Global Impact of Biotech Crops: Socio-Economic and Environmental Effects, 1996-2006
Graham Brookes and Peter Barfoot
PG Economics Ltd., Dorchester, UK
Genetically modified (GM) crops have been grown commercially on a substantial scale for eleven years. This paper updates the assessment of the impact this technology is having on global agriculture from both economic and environmental perspectives. It examines specific global economic impacts on farm income and environmental impacts associated with pesticide usage and greenhouse gas (GHG) emissions for each of the countries where GM crops have been grown since 1996. The analysis shows that there have been substantial net economic benefits at the farm level amounting to $6.94 billion in 2006 and $33.8 billion for the eleven-year period (in nominal terms). The technology has reduced pesticide spraying by 286 million kg and, as a result, decreased the environmental impact associated with herbicide and insecticide use on these crops by 15.4%. GM technology has also significantly reduced the release of GHG emissions from this cropping area, which, in 2006, was equivalent to removing 6.56 million cars from the roads.
Key words: yield, cost, income, environmental impact quotient, carbon sequestration, GM crops.Introduction
This article presents the findings of research into the global economic and environmental impact of GM crops since their commercial introduction in 1996. It updates the findings of earlier analyses presented by the authors in AgBioForum 8(2&3) and 9(3).1
The economic impact analysis concentrates on farm income effects because this is a primary driver of adoption amongst farmers (both large commercial and small-scale subsistence). The environmental impact analysis focuses on the environmental impacts associated with changes in the amount of insecticides and herbicides applied to the GM crops relative to conventionally grown alternatives. The analysis also examines the contribution of GM crops towards reducing global greenhouse gas (GHG) emissions. This arises from reduced tractor fuel consumption and additional soil sequestration (storage) associated with reduced/no-tillage cultivation2 facilitated by the application of GM herbicide-tolerant (GM HT) technology.
The report is based largely on extensive analysis of existing farm-level impact data from GM crops. Primary data for impacts of commercial cultivation were not available for every crop, in every year, or for each country, but all identified, representative, previous research has been utilized. The findings of this research have been used as the basis for the analysis presented,3 although, where relevant, primary analysis has been undertaken from base data, most notably in relation to the environmental impacts.
The analysis presented is largely based on the average performance and impact recorded in different crops. The economic performance and environmental impact of the technology at the farm level vary widely, both between and within regions/countries. As a result, the impact of this technology and any new technology, GM or otherwise, is subject to variation at the local level. Thus, the performance and impact should be considered on a case-by-case basis in terms of crop and trait combinations. This study examines the impact of the technology at the trait and crop level, including where stacked traits are available to farmers.
Agricultural production systems are dynamic and vary with time. This analysis seeks to address this issue, wherever possible, by comparing GM production systems with the most likely conventional alternative that could provide competitive levels of efficacy, if GM technology had not been available. This approach has been used by other researchers (e.g., Sankula, 2006; Sankula & Blumenthal, 2004).
Farm Income Effects
The methodology used for assessing the farm-level income impact has been to review existing literature, from as many years of relevant comparable data as possible, and to use the findings as the basis for the impact estimates over the period examined. All values presented are nominal for the year shown. The base currency used is the US dollar and all financial impacts in other currencies have been converted to US dollars at prevailing annual average exchange rates for each year. The approach reflects 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 labor),4 crop quality (e.g., 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 for facilitating the planting of a second crop in a season (e.g., second crop soybeans in Argentina following wheat that, in the absence of the GM HT seed, would most likely not have 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 the application of actual (average) farm prices for each year, the analysis also indirectly takes into account the possible impact of GM crop adoption on global crop supply and world prices.
