GM crops: global socio-economicand environmental impacts 19962016

Graham Brookes & Peter Barfoot

PG Economics Ltd, UK

Dorchester, UK
June 2018

GM crop impact: 1996-2016

Table of contents
Foreword........................................................................................................................................................8
Executive summary and conclusions .........................................................................................................9
1 Introduction ..............................................................................................................................................18
1.1 Objectives ..........................................................................................................................................18
1.2 Methodology .....................................................................................................................................18
1.3 Structure of report ............................................................................................................................18
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 1996-2016 ...................................................................25
3.1 Herbicide tolerant soybeans ...........................................................................................................27
3.1.1 The US ........................................................................................................................................27
3.1.2 Argentina ...................................................................................................................................29
3.1.3 Brazil ...........................................................................................................................................31
3.1.4 Paraguay and Uruguay ............................................................................................................32
3.1.5 Canada ........................................................................................................................................33
3.1.6 South Africa ...............................................................................................................................34
3.1.7 Romania .....................................................................................................................................34
3.1.8 Mexico ........................................................................................................................................36
3.1.9 Bolivia .........................................................................................................................................37
3.1.10 Summary of global economic impact ...................................................................................37
3.2 Insect resistant soybeans .................................................................................................................38
3.3 Herbicide tolerant maize .................................................................................................................39
3.3.1 The US ........................................................................................................................................39
3.3.2 Canada ........................................................................................................................................40
3.3.3 Argentina ...................................................................................................................................41
3.3.4 South Africa ...............................................................................................................................42
3.3.5 Philippines .................................................................................................................................42
3.3.6 Brazil ...........................................................................................................................................43
3.3.7 Colombia ....................................................................................................................................43
3.3.8 Uruguay .....................................................................................................................................43
3.3.9 Paraguay ....................................................................................................................................44
3.3.10 Vietnam ....................................................................................................................................44
3.3.11 Summary of global economic impact ...................................................................................44
3.4 Herbicide tolerant cotton ................................................................................................................44
3.4.1 The US ........................................................................................................................................44
3.4.2 Other countries ..........................................................................................................................45
3.4.3 Summary of global economic impact .....................................................................................46
3.5 Herbicide tolerant canola ................................................................................................................46
3.5.1 Canada ........................................................................................................................................46
3.5.2 The US ........................................................................................................................................48
3.5.3 Australia .....................................................................................................................................49©PG Economics Ltd 20182

GM crop impact: 1996-2016

3.5.4 Summary of global economic impact .....................................................................................51
3.6 GM herbicide tolerant (GM HT) sugar beet .................................................................................51
3.6.1 US ................................................................................................................................................51
3.6.2 Canada ........................................................................................................................................54
3.7 GM insect resistant43F (GM IR) maize ..........................................................................................54
3.7.1 US ................................................................................................................................................54
3.7.2 Canada ........................................................................................................................................55
3.7.3 Argentina ...................................................................................................................................56
3.7.4 South Africa ...............................................................................................................................57
3.7.5 Spain ...........................................................................................................................................58
3.7.6
Other EU countries ...........................................................................................................59
3.7.7 Brazil ...........................................................................................................................................59
3.7.8 Other countries ..........................................................................................................................60
3.7.9 Summary of economic impact .................................................................................................61
3.8 Insect resistant (Bt) cotton (GM IR) ................................................................................................61
3.8.1 The US ........................................................................................................................................61
3.8.2 China ...........................................................................................................................................62
3.8.3 Australia .....................................................................................................................................63
3.8.4 Argentina ...................................................................................................................................64
3.8.5 Mexico ........................................................................................................................................65
3.8.6 South Africa ...............................................................................................................................66
3.8.7 India ............................................................................................................................................67
3.8.8 Brazil ...........................................................................................................................................68
3.8.9
Other countries .................................................................................................................69
3.8.10 Summary of global impact.....................................................................................................70
3.9 Other GM crops ................................................................................................................................70
3.9.1 Maize/corn rootworm resistance ............................................................................................70
3.9.2 Virus resistant papaya ..............................................................................................................71
3.9.3 Virus resistant squash ..............................................................................................................72
3.9.4 Drought tolerant maize ............................................................................................................72
3.9.5 Other crops ................................................................................................................................72
3.10 Indirect (non-pecuniary) farm level economic impacts ............................................................73
3.11 Production effects of the technology ...........................................................................................75
3.12 Trade flows and related issues .....................................................................................................77
4 The environmental impact of GM crops...............................................................................................79
4.1 Use of insecticides and herbicides .................................................................................................79
4.1.1 GM herbicide tolerant (to glyphosate) soybeans (GM HT) .................................................82
4.1.2 GM herbicide tolerant (to glyphosate) and insect resistant soybeans (Intacta) ................94
4.1.3 GM Herbicide tolerant (GM HT) maize .................................................................................94
4.1.4 GM HT Herbicide tolerant (GM HT) cotton........................................................................101
4.1.5 GM Herbicide tolerant (GM HT) canola ..............................................................................107
4.1.6 GM HT sugar beet...................................................................................................................110
4.1.7 GM IR maize ............................................................................................................................111
4.1.8 GM insect resistant (GM IR) cotton ......................................................................................117
4.1.9 Other environmental impacts - development of herbicide resistant weeds and weed
shifts ...................................................................................................................................................124
4.2.2 Soil carbon sequestration .......................................................................................................126
4.2.1 Tractor fuel use ........................................................................................................................127©PG Economics Ltd 20183

GM crop impact: 1996-2016

4.2.2 Soil carbon sequestration .......................................................................................................129
4.2.3 Herbicide tolerance and conservation tillage ......................................................................132
4.2.4 Herbicide tolerant soybeans ..................................................................................................133
4.2.5 Herbicide tolerant maize ........................................................................................................145
4.2.6 Herbicide tolerant canola .......................................................................................................149
4.2.7 Herbicide tolerant cotton .......................................................................................................151
4.2.8 Insect resistant cotton .............................................................................................................152
4.2.9 Insect resistant maize..............................................................................................................153
4.2.10 Insect resistant soybeans ......................................................................................................154
4.2.11 Intensification of crop production ......................................................................................154
4.2.12 Summary of carbon sequestration impact .........................................................................155
Appendix 1: Base yields used where GM technology delivers a positive yield gain......................158
Appendix 2: Impacts, assumptions, rationale and sources for all trait/country combinations .....159
Appendix 3: Additional information relating to the environmental impact: example comparisons.....................................................................................................................................................................175
Appendix 4: The Environmental Impact Quotient (EIQ): a method to measure the environmental
impact of pesticides ..................................................................................................................................184
Appendix 5 Soil carbon sequestration key literature...........................................................................188
References ..................................................................................................................................................194

Table of tables
Table 1: Global farm income benefits from growing GM crops 1996-2016: million US $ .................10
Table 2: GM crop farm income benefits 1996-2016 selected countries: million US $.........................11
Table 3: GM crop farm income benefits 2016: developing versus developed countries: million US$ ............................................................................................................................................................11
Table 4: Cost of accessing GM technology (million $) relative to the total farm income benefits
2016 ......................................................................................................................................................12
Table 5: Additional crop production arising from positive yield effects of GM crops .....................13
Table 6: Impact of changes in the use of herbicides and insecticides from growing GM crops
globally 1996-2016 ..............................................................................................................................14
Table 7: GM crop environmental benefits from lower insecticide and herbicide use 1996-2016:
developing versus developed countries .........................................................................................15
Table 8: Context of carbon sequestration impact 2016: car equivalents ..............................................17
Table 9: GM share of crop plantings in 2016 by country (% of total plantings) .................................24
Table 10: Farm level income impact of using GM HT soybeans (first generation) in the US 19962016 ......................................................................................................................................................28
Table 11: Farm level income impact of using GM HT soybeans in Argentina 1996-2016 ................30
Table 12: Farm level income impact of using GM HT soybeans in Brazil 1997-2016 ........................31
Table 13: Farm level income impact of using GM HT soybeans (first generation) in Canada 19972016 ......................................................................................................................................................33
Table 14: Farm level income impact of using GM HT soybeans in South Africa 2001-2016 ............34
Table 15: Farm level income impact of using herbicide tolerant soybeans in Romania 1999-2006 .35
Table 16: Farm level income impact of using GM HT soybeans in Mexico 2004-2016......................36
Table 17: Farm level income impact of using GM HT soybeans in Bolivia 2005-2016 ......................37
Table 18: Main impacts of insect resistant soybeans 2013/14 to 2016/17 .............................................39
Table 19: Farm level income impact of using GM HT maize in Brazil 2010-2016..............................43©PG Economics Ltd 20184

GM crop impact: 1996-2016

Table 20: Farm level income impact of using GM HT cotton in the US 1997-2016 ............................45
Table 21: Summary of farm level impact of using GM HT cotton: other countries:..........................46
Table 22: Farm level income impact of using GM HT canola in Canada 1996-2016..........................47
Table 23: Farm level income impact of using GM HT canola in Australia 2008-2016 ($US) ............51
Table 24: Farm level income impact of using GM HT sugar beet in the US 2007-2016.....................53
Table 25: Farm level income impact of using GM IR maize in the US 1996-2016 ..............................54
Table 26: Farm level income impact of using GM IR maize in South Africa 2000-2016....................57
Table 27: Farm level income impact of using GM IR maize in Spain 1998-2016 ................................58
Table 28: Farm level income impact of using GM IR maize in other EU countries 2016 ..................59
Table 29: Farm level income impact of using GM IR maize in Brazil 2008-2016 ...............................59
Table 30: Farm level income impact of using GM IR cotton in the US 1996-20165............................61
Table 31: Farm level income impact of using GM IR cotton in China 1997-2016...............................62
Table 32: Farm level income impact of using GM IR cotton in Australia 1996-2016 .........................64
Table 33: Farm level income impact of using GM IR cotton in Mexico 1996-2016 ............................65
Table 34: Farm level income impact of using GM IR cotton in India 2002-2016 ................................68
Table 35: Values of non-pecuniary benefits associated with GM crops in the US .............................74
Table 36: Additional crop production arising from positive yield effects of GM crops ...................75
Table 37: Average (%) yield gains GM IR cotton and maize 1996-2016 ..............................................76
Table 38: Share of global crop trade accounted for GM production 2016/17 (million tonnes).........78
Table 39: Share of global crop derivative (meal) trade accounted for GM production 2016/17(million tonnes) ..................................................................................................................................78
Table 40: Herbicide usage on soybeans in the US 1996-2016 ................................................................83
Table 41: Herbicide usage on GM HT and conventional soybeans in the US 1996-2016 ..................84
Table 42: Average ai use and field EIQs for conventional soybeans 2006-2015 to deliver equal
efficacy to GM HT soybeans .............................................................................................................86
Table 43: National level changes in herbicide ai use and field EIQ values for GM HT soybeans in
the US 1996-2016 ................................................................................................................................86
Table 44: National level changes in herbicide ai use and field EIQ values for GM HT soybeans in
Canada 1997-2016 ..............................................................................................................................87
Table 45: National level changes in herbicide ai use and field EIQ values for GM HT soybeans in
Brazil 1997-2016 ..................................................................................................................................89
Table 46: Herbicide usage on maize in the US 1996-2016 .....................................................................95
Table 47: Average US maize herbicide usage and environmental load 1997-2016: conventional
and GM HT .........................................................................................................................................95
Table 48: Average ai use and field EIQs for conventional maize 2007-2015 to deliver equal efficacy
to GM HT maize .................................................................................................................................96
Table 49: National level changes in herbicide ai use and field EIQ values for GM HT maize in the
US 1997-2016 .......................................................................................................................................97
Table 50: Change in herbicide use and environmental load from using GM HT maize in Canada
1999-2016 .............................................................................................................................................98
Table 51: Herbicide usage on cotton in the US 1996-2016 ...................................................................101
Table 52: Herbicide usage and its associated environmental load: GM HT and conventional cottonin the US 1997-2016 ..........................................................................................................................102
Table 53: Average ai use and field EIQs for conventional cotton 2006-2016 to deliver equal
efficacy to GM HT cotton ................................................................................................................103
Table 54: National level changes in herbicide ai use and field EIQ values for GM HT cotton in the
US 1997-2016 .....................................................................................................................................104©PG Economics Ltd 20185

GM crop impact: 1996-2016

Table 55: National level changes in herbicide ai use and field EIQ values for GM HT cotton inAustralia 2000-2016 ..........................................................................................................................105
Table 56: Active ingredient and field EIQ differences conventional versus GM HT canola US 19992016 ....................................................................................................................................................107
Table 57: Average US maize insecticide usage and its environmental load 1996-2016: conventionalversus GM IR (insecticides largely targeted at stalk boring and rootworm pests) .................112
Table 58: National level changes in insecticide ai use and field EIQ values for GM IR maize in the
US 1996-2016 (targeted at stalk boring and rootworm pests) ....................................................113
Table 59: National level changes in insecticide ai use and field EIQ values for GM IR cotton in the
US 1996-2016 .....................................................................................................................................118
Table 60: National level changes in insecticide ai use and field EIQ values for GM IR cotton in
China 1997-2016 ...............................................................................................................................119
Table 61: Comparison of insecticide ai use and field EIQ values for conventional, Ingard andBollgard II cotton in Australia........................................................................................................120
Table 62: National level changes in insecticide ai use and field EIQ values for GM IR cotton inAustralia 1996-2016 ..........................................................................................................................120
Table 63: National level changes in insecticide ai use and field EIQ values for GM IR cotton in
Argentina 1998-2016 ........................................................................................................................121
Table 64: US soybean: tractor fuel consumption by tillage method (litres/ha) ................................127
Table 65: Total farm diesel fuel consumption estimate (litres/ha) .....................................................128
Table 66: Tractor fuel consumption by tillage method (litre/ha) 2012...............................................129
Table 67: COMET-Planner: carbon sequestration by conservation practice (average) ...................130
Table 68: Summary of the potential of corn and soybeans cultivation systems to reduce net
emissions or sequester carbon (kg of carbon/ha/year) ................................................................131
Table 69: US soybean: tillage practices and the adoption of GM HT cultivars 1996-2016 (millionha).......................................................................................................................................................133
Table 70: US soybean: consumption of tractor fuel used for tillage (1996-2016)..............................134
Table 71: US soybeans: permanent reduction in tractor fuel consumption and reduction in carbon
dioxide emissions (1996-2016) ........................................................................................................135
Table 72: US soybeans: potential soil carbon sequestration (1996 to 2016) .......................................136
Table 73: US soybeans: potential additional soil carbon sequestration (1996 to 2016)....................136
Table 74: Argentine soybeans: tillage practices and the adoption of GM HT cultivars 1996-2016(million ha)........................................................................................................................................138
Table 75: Argentine soybeans: permanent reduction in tractor fuel consumption and reduction incarbon dioxide emissions (1996-2016) ...........................................................................................138
Table 76: Argentine soybeans: potential additional soil carbon sequestration (1996 to 2016) .......140
Table 77: Southern Brazil (Santa Catarina, Parana and Rio Grande de Sol states) soybeans: tillage
practices and the adoption of biotech cultivars 1997-2016 (million ha) ...................................141
Table 78: Brazil (3 southernmost states) soybeans: permanent reduction in tractor fuelconsumption and reduction in carbon dioxide emissions (1997-2016).....................................142
Table 79: Brazil (3 southern most states) soybeans: potential additional soil carbon sequestration(1997 to 2016) ....................................................................................................................................143
Table 80: US maize: tillage practices and the adoption of GM HT cultivars 1997-2016 (million ha)............................................................................................................................................................145
Table 81: US maize: consumption of tractor fuel used for tillage (1997-2016) .................................146
Table 82: US maize: permanent reduction in tractor fuel consumption and reduction in carbon
dioxide emissions (1997-2016) ........................................................................................................147
Table 83: US maize: potential soil carbon sequestration (1997 to 2016) ............................................148©PG Economics Ltd 20186

GM crop impact: 1996-2016

Table 84: US maize: potential additional soil carbon sequestration (1997 to 2016) .........................148
Table 85: Canadian canola: permanent reduction in tractor fuel consumption and reduction incarbon dioxide emissions (1996-2016) ...........................................................................................150
Table 86: Canadian canola: potential additional soil carbon sequestration (1996 to 2016).............151
Table 87: Permanent reduction in global tractor fuel consumption and carbon dioxide emissions
resulting from the cultivation of GM IR cotton (1996-2016) ......................................................152
Table 88: Summary of carbon sequestration impact 1996-2016 ..........................................................156
Table 89: Context of carbon sequestration impact 2016: car equivalents ..........................................157

Table of figures
Figure 1: GM crop plantings 2016 by crop (base area of the four GM crops: 177.6 million hectares(ha)) ......................................................................................................................................................20
Figure 2: 2016: share of GM crops in global plantings of key crops (ha) ............................................21
Figure 3: Global GM crop plantings by crop 1996-2016 (ha) ................................................................21
Figure 4: Global GM crop plantings by main trait and crop: 2016.......................................................22
Figure 5: Global GM crop plantings 2016 by country ............................................................................23
Figure 6: National farm income benefit from using GM HT soybeans in Paraguay and Uruguay
1999-2016 (million $) ..........................................................................................................................32
Figure 7: Global farm level income benefits derived from using GM HT soybeans 19962016(million $) ....................................................................................................................................38
Figure 8: National farm income impact of using GM HT maize in the US 1997-2015 (million $) ...40
Figure 9: National farm income impact of using GM HT maize in Canada 1999-2016 ($ million) .41
Figure 10: National farm income impact: GM HT canola in the US 1999-2016 (million $)...............49
Figure 11: National farm income impact: GM IR maize in Canada 1996-2016 (million $) ...............56
Figure 12: National farm income impact: GM IR cotton in Argentina 1998-2016 (million $) ..........65
Figure 13: National farm income impact: GM IR cotton in South Africa 1998-2016 (million $) ......67
Figure 14: Non-pecuniary benefits derived by US farmers 1996-2016 by trait ($ million) ...............75
Figure 15: Reduction in herbicide use and the environmental load from using GM HT soybeans in
all adopting countries 1996-2016......................................................................................................93
Figure 16: Reduction in herbicide use and the environmental load from using GM HT maize in
adopting countries 1997-2016 .........................................................................................................101
Figure 17: Reduction in herbicide use and the environmental load from using GM HT cotton in
the US, Australia, Argentina and South Africa 1997-2016 .........................................................107
Figure 18: Reduction in herbicide use and the environmental load from using GM HT canola in
the US, Canada and Australia 1996-2016 ......................................................................................109
Figure 19: Reduction in insecticide use and the environmental load from using GM IR maize in
adopting countries 1996-2016 .........................................................................................................116
Figure 20: Average cotton insecticide usage: 1996-2016 (average kg active ingredient/ha) ...........118
Figure 21: Reduction in insecticide use and the environmental load from using GM IR cotton in
adopting countries 1996-2016 .........................................................................................................124©PG Economics Ltd 20187

GM crop impact: 1996-2016

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 13th 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.
Given the controversy that the use of this technology engenders in some debates and for somepeople, the work contained in this paper has been submitted and accepted for publication in a peer
reviewed publication. The length of this paper, at over 200 pages, is too long for acceptance forpublication as a single document in peer reviewed journals. Therefore, the authors submitted two
papers focusing separately on the economic and environmental impacts of the technology. Thesepapers have been accepted for publication in the peer reviewed journal, GM Crops and Food (withopen access). The environmental impact paper is available at volume 9, issue 2 2018, DOI:
10.1080/21645698.2018.1476792. The economic impact paper is also forthcoming at volume 9, issue
2 or 3, 2018, DOI: 10.1080/21645698.2018.1464866. These papers follow on from 25 previous peer
reviewed papers by the authors 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 andassumptions used are detailed in the paper2
For example, last year’s global impact report covering the years 1996-2015 can be found in the GM Crops journal 2017, vol 8, issue
3, p 156-193 (economic impacts) and 2017, vol 8, issue 2, p117-147 (environmental impacts). See also www.pgeconomics.co.uk for a
full list of these peer review papers©PG Economics Ltd 20188

GM crop impact: 1996-2016

Executive summary and conclusions
This study presents the findings of research into the global socio-economic and environmental
impact of genetically modified (GM) crops in the twenty-one 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 (Table 1). In 2016, the direct global farm income
benefit from GM crops was $18.2 billion. This is equivalent to having added 5.4% to the value of
global production of the four main crops of soybeans, maize, canola and cotton. Since 1996, farmincomes have increased by $186.1 billion.
The largest gains in farm income in 2016 have arisen in the maize sector, largely from yield gains.
The $4.81 billion additional income generated by GM insect resistant (GM IR) maize in 2016 has
been equivalent to adding 5.7% to the value of the crop in the GM crop growing countries, or
adding, the equivalent of 3.1% to the $138 billion value of the global maize crop in 2016.
Cumulatively since 1996, GM IR technology has added $50.6 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 2016, cotton farm income levels in the GM adopting countries increased by $3.7
billion and since 1996, the sector has benefited from an additional $55.9 billion. The 2016 income
gains are equivalent to adding 13.8% to the value of the cotton crop in these countries, or 10.6% to
the $36 billion value of total global cotton production. This is a substantial increase in value
added terms for two new cotton seed technologies.
Significant increases to farm incomes have also resulted in the soybean and canola sectors. The
GM HT technology in soybeans has boosted farm incomes by $4.37 billion in 2016, and since 1996
has delivered $54.5 billion of extra farm income. The fourth year of adoption of ‘Intacta’soybeans (combining HT and IR traits) in South America also provided $2.49 billion of additionalfarm income and over the four years since 2013 has delivered $5.2 billion of additional farmincome. In the canola sector (largely North American) an additional $5.97 billion has been
generated (1996-2016).
Table 2 summarises farm income impacts in key GM crop adopting countries. This highlights theimportant 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 a range of GM
cultivars in the US. It also illustrates the growing level of farm income benefits being obtained inSouth Africa, the Philippines, Mexico and Colombia.
In terms of the division of the economic benefits obtained by farmers in developing countries
relative to farmers in developed countries, Table 3 shows that in 2016, 54.8% of the farm income
benefits have been earned by developing country farmers. The vast majority of these income3

See section 3 for details©PG Economics Ltd 20189

GM crop impact: 1996-2016

gains for developing country farmers have been from GM IR cotton and GM HT soybeans 4. Overthe twenty-one years, 1996-2016, the cumulative farm income gain derived by developing
country farmers was 51.7% ($96.2 billion).
Examining the cost farmers pay for accessing GM technology, Table 4 shows that across the fourmain GM crops, the total cost in 2016 was equal to 29% of the total technology gains (inclusive offarm income gains plus cost of the technology payable to the seed supply chain 5). In terms ofinvestment, this means that for each extra dollar invested in biotech crop seeds, farmers gained
an average $3.49.
For farmers in developing countries the total cost was equal to 20% of total technology gains,whilst for farmers in developed countries the cost was 37% of the total technology gains. Whilst
circumstances vary between countries, the higher share of total technology gains accounted forby farm income gains in developing countries, relative to the farm income share in developed
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 per hectare
basis derived by developing country farmers relative to developed country farmers.
Table 1: Global farm income benefits from growing GM crops 1996-2016: million US $Trait

GM herbicide
tolerant soybeans
GM herbicide
tolerant and insect
resistant soybeans
GM herbicide
tolerant maize
GM herbicide
tolerant cotton
GM herbicide
tolerant canola
GM insectresistant maize
GM insectresistant cotton
OthersTotalsIncrease in farmincome 2016

Increase in farmincome 1996-2016

Farm income
benefit in 2016 as% of total value of
global productionof crop54,524.4

Farm income
benefit in 2016 as% of total value of
production ofthese crops in GM
adopting
countries
4.3

4,373.3
2,490.9

5,211.5

4.8

2.3

2,104.9

13,108.1

2.2

1.2

130.1

1,916.9

0.5

0.4

509.9

5,970.9

5.5

1.8

4,809.1

50,565.5

5.7

3.1

3,695.2

53,986.9

13.3

10.2

81.5
18,194.9

817.9
186,102.1

Not applicable
5.4

Not applicable
8.5

4

4.0

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 this paper 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, seed multipliers, plant breeders,
distributors and the GM technology providers©PG Economics Ltd 201810

GM crop impact: 1996-2016

Notes: All values are nominal. Others = Virus resistant papaya and squash, herbicide tolerant sugar beetand drought tolerant maize. Totals for the value shares exclude ‘other crops’ (ie, relate to the 4 main crops ofsoybeans, maize, canola and cotton). Farm income calculations are net farm income changes after inclusionof impacts on yield, crop quality and key variable costs of production (eg, payment of seed premia, impact
on crop protection expenditure)

Table 2: GM crop farm income benefits 1996-2016 selected countries: million US $GM HTsoybeans

GM HT
maize

GM HT
cottonGM HTcanola

GM IR
maize

GM IR
cottonGM
HT/IRsoybeans
N/a497.4
4,207.4
437.1
N/a
N/a

Total

US
25,626.5
8,450.0
1,135.5360.9
38,509.95,430.5
79,513.3
Argentina
18,567.3
2,391.9
183.9
N/a1,108.8
921.0
23,670.3
Brazil7,220.2
1,831.9
180.3
N/a6,222.9
134.9
19,797.6
Paraguay
1,199.1
4.0
N/a
N/a
32.0
N/a
1,664.2
Canada
863.5
185.3
N/a
5,520.0
1,457.8
N/a8,026.6
South
38.4
65.2
4.8
N/a
2,173.2
34.5
2,316.1
Africa
China
N/a
N/a
N/a
N/a
N/a
19,644.9
N/a19,644.9
India
N/a
N/a
N/a
N/a
N/a
21,121.7
N/a21,121.7
Australia
N/a
N/a
113.2
89.9
N/a
953.7
N/a
1,156.8
Mexico
6.1
N/a
274.4
N/a
N/a
272.1
N/a
552.6
Philippines
N/a
171.0
N/a
N/a
553.0
N/a
N/a
724.0
Romania
44.6
N/a
N/a
N/a
N/a
N/a
N/a
44.6
Uruguay
183.2
1.4
N/a
N/a
29.6
N/a
69.5
283.7
Spain
N/a
N/a
N/a
N/a
274.8
N/a
N/a
274.8
Other EU
N/a
N/a
N/a
N/a
24.6
N/a
N/a
24.6
Colombia
N/a
6.0
24.8
N/a
130.0
21.1
N/a
181.9
Bolivia
775.6
N/a
N/a
N/a
N/a
N/a
N/a
775.6
Myanmar
N/a
N/a
N/a
N/a
N/a
358.4
N/a
358.4
Pakistan
N/a
N/a
N/a
N/a
N/a
4,794.3
N/a4,794.3
Burkina
N/a
N/a
N/a
N/a
N/a
204.6
N/a
204.6
Faso
Vietnam
N/a
1.4
N/a
N/a
4.0
N/a
N/a
5.4
Honduras
N/a
N/a
N/a
N/a
11.5
N/a
N/a
11.5
Notes: All values are nominal. Farm income calculations are net farm income changes after inclusion of
impacts on yield, crop quality and key variable costs of production (eg, payment of seed premia, impact on
crop protection expenditure). N/a = not applicable. US total figure also includes $757.5 million for othercrops/traits (not included in the table). Also, not included in the table is $10.7 million extra farm income
from GM HT sugar beet in Canada

Table 3: GM crop farm income benefits 2016: developing versus developed countries: million
US $GM HT soybeans
GM HT & IR soybeans
GM HT maize
GM HT cotton
GM HT canola
GM IR maize©PG Economics Ltd 2018

Developed
2,599.201,235.850.8
509.9
3,243.8

11

Developing
1,774.1
2,490.9
869.1
79.3
0
1,565.2

GM crop impact: 1996-2016

GM IR cotton
512.2
3,183.0
GM virus resistant papaya and81.5
0squash, GM HT sugar beet, GM
DT maize
Total
8,233.2
9,961.6
Developing countries = all countries in South America, Mexico, Honduras, Burkina Faso, India, China,
Pakistan, Myanmar, the Philippines and South Africa

Table 4: Cost of accessing GM technology (million $) relative to the total farm income benefits
2016
Cost oftechnology: allfarmers

Farmincomegain: allfarmers

Total benefitof technology
to farmers andseed supply
chain

Cost oftechnology:
developing
countries

Farm income
gain:developing
countries

Total benefit oftechnology tofarmers and seedsupply chain:developing
countries
1,940.5

GM HT
2,256.7
4,373.3
6,630.0
166.4
1,774.1
soybeans
GM HT
733.4
2,490.9
3,224.3733.4
2,490.9
3,224.3& IR
soybeans
GM HT
1,127.4
2,104.9
3,232.3
265.3
869.1
1,134.4
maize
GM HT
251.1
130.1
381.2
25.4
79.3
104.7
cotton
GM HT
106.1
509.9
616.0
0
0
0
canolaGM IR
2,138.4
4,809.1
6,947.5
945.2
1,565.2
2,510.4
maize
GM IR
583.3
3,695.2
4,278.5315.1
3,183.0
3,498.1
cottonOthers
94.8
81.5
176.3
0
0
0
Total
7,291.2
18,194.9
25,486.1
2,450.8
9,961.6
12,412.4
N/a = not applicable. Cost of accessing technology based on the seed premia paid by farmers for using GM
technology relative to its conventional equivalents

Production effects of the technology
Based on the yield impacts used in the direct farm income benefit calculations (see section 3 andappendix 2) 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 5).
The GM IR traits, used in maize and cotton, have accounted for 93.5% of the additional maize
production and 98.9% 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©PG Economics Ltd 201812

GM crop impact: 1996-2016

conventional technology (such as application of insecticides and seed treatments). The average
yield impact across the total area planted to these traits over the 21 years since 1996 has been
+14% for maize and +15% for cotton.
The primary impacts of GM HT technology have been to provide more cost effective (lessexpensive) and easier weed control. In some countries, the improved weed control has led tohigher yields, though the main source of additional production has been via the facilitation of notillage production systems and how this has shortened the production cycle and enabled many
farmers in South 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 166.8
million tonnes to soybean production in Argentina and Paraguay between 1996 and 2016(accounting for 83.4% of the total GM HT-related additional soybean production). Intacta (IR)soybeans have also added a further 13.46 million tonnes to global soybean production.
Table 5: Additional crop production arising from positive yield effects of GM crops
1996-2016 additional production(million tonnes)
Soybeans
213.47
Maize
404.9
Cotton27.47
Canola
11.65
Sugar beet
1.20
Note: Sugar beet, US and Canada only (from 2008)2016 additional production(million tonnes)
31.56
47.36
2.27
1.00
0.17

Environmental impact from changes in insecticide and herbicide use 6
To examine this impact, the study has analysed both active ingredient use and utilised theindicator 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 (Table 6). Since 1996, the use ofpesticides on the GM crop area was reduced by 671.2 million kg of active ingredient (8.2%
reduction), and the environmental impact associated with herbicide and insecticide use on thesecrops, as measured by the EIQ indicator, fell by18.4%.
In absolute terms, the largest environmental gain has been associated with the adoption of GM
insect resistant (IR) technology. GM IR cotton has contributed a 43% reduction in the total
volume of active ingredient used on GM crops (-288 million kg active ingredient, equivalent to a

6

See section 4.1©PG Economics Ltd 201813

GM crop impact: 1996-2016

29.9% reduction in insecticide use on the GM IR cotton area) and a 32.3% reduction in the total
field EIQ indicator measure associated with GM crop use (1996-2016) due to the significant
reduction in insecticide use that the technology has facilitated, in what has traditionally been an
intensive user of insecticides. Similarly, the use of GM IR technology in maize has led toimportant reductions in insecticide use (92.1 million kg of active ingredient), with associatedenvironmental benefits.
The volume of herbicides used in GM maize crops also decreased by 239.3 million kg (1996-2016),
an 8.1% reduction, whilst the overall environmental impact associated with herbicide use on
these crops decreased by a significantly larger 12.5%. This highlights the switch in herbicides
used with most GM herbicide tolerant (HT) crops to active ingredients with a moreenvironmentally benign profile than the ones generally used on conventional crops.
Important environmental gains have also arisen in the soybean and canola sectors. In thesoybean sector, whilst herbicide use increased by 13 million kg (+0.4%: 1996-2016), the associatedenvironmental impact of herbicide use on this crop area decreased (improved) by 13.4%, due to aswitch to more environmentally benign herbicides. In the canola sector, farmers reduced
herbicide use by 27.3 million kg (an 18.2% reduction) and the associated environmental impact ofherbicide use on this crop area fell by 29.7% (due to a switch to more environmentally benign
herbicides).
In terms of the division of the environmental benefits associated with less insecticide andherbicide use for farmers in developed countries relative to farmers in developing countries,
Table 7 shows a 50%:50% split of the environmental benefits (1996-2016) respectively indeveloped (50%) and developing countries (50%). Sixty-five per cent of the environmental gains
in developing countries have been from the use of GM IR cotton.
Table 6: Impact of changes in the use of herbicides and insecticides from growing GM crops
globally 1996-2016
Trait

GM herbicide
tolerantsoybeans
GM herbicide
tolerant &
insect resistantsoybeans
GM herbicide
tolerant maize
GM herbicide
tolerant canola
GM herbicide
tolerant cotton

Change involume ofactiveingredientused(million kg)+13.0

Change infield EIQ
impact (interms ofmillion field
EIQ/ha units)-8,526% change inai use on
GM crops-7.4©PG Economics Ltd 2018

Area GM trait
2015 (million
ha)

+0.4

% change inenvironmental
impact associatedwith herbicide &
insecticide use on
GM crops
-13.4

-678

-6.1

-6.3

22.3

-239.3-7,859

-8.1

-12.5

51.6

-27.3

-931

-18.2

-29.7

8.7

-29.1

-706

-8.2

-10.7

5.0

14

72.7

GM crop impact: 1996-2016

GM insectresistant maize
GM insectresistantcottonGM herbicide
tolerant sugar
beet
Totals-92.1-4,142

-56.1

-58.6

51.4

-288.0-12,762

-29.9

-32.3

20.5

-1.0

-43

-9.9

-19.4

0.47

-671.2-35,647

-8.2

-18.4

Table 7: GM crop environmental benefits from lower insecticide and herbicide use 1996-2016:
developing versus developed countries

GM HT soybeans
GM HT & IR soybeans
GM HT maize
GM HT cotton
GM HT canola
GM IR maize
GM IR cotton
GM HT sugar beet
Total

Change in field EIQ impact (in termsof million field EIQ/ha units):
developed countries-5,600.9
0-6,728.3-583.3-930.6-2,805.7-1,080.5-43.4-17,772.7

Change in field EIQ impact (in termsof million field EIQ/ha units):
developing countries-2,924.7-678.5-1,130.8-123.10-1,336.4-11,681.2
0-17,874.7

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 41 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 40%-60% of the total area annually devoted to maize, cotton, canola, soybeans and sugar beet(the crops in which GM HT technology is used).
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. This change in weed management emphasis also
reflects the broader agenda of developing strategies across all forms of cropping systems tominimise and slow down the potential for weeds developing resistance to existing control
methods. At the macro level, these changes have influenced the mix, total amount, cost andoverall profile of herbicides applied to GM HT crops in the last 15 years and this is reflected in
the data presented in this paper.

©PG Economics Ltd 201815

GM crop impact: 1996-2016

Impact on greenhouse gas (GHG) emissions 7
The scope for GM crops contributing to lower levels of GHG emissions comes from two principal
sources:••

Reduced fuel use from less frequent herbicide or insecticide applications and a reductionin the energy use in soil cultivation. The fuel savings associated with making fewer
spray runs (relative to conventional crops) and the switch to conservation, reduced andno-till farming systems, have resulted in permanent savings in carbon dioxide emissions.
In 2016, this amounted to about 2,945 million kg (arising from reduced fuel use of 1,309
million litres). Over the period 1996 to 2016 the cumulative permanent reduction in fueluse is estimated at 29,169 million kg of carbon dioxide (arising from reduced fuel use of
10,925 million litres);
The use of ‘no-till’ and ‘reduced-till’ 8 farming systems. These production systems haveincreased significantly with the adoption of GM HT crops because the GM HT
technology has improved farmers’ ability to control competing weeds, reducing the needto rely on soil cultivation and seed-bed preparation as means to getting good levels of
weed control. As a result, tractor fuel use for tillage is reduced, soil quality is enhanced
and levels of soil erosion cut. In turn more carbon remains in the soil and this leads tolower GHG emissions. Based on savings arising from the rapid adoption of notill/reduced tillage farming systems in North and South America, an extra 6,586 million
kg of soil carbon is estimated to have been sequestered in 2016 (equivalent to 24,172
million kg of carbon dioxide that has not been released into the global atmosphere).
Cumulatively, the amount of carbon sequestered is likely to be higher due to year-onyear benefits to soil quality; however, it is equally likely that the total cumulative soil
sequestration gains are not the sum of each individual year’s estimated saving because
only a proportion of the crop area will have remained in permanent no-till and reduced
tillage. It is not possible to confidently estimate cumulative soil sequestration gains thattake into account reversions to conventional tillage because of a lack of data.
Consequently, our estimate of 251,390 million kg of carbon dioxide not released into theatmosphere for the cumulative period 1996-2016 should be treated with caution.

