since 2008. In 2020,
all of crop of 17,400 ha used this technology. We are not aware of any published analysis of the
impact of GM HT sugar beet in Canada, but if the same assumptions used in the US are applied
to Canada, the total farm income gain in 2020 was $3.7 million and cumulatively since 2008, theincome gain has been $21.9 million.

©PG Economics Ltd 202257

GM crop impact: 1996-2020

3.2 Insect resistant crops

3.2.1 GM insect resistant 40 (GM IR) maize
3.2.1.1 US
GM IR maize was first planted in the US in 1996 and in 2020 seed containing GM IR traits wasplanted on 82% (27.37 million ha) of the total US maize crop.
The farm level impact of using GM IR maize in the US since 1996 is summarised in Figure 28:
•

•

•

•

40

The primary impact has been increased average yields. Much of the analysis in earlyyears of adoption (summarised for example in Marra et al (2002) and James (2002))
identified an average yield impact of about +5%. More comprehensive work by
Hutchison et al (2010) examined impacts over the 1996-2009 period and considered thepositive yield impact on non-GM IR crops of ‘area-wide’ adoption of the technology. The
key finding of this work puts the average yield impact at +7%. This latter analysis has
been used as the basis for our analysis below;
The net impact on cost of production has been a small increase of between $1/ha and$9/ha (additional cost of the technology being higher than the estimated average
insecticide cost savings of $15-$16/ha). In the last few years however, with the rising costof the technology 41, the net impact on costs has been an increase of $7/ha to $27/ha;
The annual total national farm income benefit from using the technology has risen from
$13.54 million in 1996 to $1.93 billion in 2020. The cumulative farm income benefit overthe 1996-2020 period (in nominal terms) was $34.3 billion;
The average net farm income gain over the period 1996-2020 has been +$81.5/ha.

The first generation being resistant to stalk boring pests but later generations including resistance against

cutworms and earworms
41

Which tends to be mostly purchased as stacked-traited seed – for this aspect of technology the seed premiumhas been in the range of $25/ha to $30/ha in recent years compared to the ‘lower $20s/ha 10-15 years ago©PG Economics Ltd 2022

58

GM crop impact: 1996-2020

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

140.001996

Figure 28: Farm level income impact of using GM IR maize in the US 1996-2020 ($/ha)

120.00100.00
80.00
60.00
40.00
20.00
(20.00)(40.00)Pest control cost saving
Net impact on costs after deduction of cost of technology
Farm income impact inclusive of yield gain

Sources and notes:
1. Impact data based on a combination of studies including the ISAAA (James) review (2002), Marra
et al (2002), Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006), Johnson & Strom(2008) and Hutchison et al (2010)
2. Yield impact +7% based on Hutchison et al (2010)
3. Insecticide cost savings based on the above references but applied to only 10% of the total crop area
based on historic usage of insecticides targeted at stalk boring pests
4. – (minus) value for net cost savings means the cost of the technology is greater than the other costsavings

3.2.1.2 Canada
GM IR maize has also been grown commercially in Canada since 1996. In 2020, it accounted for
81% (1.14 million ha) of the total Canadian maize crop. The impact of this technology in Canada
has been very similar to the impact in the US (similar yield and cost of production impacts). At
the farm level this has resulted in net farm income gains (after deduction of the technology cost,
pest control cost savings and yield gains) of between $24/ha and $140/ha (Figure 29). At thenational level, this equates to additional farm income generated from the use of GM IR maize of$87.7 million in 2020 and cumulatively since 1996, additional farm income (in nominal terms) of$1.39 billion. On a per hectare basis, the average farm income benefit has been $74.92/ha (19972020).

©PG Economics Ltd 202259

GM crop impact: 1996-2020

Figure 29: Farm income impact: GM IR maize in Canada 1996-2020 ($/ha)
160.0
130.4

140.0

139.8
122.5

120.0
100.0

86.7

81.5

80.4

80.0

63.2
54.7
51.1
60.0
39.4
45.9
38.8
37.7
34.432.7
27.7
40.0
23.2

60.0

79.3
73.4

77.1

75.2

62.0

68.2

77.2

20.0

Notes:
1.

2.
3.

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.0

Yield increase of 7% based on US analysis. Cost of technology and insecticide cost savings also
based on US analysis – insecticide cost savings constrained to 10% of total crop area to reflect
historic insecticide use for stalk borer pest control
GM IR area planted in 1996 = 1,000 ha
All values for prices and costs denominated in Canadian dollars have been converted to US dollars
at the annual average exchange rate in each year

3.2.1.3 Argentina
In 2020, GM IR maize traits were planted on 93% (5.95 m ha) of the total Argentine maize crop(first planted in 1998).
The main impact of using the technology on farm profitability has been via yield increases.
Various studies (eg, see ISAAA review in James (2002)) have identified an average yield increasein the region of 8% to 10%; hence an average of 9% has been used in the analysis up to 2004.
Subsequent (industry source) estimates provided to the authors put the average yield increase in
the 2005-2015 period to be between 5% and 6%. Our analysis uses a yield increase value of 5.5%
for the years from 2004 (see also note relating to yield impact of stacked-traited seed in section
3.3.3: GM HT maize in Argentina).
No savings in costs of production have arisen because very few maize growers have traditionallyused insecticides as a method of control for corn boring pests. Therefore, average costs ofproduction increased by between $20/ha-$27/ha (the cost of the technology) in years up to 2006.
From 2007, with stacked-traited seed becoming available and widely used, the additional cost ofthe (IR part) technology relative to conventional seed has been in the range of $10/ha-$33/ha, withan average cost over the 1998-2020 period of $23.12/ha.
The net impact on farm profit margins (inclusive of the yield gain and after deduction of thetechnology cost) has been an increase of between $3/ha and $66/ha. In 2020, the national level
impact on profitability was an increase of $204.2 million. Cumulatively, the farm income gain,
since 1998 has been $1.9 billion.

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

3.2.1.4 South Africa
GM IR maize has been grown commercially in South Africa since 2000. In 2020, 79% (2.07 millionha) of the country’s total maize crop of 2.6 million ha used varieties containing GM IR
technology.
The impact on farm profitability is summarised in Figure 30. The main impact has been an
average yield improvement of between 5% and 32% in the years 2000-2004, with an average ofabout 15% (used as the basis for analysis 2005-2007). In 2008 and 2009, the estimated yield impact
was +10.6% 42 (this has been used as the basis of the analysis for 2010 onwards). The cost of thetechnology, $9/ha to $17/ha has broadly been equal to the average cost savings from no longer
applying insecticides to control corn borer pests, as shown in Figure 30. The average farmincome gain after inclusion of yield gains was been in a range of $21/ha to $130/ha (average$93.6/ha 2000-2020)
At the national level, the increase in farm income in 2020 was $215.5 million and cumulatively
since 2000 it has been $2.57 billion.
Figure 30: Farm level income impact of using GM IR maize in South Africa 2000-2020 ($/ha)

200.00150.00100.0050.00
0.00-50.00Pest control cost saving
Impact on costs after deduction of cost of technology
Farm income impact inclusive of yield gain

Sources and notes:
1. Impact data (sources: Gouse (2005 & 2006) and Van Der Weld (2009))
2. Negative value for the net cost saving = a net increase in costs (ie, the extra cost of the GM
technology was greater than the savings from less expenditure on insecticides)
3. All values for prices and costs denominated in South African Rand have been converted to US
dollars at the annual average exchange rate in each year

3.2.1.5 Spain
Spain has been commercially growing GM IR maize since 1998 and in 2020, 28% (98,150 ha) of thecountry’s maize crop was planted to varieties containing a GM IR trait. As in the other countries
42

Van der Weld (2009)©PG Economics Ltd 2022

61

GM crop impact: 1996-2020

planting GM IR maize, the main impact on farm profitability has been increased yields (anaverage increase in yield of 6.3% across farms using the technology in the early years ofadoption). With the availability and widespread adoption of the Mon 810 trait from 2003, thereported average positive yield impact is about +10% 43. There has also been a net annual averagesaving on cost of production (from lower insecticide use) of between $37/ha and $61/ha 44 in theearly years of adoption. This has been the basis of analysis to 2008. From 2009, the analysis
draws on Riesgo et al (2012), as summarised in Brookes (2019). Over the period 1998-2020, theaverage coat of the technology has been$41.9/ha and the average farm income gain $209.6/ha(Figure 31). This income gain derives mostly from higher yields, with an average of about$20.7/ha coming from less expenditure on insecticides. At the national level, these yield gains
and cost savings have resulted in higher farm income, which in 2020 was 22.9 million andcumulatively since 1998 the increase in farm income (in nominal terms) has been $371.9 million.
ii

Figure 31: Farm level income impact of using GM IR maize in Spain 1998-2020 ($/ha)
350.0

320.3

250.0

255.9

225.4

204.5

200.0
150.0
95.2
100.0

102.2
89.5

95.6

121.7

232.9
227.9

214.5
182.1
198.0
194.6
182.0

172.3

144.7

221.9

2019

274.6

2017

300.0

292.5

111.9

100.6

50.0

2020

2018

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

0.0

Sources and notes:
1. Impact data (based on Brookes (2003), Brookes (2008), Brookes (2019) and Riesgo et al (2012)).
Yield impact +6.3% to 2004 and 10% 2005-2008, +12.6% 2009 onwards. Cost of technology based on€18.5/ha to 2004 and €35/ha from 2005, insecticide cost savings €42/ha to 2008, €6.4/ha 2009
onwards
2. All values for prices and costs denominated in Euros have been converted to US dollars at theannual average exchange rate in each year

3.2.1.6 Other EU countries
In 2020, the only other EU member state where GM IR maize was planted was Portugal (4,216 haout of a total crop of 76,000 ha). A summary of the impact of GM IR technology in Portugal ispresented in Table 12. This shows that in 2020, the additional farm income derived from using
43

The cost of using this trait has been higher than the pre-2003 trait (Bt 176) – rising from about €20/ha to€35/ha44

Source: Brookes (2003) and Alcade (1999)©PG Economics Ltd 2022

62

GM crop impact: 1996-2020

GM IR technology was +$0.918 million, and cumulatively over the period 2005-2020, the total
income gain was $14.7 million (an average of +$160/ha).
Table 12: Farm level income impact of using GM IR maize in Portugal 2020
Year firstplanted
GM IR
maize

Area
(hectares)

Yield
impact(%)

Cost oftechnology($/ha)

Cost savings(beforededuction of costof technology:
$/ha)
0

Net
increase in
gross
margin($/ha)
217.8

Impact on farmincome at anational level(million $)

2005
4,216
+12.5
42.66
0.918
Source and notes:
1. Source: based on Brookes (2008)
2. All values for prices and costs denominated in Euros have been converted to US dollars at theannual average exchange rate in each year

3.2.1.7 Brazil
Brazil first used GM IR maize technology in 2008. In 2020, 18 million ha of GM IR maize wereplanted (91% of the total crop). Analysis from Galvao (2009-2015) and Kleffmann/Kynetec
pesticide usage data has been used as the basis for estimating the aggregate impacts on farmincome and is presented in Table 13. Over the period 2008-2020, the average yield gain has been
+11.5%, the average cost of the technology $56/ha and the average farm income gain $53.7/ha. In
2020, the total income gain was $201.1 million, with the cumulative benefit since 2008 equal to$7.86 billion.
Table 13: Farm level income impact of using GM IR maize in Brazil 2008-2020
Year

Cost savings ($/ha)

Net cost savings
inclusive of cost oftechnology ($/ha)
20.93-14.63-5.39-46.25-38.86-29.0950.93-41.44-41.08-33.46-42.10-42.1-42.1

Net increase in grossmargin ($/ha)

Impact on farm income
at a national level ($millions)
96.22
144.54414.74
1,141.40
964.791,373.70
651.70499.36936.43404.63413.88563.66202.00

2008
41.98
66.36
2009
44.21
30.37
2010
48.60
55.74
2011
23.13
131.48
2012
13.35
88.12
2013
18.22
115.63
2014
16.69
54.72
2015
13.58
40.33
2016
13.46
62.93
2017
17.04
29.58
2018
15.07
29.67
2019
15.07
34.69
2020
15.07
11.14
Sources and notes:
1. Impact data (source : Galvão (2009-2015)) and Kleffmann
2. Negative value for the net cost savings = a net increase in costs (ie, the extra cost of the technology
exceeded the savings on other costs (eg, less expenditure on insecticides)
3. All values for prices and costs denominated in Brazilian Real have been converted to US dollars at
the annual average exchange rate in each year

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GM crop impact: 1996-2020

3.2.1.7 Philippines
GM IR maize has been grown commercially in Philippines since 2003. In 2020, 683,085 hectares
out of total plantings of 2.57 million (27%) were to varieties containing GM IR technology.
Estimates of the impact of using GM IR (sources: Gonsales (2005), Yorobe (2004) and Ramon(2005)) show annual average yield increases in the range of 14.3% to 34%. The mid-point of thisrange (+24.15%) was used for the years 2003-2007. From 2008, a yield impact of +18% has beenused based on Gonsales et al (2009). Based on the findings of these research papers, there has
been a small average annual insecticide cost saving of about $12/ha-$15/ha and with an average
cost of the technology of $42/ha, the net impact on costs of production has been an increase of
between $18/ha and $32/ha (Figure 32). However, with the positive yield impact, the average net
impact on farm profitability has been between +$37/ha and $119/ha (average $103.75/ha). In 2020,
the national farm income benefit derived from using the technology was $73.7 million andcumulative farm income gain since 2003 has been $851 million.
Figure 32: Farm level income impact of using GM IR maize in Philippines 2003-2020 ($/ha)
140.002003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

120.00100.00
80.00
60.00
40.00
20.00
(20.00)(40.00)Pest control cost saving
Net impact on costs after deduction of cost of technology
Farm income impact inclusive of yield gain

3.2.1.8 Colombia
GM IR maize was first grown commercially in 2006, initially on a restricted basis and post 2007,
on an unrestricted basis. In 2020, GM maize was planted on 96,250 ha, of which 92.5% contained
both IR and HT traits. Based on analysis summarised in Brookes (2020), which draws on researchby Mendez et al (2011) and Celeres (2017 and 2019), the average yield gain from improved pest
control has been +17.1%, with average savings on pest control costs of $44.6/ha. The net impact
on costs of production has been marginally negatives, due to the average cost of the technology
of $47.7/ha. When the yield gain is taken into consideration, significant average farm income
gains have occurred, equal to $263/ha (2006-2020). At the national level, these farm income gains
were $17.6 million in 2020 and cumulatively since 2006 have been $214.8 million.

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GM crop impact: 1996-2020

3.2.1.9 Vietnam
GM stacked maize (HT and IR traits) was first planted commercially in 2015, and in 2020 was
planted on 92,000 ha (9.7% of the total crop). Based analysis by Brookes (2017) and Brookes andDinh (2021), the yield gain attributable to the IR trait was estimated to be about +7% in the firsttwo years and +10.2% in the period 2019-2021 (average all years +9%). Coupled with an average
cost of technology of $29.08/ha (IR trait only), the average farm income gain over the six years ofadoption has been $119.82/ha (inclusive of average insecticide cost savings of $49.52/ha). At thenational level, this equates to an aggregate net farm income gain of $12 million in 2020 and $37.9
million 2015-2020.

3.2.1.10 Other countries
Uruguay. GM IR maize has been grown in Uruguay since 2004, and in 2020, 82% (117,690 ha) of
the crop used seed containing this technology. Using Argentine data as the basis for assessing
impact, the average farm income gain over the 2004-2020 period has been +$33.35/ha. In 2020, theaggregate income gain was $4.2 million and cumulatively the farm income gain has been $46.8
million.
Honduras. Here farm level ‘trials’ have been permitted since 2003, and in 2020, 38,000 ha used
GM IR traits (12% of the crop). Evidence from Falck Zepeda et al (2009) indicated that the
primary impact of the technology has been to increase average yields (in 2008 +24%). As
insecticides have not traditionally been used by most farmers, no costs of production savings
have arisen. No seed premium was charged during the trials period for growing (2003-2006),
though for the purposes of our analysis, a seed premium of $30/ha was assumed. From 2006, theseed premium applied is based on Falck-Zepeda et al (2009) at $100/ha. Based on these costs, theestimated farm income benefit derived from the technology in 2020 was $5.8 million andcumulatively since 2003 the income gain has been $32.4 million.
Paraguay. The first commercial crop of maize using this technology was grown in 2013-14. In
2020, 72% of the total crop (720,000 ha total crop) used seed containing this technology.
Applying impact analysis from Argentina (in terms of average yield impacts and insecticide
saving assumptions), together with a seed premium of about $16/ha (source: MonsantoParaguay), the average farm income gain from using the technology has been +$21.9/ha ($24.8/ha
in 2020). At the national level, this is equivalent to a total farm income gain of $12.8 million in2020 and over the eight years, the total farm income benefit has been $71 million.

3.2.1.11 Summary of economic impact
In global terms, the farm level impact of using GM IR maize was $2.79 billion in 2020.
Cumulatively since 1996, the benefit has been (in nominal terms) $49.7 billion. This farm income
gain has mostly derived from improved yields (less pest damage) although in some countries’
farmers have derived a net cost saving associated with reduced expenditure on insecticides.
In terms of the total value of maize production from the countries growing GM IR maize in 2020,
the additional farm income generated by the technology is equal to a value-added equivalent of
6.1%. Relative to the value of global maize production in 2018, the farm income benefit added theequivalent of 2.8%.

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GM crop impact: 1996-2020

3.2.2 Insect resistant (Bt) cotton (GM IR)
3.2.2.1 The US
GM IR cotton has been grown commercially in the US since 1996, and in 2020 was used on 88%(3.03 million ha) of total cotton plantings. The farm income impact of using GM IR cotton issummarised in Figure 33. The primary benefit has been increased yields (by 9%-11%), althoughsmall net savings in costs of production have also been obtained (reduced expenditure on
insecticides being marginally greater than the cost of the technology for Bollgard I) in the firsttwelve years of adoption. With the move to the increasing adoption of the second generation of
the technology since then, the average cost of the technology has been greater than the averagesaving in pest control costs, with all of the income gains arising from yield gains (Figure 33).
Overall, average profitability levels increased by between $53/ha-$115/ha with the first generationof IR cotton (with a single Bt gene) and by between $87/ha and $151/ha in 2003-2020 with thesecond generation of IR cotton (containing two Bt genes and offering a broader spectrum ofcontrol). Overall, the average farm income gain (1996-2020) has been $110.83/ha. The net
aggregated farm income gain in 2020 of $291.3 million. Cumulatively, since 1996 the farm income
benefit has been $7.07 billion.

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

200.001996

Figure 33: Farm level income impact of using GM IR cotton in the US 1996-2020 ($/ha)

150.00100.0050.00
0.00-50.00Contribution of change in cost of production

Contribution of yield gain

Sources and notes:
1. Impact data based on Gianessi & Carpenter (1999), Carpenter & Gianessi (2002), Sankala &Blumenthal (2003 & 2006), Johnson & Strom (2008), Marra et al (2002) and Mullins & Hudson (2004)
2. Yield impact +9% 1996-2002 Bollgard I and +11% 2003-2004, +10% 2005 onwards Bollgard II
3. Average cost of technology: 1996-2020 $49.03/ha
4. Average insecticide cost savings 1996-2020: $41.77/ha

3.2.2.2 China
China first planted GM IR cotton in 1997, since when the area planted to GM IR varieties has
increased to 95% of the total 3.09 million ha crop in 2020.

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GM crop impact: 1996-2020

As in the US, a major farm income impact has been via higher yields of +8% to +10% on the crops
using the technology, although there have also been significant cost savings on insecticides used
and the labour previously used to undertake spraying. Overall, annual average costs have fallen(eg, by $80/ha-$90/ha in the last four years) and coupled with the yield gains, net returns haveincreased significantly. In 2020, the average increase in profitability was +$511.67/ha and for theperiod 1996-2020 has been $376.6/ha. At the aggregate level, the net national gain was $1.58
billion and cumulatively since 1997 the farm income benefit has been $26.27 billion (Table 14).
Table 14: Farm level income impact of using GM IR cotton in China 1997-2020
Year

Cost savings (net after cost of Net increase in gross
Increase in farm income at atechnology: $/ha)margins ($/ha)national level ($ millions)
1997
194
333
11.33
1998
194
310
80.97
1999
200
278
181.672000-14
123150.182001
378
472
1,026.26
2002
194
327
687.27
2003
194
328
917.002004
194
299
1,105.26
2005
145
256
845.582006
146
226
792.28
2007
152
248
942.7
2008
167
244
933.7
2009
170
408
1,457.8
2010
176
503
1,736.5
2011
184
559
2,198.8
2012
27.5
401
1,583.7
2013
29.1
376
1,579.3
2014
28.2
347
1,401.2
2015
28.3
338
1,223.9
2016
26.07
476
1,445.9
2017
26.59
470
1,425.5
2018
26.19
469
1,493.4
2019
25.07
448
1,468.1
2020
25.11
512
1,579.8
Sources and notes:
1. Impact data based on Pray et al (2002) which covered the years 1999-2001. Other years based on
average of the 3 years, except 2005 onwards based on Shachuan (2006) – personal communication
2. Negative cost savings in 2000 reflect a year of high pest pressure (of pests not the target of GM IR
technology) which resulted in above average use of insecticides on GM IR using farms
3. Yield impact +8% 1997-1999 and +10% 2000 onwards
4. Negative value for the net cost saving in 2000 = a net increase in costs (ie, the extra cost of thetechnology was greater than the savings on insecticide expenditure – a year of lower than averagebollworm pest problems
5. Average cost of technology 1996-2020 $53.08/ha
6. All values for prices and costs denominated in Chinese Yuan have been converted to US dollars at
the annual average exchange rate in each year

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GM crop impact: 1996-2020

3.2.2.3 Australia
Australia planted 95% of its 2020 cotton crop (total crop of 280,000 ha) to varieties containing GM
IR traits (Australia first planted commercial GM IR cotton in 1996).
Unlike the other main countries using GM IR cotton, Australian growers have rarely derived
yield gains from using the technology (reflecting the effective use of insecticides for pest control
prior to the availability of GM IR seed technology); with the primary farm income benefit being
derived from lower costs of production (Figure 34). More specifically:•••In the first two years of adoption of the technology (Ingard, single gene Bt cotton), small
net income losses were derived, mainly because of the relatively high price charged forthe seed. Since this price was lowered in 1998, the net income impact has been positive,
with cost savings of between $54/ha and $90/ha, mostly derived from lower insecticide
costs (including application) more than offsetting the cost of the technology;
From the mid-2000s, Bollgard II cotton (containing two Bt genes) has been available
offering effective control of a broader range of cotton pests. Despite the higher costs ofthis technology, users have continued to make significant net cost savings of between$186/ha to $270/ha. The average increase in farm income over the period 1996-2020 has
been $204.91/ha;
At the national level in 2020, the net farm income gain was $44.3 million andcumulatively since 1996 the gains have been $1.136 billion.

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

600.001996

Figure 34: Farm level income impact of using GM IR cotton in Australia 1996-2020 ($/ha)

500.00400.00300.00200.00100.000.00-100.00
Pest control cost savings

Total cost saving after deduction of technology cost

Sources and notes:
1. Impact data based on Fitt (2001) and CSIRO for Bollgard II since 2004
2. Average cost of technology 1996-2020: $233.94/ha
3. All values for prices and costs denominated in Australian dollars have been converted to US
dollars at the annual average exchange rate in each year

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GM crop impact: 1996-2020

3.2.2.4 Argentina
GM IR cotton has been planted in Argentina since 1998. In 2020, it accounted for 98% (441,000ha) of total cotton plantings.
The main impact in Argentina has been yield gains of 30%. This has more than offset the cost ofusing the technology 45. In terms of gross margin, cotton farmers have gained between $25/ha and$317/ha annually during the period 1998-2018 46. The average increase in farm income over theperiod 1998-2020 has been $234.1/ha. At the national level, the farm income gain was $90.9
million in 2020 (Figure 35). Cumulatively since 1998, the farm income gain from use of thetechnology has been $1.24 billion.

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

600.001996

Figure 35: National farm income impact: GM IR cotton in Argentina 1998-2020 (million $)500.00400.00300.00200.00100.000.00-100.00
Pest control cost savings

Total cost saving after deduction of technology cost

Sources and notes:
1. Impact data (source: Qaim & De Janvry (2002) and for 2005 and 2006 Monsanto LAP, although thecost of technology in 2005 from Monsanto Argentina). Area data : source ArgenBio
2. Yield impact +30%, average cost of technology 1998-2018 $50.37/ha, cost savings (reduced
insecticide use) in the last seven years $54/ha-$69/ha (average 1999-2020 $53.61/ha),
3. All values for prices and costs denominated in Argentine Pesos have been converted to US dollars
at the annual average exchange rate in each year

3.2.2.5 Mexico
GM IR cotton has been planted commercially in Mexico since 1996. In 2020, GM IR cotton wasplanted on 103,305 ha (69% of total cotton plantings).
The main farm income impact of using the technology has been yield improvements of between
7% and 16% over the last twelve years (average gain of 11.5% 1996-2020). In addition, there have45

The cost of the technology used in the years up to 2004 was $86/ha (source: Qaim & DeJanvry). From 2005,

the technology cost assumption has been 116 pesos/ha ($20/ha- $40/ha: source: Monsanto Argentina). The
average technology cost 1999-2018 was $28.17/ha
46

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GM crop impact: 1996-2020

been important savings in the cost of production (lower insecticide costs). The cost of technology
has annually been between $48/ha and $99.5/ha, based on estimated share of the trait largely soldas a stacked trait, with an average value over the 1996-2020 period of $61/ha. The insecticide costsavings between $9/ha and $121/ha and net impact on costs have been between -$40/ha and +$48/ha - derived from and based on Traxler et al (2001), and updated from industry data (Figure36). Overall, the annual net increase in farm profitability has been within the range of $104/ha
and $378/ha. At the national level, the farm income benefit in 2020 was $17.5 million (average of$169.6/ha) and cumulatively since 1996, the farm income benefit has been $407.4 million (averageof $207.9/ha).

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

450.00400.00350.00300.00250.00200.00150.00100.0050.00
0.00-50.00-100.00

1996

Figure 36: Farm level income impact of using GM IR cotton in Mexico 1996-2020

Pest control cost savings
Net impact on costs after deduction of cost of technology
Impact on income inclusive of yield gain

Sources and notes:
1. Impact data based on Traxler et al (2001) covering the years 1997 and 1998. Yield changes in otheryears based on official reports submitted to the Mexican Ministry of Agriculture by MonsantoComercial (Mexico)
2. Yield impacts: average 1996-2018 +11% (annual range +6% to +37%)
3. All values for prices and costs denominated in Mexican Pesos have been converted to US dollars at
the annual average exchange rate in each year

3.2.2.6 South Africa
In 2020, GM IR cotton 47 was planted on 95% (15,370 ha) of the cotton crop in South Africa.
The main impact on farm income has been significantly higher yields (an annual average increaseof about 24%). In terms of cost of production, the additional cost of the technology (between$17/ha and $24/ha for Bollgard I and $30/ha to $50/ha for Bollgard II (2006 onwards)) has been
greater than the insecticide cost and labour (for water collection and spraying) savings ($12/ha to$23/ha), resulting in an increase in overall cost of production of $2/ha to $32/ha (Figure 37).
47

First planted commercially in 1998

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GM crop impact: 1996-2020

Combining the positive yield effect and the increase in cost of production, the net effect on
profitability has been an annual increase of between $27/ha and $400/ha (average gain of$224.5/ha 1998-2020).
At the national level, the aggregated farm income benefits have varied, largely in line with thechanges in area planted to cotton (which has varied between 7,000 ha and 150,000 ha per year).
Cumulatively since 1998, the farm income benefit has been $74.9 million.

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

450
400
350
300
250
200
150
100
50
0
-50
-100

1998

Figure 37: Farm income impact: GM IR cotton in South Africa 1998-2020 ($/ha)

Pest control cost savings
Impact on costs of production after technology cost deduction
Impact on income inclusive of yield gain

Sources and notes:
1. Impact data based on Ismael et al (2002)
2. Yield impact +24%, cost of technology $14/ha-$24/ha for Bollgard I and $30/ha-$50/ha for Bollgard
II, cost savings (reduced insecticide use) $8/ha-$23/ha
3. All values for prices and costs denominated in South African Rand have been converted to US
dollars at the annual average exchange rate in each year
4. The decline in the total farm income benefit 2004 and 2005 relative to earlier years reflects thedecline in total cotton plantings. This was caused by relatively low farm level prices for cotton in2004 and 2005 (reflecting a combination of relatively low world prices and a strong South African
currency)

3.2.2.7 India
GM IR cotton has been planted commercially in India since 2002. In 2020, 12.22 million ha wereplanted to GM IR cotton which is equal to 94% of total plantings.
The main impact of using GM IR cotton has been major increases in yield 48. With respect to costof production, the average cost of the technology (seed premium: $49/ha to $54/ha) up to 2006
48

Bennett et al (2004) found average yield increases of 45% in 2002 and 63% in 2003 (average over the twoyears of 54%) relative to conventionally produced cotton. Survey data from Monsanto (2005) confirmed thishigh yield impact (+58% reported in 2004) and from IMRB (2006) which found an average yield increase of
64% in 2005 & IMRB (2007) which found a yield impact of +50% in 2006. Later work by Gruere (2008), Qaim
(2009) and Herring and Rao (2012) have all confirmed significant yield increases in the range of +30% to +40%

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GM crop impact: 1996-2020

was greater than the average insecticide cost savings of $31/ha-$58/ha resulting in a net increasein costs of production (Figure 38). Following the reduction in the seed premium in 2006 to
between $12/ha-$20/ha, farmers have made a net cost saving of $16/ha-$25/ha. The average seedpremium for the period 2002-2020 has been equal to $15.4/ha. Coupled with the yield gains,
important net gains to levels of profitability have been achieved of between $82/ha and $356/ha(the average increase in farm income 2002-2020 has been $181.8/ha). At the national level, theaggregate farm income gain in 2020 was $1.52 billion and cumulatively since 2002 the farmincome gains have been $27.4 billion.
Figure 38: Farm level income impact of using GM IR cotton in India 2002-2020 ($/ha)

400.00350.00300.00250.00200.00150.00100.0050.00
0.00-50.00Pest control cost savings
Impact on cost of production after deduction of technology cost
Impact on income inclusive yield gain

Sources and notes:
1. Impact data based on Bennett et al (2004), IMRB (2005 & 2007), Gruere (2008), Qaim (2009), Herringand Rao (2012)
2. All values for prices and costs denominated in Indian Rupees have been converted to US dollars at
the annual average exchange rate in each year

3.2.2.8 Brazil
GM IR cotton was planted commercially in Brazil for the first time in 2006, and in 2020 was
planted on 1.17 million ha (77% of the total crop). The area planted to GM IR cotton in the earlyyears of availability fluctuated (eg, 358,000 ha in 2007 and 116,000 ha in 2009) largely due to theperformance of the seed containing the GM IR trait compared to leading conventional varieties.
In 2006, on the basis of industry estimates of impact of GM IR cotton relative to similar varieties(average yield gain of +6% and a net cost saving from reduced expenditure on insecticides after
deduction of the premium paid for using the technology of about +$25/ha), a net farm income
gain of about $125/ha was realised. In subsequent years, however, improved conventionalvarieties in which the GM IR trait was not present dominated production because of theirsuperior yields. As a result, varieties containing the GM IR trait have delivered inferior yields(despite offering effective control against bollworm pests) relative to the leading conventionalvarieties. In addition, boll weevil is a major pest in many areas, a pest that the GM IR technology
does not target. Analysis by Galvao (2009 & 2010) estimated that the yield performance of the©PG Economics Ltd 202272

GM crop impact: 1996-2020

varieties containing GM IR traits was lower (by –2.7% to -3.8%) than the leading conventional
alternatives available in 2007-2009. As a result, the average impact on farm income (after taking
into consideration insecticide cost savings and the seed premium) has been negative (-$34.5/ha in2007, a small net gain of about $2/ha in 2008 and a net loss of -$44/ha in 2009: Figure 39). Not
surprisingly, at the country level, this resulted in net aggregate losses in 2007 and 2009 fromusing the technology (eg, -$5 million in 2009). In 2010, stacked traits (containing GM HT and GM
IR traits) became available in some of the leading varieties for the first time and this has
contributed to the increase in plantings since 2010. Annual estimates of the impact of thistechnology (Galvao (2010-2015)) found average yield impacts in a range of -1.8% to +3% relative
to the best performing conventional varieties.
Based on these yield findings, an average seed premium of $47.54/ha and average insecticide
costs savings of $61.95/ha, the average net farm gain derived from using this technology over theperiod 2006-2020 has been $86.26/ha. At the national level this equates to an aggregate net
income gain of $70.8 million in 2020 and cumulatively, since 2006, of $435.1 million.
Figure 39: Farm level income impact of using GM IR cotton in Brazil 2006-2020 ($/ha)
140.002006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

120.00100.00
80.00
60.00
40.00
20.00
0.00
-20.00-40.00-60.00Pest control cost savings
Impact on cost of prodcution after deduction for technology cost
Impact on income inclusive of yield gain

3.2.2.9 Colombia
GM IR cotton has been grown commercially in Colombia since 2000, with this technology used inabout 54% of the, 8,617 ha total crop (in stacked seed offering herbicide tolerance and insect
resistance).
Based on analysis summarised in Brookes (2020), which draws on research by Zambrano et al(2009), Fonseca and Zambrano (2010) and Celeres (2017 and 2019), the main impact has been a©PG Economics Ltd 202273

GM crop impact: 1996-2020

significant improvement in yield 49. Studies have identified a wide range of yield benefits byregion (eg, a range of +9% to +75%, with an average yield gain of +35%: Zambrano et al, 2009)
from improved pest control, coupled with savings on pest control costs (of between $41/ha and£63/ha: average of $55/ha). The net impact on costs of production has been negative, due to theaverage cost of the technology of $97/ha relative to the average pest control cost saving of $55/ha.
However, when the yield gain is taken into consideration, significant average farm income gains
have occurred, equal to $292/ha (2006-2020). At the national level, these farm income gains were
£1 million in 2020 and cumulatively since 2003 have been $100 million.

3.2.2.10 Other countries
Burkina Faso: GM IR cotton was first grown commercially in 2008. In 2015, GM IR cotton
accounted for 50% (330,000 ha) of total plantings. Based on analysis by Vitale et al (2006, 2008
and 2009), the main impact of the technology is improved yields (by +18% to +20%) and savingsin insecticide expenditure of about $52/ha. Based on a cost of technology of $53/ha, the net
impact on cost of production is marginally negative, but inclusive of the yield gains, the net
income gain in 2015 was $81.9/ha. The total aggregate farm income gain, in 2015 was $27 million
and cumulatively, since 2008, it has been $204.6 million. Since 2016, no GM IR cotton has beengrown because of a temporary ban imposed by the government. This was due to difficulties inselling the cotton from the varieties containing the trait because the fibres are shorter than mostmarkets want (note this is not related to any impact of the GM IR technology but relates to thevarieties containing the technology).
Pakistan: After widespread ‘illegal’ planting of GM IR cotton in Pakistan for several years, it was
officially permitted in 2009 and in 2020, 95% of the crop (2.09 million ha) used this technology.
Initial analysis of the impact draws on Nazli et al (2010) which identified an average yield gain of+12.6%, seed premium of about $14/ha-$15/ha and an average insecticide cost saving of about$20/ha. Based on this analysis (undertaken during a period when unofficial and largely illegal
seed was used), the average farm income benefit in 2009 was $37/ha. Subsequent analysis by
Kouser and Qaim (2013) has formed the basis of our estimates for impacts from 2010 to 2015.
This is based on a yield benefit of +22%, a technology (seed) premium of about $4-$5/ha and crop
protection savings of $10-$12/ha. Since 2016, the average yield gain assumption has been
reduced (to 10% by 2020) in line with declining levels of control of the pink bollworm pest by thetechnology. For 2020, the estimated average farm income benefit was $63.9/ha. At the national
level this is equal to a net farm income gain of $133.7 million. Cumulatively since 2009, the farmincome benefit of using this technology is $5.53 billion.
Myanmar: GM IR cotton has been grown in Myanmar since 2007 and in 2020, 213,600 ha (89% of
the total crop) used seed containing the trait. Data on the impact of the technology in Myanmar
is limited, with the brief report from the USDA (2011) being the only one identified. This
indicated that the technology has been used exclusively in ‘long staple’ varieties and wasdelivering up to a 70% improvement in yield (source: extension advisors). Given ‘long staple’
varieties account for only a part of the total crop, our analysis uses a more conservative average

49

Although it should be noted that the early years of adoption of the stacked traited seed, yield performance

was poor relative to conventional varieties because the technology was not available in some of the leading
varieties and/or in varieties suited to growing in some regions – see Brookes, 2020 for additional discussion©PG Economics Ltd 202274

GM crop impact: 1996-2020

yield of +30% and applies this only to the ‘long staple’ area (estimates thereof). In addition, due
to the lack of data on seed premia and cost savings (relating to labour and insecticide use), we
have used data based on costs and impacts from India. Based on these assumptions, the average
income gain in 2020 was $224.8/ha, which at the national level amounts to a gain of $48 million.
Cumulatively the average farm income gain since 2007 has been £178/ha, with a national level
gain of $552.7 million.
Sudan and Paraguay: These countries have respectively been using GM IR cotton since 2012 and2013. No detailed impact analysis has been identified for the technology in these countries.

3.2.2.11 Summary of global impact
In global terms, the farm level impact of using GM IR cotton was $3.8 billion in 2020.
Cumulatively since 1996, the farm income benefit has been $70.6 billion. Within this, 84% of the
farm income gain has derived from yield gains (less pest damage) and the balance (16%) fromreduced expenditure on crop protection (spraying of insecticides).
In terms of the total value of cotton production from the countries growing GM IR in 2020, theadditional farm income generated by the technology is equal to a value-added equivalent of
11.8%. Relative to the value of global cotton production in 2020, the farm income benefit added
the equivalent of 11.6%.

3.3 Other GM crops

3.3.1 Maize/corn rootworm resistance
GM IR (resistant to corn rootworm (CRW)) maize has been planted commercially in the US since2003. In 2020, there were 11.2 million ha of maize planted containing GM IR traits for the controlof CRW (34% of the total US crop).
The main farm income impact 50 has been higher yields of about 5% relative to conventionalmaize. In addition, there has been an average insecticide cost saving of $24.9/ha (average acrossall of the area planted to CRW resistant maize: range of $23/ha-$39/ha 51). The average cost of thetechnology over the period 2003-2020 has been $25.19/ha, illustrating that there has been amarginal overall increase in the cost of production. However, after taking into consideration thepositive yield impact of the technology, the net impact on farm profitability has been between an

50

Impact data based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006), Johnson and Strom(2008) and Rice (2004)
51

The average area on which the insecticide cost savings have been applied has been limited to the historicarea typically treated with insecticides for rootworm pests (about 40% of the total crop). In addition, from2012, the area on which this saving has been applied has been reduced to reflect increased spraying with
insecticides that target rootworm pests by some farmers who perceive they may have problems withrootworm developing resistance to the IR technology. Thus, the average insecticide cost saving across thearea traditionally using insecticides for the control of CRW in 2020 was $40.9/ha, which divided across thetotal area of maize using GM IR CRW control seed was $26.3/ha©PG Economics Ltd 202275

GM crop impact: 1996-2020

average increase in income over the 2003-2020 period of $77.5/ha (annual range of +$24/ha to+$102/ha: Figure 40).
At the national level, aggregate farm income increased by $840 million in 2020. Cumulatively
since 2003, the total farm income gain from the use of GM IR CRW technology in the US maizecrop has been +$17.42 billion.
GM IR CRW traited-seed was also planted commercially for the first time in 2004 in Canada. In
2020, the area planted to CRW resistant varieties was 0.73 million ha (52% of the crop). Based on
US costs, insecticide cost savings and yield impacts, this has resulted in additional income at thenational level of $58.3 million in 2020 (cumulative total since 2004 of $652.9 million).
At the global level, the extra farm income derived from GM IR CRW maize use has been $18.07
billion.
Figure 40: Farm level income impact of using GM IR CRW control maize in the US 2003-2020($/ha)

120

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

100
80
60
40
20
0
-20
Pest control cost savings
Impact on cost of production after deduction for technology cost
Impact on income inclusive of yield gain

Sources and notes:
1. Impact data based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006), Johnson
and Strom (2008) and Rice (2004)

3.3.2 Virus resistant papaya
Ringspot resistant papaya has been commercially grown in the US (State of Hawaii) since 1999,
and in 2020, 77% of the state’s papaya crop was GM virus resistant (187 ha of fruit bearing trees).
The main farm income impact of this technology has been to significantly increase yields relative
to conventional varieties. Compared to the average yield in the last year before the first biotech©PG Economics Ltd 2022

76

GM crop impact: 1996-2020

cultivation (1998), the annual yield increase of biotech papaya relative to conventional crops has
been within a range of +15% to +77% (17% in 2020).
In terms of profitability 52, the net annual impact has been an improvement of between $2,400/ha
and $11,400/ha, and in 2020, this amounted to a net farm income gain of $1,515/ha and an
aggregate benefit across the state of $0.28 million. Cumulatively, the farm income benefit since1999 has been $36.4 million.
Virus resistant papaya are also reported to have been grown in China, (9,500 ha in 2020). No
impact data on this technology has been identified.