This approach may both overstate or understate the real impact of GM technology for some trait, crop, and country combinations. However, since impact data for every trait, crop, location, and year are not available, the authors have had to extrapolate available impact data to years for which no data are available. Therefore, the authors acknowledge that this represents a weakness of the research. However, the use of current prices does incorporate some dynamic degree into the analysis that would otherwise be missing if constant prices had been used. Where yield impacts have been identified for specific years, these have been used. Hence, the analysis takes into account variation in the impact of the technology on yield according to its effectiveness in dealing with (annual) fluctuations in pest and weed infestation levels.5 Nevertheless, much of the reviewed literature only contains an analysis for one or a limited number of years. Where analysis is this limited, the impacts identified have been converted into a percentage change impact and applied to all other years on the basis of the prevailing average yield recorded. For example, if a study identified a yield gain of 5% in year one, this 5% yield increase was then applied to the average yield recorded in each other year. If more than one study identified different levels of yield impact, the more conservative yield impacts have been used. For example, in relation to the impact of GM insect resistant (GM IR) cotton in the United States, analysis by Sankula and Blumenthal (2004) put the average positive yield impact of the first generation of the trait (known by its trade name as Bollgard I) at +9%, while the average yield impact based on Marra, Pardey, and Alston (2002) is +11%; the yield impact used in this paper was +9%.6 More specific examples of how this methodology has been applied are presented in Appendix 1. The key impact assumptions used for the analysis are summarized in Appendix 2.
GM technology has had a very positive impact on farm income derived from a combination of enhanced productivity and efficiency gains (Table 1). In 2006, the direct global farm income benefit from GM crops was $6.94 billion. This is equivalent to having added 3.8% to the value of global production of the four main crops of soybeans, maize, canola, and cotton. Since 1996, farm incomes have increased by $33.8 billion.
Table 1. Global farm income benefits from growing GM crops, 1996-2006 ($ million).
The largest gains in farm income have arisen in the soybean sector, largely from cost savings. The $3 billion additional income generated by GM HT soybeans in 2006 has been equivalent to adding 6.7% to the value of the crop in the GM-growing countries or adding the equivalent of 5.6% to the $55 billion value of the global soybean crop in 2006. These economic benefits should, however, be placed within the context of a significant increase in the level of soybean production in the main GM-adopting countries. Since 1996, the soybean area in the leading soybean-producing countries of the United States, Brazil, and Argentina increased by 60%.
Substantial gains have also arisen in the cotton sector through a combination of higher yields and lower costs. In 2006, cotton farm income levels in the GM-adopting countries increased by $2.15 billion and since 1996, the sector has benefited from an additional $9.6 billion. The 2006 income gains are equivalent to adding 13.1% to the value of the cotton crop in these countries, or 7.8% to the $27.3 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 maize and canola sectors. The combination of GM IR and GM HT technology in maize has boosted farm incomes by $4.74 billion since 1996. In the North American canola sector, an additional $1.1 bIllion has been generated.
Table 2 summarizes farm income impacts in key GM adopting countries. This highlights the important farm income benefit arising from GM HT soybeans in South America (Argentina, Brazil, Paraguay, and Uruguay), GM IR cotton in China and India, and a range of GM cultivars in the United States. It also illustrates the growing level of farm income benefits being obtained in South Africa, the Philippines, and Mexico.
Table 2. GM crop farm income benefits in selected countries, 1996-2006 ($ million).
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 2006, just over half of the farm income benefits (53%) have been earned by developing-country farmers. The vast majority of these income gains for developing-country farmers have been from GM IR cotton and GM HT soybeans.7 Over the eleven years, 1996-2006, the cumulative farm income gain derived by developing country farmers was $16.4 billion (48.5% of the total).
Table 3. GM crop farm income benefits in developing versus developed countries, 2006 ($ million).
Examining the cost farmers pay for accessing GM technology, Table 4 shows that across the four main GM crops, the total cost in 2006 was equal to 28% of the total technology gains (inclusive of farm income gains plus cost of the technology payable to the seed supply chain).8
Table 4. Cost of accessing GM technology relative to the total farm income benefits, 2006 ($ million).
For farmers in developing countries the total cost was equal to about 17% of total technology gains, while it was equal to 38% for farmers in developed countries. While circumstances vary between countries, the higher share of total technology gains accounted for by farm income gains in developing countries relative to the farm income share in developed countries reflects factors such as weaker provision and enforcement of intellectual property rights in developing countries.
