| Literature DB >> 30110188 |
Abstract
This study assesses the economic and environmental impacts that have arisen from the adoption and use of genetically modified (GM) herbicide tolerant (HT) and insect resistant (IR) soybeans in South America in the five years since first planted in 2013/14. A total of 73.6 million hectares have been planted to soybeans containing these traits since 2013/14, with farmers benefiting from an increase in income of $7.64 billion. For every extra $1 spent on this seed relative to conventional seed, farmers have gained an additional $3.88 in extra income. These income gains have arisen from a combination of higher yields (+ 9.2% across the four countries using the technology) and lower costs of weed and pest control. The seed technology has reduced pesticide spraying by 10.44 million kg (-15.1%) and, as a result, decreased the environmental impact associated with herbicide and insecticide use on these crops (as measured by the indicator, the Environmental Impact Quotient (EIQ)) by 30.6%. The technology has also facilitated important cuts in fuel use and tillage changes, resulting in a significant reduction in the release of greenhouse gas emissions from the GM cropping area. In 2017/18, this was equivalent to removing 3.3 million cars from the roads.Entities:
Keywords: GM crop impacts; Intacta soybeans; farm income; yield
Mesh:
Substances:
Year: 2018 PMID: 30110188 PMCID: PMC6290983 DOI: 10.1080/21645698.2018.1479560
Source DB: PubMed Journal: GM Crops Food ISSN: 2164-5698 Impact factor: 3.074
GM Intacta soybean plantings 2013/14–2017/18 (million ha).
| Country | 2013/14 | 2014/15 | 2015/16 | 2016/17 | 2017/18 |
|---|---|---|---|---|---|
| Argentina | 0.6 (3%) | 1.13 (6%) | 2.91 (15%) | 3.16 (17%) | 3.84 (20%) |
| Brazil | 1.16 (4%) | 5.87 (18%) | 12.76 (38%) | 17.29 (51%) | 18.17 (52%) |
| Paraguay | 0.01 (3%) | 0.78 (23%) | 1.22 (36%) | 1.48 (45%) | 1.53 (45%) |
| Uruguay | 0.26 (18%) | 0.22 (17%) | 0.28 (25%) | 0.36 (33%) | 0.43 (33%) |
Sources: derived from Argenbio, ISAAA, Monsanto, Kleffmann Note 2017/18 provisional estimates
Farm income gains derived from GM Intacta soybeans (‘000$).
| Country | 2017/18 | Cumulative 2013/14–17/18 | Cumulative area planted to Intacta (’000 ha) |
|---|---|---|---|
| Argentina | 259.4 | 756.8 | 11,632 |
| Brazil | 1,904.0 | 6,111.5 | 55,254 |
| Paraguay | 226.3 | 663.4 | 5,114 |
| Uruguay | 38.7 | 108.3 | 1,556 |
| 73,556 |
Sources: Brookes G and Barfoot P (2017a[2] and updated)
Additional soybean production from positive yield effects of Intacta soybeans (‘000 tonnes).
| Country | 2017/18 | Cumulative 2013/14–17/18 |
|---|---|---|
| Argentina | 798 | 2,480 |
| Brazil | 5,232 | 15,692 |
| Paraguay | 528 | 1,638 |
| Uruguay | 89 | 302 |
Sources: Brookes G and Barfoot P (2017a[2] and updated)
Impact of using Intacta soybeans changes in South America: changes in herbicide and insecticide use and associated environmental impact (as measured by EIQ indicator) 2013/14-2017/18
| Trait | Change in volume of active ingredient used (million kg) | Change in field EIQ impact (in terms of million field EIQ/ha units) | Percent Change in active ingredient use on GM crops | Percent change in environmental impact associated with herbicide & insecticide use on GM crops | Cumulative Intacta area 2013/14-2017/18 (million ha) |
|---|---|---|---|---|---|
| GM herbicide tolerance | + 0.55 | −412.8 | + 0.2 | −10.3 | |
| GM insect resistance | −10.99 | −976.4 | −15.9 | −21.5 | |
| Totals | −10.44 | −1,389.2 | −15.1 | −30.6 | 73.56 |
Source: Derived from Brookes G and Barfoot P[3]
Permanent carbon sequestration impacts 2013/14–2017/18 arising from reduced fuel use: car equivalents.
| Crop/trait/country | Permanent fuel saving (million litres) | Permanent reduced carbon dioxide emissions arising from lower fuel use (million kg of carbon dioxide) | Permanent lower emissions from reduced fuel use: as average family car equivalents removed from the road for a year (‘000) |
|---|---|---|---|
| Argentina | 222.4 | 593.7 | 366.7 |
| Brazil | 307.1 | 820.1 | 506.5 |
| Paraguay, Uruguay | 74.9 | 199.9 | 123.5 |
| Argentina | 9.8 | 26.1 | 16.1 |
| Brazil | 152.0 | 405.7 | 250.6 |
| Paraguay, Uruguay | 8.3 | 22.4 | 13.8 |
Notes: Assumption: an average family car in 2017 produces 129 grams of carbon dioxide per km. A car does an average of 12,553 km/year and therefore produces 1,619 kg of carbon dioxide/year
Source: Brookes G and Barfoot P (2017b[3]) and updated
Carbon sequestration impacts 2017/18: car equivalents.