3.3.3 Virus resistant squash
GM virus resistant squash has also been grown in some states of the US since 2004. It isestimated to have been planted on 1,000 ha in 2020 53 (6% of the total crop).
Based on analysis from Johnson & Strom (2008), the primary farm income impact of using GM
virus resistant squash has been derived from higher yields which in 2020, added a net gain tousers of $10.5 million. Cumulatively, the farm income benefit since 2004 has been $329.6 million.

3.3.4 Drought tolerant maize
Drought tolerant maize has been grown in parts of the US since 2014, and in 2020 was planted on
1.42 million hectares. Drawing on yield comparison data with other (non- GM) drought tolerantmaize and field trials data (source: Monsanto US Field Trials Network in the Western Great
Plains), this suggests that the technology is providing users with a net yield gain of 2.3% to 2.6%
and a small cost saving in irrigation costs 54. After taking into consideration, the additional cost of
the seed compared to non-GM drought tolerant maize, the average gross farm income gain overthe seven-year period of use has been $16.7/ha. In 2020, this resulted to an aggregate farmincome gain of about $35.3 million and over the period 2014-2020, a total gain of $131.8 million.

3.3.5 Insect resistant brinjal
Insect resistant brinjal (resistant to the brinjal fruit and shoot borer), has been grown in
Bangladesh since 2014, and in 2020, it was grown on 13% (6,310 ha) of the country’s crop.
Drawing on analysis by Mondal and Akter, (2018), Prodhan et al, (2018), Ahmed et al, (2019) and
Shelton, (2020), the main impacts of the technology have been higher yields (+15% to +20%),
better quality produce (equivalent to a 10% higher price paid for fruit) and lower costs of pest
control equal to about $88/ha. The cost of the technology has to date been zero with the52

Impact data based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006) and Johnson andStrom (2008)
53

Mostly found in Georgia and Florida

A 7% water saving applied to a baseline cost from the USDA ERS Prairie Gateway region which is wheremost DG maize is grown

54©PG Economics Ltd 2022

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GM crop impact: 1996-2020

technology being made available freely by the extension service. As a result, the net impact onfarm income has been positive, with an average increase in farm income over the period 20142020 of +679/ha (annual range of between +$616/ha and +$704/ha). At the national level, thecumulative fam income benefit from using this technology since its first introduction in 2014 has
been $9.75 million.

3.3.6 Other cropsa) Potatoes
GM IR potatoes were grown commercially in the US between 1996 and 2000 (planted on 4% of
the total US potato crop in 1999 (30,000 ha)). This technology was withdrawn in 2001 when thetechnology provider (Monsanto) withdrew from the market to concentrate on GM trait
development in maize, soybeans, cotton and canola. This commercial decision was also probably
influenced by the decision of some leading potato processors and fast food outlets to stop using
GM potatoes because of perceived concerns about this issue from some of their consumers, eventhough the GM potato provided the producer and processor with a lower cost, higher yielding
and more consistent product. It also delivered significant reductions in insecticide use(Carpenter & Gianessi (2002)).
High starch potatoes were also approved for planting in the EU in 2010 and a small area wasplanted in member states such as Sweden, the Czech Republic and Germany until the technology
provider withdrew the product from the market in 2012. There is no data available on the impactof this technology.
Lastly, GM potatoes that convey resistance to late fungal blight in potatoes and offer traits that
improve potato quality in terms of reduced bruising and browning, lower acrylamide levels andlower levels of reducing sugars have also been grown commercially on a small-scale, in the US
since 2014 (1,780 ha in 2020), and in Canada since 2017 (40 ha in 2020). No impact analysis ispresented here due to the lack of published studies on the subject.
b) Alfalfa
GM HT alfalfa was first commercialised in the US in 2007 on about 100,000 ha. However,between 2008 and 2010, it was not allowed to be planted due to legal action requiring thecompletion of additional environmental impact assessments. This was completed by 2010 andcommercial use of the technology allowed to be resumed in 2011. Approximately 1.28 million haof GM alfalfa were being cropped in 2020. The technology is reported to offer improved weed
control, better yields and higher quality forage. No impact analysis is presented here due to thelack of published studies on the impact.
In addition, GM low lignin alfalfa has been available since 2016 and in 2020 was planted on about
120,000 ha. No impact analysis is presented here due to the lack of published studies on theimpact.

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GM crop impact: 1996-2020

3.4 Indirect (non-pecuniary) farm level economic impacts
As well as the tangible and quantifiable impacts identified and analysed on farm profitability
presented above, there are other important impacts of an economic nature. These include
impacts on a broader range of topics such as labour use, households and local communities. The
literature on these impacts is developing and a full examination of these impacts potentially
merits a study in its own right. These issues are not examined in depth in this work as to do sowould add considerably to an, already, long report. As such, this section provides only asummary of some of the most important additional, and mostly intangible, difficult to quantify,
impacts.
Many of the impact studies 55 cited in this report have identified the following reasons as being
important influences for adoption of the technology:
Herbicide tolerant crops• Increased management flexibility and convenience that comes from a combination of theease of use associated with broad-spectrum, post emergent herbicides like glyphosate
and the increased/longer time window for spraying. This not only frees up management
time for other farming activities but also allows additional scope for undertaking offfarm, income earning activities;• In a conventional crop, post-emergent weed control is important and relies on herbicide
applications after the weeds and crop are established. As a result, the crop may suffer‘knock-back’ to its growth from the effects of the herbicide. In the GM HT crop, thisproblem is avoided because the crop is tolerant to the herbicide;• Facilitates the adoption of conservation or no tillage systems. This provides for
additional cost savings such as reduced labour and fuel costs associated with ploughing,additional moisture retention and reductions in levels of soil erosion;• Improved weed control has contributed to reduced harvesting costs – cleaner crops haveresulted in reduced times for harvesting and improved harvest quality which in somecases has led to price bonuses;• Elimination of potential damage caused by soil-incorporated residual herbicides incurrent crops and follow-on crops (eg, TT canola in Australia). This also means less need
to apply herbicides post-emergence and in a follow-on crop because of the improved
levels of weed control;• A contribution to the general improvement in human safety (as manifest in greater peaceof mind about own and worker safety) from a switch to more environmentally benign
products.
Insect resistant crops• Production risk management/insurance purposes – the technology takes away much of
the worry of significant pest damage occurring and is, therefore, highly valued;• A ‘convenience’ benefit derived from having to devote less time to crop walking and/or
applying insecticides;• Savings in energy use – mainly associated with less use of aerial spraying;
For example, relating to HT soybeans; USDA (1999), Gianessi & Carpenter (2000), Qaim & Traxler (2002),
Brookes (2008); relating to insect resistant maize, Rice (2004); relating to insect resistant cotton Ismael et al(2002), Pray et al (2002)
55©PG Economics Ltd 2022

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GM crop impact: 1996-2020

•
•

•

•

Savings in machinery use (for spraying and possibly reduced harvesting times);
Higher quality of crop. There is a growing body of research evidence relating to thesuperior quality of GM IR maize relative to conventional and organic maize from theperspective of having lower levels of mycotoxins;
Improved health and safety for farmers and farm workers (from reduced handling anduse of pesticides, especially in developing countries where many apply pesticides withlittle or no use of protective clothing and equipment);
Shorter growing season (eg, for some cotton growers in India) which allows some
farmers to plant a second crop in the same season 56. Also some Indian cotton growers
have reported knock on benefits for bee keepers as fewer bees are now lost to insecticide
spraying.

Since the early 2000s, a number of farmer-survey based studies in the US have also attempted tobetter quantify these non-pecuniary benefits. These studies have usually employed contingent
valuation techniques 57 to obtain farmers’ valuations of non-pecuniary benefits. A summary ofthese findings is shown in Table 15.
Table 15: Values of non-pecuniary benefits associated with GM crops in the US
Survey2002 IR (to rootworm) corn growers survey
2002 soybean (HT) farmers survey
2003 HT cropping survey (corn, cotton & soybeans)– North Carolina
2006 HT (flex) cotton survey
Source: Marra & Piggot (2006) and (2007)

Median value ($/hectare)
7.41
12.35
24.71
12.35 (relative to first generation HT cotton)

Aggregating the impact to US crops 1996-2020
The approach used to estimate the non-pecuniary benefits derived by US farmers from biotech
crops over the period 1996-2020 has been to draw on the values identified by Marra and Piggot(2006 & 2007) and to apply these to the GM crop planted areas in this period.
Figure 41 summarises the values for non-pecuniary benefits derived from GM crops in the US
and shows an estimated (nominal value) benefit of $1.1 billion in 2020 and a cumulative total
benefit (1996-2020) of $19.2 billion. Relative to the value of direct farm income benefits presented
above, the non-pecuniary benefits were equal to 15% of the total direct income benefits in 2020
and 17.3% of the total cumulative (1996-2020) direct farm income. This highlights the important
contribution this category of benefit has had on biotech trait adoption levels in the US, especiallywhere the direct farm income benefits have been identified to be relatively small (eg, HT cotton).
Estimating the impact in other countries
It is evident from the literature review that GM technology-using farmers in other countries also
value the technology for a variety of non-pecuniary/intangible reasons. The most appropriate
56

Notably maize in India

57

Survey based method of obtaining valuations of non-market goods that aims to identify willingness to pay

for specific goods (eg, environmental goods, peace of mind, etc) or willingness to pay to avoid something
being lost

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GM crop impact: 1996-2020

methodology for identifying these non-pecuniary benefit valuations in other countries would beto repeat the type of US farmer-surveys in other countries. Unfortunately, the authors are notaware of any such studies having been undertaken to date.
Figure 41: Non-pecuniary benefits derived by US farmers 1996-2020 by trait ($ million)
8,000

7,646

7,000
6,000

5,153

5,000
3,499

4,000
3,000

1,418

2,000
1,000
0

387

203

367

HT soyIR corn

HT corn
2018

1,363

67

71

8 128

IR cotton

HT cotton

HT canola

Cumulative

3.5 Production effects of the technology
Based on the yield assumptions used in the direct farm income benefit calculations presented
above (see Appendix 1) and taking into account the second soybean crop facilitation in SouthAmerica, GM crops have added important volumes to global production of maize, cotton, canolaand soybeans (Table 16).
Table 16: Additional crop production arising from positive yield effects of GM crops (million
tonnes)
1996-2020
Soybeans
330.35Maize
594.58
Cotton37.01
Canola
15.77
Sugar beet
1.87
Note: Sugar beet, US and Canada only (from 2008)

2020
33.48
47.9
2.26
1.00
0.15

The GM IR traits, used in maize and cotton, have accounted for 91.1% of the additional maize
production and 98.2% of the additional cotton production. Positive yield impacts from the use ofthis technology have occurred in all user countries (except for GM IR cotton in Australia 58) when

58

This reflects the levels of Heliothis and Helicoverpa (boll and bud worm) pest control previously obtainedwith intensive insecticide use. The main benefit and reason for adoption of this technology in Australia hasarisen from significant cost savings (on insecticides) and the associated environmental gains from reduced
insecticide use©PG Economics Ltd 2022

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GM crop impact: 1996-2020

compared to average yields derived from crops using conventional technology (such as
application of insecticides and seed treatments). The average yield impact across the total area
planted to these traits over the 25 years since 1996 has been +17.7% for maize and +14.5% forcotton (Table 17).
As indicated earlier, the primary impact of GM HT technology has been to provide more costeffective (less expensive) and easier weed control, as opposed to improving yields. The
improved weed control has, nevertheless, delivered higher yields in some countries. The main
source of additional production from this technology has been via the facilitation of no tillage
production systems shortening the production cycle, and how it has enabled many farmers inSouth America to plant a crop of soybeans immediately after a wheat crop in the same growing
season. This second crop, additional to traditional soybean production, has added 222.7 million
tonnes to soybean production in Argentina and Paraguay between 1996 and 2020. The remaining
additional GM-related soybean production has come from the second generation of GM HT
soybeans grown in North American countries since 2008 and where the GM HT technology has
enabled farmers to obtain higher yield via improved levels of weed control, with Intacta soybeans
having added a further 44.4 million tonnes since 2013.
Table 17: Average (%) yield gains GM IR cotton and maize 1996-2020

US
China
South Africa
Honduras
MexicoArgentina

Maize insect resistanceto corn boring pests
7.0
N/a
11.6
23.9
N/a
5.8

Philippines
Spain
Uruguay
India
Colombia
CanadaBrazilPakistan
Myanmar
Australia
Paraguay
Vietnam
Notes: N/a = not applicable©PG Economics Ltd 2022

Maize insect resistanceto rootworm pests
5.0
N/a
N/a
N/a
N/a
N/a

Cotton insect resistance

N/a
N/a
N/a
N/a
N/a
5.0
N/a
N/a
N/a
N/a
N/a
N/a

N/a
N/a
N/a
29.0
25.0
N/a
1.8
18.0
30.5
Nil
Not available
N/a

18.1
11.6
5.5
N/a
17.1
7.0
11.5
N/a
N/a
N/a
5.5
9.0

82

9.9
10.0
24.0
N/a
11.0
30.0

GM crop impact: 1996-2020

4 The environmental impact of GM crops
This section examines the environmental impact of using GM crops over the last twenty-fiveyears. The two key aspects of environmental impact explored are:a.
b.

Impact associated with insecticide and herbicide use.
Impact on carbon emissions.

These are presented in the sub-sections below.

4.1 Impact associated with insecticide and herbicide use
The control of pests and reduction of weed competition in agricultural production systems is vitalif adequate quantities of good quality food are to be consistently made available to feed the(growing) world’s population. The primary way in which this has been delivered in global
agriculture has been through the use of pesticides which have therefore made important
contributions to improving crop yields, the quality of produce and in turn, improved global foodsecurity (Cooper and Dobson, 2007, Aktar, Sengupta and Chowdhury, 2009). However, despite
these benefits, pesticides can be hazardous to humans and the environment, having the potential
to disperse into the environment and contaminate/poison non-target species. The consequencesof pesticide use have been documented and discussed by many (eg, Bourget and Guillemaud,
2016, Sud, 2020), with pesticide regulatory systems in place ‘to balance the societal and economic
benefits with the unintentional and undesirable environmental and health impacts’ (Lewis et al, 2021).
Against this background, the regulatory approval and subsequent widespread commercial
availability of GM crops in the mid-1990s ushered in a major change to how some pests andweeds were controlled in the crops where the seed technology has become widely used (canola,cotton, maize and soybeans).
An important component of any assessment of the environmental impact of widespread GM crop
cultivation is therefore identifying how their use has impacted on pest and weed control practices
and, in particular on how insecticide and herbicide use has altered. In turn, this requires
comparisons of the respective weed and pest control measures used on GM versus the‘conventional alternative’ form of production and how these may disperse into the environmentand have negative consequences for non-target species. This presents a number of challenges.
How to measure environmental and human health impacts: an appropriate indicator
The challenge to developing an appropriate indicator for evaluating potential non-target effectsof pesticide use requires taking account of differences in terms of environmental and humanhealth impacts of the numerous pesticide active ingredients used and be sensitive enough to takeaccount of differences to the amount (of each) applied to crops. An indicator also needs toadaptable enough to take account of changes in the availability of pesticides via the withdrawalof some from use and the introduction of new chemistry to the marketplace.
To assess the risks and impact of pesticide use in a consistent but simplified manner a number ofindicators have been developed. Some of these are hazard-based, whilst others try to consider
risk.

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GM crop impact: 1996-2020

The most common (and crudest) form of indicator used (and which has been most commonly
been presented in the literature relating to the impact associated with GM crop use) has been
simply to examine impact in terms of the volume (quantity) of pesticide active ingredient applied
under the principle that ‘more is bad for the environment and less is better for the environment’.
Whilst this approach is sensitive enough to take account of changes in the amount applied andcan accommodate the changing availability of different active ingredients, it is not a goodmeasure of environmental impact because the toxicity of each pesticide is not directly related tothe amount (weight) applied and there is consideration of how the active ingredients disperse
into the environmental or may affect non target species.
There exist alternative measures that could be used. These include:
-

-

-

-

-

The Environmental Impact Quotient (EIQ) developed at Cornell University by Kovach etal (1992) and updated annually. This hazard-based indicator is one of the earliest
indicators developed and uses a scoring system approach to determine the impact of apesticide on humans, groundwater and bio-diversity. Rating values are given for effects
on farm workers, consumers, toxicity to beneficial insects, toxicity to bees, fish and birds,
plant surface half-life, chronic health effects, run off and leaching potential, soil residue
half-life and mode of action. These are added to produce a single EIQ rating per active
ingredient, with the EIQ indicator value for each active ingredient determined by theamount applied;
The Environmental Yardstick for Pesticides developed in the Netherlands, whichquantifies risk of pesticide use at the field, regional and national level by allocating
environmental impact points for risks to groundwater, aquatic species and soil organisms(Reus and Leenderste, 2000);SYNOPS indicator, developed to support the German National Action Plan on the
Sustainable Use of Plant Protection Products (Strassemeyer and Gutsche, 2010) whichassess the acute and chronic pesticide risks to soil and surface water and non-target
pollinator species through the calculation of Predicted Environmental Concentrations(PECs);The Norwegian pesticide risk indicator (NERI) was developed both as a tool to assess
pesticide use risk and as a method for taxation of pesticides (Stenrød et al, 2008). It uses a
rating system for human health impacts (4 risk classes according to the risk phrases on
product labels) and environmental risk by adding up rating scores for effects onearthworms, bees, birds, aquatic organisms, mobility and leaching potential, persistence,
bioaccumulation and formulation type. The accumulated rating scores are then used toclassify pesticides into three environmental risk classes and grouped into several classes
subject to different tax levels;
Like NERI, the Pesticide Load (PL) risk indicator developed in Denmark was primarily
developed to form the basis for a national pesticide tax system (Kudsk et al, 2018). The
indicator is made up of three categories of indicator that aim to measure the potential
pressure on human health, environmental fate and ecotoxicity. This does not measure
actual impact but aims to reflect the relative environmental pressures from the differing
hazards of each pesticide and the amount of each applied. In relation to theenvironmental fate ecotoxicity indicators, pesticide loading points for each pesticide ismeasured against a benchmark reference substance that is classified as the most harmful
active ingredient for each parameter (eg, longest soil half-life) and all other substances
are expressed relative to this reference active ingredient;©PG Economics Ltd 2022

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GM crop impact: 1996-2020

-

-

-

Total Applied Toxicity (TAT). This indicator uses regulatory threshold levels for impactsof pesticide active ingredients on eight different groups of non-target species as
indicators of potential impact on bio-diversity (Schulz et al, 2021). The authors applied
this approach to assess environmental impacts associated with insecticide and herbicide
use in maize and soybeans in the US;
The Ecological Relative Risk (EcoRR) indicator (Sanchez-Bayo et al, 2002). This is a sitespecific indicator that assesses and compares the ecotoxicological risk of pesticides on
ecosystems. It compares relative risks between different pesticides and assesses thepotential ecological impact of their residues. The EcoRR approach is based on standard
frameworks for risk assessment (eg, Predicted Environmental Concentration (PEC) or
toxicity) but takes account of factors such as persistence of residues and biodiversity of
ecosystems;
The European Union’s Harmonised Environmental Indicators for Pesticide Risk (HAIR)
is a set of indicators developed for calculating trends in aggregated risks associated withthe agricultural use of pesticides. This is a series of models for the evaluation of theenvironmental fate of pesticides (eg, PEARL - Pesticide Emission Assessment at Regionaland Local scales that model’s pesticide behaviour in the soil-plant system). It has beenused to classify pesticides used in European agriculture into different risk categories so
as to set a baseline for the reduction in the aggregate level of risks associated withpesticide use. Success (or failure) in this goal is largely determined via monitoring andcollecting data on the sales of products in each pesticide risk category, with sales figures
used as a proxy for use (and ultimate impact).

Whilst the list of indicators above represent some, not a full list of those available, it highlights
the range of indicators, each of which was originally developed with a specific purpose in mind
(eg, as a vehicle for establishing a pesticide tax) and/or targeting specific local, regional or
national impact assessment. Hazard based indicators do not assess risk or probability of
exposure to pesticides typically rely to some extent on qualitative assumptions and ratings drawn
from product label and regulatory threshold information for the scaling and weighting of(quantitative) risk information. This can result, for example in the case of the EIQ indicator, in a
low risk rating for one factor (eg, impact on farm workers) possibly cancelling out a high-risk
rating factor for another factor (eg, impact on ecology). Other models or indicators that attempt
to include risk of exposure into the assessments typically require site-specific or local/regional
level data on issues such ground water levels or soil structure or at least the application ofstandard scenario models for exposure at a number of locations. This is why indicator/models
such as SYNOPS was developed for specific applicability to Germany are country-specific in theirapplication and replication/adaption of such models to other countries (as is the case in respect of
Norway and Switzerland) is difficult, time consuming and requires adaption to reflect differinglevels of information.
For the purposes of our analysis, an indicator is required that is readily available and applicable
across a range of crops (notably the four main crops where GM crop technology is widely used),grown in more than 20 countries on an area of approximately 186 million hectares (2020). This
encompasses a wide range of climates, soil types, weather, agricultural production systems, ecosystems, non-target species and pest and weed control practices. Whilst a risk rating type modelsuch as SYNOPS might represent an ideal to utilise, the transferability/applicability of such an
exercise to this context is undeliverable.

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GM crop impact: 1996-2020

The indicator that has been used most by various analysts to assess the environmental impact
associated with changes to pest and weed control practices with the growing of GM crops has
been the EIQ. It was originally developed to allow for the comparison of the environmental
impact of different crop protection systems used as more integrated forms of pest and weed
control were introduced in the US, in the 1990s. Its early adaption and use in respect of the use ofGM crop technology relative to conventional (non-GM) cropping was made by Brimner et al,2004 and Kleiter, 2005, with this author also using it first in 2005. It has also subsequently beenused by others (eg, Biden et al, 2018). As indicated above, the EIQ integrates the various rating
values for effects on farm workers, consumers, toxicity to beneficial insects, toxicity to bees, fish
and birds, plant surface half-life, chronic health effects, run off and leaching potential, soil residue
half-life and mode of action to produce a single EIQ rating per active ingredient, with the EIQ
indicator value (or field EIQ) for each active ingredient determined by the amount applied. For
example, the EIQ rating for glyphosate is 15.33. By using this rating multiplied by the amount ofglyphosate used per hectare (eg, a hypothetical example of 1.1 kg applied per ha), the field EIQ
value for glyphosate would be equivalent to 16.86/ha. The EIQ indicator used is therefore acomparison of the sum of the field EIQ/ha for each pesticide used for a conventional (non-GM)
versus GM crop production system, with the total environmental impact or load of each system, adirect function of respective field EIQ/ha values and the area planted to each type of production(GM versus conventional).
The author of this analysis have used the EIQ indicator now for several years because it:••

Summarises significant amounts of information on pesticide impact into a single value
that, with data on usage rates (amount of active used per hectare) is transferable andrelatively easy to use/apply across crops and production systems across the many
diverse regions and countries where GM crops have been widely grown;
Provides an improved assessment of the impact of GM crops on the environment whencompared to only examining changes in volume of active ingredient applied, because it
draws on some of the key toxicity and environmental exposure data related to individual
products, as applicable to impacts on farm workers, consumers and ecology.

Whilst utilising the EIQ indicator in this analysis, the author acknowledges that it is only ahazard indicator and, as indicated above, it has important weaknesses. These have been
discussed by others such as Peterson R and Schleier J (2014) and Kniss A and Coburn C (2015).
Undertaking such an exercise at a global level would require a substantial and ongoing input oflabour and time, if comprehensive environmental impact of pesticide change analysis is to becompleted. It is not surprising that no such exercise has, to date been undertaken. It is hopedthat in the near future indicators that better consider risks of pesticide exposure and the fate ofpesticides in the environment but at the same time are transferable and reasonably easy to use
and apply to a variety of different cropping systems around the world.
Despite the acknowledged weaknesses of the EIQ as an indicator of environmental impact
associated with pesticide use, the author of this paper continues to use it because no otherindicator currently offers the scope for relatively easy transferability and use across a wide rangeof crops, and countries. In this paper, the EIQ indicator is used in conjunction with examiningchanges in the amount of pesticide active ingredient applied to GM crops relative to conventional(non-GM) crops.

©PG Economics Ltd 2022

86GM crop impact: 1996-2020

Availability and representativeness of data.
Assessing the environmental impact associated with crop protection and weed control practices
used with GM crops relative to conventional alternatives, requires making comparisons of themethods used, most notably relating to the use of insecticides and herbicides. Such comparison
data ideally derives from farm level surveys which collect usage data on the different forms of
production. A search of the literature on insecticide or herbicide use change with GM crops
shows that the number of studies exploring these issues is fairly limited (eg, Qaim and Traxler,
2005, Pray C, 2002) with even fewer (eg, Brookes, 2005, Brookes, 2009) especially in terms ofproviding data to the individual active ingredient level. Secondly, national level pesticide usage
survey data is also limited. There are no published, detailed, annual pesticide usage surveys
conducted by national authorities in any of the countries currently growing GM crop traits. Of
the GM crop growing countries, the US, through the US Department of Agriculture (USDA) is the
only country that regularly publishes pesticide usage surveys on some of the crops in which GM
technology is used. However, these are not conducted on an annual basis for each crop (eg, thelast time maize was included was 2018 and previous to this, in 2016, 2014, 2010 and 2005, forsoybeans the last time included was 2020 and before that 2018 and 2015) and do not disaggregate
usage by production type (GM versus conventional).
The only sources of pesticide usage data on the crops in which GM technology has been usedaround the world derive from two main sources:••

Ad hoc/bespoke studies of the impact of using GM crop technology relative toconventional alternative crops. These are typically crop specific and limited both interms of time periods covered (1-3 years) and may be local in nature rather thanreasonably representative of a national perspective;
Private market research companies that undertake farm level surveys of crop-specificpesticide use on a regular basis. These are primarily conducted to collect data(typically to the product and brand level) in order to service the market intelligenceand information requirements of businesses that sell crop protection products andcan be found in many countries. The most comprehensive datasets from thesesources typically focus on usage in the larger agricultural producing countries suchas the US, Canada, Brazil, Argentina, Paraguay, South Africa, the EU, Australia,
China and India. Access to these datasets requires the payment of subscriptions tothe suppliers and typically comes with restrictions on the publication ofdisaggregated levels of data (in particular to the brand and product level). With the
exception of the data available relating to pesticide use on a limited range of crops in
the USA, this source of data does not differentiate between use of active ingredientsor products by production type (GM versus conventional).

In this analysis, the author draws on both categories of data. This includes reviewing literature
on published GM crop impact studies both on peer reviewed and other literature. It draws on
relevant publicly available pesticide usage survey data (primarily USDA) and has accessedprivate market research sources from the primary providers over the last 20 years, most notably
Kynetec and Kleffmann, which have both collected pesticide usage data on many crops in a
number of countries around the world. Access to these private sources of data has been
facilitated by the primary sponsor of this study – Bayer Crop Science. Details of the sources used
for analysis by crop and country are detailed in Appendix 2. This means that this analysis draws
on the most comprehensive and detailed sources of pesticide usage available at a global level. It©PG Economics Ltd 2022

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GM crop impact: 1996-2020

also means that the EIQ indicator calculations made in the course of the analysis takes into
consideration all of the main pesticides used in the production of the crops where GM crop
technology is used. For example, in the US, this relates to about 55, 50 and 40 herbicides
respectively used in soybeans, maize and cotton crops, in Brazil, 40 and 30 herbicides respectively
used on soybean and maize crops and in Argentina, about 60 and 20 herbicides used on soybeans
and maize. Similarly EIQ values associated with the use of about 30 insecticides used in cottongrown in Australia and India, 45 in China and about 50 in the US.
Whilst the research has accessed and utilised these comprehensive sources of (pesticide use) data,
it is important to recognise the limitations than come with this data for the purposes of the analysis.
A primary objective of the research is to assess the environmental impact of crop protection practicedifferences between production systems that use GM crop technology and those that use
conventional technology (based on the EIQ indicator). In order to do this herbicide and insecticide
usage changes with GM crop technology adoption require identification in terms of not only what
is currently used with GM crops, but also in the ‘counterfactual situation’, that is, what
herbicides/insecticides might reasonably be expected to be used in the absence of crop
biotechnology on the relevant crops (ie, if the entire crops reverted to using non-GM production
methods).
The most straightforward way of doing this is from observations and surveys of crop protection
practices on farms using the different production systems. As such, this source of data from ad
hoc/bespoke surveys of usage on farms using GM versus non GM technology has been utilised inthis analysis, where available. This category of data does not cover every trait, crop, country or
year and therefore alternative sources and assumptions are required.
As indicated above, an important source of data used is the regular farm level pesticide usage
survey data collected by private market research companies and made available on subscription.
For all countries studied, with the exception of the US, this data source does not disaggregate usage
for each active ingredient to production type (GM versus non-GM) and therefore this source has
been used in the following way:••

Where GM-herbicide traited crops account for all or almost all (90% plus) of production ina country (eg, soybeans in all of the South American countries), the herbicide (and/or
insecticide) usage data is assumed to represent the GM HT and/or GM IR crop;
For conventional crops and GM HT/IR crops where the less than 90% of the crop is GM
HT/IR, estimates of herbicide use in overall weed/pest control systems are based on
information drawn from extension and industry advisors in each country (some of thisderives from literature such as weed control guides from extension services and some fromdirect contact with advisors in such services, academics and industry representatives). In
all cases, the aim has been to identify the weed/pest control practices that farmers mightreasonably be expected to use (including typical herbicide and insecticide application
rates) in both GM HT/IR and conventional crops. In relation to GM IR versus conventional
crop pest control practices the focus has been on products used to control only the pests
that the GM IR technology targets control (typically lepidopteran pests (and rootworm inNorth America) and not products used to control other categories of pests (eg, sucking
pests and (cotton) weevils). In addition, in the early years of adoption of GM traited crops,
the usage assumed for conventional crops has been cross checked with recorded usage
levels in the years immediately prior to the introduction of GM technology to ensure that©PG Economics Ltd 2022

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GM crop impact: 1996-2020

usage levels derived from the extension service approach did not over (or understate)
likely usage levels.
In the case of the US, where pesticide usage data for the crops of cotton, maize and soybeans isavailable at a disaggregated level (GM versus conventional crop), the approach used reflects therelative balance of the total crop accounted for GM versus conventional as follows:•••

Recorded herbicide and insecticide usage (to the active ingredient level) for GM traitedcrops has been used for all years;
Recorded herbicide and insecticide usage (to the active ingredient level) for conventional
crops has been used for all years until the conventional share of total production fell
below 30% of the crop (2001 for cotton and soybeans and 2007 for maize);
For conventional cotton and soybeans post 2001 and maize post 2012, estimates based on
extension service type sources have been used (statistical source: USDA NASS 2022).

In the case of the US analysis, the reasons why herbicide/insecticide usage levels identified for theincreasingly small conventional crop were not used and have been replaced by usage patterns
identified from ‘extension service’ type sources reflects the author’s assessment that these levelsof usage are unrepresentative of what might reasonably be expected if all of the (majority) area
using GM technology reverted to conventional (non-GM) production systems. More specifically:••

Although pest/weed damage and competition varies by year, region and within region,
farmers’ who consistently farm conventionally rather than using GM seed may be thosewith relatively low levels of pest/weed problems, and hence see little, if any economic
benefit from using the GM traits targeted at these pest/weed problems. In addition, late or
non-adopters of new technology in agriculture are typically those who generally make lessuse of newer technologies than earlier adopters. As a result, insecticide/herbicide usage
levels on non-adopting (conventional) farms tend to be below the levels that would
reasonably be expected on an average farm with more typical pest/weed problems andwhere farmers are more willing to adopt new technology;
Some of the farms continuing to sow conventional seed, use extensive, low intensity
production methods (including organic) which feature, limited (below average) use ofherbicides/insecticides. If the pesticide usage patterns of this sub-set of growers are used
as a proxy to represent usage patterns if all farmers returned to farming without GM
technology, this is likely to understate pesticide usage for the majority of farmers. For
example, prior to the adoption of GM HT cotton in the US in the mid-1990s, when all of
the crop was conventional, about 90% of the crop was typically receiving some use ofherbicides for weed control and the average amount of herbicide used (kg/ha) and average
EIQ/ha value for herbicide use on this crop were respectively about 2.54 kg ai/ha with
54/ha. Within this cotton farmers in Texas, where many producers practice extensive
production systems (little or no use of inputs like pesticides), the average amount of
herbicide active ingredient used and average EIQ/ha were respectively about 1.54 kg/ha
and an average EIQ/ha of 31.1 (Texas then accounted for just under 60% of the US cottoncrop). In 2020, the conventional cotton crop accounted for about 4% of the total crop (about
138,000 ha), of which 84% of the crop received some form of herbicide use as part of weed
control and 80% of the crop was located in Texas. Using the recorded average usage figures
for herbicide use in Texas in 2020 (about 1 kg ai/ha and an EIQ/ha value of about 21/ha) as©PG Economics Ltd 2022

89

GM crop impact: 1996-2020••

a proxy for what might be used if all of the US cotton reverted to conventional (non-GM)
production methods method, is therefore likely to significantly understate likely usage;
The widespread adoption of GM IR technology has resulted in ‘area-wide’ suppression oftarget pests in maize, cotton and soybean crops. As a result, conventional farmers (eg, ofmaize in the US) have benefited from this lower level of pest infestation and the associatedreduced need to apply insecticides (Hutchison et al, 2010).
Many farmers have experienced improvements in pest/weed control with GM technology
compared to the conventional control methods previously used. If these farmers were toswitch back to using conventional techniques, it is likely that most would want to maintainpest/weed control levels obtained with GM traits and therefore some would probably use
higher levels of insecticide/herbicide than they did in the pre-GM crop days (eg, as
identified by Brookes (2008) relating to IR maize growers in Spain). Nevertheless, thedecision to use more pesticide or not would be made according to individual assessmentof, for example, the potential benefits (eg, from higher yields) compared to the cost ofadditional pesticide use.

This methodology has been used by others in relation to analysis of pesticide use change withGM crops in the US such as Sankala and Blumenthal, 2003, Sankala and Blumenthal, 2006,
Johnson and Strom, 2006.
Details of how this methodology has been applied to the 2020 calculations, sources used for each
trait/country combination examined and examples of typical conventional versus GM pesticide
applications are provided in Appendix 3.

4.1.1 GM herbicide tolerant (to glyphosate) soybeans (GM HT)a) The US
The average amount of herbicide active ingredient (ai) used per hectare on the US soybean crop
has been fairly stable for the period to 2006, but has increased since then (Figure 42). The average
field EIQ/ha load has followed a broadly similar pattern of change as the amount of active
ingredient used (Figure 43).

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GM crop impact: 1996-2020

Figure 42: Average herbicide usage on soybeans in the US 1996-2020 (kg/ha)
3
2.6
2.36

2.5

1.5
1

2.03

2

1.97

2
1.53
1.291.23

1.221.09
1.09 1.23
1.05
1.02
0.73

0.5

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0

Source: USDA NASS. Note - no collection of data in 2003, 2007-2011, 2013, 2014, 2016, 2019

Figure 43: Average herbicide usage on soybeans in the US 1996-2020 (EIQ/ha)
60
47.64

50
42.51
40
30

34.6

34.5

32
26.2
22

21.5
19.620.2

20

21.4

20.2
16.9
15.2

13.4

10

2020

2019

2018

2017

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

2016

0

0

Source: USDA NASS. Note - no collection of data in 2003, 2007-2011, 2013, 2014, 2016, 2019

A comparison of the amount of herbicide active ingredient applied to conventionally grownsoybeans (per ha) and GM HT soybeans shows that herbicide ai use on conventional soybeans
has also followed a similar pattern of changes in herbicide use with GM HT soybeans. Broadly,
the average amount of herbicide active ingredient applied to both types of production was fairly
stable up to the mid-2000s (at around 1.1 to 1.3kg/ha for conventional compared to 1.3 to 1.4kg/ha
for GM HT soybeans). Since 2006, the average amount of herbicide active ingredient applied toboth forms of production has increased in a similar way so that in the last five years the averageamount of herbicide active ingredient applied to the GM HT crop (which accounts for 93%-94%©PG Economics Ltd 2022

91

GM crop impact: 1996-2020of the total crop) has been in the range 2.5 kg/ha to 3.0 kg/ha compared to the average amount of
herbicide active ingredient applied to the conventional crop (which accounts for 6%-7% of thetotal crop) which has been in the range of 1.75 kg/ha to 2.2 kg/ha 59.
The increased usage of herbicides on GM HT soybeans partly reflects the increasing incidence of
weed resistance to glyphosate that has occurred in recent years (see section 4.1.9 for additional
discussion). This has been attributed to how glyphosate was used; because of its broad-spectrum
post-emergence activity, it was often used as the sole method of weed control. This approach to
weed control put selection pressure on weeds and as a result contributed to the evolution of
weed populations predominated by resistant individual weeds. In addition, the facilitating roleof the technology in the adoption of no and reduced tillage production techniques has also
contributed to the emergence of weeds resistant to herbicides like glyphosate and to weed shifts
towards those weed species that are inherently not well controlled by glyphosate. Some of theglyphosate resistant species, such as marestail (Conyza canadensis), waterhemp (Amaranthus
tuberculatus) and palmer pigweed (Amaranthus palmeri) are now widespread in the US.
As a result, over the last 20 years, growers of GM HT crops in the US have been using otherherbicides (with different and complementary modes of action) in combination with glyphosate
and in some cases adopting cultural practices (eg, reverting back to ploughing) in more
integrated weed management systems. In addition, GM HT crops tolerant to other herbicides(often stacked with glyphosate) have also become available from 2016 (notably to dicamba and 2
4 D).
At the macro level, these changes have influenced the mix, total amount and overall
environmental profile of herbicides applied to GM HT soybeans (and to cotton, maize andcanola) in the last 20 years. For example, in the 2020 US GM HT soybean crop, approximately
two-thirds of the crop area was planted to varieties that were tolerant to other herbicides (inaddition to tolerance to glyphosate) and even where single tolerance-traited crops were planted,
almost all of these crops received an additional herbicide treatment of other active ingredients(notably sulfentrazone, S metolachlor, 2 4 D, metribuzin, metsulfuron and pyrosulfone). This
compares with only 14% of the GM HT soybean crop (almost all tolerant to only glyphosate)
receiving a treatment of one of the next four most used herbicide active ingredients (after
glyphosate) in 2006. As a result, the average amount of herbicide active ingredient applied to the
GM HT soybean crop in the US (per hectare) doubled over this period. It is interesting to notethat by 2016, glyphosate accounted for a lower share of total active ingredient use on the GM HT
crop (63%) than in 1998 when it accounted for 82% of total active ingredient use, highlighting thecontinued value to farmers of using glyphosate because of its broad-spectrum activity, in
addition to using other herbicides in line with integrated weed management advice. This
continues in 2020, with the availability of additional options for weed control via varieties withGM HT tolerance to other herbicides. Whilst alternatives to glyphosate tolerant varieties areavailable, the vast majority used contain tolerance to glyphosate plus at least one other herbicide.
On the small conventional crop, the average amount of herbicide active ingredient applied also
doubled over the period 2006-2020. The increase in the use of herbicides on the conventional
soybean crop in the US can also be mainly attributed to the on-going development of weed

59

Sources: derived from USDA NASS, University extension services and Kynetec©PG Economics Ltd 2022

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GM crop impact: 1996-2020

resistance to non-glyphosate herbicides commonly used and highlights that the development ofweed resistance to herbicides is a problem faced by all farmers, regardless of production method.
A comparison of average field EIQs/ha also shows fairly stable values for both conventional and
GM HT soybean crops for most of the period to the mid-2000s, followed by increases in the last
20 years (Figure 43). The average load rating for GM HT soybean crops was lower than the
average load rating for conventional soybeans for most of the period up to the mid-2000s, despite
the continued shift to no/low tillage production systems that rely much more on herbicide-based
weed control than conventional tillage systems and the adoption of reactive and proactive weed
resistance management programmes. Since 2006, the average field EIQ/ha ratings on GM HT
soybean and conventional soybean crops have increased significantly on both production
systems.
Figure 44: A comparison of the average EIQ/ha for conventional and GM HT soybeans in the
US 1996-2020
60.00
50.00
40.00
30.00
20.00
10.00

GM HT

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00

Conventional

Sources: derived from USDA NASS, Kynetec and University extension services

The comparison data between the GM HT crop and the conventional alternative presented aboveis, however, of limited value because of bias in respect of the conventional crop usage data. Thevery small area of conventional crop from which herbicide usage data is obtained means that thedata poorly represents what might reasonably be considered as the ‘conventional alternative’ if
GM HT technology was not available.
The reasons why the conventional cropping data set is likely to be biased and unrepresentative ofthe levels of herbicide use that might reasonably be expected in the absence of biotechnology
include:•Whilst the degree of weed problems/damage vary by year, region and within region,
farmers who continue to farm conventionally may be those with relatively low levels of
weed problems, and hence see little, if any, economic benefit from using the GM HT traits
targeted at minimal weed problems. Their herbicide usage levels therefore tend to be©PG Economics Ltd 202293

GM crop impact: 1996-2020••

below the levels that would reasonably be expected on an average farm with more typical
weed infestations;
Some of the farms continuing to use conventional seed generally use extensive, lowintensity production methods (including organic) which feature limited (below average)
use of herbicides. The usage patterns of this sub-set of growers is therefore likely tounderstate usage for the majority of farmers if they all returned to farming without the useof GM HT technology;
Some of the farmers using GM HT traits have experienced improvements in weed control
from using this technology relative to the conventional control methods previously used.
If these farmers were to now revert to using conventional techniques, it is likely that mostwould wish to maintain the levels of weed control delivered with use of the GM HT traits
and therefore some would use higher levels of herbicide than they did in the pre-GM HT
crop days.