In addition to these quantifiable direct impacts on farm profitability, there have been other important, indirect impacts that are more difficult to quantify (e.g., facilitation of adoption of reduced/no-tillage systems, reduced production risk, convenience, reduced exposure of farmers and farm workers to pesticides, improved crop quality). These less tangible benefits have often been cited by GM adopting farmers as having been important influences for adoption of the technology, although studies that have examined and attempted to quantify these impacts have, to date, been few in number. As such, this category of impact has not been analyzed in this paper and therefore represents a limitation of the methodology. It does, however, suggest that the farm income benefits quantified are conservative.
Environmental Impacts from Insecticide and Herbicide Use Changes
The most common way in which changes in pesticide use with GM crops have been presented is in terms of the volume (quantity) of pesticide applied. While comparisons of total pesticide volume used in GM and non-GM crop production systems can be a useful indicator of environmental impacts, it is an imperfect measure because it does not account for differences in the specific pest control programs used in GM and non-GM cropping systems. For example, different specific products used in GM versus conventional crop systems, differences in the rate of pesticides used for efficacy, and differences in the environmental characteristics (mobility, persistence, etc.) are masked in general comparisons of total pesticide volumes used.
To provide a more robust measurement of the environmental impact of GM crops, the analysis presented below includes both an assessment of pesticide active ingredient use, as well as an assessment of the specific pesticides used via an indicator known as the Environmental Impact Quotient (EIQ). This universal indicator, developed by Kovach, Petzoldt, Degni, and Tette (1992) and updated annually, effectively integrates the various environmental impacts of individual pesticides into a single ‘field value per hectare.’ This provides a more balanced assessment of the impact of GM crops on the environment as it draws on all of the key toxicity and environmental exposure data related to individual products, as applicable to impacts on farm workers, consumers, and ecology, and provides a consistent and comprehensive measure of environmental impact. Readers should note that the EIQ is an indicator only and therefore does not take into account all environmental issues and impacts.
The EIQ value is multiplied by the amount of pesticide active ingredient (ai) used per hectare to produce a field EIQ value. For example, the EIQ rating for glyphosate is 15.3. By using this rating multiplied by the amount of glyphosate used per hectare (e.g., a hypothetical example of 1.1 kg applied per ha), the field EIQ value for glyphosate would be equivalent to 16.83/ha.
The EIQ indicator used is therefore a comparison of the field EIQ/ha for conventional versus GM crop-production systems, with the total environmental impact or load of each system a direct function of respective field EIQ/ha values and the area planted to each type of production (GM versus non-GM). The use of environmental indicators is commonly used by researchers, and the EIQ indicator has been, for example, cited by Brimner, Gallivan, and Stephenson (2004) in a study comparing the environmental impacts of GM and non-GM canola and by Kleiter et al. (2005).
The EIQ methodology was used to calculate and compare typical EIQ values for conventional and GM crops and then aggregate these values to a national level. The level of pesticide use on the respective areas planted to conventional and GM crops in each year was compared with the level of pesticide use that would otherwise have probably occurred if the whole crop, in each year, had been produced using conventional technology. This is based on the approach used by Sankula and Blumenthal (2004) and Sankula (2006)9 that identifies and utilizes typical herbicide or insecticide treatment regimes for conventional and GM crops provided by extension and research advisors in each sector/country. This approach was selected to address gaps in the availability of herbicide or insecticide usage data in most countries that differentiate between GM and conventional crops. Additionally, this allows reasonably representative comparisons to be made between GM and non GM cropping systems when GM accounts for a large proportion of the total crop-planted area. For example, in the case of soybeans in several countries, more than 60% of the total soybean crop-planted area is GM. A comparison of the production practices of these two groups would, however, not produce a reasonably representative comparison of the GM versus conventional alternative because the remaining non-adopters are likely to be farmers in a region characterized by lower than average weed or pest pressures or with a tradition of less-intensive production systems. Hence, their levels of pesticide use are likely to be lower than the average pesticide-use level that would otherwise occur if the entire crop was planted to conventional cultivars (i.e., the GM crop area reverted back to conventional cultivars).
