Transgenic Res (2020) 29:229–242
https://doi.org/10.1007/s11248-020-00193-z(0123456789().,-volV)(0123456789().,-volV)

ORIGINAL PAPER

Consideration of familiarity accumulated in the conﬁned
ﬁeld trials for environmental risk assessment of genetically
modiﬁed soybean (Glycine max) in Japan
Akane Matsushita
Ryo Ohsawa. Hidetoshi Goto . Yasuyuki Takahashi . Mai Tsuda .

Received: 8 May 2019 / Accepted: 21 January 2020 / Published online: 29 January 2020
© The Author(s) 2020

Abstract To date, there have been 160 regulatory
approvals for environmental safety in Japan for the
major genetically modified (GM) crops, including
corn, soybean, canola and cotton. Confined field trials(CFTs) have been conducted in Japan for all single
events, which contain various traits. The accumulated
information from these previously conducted CFTs,
as well as the agronomic field study data from othercountries, provides a rich source of information toestablish “familiarity” with the crops. This familiarity
can be defined as the knowledge gained throughexperience over time, and used to inform theenvironmental risk assessments (ERA) of new GM
crops in Japan. In this paper, we compiled agronomic

Electronic supplementary material The online
version of this article (https://doi.org/10.1007/s11248020-00193-z) contains supplementary material, whichis available to authorized users.
A. Matsushita (&)
Dupont Production Agriscience K.K., Sanno Park Tower,
2-11-1, Nagata-cho, Chiyoda-ku, Tokyo 100-6110, Japane-mail: akane.matsushita@corteva.com
H. GotoBayer CropScience K.K., Marunouchi Kitaguchi Bldg,
1-6-5, Marunouchi, Chiyoda-ku, Tokyo 100-8262, Japan

data from the CFTs performed in Japan for 11 GM
soybean events which obtained food, feed andenvironmental safety approvals from regulatory
agencies in Japan. These CFTs were conducted bymultiple developers according to Japan regulations to
support the ERA of these GM soybean, covering
standard measurement endpoints evaluated acrossdevelopers in Japan. With this dataset, we demonstrate how familiarity gained from the CFTs of GM
soybeans in Japan can be used to inform on the ERAof new GM soybean events. By leveraging thisconcept of familiarity, we discuss potential enhancements to the ERA process for GM soybean events inJapan.
Keywords Genetically modified crops ·Environmental risk assessment · Confined field trials ·Familiarity · Data transportability

M. Tsuda · R. Ohsawa
Gene Research Center, Tsukuba Plant Innovation
Research Center, University of Tsukuba, 1-1-1 Tennodai,
Tsukuba, Ibaraki 305-8572, Japan
M. Tsuda · R. Ohsawa
Faculty of Life and Environmental Sciences, University ofTsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8572,
Japan

Y. Takahashi
Dow AgroSciences Japan Ltd., Sanno Park Tower, 2-11-1,
Nagata-cho, Chiyoda-ku, Tokyo 100-6110, Japan

123

230

Introduction
Japan is one of the top import countries of geneticallymodified (GM) crop products, especially from the US(USDA 2013). Although no GM crops are commercially cultivated in Japan, both cultivation approvaland food and feed safety approvals are required forimport and use of GM crops as food, feed andprocessing. The cultivation approval assesses thepotential environmental impacts if, for example,
imported grain is spilled during transportation or ifconventional seeds that have been imported forplanting in Japan are contaminated with GM events.
As part of the environmental risk assessment (ERA),
confined field trials (CFTs) are required to be
conducted in Japan, to compare the agronomic andphenotypic characteristics between the GM crop andan appropriate non-GM near isogenic control variety.
The requirements for ERA, as a part of the GM
product assessment and authorization, are specified
by two regulatory agencies, the Ministry of Agriculture, Forestry and Fisheries (MAFF) and the Ministryof Environment (MOE), under the domestic law
enforced in 2004 to implement the Cartagena Protocol on Biosafety (J-BCH 2018a). In 2004, when thecurrent regulatory framework was established, therequirement to generate in-country CFT data to
inform the ERA for import was likely posed toaddress uncertainty about the potential effects of theJapanese environment on phenotypic and agronomic
characteristics of GM crops (Yogo 2010). In comparison, Environmental Risk Assessments (ERA) andin-country CFTs are not typically required for importapprovals in other countries (EFSA 2010; RDA
2014). This existing requirement for conducing CFTs
in Japan should be reassessed to determine if it
informs the ERA.
There is a two-step approval process that must be
followed, prior to submitting an application for
cultivation approval in Japan: first, an ERA for CFT
use is done considering laboratory and glass-house
data (to characterize the intended trait, including
molecular characterization studies and bioassays) andfield data which is collected in other countries,
typically in US. Next, if CFT approval is granted,
GM events are planted along with non-GM controls
in CFTs in Japan, to allow a comparative assessmentof plant characteristics, e.g., phenotypic and agronomic characteristics between the GM crop and an

123

Transgenic Res (2020) 29:229–242

appropriate non-GM near isogenic control variety.
Using this information, in addition to host plant
information and other related information, the following three assessment endpoints are evaluated: (1)competitiveness of the GM plant with wild plants forresources such as nutrients, sunlight, habitat, etc.; (2)production of harmful substances that interfere withthe growth of wild plants, animals, or microorganisms; and (3) outcrossing potential with wild
relatives, resulting in introgression of transgenic
DNA (J-BCH 2018b). If one or more unanticipated(other than the intended trait) statistically significant
differences are observed between the GM crop andthe control in the CFT, the differences need to beassessed for biological relevance, specifically assessing if the GM plant will have increased
competitiveness with wild plants, will produce
harmful substances that affect wild plants, animals,or microorganisms, or will have increased outcrossing potential. To assess biological relevance of anobserved difference, it is important to understand thebasic biology of the crop, the characteristics of theintroduced trait, the receiving environment for theGM crop, and the potential interactions between thesefactors (Nickson 2008). Biological relevance ofobserved difference can be evaluated by considering
if the values for the GM crop fall within the range ofthe values for non-GM crops described in literature.
One limitation of Japan’s required CFT is thatpublicly available agronomic data from GM and its
near isogenic line of non-GM crops grown in Japan iscurrently not available to assist this assessment,
which makes understanding biological relevancedifficult.
Environmental risk assessment should be conducted using problem formulation, following ascience based approach, and leveraging familiarity.
A problem formulation based approach to risk
assessment assesses existing data to determine if
there is a plausible and testable hypothesis forenvironmental harm. This problem formulation
approach helps identify if additional data is needed
to inform the risk assessment (Raybould and Macdonald 2018). Additionally, the globally recognizedconcept of familiarity was originally developed by
OECD (1993) and is another key concept for the risk
assessment of GM crops. Familiarity can be definedas the knowledge gained through experience overtime. The concepts of both problem formulation andTransgenic Res (2020) 29:229–242