In addition, the use of no/low tillage production systems also tends to be less prominent amongst
conventional soybean growers compared to GM HT growers. As such, the average herbicide
ai/ha and EIQ/ha values recorded for all remaining conventional soybean growers tends to falland be lower than the average would have been had all growers still been using conventional
technology.
This problem of bias has been addressed, firstly by using the average recorded values forherbicide usage on conventional crops for years only when the conventional crop accounted formore than 50% of the total crop and, secondly, in other years (eg, from 1999 for soybeans, from2001 for cotton and from 2007 for maize in the US) applying estimates of the likely usage if thewhole US crop was no longer using crop biotechnology, based on opinion from extension andindustry advisors across the US 60. In addition, the usage levels identified from this methodology
were cross checked (and subject to adjustment) against historic average usage levels of key
herbicide active ingredients from sources such as USDA NASS and Kynetec, so as to minimise
the scope for understating or overstating likely usage levels on the conventional alternative.
Based on this approach, the respective values for conventional soybeans since 2006 are shown in
Table 18. The key features of this comparison are that the average amount of active ingredientused on conventional soybeans, if this type of production were to replace the current area planted
to GM HT soybeans, is roughly similar to current GM HT herbicide usage levels, but a switch toconventional soybeans would result in a higher average field EIQ/ha value (in other words theconventional soybean system would be worse for the environment in terms of toxicity than the
GM HT system).
Table 18: Average ai use and field EIQs for conventional soybeans 2006-2018 to deliver equal
efficacy to GM HT soybeans
Year
2006
2007
2008
60

Ai use (kg/ha)
1.49
1.60
1.62

Field EIQ/ha
36.2
33.1
36.2

Original analyses by Sankala and Blumenthal (2006) and Johnson and Strom (2008) were based on

consultations with extension advisors in over 50 US states. Subsequent years have been updated by the author©PG Economics Ltd 2022

94

GM crop impact: 1996-2020

2009
1.66
42.7
2010
1.71
46.1
2011
2.02
38.5
2012
2.14
44.0
2013
2.21
41.6
2014
2.19
42.2
2015
2.40
47.5
2016
2.41
45.6
2017
2.57
49.0
2018
2.42
45.7
2019
2.78
53.7
2020
2.78
54.7
Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetec

Using this methodology for comparing conventional versus GM HT soybean herbicide usage interms of the respective EIQ/ha values, Figure 45 shows that the average EIQ/load per ha for GM
HT soybeans has typically been lower than the conventional equivalent, although the gap
between the two has narrowed. The average load value for both production systems has also
increased between 2006 and 2020).
Figure 45: A comparison of the average EIQ/ha for weed control systems used in conventional
soybeans that delivers equal efficacy to weed control systems in GM HT soybeans in the US
2006-2020
60
50
40
30
20
10
0

GM HT

Conventional

Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetec

Aggregating these farm level impacts to the national level:•

In 2020, there was a small net increase in herbicide ai use of 1.7% (1.56 million kg). The
EIQ load was lower by 5.3% compared with the conventional (no/low tillage) alternative(ie, if all of the US soybean crop had been planted to conventional soybeans);©PG Economics Ltd 202295

GM crop impact: 1996-2020•

Cumulatively since 1996, there have been savings in both active ingredient usage and theassociated environmental impact (as measured by the EIQ indicator) of -1.8% (26.5
million kg) in active ingredient usage and -18.6% for the field EIQ load.

b) Canada
The analysis of impact in Canada is based on comparisons of typical herbicide regimes used for
GM HT and conventional soybeans and identification of the main herbicides that are no longer
used since GM HT soybeans have been adopted 61. Overall, this identifies:•••

Up to 2006, an average ai/ha and field EIQ value/ha for GM HT soybeans of 0.9 kg/ha
and 13.8/ha respectively, compared to conventional soybeans with 1.43 kg/ha of ai and afield EIQ/ha of 34.2;
2006-2015, the same values for conventional with 1.32 kg/ai and a field EIQ/ha of 20.88
for GM HT soybeans;
From 2016, conventional 1.76 kg ai/ha and an average EIQ/ha of 34.9 compared to GM
HT with 1.72 kg/ha and 28.02 EIQ/ha.

Based on these values, at the national level 62, in 2020, there was a net decrease in the volume ofactive ingredient used of 1.7% (-610,000 kg) and a 16.9% decrease in associated environmental
impact (as measured by the EIQ indicator: Table 19). Cumulatively since 1997, there has been an
5.1% saving in active ingredient use (3 million kg) and a 20.4% saving in field EIQ/ha indicatorvalue.
Table 19: National level changes in herbicide ai use and field EIQ values for GM HT soybeansin Canada 1997-2018

61

Year

ai saving (kg)EIQ saving (units)% decrease in ai (- =increase)% EIQ saving

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

530
25,973
106,424
112,434
169,955
230,611276,740
351,170
373,968
84,13075,86096,800103,374
113,729
97,749119,977

20,4081,000,094
4,097,926
4,329,353
6,544,233
8,879,827
10,656,037
13,522,035
14,399,885
10,191,227
9,167,500
11,726,000
12,521,832
13,776,201
11,840,550
14,533,032

0.03
1.8
7.4
7.4
11.1
15.7
18.5
20.4
22.2
4.8
4.5
5.6
5.2
5.4
4.4
5.0

0.06
3.0
11.9
11.9
17.9
25.4
29.8
32.8
35.8
24.5
22.7
28.5
26.5
27.3
22.2
25.3

Sources: George Morris Center (2004) and the (periodically) updated Ontario Weed Control Guide

Savings calculated by comparing the ai use and EIQ load if all of the crop was planted to a conventional(non-GM) crop relative to the ai and EIQ levels on the actual areas of GM and non-GM crops in each year

62

©PG Economics Ltd 202296

GM crop impact: 1996-2020

2013
2014
2015
2016
2017
2018
2019
2020

133,634
149,969
65,157
67,142
84,23573,787
69,94761,434

16,187,269
18,165,957
12,734,412
13,122,473
16,463,031
14,421,142
13,670,602
12,006,856

5.0
3.7
1.7
1.7
1.6
1.7
1.8
1.7

25.3
24.1
16.7
17.1
16.1
16.3
17.3
16.9

c) Brazil
Drawing on herbicide usage data from private market research sources (AMIS Global andKleffmann), plus industry and extension advisers, the annual average use of herbicide active
ingredient per ha in the early years of GM HT adoption was estimated to be a difference of
0.22kg/ha (ie, GM HT soybeans used 0.22 kg/ha less of herbicide active ingredient) and resulted
in a net saving of 15.62 field EIQ/ha units. More recent data on herbicide usage from the same
sources, suggests changes in herbicide regimes used in both systems, partly due to changes inherbicide availability, prices, increasing adoption of reduced/no tillage production practices (inboth conventional and GM HT soybeans) and weed resistance issues. As a result, estimatedvalues for the respective systems in 2020 (see Appendix 3) were:••An average active ingredient usage of 3.1 kg/ha for GM HT soybeans compared to 3.16kg/ha for conventional soybeans;
The average field EIQ/ha value for the two production systems were 48.95/ha for GM HT
soybeans compared to 54.72/ha for conventional soybeans 63.

Based on the above herbicide usage data, (Table 20):••

In 2020, the total herbicide active ingredient use was 1.7% lower on GM HT crops than it
would likely have been if the crop had been conventional. The EIQ/ha environmentalload was 10.1% lower than if the crop had been conventional;
Cumulatively since 1997, there has been a 0.5% increase in herbicide active ingredient use(7.9 million kg). However, there has been a 7.7% reduction in the environmental impact.

Table 20: National level changes in herbicide ai use and field EIQ values for GM HT soybeansin Brazil 1997-2020
Year

1997
1998
1999
63

ai saving (kgnegative sign
denotes increase in
ai use)22,333
111,667
263,533

EIQ saving (units)% decrease in ai (- =increase)% EIQ saving

1,561,667
7,808,333
18,427,667

0.1
0.3
0.7

0.3
1.4
3.3

Inclusive of herbicides (mostly glyphosate) used in no/low tillage production systems for burndown.

Readers should note that this data is based on recorded usage of key actives for the two production systems
and does not indicate if equal efficacy to the GM HT system is achieved in the conventional system©PG Economics Ltd 202297

GM crop impact: 1996-2020

2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020

290,333
292,790
389,145
670,000
1,116,667
2,010,000
2,546,000-2,928,750-2,930,400-3,564,000-4,040,300-4,722,073-5,663,575-1,716,122-1,842,482
1,806,682
1,886,378
1,956.742
1,999,214
2,046,270
2,115,113

20,301,667
20,473,450
27,211,105
46,850,000
78,083,333
140,550,000
178,030,000-38,073,750-38,095,200-46,332,000-52,523,900
67,340,860
80,767,507
188,138,287
201,991,139
180,421,820
188,421,820
195,450,242
199,692,556
203,889,922
210,749,397

0.7
0.7
0.8
1.2
1.7
2.9
4.0
-4.5
-8.4
-9.3
-10.2
-7.0
-7.6
-2.3
-2.3
1.7
1.8
1.8
1.7
1.8
1.7

3.4
3.4
3.8
5.9
8.4
14.4
19.8
-4.1
-6.5
-7.2
-7.9
6.1
6.6
13.3
13.3
9.9
10.2
10.3
10.1
10.1
10.1

d) Argentina
In assessing the changes in herbicide use associated with the adoption of GM HT soybeans inArgentina, it is important to take into consideration the following contextual factors:••

Prior to the first adoption of GM HT soybeans in 1996, 5.9 million ha of soybeans weregrown, mostly using conventional tillage systems. The average use of herbicides waslimited (1.1 kg ai/ha with an average field EIQ/ha value of 21);
In 2020, the area planted to soybeans was 18.5 million ha. Almost all of this (97%) was
planted to varieties containing the GM HT trait, and 90% plus of this area used
no/reduced tillage systems that rely more on herbicide-based weed control programmes
than conventional tillage systems.

Since 1996, the use of herbicides in Argentine soybean production has increased, both in terms ofthe volume of herbicide ai used and the average field EIQ/ha loading. In 2020, the estimatedaverage herbicide ai use was 3.59 kg/ha and the average field EIQ was 54.53/ha 64. Given morethan 99% of the total crop is GM HT; these values effectively represent the typical values of use
and impact for GM HT soybeans in Argentina.
These changes should, however, be assessed within the context of the fundamental changes intillage systems that have occurred over the 1996-2020 period (some of which may possibly havetaken place in the absence of the GM HT technology 65). Also, the expansion in soybean plantings
64

Source: AMIS Global (national herbicide usage data based on farm surveys)

65

It is likely that the trend to increased use of reduced and no till systems would have continued in the absenceof GM HT technology. However, the availability of this technology has probably played a major role infacilitating and maintaining reduced and no till systems at levels that would otherwise have not arisen©PG Economics Ltd 202298

GM crop impact: 1996-2020

has included some areas that had previously been considered too weedy for profitable soybean
cultivation. This means that comparing current herbicide use patterns with those of 20 years ago
is not a reasonably representative comparison of the levels of herbicide use under a GM HT
reduced/no tillage production system and a conventional reduced/no tillage soybean production
system.
To make a representative comparison of usage of the GM HT crop, with what might reasonably
be expected if all of the GM HT crop reverted to conventional soybean production, requires
identification of typical herbicide treatment regimes’ for conventional soybeans that would
deliver similar levels of weed control (in a no tillage production system) as achieved in the GM
HT system. To do this, we identified a number of alternative conventional treatments (seeAppendix 3 for the 2020 alternatives). Based on these, the current GM HT largely no tillage
production system, has a marginally lower volume of herbicide ai use (3.59 kg/ha compared to
3.62 kg/ha) than its conventional no tillage alternative. In terms of associated environmental
impact, as measured by the EIQ methodology, the GM HT system delivers an 11% improvement(GM HT field EIQ of 54.53/ha compared to 62.04/ha for conventional no/low tillage soybeans).
At the national level these reductions in herbicide use 66 are equivalent to:••

In 2020, a 0.7% decrease in the volume of herbicide ai used (0.43 million kg) and a net
11.8% reduction in the associated environmental impact, as measured by the EIQ
indicator (120 million EIQ/ha units);
Cumulatively since 1996, there has been a net increase in herbicide ai use of +0.6% (+7.7
million kg) but a lower (net environmental gain) field EIQ load of 9.4% lower (1.97
million field EIQ/ha units) than the level that might reasonably be expected if the total
Argentine soybean area had been planted to conventional cultivars using a no/low
tillage production system.

e) Paraguay
The analysis presented below for Paraguay is based on AMIS Global/Kleffmann usage data forthe soybean crop and estimates of conventional alternative equivalents. Based on this, therespective differences for herbicide ai use and field EIQ values for GM HT and conventional
soybeans in 2020 were:••Conventional soybeans: average volume of herbicide used 3.3 kg/ha and a field EIQ/havalue of 51.84/ha;
GM HT soybeans: average volume of herbicide used 3.57 kg/ha and a field EIQ/ha valueof 44.43/ha.

Using these values, the level of herbicide ai use and the total EIQ load in 2020 were respectively
8.1% higher in terms of active ingredient use (+0.84 million kg), but lower by 14% in terms of
associated environmental impact as measured by the EIQ indicator. Cumulatively, since 1999,
herbicide ai use has been 6.8% higher (8.5 million kg 67) whilst the associated environmental

66

Based on comparing the current GM HT no till usage with what would reasonably be expected if the same

area and tillage system was planted to a conventional (non-GM) crop and a similar level of weed control wasachieved
67

Up to 2006, estimated ai use was slightly higher for conventional relative to GM HT soybeans by 0.03 kg/ha©PG Economics Ltd 202299

GM crop impact: 1996-2020

impact, as measured by the EIQ indicator, was 9.3% lower (ie, despite an increase in active
ingredient use, there was a net improvement in environmental impact associated with herbicideuse).
f) Uruguay
Analysis for Uruguay also draws on AMIS Global/Kleffmann data and estimates of the herbicide
regime on conventional alternatives that would deliver a level of weed control with equal efficacy
to GM HT soybeans. Based on this, the respective values for 2020 were:••Conventional soybeans: average volume of herbicide used 3.04 kg/ha and a field EIQ/havalue of 62.04/ha;
GM HT soybeans: average volume of herbicide used 3.01 kg/ha and a field EIQ/ha valueof 46.23/ha.

Using these values, the level of herbicide ai use and the total EIQ load in 2020 were respectively
0.7% higher in terms of active ingredient use (+29,000 kg), but lower by 24.7% in terms of
associated environmental impact as measured by the EIQ indicator. Cumulatively, since 1999,
herbicide ai use has been 1.1% higher (704,000 kg) whilst the associated environmental impact, asmeasured by the EIQ indicator, was 14.2% lower.
g) Bolivia
As no data on herbicide use in Bolivia has been identified, usage values and assumptions fordifferences in the adjacent country of Paraguay have been used. On this basis, the impact values
are as follows:••

In 2020, an 8% increase in the volume of herbicide ai used (365,000 kg) but a net 13.9%
reduction in the associated environmental impact, as measured by the EIQ indicator;
Cumulatively since 2005, there has been a net increase in herbicide ai use of 7% (+3million kg) but a net reduction in the field EIQ load of 9%.

h) Romania
Romania joined the EU at the beginning of 2007 and therefore was no longer officially permitted
to grow GM HT soybeans. The analysis below therefore refers to the period 1999-2006. Based on
herbicide usage data for the years 2000-2003 from Brookes (2005), the adoption of GM HT
soybeans in Romania has resulted in a small net increase in the volume of herbicide active
ingredient applied, but a net reduction in the EIQ load. More specifically:••

The average volume of herbicide ai applied has increased by 0.09 kg/ha to 1.35 kg/ha;
The average field EIQ/ha has decreased from 23/ha for conventional soybeans to 21/ha
for GM HT soybeans.

This data has been used as the base for analysis of the environmental impact associated withherbicide use up to 2003. For the period 2003 to 2006, this has been updated by herbicide usage
data from AMIS Global. Accordingly, in 2006, the average amount of herbicide active ingredientapplied to the GM HT soybean crop was 0.87 kg/ha (field EIQ/ha of 13.03) compared to 0.99 kg/ha
for conventional soybeans (field EIQ/ha of 19.09). Overall, during the 1999-2006 period, the total
volume of herbicide ai use was 2% higher (equal to about 15,600 kg) than the level of use if thecrop had been all non-GM since 1999 but the field EIQ load had fallen by 11%.

©PG Economics Ltd 2022100

GM crop impact: 1996-2020

With the banning of planting of GM HT soybeans in 2007, there has been a net negativeenvironmental impact associated with herbicide use on the subsequent Romanian soybean crop,
as farmers will have had to resort to conventional chemistry to control weeds. For example,
based on AMIS Global herbicide usage data for 2011, when the entire crop was conventional, theaverage amount of herbicide active ingredient applied per ha had increased by 80% and theaverage field EIQ/ha rating by 95% relative to 2006 usage levels on GM HT soybeans. Thissuggests a significant deterioration in the environmental impact associated with herbicide usage
on soybeans since the GM HT technology was banned from usage.
i) South Africa
GM HT soybeans have been grown in South Africa since 2000. Analysis of impact on herbicide
use and the associated environmental impact of these crops (based on AMIS Global/Kleffmann
data and typical herbicide programmes for GM HT soybeans and conventional soybeans: see
Appendix 3) shows the following:
Since 1999, the total volume of herbicide ai use has been 9.9% lower (equal to 1.4 million
kg of ai) than the level of use if the crop had been conventional;
The field EIQ load has fallen by 26.4% since 1999 (in 2020 the EIQ load was 31% lower).

••j) Mexico
Analysis of the impact on herbicide use and the associated environmental impact of the plantingof GM HT soybeans in Mexico (planted on a farm level trial basis 2004-2012 and then permitted
without restriction until 2016 68) on an annual area of between 2,000 ha and 20,000 ha) shows thefollowing:
Conventional soybeans: in 2016, the average volume of herbicide used was 1.76 kg/ha
and the associated field EIQ/ha value was 41.02/ha;
GM HT soybeans: the average volume of herbicide used was 1.62 kg/ha and theassociated field EIQ/ha value was 24.83/ha.

••

Between 2004 and 2016, the total volume of herbicide ai use has been 0.8% lower (equal to about
21,900 kg of ai) than the level of use if the crop had been conventional. The field EIQ load was
also lower by 3.7%.
k) Summary of impact
Across all of the countries that have adopted GM HT soybeans since 1996, the net impact on
herbicide use and the associated environmental impact 69 has been (Figure 46):•

In 2020 a 0.02% decrease in the total volume of herbicide ai applied (-0.01 million kg)
and a 9.3% reduction in the environmental impact (measured in terms of the field
EIQ/ha load);68

Not permitted for planting since 2017

69

Relative to the expected herbicide usage if all of the GM HT area had been planted to conventional varieties,

using the same tillage system (largely no/low till) and delivering an equal level of weed control to thatobtained under the GM HT system©PG Economics Ltd 2022

101

GM crop impact: 1996-2020•

Since 1996, 0.1% less herbicide ai has been used (3 million kg) and the environmental
impact associated with herbicide use on this global GM HT soybean crop area has fallen(an environmental improvement) by 12.5%.

This analysis takes into consideration changes in herbicide use over the last 15 years, on both GM
HT and conventional soybeans, that have occurred to specifically address the issue of weed
resistance to glyphosate (and other herbicides) in most regions. Compared to the early 2000s, theamount of herbicide active ingredient applied and number of herbicides used with GM HT
soybeans in many regions has increased, and the associated environmental profile, as measured
by the EIQ indicator, deteriorated. However, relative to the conventional alternative, theenvironmental profile of GM HT soybean crop use has continued to offer important advantages 70
and in most cases, provides an improved environmental profile compared to the conventional
alternative (as measured by the EIQ indicator).
Figure 46: Reduction in herbicide use and the environmental load from using GM HT
soybeans in all adopting countries 1996-2020
0.0%
-2.0%

-0.1%

Ai change

EIQ change-0.02%

-4.0%
-6.0%
-8.0%
-10.0%-9.3%-12.0%-14.0%

Cumulative2020-12.5%

4.1.2 GM herbicide tolerant (to glyphosate) and insect resistant soybeans(Intacta)
GM IR soybeans (stacked with second generation a GM HT trait) were planted commercially inSouth America for the first time in 2013-14 (Brazil, Argentina, Uruguay and Paraguay). Drawing
on pre-adoption insecticide usage data (source: AMIS Global/Kleffmann) and post adoption site
monitoring of conventional versus Intacta soybean plots (source: Monsanto), the following key
points relating to insecticide use change have been identified:

70

Also, many of the herbicides used in conventional production systems had significant resistance issues

themselves in the mid-1990s. This was, for example, one of the reasons why glyphosate tolerant soybeans
were rapidly adopted, as glyphosate provided good control of these weeds©PG Economics Ltd 2022102

GM crop impact: 1996-2020••

Intacta soybeans have enabled soybean growers to reduce the average number of
insecticide treatments by about 4 (from an average of 8-10 sprays on conventional or GM
HT only crops) in Brazil. In the other three adopting countries, average insecticide
treatments have fallen by an average of 1.5;
The average insecticide use saving from using Intacta soybeans has been about 0.17 kg ofactive ingredient and an associated field EIQ/ha saving of 17.25/ha in Brazil. In the othercountries, the average insecticide use saving has been about 0.08 kg of active ingredientand an associated field EIQ/ha saving of 3.1/ha;

Based on these savings, in 2020, the use of this technology resulted in a reduction of 4.5 million
kg of insecticide active ingredient use, equal to 14.6% of total insecticide used on the soybean
crops in the four countries. The EIQ saving in 2020 was equal to -27.7%. Over the eight years, thetotal insecticide active ingredient usage saving has been 23.9 million kg (-9.8%) and the associatedenvironmental impact, as measured by the EIQ indicator fell by 17.8%.

4.1.3 GM Herbicide tolerant (GM HT) maizea) The US
The use of herbicides on the US maize crop has followed similar trends to the use of herbicides onsoybeans. The average amount of herbicide active ingredient used on the US maize crop was
fairly stable (2.0-2.3 kg/ha) in the period to the mid-2000s before increasing over the next decade
to an average of over 3 kg/ha (Figure 47). The average field EIQ/ha load has also followed asimilar pattern of change as the amount of active ingredient used, although the rate of increase inrecent years has been less significant than the rate of increase in active ingredient use (Figure 48);
Figure 47: Average herbicide usage on maize in the US 1996-2020 (kg/ha)
3.5
3

3.2

3.01
2.64

2.5

2.3

2.47

2.45

2.36

2.19
2.3
2.29
2.15
2.06

2.92

2.1

2
1.5
1
0.5

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0

Sources and notes: derived from NASS pesticide usage data. No data collected in 2004, 2006-2009, 20112013, 2015, 2017 and 2019

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

Figure 48: Average herbicide usage on maize in the US 1996-2020 (EIQ/ha)
70
60

58.4

54.4

48.8
51.3
46.2
48.2
47.5
45.6
43.4

50

51.1

49.2

62.4
56.92

47

40
30
20
10

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0

Sources and notes: derived from NASS pesticide usage data. No data collected in 2004, 2006-2009, 20112013, 2015, 2017 and 2019

In relation to the use of herbicides on the GM HT and conventional crops, the average amount of
herbicide used on the GM HT maize crop was about 0.6 to 0.7 kg/ha lower than the averageamount used on conventional crop in the period to about 2007. Since then, the differential
between the GM HT crop (which has accounted for more than 85% of the total crop each year
since 2013) and small residual conventional crop has narrowed, so that by 2010, average levels ofactive ingredient use were broadly similar and since 2011, the average amount of herbicide active
applied to the GM HT crop has been higher than the usage on the residual conventional crop
(11% of the total crop in 2020). The average field EIQ/ha value relating to the GM HT crop has
typically been about 20/ha units lower than the EIQ/ha load on the conventional crop, although
the difference between the average EIQ/ha value in the two production systems has narrowed,
with the GM HT average value being higher than the conventional value since 2013 (Figure 49).
The recent increase in ai use and the associated field EIQ/ha for GM HT maize mainly reflects theincreasing development of herbicide resistance and the adoption of more integrated weed
management practices designed to address the issue of weed resistance to glyphosate (see section
4.1.9 for more detailed discussion). There has been an increasing proportion of the GM HT crop
receiving additional treatments with herbicides such as acetochlor, atrazine, 2 4,D, mesotrione, S
metolachlor and tembotrione as recommended by extension advisors and weed scientists. In
addition, as with GM HT soybeans, US farmers have also been able to use an increasing array ofstacked-traited GM HT varieties in recent years (eg, combinations of tolerance to the active
ingredients glyphosate, glufosinate and 2 4 D).

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

Figure 49: A comparison of the average EIQ/ha for conventional and GM HT maize in the US
1996-2020
80
70
60
50
40
30
20
10

GM HT

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0

Conventional

Sources: derived from USDA NASS, Kynetec and University extension services

As with soybeans (see section 4.1.1 a), the comparison data between the GM HT crop and theconventional alternative presented above is of limited value because of bias in respect of theconventional crop usage data. The very small area of conventional crop from which herbicide
usage data is obtained means that the data poorly represents what might reasonably beconsidered as the ‘conventional alternative’ if GM HT technology was not available.
This bias has been addressed, by using the average estimated values for herbicide usage on
conventional crops for years only when the conventional crop accounted for more than 50% of
the total crop and, secondly, in other years (from 2007 for maize in the US) applying estimates ofthe likely usage if the whole US crop was no longer using crop biotechnology, based on opinion
from extension and industry advisors across the US 71. In addition, the usage levels identified
from this methodology were cross checked (and subject to adjustment) against historic average
usage levels of key herbicide active ingredients from sources such as USDA NASS and Kynetec,
so as to minimise the scope for understating or overstating likely usage levels on the conventional
alternative. Based on this approach, the respective values for conventional maize since 2007 areshown in Table 21.
Table 21: Average ai use and field EIQs for conventional maize 2007-2018 to deliver equal
efficacy to GM HT maize
Year
2007
2008
2009
71

Ai use (kg/ha)
3.48
3.48
3.78

Field EIQ/ha
60.22
56.21
56.28

Original analyses by Sankala and Blumenthal (2006) and Johnson and Strom (2008) were based on

consultations with extension advisors in over 50 US states. Subsequent years have been updated by the author©PG Economics Ltd 2022

105

GM crop impact: 1996-2020

2010
3.88
57.95
2011
3.43
54.62
2012
2.91
54.89
2013
3.37
60.84
2014
3.40
67.28
2015
3.41
67.36
2016
3.60
70.32
2017
3.47
68.84
2018
3.38
67.34
2019
3.78
76.86
2020
3.74
75.72
Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetec

Using this methodology for comparing conventional versus GM HT maize herbicide usage interms of the respective EIQ/ha values, Figure 50 shows that the average EIQ/load per ha for GM
HT maize has typically been lower than the conventional equivalent, although the gap between
the two has narrowed.
Figure 50: A comparison of the average EIQ/ha for weed control systems used in conventionalmaize that delivers equal efficacy to weed control systems in GM HT maize in the US 20072020
90
80
70
60
50
40
30
20
10
0

GM HT

Conventional

Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetec

Aggregating these farm level impacts to the national level:••

In 2020, the annual saving in the volume of herbicide active ingredient use was 6.4% (8million kg). The annual field EIQ load on the US maize crop was also lower by 13.9% in
2020;
The cumulative decrease in active ingredient use since 1997 has been -8.7% (220.3 millionkg), and the cumulative reduction in the field EIQ load was 7.4%.

©PG Economics Ltd 2022

106

GM crop impact: 1996-2020b) Canada
The impact on herbicide use in the Canadian maize crop has been similar to the impact reported
above in the US. Using industry sourced information 72 about typical herbicide regimes forconventional and GM HT maize and how these have changed (see Appendix 3 for the current
comparison), the key impact findings are:
In 2020, the herbicide ai/ha load on a GM HT crop has been between 2.81 kg/ha (GMglyphosate tolerant) and 1.97 kg/ha (GM glufosinate tolerant) lower than theconventional maize equivalent crop (average herbicide ai use at 2.97 kg/ha);
The field EIQ/ha values for GM glyphosate and GM glufosinate tolerant maize arerespectively 54.44/ha and 43.38/ha compared to 67.91/ha for conventional maize;
At the national level in 2020 (based on the plantings of the different production systems),
the reductions in herbicide ai use and the total field EIQ load were respectively 5.8%
(241,000 kg kg) and 19.8%;
Cumulatively since 1997, total national herbicide ai use has fallen by 8% (6.6 million kg)
and the total EIQ load has fallen by 15.9%.

•

•
•

•

c) South Africa
Drawing on herbicide usage data from AMIS Global/Kleffmann and industry level sources thatcompare typical weed control practices for conventional and GM HT maize in South Africa), theimpact of using GM HT technology in the South African maize crop has been:•••

On a per hectare basis in 2020 there has been a 0.11 kg increase in the amount of
herbicide active ingredient used but a decrease (environmental improvement) in the
average field EIQ of 6.99/ha (GM HT crop average of 2.33 kg ai/ha and field EIQ/ha valueof 39.46/ha, conventional 2.22 kg ai/ha and average EIQ/ha value 46.45/ha);In 2020, at the national level, the amount of herbicide used was 230,000 kgs (+3.8%)
higher than the amount that would probably have been used if the crop had all beenplanted to conventional seed. The total field EIQ load was, however 12% lower;
Cumulatively since 2003, total national herbicide ai use has fallen by 1.1% (1.4 millionkg) and the total EIQ load has fallen by 7.8%.

d) Argentina
Using a combination of AMIS Global/Kleffmann herbicide usage data and industry estimates oftypical herbicide regimes for the two different systems (see Appendix 3), the impact of GM HT
maize use in Argentina has been as follows (first used commercially in 2004):
•

•

72

The average volume of herbicide ai applied to GM HT maize was typically lower than
the amount used on the conventional crop, although more recently the amount used on
the GM HT crop has increased – in 2020 the average amount used on the GM HT crop
was higher, at about 3.99 kg ai/ha compared to about 3.53 kg ai/ha for conventionalmaize;
The average field EIQ/ha load for GM HT maize has been significantly lower than theconventional counterpart, although with the increase in ai use on the GM HT crop in

Including the Weed Control Guide (2004 and updated) from the Departments’ of Agriculture in Ontario,

Manitoba and Saskatchewan©PG Economics Ltd 2022

107

GM crop impact: 1996-2020••

recent years the difference between the two systems has narrowed. In 2020, therespective average EIQ/ha values were 71.8/ha for GM HT maize and 73.61/ha for
conventional maize;
The increase in the volume of herbicide used in 2020 was 2.91 million kg (+12.9%). Since
2004, there has been a net increase in usage of 5.5% (12.8 million kg);
In terms of the field EIQ load, the reduction in 2020 was 2.5% and over the period 20042020, the EIQ load factor fell by 4%.

e) Brazil
Brazil first used GM HT maize commercially in 2010, and in 2020, the area planted to seedcontaining this trait was 16.4 million ha. Drawing on a combination of sources (AMIS
Global/Kleffmann, industry and Galvao (2012-2015)); the estimated environmental impact
associated with changes in herbicide use on this crop is as follows:
•

•
•
•

The average amount of herbicide active use and associated field EIQ/ha rating for GM
HT maize in 2020 was 2.81 kg/ha and 48.86/ha respectively. This compared withconventional maize with herbicide active ingredient use of 2.81 kg/ha and a field EIQ
rating of 56.45/ha;
In 2020, the use of GM HT technology resulted no change in the use of herbicide active
ingredient but a reduction in the EIQ rating of 11.2%;
Cumulatively (2010-2020), the herbicide active ingredient usage saving has been 1.4% (8.1
million kg), with an EIQ load reduction of 9.3%.

f) Uruguay
GM HT maize was first used in Uruguay in 2011, and in 2020 was planted on 90% of the maizecrop (126,000 ha of GM HT maize – all as stacked seed with both GM HT and GM IR traits).
Industry contacts point to weed control practices and herbicides used in Uruguay to be very
similar to those used in Argentina. We have therefore applied the Argentine herbicide usage
assumptions for both conventional and GM HT maize crops in Uruguay. Based on theseassumptions, since 2011, the adoption of GM HT maize has resulted in a net increase in herbicide
ai use on the maize crop of 171,000 kg of active ingredient (+6.1%) but a 4% improvement in theaggregate field EIQ/ha load.
g) Philippines
GM HT maize was first used in the Philippines in 2006, and in 2020 was planted on 27% of thetotal maize crop (686,000 ha of GM HT maize). Based on Kleffmann and Kynetec data andunpublished survey work amongst farmers in 2017 by the authors, this points to:•••

The average amount of herbicide active use and associated field EIQ/ha rating for GM
HT maize in 2020 was 1.92 kg/ha and 32.93/ha respectively. This compared withconventional maize with herbicide active ingredient use of 1.9 kg/ha and a field EIQ
rating of 43.41/ha;
In 2020, the use of GM HT technology resulted a marginal 1% (10,000 kg) increase in
herbicide active ingredient use but a reduction in the EIQ rating of 24%;
Cumulatively (2006-2020), the herbicide active ingredient usage saving has been
marginally higher (+1% - 0.1 million kg), with an EIQ load reduction of 19%.

©PG Economics Ltd 2022108

GM crop impact: 1996-2020h) Vietnam
GM HT maize was first used in 2015, and in 2020 was planted on 9.7% of the total maize crop
(92,000 ha of GM HT maize – all as stacked seed with both GM HT and GM IR traits).
Based on Kleffmann and Kynetec data and analysis by the author in 2017 and 2020, this shows
that:
•

•

The average amount of herbicide active ingredient used and associated field EIQ/harating for GM HT maize in 2020 was 2.08 kg/ha and 37.99/ha respectively. This
compared with conventional maize with herbicide active ingredient use of 2.88 kg/ha anda field EIQ rating of 59.74/ha;
Cumulatively (2015-2020), the herbicide active ingredient usage saving has been 2.2%
(0.25 million kg), with an EIQ load reduction of 2.9%.

i) Colombia
GM HT maize was planted on 109,000 ha (58% of the commercial total crop) in 2020. Drawing on
analysis in Brookes (2020), which also draws on a study by Mendez et al (2011) and surveys ofmaize growers in 2015 and 2017 by Celeres:•••

The average amount of herbicide active use and associated field EIQ/ha rating for GM
HT maize in 2020 was 2.07 kg/ha and 40.98/ha respectively. This compared withconventional maize with herbicide active ingredient use of 2.51 kg/ha and a field EIQ
rating of 59.05/ha;
In 2020, the use of GM HT technology resulted a reduction in the use of herbicide active
ingredient of 48,800 kg (-26%) and a reduction in the EIQ rating of 26%;
Cumulatively (2015-2020), the herbicide active ingredient usage saving has been 15%(367,000 kg), with an EIQ load reduction of 26%.

j) Other countries
GM HT maize was also grown in Paraguay (472,000 ha in 2020). Analysis of the environmental
impact associated with changes in herbicide use on this crop has not been possible due to a lackof data.
k) Summary of impact
In the countries where GM HT maize has been most widely adopted, there has been a net
decrease in both the volume of herbicides applied to maize and a net reduction in theenvironmental impact applied to the crop (Figure 51). More specifically:••

In 2020, total herbicide ai use was 2.3% lower (5.1 million kg) than the level of use if thetotal crop had been planted to conventional varieties. The EIQ load was also lower by
11.7%;
Cumulatively since 1997, the volume of herbicide ai applied is 6.2% lower than its
conventional equivalent (a saving of 224 million kg). The EIQ load has been reduced by
7.8%.

As with the GM HT soybean analysis, this analysis takes into consideration changes in herbicideuse, in recent years, on GM HT maize that have specifically addressed the issue of weed
resistance to glyphosate in some regions. The trend in herbicide use is broadly similar to©PG Economics Ltd 2022

109GM crop impact: 1996-2020

soybeans, though less significant; the average amount of herbicide active ingredient use initiallyfell with the adoption of GM HT maize, but has, in the last few years, increased. At the sametime, usage levels on conventional maize crops have also tended to increase, partly due to weed
resistance (to herbicides other than glyphosate). Overall, however, the net environmental impact
associated with the herbicides used on GM HT crops continues to represent an improvement
relative to environmental impact associated with herbicide use on conventional forms of
production.
Figure 51: Reduction in herbicide use and the environmental load from using GM HT maize in
adopting countries 1997-2020
0.0%
-2.0%

Ai change

EIQ change

-2.3%

-4.0%
-6.0%
-8.0%

-6.2%
-7.8%

-10.0%-12.0%-11.7%-14.0%
Cumulative2020

4.1.4 GM HT Herbicide tolerant (GM HT) cottona) The US
The use of herbicides on the US cotton crop has followed similar trends to the use of herbicides
on soybeans and maize. The average amount of herbicide active ingredient used on the US
cotton crop was reasonably stable (1.9-2.4 kg/ha) in the period to the mid-2000s before increasingover the next decade to an average of over 3 kg/ha (Figure 52). The average field EIQ/ha load has
also followed a similar pattern of change as the amount of active ingredient used, although therate of increase in recent years has been less significant than the rate of increase in active
ingredient use (Figure 53).