GM crops have contributed to a significant reduction in the environmental impact of production agriculture on the areas devoted to GM crops (Table 5). Since 1996, the use of pesticides on the GM crop area was reduced by 286 million kg of active ingredient, a 7.9% reduction, and the overall environmental impact associated with herbicide and insecticide use on these crops was reduced by 15.4%. In absolute terms, the largest environmental gain has been associated with the adoption of GM HT soybeans and reflects the large share of global soybean plantings accounted for by GM soybeans. The volume of herbicides used in GM soybean crops decreased by 62.4 million kg (1996-2006), a 4.4% reduction, and, the overall environmental impact associated with herbicide use on these crops decreased by 20.4% (relative to the volume that would have probably been used if this cropping area had been planted to conventional soybeans). It should be noted that in some countries, such as in South America, the adoption of GM HT soybeans coincided with increases in the volume of herbicides used relative to historic levels. This largely reflects the facilitating role of the GM HT technology in accelerating and maintaining the switch away from conventional tillage to no/low-tillage production systems with their inherent other environmental benefits (notably reductions in GHG emissions&emdash;see next section—and reduced soil erosion). Despite this net increase in the volume of herbicides used in some countries, the associated environmental impact (as measured by the EIQ methodology) still fell as farmers switched to herbicides with a more environmentally benign profile.
Table 5. Impact of changes in the use of herbicides and insecticides from growing GM crops globally, 1996-2006.
Major environmental gains have also been derived from the adoption of GM IR cotton. These gains were the largest of any crop on a per-hectare basis. Since 1996, farmers have used 128.4 million kg less insecticide in GM IR cotton crops (a 22.9% reduction), and this has reduced the associated environmental impact of insecticide use on this crop area by 24.6%. Important environmental gains have also arisen in the maize and canola sectors. In the maize sector, herbicide and insecticide use decreased by 54.9 million kg and the associated environmental impact of pesticide use on this crop area decreased due to a combination of reduced insecticide use (5.3%) and a switch to more environmentally benign herbicides (4.6%). In the canola sector, farmers reduced herbicide use by 7.9 million kg (a 12.6% reduction) and the associated environmental impact of herbicide use on this crop area fell by 24% (due to a switch to more environmentally benign herbicides).
The impact of changes in insecticide and herbicide use at the country level (for the main GM-adopting countries) is summarized in Table 6.
Table 6. Changes in the ‘environmental impact’ from changes in pesticide use associated with GM crop adoption in selected countries, 1996-2006 (% reduction in field EIQ values).
In terms of the division of the environmental benefits associated with less insecticide and herbicide use for farmers in developing countries relative to farmers in developed countries, Table 7 shows that just over half of the environmental benefits (1996-2006) associated with lower insecticide and herbicide use have been in developing countries (52%). The vast majority of these environmental gains have been from the use of GM IR cotton and GM HT soybeans.
Table 7. GM crop environmental benefits from lower insecticide and herbicide use in developing versus developed countries, 1996-2006.
Impact on Greenhouse Gas Emissions
Reductions in the level of GHG emissions from GM crops derive from two principle sources (Conservation Technology Information Center [CTIC], 2002; Fabrizzi, Morónc, & García, 2003; Jasa, 2002; Johnson et al., 2005; Lazarus & Selley, 2005; Liebig et al., 2005; Reicosky, 1995; Robertson, Paul, & Harwood, 2000; West & Post, 2002). First, GM crops contribute to a reduction in fuel use due to less-frequent herbicide or insecticide applications and a reduction in the energy use in soil cultivation. For example, Lazarus and Selley (2005) estimated that one pesticide spray application uses 1.045 liters of fuel, which is equivalent to 2.87 kg/ha of carbon dioxide emissions. In this analysis we used the conservative assumption that only GM IR crops reduced spray applications and, ultimately, GHG emissions.