familiarity should be considered when determining if
CFT conducted in Japan will inform the risk assessment. For example, large multi-location field trials,
which are carried out typically in the country ofdevelopment, are performed and the comparative
assessments of the agronomic and phenotypic characteristics are used to support the ERA for cultivationof GM crops (Garcia-Alonso et al. 2014). However,in the case of the Japan CFTs, the null hypotheses of
no difference between a GM crop and a comparator istested in the Japanese environment, even if data fromanother geography demonstrates no difference andthere is no plausible hypothesis for how the event
would be different in the Japanese environment. To
date, there have been around 160 regulatory
approvals for environmental safety in Japan for the
major GM crops, including corn [Zea mays subsp.
mays (L.) Iltis], soybean [Glycine max (L.) Merr.],
canola (Brassica napus L.) and cotton (Gossypium
hirsutum L.), and CFTs have been conducted in Japanfor all single events. Assessed events have expressedvarious traits, including herbicide tolerance, insect
resistance and nutritional improvement. Based on the
CFT data conducted in Japan, the ERA for all of these
events concluded that the GM crop exhibits noadverse effect upon the natural environment in Japanand are comparable to conventional crops, with the
exception of the introduced trait. In all cases to date,the conclusions from the CFTs in Japan are the sameas the conclusions from agronomic data developed
from cultivation (exporting) countries. Therefore, theagronomic data collected to support cultivation
approvals in other countries can be leveraged for
the ERA in Japan, and a CFT in Japan should only berequired if there is a plausible hypothesis for how GM
event would lead to adverse effects in the Japaneseenvironment.
Recently, the regulatory authorities in Japan haveupdated the regulations for GM maize containing
familiar traits. In cases where the GM maize contains
a transgene that has previously been reviewed inJapan (e.g., MAFF 2014), the ERA can be conductedusing CFT data from other countries. The Japanese
regulators recognized that the accumulated information from previously conducted CFTs in Japan, as
well as the agronomic field study data from othercountries, provides a robust data set, and the resulting
familiarity can be used to inform the ERA of newmaize events containing similar traits in the future.

231

To date, there have been three GM corn events which
satisfied these criteria and were exempted from incountry CFTs. On the other hand, for other crops likesoybean, an in-country CFT is still required to be
conducted for the ERA in Japan.
In this publication, we compiled agronomic datafrom eleven CFTs of GM soybean events, which canbe used to increase familiarity and improve theevaluation system for ERA of GM soybean in Japan.
These CFTs have been conducted by multiple
developers to support product approval for environmental safety in Japan, but the data has not been
disclosed previously in the literature. Based on thecompiled data which covers common measurement
endpoints currently evaluated in the CFTs, wedemonstrate how familiarity gained from the data
accumulated in the CFTs of GM soybean in Japan
can be used to inform on the ERA of new GM
soybean events. Furthermore, leveraging the conceptof familiarity, we discuss potential enhancements tothe ERA process for GM soybean in Japan including
the transportability of CFT data between countries
and leveraging existing data to inform the risk
assessment of new events.

Materials and methods
EventsSince 2004, a total of sixteen GM soybean events
have been evaluated after implementation of the
Cartagena domestic law in Japan. The developers ofeach soybean event were consulted to determine if
the CFT data from Japan could be released for use inthis publication. Of these sixteen soybean events, theCFT data from eleven events were approved for use
in this publication by Monsanto (now Bayer CropScience), Dow AgroSciences and Dupont Pioneer(now Corteva Agriscience). These events are summarized in Table 1, including herbicide tolerance(HT), insect resistance (IR) and nutritional improvement (NI) traits. In CFTs, each event was comparedwith a corresponding near-isogenic control line
(NIL).

123

232

Transgenic Res (2020) 29:229–242

Table 1 Eleven GM soybean events that were tested in CFT in Japan and authorized in Japan since 2004
OECD UI

Developer

Trait
HT

Inserted gene(s)IRNI

Detail

DAS-68416-4

Dow AgroSciences✓

Aryloxyalcanoate andglufosinate tolerance

aad-12, pat

DAS-444Ø6-6

Dow AgroSciences✓

aad-12, 2mepsps, pat

DAS-81419-2

Dow AgroSciences✓

Aryloxyalcanoate,glyphosate andglufosinate tolerance
Lepidopteran resistance andglufosinate tolerance

DP-356Ø43-5

Dupont Pioneer✓

DP-3Ø5423-1

Dupont Pioneer✓✓

MON-89788-1

Monsanto Company

MON-87769-7

Monsanto Company

MON-877Ø1-2

Monsanto Company

MON-877Ø5-6

Monsanto Company✓

MON-877Ø8-9

Monsanto Company✓

MON-87751-7

Monsanto Company✓

Glyphosate andsulfonylurea tolerance

gat4601, gm-hra✓

High oleic acid andsulfonylurea tolerance
Glyphosate tolerance

gm-fad2-1, gm-hra✓

Stearidonic acid production

Pj.D6D, Nc.Fad3

Lepidopteran resistancecry1AcLow saturated fatty acids,
high oleic acid andglyphosate tolerance

fad2-1A, fatb1-A, cp4epsps

Dicamba tolerance

dmo

Lepidopteran resistancecry1A.105, cry2Ab2✓✓✓

cry1Ac, cry1F, pat

cp4epsps

HT herbicide tolerance, IR insect resistance, NI nutritional improvement

Overview of CFT experimental design
Each CFT was conducted independently by thecorresponding developers from 2005 to 2015 inconfined fields that are located across Japan, including Ibaraki, Tochigi, Shizuoka and Fukuoka (Online
Resource 1). Cold tolerance of some events were
measured in the glasshouse located in US, see
Supplementary information). Cultivation was performed under conventional field management
practices. All studies except outcrossing rate werecomparative studies, where the GM crop and the nonGM NIL comparator were grown in the same field,
and their growth and agronomic characteristics werecompared, based on the evaluation items indicated in
the guideline (J-BCH 2018a). The experimental
protocols used by each developer are similar, but
not identical; for example, the number of samples or
the number of replicates may be different, dependingon the protocol used by the developer. Hence,
hereafter generalized methods that were used foreach evaluation item are described. For more detail,see Online Resource 2. Likewise, the methods forstatistical analysis adopted by each developer are
similar, but not identical. Statistical details for each123