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110

GM crop impact: 1996-2020

Figure 52: Average herbicide usage on cotton in the US 1997-2019 (kg/ha)
4.5

4.12

4
3.5

3.07

3
2.43

2.5

2.18
2.14

2.7

2.18

2.8

2.5

2.27

1.89

2
1.5
1
0.5

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0

Sources and notes: USDA NASS pesticide usage data (no data collected in 2002, 2004, 2006, 2008, 2009, 20112014, 2016, 2018, 2020), Although data was also collected in 2005, these results are not included because they
are inconsistent with all other data

Figure 53: Average herbicide usage on cotton in the US 1997-2019 (EIQ/ha)
90
76.65

80
70

65.22

60
50

47.4

36.2

42.5

35.2

35.6

40

55.2

53.11

33.9

27.5

30
20
10

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0
Sources and notes: USDA NASS pesticide usage data (no data collected in 2002, 2004, 2006, 2008, 2009, 20112014, 2016, 2018, 2020), Although data was also collected in 2005, these results are not included because they
are inconsistent with the data for other years

Comparing the use of herbicides on the GM HT and conventional crops, the average amount of
herbicide used on the GM HT crop has been consistently higher than the average amount used on
the conventional crop. In terms of the average field EIQ/ha, there has been a marginally lower
average field EIQ rating for GM HT cotton in the first few years of adoption, but since then, theaverage field EIQ/ha rating has been higher than conventional cotton by an increasing amount(Figure 54).

©PG Economics Ltd 2022

111

GM crop impact: 1996-2020

As in the case of GM HT soybeans and maize, the increase in ai use and the associated field
EIQ/ha for GM HT cotton since the mid-2000s largely reflects the increasing development of
herbicide resistance and the adoption of more integrated weed management practices designed
to address the issue of weed resistance to glyphosate (see section 4.1.9 for more detailed
discussion). The average amount of herbicide active ingredient used on GM HT cotton in the US
has increased through a combination of additional usage of glyphosate (about a 30% increase inusage per hectare) in conjunction with increasing use of other herbicides. All of the GM HT croparea planted to seed tolerant to glyphosate received treatments of glyphosate and at least one of
the next five most used herbicides (trifluralin, acetochlor, diuron, flumioxazin and paraquat).
This compares with 2006, when only three-quarters of the glyphosate tolerant crop received atleast one treatment from the next five most used herbicides (2 4-D, trifluralin, pyrithiobic,
pendimethalin and diuron). This shows that US cotton farmers now make increasing use ofadditional herbicides with different modes of action for managing weed resistance (toglyphosate). Many are also making increasing use of GM HT crops tolerant to other herbicides
such as to glufosinate (crops with stacked traits conveying tolerance to both glyphosate andglufosinate. For example, about a third of the GM HT cotton area in the US was probably using
glufosinate for ‘over the top’ weed control by 2016 compared to 10% of the crop five years earlier.
Figure 54: A comparison of the average EIQ/ha for conventional and GM HT cotton in the US
1997-2020
100.00
90.00
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
-

GM HT

Conventional

Sources: derived from USDA NASS, Kynetec and University extension services

As with soybeans and maize discussed above, the comparison data between the GM HT crop andthe conventional alternative presented above is of limited value because of bias in respect of theconventional crop usage data. The very small area of conventional crop from which herbicide
usage data is obtained means that the data poorly represents what might reasonably beconsidered as the ‘conventional alternative’ if GM HT technology was not available. This isparticularly relevant in the case of the US cotton crop because much of the residual conventional
crop area involves extensive, low intensity production methods (including organic) whichfeature, limited (below average) use of herbicides. The usage patterns of this sub-set of growers©PG Economics Ltd 2022

112

GM crop impact: 1996-2020

is therefore likely to understate usage for the majority of farmers if they all returned to farming
without the use of GM technology
This bias has been addressed, by applying estimates of the likely usage if the whole US crop was
no longer using crop biotechnology, based on opinion from extension and industry advisors
across the US 73. In addition, the usage levels identified from this methodology were crosschecked (and subject to adjustment) against historic average usage levels of key herbicide active
ingredients from sources such as USDA NASS and Kynetec, so as to minimise the scope forunderstating or overstating likely usage levels on the conventional alternative. Based on thisapproach, the respective values for conventional cotton since 2006 are shown in Table 22.
Table 22: Average ai use and field EIQs for conventional cotton 2006-2020 to deliver equal
efficacy to GM HT cottonYear
ai use (kg/ha)
Field EIQ/ha
2006
3.75
65.57
2007
3.88
63.75
2008
4.26
76.10
2009
3.84
69.61
2010
4.07
72.32
2011
4.48
77.35
2012
4.54
78.31
2013
4.96
79.25
2014
4.71
76.07
2015
4.82
83.03
2016
4.57
85.42
2017
4.41
78.83
2018
3.89
76.34
2019
4.49
87.30
2020
4.50
90.28
Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetec

Using this methodology for comparing conventional versus GM HT maize herbicide usage interms of the respective EIQ/ha values, Figure 55 shows that the average EIQ/load per ha for GM
HT maize has typically been lower than the conventional equivalent, although the gap between
the two has narrowed.
Applying this basis for comparing herbicide regimes for conventional and GM HT cotton at thenational level, the impact of using the GM HT technology in 2020 resulted in a 2.4% increase in
the amount of herbicide use (0.38 million kg) but a 3.8% decrease in the associated environmental
impact, as measured by the EIQ indicator. Cumulatively since 1997, there have been savings in
herbicide use of 6.5% for ai use (25.7 million kg) and a 5.9% reduction in the associatedenvironmental impact, as measured by the EIQ indicator.

73

Original analyses by Sankala and Blumenthal (2006) and Johnson and Strom (2008) were based on

consultations with extension advisors in over 50 US states. Subsequent years have been updated by the author©PG Economics Ltd 2022

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GM crop impact: 1996-2020

Figure 55: A comparison of the average EIQ/ha for weed control systems used in conventional
cotton that delivers equal efficacy to weed control systems in GM HT maize in the US 20072020
100
90
80
70
60
50
40
30
20
10
0

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
GM HT

Conventional

Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2020,
based on University Extension Services, Industry, USDA NASS and Kynetecb) Australia
Drawing initially on information from the University of New England study from 2003 74, andthen subsequent analysis of typical herbicide treatment programmes for GM HT andconventional cotton (based on industry (eg, Monsanto, 2016) and extension assessments of
conventional versus the newer ‘Roundup Ready Flex’ cotton that is widely used in Australia (seeAppendix 3) shows the following:••

The herbicide ai/ha load on the original first-generation GM HT crop was about 0.11
kg/ha higher (at 2.87 kg/ha) than the conventional cotton equivalent crop (2.77 kg/ha).
With the introduction of the Roundup Ready Flex cotton in 2006, the average amount of
herbicide active ingredient applied to the GM HT crop has, however fallen to an averagelevel lower than the conventional equivalent. In 2020, the average herbicide ai use/ha on
the GM HT crop was about 5.26 kg/ha compared to 7.47 kg/ha on the conventional
equivalent crop 75;
The average field EIQ/ha value for the original GM HT cotton was 65/ha, compared to69/ha for conventional cotton. Under the Roundup Ready Flex versus conventional
equivalent, the environmental load difference in favour of the GM HT cotton increased.
In 2020, the average field EIQ/ha for GM HT cotton was 90/ha compared to 143/ha for theconventional cotton equivalent;

74

Doyle et al (2003)

75

Based on advisor recommendation to deliver equal efficacy of weed control to ‘Flex cotton’ and inclusive of

weed control in the pre-plant phase©PG Economics Ltd 2022

114

GM crop impact: 1996-2020••

Based on the above data, at the national level, in 2020, herbicide ai use has been 29.5%
lower (-617,000 kg of ai) than the level expected if the whole crop had been planted toconventional cotton cultivars. The total field EIQ load was 37% lower;
Cumulatively since 2000, total national herbicide ai use has fallen by 20.5% (6.5 millionkg) and the total EIQ load decreased by 26.7%.

c) South Africa
Using industry level sources that compare typical weed control programmes for conventional
and GM HT cotton in South Africa (see appendix 3), the impact of using GM HT technology in
the South African cotton crop has been:•••

In 2020, there has been an average 0.1 kg decrease in the amount of herbicide active
ingredient used and a 13% decrease in the environmental impact, as measured by the
EIQ indicator (-4.3 field EIQ/ha units);
At the national level, the amount of herbicide used in 2020 was 162 kg (0.6%) lower than
the amount that would probably have been used if the crop had all been planted toconventional seed. The total field EIQ load was, however, a more significant 13.4%
lower;
Cumulatively since 2001, total national herbicide ai use increased by 0.5% (3,800 kg), but
the total EIQ load fell by 9.4%. This shows that although the amount of herbicide usedon the cotton crop has increased since the availability and use of GM HT cotton, theassociated environmental impact of herbicide use on the cotton crop has fallen.

d) Argentina
GM HT cotton has been grown commercially in Argentina since 2002, and in 2020, all of thecotton crop (450,000 ha) used seed containing this trait.
Based on industry and extension sources relating to typical weed control programmes for GM HT
and conventional cotton (GM HT 4.06 kg ai/ha and EIQ/ha of 63.96/ha, conventional 4.72 kg ai/haand EIQ/ha 78.40/ha), the impact of using this technology on herbicide use and the associatedenvironmental impact has been:••

In 2020, the national level reduction in the amount of herbicide applied to the cotton crop
was 296,000 kg (-16%) lower than would otherwise have occurred if the whole crop had
been planted to conventional varieties. The associated EIQ load was 18% lower;
Cumulatively, since 2002, the amount of herbicide active ingredient applied had fallen
26% (-6.2 million kg). The field EIQ rating associated with herbicide use on theArgentine cotton crop fell 27% over the same period.

e) Colombia
GM HT cotton was first grown commercially in Colombia in 2002, and in 2020, 56% of the cotton
crop (4,825 ha of GM HT cotton) used seed containing this trait.
Drawing on analysis in Brookes (2020), which also draws on surveys of cotton growers in 2015
and 2017 by Celeres:•

The average amount of herbicide active use and associated field EIQ/ha rating for GM
HT cotton in 2020 were 1.79 kg/ha and 28.03/ha respectively. This compared with©PG Economics Ltd 2022

115

GM crop impact: 1996-2020••

conventional cotton with herbicide active ingredient use of 2.305 kg/ha and a field EIQ
rating of 38.21/ha;
In 2020, the use of GM HT technology resulted a reduction in the use of herbicide active
ingredient of 2,470 kg (-12%) and a reduction in the EIQ rating of 15%;
Cumulatively (2006-2020), the herbicide active ingredient usage saving has been 7.7%
(47,700 kg), with an EIQ load reduction of 6.6%.

f) Other countries
Cotton farmers in Mexico, Brazil and Paraguay have also been using GM HT technology since2005, 2009 and 2013 respectively. No analysis is presented for the impact of using this technology
in these countries because of the limited availability of herbicide usage data.
g) Summary of impact
In 2020, the overall effect of using GM HT cotton technology (Figure 56) in the adopting countries
has been a reduction in herbicide ai use 76 of 2.8% and a decrease in the total environmental
impact of 8.6%. Cumulatively since 1997, herbicide ai use fell by 8.5% (-38.4 million kg) and theassociated environmental impact fell by 8.8%.
As with the analysis of herbicide use changes on GM HT soybeans and maize, this analysis takes
into consideration changes in herbicide use, in recent years, on GM HT cotton that have occurredto specifically address the issue of weed resistance to glyphosate in some regions (notably theUS). Such actions have resulted in a significant number of (US) cotton farmers using additional
herbicides to glyphosate with GM HT cotton (that were not used in the early years of GM HT (toglyphosate) crop adoption) and can be seen in the increase in the average amounts of herbicide
active ingredient applied per ha. Nevertheless, the net environmental impact associated with the
herbicides used on GM HT crops in 2020 continues to represent an improvement relative to theenvironmental profile of herbicides that would likely be used if the crop reverted to using
conventional (non-GM) technology.

76

Relative to the herbicide use expected if all of the GM HT area had been planted to conventional cultivars,

using the same tillage system and providing the same level of weed control as delivered by the GM HT system©PG Economics Ltd 2022

116

GM crop impact: 1996-2020

Figure 56: Reduction in herbicide use and the environmental load from using GM HT cottonin the US, Australia, Argentina, Colombia and South Africa 1997-2020
0.0%
-1.0%

Ai change

EIQ change

-2.0%
-3.0%

-2.8%

-4.0%
-5.0%
-6.0%
-7.0%
-8.0%
-9.0%

-8.5%

-8.8%

-8.6%

-10.0%
Cumulative2020

4.1.5 GM Herbicide tolerant (GM HT) canolaa) The US
Based on analysis of typical herbicide treatments for conventional, GM glyphosate tolerant andGM glufosinate tolerant canola (sources: Sankala and Blumenthal (2003 & 2006), Johnson andStrom (2008), university and private extension advisory services, industry analysts and Kynetec),
the changes in herbicide use and resulting environmental impact arising from adoption of GM
HT canola in the US since 1999 77 are summarised in Figure 57 and Figure 58. These show
consistent savings in terms of both the amount of herbicide active ingredient applied and the EIQ
value for glyphosate and glufosinate tolerant canola relative to conventional canola.

77

The USDA pesticide usage survey does not include coverage of canola©PG Economics Ltd 2022

117

GM crop impact: 1996-2020

Figure 57: Average active ingredient differences conventional versus GM HT canola US 19992020
0.90
0.80

0.74

0.80 0.80

0.74 0.74

0.73 0.73
0.65

0.70

0.66

0.61

0.60

0.51

0.59

0.62

0.52

0.50
0.35

0.40

0.25

0.30

0.29

0.32

0.20

0.25
0.21

0.25

0.29

0.10
-

Sources: derived from Sankala & Blumenthal (2003 & 2006), Johnson & Strom (2008), university and private
sector extension advisors, industry analysts and Kynetec
Note: Values shown are weighted average (by area planted) of glyphosate tolerant and glufosinate tolerant
GM HT canola compared to conventional canola

Figure 58: Average EIQ/ha differences conventional versus GM HT canola US 1999-2020
25.00

20.79

20.00

17.83

15.75
14.86 14.86
15.00

17.87

20.62
18.92

18.94
16.91
12.09
13.08
10.41
11.48

12.16
11.79
9.31
11.17 10.67
10.09
10.00
9.41

10.00

5.00

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

-

Sources: derived from Sankala & Blumenthal (2003 & 2006), Johnson & Strom (2008), university and private
sector extension advisors, industry analysts and Kynetec
Note: Values shown are weighted average (by area planted) of glyphosate tolerant and glufosinate tolerantvarieties

The reduction in the volume of herbicides used was equal to 429,000 kg of active ingredient (55.9%) in 2020. In terms of the EIQ load, this had fallen by 45.4% compared to the load that©PG Economics Ltd 2022

118

GM crop impact: 1996-2020

would otherwise have been applied if the entire crop had been planted to conventional varieties.
Cumulatively, since 1999, the amount of active ingredient use has fallen by 38% (-5.1 million kgai), and the EIQ load reduced by 46.6%.
b) Canada
Reductions in herbicide use and the environmental ‘foot print’ associated with the adoption of
GM HT canola, have also been found in Canada:
•

•

•

•

The analysis applied to the early years of adoption is based on the average volume ofherbicide ai applied to GM HT canola being 0.65 kg/ha (GM glyphosate tolerant) and
0.39 kg/ha (GM glufosinate tolerant), compared to 1.13 kg/ha for conventional canola.
This analysis has been applied to the years to 2004. From 2005, the conventional‘alternative’ used includes the comparison of ‘Clearfield’ canola, which makes up the
majority of the small are planted to non-GM varieties 78. As in the US, in 2020, in termsof active ingredient use, GM HT canola tolerant to glyphosate uses marginally more
(0.01 kg/ha) and GM HT canola tolerant to glufosinate uses 0.35 kg/ha less than theconventional alternative;
The average field EIQ/ha load for GM HT canola has been consistently lower than theconventional counterpart (in 2020, 14/ha for GM glyphosate tolerant canola, 11.2/ha for
GM glufosinate tolerant canola and 14.52/ha for conventional canola);On the basis of these comparisons with conventional canola, the reduction in thevolume of herbicide used was 1.6 million kg (a reduction of 21.7%) in 2020. Since 1996,
the cumulative reduction in usage has been 20% (26.9 million kg);
In terms of the field EIQ load, the reduction in 2020 was 37% and over the period 19962020, the EIQ load factor fell by 30%.

c) Australia
Australia first allowed commercial planting of GM HT canola in 2008. Based on analysis ofFischer & Tozer (2009) which examined the use of GM HT (to glyphosate) canola relative totriazine tolerant (non-GM) and ‘Clearfield’ canola, the average savings from adoption of the GM
HT system were 0.4 kg/ha of active ingredient use and a reduction in the average field EIQ/ha of
2.74/ha (when weighted by type of conventional canola the GM HT replaced (ie, triazine tolerantor ‘Clearfield’)). These comparisons have been updated in recent years (sources: MonsantoAustralia (2016), Hudson and Richards (2014a and 2014b) to reflect changes in weed management
practices (notably for weed resistance management). In 2020, the average 79 savings relative toconventional (HT) canola were 0.5 kg/ha for herbicide active ingredient usage and 22.31/ha for
the field EIQ/ha value. At the national level, this resulted in a net saving of 0.29 million kg ofactive ingredient (a 9% saving across the total canola crop) and an 12.3% reduction in theassociated environmental impact of herbicide use (as measured by the EIQ indicator) on the 2020
Australian canola crop. Since 2008, the total herbicide active ingredient saving arising from use
of GM HT canola has been about 2.12 million kg of active ingredient (-5.5%), with the EIQ load
falling by 7.6%.

78

Herbicide tolerant by a non-GM process, tolerant to the imidazolinone group of herbicides

79

Weighted by sales of seed between TT, ‘Clearfield’ and GM HT©PG Economics Ltd 2022

119GM crop impact: 1996-2020d) Summary of impact
In the countries where GM HT canola has been adopted, there has been a net decrease in both thevolume of herbicides applied to canola and the environmental impact applied to the crop (Figure59). More specifically:••

In 2020, total herbicide ai use was 20% lower (2.3 million kg) than the level of use if thetotal crop had been planted to conventional varieties. The EIQ load was also lower by
25.4%;
Cumulatively since 1996, the volume of herbicide ai applied was 18.1% lower than its
conventional equivalent (a saving of 34.1 million kg). The EIQ load had been reduced by
25.9%.

Figure 59: Reduction in herbicide use and the environmental load from using GM HT canolain the US, Canada and Australia 1996-2020
0.0%

Ai change

EIQ change-5.0%-10.0%-15.0%-20.0%-18.1%-20.3%-25.0%-25.9%-25.4%-30.0%
Cumulative2020

4.1.6 GM HT sugar beet
The USGM HT sugar beet was first planted on a small area in the US in 2007, and in 2020 accounted forall of the crop (462,280 ha). In terms of weed control, the use of this technology has resulted in aswitch in use from a number of selective herbicides plus some hand/mechanical weeding to aglyphosate-based herbicide weed control programme. Drawing on evidence from a combinationof sources (Khan 2008, Stachler et al, 2012, university extension services, industry analysts andthe Kynetec dataset on pesticide use), the analysis below summarises the environmental impact.
The switch to GM HT sugar beet has resulted in limited environmental impact associated withherbicide use changes. Sugar beet has traditionally been a crop in which several treatments of
selective herbicides were used, often supplemented by manual weeding (due to the susceptibilityof crop to damage from herbicides, especially at early stages of growth). The switch to using
glyphosate tolerant crop technology resulted in the application of several herbicides (typicallywith low application rates in terms of amount of active ingredient applied) and manual weeding©PG Economics Ltd 2022120

GM crop impact: 1996-2020

being replaced, initially by 2-3 applications of glyphosate. The net impact of this was broadly
neutral or a limited reduction in the volume of herbicide use (in terms of active ingredientapplied), coupled with a small net reduction (improvement) in the associated environmental
impact, as measured by the EIQ indicator. For several subsequent years, the average amount of
herbicide applied to the GM HT crop has increased as farmers increasingly adopted more
integrated weed management practices to address the development of weeds resistant toherbicides (both weeds resistant to glyphosate and other herbicides). Relative to the baseline
profile of herbicide usage on conventional sugar beet in 2007, the impact of these changes has
been a net increase in the average amount of herbicide applied to GM HT sugar beet crops and amarginal worsening of the environmental impact, as measured by the EIQ indicator. However,revising/updating the conventional baseline weed control practices that would likely be requiredin 2020 to deliver the same level of weed control in a conventional crop as obtained in a GM HT
crop, the comparison of herbicide regimes suggests that the GM HT crop would use marginallymore herbicide, in terms of amount of active ingredient applied and would have a slightly higher
EIQ/ha value than the conventional equivalent (GM HT 3.57 kg ai/ha and a field EIQ/ha value of
62.65, compared to conventional 3.42 kg ai/ha, with a field EIQ/ha value of 62.52). Taking thesechanges into consideration, in 2020, the use of GM HT sugar beet resulted in an increase in theamount of herbicide active ingredient used of 4% (69,000 kg) and a net increase in the associatedEIQ value of 0.2%. Cumulatively, since 2007, and taking into consideration the changes inherbicide usage and weed control practices that have occurred during this period relative to theconventional alternative 80, there has been a net decrease in the amount of herbicide active
ingredient used of 0.76 million kg (-4%) and a net reduction in the environmental load associatedwith herbicide use, as measured by the EIQ indicator of 15.5%.
GM HT sugar beet is also planted on a small area (17,400 ha in 2020) in Canada. Due to the lackof publicly available data on sugar beet herbicide use in Canada, no environmental impact
analysis is presented. The impact is likely to be similar to the impact in the US.

4.1.7 GM IR maizea) The US
Since 1996, when GM IR maize was first used commercially in the US, the average volume of
insecticide use across the whole crop has fallen (Figure 60).

80

Which in effect is a largely hypothetical alternative given that almost all of the crop uses GM HT technology©PG Economics Ltd 2022

121GM crop impact: 1996-2020

Figure 60: Average insecticide use on maize 1996-2020 (kg active ingredient/ha)
0.70

0.61 0.60

0.60
0.51

0.50

0.52
0.47

0.46

0.40
0.30

0.30

0.23

0.21

0.17

0.20

0.15

0.19

0.18

0.14

2020

2017

2019

2018

2016

2015

2009

-

2014

2008

-

2013

-

2012

-

2011

-

2010

-

2007

2005

2004

2002

2001

2000

1999

1998

1997

1996

2003

-

-

2006

0.10

Source: USDA NASS (no surveys of insecticide use in 2003, 2006-2009, 2011-2013, 2016-2017, 2019)
Note This relates to the average usage per ha of crop that used insecticides (eg, in 1996, this was estimated to
be on about a third of the crop, and in 2020 was about 17% of the crop

During this 25-year period the average amount of insecticide used has fallen on both theconventional and GM IR crop, although the level of insecticide ai use on the GM IR crop has been
consistently lower than the average usage level on the conventional crop.
However, examining the impact of GM IR traits on insecticide use is more complex because:••

There are a number of pests for the maize crop. These vary in incidence and damage by
region and year and typically affect only a proportion of the total crop. In the case of GM
IR maize, this comprises two main traits that target stalk boring pests and the cornrootworm (second generation events have also included protection against cutworms
and earworms). In the US, historically, a maximum of about 10% of the crop was treatedwith insecticides for the control of stalk boring pests each year and about 30% of the US
maize area treated with insecticides for corn rootworm control. This means thatassessing the impact of the GM IR technology requires disaggregation of insecticide
usage specifically targeted at these pests and limiting the maximum impact area to theareas that would otherwise require insecticide treatment, rather than necessarily
applying insecticide savings to the entire area planted to seed containing GM IR traits
targeting these pests. This is particularly relevant if conclusions are to be drawn fromexamination of insecticide usage changes overall and of the proportion of the US maizecrop typically receiving treatments of insecticides. Of note here has been the significant
increase in the proportion of the US maize crop that has technically been in receipt ofinsecticides in terms of ‘area treated’ (equally applicable to GM IR and conventional
crops) over the last 15 years. This reflects the growing preference by farmers for sowing
maize seed that has been treated with the insecticides clothiandin and thiamethoxam andis unrelated to the adoption of GM IR technology;
The first users of the GM IR technology have tended to be farmers who regularly
experience economic levels of damage from the GM IR target pests. This means that once
the level of adoption (in terms of areas planted to the GM IR traits) is in excess of the©PG Economics Ltd 2022

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GM crop impact: 1996-2020•

areas normally treated with insecticide sprays for these pests, it is likely that additional
areas planted to the traits are largely for insurance purposes and no additional insecticide
savings would arise (if assumed across all of the GM IR area). Secondly, as adoption
levels have increased, using the recorded level of insecticide use on the small
conventional crop as a base for making comparisons with insecticide use on the GM IR
area is likely to understate the insecticide savings associated with the adoption of the GM
IR technology, because the limited number of conventional farmers are increasingly
likely to be in locations where pest pressure levels (for the pests that the GM IR
technology targets) are lower than the levels of pest pressure in the majority of thecountry and hence are likely to use relatively low levels of insecticides;
The widespread adoption of GM IR maize technology has also resulted in ‘area-wide’
suppression of target pests such as stalk borers in maize crops. As a result, conventional
farmers have benefited from this lower level of pest infestation and the associatedreduced need to conduct insecticide applications (see for example, Hutchison et al(2010)).

In order to address these issues, our approach has been to first identify the insecticides typicallyused to treat the stalk boring and rootworm pests and their usage rates from sources such as
extension services, USDA NASS data, private pesticide usage databases (eg, Kynetec) andrelevant literature (eg, Carpenter & Gianessi (1999)). Drawing on these sources we identified
average usage of insecticides for the control of stalk boring pests and rootworm at about 0.6 kg/ha. The corresponding field EIQ/ha value was about 30/ha.
In the early years of adoption, these active ingredient and field EIQ saving were then applied tothe maximum of the area historically receiving insecticide spray treatments for stalk boring pests
and corn rootworm (about a third of the US maize crop) or the GM IR area targeting these pests,
whichever was the smaller of the two areas. The maximum area to which these changes havebeen applied in years since the early 2000s has been based on the difference between thismaximum treated area (33% of total crop) and the estimated total base crop area recorded ashaving received insecticide treatments (sources USDA NASS and Kynetec)
Based on this approach, at the national level, the use of GM IR maize has resulted in a saving in
the area treated with insecticides of about 5.5 million ha in 2020 and a saving in the volume of
insecticide ai use of 3.3 million kg ai (a 50% saving). The annual field EIQ load also fell by 50% in
2020. Since 1996, the cumulative decrease in insecticide ai use targeted at these pests has been
37% (60.8 million kg), and the cumulative reduction in the field EIQ load has been 38%.
b) Canada
As in the US, the main impact has been associated with reduced use of insecticides. Based on
analysis of a typical insecticide treatment regime targeted at corn boring pests prior to theintroduction of GM IR technology that is now no longer required 81, this has resulted in a farmlevel saving of 0.43 kg/ha of ai use and a reduction of the field EIQ/ha of 20.7/ha. Applying thissaving to the area devoted to GM IR maize in 1997 and then to a maximum of 5% of the total

81

And limiting the national impact to 5% of the total maize crop in Canada – the estimated maximum areathat probably received insecticide treatments targeted at corn boring pests before the introduction of GM IR
maize©PG Economics Ltd 2022

123GM crop impact: 1996-2020

Canadian maize area in any subsequent year, the cumulative reduction in insecticide ai use
targeted at stalk boring pests has been 914,500 kg (-89%). In terms of environmental load, thetotal EIQ/ha load has fallen by 62% 82.
c) SpainAnalysis for Spain draws on insecticide usage data from the early years of GM IR trait adoption,
when the areas planted with this trait were fairly low (1999-2001 – from Brookes (2003)), andrestricts the estimation of insecticide savings to a maximum of 10% of the total maize crop area
which may have otherwise received insecticide treatments for corn boring pests. This analysis
has been subsequently checked and updated (based on extension advice and industry analyst
information) to reflect changing pest control practices and products available for control, with thelatest estimated impacts drawn from Brookes (2019). Overall, the adoption of GM IR maize
technology, has led to a significant net decrease in both the volume of insecticide used and theassociated field EIQ/ha load 83. More specifically:••

The volume of total maize insecticide ai use was 37.5% lower than the level would
probably have been if the entire crop had been conventional in 2020 (-33,250 kg). Since
1998 the cumulative saving (relative to the level of use if all of the crop had been
conventional) has been 745,750 kg of insecticide ai (a 37% decrease);
The field EIQ/ha load has fallen by 21% since 1999. In 2020, the field EIQ load was 20%
lower than its conventional equivalent.

d) Argentina
Although GM IR maize has been grown commercially in Argentina since 1998, the environmental
impact of the technology has been very small. This is because insecticides have not traditionallybeen used on maize in Argentina (the average expenditure on all insecticides has only been $1$2/ha), and very few farmers have used insecticides targeted at stalk boring pests. This absenceof conventional treatments reflects several reasons including poor efficacy of the insecticides, theneed to get spray timing right (at time of corn borer hatching, otherwise insecticides tend to beineffective once the pest has bored into the stalk), seasonal and annual variations in pest pressure
and lack of awareness as to the full level of yield damage inflicted by the pest. As indicated in
section 3, the main benefits from using the technology have been significantly higher levels of
average yield, reduced production risk and improved quality of grain.
e) South Africa
Due to the limited availability of insecticide usage data in South Africa, the estimates of the
impact of GM IR maize in South Africa presented below are based on the following assumptions(derived from extension advisors and industry analysts):•

82

Irrigated crops are assumed to use two applications of cypermethrin to control stalkboring pests. This equates to about 0.168 kg/ha of active ingredient and a field EIQ of
6.11/ha (applicable to area of 200,000 ha);This relates to the total insecticide usage that would otherwise have probably been used on the Canadianmaize crop to combat corn boring pests
83

The average volume of insecticide ai use saved has been 0.96 kg/ha with an average field EIQ of 26/ha©PG Economics Ltd 2022

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GM crop impact: 1996-2020••

A dry land crop area of about 1,768,000 ha is assumed to receive an average of one
application of cypermethrin. This amounts to 0.084 kg/ha of active ingredient and has afield EIQ of 3.06/ha;
The first 200,000 ha to adopt GM IR technology is assumed to be irrigated crops.

Based on these assumptions:••

In 2020, the adoption of GM IR maize resulted in a net reduction in the volume of
insecticides used of 165,300 kg (relative to the volume that would probably have beenused if 1.768 million ha had been treated with insecticides targeted at stalk boring pests).
The EIQ load (in respect of insecticide use targeted at these pests) was 100% lower than it
would otherwise have been in the absence of use of the GM IR technology);
Cumulatively since 2000, the reductions in the volume of ai use and the associatedenvironmental load from sprayed insecticides were both 75.7% (2.6 million kg ai).

f) Brazil
The GM IR maize area in Brazil, in 2020, was 18 million ha (first planted commercially in 2008).
Various stalk boring and other pests are commonplace in the Brazilian maize crop, with the Fall
Armyworm (Spodoptera) being a major pest, and approximately 50% of the total annual crop has
regularly been treated with insecticides targeting this pest (typically five spray treatments/crop).
The availability of GM IR maize that targets this pest has allowed users to decrease the number of
insecticide spray runs from about five to two and significantly reduce the use of insecticides suchas methomyl, lufenuron, triflumuron, spinosad and thiodicarb. As a result, the typical averagesaving in active ingredient use has been 0.356 kg/ha and the field EIQ/ha saving has been
21.5/ha 84. Applying these savings to the national level (constrained to a maximum of 48% of thetotal maize crop that has been the historic average annual area receiving insecticide treatments),
this resulted in 2 million kg of insecticide active ingredient saving in 2020. This represents a 60%
reduction in the amount of insecticide used and an 80% reduction in the associatedenvironmental impact associated with insecticide use, as measured by the EIQ indicator.
Cumulatively, the ai and field EIQ savings have been respectively 56% and 75% lower than theywould otherwise have been if this technology had not been used (a saving of 19.9 million kg ofai).
g) Colombia
GM IR maize was planted on 96,250 ha (51% of the commercial total crop) in 2020. Drawing on
analysis in Brookes (2020), which also draws on a study by Mendez et al (2011) and surveys ofmaize growers in 2015 and 2017 by Celeres:
•

•

84

The average amount of insecticide active use and associated field EIQ/ha rating for GM
IR maize in 2020 was 0.07 kg/ha and 1.9/ha respectively. This compared withconventional maize with herbicide active ingredient use of 0.287 kg/ha and a field EIQ
rating of 9.25/ha;
In 2020, the use of GM IR technology resulted a reduction in the use of insecticide active
ingredient of 11,860 kg (-74%) and a reduction in the EIQ rating of 79%;

Based on AMIS Global data for the 2006-2009 period©PG Economics Ltd 2022

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GM crop impact: 1996-2020

Cumulatively (2009-2020), the insecticide active ingredient usage saving has been 60%(277,000 kg), with an EIQ load reduction of 61%.

•h) Vietnam
GM IR maize was first used in 2015, and in 2020 was planted on 9.2% of the total maize crop
(92,000 ha of GM IR maize – all as stacked seed with both GM HT and GM IR traits).
Based on Kleffmann and Kynetec data and analysis by the author in 2017 and 2020, this showsthat:
The average amount of insecticide active ingredient and associated field EIQ/ha rating
saved from no longer using insecticides targeted at the Asian Corn Borer pest was equal
to 0.29 kg/ha, based on average insecticide use on the GM IR crop of 0.068 kg ai/ha and0.356 kg ai/ha for conventional maize. The EI saving was 11.22/ha based on 2.86/ha for
the GM IR maize crop and 14.06/ha for conventional maize (based on recorded
insecticide use 2012-2014: sources: Kleffmann and Kynetec and Brookes and Dinh 2020).
The maximum area on which these insecticides are annually applied is estimated to beabout 725,000 ha;
Based on these savings, over the six years of adoption of GM IR maize technology, theinsecticide active ingredient usage saving and EIQ load reduction have respectively been
5.9% (a saving of 90,970 kg of insecticide active ingredient usage) and 5.8%.

••i) Other countries
GM IR maize has also been grown on significant areas in the Philippines (since 2003: 683,300 ha
planted in 2020), in Uruguay (since 2004: 117,690 ha in 2020), in Honduras (since 2003: 38,000 hain 2020) and in Paraguay (since 2013, 518,400 ha in 2020). Due to limited availability on
insecticide use on maize crops 85, it has not been possible to analyse the impact of reduced
insecticide use and the associated environmental impact in these countries.
j) Summary of impact
Across all of the countries that have adopted GM IR maize since 1996, the net impact on
insecticide use and the associated environmental load (relative to what could have been expected
if all maize plantings had been to conventional varieties) have been (Figure 61):
•

•

85

In 2020, a 53.1% decrease in the total volume of insecticide ai applied (5.6 million kg)
and a 60.7% reduction in the environmental impact (measured in terms of the field
EIQ/ha load 86);
Since 1996, 41.2% less insecticide ai has been used (85.4 million kg) and theenvironmental impact from insecticides applied to the maize crop has fallen by 45.4%.

Coupled with the ‘non’ application of insecticide measures to control some pests by farmers in many

countries and/or use of alternatives such as biological and cultural control measures
86

Readers should note that these estimates relate to usage of insecticides targeted mainly at stalk boring androotworm pests. Some of the active ingredients traditionally used to control these pests may still be used with
GM IR maize for the control of some other pests thatat some of the GM IR technology does not target©PG Economics Ltd 2022

126GM crop impact: 1996-2020

Figure 61: Reduction in insecticide use and the environmental load from using GM IR maizein adopting countries 1996-2020
0.0%

Ai change

EIQ change-10.0%-20.0%-30.0%-40.0%-41.2%-50.0%-45.4%-53.1%-60.0%-60.7%-70.0%
Cumulative2020

4.1.8 GM insect resistant (GM IR) cottona) The US
Whilst the annual average volume of insecticides used on the US cotton crop has fluctuated (as tobe expected according to variations in regional and yearly pest pressures), there has been anunderlying decrease in usage since the mid-1990s (Figure 62). Applications on GM IR crops andthe associated environmental impact have also been consistently lower for most years until 2007.
Drawing conclusions from the usage data for the conventional versus GM IR cotton alone should,
however, be treated with caution for a number of reasons (see also section 4.1.7):••

There are a number of pests for the cotton crop. These vary in incidence and damage by
region and year and may affect only a proportion of the total crop. In the case of GM IR
cotton, this comprises traits that target various Heliothis and Helicoverpa pests (eg,budworm and bollworm). These are major pests of cotton crops in all cotton growing
regions of the world (including the US) and can devastate crops, causing substantial
reductions in yield, unless crop protection practices are employed. In the US, all of thecrop may typically be treated with insecticides for Heliothis/Helicoverpa pests each year
although in some regions, notably Texas, the incidence and frequency of pest pressure
tends to be much more limited than in other regions. In addition, there are pests such asboll weevil which are not targeted by current GM IR traits and crops receive insecticide
treatments for these pests. This means that assessing the impact of the GM IR cotton
technology requires disaggregation of insecticide usage specifically targeted at the
Heliothis/Helicoverpa pests, and possibly limiting the maximum impact area to the areasthat would otherwise require insecticide treatment, rather than necessarily applying
insecticide savings to the entire area planted to seed containing GM IR traits targetingthese pests;
The widespread adoption of GM insect resistant technology has resulted in ‘area-wide’
suppression of target pests such as some Heliothis/Helicoverpa pests in cotton crops. As a

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127GM crop impact: 1996-2020•

result, some conventional farmers have benefited from this lower level of pest infestationand the associated reduced need to conduct insecticide treatments (Wu et al (2008));
Typically, the first users of the GM IR technology are farmers who regularly experience
economic levels of damage from the GM IR target pests. This means that once the levelsof adoption (in terms of areas planted to the GM IR traits) become significant (above 50%of the US crop from 2005, and 88% in 2020), it is likely that the residual conventional crop
tends to be found in regions where the pest pressure and damage from
Heliothis/Helicoverpa pests is lower than would otherwise be the case in the regions where
GM IR traits have been adopted. Hence, using data based on the average insecticide useon this residual conventional crop as an indicator of insecticide use savings relating to theadoption of GM IR traits probably understates the insecticide savings.

In order to address these issues, our approach has been to first identify the insecticides typicallyused to treat the Heliothis/Helicoverpa pests and their usage rates from relevant literature (eg,Carpenter & Gianessi (1999), Sankala & Blumenthal (2003 & 2006)) and insecticide usage sources
such as USDA NASS and Kynetec. This identified average usage of a number of insecticides
commonly used for the control of these pests in terms of amount of active ingredient applied,field EIQ/ha values and the proportion of the total crop receiving each active ingredient in abaseline period of 1996-2000. We identified that the average amount of insecticide active
ingredient used for targeting these pests was about 0.14 kg ai/ha and the associated average
EIQ/ha was about 6/ha.
As almost all of the US cotton crop has commonly received treatments each season for the controlof these pests, these active ingredient and field EIQ saving were then applied to the GM IR areatargeting these pests.
At the national level, the use of GM IR cotton has resulted in an annual saving in the volume of
insecticide ai use of 12% in 2020 (0.424 million kg) and the annual field EIQ load on the US cotton
crop also fell by 16% in 2020. Since 1996, the cumulative decrease in insecticide ai use has been
8% (8.93 million kg), and the cumulative reduction in the field EIQ load has been 10%.