In addition to the reduction in the number of herbicide applications, there has been a shift from conventional tillage to reduced/no till. This has had a marked impact on tractor fuel consumption due to energy-intensive cultivation methods being replaced with no/reduced tillage and 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.10 Before the introduction of GM HT soybean cultivars, no-tillage (NT) systems were practiced by some farmers using a number of herbicides and with varying degrees of success. The opportunity for growers to control weeds with a non-residual foliar herbicide as a “burndown” pre-seeding treatment followed by a post-emergent treatment when the soybean crop became established has made the NT system more reliable, technically viable, and commercially attractive. These technical advantages, combined with the cost advantages, have contributed to the rapid adoption of GM HT cultivars and the near doubling of the NT soybean area in the United States (also more than a five-fold increase in Argentina). In both countries, GM HT soybeans are estimated to account for more than 95% of the NT soybean crop area.
Substantial growth in NT production systems have also occurred in Canada, where the NT canola area increased from 0.8 million ha to 2.6 million ha (equal to about half of the total canola area) between 1996 and 2005 (95% of the NT canola area is planted with GM HT cultivars). Similarly the area planted to NT in the US cotton crop increased from 0.2 million ha to 1 million ha over the same period (of which 86% is planted to GM HT cultivars).
The fuel savings we used resulting from changes in tillage systems are drawn from estimates from studies by Jasa (2002) and CTIC (2002). The adoption of NT farming systems is estimated to reduce cultivation fuel usage by 32.52 liters/ha compared with traditional conventional tillage and 14.7 liters/ha compared with (the average of) reduced tillage cultivation. In turn, this results in reductions of carbon dioxide emissions of 89.44 kg/ha and 40.43 kg/ha, respectively.
Secondly, the use of NT and reduced-till farming systems that utilize less plowing increase the amount of organic carbon in the form of crop residue that is stored or sequestered in the soil. This carbon sequestration reduces carbon dioxide emissions to the environment. Rates of carbon sequestration have been calculated for cropping systems using normal tillage and reduced tillage and these were incorporated in our analysis on how GM crop adoption has played an important facilitative role in increasing carbon sequestration, and ultimately, on reducing the release of carbon dioxide into the atmosphere. Of course, the amount of carbon sequestered varies by soil type, cropping system, and eco-region. In North America, the International Panel on Climate Change estimates that the conversion from conventional-tillage to no tillage (NT) systems stores between 50 kg carbon/ha-1 yr and 1,300 kg carbon/ha-1 yr (average 300 kg carbon/ha-1 yr). In the analysis presented below, a conservative saving of 300 kg carbon/ha-1 yr was applied to all NT agriculture and 100 kg carbon/ha-1 yr was applied to reduced-tillage agriculture. Where some countries aggregate their no- and reduced-till data the reduced-tillage saving value of 100 kg carbon/ha-1 yr was used. One kg of carbon sequestered is equivalent to 3.67 kg of carbon dioxide. These assumptions were applied to the reduced pesticide spray applications data on GM IR crops, derived from the farm-income literature review, and the GM HT crop areas using no/reduced tillage (limited to the GM HT soybean crops in North and South America and GM HT canola crop in Canada).11
Table 8 summarizes the impact on GHG emissions associated with the planting of GM crops between 1996 and 2006. In 2006, the permanent carbon dioxide savings from reduced fuel use associated with GM crops was 1.2 billion kg. This is equivalent to removing 540,000 cars from the road for a year.
Table 8. Impact of GM crops on carbon sequestration impact, 2006 (car equivalents).
The additional soil carbon sequestration gains resulting from reduced tillage with GM crops accounted for a reduction in 13.5 billion kg of carbon dioxide emissions in 2006. This is equivalent to removing 6 million cars from the roads for a year. In total, the carbon savings from reduced fuel use and soil carbon sequestration in 2006 were equal to removing 6.56 million cars from the road (equal to 25% of all registered private cars in the United Kingdom).