CFT are not provided here, but the appropriateness ofthe statistical methods used for each CFT werereviewed and confirmed by academic experts during
regulatory review processes.
Agronomic characterization
Measurement endpoints for the agronomic characteristics that are commonly used by developers in CFTs
for ERA in Japan are; germination rate, flowering
stage, maturity stage, main stem length, number ofnodes, number of branches, number of pods, pod
shattering, weight of grain and weight of 100 grains.
Definition of each endpoint is provided in Online
Resource 3.
Cold tolerance during the early stages of growth
Seeds were planted in pots and grown in a glasshouseor a growth chamber (20–25 °C). Seedlings at the V1
growth stage were transferred to either a growthchamber where the average temperature was maintained at approximately 4 °C or an open plot where
the average temperature was 3 °C. Survival or
damage (wilting, fading and necrosis) of theTransgenic Res (2020) 29:229–242

seedlings was either monitored by visual observation
or by assessing plant height and dry weight, whichwere measured after 2–4 weeks to determine any
differences between the GM and NIL plants in termsof their tolerance to cold temperatures.
Overwintering
After the harvest period, unharvested plants were left
on the trial field and were monitored to determine ifthey survived through the following winter period.
Plant survival was monitored until the end of the trial(Online Resource 1), to determine any differences
between the GM and NIL plants in terms of theirability to survive over the winter.
Pollen viability observation
Unopened flower buds were dissected from plants at
the flowering stage. Anthers within were removed
and dipped into either 1–3% potassium iodide
solution, Alexander solution (Alexander 1969), or
acetocarmine solution. Subsequently, a sample of thesolution which contained soybean pollen wasremoved and observed under an optical microscope.
The ratio of stained pollen grains to total pollen
grains was observed, and the diameter of pollen
grains was measured to determine any differences
between the GM and NIL plants in terms of theirpollen viability.
Germination rate and dormancy of harvested
seeds
At harvest, seeds were collected from 15 to 48 plants
in each plot and seeds were bulked. Seeds from eachbulked sample were sown in an open plot or inculture dishes without any treatment to assess
germination rate and seed dormancy. At least 5 days
after planting, germination rates were determined by
calculating the ratio of the number of establishedseedlings in the open plot or the number of germinated seeds in culture dishes to the total number ofseeds used for the study.
Succeeding crop test
At harvest, soil samples (approximately 209209
20 cm3) were collected from underneath several

233

soybean plants in each plot. Root tissues were
removed, and the soil samples were composited foreach plot. Field soil from each plot was then placed inpots and radish seeds were planted and maintained at
25 °C in a controlled environment. After 1–2 weeks,
the seedling establishment rate for radish seeds wasmeasured. Additionally, soil from representative
seedlings was gently removed, and after drying
seedlings in a thermal incubator, the dry weight ofthe seedlings was measured.
Plough-in test
Soybean plants were harvested from the field andwere dried in a controlled incubator or glasshouse.
The dried plant materials were ground with a grinder
mill, and the powdered materials were pooled andincorporated into potting media at a rate of 0.5 or 1%
to make the test soil. Test soil was placed in pots andradish seeds were planted and maintained at 25 °C in
the controlled environment. After 1–2 weeks, theseedling establishment rate for radish seeds wasmeasured. Additionally, soil from representative
seedlings was gently removed, and after drying
seedlings in a thermal incubator, the dry weight ofthe seedlings was measured.
Soil microflora test
Soil samples (approximately 400 ml) were taken fromunderneath plants in each field plot and soil microorganisms were counted using a dilution plate method(Asanuma et al. 2011). A small sub-sample of eachsoil sample was mixed with sterilized water or an
appropriate buffer. Supernatant was removed tocreate the first diluted solution (10−1), and thentenfold serial dilutions were prepared. An aliquot of
each dilution was inoculated onto Rose Bengal agar
medium for ﬁlamentous fungi, and PTYG agar orsimilar medium for bacteria and actinomycetes, andthen plates were incubated in the dark at 25 °C for
7 days. Several replicate plates of each media anddilution were used, and plates containing the optimal
density of colonies (10–300 colony forming units;
CFUs) were counted. The total number of bacterial,actinomycete and ﬁlamentous fungal CFUs were
calculated and reported as the number of CFUs per
1 g of dry soil.

123

234

Outcrossing test
Non-GM NIL plants were planted in the field site inan area adjacent to GM plants and both plants weregrown to maturity. To assess outcrossing from GM
plants to non-GM NIL plants, seeds were collectedfrom the non-GM NIL plants and were subsequently
planted and grown to the V2–V4 stage in an open plot
or in pots and grown in a glasshouse. To determine if
outcrossing occurred (i.e., presence of a GM trait in
the non-GM NIL progeny), the progenies of the nonGM plants were either sprayed with herbicide (theherbicide that corresponds to the herbicide resistancetrait in the GM plants), characterized by PCR (todetect DNA sequence of the transgene), or assessedby lateral flow immunochromatographic assays (todetect the transgenic protein).

Results: dataset compiled from CFTs for elevensoybean events
Agronomic characterization
The common agronomic characteristics measured in
CFTs across the 11 soybean events include germination or seedling establishment rate (G/SE rate; %),flowering stage (date), maturity stage (date), mainstem length (cm), number of nodes, number ofbranches, number of pods, and pod shattering (J-BCH
2018c; Table 2). With the exception of two soybean
events, DAS-68416-4 (99.0% for GM vs. 80.2% for
non-GM NIL) and MON-877Ø8-9 (99.2% for GM vs.
100% for non-GM NIL), there were no statisticallysignificant differences in G/SE rate between the GM
and non-GM NIL plants across the CFTs (Table 2).
The G/SE rate of DAS-68416-4 soybean was reevaluated in the glass house, and exhibited no statisticallysignificant differences in this assessment (98.3% for
GM vs. 95.0% for non-GM NIL), indicating that thestatistically significant difference observed in seedling establishment rate in the field for this event may
not have been a true biological difference. Similarly,
while the G/SE rate of MON-877Ø8-9 was decreased
compared to control, the rate of MON-877Ø8-9
remained above 99%, indicating that this difference is
not biologically relevant. With the exception of
MON-87751-7 (104.2 cm for GM vs. 108.7 cm for
non-GM NIL), there were no statistically significant