Placing these carbon sequestration benefits within the context of the carbon emissions from cars,
Table 8 shows that:
•
•
•

•

In 2016, the permanent carbon dioxide savings from reduced fuel use were the equivalentof removing 1.82 million cars from the road;
The additional probable soil carbon sequestration gains in 2016 were equivalent toremoving 14.93 million cars from the roads;
In total, in 2016, the combined GM crop-related carbon dioxide emission savings fromreduced fuel use and additional soil carbon sequestration were equal to the removal fromthe roads of 16.75 million cars, equivalent to 54.3% of all registered cars in the UK;
It is not possible to confidently estimate the probable soil carbon sequestration gains
since 1996. If the entire GM HT crop in reduced or no tillage agriculture during the lasttwenty-one years had remained in permanent reduced/no tillage then this would have7

See section 4.2
No-till farming means that ground is hardly disturbed at planting (not ploughed), while reduced tillage means that ground isdisturbed less than it would be with traditional tillage systems. For example, under a no-till farming system, soybean seeds are planted
through the organic material that is left over from a previous crop such as corn, cotton or wheat

8©PG Economics Ltd 201816

GM crop impact: 1996-2016

resulted in a carbon dioxide saving of 251,390 million kg, equivalent to taking 155.2
million cars off the road. However, this is a maximum possibility and the actual levels ofcarbon dioxide reduction are likely to be lower.
Table 8: Context of carbon sequestration impact 2016: car equivalents
Crop/trait/country

Permanent
carbon dioxidesavings arisingfrom reduced
fuel use(million kg ofcarbon dioxide)

Permanent fuelsavings: asaverage family
car equivalents
removed fromthe road for ayear (‘000s)

Potential
additional soil
carbonsequestration
savings (million
kg of carbon
dioxide)Soil carbon
sequestration
savings: as averagefamily car
equivalents removed
from the road for ayear (‘000s)

HT soybeans
Argentina
709.0
437.8
7,186.9
4,438.2
Brazil509.3
314.5
5,163.1
3,188.4
Bolivia, Paraguay,
175.2
108.2
1,776.4
1,097.0
Uruguay
US
533.4
329.4
2,870.7
1,772.8
Canada
47.3
29.2
249.2
153.9
HT maize
US
416.2
257.0
5,902.8
3,645.2
Canada
19.2
11.9
54.2
33.5
HT canola
Canada
191.8
118.5
968.4
598.0
IR maize
Brazil
100.1
61.8
0.0
0.0
USA, Canada,
12.2
7.5
0.0
0.0
South.Africa, Spain
IR cotton
Global
41.6
25.7
0.0
0.0
IR soybeans
S.America
190.1
117.4
0.0
0.0
Total
2,945.4
1,818.9
24,171.7
14,927.0
Notes:
1. Assumption: In all previous editions of this report the authors have assumed that an averagefamily car in the UK produces 150 grams of carbon dioxide per km, is driven over a distance of
15,000 km/year and therefore produces 2,250 kg of carbon dioxide/year. With the introduction oflower carbon dioxide emission vehicles and a trend to drive each car fewer miles per year theauthors have used the following 2017 data; 129 grams of carbon dioxide per km(http://www.carpages.co.uk/co2/); and 12,553 km/year(https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/633077/nationaltravel-survey-2016.pdf ) equating to 1,619 kg of carbon dioxide/year.
2. IR soybeans = savings from reduced insecticide use. All other savings associated with the HT stackin ‘Intacta’ soybeans included under HT soybeans©PG Economics Ltd 201817

GM crop impact: 1996-2016

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-one years, 1996-2016 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-one 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;• Trade flows: developments of imports and exports and prices;• Drivers for adoption such as farm type and structure
Environmental impacts on:• Insecticide and herbicide use, including conversion to an environmental impact
measure 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.

1.3 Structure of report
The report is structured as follows:9

The authors acknowledge that funding towards the researching of this paper was provided by Monsanto. The material presented inthis paper is, however, the independent view of the authors – it is a standard condition for all work undertaken by PG Economics that
all reports are independently and objectively compiled without influence from funding sponsors
10This study updates earlier studies first produced in 2005 and updated annually, covering first, the first nine then subsequent years ofGM crop adoption globally. Readers should, however, note that some data presented in this 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
The Environmental Impact Quotient (EIQ), based on Kovach J et al (1992 & annually updated) – see references
12
See References
13
Where several pieces of research of relevance to one subject (eg, the impact of using a biotech trait on the yield of a crop) have been
identified, the findings used have been largely based on the average©PG Economics Ltd 201818

GM crop impact: 1996-2016

•
•
•
•

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, structure and size, prices, production impact and trade flows;
Section four: environmental impacts covering impact of changes in herbicide andinsecticide use and contributions to reducing GHG emissions.

©PG Economics Ltd 201819

GM crop impact: 1996-2016

2 Global context of GM crops
This section provides a broad overview of the global development of GM crops over the twentyone years, 1996-2016.

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 2016, the global planted area
was 177.6 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 48% of the global plantings to these fourcrops in 2016.

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 1) 14. In 2016, GM soybeans accounted for the largest share (52%), followed by corn (30%),
cotton (13%) and canola (5%).
Figure 1: GM crop plantings 2016 by crop (base area of the four GM crops: 177.6 million ha)
Cotton12%Canola5%

Soybeans
51%
Corn
32%

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 2016 there were also additional GM crop plantings of papaya (395 hectares), squash (1,000 hectares), sugar beet (456,000 ha) andalfalfa (about 1.23 million ha) in the US. There were also 9,000 hectares of papaya in China, 12,000 of sugar beet in Canada and 700
ha of insect resistant brinjal in Bangladesh©PG Economics Ltd 201820

GM crop impact: 1996-2016

In terms of the share of total global plantings to these four crops, GM traits accounted for the
majority of soybean plantings (75%) in 2016. For the other three main crops, the GM shares were
29% for maize/corn, 72% for cotton and 26% for canola (Figure 2).
Figure 2: 2016: 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

29,898,353

128,223,283

8,478,513

25,007,727

GM area

90,401,647

57,376,717

21,101,487

8,742,273

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 3.
Figure 3: Global GM crop plantings by crop 1996-2016 (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
0
1996

1998

2000

Soybeans

2002

2004

Corn

2006

Cotton

2008

2010

2012

2014

CanolaSources: 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 201821

GM crop impact: 1996-2016

2.2.2 By trait
Figure 4 summarises the breakdown of the main GM traits planted globally in 2016. GM
herbicide tolerant (HT) soybeans dominate, accounting for 36% of the total, followed by insect
resistant (IR: largely Bt), HT maize, IR soybeans (also containing HT technology) and IR cottonwith respective shares of 21%, 21%, 9% and 8% 15.
Figure 4: Global GM crop plantings by main trait and crop: 2016
HT sugar beet
0.2%
Ht canola
3.5%

IR soybeans
8.9%

IR cotton
8.1%

Ht soy36.1%

HT corn
20.6%
IR corn
20.6%

Ht cotton
2.0%

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 2016 (38%), followed by Brazil (28%).
The other main countries planting GM crops were Argentina, India, Canada and China (Figure
5).

15

The reader should note that the total plantings by trait produces a higher global planted area (251 million ha) than the global area bycrop (177.6 million ha) because of the planting of some crops containing the stacked traits of herbicide tolerance and insect resistance©PG Economics Ltd 201822

GM crop impact: 1996-2016

Figure 5: Global GM crop plantings 2016 by country
India
6%

Others7%

US38%

Argentina
13%

Brazil28%

Canada
6%

China
2%

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 9 shows that, in
2016, 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 been reached in 2016. All of the US sugar beet crop also used GM HT technology
in 2016;
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 16 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 small
cotton crop (17,800 ha in 2016);
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 2016. 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 2016. GM virus resistant papaya has also beenused in China since 2008. In India, IR cotton was first adopted in 2002, and its use

16

The only other African country where GM crops were grown commercially in 2016 was IR cotton in Sudan - first grown commerciallyin 2012 and where GM IR cotton was planted on 121,000 ha in 2016

©PG Economics Ltd 201823

GM crop impact: 1996-2016•

increased rapidly in subsequent years, so that by 2016 this technology dominates total
cotton production (96% of the total). IR cotton is also grown in Pakistan and Myanmar.
In the Philippines, IR maize was first used commercially in 2003, with HT maize also
adopted from 2006. Vietnam adopted IR/HT maize in 2015 and 3% of the crop used
seed containing this technology in 2016. 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 9: GM share of crop plantings in 2016 by country (% of total plantings)
USA
CanadaArgentina
South Africa
Australia
China
Philippines
Paraguay
BrazilUruguay
India
Colombia
MexicoBolivia
Vietnam
Pakistan
Myanmar
Note: N/a = not applicable©PG Economics Ltd 2018

Soybeans
94
87
99
95
N/a
N/a
N/a
96
96
98
N/a
N/a
1
91
N/a
N/a
N/a

Maize
92
92
96
91
N/a
N/a
24
44
88
86
N/a
19
N/a
N/a
3
N/a
N/a

24

Cotton
93
N/a
100
100
98
95
N/a
100
78
N/a
96
52
98
N/a
N/a
97
93

Canola
90
95
N/a
N/a
19
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a
N/a

GM crop impact: 1996-2016

3 The farm level economic impact of GM crops 19962016
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:••

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 17. 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;
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 the17

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 201825

GM crop impact: 1996-2016••

analysis 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 18), 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 thisresearch are summarised 19 and extrapolated to the cumulative biotech crop planted areas in the
US over the period 1996-2016.

18
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 most cases the analysis relates to impact of crop
protection and seed cost only
19
Notably relating to the US - Marra and Piggott (2006)©PG Economics Ltd 201826

GM crop impact: 1996-2016

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 soybeans
3.1.1 The US
First generation GM HT soybeans
In 2016, 94% (31.5 million ha) of the total US soybean crop was planted to GM HT cultivars. Of
this, 10.3 million ha were first generation GM HT soybeans. The farm level impact of using thistechnology since 1996 is summarised in Table 10.
The key features are as follows:•••

The primary impact has been to reduce the cost of production, 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, has been the period between 2008 and2010, when the cost savings declined, mainly because of the significant increase in the
global price of glyphosate relative to increases in the price of other herbicides (commonlyused on conventional soybeans). In addition, growers of GM HT soybean crops havebeen increasingly faced with the problem of weed species becoming resistant toglyphosate during the last 15 years. This has resulted in the need to include otherherbicides (with different and complementary modes of action) in combination withglyphosate to address the weed resistance (to glyphosate) issues (see section 4 for moredetailed discussion of this issue). At the macro level, these changes have influenced themix, volume; cost and overall profile of herbicides applied to GM HT soybeans and isshown here by the annually changing levels of cost savings associated with the adoptionof GM HT technology;
Against the background of underlying improvements in average yield levels over the
1996-2016 period (via improvements in plant breeding, including the adoption of second
generation HT soybeans – see below), the specific yield impact of the first generation of
GM HT technology has been neutral 20;
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 declined as the total area planted to this trait has fallen in line withincreased adoption of second generation GM HT soybeans (see below). In 2016, the total
income gain from first generation HT soybeans was $159.8 million. The cumulative farmincome benefit over the 1996-2016 period (in nominal terms) was $13.3 billion.

20
Some early studies of the impact of GM HT soybeans in the US suggested that GM HT soybeans produced lower yields thanconventional soybean varieties. Where this may have occurred it applied only in early years of adoption, when the technology was notpresent in all leading varieties suitable for all of the main growing regions of the USA. By 1998/99 the technology was available inleading varieties and no statistically significant average yield differences have been found between GM (first generation) andconventional soybean varieties©PG Economics Ltd 201827

GM crop impact: 1996-2016

Table 10: Farm level income impact of using GM HT soybeans (first generation) in the US
1996-2016
Year

Cost savings($/ha)Net cost saving/increase in grossmargins, inclusive of cost oftechnology ($/ha)
10.39
10.39
19.03
19.03
19.03
58.56
58.56
61.19
40.33
44.71
32.25
60.48
32.37
15.90
28.29
14.60
25.62
13.30
15.91
19.29
15.56

Increase in farm income at anational level ($ millions)

1996
25.2
5.0
1997
25.2
33.2
1998
33.9
224.1
1999
33.9
311.9
2000
33.9
346.6
2001
73.4
1,298.5
2002
73.4
1,421.7
2003
78.5
1,574.9
2004
60.1
1,096.8
2005
69.4
1,201.4
2006
57.0
877.1
2007
85.2
1,417.2
2008
57.1
899.5
2009
54.7
437.2
2010
66.2
761.9
2011
67.1
312.0
2012
71.3
402.7
2013
62.7
148.3
2014
59.8
165.1
2015
68.3
202.6
2016
73.1
159.8
Sources and notes:
1. Impact data 1996-1997 based on Marra et al (2002), 1998-2000 based on Carpenter and Gianessi(1999) and 2001 onwards based on Sankala & Blumenthal (2003 & 2006), Johnson and Strom (2008)
plus updated 2008 onwards to reflect recent changes in herbicide prices and weed control
programmes
2. Cost of technology: $14.82/ha 1996-2002, $17.3/ha 2003, $19.77/ha 2004, $24.71/ha 2005-2008,$38.79/ha 2009, $37.95/ha 2010, $52.53/ha 2011, $45.71/ha 2012, $49.42/ha 2013, $43.93 in 2014, $48.97
2015, $57.49 2016
3. 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 comparisons
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 21.2 million ha in 2016 (63% 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 a

©PG Economics Ltd 201828

GM crop impact: 1996-2016

result, reports of first year performance 21 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% (+8.9% 2016) 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 $59.34/ha), the net impact on farm income in 2016, inclusive of yield gain, was +$110/ha.
Aggregated to the national level this was equal to an improvement in farm income of $2.33 billion
in 2016 and cumulatively since 2009, the total farm income gain has been $12.3 billion. The
technology also increased US soybean production by 29 million tonnes since 2009.

3.1.2 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 (99% plus). 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 (Table 11). More specifically:
•
•

•

•

•

21
22

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-$30/ha. Net income gains have been in the range of$14/ha-$24/ha;
The net income gain from use of the GM HT technology at a national level was $363
million in 2016. Since 1996, the cumulative benefit (in nominal terms) has been $6.3
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. Twenty-eight per cent of the total Argentine soybean crop was second cropin 2016 22, 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 to

The authors are not aware of any survey-based assessment of performance in 2009
The second crop share was about 5.2 million ha in 2016

©PG Economics Ltd 201829

GM crop impact: 1996-2016•

national soybean farm income of $732 million in 2016 and $12.3 billion cumulatively since
1996;
The total farm income benefit inclusive of the second cropping was $1.09 billion in 2016
and $18.6 billion cumulatively between 1996 and 2016.

Table 11: Farm level income impact of using GM HT soybeans in Argentina 1996-2016
Year

Cost savings ($/ha)

Net saving on
costs (inclusive of
cost of technology:$/ha)Increase in farmincome at anational level ($millions)

Increase in farmincome fromfacilitating
additional second
cropping ($ millions)
0
25
43
118
143
273
373
416
678
527
699
1,134
754
736
1,134
1,184
845
1,002
784
666
732

1996
26.10
22.49
0.9
1997
25.32
21.71
42
1998
24.71
21.10
115
1999
24.41
20.80
152
2000
24.31
20.70
205
2001
24.31
20.70
250
2002
29.00
27.82
372
2003
29.00
27.75
400
2004
30.00
28.77
436
2005
30.20
28.96
471
2006
28.72
26.22
465
2007
28.61
26.11
429
2008
16.37
13.87
230
2009
16.60
14.10
256
2010
18.30
15.80
285
2011
17.43
14.93
275
2012
16.48
13.98
269
2013
26.77
24.27
463
2014
25.41
22.91
425
2015
26.60
24.10
395
2016
26.13
23.63
363
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 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. 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). The source of gross margin data comes from Grupo CEO and the Argentine
Ministry of Agriculture
4. Additional information is available in Appendix 2
5. 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)©PG Economics Ltd 201830

GM crop impact: 1996-2016

6.

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
started to decline as increasing numbers of farmers plant the stacked (HT and IR) soybeans

3.1.3 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 2016 23.
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 2016 (Table 12). The net cost saving after deduction of the technology fee (assumed to be$7.5/ha in 2016) has been between $9/ha and $60/ha in recent years. At a national level, theadoption of GM HT soybeans increased farm income levels by $502 million in 2016.
Cumulatively over the period 1997 to 2016, farm incomes have risen by $7.22 billion (in nominal
terms).
Table 12: Farm level income impact of using GM HT soybeans in Brazil 1997-2016
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

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

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
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
23

Until 2003 all plantings were technically illegal©PG Economics Ltd 201831

GM crop impact: 1996-2016

2.

3.
4.

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
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
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
started to decline as increasing numbers of farmers plant the stacked (HT and IR) soybeans

3.1.4 Paraguay and Uruguay
GM HT soybeans have been grown since 1999 and 2000 respectively in Paraguay and Uruguay.
In 2016, they accounted for 96% of total soybean plantings in Paraguay and 98% of the soybean
plantings in Uruguay 24. Using the original farm level impact data derived from Argentine
research (on conventional alternatives) and 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) 25, Figure 6 summarises the national farm level
income benefits that have been derived from using the technology. In 2016, the respective
national farm income gains were $30.9 million in Paraguay ($83.1 million including second crop
benefits) and $24.2 million in Uruguay.
Figure 6: National farm income benefit from using GM HT soybeans in Paraguay and Uruguay
1999-2016 (million $)100.00
90.00
80.00
70.00
Million $

60.00
50.00
40.00
30.00
20.00
10.00
0.00

1

2

3

4

5

6

7

Paraguay24

8

9

10 11 12 13 14 15 16 17 18

Uruguay

As in Argentina, the majority of plantings are to farm saved or uncertified seed
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 inthese countries (source: based on AMIS Global/Kleffmann)
25©PG Economics Ltd 201832

GM crop impact: 1996-2016

3.1.5 CanadaFirst generation GM HT soybeans
GM HT soybeans were first planted in Canada in 1997. In 2016, the share of total plantings
accounted for by first generation GM HT soybeans was 35% (0.78 million ha).
At the farm level, the main impacts of use have been similar to the impacts in the US. The
average farm income benefit has been within a range of $14/ha-$45/ha and the increase in farmincome at the national level was $12.1 million in 2016 (Table 13). The cumulative increase in farmincome since 1997 has been $200.6 million (in nominal terms).
Table 13: Farm level income impact of using GM HT soybeans (first generation) in Canada
1997-2016
Year

Cost savings ($/ha)

Net cost saving/increase ingross margin (inclusive oftechnology cost: $/ha)
41.17
35.05
31.64
31.65
29.17
27.39
14.64
17.48
18.85
23.53
24.52
14.33
14.54
16.83
17.72
18.71
19.50
18.16
39.66
15.55

Impact on farm income at anational level ($ millions)

1997
64.28
0.041
1998
56.62
1.72
1999
53.17
6.35
2000
53.20
6.71
2001
49.83
9.35
2002
47.78
11.92
2003
49.46
7.65
2004
51.61
11.58
2005
55.65
13.30
2006
59.48
17.99
2007
61.99
16.87
2008
56.59
12.61
2009
55.01
12.66
2010
43.93
12.43
2011
44.31
9.45
2012
45.20
10.2
2013
45.05
2.55
2014
42.0
2.30
2015
74.84
22.5
2016
49.51
12.07
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. 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

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 1.14 million ha in 2016, equal to 52% 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 +$82.6/ha in 2016, with an aggregate increase in farmincome of +$94.3 million. Since 2009, the total farm income gain has been $662.8 million.

©PG Economics Ltd 201833

GM crop impact: 1996-2016

3.1.6 South Africa
The first year GM HT soybeans were planted commercially in South Africa was 2001. In 2016,
545,000 hectares (95%) of total soybean plantings were to varieties containing the GM HT trait. In
terms of impact at the farm level, net cost savings of between $1/ha and $31/ha have beenachieved through reduced expenditure on weed control (Table 14). At the national level, theincrease in farm income was $16.2 million in 2016. Cumulatively the farm income gain since 2001
has been $38.4 million 26.
Table 14: Farm level income impact of using GM HT soybeans in South Africa 2001-2016
Year

Cost savings ($/ha)

Net cost saving/increase ingross margin after inclusionof technology cost ($/ha)
7.02
5.72
7.90
9.14
9.12
5.17
5.01
1.77
0.54
5.56
1.95
4.51
8.70
7.94
8.72
29.7

Impact on farm income at anational level ($ millions)

2001
26.72
0.042
2002
21.82
0.097
2003
30.40
0.24
2004
34.94
0.46
2005
36.17
1.42
2006
33.96
0.83
2007
32.95
0.72
2008
25.38
0.32
2009
26.33
0.14
2010
33.64
1.97
2011
26.62
0.78
2012
28.20
2.10
2013
10.26
4.0
2014
9.32
4.9
2015
9.90
4.2
2016
30.7
16.2
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

3.1.7 Romania
In 2016, farmers in Romania are not permitted to plant GM HT soybeans, having joined the EU at
the start of 2007 (the EU regulatory authorities have not completed the process of evaluating past
applications for the approval for planting GM HT soybeans and currently there is no 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:

26

This possibly understates the beneficial impact because it does not take into consideration any savings from reduced labour for hand
weeding for some farms©PG Economics Ltd 201834

GM crop impact: 1996-2016

•

•

•
•

•

Yield gains of an average of 31% 27 have been recorded. This yield gain has arisen fromthe substantial improvements in weed control 28. In recent years, as fields have beencleaned of problem weeds, the average yield gains have decreased and were reported at+13% in 2006 29;
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 30) and cost savings derived;
The average net increase in gross margin in 2006 was $59/ha (an average of $105/ha overthe eight years of commercial use: Table 15);
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 31 (theannual average increase in production over the eight years was equal to 10.1%).

Table 15: 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

27

Source: Brookes (2005)
Weed infestation levels, particularly of difficult to control weeds such as Johnson grass, have been very high in Romania. This islargely a legacy of the economic transition during the 1990s which resulted in very low levels of farm income, abandonment of land andvery low levels of weed control. As a result, the weed bank developed substantially and has subsequently been very difficult to control,
until the GM HT soybean system became available (glyphosate has been the key to controlling difficult weeds like Johnson grass)
29
Source: Farmer survey conducted in 2006 on behalf of Monsanto Romania
30
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
31
Derived by calculating the yield gains made on the GM HT area and comparing this increase in production relative to total soybean
production
28©PG Economics Ltd 201835

GM crop impact: 1996-2016

3.
4.

Technology cost includes cost of herbicides
The technology was not permitted to be planted from 2007 – due to Romania joining the EU

3.1.8 Mexico
GM HT soybeans were first planted commercially in Mexico in 1997 on a trial basis and allowed‘unrestricted’ from 2012. In 2016, 2,810 ha (out of total plantings of 211,000 ha) were planted tovarieties containing the GM HT trait.
At the farm level, the main impacts of use have been a combination of yield increase (a range of+2% to +13%, varying on a yearly basis) from better weed control and (herbicide) cost savings. In
recent years, however, the GM HT trait has not been available in the latest varieties and therefore
the average yield of the GM soybeans (inclusive of yield gains from better weed control) has
typically been lower than the latest conventional varieties. The recorded average yield difference
between the GM HT soybeans and conventional alternatives has been between -1% and -2%. As
a result, the average farm income impact has been within a range of -$3/ha and +$89/ha (inclusiveof yield impact, cost savings and after payment of the technology fee/seed premium). In 2016, theincome effect was marginally positive (+$6/ha), as the cost savings associated with lower weed
control with the GM HT soybeans were larger than the revenue loss from a lower average yieldof -1.8%.
Table 16: 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 201836

GM crop impact: 1996-2016

3.1.9 Bolivia
GM HT soybeans were officially permitted for planting in 2009, although ‘illegal’ plantings haveoccurred for several years. For the purposes of analysis in this section, impacts have been
calculated back to 2005, when an estimated 0.3 million ha of soybeans used GM HT technology.
In 2016, 1 million ha (91% of total crop) used GM HT technology.
The main impacts of the technology 32 have been (Table 17):
•

•

•
•

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 2016;
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;
Overall in 2016, the average farm income gain from using GM HT soybeans was $52/ha,
resulting in a total farm income gain of $54 million. Cumulatively since 2005, the total
farm income gain is estimated at $776 million.

Table 17: Farm level income impact of using GM HT soybeans in Bolivia 2005-2016
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
Sources and notes:
1. Impact data based on Fernandez et al (2009). Average yield gain assumed +15%, cost of technology$3.32/ha

3.1.10 Summary of global economic impact
In global terms, the farm level impact of using GM HT technology in soybeans (excluding Intacta:
see section 3.2) was $3.59 billion in 2016 (Figure 9). If the second crop benefits arising inArgentina are included this rises to $4.37 billion. Cumulatively since 1996, the farm income

32

Based on Fernandez et al (2009)©PG Economics Ltd 201837

GM crop impact: 1996-2016

benefit has been (in nominal terms) $41.6 billion ($54.5 billion if second crop gains in Argentina
and Paraguay are included).
In terms of the total value of global soybean production in 2016, the additional farm income(inclusive of Argentine second crop gains) generated by the technology is equal to a value-added
equivalent of 4%.
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, $24.6 billion (45%) is due to yieldgains/second crop benefits and the balance, 55%, is due to cost savings.
Figure 7: Global farm level income benefits derived from using GM HT soybeans 1996-2016(million $)6,000

million $

5,000
4,000
3,000
2,000
1,000
0
96 97 98 99 0

1

2

3

4

5

6

Arg and Parag 2nd crop gains

7

8

9 10 11 12 13 14 15 16
Direct benefits

3.2 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 four-year period to 2016-17 is shown in Table 18.

©PG Economics Ltd 201838

GM crop impact: 1996-2016

The total farm income gain recorded on a cumulative total usage area of 49.6 million ha was $5.21
billion.
Table 18: Main impacts of insect resistant soybeans 2013/14 to 2016/17
Cumulative
area planted(‘000 ha)Average yieldgain (%)

Average costof technology(seedpremium)($/ha)
37.16
34.93
35.19
40.16

Average farmincome gain($/ha)

Aggregate
farm income
gain (million$)

Brazil
37,083+9.4
113.56
4,207.4
Argentina
7,791
+7.3
63.84
497.4
Paraguay
3,584
+11.2
121.97437.1
Uruguay
1,127
+7.6
61.68
69.5
Total
49,5855,211.4
Notes:
1. Impact data based on pre-commercial trials in 2011 and 2013 and post production farm surveys(post market monitoring: Monsanto)
2. Impact on cost of production includes herbicide cost savings, as indicated in section 3.1 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

3.3 Herbicide tolerant maize
3.3.1 The US
Herbicide tolerant maize 33 has been used commercially in the US since 1997 and in 2016 wasplanted on 89% of the total US maize crop. The impact of using this technology at the farm levelis summarised in Figure 8. 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 1996-2016 has been $24.21/ha ($26.54/ha in 2016) and the average weed
control cost savings equal to $52.5/ha ($65.33/ha in 2016). Average profitability has therefore
improved by $28.29/ha over the 1996-2016 period ($38.79/ha in 2016). The net gain to farmincome in 2016 was $1,212 million and cumulatively, since 1997, the farm income benefit has been
$8.45 billion.

33

Tolerant to glufosinate ammonium or to glyphosate (or both herbicides), although cultivars tolerant to glyphosate have accounted forthe majority of plantings©PG Economics Ltd 201839

GM crop impact: 1996-2016

Figure 8: National farm income impact of using GM HT maize in the US 1997-2015 (million $)
1,400
1,200

1,089

1,212
1,083 1,132

1,000Million $

822
800

669

600
400

400
200
0

3

42 37 57 61

97 98 9901

96 120
2

3

169

4

206

5

322

392 378

162

6

7

8

9

10 11 12 13 14 15 16

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

3.3.2 Canada
In Canada, GM HT maize was first planted commercially in 1999. In 2016, the proportion of total
plantings accounted for by varieties containing a GM HT trait was 97%. As in the US, the main
benefit has been to reduce costs and to improve profitability levels. Average annual profitability
has improved by $14.8/ha over the period 1999-2016, based on weed control savings of $44.67/ha
less the average additional cost of the technology over this period of $29.87/ha. In 2016, theaverage farm income gain was $18.43/ha (seed premium $26.11/ha) resulting in an aggregate
increase in farm income of $23.7 million. Since 1999 the farm income benefit has been $185.3
million (Figure 9).

©PG Economics Ltd 201840

GM crop impact: 1996-2016

Figure 9: National farm income impact of using GM HT maize in Canada 1999-2016 ($ million)
35.0
28.6 27.9

30.0

24.3 23.7

25.0
20.0
15.0
8.7

10.0
5.0
0.8

1.8

2.5

3.6

3.4

4.9

11.2 11.6

9.8

8.2

6.7
3.7

4.2

0.0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Source and notes: Impact analysis based on data from Ontario Ministry of Agriculture, Kleffmann herbicide
usage data and Monsanto Canada

3.3.3 Argentina
GM HT maize was first planted commercially in Argentina in 2004, and in 2016, varieties
containing a GM HT trait were planted on 4.19 million ha (87% 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 2016,
when 87% of the total crop used varieties containing an HT trait, 86% 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 about $15.8/ha over the period
2004-2016s;• 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 2004-2016 period has been $100.7/ha ($140.13/ha in 2016);• In 2016, the additional farm income at a national level, from using single traited GM HT
technology, was +$83.9 million, and cumulatively since 2004, the income gain has been
$364.8 million.

©PG Economics Ltd 201841

GM crop impact: 1996-2016

Stacked-traited GM HT seed
• The average yield gain identified since adoption has been +15.75% 34. Given the average
yield impact identified for the early years of adoption of the single traited GM IR maize
was +5.5% (see section 3.7), our analysis has applied this level of impact to the GM IR
component of the study (section 3.7), 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 2007-2016 has been $19.34/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 2016 was +$129.75/ha,
giving an aggregated national level farm income gain of $466 million. Cumulatively
since 2007, the farm income gain has been $2,027 million.

3.3.4 South Africa
Herbicide tolerant maize has been grown commercially in South Africa since 2003, and in 2016,1.93 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 2016 having been $5.2/ha (based on anaverage cost of technology of $14.21/ha and an average wed control cost reduction of $19.41/ha.
In 2016, the net farm income gain was +$9/ha. At the national level, this is equivalent to a net
gain of $17.4 million in 2016 and since 2003, the cumulative income gain has been $65.2 million.
Readers should note that these cost savings do not take into consideration any labour cost savingthat 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 yield gains of between +3% and +8% when using this technology relative toconventional maize growing in which hand weeding was the primary form of weed control
practice.

3.3.5 Philippines
GM HT maize was first grown commercially in 2006, and in 2016 was planted on 655,000
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
2006-2016, the average cost of the technology (seed premium) has been $39/ha ($42/ha in 2016),
which compared to the average reduction in weed control costs of $32/ha, resulted in a netincrease in total costs of production of about $7/ha 35. Nevertheless, the average impact on income
has been +$31.2/ha due to the higher yields. In 2016, the average net farm income gain from

34

Based on farm level feedback/surveys to the technology providers

35

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

©PG Economics Ltd 201842

GM crop impact: 1996-2016

using GM HT maize was +$22/ha, which at the national level was equal to +$14.4 million.
Cumulatively, since 2006, the total farm income gain has been $171 million.

3.3.6 Brazil
2016 was the eighth year in which GM HT maize was planted in Brazil (on 68% of the total crop:
11.91 million ha). A summary of the impacts of using this technology are shown in Table 19.
This shows that the technology is estimated to have delivered an average yield gain from
improved weed control of just over 4%. The average cost of production has increased slightly (by$3.48/ha), as the cost of the technology (seed premium: $17.56/ha) has been marginally greaterthan the savings from lower weed control costs$14.08/ha). In net farm income terms, inclusive ofyield gain, the average farm income gain has been $38/ha (just under $24/ha in 2016). At thenational level, the farm income gain was $282.8 million in 2016, and $1.83 billion (2009-2016).
Table 19: Farm level income impact of using GM HT maize in Brazil 2010-2016
Year

Average costof technology($/ha)

2016
Cumulative
2010-2016+10.57+17.56

Average yieldgain from
improved
weed control
%
+3
+4.1

Average change
in cost of
production (after
deduction of seedpremium: $/ha)
+4.45
+3.48

Averageincrease in net
farm income($/ha)+23.75+38.05

Increase infarm income
at a national
level ($
millions)
282.8
1,832

Source and notes: Galvao (2010-2015), industry data (on seed premiums and performance monitoring onfarms) and Kleffmann data on herbicide use

3.3.7 Colombia
GM HT maize was first planted in Colombia in 2009 and in 2016, 86,000 ha (19% of the total crop)used this technology (in the form of stacked traited seed, with GM IR technology). Analysis of its
impact is limited, with a study by Mendez et al (2011) being the only publicly available material.
This analysis focused only on a small area in one region of the country (San Juan valley) andtherefore is unlikely to be fully representative of (potential) impact across the country.
Nevertheless, as this represents the only available data, we have included it for illustrative
purposes. The analysis identified a positive yield impact of +22% for the stacked traited seed (HTtolerance to glufosinate and IR resistance to corn boring pests) and for the purposes of ouranalysis, all of this yield gain has been included/attributed to the GM IR component of thetechnology, as presented in section 3.7.8. 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 $13.2/ha in 2016 (seedpremium of $19/ha, counterbalanced by weed control cost savings of $32/ha). At the national
level, the total income gain in 2016 was $1.14 million ($5.96 million since 2009).

3.3.8 Uruguay
Maize farmers in Uruguay gained access to GM HT maize technology in 2011 (via stacked traitedseed) and 48,800 ha of the country’s 57,000 ha crop used this technology in 2016. Whilst the©PG Economics Ltd 201843

GM crop impact: 1996-2016

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 small
levels of farm income gains of about $3.7/ha, equal to about $0.18 million at the national level in2016 ($1.36 million: 2011-2016).

3.3.9 Paraguay
GM HT technology was used for the first time in 2013 in Paraguay, and in 2016, 37% of thecountry’s maize crop (260,000 ha) used seed containing this trait. Based on an average seedpremium of $15.6/ha (source: industry) and an estimated average herbicide cost saving of$18.2/ha (sources: industry and AMIS Global 2013 and 2015), the average farm income gain has
been $2.6/ha (2016 $5.9/ha). At the national level, this was equal to about $1.56 million in 2016
and a cumulative gain of $4.05 million since 2013.

3.3.10 Vietnam
GM HT maize was first planted commercially in 2015, and in 2016 was planted on 35,000 ha (3%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. Assuming that 5% of
this yield gain has arisen from improved weed control, coupled with a cost of technology of$25.9/ha, the average farm income gain over the two years of adoption has been $37.3/ha. At thenational level, this equates to an aggregate net farm income gain of $1.43 million.

3.3.11 Summary of global economic impact
In global terms, the farm level economic impact of using GM HT technology in maize was $2.1
billion in 2016 (58% of which was in the US). Cumulatively since 1997, the farm income benefit
has been (in nominal terms) $13.1 billion. Of this, 66% has been due to cost savings and 34% 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.

3.4 Herbicide tolerant cotton
3.4.1 The US
GM HT cotton was first grown commercially in the US in 1997 and in 2016 was planted on 89% of
total cotton plantings 36.
The farm income impact of using GM HT cotton is summarised in Table 20. The primary benefit
has been to reduce costs, and hence improve profitability levels. Over the period to 2016, theaverage farm income gain has been $20/ha. In 2016, the net income gain was $10.72/ha. Overall,
the aggregate net direct farm income impact in 2016 is estimated to be $36.7 million (this does not

36

Although there have been GM HT cultivars tolerant to glyphosate and glufosinate, glyphosate tolerant cultivars have dominated©PG Economics Ltd 201844

GM crop impact: 1996-2016

take into consideration any non-pecuniary benefits associated with adoption of the technology:
see section 3.10). Cumulatively since 1997 there has been a net farm income benefit from using
the technology of $1.13 billion.
Table 20: Farm level income impact of using GM HT cotton in the US 1997-2016
Year

Cost savings($/ha)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

34.12
34.12
34.12
34.12
65.59
65.59
65.59
83.35
71.12
73.66
76.01
77.60
83.69
94.81
99.24
91.08
94.73
88.22
82.78
78.14

Net cost saving/increase in grossmargins, inclusive of cost oftechnology ($/ha)
21.28
21.28
21.28
21.28
45.27
45.27
45.27
48.80
2.89
3.31
5.40
6.14
7.49
13.57
17.64
16.95
20.60
14.09
8.65
10.72

Increase in farm income at anational level ($ millions)
12.56
30.21
53.91
61.46
161.46153.18129.75154.72
9.57
13.29
16.56
12.79
18.96
46.72
49.33
50.14
51.71
47.51
24.68
36.72

Source and notes:
1.

Impact analysis based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006) andJohnson & Strom (2008) and own analysis from 2008

2.