| Crop/trait/country | Permanent reduced carbon dioxide emissions arising from lower fuel use (million kg of carbon dioxide) | Permanent lower emissions from reduced fuel use: as average family car equivalents removed from the road for a year (‘000) | Potential additional soil carbon sequestration (million kg of carbon dioxide) | Soil carbon sequestration gains as average family car equivalents removed from the road for a year (‘000s) |
|---|---|---|---|---|
| Argentina | 141.80 | 87.60 | 1,437.38 | 887.82 |
| Brazil | 269.95 | 166.74 | 2,736.43 | 1,690.20 |
| Paraguay, Uruguay | 57.73 | 35.66 | 584.78 | 361.20 |
| Argentina | 8.60 | 5.31 | 0 | 0 |
| Brazil | 122.30 | 75.54 | 0 | 0 |
| Paraguay, Uruguay | 5.40 | 3.34 | 0 | 0 |
Notes: Assumption: an average family car in 2017 produces 129 grams of carbon dioxide per km. A car does an average of 12,553 km/year and therefore produces 1,619 kg of carbon dioxide/year
Source: Brookes G and Barfoot P (2017b[3]) and updated
| Country | Area of trait (000ʹ ha) | Yield assumption % change | Base yield (tonnes/ha) | Farm level price: $/tonne) | Cost of tech ($/ha) | Impact on costs, net of cost of tech ($/ha) | Change in farm income ($/ha) | Change in farm income at national level (‘000 $) | Production impact (‘000 tonnes) |
|---|---|---|---|---|---|---|---|---|---|
| Brazil | 18,471 | + 9.4 | 3.06 | 316 | + 37.59 | −13.91 | + 104.78 | 1,904,024 | 5,232 |
| Paraguay | 1,530 | + 11.5 | 2.99 | 318 | + 24.75 | −38.04 | + 147.88 | 226,256 | 528 |
| Argentina | 3,840 | + 7.1 | 2.93 | 248 | + 24.71 | −16.02 | + 67.54 | 259,367 | 798 |
| Uruguay | 429 | + 7.0 | 2.96 | 333 | + 29.87 | −21.07 | + 90.29 | 38,734 | 89 |
Sources:
Areas planted: ISAAA, Kleffmann, Monsanto
Yield gain: Monsanto pre-commercial trials in 2011 and 2013 plus post production farm surveys (unpublished post market monitoring: Monsanto)
Cost of technology: Monsanto, Kleffmann
Weed control cost comparisons: Brookes and Barfoot (2017a) which compares GM HT weed control practices derived from Kleffmann usage data, with conventional weed control practices that would deliver similar levels of weed control as the GM HT system as advised by extension and industry sources (see below)
Insecticide use changes based on Monsanto pre-commercial trials in 2011 and 2013 plus post production farm surveys (unpublished post market monitoring: Monsanto) and Kleffmann insecticide use data
Notes:
1. Weed cost changes (GM HT versus conventional): Brazil: -$40.05/ha, Argentina: -$26.13/ha, Paraguay: -$22.75/ha, Uruguay: -$36.94/ha
2. Insecticide cost changes: Brazil: $11.46/ha, Argentina: $14.6/ha, Paraguay: $40.04/ha, Uruguay: $14/ha
3. The cost of the technology represents the value paid by farmers to the seed supply chain including sellers of seed to farmers, seed multipliers, plant breeders, distributors and the GM technology providers. It does not represent the value accruing to the technology providers but to the whole seed supply chain. The range in values across countries for cost of technology reflects reasons such as the price charged by different stages in the supply chain, exchange rates and average seed rates
4. Yield gains derive from a combination of reduction of pest damage (IR trait) and the positioning of the HT trait in the DNA of the germplasm of Intacta soybean varieties
| Country | Area of trait (‘000 ha) | Average ai use GM crop (kg/ha) | Average ai use if conventional (kg/ha) | Average field EIQ/ha GM crop | Average field EIQ/ha if conventional | Aggregate change in ai use (‘000 kg) | Aggregate change in field EIQ/ha units (millions) |
|---|---|---|---|---|---|---|---|
| Brazil | 18,471 | 1.43 | 1.6 | 30.65 | 47.9 | 3,134.0 | 313.5 |
| Paraguay | 1,530 | 0.23 | 0.31 | 6.18 | 9.28 | 122.4 | 1.9 |
| Argentina | 3,840 | 0.23 | 0.31 | 6.18 | 9.28 | 307.2 | 4.8 |
| Uruguay | 429 | 0.23 | 0.31 | 6.18 | 9.28 | 34.3 | 0.5 |
Sources: Insecticide use changes based on Monsanto pre-commercial trials in 2011 and 2013 plus post production farm surveys (unpublished post market monitoring: Monsanto) and Kleffmann insecticide use data
Note:
1. The area on which insecticide use changes are calculated in each country is constrained to the lower of the area planted to Intacta soybeans or the maximum area traditional treated with insecticides for control of the pests that Intacta soybeans provides control. For Brazil and Paraguay, the maximum area treated is assumed to be 30% of the total crop and in Argentina and Paraguay, it is 40% of the total crop
2. The insecticide savings relate only to savings associated with treatments that targeted the pests that the Intacta technology controls and do not relate to total insecticide use. This is deliberate because total insecticide use includes use of insecticides applied for control of pests that the Intacta technology does not target. Use of insecticides for this purpose will vary on a yearly basis according to pest pressures. The baseline assumptions for what insecticides are used for control of pests now controlled by Intacta technology, their typical usage levels and frequency of application are based on Kleffmann data from the immediate years before Intacta was commercially available and field-based experience of Monsanto in-country staff
| Active ingredient (kg/ha) | Field EIQ/ha value | |
|---|---|---|
| 3.59 | 54.53 | |
| Source: Kleffmann dataset on pesticide use 2015/16 | ||
| Glyphosate | 2.27 | 34.80 |
| Metsulfuron | 0.03 | 0.50 |
| 2 4 D | 0.4 | 8.28 |
| Imazethapyr | 0.10 | 1.96 |
| Diflufenican | 0.03 | 0.29 |
| Clethodim | 0.19 | 3.23 |
| Glyphosate | 2.27 | 34.80 |
| Dicamba | 0.12 | 3.04 |
| Acetochlor | 1.35 | 26.87 |
| Haloxifop | 0.18 | 4.00 |
| Sulfentrazone | 0.19 | 2.23 |
| Glyphosate | 2.27 | 34.80 |
| Atrazine | 1.07 | 24.50 |
| Bentazon | 0.60 | 11.22 |
| 2 4 D ester | 0.4 | 6.12 |
| Imazaquin | 0.024 | 0.37 |
| Glyphosate | 2.27 | 34.80 |
| 2 4 D amine | 0.4 | 8.28 |
| Flumetsulam | 0.06 | 0.94 |
| Fomesafen | 0.25 | 6.13 |
| Chlorimuron | 0.05 | 0.96 |
| Fluazifop | 0.12 | 3.44 |
| Glyphosate | 2.27 | 34.80 |
| Metsulfuron | 0.03 | 0.50 |
| 2 4 D amine | 0.8 | 16.56 |
| Imazethapyr | 0.1 | 1.96 |
| Haloxifop | 0.18 | 4.00 |
| Glyphosate | 2.27 | 34.80 |
| Metsulfuron | 0.03 | 0.50 |
| 2 4 D amine | 0.8 | 16.56 |
| Imazethapyr | 0.1 | 1.96 |
| Clethodim | 0.24 | 4.08 |
Sources: AAPRESID, Kleffmann AMIS Global, Monsanto Argentina
| Active ingredient (kg/ha) | Field EIQ/ha value | |
|---|---|---|
| 3.10 | 48.95 | |
| Source: Kleffmann dataset on pesticide use 2015/16 | ||
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Clomozone | 0.93 | 18.26 |
| Diclosulam | 0.03 | 0.29 |
| Imazethapyr | 0.3 | 5.88 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| 3.94 | 70.45 | |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Sulfentrazone | 0.36 | 4.22 |
| Diclosulam | 0.03 | 0.29 |
| Cloransulam | 0.04 | 0.45 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| Haloxyfop | 0.05 | 1.11 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Imazethapyr | 0.3 | 5.88 |
| Diclosulam | 0.03 | 0.29 |
| Cloransulam | 0.04 | 0.45 |
| Fomesafen | 0.2 | 4.95 |
| Clethodim | 0.2 | 3.40 |
| Haloxyfop | 0.05 | 1.11 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Chlorimuron | 0.04 | 0.77 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Clomozone | 0.93 | 18.26 |
| Diclosulam | 0.03 | 0.29 |
| Imazethapyr | 0.3 | 5.88 |
| Lactofen | 0.07 | 2.90 |
| Haloxyfop | 0.05 | 1.11 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Imazethapyr | 0.3 | 5.88 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| 2.98 | 51.90 | |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Cloransulam | 0.04 | 0.45 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| Haloxyfop | 0.05 | 1.11 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Diclosulam | 0.03 | 0.29 |
| Cloransulam | 0.04 | 0.45 |
| Fomesafen | 0.2 | 4.95 |
| Clethodim | 0.2 | 3.40 |
| Haloxyfop | 0.05 | 1.11 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Chlorimuron | 0.04 | 0.77 |
| Lactofen | 0.07 | 2.90 |
| Clethodim | 0.2 | 3.40 |
| Glyphosate | 1.89 | 28.97 |
| 2 4 D | 0.52 | 10.75 |
| Imazethapyr | 0.3 | 5.88 |
| Lactofen | 0.07 | 2.90 |
| Haloxyfop | 0.05 | 1.11 |
1. Sources: Kleffmann AMIS Global, Monsanto Brazil
2. Note: Weighting: relatively high weed levels 60%: relatively low weed problems 40%