123

Transgenic Res (2020) 29:229–242

differences between GM and corresponding non-GM
NIL plants for main stem length (Table 2). In thiscase, the main stem length of MON-87751-7 wasdetermined to fall within the range of values reported
for other commercial varieties (J-BCH 2018c), indicating this difference is not biologically relevant.
With the exception of MON-877Ø5-6 (7.0 for GM vs.
6.1 for non-GM), there were no statistically significant differences between GM and corresponding
control for number of branches (Table 2), and nostatistical differences were observed for any soybean
event for number of nodes (Table 2) or number ofpods (Table 3). Since there was no significant impact
on the number of pods per plant in MON-877Ø5-6
soybean, there is no evidence of changing seedproduction ability.
Flowering time and maturity date endpoints were
not statistically analyzed, and all GM and non-GM
NIL controls had similar dates for both endpoints.
Only two soybean events had slightly different
flowering times (DP-3Ø5423-1 and MON-87751-7),
however these differences were very small (with only
a few days of difference; Table 2). Results for pod
shattering across 11 CFTs were consistent, where
there were no reported differences in pod shattering
between the GM and corresponding non-GM NIL
controls based on visual observation of representativeplants.
Cold tolerance of early developmental stage
and overwintering
To assess cold tolerance, the health and viability ofGM and non-GM NIL soybean plants were assessed
after being grown under cold temperatures in growthchamber (4 °C) or open plot. Across all 11 CFTs, all
GM and non-GM NIL withered after growing for 2–
5 weeks under these low temperature conditions. No
differences were reported between any of the GM
soybean events, when compared to their respective
non-GM NIL controls, indicating that these GM traits
did not increase the tolerance of the GM plants tocold. Similarly, when GM plants were compared to
non-GM NIL control plants, there were no differences in their ability to survive the winter season. All
plants, whether they were GM or non-GM soybean,
withered and did not survive the overwintering test.

Transgenic Res (2020) 29:229–242

235

Table 2 Agronomic characteristics of GM and non-GM control soybeans tested in CFTs in Japan
OECD UI

G/SE rate (%)
GM

Flowering time (MM/ Maturity dateDD)
(MM/DD)
ControlGM

ControlGM

Main stem
length (cm)Control GM

Number ofnodes

Number of
branchesControl GM

Control GM Control

DAS-68416-4

99.0* (98.3)a 80.2 (95.0) 8/6–9/15

8/6–9/15

10/20 10/20

84.8

86.5

23.1

23

7.8

7.9

DAS-444Ø6-6

94.3

86.5

8/6–9/15

8/6–9/15

10/20 10/20

97.6

89.3

23.8

23

9.2

8.2

DAS-81419-2

92.2

94.8

8/26–10/2 8/26–10/2 11/1

11/1

52.0

62.9

15.9

15.6

4.0

4.0

DP-356Ø43-5

87

89

8/1

8/1

10/16 10/16

47.5

55.2

13

13.7

1.9

2.3

DP-3Ø5423-1

99.3

97.2

7/9

7/8

10/23 10/23

61.8

59.3

14.3

14.3

4.2

4

MON-89788-1 99.17

97.78

7/27–9/8

7/27–9/8

10/17 10/17

67.63

67.97 18.40 18.53

7.60 7.80

MON-87769-7 96.72

97.97

8/21–9/16 8/21–9/16 11/10 11/10

68.13

68.11 18.58 18.88

5.73 5.68

MON-877Ø1-2 71.3

76.0

9/4–9/24

9/4–9/24

12/8

12/8

59.0

56.2

13.6

13.5

7.0

MON-877Ø5-6 98.3

91.6

8/2–9/2

8/2–9/2

11/9

11/9

71.1

73.5

19.6

20.5

7.0* 6.1

MON-877Ø8-9 99.2*

100.0

7/16–9/8

7/16–9/8

11/2

11/2

82.1

78.5

21.1

21.0

7.3

7.4

NC

7/8–8/12

7/4–8/12

10/29 10/29

104.2* 108.7

21.9

22.4

6.7

6.8

b

MON-87751-7 NC

6.5

Average values for each measurement endpoints related to agronomic performance are provided. Since each value was taken fromoriginal dossiers as is, significant figures are not consistent. Asterisk indicates statistically significant difference (P\0.05)
aG/SE rate of DAS-68416-4 was reevaluated in the glass house and exhibited no statistically significant difference between GM andnon-GM NIL (98.3 vs. 95.0%, respectively)b

NC not conducted

Table 3 Productivity of grain and germination rate of harvested seeds of the GM soybeans
Number of podsa

Grain weight per plant (g)aWeight of 100 grains (g)a

G/SE rate for harvested seeds (%)aGM

Control

GM

GM

GM

DAS-68416-4

199.1

223.4

69.9

85.1

15.2

15.5

100

100

DAS-444Ø6-6

269.2

289.2

102.8

120.4

16.1

16.2

100

100

DAS-81419-2

83.6

95.8

30.5

39.1

16.9

17.9

100

100

DP-356Ø43-5

43.9

57.1

16.7

20.4

16.9

15.7

97

100

DP-3Ø5423-1

72.6

73.5

33.3

31.6

20

19.2

98.5

98

MON-89788-1

138.13134.80

52.87

57.82

17.12

18.54

100.00100.00MON-87769-7
MON-877Ø1-2

92.45
67.1

94.48
69.1

38.71
31.2

39.38
29.8

20.33
25.3

21.58
24.9

99.44
91.7

100
94.4

MON-877Ø5-6 105.6

103.1

45.3

47.6

18.2*

19.4

98.9

98.9

MON-877Ø8-9 122.7

125.8

54.7*

51.0

20.6*

19.6

98.5

98.0

MON-87751-7

134.9

64.9*

58.8

24.0

24.9

98.5

97.0

Event name

133.4

Control

Control

ControlaAverage values for each measurement endpoint are provided. Since each value was taken from original dossiers without
modification, significant figures reported are not consistent. Asterisk indicates statistically significant difference (P\0.05)

Pollen viability and size
After staining, the pollen from GM and non-GM NIL
plants was observed microscopically to determine
viability. There were no statistically significant

differences in pollen viability (staining %) of theGM soybean events and their respective non-GM NIL
controls for any of the events analyzed quantitatively(Online Resource 4). There were also no statisticaldifferences in pollen size between GM soybean

123

236

events and their respective non-GM NIL controls forany of the events analyzed quantitatively (Online
Resource 4). Some protocols used by some ofdevelopers did not assess pollen viability using aquantitative method, however no visual differences inpollen viability were reported for these events, and all
GM soybean plants across the 11 CFTs were reported
to have viable and normal-shaped pollen.