Average cost of technology 1997-2007: $49.95/ha (sources: industry, Kynetec)

3.4.2 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 2016, 98% (560,000 ha), 100%
(240,000 ha), 100% (17,840 ha), 98% (98,000 ha), 52% (9,075 ha) and 66% (623,000 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. In Australia, although research has been conducted into the©PG Economics Ltd 201845

GM crop impact: 1996-2016

impact of using GM HT cotton (eg, Doyle et al (2003)) this does not provide quantification of the
impact 37. Drawing on industry source estimates 38, the main impacts are summarised in Table 21.
Table 21: Summary of 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$)+63.5

Averagereduction in
weed control
costs before
deduction oftechnology
cost ($/ha)-91.20Australia(2000-2016)
Argentina(2002-2016)
South Africa(2001-2016)
Mexico (20062016)
Colombia(2006-2016)
Brazil (20092016)

Nil+27.70+113.20+1.6+20.49-23.83+42.79+183.90Nil+19.49-52.06+32.57+4.80+12+58.75-38.87+266.94+274.4+4+153.0-194.06+94.71+24.79+1.6+37.30-61.66+61.79+180.33.4.3 Summary of global economic impact
Across the seven countries using GM HT cotton in 2016, the total farm income impact derived
from using GM HT cotton was +$130.1 million. Cumulatively since 1997, there have been net
farm income gains of $1.92 billion. Of this, 72% has been due to cost savings and 28% to yieldgains (from improved weed control relative to the level of weed control achieved using
conventional technology).

3.5 Herbicide tolerant canola
3.5.1 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 2016 was 95% of
the total crop (7.68 million ha of GM HT crop).
The farm level impact of using GM HT canola in Canada since 1996 is summarised in Table 22.
The key features are as follows:•

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

37

This largely survey-based research observed a wide variation of impact with yield and income gains widely reported for many farmers
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 and Galvão (2010-2015)38©PG Economics Ltd 201846

GM crop impact: 1996-2016

•

•

•

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 39 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 table 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 $473 million in 2016. The cumulative farm income benefit over the
1996-2016 period (in nominal terms) was $5.52 billion.

Table 22: Farm level income impact of using GM HT canola in Canada 1996-2016
Year

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

Cost savings($/ha)

28.59
28.08
26.21
26.32
26.32
25.15
24.84
28.04
21.42
23.11
34.02
35.44
40.59
33.29
40.94

Cost savings
inclusive of cost oftechnology ($/ha)
-4.13
-4.05
-3.78
-3.79
-3.79
-1.62
-3.59
-4.05
+4.44
+4.50
+16.93+17.46+22.45+13.52+22.78Net cost
saving/increase ingross margins($/ha)
45.11
37.11
36.93
30.63
22.42
23.10
29.63
41.42
19.09
32.90
50.71
66.39
69.82
55.40
78.46

39

Increase in farm income at anational level ($ millions)

6.23
21.69
70.18
90.33
59.91
53.34
61.86
132.0870.72
148.12233.13341.44389.94321.42475.34The 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 201847

GM crop impact: 1996-2016

2011
51.65
+32.7665.81
457.242012
47.52+28.8055.84
445.85
2013
23.15
+5.08
74.06
549.68
2014
20.05
+4.99
66.59
527.33
2015
20.24
+8.45
79.82
601.282016
24.85+12.9861.57
472.89Sources 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. For GM glufosinate tolerant varieties, the yield 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
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

3.5.2 The US
GM HT canola has been planted on a commercial basis in the US since 1999. In 2016, 90% of the
US canola crop was GM HT (613,600 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 3.5.1) 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’);
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 ($8/ha in 2016) for glufosinate tolerant canola
and $19-$79/ha for glyphosate tolerant canola ($23/ha 2016);
The net impact on gross margins has been between +$22/ha and +$90/ha ($43.7/ha in2016) for glufosinate tolerant canola, and between +$23/ha and +$61/ha for glyphosate
tolerant canola ($25.4/ha in 2016);
At the national level the total farm income benefit in 2016 was $21.4 million (Figure 10)
and the cumulative benefit since 1999 has been $360.9 million.

©PG Economics Ltd 201848

GM crop impact: 1996-2016

Figure 10: National farm income impact: GM HT canola in the US 1999-2016 (million $)
35.0
30.0

22.9

20.0
15.0

12.8

21.3

20.2

18.9 18.1

27.6

26.8

26.5

25.0
Million $

31.1

31.1

17.2

22.2

21.4

16.0

11.2 11.4

10.0
5.0

4.1

0.0
99

0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16

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 3.5.1

3.5.3 Australia
GM HT canola was first planted for commercial use in 2008. In 2016, GM HT canola was plantedon 448,000 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
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©PG Economics Ltd 201849

GM crop impact: 1996-2016••

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 23, 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 has 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 $34.7/ha and a total farm income gain of $15.5 million in
2016. Cumulatively since 2008, the total farm income gain has been $89.9 million (Table 21).
It is noted that the share of GM HT canola has risen to only 20% 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 withweeds 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.

©PG Economics Ltd 201850

GM crop impact: 1996-2016

Table 23: Farm level income impact of using GM HT canola in Australia 2008-2016 ($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
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. Quality (price) premium of 2.1% applied on thebasis of this level of increase in average oil content. In 2010 because of a non GM canola pricepremia of 7%, the net impact on price was to apply a price discount of -4.9%. In 2011 because of anon GM canola price premia of 7%, the net impact on price was to apply a price discount of -2.9%.
Since 2012, the price discount applied is -2%

3.5.4 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 $509.9 million in 2016. Cumulatively since 1996, the farm income benefit has
been (in nominal terms) $5.97 billion. Within this, 76% has been due to yield gains and thebalance (24%) has been from cost savings.
In terms of the total value of canola production in these three countries in 2016, the additionalfarm income generated by the technology is equal to a value-added equivalent of 5.5%. Relative
to the value of global canola production in 2016, the farm income benefit added the equivalent of
1.82%.

3.6 GM herbicide tolerant (GM HT) sugar beet

3.6.1 USGM HT sugar beet was first grown commercially in the US in 2007. In 2016, 455,800 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©PG Economics Ltd 201851

GM crop impact: 1996-2016

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 forherbicides 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 40 ), 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 3.10, estimated in the corn, 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

40

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 201852

GM crop impact: 1996-2016

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 (Table 24) 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, these havebeen updated to reflect changes in seed prices/premia, herbicide usage patterns and herbicide
prices. This shows a net farm income gain in 2016 of $48.3 million to US sugar beet farmers(average gain per hectare of $105.95/ha). Cumulatively, the farm income gain, since 2007 has
been $454 million.
Table 24: Farm level income impact of using GM HT sugar beet in the US 2007-2016
Year

Average costsaving ($/ha)

Average cost savings Average net increase
Increase in farm income at(net after cost ofin gross margins
a national level (‘000 $)technology: $/ha)($/ha)
2007
353.35222.39584.00473
2008
141.50-10.6675.48
19,471.4
2009
142.5
-8.69
108.0946,740.9
2010
142.5
-8.69
153.94
68,529.6
2011
101.81-46.19112.0751,167.2
2012
101.81-46.19113.0955,452.3
2013
149.81+1.81
115.4852,849.0
2014
154.22+6.22
117.2653,326.8
2015
163.84+15.84120.8254,883.8
2016
150.54+2.54
105.9548,290.8
Sources 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+2.79%, +3.21%, +3.21%, +3.19%, +3.27%, +3.12%, +3.2%, +3.55%, +3.58% respectively for 2008, 2009,2010, 2011, 2012, 2013, 2014, 2015, 2016
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 was used

©PG Economics Ltd 201853

GM crop impact: 1996-2016

3.6.2 Canada
GM HT sugar beet has also been used in the small Canadian sugar beet sector since 2008. In 2016,all of crop of 111,575 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 2016 was $1.44 million and cumulatively since 2008, theincome gain has been $12.14 million.

3.7 GM insect resistant 41 (GM IR) maize
3.7.1 USGM IR maize was first planted in the US in 1996 and in 2016 seed containing GM IR traits wasplanted on 79% (27.73 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 Table 25:
•

•

•

•

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 revised analysis has
been used as the basis for our analysis below. In 2016, this additional production is equal
to an increase in total US maize production of +6%;
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 42, 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 $2.07 billion in 2016. The cumulative farm income benefit overthe 1996-2016 period (in nominal terms) was $25.3 billion;
The average net farm income gain over the period 1996-2016 has been +$80.91/ha.

Table 25: Farm level income impact of using GM IR maize in the US 1996-2016
Year

Cost saving($/ha)

1996
1997
1998
1999
2000
2001
2002
2003

15.50
15.50
8.12
5.98
8.16
8.16
6.33
5.34

Cost savings (net after
cost of technology:
$/ha)
-9.21
-9.21
-12.18-14.32-14.08-14.08-15.91-16.9041

Net increase in grossmargins ($/ha)
45.53
39.38
27.93
23.63
25.37
28.34
30.96
31.22

Increase in farmincome at a national
level ($ millions)
13.54
96.0
179.2
188.5
163.3
160.0
234.7
297.9

The first generation being resistant to stalk boring pests but latter generations including resistance against cutworms and earworms
Which tends to be mostly purchased as stacked-traited seed – for this aspect of technology the seed premium has been in the range of$25/ha to $30/ha in recent years compared to the ‘lower $20s/ha 10-15 years ago
42©PG Economics Ltd 201854

GM crop impact: 1996-2016

2004
4.82
-17.42
33.84
420.0
2005
4.54
-12.76
33.15
381.4
2006
3.98
-13.33
55.23
752.4
2007
3.24
-14.0666.05
1,375.9
2008
2.79-14.1389.20
1,755.7
2009
2.52-18.1478.81
1,738.2
2010
2.52-21.4087.43
1,799.7
2011
2.45-21.25127.203,101.9
2012
2.37-21.87114.152,905.1
2013
2.09-24.1498.13
2,875.9
2014
1.99-25.5089.58
2,628.92015
1.96-26.0474.86
2,170.8
2016
2.01-23.7366.38
2,067.3
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

3.7.2 Canada
GM IR maize has also been grown commercially in Canada since 1996. In 2016, it accounted for
79% (1.05 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 national level, this equates to additional farm income generated from the use of GM IR maizeof $64.9 million in 2016 (Figure 11) and cumulatively since 1996, additional farm income (innominal terms) of $1.04 billion. On a per hectare basis, the average farm income benefit has been
$75.09/ha (1997-2016).

©PG Economics Ltd 201855

GM crop impact: 1996-2016

Figure 11: National farm income impact: GM IR maize in Canada 1996-2016 (million $)
160.0

143.1

140.0

122.3

Million $

120.0

103.1

100.0

81.8

80.0

66.8

60.0

61.1

73.3

65.0

52.1

35.8

40.0
20.0

107.7

3.2

9.8 12.1

7.6 11.2

18.4 19.7

23.1 20.0

2

4

0.0
97 98 99
Notes:
1.

2.
3.

0

1

3

5

6

7

8

9

10 11 12 13 14 15 16

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

3.7.3 Argentina
In 2016, GM IR maize traits were planted on 84% 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.
More recent trade source estimates provided to the authors put the average yield increase in thelast 10 years to be between 5% and 6%. Our analysis uses a yield increase value of 5.5% for theyears 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. As such, average costs ofproduction increased by $20/ha-$27/ha (the cost of the technology) in years up to 2006. From2007, with stacked-traited seed becoming available and widely used, the additional cost of thetechnology relative to conventional seed has been in the range of $10/ha-$33/ha, with an average
cost over the 1998-2016 period of $25.05/ha.

©PG Economics Ltd 201856

GM crop impact: 1996-2016

The net impact on farm profit margins (inclusive of the yield gain) has, in recent years, been an
increase of $3/ha to $66/ha. In 2016, the national level impact on profitability was an increase of$233.7 million. Cumulatively, the farm income gain, since 1998 has been $1.11 billion.

3.7.4 South Africa
GM IR maize has been grown commercially in South Africa since 2000. In 2016, 91% of thecountry’s total maize crop of 2.63 million ha used GM IR cultivars.
The impact on farm profitability is summarised in Table 26. 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% 43 (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.
At the national level, the increase in farm income in 2016 was $293.6 million and cumulatively
since 2000 it has been $2.17 billion. In terms of national maize production, the use of GM IR
technology has resulted in a net increase in national maize production of 9.6% in 2016.
Table 26: Farm level income impact of using GM IR maize in South Africa 2000-2016
Year

Cost savings ($/ha)

Net cost savings
inclusive of cost oftechnology ($/ha)
1.87
1.51
0.6
0.4
0.46
0.47
-2.36
0.22
-4.55
-2.12
-2.30
-1.64
-0.97
-0.31
0.00
-0.78
0.00

Net increase in grossmargin ($/ha)

Impact on farm income
at a national level ($millions)
3.31
4.46
19.35
14.66
8.43
19.03
63.05
225.70145.20148.94132.61140.89272.26305.92
218.19157.54293.61

2000
13.98
43.77
2001
11.27
34.60
2002
8.37
113.98
2003
12.82
63.72
2004
14.73
20.76
2005
15.25
48.66
2006
14.32
63.75
2007
13.90
182.90
2008
11.74
87.07
2009
12.83
62.05
2010
13.97
70.58
2011
12.65
77.20
2012
12.79
112.502013
11.39
129.63
2014
11.06
82.21
2015
10.19
89.93
2016
10.20
122.75
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
43

Van der Weld (2009)©PG Economics Ltd 201857

GM crop impact: 1996-2016

3.7.5 Spain
Spain has been commercially growing GM IR maize since 1998 and in 2016, 36% (129,100 ha) of
the country’s maize crop was planted to varieties containing a GM IR trait.
As in the other countries planting GM IR maize, the main impact on farm profitability has been
increased yields (an average increase in yield of 6.3% across farms using the technology in theearly years of adoption). With the availability and widespread adoption of the Mon 810 traitfrom 2003, the reported average positive yield impact is about +10% 44. There has also been a net
annual average saving on cost of production (from lower insecticide use) of between $37/ha and$61/ha 45 in the early years of adoption (Table 27). This has been the basis of analysis to 2008.
From 2009, the analysis draws on Riesgo et al (2012). Over the period 1998-2016, the average coatof the technology has been$42/ha and the average farm income gain $206.7/ha. This income gain
derives mostly from higher yields, with an average of about $23/ha coming from less expenditure
on insecticides. At the national level, these yield gains and cost savings have resulted in farmincome being boosted, in 2016, by $23.5 million and cumulatively since 1998 the increase in farmincome (in nominal terms) has been $274.8 million.
ii

Relative to national maize production, the yield increases derived from GM IR maize wereequivalent to a 3.1% increase in national production (2015).
Table 27: Farm level income impact of using GM IR maize in Spain 1998-2016
Year

Cost savings ($/ha)

Net cost savings
inclusive of cost oftechnology ($/ha)
3.71
12.80
12.94
21.05
22.18
26.58
28.79
8.72
8.78
9.55
10.25
-39.33-39.27-37.72-36.75-37.97-37.92-31.70-31.53

Net increase in grossmargin ($/ha)

Impact on farm income
at a national level ($millions)
2.14
2.56
2.24
1.10
2.10
3.93
6.52
7.70
10.97
20.63
17.86
13.11
19.59
28.47
37.25
29.38
26.04
19.61
23.50

1998
37.40
95.16
1999
44.81
102.20
2000
38.81
89.47
2001
37.63
95.63
2002
39.64
100.652003
47.50
121.682004
51.45
111.932005
52.33
144.74
2006
52.70
204.5
2007
57.30
274.592008
61.49
225.362009
8.82
172.312010
8.80
255.872011
8.46
292.53
2012
8.24
320.3
2013
8.51
214.5
2014
8.50
198.0
2015
7.11
182.0
2016
7.09
182.1
Sources and notes:
1. Impact data (based on Brookes (2003), Brookes (2008) 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 2004and €35/ha from 2005, insecticide cost savings €42/ha to 2008, €6.4/ha 2009 onwards

44
45

The cost of using this trait has been higher than the pre-2003 trait (Bt 176) – rising from about €20/ha to €35/ha
Source: Brookes (2003) and Alcade (1999)©PG Economics Ltd 201858

GM crop impact: 1996-2016

2.

All values for prices and costs denominated in Euros have been converted to US dollars at theannual average exchange rate in each year

3.7.6 Other EU countries
A summary of the impact of GM IR technology in other countries of the EU is presented in Table
28. This shows that in 2016, the additional farm income derived from using GM IR technology inthese three countries was +$1.07 million, and cumulatively over the period 2005-2016, the total
income gain was $24.6 million.
Table 28: Farm level income impact of using GM IR maize in other EU countries 2016
Year firstplanted
GM IR
maize

Area
(hectares)

Yield
impact(%)

Cost oftechnology($/ha)

Cost
savings(beforedeductionof cost oftechnology:
$/ha)
0
19.91

Net
increasein grossmargin($/ha)

Impact on
farm
income ata national
level(million
$)
1.05
0.01

Portugal
2005
7,069
+12.5
38.72
149.12
Czech
2005
75
+10
38.72
111.27
Republic
Slovakia
2005
138
+12.3
38.72
0
86.97
0.01
Total
7,282
1.07
other EU
(excluding
Spain)
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

3.7.7 Brazil
Brazil first used GM IR maize technology in 2008. In 2016, 14.88 million ha of GM IR maize wereplanted (85% of the total crop). Analysis from Galvao (2009-2015) and Kleffmann pesticide usage
data has been used as the basis for estimating the aggregate impacts on farm income and ispresented in Table 29. Over the period 2008-2016, the average yield gain has been +11.8%, theaverage cost of the technology $56.3/ha and the average farm income gain 73.79/ha. In 2016, thetotal income gain was $936.5 million, with the cumulative benefit since 2008 equal to $6.22 billion.
Table 29: Farm level income impact of using GM IR maize in Brazil 2008-2016
Year

Cost savings ($/ha)

2008
2009
2010
2011
2012
2013

41.98
44.21
48.60
23.13
13.35
18.22

©PG Economics Ltd 2018

Net cost savings
inclusive of cost oftechnology ($/ha)
20.93-14.63-5.39-46.25-38.86-29.0959

Net increase in grossmargin ($/ha)
66.36
30.37
55.74
131.4888.12
115.63

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

GM crop impact: 1996-2016

2014
16.69
50.93
54.72
651.702015
13.58-41.4440.33
499.362016
13.46-41.0862.93
936.43
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

3.7.8 Other countries
GM IR maize has been grown commercially in:
•

•

•

•

•

The Philippines since 2003. In 2016, 652,610 hectares out of total plantings of 2.68 million(24%) were GM IR. 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 this range (+24.15%) was used for the years 2003-2007.
From 2008, a yield impact of +18% has been used based on Gonsales et al (2009). Basedon the findings of these research papers, a small average annual insecticide cost savingof about $12/ha-$15/ha and average cost of the technology of $42/ha have been used.
The net impact on farm profitability has been +$100.17/ha. In 2016, the national farmincome benefit derived from using the technology was $68 million and cumulative farmincome gain since 2003 has been $553 million;
Uruguay since 2004, and in 2016, 46,400 ha (81% of the total crop) were GM IR. Using
Argentine data as the basis for assessing impact, the average farm income gain over the
2004-2016 period has been +$30.1/ha. In 2016, the aggregate income gain was $2.82
million and cumulatively the farm income gain has been $29.6 million;
Honduras. Here farm level ‘trials’ have been permitted since 2003, and in 2016, 38,700 ha
used GM IR traits. 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 productionsavings 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 wasassumed. From 2006, the seed premium applied is based on Falck-Zepeda et al (2009) at$100/ha. Based on these costs, the estimated farm income benefit derived from thetechnology in 2016 was $1.11 million and cumulatively since 2003 the income gain has
been $11.47 million;
Colombia. GM IR maize has been grown on a ‘trial basis’ since 2007 in Colombia. In
2016, seed containing this technology was used on 18% of the crop (79,750 ha). Based on
analysis from Mendez et al (2011) which explored impacts in one small region (San Juanvalley), the average yield gain was +22%, the seed premium about $47/ha and thesavings in insecticide use equal to about $51/ha (ie, a net cost saving of about $5/ha).
Inclusive of the yield gain, the average farm income gain in the period 2007-2016 has
been $274.9/ha. The aggregated net farm income gain in 2016 was $26.6 million andcumulatively since 2007, the net farm income gain has been $130 million;
Paraguay. The first commercial crop of maize using this technology was grown in 201314. In 2016, 42% of the total crop (710,000 ha total crop) used seed containing this©PG Economics Ltd 201860

GM crop impact: 1996-2016•

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: Monsanto Paraguay), the average farm income gain from using thetechnology has been +$19.4/ha ($31/ha in 2016). At the national level, this is equivalent
to a total farm income gain of $9.3 million in 2016 and over the four years, the total farmincome benefit has been $32 million.
Vietnam. GM stacked maize (HT and IR traits) was first planted commercially in 2015,
and in 2016 was planted on 35,000 ha (3% of the total crop). Based analysis by Brookes(2017), the yield gain attributable to the IR trait is +7.2%. Coupled with a cost oftechnology of $38.88/ha (IR trait only), the average farm income gain over the two yearsof adoption has been $105.22/ha (inclusive of insecticide cost savings of $66.85/ha). At
the national level, this equates to an aggregate net farm income gain of $4.05 million for
the two years 2015 and 2016.

3.7.9 Summary of economic impact
In global terms, the farm level impact of using GM IR maize was $3.72 billion in 2016.
Cumulatively since 1996, the benefit has been (in nominal terms) $36.9 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 2016,
the additional farm income generated by the technology is equal to a value-added equivalent of
4.2%. Relative to the value of global maize production in 2016, the farm income benefit added theequivalent of 2.3%.

3.8 Insect resistant (Bt) cotton (GM IR)
3.8.1 The US
GM IR cotton has been grown commercially in the US since 1996, and in 2016 was used on 84%(3.23 million ha) of total cotton plantings.
The farm income impact of using GM IR cotton is summarised in Table 30. The primary benefit
has been increased yields (by 9%-11%), although small net savings in costs of production havealso been obtained (reduced expenditure on insecticides being marginally greater than the cost of
the technology for Bollgard I). Overall, average profitability levels increased by $53/ha-$115/hawith Bollgard I cotton (with a single Bt gene) between 1996 and 2002 and by between $87/ha and$151/ha in 2003-2016 with Bollgard II (containing two Bt genes and offering a broader spectrumof control). Overall, the average farm income gain (1996-2016) has been $110.67/ha. The net
aggregated farm income gain in 2016 of $408.5 million. Cumulatively, since 1996 the farm income
benefit has been $5.43 billion.
Table 30: Farm level income impact of using GM IR cotton in the US 1996-2016
Year
1996

Cost savings (net after
cost of technology: $/ha)
4.98©PG Economics Ltd 2018

Net increase in gross margins($/ha)
115.32

61

Increase in farm income at anational level ($ millions)94.69

GM crop impact: 1996-2016

1997
4.98
103.47
87.28
1998
4.98
88.54
80.62
1999
4.98
65.47
127.29
2000
4.98
74.11
162.88
2001
4.98
53.04
125.22
2002
4.98
69.47
141.862003
5.78
120.49239.982004
5.78
107.47261.232005
24.48
117.81
332.41
2006
-5.77
86.61
305.172007
2.71
114.50296.00
2008
2.71
98.22
189.502009
2.71
128.04296.792010-21.02
122.65395.282011-21.02151.13434.11
2012-21.02144.45421.842013-17.61131.02300.81
2014-17.61129.33402.602015-17.61100.95271.852016-13.13126.39408.49Sources 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: 1996-2016 $49.37/ha
4. Average insecticide cost savings 1996-2016: $44.75/ha

3.8.2 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 2.9 million ha crop in 2016.
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 2016, the average increase in profitability was +$359.5/ha and for theperiod 1996-2016 has been $349/ha. At the aggregate level, the net national gain was $990 million
and cumulatively since 1997 the farm income benefit has been $19.64 billion (Table 31).
Table 31: Farm level income impact of using GM IR cotton in China 1997-2016
Year
1997
1998
1999
2000
2001
2002
2003

Cost savings (net after cost oftechnology: $/ha)
194
194
200
-14
378
194
194

©PG Economics Ltd 2018

Net increase in grossmargins ($/ha)
333
310
278
123
472
327
328

62

Increase in farm income at anational level ($ millions)
11.33
80.97
181.67150.181,026.26
687.27917.00GM crop impact: 1996-2016

2004
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
319
1,306.8
2015
28.3
338
1,005.0
2016
26.07
359
990.4
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 1996-2016 $52.81/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

3.8.3 Australia
Australia planted 95% of its 2016 cotton crop (total crop of 580,000 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 cultivars); with the primary farm income benefit being derived
from lower costs of production (Table 32). 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 $186/ha to$270/ha. The average increase in farm income over the period 1996-2016 has been
$210.81/ha;
At the national level in 2016, the net farm income gain was $103.74 million andcumulatively since 1996 the gains have been $953.7 million.

©PG Economics Ltd 201863GM crop impact: 1996-2016

Table 32: Farm level income impact of using GM IR cotton in Australia 1996-2016
Year

Cost of
Net increase in gross margins/cost
Increase in farm income at atechnology ($/ha) saving after cost of technology ($/ha) national level ($ millions)1996-191.7
-41.0
-1.63
1997
-191.7
-35.0
-2.04
1998
-97.4
91.0
9.06
1999
-83.9
88.1
11.80
2000
-89.9
64.9
10.71
2001
-80.9
57.9
7.87
2002
-90.7
54.3
3.91
2003
-119.3
256.1
16.3
2004
-179.5
185.8
45.7
2005
-229.2
193.4
47.9
2006
-225.9
190.7
22.49
2007
-251.33
212.1
11.73
2008
-264.26
199.8624.23
2009-257.75232.2737.05
2010-292.17263.28125.02
2011-298.77
269.23148.482012-300.93265.50108.792013-289.58244.4397.42
2014-270.51228.3444.72
2015-225.39190.2648.19
2016-223.05
188.28103.74
Sources and notes:
1. Impact data based on Fitt (2001) and CSIRO for Bollgard II since 2004
2. Average cost of technology 1996-2016: $235.33/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

3.8.4 Argentina
GM IR cotton has been planted in Argentina since 1998. In 2016, it accounted for 92% of total
cotton plantings (220,800 ha).
The main impact in Argentina has been yield gains of 30%. This has more than offset the cost ofusing the technology 46. In terms of gross margin, cotton farmers have gained between $25/ha and$317/ha annually during the period 1998-2015 47. The average increase in farm income over theperiod 1998-2016 has been $240/ha. At the national level, the farm income gain was $52.2 million
in 2016 (Figure 12). Cumulatively since 1998, the farm income gain from use of the technology
has been $921 million.

46
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 insecticide cost savings have been $54/ha-$74/ha(average of $49.78/ha for the period 1998-2016)47
The variation in margins has largely been due to the widely fluctuating annual price of cotton©PG Economics Ltd 201864

GM crop impact: 1996-2016

Figure 12: National farm income impact: GM IR cotton in Argentina 1998-2016 (million $)160.0

140.7144.6

140.0

112.7

120.0
Million $

150.4

114.8

100.0
80.0

65.9

60.0
40.0
20.0
0.0

52.2

44.3
26.2 27.4
0.3 1.0 2.1 0.2 1.1
98 99

0

1

2

9.2 13.7
3

4

2.9
5

11.2
6

7

8

9

10 11 12 13 14 15 16

Sources and notes:
1. Impact data (source: Qaim & De Janvry (2002) and for 2005 and 2006 Monsanto LAP, although costof technology in 2005 from Monsanto Argentina). Area data : source ArgenBio
2. Yield impact +30%, cost of technology $86/ha ($40/ha 2005), cost savings (reduced insecticide use)in the last five years $54/ha-$69/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

3.8.5 Mexico
GM IR cotton has been planted commercially in Mexico since 1996. In 2016, GM IR cotton wasplanted on 94,000 ha (94% 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 ten years. In addition, there have been important savings in the cost of
production (lower insecticide costs) 48. Overall, the annual net increase in farm profitability has
been within the range of $104/ha and $378/ha (Table 33). At the national level, the farm income
benefit in 2016 was $19.6 million and the impact on total cotton production was an increase of
14%. Cumulatively since 1996, the farm income benefit has been $272.1 million.
Table 33: Farm level income impact of using GM IR cotton in Mexico 1996-2016
Year
1996
1997
1998

Cost savings (net after
cost of technology: $/ha)
58.1
56.1
38.4

Net increase in grossmargins ($/ha)
354.5
103.4
316.4

48

Increase in farm income at anational level ($ millions)
0.3
1.7
11.3

Cost of technology has annually been between $48/ha and $99.5/ha, based on estimated share of the trait largely sold as a stacked
trait, insecticide cost savings 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

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GM crop impact: 1996-2016

1999
46.5
316.8
5.3
2000
47.0
262.4
6.8
2001
47.6
120.6
3.0
2002
46.1
120.8
1.8
2003
41.0
127.7
3.3
2004
39.3
130.4
6.2
2005
40.8
132.3
10.4
2006
20.4
124.4
6.4
2007
20.5
139.7
8.4
2008
19.9
150.4
10.5
2009
-22.16
253.2
7.7
2010
-40.81
220.8
10.9
2011
-37.61
290.3
29.0
2012
-60.16
127.0
12.7
2013
-57.75
199.5
19.9
2014
-40.71
378.3
58.26
2015
-47.66
268.6
31.71
2016
-38.78208.6
19.61
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 1996-2016 +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

3.8.6 South Africa
In 2016, GM IR cotton 49 was planted on all of the cotton crop in South Africa (17,840 ha).
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. Combining thepositive yield effect and the increase in cost of production, the net effect on profitability has been
an annual increase of between $27/ha and $507/ha (average gain of $151.5/ha 1998-2016).
At the national level, the aggregated farm income benefits have varied ((Figure 13)), largely inline with the changes in area planted to cotton (which has varied between 7,000 ha and 18,000 ha
per year). Cumulatively since 1998, the farm income benefit has been $34.5 million.

49

First planted commercially in 1998

©PG Economics Ltd 201866

GM crop impact: 1996-2016

Figure 13: National farm income impact: GM IR cotton in South Africa 1998-2016 (million $)
6,000

5,678

5,000
4,024
3,549

'000 $

4,000

3,912

3,000

2,630

2,335

2,122
2,000

1,589
1,2451,214

1,000
0

4 143
98 99

544

0

1,178
968

517

385
1

1,1921,257

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16

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) $12/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)

3.8.7 India
GM IR cotton has been planted commercially in India since 2002. In 2016, 10.42 million ha wereplanted to GM IR cotton which is equal to 96% of total plantings.
The main impact of using GM IR cotton has been major increases in yield 50. With respect to costof production, the average cost of the technology (seed premium: $49/ha to $54/ha) up to 2006
was greater than the average insecticide cost savings of $31/ha-$58/ha resulting in a net increasein costs of production. 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 seed premium for theperiod 2002-2016 is equal to about $17/ha. Coupled with the yield gains, important net gains tolevels of profitability have been achieved of between $82/ha and $356/ha (the average increase infarm income 2002-2016 has been $207/ha). At the national level, the aggregate farm income gain

50
Bennett et al (2004) found average yield increases of 45% in 2002 and 63% in 2003 (average over the two years of 54%) relative toconventionally produced cotton. Survey data from Monsanto (2005) confirmed this high yield impact (+58% reported in 2004) andfrom 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 rangeof +30% to +40%

©PG Economics Ltd 201867

GM crop impact: 1996-2016

in 2016 was $1.52 billion and cumulatively since 2002 the farm income gains have been $21.12
billion (Table 34).
The impact on total cotton production was an increase of 23% in 2016.
Table 34: Farm level income impact of using GM IR cotton in India 2002-2016
Year

Cost savings (net after
Net increase in gross
Increase in farm income at a
cost of technology: $/ha) margins ($/ha)national level ($ millions)2002-12.42
82.66
3.69
2003
-16.2
209.8520.98
2004-13.56193.3696.68
2005-22.25255.96332.742006
3.52
221.02
839.892007
26.41
356.852,093.97
2008
24.28
256.73
1,790.16
2009
22.19
211.17
1,754.96
2010
23.10
265.802,498.53
2011
22.64
287.07
3,056.76
2012
19.77
198.292,141.58
2013
18.03
191.57
2,107.29
2014
17.31
137.291,604.05
2015
16.47
117.671,330.30
2016
15.72
146.22
1,523.00
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

3.8.8 Brazil
GM IR cotton was planted commercially in Brazil for the first time in 2006, and in 2016 wasplanted on 511,360 ha (54% of the total crop). The area planted to GM IR cotton in the early yearsof 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. Since then, however, improved conventional varieties inwhich the GM IR trait is not present have dominated production because of their superior 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 conventional varieties. In
addition, boll weevil is a major pest in many areas, a pest that the GM IR technology does nottarget. Analysis by Galvao (2009 & 2010) estimated that the yield performance of the 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). Not surprisingly,
at the country level, this resulted in net aggregate losses in 2007 and 2009 from using the©PG Economics Ltd 201868

GM crop impact: 1996-2016

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 theincrease in plantings since 2010. Annual estimates of the impact of this technology (Galvao (20102015)) 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 $33.1/ha andaverage insecticide costs savings of $49.44/ha, the average net farm gain derived from using thistechnology over the period 2006-2016 has been $40.43/ha. At the national level this equates to an
aggregate net income gain of $34.2 million in 2016 and cumulatively, since 2006, of $134.9 million.

3.8.9 Other countries•••

Colombia. GM IR cotton has been grown commercially in Colombia since 2002 (8,850 ha
planted in 2016 out of a total cotton crop of 17,500 ha). Drawing on recent analysis of impact
by Zambrano et al (2009), the main impact has been a significant improvement in yield(+32%). On the cost side, this analysis shows that GM IR cotton farmers tend to havesubstantially higher expenditures on pest control than their conventional counterparts which,when taking into consideration the approximate $70/ha cost of the technology, results in a net
addition to costs of between $200/ha and $280/ha (relative to typical expenditures by
conventional cotton growers). Nevertheless, after taking into consideration the positive yield
effects, the net impact on profitability has been positive. In 2008, the average improvement in
profitability was about $90/ha and the total net gain from using the technology was $1.8
million 51. Since the Zambrano work, the use of GM IR cotton has seen problems with
reduced yield benefits in 2009 due mainly to heavy rains in the planting season delaying
planting, followed by lack of rain in the growing season and the increasing availability ofstacked traited seed. For the purposes of this analysis, from 2010 estimates of impact are
based on industry source data which were a net yield benefit of +10%, seed premium of$104/ha-$171/ha (average of $126/ha (2002-2016) and insecticide cost savings of between$50/ha to $87/ha (average of $81.6/ha 2002-2016). As a result, the net farm income benefit
over the 2002-2016 period has been $68.45/ha. At the national level, the aggregate farmincome gain was $0.3 million in 2016 and cumulatively, since 2002 it has been $21.1 million;
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%) andsavings in 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. In 2016, no GM IR cotton
was grown because of a temporary ban imposed by the government. This was due todifficulties in selling the cotton from the varieties containing the trait because the fibres areshorter than most markets want (note this is not related to any impact of the GM IR
technology but relates to the varieties 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 2016, 97% of the crop (2.33 million ha) used this51
Given that the Zambrano et al work identified important differences between the baseline level of insecticide use by GM IR cotton
users and conventional cotton farmers (pre-adoption of the technology), this probably understates the cost savings associated with thetechnology. A more representative assessment of the impact compares the costs (post adoption) of GM IR technology users with thelikely costs of reverting back to conventional technology on these farms©PG Economics Ltd 201869

GM crop impact: 1996-2016••

technology. Initial analysis of the impact draws on Nazli et al (2010) which identified anaverage 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 ourestimates for impacts from 2010. 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. For 2016, theestimated average farm income benefit was $207.4/ha. At the national level this is equal to a
net farm income gain of $482.7 million. Cumulatively since 2009, the farm income benefit ofusing this technology is $4.79 billion;
Myanmar: GM IR cotton has been grown in Myanmar since 2007 and in 2016, 223,000 ha (93%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 was delivering 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 moreconservative average 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 tolabour and insecticide use), we have used data based on costs and impacts from India. Basedon these assumptions, the average income gain in 2016 was $226/ha, which at the national
level amounts to a gain of $50.5 million. Cumulatively the farm income gain since 2007 has
been $358.4 million;
Sudan and Paraguay: These countries have respectively been using GM IR cotton since 2012
and 2013. No detailed impact analysis has been identified for the technology in thesecountries.

3.8.10 Summary of global impact
In global terms, the farm level impact of using GM IR cotton was $3.69 billion in 2016.
Cumulatively since 1996, the farm income benefit has been (in nominal terms) $54 billion. Within
this, 81% of the farm income gain has derived from yield gains (less pest damage) and thebalance (19%) from reduced expenditure on crop protection (spraying of insecticides).
In terms of the total value of cotton production from the countries growing GM IR in 2016, theadditional farm income generated by the technology is equal to a value-added equivalent of
13.3%. Relative to the value of global cotton production in 2016, the farm income benefit added
the equivalent of 10.2%.

3.9 Other GM crops
3.9.1 Maize/corn rootworm resistance
GM IR (resistant to corn rootworm (CRW)) maize has been planted commercially in the US since2003. In 2016, there were 16.6 million ha of GM IR CRW maize (47% of the total US crop).