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GM crop impact: 1996-2020

Figure 62: Average cotton insecticide usage: 1996-2020 (average active ingredient use: kg/ha)
2.50
2.00
1.50
1.00
0.50
-

Sources: derived from USDA NASS, University Extension Services and Kynetecb) China
Since the adoption of GM IR cotton in China there have been substantial reductions in the use of
insecticides. In terms of the average volume of insecticide ai applied to cotton, the application toa typical hectare of GM IR cotton in the earlier years of adoption was about 1.35 kg/ha, compared
to 6.02 kg/ha for conventionally grown cotton (a 77% decrease) 87. In terms of an average field
EIQ load/ha the GM IR cotton insecticide load was 61/ha compared to 292/ha for conventional
cotton. More recent assessments of these comparisons from sources such as industry advisorsand market research sources like Kleffmann and Kynetec put, for example, the current
comparison as the average conventional treatment at 2.737 kg/ha, with a field EIQ/ha of 103.4/ha,compared to 1.67 kg/ha and a field EIQ/ha of 73.0/ha for GM IR cotton (see Appendix 3 fordetails).
Based on these differences, the amount of insecticide ai used and its environmental load impact
were respectively 41% and 28% lower in 2020 than the levels that would have occurred if only
conventional cotton had been planted. Cumulatively since 1997, the volume of insecticide use
has decreased by 30.1% (138.8 million kg ai) and the field EIQ load has fallen by 30.2%.
c) Australia
Using a combination of data from AMIS Global/Kleffmann, industry sources and CSIRO 88, thefollowing changes in insecticide use on Australian cotton have occurred:•

There has been a significant reduction in both the volume of insecticides used and theenvironmental impact associated with this spraying (Table 23);

87

Sources: based on a combination of industry views and Pray et al (2001)

88

The former making a direct comparison of insecticide use of Bollgard II versus conventional cotton and thelatter a survey-based assessment of actual insecticide usage in the years 2002-03 and 2003-04©PG Economics Ltd 2022

129

GM crop impact: 1996-2020

•

•

•

The average field EIQ/ha value of the Ingard technology was less than half the average
field EIQ/ha for conventional cotton. In turn, this saving has been further increased withthe availability and adoption of the Bollgard II cotton from 2003/04;
The total amount of insecticide ai used and its environmental impact has been
respectively 53% (0.43 million kg) and 57% lower in 2020 than the levels that would haveoccurred if only conventional cotton had been planted;
Cumulatively, since 1996 the volume of insecticide use is 30% lower (14 million kg) than
the amount that would have been used if GM IR technology had not been adopted andthe field EIQ load has fallen by 32%.

Table 23: Comparison of insecticide ai use and field EIQ values for conventional, Ingard andBollgard II cotton in Australia
Conventional
IngardBollgard II
Active ingredient use
11.0 (2.1)
4.3
2.2 (0.91)(kg/ha)Field EIQ value/ha
220 (65)97
39 (25.0)
Sources and notes: derived from industry sources and CSIRO 2005. Ingard cotton grown from 1996,
Bollgard from 2003/04 (bracketed figures = values updated/revised from 2011)d) Argentina
Adoption of GM IR cotton in Argentina has also resulted in important reductions in insecticide
use 89:••••The average volume of insecticide ai used by GM IR cotton growers is 36.4% lower than
the average of 0.736 kg/ha for conventional cotton growers in 2020;
The average field EIQ/ha is also significantly lower for GM IR cotton growers (38.2/ha for
conventional growers compared to 15.1/ha for GM IR growers);
The total amount of ai used and its environmental impact have been respectively 43%(143,940 kg) and 59% lower in 2020 than the levels that would have occurred if only
conventional cotton had been planted;
Cumulatively since 1998, the volume of insecticide use is 21.9% lower (1.82 million kg)
and the EIQ/ha load 31.1% lower than the amount that would have been used if GM IR
technology had not been adopted.

e) India
The analysis presented below is based on insecticide usage data from AMIS Global/Kleffmann
and typical spray regimes for GM IR and conventional cotton (source: Monsanto India 2006, 2009,2011, 2013 and 2017). The respective differences for ai use (see appendix 3) and field EIQ values
for GM IR and conventional cotton used in 2020 are:••89

Conventional cotton: average volume of insecticide used was 1.72 kg/ha and a field
EIQ/ha value of 73.76/ha;
GM IR cotton: average volume of insecticide used was 0.605 kg/ha and a field EIQ/havalue of 16.61/ha.

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GM crop impact: 1996-2020

Based on these values, the level of insecticide ai use and the total EIQ load in 2020 wererespectively 61% (13.7 million kg) and 72.8% lower than would have been expected if the total
crop had been conventional cotton. Cumulatively, since 2002, the insecticide ai use was 36.4%
lower (165 million kg) and the total EIQ load 46.2% lower.
f) Brazil
GM IR cotton was first planted commercially in 2006 (in 2020, on 1.17 million ha, 77% of the totalcrop). Due to the limited availability of data, the analysis presented below is based on theexperience in Argentina (see above). Thus, the respective differences for insecticide ai use andfield EIQ values for GM IR and conventional cotton used as the basis for the analysis are:••Conventional cotton: average volume of insecticide used is 0.736 kg/ha and a field EIQ/havalue of 38.2/ha;
GM IR cotton: average volume of insecticide used 0.41 kg/ha and a field EIQ/ha value of
15.1/ha.

Using these values, the level of insecticide ai use and the total EIQ load in 2020 were respectively
34% (382,000 kg) and 46% lower than would have been expected if the total crop had been
conventional cotton. Cumulatively since 2006, the total active ingredient saving has been 2.5
million kg (18%) and the EIQ/ha load factor has fallen by 26%.
g) Mexico
GM IR cotton has been grown in Mexico since 1996, and in 2020, 103,300 ha (69% of the total crop)
were planted to varieties containing GM IR traits.
Drawing on industry level data that compares typical insecticide treatments for GM IR andconventional cotton (see appendix 3), the main environmental impact associated with the use of
GM IR technology in the cotton crop has been a significant reduction in the environmental impact
associated with insecticide use on cotton. More specifically:•••

On a per ha basis, GM IR cotton uses 31% less (-1.6 kg) insecticide than conventional
cotton. The associated environmental impact, as measured by the EIQ indicator, of the
GM IR cotton is a 32% improvement on conventional cotton (a field EIQ/ha value of
56.6/ha compared to 137/ha for conventional cotton);
In 2020, at a national level, there had been a 21.4% saving in the amount of insecticide
active ingredient use (168,000 kg) applied relative to usage if the whole crop had beenplanted to conventional varieties. The field EIQ load was 21.2% lower;
Cumulatively since 1996, the amount of insecticide active ingredient applied was 16.6%(3.2 million kg) lower relative to usage if the Mexican cotton crop had been planted toonly conventional varieties over this period. The field EIQ load was 16.5% lower than it
would otherwise have been if the whole crop had been using conventional varieties.

h) Colombia
GM IR cotton has been grown commercially in Colombia since 2002. In 2020, 54% of the cotton
crop (4,615 ha of GM HT cotton) used seed containing this trait.
Drawing on analysis in Brookes (2020), which also draws on surveys of cotton growers in 2015
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GM crop impact: 1996-2020

The average amount of insecticide active use and associated field EIQ/ha rating for GM
IR cotton in 2020 were 0.3 kg/ha and 8.49/ha respectively. This compared withconventional cotton with insecticide active ingredient use of 0.69 kg/ha and a field EIQ
rating of 20.29/ha;
In 2020, the use of GM HT technology resulted a reduction in the use of insecticide active
ingredient of 1,560 kg (-26%) and a reduction in the EIQ rating of 31%;
Cumulatively (2002-2020), the insecticide active ingredient usage saving has been 59%(182,120 kg), with an EIQ load reduction of 63%.

•••i) Other countries
Cotton farmers in South Africa, Burkina Faso, Pakistan, Myanmar and Sudan have also beenusing GM IR technology in recent years. Analysis of the impact on insecticide use and theassociated environmental ‘foot print’ are not presented for these crops because of the lack of
insecticide usage data.
j) Summary of impact
Since 1996, the net impact on insecticide use and the associated environmental ‘foot print’(relative to what could have been expected if all cotton plantings had been to conventionalvarieties) in the main GM IR adopting countries has been (Figure 63):••

In 2020, a 49.9% decrease in the total volume of insecticide ai applied (18.8 million kg)
and a 56.4% reduction in the environmental impact (measured in terms of the field
EIQ/ha load);
Since 1996, 29.9% less insecticide ai has been used (338.9 million kg) and theenvironmental impact from insecticides applied to the cotton crop has fallen by 34.4%.

Figure 63: Reduction in insecticide use and the environmental load from using GM IR cottonin adopting countries 1996-2020
0.0%

Ai change

EIQ change-10.0%-20.0%-30.0%-29.9%-34.4%-40.0%-50.0%-49.9%-60.0%-56.4%
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GM crop impact: 1996-2020

4.1.9 Other environmental impacts - development of herbicide resistantweeds and weed shifts
As indicated in section 4.1.1, weed resistance to glyphosate has become a major issue affectingsome farmers using GM HT (tolerant to glyphosate) crops.
This resistance development should, however, be placed in context. All weeds have the ability todevelop resistance to all herbicides and there are hundreds of resistant weed species confirmed in
the International Survey of Herbicide Resistant Weeds (www.weedscience.org), and reports ofherbicide resistant weeds pre-date the use of GM HT crops by decades There are, for example,
169 weed species that are resistant to ALS herbicides (eg, imazethapyr, cloransulam methyl) and
87 weed species resistant to photosystem II inhibitor herbicides (eg, atrazine). Worldwide there
are currently (accessed May 2022) 56 weeds species resistant to glyphosate of which several are
not associated with glyphosate tolerant crops (www.weedscience.org). In the US, there are
currently 17 weeds recognised as exhibiting resistance to glyphosate, of which two are notassociated with glyphosate tolerant crops. In Argentina, Brazil and Canada, where GM HT crops
are widely grown, the number of weed species exhibiting resistance to glyphosate arerespectively 17,11 and 8. Some of the glyphosate-resistant species, such as marestail (Conyza
canadensis), waterhemp (Amaranthus tuberculatus) and palmer pigweed (Amaranthus palmeri) in theUS, are now widespread, with the affected area being possibly within a range of 60%-80% of thetotal area annually devoted to maize, cotton and soybeans.
Where farmers are faced with the existence of weeds resistant to glyphosate in GM HT crops,
they are advised to be proactive and include other herbicides (with different and complementary
modes of action) in combination with glyphosate and in some cases to adopt cultural practices
such as ploughing in their integrated weed management systems. This change in weed
management emphasis also reflects the broader agenda of developing strategies across all formsof cropping systems to minimise and slow down the potential for weeds developing resistance toexisting technology solutions for their control. In addition, as referred to earlier, GM HT crops
tolerant to other herbicides (often stacked with glyphosate) have also become available from 2016
in some countries (notably to dicamba and 2 4 D in the USA). At the macro level, these changes
have influenced the mix, total amount, cost and overall profile of herbicides applied to GM HT
crops in the last 20 years.
For example, in the 2020 US GM HT soybean crop, approximately 90% of the crop area wasplanted to varieties that were tolerant to other herbicides (in addition to tolerance to glyphosate)and even where crops were planted that were tolerant to only one herbicide, all of these crops
received an additional herbicide treatment of other active ingredients (notably sulfentrazone, S
metolachlor, 2 4 D, metribuzin, metsulfuron and pyroxasulfone). This compares with only 14%of the GM HT soybean crop (almost all tolerant to only glyphosate) receiving a treatment of oneof the next four most used herbicide active ingredients (after glyphosate) in 2006. As a result, theaverage amount of herbicide active ingredient applied to the GM HT soybean crop in the US (perhectare) doubled over this period. The increase in non-glyphosate herbicide use was primarily inresponse to public and private sector weed scientist recommendations to diversify weed
management programmes and not to rely on a single herbicide mode of action for total weed
management. It is interesting to note that by 2016, glyphosate accounted for a lower share of
total active ingredient use on the GM HT crop (63%) than in 1998 when it accounted for 82% of©PG Economics Ltd 2022

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total active ingredient use. This illustrates that farmers have continued to use glyphosate becauseof its broad-spectrum activity in addition to using other herbicides in line with integrated weed
management advice. This continues in 2020, with the availability of additional options for weed
control via varieties with GM HT tolerance to other herbicides. Almost all of the new GM HT
seed technology used is tolerant to glyphosate and other herbicides rather than being only
tolerant to other (than glyphosate) herbicides.
On the small conventional (soybean) crop, the average amount of herbicide active ingredientapplied also doubled over the period 2006-2020. This increase in usage largely reflected a shift in
herbicides used rather than increased dose rates for some herbicides. The increase in the use ofherbicides on the conventional soybean crop in the US can also be mainly attributed to the ongoing development of weed resistance to non-glyphosate herbicides commonly used andhighlights that the development of weed resistance to herbicides is a problem faced by all
farmers, regardless of production method.
Relative to the conventional alternative, the environmental profile of GM HT crop use has,nevertheless, continued to offer important advantages and in most cases, provides an improved
environmental profile compared to the conventional alternative (as measured by the EIQ
indicator).

4.2 Soil carbon sequestration
This section assesses the contribution of GM crop adoption to reducing the level of greenhousegas (GHG) emissions. The three main GHGs of relevance to agriculture are carbon dioxide (CO2),
nitrous oxide (N2O) and methane (CH4). The scope for GM crops contributing to lowering levelsof GHG comes from three principal sources:a) Reduced fuel use from fewer herbicide or insecticide applications;b) The use of ‘no-till’ and ‘reduced-till’ farming systems collectively referred to asconservation tillage, have increased significantly with the adoption of GM HT crops (seebelow for definitions). The GM HT technology has improved farmers’ ability to control
weeds, reducing the need to rely on soil cultivation and seed-bed preparation as means togetting good levels of weed control. The advantages of conservation tillage include:
•
•
•
•
•

90

Lower fuel costs (less soil preparation; ploughing, harrowing, rolling etc);
Reduced labour requirements associated with soil preparation;
Enhanced soil quality and reduced levels of soil erosion, resulting in more carbon
remaining in soil, which leads to lower GHG emissions 90;
Improved levels of soil moisture conserving;
Reduced soil temperature fluctuations from the insulating properties of crop
residues. This has a positive impact on both the physical, chemical andmicrobiological properties of soil (Mathew et al (2012)); andThe International Panel on Climate Change (IPCC) has agreed that conservation/no till cultivation leads tohigher levels of soil carbon. https://www.ipcc.ch/2019/08/08/land-is-a-critical-resource_srccl/©PG Economics Ltd 2022

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GM crop impact: 1996-2020c)

Additional carbon dioxide can be assimilated where the GM technology leads to theintensification of crop production resulting in higher crop yields, additional cropping
and the use of cover crops (see section 4.2.11).

Overall, the reduction of GHGs can be measured in terms of the amount of carbon dioxide
removed from the atmosphere by reduced consumption of fuel and additional storing andsequestration of carbon in the soil with NT/RT tillage practices.
In the analysis below, we have differentiated soil tillage systems into three categories depending
upon their impact on soil disturbance:•••

Conventional tillage (CT): conventionally tilled prior to planting the next crop (residue
cover 0%-15%) eg, inversion tillage using a plough followed by multiple cultivation trips;
Reduced tillage (RT): full width tillage that disturbs the entire soil surface prior toplanting the next crop, tillage tools such as chisel ploughs, field cultivators, rotary
harrows are used and weeds are controlled by cultivation and herbicides. With RT
methods of mulch-till and ridge till, crop residue remains on the surface (thiscorresponds to a residue cover of 16%-30% for all crops other than maize, for which there
is a reduced tillage category with a higher crop residue cover of 31%-50%); andNo-till (NT): the least intensive form of tillage where a minimal amount of soil
disturbance is made to ensure a good crop stand and yield. NT methods include zerotill, slot till, direct seeding and strip-till. The soil is not tilled prior to planting the next
crop and substantial crop residue remains on the surface (this corresponds to a residue
cover of >30% for all crops other than maize, for which the residue cover is >50%).

4.2.1 Tractor fuel usea) Reduced and no tillage
The adoption and (more importantly) maintenance of conservation tillage systems, notably NT
systems, has been facilitated by the availability of GM HT crops. To estimate fuel savings fromconservation tillage systems, we have reviewed reports and data from a number of sources, ofwhich the main ones were: the United States Department of Agriculture’s (USDA) Conservation
Effects Assessment Project (CEAP); the USDA Energy Estimator for Tillage Model (2014); and the
USDA online tool for estimating carbon storage in agroforestry practices (COMET-VR):•

The USDA’s Conservation Effects Assessment Project (CEAP) uses the Soil Intensity
Rating (STIR) to calculate the rate of soil disturbance for each form of tillage method,
their frequency and depth. For each implement used, fuel consumption was estimatedand given a diesel equivalent for each tillage implement used. For example, a no-till drill
has a STIR of 2 and consumes 3.3 litres/ha, a chisel plough has a STIR of 78 and consumes
10.3 litres/ha, a mouldboard plough a STIR of 87 and consumes 17.6 litres/ha. For land to
be considered under NT cultivation, the STIR value for each crop in the rotation should
be no great than 20, for RT (mulch-till) the STIR value should be greater than 60. The
relative differences in the quantity of fuel used for each tillage type is illustrated in the
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Table 24: Estimated reduction in fuel use from adoption of conservation tillage (litres/ha)
Tillage type

STIR

Fuel use

CT

>60

56.6

Saving on CT

NT

<20

17.7

-38.9

RT (mulch till)>20 - <60

33.3

-23.3

Source: USDA CEAP-Crop Conservation Insight August 2016

The USDA CEAP-Crop Conservation Insight (2016) estimated that annually in the US thewidespread adoption of conservation tillage has resulted in:




•

Fuel use reduction of 3,075.3 million litres of diesel equivalents, roughly equal to theenergy used by 3.2 million US households;
Carbon dioxide emissions reduced by 8.3 million tonnes; andNT has been adopted on 53% of all cropping land and accounts for 72% of the
reduction on fuel use and related emissions.

The USDA’s Energy Estimator for Tillage Model estimates diesel fuel use and costs in the
production of key crops by specific locations across the US and compares potential
energy savings between conventional tillage and alternative tillage systems. The
quantity of tractor fuel used for seed-bed preparation, herbicide spraying and planting ineach of these systems is illustrated for soybeans planted in Illinois (Table 25). CT requires
49.01 litres/ha, compared to mulch till at 40.88 litres/ha, ridge till 32.36 litres/ha and NT
21.79 litres/ha;

Table 25: US soybean: tractor fuel consumption by tillage method (litres/ha)
Year 1 – IllinoisCT

Mulch till

Ridge-till

NT

Chisel

0.00

9.35

0.00

0.00

Plough, mouldboard

17.48

0.00

0.00

0.00

Disk, tandem light finishing

3.74

3.74

0.00

0.00

Cultivator, field 6-12 in sweeps

6.92

6.92

0.00

0.00

Planter, double disk operation

4.12

4.12

4.12

0.00

Planter, double disk operation w/fluted coulter

0.00

0.00

0.00

5.04

Cultivator, row - 1st pass ridge till

0.00

0.00

5.79

0.00

Cultivator, row - 2nd pass ridge till

0.00

0.00

6.92

0.00

Sprayer, post emergence

1.22

1.22

0.00

1.22

Sprayer, insecticide post emergence

1.22

1.22

1.22

1.22

Harvest, killing crop 50% standing stubble

14.31

14.31

14.31

14.31

49.01

40.88

32.36

21.79

8.13

16.65

27.22

Total fuel use:
Saving on CT:
Source: USDA Energy Estimator 2012•

The fuel saving obtained by a switch from CT to mulch-till, ridge-till and NT for maize
and soybeans across the three most important crop management zones (CMZ's) in the US
is illustrated in Table 26. The adoption of NT in maize results in a 24.41 litre/ha saving©PG Economics Ltd 2022

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compared with CT and in the case of soybeans, the NT saving is 27.12 litre/ha 91, a savingof 44.8% and 55.3% respectively; andTable 26: Total farm diesel fuel consumption estimate (litres/ha)
Crop (crop management zones)CT

Mulch-till

Ridge-till

NT

54.50

46.98

36.39

30.09

Potential fuel savings over conventional tillage

7.52

18.11

24.41

Saving CT:

13.8%

33.2%

44.8%

38.62

33.74

21.89

Potential fuel savings over conventional tillage

10.39

15.27

27.12

Saving on CT:

21.2%

31.2%

55.3%

Maize (Minnesota, Iowa & Illinois)
Total fuel use

Soybeans (Iowa, Illinois & Nebraska)
Total fuel use

49.01

Source: USDA Energy Estimator 2012•

The Voluntary Reporting of Greenhouse Gases-Carbon Management Evaluation Tool
(COMET-VR) gives a higher reduction of 41.8 litres/ha when CT is replaced by NT on
non-irrigated maize and a reduction of 59.7 litres/ha in the case of soybeans in Nebraska.

In our analysis 92 presented below, it is assumed that the adoption of NT farming systems insoybean production reduces cultivation and seedbed preparation fuel usage by 27.12 litres/hacompared with traditional CT and in the case of RT cultivation by 10.39 litres/ha. In the case ofmaize, NT results in a saving of 24.41 litres/ha and in the case of RT 7.52 litres/ha, compared with
CT. These are conservative estimates and are in line with the USDA Fuel Estimator for soybeans
and maize.
In terms of GHG, each litre of tractor diesel consumed contributes an estimated 2.67 93 kg ofcarbon dioxide into the atmosphere. The adoption of NT and RT systems in respect of fuel use
therefore results in reductions of carbon dioxide emissions of 72.41 kg/ha and 27.74 kg/ha
respectively for soybeans and 65.17 kg/ha and 20.08 kg/ha for maize.
b) Reduced application of herbicides and insecticides
For both herbicide and insecticide spray applications, the quantity of energy required to apply
pesticides depends upon the application method. For example, in the US, a typical method of
application is with a 90-foot boom sprayer which consumes approximately 0.84 litres/ha 94 (0.6591These figures have not differed since 2012 when the USDA Energy Estimator for Tillage Model(https://ecat.sc.egov.usda.gov/) was last updated
92

In previous editions of this report, the authors have used different savings that reflect changing estimatesof fuel use by the USDA Energy Estimator. In reports covering the period up to 2010 savings of 27.22 litres/hafor NT and 9.56 litres/ha for RT compared to CT were used for both maize and soybeans.
93

In previous editions of this report up to 2010 the authors have applied a co-efficient of 2.75 to convert 1 litre

of diesel to kgs of carbon dioxide. All subsequent reports use the updated figure of 2.6676 rounded to 2.67.
94

In previous editions of this report (up to and including the 5th report covering 1996-2009) the authors haveused 1.31 litres/ha.

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litres/ha for a self-propelled sprayer and 1.12 litres/ha for a tractor pulled sprayer (Lazarus(2019)). One less spray application therefore reduces carbon dioxide emissions by 2.24 kg/ha.
The conversion of one hectare of CT to NT equates to a saving of approximately 587 km travelled
by a standard family car 95 and one less spray pass per hectare is equal to a saving of nearly 18.2
km travelled.

4.2.2 Soil carbon sequestration
The use of RT/NT farming systems increases the amount of organic soil carbon in the upper soil
layer in the form of crop roots and harvest residue that is not otherwise inverted into the sub-soil
if CT is used. Appendix 5 summarises some of the key research which has examined therelationship between carbon sequestration and different tillage systems. This literature review
shows that the amount of carbon sequestered varies by soil type, cropping system, eco-region
and tillage depth. It also shows that tillage systems can impact on levels of other GHG emissions
such as methane and nitrous oxide and on crop yield.
Complex models are available to estimate the level of carbon sequestered depending upon
historic, present and future cropping systems. For example, the USDA’s COMET-Planner applies
emission reduction coefficients for changes in tillage practice from CT to NT and RT based on ameta-analysis of the relevant literature (Table 27). In this tool, coefficients are generalized at thenational-scale and differentiated by dry and humid climate zones with the values shown asemission reductions relative to baseline management (positive values mean a decrease inemissions due to the implementation of the tillage practice). For example, the conversion of one
hectare of crop land from CT to NT in a moist/humid environment will result in 1,037.8 kg ofcarbon dioxide/ha/year being sequestered; this is equivalent to 282.8 kg carbon/ha/year 96.
Table 27: COMET-Planner: carbon sequestration by conservation practice (average)
Conservation PracticeStandard
CT to NT (CPS 329)
CT to RT (CPS 345)

Climate zone

Carbon dioxide(kg CO2 eq/ha/year)

Carbon(kg carbon/ha/year)

Dry/semi arid

568.3

154.9

Moist/humid

1,037.8

282.8

Dry/semi arid

247.1

67.3

Moist/humid

321.2

87.5

Source: COMET-Planner Carbon and Greenhouse Gas Evaluation for NRCS Conservation Practice Planning
Notes: 1 kg carbon equals 3.67 kg carbon dioxide

95

Assumed standard UK family car carbon dioxide emission rating = 123.4 grams/km. Therefore 72.41 kg ofcarbon dioxide divided by 123.4 grams/km = 587 km.
96

Personal communication November 2019: E.D.Mass, Ohio State University Carbon Management andSequestration Center has observed similar carbon sequestrations rates of approximately 282.8 kg/C/ha/yr in
the initial twenty years of conversion from CT to NT with an anticipated average of 178 kg/C/ha/yr over fifty
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Our analysis for the US uses the COMET-VR 2.0 tool 97 for three key soybean and maize
production states and assumes the adoption of NT from CT in all states, a clay loam soil withaverage fertiliser usage, a non-irrigated maize-soybean rotation in Minnesota and Illinois and asoybean-maize-winter-wheat rotation in South Dakota. Using the COMET-VR 2.0 tool, the levelof carbon sequestered estimated to be stored is higher with NT by 117.5, 114.4 and 112.9 kg
carbon/ha/year respectively compared to the CT system for each of the three states for the
projected period 2013-2023.
Analysis using the Michigan State University - US Cropland Greenhouse Gas Calculator 98 formaize-soybean rotations in the same locations over a ten-year projected period estimated that NT
sequesters an additional 123 kg carbon/ha/year compared to RT and 175 kg carbon/ha/yearcompared to CT.
Analysis of individual crops using the Michigan State University - US Cropland Greenhouse Gas
indicates that NT maize is a net carbon sink of 244 kg carbon/ha/year, whereas, NT soybean is amarginal net source of carbon of 43 kg carbon/ha/year. The difference between maize NT and CT
is 247 kg carbon/ha/year and for soybeans 103 kg carbon/ha/year (Table 28).
Table 28: Summary of the potential of maize and soybeans cultivation systems to reduce net
emissions or sequester carbon (kg of carbon/ha/year)
Carbon sequestered
Maize

SoybeanConventional-3

Carbon sequestered difference to NT-247

Reduced72-171

No-till244

0Conventional

-146

-103

Reduced-114-72

No-till-430Source: Michigan State University - US Cropland Greenhouse Gas Calculator

Differences in carbon soil sequestration rates between maize and soybeans can be partiallyexplained by the greater plant matter residue contribution of the maize crop in the soybeanmaize rotation. Research by Alvarez & Steinbach (2012) estimated that maize contributes 7,178
Mg/ha/year of dry matter as crop residue compared to soybeans which contribute only 3,373
Mg/ha/year. Soybean roots have less mass and length than maize roots which may also influence
different rates of soil carbon sequestration.

97

COMET-VR 2.0 is a web-based tool that provides estimates of carbon sequestration and net greenhouse gas

emissions from soils and biomass for US farms. It links databases containing information on soils, climate
and management practices to run an ecosystem simulation model as well as empirical models for soil N2O
emissions and CO2 from fuel usage for field operations.
http://www.comet2.colostate.edu/.

In

2014

the

http://cometfarm.nrel.colostate.edu/
98

http://surf.kbs.msu.edu/©PG Economics Ltd 2022

139

tool

In 2011, an updated version was released was

updated

to

COMET

FARM

-

GM crop impact: 1996-2020

Overall, the literature highlights the difficulty in estimating the contribution NT/RT systems tosoil carbon sequestration levels. If a specific crop area is in continuous NT crop rotation, the fullsoil carbon sequestration (storage) benefits described in the literature can be realised. However,if the NT crop area is returned to a conventional tillage system, a proportion of the soil organiccarbon gain will be lost. The temporary nature of this form of carbon storage only becomespermanent when farmers adopt a continuous NT system, which as indicated earlier, is highly
reliant on having an effective (typically herbicide-based) weed control system. As discussed
later, the increasing emergence of weeds resistant to glyphosate (the main herbicide used for‘over the crop’ weed control in GM HT crops) has reduced the effectiveness of weed control
systems solely based on herbicide use for some farmers and resulted in some reversion to CT
production systems in order to improve their overall levels of weed control. This has likely
reduced the year on year absolute levels of carbon sequestration facilitated by GM HT crops
relative to several years ago (see for example Lu et al (2022), Van Deynze et al (2021)). The
estimates presented in this paper take this factor of influence into account by using the latest
available data on the adoption of NT, RT and CT production systems.
Estimating long-term soil carbon sequestration is also complicated by the hypothesis typicallyused in soil carbon models that the level of soil organic carbon (SOC) reaches an equilibrium
when the amount of carbon stored in the soil equals the amount of carbon released (the CarbonStock Equilibrium (CSE)). This implies that as equilibrium is reached, the rate of soil carbon
sequestration may decline and therefore if equilibrium is being reached after many years of land
being in NT with GM HT crops, the rate of carbon sequestration may be declining. The estimatespresented in this paper assume that a constant rate of carbon sequestration occurs because of therelatively short time period that NT/RT production systems have been operated (the time periodthat land may have been in ‘permanent non-cultivation is a maximum of 20-25 years). In
addition, some researchers question whether the CSE assumption that is used in most soil models
is valid because of the scope for very old soils to continue to store carbon (Lal, 2004).
In sum, drawing on these models and the literature discussed in Appendix 5, the analysis
presented in the following sub-sections assumes the following:
US: In previous reports (covering the period up to 1996-2011) no differentiation was madebetween maize and soybeans. The assumptions used were based on research as discussed earlier
and uses differences between NT and CT of 400 kg of carbon/ha/year of soil carbon sequestered(NT systems store 375 kg of carbon/ha/year; RT systems store 175 kg of carbon/ha/year; and CT
systems release 25 kg of carbon/ha/year).
In this report (and the previous five), the soil carbon sequestered by tillage system for maize incontinuous rotation with soybeans is assumed to be a net sink of 250 kg of carbon/ha/year based
on:
•
•
•

NT systems store 251 kg of carbon/ha/year;
RT systems store 75 kg of carbon/ha/year;
CT systems store 1 kg of carbon/ha/year.

The soil carbon sequestered by tillage system for soybeans in a continuous rotation with maize isassumed to be a net reduction of 100 kg of carbon/ha/year (all soybean tillage systems emit

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carbon but the NT and RT systems emit less relative to the CT system) based on:•••

NT systems release 45 kg of carbon/ha/year;
RT systems release 115 kg of carbon/ha/year;
CT systems release 145 kg of carbon/ha/year.

South America (Argentina, Brazil, Paraguay and Uruguay): soil carbon retention is 175 kg
carbon/ha/year for NT soybean cropping and CT systems release 25 kg carbon/ha/year (adifference of 200 kg carbon/ha/year). In previous reports (up to 1996-2013) the difference used
was 300 kg carbon/ha/year.
Where the use of GM crop seed technology has resulted in a reduction in the number of herbicide
or insecticide applications or the consistent use of less intensive cultivation practices (lessploughing) this has provided (and continues to provide) a permanent reduction in carbon
dioxide emissions.

4.2.3 Herbicide tolerance and conservation tillage
The adoption of GM HT crops has impacted on the type of herbicides applied, the method of
application (foliar, broadcast, soil incorporated) and the number of herbicide applications. For
example, the adoption of GM HT canola in North America has resulted in applications of residualsoil-active herbicides being mostly replaced by post-emergence applications of broad-spectrum
herbicides with foliar activity (Brimner et al (2005)). Similarly, in the case of GM HT cotton theuse of glyphosate to control both grass and broadleaf weeds, post-emergent, largely replaced theuse of soil residual herbicides applied pre- and post-emergence (McClelland et al (2000)). The
type and number of herbicide applications changed, sometimes (but often not) resulting in a
reduction in the number of herbicide applications (see section 3).
In addition, there has been a shift from CT to RT and NT. This has had a marked effect on tractor
fuel consumption due to energy-intensive cultivation methods being replaced with RT/NT andlargely herbicide-based weed control systems. The GM HT crop where this is most evident is HT
soybeans. Here, adoption of the technology has made an important contribution to facilitating
the adoption of RT or NT farming systems. Before the introduction of GM HT soybean cultivars,
RT/NT systems were practised by some farmers with varying degrees of success using a numberof herbicides. The opportunity for growers to control weeds with a non-residual foliar herbicide
as a “burn down” pre-seeding treatment, followed by a post-emergent treatment when thesoybean crop became established, made the RT/NT systems more reliable, technically viable andcommercially attractive. These technical and cost advantages have contributed to the rapid
adoption of GM HT seed and RT/NT production systems. For example, there has been a 45%
increase in the RT/NT soybean area in the US and a six-fold increase in Argentina since 1996. In
2020, RT/NT production accounted for 80% and 92% respectively of total soybean production in
the US and Argentina, with 84% and 94% respectively of the RT/NT soybean crop area in eachcountries using GM HT technology.

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4.2.4 Herbicide tolerant soybeans
4.2.4.1 The US
The importance of GM HT soybeans in the adoption of a NT system was first highlighted by adetailed study undertaken by the American Soybean Association “The Conservation Tillage
Study 99” (2001). This study found that the availability of GM HT soybeans facilitated andencouraged farmers to implement reduced tillage practices; a majority of growers surveyed
indicated that GM HT soybean technology had been the factor of greatest influence in theiradoption of reduced tillage practices. Fernandez-Cornejo et al (2012) concluded over an elevenyear period (1996-2006) that GM HT soybean adoption had led to a significant increase in the
adoption of conservation tillage (RT/NT). This study concluded that a one percent increase in
GM HT soybean adoption leads to a 0.21% increase in conservation tillage.
The area of soybeans cultivated in the US has increased substantially (28%) from 26.0 million hain 1996 to 33.3 million ha in 2020. Over the same period, the soybean area planted using NT and
RT has changed significantly. The CT area fell from 7.51 million ha in 1996 to 2.9 million ha in2013 before increasing to between 5 and 7 million ha in recent years (6.8 million ha in 2020). The
area planted using RT 100 increased from 10.8 million ha in 1996 to a high of 17.5 million ha in 2017(16.3 million ha in 2020) and the area planted using NT increased from 7.7 million ha in 1996 to ahigh of 16.0 million ha in 2013 before falling back to 10.3 million ha in 2020 (Figure 64). Barrera(2016) identified a reduction in the area of NT in 2015, while RT saw a nominal increase for bothmaize and soybeans and the changes presented here confirm this recent trend as more farmers
revert to CT production systems in order to improve control of weeds exhibiting resistance toglyphosate (and other herbicides).
Figure 64: US soybean: crop area by tillage practices 1996-2020 (hectares)
20,000,000
18,000,000
16,000,000
14,000,000
12,000,000
10,000,000
8,000,000
6,000,000
4,000,000
2,000,000

NT

RT

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0

CT

Adapted from Conservation Technology Information Center’s (CTIC) National Crop Residue Management
farm survey - https://www.ctic.org/CRM 1996-2004 & Operational Tillage Management System -99

https://soygrowers.com/news-releases/asa-study-confirms-environmental-benefits-of-biotech-soybeans/

100

Includes some pre-planting minimum tillage with 16-30% crop residue©PG Economics Ltd 2022

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GM crop impact: 1996-2020

https://www.ctic.org/OpTIS ased on remote sensing data for top five cropping states - Illinois, Iowa,
Nebraska, Indiana & Minnesota 2005-2020.

The most rapid rate of adoption of the GM HT technology has been by farmers using NT/RT
systems (GM HT cultivars accounting for an estimated 95% of total NT soybeans by 2006 and
95% in RT soybeans by 2014). This compares with CT systems where GM HT cultivars accountfor an estimated 76% of total CT plantings in 2020 (Figure 65).
Figure 65: US GM HT soybeans by tillage 1996-2020 (million ha)
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00

GM area

Non GM area

NT-GM

RT-GM

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00

CT-GM

a) Fuel consumption
Based on the soybean crop area planted by tillage system, type of seed planted (GM HT andconventional) and applying the fuel usage consumption rates presented in section 4.2.1, the total
consumption of tractor fuel has increased by 24% (233 million litres) between 1996 and 2020 while
the area planted increased by 28%. Over the same period, the average fuel usage fell 2.8% (from36.6 litres/ha to 35.6 litres/ha). In 2020, the average tillage fuel consumption on the GM HT
planted area was 34.8 litres/ha compared to 47.0 litres/ha for the conventional non-GM crop.
These changes to tillage fuel use and the resultant reduction on carbon dioxide emissions in US
soybeans for the 1996-2020 period are summarised in Figure 66. Cumulatively, this amounted toa permanent reduction in tillage fuel usage of 1,687 million litres which equates to a reduction incarbon dioxide emission of 4,503 million kg over this period.

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Figure 66: US soybeans permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg)
474.3

500.0
450.0
400.0
350.0
300.0

233.7
233.6
211.2
199.0
192.3

250.0
200.0
150.0
100.0

113.7
62.4 73.1

271.7

269.1

147.6

142.0

258.7
238.8

297.5
260.4
225.6
166.8

103.8

96.9
104.7

95.2

50.0 31.0
0.0b) Soil carbon sequestration
Using estimates of the soil carbon sequestered by tillage system for maize and soybeans incontinuous rotation (the soybean NT system is assumed to release 45 kg of carbon/ha/year; theRT system releases 115 kg carbon/ha/year; and the CT system releases 145 kg carbon/ha/year) 101
and based on the crop area planted by tillage system and type of seed planted (GM HT andconventional non-GM), our estimates of soil carbon changes are summarised below:••

The average level of carbon released per ha decreased by 3.4% (3.5 kg carbon/ha/year)
from 102.9 to 99.5 kg carbon/ha/year. In 2013 when the area in NT was at its highest the
average release dropped to 81.3 kg/carbon/ha/yr;
Although the area planted to soybeans in 2020 was 28% higher (at 33.3 million ha) than in
1996, the rate of total carbon released into the environment increased by only 24.1% (arelease of 2,672 million kg in 1996 compared to 3,316 million kg carbon/year in 2020).

Cumulatively, since 1996 the increase in soil carbon sequestered due to the increase in RT and NT
in US soybean production systems has been 5,978 million kg of carbon which, in terms of carbon
dioxide emissions, equates to a saving of 21,938 million kg of carbon dioxide that would
otherwise have been released into the atmosphere (Appendix 6). In 2013, the additional carbon
sequestered peaked at 663 million kg (2,433 million kg carbon dioxide) when the average increasein carbon sequestered relative to 1996 was 21.6 kg carbon per ha (Figure 67). Readers should notethat these estimates take into consideration the loss in carbon sequestration that has arisen as
some of the land using RT/NT has returned to CT in order to address weed resistance issues.