Transgenic Res (2020) 29:229–242

Miscroflora test
No statistically significant differences were observedin the number of micro-organisms (bacteria, actinomycetes and filamentous fungi) in soil collected fromGM soybean plants, compared to soil collected fromtheir non-GM controls (Online Resource 5).
Outcrossing test

Productivity of grain
Across the 11 CFTs, total number of pods, grain
weight per plant, weight of 100 grains and germination of harvested seeds were measured (J-BCH
2018c; Table 3). Statistically significant differenceswere observed in grain weight per plant and theweight of 100 grains for MON-877Ø8-9 compared tothe controls (54.7 vs. 51.0 g and 20.6 vs. 19.6 g,
respectively; Table 3), The differences in weight of
100 grains for MON-877Ø5-6 compared to thecontrol (18.2 g vs. 19.4 g; Table 3) and in grain
weight per plant for MON-87751-7 (64.9 g vs. 58.8 g;
Table 3) were also statistically significant.
Germination or seedling establishment rate
for harvested seeds
The G/SE rate of harvested seeds from both GM
soybean and the non-GM NIL controls were measured by collecting seeds at harvest and replanting
them in open plots or culture dishes (J-BCH 2018c).
For all events across the 11 CTFs, the GM soybean
and the non-GM NIL control soybeans both germinated or established at a similar rate, with rates
exceeding 90% (Table 3).
Succeeding crop and plough-in tests
To assess the potential effects of the GM soybean
plants on a succeeding crop, radish seeds wereplanted in soil from the GM or non-GM soybean
field plots (succeeding crop test) or were planted inmedia containing ground GM or non-GM soybean
plant tissue (plough-in test). In both tests, there wereno statistically significant differences observed in the
G/SE rate or dry weight of radish plants that weregrown under either assessment (Online Resource 5),
indicating that the GM soybeans did not affect theability of the succeeding crop to germinate or grow.

123

Outcrossing potential was determined using GM
soybean as pollen donor and assessing soybean seeds
obtained from non-GM control (planted adjacent to
GM soybean plots) to determine if any of the hybrid
progeny seeds contained the transgene. The outcrossing rate across all 11 GM soybean events wasconsistent and low, where outcrossing from most of
the events was 0%. The few events that were above
0% had outcrossing rates of 0.10–0.23% (Online
Resource 6), which are still within the range ofnatural outcrossing rates reported in literature.
Additional analysis of agronomic datafrom CFTs: correlation analysis
To better visualize any differences between GM
soybeans and non-GM soybeans and to identify any
potential unintended impacts, the agronomic endpoints related to competitiveness were also comparedusing two-dimensional correlation analysis (Fig. 1).
A range of variation was observed in the mean valueof each measurement endpoint for non-GM soybeans(X axis), which is also the case for GM soybeans(Y axis). The mean values between each GM soybean
and its corresponding non-GM soybean control are
not necessarily equal, but the individual data points
representing each pair are distributed around Y=X
and a strong correlation was observed in most of themeasurement endpoint (R≥0.80). Additionally, no
statistically significant differences were observed
between GM soybean and non-GM control soybean
for these endpoints. The only low correlation wasobserved in germination rate of starting seed. For thisendpoint, the difference in the conditions used forstorage or treatment of seeds used for each CFT
likely caused the variation observed here for germination rate of starting seed. Thus, it is unlikely thatthe difference in the germination rate of starting seeds
is biologically relevant.

Transgenic Res (2020) 29:229–242

237

Fig. 1 Correlation in key agronomic characteristics between
GM soybean and non-GM comparator in Japan CFT. Each pairof the mean value of the major measurement endpoints for the
11 GM soybean (Y axis) and corresponding non-GM NIL

soybean (X axis) were plotted, and Pearson’s r was calculatedby dividing the covariance of X and Y by the standard
deviations of X and Y. Dotted lines in each chart represent Y=
X

Discussion

assessment endpoints. Leveraging familiarity (forexample, understanding the nature of the crop andthe characteristics of GM traits) and existing data isvery important for being able to assess results of
CFTs and objectively assess biological relevance ofdifference observed in the receiving environment ofJapan. However, a limitation of CFT is that agronomic data from GM crops and their near isogenic
line of non-GM crops grown in Japan is currently not
publicly available to assist the assessment, whichmakes understanding biological relevance difficult.
Therefore, one goal of this paper was to summarize
and publish a comprehensive dataset from CFTs for
GM soybean previously conducted in Japan, which
will build familiarity and inform the biologicalrelevance assessment for future soybean CFTs.
In this study, CFT data from 11 GM soybean
events were collected and summarized. In each CFT,a comparative assessment of the agronomic characteristics was conducted to determine differences
between the GM crop and a near-isogenic comparator
line which were both grown under representativeenvironmental conditions and management practices
in Japan. The datasets from each CFT were used toevaluate three assessment endpoints: (1) competitiveness of the GM plant with wild plants for resources
such as nutrients, sunlight, habitat, etc.; (2) production of harmful substance that interfere with the

The ERA of GM crops in Japan aims to test the
hypothesis that the GM crop is not different than theconventional crop in terms of its potential impact on
domestic biodiversity by evaluating competitiveness,
production of harmful substances, and ability tooutcross. Other countries, with the exception ofChina, do not require an ERA with in-country CFTs
for import of grain for food and feed use. Even
though no cultivation is intended in Japan, in-country
CFTs are required for the ERA of GM crops to assess
the potential for environmental impacts if the GM
grain is unintentionally grown (for example, if grainis spilled during transportation, at port of entry). This
paper has been prepared with two goals in mind:
First, to publish a comprehensive dataset of soybean
agronomic data from GM and non-GM soybean
grown in CFTs in Japan; and second, to question thevalue of requiring in-country CFTs for cultivation
approval in Japan.
Comprehensive dataset of agronomic data
for soybeans grown in Japan environment
Any statistically significant differences detected in
the CFT need to be assessed to determine potential
for biological relevance to above mentioned three