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GM crop impact: 1996-2016

The main farm income impact 52 has been higher yields of about 5% relative to conventionalmaize. The impact on average costs of production has been +$2/ha to +$12/ha (based on anaverage cost of the technology of $25/ha-$42/ha and an insecticide cost saving of $23/ha-$37/ha 53).
The average cost of the technology over the period 2003-2016 has been $25.32/ha. As a result, thenet impact on farm profitability has been between +$24/ha to +$102/ha, with the average gain
over the 2002-2016 period being $77/ha.
At the national level, aggregate farm income increased by $1.01 billion in 2016. Cumulatively
since 2003, the total farm income gain from the use of GM IR CRW technology in the US maizecrop has been +$13.2 billion.
GM IR CRW cultivars were also planted commercially for the first time in 2004 in Canada. In
2016, the area planted to CRW resistant varieties was 0.7 million ha. Based on US costs,
insecticide cost savings and yield impacts, this has resulted in additional income at the national
level of $47.9 million in 2016 (cumulative total since 2004 of $420.6 million).
At the global level, the extra farm income derived from GM IR CRW maize use has been $13.62
billion.

3.9.2 Virus resistant papaya
Ringspot resistant papaya has been commercially grown in the US (State of Hawaii) since 1999,
and in 2016, 75% of the state’s papaya crop was GM virus resistant (395 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
cultivation (1998), the annual yield increase of biotech papaya relative to conventional crops has
been within a range of +15% to +77% (17% in 2016). At a state level, this was equivalent to a
12.75% increase in total papaya production.
In terms of profitability 54, the net annual impact has been an improvement of between $2,400/ha
and $11,400/ha, and in 2016, this amounted to a net farm income gain of $3,253/ha and an
aggregate benefit across the state of $1.28 million. Cumulatively, the farm income benefit since1999 has been $29.2 million.
Virus resistant papaya are also reported to have been grown in China, (8,350 ha in 2016). No
impact data on this technology has been identified.

52

Impact data based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006), Johnson and Strom (2008) and Rice (2004)
The average area on which the insecticide cost savings have been applied has been limited to the historic area typically treated with
insecticides for rootworm pests (about 40% of the total crop). In addition, from 2012, 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 haveproblems with rootworm developing resistance to the IR technology
54
Impact data based on Carpenter & Gianessi (2002), Sankala & Blumenthal (2003 & 2006) and Johnson and Strom (2008)
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GM crop impact: 1996-2016

3.9.3 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 2016 55 (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 2016, added a net gain tousers of $10.4 million. Cumulatively, the farm income benefit since 2004 has been $289.2 million.

3.9.4 Drought tolerant maize
Drought tolerant maize has been grown in parts of the US since 2014, and in 2016 was planted on
1.34 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% and asmall cost saving in irrigation costs 56. After taking into consideration, the additional cost of theseed compared to non-GM drought tolerant maize, the average gross farm income gain over thethree- year period of use has been about $15/ha. In 2016, this resulted to an aggregate farmincome gain of about $20 million and over the period 2014-2016, a total gain of $33.3 million.

3.9.5 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.
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 1.23 million ha
55

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 corn is grown
56©PG Economics Ltd 201872

GM crop impact: 1996-2016

of GM alfalfa were being cropped in 2016. The technology is reported to offer improved weed
control, better yields and higher quality forage. No analysis is presented here due to the lack ofpublished studies on the impact.

3.10 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 57 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.

57
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)©PG Economics Ltd 201873

GM crop impact: 1996-2016

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;• 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 corn relative to conventional and organic corn 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 58. 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 59 to obtain farmers’ valuations of non-pecuniary benefits. A summary ofthese findings is shown in Table 35.
Table 35: 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 1996-2016
The approach used to estimate the non-pecuniary benefits derived by US farmers from biotech
crops over the period 1996-2016 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 14 summarises the values for non-pecuniary benefits derived from GM crops in the US
and shows an estimated (nominal value) benefit of $1.17 billion in 2016 and a cumulative total
benefit (1996-2016) of $14.59 billion. Relative to the value of direct farm income benefits
presented above, the non-pecuniary benefits were equal to 16% of the total direct income benefits
in 2016 and 18.2% of the total cumulative (1996-2016) direct farm income. This highlights theimportant contribution this category of benefit has had on biotech trait adoption levels in the US,

58

Notably maize in India
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 lost59

©PG Economics Ltd 201874

GM crop impact: 1996-2016

especially where 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
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 14: Non-pecuniary benefits derived by US farmers 1996-2016 by trait ($ million)
7,000

6,073

6,000
5,000
3,688

4,000
2,638

3,000
2,000
1,000
0

1,091
389

245

386

HT soyIR corn

HT corn
2016

1,008

72

75

8 91

IR cotton

HT cotton

HT canola

Cumulative

3.11 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 36).
Table 36: Additional crop production arising from positive yield effects of GM crops
1996-2016 additional production(million tonnes)
Soybeans
213.47
Maize
404.91
Cotton27.47
Canola
11.65
Sugar beet
1.20
Note: Sugar beet, US and Canada only (from 2008)©PG Economics Ltd 201875

2016 additional production(million tonnes)
31.56
47.36
2.27
1.01
0.17

GM crop impact: 1996-2016

The GM IR traits, used in maize and cotton, have accounted for 93.5% of the additional maize
production and 98.9% 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 60) whencompared 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 21 years since 1996 has been +14% for maize and +15% for cotton(Table 37).
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 166.8 million
tonnes to soybean production in Argentina and Paraguay between 1996 and 2016 (accounting for
83.4% of the total GM-related additional soybean production). Intacta soybeans have contributed
a further 13.46 million tonnes since 2013.
Table 37: Average (%) yield gains GM IR cotton and maize 1996-2016
Maize insect resistanceto corn boring pests
US
7.0
China
N/a
South Africa
11.1
Honduras
23.8
MexicoN/aArgentina
6.0
Philippines
18.2
Spain
11.2
Uruguay
5.6
India
N/a
Colombia
21.8
Canada7.0
Brazil11.8
PakistanN/aMyanmarN/aAustralia
N/aParaguay
5.5
Vietnam
7.2
Notes: N/a = not applicable

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

Cotton insect resistance
9.9
10.0
24.0
N/a
11.0
30.0
N/a
N/a
N/a
31.0
18.0
N/a
1.3
21.0
30.9
Nil
Not available
N/a

60 This reflects the levels of Heliothis and Helicoverpa (boll and bud worm) pest control previously obtained withintensive insecticide use. The main benefit and reason for adoption of this technology in Australia has arisen fromsignificant cost savings (on insecticides) and the associated environmental gains from reduced insecticide use©PG Economics Ltd 201876

GM crop impact: 1996-2016

3.12 Trade flows and related issuesa) Share of global exports
Looking at the extent to which the leading GM producing countries are traders (exporters) ofthese crops and key derivatives (Table 38 and Table 39) show the following:
•

•

•

•

Soybeans: in 2016/17, 42% of global production was exported and 97% of this trade camefrom countries which grow GM soybeans. As there has been some development of amarket for certified conventional soybeans and derivatives (mostly in the EU, Japan andSouth Korea), this has necessitated some segregation of (certified) non GM/conventional
exports from supplies that may contain GM origin material, or sourcing from countries
where GM HT soybeans are not grown. Based on estimates of the size of the certified
non-GM/conventional soy markets in the EU and SE Asia (the main markets) 61, between
2% and 2.4% of global trade in soybeans is probably required to be certified asconventional. A similar pattern occurs in soymeal, where 89%-92% of globally traded
meal probably contains GM material;
Maize: 13% of global production was internationally traded in 2016/17 62. Within theleading exporting nations, the GM maize growers of the US, Argentina, Brazil, Paraguay,South Africa and Canada are important players (73% of global trade). As there has beensome limited development of a distinct market which requires certified conventionalmaize (mostly in the EU, Japan and South Korea), this has necessitated some segregationof exports into GM versus certified conventional supplies. The likely share of global
trade accounted for by GM maize exports is 68%-73%;
Cotton: in 2016/17, 35% of global production was traded internationally. Of the leading
exporting nations, the GM cotton growing countries of the US, Australia, India and Brazil
are prominent exporters, with exports from all GM cotton growing countries accounting
for 75% of global trade. Given that the market for certified conventional cotton is verysmall, virtually all of this share of global cotton trade from GM cotton growing countries
is probably not subject to any form of segregation and hence may contain GM derived
material 63. In terms of cottonseed-meal the GM share of global trade is 50%;Canola: 21% of global canola production in 2016/17 was exported, with Canada being themain global trading country. The share of global canola exports accounted for by thethree GM HT canola producing countries (Canada, the US and Australia) was 89% in
2016/17. As there has been only a very small development of a market for certified
conventional canola globally (the EU, the main market where certified conventional
products are required, has been largely self-sufficient in canola and does not currently
grow GM canola), non-segregated GM exports probably account for 89% of global trade.
For canola/rapemeal, the GM share of global trade is about 78%.

61

Brookes (2008b) and updated from industry sources and own research
Maize is an important subsistence crop in many parts of the world and hence the majority of production is consumed within the countryof production
63
We consider this to be a reasonable assumption; we are not aware of any significant development of a certified conventional versus
biotech cotton market and hence there is little evidence of any active segregation of exports
62©PG Economics Ltd 201877

GM crop impact: 1996-2016

Table 38: Share of global crop trade accounted for GM production 2016/17 (million tonnes)
Soybeans
Maize
CottonCanolaGlobal production
351.3
1,075.0
23.25
74.0
Global trade (exports)
147.4
141.7
8.1
15.9
Share of global trade from GM
143.5 (97%)
103.7 (73%)
6.1 (75%)
14.2 (89%)
producers
Estimated size of market
3.0-3.5
7.0
Negligible
0.1
requiring certified conventional(in countries that have importrequirements)
Estimated share of global trade140.0-143.5
96.7-103.7
6.1
14.1-14.2
that may contain GM (ie, notrequired to be segregated)
Share of global trade that may
95% to 97%
68%-73%75%
88.7% tobe GM
89%
Sources: derived from and updated - USDA & Oil World statistics, Brookes (2008b)
Notes: Estimated size of market requiring certified conventional in countries with import requirements
excludes countries with markets for certified conventional for which all requirements are satisfied bydomestic production (eg, maize in the EU). Estimated size of certified conventional market for soybeans(based primarily on demand for derivatives used mostly in the food industry): main markets - EU 2.25-2.75
million tonnes bean equivalents, Japan and South Korea 0.75 million tonnes

Table 39: Share of global crop derivative (meal) trade accounted for GM production 2016/17(million tonnes)
Soymeal

Cottonseed meal

Canola/rape
meal
40.0
6.0
4.7 (78%)
Negligible

Global production
226.4
13.5
Global trade (exports)
64.6
0.34
Share of global trade from GM producers
59.7 (92%)
0.17 (50%)
Estimated size of market requiring certified
1.6-2.0
Negligible
conventional (in countries that have importrequirements)
Estimated share of global trade that may
57.7-59.7
0.17
4.7
contain GM (ie, not required to besegregated)
Share of global trade that may be GM
89%-92%50%
78%
Sources: derived from and updated - USDA & Oil World statistics, Brookes (2008b)
Notes: Estimated size of certified conventional market for soymeal: EU 1.5-1.9 million tonnes, Japan andSouth Korea 0.1 million tonnes (derived largely from certified conventional beans referred to in above table)©PG Economics Ltd 201878

GM crop impact: 1996-2016

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

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

These are presented in the sub-sections below.

4.1 Use of insecticides and herbicides
Assessment of the impact of GM crops on insecticide and herbicide use requires comparisons of
the respective weed and pest control measures used on GM versus the ‘conventional alternative’
form of production. This presents a number of challenges relating to availability andrepresentativeness.
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 changewith GM crops shows that the number of studies exploring these issues is limited with evenfewer providing data to the pesticide (active ingredient) level. Secondly, national level pesticide
usage survey data is also extremely limited; there are no published, detailed, annual pesticide
usage surveys conducted by national authorities in any of the countries currently growing GM
crop traits. The only country in which pesticide usage data is collected (by private market
research companies) on an annual basis, and which allows a comparison between GM andconventional crops to be made, is the US 64.
Even where national pesticide use survey data is available, it can be of limited value. Quantifying
herbicide or insecticide usage changes with GM crop technology adoption requires an assessmentof, not only what is currently used with GM crops, but also what herbicides/insecticides mightreasonably be expected to be used in the absence of crop biotechnology on the relevant crops (ie, if
the entire crops used non-GM production methods). Applying usage rates for the current(remaining) conventional crops is one approach, however, this invariably under estimates what
usage might reasonably be in the absence of crop biotechnology, because the conventional
cropping dataset used relates to a relatively small, unrepresentative share of total crop area. Thishas been the case, for example, in respect of the US maize, canola, cotton and soybean crops formany years. Thus in 2016, the conventional share (not using GM HT technology) of each crop wasonly 6%, 8%, 7% and 5% respectively for soybean, maize, cotton and canola, with the conventional
share having been below 50% of the total since 1999 in respect of the soybean crop, since 2001 forthe cotton and canola crops, and since 2007 for the maize crop (source: USDA).
The reasons why herbicide/insecticide usage levels from this small conventional crop dataset isunrepresentative of what might reasonably be expected if all of the current area growing GM crops
reverted to conventional seed types are:64

The US Department of Agriculture also conducts pesticide usage surveys but these are not conducted on an annual basis (eg, the lasttime maize was included was 2016 and previous to this in 2014, 2010 and 2005) and do not disaggregate usage by production type (GMversus conventional)©PG Economics Ltd 201879

GM crop impact: 1996-2016

•

•

•

•

Although pest/weed problems/damage vary by year, region and within region, farmers’
who consistently farm conventionally may be those with relatively low levels of pest/weed
problems, and hence see little, if any economic benefit from using the GM traits targetedat these pest/weed problems. In addition, late or non-adopters of new technology inagriculture are typically those who generally make less use of newer technologies thanearlier adopters. As a result, insecticide/herbicide usage levels non-adopting farmers tend
to be below the levels that would reasonably be expected on an average farm with more
typical pest/weed infestations and where farmers are more wiling to adopt newtechnology;
Some of the farms continuing to use conventional seed use extensive, low intensity
production methods (including organic) which feature, limited (below average) use ofherbicides/insecticides. 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 technology;
The widespread adoption of GM IR technology has resulted in ‘area-wide’ suppression oftarget pests in maize and cotton crops. As a result, conventional farmers (eg, of maize in
the US) have benefited from this lower level of pest infestation and the associated reduced
need to apply insecticides (Hutchison et al, 2010).
Some 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 use higher
levels of insecticide/herbicide than they did in the pre-GM crop days. Nevertheless, thedecision to use more pesticide or not would be made according to individual assessmentof the potential benefits (eg, from higher yields) compared to the cost of additional
pesticide use.

The poor representativeness of the small conventional dataset has been addressed by firstly,using the average recorded values for insecticide/herbicide usage on conventional crops for years
only when the conventional crop accounted for the majority of the total crop and, secondly, inother years (eg, from 1999 for soybeans, from 2001 for cotton and from 2007 for maize in the US)
applying estimates of the likely usage if the whole crop was no longer using crop biotechnology,
based on opinion from extension and industry advisors across the country as to what farmers
might reasonably be expected to do for pest and weed control practices, including typicalinsecticide/herbicide application rates. Lastly, these ‘extension service’ identified application
rates were cross checked (and subject to adjustment) with recorded usage levels of key herbicide
and insecticide active ingredients from pesticide usage surveys (where available) so as tominimise the chance of usage levels for the conventional alternative being overstated. Overall,this approach has been applied in a number of countries where pesticide usage data is available,
though in some, because of the paucity of available data, the analysis relies more on
extension/advisor opinion and knowledge of actual and potential pesticide use.
This methodology has been used by others (Sankala and Blumenthal, 2003, Sankala andBlumenthal, 2006, Johnson and Strom, 2006). It also has the advantage of providing comparisonsof current crop protection practices on both GM crops and the conventional alternatives and sotakes into account dynamic changes in crop protection and weed control management practices
and technologies (eg, to address weed resistance development) rather than making comparisons©PG Economics Ltd 201880

GM crop impact: 1996-2016

solely on past practices. Details of how this methodology has been applied to the 2016
calculations, sources used for each trait/country combination examined and examples of typicalconventional versus GM pesticide applications are provided in Appendix 3.
The environmental impact associated with pesticide use changes with GM crops has mostcommonly been presented in the literature in terms of the volume (quantity) of pesticide applied.
This is, however, not a good measure of environmental impact because the toxicity of eachpesticide is not directly related to the amount (weight) applied. There exist alternative (andbetter) measures that have been used by a number of authors of peer reviewed papers to assess
the environmental impact of pesticide use change with GM crops. In particular, there are anumber of peer reviewed papers that utilise the Environmental Impact Quotient (EIQ) developedat Cornell University by Kovach et al (1992) and updated annually (eg, Brimner et al, 2004,
Kleiter, 2005, Biden S et al, 2018). This effectively integrates the various environmental impacts ofindividual pesticides into a single ‘field value per hectare’. The EIQ value is multiplied by theamount of pesticide active ingredient (ai) used per hectare to produce a field EIQ value. 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 field EIQ/ha for conventional versus GM crop production systems, with thetotal environmental impact or load of each system, a direct function of respective field EIQ/havalues and the area planted to each type of production (GM versus conventional). The EIQ
indicator 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 onsome of the key toxicity and environmental exposure data related to individual products, asapplicable to impacts on farm workers, consumers and ecology.
The authors of this analysis have also 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) can be readily used tomake comparisons between different production systems across many regions andcountries;
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.

The authors, do, however acknowledge that the EIQ is only a hazard indicator and has important
weaknesses (see for example, Peterson R and Schleier J (2014) and Kniss A and Coburn C (2015)).
It is a hazard rating indicator that does not assess risk or probability of exposure to pesticides. It
also relies on qualitative assumptions for the scaling and weighting of (quantitative) risk
information that can result, for example, in a low risk rating for one factor (eg, impact on farmworkers) may cancel out a high-risk rating factor for another factor (eg, impact on ecology).
Fundamentally, assessing the full environmental impact of pesticide use changes with different
production systems is complex and requires an evaluation of risk exposure to pesticides at a sitespecific level. This requires substantial collection of (site-specific) data (eg, on ground waterlevels, soil structure) and/or the application of standard scenario models for exposure in a
number of locations. Undertaking such an exercise at a global level would require a substantial©PG Economics Ltd 201881

GM crop impact: 1996-2016

and ongoing input of labour and time, if comprehensive environmental impact of pesticidechange analysis is to be completed. It is not surprising that no such exercise has, to date been
undertaken, or likely to be in the near future.
Despite the acknowledged weaknesses of the EIQ as an indictor of pesticide environmental
impact, the authors of this paper continue to use it because it is, in our view, a superior indicator
to only using amount of pesticide active ingredient applied. In this paper, the EIQ indicator isused in conjunction with examining changes in the volume of pesticide active ingredient applied.
Detailed examples of the relevant amounts of active ingredient used and their associated field
EIQ values for GM versus conventional crops for the year 2016 are presented in Appendix 3.

4.1.1 GM herbicide tolerant (to glyphosate) soybeans (GM HT)a) The USA
In examining the impact on herbicide usage in the US, two main sources of information havebeen drawn on: USDA (NASS) national pesticide usage data and Kynetec (private market
research sector) national farm survey-based pesticide usage data. Based on these sources of
information, the main features relating to herbicide usage on US soybeans over the last 21 years
have been (Table 40 and Table 41):•••

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;The average field EIQ/ha load has followed a broadly similar pattern of change as theamount of active ingredient used, although the rate of increase in recent years has beenless significant than the rate of increase in active ingredient use;
A comparison of conventionally grown soybeans (per ha) with GM HT soybeans (Table41) shows that herbicide ai use on conventional soybeans has also followed a similar
pattern of change to GM HT soybeans. Initially usage was fairly stable (at around 1.1 to
1.3kg/ha compared to 1.3 to 1.4kg/ha for GM HT soybeans). Since 2006, the averageamount of herbicide active ingredient applied to conventional soybeans has followed thesame upward path as usage on GM HT soybeans. The increased usage of herbicides on
GM HT soybeans partly reflects the increasing incidence of weed resistance to glyphosatethat 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 postemergence 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 theevolution of weed populations predominated by resistant individual weeds. In addition,
the facilitating role of the technology in the adoption of no and reduced tillage
production techniques has also contributed to the emergence of weeds resistant toherbicides like glyphosate and to weed shifts towards those weed species that are
inherently not well controlled by glyphosate. Some of the glyphosate 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 15 years, growers of GM HT crops in the US have been using
other herbicides (with different and complementary modes of action) in combination©PG Economics Ltd 201882

GM crop impact: 1996-2016

with glyphosate and in some cases adopting cultural practices (eg, reverting back toploughing) in more integrated weed management systems.

•

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, corn andcanola) in the last 15 years. This is shown in the evidence relating to changes in herbicideuse, as illustrated in Table 40 and Table 41. Thus, in 2016, 89% of the GM HT soybean
crop received an additional herbicide treatment of one of the four most used, after
glyphosate, active ingredients 65 2,4-D, chlorimuron, fomesafen and sulfentrazone. This
compares with 14% of the GM HT soybean crop receiving a treatment of one of the fourmost used (after glyphosate) herbicide active ingredients in 2006. As a result, the averageamount of herbicide active ingredient applied to the GM HT soybean crop in the US (perhectare) increased by 81% over this period. This compared with the average amount of
herbicide active ingredient applied to the small conventional (non-GM) soybean
alternative which increased by 94% over the same period. The increase in the use ofherbicides on conventional soybeans reflects a shift in herbicide use (more herbicides)
rather than an increase in dose rates and can therefore be partly attributed to the ongoing development of weed resistance to non-glyphosate herbicides commonly used.
This highlights that the development of weed resistance to herbicides is a problem facedby all farmers, regardless of production method (also see section 4.1.9 for more detailed
discussion of weed resistance issues);
A comparison of average field EIQs/ha also shows fairly stable values for bothconventional and GM HT soybean crops for most of the period to the mid-2000s,
followed by increases in the last 15 years. The average load rating for GM HT soybean
crops was lower than the average load rating for conventional soybeans for most of theperiod 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 andconventional soybean crops have increased significantly on both production systems.

Table 40: Herbicide usage on soybeans in the US 1996-2016

65

Year

Average ai use(kg/ha): NASS data

1996
1997
1998
1999
2000
2001
2002
2003
2004

1.02
1.22
1.09
1.05
1.09
0.73
1.23
N/a
1.29

Average ai use:
Kynetec data: index
1998=100
N/a
N/a
100
94.9
96.0
100.1
97.8
104.7
106.1

Average field
EIQ/ha: NASS data

Average field EIQ/ha:
based on Kynetec data

22.0
26.2
21.5
19.6
20.2
13.4
21.4
N/a
15.2

N/a
N/a
25.8
23.2
23.1
23.5
21.6
22.6
22.6

The four most used herbicide active ingredients used on soybeans after glyphosate (source: derived from

Kynetec)©PG Economics Ltd 201883

GM crop impact: 1996-2016

2005
1.23
106.3
20.2
22.6
2006
1.53
101.3
16.9
21.4
2007
N/a
113.0
N/a
23.6
2008
N/a
125.1
N/a
26.1
2009
N/a
125.7
N/a
26.6
2010
N/a
135.0
N/a
28.8
2011
N/a
144.8
N/a
31.3
2012
1.97
160.9
32.0
35.0
2013
N/a
166.1
N/a
35.9
2014
N/a
165.6
N/a
35.9
2015
1.93
179.0
34.5
40.8
2016
N/a
183.7
N/a
43.4
Sources: NASS data - no collection of data in 2003, 2007-2011, 2013, 2014. Kynetec 1998-2016, N/A = notavailable. Average ai/ha figures derived from Kynetec dataset are not permitted by Kynetec to be published

Table 41: Herbicide usage on GM HT and conventional soybeans in the US 1996-2016
Year

Average ai use
Average ai use
Average field
Average field EIQ/ha:(kg/ha) index(kg/ha) index
EIQ/ha: conventional GM HT
1998=100:
1998=100: GM HT
conventional
1996
93.6
93.6
28.3
22.8
1997
111.9
111.9
34.1
27.2
1998
100
100
28.1
22.2
1999
90.3
97.0
25.7
21.5
2000
86.6
99.2
24.5
22.3
2001
91.6
100.8
26.0
22.7
2002
85.2
97.7
24.2
21.1
2003
83.5
104.5
23.6
22.5
2004
84.2
106.0
23.7
22.5
2005
86.2
105.8
23.7
22.5
2006
79.5
100.0
21.3
21.4
2007
90.5
111.3
24.6
23.5
2008
95.1
122.6
25.3
26.1
2009
94.7
124.1
24.5
26.7
2010
97.3
133.1
26.4
28.9
2011
115.7
142.1
29.6
31.4
2012
142.1
157.1
36.7
34.8
2013
119.3
163.2
29.7
36.4
2014
121.3
162.7
31.7
36.2
2015
160.5
180.4
39.2
40.9
2016
166.2
185.0
40.9
43.6
Source: derived from Kynetec
Notes:
1. N/A = not available
2. Kynetec does not permit the publishing of average ai/ha figures derived from its dataset
3. 1996 and 1997 estimated based on trend in aggregate usage 1996-1998 from USDA NASS

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 the©PG Economics Ltd 201884

GM crop impact: 1996-2016

data 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
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 corn 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 66. 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 the Kynetec dataset, so as to minimise the scope forunderstating 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 42. These usage levels were then compared to typical and recommended weed control
regimes for GM HT soybeans and recorded usage levels on the GM HT crop (which accounted
for over 90% of the total crop since 2007), using the dataset from Kynetec. The key features of this66

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 201885

GM crop impact: 1996-2016

comparison are that the average amount of active ingredient used 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 to conventional soybeans would
result in a higher average field EIQ/ha value (in other words the conventional soybean system
would be worse for the environment in terms of toxicity than the GM HT system).
Table 42: Average ai use and field EIQs for conventional soybeans 2006-2015 to deliver equal
efficacy to GM HT soybeansYear
Ai use (kg/ha)
Field EIQ/ha
2006
1.49
36.2
2007
1.60
33.1
2008
1.62
36.2
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
45.2
Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2016,
including drawing on Kynetec usage data

Using this methodology for comparing conventional versus GM HT soybean herbicide usage, theestimated national level changes in herbicide use and the environmental impact associated withthe adoption of GM HT soybeans 67 (Table 43) shows:••

In 2016, there was a small net increase in herbicide ai use of 4% (3.2 million kg). The EIQ
load was, however lower by 3.3% compared with the conventional (no/low tillage)
alternative (ie, if all of the US soybean crop had been planted to conventional soybeans);Cumulatively since 1996, there have been savings in both active ingredient usage and theassociated environmental impact (as measured by the EIQ indicator) of -2.7% (29.4
million kg) in active ingredient usage and -22.1% for the field EIQ load.

Table 43: National level changes in herbicide ai use and field EIQ values for GM HT soybeansin the US 1996-2016
Yearai decrease (kg)EIQ saving (units)% decrease in ai% EIQ saving

1996
1997
1998
1999

-19,425-191,825-588,830
3,278,025

2,670,982
22,059,893
68,422,098
252,080,123

-0.06
-0.47
-1.58
7.37

0.36
2.28
8.36
22.91

67
The approach compares the level of herbicide use (herbicide ai use and field EIQ/ha values) on the respective areas planted toconventional and GM HT soybeans in each year by comparing actual usage on the GM HT crop with the level of herbicide use thatwould reasonably be expected to be applied if this crop reverted to conventional production systems (non GM) and achieved the samelevel of weed control as delivered in the GM HT system©PG Economics Ltd 201886

GM crop impact: 1996-2016

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

3,095,913
3,326,588
4,613,517
2,573,857
2,175,637
2,418,454
4,352,219
2,812,022-277,900
408,283-1,884,457
3,640,381
1,433,276
1,142,180
316,879
23,153-3,238,217

265,520,040
315,804,125
382,436,255
370,120,593
391,614,725
386,415,219
402,575,262
224,258,717
279,284,006
450,049,449
504,119,014
200,566,762
264,296,169
147,055,676
187,842,449
206,876,139
50,550,160

6.89
7.44
10.48
5.82
4.82
5.62
9.56
6.83
-0.57
0.78
-3.50
6.00
2.17
1.68
0.43
-0.03
-4.0

23.90
28.54
35.10
33.77
35.05
36.26
36.43
26.31
25.57
34.12
34.68
17.35
19.49
11.53
13.33
13.14
3.34

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 68. 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;
2016, conventional 1.79 kg ai/ha and an average EIQ/ha of 33.71 compared to GM HT
with 1.52 kg/ha and 23.3 EIQ/ha.

Based on these values, at the national level 69, in 2016, there was a net decrease in the volume ofactive ingredient used of 11.4% (-518,000 kg) and a 26% decrease in associated environmental
impact (as measured by the EIQ indicator: Table 44). Cumulatively since 1997, there has been a
8.4% saving in active ingredient use (3.3 million kg) and a 22.1% saving in field EIQ/ha indicatorvalue.
Table 44: National level changes in herbicide ai use and field EIQ values for GM HT soybeansin Canada 1997-2016
Yearai saving (kg)EIQ saving (units)% decrease in ai (- =increase)

1997
1998
1999

530
25,973
106,424

20,4081,000,094
4,097,926

0.03
1.85
7.41

68

% EIQ saving

0.06
2.98

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 tothe ai and EIQ levels on the actual areas of GM and non GM crops in each year
69

©PG Economics Ltd 201887

GM crop impact: 1996-2016

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

112,434
169,955
230,611276,740
351,170
373,968
84,13075,86096,800103,374
113,729
97,749119,977
133,634
149,969
204,778
517,955

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
16,187,269
18,165,957
24,805,156
19,967,913

7.41
11.12
15.75
18.53
20.38
22.24
4.85
4.49
5.63
5.23
5.38
4.38
5.0
5.0
4.69
6.60
16.40

11.93
17.90
25.36
29.83
32.82
35.80
24.54
22.71
28.52
26.49
27.27
22.2
25.3
25.3
23.8
33.2
26.5

c) Brazil
Drawing on herbicide usage data from AMIS Global and Kleffmann, plus information fromindustry 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, however, suggests a change in herbicide
regimes used in both systems, partly due to changes in herbicide availability, prices, increasing
adoption of reduced/no tillage production practices (in both conventional and GM HT soybeans)
and weed resistance issues. As a result, estimated values for the respective systems in 2016 (seeAppendix 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 70.

Based on the above herbicide usage data, (Table 45):••

In 2016, the total herbicide active ingredient use was 1.8% lower on GM HT crops than it
would likely have been if the crop had been conventional. The EIQ/ha environmentalload was 10.2% lower than if the crop had been conventional;
Cumulatively since 1997, there has been a 2.4% increase in herbicide active ingredient use(28.1 million kg). However, there has been a 6.6% reduction in the environmental impact(1,240 million field EIQ/ha units).

70

Inclusive of herbicides (mostly glyphosate) used in no/low tillage production systems for burndown. Readers should note that thisdata 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 201888

GM crop impact: 1996-2016

Table 45: National level changes in herbicide ai use and field EIQ values for GM HT soybeansin Brazil 1997-2016
Year

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

ai saving (kgnegative sign
denotes increase in
ai use)22,333
111,667
263,533
290,333
292,790
389,145
670,000
1,116,667
2,010,000
2,546,000-5,701,493-5,704,705-6,642,000-7,529,650-4,722,073-5,663,575-1,716,122-1,842,482
1,806,682
1,886,378

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

1,561,667
7,808,333
18,427,667
20,301,667
20,473,450
27,211,105
46,850,000
78,083,333
140,550,000
178,030,000-45,847,926-45,028,156-54,763,974-62,082,740
67,340,860
80,767,507
188,138,287
201,991,139
180,421,820
188,421,820

0.1
0.3
0.7
0.7
0.7
0.8
1.2
1.7
2.9
4.0
-8.8
-16.3
-17.3
-19.1
-7.0
-7.6
-2.3
-2.3
1.7
1.8

0.3
1.4
3.3
3.4
3.4
3.8
5.9
8.4
14.4
19.8
-4.9
-7.6
-8.5
-9.3
6.1
6.6
13.3
13.3
9.9
10.2

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 2016, the area planted to soybeans was 18.6 million ha. Almost all of this (99.5%) 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 2016, the estimatedaverage herbicide ai use was 3.59 kg/ha and the average field EIQ was 54.53/ha 71. Given 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.

71

Source: AMIS Global (national herbicide usage data based on farm surveys)©PG Economics Ltd 201889

GM crop impact: 1996-2016

These changes should, however, be assessed within the context of the fundamental changes intillage systems that have occurred over the 1996-2016 period (some of which may possibly havetaken place in the absence of the GM HT technology 72). Also, the expansion in soybean plantings
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 2016 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 73 are equivalent to:••

In 2016, a 0.7% decrease in the volume of herbicide ai used (0.5 million kg) and a net 12%
reduction in the associated environmental impact, as measured by the EIQ indicator (138
million EIQ/ha units);
Cumulatively since 1996, there has been a net increase in herbicide ai use of +1.1% (+10.8
million kg) but a lower (net environmental gain) field EIQ load of 8.8% lower (1.48
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 2016 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.

72

It is likely that the trend to increased use of reduced and no till systems would have continued in the absence of GM HT technology.
However, the availability of this technology has probably played a major role in facilitating and maintaining reduced and no till systems
at levels that would otherwise have not arisen
73
Based on comparing the current GM HT no till usage with what would reasonably be expected if the same area and tillage system wasplanted to a conventional (non-GM) crop and a similar level of weed control was achieved©PG Economics Ltd 201890

GM crop impact: 1996-2016

Using these values, the level of herbicide ai use and the total EIQ load in 2016 were respectively
7.9% higher in terms of active ingredient use (+0.86 million kg), but lower by 13.7% in terms of
associated environmental impact as measured by the EIQ indicator (23.4 million EIQ/ha units).
Cumulatively, since 1999, herbicide ai use has been 6.1% higher (5 million kg 74) whilst theassociated environmental impact, as measured by the EIQ indicator, was 7% lower (ie, despite anincrease in active ingredient use, there was a net improvement in environmental impact
associated with herbicide use).
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 2016 were:••Conventional soybeans: average volume of herbicide used 3.0 kg/ha and a field EIQ/havalue of 52.91/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 2016 were respectively
0.7% higher in terms of active ingredient use (+29,000 kg), but lower by 11.8% in terms of
associated environmental impact as measured by the EIQ indicator (-8 million EIQ/ha units).
Cumulatively, since 1999, herbicide ai use has been 2.7% higher (812,000 kg) whilst the associatedenvironmental impact, as measured by the EIQ indicator, was 7.4% 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 2016, a 7.5% increase in the volume of herbicide ai used (278,000 kg) but a net 13%
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 6% (+1.6
million kg) but a net reduction in the field EIQ load of 5%.

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:••

74

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.

Up to 2006, estimated ai use was slightly higher for conventional relative to GM HT soybeans by 0.03 kg/ha©PG Economics Ltd 201891

GM crop impact: 1996-2016

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%.
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 treatment regimes for GM HT soybeans and conventional soybeans:
see Appendix 3) shows the following:••

Since 1999, the total volume of herbicide ai use has been 7.6% lower (equal to 630,000 kg
of ai) than the level of use if the crop had been conventional;
The field EIQ load has fallen by 22.9% (equal to 37 million field EIQ/ha units) since 1999
(in 2016 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) on an annual area of between 2,000 ha and 20,000 ha) shows the following:••

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.

Since 2004, the total volume of herbicide ai use has been 0.8% lower (equal to about 21,900 kg ofai) 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 75 has been (Figure 15):75

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 that obtained under the GM HT system©PG Economics Ltd 201892

GM crop impact: 1996-2016••

In 2016, a 0.5% increase in the total volume of herbicide ai applied (1.3 million kg) but
an 9% reduction in the environmental impact (measured in terms of the field EIQ/haload);
Since 1996, 0.4% more herbicide ai has been used (13 million kg) but the environmental
impact applied to the soybean crop has fallen (an environmental improvement) by
13.4%.

This analysis takes into consideration changes in herbicide use, in recent years, on GM HT
soybeans, that have occurred to specifically address the issue of weed resistance to glyphosate insome regions. Compared to the early 2000s, the amount of herbicide active ingredient appliedand number of herbicides used with GM HT soybeans in many regions has increased, and theassociated environmental profile, as measured by the EIQ indicator, deteriorated. However,relative to the conventional alternative, the environmental profile of GM HT soybean crop use
has continued to offer important advantages 76 and in most cases, provides an improved
environmental profile compared to the conventional alternative (as measured by the EIQ
indicator).
Figure 15: Reduction in herbicide use and the environmental load from using GM HT
soybeans in all adopting countries 1996-2016

0.5%

0.4%

2.0%
0.0%
-2.0%
-4.0%
-6.0%
-8.0%
-9.0%

-10.0%-12.0%-14.0%-13.4%
2016

Cumulative
Ai

EIQ

76

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 controlof these weeds©PG Economics Ltd 201893

GM crop impact: 1996-2016

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:••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 2016, the use of this technology resulted in a reduction of 3.4 million
kg of insecticide active ingredient use, equal to 11.1% of total insecticide used on the soybean
crops in the four countries. The EIQ saving in 2016 was equal to 11.5%. Over the four years, thetotal insecticide active ingredient usage saving has been 7.4 million kg (-6.1%) and the associatedenvironmental impact, as measured by the EIQ indicator fell by 6.1%.