101

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GM crop impact: 1996-2020

Figure 67: US soybeans - potential additional carbon dioxide sequestered 1996-2020 (million
kg)
3,000
2,433

2,500

2,000

1,500

1,089
975

1,000

500

297

575
364

1,206
1,206

1,329

1,335

1,487

1,207
1,271

1,272
1,068

952
598

655

757

417
463

435

407

141
0

4.2.4.2 Argentina
Since 1996, the area planted to soybeans in Argentina, has increased substantially from 5.9 to 16.5
million ha (+180%). Over the same period, the area planted using NT practices also increased byseven fold from an estimated 2.2 to 15.1 million ha, whilst the area planted using CT decreased
from 3.8 to 1.3 million ha (Figure 68).
Figure 68: Argentina soybeans tillage practices 1996-2020 (million ha)
20.00
18.00
16.00
14.00
12.00
10.00
8.00
6.00
4.00
2.00
0.00

NT

CT

Adapted from Benbrook (2005), Trigo (2016) and AAPRESID (2018), Argenbio (2020)©PG Economics Ltd 2022

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GM crop impact: 1996-2020

As in the US, a key driver for the growth in NT soybean production has been the availability of
GM HT soybeans (Figure 69), which in 2020, accounted for 97% of the total Argentine soybean
area. Finger et al (2009: based on a survey of Argentine soybean growers) identified that the
combination of herbicide tolerance and NT were the key drivers to adoption of GM HT soybeans,facilitating easier crop management and reducing herbicide costs. As indicated in section 3, theavailability of this technology has also provided an opportunity for growers to ‘second crop
soybeans’ in a NT system with wheat. In the early to mid-1990’s, 5%-10% of the total soybean
crop was a second crop following on from wheat (in the same season). In the last twenty years,
the second crop soybean area has been significantly higher, within a range of 15%-30% of thetotal soybean area (the maximum each year influenced by the total area planted to wheat).
Figure 69: Argentina GM HT soybeans by tillage practice 1996-2020 (million ha)
25.00
20.00
15.00
10.00
5.00

GM area

Non-GM

NT-GM

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00

CT-GM

During the 1990’s and early 2000’s, NT stimulated an increase in the soybean-maize rotation
which reduced insect pressure, restored soil organic matter (SOM), increased crop residue input
and nutrient cycling. Therefore, the use of maize and other cover crops in the soybean rotation
has resulted in a more sustainable approach to soil management. Nevertheless, a soybeansoybean monoculture accounts for the majority of production mainly because of the relatively
higher costs of growing maize and its greater vulnerability to drought (Wingeyer et al, (2015)).
It should also be noted that in the early 1990’s, NT farming helped to reduce soil erosion by over
90% (from about 10+ tonnes/ha of soil loss to about 1 tonne/ha), contributed to additional water
accumulated in the top four inches (8.8 cm) of soil, higher crop yields, as well as, reducing fueluse and labour costs. However, AAPRESID also estimate that the area of NT in Argentina
peaked in 2012 at 92% and fell back marginally subsequently (eg, to 90% in 2015) due todifficulties some farmers have faced with the control of glyphosate resistant weeds, necessitating
reverting to ploughing to improve weed control and soil tyre compaction (Argentine No-Till
Farmers Association (AAPRESID) (2018)). Interestingly, in 2020 their estimate of the proportionof the Argentine soybean crop using NT was higher at 92%.

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a) Fuel consumption
Between 1996 and 2020, total fuel consumption associated with soybean cultivation increased by
71% from 231.5 to 396.2 million litres/year. However, during this period, the average quantity offuel used per ha fell 39% from 39.1 to 24.1 litres/ha, due mainly to the widespread adoption of
GM HT soybean seed and NT systems. If the proportion of the soybean crop in 2020 in NT
production had remained at the NT share level applicable in 1996, an additional 4,433 million
litres of fuel would have been used and at this level of fuel usage, an additional 11,837 million kg
of carbon dioxide would otherwise have been released into the atmosphere (Figure 70).
Figure 70: Argentina soybeans permanent reduction in carbon dioxide emissions resulting
from a reduction in fuel use 1996-2020 (million kg)
900
800

657

700

615

600

447

500

435

796

754

739
696

598

596

649

663

474

353

400
287

300
179

200
100

545

667

709

738

39 57 59840b) Soil carbon sequestration
Over the two decades to the late 1990s, soil degradation levels were reported to have increased in
the humid and sub-humid regions of Argentina. The main cause of this was attributed to leaving
land fallow following a wheat crop in a wheat-soybean crop rotation. This resulted in soils being
relatively free of weeds and crop residues but exposed to heavy summer rains which often led toextensive soil degradation and loss.
Research into ways of reducing soil degradation and loss was undertaken (mostly relating to theuse of NT systems 102) and this identified that NT systems could play an important role. As such,in the last twenty years, there has been an intensive programme of research and technology
transfer targeted at encouraging Argentine growers to adopt NT systems.
Specific research into soil carbon sequestration in Argentina includes the following:• Fabrizzi et al (2003) indicated that a higher level of total organic carbon was retained in
the soil with NT system compared with a CT system, but no quantification was provided;

Trials conducted by INTA found that direct sowing increases the yields of wheat and second soybean
crop in rotation. Other benefits observed were: less soil inversion leaving a greater quantity of stubble on thesurface, improvements in hydraulic conductivity, more efficient use of soil water, and higher soil organic
matter contents.
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GM crop impact: 1996-2020

•

•

•

Steinbach (2006) modelled the impact on the conversion of the Argentinean Pampas to
NT to mitigate the global warming effect. This work estimated that NT conversion
would result in an increase of soil organic carbon (SOC) of 74 million tonnes of carbon,
about twice the annual carbon emissions from fossil fuel consumed in Argentina.
However, the report concluded that the increased emissions of nitrous oxide might offset
the carbon mitigation of NT after 35 years;
Derpsch et al (2010) estimated that two-thirds of the area under NT systems in SouthAmerica was permanently in NT, which in Argentina was over 70% of the NT crop area.
This suggested that these carbon sequestration gains may be of a permanent nature; andResults from a 15-year experiment in the semi-arid Argentine Pampa (Alvarez et al(2014)) to evaluate a combination of three tillage systems (NT, NT with cover crop in
winter and RT) and two crop sequences (soybean–maize and soybean monoculture)concluded both factors (tillage system and crop sequence) affects the total organic carbon(TOC) stock. The total organic carbon stock, up to a depth of 100 cm showed signiﬁcantdifferences between soils under different tillage systems, with the two NT systems
having an 8% higher stock than the RT system (an extra accumulation of 333 kg
TOC/ha/year). In addition, at 0–30 cm depth, the NT systems had 267 kg TOC/ha/year
more than the RT system. The crop sequence of soybean–maize also had a 3% higher
level of organic carbon up to 100 cm soil depth (an extra accumulation of 133 kg
TOC/ha/year) than the soybean monoculture crop system.

Our analysis below applies a conservative estimate of soil carbon retention of 175 kg carbon/ha/yr
for NT and a release of 25 kg carbon/ha/yr for CT soybean cropping in Argentina. This estimatesthat the widespread adoption of NT/RT production systems, facilitated by GM HT soybean
technology has resulted in a cumulative total of 32,693 million kg of carbon, which equates to asaving of 119,985 million kg of carbon dioxide having been retained in the soil that would
otherwise have been released into the atmosphere (Figure 71 and Appendix 6).
Figure 71: Argentina soybeans - potential additional carbon dioxide sequestered 1996-2020(million kg)
9,000

8,066
7,187
7,643 7,496
7,477
6,762
7,050
6,725
6,235 6,655
6,066 6,584
6,040
5,526

8,000
7,000
6,000
4,531

5,000

3,577

4,000

2,905

3,000

1,819

582

2,000
1,000

4,802
4,411

397

593

856

-

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4.2.4.3 Brazil
In earlier reports (up to 1996-2009), Brazil was excluded from the analysis of carbon savings
associated with the facilitating role of GM HT soybeans on the adoption of NT/RT systems,
largely because NT/RT systems were commonplace in the sector before the legal availability of
GM HT soybeans in 2003. However, after consultation with several analysts in Brazil, who haveexamined the factors influencing the adoption of NT/RT systems in Brazil, we have partially
included some of the Brazilian GM HT soybean area in the calculations of carbon savings(included first in the report covering the period 1996-2010). This analysis includes the area
devoted to GM HT soybeans in the southern states of Santa Catarina, Paraná and Rio Grande de
Sol where the agricultural conditions are similar to those in Argentina and where the availabilityof GM HT soybean technology is considered to have played an important role in allowing
farmers to adopt NT/RT systems.
From 1997 when GM HT soybeans were first planted in Brazil (illegally), the total area of GM HT
soybeans has increased from 0.1 million ha to 36.7 million ha in 2020, of which these southernstates accounted for 32.4% (12.4 million ha). The vast majority of soybean production in thesestates uses NT systems (94%: 11.1 million ha), with virtually all of the NT area being GM HT
soybeans (Figure 72).
Figure 72: Brazil soybeans tillage practices 1996-2020 (million ha)
12.00
10.00
8.00
6.00
4.00
2.00

NT

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

0.00

CT

a) Fuel consumption
The Brazilian Federation of ‘direct planting’ (FEBRAPDP) and the Brazilian Agricultural Research
Corporation (Embrapa) estimate that the conversion from CT to NT results in fuel savings of
between 60%-70%. This compares with a 55% reduction in the US (see section 4.2.4.1). In theanalysis below, the more conservative fuel consumption rates used in the US (21.89 litres/ha for
NT and 49.01 litres/ha for CT - a reduction of 55% for NT relative to CT) are applied to the GM
HT soybean area planted in the three southern Brazilian states.

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Total fuel consumption in soybean cultivation has increased by 20% from 253 to 304.5 million
litres/year between 1997 and 2020. This increase in aggregate fuel use reflects the 91.9% increasein the area planted to soybeans in these three states during this period. However, the averagequantity of fuel used per ha fell 39.8% from 40.9 to 24.6 litres/ha largely as a result of the adoptionof GM HT technology and its facilitating role in the widespread change from CT to NT
production methods. If the mix of tillage practices prevailing in 1997 (where CT dominated)were applicable in 2020 in the three southern states, an additional 2,749 million litres of fuelwould have been used. At this level of fuel usage, an additional 7,341 million kg of carbon
dioxide would otherwise have been released into the atmosphere (Figure 73).

Figure 73: Brazil soybeans permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg)
600.00502
500.00456
364

400.00342
269

300.00178200.00100.00
0.00

0.00

22

44

65

99

218

240

267

481

514
498

538
516 525

408
363

298

136

b) Soil carbon sequestration
The rate of carbon sequestration in Brazil has been researched by several analysts. Bayer et al(2006) estimated the mean rate of carbon sequestration in NT Brazilian tropical soils to be 350 kg
carbon/ha/year, similar to the 340 kg carbon/ha/year reported for soils from temperate regions,
but lower than the 480 kg/ha/year estimated for southern Brazilian sub-tropical soils. Amado &Bayer (2008) estimated an average carbon sequestration rate of 170 kg carbon/ha/year (0.0 – 440kg carbon/ha/year) for NT soils in the south (sub-tropical) and middle-west (tropical) regions ofBrazil. The highest level of carbon sequestration (360 to 420 kg carbon/ha/year) occurs in
intensive cropping systems because of relatively high crop residue levels in the maize/soybean
rotation or where winter and summer cover crops are used.
Our analysis applies a conservative soil carbon retention value of 200 kg of carbon/ha/year for NT
soybean relative to CT cropping in Brazil (as applied in Argentina), a cumulative total of 20,275
million kg of carbon (equal to a saving of 74,409 million kg of carbon dioxide) has been retainedin the soil that would otherwise have been released into the atmosphere (Figure 74).

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Figure 74: Brazil soybeans - potential additional carbon dioxide sequestered 1996-2020 (million
kg)
6,000
4,877
5,000

5,085

5,212
5,047

5,450
5,232 5,322

4,621
3,687

4,000

3,463

4,135
3,676

2,724
3,019
2,704
2,206 2,435

3,000
2,000
1,000
225

444

1,809
1,374
1,004
659

0

4.2.4.4 Bolivia, Paraguay and Uruguay
NT systems have also become important in soybean production in Bolivia, Paraguay and
Uruguay, where the majority of production in these countries use NT systems. Across the three
countries, the area planted to soybeans has increased from 1.8 million ha to 5.6 million ha
between 1999 and 2020 (Paraguay 1.2 to 3.15 million ha, Uruguay 8,900 ha to 1.1 million ha andBolivia 0.6 to 1.39 million ha) and the area of GM soybeans from 58,000 ha to 5.64 million ha.
a) Fuel consumption
Using the findings and assumptions applied to Argentina 103 (see above), the savings in fuelconsumption for soybean production between 1999 and 2020 (associated with changes in NT/RT
tillage systems, the adoption of GM HT technology and comparing the proportion of NT
soybeans in 2020 with the 1999 level) has been 899 million litres. At this level of fuel saving, thereduction in the level of carbon dioxide released into the atmosphere has been 2,401 million kg.
b) Soil carbon sequestration
Applying the same rate of soil carbon retention for NT soybeans as Argentina, the cumulative
increase in soil carbon since 1999, due to the increase in NT in Bolivia, Paraguay and Uruguay
soybean production systems, has been 6,633 million kg of carbon. In terms of carbon dioxide
emission this equates to a saving of 24,342 million kg of carbon dioxide that may otherwise havebeen released into the atmosphere.
103

We are not aware of any country-specific studies into NT/RT systems in these three countries. However,analysts consulted in each country have confirmed that the availability of GM HT technology in soybeans has
been an important driver behind the use of NT/RT production systems. We have applied carbon change
assumptions in these countries based on findings from Argentina because this represents the only available
data from a neighbouring country. We acknowledge this represents a weakness to the analysis and thefindings should be treated with caution.

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4.2.4.5 Canada
During the period 1996 to 2008 period, tillage practices across the Canadian Prairies changed
considerable with RT/NT increasing from 20% to 55% of the crop area. The introduction of GM
HT soybeans in 1997 contributed to this transition, as well as, the doubling of the soybean croparea from 1.1 million ha in 1997 to 2 million ha in 2020. Within this, the NT soybean area
increased from 0.2 million ha in 1997 to 1.1 million ha in 2020 whilst the RT area increased from
0.3 million ha to 0.35 million ha and the CT area increased from 0.5 million ha to 0.57 million ha.
a) Fuel consumption
Using the fuel saving assumption identified for US soybeans and applying these to Canada, thesavings in fuel consumption for soybean production between 1997 and 2020 has been 255 million
litres. At this level of fuel saving, the reduction in the level of carbon dioxide released into theatmosphere has been 681 million kg.
b) Soil carbon sequestration
Applying the same carbon sequestration assumptions used for US soybeans, the cumulative
increase in soil carbon since 1997, due to the increase in NT soybean production systems, hasbeen 971 million kg of carbon. In terms of carbon dioxide emission this equates to a saving of
3,563 million kg of carbon dioxide that may otherwise have been released into the atmosphere.

4.2.5 Herbicide tolerant maize
4.2.5.1 The US
The area of maize cultivated in the US has fluctuated over the last 24 years between 30.6 millionha (2001) and 37.9 million ha (2007); in 2020 it was 33.4 million ha. Over the 1997-2020 period 104,
the maize area using CT with less than 15% crop residue fell by 75% (11.1 to 2.7 m ha), RT with
between 15-30% crop residue increased by 55% (7.8 to 12.1 m ha) and the NT with crop residue inexcess of 30% maize area increased by 39% (13.3 to 18.6 m ha) - Figure 75.

104

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GM crop impact: 1996-2020

Figure 75: US maize: crop area by tillage practices 1996-2020 (million ha)
25.00
20.00
15.00
10.00
5.00
0.00

NT

RT

CT

Adapted from Conservation Technology Information Center’s (CTIC) National Crop Residue Management
farm survey - https://www.ctic.org/CRM 1996-2004 & Operational Tillage Management System https://www.ctic.org/OpTIS based on remote sensing data for top five cropping states - Illinois, Iowa,
Nebraska, Indiana & Minnesota 2005-2020.

The most rapid rate of adoption of GM HT maize technology has been by growers using NT
systems (GM HT cultivars has accounted for more than 90% of the total NT maize since 2006).
This compares with CT systems for maize where GM HT cultivars account for 70% of total maize
plantings in 2020 - Figure 76.
Figure 76: US GM HT maize by tillage 1996-2020 (million ha)
35.00
30.00
25.00
20.00
15.00
10.00
5.00

GM HT area

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Non-GM

NT-GM

153

RT-GM

CT-GM

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0.00

GM crop impact: 1996-2020

a) Fuel consumption
Based on the maize crop area planted by tillage system, type of seed planted (biotech andconventional) and applying the fuel usage consumption rates presented in section 4.2.1 for maize,
the total consumption of tractor fuel between 1997 and 2020 has decreased by 6.9% (94.9 million
litres). Over the same period, the area planted to maize increased by 3.7%, highlighting a fall in
average fuel usage of 11% (from 42.6 litres/ha to 38.2 litres/ha). A comparison of GM HT versus
conventional production systems shows that in 2020, the average tillage fuel consumption on the
GM HT planted area was 36.9 litres/ha compared to 48.8 litres/ha for the conventional crop.
These changes to tillage fuel use and the resultant reduction on carbon dioxide emissions in US
maize for the 1996-2020 period are summarised in (Figure 77). The negative data for the period
1998 to 2004 illustrate the increase in carbon dioxide emissions resulting from the marginalincrease in the crop area. The cumulative permanent reduction in tillage fuel use in US maize is2,257 million litres which equates to a reduction in carbon dioxide emission of 6,027 million kg.
Figure 77: US maize permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1996-2020 (million kg)
700
561

600

582

554

500
400

312

300

375
290 309

362

390

418

565
395

438
323

384

388

200
100
0
-100
-200

-48

-75
-77
-111 -105 -110 -92

Note: The negative data for the period 1998 to 2004 illustrate the increase in carbon dioxide emissions
resulting from the marginal increase in the crop area and the proportion in CT.

b) Soil carbon sequestration
Based on and using estimates of the soil carbon sequestered by tillage system for maize andsoybeans in continuous rotation, the maize NT system is assumed to store 251 kg ofcarbon/ha/year, the RT system assumed to store 75 kg carbon/ha/year and the CT system
assumed to store 1 kg carbon/ha/year) 105. Based on these assumptions and using the crop area

105

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GM crop impact: 1996-2020

planted by tillage system and type of seed planted (GM HT and conventional), our estimates of
total soil carbon sequestered are:An increase of 1,630 million kg carbon/year (from 3,943 million kg in 1997 to 5,570 million
kg carbon/year in 2020) due to a combination of an increase in the crop area and the
NT/RT maize area;
The average amount of carbon sequestered per ha increased by 37.8% from 122.5 in 1997
to 166.9 kg carbon/ha/year in 2020.

••

Cumulatively, since 1997 the increase in soil carbon due to the increase in RT and NT in US maize
production systems has been 22,948 million kg of carbon which, in terms of carbon dioxide
emissions, equates to a saving of 84,218 million kg of carbon dioxide that would otherwise havebeen released into the atmosphere (Figure 78 and Appendix 6). This estimate does not take into
consideration the potential loss in carbon sequestration that might arise from a return toconventional tillage.
Figure 78: US maize - potential additional carbon dioxide sequestered 1996-2020 (million kg)
10,000
7,885

8,000
6,000

4,339

5,230
4,025
4,274

7,794

8,178

5,839
5,451
5,044

7,951
6,118

5,480
5,359

5,438

4,498

4,000
2,000
0
-2,000-4,000-673-1,080 -1,552 -1,546 -1,291-1,480-1,063

Note: The negative data for the period 1998 to 2004 illustrate the increase in carbon dioxide emissions
resulting from the marginal increase in the crop area and the proportion in CT

4.2.5.2 Canada
Against the background of increasing adoption of NT and RT (see section 4.2.4.5) and afluctuating maize area (1.4 million ha in 2020), the introduction and increasing adoption of GM
HT maize technology (from 1999) has facilitated a significant increase in the NT maize area from
0.3 million ha in 1999 to 0.77 million ha in 2020.
a) Fuel consumption
Using the US maize fuel saving assumptions (section 4.2.5.1), the saving in fuel consumption for
Canadian maize production between 1999 and 2020 (associated with changes in RT/NT systems,
the adoption of GM HT technology and comparing the proportion of NT maize in 2020 with the1999 level) has been 121.1 million litres. This level of fuel saving is equal to a reduction in thelevel of carbon dioxide released into the atmosphere of 323 million kg.

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GM crop impact: 1996-2020b) Soil carbon sequestration
Applying the US carbon sequestrations assumptions for maize to the Canadian crop, thecumulative increase in soil carbon since 1999 has been 330 million kg of carbon. In terms ofcarbon dioxide emission savings, this equates to 1,213 million kg of carbon dioxide that mayotherwise have been released into the atmosphere.
4.2.5.3 South America
In relation to both Argentina and Brazil it has not been possible to assess if the maize area in
NT/RT has increased due to the availability of GM HT maize because of a lack of relevant data.
However, the following should be noted:••

in Argentina, GM HT maize was first available for use in 2004, but seed containing thistrait did not account for more than 50% of the total crop until 2011 (98% of 2020 cropused the HT technology). Therefore, it is unlikely that the availability of GM HT
technology has played a significant role in the development of NT/RT farming in theArgentine maize crop;in Brazil, GM HT maize was first adopted on a widespread basis in 2011. Therefore, any
increase in the use of NT/RT in the maize sector up to this date cannot be attributed toany facilitating role of the technology.

4.2.6 Herbicide tolerant canola
The analysis presented below relates to Canada only and does not include the US GM HT canola
crop, as the area devoted to canola in the US is relatively small by comparison to the area in
Canada (0.72 million ha in the US in 2020 compared to 8.3 million ha in Canada).
Research identified that included examination of the impact of using GM HT technology incanola on carbon emissions includes:••

Smyth et al (2011) which surveyed 600 canola farmers in the three main canola growing
provinces of Western Canada in the years 2007-2009, to evaluate the environmental
impacts of the adoption of HT canola. As well as a reduction in the total number of
herbicide applications (resulting in a decrease of herbicide active ingredient being
applied), there were fewer tillage passes, improving moisture conservation, decreasing
soil erosion and a substantial contribution to carbon sequestration. This research
estimated that, by 2009, approximately 1 million tonnes of carbon (3.67 million tonnes ofcarbon dioxide) had either been sequestered or no longer released under land
management systems facilitated by HT canola production, as compared to 1995;
Awada et al (2014) identified that conservation tillage, notably NT, became profitable andpopular with the majority of Canadian arable farmers during and after the late 1990’s andattributed an important role in the adoption of NT to the availability of GM HT canola.
The increased use of NT contributed to a significant decrease in the area under summer
fallow and to the increase in the area sown to canola and pulse crops. These changes
contributed to the reduction of land degradation and to decreases in greenhouse gas(GHG) emissions.

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

a) Fuel consumption
Our estimate for the cumulative, permanent reduction in tillage fuel use in Canadian canola forthe period 1996-2020 is 1,067 million litres, which equates to a reduction in carbon dioxide
emissions of 2,848 million kg (Figure 79).
Figure 79: Canadian canola permanent reduction in carbon dioxide emissions resulting from a
reduction in fuel use 1997-2020 (million kg)
250
203

200

185

177

197 191192

219 216

197
200

154
150

123

100

78
44

50
12 13 13 11

87

136

103

58

18 23

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

0

b) Soil carbon sequestration
The analysis of soil carbon sequestration levels associated with GM HT canola in Canada is basedon the carbon sequestration co-efficient/assumptions derived by McConkey et al (2007). Our
analysis based on this research shows a cumulative increase in soil carbon storage, associatedwith RT and NT in Canadian canola production between 1996 and 2020, of 3,917 million kg ofcarbon, which in terms of carbon dioxide emissions, equates to a saving of 14,375 million kg ofcarbon dioxide that would otherwise have been released into the atmosphere (Figure 80).
Additional information is also provided in Appendix 6. Readers should note these estimates are
based on a soil sequestration rate of 55 kg carbon/ha/year which is significantly lower than therate used in the US for maize (250 kg carbon/ha/year) due to a combination of lower temperaturesand different soil types in the Canadian canola growing regions compared to the US.

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GM crop impact: 1996-2020

Figure 80: Canadian canola - potential additional carbon dioxide sequestered 1997-2020(million kg)
1,200
1,024
1,000

891

932

964

1,106
968

1,088
1,009 992

777

800
620
600

684

522
393

400
224
200

995

437

295

90 11758 65 66 58

04.2.7 Herbicide tolerant cotton
The contribution to reduced levels of carbon sequestration arising from the adoption of GM HT
cotton is likely to have been marginal and hence no assessments are presented. Although thearea of NT cotton has increased significantly in countries such as the US, NT cotton accounted for
only 18% of the crop area by 2015 (Claassen et al (2018)). Therefore, no analysis has been
undertaken relating to possible fuel usage and soil carbon sequestration savings associated withthe adoption of GM HT cotton in the US. However, the importance of GM HT cotton in
facilitating NT cotton tillage has been confirmed by Doane Marketing Research Conservation
Tillage Study 106 (2002) which identified the availability of GM HT cotton as a key driver for the
adoption of NT production practices.

4.2.8 Insect resistant cotton
The cultivation of GM IR cotton has resulted in a significant reduction in the number of
insecticide spray applications. Between 1996 and 2020, the global cotton area planted with GM IR
cultivars increased from 0.8 million ha to 23.2 million ha. Based on a conservative estimate offour fewer insecticide sprays being required for the cultivation of GM IR cotton relative toconventional cotton and applying this to the relevant global area (excluding Burkina Faso, China,
Pakistan, Myanmar, Sudan and India 107) of GM IR cotton over the period 1996-2020, suggests that
there has been a reduction of 339 million ha of cotton ‘spray’ area. The resulting cumulativesaving in tractor fuel consumption has been 285 million litres. This represents a permanent
reduction in carbon dioxide emissions of 760 million kg (Figure 81).

106

https://slideplayer.com/slide/7861322/

107

Excluded because all spraying is assumed to be undertaken by hand

©PG Economics Ltd 2022

158

GM crop impact: 1996-2020

Figure 81: Permanent reduction in global tractor fuel consumption and carbon dioxide
emissions resulting from the cultivation of GM IR cotton (1996-2020)
60

55
49 49

50
41 40

40

35

30
19

20
10

8

8

22 23

25
19 19

29

29
23

37

34

38

42

45

35

27

9

0

4.2.9 Insect resistant maize
Limited analysis of the possible contribution to reduced levels of carbon sequestration from theadoption of GM IR maize (via fewer insecticide spray runs) is presented. This is because theimpact of IR maize adoption on carbon sequestration is likely to have been small for thefollowing reasons:•••in some countries (eg, Argentina, Philippines) insecticide use for the control of pests
targeted by the technology (eg, corn borer pests) has traditionally been negligible;
even in countries where insecticide use for the control of relevant pests targeted by
the technology has been practised, the share of the total crop treated has been limited(eg, in the US about 10% and 30% respectively of the crop treated for corn borer androotworm pests);
Control practices for CRW in the US often includes the application of insecticides via
seed dressing.

4.2.9.1 Brazil
The impact of using GM IR maize in Brazil (since 2008) has resulted in farmers reducing the
average number of insecticide spray runs by three (from five to two). This equates to a cut of 439
million ha of maize being sprayed in the period 2008-2020, with a cumulative saving in tractor
fuel of 369 million litres. This is equivalent to a permanent reduction in carbon dioxide emissionsof 984 million kg.
4.2.9.2 US, Canada, South Africa and Spain
Our estimates of the fuel and carbon dioxide savings associated with reduced application of
insecticides with GM IR maize in these countries is based on historic patterns of insecticide
application and therefore limited to:©PG Economics Ltd 2022

159

GM crop impact: 1996-2020••

A maximum area equal to the lower of the GM IR area or 10% of the total crop in the US,
Canada and Spain;
The lower of the GM IR area (2 million ha (2020)) or 1.7 million ha in South Africa.

Assuming that there has been an average saving of one insecticide spray run on these areas eachyear since adoption of the technology, this equates to a reduction in the area sprayed over the
1996 to 2020 period of 108.2 million ‘spray’ ha. The resultant, cumulative saving in tractor fuelequates to 90.2 million litres, equivalent to a permanent reduction in carbon dioxide emissions of
243 million kg.

4.2.10 Insect resistant soybeans
IR soybean technology was first used commercially in South America in 2013, and in 2020 was
planted on 29.5 million ha in Argentina, Brazil, Paraguay and Uruguay. The adoption of thistechnology has enabled farmers to reduce the average number of insecticide spray applications
per ha by four in Brazil, two in Paraguay and one each in Argentina and Uruguay. The
cumulative saving in tractor fuel use over this period has, therefore been equal to 449 million
litres, equivalent to a permanent reduction in carbon dioxide emissions of 1,199 million kg.

4.2.11 Intensification of crop production
As well as the adoption of GM technology facilitating the reduction in level of greenhouse gas
emissions via reduced fuel use and additional soil carbon sequestration, the technology alsodelivers GHG emission benefits via the improvements in crop production. As indicated in
section 3, the adoption of GM technology has resulted in additional production from a
combination of higher yields and facilitation of second cropping of soybeans after a wheat crop in
South America.
Estimating the possible GHG emissions savings associated with this additional production is,
however, difficult due to the complex array of variables that impact on this and which vary bylocation. As such, no estimates are provided in this report. Nevertheless, the following points
are important to recognise in furthering the debate about the potential GHG emission impacts
associated with the use of GM crops and intensification of production:•••

Higher yielding crops assimilate more carbon dioxide into carbohydrate, oxygen andwater than lower yielding crops. Based on Lohry (1998) and applying to the 2020 level ofadditional global maize production (47.9 million tonnes) due to GM cultivars, thisadditional production assimilated about 144 million tonnes of carbon dioxide (which wasconverted by photosynthesis, sunlight, nutrients and water into oxygen and grain);
Increasing crop yields result in an increase in carbon inputs from crop residues into soils
which have a positive effect on soil carbon stocks (Berntsen et al (2006));
Improved yields and additional production from second cropping (of soybeans in SouthAmerica) effectively ‘replaces’ the need to extend crop production into new lands (which
will require the switching of land uses from other crops, grazing land and/or nonagricultural land converted into cropping of soybeans, maize, cotton and canola). Where
this land that would otherwise have been brought into agriculture remains in alternative©PG Economics Ltd 2022160

GM crop impact: 1996-2020

•

•

•

uses that sequester important levels of GHGs (eg, forestry), it is likely that the net effecton GHG emissions is positive;
Intensification of production is crucial if new land is not to be brought into production.
For example, analysis by Tilman et al (2011) into meeting projected global food demandby 2050 suggests that moderate intensification delivers significant (three-fold)greenhouse gas emission savings compared to a scenario of no additional intensification;
A question often posed about GHG emissions and more intensive agriculture is the scopefor additional usage of nitrogen resulting in higher levels of nitric oxide emissions morethan offsetting any carbon gains. Researchers such as Burney et al (2010 108) have,
however, concluded that intensification of agriculture leads to a net reduction in GHG
emissions even though fertiliser production and application tends to increase. A metaanalysis of 19 independent studies by van Groenigen et al (2011) also concluded that theaims of optimal agricultural production and low GHG emissions are consistent anddeliverable. In particular, emissions of nitrous oxide should be assessed as a function ofcrop nitrogen uptake and crop yield with nitrous oxide emissions tending to be stable inrespect of yield levels provided nitrogen is applied efficiently and without waste. In
addition, Katterera et al (2012) estimated that soil carbon stocks can increase by between
1kg-2kg of carbon for each kg of nitrogen fertiliser applied, with extensive production
systems tending to result in lower soil carbon stocks than more intensively managed
land; and
Maintaining optimum nitrogen fertilisation is considered to be critical for maintaining or
increasing the SOC in the Mid-West part of the US (Poffenbarger et al (2017)).

Overall, the GHG emission savings arising from both the direct impact and facilitating role of GM
technology (plus the productivity enhancing impact of the technology) ‘fits’ well with the global
need to sustainably intensify production systems.

4.2.12 Summary of carbon sequestration impacta) Reduced fuel use
The fuel savings arising from making fewer insecticide applications with the use of GM IR crop
technology in maize, cotton and soybeans and the switch from CT to RT/NT systems facilitatedby GM HT crops, have delivered permanent savings in carbon dioxide emissions. Over theperiod 1996 to 2020, the cumulative permanent reduction in fuel use has been about 39,147
million kg of carbon dioxide, arising from reduced fuel use of 14,662 million litres. In terms of car
equivalents, this is equal to taking 25.9 million cars off the road for a year (Table 29).
The largest fuel use-related reductions in carbon dioxide emissions have come from the adoptionof GM HT technology and how it has facilitated a switch to RT/NT production systems with their
reduced soil cultivation practices. This accounted for 92% of the fuel and carbon dioxide savingsin the period 1996-2020, within which GM HT soybeans accounted for the largest contribution(68% of the total savings). These savings have been greatest in South America.

108

Albeit examining the impact on GHG emissions from general intensification of agriculture between 1961

and 2005©PG Economics Ltd 2022

161

GM crop impact: 1996-2020

In 2020, the fuel related savings were 2,330 million kg of carbon dioxide, arising from reduced
fuel use of 948 million litres. These savings are equivalent to taking 1.68 million cars off the roadfor one year.
Table 29: Carbon storage/sequestration from reduced fuel use with GM crops 1996-2020
Crop/trait/country

Fuel saving(million litres)

Permanent carbon
dioxide savings arisingfrom reduced fuel use(million kg of carbon
dioxide)Permanent fuel savings:
as average family car
equivalents removed
from the road for a year(‘000s)HT soybeans
Argentina
4,433
11,837
7,844
Brazil
2,749
7,341
4,865
Bolivia, Paraguay, Uruguay
899
2,401
1,591
US
1,687
4,503
2,984
Canada255
681
451
HT maize
US
2,257
6,027
3,994
Canada121
323
214
HT canola
Canada: GM HT canola
1,067
2,848
1,887
IR maize
Brazil369
984
652
US/Canada/Spain/South
Africa91
243
161
IR cotton – global
285
760
504
IR soybeans – SouthAmerica
449
1,199
795
Total
14,662
39,14725,942
Notes:
1
Assumption: an average family car in 2020 produces 123.4 grams of carbon dioxide per km. A car
does an average of 12,231 km/year and therefore produces 1,509 kg of carbon dioxide/year
2
GM IR cotton. India, Pakistan, Myanmar and China excluded because insecticides assumed to be
applied by hand, using back pack sprayersb) Additional soil carbon storage/sequestration
The widespread adoption and maintenance of RT/NT production systems in North and SouthAmerica, has, as well as reducing tractor fuel use for tillage, enhanced soil quality and cut levelsof soil erosion. In turn, more carbon has remained stored in the soil leading to lower emissions ofcarbon dioxide.
Based on the areas of GM HT crops using RT/NT production systems in North and SouthAmerica in 2020, we estimate that an extra 5,750 million kg of soil carbon has been sequestered in2020. This is equivalent to 21,101 million kg of carbon dioxide that has not been released into theglobal atmosphere. In terms of removing vehicles from the road, these savings are equivalent totaking 14 million cars off the road for one year (Table 30).

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GM crop impact: 1996-2020

Table 30: Context of carbon sequestration impact 2020: car equivalents
Crop/trait/country

Additional carbon
stored in soil
(million kg ofcarbon)Potential
additional soil
carbonsequestration
savings (million
kg of carbon
dioxide)Soil carbon
sequestration savings: asaverage family car
equivalents removed
from the road for a year(‘000s)

1,832.5
1,485.0
490.7
110.9
62.9

6,725.2
5,450.1
1,800.8
407.0
230.7

4,445.8
3,611.0
1,193.1
269.6
152.9

1,481.6
15.6

5,437.6
57.4

3,602.7
38.0

270.4

992.4

657.5

0
0
0
0
5,749.6000021,101.1000013,980.7

HT soybeans
Argentina
BrazilBolivia, Paraguay, Uruguay
US
CanadaHT maize
US
CanadaHT canola
Canada: GM HT canola
IR maize
BrazilUS/Canada/Spain/South Africa
IR cotton – global
IR soybeans – South America
Total

If the annual estimates of soil carbon sequestration are aggregated over the 1996-2020 period,
then the additional amount of soil carbon sequestered since 1996 has been equivalent to 344,044
million kg of carbon dioxide that has not been released into the global atmosphere, equivalent totaking about 228 million cars off the road over this period. Readers should, however, note that
this estimate is likely to significantly overstate the true soil carbon sequestration benefits from theadoption of RT/NT systems over this 24 year period because some of the additional soil carbon
sequestration gains from RT/NT systems will have been lost from some subsequent ploughing ofland in these crops and production systems.
Estimating these possible losses that may arise from subsequent ploughing would be complex
and difficult to undertake. One study from the US (Claassen R et al (2018)) estimated thatapproximately 20% of the combined area of corn, soybeans, cotton and wheat in the USA were incontinuous NT/RT production systems during the period 2012-2016. This factor should therefore
be taken into account when using the estimates presented in this paper. In addition, it should be
noted that soil carbon savings are based on savings arising from the rapid adoption of RT/NT
farming systems, for which the availability of GM HT technology, has been cited by many
farmers as an important facilitator. GM HT technology has therefore probably been an important
contributor to this increase in soil carbon sequestration but is not the only factor of influence.
Other influences such as the availability of relatively cheap generic glyphosate (the real price ofglyphosate fell threefold between 1995 and 2000 once patent protection for the product expired)have also been important.

©PG Economics Ltd 2022163

GM crop impact: 1996-2020

Overall, it is not possible to confidently estimate cumulative soil sequestration gains that take
into account reversions to conventional tillage because of a lack of data.
Returning to the 2020 analysis of carbon emission savings from both sources of fuel related
savings and soil carbon storage, aggregating these benefits results in the total carbon dioxidesavings in 2020 being equal to about 23,631 million kg, equivalent to taking 15.6 million cars off
the road for a year. This is equal to 49% of registered cars in the UK.