123

238

growth of wild plants, animals, or microorganisms;
and (3) outcrossing potential with wild relatives,
resulting in introgression of transgenic DNA. Specifically, a suite of agronomic measurement endpoints(summarized in Tables 2, 3, and Online Resource 4)
were used to assess if the GM plant has increased
competitiveness. The measurement endpoints in succeeding crop test, plow-in test and microflora test
(Online Resource 5) were used to assess if the GM
crop interferes with the growth of other plants,
animals, or microbes, and the measurement endpoints
in outcrossing test (Online Resource 6) were used toassess potential for outcrossing with wild relatives.
Results from all 11 CFTs conducted in Japan fordifferent GM soybean events reported no adverse
effects on these three assessment endpoints (J-BCH
2018c). Where measurement endpoints measured
across all these comparisons reported statisticallysignificant differences between GM soybean and nonGM comparators for some events (for example, G/SE
rate, main stem length, and number of nodes; Table 2
and grain weight per plant and weight of 100 grains;
Table 3), a biological relevance assessment was
conducted.
All of the CFTs and the biological relevanceassessments were conducted independently by eachof the developers of the GM products. Although thecriteria adopted across these 11 CFTs were not
identical due to differences in field study methods
between developers, all these measurement endpoints
were determined to be comparable between GM cropand non-GM control, in a case-by-case manner. Thisaccumulated agronomic data from CFTs of GM
soybean can be used to build familiarity and informthe biological relevance assessment of future CFTs
for GM soybeans grown in Japan. Also, the ERA ofthese GM soybeans can be used to inform on the ERA
for future GM soybean events.
Informing the biological relevance assessment
It is important to understand the natural variability inagronomic endpoints for soybeans grown in Japan.
Irrespective of the introduced trait, there is expected
to be variability in measurement endpoints fordifferent agronomic parameters. This can be observedin the data presented in this study for non-GM NIL
soybeans across the 11 CFTs. The observed naturalvariation in the mean value for each agronomic

123

Transgenic Res (2020) 29:229–242

characteristic of non-GM soybeans summarized fromthese CFTs (Tables 1, 2 and Online Resource 4–6)
can serve as a reference to inform on the biologicalrelevance assessment of soybeans in future CTFs
conducted in Japan. Agronomic characteristic
between GM soybean and the non-GM comparator
could be statistically different in CFTs due to genetic
and environmental variation, as demonstrated inseveral examples above; however, the variation inagronomic characteristics of host crops grown in thetest fields can serve as a clear baseline to interpret
biological relevance of the difference identified
between GM soybean and the control. Although thedifferences in the methods across developers forcertain measurements needs to be considered (seeSupplementary information for more detail), thedataset of non-GM soybean shown here was obtained
under the common objective of CFTs and can bereferred to for biological relevance assessments in the
future. While it could be argued that there is low
genotypic diversity in the non-GM soybeans used
across these eleven CFTs (Jack, Maverick, A3244,
A3525, A5547, A3555), there is considerable environmental variation represented (9 different
environments in terms of year9site; Online Resource1). Thus, these data represent various conditions inJapan, and the dataset can be added to over time as
new data is available to increase genotypic andenvironmental diversity.
Informing the ERA for future GM soybean events
The goal of the CFT for these GM soybean events is to
identify any unintended changes from the transformation process or the introduced traits on thephenotypically observable agronomic characteristicsof the GM soybean. As shown using correlation
analysis, there are no biologically meaningful difference between GM soybeans and non-GM soybeans foragronomic endpoints related to competitiveness(Fig. 1). Moreover, the differences between GM andcorresponding non-GM soybeans (indicated by the
distance of each data point from Y=X; Fig. 1) aremuch smaller than the differences within the non-GM
soybeans (indicated by the range of X in the measured
agronomic endpoints; Fig. 1), indicating that thenatural variation within non-GM soybeans results ingreater differences in these agronomic endpoints thanthat introduced with the genetic modification.

Transgenic Res (2020) 29:229–242

The information from the eleven independent
CFTs of GM soybean summarized here supports thatthe agronomic characteristic of GM soybean iscomparable to their respective non-GM NIL soybean
comparators. This information can be used to informthe ERA for future GM soybean events, since nobiologically relevant differences that could lead toenvironmental harm in the Japanese environment
were observed irrespective of traits conferred by theinserted genes.
Assessing the value of requiring in-country CFTs
for cultivation approval in Japan
Familiarity of the crop
The basic biology of cultivated soybean is well
documented in the literature and can be leveraged forfamiliarity of safe use in Japan. Soybean is commonly considered one of the oldest cultivated crops(Hymowitz 1970) and has long history of safe use inJapan. Soybean plants are annuals and do not survive
vegetatively in geographic regions with cold wintersfrom one growing season to the next as soybean seeds
are the only survival structures (Hymowitz and Singh1987). Since soybean seeds do not retain highgermination rates and vigor for long periods, fresh,
properly grown and handled seed is required forcommercial varieties each growing season (TeKrony
1987). Conventional soybean does not possess any of
the attributes commonly associated with weeds, suchas long persistence of seed in the soil, the ability toinvade and become a dominant species in new ordiverse landscapes, or the ability to compete wellwith native vegetation (Baker 1974), and is known tohave low weediness potential (OECD 2000).
Familiarity with GM soybeans
In the ERA for a GM soybean event in Japan,
intended trait should be assessed to determine if any
plausible hypotheses can be developed for how theGM soybean could have increased weediness inJapanese environment. To date, no plausible hypotheses have been developed for ERA of GM soybean(for example, no changes in agronomic characteristics related to weediness were observed in fieldstudies conducted in other countries), and theconclusions that GM soybeans are as safe as non-239

GM soybeans is supported by decades of safe use.
CFTs were originally required to address concernsthat unanticipated phenotypic or agronomic changes
in GM crops could occur in the Japanese environment. However, the results of these comprehensive
CFTs done in Japan, which conclude that there are no
biologically relevant unintended changes in agronomic characteristics, supports a conclusion thatunintended changes in GM soybean are unlikely in
the Japanese environment. In fact, the likelihood of
having any biologically relevant differences in the
GM plant that could lead to environmental harm isremote, due to the extensive breeding, screening, andadvancement cycles that GM crops, like non-GM
crops, advance through as part of the conventional
breeding process and for commercialization (Glennet al. 2017; Prado et al. 2014). In this breeding
program, events with any unfavorable characteristics
which would limit commercial viability are eliminated and not advanced through the breeding andscreening process.
Familiarity based on existing agronomic datafrom other countries
GM crops are extensively tested for specified criteria(e.g., molecular characterization, phenotypic andagronomic performance; Glenn et al. 2017; Prado
et al. 2014) in the country where the GM crop wasdeveloped to collect data to support global regulatory
approvals. The data package submitted to regulatory
authorities usually includes agronomic characterization of GM crops collected from large multi-location
field trials. Prior to conducting the Japan CFTs, the11 GM soybean events assessed in this paper were
evaluated in multi-location field trials in the US andother countries, which provides agronomic data frombroad range of environmental conditions and agricultural ecosystems representative of where the crop
is typically grown. Furthermore, these soybean lines
all have been tested and approved for environmental
safety for growing (not only for import as in Japan) in
the US and Canada, and many have also been
approved for growing in Brazil and/or Argentina. The
extensive agronomic datasets from these multi-location field studies in other countries should betransportable and used to inform the ERA for
cultivation approval in Japan. This is especially true