4.1.3 GM Herbicide tolerant (GM HT) maizea) The US
Drawing on the two main statistical sources of pesticide usage data (USDA and Kynetec), Table
46 and Table 47 summarise the key features:•••

The average herbicide ai/ha used on a GM HT maize crop has been about 0.6 to 0.7 kg/ha
lower than the average usage on the residual conventional crop in the period to about
2007. Since then, the differential between the increasingly GM HT crop and small
conventional crop has narrowed, so that by 2010, average levels of active 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 small conventional crop;
The average field EIQ/ha used on a GM HT crop has been about 20/ha units lower thanthe conventional crop, although as with the amount of active ingredient use, thedifference has narrowed and the GM HT average value is now higher than theconventional value;
The recent increase in ai use and the associated field EIQ/ha for GM HT maize mainlyreflects the increasing concern about herbicide resistance and the adoption of integrated
weed management practices designed to address the issue of weed resistance toglyphosate (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 asacetochlor, atrazine, 2 4,D, mesotrione, S metolachlor and tembotrione as recommended
by extension advisors and weed scientists.

©PG Economics Ltd 201894

GM crop impact: 1996-2016

Table 46: Herbicide usage on maize in the US 1996-2016
Year

Average ai use(kg/ha): NASS data

Average ai use
Average field
Average field EIQ/ha:(kg/ha) index
EIQ/ha: NASS data
Kynetec data
1998=100: Kynetec
data
1996
2.64
N/a
54.4
N/a
1997
2.30
N/a
48.2
N/a
1998
2.47
100
51.3
62.0
1999
2.19
88.1
45.6
54.7
2000
2.15
87.8
46.2
54.5
2001
2.30
86.6
48.8
53.8
2002
2.06
82.4
43.4
51.1
2003
2.29
83.2
47.5
51.2
2004
N/a
80.0
N/a
48.9
2005
2.1
80.6
51.1
48.7
2006
N/a
79.5
N/a
47.7
2007
N/a
85.0
N/a
49.8
2008
N/a
88.7
N/a
50.9
2009
N/a
86.9
N/a
49.7
2010
2.36
90.5
49.2
51.4
2011
N/a
91.6
N/a
51.8
2012
N/a
95.6
N/a
53.8
2013
N/a
101.3
N/a
56.8
2014
2.45
100.7
47.0
56.2
2015
N/a
101.6
N/a
57.2
2016
3.01
105.6
58.4
59.8
Sources and notes: derived from NASS pesticide usage data 1996-2003 and 2010 (no data collected in 2004,
2006-2009, 2011-2013, 2015), Kynetec data from 1998-2016. N/a = not available. Kynetec does not permit
publishing of average ai/ha figures derived from its dataset

Table 47: Average US maize herbicide usage and environmental load 1997-2016: conventional
and GM HT
Year

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

©PG Economics Ltd 2018

Average ai/ha(kg) index
1998=100:
conventional
92.3
100
88.0
89.1
87.9
85.3
87.4
85.3
87.9
88.0
92.9
88.0
87.9

Average ai/haindex 1998=100(kg): GM HT

Average field
EIQ:
conventional

Average field EIQ: GM
HT

98.9
100
99.5
97.9
105.9
99.5
100.0
101.1
109.1
111.8
127.8
140.1
136.4

59.5
63.1
55.9
56.5
56.0
54.5
55.6
54.7
56.2
56.4
59.4
56.2
56.1

36.8
36.9
36.8
35.7
38.3
35.6
34.8
35.2
38.5
40.1
45.9
50.2
49.0

95

GM crop impact: 1996-2016

2010
90.3
142.2
58.1
50.8
2011
86.0
144.9
54.7
51.4
2012
86.0
151.9
55.1
53.7
2013
84.3
161.0
53.7
57.3
2014
88.3
159.4
55.5
56.3
2015
88.3
161.5
55.6
57.4
2016
91.0
166.5
56.5
60.2
Sources and notes: derived from Kynetec. 1997 based on the average of the years 1998-1999. Kynetec does
not permit publishing of average ai/ha figures derived from its dataset

As the herbicide usage data for the relatively small conventional crop presented above is likely to
be biased and unrepresentative (see section 4.1.1), the alternative that would deliver a similarlevel of weed control to the level delivered in the GM HT system, based on recommended
practices from extension advisors and industry analysts 77 since 2007 78 is summarised in Table 48.
These conventional crop herbicide usage levels were then compared to recorded usage levels on
the GM HT crop (which accounted for a majority of the total crop since 2007), using the dataset
from Kynetec.
Table 48: Average ai use and field EIQs for conventional maize 2007-2015 to deliver equal
efficacy to GM HT maizeYear
Ai use (kg/ha)
Field EIQ/ha
2007 and 2008
3.48
77.15
2009
3.78
78.81
2010
3.88
81.46
2011
3.43
84.10
2012
3.43
84.10
2013
3.37
60.84
2014
3.40
67.28
2015
3.41
67.36
2016
3.60
70.32
Sources: Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated for this research for 2009-2016,
including drawing on Kynetec data

Through this more representative usage data for conventional maize and comparison with GM
HT maize, it is evident that the average herbicide active ingredient use for conventional maize ishigher than GM HT maize. The associated environmental load, as measured by the EIQ
indicator, for conventional corn is also significantly worse for conventional corn when compared
to GM HT maize.
At the national level (Table 49), in 2016, there has been an annual saving in the volume ofherbicide active ingredient use of 10.6% (13.4 million kg). The annual field EIQ load on the US
maize crop has also fallen by 12.8% in 2016 (equal to 316 million field EIQ/ha units). The
cumulative decrease in active ingredient use since 1997 has been 10% (218 million kg), and thecumulative reduction in the field EIQ load has been 13.7%.

77

The 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
78
The conventional share of total maize plantings has been below 50% since 2007

©PG Economics Ltd 201896

GM crop impact: 1996-2016

Table 49: National level changes in herbicide ai use and field EIQ values for GM HT maize in
the US 1997-2016
Yearai decrease (kg)EIQ saving (units)% decrease in ai% EIQ saving

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

108,290
1,862,202
1,131,872
1,893,007
1,593,072
2,643,638
3,578,625
4,285,776
5,076,926
6,162,189
21,470,045
17,242,687
26,940,136
27,996,062
17,630,870
1,806,896
10,856,499
12,657,665
11,270,306
13,401,458

2,701,300
43,612,096
28,046,894
47,009,679
43,307,050
72,297,763
99,247,200
126,300,520
152,393,842
185,550,355
616,328,159
540,738,699
653,791,105
704,261,601
799,755,854
812,586,944
105,247,722
327,474,109
290,758,614
316,543,222

0.1
1.9
1.4
2.2
2.0
3.2
4.3
5.2
5.8
7.4
16.3
15.6
22.1
22.0
15.0
11.8
9.1
11.1
10.1
10.6

0.1
2.1
1.6
2.6
2.5
4.2
5.6
7.1
8.2
10.4
21.1
22.0
25.8
26.4
27.7
27.0
4.9
14.5
13.2
12.8

b) 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 79 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:
•

•
•

•

79

In 2016, the herbicide ai/ha load on a GM HT crop has been between 0.19 kg/ha (GMglyphosate tolerant) and 1.03 kg/ha (GM glufosinate tolerant) lower than theconventional maize equivalent crop (average herbicide ai use at 3.07 kg/ha);
The field EIQ/ha values for GM glyphosate and GM glufosinate tolerant maize arerespectively 14.2/ha and 25.26/ha compared to 70.11/ha for conventional maize;
At the national level in 2016 (based on the plantings of the different production systems),
the reductions in herbicide ai use and the total field EIQ load were respectively 7.1%
(257,000 kg kg) and 22.6% (18.4 million: Table 50);
Cumulatively since 1997, total national herbicide ai use has fallen by 15.4% (9.64 millionkg) and the total EIQ load has fallen by 19.8% (280 million field EIQ units).

Including the Weed Control Guide (2004 and updated) from the Departments’ of Agriculture in Ontario, Manitoba and Saskatchewan©PG Economics Ltd 201897

GM crop impact: 1996-2016

Table 50: Change in herbicide use and environmental load from using GM HT maize in
Canada 1999-2016
Year

Total ai saving (kg)

1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

59,324
121,985
177,902
255,305
209,556
203,320
467,088
501,479
697,961
565,770
776,103584,446
998,008
1,127,079
1,260,672
1,045,165
254,655
257,179

Total field EIQ reductions (inunits per hectare)
1,439,924
2,991,494
4,461,172
6,377,468
5,334,283
5,234,173
11,963,706
13,110,306
18,379,776
14,979,769
20,837,313
15,557,562
27,307,021
30,904,561
34,570,157
28,660,528
18,217,330
18,397,837c) South Africa
Drawing on herbicide usage data from AMIS Global/Kleffmann and industry level sources thatcompare typical herbicide treatment regimes for conventional and GM HT maize in South
Africa), the impact of using GM HT technology in the South African maize crop has been:•••

On a per hectare basis in 2016 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 2016, at the national level, the amount of herbicide used was 212,000 kgs (+3.6%)
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 11% lower;
Cumulatively since 2003, total national herbicide ai use has fallen by 2.1% (2.3 millionkg) and the total EIQ load has fallen by 6.9%.

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):•

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 2016 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;©PG Economics Ltd 201898

GM crop impact: 1996-2016•••

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
recent years the difference between the two systems has narrowed. In 2016, 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 2015 was 1.95 million kg (+11.5%). Since
2004, there has been a small net increase in usage of 0.7% (1 million kg);
In terms of the field EIQ load, the reduction in 2016 was 2.2% (-7.6 million field/haunits) and over the period 2004-2016, the EIQ load factor fell by 5.2%.

e) Brazil
Brazil first used GM HT maize commercially in 2010, and in 2016, the area planted to seedcontaining this trait was 11.9 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 2016 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 2016, the use of GM HT technology resulted no change in the use of herbicide active
ingredient but a reduction in the EIQ rating of 9%;
Cumulatively (2010-2016), the herbicide active ingredient usage saving has been 2% (-8.1
million kg), with an EIQ load reduction of 8.2%.

f) Uruguay
GM HT maize was first used in Uruguay in 2011, and in 2016 was planted on 86% of the total
maize crop (48,850 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 62,850 kg of active ingredient (+2.6%) but a 4.8% improvement in theaggregate field EIQ/ha load.
g) Philippines
GM HT maize was first used in the Philippines in 2006, and in 2016 was planted on 24% of thetotal maize crop (655,000 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 2016 was 1.44 kg/ha and 22.08/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 2016, the use of GM HT technology resulted a 23% (0.3 million kg) decrease in
herbicide active ingredient use and a reduction in the EIQ rating of 46%;
Cumulatively (2006-2016), the herbicide active ingredient usage saving has been 17% (2.5 million kg), with an EIQ load reduction of 35%.

©PG Economics Ltd 201899

GM crop impact: 1996-2016h) Vietnam
GM HT maize was first used in 2015, and in 2016 was planted on 3% of the total maize crop
(35,000 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, this shows that:• The average amount of herbicide active ingredient use and associated field EIQ/ha ratingfor GM HT maize in 2016 was 0.984 kg/ha and 15.8/ha respectively. This compared withconventional maize with herbicide active ingredient use of 1.01 kg/ha and a field EIQ
rating of 20.55/ha;• Cumulatively (2015-2016), the herbicide active ingredient usage saving has been 0.1% (1,000 kg), with an EIQ load reduction of 0.7%.
i) Other countries
GM HT maize was also grown in Colombia on 86,000 ha in 2016 and in Paraguay (260,000 ha).
Analysis of the environmental impact associated with changes in herbicide use on these crops has
not been possible due to a lack of data.
j) 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 16). More specifically:••

In 2016, total herbicide ai use was 5.8% lower (11.8 million kg) than the level of use if thetotal crop had been planted to conventional varieties. The EIQ load was also lower by
11.3%;
Cumulatively since 1997, the volume of herbicide ai applied is 8.1% lower than its
conventional equivalent (a saving of 239 million kg). The EIQ load has been reduced by
12.5%.

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 tosoybeans, 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.

©PG Economics Ltd 2018100

GM crop impact: 1996-2016

Figure 16: Reduction in herbicide use and the environmental load from using GM HT maize in
adopting countries 1997-2016

0.0%
-2.0%
-4.0%
-5.8%

-6.0%
-8.0%

-8.2%

-10.0%-11.3%-12.0%-12.5%-14.0%

2016

Cumulative
Ai

EIQ

4.1.4 GM HT Herbicide tolerant (GM HT) cottona) The USA
Drawing on the herbicide usage data from the USDA and GfK, both the volume of ai used andthe average field EIQ/ha on the US cotton crop remained fairly stable to the mid 2000s, although
since then there has been a rise in usage (Table 51).
Table 51: Herbicide usage on cotton in the US 1996-2016
Year

Average ai use(kg/ha): NASS data

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

1.98
2.43
2.14
2.18
2.18
1.89
N/a
2.27
N/a
N/p
N/a
2.7
N/a
N/a
2.5

©PG Economics Ltd 2018

Average ai use(index 1998=100):
Kynetec data
N/a
N/a
100
89.2
95.4
97.1
96.9
95.1
103.1
107.7
105.0
107.3
113.2
122.5
142.0

101

Average field
EIQ/ha: NASS data

Average field EIQ/ha:
based on Kynetec data

53.19
42.50
35.60
36.20
35.20
27.50
N/a
33.90
N/a
N/p
N/a
47.40
N/a
N/a
53.11

N/a
N/a
45.3
40.1
42.5
42.9
42.3
41.4
44.5
46.4
45.8
45.5
48.8
53.1
61.5

GM crop impact: 1996-2016

2011
N/a
145.9
N/a
64.9
2012
N/a
159.2
N/a
69.4
2013
N/a
167.2
N/a
72.8
2014
N/a
178.9
N/a
72.9
2015
3.73
182.5
64.40
77.7
2016
N/a
177.8
N/a
75.8
Sources and notes: derived from NASS pesticide usage data 1996-2003 and 2010 (no data collected in 2002,
2004, 2006, 2008, 2009, 2011-2014, 2016), Kynetec data from 1998-2016. N/p = Not presented - 2005 results
based on NASS data are significantly different and inconsistent with previous trends and Kynetec data.
These results have therefore not been presented. N/a = not available, Kynetec does not permit publishing of
average ai/ha figures derived from its dataset

A comparison of average active ingredient usage for GM HT and conventional cotton (Table 52),shows that the average level of herbicide ai use (per ha) on GM HT cotton has been consistently
higher than the average level of usage on the relatively small conventional cotton crop. In termsof 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, the average field EIQ/ha rating has
been higher than conventional cotton.
Table 52: Herbicide usage and its associated environmental load: GM HT and conventional
cotton in the US 1997-2016
Year

Average ai use
Average ai use
Average field
Average field EIQ/ha:(index 1998=100):(index 1998=100):
EIQ/ha: conventional GM HT cotton
conventional
GM HT cotton
cottoncotton
1997
92.3
95
40.3
45.7
1998
100
100
43.5
46.1
1999
83.3
90.0
37.1
40.8
2000
91.0
92.8
41.3
41.7
2001
85.7
99.5
38.1
44.8
2002
83.8
99.3
37.7
43.8
2003
75.2
100.2
33.1
44.4
2004
73.5
107.4
32.9
47.4
2005
72.9
111.1
33.5
48.9
2006
79.4
106.6
35.2
48.1
2007
78.3
107.4
33.7
47.3
2008
89.9
112.4
37.5
50.5
2009
78.2
123.6
35.4
55.5
2010
101.2
141.3
42.7
63.5
2011
81.1
144.0
37.4
66.6
2012
56.7
156.0
26.3
70.9
2013
61.9
167.1
24.7
76.3
2014
69.2
173.4
30.5
77.1
2015
123.7
175.4
53.7
80.7
2016
84.4
172.7
41.1
80.1
Sources and notes: derived from Kynetec 1998-2016. 1997 based on the average of the years 1997-1999.
Kynetec does not permit publishing of average ai/ha figures derived from its dataset©PG Economics Ltd 2018102

GM crop impact: 1996-2016

As the herbicide usage data for the conventional crop presented in Table 52 is likely to be biased
and unrepresentative 80, an alternative that would deliver a similar level of weed control to thelevel delivered in the GM HT system, based on recommended practices from extension advisors
and industry analysts 81 since 2006, is summarised in Table 53. These conventional crop herbicide
usage levels were then compared to recorded usage levels on the GM HT crop since 2006, using
the dataset from Kynetec.
Table 53: Average ai use and field EIQs for conventional cotton 2006-2016 to deliver equal
efficacy to GM HT cottonYear
ai use (kg/ha)
Field EIQ/ha
2006
2.61
49.3
2007
2.98
52.1
2008
3.26
60.1
2009
3.59
64.6
2010
4.07
73.6
2011
4.48
85.0
2012
4.54
88.9
2013
4.96
95.3
2014
4.71
90.2
2015
4.82
89.0
2016
5.07
92.6
Sources: based on Sankala & Blumenthal (2006), Johnson & Strom (2008) and updated to reflect changes in
weed resistance management practices

Using this more representative herbicide usage data for conventional cotton and comparing it torecorded GM HT usage, the average herbicide active ingredient use and the associatedenvironmental load, as measured by the EIQ indicator, for conventional cotton is higher than GM
HT cotton. Since the mid 2000s, the average amount of herbicide active ingredient used on GM
HT cotton has increased through a combination of additional usage of glyphosate (about a 30%
increase in usage per hectare) in conjunction with increasing use of other herbicides. All of the
GM HT crop area planted to seed tolerant to glyphosate received treatments of glyphosate and at
least one of the next five most used herbicides (trifluralin, acetochlor, S metolachlor, fomesafen
and pendimethalin). This compares with 2006, when only three-quarters of the glyphosate
tolerant crop received at least one treatment from the next five most used herbicides (2 4-D,
trifluralin, pyrithiobic, pendimethalin and diuron). In other words, a quarter of the glyphosate
tolerant crop used only glyphosate for weed control in 2006 compared to none of the crop relying
solely on glyphosate in 2016. This suggests that US cotton farmers are increasingly adopting
recommended practices for managing weed resistant to glyphosate (and other herbicides).
Using this basis for comparing herbicide regimes for conventional and GM HT cotton at thenational level (Table 54), shows that the impact of using the GM HT technology in 2016 resulted
in a 13.4% decrease in the amount of herbicide use (2.62 million kg) and a 12% decrease in theassociated environmental impact, as measured by the EIQ indicator. Cumulatively since 1997,

80
This is particularly relevant to cotton because much of the conventional cotton crop still being grown is concentrated in regions which
traditionally use extensive production systems (eg, Texas)
81
The 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 2018103

GM crop impact: 1996-2016

there have been savings in herbicide use of 6.3% for ai use (19.7 million kg) and an 8.3% reductionin the associated environmental impact, as measured by the EIQ indicator.
Table 54: National level changes in herbicide ai use and field EIQ values for GM HT cotton in
the US 1997-2016
Yearai decrease (kg: +sign denotes increasein usage)

EIQ saving (units)% decrease in ai% EIQ saving

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

194,126
268,015
1,111,761
1,065,210
710,162
706,310
512,302+4,001+268,966+314,796
831,195
895,615
1,182,270
1,834,949
2,385,045
1,804,574
1,892,844
1,151,240
1,147,737
2,619,980

2,495,419
5,958,204
24,163,708
24,918,211
19,638,472
21,946,131
16,927,322
9,371,068
4,851,593
5,772,441
14,440,090
20,390,870
23,255,407
35,911,952
51,569,404
53,160,969
47,920,451
44,453,353
23,644,719
43,017,055

1.3
1.8
6.8
6.3
4.1
4.5
3.9
0.0
+1.8
+2.0
6.4
9.0
9.2
10.2
13.9
10.5
12.5
6.6
7.4
13.4

0.8
2.2
8.0
7.9
6.1
7.5
6.9
3.5
1.8
1.9
6.4
11.1
10.1
11.1
15.8
15.8
16.4
13.3
8.3
12.1

b) Australia
Drawing on information from the University of New England study from 2003 82, analysis of thetypical herbicide treatment regimes for GM HT and conventional cotton and more recent
industry assessments of conventional versus the newer ‘Roundup Ready Flex’ cotton that is
widely used in Australia (see Appendix 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 2016, 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 83;

82

Doyle et al (2003)
Based on advisor recommendation to deliver equal efficacy of weed control to ‘Flex cotton’ and inclusive of weed control in the preplant phase
83©PG Economics Ltd 2018104

GM crop impact: 1996-2016

•

•

•

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.
Thus in 2016, the average field EIQ/ha for GM HT cotton was 90/ha compared to 143/ha
for the conventional cotton equivalent;
Based on the above data, at the national level (Table 55), in 2016, herbicide ai use has
been 28.9% lower than the level expected if the whole crop had been planted toconventional cotton cultivars. The total field EIQ load was 36% lower;
Cumulatively since 2000, total national herbicide ai use fell by 17.5% (4.19 million kg) andthe total EIQ load decreased by 23.1%.

Table 55: National level changes in herbicide ai use and field EIQ values for GM HT cotton inAustralia 2000-2016
Yearai decrease (kg: +EIQ saving (units)% change in ai: (+% EIQ saving
sign denotes increase
sign denotes increasein usage)in usage)
2000+1,290106,030
+0.1
0.4
2001
+8,051
661,743
+0.8
3.6
2002
+9,756
801,898
+1.5
6.5
2003
+9,028742,052
+1.7
7.2
2004
+17,624
1,448,593
+2.0
9.0
2005
+24,235
1,991,945
+2.9
12.1
2006
48,910471,405
7.4
4.5
2007
23,718228,602
8.4
5.2
2008
57,591
555,084
9.0
5.5
2009
83,111801,049
10.3
6.3
2010
242,096
2,333,389
10.6
6.5
2011
527,386
13,934,069
19.3
28.0
2012
387,840
10,247,123
19.3
27.9
2013
694,208
14,885,431
34.7
40.4
2014
349,750
7,499,441
34.6
40.3
2015
595,467
14,371,774
46.3
60.8
2016
1,253,095
30,243,449
28.9
36.4
Note: From 2015 values revised and include consideration of full resistant weed management practices andpre-plant weed controlc) South Africa
Using industry level sources that compare typical herbicide treatment regimes 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 2016, 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 2016 was 178 kg (0.6%) lower than
the amount that would probably have been used if the crop had all been planted to©PG Economics Ltd 2018105

GM crop impact: 1996-2016•

conventional seed. The total field EIQ load was, however, a more significant 13.4%
lower;
Cumulatively since 2001, total national herbicide ai use increased by 2.3% (12,950 kg),but the total EIQ load fell by 13.8%. This shows that although the amount of herbicide
used on 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 2016, all of thecotton crop (240,000 ha) used seed containing this trait.
Based on industry level information relating to typical herbicide treatment regimes 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 2016, the national level reduction in the amount of herbicide applied to the cotton crop
was 0.16 million 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
25% (-5.2 million kg). The field EIQ rating associated with herbicide use on theArgentine cotton crop fell 30% over the same period.

e) Other countries
Cotton farmers in Mexico, Colombia, Brazil and Paraguay have also been using GM HT
technology since 2005, 2006, 2009 and 2013 respectively. No analysis is presented for the impactof using this technology in these countries because of the limited availability of herbicide usagedata.
f) Summary of impact
In 2016, the overall effect of using GM HT cotton technology (Figure 17) in the adopting countries
has been a reduction in herbicide ai use 84 of 16.2% and a decrease in the total environmental
impact of 16.7%. Cumulatively since 1997, herbicide ai use fell by 8.2% (-29 million kg) and theassociated environmental impact fell by 10.7%.
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 2016 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.
84

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 2018106

GM crop impact: 1996-2016

Figure 17: Reduction in herbicide use and the environmental load from using GM HT cottonin the US, Australia, Argentina and South Africa 1997-2016

0.0%
-2.0%
-4.0%
-6.0%
-8.0%

-8.2%

-10.0%-10.7%-12.0%-14.0%-16.0%-18.0%-16.2%-16.7%

2016

Cumulative
Ai

EIQ

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 identified in Sankala and Blumenthal (2003 & 2006), Johnson andStrom (2008), updates for 2014 undertaken as part of this research and data from the Kynetec
dataset, the changes in herbicide use and resulting environmental impact arising from adoptionof GM HT canola in the US since 1999 85 are summarised in Table 56. This shows consistentsavings in terms of both the amount of herbicide active ingredient applied and the EIQ value forglyphosate and glufosinate tolerant canola relative to conventional canola.
Table 56: Active ingredient and field EIQ differences conventional versus GM HT canola US
1999-2016
Year

1999
2000
2001
2002
2003
2004
2005
85

ai saving GM HT(to glyphosate:
kg/ha)
0.68
0.68
0.68
0.57
0.57
0.79
0.79

ai saving GM HT(to glufosinate:kg/ha)
0.75
0.75
0.75
0.75
0.75
0.83
0.83

The USDA pesticide usage survey does not include coverage of canola©PG Economics Ltd 2018107

EIQ saving GM
HT (to glyphosate:
field EIQ/ha)
14.8
14.8
14.8
17.7
17.7
21.2
21.2

EIQ saving GM
HT (to glufosinate:
field EIQ/ha)
18.4
18.4
18.4
18.4
18.4
19.8
19.8

GM crop impact: 1996-2016

2006
0.7
0.78
19.8
18.8
2007
0.47
0.74
15.8
17.9
2008
0.47
0.74
15.8
17.9
2009
0.11
0.72
10.2
17.6
2010
0.09
0.57
9.9
14.6
2011
-0.02
0.65
8.2
16.1
2012
-0.11
0.65
6.5
16.6
2013 and 2014
-0.10
0.64
5.1
14.1
2015
-0.09
0.65
5.3
14.5
2016
-0.14
0.67
4.7
14.7
Sources: derived from Sankala & Blumenthal (2003 & 2006), Johnson & Strom (2008) and updates of thiswork, Kynetec

The reduction in the volume of herbicides used was equal to 172,000 kg of active ingredient (23.5%) in 2016. In terms of the EIQ load, this had fallen by 6 million field EIQ units (-38%)
compared to the load that 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 30%, and the EIQ load reduced by 44%.
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 base 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 86. As in the US, in 2016, in termsof active ingredient use, GM HT canola tolerant to glyphosate uses 0.14 kg/ha more and
GM HT canola tolerant to glufosinate uses 0.67 kg/ha less than the conventional
alternative;
The average field EIQ/ha load for GM HT canola has been consistently lower than theconventional counterpart (in 2016, 18.55/ha for GM glyphosate tolerant canola, 8.58/ha
for GM glufosinate tolerant canola and 23.22/ha for conventional canola);On the basis of these comparisons with conventional canola, the reduction in thevolume of herbicide used was 2.5 million kg (a reduction of 29%) in 2016. Since 1996,
the cumulative reduction in usage has been 21% (23.6 million kg);
In terms of the field EIQ load, the reduction in 2016 was 43% (80 million field EIQ units)
and over the period 1996-2016, the EIQ load factor fell by 33%.

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 tolerant
86

Herbicide tolerant by a non-GM process, tolerant to the imidazolinone group of herbicides©PG Economics Ltd 2018108

GM crop impact: 1996-2016

or ‘Clearfield’)). These comparisons have been updated in recent years to reflect changes in weed
management practices (notably for weed resistance management) and in 2016, the average 87
savings relative to conventional (HT) canola were 0.5 kg/ha for herbicide active ingredient usageand 22.31/ha for the field EIQ/ha value. At the national level, this resulted in a net saving of 0.23
million kg of active ingredient (a 6.9% saving across the total canola crop) and a 6.3% reduction in
the associated environmental impact of herbicide use (as measured by the EIQ indicator) on the2016 Australian canola crop. Since 2008, the total herbicide active ingredient saving arising fromuse of GM HT canola has been about 1 million kg of active ingredient (-3.9%), with the EIQ load
falling by 3.4%.
d) 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 (Figure18). More specifically:••

In 2016, total herbicide ai use was 22.6% lower (2.9 million kg) than the level of use if thetotal crop had been planted to conventional varieties. The EIQ load was also lower by
35%;
Cumulatively since 1996, the volume of herbicide ai applied was 18.2% lower than its
conventional equivalent (a saving of 27.3 million kg). The EIQ load had been reduced by
29.7%.

Figure 18: Reduction in herbicide use and the environmental load from using GM HT canolain the US, Canada and Australia 1996-2016

0.0%
-5.0%
-10.0%-15.0%-18.2%-20.0%-25.0%-22.6%-30.0%-35.0%-29.7%
2016-35.0%

Cumulative
ai

87

EIQ

Weighted by sales of seed between TT, ‘Clearfield’ and GM HT©PG Economics Ltd 2018109

GM crop impact: 1996-2016

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 2016 accounted forall of the crop (455,800 ha). In terms of weed control, the use of this technology has resulted in aswitch in use from a number of selective herbicides to glyphosate. Drawing on evidence from a
combination of industry observers and the 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
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 2016 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 lessherbicide, in terms of amount of active ingredient applied and would have a slightly lower
EIQ/ha value than the conventional equivalent (GM HT 2.86 kg ai/ha and a field EIQ/ha value of
46.25, compared to conventional 3.04 kg ai/ha, with a field EIQ/ha value of 48.92). Taking thesechanges into consideration, in 2016, the use of GM HT sugar beet resulted in a reduction in theamount of herbicide active ingredient used of 9% (82,000 kg) and a net reduction in the associatedEIQ value of 5.3%. 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 88, there has been a net decrease in the amount of herbicide active
ingredient used of 1 million kg (-10%) and a net reduction in the environmental load associatedwith herbicide use, as measured by the EIQ indicator of 19.4%.
GM HT sugar beet is also planted on a small area (11,575 ha in 2016) 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.

88

Which in effect is a largely hypothetical alternative given that almost all of the crop uses GM HT technology©PG Economics Ltd 2018110

GM crop impact: 1996-2016

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 targeted at stalk boring and rootworm pests has fallen (Table 57). Whilst levels ofinsecticide ai use have fallen on both conventional and GM IR maize, usage by GM IR growers
has consistently been lower than their conventional counterparts. A similar pattern has occurredin respect of the average field EIQ value. This data therefore suggests both that insecticide use
per se has fallen on the US maize crops over the last 21 years and that usage on GM IR crops has
fallen by a greater amount. However, examining the impact of GM IR traits on insecticide use ismore 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, typically, a maximum of about 10% of the crop was treatedwith insecticides for stalk boring pests each year and about 30% of the US maize area
treated with insecticides for corn rootworm. This means that assessing the impact of the
GM IR technology requires disaggregation of insecticide usage specifically targeted atthese pests and limiting the maximum impact area to the areas that would otherwise
require insecticide treatment, rather than necessarily applying insecticide savings to theentire area planted to seed containing GM IR traits targeting these pests. This isparticularly relevant if conclusions are to be drawn from examination of insecticide usagechanges overall and of the proportion of the US maize crop 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 of insecticides 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 theinsecticides clothiandin and thiamethoxam and is unrelated to the adoption of GM IR
technology;
Typically, the first users of the GM IR technology will be those 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 theareas 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, comparing thelevel of insecticide use on the small conventional crop with insecticide use on the GM IR
area would probably understate the insecticide savings, because the small conventional
farmers tend to be those who do not suffer the pest problems that are the target of the
GM IR technology and hence do not spray their crops with appropriate insecticide
treatments;
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 treatments (see for example, Hutchison et al (2010)).

©PG Economics Ltd 2018111

GM crop impact: 1996-2016

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 the Kynetec
database and relevant literature (eg, Carpenter & Gianessi (1999)). These sources identified
average usage of insecticides for the control of stalk boring pests and rootworm at 0.59 kg/ha(0.35 kg/ha from 2006 89) and 0.4 kg/ha respectively. The corresponding field EIQ/ha values are
20/ha for stalk boring pests (10/ha from 2006) and 20.5/ha for rootworm.
These active ingredient and field EIQ savings were then applied to the maximum of the area
historically receiving insecticide spray treatments for stalk boring pests and corn rootworm (10%and 30% respectively 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 was applied in
respect of rootworm insecticide savings was also reduced from 2011 in line with the increase in
the area of the GM IR crop receiving applications of insecticides commonly used to target
rootworm pests that reflect practices adopted by some farmers concerned that rootworm pests
might be developing resistance to some of the GM IR traited seed (eg, in 2016, the maximum area
on which the rootworm insecticide savings was 30% of the crop total less 0.14 million ha).
Based on this approach, at the national level, the use of GM IR maize has resulted in a saving in
the volume of insecticide ai use of 84% (of the total usage of insecticides typically targeted at bothcorn boring pests and corn rootworm) in 2016 (5.4 million kg) and the annual field EIQ load fellby 86% in 2016 (equal to 248 million field EIQ/ha units: (Table 58). Since 1996, the cumulative
decrease in insecticide ai use targeted at these pests has been 50% (67.7 million kg), and thecumulative reduction in the field EIQ load has been 51%.
Table 57: Average US maize insecticide usage and its environmental load 1996-2016:
conventional versus GM IR (insecticides largely targeted at stalk boring and rootworm pests)
Year

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

89

Average ai/ha(kg):
conventional
0.78
0.76
0.42
0.40
0.42
0.31
0.30
0.29
0.27
0.20
0.23
0.20
0.20
0.17
0.18
0.14

Average ai/ha(kg): GM IR
0.61
0.59
0.32
0.39
0.36
0.31
0.21
0.20
0.16
0.17
0.17
0.14
0.17
0.15
0.14
0.11

Reflecting changes in nature of insecticide use on conventional crops©PG Economics Ltd 2018112

Average field
EIQ:
conventional
22.4
22.0
11.9
12.1
12.7
10.0
10.1
9.0
8.7
6.5
7.9
8.3
12.8
12.1
10.5
10.2

Average field EIQ: GM
IR
18.1
17.7
9.1
11.5
10.4
9.6
6.9
5.7
4.8
5.1
4.5
3.8
4.7
4.5
4.1
3.2

GM crop impact: 1996-2016

2012
0.20
0.12
10.1
3.8
2013
0.15
0.12
6.1
3.8
2014
0.20
0.10
8.1
4.3
2015
0.20
0.12
8.0
5.0
2016
0.21
0.13
8.1
5.1
Sources: derived from Kynetec (limited insecticides typically targeting control of stalk boring and rootworm
pests and excluding seed treatments for which there is no significant difference in the pattern of usage
between conventional and GM IR maize) and Carpenter & Gianessi (1999)

Table 58: National level changes in insecticide ai use and field EIQ values for GM IR maize in
the US 1996-2016 (targeted at stalk boring and rootworm pests)Year

ai decrease (kg)EIQ saving (units)% decrease in ai

1996
177,000
4,800,000
2.8
1997
1,443,310
39,140,608
22.5
1998
1,914,078
51,907,200
29.9
1999
1,847,762
50,108,800
28.8
2000
1,899,446
51,510,400
29.6
2001
1,807,524
49,017,600
28.2
2002
1,883,752
51,084,800
29.4
2003
2,005,348
57,484,618
31.3
2004
2,3484,892
74,133,757
36.6
2005
2,653,718
88,882,618
41.0
2006
2,514,522
103,699,853
39.2
2007
4,987,715
225,553,601
77.8
2008
4,932,847
227,547,463
77.0
2009
4,992,493
230,298,867
77.9
2010
5,081,253
234,393,262
79.3
2011
5,324,824
245,628,976
83.1
2012
5,336,800
245,444,000
83.3
2013
5,126,178
234,555,349
79.9
2014
4,855,959
222,162,443
75.7
2015
4,817,014
220,933,267
76.6
2016
5,386,329
248,183,648
83.9
Note: 2003 was the first year of commercial use of GM IR targeting corn rootworm% EIQ saving
1.7
13.6
18.1
17.4
17.9
17.0
17.8
20.0
25.8
30.9
36.1
78.4
79.1
80.1
81.5
85.4
85.2
81.5
77.2
82.2
86.2

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 90, 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
Canadian maize area in any subsequent year, the cumulative reduction in insecticide ai use

90

And limiting the national impact to 5% of the total maize crop in Canada – the estimated maximum area that probably received
insecticide treatments targeted at corn boring pests before the introduction of GM IR maize©PG Economics Ltd 2018113

GM crop impact: 1996-2016

targeted at stalk boring pests has been 746,000 kg (-88%). In terms of environmental load, thetotal EIQ/ha load has fallen by 20.4 million units (-62%) 91.
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 (2002)), 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. The differencein the data presented for Spain relative to the other countries is that the changes identified in
insecticide usage relate to total insecticide use rather than insecticides typically used to target
stalk boring pests. As a result of the adoption of GM IR maize, there has been a net decrease inboth the volume of insecticide used and the field EIQ/ha load 92. More specifically:••

The volume of total maize insecticide ai use was 39% lower than the level would
probably have been if the entire crop had been conventional in 2016 (-34,320 kg). Since
1998 the cumulative saving (relative to the level of use if all of the crop had been
conventional) was 615,000 kg of insecticide ai (a 36% decrease);
The field EIQ/ha load has fallen by 21% since 1999 (-16.5 million units). In 2016, the field
EIQ load was 22% 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:•••

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);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.