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GM crop impact: 1996-2020

Appendix 1: Base yields used where GM technology
delivers a positive yield gain
In order to avoid over-stating the positive yield effect of GM technology (where studies haveidentified such an impact) when applied at a national level, average (national level) yields usedhave been adjusted downwards (see example below). Production levels based on these adjusted
levels were then cross checked with total production values based on reported average yields
across the total crop.
Example: GM IR cotton (2020)
Count
ry

Total
production(‘000
tonnes)

G
M
IR
are
a
(‘00
0
ha)

Conventi
onal area(‘000 ha)Assumed yield
effect of
GM IR
technology

Adjustedbaseyield forconventio
nalcotton(t/ha)

GM IR
production(‘000
tonnes)Conventi
onal
production (‘000
tonnes)

3,44
3,088
3
China
1.976
3,25
6,422
0
Note: Figures subject to rounding

3,0
30
3,0
87

413

+10%

0.906

2,746

340

162

+10%

1.805

6,130

293

US

Averageyield
acrossall
forms
ofproduction(t/ha)
0.897©PG Economics Ltd 2022

Tota
l
cott
on
area
(‘000
ha)

165

GM crop impact: 1996-2020

Appendix 2: Impacts, assumptions, rationale andsources for all trait/country combinations
Country

Yield
impactassumptio
n usedRationale

Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions+7% all
years

Broad
average ofimpactidentified
fromseveralstudies/pa
pers andlatestreview/ana
lysis
covering
1996-2010
period

As identified instudies to 2008
and onwards
based onweighted seedpremia according
to sale of seedsold as single andstacked traitedseed

As identified in studies to2005 and in subsequent
year adjusted to reflect
broad cost of ‘foregone’
insecticide use

Argentina+9% all
years to2004, +5.5%
2005
onwards

Average ofreported
impacts infirst sevenyears, later
reviseddownwards for more
recentyears toreflect
profession
al opinion

Cost oftechnology drawn
from Trigo (2002)
and Trigo & Cap(2006), ie,
costed/priced atsame level as US
From 2007 basedon Trigo andindustry personalcommunications

None as maize crops not
traditionally treated with
insecticides for cornboring pest damage

Philippines+24.6% to2006,

Average ofthree

Carpenter & Gianessi(2002) found yield
impacts of +9.4% 1997,+3% 1998, +2.5% 1999
Marra et al (2002)
average impact of +5.04%
1997-2000 based a review
of five studies, James(2003) average impact of+5.2% 1996-2002, Sankala& Blumenthal (2003 &2006) range of +3.1% to+9.9%. Hutchison et al(2010) +7% examining
impact over the period
1996-2010. Canada - nostudies identified – as US- impacts qualitatively
confirmed by industry
sources (annual personalcommunications)James (2003) cites two
unpublished industry
survey reports; one for
1996-1999 showing an
average yield gain of+10% and one for 20002003 showing a yieldgain of +8%, Trigo (2002)
Trigo & Cap (2006) +10%,
Trigo (2007 & 2008)
personal communication
estimates average yield
impact since 2005 to belower at between +5%
and +6%
Gonzales (2005) foundaverage yield impact ofBased onGonzales (2005) &Based on Gonzales (2005)& Gonzales (2009)

GM IR
maize:
resistantto cornboringpests
US &Canada©PG Economics Ltd 2022

166

GM crop impact: 1996-2020

2007onwar
d +18%

studiesused allyears to2006.
Thereafter
based onGonzaleset al (2009)South
Africa+11% 2000& 2001+32% 2002+16% 2003+5% 2004+15% 20052007,+10.6%
2008
onwards

Spain

+6.3%
1998-2004+10% 20052008. 2009
onwards+12.6%

Reported
average
impactsused foryears
available(20002004),
2005-2007
based onaverage ofotheryears.
2008
onwards
based onVan derWeld(2009)
Impactbased onauthorsown
detailed,
representat
ive
analysis forperiod1998-2002
then
updated toreflect
improved
technology
based onindustry
analysis.
From 2009
based onRiesgo et al(2012)©PG Economics Ltd 2022

+23% dry season crops &+20% wet season crops;
Yorobe (2004) +38% dry
season crops & +35% wet
season crops; Ramon(2005) found +15.3% dry
season crops & +13.3%
wet season crops.
Gonzales et al (2009)+18%
Gouse et al (2005), Gouse
et al (2006 a) & b)
reported yield impacts asshown (range of +11% to+32%), Van der Weld
(2009)

Brookes (2003) identified
an average of +6.3%
using the Bt 176 trait
mainly used in the
period 1998-2004 (range+1% to +40% for theperiod 1998-2002). From
2005, 10% used based on
Brookes (2008) which
derived from industry(unpublished sources)
commercial scale trials
and monitoring of impactof the newer, dominant
trait Mon 810 in the
period 2003-2007.
Gomez Barbero &Rodriguez-Corejo (2006)
reported an average
impact of +5% for Bt 176
used in 2002-2004.
Riesgo et al (2012) +12.6%
identified as average
yield gain

167

Gonzales (2009) –the only sources
to break downthese costs. Seedpremia from 2012
based on based onweighted cost of
seed sold as single
and stacked traits
Based on the same
papers as used foryield, plus
confirmation in
2006-2011 thatthese arerepresentativevalues fromindustry sources

Sources as for cost oftechnology

Based on Brookes(2003) the only
source to break
down these costs.
The more recent
cost of technology
comes fromindustry sources(reflecting the useof Mon 810
technology).
Industry sources
also confirm value
for insecticide costsavings as being
representative.
From 2009, basedon Riesgo et al(2012) and
Brookes (2019)

Sources as for cost oftechnology

GM crop impact: 1996-2020

Other EU

Portugal+12.5%

UruguayAs
Argentina

Impacts
based onaverage ofavailable
impactdata ineach
countryAs
Argentina

Paraguay

As
Argentina

As
Argentina

Brazil+4.66%
2008, +7.3%
2009 &
2010,+20.1%
2011,+14.6%
2012,+11.1%
2013
onwards+13% 20032006+24% 2007
onwardFarmersurveys

Honduras

Colombia+22% 20072012, +16%
onwards

Vietnam+10.22%©PG Economics Ltd 2022

Based on Brookes (2008)
and Brookes (2019) whichdrew on commercial trial
and plot monitoring
reported +12% in 2005
and between +8% and+17% in 2006

Data derived fromthe same source(s)referred to foryield

Data derived from thesame source(s) referred
to for yieldNo country-specificstudies identified, so
impact analysis fromnearest country of
relevance (Argentina)
appliedNo country-specificstudies identified, so
impact analysis fromnearest country of
relevance (Argentina)
appliedGalvão A (2009, 2010,2012, 2013, 2014, 2016)

As Argentina

As Argentina

As Argentina

As Argentina

Data derived fromthe samereferences as citedfor yield impacts.
Seed premium
based onweighted averageof seed sales

Data derived from thesame references as citedfor yield impacts

A proxy seedpremium of$30/ha usedduring trials (to2005) based onseed premia in S
Africa and thePhilippines. From2006 whencommercialised
based on industry
sources
Mendez et al(2011) and
Brookes (2020)

Nil – no insecticide
assumed to be used onconventional crops

Trialsresults
2002 andfarmersurveyfindings in
2007-2008

James (2003) cited trials
results for 2002 with a
13% yield increase
Falk Zepeda J et al (2009and 2012) +24%

Mendez etal (2011)
andBrookes(2020)
Brookes(2017),
Brookesand Dinh(2021)

Mendez et al (2011) farmsurvey from 2009.
Brookes draws on 2015
and 2017 farmer surveys
conducted by Celeres
Brookes (2017), Brookes
and Dinh (2021)

168

Brookes (2017),
Brookes and Dinh
(2021)

Mendez et al (2011) and
Brookes (2020)

Brookes (2017), Brookes
and Dinh (2021)

GM crop impact: 1996-2020

GM IR
maize
(resistant
to cornrootworm)
US &CanadaYield
impactassumptio
n usedRationale

Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions+5% allyears

Based onthe impact
used bythereferences
cited

Data derived from
Sankala &Blumenthal (2006)
and Johnson S &Strom S (2008).
Seed costs 2008
onwards based onweighted seedsales of single andstacked traits
Canada - nostudies identified– as US - impacts
qualitatively
confirmed byindustry sources

As identified in studies to2005 and in subsequent
year adjusted to reflect
broad cost of ‘foregone’
insecticide use

IR cotton

Yield
impactassumptio
n used
+9% 19962002+11% 2003& 2004+10% 2005
onwards

Rationale

Sankala & Blumenthal(2003 & 2006) used +5%
in analysis citing this asconservative, themselves
having cited impacts of+12%-+19% in 2005 in
Iowa, +26% in Illinois in2005 and +4%-+8% in
Illinois in 2004. Johnson
S & Strom S (2008) used
the same basis as Sankala& Blumenthal
Rice (2004) range of+1.4% to +4.5% (based ontrials)Canada - no studies
identified – as US impacts qualitatively
confirmed by industry
sources (personalcommunications 2005,
2007 & 2010)
Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

Sankala & Blumenthal(2003 & (2006) drew on
earlier work from
Carpenter and Gianessi(2002) in which they
estimated the average
yield benefit in the 19962000 period was +9%.
Marra et al (2002)
examined the findings ofover 40 state-specificstudies covering theperiod 1996 up to 2000,
the approximate average
yield impact was +11%.
The lower of these twovalues was used for theperiod to 2002. The
higher values applied
from 2003 reflect values
used by Sankala &Blumenthal (2006) andData derived fromthe same sourcesreferred to foryield and updated
from 2008 basedon industry
sources (for theestimated share of
the insect
resistance trait in
the total seedpremia forstacked traitedseed

As identified in yieldstudy references and in
subsequent years
adjusted to reflect broad
cost of ‘foregone’
insecticide use

US©PG Economics Ltd 2022

Based onthe(conservative) impact
used bythereferences
cited

169

GM crop impact: 1996-2020

China+8% 19972001+10% 2002
onwards

Australia

None

Argentina+30% allyears©PG Economics Ltd 2022

Average ofstudiesused to2001.
Increase to
10% onbasis ofindustry
assessment
s of impact
andreportingof
unpublishe
d work by
SchuchanStudieshaveusually
identified
nosignificant
averageyield gainMore
conservati
ve of thetwo pieces
of researchusedJohnson & Strom (2008)
that take into account theincreasing use of
Bollgard II technology,
and draws on work by
Mullins & Hudson (2004)
that identified a yieldgain of +12% relative toconventional cotton. The
values applied 2005
onwards were adjusted
downwards to reflect thefact that some of the GM
IR cotton area has still
been planted to Bollgard
I
Pray et al (2002)
surveyed farm level
impact for the years 19992001 and identified yield
impacts of +5.8% in 1999,+8% in 2000 and +10.9%
in 2001
Monsanto China
personal
communications (20072014)

Fitt (2001)
Doyle (2005)
James (2002)
CSIRO (2005)

Qaim & De Janvry (2002& 2005) analysis based onfarm level analysis in
1999/00 and 2000/01+35% yield gain, Trigo &Cap (2006) used an

170

Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield

Data derived fromthe same sourcesreferred to foryield covering
earlier years ofadoption, then
CSIRO for later
years. For 20062009 cost oftechnology values
confirmed bypersonal
communicationfrom MonsantoAustralia
Data derived fromthe same sourcesreferred to foryield. Cost oftechnology all

Data derived from thesame sources referred tofor yield covering earlier
years of adoption, then
CSIRO for later years

Data derived from thesame sources referred tofor yield and cost oftechnology.

GM crop impact: 1996-2020

South
Africa+24% allyears

Lower endofestimates
appliedMexico+37% 1996+3% 1997+20% 1998+27% 1999+17% 2000+9% 2001+6.7% 2002
+6.4% 2003
+7.6% 2004
+9.25%
2005+9% 2006+9.28 2007
& 2008,+14.2%
2009,+10.34%2010 and
2011, +7.2%
2012,+8.95%
2013,+15.8%
2014 15%2015,+10.54%2016,+10.3%
2017 and2018+45% 2002+63% 2003+54% 2004+64% 2005+50% 2006& 2007

Recordedyield
impactdata usedasavailable
for almost
all years

India©PG Economics Ltd 2022

Recordedyield
impactused for
years
where
available

average gain of +30%
based on work by Elena(2001)
Ismael et al (2001)
identified yield gain of+24% for the years
1998/99 & 1999/2000.
Kirsten et al (2002) for
2000/01 season found arange of +14% (drycrops/large farms) to+49% (small farmers)
James (2002) also cited arange of impact between+27% and +48% during
the years 1999-2001
The yield impact data for1997 and 1998 is drawn
from the findings of farmlevel survey work by
Traxler et al (2001). For
all other years the data isbased on the annual crop
monitoring reports
submitted to the Mexican
Ministry of Agriculture
by Monsanto Mexico

Yield impact data 2002
and 2003 is drawn from
Bennett et al (2004), for2004 the average of 2002
and 2003 was used. 2005
and 2006 are derived
from IMRB (2006 &171

years based on
industry sources
Data derived fromthe same sourcesreferred to foryield. Values forcost of technology
and cost of
insecticide costsavings also
provided/confirm
ed from industry
sources

Data derived from thesame sources referred tofor yield.

Data derived fromthe same sourcesreferred to foryield. 2009
onwards seed costbased onweighted averageof single andstacked traited
seed sales

Data derived from thesame sources referred tofor yield.

Data derived fromthe same sourcesreferred to foryield. 2007
onwards cost oftechnology based

Data derived from thesame sources referred tofor yield. 2007 onwards
cost savings based on
industry estimates and
AMIS Global pesticide
usage data (2011)

GM crop impact: 1996-2020+40% 2008,+35% 2009& 2010,+30% 2011,+24% 2012
onwards

BrazilColombia

Burkina
Faso

Pakistan

MyanmarGM HT
soybeans

US: 1stgeneration+6.23%
2006-3.6% 2007
-2.7% 2008,-3.8% 2009,2010 nil2011+3.04%,
2012 -1.8%,
2013 +2.4%,
2014
onwards+2.38%+36.3%
2002. 2009
onwards+20.7%

Recordedyield
impacts foreach year –2013 notavailable
so 2012value
assumed+20 2008,+18.9%
2009
onwards+12.6%
2009, 2010
onwards+22%+30%

Trials 2008,
farm
survey2009
FarmsurveysYield
impactassumptio
n usedNil©PG Economics Ltd 2022

Farm
survey2007s, 2015
and 2017

2007). 2007 impact data
based on lower end of
range of impacts
identified in previous 3
years (2007 being a yearof similar pest pressure
to 2006). 2008 onwards
based on assessments ofgeneral levels of pestpressure Industry
sources), Herring andRao (2012) and Kathage,
Jonas and Qaim (2012)2006 unpublished farmsurvey data – source:
Monsanto (2008)
2007- 2010 farm survey
data from Galvão (2009,2010, 2012, 2013, 2015))

Based on Zambrano P etal (2009) and Brookes(2020) – drawing on farmsurveys by Celeres 2015
and 2017
Vitale J et al (2008) &Vitale J et al (2010)

Nazli H et al (2010),
Kouser and Qaim (2013)

Extension
serviceestimates
Rationale

USDA (2011)

Not
relevant

Not relevant

Yield references172

on industry
sources

Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield

Zambrano (2009),
Brookes (2020)

Zambrano (2009),
Brookes (2020)

Based on Vitale J
et al (2008 & 2010)

Based on Vitale J et al(2008 & 2010)

Based on datafrom same
sources as yield
impacts
No data available
so based on India
and Pakistan
Cost oftechnology
data/assumptions

Based on data from same
sources as yield impacts

Marra et al (2002)
Carpenter &Gianessi (2002)
Sankala &Blumenthal (2000& 2006)

No data available sobased on Pakistan
Cost savings (excluding
impact of seedpremium) assumptions
Marra et al (2002)
Carpenter & Gianessi(2002)Sankala & Blumenthal(2000 & 2006)

GM crop impact: 1996-2020

Canada: 1stgeneration

Nil

Not
relevant

Not relevant

US &Canada:2nd
generation+5% 2009
and 2010,+10.4%
2011,+11.2%
2012, +11%
2013, +9%2014
onwards
8.9%
Nil but
secondcropbenefits

Farm levelmonitoring
and farmer
feedback

Monsanto farmer surveys(annual)Not
relevant
except 2nd
crop – seeseparate
table
Not
relevant

Not relevantNot
relevant
except 2ndcrop

Not relevant

Argentina

BrazilNil

Paraguay

Nil but
secondcropbenefits©PG Economics Ltd 2022

Not relevant

173

Johnson S &Strom S (2008) &updated post 2008
from industry
estimates of seedpremiaGeorge MorrisCenter (2004) &updated from2008 based on
industry estimatesof seed premia
Industry estimatesof seed premia
relative to 1st
generation GM
HT seedJohnson S & Strom S(2008) & updated post2008 to reflect herbicide
price and common
product usage

Qaim & Traxler(2005), Trigo &CAP (2006) and2006 onwards(Monsanto royalty
rate)
As Argentina to
2002 (illegal
plantings). Thenbased on Parana
Department ofAgriculture(2004). Also
agreed royalty
rates from 2004
applied to all
years to 2006.
2007 onwards
based on Galvão
(2009, 2010, 2012,2013 and 2015)

Qaim & Traxler (2005),
Trigo & CAP (2006),
Rodriguez et al (2021) &updated from 2008 toreflect herbicide pricechanges
Sources as in cost oftechnology

As Argentina: nocountry-specificanalysisidentified.
Impacts
confirmed fromindustry sources(annual personalcommunications

As Argentina – herbicide
cost differences adjusted
post 2008 based on
industry sources and
AMIS Global, Kleffmannherbicide usage data
2011, 2013, 2015, 2016

George Morris Center(2004), Ontario Ministryof Agriculture & updated
for 2008 to reflectherbicide price changes
as 1st generation

GM crop impact: 1996-2020

2006-2012). Seed
cost based on
royalty rate since2007
No studies
identified. Seedpremia based on
industry sources(annually
updated)South
AfricaNil

Notrelevant

Not relevant

UruguayNilNotrelevant

Not relevant

As Argentina: nocountry-specificanalysisidentified. Seedpremia based on
industry sources

Mexico+9.1% 2004
&2005
+3.64%
2006+3.2% 2007
+2.4% 2008+13% 2009,+4% 20102-12, +9.9%
2013, -2.1%
2014, 0.75% 2015,-1.87%
2016+31%, 15%
2006

Recordedyield
impactfromstudies

From Monsanto annual
monitoring reports
submitted to Ministry ofAgriculture

No publishedstudies identified
based onMonsanto annual
monitoring
reports

Based ononly
available
study
covering
1999-2003(note notgrown in2007) plus
2006 farmsurveyBased onsurvey in
2007-08

For previous year – basedon Brookes (2005) – theonly published source
identified. Also,
Monsanto Romania(2007)

Brookes (2005)
Monsanto
Romania (2007)

Brookes (2005)
Monsanto Romania(2007)

Fernandez W et al (2009)
farm survey

Fernandez W et al(2009)

Fernandez W et al (2009)

Farm trials
and post
marketMonsanto farm trials andcommercial crop
monitoring (surveys)

As yield source
and Kleffmann

As yield source andKleffmann

Romania

Bolivia

GM HT &
IR
soybeansBrazil+15%+9.6% 2013,+9.1% 2014,©PG Economics Ltd 2022

174

No studies identified.
Based on industry
estimates (annually
updated) and AMIS
Global/Kleffmannherbicide usage data
2011, 2013, 2015, 2016
As Argentina: nocountry-specific analysis
identified. Impacts basedon industry sources and
AMIS Global/Kleffmannherbicide usage data
2011, 2013, 2015, 2016
No published studies
identified based on
Monsanto annual
monitoring reports

GM crop impact: 1996-2020

monitoring
surveyAs Brazil

US

9.4% 2015
onwards+9.1% 2013,+7.8% 2014,
7.1% 2015
onwards+12.8%
2013,+11.9%
2014, 9.1%
2015, 12.3%
2016, 11.5%
2017 and2018+8.8% 2013,+7.8% 2014,
7% 2015
onwards
Yield
impactassumptio
n usedNil

CanadaArgentina:
sold assingle trait

Argentina

Paraguay

Uruguay

GM HT
corn

Monsanto farm trials andcommercial crop
monitoring (surveys)

As yield source
and Kleffmann

As yield source andKleffmann

As Brazil

Monsanto farm trials andcommercial crop
monitoring (surveys)

As yield source

As yield source andKleffmann

As Brazil

Monsanto farm trials andcommercial crop
monitoring (surveys)

As yield source

As yield source andKleffmann

Rationale

Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

Not
relevant

Not relevant

Carpenter & Gianessi(2002)Sankala & Blumenthal(2003 & 2006)
Johnson S & Strom S(2008). 2009 onwards
updated to reflectchanges in common
herbicide treatments andpricesNil

Notrelevant

Not relevant

Carpenter &Gianessi (2002)
Sankala &Blumenthal (2003& 2006)
Johnson S &Strom S (2008).
2008 and 2009
onwards based onweighted seedsales (sold assingle and stacked
traits)No studies
identified – basedon annual
personal
communications
with industry
sources+3% cornbelt+22%
marginal
areas

Based ononly
available
analysis Corn Belt =70% ofplantings,
marginal
areas 30% -No studies identified –based on personalcommunications withindustry sources in 2007
and 2008 MonsantoArgentina & Grupo CEO(personal
communications 2007,2008 & 2011)©PG Economics Ltd 2022

175

Industry estimatesof seed premia
and weighted byseed sales
according towhether
containing single
or stacked traits

No studies identified –based on industry andextension service
estimates of herbicide
regimes and updated
since 2008 on the basis ofchanges in herbicide
price changes
No studies identified based on MonsantoArgentina & Grupo CEO(personal
communications 2007 &2008). 2008 & 2009
updated to reflectherbicide price changes

GM crop impact: 1996-2020

industry
analysis(note nosignificant
plantings
until 2006)
Farmerlevel
feedback toseedsuppliers

Argentina:
sold asstackedtrait+10.25%South
AfricaNil

Notrelevant

Philippines+15% 2006
and 2007,+5% 2008
onwards

Farm
surveyBased on unpublishedindustry analysis for 2006
&2007, thereafter
Gonsales L et al (2009)

BrazilFarm
surveyGalvão (2010, 2012, 2013,2015))

Colombia+2.5% 2010
+3.6% 2011.
+6.84%
2012 and2013, +3%
2014
onwards
Zero

Mendez etal (2011),
Brookes(2020)

UruguayZeroNotrelevant

Mendez et al (2011) farmsurvey from 2009 andCeleres farmer surveys
2015 and 2017 (seeBrookes 2020)
Not relevantParaguay

ZeroNotrelevant©PG Economics Ltd 2022

Unpublished farm level
survey feedback to
Monsanto: +15.75% yield
impact overall – forpurposes of this analysis,
5.5% allocated to IR trait
and balance to HT trait
Not relevant

Not relevant

176

As single trait

As single trait

Industry sources –annual checked

No studies identified based on Monsanto S
Africa (personalcommunications 2005,
2007 & 2008). 2008
onwards updated toreflect herbicide pricechangesMonsanto Philippines(personal
communications 2007 &2008). Gonsales L et al(2009). 2010 onwards
updated annually toreflect changes inherbicide costs

Monsanto
Philippines(personal
communications
2007 & 2008).
Gonsales L et al(2009). 2010
updated to reflectchanges in seed
costs
Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield plus AMIS
Global herbicide use data

Mendez et al(2011), Brookes(2020)

Mendez et al (2011),
Brookes (2020)

No studies
available – basedon Argentina

No studies available –based on Argentina plus
annual AMIS
Global/Kleffmannherbicide use data
No studies available –based on Argentina plus
annual AMIS

No studies
available – basedon Argentina

GM crop impact: 1996-2020

Brookes (2017)

Brookes (2017)

Global/Kleffmannherbicide use data
Brookes (2017)

Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

Not
relevant

Not relevant

Carpenter & Gianessi)
Sankala & Blumenthal(2003 & 2006)
Johnson S & Strom S(2008) and updated from2008 to reflect changes in
weed control practices
and prices of herbicides

Nil

Not
relevant

Not relevant

South
AfricaNil

Notrelevant

Not relevant

Argentina

Nil on area
using farmsaved seed,+9.3% onarea using
certified
seed

Based ononly
available
data –
company
monitoringofcommercia
l plots

No studies identified –based on personalcommunications with
Grupo CEO andMonsanto Argentina(2007, 2008, 2012)

Mexico+3.6% allyears to2007
0% 2008,+5.11%
2009,+18.1%

Based onannualmonitoring
reports to
Ministry ofAgricultur
e bySame as source for cost
data

Carpenter &Gianessi)
Sankala &Blumenthal (2003& 2006)
Johnson S &Strom S (2008)
and updated from2008 based onweighted seedsales (by single
and stacked
traited seed)
Doyle et al (2003)
Monsanto
Australia(personal
communications
2005, 2007, 2009,2010 and 2012)
No studies
identified - basedon Monsanto S
Africa (personalcommunications
2005, 2007, 2008,2010 and 2012)
No publishedstudies identified– based on
personal
communications
with Grupo CEO
and MonsantoArgentina (2007,2008 & 2010 and
2012)
No publishedstudies identified- based on
personal
communications
with MonsantoVietnam+5%

GM HT
CottonUS

Yield
impactassumptio
n usedNilAustralia©PG Economics Ltd 2022

Brookes(2017)
Rationale

177

Doyle et al (2003)
Monsanto Australia(personal
communications 2005,
2007, 2009, 2010, 2012),
2016
No studies identified based on Monsanto S
Africa (personalcommunications 2005,
2007, 2008, 2010, 2012,2016)
No published studies
identified – based on
personal
communications with
Grupo CEO andMonsanto Argentina(2007, 2008 & 2010, 2012,2013, 2016)

No published studies
identified - based on
annual personalcommunications with
Monsanto Mexico andtheir annual reportingGM crop impact: 1996-2020

Colombia
BrazilGM HT
canolaUS

Canada2010, +5.1%
2011,+13.1%
2012,+14.2%
2013,+13.3%
2014,+19.6%
2015 and2016, +16%
2017-20+4%+2.35%
2010+3.1% 2011,-1.8% 2012,+1.6% 2013,+1.6% 2014
onwards
Yield
impactassumptio
n used+6% all
years to2004. Post
2004 basedon Canada– see below+10.7% all
years to2004. Post
2004; forGM
glyphosate
tolerant
varieties
no yielddifference
2004, 2005,
2008, 2010

©PG Economics Ltd 2022

Monsanto
MexicoBrookes(2020)
Farm
surveyMexico and theirannual reporting

Brookes (2020)

Brookes (2020)

Brookes (2020)Galvão (2010, 2012, 2013,2015)

Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield

Rationale

Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

Based onthe only
identified
impactanalysis –post 2004
based onCanadian
impacts as
samealternative(conventio
nal HT)
technology
to Canadaavailable
After 2004
based ondifferences
betweenaverageannualvariety
trial resultsforClearfields(non GM
herbicide

Same as for cost data

Sankala &Blumenthal (2003& 2006))
Johnson S &Strom S (2008).
These are the only
studies identified
that examine GM
HT canola in the
US. Updated
based on industry
and extension
service estimates

Sankala & Blumenthal(2003 & 2006))
Johnson S & Strom S(2008). These are the only
studies identified thatexamine GM HT canolain the US. Updated since2008 based on changes inherbicide prices

Same as for cost data

Based on Canola
Council (2001) to2003 thenadjusted to reflect
main current non
GM (HT)
alternative of‘Clearfields’ –data derived frompersonal
communications
with the Canola

Based on Canola Council(2001) to 2003 thenadjusted to reflect maincurrent non GM (HT)alternative of‘Clearfields’ – data
derived from personalcommunications with theCanola Council (2008)
plus Gusta M et al (2009)
which includes spillover
benefits of $ Can13.49 to178

GM crop impact: 1996-2020

Australia

GM HT
sugar beet
US &Canada+4% 2006
and 2007,+1.67%
2009, +1.6%
2011, +1.5%
2012, +3.1%
2013, +3.4%
2014, +4.3%
2015, +2.6%
2016 ForGM
glufosinate
tolerant
varieties:+12% 2004,+19% 2005,+10% 2006& 2007+12% 2008+11.8%
2009,+10.9%
2010, +4.6%
2011, +4.8%
2012,+10.1%
2013, +11%2014,
+11.6%
2015, +7.3%
2016+21.08%2008,+20.9%
2009,+15.8%
2010, +7.6%
2011 and2012, +11%
2013-2015,+8% 2016
onwards

tolerant
varieties)
and GM
alternatives. GMalternativesdifferentiat
ed intoglyphosate
tolerant
andglufosinate
tolerant

Surveybased withaverageyield gain
based onweightingyield gains
fordifferent
types ofseed byseed sales
or numberof farmers
using
different
seed types

Based on survey oflicence holders by
Monsanto Australia,
Fischer and Tozer (2009)
and Hudson andRichards (2014)+12.58%2007

Farm
survey &extension

Kniss (2008)
Khan (2008)©PG Economics Ltd 2022

179

Council (2008)
plus Gusta M et al(2009)

follow on crops – applied
from 2006. Also adjusted
annually to reflectchanges in typicalherbicides used on
different crops (GM HT,
conventional, Clearfields)

Sources as foryield changes

Sources as for yieldchanges

Kniss A (2008)
Khan M (2008),

Kniss A (2010)
Khan M (2008), JonJoseph A and Sprague C

GM crop impact: 1996-2020

GM VR
crops US
PapayaSquash

+2.8% 2008
+3.3%
2009-2012,+3.1% 2013,+3.2% 2014,+3.55%
2015,+3.58%
2016,+3.25%
2017 and2018

serviceanalysis(2010) and updated
annually to reflectchanges in herbicide
usage and prices

between+15% and+77% 19992012 –relative tobase yieldof 22.86
t/ha+100% onarea
plantedBased onaverageyield in 3
years
before firstuse

Draws on only publishedsource disaggregating tothis aspect of impact

Sankala &Blumenthal (2003& 2006), Johnson S& Strom S (2008

Nil – no effective
conventional method ofprotection

assumesvirus
otherwise
destroyscrop onplantedarea

Draws on only publishedsource disaggregating tothis aspect of impact

Sankala &Blumenthal (2003& 2006), Johnson S& Strom S (2008

Sankala & Blumenthal(2003 & 2006), Johnson S& Strom S (2008) andupdating of these from2008

Readers should note that the assumptions are drawn from the references cited supplemented andupdated by industry sources (where the authors have not been able to identify specific studies).
This has been particularly of relevance for some of the herbicide tolerant traits more recently
adopted in several developing countries. Accordingly, the authors are grateful to industry
sources which have provided information on impact, (notably on cost of the technology andimpact on costs of crop protection). Whilst this information does not derive from detailed
studies, the authors are confident that it is reasonably representative of average impacts; in a
number of cases, information provided from industry sources via personal communications has
suggested levels of average impact that are lower than that identified in independent studies.
Where this has occurred, the more conservative (industry source) data has been used.
Second soybean crop benefits: Argentina
An additional farm income benefit that many Argentine soybean growers have derived comesfrom the additional scope for second cropping of soybeans. This has arisen because of thesimplicity, ease and weed management flexibility provided by the (GM) technology which has
been an important factor facilitating the use of no and reduced tillage production systems. In
turn the adoption of low/no tillage production systems has reduced the time required for
harvesting and drilling subsequent crops and hence has enabled many Argentine farmers tocultivate two crops (wheat followed by soybeans) in one season. As such, the proportion of©PG Economics Ltd 2022

180

GM crop impact: 1996-2020

soybean production in Argentina using no or low tillage methods has increased from 34% in 1996
to 90% by 2005 and has remained at over 90% since then.
Farm level income impact of using GM HT soybeans in Argentina 1996-2020 (2): second crop
soybeans
Year

Second crop area
(million ha)
0.45
0.20
0.35
0.95
1.15
2.2
2.6
2.75
3.0
2.3
3.2
4.9
3.35
3.55
4.4
4.6
3.22
3.0
4.0
3.65
4.15
4.02
4.6
5.37
5.27

Average gross margin/ha forsecond crop soybeans ($/ha)
128.78127.20125.24122.76125.38124.00143.32151.33226.04228.99218.40229.36224.87207.24257.69257.40291.00289.80195.91
168.81
153.75164.40154.19323.80269.80

Increase in income linked to
GM HT system (million $)Negligible
25.4
43.8
116.6
144.2
272.8
372.6
416.1
678.1
526.7
698.9
1.133.6754.1
735.7
1,133.8
1,184.0
938.6
879.4
777.1
616.4
637.8
660.4
713.1
1,738.1
1,422.4

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Source & notes:
1. Crop areas and gross margin data based on data supplied by Grupo CEO and the Argentine
Ministry of Agriculture. No data available before 2000, hence 2001 data applied to earlier years but
adjusted, based on GDP deflator rates
2. The second cropping benefits are based on the gross margin derived from second crop soybeansmultiplied by the total area of second crop soybeans (less an assumed area of second crop soybeansthat equals the second crop area in 1996 – this was discontinued from 2004 because of theimportance farmers attach to the GM HT system in facilitating them remaining in no tillage
production systems)©PG Economics Ltd 2022

181

GM crop impact: 1996-2020

Appendix 3: Additional information relating to theenvironmental impact: example comparisons
US Soybeans: typical herbicide regimes for conventional no tillage production systems: MidWest
Option 1
Glyphosate
24D
Flumioxazin
Chlorimuron
Lactofen
Clethodim
Total
Option 2
Glyphosate
24D
Flumioxazin
Chlorimuron
Thifensulfuron
Fomesafen
Clethodim
Total
Option 3
Glyphosate
24D
Sulfentrazone
Cloransulam
Clethodim
S Metalochlor
Total

Active ingredient (kg/ha)

Field EIQ/ha value

1.30
0.64
0.07
0.02
0.22
0.16
2.42

19.93
9.79
1.68
0.38
6.28
2.67
40.72

1.30
0.64
0.07
0.02
0.01
0.29
0.16
2.49

19.93
9.79
1.74
0.38
0.11
7.13
2.67
41.79

1.30
0.64
0.20
0.03
0.16
1.43
3.75

19.93
9.79
2.39
0.39
2.89
31.46
66.62

US Soybeans: typical herbicide regimes for conventional no tillage production systems: South
Option 1
Glyphosate
24D
Flumioxazin
Metalochlor
Fomesafen
Clethodim
Total
Option 2
Glyphosate
24D
Flumioxazin
Chlorimuron
Fomesafen
Clethodim
Total©PG Economics Ltd 2022

Active ingredient (kg/ha)

Field EIQ/ha value

1.13
0.64
0.07
1.36
0.30
0.16
3.66

17.35
9.79
1.72
29.97
7.32
2.67
68.82

1.13
0.64
0.09
0.02
0.37
0.16
2.41

17.35
9.79
2.07
0.47
9.03
2.67
41.37

182

GM crop impact: 1996-2020

Option 3
Glyphosate
24D
Metalochlor
Fomesafen
Acifloren
S Metalochlor
Clethodim
Total

1.13
0.64
1.36
0.30
0.30
1.32
0.11
5.17

17.35
9.79
29.97
7.32
7.13
29.09
1.91
102.56

US Soybeans: typical herbicide regimes for conventional crop and tillage production systems:
South
Option 1
Flumioxazin
Metalochlor
Fomesafen
Clethodim
Total
Option 2
Flumioxazin
Chlorimuron
Fomesafen
Clethodim
Total
Option 3
Metalochlor
Fomesafen
Acifloren
S Metalochlor
Clethodim
Total

Active ingredient (kg/ha)

Field EIQ/ha value

0.07
1.32
0.29
0.16
1.84

1.68
29.11
7.10
2.67
40.60

0.07
0.02
0.29
0.16
0.54

1.68
0.38
7.13
2.67
11.85

1.36
0.30
0.30
1.43
0.11
3.51

29.97
7.32
7.13
31.46
1.73
77.88

Weighted average all by tillage types: ai/ha 2.78 kg/ha, EIQ/ha 54.66©PG Economics Ltd 2022

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Estimated typical herbicide regimes for GM HT reduced/no till and conventional reduced/notill soybean production systems that will provide an equal level of weed control to the GM HT
system in Argentina 2020
GM HT soybean
Source: Kleffmann dataset on
pesticide use 2018/19
Conventional soybean
Option 1
Glyphosate
Metsulfuron
24D
Imazethapyr
Diflufenican
Clethodim
Total
Option 2
Glyphosate
Dicamba
Acetochlor
Haloxifop
Sulfentrazone
Total
Option 3
Glyphosate
Atrazine
Bentazon2 4 D ester
Imazaquin
Total
Option 4
Glyphosate
2 4 D amine
Flumetsulam
Fomesafen
Chlorimuron
Fluazifop
Total
Option 5
Glyphosate
Metsulfuron
2 4 D amine
Imazethapyr
Haloxifop
Total
Option 6
Glyphosate
Metsulfuron
2 4 D amine
Imazethapyr
Clethodim©PG Economics Ltd 2022

Active ingredient (kg/ha)
3.59

Field EIQ/ha value
54.53

2.27
0.03
0.4
0.10
0.03
0.19
3.02

34.80
0.50
8.28
1.96
0.29
3.23
49.06

2.27
0.12
1.35
0.18
0.19
4.11

34.80
3.04
26.87
4.00
2.23
70.92

2.27
1.07
0.60
0.4
0.024
4.36

34.80
24.50
11.22
6.12
0.37
77.01

2.27
0.4
0.06
0.25
0.05
0.12
3.15

34.80
8.28
0.94
6.13
0.96
3.44
54.54

2.27
0.03
0.8
0.1
0.18
3.38

34.80
0.50
16.56
1.96
4.00
57.82

2.27
0.03
0.8
0.1
0.24

34.80
0.50
16.56
1.96
4.08

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Total
3.44
57.90
Average all six conventional
3.577
61.21
options
Weighted average
3.616
62.04
Sources: AAPRESID, Kleffmann/Kynetec, Bayer Argentina
Weights (based on expected usage): option 1 10%, options 2 to 5 17.5% each, option 6 20%

GM HT versus conventional maize Argentina 2020

Conventional
Option 1
AcetochlorAtrazine
Idosulfuron
Nicosulfuron
24D
Total
Option 2AcetochlorAtrazine
Foramsulam
Idosulfuron
24D
Total
Average conventional

Active ingredient (kg/ha)

Field EIQ/ha value

1.26
1.80
0.01
0.09
0.38
3.54

25.07
41.22
0.16
1.76
5.83
74.04

1.26
1.80
0.06
0.01
0.38
3.51
3.53

25.07
41.22
0.92
0.16
5.83
73.2
73.61

GM HT corn
Acetochlor
0.84
Atrazine
0.9
Glyphosate
1.87
24D
0.38
Total
3.99
Sources: AMIS Global, Kleffmann and Monsanto/Bayer Argentina

16.72
20.61
28.65
5.83
71.81

Typical herbicide regimes for GM HT soybeans Brazil 2020
Active ingredient
Amount (kg/ha of crop)
Burndown (applicable to conventional
2.41
and GM HT)
GM HT over the top
0.69
GM HT total
3.10
Conventional over the top
0.75
Conventional total
3.16
Source: derived from Kleffmann & AMIS Global

Field EIQ/ha
39.72

Active ingredient
Conventional soybean
Option one
Metalochlor
Metribuzin
Total
Option two
S Metolachlor

Field EIQ/ha

9.23
48.95
15.0
54.72

Typical herbicide regimes for GM HT soybean in South Africa 2020

©PG Economics Ltd 2022

Amount (kg/ha of crop)

1.18
1.59
2.77

25.96
45.11
71.07

0.92

20.84

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Dimethenamid
1.05
12.62
Total
2.97
32.86
Option 3
S Metolachlor
0.92
20.24
Mesotrione
0.18
3.36
Total
1.10
23.60
Weighted average
1.95
42.51
GM HT soybean – based on AMIS
1.68
28.73
Global 2015
Source: Monsanto/Bayer South Africa, AMIS Global, Kleffmann
Note conventional weighted average, weighted by use – option 1, 70%, option 2, 20%, option 3, 10%

Typical herbicide regimes for GM HT maize in Canada 2020
Active ingredient
Conventional maize
S MetalochlorAtrazine
Mesotrione
Dicamba
Total

Amount (kg/ha of crop)
1.30
1.09
0.12
0.46
2.97

Field EIQ/ha
28.60
24.96
2.22
12.11
67.89

GM glyphosate tolerant maize
S Metalochlor
0.871
19.16
Atrazine
0.73
16.72
Glyphosate
1.21
18.55
Total
2.81
54.44
GM glufosinate tolerant maize
S Metalochlor
0.871
19.16
Atrazine
0.73
16.72
Glufosinate
0.37
7.49
Total
1.971
43.38
Sources: Weed Control Guide Ontario – annually updated, industry personal communications (various)

Typical insecticide regimes for cotton in India 2020
Active ingredient
Conventional cotton
Option 1
Imidacloprid
Thiomethoxam
Acetamiprid
Diafenthiuron
Buprofezin
Profenfos
Acephate
Cypermethrin
Metaflumizone
Novaluron
Total
Option 2
Imidacloprid
Thiomethoxam
Acetamiprid©PG Economics Ltd 2022

Amount (kg/ha of crop)