123

240

Transgenic Res (2020) 29:229–242

Fig. 2 Distribution of 100 grain weight and stem length datacollected for GM soybean and non-GM comparator in Japanand US CFTs. Each pair of the mean value of the two common
measurement endpoints between Japan CFT (circle) and in US
CFTs (diamond) for the 11 GM soybean (Y axis) andcorresponding non-GM soybean (X axis) were plotted, andPearson’s r was calculated by dividing the covariance of X and
Y by the standard deviations of X and Y. Dot lines in eachchart represent Y=X

considering that CFTs in Japan are conducted at asingle site in single year (Nakai et al. 2015).
To demonstrate that the dataset obtained from CFTs
in Japan and multi-location field studies from the US are
similar in terms of results, we compared the datasetsfrom Japan and the US CFTs. Among the characteristics
tested, plant height (i.e., stem length) and weight of 100
seeds were collected in both Japan and the US by eachdeveloper, and thus were chosen as representative datato assess for similarity of results. US CFT data for theseagronomic traits were taken from publicly available
petition documents for each event (USDA-APHIS2018). As shown in Fig. 2, for both characteristics,
individual data points corresponding to each pair ofmean values for GM soybean and non-GM comparator
tested in US CFTs distributed around Y=X as didvalues from Japan CFTs, and strong correlation wasobserved (R≥0.90). A narrower range of values wasobserved in the US dataset (Fig. 2) likely because thedata is based on CFTs in multiple sites. Consistency inthe comparability between GM soybean and non-GM
control in these two agronomic endpoints obtained in
CFTs conducted in both Japan and US irrespective oftraits conferred by the inserted genes supports that thedataset collected in US is transportable and can beutilized in the for ERA in Japan.
Based on a high level of familiarity (familiarity of
the crop, familiarity with GM soybeans, and familiarity based on existing agronomic data), we proposethat the scope of the current regulatory framework inJapan, where GM maize events with certain “familiar
genes” are exempt from the CFTs in Japan and thecultivation approval considers field data obtained inother countries, is expanded to include GM soybeans.
The exemption rule for GM maize was adopted in2014, and was based on a high-level familiarity andaccumulated experience conducting ERAs for GM
maize. In the case of GM maize, it was determinedthat the agronomic data collected from field trials in
the US is not different from the agronomic datacollected from in-country CFTs. The field data of a
GM maize obtained in other countries was determined to be sufficient to inform the ERA in Japan if:(1) the mode of action of the protein derived from theinserted gene is clearly defined from the scientificpoint of view; and (2) the effect of the inserted geneis comparable to that of the other traits which havealready been approved (MAFF 2014). It is worth
noting that the scope of the exemption of CFTs in
Japan has recently been expanded to include GM
cotton in 2019 which is also based on accumulated
experience conducting ERAs for GM cotton in Japan.

123

Conclusion
In this paper, we have summarized and comparedagronomic characteristics for 11 soybean eventsassessed in CFTs in Japan. This data helps build
familiarity for the crop, by providing agronomic dataTransgenic Res (2020) 29:229–242

which was not previously publicly disclosed. Also, thiscomprehensive dataset establishes a baseline of agronomic data which can be used to assess biologicalrelevance of agronomic differences. When CFTs in
Japan are required for the events with novel genes ortraits, the familiarity of non-GM soybeans in CFTs in
Japan that have been summarized in this paper will
provide the range of natural variation in agronomic
characteristics to better evaluate biological relevance.
Furthermore, by comparing the agronomic data from
CFTs in Japan and the US, we have demonstrated thatthe agronomic data collected in multi-location fieldtrials in other countries can be used to inform the ERA
for Japan. The concept where risk assessors in one
country can use the data and assessments from othercountries to inform their own assessments is known asdata transportability (Ahmad et al. 2016; Garcia-Alonso
et al. 2014; Nakai et al. 2015). As part of problem
formulation and leveraging a science-based approach,existing data should be used to inform the risk
assessment and can help determine when a CFT in
Japan is needed to assess risk. Therefore, we proposethat the scope of the current regulatory framework inJapan, where GM maize events with certain “familiar
genes” are exempt from the CFTs in Japan and thecultivation approval considers field data obtained inother countries, is expanded to include GM soybeans.
These familiarity-based approaches to the ERAs of GM
soybean which will have potential to reduce theregulatory burden for both developers and regulatory
authorities, while still ensuring the quality of risk
assessment.
More than two decades have passed since theregulation and related risk assessment processes ofGM crop were initially developed. The assessment
frameworks in Japan and other countries have evolved
based on our experience and increasing familiarity
with GM crops and traits over time. The concept offamiliarity and the comparative assessment, which
was originally proposed long ago, has been providing
the foundation for effective and harmonized ERA.
Extensive discussion regarding how to make use ofdata that is globally relevant from ERAs and CFTs toincrease familiarity is encouraged for more scientifically sound and risk-proportionate ERA.

Acknowledgements The authors wish to acknowledge andthank Jennifer Anderson, Nicholas Storer, Debbie A. Mahadeo,

241
Pamela M. Bachman, Ernest L. Clawson and many others fortheir editorial contributions and constructive feedback. This
Project was supported by International Life Sciences InstituteJapan (ILSI Japan).
Compliance with ethical standards
Conﬂict of interest AM, HG and YT are both employed by
Dupont Production Agriscience, Bayer CropScience, and Dow
AgroSciences, respectively. MT and RO declare that they haveno conflict of interest.
Open Access This article is licensed under a Creative
Commons Attribution 4.0 International License, which permitsuse, sharing, adaptation, distribution and reproduction in any
medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative
Commons licence, and indicate if changes were made. The
images or other third party material in this article are includedin the article’s Creative Commons licence, unless indicatedotherwise in a credit line to the material. If material is notincluded in the article’s Creative Commons licence and yourintended use is not permitted by statutory regulation or exceeds
the permitted use, you will need to obtain permission directlyfrom the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/.