91

This relates to the total insecticide usage that would otherwise have probably been used on the Canadian maize crop to combat cornboring pests
92
The average volume of all insecticide ai used is 0.96 kg/ha with an average field EIQ of 26/ha©PG Economics Ltd 2018114

GM crop impact: 1996-2016

Based on these assumptions:••

In 2016, 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 70% (1.97 million kg ai).

f) Brazil
The GM IR maize area in Brazil, in 2016, was 14.88 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 93. 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 3 million kg of insecticide active ingredient saving in 2016. This represents a
100% reduction in the environmental impact associated with insecticide use targeted at thesepests. Cumulatively, the ai and field EIQ savings have been 90% lower than they would
otherwise have been if this technology had not been used (a saving of 20.9 million kg of ai).
g) Colombia
The GM IR area in Colombia in 2016 was 79,750 ha (first grown in 2009). Based on analysis by
Mendez et al (2011), this estimates that conventional maize growers (in the San Juan valley)
typically use 0.56 kg/ai of insecticide to control maize pests, with an average field EIQ of 15.89/ha.
Applying these savings to the GM IR area in 2009-2016, the technology has contributed to asaving in insecticide active ingredient use of 0.2 million kg. In terms of both active ingredient use
and EIQ rating, this represents about a 69% reduction.
h) Vietnam
GM IR maize was first used in 2015, and in 2016 was planted on 3% of the total maize crop
(35,000 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, this shows that:•93

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 0.34 kg/ha and 9.51 field EIQ/ha (based on recorded insecticide use 2012-2014: sources:
Kleffmann and Kynetec). The maximum area on which these insecticides are annuallyapplied is estimated to be about 725,000 ha;

Based on AMIS Global data for the 2006-2009 period©PG Economics Ltd 2018115

GM crop impact: 1996-2016

Based on these savings, over the two years of adoption of GM IR maize technology, theinsecticide active ingredient usage saving and EIQ load reduction have both been 2.7% (asaving of 13,000 kg of insecticide active ingredient usage).

•i) Other countries
GM IR maize has also been grown on significant areas in the Philippines (since 2003: 653,000 ha
planted in 2016), in Uruguay (since 2004: 46,400 ha in 2016), in Honduras (since 2003: 38,700 ha in2016) and in Paraguay (since 2013, 300,000 ha in 2016). Due to limited availability on insecticide
use on maize crops 94, it has not been possible to analyse the impact of reduced insecticide use andthe 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 19):••

In 2016, an 82.3% decrease in the total volume of insecticide ai applied (8.7 million kg)
and an 88.2% reduction in the environmental impact (measured in terms of the field
EIQ/ha load 95);
Since 1996, 56.1% less insecticide ai has been used (92 million kg) and the environmental
impact from insecticides applied to the maize crop has fallen by 58.6%.

Figure 19: Reduction in insecticide use and the environmental load from using GM IR maizein adopting countries 1996-2016

0.0%-10.0%-20.0%-30.0%-40.0%-50.0%-56.1%-60.0%-58.6%-70.0%-80.0%-90.0%-82.3%
2016-88.2%

Cumulative
Ai

94

EIQ

Coupled with the ‘non’ application of insecticide measures to control some pests by farmers in many countries and/or use ofalternatives such as biological and cultural control measures
95
Readers should note that these estimates relate to usage of insecticides targeted mainly at stalk boring and rootworm 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 2018116

GM crop impact: 1996-2016

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 20). 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 aresult, 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 will be those farmers who regularly
experience economic levels of damage from the GM IR target pests. This means that once
the levels of adoption (in terms of areas planted to the GM IR traits) become significant(above 50% of the US crop from 2005, and 84% in 2016), 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 the Kynetec database andrelevant literature (eg, Carpenter & Gianessi (1999), Sankala & Blumenthal (2003 & 2006)). 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 thetotal crop receiving each active ingredient in a baseline period of 1996-2000. As most of these
insecticide active ingredients are still in use in 2016 (for control of some other pests than thosetargeted by the GM IR trait), we have calculated the potential maximum usage of each insecticide©PG Economics Ltd 2018117

GM crop impact: 1996-2016

for each year under the assumption no GM IR technology was used (using the baseline 1996-2000
adoption rates) and then compared these levels of use with actual recorded usage in each year.
The difference between the two values represents the savings in insecticide usage attributed to
the GM IR technology. The annual savings estimated have been between 0.21 kg/ha and 0.95
kg/ha of active ingredient use and the field EIQ savings have been between 7.76/ha and 20/ha. In
2016, the savings were at the higher end of this range (0.93 kg/ai/ha and the field EIQ saving of
19.8/ha). These active ingredient and field EIQ savings 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 64.2% in 2016 (3 million kg) and the annual field EIQ load on the US cotton
crop also fell by 51% in 2016 (equal to 63.9 million field EIQ/ha units). Since 1996, the cumulative
decrease in insecticide ai use has been 25.9% (22.5 million kg), and the cumulative reduction in
the field EIQ load has been 19.6% (Table 59).
Figure 20: Average cotton insecticide usage: 1996-2016 (average kg active ingredient/ha)
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

Sources: derived from Kynetec and USDA NASS

Table 59: National level changes in insecticide ai use and field EIQ values for GM IR cotton in
the US 1996-2016
Yearai decrease (kg)EIQ saving (units)% decrease in ai% EIQ saving

1996
1997
1998
1999
2000
2001
2002

213,371219,217236,617410,076564,221
136,502511,015

7,708,736
7,919,934
8,548,572
15,070,341
19,685,752
27,049,342
18,226,708

3.1
2.3
3.2
6.7
10.2
13.0
13.5

3.9
4.0
4.3
8.3
11.2
17.7
14.6

©PG Economics Ltd 2018118

GM crop impact: 1996-2016

2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

560,624649,509
1,143,628
1,193,080
929,047
613,891
689,965
1,187,626
1,152,902
1,185,258
1,968,341
2,795,226
2,533,264
3,010,411

20,236,059
23,980,157
42,105,057
43,623,825
34,274,333
22,331,832
25,161,611
43,639,636
42,225,917
43,862,290
41,977,128
59,567,486
53,592,220
63,938,943

12.8
17.4
32.3
18.4
24.9
27.2
28.7
32.6
32.8
39.8
50.6
59.1
63.5
64.2

17.4
15.5
27.6
27.6
25.1
22.5
24.8
28.2
23.0
23.7
22.9
29.7
27.5
51.1

b) 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) 96. 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 (see Appendix 3 for 2016) put 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.
Based on these differences, the amount of insecticide ai used and its environmental load impact
were respectively 41% and 28% lower in 2016 (Table 60) 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 30.9% (130.6 million kg ai) and the field EIQ load has fallen by 30.5% (6billion field EIQ/ha units).
Table 60: National level changes in insecticide ai use and field EIQ values for GM IR cotton in
China 1997-2016

96

Year

ai decrease (kg)EIQ saving (units)% decrease in ai% EIQ saving

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006

158,780
1,218,870
3,054,180
5,678,720
10,152,580
9,807,000
13,076,000
17,279,000
15,411,000
16,335,660

7,843,630
60,211,395
150,874,530
280,525,120
501,530,930
484,459,500
645,946,000
853,571,500
761,293,500
806,971,110

0.6
4.5
13.6
24.8
35.0
38.8
42.5
50.3
50.2
51.2

0.6
4.6
13.9
25.3
35.7
39.5
42.5
50.3
50.2
51.2

Sources: based on a combination of industry views and Pray et al (2001)©PG Economics Ltd 2018119GM crop impact: 1996-2016

2007
3,382,000
158,236,180
20.5
19.8
2008
3,406,920
159,402,131
21.5
20.8
2009
3,177,300
148,658,727
22.8
22.0
2010
3,070,500
143,661,795
22.5
21.7
2011
3,499,925
163,753,620
23.1
23.9
2012
3,511,940
164,315,781
24.1
24.9
2013
5,766,600
149,307,312
33.9
24.9
2014
5,618,316
145,467,981
36.7
27.0
2015
3,779.520
97,791,360
40.9
29.6
2016
3,223,350
83,724,450
40.6
27.9
Note: Change of basis in comparison data conventional versus GM IR cotton in 2007: see appendix 3 forcurrent differencesc) Australia
Using a combination of data from AMIS Global/Kleffmann, industry sources and CSIRO 97, 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 61);
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 (Table 62) has been
respectively 54% (0.65 million kg) and 59% lower in 2016 than the levels that would haveoccurred if only conventional cotton had been planted;
Cumulatively, since 1996 the volume of insecticide use is 33.9% lower (19 million kg)
than the amount that would have been used if GM IR technology had not been adopted
and the field EIQ load has fallen by 35.3%.

Table 61: 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)

Table 62: National level changes in insecticide ai use and field EIQ values for GM IR cotton inAustralia 1996-2016
Yearai decrease (kg)EIQ saving (units)%decrease in ai% EIQ saving

1996
1997

266,945
390,175

4,900,628
7,162,905

6.1
9.1

5.6
8.4

97

The former making a direct comparison of insecticide use of Bollgard II versus conventional cotton and the latter a survey-based
assessment of actual insecticide usage in the years 2002-03 and 2003-04©PG Economics Ltd 2018120

GM crop impact: 1996-2016

1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

667,052
896,795
1,105,500
909,538
481,911427,621
1,932,876
2,177,393
1,037,850
486,886
1,066,894
1,403,591
2,925,150
656,285
487,625474,309
233,052
301,452
655,690

12,245,880
16,463,550
20,295,000
16,697,496
8,847,021
7,850,352
39,755,745
44,785,011
21,346,688
10,014,368
21,944,078
28,869,319
60,165,015
22,076,545
16,403,053
15,955,117
7,839,555
10,140,440
22,056,530

12.2
15.2
19.6
23.8
19.1
20.1
58.3
64.4
62.9
69.2
66.5
69.9
73.0
53.9
54.4
53.7
52.2
53.1
53.8

11.2
14.0
18.0
21.9
17.6
18.4
60.0
66.2
64.7
71.1
68.4
71.9
75.0
58.6
59.1
58.3
56.8
57.8
58.5

d) Argentina
Adoption of GM IR cotton in Argentina has also resulted in important reductions in insecticide
use 98:••••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 2016;
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 (Table 63) have been
respectively 44% (78,000 kg) and 60% lower (5.5 million field EIQ/ha units in 2016) thanthe levels that would have occurred if only conventional cotton had been planted;
Cumulatively since 1998, the volume of insecticide use is 24% lower (1.74 million kg) andthe EIQ/ha load 34% lower (117 million field EIQ/ha units) than the amount that would
have been used if GM IR technology had not been adopted.

Table 63: National level changes in insecticide ai use and field EIQ values for GM IR cotton in
Argentina 1998-2016

98

Year

ai decrease (kg)EIQ saving (units)% decrease in ai% EIQ saving

1998
1999
2000
2001
2002
2003

2,550
6,120
12,750
5,100
10,20023,664160,000
384,000
800,000
320,000
640,000
1,484,800

0.3
0.8
3.3
1.1
5.4
17.6

0.3
1.1
4.5
1.6
7.4
23.9

Based on data from Qaim and De Janvry (2005)©PG Economics Ltd 2018121

GM crop impact: 1996-2016

2004
22,4001,408,000
6.0
8.2
2005
9,180
576,000
3.2
4.4
2006
35,904
2,252,800
9.6
13.1
2007
66,2184,154,880
21.8
29.7
2008
121,176
7,603,200
44.1
60.1
2009
145,370
9,121,280
35.9
48.9
2010
201,030
14,190,336
43.4
59.0
2011
165,158
11,658,250
42.3
57.6
2012
128,928
9,100,800
43.8
59.6
2013
179,520
12,672,000
41.3
56.3
2014
134,379
9,485,568
44.3
60.4
2015
133,824
9,446,400
44.3
60.4
2016
78,336
5,529,600
44.3
60.4
Notes: derived from sources including CASAFE and AMIS Global. Decrease in impact for 2005 associatedwith a decrease in GM IR plantings in that yeare) 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 2016 are:••Conventional cotton: average volume of insecticide used was 1.72 kg/ha and a field
EIQ/ha value of 79.76/ha;
GM IR cotton: average volume of insecticide used was 0.6 kg/ha and a field EIQ/ha valueof 16.61/ha.

Based on these values, the level of insecticide ai use and the total EIQ load in 2016 wererespectively 62% (11.7 million kg) and 74% (595 million field EIQ/ha units) lower than would
have been expected if the total crop had been conventional cotton. Cumulatively, since 2002, theinsecticide ai use was 30.4% lower (111 million kg) and the total EIQ load 38.9% lower (5.44
billion EIQ/ha units).
f) Brazil
GM IR cotton was first planted commercially in 2006 (in 2016, on 511,000 ha, 54% 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 2016 were respectively
25% (166,000 kg) and 33% (11.8 million EIQ/ha units) lower than would have been expected if thetotal crop had been conventional cotton. Cumulatively since 2006, the total active ingredientsaving has been 1.1 million kg (13%) and the EIQ/ha load factor has fallen by 17%.

©PG Economics Ltd 2018122

GM crop impact: 1996-2016g) Mexico
GM IR cotton has been grown in Mexico since 1996, and in 2016, 94,000 ha (94% 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 2016, at a national level, there had been a 29% saving in the amount of insecticide
active ingredient use (152,000 kg) applied relative to usage if the whole crop had beenplanted to conventional varieties. The field EIQ load was 29% lower;
Cumulatively since 1996, the amount of insecticide active ingredient applied was 13.9%(2 million kg) lower relative to usage if the Mexican cotton crop had been planted to only
conventional varieties over this period. The field EIQ load was 13.8% lower than it
would otherwise have been if the whole crop had been using conventional varieties.

h) Other countries
Cotton farmers in South Africa, Colombia, Burkina Faso, Pakistan, Myanmar and Sudan havealso been using GM IR technology in recent years. Analysis of the impact on insecticide use andthe associated environmental ‘foot print’ are not presented for these crops because of the lack of
insecticide usage data.
i) 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 21):••

In 2016, a 55.9% decrease in the total volume of insecticide ai applied (18.9 million kg)
and a 59.4% reduction in the environmental impact (measured in terms of the field
EIQ/ha load);
Since 1996, 29.9% less insecticide ai has been used (288 million kg) and theenvironmental impact from insecticides applied to the cotton crop has fallen by 32.3%.

©PG Economics Ltd 2018123GM crop impact: 1996-2016

Figure 21: Reduction in insecticide use and the environmental load from using GM IR cottonin adopting countries 1996-2016

0.0%-10.0%-20.0%-30.0%-29.9%-32.3%-40.0%-50.0%-60.0%-55.9%
2016-59.4%

Cumulative
Ai

EIQ

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,
160 weed species that are resistant to ALS herbicides and 74 weed species resistant tophotosystem II inhibitor herbicides. Worldwide there are currently (accessed March 2018) 41
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 not associated 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 are respectively 9, 8 and 5. Some of the glyphosateresistant species, such as marestail (Conyza canadensis), waterhemp (Amaranthus tuberculatus) andpalmer pigweed (Amaranthus palmeri) in the US, are now reasonably widespread, with theaffected area being possibly within a range of 40%-60% of the total area annually devoted tomaize, cotton and soybeans.
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. This change in weed management emphasis also

©PG Economics Ltd 2018124

GM crop impact: 1996-2016reflects the broader agenda of developing strategies across all forms of cropping systems tominimise and slow down the potential for weeds developing resistance to existing control
methods. At the macro level, these changes have influenced the mix, total amount, cost andoverall profile of herbicides applied to GM HT crops in the last 15 years.
For example, in the 2016 US GM HT soybean crop, 89% of the GM HT soybean crop received an
additional herbicide treatment of one of the following (four most used, after glyphosate) active
ingredients 2,4-D (used before crop planting), chlorimuron, fomesafen and sulfentrazone (eachused primarily after crop planting). This compares with 14% of the GM HT soybean crop
receiving a treatment of one of the next most used four 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) increased by 90% over this period. The increase in
non-glyphosate herbicide use is primarily in response 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 in 2016,
glyphosate accounted for a lower share of total active ingredient use on the GM HT crop (63%) as
in 1998 when it accounted for 82% of total active ingredient use, highlighting that, although
farmers are making additional use of non-glyphosate herbicides, they continue to realise value inusing glyphosate because of its broad-spectrum activity. On the small conventional crop, theaverage amount of herbicide active ingredient applied increased by 94% over the same period
reflecting a shift in herbicides used rather than increased dose rates for some herbicides. The
increase in the use of herbicides on the conventional soybean crop in the US can also be partly
attributed to the on-going development of weed resistance to non-glyphosate herbicides
commonly used and highlights that the development of weed resistance to herbicides is aproblem faced by all farmers, regardless of production method. It is also interesting to note thatsince the mid-2000s, 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 in usage per hectare) in conjunction with increasing use of other herbicides. All of the
GM HT crop area 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 andparaquat). This compares with 2006, when only three-quarters of the glyphosate tolerant crop
received at least one treatment from the next five most used herbicides (2 4-D, trifluralin,pyrithiobic, pendimethalin and diuron). In other words, a quarter of the glyphosate tolerant cropused only glyphosate for weed control in 2006 compared to none of the crop relying solely on
glyphosate in 2016. This shows that US cotton farmers now make increasing use of additional
herbicides with different modes of action for managing weed resistance (to glyphosate). Many
are also making increasing use of glufosinate for ‘over the top’ treatments of GM HT cotton
tolerant to both glyphosate and glufosinate (used on 32% of the GM HT cotton area in the US,
compared to 10% of this area in 2012), as farmers rotate or alternate the primary herbicide used
for weed control in these crops.
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).

©PG Economics Ltd 2018125

GM crop impact: 1996-2016

4.2.2 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’ (NT) and ‘reduced-till’ (RT) 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:
•
•
•
•
•

c)

Lower fuel costs (less ploughing);
Reduced labour requirements;
Enhanced soil quality and reduced levels of soil erosion, resulting in more carbon
remaining in soil, which leads to lower GHG emissions 99;
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)).

Additional carbon dioxide can be assimilated where the GM technology leads to higher
yields and levels of production (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 of carbon
in the soil with no/reduced 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): uses the traditional mouldboard plough followed by multiple
tillage trips (up to 15) and results in less than 15% of old crop residue remaining on thesurface;
Reduced Tillage (RT): less intensive tillage resulting in reduced soil disturbance. RT
includes ‘mulch-till’ that disturbs 100% of the soil and requires 1-3 tillage passes and‘ridge-till’ where 4-6 inch high ridges are built during row cultivation and then 1-2 inchesof the ridge are scraped off during planting. In RT 15%-30% of old crop residue remains
on the surface after planting;No-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. At least 30% of old crop
residue commonly remains on the surface through which new crop seeds are planted.

99

The International Panel on Climate Change (IPCC) has agreed that conservation/no till cultivation leads to higher levels of soil carbon.
http://www.ipcc.ch/ipccreports/sres/land_use/index.php?idp=174©PG Economics Ltd 2018126

GM crop impact: 1996-2016

4.2.1 Tractor fuel usea) Reduced and no tillage
The adoption of conservation tillage systems, notably NT systems, has been facilitated by theavailability of GM HT crops. To estimate fuel savings from reduced tillage, we have reviewed
reports and data from a number of sources, of which the main ones were: the United States
Department of Agriculture’s (USDA) Energy Estimator for Tillage Model (2014), the USDA online
tool for estimating carbon storage in agroforestry practices (COMET-VR), Reeder (2010) and the
University of Illinois (2006):•

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 USA and compares potential
energy savings between conventional tillage (CT) 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 64).
Conventional tillage requires 49.01 litres/ha, compared to mulch till at 40.88 litres/ha,
ridge till 32.36 litres/ha and no-till 21.79 litres/ha;

Table 64: US soybean: tractor fuel consumption by tillage method (litres/ha)
Conventionaltillage

Mulch till

Ridge-till

No-till

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
Planter, double disk operation w/fluted
coulter

4.12

4.12

4.12

0.00

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

Year 1 – Illinois

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 conventional tillage:
Source: USDA Energy Estimator 2012•

The fuel saving obtained by a switch from conventional tillage to mulch-till, ridge-till andno-till for corn and soybeans across the three most important crop management zones(CMZ's) in the US is illustrated in Table 65. The adoption of no-till in corn results in a
24.41 litre/ha saving compared with conventional tillage and in the case of soybeans, theno-till saving is 27.12 litre/ha 100, a saving of 44.8% and 55.3% respectively;

100

These figures have not differed since 2012 when the USDA Energy Estimator for Tillage Model (https://ecat.sc.egov.usda.gov/) waslast updated©PG Economics Ltd 2018127

GM crop impact: 1996-2016

Table 65: Total farm diesel fuel consumption estimate (litres/ha)
Crop (crop management zones)

Conventional

Mulch-till

Ridge-till

No-till

46.98

36.39

30.09

Potential fuel savings over conventional tillage

7.52

18.11

24.41

Saving

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

21.2%

31.2%

55.3%

tillageCorn (Minnesota, Iowa & Illinois)
Total fuel use

54.50

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 41.81 litres/ha when conventional tillage isreplaced by no-till on non-irrigated corn and a reduction of 59.68 litres/ha in the case ofsoybeans in Nebraska;
The University of Illinois (2006) compared the relative fuel use across four different
tillage systems for both corn and soybeans. The ‘deep’ tillage and ‘typical’ intensive
systems required 36.01 litres/ha compared to the strip-till and no-till systems which used
22.92 litres/ha – a reduction of 13.09 litres/ha;
Reeder (2010) estimated that RT or NT typically uses 19 to 38 litres/ha less diesel fuel thanconventional tillage;
Analysis by the Jasa (2002) at the University of Nebraska calculated fuel use based onfarm survey data for various crops and tillage systems. Intensive tillage (resulting in 0%15% crop residue) using the mouldboard plough uses 49.39 litres/ha, reduced tillage(15%-30% residue) based on a chisel plough and/or combination of disk passes uses
28.34-31.24 litres/ha, conservation tillage (>30% residue) based on ridge tillage 25.16
litre/ha and no-till and strip-tillage 13.38 litres/ha - a reduction of 36.01 litres/hacompared to intensive tillage;
Other analysts have suggested similar savings in fuel from no-till. For example, the
USDA 2007 Farm Bill Theme Paper ‘Energy and Agriculture’ stated: ‘During the past
couple of decades, the Natural Resources Conservation Service (NRCS) has helped farmers adopt
no-till practices on about 25 million hectares of cropland. Assuming an average saving of 33.13
litres/ha in diesel fuel, this amounts to savings of 821 million litres of diesel fuel per year with costsavings to farmers of about $500 million per year.’In our analysis 101 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 conventional tillage and in the case of RT cultivation by 10.39 litres/ha.
In the case of maize, NT results in a saving of 24.41 litres/ha and in the case of RT 7.52 litres/ha,
compared with conventional intensive tillage. These are conservative estimates and are in line

101

In previous editions of this report, the authors have used different savings that reflect changing estimates of fuel use by the USDA
Energy Estimator. In reports covering the period up to 2010 savings of 27.22 litres/ha for NT and 9.56 litres/ha for RT compared to CT
were used©PG Economics Ltd 2018128

GM crop impact: 1996-2016

with the USDA Fuel Estimator for soybeans and maize. The amount of tractor fuel used for seedbed preparation, herbicide spraying and planting in each of these systems is shown in Table 66.
Table 66: Tractor fuel consumption by tillage method (litre/ha) 2012
Tillage system

US soybean

US maize

litres/ha

litres/ha

49.01

54.50

Mulch till - Reduced tillage (RT): chisel plough, disc and seed planting

38.62

46.98

No-till (NT): fertiliser knife, seed planting plus 2 sprays

21.89

30.09

Intensive tillage: traditional cultivation: mouldboard plough, disc andseed planting etc.

Source: Adapted from USDA Fuel Estimator 2012

In terms of GHG, each litre of tractor diesel consumed contributes an estimated 2.67 102 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/CO2/ha and 27.74
kg/CO2/ha respectively for soybeans and 65.17 kg/CO2/ha and 20.08 kg/CO2/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 50-foot boom sprayer which consumes approximately 0.84 litres/ha 103(Lazarus (2015)). One less spray application therefore reduces carbon dioxide emissions by 2.24
kg/ha 104. Approximately 20% of pesticides in the US are applied by crop dusters which have amarginally lower carbon footprint than boom sprayers (National Agricultural Aviation
Association 2017).
The conversion of one hectare of conventional tillage to no-till equates to a saving ofapproximately 561 km travelled by a standard family car 105 and one less spray pass per hectare isequal to a saving of nearly 17.4 km travelled.

4.2.2 Soil carbon sequestration
The use of RT/NT farming systems increases the amount of organic soil carbon in the form ofcrop residue that is stored or sequestered in the soil and therefore reduces carbon dioxide
emissions to the environment. Appendix 5 summarises some of the key research which has
examined the relationship between carbon sequestration and different tillage systems. This
literature review shows that the amount of carbon sequestered varies by soil type, cropping

102
In previous editions of this report the authors have applied a co-efficient of 2.75 to convert 1 litre of diesel to kgs of carbon dioxide.
This report (and the reports covering the period 1996-2011, 1996-2012, 1996-2013 and 1996-2014) uses the updated figure of 2.6676
rounded to 2.67.
103
In previous editions of this report (up to and including the 5th report covering 1996-2009) the authors have used 1.31 litres/ha.
104
Given that many farmers apply insecticides via sprayers pulled by tractors, which tend to use higher levels of fuel than self-propelledboom sprayers, the estimates used in this section (for reductions in carbon emissions), which are based on self-propelled boom
application, probably understate the carbon benefits.
105
Assumed standard UK family car carbon dioxide emission rating = 129 grams/km. Therefore 72.41 kg of carbon dioxide divided by
129g/km = 561 km.

©PG Economics Ltd 2018129

GM crop impact: 1996-2016

system, eco-region and tillage depth. It also shows that tillage systems can impact on levels ofother GHG emissions such as methane and nitrous oxide and on crop yield.
Overall, the literature highlights the difficulty in estimating the contribution NT/RT systems canmake to soil carbon sequestration, because of the dynamic nature of soils, climate, cropping types
and patterns. If a specific crop area is in continuous NT crop rotation, the full soil carbon
sequestration benefits described in the literature can be realised. However, if the NT crop area isreturned to a conventional tillage system, a proportion of the soil organic carbon gain will be lost.
The temporary nature of this form of carbon storage only becomes permanent when farmers
adopt a continuous NT system, which, as indicated earlier, is highly dependent upon having
effective herbicide-based weed control systems.
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 conventional tillage to NT and
RT based on a meta-analysis of the literature on the subject (Table 67). In this tool coefficients are
generalized at the national-scale and differentiated by dry and humid climate zones with thevalues shown being emission reductions relative to baseline management (positive values mean adecrease in emissions due to the implementation of the tillage practice). For example, theconversion of one hectare of crop land from CT to NT in a moist/humid environment will resultin 1,037.8 kg of carbon dioxide/ha/year being sequestered; this is equivalent to 282.8 kg
carbon/ha/year.
Table 67: 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. 1 kg carbon equals 3.67 kg carbon dioxide

Our analysis for the US uses the COMET-VR 2.0 tool 106 for three key soybean and corn
production states and assumes the adoption of NT from CT in all states, a clay loam soil withaverage fertiliser usage, a non-irrigated corn-soybean rotation in Minnesota and Illinois and asoybean-corn-winter-wheat rotation in South Dakota. Using the COMET-VR 2.0 tool, the level ofcarbon 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.

106

COMET-VR 2.0 is a web-based tool that provides estimates of carbon sequestration and net greenhouse gas emissions from soils andbiomass for US farms. It links databases containing information on soils, climate and management practices to run an ecosystemsimulation model as well as empirical models for soil N2O emissions and CO2 from fuel usage for field operations. In 2011, an updated
version was released - http://www.comet2.colostate.edu/. In 2014 the tool was updated to COMET FARM http://cometfarm.nrel.colostate.edu/©PG Economics Ltd 2018130

GM crop impact: 1996-2016

Analysis using the Michigan State University - US Cropland Greenhouse Gas Calculator 107 forcorn-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 corn 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 corn NT and CT
is 247 kg carbon/ha/year and for soybeans 103 kg carbon/ha/year (Table 68).
Table 68: Summary of the potential of corn and soybeans cultivation systems to reduce net
emissions or sequester carbon (kg of carbon/ha/year)

Corn

Carbon sequestered(kg/ha/year)-3

Carbon sequestered - difference toNT (kg/ha/year)-247

Reduced72-171

No-till244

0Conventional

-146

-103

Reduced-114-72

No-till-43

0Conventional

Soybean

Source: Michigan State University - US Cropland Greenhouse Gas Calculator

Differences in carbon soil sequestration rates between corn and soybeans can be explained by thegreater plant matter residue contribution of the corn crop in the soybean-corn rotation. Research
by Alvarez & Steinbach (2012) estimated that corn/maize contributes 7,178 Mg/ha/year of dry
matter as crop residue compared to soybeans which contribute less (by 50%) at 3,373 Mg/ha/year.
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 (up to 1996-2011) no differentiation was made between corn andsoybeans. 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 (NTsystems store 375 kg of carbon/ha/year; RT systems store 175 kg of carbon/ha/year; and CT
systems store 25 kg of carbon/ha/year). In this report (and the previous three), the soil carbon
sequestered by tillage system for corn in continuous rotation with soybeans is assumed to be a
net sink of 250 kg of carbon/ha/year based on:
•
•
•

107

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.

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GM crop impact: 1996-2016

The soil carbon sequestered by tillage system for soybeans in a continuous rotation with corn isassumed to be a net sink of 100 kg of carbon/ha/year 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 biotech crops has resulted in a reduction in the number of spray passes or theconsistent use of less intensive cultivation practices (less ploughing) this has provided (andcontinues 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 (2004)). 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 conventional tillage to reduced-till and no-till. This has
had a marked effect on tractor fuel consumption due to energy-intensive cultivation methods
being replaced with no/reduced tillage and largely herbicide-based weed control systems. The
GM HT crop where this is most evident is GM HT soybeans. Here, adoption of the technology
has made an important contribution to facilitating the adoption of reduced or no tillage
farming 108. Before the introduction of GM HT soybean cultivars, NT systems were practised bysome farmers with varying degrees of success using a number of herbicides. The opportunity forgrowers to control weeds with a non-residual foliar herbicide as a “burn down” pre-seeding
treatment, followed by a post-emergent treatment when the soybean crop became established,
made the NT system more reliable, technically viable and commercially attractive. These
technical and cost advantages have contributed to the rapid adoption of GM HT cultivars and asubstantial increase in the NT soybean area in the US (also more than a seven-fold increase inArgentina). In both countries, GM HT soybeans are estimated to account for over 95% of the NTsoybean crop area.

108

See for example, CTIC 2002.

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GM crop impact: 1996-2016

4.2.4 Herbicide tolerant soybeans
4.2.4.1 The US
The area of soybeans cultivated in the US has increased from 26 million ha in 1996 to 33.5 million
ha in 2016. Over the same period, the soybean area planted using conventional tillage (CT) fellby 24% (from 7.5 million ha to 5.7 million ha), the area planted using RT 109 decreased by 22%(from 10.7 million ha to 8.4 million ha) and the area planted using NT increased by 151% (from7.7 million ha to 19.4 million ha: Table 69).
The most rapid rate of adoption of the GM HT technology has been by farmers using NT systems(GM HT cultivars accounting for an estimated 99% of total NT soybeans by 1999). This compareswith conventional tillage systems where GM HT cultivars account for an estimated 68.3% of total
conventional tillage plantings (Table 69).
Table 69: US soybean: tillage practices and the adoption of GM HT cultivars 1996-2016 (million
ha)
Total

No-tillarea

ReducedConven

Total

Total

No till

ReducedConventtill

tional tillGM

convenGMtill GM

ional

HT

tional areaHT

HT areaarea(non-GM)area

tillage
GM HT
area

25.98
7.72
10.75
7.51
0.49
25.49
0.37
0.11
1996
28.33
8.72
12.03
7.58
3.20
25.13
1.62
1.20
1997
29.14
9.28
12.69
7.17
11.78
17.36
8.52
2.54
1998
29.84
9.65
12.78
7.41
16.39
13.45
9.55
5.11
1999
30.15
9.90
12.69
7.56
18.21
11.94
9.80
5.71
2000
29.99
10.16
12.53
7.30
22.18
7.81
10.05
9.40
2001
29.55
10.31
12.26
6.98
24.28
5.27
10.20
11.03
2002
29.71
10.92
12.30
6.49
25.74
3.97
10.81
11.68
2003
30.28
11.69
12.51
6.08
27.20
3.08
11.57
11.88
2004
28.88
11.64
11.41
5.83
26.87
2.01
11.52
10.84
2005
30.56
12.84
11.52
6.20
27.20
3.36
12.71
11.06
2006
25.76
11.20
9.53
5.03
23.43
2.33
11.09
9.15
2007
30.20
13.59
10.66
5.95
27.79
2.41
13.47
10.24
2008
30.91
14.28
10.54
6.09
28.13
2.78
14.16
10.22
2009
31.56
14.99
10.89
5.68
29.35
2.21
14.89
10.56
2010
30.06
16.23
8.72
5.11
28.25
1.81
16.13
8.45
2011
30.82
17.26
8.32
5.24
28.67
2.15
17.17
8.16
2012
30.71
17.81
7.68
5.22
28.55
2.16
17.74
7.52
2013
33.43
19.39
8.36
5.68
31.42
2.01
19.33
8.19
2014
33.12
19.21
8.28
5.63
31.14
1.98
19.17
8.12
2015
2016
33.48
19.42
8.37
5.69
31.47
2.01
19.38
8.20
Source: Adapted from Conservation Tillage and Plant Biotechnology (CTIC) 1998, 2000, 2002, 2006, 2007
and 2008, GfK Kynetec, USDA-ERS ARMS (2016) Phase II soybean survey, Barrera (2016) No-Till Farmer
Magazine 8th Annual Benchmarking Study 2015, Dobberstein J. (2015)
Note: RT includes mulch and ridge till
109

Includes mulch and ridge till

©PG Economics Ltd 2018

133

0.01
0.38
0.72
1.73
2.70
2.73
3.05
3.25
3.75
4.51
3.43
3.19
4.08
3.75
3.90
3.67
3.34
3.29
3.90
3.85
3.89

GM crop impact: 1996-2016

The importance of GM HT soybeans in the adoption of a NT system has also been confirmed by
an American Soybean Association (ASA) study (2001) of conservation tillage. This study foundthat the availability of GM HT soybeans facilitated and encouraged 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 their adoption of reduced tillage practices.
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 only 7.9% (75.2 million litres - 1996 to 2016:Table 70)
while the area planted increased by 28.9%. Over the same period, the average fuel usage fell
16.3% (from 36.6 litres/ha to 30.7 litres/ha). A comparison of GM HT versus conventional
production systems shows that in 2016, the average tillage fuel consumption on the GM HT
planted area was 29.6 litres/ha compared to 47.6 litres/ha for the conventional crop.
Table 70: US soybean: consumption of tractor fuel used for tillage (1996-2016)
Total fuelAverage

Conventional average

GM HT average

consumption (million(litre/ha)(litre/ha)(litres/ha)

36.6
36.2
35.8
35.8
35.7
35.5
35.2
34.7
34.2
34.0
33.7
33.4
33.1
32.9
32.5
31.4
31.0
30.7
30.7
30.7
30.7

36.9
36.9
41.7
42.9
42.7
44.5
46.1
46.7
45.9
44.4
46.4
46.1
45.8
46.7
46.2
46.0
47.1
47.4
47.4
47.6
47.6

26.0
31.4
27.1
30.0
31.2
32.3
32.9
32.9
32.9
33.2
32.1
32.1
32.0
31.6
31.5
30.4
29.8
29.4
29.6
29.6
29.6

litres)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

952.1
1,027.0
1,044.9
1,067.9
1,077.2
1,064.2
1,040.9
1,032.1
1,036.9980.9
1,029.7859.6
1,001.0
1,018.0
1,027.1
942.2
956.1
942.1
1,025.5
1,016.3
1,027.3

The cumulative permanent reduction in tillage fuel use in US soybeans is summarised in Table
71. This amounted to a reduction in tillage fuel usage of 2,009 million litres which equates to a
reduction in carbon dioxide emission of 5,365 million kg.

©PG Economics Ltd 2018134

GM crop impact: 1996-2016

Table 71: US soybeans: permanent reduction in tractor fuel consumption and reduction incarbon dioxide emissions (1996-2016)
Annual reduction

Crop area

Total fuel saving

Carbon dioxidebased on 1996 average(million ha)(million litres)(million kg)

25.98
28.33
29.15
29.84
30.15
29.99
29.54
29.71
30.28
28.88
30.56
25.75
30.21
30.91
31.56
30.05
30.82
30.70
33.42
33.12
33.48

0.00
11.36
23.38
25.65
27.66
34.94
41.72
56.64
72.69
77.46
90.46
84.17
106.06114.73129.58159.19173.59183.19199.42
197.63199.772,009.31

0.00
30.33
62.41
68.50
73.86
93.28
111.39151.23194.09206.82241.52224.73283.19306.33345.99425.04463.49489.12532.46527.67533.395,364.84(litres/ha)
0.00
0.40
0.80
0.86
0.92
1.16
1.41
1.91
2.40
2.68
2.96
3.27
3.51
3.71
4.11
5.30
5.63
5.97
5.97
5.97
5.97

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

Total
Assumption: baseline fuel usage is the 1996 level of 36.6 litres/hab) Soil carbon sequestration
Based on the crop area planted by tillage system and type of seed planted (GM HT andconventional) and using estimates of the soil carbon sequestered by tillage system for corn andsoybeans in continuous rotation; the soybean NT system is assumed to release 45 kg ofcarbon/ha/year; the RT system releases 115 kg carbon/ha/year; and the CT system releases 145 kg
carbon/ha/year) 110.
Our estimates of total soil carbon sequestered for the US soybean crop over the 1996 to 2016
period are (Table 72):••

Although the area planted to soybeans has increased by 7.5 million ha, there has been asmall aggregate decrease of 10.4 million kg carbon/year (a release of 2,672 million kg in1996 compared to 2,662 million kg carbon/year in 2016);
the average level of carbon released per ha decreased by 22.7% (23.4 kg carbon/ha/year)
from 102.9 to 79.5 kg carbon/ha/year.