Field EIQ/ha

0.06
0.05
0.05
0.1
0.07
0.81
0.63
0.1
0.03
0.02
1.92

2.2
1.67
1.45
2.53
2.55
48.28
15.79
3.64
0.82
0.29
79.22

0.06
0.05
0.05

2.2
1.67
1.45

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Novaluron
0.02
0.29
Chloripyrifos
0.39
10.58
Profenfos
0.81
48.28
Metaflumizone
0.03
0.82
Emamectin
0.01
0.29
Total
1.42
65.58
Average conventional
1.67
72.40
Weighted average conventional
1.72
73.76
GM IR cotton
Imidacloprid
0.06
2.2
Thiomethoxam
0.05
1.67
Acetamiprid
0.05
1.45
Novaluron
0.02
0.29
Buprofezin
0.07
2.55
Acephate
0.63
15.79
Total
0.89
23.95
Option 2
Imidacloprid
0.06
1.54
Thiomethoxam
0.05
1.67
Acetamiprid
0.05
2.30
Novaluron
0.02
0.29
Total
0.18
5.61
Average GM IR cotton
0.53
14.78
Weighted average conventional
0.604
16.61
Difference GM versus
1.12
57.15
conventional
Source: Bayer India, AMIS Global/Kynetec
Note weighted average for GM IR cotton based on insecticide usage – option 1 60%, option 2 40%
Typical insecticide regimes for cotton in China 2020
Active ingredient
Amount (kg/ha of crop)
Field EIQ/ha
Conventional cotton
Imidacloprid
0.162
5.95
Abamectin
0.032
1.11
Chlorpyrifos
0.64
17.18
Deltamethrin
0.068
1.93
Phoxim
0.89
22.25
Lambda cyhalothrin
0.105
4.99
Profenphos
0.84
50.0
Total
2.737
103.41
GM IR cotton
Imidacloprid
0.108
3.96
Abamectin
0.032
1.11
Chlorpyrifos
0.448
12.03
Deltamethrin
0.034
0.96
Phoxim00Lambda cyhalothrin
0.105
4.99
Profenphos
0.84
50.0
Total
1.567
73.02
Sources: Monsanto/Bayer China, AMIS Global, Kleffmann, Plant Protection Institute of the Chinese
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Appendix 4: The Environmental Impact Quotient (EIQ): a
method to measure the environmental impact ofpesticides
The material presented below is from the original by the cited authors of J. Kovach, C. Petzoldt, J.
Degni, and J. Tette, IPM Program, Cornell University,
Methods
Extensive data are available on the environmental effects of specific pesticides, and the data usedwere gathered from a variety of sources. The Extension Toxicology Network (EXTOXNET), a
collaborative education project of the environmental toxicology and pesticide education
departments of Cornell University, Michigan State University, Oregon State University, and the
University of California, was the primary source used in developing the database (Hotchkiss etal. 1989). EXTOXNET conveys pesticide-related information on the health and environmental
effects of approximately 100 pesticides. A second source of information used was CHEM-NEWSof CENET, the Cornell Cooperative Extension Network. CHEM-NEWS is a computer program
maintained by the Pesticide Management and Education Program of Cornell University that
contains approximately 310 US EPA - Pesticide Fact Sheets, describing health, ecological, andenvironmental effects of the pesticides that are required for the re-registration of these pesticides(Smith and Barnard 1992).
The impact of pesticides on arthropod natural enemies was determined by using the SELCTV
database developed at Oregon State (Theiling and Croft 1988). These authors searched theliterature and rated the effect of about 400 agrichemical pesticides on over 600 species ofarthropod natural enemies, translating all pesticide/natural enemy response data to a scaleranging from one (0% effect) to five (90-100% effect).
Leaching, surface loss potentials (runoff), and soil half-life data of approximately 100 compounds
are contained in the National Pesticide/Soils Database developed by the USDA Agricultural
Research Service and Soil Conservation Service. This database was developed from the GLEAMS
computer model that simulates leaching and surface loss potential for a large number ofpesticides in various soils and uses statistical methods to evaluate the interactions between
pesticide properties (solubility, absorption coefficient, and half-life) and soil properties (surface
horizon thickness, organic matter content, etc.). The variables that provided the best estimate ofsurface loss and leaching were then selected by this model and used to classify all pesticides intorisk groups (large, medium, and small) according to their potential for leaching or surface loss.
Bee toxicity was determined using tables by Morse (1989) in the 1989 New York State pesticide
recommendations, which contain information on the relative toxicity of pesticides to honey bees
from laboratory and field tests conducted at the University of California, Riverside from 1950 to1980. More than 260 pesticides are listed in this reference.
In order to fill as many data gaps as possible, Material Safety Data Sheets (MSDS) and technicalbulletins developed by the agricultural chemical industry were also used when available.
Health and environmental factors that addressed some of the common concerns expressed byfarm workers, consumers, pest management practitioners, and other environmentalists were

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evaluated and are listed in Figure 1. To simplify the interpretation of the data, the toxicity of theactive ingredient of each pesticide and the effect on each environmental factor evaluated weregrouped into low, medium, or high toxicity categories and rated on a scale from one to five, with
one having a minimal impact on the environment or of a low toxicity and five considered to behighly toxic or having a major negative effect on the environment.
All pesticides were evaluated using the same criteria except for the mode of action and plantsurface persistence of herbicides. As herbicides are generally systemic in nature and are notnormally applied to food crops we decided to consider this class of compounds differently, so all
herbicides were given a value of one for systemic activity. This has no effect on the relative
rankings within herbicides, but it does make the consumer component of the equation for
herbicides more realistic. Also, since plant surface persistence is only important for postemergent herbicides and not pre-emergent herbicides, all post-emergent herbicides wereassigned a value of three and pre-emergent herbicides assigned a value of one for this factor.
The rating system used to develop the environmental impact quotient of pesticides (EIQ) modelis as follows (l = least toxic or least harmful, 5 = most toxic or harmful):
•
•
•
•
•
•
•
•
•
•

Mode of Action: non-systemic- 1, all herbicides – 1, systemic – 3
Acute Dermal LD50 for Rabbits/Rats(m&/kg): >2000 – 1, 200 - 2000 – 3, 0 - 200 – 5
Long-Term Health Effects: little or none – 1, possible- 3, definite – 5
Plant Surface Residue Half-life: l-2 weeks- 1, 2-4 weeks- 3, > 4 weeks – 5, pre-emergent
herbicides – l, post-emergent herbicides – 3
Soil Residue Half-life: Tl/2 <30 days – 1, Tl/2=30-100 days – 3, Tl/2 >100 days – 5
Toxicity to Fish-96 hr LC50: > 10 ppm – 1, 1-10 ppm – 3, < 1 ppm – 5
Toxicity to Birds-8 day LC50: > 1000 ppm – 1, 100-1000 ppm – 3, 1-100 ppm – 5
Toxicity to Bees: relatively non toxic – 1, moderately toxic – 3, highly toxic – 5
Toxicity to Beneficials: low impact- 1, moderate impact – 3, severe impact – 5
Groundwater and Runoff Potential: small – 1, medium – 3, large -5

In order to further organise and simplify the data, a model was developed called theenvironmental impact quotient of pesticides (EIQ). This model reduces the environmental
impact information to a single value. To accomplish this, an equation was developed based on
the three principal components of agricultural production systems: a farm worker component, aconsumer component, and an ecological component. Each component in the equation is given
equal weight in the final analysis, but within each component, individual factors are weighted
differently. Coefficients used in the equation to give additional weight to individual factors arealso based on a one to five scale. Factors carrying the most weight are multiplied by five,medium-impact factors are multiplied by three, and those factors considered to have the least
impact are multiplied by one. A consistent rule throughout the model is that the impact potentialof a specific pesticide on an individual environmental factor is equal to the toxicity of thechemical times the potential for exposure. Stated simply, environmental impact is equal totoxicity times exposure. For example, fish toxicity is calculated by determining the inherent
toxicity of the compound to fish times the likelihood of the fish encountering the pesticide. In thismanner, compounds that are toxic to fish but short-lived have lower impact values thancompounds that are toxic and long-lived.

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The EIQ Equation
The formula for determining the EIQ value of individual pesticides is listed below and is theaverage of the farm worker, consumer, and ecological components:
EIQ={C[(DT*5)+(DT*P)]+[(C*((S+P)/2)*SY)+(L)]+[(F*R)+(D*((S+P)/2)*3)+(Z*P*3)+(B*P*5)]}/3
DT = dermal toxicity, C = chronic toxicity, SY = systemicity, F = fish toxicity, L = leachingpotential, R = surface loss potential, D = bird toxicity, S = soil half-life, Z = bee toxicity, B =beneficial arthropod toxicity, P = plant surface half-life.
Farm worker risk is defined as the sum of applicator exposure (DT* 5) plus picker exposure(DT*P) times the long-term health effect or chronic toxicity (C). Chronic toxicity of a specificpesticide is calculated as the average of the ratings from various long-term laboratory tests
conducted on small mammals. These tests are designed to determine potential reproductive
effects (ability to produce offspring), teratogenic effects (deformities in unborn offspring),
mutagenic effects (permanent changes in hereditary material such as genes and chromosomes),and oncogenic effects (tumour growth). Within the farm worker component, applicator exposure
is determined by multiplying the dermal toxicity (DT) rating to small laboratory mammals(rabbits or rats) times a coefficient of five to account for the increased risk associated withhandling concentrated pesticides. Picker exposure is equal to dermal toxicity (DT) times therating for plant surface residue half-life potential (the time required for one-half of the chemical
to break down). This residue factor takes into account the weathering of pesticides that occurs inagricultural systems and the days to harvest restrictions that may be placed on certain pesticides.
The consumer component is the sum of consumer exposure potential (C*((S+P)/2)*SY) plus thepotential groundwater effects (L). Groundwater effects are placed in the consumer component
because they are more of a human health issue (drinking well contamination) than a wildlife
issue. Consumer exposure is calculated as chronic toxicity (C) times the average for residue
potential in soil and plant surfaces (because roots and other plant parts are eaten) times thesystemic potential rating of the pesticide (the pesticide's ability to be absorbed by plants).
The ecological component of the model is composed of aquatic and terrestrial effects and is thesum of the effects of the chemicals on fish (F*R), birds (D*((S+P)/2)*3), bees (Z*P*3), and beneficial
arthropods(B*P*5). The environmental impact of pesticides on aquatic systems is determined bymultiplying the chemical toxicity to fish rating times the surface runoff potential of the specificpesticide (the runoff potential takes into account the half-life of the chemical in surface water).
The impact of pesticides on terrestrial systems is determined by summing the toxicities of thechemicals to birds, bees, and beneficial arthropods. As terrestrial organisms are more likely tooccur in commercial agricultural settings than fish, more weight is given to the pesticidal effects
on these terrestrial organisms. Impact on birds is measured by multiplying the rating of toxicity
to birds by the average half-life on plant and soil surfaces times three. Impact on bees ismeasured by taking the pesticide toxicity ratings to bees times the half-life on plant surfaces times
three. The effect on beneficial arthropods is determined by taking the pesticide toxicity rating tobeneficial natural enemies, times the half-life on plant surfaces times five. As arthropod natural
enemies spend almost all of their life in agro ecosystem communities (while birds and bees are
somewhat transient), their exposure to the pesticides, in theory, is greater. To adjust for thisincreased exposure, the pesticide impact on beneficial arthropods is multiplied by five.
Mammalian wildlife toxicity is not included in the terrestrial component of the equation because
mammalian exposure (farm worker and consumer) is already included in the equation, and these©PG Economics Ltd 2022

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health effects are the results of tests conducted on small mammals such as rats, mice, rabbits, anddogs.
After the data on individual factors were collected, pesticides were grouped by classes(fungicides, insecticides/miticides, and herbicides), and calculations were conducted for eachpesticide. When toxicological data were missing, the average for each environmental factor
within a class was determined, and this average value was substituted for the missing values.
Thus, missing data did not affect the relative ranking of a pesticide within a class.
The values of individual effects of each pesticide (applicator, picker, consumer, groundwater,
aquatic, bird, bee, beneficials), the major components of the equation (farm worker, consumer,
and ecological) and the average EIQ values are presented in separate tables (see references).
EIQ field use rating
Once an EIQ value has been established for the active ingredient of each pesticide, field use
calculations can begin. To accurately compare pesticides and pest management strategies, thedose, the formulation or percent active ingredient of the product, and the frequency of
application of each pesticide, need to be determined. To account for different formulations of thesame active ingredient and different use patterns, a simple equation called the EIQ field use
rating was developed. This rating is calculated by multiplying the EIQ value for the specificchemical obtained in the tables by the percent active ingredient in the formulation by the rate peracre used (usually in pints or pounds of formulated product);EIQ Field Use Rating = EIQ x % active ingredient x Rate
By applying the EIQ Field Use Rating, comparisons can be made between different pest
management strategies or programs. To compare different pest management programs, EIQ Field
Use Ratings and number of applications throughout the season are determined for each pesticide
and these values are then summed to determine the total seasonal environmental impact of theparticular strategy.

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Appendix 5 Soil carbon sequestration key literature
Soil organic carbon can be depleted through:••the long-term use of poor farming practices; andthe conversion of natural ecosystems (such as forest lands, prairie lands and steppes) intocrop and grazing land.

These uses deplete the soil organic carbon pool by increasing the rate of conversion of soilorganic matter to carbon dioxide, thereby reducing the input of biomass carbon and accentuating
losses by erosion. Most agricultural soils have lost 30 tonnes/ha to 40 tonnes/ha of carbon, andtheir current reserves of soil organic carbon are lower than their potential capacity.
The significant degradation of crop soils by the oxidation of soil carbon into carbon dioxide
started in the 1850’s with the introduction of large-scale soil cultivation using the mouldboard
plough. The effect of ploughing on soil carbon has been measured for a selection of cultivation
techniques (after tilling wheat). Using a mouldboard plough results in soil carbon losses far
exceeding the carbon value of the previous wheat crop residue and depleting soil carbon by 1,990
kg/ha compared with a no-tillage system. Furthermore, Lal et al (1999) estimated that the global
release of soil carbon since 1850 from land use changes has been 136 +/- 55 Pg 109 (billion tonnes) of
carbon. This is approximately half of the total carbon emissions from fossil fuels (270 +/- 30 Pg(billion tonnes)), with soil cultivation accounting for 78 +/- 12 Pg and soil erosion 26 +/- 9 Pg ofcarbon emissions. Lal et al (1998) also estimated that the potential of carbon sequestration in soil,
biota and terrestrial ecosystems may be as much as 3 Pg C per year (1.41 parts per million of
atmospheric carbon dioxide). A strategy of soil carbon sequestration over a period of 25-50 years
could therefore have a substantial impact on lowering the rate at which carbon dioxide is risingin the atmosphere providing the necessary time to adopt alternative energy strategies.
Reversing this trend can be achieved by a variety of soil and crop management technologies that
increase soil organic carbon storage (i.e. an increase of soil organic carbon) and soil organiccarbon sequestration through the removal of atmospheric carbon dioxide. These include:
•
•
•
•
•
•

no-till farming with residue mulch and cover cropping;
integrated nutrient management (INM), which balances nutrient application with use oforganic manures and inorganic fertilizers;
various crop rotations (including agroforestry);use of soil amendments (such as zeolites, biochar, or compost); andimproved pastures with recommended stocking rates and controlled fire as a rejuvenate
method (Lal (2009)).

The production benefits of increasing soil carbon storage include increased soil infiltration,
fertility and nutrient cycling, decreased wind and water erosion, minimal soil compaction,enhanced water quality, decreased carbon emissions, impeding pesticide movement andgenerally enhanced environmental quality. The soil management practices that sequester soil
carbon are consistent with a more sustainable and less chemically dependent agriculture.
109

1 Pg of soil carbon pool equates to 0.47 parts per million, of atmospheric carbon dioxide.

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Quantification of the impacts of tillage on carbon stocks is complex due to the combination andcomplexities of soil, climate and management conditions, especially crop type and rotation.
Chenu et al (2018) discuss in detail the knowledge gaps and potential to increase organic carbon
stocks, for example how can we increase carbon stocks, at which rate and for how long, where do
we prioritize SOC storage, how do we estimate the potential gain and what agricultural practices
should we implement?
Issues affecting the levels of carbon sequestration include:
•
•
•
•
•
•

Soil and climatic factors;
Shallow sampling may introduce a bias in estimating carbon sequestration in NT;
Initial soil carbon levels;
Crop biomass production (soil carbon inputs) including roots and associatedmycorrhizea;
Organic carbon mineralization (soil carbon outputs); andSoil erosion and re-deposition on soil organic gains and losses.

There is general agreement that the technical potential for sequestration of carbon in soil issignificant but there are differences on the magnitude of the potential. Zomer et al (2017) estimatethat croplands worldwide could sequester between 0.90 and 1.85 Pg C/yr, equivalent to 26-53% of
the target of the “4p1000 Initiative: Soils for Food Security and Climate” 110. However, there areoften significant limitations to achieving the potential by location and within specific farming
systems, including a lack of biomass and other inputs. Efforts to sequester carbon should
concentrate on soils that have become degraded due to long periods of intensive arable croppingin temperate climatic regions in Asia, Europe and North America (van Groenigen et al (2017)).
A number of researchers have examined issues relating to carbon sequestration and different
tillage systems and the following are of note:
•

•

•

110

Buragiene et al (2019) reviewed different tillage technologies and their effect on carbon
dioxide emissions from the soil. Their research concluded that deep ploughing
immediately increases carbon dioxide emissions up to seven times higher that NT;
Mangalassery et al (2014) analysed the greenhouse gas (GHG) balance for the carbon
dioxide, methane and nitrous oxide emissions for conventional tillage and zero tillage
systems. This research concluded that the net global warming potential underconventional tillage systems was 26%-31% higher than zero tillage. Although nitrous
oxide emissions increased under zero tillage this was counter-balanced by a significant
reduction in potential carbon dioxide and methane emissions which is closely linked to
the geometry of the soil porous architecture;
Nicoloso & Rice (2019) undertook a global meta-analysis assessing carbon and nitrogenstorage and sequestration in no-till soils from the most important agricultural regions of
the world. Their study identified that NT soils store both more carbon and nitrogen (upto 100 cm depth) than tilled soils. However, carbon sequestration depended on; an

4p1000 - The aim of the initiative is to demonstrate that agriculture, and in particular agricultural soils canplay a crucial role where food security and climate change are concerned. https://www.4p1000.org/©PG Economics Ltd 2022

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GM crop impact: 1996-2020

•

•

•

•

•

•

•

111

increase in crop frequency (eg. the rapid replanting of arable land following harvest);
additional nitrogen inputs applied to each crop to ensure crop establishment; anddecreased soil disturbance. Single cropping with land left fallow between harvesting andreseeding lacks carbon inputs to maintain soil carbon throughout the soil profile. The useof legumes alleviates nitrogen losses and supply extra nutrient to support carbon
sequestration. Their findings indicate that no-till can effectively mitigate climate change
by either avoiding CO₂ emissions from tilled soils or by promoting soil carbon
sequestration in intensified agricultural systems;
West & Marland (2003) estimated that the net carbon flux from the conversion from CT to
NT was a decrease of 468 kg/carbon/ha/yr for maize, 32 kg/carbon/ha/yr for wheat and
371 kg/carbon/ha/yr for soybeans released to the atmosphere;West & Post (2002). This work analysed 67 long-term agricultural experiments,
consisting of 276 paired treatments. These results indicate, on average, that a change
from CT to NT can sequester 57 +/- 14 g carbon per square metre per year (grams carbon
m-2 year-1), excluding a change to NT in wheat-fallow systems. The cropping system thatobtained the highest level of carbon sequestration when tillage changed from CT to NT
was maize - soybeans in rotation (90 +/- 59 grams carbon m-2 year-1). This level of carbon
sequestration equates to 900 +/- 590 kg/carbon/ha/yr, which would have decreased carbon
dioxide level in the atmosphere by 3,303 +/- 2,165 kg of carbon dioxide per ha/year 111;
Ogle et al (2005) reviewed the impact of CT compared with NT in different climatic
environments. They found that converting from CT to NT over a twenty-year period
resulted in an increase in SOC storage of 23% in tropical moist climates, 17% in tropicaldry climates, 16% in temperate moist and 10% in dry climatic conditions;
Huggins et al (2007) assessed over a 14-year period crop sequence and tillage effect on
SOC dynamics and storage, in continuous maize or soybeans and alternating maizesoybeans under different tillage treatments. CT soybeans and fallow decreased SOC at
an average annual loss of 3.7 Mg/carbon/ha/yr, while chisel plough (RT) with continuous
maize or maize-soybeans and NT with continuous maize, averaged an annual loss of 1.6
Mg/carbon/ha/yr. They concluded that without large additional carbon inputs (eg,manures, cover crops, perennial crops) the potential to approach SOC levels of native
sites is limited with annual cropping and RT;
Johnson et al (2005) summarised how alternative tillage and cropping systems interact tosequester soil organic carbon (SOC) and impact on GHG emissions from the main
agricultural area in central USA. This analysis estimated that the rate of SOC storage in
NT compared to CT has been significant, but variable, averaging 400 +/- 61kg/carbon/ha/yr;
Calegari et al (2008) conducted a 19-year experiment comparing CT and NT management
systems with various winter cover crop treatments in Brazil. The research identified that
the NT system led to 64.6% more carbon being retained in the upper soil layer than in the
CT system. It also found that using NT with winter cover crops resulted in soil
properties that most closely resembled an undisturbed forest (ie, best suited forgreenhouse gas storage). In addition, both maize and soybean yields were found to berespectively 6% and 5% higher, under NT, than CT production systems;
Eagle et al (2012) examined the literature on GHG mitigation potential of conservation
tillage and NT. Based on 280 field comparisons of soil carbon response to NT the average

Conversion factor for carbon sequestered into carbon dioxide = 3.67.

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

•

•

•

•

•

•

•

•

mitigation potential was estimated at 1,200 kg of carbon dioxide per hectare per yearwith a range of -200 to 3,200;
Olson et al (2013) evaluated soil carbon levels over a 24-year period on eroded soils inSouthern Illinois that were under a maize and soybeans rotation that used different
tillage systems. The NT system stored and retained 7.8 tonnes of carbon per ha morethan CT plots;
Kahlona et al (2013) evaluated different tillage practices and the importance of mulchingon soil physical properties and carbon sequestration over a period of 22 years. The NTplots consistently resulted in positive effects on soil physical attributes and total carbon
concentration;
Haruna & Nkongolo (2019) reviewed the rate of change in soil organic matter (SOM) for
maize and soybeans with and without cover crops under CT vs NT. NT resulted in 4%
higher SOM and 8% higher SOM with a cover crop;
Bernoux et al (2006) reviewed cropping systems, carbon sequestration and erosion in
Brazil. Over 30 years of NT practice carbon levels in topsoil increased. This paper
reviewed several studies and identified the rate of carbon storage in the top 40 cm of thesoil ranges from 400 to 1,700 kg carbon/ha/year in the Cerrado region. The mean rates ofcarbon storage in the soil surface area (0-20 cm) varied from 600 to 680 kg carbon/ha/yearwith the greatest variation in the southern region of -70 to 1,600 kg carbon/ha/year(standard deviation 680 +/- 540 kg carbon/ha/year). In addition, in Brazilian conditions
direct seeding offers the scope for earlier sowing of crops, shortening the total production
cycle, facilitating a second crop in the same season. This results in more carbon being
returned to the soil;
IPCC estimates put the rate of soil organic carbon (SOC) sequestration by the conversion
from conventional to all conservation tillage (NT and RT) in North America within arange of 50 to 1,300 kg carbon/ha/year (it varies by soil type, cropping system and ecoregion), with a mean of 300 kg carbon/ha/year;
The adoption of NT systems has also had an impact on other GHG emissions such as
methane and nitrous oxide which are respectively 23 and 296 times more potent thancarbon dioxide. Robertson et al (2000) and Sexstone et al (1985) suggested that the
adoption of NT (sequestering SOC) could do so at the expense of increased nitrous oxide
production if growers were to increase the use of nitrogen fertiliser in NT production
systems;
Robertson et al (2000) measured gas fluxes for carbon dioxide, nitrous oxide and methaneand other sources of global warming potential (GWP) in cropped and unmanaged
ecosystems over the period 1991 to 1999. They found that the net GWP was highest for
conventional tillage systems at 114 grams of carbon dioxide equivalents/ha/yearcompared with 41 grams/ha/year for an organic system with legumes cover and 14
grams/ha/year for a NT system (with liming) and minus 20 grams/ha/year for a NT
system (without liming). The major factors influencing the beneficial effect of NT overCT and organic systems is the high level of carbon sequestration and reduced use of fuelresulting in emissions of 12 grams of carbon dioxide equivalents m-2 year-1 comparedwith 16 grams in CT and 19 grams for organic tillage. The release of nitrous oxide interms of carbon dioxide was equivalent in the organic and NT systems due to theavailability of nitrogen under the organic system compared with the targeted use of
nitrogen fertiliser under the NT systems;
The importance of nitrogen fixing legume grain crops has also been investigated byAlmaraz (2009). They studied the GHG emission associated with N2 fixing soybean©PG Economics Ltd 2022

195

GM crop impact: 1996-2020

•

•

•

•

•

•

•

grown under CT and NT tillage systems. Their findings suggest that using NT in Nfixing legume crops may reduce both carbon dioxide and N2O emissions in comparison
to CT, because in the CT system, harvest residue is incorporated into the soil during
ploughing (increasing N2O emissions);
Omonode et al (2011) assessed N2O emissions in maize following three decades ofdifferent tillage and rotation systems. Seasonal cumulative N2O emissions weresignificantly lower by 40%-57% under NT compared to long term chisel and mouldboard
plough tillage systems, due to soil organic C decomposition associated with higher levelsof soil residue mixing and higher soil temperatures;
Using IPCC emission factors, Johnson et al (2005) estimated the offsetting effect ofalternative fertiliser management and cropping systems. For a NT cropping system thatreceived 100 kg N per ha per year (net from all sources), the estimated annual nitrous
oxide emission of 2.25 kg N per ha per year would have to increase by 32%-97% tocompletely offset carbon sequestration gains of 100-300 kg per ha per year;
Baker et al (2007) identified 37 out of 45 studies (from 17 experiments) with sampling
depth <30 cm at which NT treatments (82%) reported more SOC than in the CT control
with a mean annual SOC gain of 380 +/- 720 kg/ha/yr. In contrast, in 35 of 51 studies(from 5 experiments) with sampling depths >30 cm, the NT treatments registered less
SOC relative to CT with a mean annual loss of -230 +/- 970 kg/ha/yr. This work
questioned the premise that NT leads to positive carbon sequestration compared to CT.
In both cases, however, the standard error associated with the estimates was so large thatthe mean (impact of tillage) was not considered to be significant;Research by Angers & Eriksen-Hamel (2008) and Blanco-Canqui & Lal R. (2007) foundthat the majority of SOC increase under NT is in the top 10 to 15 cm of soil withinsignificant changes (or even decreases) in SOC relative to CT at depths over 15 cm.
Hence, newly sequestered carbon in a NT system is accumulated where it is mostvulnerable to environmental and management pressures. This makes any permanent
increase in SOC associated with NT systems vulnerable to changes in environmentalpressures and soil management practices;
Angers & Eriksen-Hamel’s (2008) work also compared NT and full-inversion tillage (FIT)
trials and found that while there was a statistically significant increase in total SOC stocks
under NT (100.3 versus 95.4 Mg C ha-1 for NT and FIT respectively in the upper 10 cm), to
the 21-25 cm soil depth (which corresponds to the mean ploughing depth (23 cm)), theaverage SOC content was significantly greater under FIT than NT. It was also greater
under FIT just below the average depth of ploughing (26-35 cm). However, there wassignificantly more SOC (4.9 Mg ha-1) under NT than FIT across all depths and thisdifference in favour of NT increased weakly with the duration of the experiment;
Syswerda et al (2011) examined whether soil sequestration gains in the surface layer may
result in soils losing carbon at depth under NT compared with CT. Results indicated that
surface soil carbon concentrations and total carbon pools were significantly greater under
NT than CT. No difference in soil carbon at depth was identified although carbon levels
were found to be variable. Also, there was no evidence of carbon gains in the surface
soils of NT being either offset or magnified at depth;
Kong & Six (2010) researched the relative importance of crop roots compared with crop
residue eg stalks, leaves etc. Their analysis demonstrated that at the end of the maize
growing season, 52% of the root-derived carbon was still present in the soil, while only
4% of crop residue-derived carbon remained. These results suggest that root carbon
contributes more to overall carbon stabilization than crop residue carbon;©PG Economics Ltd 2022

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Al-Kaisi et al (2005) evaluated the effects of different tillage systems on soil organiccarbon (SOC) and nitrogen (SON), residue carbon and nitrogen inputs and crop (maize
and soybean) yields in Iowa. Yields of both maize and soybean were comparable in NT
and mouldboard tillage systems but in NT and strip-tillage there was a significant
increase in SOC of 14.7% and 11.4% respectively. Changes in SON due to tillage weresimilar to those observed with the SOC experiments;
The maize-soybean rotation in the US offers the opportunity for considerable carbon
sequestration under NT systems. Hollinger et al (2005) measured the carbon flux from1997 to 2002 to evaluate the carbon budget for maize and soybean in rotation that had
been in NT cultivation for over 14 years. The carbon sink when planted with maize was
576 g C m per year and soybean 33 g C m per year. Accounting for 100% grain
consumption, maize acts as a C-sink of 184 g C m per year while soybean becomes a Csource of 94 g C m per year. As these crops are generally grown in rotation, this system
is a net sink of 90 g C m per year;
Long term research comparing CT with NT has demonstrated that NT results in higher
soil carbon and nitrogen contents, microbial biomass and enzyme activities at the 0-5 cm
depth (Mathew et al (2012));
NT soils are more biologically active and diverse, have higher nutrient loading capacities,
release nutrients gradually and continuously and have better soil structure than reduced
or cultivated soils (Clapperton, J. (2003)). By enhancing the organic matter, a higher
Carbon-Stock Equilibrium (CSE) can be achieved;
Bernacchi et al (2005) estimated that if the total area of maize/soybeans in the US
converted to NT, 21.7 Tg C (21.7 million tonnes) would be sequestered annually(approximately 350 kg/C/ha/yr), an offset of about 2% of annual US carbon emissions atthat time;
The most effective natural method of achieving soil carbon sequestration is by theabsorption of atmospheric carbon dioxide in plants by photosynthesis, where plants
convert carbon dioxide into plant tissue (lignin and carbohydrates) and oxygen. When aplant dies, a portion of the stored carbon is left behind in the soil by decomposing plant
residue (eg, roots, stalks) and a larger portion is emitted back into the atmosphere. This
plant residue carbon pool contributes 20% to 23% of the total carbon present in maizebased agricultural ecosystems. Short-term carbon sequestration estimates largely reflect
plant residue carbon pool changes which are driven by crop inputs and net
decomposition differences (Kochsiek et al. (2012)). Decomposition rates tend to be
proportional to the amount of organic matter, the physiochemical and microbial
properties of the soil;
The potential for maximising soil sequestration tends to be higher indegraded/desertified soils, and soils that have been managed with extractive farming
practices, than it is in good-quality soils that have been managed according torecommended management practices (RMPs). Thus, converting degraded/desertified
soils into restorative land and adopting RMPs can increase the soil carbon pool. The rateof soil carbon sequestration through the adoption of RMPs on degraded soils ranges from100 kg/ha per year in warm and dry regions to 1,500 kg/ha per year in cool and temperateregions. Lal R. (2010) estimated the technical potential of soil organic carbon
sequestration through adoption of RMPs for world cropland soils (1.5 billion ha) to be 0.6
billion to 1.2 billion tonnes of carbon per year and about 3 billion tonnes of carbon peryear in soils of all ecosystems (eg, cropland, grazing land, forest lands, degraded lands
and wetlands;
-2

-2

-2

-2

-2

•

•

•

•

•

©PG Economics Ltd 2022

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GM crop impact: 1996-2020••

In some cases, intermittent tillage, during long‐term RT or NT is needed to reduce soil
compaction, for weed control, or to reduce pests or pathogens. While intermittent tillage
can cause a decrease in soil stocks, up to 80% of soil gains from NT practices can be
maintained when implementing NT with intermittent tillage (Conant et al (2007),
Venterea et al (2006)); andWalia et al (2017) examined in southern Illinois the tillage and fertiliser use effects on bulk
density and soil carbon concentrations over a 44-year period (20 years in continuous
maize and 24 years in maize–soybean rotation). NT management increased carbon stocks
compared to tillage for depths of between 0 to 15 cm. NT combined with NPK (nitrogen,phosphorus and potassium) fertiliser maintained greater cumulative soil carbon stocks to
1 metre soil depth than either undisturbed forest soils or restored prairie soils.
Additionally, NT/NPK had a maximum soil carbon increase over time of 360 kg
carbon/ha/year for the top 15 cm over 44 years.

Some studies have questioned the accuracy and the level of carbon sequestered previously
projected for NT compared with CT (eg Virto et al (2012)). Yang et al (2013) concluded that NT
has been widely adopted because it reduces labour, fuel and machinery costs, conserves water,and reduces soil erosion which has contributes to improved soil quality and agricultural
sustainability. However, it may not be appropriate to attribute all the higher carbon content in
the surface of NT soil to either increased carbon input or reduced carbon mineralization (output)
relative to CT, when the differences may be due to soil erosion.
Powlson et al (2014) questioned the assumptions of the UN Emissions Gap Report 2013 which
presented a case that additional adoption of NT could further contribute to more carbon
sequestration because much of the most suitable land for adoption of NT is already using thisproduction system. Powlson did, however, acknowledge that widespread adoption of NT in
North and South America had delivered important carbon sequestration savings and if this land
was to revert to CT, it would result in significant carbon release.
Lastly, Olge et al (2019) explored literature relating to the adoption of NT management, carbon
storage and the 4 per mille (4p1000) initiative promoted through the UN Framework Convention
on Climate Change. The research concluded that SOC storage can be higher under NT
management in some soil types and climatic conditions even with redistribution of SOC, andcontribute to reducing net greenhouse gas emissions. However, uncertainties tend to make thisapproach less attractive as a contributor to stabilise the climate system compared to other options.
This research concluded that the adoption of NT may be better viewed as a method of:
•
•
•
•

112

Reducing soil erosion;
Adapting to climate change;
Ensuring food security; andValuing any increase in SOC storage as a “co-benefit 112” for society in terms of reducing
greenhouse gas emission.

Co-benefits of climate change mitigation as defined in the 4th Assessment Report of the Intergovernmental

Panel on Climate Change are the positive benefits related to the reduction of greenhouse gases©PG Economics Ltd 2022

198

GM crop impact: 1996-2020

The discussion above illustrates the difficulty in estimating the contribution NT systems canmake to soil carbon sequestration. The modelling of soil carbon sequestration is also made moredifficult by the dynamic nature of soils, climate, cropping types and patterns. If a specific croparea is in continuous NT crop rotation, the full SOC benefits described above can be realised.
However, if the NT crop area is returned to a CT system, a proportion of the SOC gain will be
lost. The temporary nature of this form of carbon storage will only become permanent when
farmers adopt a continuous NT system which itself tends to be highly dependent upon effective
herbicide-based weed control systems.

©PG Economics Ltd 2022

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GM crop impact: 1996-2020

Appendix 6: Additional carbon sequestration impactdata
US soybeans: potential additional soil carbon sequestration (1996 to 2020)
Annual increase in

Crop area (million ha)

Total additional

Total additional

carbonCarbon dioxidebased on 1996 averagesequesteredsequestered(kg carbon/ha)(million kg)(million kg)

carbon sequestered

0.00
38.34
80.93
99.20
156.72265.69296.63328.58328.68259.54162.98362.00118.43178.52363.72346.34328.84662.98346.53405.15206.14291.082017
126.21
2018113.562019110.902020
5,977.68
Total
Assumption: carbon sequestration remains at the 1996 level of -102.9 kg carbon/ha/year
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

©PG Economics Ltd 2022

0.0
1.4
2.8
3.3
5.2
8.9
10.0
11.1
10.9
9.0
5.3
14.1
3.9
5.8
11.5
11.5
10.7
21.6
10.4
12.2
6.2
8.0
3.5
3.7
3.3

26.0
28.3
29.1
29.8
30.1
30.0
29.5
29.7
30.3
28.9
30.6
25.8
30.2
30.9
31.6
30.1
30.8
30.7
33.4
33.1
33.5
36.2
35.7
30.3
33.3

200

0.00
140.70297.02364.07575.18975.081,088.65
1,205.88
1,206.27
952.50598.13
1,328.53
434.63655.17
1,334.86
1,271.05
1,206.86
2,433.14
1,271.76
1,486.89
756.53
1,068.25
463.17416.76406.9921,938.05

GM crop impact: 1996-2020

Argentine soybeans: potential additional soil carbon sequestration (1996 to 2020)
Annual increase in

Crop area

Total additional

Total additional

carbon sequestered based(million ha)carbon sequestered

Carbon dioxide(million kg)

sequesteredon 1996 average(kg carbon/ha)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

(million kg)

108.17158.52161.68233.27495.53791.51974.71
1,234.69
1,202.00
1,308.48
1,505.72
1,699.00
1,813.37
1,842.45
1,958.28
2,037.25
2,197.86
2,082.52
2,042.51
1,921.082017
1,650.93
2018
1,645.72
2019
1,793.94
2020
1,832.48
Total
32,693.50
Assumption: NT = +175 kg carbon/ha/yr, Conventional Tillage CT = -25 kg carbon/ha/yr©PG Economics Ltd 2022

16.92
22.80
19.77
22.03
43.09
61.05
72.20
86.07
79.08
81.02
90.79
101.33
97.49
101.23105.28105.28111.28105.28105.28103.28101.2899.28
107.28111.28

5.91
6.39
6.95
8.18
10.59
11.50
12.96
13.50
14.34
15.20
16.15
16.59
16.77
18.60
18.20
18.60
19.35
19.75
19.78
19.40
18.60
16.30
16.58
16.72
16.47

201

396.98581.78593.38856.091,818.58
2,904.83
3,577.19
4,531.31
4,411.35
4,802.13
5,526.00
6,235.34
6,655.06
6,761.81
7,186.90
7,476.69
8,066.14
7,642.84
7,496.01
7,050.37
6,058.91
6,039.79
6,583.76
6,725.21
119,985.15

GM crop impact: 1996-2020

US maize: potential additional soil carbon sequestration (1997 to 2020)
Annual increase in carbon

Crop area

sequestered based on 1997 average(million ha)(kg carbon/ha)

Additional

Additional carbon

carbondioxide sequesteredsequestered(million kg)(million kg)
0.00-183.41-294.20-422.85-403.30-421.26-351.70-289.56
1,182.31
1,096.74
1,164.52
1,425.16
2,148.54
2,123.58
1,374.40
1,485.39
1,591.05
2,228.31
2,166.55
1,666.96
1,225.70
2017
1,460.15
2018
1,493.05
2019
1,481.63
2020
22,947.76
Total
Assumption: carbon sequestration remains at the 1997 level of 122.5 kg carbon/ha/year
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

©PG Economics Ltd 2022

0.0
-5.7
-9.4
-13.1
-13.2
-13.2
-11.1
-8.9
35.7
34.6
30.7
44.8
66.7
64.8
40.0
42.0
44.8
66.2
66.3
47.5
36.6
44.1
45.4
44.4

32.2
32.4
31.3
32.2
30.6
31.9
31.8
32.5
33.1
31.7
37.9
31.8
32.2
32.8
34.4
35.4
35.5
33.6
32.7
35.1
33.5
33.1
32.9
33.4

202

0.00
-673.13-1,079.72-1,551.87-1,480.12-1,546.04-1,290.73-1,062.68
4,339.09
4,025.05
4,273.78
5,230.35
7,885.12
7,793.55
5,044.06
5,451.39
5,839.16
8,177.91
7,951.23
6,117.73
4,498.33
5,358.74
5,479.51
5,437.57
84,218.29

GM crop impact: 1996-2020

Canadian canola: potential additional soil carbon sequestration (1996 to 2020)
Annual increase in carbon

Crop area

sequestered based on 1996

(million ha)

average (kg carbon/ha)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

0.0
3.3
3.3
3.3
3.3
6.5
9.8
13.0
16.3
19.5
22.8
24.1
26.0
29.3
32.5
32.5
32.5
32.5
32.5
32.5
32.5
32.5
32.5
32.5
32.5

Carbon dioxidesequestered(million kg)(million kg)
3.5
4.9
5.4
5.6
4.9
3.8
3.3
4.7
4.9
5.5
5.2
5.9
6.5
6.4
6.5
7.5
8.6
7.8
8.3
8.1
8.1
9.3
9.1
8.5
8.3

2017
2018
2019
2020
Total
Notes: NT/RT = +55 kg of carbon/ha/yr CT = -10 kg of carbon/ha/yr©PG Economics Ltd 2022

Total carbon

203

0.00
15.83
17.64
18.08
15.79
24.60
31.80
60.96
80.26
107.07119.17142.16168.86186.50211.72242.81279.01
253.91
271.18262.70263.87301.37296.40274.82270.403,916.91

0.00
58.09
64.75
66.37
57.96
90.30
116.71223.72294.55392.96437.36521.72619.71
684.44777.00891.101,023.98
931.84995.23964.10968.391,106.04
1,087.79
1,008.59
992.37
14,375.06

GM crop impact: 1996-2020

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