References
Ahmad A, Negri I, Oliveira W, Brown C, Asiimwe P, Sammons B, Horak M, Jiang C, Carson D (2016)
Transportable data from non-target arthropod field studies
for the environmental risk assessment of geneticallymodified maize expressing an insecticidal double-stranded
RNA. Transgenic Res 25:1–17. https://doi.org/10.1007/
s11248-015-9907-3
Alexander MP (1969) Differential staining of aborted andnonaborted pollen. Stain Technol 44:117–122. https://doi.
org/10.3109/10520296909063335
Asanuma Y, Jinkawa T, Tanaka H, Gondo T, Zaita N, Akashi
R (2011) Assays of the production of harmful substancesby genetically modified oilseed rape (Brassica napus L.)
plants in accordance with regulations for evaluating theimpact on biodiversity in Japan. Transgenic Res 20:91–
97. https://doi.org/10.1007/s11248-010-9398-1
Baker HG (1974) The evolution of weeds. Annu Rev Ecol Syst
5:1–24.
https://doi.org/10.1146/annurev.es.05.110174.
000245EFSA (2010) Guidance on the environmental risk assessmentof genetically modified plants. EFSA J 8:1879. https://doi.
org/10.2903/j.efsa.2010.1879
Garcia-Alonso M, Hendley P, Bigler F, Mayeregger E, Parker
R, Rubinstein C, Satorre E, Solari F, McLean MA (2014)
Transportability of confined field trial data for environmental risk assessment of genetically engineered plants: aconceptual framework. Transgenic Res 23:1025–1041.
https://doi.org/10.1007/s11248-014-9785-0

123

242
Glenn KC, Alsop B, Bell E, Goley M, Jenkinson J, Liu B,
Martin C, Parrott W, Souder C, Sparks O, Urquhart W,
Ward JM, Vicini JL (2017) Bringing new plant varieties
to market: plant breeding and selection practices advancebeneficial characteristics while minimizing unintended
changes. Crop Sci 57:2906–2921. https://doi.org/10.2135/
cropsci2017.03.0199
Hymowitz T (1970) On the domestication of the soybean. EconBot 24:408–421. https://doi.org/10.1007/bf02860745
Hymowitz T, Singh RJ (1987) Taxonomy and speciation. In:
Wilcox JR (ed) Soybeans: improvement, production, anduses. American Society of Agronomy, Madison, pp 23–48
J-BCH (2018a) Concerning the application for approval of type1 use regulations with regard to the genetically modified
plants, the production or circulation of which falls within
the jurisdiction of the Minister of Agriculture, Forestry
and Fisheries. Japan Biosafety Clearing House. http://
www.biodic.go.jp/bch/download/law/notification_maff_
280819_plant_rev1.pdf. Accessed 15 Nov 2018
J-BCH (2018b) The guidance of implementation of assessment.
Japan Biosafety Clearing House. http://www.biodic.go.jp/
bch/download/en_law/en_assessment_guidence.doc.
Accessed 15 Nov 2018
J-BCH (2018c) Japan biosafety clearing house website. Japan
Biosafety Clearing House. http://www.biodic.go.jp/bch/.
Accessed 15 Nov 2018
MAFF (2014) Partial amendments to the law concerning theapplication for approval of type 1 use regulations withregard to the genetically modified plants, the production
or circulation of which falls within the jurisdiction of the
Minister of Agriculture, Forestry and Fisheries. Ministryof Agriculture, Forestry, and Fisheries. http://www.maff.
go.jp/j/syouan/nouan/carta/c_data/notice/pdf/01_tree_
20141205.pdf. Accessed 15 Nov 2018
Nakai S, Hoshikawa K, Shimono A, Ohsawa R (2015) Transportability of confined field trial data from cultivation toimport countries for environmental risk assessment ofgenetically modified crops. Transgenic Res 24:929–944.
https://doi.org/10.1007/s11248-015-9892-6
Nickson TE (2008) Planning environmental risk assessment for
genetically modified crops: problem formulation for
stress-tolerant crops. Plant Physiol 147:494–502.
https://doi.org/10.1104/pp.108.118422
OECD (1993) Safety considerations for biotechnology: scaleup of crop plants. Organisation for Economic Co-

123

Transgenic Res (2020) 29:229–242
operation and Development. http://www.oecd.org/dataoecd/26/26/1958527.pdf
OECD (2000) Consensus document on the biology of Glycinemax (L.) Merr. (Soybean). Organisation for Economic Cooperation and Development
Prado JR, Segers G, Voelker T, Carson D, Dobert R, Phillips J,
Cook K, Cornejo C, Monken J, Grapes L, Reynolds T,
Martino-Catt S (2014) Genetically engineered crops: from
idea to product. Annu Rev Plant Biol 65:769–790.
https://doi.org/10.1146/annurev-arplant-050213-040039
Raybould A, Macdonald P (2018) Policy-led comparativeenvironmental risk assessment of genetically modified
crops: testing for increased risk rather than profilingphenotypes leads to predictable and transparent decisionmaking. Front Bioeng Biotechnol 6:43. https://doi.org/10.
3389/fbioe.2018.00043
RDA (2014) Consolidated notice for transboundary movement,
etc. of living modified organisms. Rural Development
Administration. http://www.biosafety.or.kr/03_data/001/
통합고시.pdf. Accessed 15 Nov 2018
TeKrony DM (1987) Seed production and technology. In:
Wilcox JR (ed) Soybeans: improvement, production, anduses. American Society of Agronomy, Madison, pp 295–
354
USDA (2013) Japan agricultural biotechnology annual report:
Japan’s approval remains a key for commercial release of
GE crops. United States Department of Agriculture.
http://gain.fas.usda.gov/Recent%20GAIN%20Publica
tions/Agricultural%20Biotechnology%20Annual_Tokyo_
Japan_8-27-2013.pdf. Accessed 15 Nov 2018
USDA-APHIS (2018) Animal and plant health inspection
service (APHIS) website. United States Department ofAgriculture, Animal and Plant Health Inspection Service.
https://www.aphis.usda.gov/aphis/home/. Accessed 15
Nov 2018
Yogo Y (2010) Environmental risk assessment for type I use ofgenetically modified crops. J Pestic Sci 37:377–382.
https://doi.org/10.1584/jpestics.35.377
Publisher's Note Springer Nature remains neutral withregard to jurisdictional claims in published maps andinstitutional affiliations.