110

The actual rate of soil carbon sequestered by tillage system is, however, dependent upon soil type, soil organic content, quantity andtype of crop residue, so these estimates are indicative averages©PG Economics Ltd 2018135

GM crop impact: 1996-2016

Table 72: US soybeans: potential soil carbon sequestration (1996 to 2016)
Total carbon sequestered (million kg)

Average(kg carbon/ha/yr)

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

- 2,672.23- 2,874.83- 2,917.27- 2,978.15- 3,000.83- 2,957.01- 2,884.96- 2,846.80- 2,845.91- 2,680.60- 2,801.18- 2,328.83- 2,700.74- 2,737.44- 2,750.50- 2,473.26- 2,493.59- 2,440.95- 2,657.22- 2,633.35- 2,661.88-102.9-101.5-100.1
-99.8
-99.5
-98.6
-97.7
-95.8
-94.0
-92.8
-91.7
-90.4
-89.4
-88.6
-87.2
-82.3
-80.9
-79.5
-79.5
-79.5
-79.5

Cumulatively, since 1996 the increase in soil carbon sequestered due to the increase in RT and NT
in US soybean production systems has been 7,715 million kg of carbon which, in terms of carbon
dioxide emissions, equates to a saving of 28,315 million kg of carbon dioxide that would
otherwise have been released into the atmosphere (Table 73). Readers should note that thisestimate does not take into consideration the potential loss in carbon sequestration that may arise
if some of the land using RT/NT is returned to conventional tillage.
Table 73: US soybeans: potential additional soil carbon sequestration (1996 to 2016)
Annual increase in

Crop area (million ha)

Total additional

Total additional

carbon sequesteredcarbonCarbon dioxidebased on 1996 averagesequesteredsequestered(kg carbon/ha)(million kg)(million kg)

0.00
39.33
80.93
91.02
100.23127.80153.56208.80268.210.00
144.35297.02334.06367.85469.04563.58766.29984.34

1996
1997
1998
1999
2000
2001
2002
2003
2004

©PG Economics Ltd 2018

0.0
1.4
2.8
3.1
3.3
4.3
5.2
7.0
8.9

26.0
28.3
29.1
29.8
30.1
30.0
29.5
29.7
30.3

136

GM crop impact: 1996-2016

289.94342.60319.96406.34441.73495.86617.90676.92717.28780.83773.82782.207,715.26
Total
Assumption: carbon sequestration remains at the 1996 level of -102.9 kg carbon/ha/year
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

10.0
11.2
12.4
13.5
14.3
15.7
20.6
22.0
23.4
23.4
23.4
23.4

28.9
30.6
25.8
30.2
30.9
31.6
30.1
30.8
30.7
33.4
33.1
33.5

1,064.08
1,257.35
1,174.25
1,491.28
1,621.16
1,819.80
2,267.71
2,484.29
2,632.42
2,865.65
2,839.91
2,870.68
28,315.10

4.2.4.2 Argentina
Since 1996, the area planted to soybeans in Argentina, has increased from 5.91 to 18.6 million ha(+215%). Over the same period, the area planted using NT practices also increased substantiallyfrom 2.15 to 16.6 million ha, whilst the area planted using conventional tillage decreased from3.76 to 2.05 million ha (Table 74).
As in the US, a key driver for the growth in NT soybean production has been the availability of
GM HT soybeans, which in 2016, accounted for 99.5% of the total Argentine soybean area. Finger
et al (2009: based on a survey of Argentine soybean growers) identified that the combination ofherbicide tolerance and NT were the key drivers to adoption of GM HT soybeans, facilitatingeasier crop management and reducing herbicide costs. As indicated in section 3, the availabilityof this technology has also provided an opportunity for growers to ‘second crop soybeans’ in a
NT system with wheat. In the early to mid-1990s, 5%-10% of the total soybean crop was a second
crop following on from wheat (in the same season). In the last ten years, the second crop soybean
area has been significantly higher, within a range of 15%-30% of the total soybean area (themaximum each year influenced by the total area planted to wheat).
During the 1990s and early 2000s, NT stimulated an increase in the soybean-maize rotation which
reduced insect pressure, restored soil organic matter (SOM), and 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 1990s, NT farming helped to reduce soil erosion by 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, contributed to higher crop yields of up to 11%,
as well as reducing fuel use and labour costs (source: Argentine No-Till Farmers Association(AAPRESID) 2009).

©PG Economics Ltd 2018137

GM crop impact: 1996-2016

Table 74: Argentine soybeans: tillage practices and the adoption of GM HT cultivars 1996-2016(million ha)
Total area

No-till (NT)Convention

Total GM

Total conven

NT GM

CT GM

al till (CT)HT areational area

HT area

HT area

0.04
1.76
3.32
3.78
5.02
6.66
8.67
9.78
11.39
11.54
12.41
13.56
14.59
15.83
15.83
16.55
17.22
17.58
17.60
17.27
16.56

0.00
0.00
1.48
2.86
3.98
4.27
3.78
3.45
2.67
3.41
3.43
2.86
2.01
2.35
2.19
1.86
2.03
2.07
2.08
2.03
1.95

(non-GM)
1996
5.91
2.15
3.76
1997
6.40
2.87
3.53
1998
6.95
3.32
3.63
1999
8.18
3.78
4.40
2000
10.59
5.02
5.57
2001
11.50
6.66
4.84
2002
12.96
8.67
4.29
2003
13.50
9.78
3.72
2004
14.35
11.39
2.96
2005
15.20
11.54
3.66
2006
16.15
12.41
3.74
2007
16.59
13.56
3.03
2008
16.77
14.59
2.18
2009
18.60
15.83
2.77
2010
18.20
15.83
2.37
2011
18.60
16.55
2.05
2012
19.35
17.22
2.13
2013
19.75
17.58
2.17
2014
19.78
17.60
2.18
2015
19.40
17.27
2.13
2016
18.60
16.55
2.05
Adapted from Benbrook, Trigo and AAPRESID (2012)

0.04
1.76
4.80
6.64
9.00
10.93
12.45
13.23
14.06
14.95
15.84
16.42
16.60
18.18
18.02
18.41
19.25
19.65
19.68
19.30
18.51

5.87
4.64
2.15
1.54
1.59
0.57
0.51
0.27
0.29
0.25
0.31
0.17
0.17
0.42
0.18
0.19
0.10
0.10
0.10
0.10
0.09

a) Fuel consumption
Between 1996 and 2016, total fuel consumption associated with soybean cultivation increased by
99.8% from 231.5 to 462.6 million litres/year. However, during this period, the average quantityof fuel used per ha fell 36.5% from 39.1 to 24.9 litres/ha, due mainly to the widespread adoptionof GM HT soybean seed and NT systems. If the proportion of NT soybeans in 2016 (applicable tothe total 2016 area planted) had remained at the 1996 level, an additional 3,483 million litres offuel would have been used. At this level of fuel usage, an additional 9,300 million kg of carbon
dioxide would otherwise have been released into the atmosphere (Table 75).
Table 75: Argentine soybeans: permanent reduction in tractor fuel consumption and reduction
in carbon dioxide emissions (1996-2016)

1996
1997
1998
1999

©PG Economics Ltd 2018

Annual reduction
based on 1996
average of 39.1
(litres/ha)
0.0
2.3
3.1
2.7

Crop area(million ha)

Total fuel saving(million litres)

Carbon dioxide(million kg)

5.9
6.4
7.0
8.2

0.0
14.7
21.5
21.9

0.00
39.16
57.39
58.54

138

GM crop impact: 1996-2016

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

3.0
5.8
8.3
9.8
11.7
10.7
11.0
12.3
13.7
13.2
13.7
14.3
14.3
14.3
14.3
14.3
14.3

10.6
11.5
13.0
13.5
14.3
15.2
16.2
16.6
16.8
18.6
18.2
18.6
19.4
19.8
19.8
19.4
18.6

Total
Note: based on 21.89 litres/ha for NT and 49.01 litres/ha for CT

31.6
67.2
107.3
132.2
167.4
163.0
177.4
204.2
230.4
245.9
249.8
265.5
276.3
282.0
282.4
277.0
265.5

84.45
179.41286.57352.90447.02435.19473.74545.15615.13656.53667.06709.00737.59752.84753.98739.49709.003,483.2

9,300.14b) 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/first soybean crop rotation. This resulted in soils
being relatively free of weeds and crop residues but exposed to heavy summer rains which often
led to extensive soil degradation and loss.
Research into ways of reducing soil degradation and loss was undertaken (mostly relating to theuse of NT systems 111) 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 is limited. Fabrizzi et al (2003)
indicated that a higher level of total organic carbon was retained in the soil with NT systemcompared with a CT system, but no quantification was provided. Detailed research by Steinbach(2006) modelled the impact on the conversion of the Argentinean Pampas to no-till to mitigate theglobal warming effect. This work estimated that NT conversion would result in an increase ofsoil 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 no-till after 35 years. Derpsch etal (2010) estimates that two-thirds of the area under NT systems in South America is permanently
in NT, which in Argentina is over 70% of the NT crop area. This suggests that these carbon
sequestration gains are of a permanent nature.

111

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 the surface, improvements in hydraulicconductivity, more efficient use of soil water, and higher soil organic matter contents.

©PG Economics Ltd 2018139

GM crop impact: 1996-2016

Results from a 15-year experiment in the semi-arid Argentine Pampa to evaluate a combination of
three tillage systems (no tillage, no tillage with cover crop in winter and reduced tillage) and two
crop sequences (soybean–maize and soybean monoculture) concluded that NT tillage system had
a greater impact on total organic carbon (TOC) stock than crop sequence (Alvarez et al (2014)).
Total organic carbon stock, up to a depth of 100 cm showed signiﬁcant differences between soils
under different tillage systems (RT < NT = NT with cover crop), the last ones having 8% morethan the RT treatment. Soybean–maize had 3% more organic carbon up to 100 cm depth than thesoybean monoculture. Up to 100 cm depth, the NT treatments accumulated 333 kg TOC/ha/year
more than RT, while the soybean-maize sequence accumulated only 133 kg TOC/ha/year morethan soybean monoculture. At 0–30 cm depth, the NT treatments had 267 kg TOC/ha/year morethan the RT treatment.
Applying a conservative estimate of soil carbon retention of 175 kg carbon/ha/yr for NT and arelease of 25 kg carbon/ha/yr for CT soybean cropping in Argentina, a cumulative total of 25,687
million kg of carbon, which equates to a saving of 94,272 million kg of carbon dioxide, has beenretained in the soil that would otherwise have been released into the atmosphere (Table 76).
Table 76: Argentine soybeans: potential additional soil carbon sequestration (1996 to 2016)
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)
0.0
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
101.23105.28105.28105.28105.28105.28105.28(million kg)

0.0
1996
108.17
1997
158.52
1998
161.681999
233.27
2000
495.53
2001
791.51
2002
974.712003
1,234.69
2004
1,202.00
2005
1,308.48
2006
1,505.72
2007
1,699.00
2008
1,813.37
2009
1,842.45
2010
1,958.28
2011
2,037.25
2012
2,079.36
2013
2,082.52
2014
2,042.51
2015
2016
1,958.28
25,687.30
Total
Assumption: NT = +175 kg carbon/ha/yr, Conventional Tillage CT = -25 kg carbon/ha/yr©PG Economics Ltd 2018

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

140

0.0
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
7,631.25
7,642.84
7,496.01
7,186.90
94,272.39

GM crop impact: 1996-2016

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 in theBrazilian soybean sector, 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 have examined 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 calculationsof 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 andwhere the availability of GM HT soybean technology is considered to have played an importantrole 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 33.9 million ha in 2016, of which these southernstates accounted for 33.7% (11.02 million ha). The vast majority of soybean production in thesestates uses NT systems (90%: 10.55 million ha), with virtually all of the NT area being GM HT
soybeans (Table 77).
Table 77: Southern Brazil (Santa Catarina, Parana and Rio Grande de Sol states) soybeans:tillage practices and the adoption of biotech cultivars 1997-2016 (million ha)
Total area

No-till

Convention

Total GM

Total

NT GM HTNT non-al tillage

HT areaconventional

area

GM HT

0.10
0.50
1.18
1.30
1.31
1.74
2.87
3.01
3.32
5.36
5.98
6.09
7.03
7.67
7.74
8.60
9.44
9.97
10.39
10.55

1.76
1.64
1.24
1.39
2.11
2.38
2.05
2.57
2.49
0.83
0.16
0.49
0.36
0.09
0.00
0.00
0.00
0.00
0.00
0.00

area
(non-GM)
1997
6.19
1.86
4.33
0.10
6.09
1998
6.12
2.14
3.98
0.50
5.62
1999
6.05
2.42
3.63
1.18
4.87
2000
5.98
2.69
3.29
1.30
4.68
2001
6.84
3.42
3.42
1.31
5.53
2002
7.49
4.12
3.37
1.74
5.75
2003
8.21
4.92
3.29
2.87
5.34
2004
8.59
5.58
3.01
3.01
5.58
2005
8.30
5.81
2.49
3.32
4.98
2006
8.25
6.19
2.06
5.36
2.89
2007
8.19
6.14
2.05
5.98
2.21
2008
8.23
6.58
1.65
6.09
2.14
2009
8.90
7.39
1.51
7.03
1.87
2010
9.13
7.76
1.37
7.67
1.46
2011
9.11
7.74
1.37
8.01
1.09
2012
9.88
8.60
1.28
8.90
0.98
2013
10.49
9.44
1.05
9.86
0.63
2014
11.07
9.97
1.10
10.41
0.66
2015
11.54
10.39
1.15
10.85
0.69
2016
11.72
10.55
1.17
11.02
0.70
Adapted from FEBRAPDP, AMIS Global, CONAB and personal communications
NT = No-till©PG Economics Ltd 2018141

GM crop impact: 1996-2016a) 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% (Plataforma Plantio Direto (2006)). This compares with a 55% reduction in the
US (see section 4.2.4.1). In the analysis below, the more conservative fuel consumption rates usedin the US (21.89 litres/ha for NT and 49.01 litres/ha for CT - a reduction of 55% for NT relative toCT) are applied to the GM HT soybean area planted in the three southern Brazilian states.
Total fuel consumption in soybean cultivation has increased by 14% from 253 to 288.4 million
litres/year between 1997 and 2016. This increase in aggregate fuel use largely reflects the 89%
increase in the area planted to soybeans in these three states during this period. However, theaverage quantity of fuel used per ha fell 39.8% from 40.9 to 24.6 litres/ha largely as a result of the
adoption of 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 2016 in the three southern states, an additional 1,970 million litres of fuelwould have been used. At this level of fuel usage, an additional 5,259 million kg of carbon
dioxide would otherwise have been released into the atmosphere (Table 78).
Table 78: Brazil (3 southernmost states) soybeans: permanent reduction in tractor fuelconsumption and reduction in carbon dioxide emissions (1997-2016)
Annual reduction
based on 1997
average of 40.9
(litres/ha)
0.00
1.36
2.71
4.07
5.42
6.78
8.14
9.49
10.85
12.20
12.20
13.56
14.37
14.92
14.92
15.46
16.27
16.27
16.27
16.27

Crop area(million ha)

0.00
8.30
16.40
24.34
37.09
50.76
66.83
81.52
89.98
100.6599.89
111.56127.94136.24135.83152.79170.74180.20187.77190.77
1,969.60
Total
Note: based on 21.89 litres/ha for NT and RT and 49.01 litres/ha for CT
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

©PG Economics Ltd 2018

6.19
6.12
6.05
5.98
6.84
7.49
8.21
8.59
8.30
8.25
8.19
8.23
8.90
9.13
9.11
9.88
10.49
11.07
11.54
11.72

Total fuel saving(million litres)

142

Carbon dioxide(million kg)

0.00
22.15
43.80
65.00
99.03
135.53178.43217.65240.26268.73266.71297.86341.60363.75362.66407.95455.87481.13501.35509.355,258.81

GM crop impact: 1996-2016b) 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 14,525
million kg of carbon (equal to a saving of 53,307 million kg of carbon dioxide) has been retainedin the soil that would otherwise have been released into the atmosphere (Table 79).
Table 79: Brazil (3 southern most states) soybeans: potential additional soil carbon
sequestration (1997 to 2016)
Annual increase in

Crop area

Total addition carbon

Total addition

carbon sequestered(million ha)sequestered

Carbon dioxide(million kg)

sequesteredbased on 1997
average(million kg)(kg carbon/ha)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
90.0
100.0
106.0
110.0
110.0
114.0
120.0
120.0
120.0
120.0

6.2
6.1
6.0
6.0
6.8
7.5
8.2
8.6
8.3
8.2
8.2
8.2
8.9
9.1
9.1
9.9
10.5
11.1
11.5
11.7

Total
Assumption: NT/RT = +175 kg carbon/ha/yr, CT = -25 kg carbon/ha/yr©PG Economics Ltd 2018

143

0.00
61.19
120.98179.52273.52374.35492.84601.16663.60742.23736.65822.70943.51
1,004.69
1,001.67
1,126.76
1,259.12
1,328.89
1,384.75
1,406.83
14,524.96

0.00
224.57444.00658.84
1,003.82
1,373.86
1,808.72
2,206.26
2,435.41
2,723.98
2,703.51
3,019.31
3,462.67
3,687.19
3,676.13
4,135.23
4,620.99
4,877.03
5,082.04
5,163.07
53,306.63

GM crop impact: 1996-2016

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 5.86 million ha
between 1999 and 2016 (Paraguay 1.17 to 3.3 million ha, Uruguay 8,900 ha to 1.26 million ha andBolivia 0.62 to 1.3 million ha) and the area of GM soybeans from 58,000 ha to 5.6 million ha.
a) Fuel consumption
Using the findings and assumptions applied to Argentina 112 (see above), the savings in fuelconsumption for soybean production between 1999 and 2016 (associated with changes in
no/reduced tillage systems, the adoption of GM HT technology and comparing the proportion of
NT soybeans in 2016 with the 1999 level) has been 640 million litres. At this level of fuel saving,
the reduction in the level of carbon dioxide released into the atmosphere has been 1,709 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 4,719 million kg of carbon. In terms of carbon dioxide
emission this equates to a saving of 17,319 million kg of carbon dioxide that may otherwise havebeen released into the atmosphere.
4.2.4.5 Canada
During the period 1996 to 2008 period, tillage practices across the Canadian Prairies changed
considerable with NT increasing from 15% to 51% of the crop prairie area. Since 2009, the NT
area accounted for between 52% and 55% of the tillage area, with the RT and CT shares being
17%-22% and 26%-28% respectively.
The introduction of GM HT soybeans in 1997 facilitated this transition as well as the doubling of
the soybean crop area from 1.06 million ha in 1997 to 2.2 million ha in 2016. Within this, the NTsoybean area increased five-fold from 0.21 million ha in 1997 to 1.2 million ha in 2016 whilst the
RT area increased from 0.33 million ha to 0.37 million ha and the CT area increased from 0.52
million ha to 0.62 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 2016 has been 176.2
million litres. At this level of fuel saving, the reduction in the level of carbon dioxide released
into the atmosphere has been 470.5 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, has
112

We are not aware of any country-specific studies into NT/RT systems in these three countries. However, analysts consulted in eachcountry 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 thisrepresents the only available data from a neighbouring country. We acknowledge this represents a weakness to the analysis and thefindings should be treated with caution.

©PG Economics Ltd 2018144

GM crop impact: 1996-2016

been 669.5 million kg of carbon. In terms of carbon dioxide emission this equates to a saving of
2,457.1 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 20 years between 30.64 millionha (2001) and 37.88 million ha (2007); in 2016 it was 35.11 million ha. Over the 1997-2016
period 113, the maize area using conventional tillage (CT) fell by 20% (11.05 to 8.43 m ha), reduced
tillage (RT) fell by 19% (15.57 to 12.99 m ha) and the no-till (NT) maize area increased by 136%
(5.57 to 13.69 m ha: Table 80).
The most rapid rate of adoption of GM HT maize technology has been by growers using NT
systems (GM HT cultivars accounted for an estimated 99% of total NT maize in 2016). This
compares with conventional tillage systems for maize where GM HT cultivars account for about
57.3% of total maize plantings (Table 80).
Table 80: US maize: tillage practices and the adoption of GM HT cultivars 1997-2016 (million
ha)
Total

No-tillarea

ReducedConven

Total

Total

No till

ReduceCon-tilltionalGM HT

convenGM HTd tillvention

till

area

tional

area

GM HT

al

area

tillage

area

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015

32.19
32.44
31.32
32.19
30.64
31.93
31.81
32.47
33.10
31.70
37.88
31.82
32.21
32.78
34.35
35.36
35.48
33.64
32.68

5.57
5.95
6.17
6.77
6.57
6.98
7.11
7.42
8.11
8.28
10.22
8.35
9.58
10.49
11.68
12.73
13.13
12.78
12.75

15.57
13.32
12.13
11.73
11.14
11.59
11.50
11.69
11.74
11.08
13.87
11.84
11.92
12.13
12.71
13.08
13.13
12.45
12.09

11.05
13.17
13.02
13.69
12.93
13.36
13.20
13.36
13.25
12.34
13.79
11.63
10.71
10.16
9.96
9.55
9.22
8.41
7.84

113

0.12
1.66
1.47
2.25
2.45
3.83
4.77
6.50
8.61
11.41
19.70
20.04
21.90
22.95
24.73
25.81
30.16
29.94
29.07

(non

GM HT

GM)

area

32.07
30.78
29.85
29.94
28.19
28.10
27.04
25.97
24.49
20.29
18.18
11.78
10.31
9.83
9.62
9.55
5.32
3.70
3.59

0.12
1.19
1.23
1.69
1.97
3.14
3.55
4.64
6.08
7.85
9.71
8.26
9.49
10.38
11.56
12.60
13.00
12.66
12.62

0.00
0.47
0.24
0.56
0.48
0.68
1.19
1.79
2.40
2.94
8.61
10.03
10.90
10.72
11.21
11.22
12.37
11.86
11.51

0.00
0.00
0.00
0.00
0.00
0.01
0.03
0.07
0.13
0.62
1.38
1.75
1.51
1.85
1.96
1.99
4.79
5.42
4.94

GM HT maize was first planted commercially in the US in 1997. However, 1998 was the first year of widespread adoption of thetechnology©PG Economics Ltd 2018145

GM crop impact: 1996-2016

2016
35.11
13.69
12.99
8.43
31.24
3.86
13.55
12.86
4.83
Source: Adapted from Conservation Tillage and Plant Biotechnology (CTIC) 1998, 2000, 2002, 2006, 2007
and 2008, GfK Kynetec, USDA-ERS ARMS (2016), Phase II Soybean Survey, No-Till Farmer (2016) 8th annual
benchmark study of tillage
Note: Reduced tillage includes mulch till and ridge tilla) 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 2016 has decreased by 1.3% - 19.8 million
litres: Table 81). Over the same period, the area planted to maize increased by 9%, highlighting afall in average fuel usage of 9.4% (from 46.6 litres/ha to 42.2 litres/ha). A comparison of GM HT
versus conventional production systems shows that in 2016, the average tillage fuel consumption
on the GM HT planted area was 40.8 litres/ha compared to 53.4 litres/ha for the conventional
crop.
Table 81: US maize: consumption of tractor fuel used for tillage (1997-2016)
Total fuelAverage

Conventional average

GM HT average

consumption(litre/ha)(litre/ha)(litres/ha)

46.6
46.9
46.8
46.6
46.5
46.4
46.3
46.2
45.9
45.5
45.2
45.3
44.5
43.9
43.4
42.9
42.7
42.4
42.2
42.2

46.7
47.6
47.5
47.6
47.7
48.2
48.4
49.0
49.6
51.0
51.6
53.2
53.5
53.2
53.0
52.7
52.8
52.5
52.4
53.4

30.1
34.9
32.8
34.3
33.4
33.1
34.4
35.0
35.2
35.8
39.2
40.7
40.2
39.9
39.7
39.3
40.9
41.2
40.9
40.8

(million litres)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

1,501.2
1,522.6
1,465.0
1,501.1
1,425.5
1,482.5
1,473.5
1,500.4
1,517.7
1,442.3
1,710.8
1,441.5
1,431.8
1,439.4
1,491.6
1,518.0
1,514.4
1,427.9
1,379.0
1,481.4

The cumulative permanent reduction in tillage fuel use in US maize is summarised in Table 82.
This amounted to a reduction in tillage fuel usage of 1,164 million litres which equates to a
reduction in carbon dioxide emission of 3,109 million kg.

©PG Economics Ltd 2018146

GM crop impact: 1996-2016

Table 82: US maize: permanent reduction in tractor fuel consumption and reduction in carbon
dioxide emissions (1997-2016)
Annual reduction

Crop area

Total fuel saving

Carbon dioxidebased on 1997 average(million ha)(million litres)(million kg)

32.19
32.44
31.32
32.19
30.64
31.93
31.81
32.47
33.10
31.70
37.88
31.82
32.21
32.78
34.35
35.36
35.48
33.64
32.68
35.11

0.00
-9.58
-4.43
0.39
3.30
6.50
10.00
13.82
25.85
36.02
55.82
42.72
70.34
89.53
110.60131.10140.20141.16145.09155.870.00-25.57-11.84
1.03
8.81
17.34
26.71
36.90
69.01
96.18
149.05114.06187.80239.05295.29350.03374.33376.91387.39416.17

1,164.29

3,108.65(litres/ha)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

0.00
-0.30
-0.14
0.01
0.11
0.20
0.31
0.43
0.78
1.14
1.47
1.34
2.18
2.73
3.22
3.71
3.95
4.20
4.44
4.44

Total
Assumption: baseline fuel usage is the 1997 level of 46.6 litres/hab) Soil carbon sequestration
Based on the crop area planted by tillage system and type of seed planted (GM HT andconventional) and using estimates of the soil carbon sequestered by tillage system for corn andsoybeans in continuous rotation, the corn 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) 114, our estimates of total soil carbon sequestered are (Table
83):
•

•

an increase of 1,842 million kg carbon/year (from 2,577 million kg in 1997 to 4,419 million
kg carbon/year in 2016) due to a combination of an increase in the crop area and the NT
corn area;
the average amount of carbon sequestered per ha increased by 57.2% from 80.1 in 1997 to
125.9 kg carbon/ha/year in 2016.

114

The actual rate of soil carbon sequestered by tillage system is, however, dependent upon soil type, soil organic content, quantity andtype of crop residue©PG Economics Ltd 2018147

GM crop impact: 1996-2016

Table 83: US maize: potential soil carbon sequestration (1997 to 2016)
Total carbon sequestered (million kg)

Average(kg carbon/ha/yr)

1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

2,577.15
2,506.56
2,471.17
2,593.19
2,497.79
2,634.48
2,661.08
2,753.20
2,927.43
2,919.69
3,617.98
2,996.31
3,310.30
3,552.94
3,895.02
4,185.92
4,288.67
4,151.08
4,113.59
4,419.20

80.1
77.3
78.9
80.5
81.5
82.5
83.7
84.8
88.5
92.1
95.5
94.2
102.8
108.4
113.4
118.4
120.9
123.4
125.9
125.9

Cumulatively, since 1997 the increase in soil carbon due to the increase in RT and NT in US maize
production systems has been 12,142 million kg of carbon which, in terms of carbon dioxide
emissions, equates to a saving of 44,560 million kg of carbon dioxide that would otherwise havebeen released into the atmosphere (Table 84). This estimate does not take into consideration thepotential loss in carbon sequestration that might arise from a return to conventional tillage.
Table 84: US maize: potential additional soil carbon sequestration (1997 to 2016)
Annual increase in carbon

Crop area

Additional

Additional carbon

sequestered based on 1997 average(million ha)carbondioxide sequesteredsequestered(million kg)(kg carbon/ha)(million kg)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007

©PG Economics Ltd 2018

0.0
-2.8
-1.2
0.5
1.5
2.4
3.6
4.7
8.4
12.0
15.4

32.2
32.4
31.3
32.2
30.6
31.9
31.8
32.5
33.1
31.7
37.9

148

0.00
-90.93-36.32
15.56
44.90
78.15
114.19153.64277.58381.73585.140.00-333.70-133.2957.11
164.78286.81419.09563.84
1,018.73
1,400.94
2,147.48

GM crop impact: 1996-2016

2008
2009
2010
2011
2012
2013
2014
2015
2016

14.1
22.7
28.3
33.3
38.3
40.8
43.3
45.8
45.8

31.8
32.2
32.8
34.4
35.4
35.5
33.6
32.7
35.1

448.24731.42928.21
1,144.48
1,354.80
1,448.05
1,457.30
1,497.16
1,608.38

Total
12,141.68
Assumption: carbon sequestration remains at the 1997 level of 80.1 kg carbon/ha/year

1,645.05
2,684.32
3,406.54
4,200.22
4,972.11
5,314.33
5,348.30
5,494.56
5,902.76
44,559.98

4.2.5.2 Canada
Against the background of increasing adoption of NT and RT in the Canadian Prairies (seesection 4.2.4.5) and a fluctuating maize area (1.325 million ha in 2016), the introduction andincreasing adoption of GM HT maize technology (from 1999) has facilitated the doubling of themaize NT area from 0.34 million ha in 1999 to 0.729 million ha in 2016.
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 2016 (associated with changes in RT/NT systems,
the adoption of GM HT technology and comparing the proportion of NT corn in 2016 with the1999 level) has been 90 million litres. This level of fuel saving is equal to a reduction in the levelof carbon dioxide released into the atmosphere of 241 million kg.
b) Soil carbon sequestration
Applying the US carbon sequestrations assumptions for maize to the Canadian crop, thecumulative increase in soil carbon since 1999 has been 267 million kg of carbon. In terms ofcarbon dioxide emission savings, this equates to 980 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 recently or is currently increasing due to the availability of GM HT maize because of alack of relevant data and analysis. However, the following should be noted:••

in Argentina, GM HT maize was first available for use in 2004, yet has only become
widely adopted in recent years (64% of 2015 crop used the technology). Therefore, it isunlikely that the availability of GM HT technology has played a significant role in thedevelopment of NT/RT farming in the Argentine 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 (0.68 million ha in the US in 2016 compared to 8.12 million ha in Canada).

©PG Economics Ltd 2018149

GM crop impact: 1996-2016

Smyth et al (2011) surveyed 600 canola farmers in the three prairie 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 ofherbicide active ingredient being applied), there were fewer tillage passes, improving moisture
conservation, decreasing soil erosion and a substantial contribution to carbon sequestration in
annual cropland. This research estimated that, by 2009, approximately 1 million tonnes of carbon(3.67 million tonnes of carbon dioxide) had either been sequestered or no longer released underland management systems facilitated by HT canola production, as compared to 1995.
Awada L et al (2014) identified that conservation tillage, notably NT, became profitable for, andpopular wit, the majority of Canadian arable farmers during and after the late 1990s 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.
a) Fuel consumption
Our estimate for the cumulative, permanent reduction in tillage fuel use in Canadian canola forthe period 1996-2016 is 755.4 million litres, which equates to a reduction in carbon dioxide
emissions of 2016.8 million kg (Table 85).
Table 85: Canadian canola: permanent reduction in tractor fuel consumption and reduction incarbon dioxide emissions (1996-2016)

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

Annual reduction based on
1996 average 30.6 (l/ha)
0.0
0.9
0.9
0.9
0.9
1.8
2.7
3.5
4.4
5.3
6.2
6.5
7.1
8.0
8.8
8.9
8.9
8.9
8.9
8.9
8.9

Crop area(million ha)
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

Total
Note fuel usage NT/RT = 17.3 litres/ha CT = 35 litres/ha©PG Economics Ltd 2018150

Total fuel saving(million litres)
0.0
4.3
4.8
4.9
4.3
6.7
8.7
16.6
21.9
29.2
32.5
38.7
46.0
50.8
57.7
66.1
76.0
69.1
73.8
71.5
71.9
755.4

Carbon dioxide(million kg)
0.00
11.51
12.83
13.15
11.48
17.89
23.12
44.32
58.35
77.85
86.64
103.36122.77135.59153.93176.54202.86
184.61
197.16
191.00191.852,016.81

GM crop impact: 1996-2016b) 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). Table 86
summarises this analysis and shows a cumulative increase in soil carbon storage, associated with
the increase in RT and NT in Canadian canola production between 1996 and 2016, of 2,774 million
kg of carbon, which in terms of carbon dioxide emissions, equates to a saving of 10,180 million kg
of carbon dioxide that would otherwise have been released into the atmosphere. Readers shouldnote these estimates are based on a soil sequestration rate of 55 kg carbon/ha/year (based on
McConkey et al (2007)) which is significantly lower than the rate used in the US for corn (250 kg
carbon/ha/year) due to a combination of lower temperatures and different soil types in the
Canadian canola growing regions compared to the US corn-soybean production belt.
Table 86: Canadian canola: potential additional soil carbon sequestration (1996 to 2016)
Annual increase in carbon

Crop area

Total carbon

Carbon dioxidesequestered based on 1996

(million ha)sequestered(million kg)(million kg)

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

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

Total
Notes: NT/RT = +55 kg of carbon/ha/yr CT = -10 kg of carbon/ha/yr

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
271.18262.70263.872,773.92

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
931.84995.23964.10968.3910,180.28

4.2.7 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, it still only represented©PG Economics Ltd 2018151

GM crop impact: 1996-2016

23.7% of the total cotton crop in 2009 115. Therefore, no analysis has been undertaken relating topossible fuel usage and soil carbon sequestration savings associated with the 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 (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 2016, the global cotton area planted with GM IR
cultivars increased from 0.77 million ha to 21.1 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 116) of GM IR cotton over the period 1996-2016, suggests that
there has been a reduction of 250 million ha of cotton ‘spray’ area. The resulting cumulativesaving in tractor fuel consumption has been 210 million litres. This represents a permanent
reduction in carbon dioxide emissions of 561 million kg (Table 87).
Table 87: Permanent reduction in global tractor fuel consumption and carbon dioxide
emissions resulting from the cultivation of GM IR cotton (1996-2016)

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
115
116

Total cotton area
in GM IR
growing countries
excluding
Burkina Faso,
India, Pakistan,
Myanmar, Sudan
and China(million ha)
6.64
6.35
7.20
7.42
7.29
7.25
6.36
5.34
6.03
6.34
7.90
6.07
4.51
5.33
7.13
6.61
5.72

GM IR area
excluding
Burkina Faso,
India, Pakistan,
Myanmar,
Sudan andChina
(million ha)

Total spray runs
saved
(million ha)

Fuel saving(million litres)

CO2 emissions
saved(million kg)

0.86
0.92
1.05
2.11
2.43
2.55
2.17
2.17
2.79
3.21
3.94
3.25
2.54
2.96
4.59
4.43
4.07

3.45
3.67
4.20
8.44
9.72
10.18
8.69
8.70
11.17
12.84
15.75
12.99
10.16
11.83
18.37
17.70
16.30

2.90
3.09
3.53
7.09
8.17
8.55
7.30
7.30
9.38
10.78
13.23
10.91
8.53
9.94
15.43
14.87
13.69

7.73
8.24
9.43
18.92
21.81
22.84
19.49
19.50
25.05
28.79
35.33
29.14
22.78
26.54
41.21
39.71
36.55

2009 is the latest year for which no tillage data in cotton is available
Excluded because all spraying is assumed to be undertaken by hand

©PG Economics Ltd 2018152

GM crop impact: 1996-2016

2013
2014
2015
2016

5.29
5.57
5.00
5.74

3.75
4.20
3.95
4.63

15.01
16.80
15.78
18.53

12.61
14.11
13.26
15.57

Total
250.28210.24
Notes: assumptions: 4 tractor passes per ha, 0.84 litres/ha of fuel per insecticide application

33.66
37.67
35.40
41.57
561.344.2.9 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 253
million ha of maize being sprayed in the eight years 2008-2016, with a cumulative saving intractor fuel of 213 million litres. This is equivalent to a permanent reduction in carbon dioxide
emissions of 567 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:••

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 (2.4 million ha in 2015) 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 2016 period of 87.3 million ‘spray’ ha. The resultant, cumulative saving in tractor fuelequates to 73.3 million litres, equivalent to a permanent reduction in carbon dioxide emissions of
196 million kg.

©PG Economics Ltd 2018153

GM crop impact: 1996-2016

4.2.10 Insect resistant soybeans
IR soybean technology was first used commercially in South America in 2013, and in 2016 wasplanted on 23.47 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 four-year period has, therefore been equal to 140.7
million litres, equivalent to a permanent reduction in carbon dioxide emissions of 376 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 2015 level ofadditional global corn production (40.3 million tonnes) due to GM cultivars, thisadditional production assimilated about 136 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, corn, cotton and canola). Where
this land that would otherwise have been brought into agriculture remains in alternative
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 117) have,
however, concluded that intensification of agriculture leads to a net reduction in GHG

117 Albeit examining the impact on GHG emissions from general intensification of agriculture between 1961 and 2005

©PG Economics Ltd 2018154

GM crop impact: 1996-2016•

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.
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 impact
A summary of the carbon sequestration impact is presented in Table 88. This shows thefollowing key points:••

The permanent savings in carbon dioxide emissions (arising from reduced fuel use of
10,925 million litres of fuel) since 1996 have been about 29,169 million kg;
The additional amount of soil carbon sequestered since 1996 has been equivalent to251,390 million kg of carbon dioxide that has not been released into the global
atmosphere 118. The reader should note that these soil carbon savings are based onsavings arising from the rapid adoption of NT/RT farming systems in North and SouthAmerica (Argentina and Southern Brazil), 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 theavailability of relatively cheap generic glyphosate (the real price of glyphosate fell
threefold between 1995 and 2000 once patent protection for the product expired) havealso been important. Cumulatively, the amount of carbon sequestered may be higher
than these estimates due to year-on-year benefits to soil quality; however, it is equally
likely that the total cumulative soil sequestration gains have been lower because only aproportion of the crop area will have remained in NT/RT. For example, in 2016 theNT/RT data from the US shows that 83% of the soybean crop (27.8 million ha) is typicallyusing NT/RT, whilst 76% of the maize crop (26.7 million ha) derives from NT/RT. Given
that the soybean: corn rotation is a common system in the US (though not the only
system of production for either crop), this suggests that an important area in RT/NT one
year (whilst planted to maize) remain in NT the next year for a following soybean crop.

118
These estimates are based on fairly conservative assumptions and therefore the true values could be higher. Also, some of theadditional soil carbon sequestration gains from RT/NT systems may be lost if subsequent ploughing of the land occurs. Estimating thepossible losses that may arise from subsequent ploughing would be complex and difficult to undertake. This factor should be taken into
account when using the estimates presented in this section of the report©PG Economics Ltd 2018155

GM crop impact: 1996-2016

The estimate of 251,390 million kg of carbon dioxide not released into the atmosphereshould be treated with caution. It is a theoretical potential, with the actual level of carbon
dioxide savings occurring across a probable wide variation.
Table 88: Summary of carbon sequestration impact 1996-2016
Crop/trait/country

Permanent fuelPotential carbon dioxide

Potential carbon dioxidesaving (million

saving from reduced fuelsaving from soil carbon

litres)use (million kg)

sequestration (million kg)

HT soybeans
Argentina
3,483
9,300
94,272
Brazil1,970
5,259
53,307
Bolivia, Paraguay,
640
1,709
17,319Uruguay
US
2,009
5,365
28,315
Canada
176
471
2,457
HT maize
US
1,164
3,109
44,560
Canada90241980
HT canola
Canada755
2,017
10,180IR maize
Brazil
213
567
0USA, Canada, South73
196
0Africa, Spain
IR cotton
Global210561
0
IR soybeans
Argentina, Brazil,
141
376
0
Paraguay, Uruguay
Total
10,92429,171
251,390
Note IR soybeans = savings from reduced insecticide use. All other savings associated with the HT stack in‘Intacta’ soybeans included under HT soybeans

Examining further the context of the carbon sequestration benefits, Table 89 measures the carbon
dioxide equivalent savings associated with planting of biotech crops for the latest year (2016), in
terms of the number of car use equivalents. This shows that in 2016, the permanent carbon
dioxide savings from reduced fuel use (2,946 million kg carbon dioxide) was the equivalent ofremoving 1.82 million cars from the road for a year and the additional soil carbon sequestration
gains (24,172 million kg carbon dioxide) were equivalent to removing 14.93 million cars from theroads. In total, biotech crop-related carbon dioxide emission savings in 2016 were equal to theremoval from the roads of 16.75 million cars, equal to 54.3% of all registered cars in the UK.

©PG Economics Ltd 2018156

GM crop impact: 1996-2016

Table 89: Context of carbon sequestration impact 2016: car equivalents
Crop/trait/country

Permanent

Permanent fuelPotential

Soil carbon

carbon dioxidesavings: asadditional soil

sequestration

savings arising

average family

carbonsavings: as average

from reduced

car equivalents

sequestration

family carfuel use

removed fromsavings (million

equivalents removed(million kg of

the road for a

kg of carbon

from the road for a

carbon dioxide)

year (‘000s)

dioxide)year (‘000s)

HT soybeans
Argentina
709.0
437.8
7,186.9
4,438.2
Brazil509.3
314.5
5,163.1
3,188.4
Bolivia, Paraguay,
175.2
108.2
1,776.4
1,097.0
Uruguay
US
533.4
329.4
2,870.7
1,772.8
Canada
47.3
29.2
249.2
153.9
HT maize
US
416.2
257.0
5,902.8
3,645.2
Canada
19.2
11.9
54.2
33.5
HT canola
Canada
191.8
118.5
968.4
598.0
IR maize
Brazil
100.1
61.8
0.0
0.0
USA, Canada, South
12.2
7.5
0.0
0.0
Africa, Spain
IR cotton
Global
41.6
25.7
0.0
0.0
IR soybeansSouth America
190.1
117.4
0.0
0.0
Total
2,945.4
1,818.9
24,171.7
14,927.0
Notes:
1. Assumption: In all previous editions of this report the authors have assumed that an averagefamily car in the UK produces 150 grams of carbon dioxide per km, is driven over a distance of
15,000 km/year and therefore produces 2,250 kg of carbon dioxide/year. With the introduction oflower carbon dioxide emission vehicles and a trend to drive each car fewer miles per year theauthors have used the following 2017 data; 129 grams of carbon dioxide per km(http://www.carpages.co.uk/co2/); and 12,553 km/year(https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/633077/nationaltravel-survey-2016.pdf ) equating to 1,619 kg of carbon dioxide/year.
2. IR soybeans = savings from reduced insecticide use. All other savings associated with the HT stackin ‘Intacta’ soybeans included under HT soybeans

Due to the limitations referred to above, no estimate of cumulative (1996-2016) carbon dioxidesavings as car-equivalents has been provided.

©PG Economics Ltd 2018157

GM crop impact: 1996-2016

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 (2016)
Count
ry

Av
Total
Total
yield
area
producacross
(‘000
tion
all
ha)
(‘000
forms
tonnes)ofproduction(t/ha)
US
0.972
3,848
3,740
China
1.708
2,900
4,953
Note: Figures subject to rounding©PG Economics Ltd 2018

GM
IR
area
(‘000
ha)

Conventionalarea(‘000 ha)Assumed yield
effect of
GM IR
technology

Adjustedbaseyield forconventio
nalcotton(t/ha)

GM IR
production(‘000
tonnes)Conventio
nalproduction(‘000
tonnes)

3,232
2,755

616
145

+10%
+10%

0.897
1.56

3,189
4,727

552
226

158

GM crop impact: 1996-2016

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
corn:
resistantto cornboringpests
US &Canada©PG Economics Ltd 2018159

GM crop impact: 1996-2016

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 2018+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

160

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
derive 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)

Sources as for cost oftechnology

GM crop impact: 1996-2016

Other EU

France+10%,
Germany+4%,Portugal+12.5%,
Czech
Republic+10%,
Slovakia+12.3%,
Poland+12.5%,
Romania+7.1% 2007,+9.6% 2008
& +4.8%2009
onwardImpacts
based onaverage ofavailable
impactdata ineach
country

UruguayAs
Argentina

As
Argentina

Paraguay

As
Argentina

As
Argentina

Brazil+4.66%
2008, +7.3%
2009 &
2010,+20.1%
2011,+14.6%
2012,

Farmersurveys©PG Economics Ltd 2018

Based on Brookes (2008)
which drew on a numberof sources. For France 4
sources with average
yield impacts of +5% to+17%, for Germany thesole source had averageannual impacts of +3.5%
and +9.5% over a twoyear period, for Czech
Republic three studies
identified average
impacts in 2005 of an
average of 10% and arange of +5% to +20%; forPortugal, commercial
trial and plot monitoring
reported +12% in 2005
and between +8% and+17% in 2006; in Slovakia
based on trials for 20032007 and 2006/07
plantings with yieldgains averaging between+10% and +14.7%; in
Poland based on variety
trial tests 2005 andcommercial trials 2006
which had a range of+2% to +26%; Romania
based on reported impact
by industry sources
No 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)

161

Data derived fromthe same source(s)referred to foryield

Data derived from thesame source(s) referred
to for yield

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

GM crop impact: 1996-2016

Honduras+11.1%
2013-2015+13% 20032006+24% 2007
onwardTrialsresults
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%

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)
Brookes (2017)

Nil – no insecticide
assumed to be used onconventional crops

Mendez etal (2011)
Brookes(2017)
Rationale

Mendez et al (2011) farmsurvey from 2009
Brookes (2017)
Yield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

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

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

Data derived fromthe same sourcesreferred to for

As identified in yieldstudy references and in
subsequent years

Colombia+22%

Vietnam

+7.2%

GM IR
corn
(resistant
to cornrootworm)
US &CanadaYield
impactassumptio
n used+5% allyears

Based onthe impact
used bythereferences
cited

IR cotton

Yield
impactassumptio
n used
+9% 19962002

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

Based onthe(conservati

Sankala & Blumenthal(2003 & (2006) drew on
earlier work fromUS

©PG Economics Ltd 2018162

Mendez et al (2011)
Brookes (2017)

GM crop impact: 1996-2016+11% 2003& 2004+10% 2005
onwardsve) impact
used bythereferences
cited

China

+8% 19972001+10% 2002
onwards

Australia

None

Average ofstudiesused to2001.
Increase to
10% onbasis ofindustry
assessment
s of impact
andreportingof
unpublishe
d work by
SchuchanStudieshave©PG Economics Ltd 2018

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) andJohnson & 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)

163

yield and updated
from 2008 basedon industry
sources (for theestimated share of
the insect
resistance trait in
the total seedpremia forstacked traitedseedadjusted to reflect broad
cost of ‘foregone’
insecticide use

Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield

Data derived fromthe same sources

Data derived from thesame sources referred toGM crop impact: 1996-2016

usually
identified
nosignificant
averageyield gain

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 anaverage 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

Argentina+30% all
years

More
conservati
ve of thetwo pieces
of research
used

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 andRecordedyield
impactdata usedasavailable
for almost
all years©PG Economics Ltd 2018164referred 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
years based on
industry sources

for yield covering earlier
years of adoption, then
CSIRO for later years

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 from thesame sources referred tofor yield and cost oftechnology.

GM crop impact: 1996-2016

India

BrazilColombia

2011, +7.2%
2012,+8.95%
2013,+15.8%
2014 15%2015,+10.54%
2016+45% 2002+63% 2003+54% 2004+64% 2005+50% 2006& 2007+40% 2008,+35% 2009& 2010,+30% 2011,+24% 201216+6.23%
2006-3.6% 2007
-2.7% 2008,-3.8% 2009,2010 nil2011+3.04%,
2012 -1.8%,
2013 +2.4%,
2014-2016+2.38%+30% allyears
except 2009
+15%, 2010
onward+10%©PG Economics Ltd 2018

Recordedyield
impactused for
years
where
available

Recordedyield
impacts foreach year –2013 notavailable
so 2012value
assumedFarmsurvey2007
comparing
performan
ce of GMIR versus
convention
al growers.
2009
onwards
based onYield 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 &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))

Data derived fromthe same sourcesreferred to foryield. 2007
onwards cost oftechnology basedon industry
sources

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

Data derived fromthe same sourcesreferred to foryield

Data derived from thesame sources referred tofor yield

Based on Zambrano P etal (2009) and trade
estimates (2009, 2011,2013)

Assumed as
Mexico – nobreakdown ofseed premiumprovided inZambrano (2009).
From 2008 basedon weighted costof seed sold assingle and stacked
traitsData derived from
Zambrano P (2009). Cost
savings excluding seedpremium derived from
Zambrano as total costsavings less assumed
seed premium. 2010
onwards seed premium& cost savings fromindustry sources165

GM crop impact: 1996-2016

Burkina
Faso

Pakistan

MyanmarGM HT
soybeans

US: 1stgeneration+20 2008,+18.9%
2009
onwards+12.6%
2009, 2010
onwards
+22%
+30%

Yield
impactassumptio
n usedNil

tradeestimates
Trials 2008,
farm
survey2009
Farmsurveys

Vitale J et al (2008) &Vitale J et al (2010)

Based on Vitale J
et al (2008 & 2010)

Based on Vitale J et al(2008 & 2010)

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

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

Extension
serviceestimates
Rationale

USDA (2011)

Not
relevant

Not relevant

Yield references

Canada: 1stgeneration

Nil

Not
relevant

Not relevant

US &Canada:2nd
generation+5% 2009
and 2010,+10.4%
2011,+11.2%
2012, +11%
2013, +9%
2014-16,
8.9%
Nil but
secondcropbenefits

Farm levelmonitoring
and farmer
feedback

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

Not relevant

Argentina

BrazilNil©PG Economics Ltd 2018

Not relevant

166

No data available sobased on Pakistan
Cost savings (excluding
impact of seedpremium) assumptions

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

Qaim & Traxler (2005),
Trigo & CAP (2006) &updated from 2008 toreflect herbicide pricechangesGeorge Morris Center(2004), Ontario Ministryof Agriculture & updated
for 2008 to reflectherbicide price changes
as 1st generation

Sources as in cost oftechnology

GM crop impact: 1996-2016

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)
Paraguay

Nil but
secondcropbenefits

Not
relevant
except 2ndcrop

Not relevant

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,

Recordedyield
impactfromstudies

From Monsanto annual
monitoring reports
submitted to Ministry ofAgriculture

No publishedstudies identified
based onMonsanto annual
monitoring
reports©PG Economics Ltd 2018167

As Argentina: nocountry-specificanalysisidentified.
Impacts
confirmed fromindustry sources(annual personalcommunications
2006-2012). Seed
cost based on
royalty rate since2007
No studies
identified. Seedpremia based on
industry sources(annually
updated)As Argentina – herbicide
cost differences adjusted
post 2008 based on
industry sources and
AMIS Global, Kleffmannherbicide usage data
2011, 2013, 2015, 2016

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: 1996-2016

Romania

Bolivia

GM HT &
IR
soybeansBrazilArgentina

Paraguay

Uruguay

GM HT
corn

US

-1.87%
2016+31%, 15%
2006

+15%

+9.6% 2013,+9.1% 2014,
9.4% 2015
and 2016+9.1% 2013,+7.8% 2014,
7.1% 2015
and 2016+12.8%
2013,+11.9%
2014, 9.1%
2015, 12.3%
2016+8.8% 2013,+7.8% 2014,
7% 2015
and 2016
Yield
impactassumptio
n usedNil©PG Economics Ltd 2018

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
marketmonitoring
surveyAs Brazil

Monsanto farm trials andcommercial crop
monitoring (survey)

As yield source
and Kleffmann

As yield source andKleffmann

Monsanto farm trials andcommercial crop
monitoring (survey)

As yield source
and Kleffmann

As yield source andKleffmann

As Brazil

Monsanto farm trials andcommercial crop
monitoring (survey)

As yield source

As yield source andKleffmann

As Brazil

Monsanto farm trials andcommercial crop
monitoring (survey)

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).
2008 and 2009
onwards based onweighted seed

Carpenter & Gianessi(2002)Sankala & Blumenthal(2003 & 2006)
Johnson S & Strom S(2008). 2009 onwards
updated to reflectchanges in common
herbicide treatments andprices168

GM crop impact: 1996-2016

sales (sold assingle and stacked
traits)No studies
identified – basedon annual
personal
communications
with industry
sources

CanadaNil

Notrelevant

Not relevant

Argentina:
sold assingle trait+3% cornbelt+22%
marginalareas

No studies identified –based on personalcommunications withindustry sources in 2007
and 2008 MonsantoArgentina & Grupo CEO(personal
communications 2007,2008 & 2011)

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

Argentina:
sold asstackedtrait+10.25%

Based ononly
available
analysis Corn Belt =70% ofplantings,
marginal
areas 30% industry
analysis(note nosignificant
plantings
until 2006)
Farmerlevel
feedback toseedsuppliers

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

As single trait

As single trait

South
AfricaNil

Notrelevant

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

Industry sources –annual checked

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

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

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

Brazil

+2.5% 2010

Farm
surveyGalvão (2010, 2012, 2013,2015))©PG Economics Ltd 2018169

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

Data derived from thesame sources referred toGM crop impact: 1996-2016

Colombia+3.6% 2011.
+6.84%
2012 and2013, +3%
2014-2016
Zero

Uruguay

ZeroParaguayreferred to foryield

for yield plus AMIS
Global herbicide use data

Mendez et al (2011)

Mendez etal (2011)
Not
relevant

Mendez et al (2011) farmsurvey from 2009
Not relevant

Mendez et al(2011)
No studies
available – basedon Argentina

Zero

Not
relevant

Not relevant

No studies
available – basedon Argentina

Vietnam+5%

Brookes (2017)

Brookes (2017)

GM HT
CottonYield references

Cost oftechnology
data/assumptions

Cost savings (excluding
impact of seedpremium) assumptions

US

Yield
impactassumptio
n usedNil

Brookes(2017)
Rationale

No studies available –based on Argentina plus
annual AMIS
Global/Kleffmannherbicide use data
No studies available –based on Argentina plus
annual AMIS
Global/Kleffmannherbicide use data
Brookes (2017)

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

Australia

Nil

Notrelevant

Not relevant

South
AfricaNil

Notrelevant

Not relevant

Argentina

Nil on area
using farm

Based ononly

No studies identified –based on personal

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©PG Economics Ltd 2018170

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

GM crop impact: 1996-2016

MexicoColombia

BrazilGM HT
canolaUS

saved seed,+9.3% onarea using
certifiedseedavailable
data –
company
monitoringofcommercia
l plots

communications with
Grupo CEO andMonsanto Argentina(2007, 2008, 2012)+3.6% allyears to2007
0% 2008,+5.11%
2009,+18.1%
2010, +5.1%
2011,+13.1%
2012,+14.2%
2013,+13.3%
2014,+19.6%
2015 and2016+4%

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

Based ononly
available
data –
company
monitoringofcommercia
l plotsFarm
survey+2.35%
2010+3.1% 2011,-1.8% 2012,+1.6% 2013,+1.6%
2014-16
Yield
impactassumptio
n used+6% all
years to2004. Post
2004 basedon Canada– see below©PG Economics Ltd 2018

– based on
personal
communications
with Grupo CEO
and MonsantoArgentina (2007,2008 & 2010 and
2012)
No publishedstudies identified- based on
personal
communications
with MonsantoMexico and theirannual reporting

personal
communications with
Grupo CEO andMonsanto Argentina(2007, 2008 & 2010, 2012,2013, 2016)

As cost data

No publishedstudies identified– based on
personal
communications
with MonsantoColombia (2010,2012, 2013)

No published studies
identified – based on
personal
communications with
Monsanto Colombia(2010, 2012, 2013)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 onSame as for cost data

Sankala &Blumenthal (2003& 2006))
Johnson S &Strom S (2008).
These are the only
studies identified

Sankala & Blumenthal(2003 & 2006))
Johnson S & Strom S(2008). These are the only
studies identified thatexamine GM HT canolain the US. Updated since171

No published studies
identified - based on
annual personalcommunications with
Monsanto Mexico andtheir annual reportingGM crop impact: 1996-2016

Canada+10.7% all
years to2004. Post
2004; forGM
glyphosate
tolerant
varieties
no yielddifference
2004, 2005,
2008, 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 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©PG Economics Ltd 2018

Canadian
impacts as
samealternative(conventio
nal HT)
technology
to Canadaavailable
After 2004
based ondifferences
betweenaverageannualvariety
trial resultsforClearfields(non GM
herbicidetolerant
varieties)
and GM
alternatives. GMalternativesdifferentiat
ed intoglyphosate
tolerant
andglufosinate
tolerant

Same as for cost data

172

that examine GM
HT canola in the
US. Updated
based on industry
and extension
service estimates2008 based on changes inherbicide prices

Based on Canola
Council (2001) to2003 thenadjusted to reflect
main current non
GM (HT)
alternative of‘Clearfields’ –data derived frompersonal
communications
with the Canola
Council (2008)
plus Gusta M et al(2009)

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

GM crop impact: 1996-2016

Australia

GM HT
sugar beet
US &CanadaGM VR
crops US
PapayaSquash

+21.08%2008,+20.9%
2009,+15.8%
2010, +7.6%
2011 and2012, +11%
2013-2015,+8% 2016

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)

Sources as foryield changes

Sources as for yieldchanges+12.58%2007+2.8% 2008
+3.3%
2009-2012,+3.1% 2013,+3.2% 2014,+3.55%
2015,+3.58%
2016

Farm
survey &extension
serviceanalysis

Kniss (2008)
Khan (2008)

Kniss A (2008)
Khan M (2008),

Kniss A (2010)
Khan M (2008), JonJoseph A and Sprague C(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 and©PG Economics Ltd 2018173

GM crop impact: 1996-2016

impact 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 ofsoybean 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 1996-2015 (2): second crop
soybeans
Year

Second crop area
(million ha)
0.45
0.65
0.8
1.4
1.6
2.4
2.7
2.8
3.0
2.3
3.2
4.94
3.35
3.55
4.40
4.60
2.90
3.46
4.00
3.94
5.2

Average gross margin/ha forsecond crop soybeans ($/ha)
128.78127.20125.24122.76125.38124.00143.32151.33226.04228.99218.40229.36224.87207.24257.70257.40291.00289.80195.91
168.81140.80

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
736.0
1,133.8
1,184.0
844.6
1,001.6
783.6
665.9
732.2

1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
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 2018174

GM crop impact: 1996-2016

Appendix 3: Additional information relating to theenvironmental impact: example comparisons
US Soybeans: typical herbicide regimes for conventional no tillage production systems: Mid
West
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
Total

Active ingredient (kg/ha)

Field EIQ/ha value

1.16
0.66
0.08
0.02
0.21
0.17
2.30

17.78
10.11
1.89
0.43
3.15
2.89
36.25

1.16
0.66
0.07
0.02
0.01
0.32
0.17
2.41

17.78
10.11
1.74
0.43
0.11
7.83
2.89
40.89

1.17
0.66
0.20
0.03
0.17
2.22

17.78
10.11
2.39
0.39
2.89
33.56

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
Option 3©PG Economics Ltd 2018

Active ingredient (kg/ha)

Field EIQ/ha value

1.16
0.66
0.07
1.36
0.30
0.17
3.72

17.78
10.11
1.78
29.97
7.32
2.89
69.85

1.16
0.66
0.07
0.02
0.33
0.17
2.41

17.78
10.11
1.78
0.4
8.07
2.89
41.03

175

GM crop impact: 1996-2016

Glyphosate
24D
Metalochlor
Fomesafen
Acifloren
S Metalochlor
Clethodim
Total

1.16
0.66
1.36
0.30
0.32
1.51
0.17
5.48

17.78
10.11
29.97
7.32
7.48
33.22
2.89
108.77

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
1.51
0.33
0.17
2.08

1.72
33.22
8.07
2.89
45.90

0.08
0.02
0.32
0.17
0.59

1.89
0.43
7.82
2.89
13.03

1.36
0.30
0.32
1.51
0.17
3.66

29.97
7.32
7.48
33.22
2.89
80.88

Weighted average all by tillage types: ai/ha 2.41 kg/ha, EIQ/ha 45.20©PG Economics Ltd 2018176

GM crop impact: 1996-2016

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 2016
GM HT soybean
Source: AMIS Global dataset on
pesticide use 2016
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©PG Economics Ltd 2018

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
49.07

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

34.80
0.50
16.56
1.96

177

GM crop impact: 1996-2016

Clethodim
0.24
Total
3.58
Average all six conventional
3.62
options
Sources: AAPRESID, AMIS Global, Kleffmann, Monsanto Argentina

4.08
61.21
62.04

GM HT versus conventional maize Argentina 2016

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 Argentina

16.72
20.61
28.65
5.83
71.81

Typical herbicide regimes for GM HT soybeans Brazil 2016
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
9.23
48.95
15.0
54.72

Typical herbicide regimes for GM HT soybean in South Africa 2016
Active ingredient
Conventional soybean
Option one
Metalochlor
Metribuzin
Total
Option two©PG Economics Ltd 2018

Amount (kg/ha of crop)

1.18
1.59
2.77

178

Field EIQ/ha

25.96
45.11
75.07

GM crop impact: 1996-2016

S Metolachlor
0.92
20.13
Dimethenamid
1.05
12.62
Total
1.97
32.75
Option 3
S Metolachlor
0.92
20.13
Mesotrione
0.18
18.60
Total
1.10
23.60
Weighted average
1.95
38.73
GM HT soybean – based on AMIS
1.68
28.73
Global 2014
Source: Monsanto South Africa, AMIS Global, Kleffmann
Note conventional average weighted by active ingredient use in AMIS Global and Kleffmann – option 1,
70%, option 2, 20%, option 3, 10%

Typical herbicide regimes for GM HT cotton in South Africa 2016
Active ingredient
Conventional cotton
Option one
Trifluralin
Total
Option two
S Metolachlor
Flumeturon
Prometryn
Total
Option 3
Trifluralin
Cyanazine
Total
Option 4
Trifluralin
Flumeturon
Prometryn
AcetochlorAtrazine
Total
Option 5
Trifluralin
Flumeturon
Prometryn
Total
Average conventional
GM HT cotton
Glyphosate
Source: Monsanto South Africa

Amount (kg/ha of crop)

Field EIQ/ha

1.12
1.12

21.06
21.06

0.96
0.4
0.5
1.85

20.9
5.72
7.70
34.48

1.12
0.85
1.97

21.06
11.56
32.62

1.12
0.4
0.5
0.32
0.128
2.093

21.06
5.72
7.70
6.37
2.93
43.77

0.75
0.4
0.5
1.65
1.81

14.10
5.72
7.70
27.52
31.86

1.8

27.59

Typical herbicide regimes for GM HT maize in Canada 2016
Active ingredient
Conventional maize
MetalochlorAtrazine©PG Economics Ltd 2018

Amount (kg/ha of crop)
1.40
1.09

179

Field EIQ/ha
30.80
24.96

GM crop impact: 1996-2016

Mesotrione
Dicamba
Total

0.12
0.46
3.07

2.22
12.11
70.11

GM glyphosate tolerant maize
Metalochlor
0.94
20.64
Atrazine
0.73
16.72
Glyphosate
1.31
18.55
Total
2.88
55.91
GM glufosinate tolerant maize
Metalochlor
0.94
20.64
Atrazine
0.79
16.72
Glufosinate
0.37
7.49
Total
2.04
44.65
Sources: Weed Control Guide Ontario – annually updated, industry personal communications (various),
Kleffmann

Typical insecticide regimes for cotton in India 2016
Active ingredient
Conventional cotton
Option 1
Imidacloprid
Thiomethoxam
Acetamiprid
Diafenthiuron
Buprofezin
Profenfos
Acephate
Cypermethrin
Metaflumizone
Novaluron
Total
Option 2
Imidacloprid
Thiomethoxam
Acetamiprid
Novaluron
Chlorpyrifos
Profenfos
Metaflumizone
Emamectin
Total
Average conventional
Weighted average
GM IR cotton
Imidacloprid
Thiomethoxam
Acetamiprid
Novaluron
Buprofezin
Acephate©PG Economics Ltd 2018

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
0.02
0.39
0.81
0.03
0.01
1.42
1.67
1.72

2.2
1.67
1.45
0.29
10.58
48.28
0.82
0.29
65.59
72.41
73.76

0.06
0.05
0.05
0.02
0.07
0.63

2.2
1.67
1.45
0.29
2.55
15.79

180

GM crop impact: 1996-2016

Total
0.89
23.95
Option 2
Imidacloprid
0.06
2.20
Thiomethoxam
0.05
1.67
Acetamiprid
0.05
1.45
Novaluron
0.02
0.29
Total
0.18
5.61
Weighted average GM IR cotton
0.605
16.61
Source: Monsanto India, AMIS Global
Note weighted average for GM IR cotton based on insecticide usage – option 1 60%, option 2 40%

Typical insecticide regimes for cotton in China 2016
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 China, AMIS Global, Kleffmann, Plant Protection Institute of the Chinese Academy ofAgricultural Sciences

Typical herbicide regimes for GM HT cotton Australia 2016
Active ingredient
Conventional cotton
Option 1 ‘dirty’
Trifluralin
DiuronGlyphosate
Prometryn
Flumeturon
DiuronMetalochlor
Clethodim
Prometryn
Total
Option 2 ‘moderate’
Trifluralin
Glyphosate©PG Economics Ltd 2018

Amount (kg/ha of crop)

Field EIQ/ha

1.2
0.925
0.9
0.66
0.44
1.85
1.44
0.12
1.25
8.78

22.60
24.48
13.80
10.14
6.28
48.97
31.68
2.04
19.21
179.20

1.2
0.45

22.60
6.90

181

GM crop impact: 1996-2016

Flumeturon
0.66
9.42
Flumeteron
0.4
5.71
Prometryn
1
15.37
Prometryn
1.5
23.06
Clethodim
0.12
2.04
Metalochlor
1.44
31.68
Total
6.77
116.77
Option 3 ‘clean’Diuron1.0
26.47
Glyphosate
0.45
6.90
Flumeteron
0.44
6.28
Prometryn
0.66
10.14
Paraquat
0.25
6.18
Diquat0.2
4.95
Pyrithiobic sodium
0.006
0.13
Prometryn
0.66
10.14
Total
3.666
71.19
GM HT cotton
Option 1 ‘ dirty’
Trifluralin
0.864
16.27
Diuron0.46
12.18
Prometryn
0.66
10.14
Flumeteron
0.44
6.28
Glyphosate over the top
3.105
47.60
Glyphosate burn down
0.48
7.36
Total
6.009
99.83
Option 2 ‘ moderate’Pendimethalin
0.99
29.87
Flumeteron
0.44
6.28
Glyphosate over the top
3.11
47.60
Glyphosate burn down
0.48
7.36
Total
5.02
91.11
Option 3 ‘ clean’Glyphosate over the top
2.07
31.73
Glyphosate burn down
0.45
6.90
Total
2.52
38.63
Source: Monsanto Australia, Kleffmann. Weightings applied dirty 60%, moderate 40%, clean 20% for both
GM HT and conventional

Typical insecticide regimes for cotton in Mexico 2016
Active ingredient
Conventional cotton
Lambda cyhalothrin
Cypermethrin
Monocrotophos
Methidathion
Triazophos
Methomyl
Chlorpyrifos
Chlorfenapyr
Endosulfan

Amount (kg/ha of crop)

Field EIQ/ha

0.04
0.16
0.6
0.622
0.6
0.225
0.96
0.12
1.08

1.89
5.82
22.08
20.34
21.36
4.95
25.82
5.53
41.69

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GM crop impact: 1996-2016

Azinphos methyl
Parathion methyl
Total
GM IR cotton
Lambda cyhalothrin
Cypermethrin
Monocrotophos
Methomyl
Chlorpyrifos
Chlorfenapyr
Endosulfan
Azinphos methyl
Parathion methyl
Total

0.315
0.5
5.222

14.52
13.0
177.00

0.02
0.08
0.3
0.225
0.96
0.12
1.08
0.315
0.5
3.60

0.94
2.91
11.04
4.95
25.82
5.53
41.69
14.52
13.0
120.41

Typical conventional insecticide regime for maize (targeting corn boring pests) in Colombia
2016
Active ingredient
Amount (kg/ha of crop)
Luferon0.0225Chlorifluzanon
0.05
Chlorpyrifos
0.325
Mathavin
0.162
Total
0.561
Source: Mendez et al (2011)
Note: GM IR maize replaces the above treatment©PG Economics Ltd 2018183

Field EIQ/ha
0.37
1.82
8.73
4.97
15.89

GM crop impact: 1996-2016

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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GM crop impact: 1996-2016

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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GM crop impact: 1996-2016

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 2018186

GM crop impact: 1996-2016

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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GM crop impact: 1996-2016

Appendix 5 Soil carbon sequestration key literature
Soil organic carbon can be depleted through:••the long-term use of 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 by Reicosky (1995) for aselection of cultivation techniques (after tilling wheat). Using a mouldboard plough results insoil carbon losses far exceeding the carbon value of the previous wheat crop residue anddepleting 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 119 (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 of carbon emissions. Lal 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 whichcarbon dioxide is rising in 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 carbon sequestration. 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(Reicosky (2004)).
119

1 Pg of soil carbon pool equates to 0.47 parts per million, of atmospheric carbon dioxide.

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GM crop impact: 1996-2016

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.
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);
Organic carbon mineralization (soil carbon outputs);
Soil erosion and re-deposition on soil organic gains and losses.

A number of researchers have examined issues relating to carbon sequestration and different
tillage systems and the following are of note:
•

•

•

•

•

120

West and Marland (2001) estimated that the net carbon flux from the conversion fromconventional tillage to no-till was a decrease of 468 kg/carbon/ha/yr for corn, 32
kg/carbon/ha/yr for wheat and 371 kg/carbon/ha/yr for soybeans released to theatmosphere;West and Post (2002). This work analysed 67 long-term agricultural experiments,
consisting of 276 paired treatments. These results indicate, on average, that a change
from conventional tillage (CT) to no-till (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 that obtained the highest level of carbon sequestration
when tillage changed from CT to NT was corn: 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 120;
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 corn or soybeans and alternating cornsoybeans 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 with continuous corn
or corn-soybeans and NT with continuous corn, averaged an annual loss of 1.6
Mg/carbon/ha/yr. They concluded that without large additional carbon inputs (egmanures, cover crops, perennial crops) the potential to approach SOC levels of native
sites is limited with annual cropping and reduced tillage;
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);

Conversion factor for carbon sequestered into carbon dioxide = 3.67.

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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 no-till theaverage mitigation potential was estimated at 1,200 kg of carbon dioxide per hectare per
year with 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 corn and soybeans rotation that used different tillage
systems. The NT system stored and retained 7.8 tonnes of carbon per ha more than 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;
Bernoux et al (2006) reviewed cropping systems, carbon sequestration and erosion in
Brazil. Over 30 years of no-tillage 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 no-till system (with liming) and minus 20 grams/ha/year for a NT
system (without liming). The major factors influencing the beneficial effect of no-till overconventional and organic systems is the high level of carbon sequestration and reduced
use of fuel resulting in emissions of 12 grams of carbon dioxide equivalents m-2 year-1©PG Economics Ltd 2018190

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compared with 16 grams in conventional tillage and 19 grams for organic tillage. The
release of nitrous oxide in terms of carbon dioxide was equivalent in the organic and NT
systems due to the availability of nitrogen under the organic system compared with thetargeted 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
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 corn following three decades of different
tillage and rotation systems. Seasonal cumulative N2O emissions were significantly
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 levels of 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) expressed caution with the premise that NT results in positive carbon
sequestration compared with CT. Their analysis 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. In both cases, however, the standard error associated with the estimates was solarge that the mean (impact of tillage) was not considered to be significant;Research by Angers and Eriksen-Hamel (2008) and Blanco-Canqui and Lal (2008) 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 and 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 10cm), to the 21-25 cm soil depth (which corresponds to the mean ploughing depth (23cm)), the average 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,overall there was significantly more SOC (4.9 Mg ha-1) under NT than FIT across all
depths and this difference in favour of NT increased weakly with the duration of theexperiment;
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©PG Economics Ltd 2018191

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were found to be variable. Also there was no evidence of carbon gains in the surface soilsof NT being either offset or magnified at depth;
Al-Kaisi (2005) evaluated the effects of different tillage systems on soil organic carbon(SOC) and nitrogen (SON), residue carbon and nitrogen inputs and crop (corn andsoybean) yields in Iowa. Yields of both corn and soybean were comparable in NT andmouldboard 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 were similar to
those observed with the SOC experiments;
The corn-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 corn and soybean in rotation that had been
in NT cultivation for over 14 years. The carbon sink when planted with corn was 576 g C
m per year and soybean 33 g C m per year. Accounting for 100% grain consumption,corn acts as a C-sink of 184 g C m per year while soybean becomes a C-source 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, havehigher nutrient loading capacities, release nutrients gradually and continuously and havebetter 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) estimate that if the total area of corn/soybeans in the US converted
to no-till, 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 USA carbon emissions;
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

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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));
Walia et al (2017) quantified tillage and fertiliser management effects after 44 years (20years in continuous corn and 24 years in corn–soybean rotation) on bulk density and soil
carbon concentrations. No-till management increased carbon stocks compared to tillage
treatments for depths of between 0 to 15 cm and was greater than the chisel plough
treatment for soil depths between 0 to 100 cm. No-till combined with NPK (nitrogen,phosphorus and potassium) maintained greater cumulative soil carbon stocks to 1 metre
than either undisturbed forest soils or restored prairie soils. Additionally, NT/NPK had
the 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.
Lastly, 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.
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 conventional tillage 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.

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