This article quantified the cumulative global impact of GM technology on farm income, pesticide usage, and GHG emissions from 1996 to 2006. The analysis shows that there have been substantial economic benefits at the farm level, amounting to a cumulative total of $33.8 billion. Just over half of this has been derived by farmers in developing countries. GM technology has also resulted in 286 million kg less pesticide use by growers and a 15.4% reduction in the environmental impact associated with insecticide and herbicide use on the GM crop area. GM crops have also made a significant contribution to facilitating a reduction in GHG emissions, equal to a 14.76 billion kg of carbon dioxide in 2006. This is the equivalent of removing 6.56 million cars from the roads for a year.
The impacts identified are, however, probably conservative, reflecting the limitations of the methodologies used to estimate each of the three main categories of impact, and the limited availability of relevant data. As such, subsequent research at the trait and country level might usefully extend the analysis to incorporate more sophisticated consideration of dynamic economic impacts and some of the less tangible economic impacts (e.g., on labor savings). Further useful analysis of the environmental impact might also include additional environmental indicators, such as impact on soil erosion.
1 Readers should note that some data presented in this article are not directly comparable with data presented in the previous two articles because the current article takes into account the availability of new data and analysis (including revisions to data for earlier years).
2 No-till farming means that the ground is not plowed at all, while reduced tillage means that the ground is disturbed 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 without any soil disturbance.
3 Where several pieces of research relevant to one subject (e.g., the impact of using a GM trait on the yield of a crop) have been identified, the findings used have been largely based on the most conservative finding.
4 Inclusion of the impact on these cost categories are, however, more limited than the impacts on seed and crop protection costs because only a few authors that we reviewed have included consideration of such costs in their analysis. Therefore in most cases the analysis relates to impact of crop protection and seed cost only.
5 Examples where such data is available include the impact of Bt cotton in India (see Asia-Pacific Consortium on Agricultural Biotechnology [APCoAB], 2006; Bennett, Ismael, Kambhampati, & Morse, 2004; IMRB International, 2007), in Mexico (see Monsanto Comercial Mexico, 2005, 2007; Traxler, Godoy-Avilla, Falck-Zepeda, & Espinoza-Arellano, 2001), and in the United States (see Mullins & Hudson, 2004; Sankula, 2006; Sankula & Blumenthal, 2004).
6 The average base yield has been adjusted downwards (if necessary) to account for any positive yield impact of the technology. In this way, the impact on total production of any yield gains is not overstated. The authors do however, acknowledge that the use of this assumption may still over- or understate the yield effects in some years because yield impact findings from a limited number of years have been used as the basis for estimating impact in other years. However, in the absence of comprehensive yield impact analysis for each trait, country, and year, the authors consider this an appropriate approach to take in order to estimate cumulative impact.
7 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 (2007).
8 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.
11 Due to the likely small-scale impact and/or lack of tillage-specific data relating to GM HT maize and cotton crops (and the US GM HT canola crop), analysis of possible GHG emission reductions in these crops have not been included. The no/reduced-tillage areas to which these soil carbon reductions were applied were limited to the increase in the area planted to no/reduced tillage in each country since GM HT technology has been commercially available. In this way, the authors have tried to avoid attributing no/reduced-tillage soil carbon sequestration gains to GM HT technology on cropping areas that were using no/reduced-tillage cultivation techniques before GM HT technology became available.
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Appendix 1. Examples of Farm Income Methodology Application
Table A1. Farm-level income impact of using GM IR maize in the United States, 1996-2006.
Table A2. Farm-level income impact of using GM IR cotton in India, 2002-2006.
Table A3. Farm-level income impact of using GM HT soybeans in Argentina, 1996-2006.a
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. As such, the proportion of soybean production in Argentina using no- or low-tillage methods has increased from 34% in 1996 to 90% by 2005. Also, 20% of the total Argentine soybean crop was second crop in 2006, compared to 8% in 1996. Based on the additional gross margin income derived from second crop soybeans (see below), this has contributed a further boost to national soybean farm income of $699 million in 2006 and $3.29 billion cumulatively since 1996.
Table A4. Farm-level income impact of using GM HT soybeans in Argentina, 1996-2006: Second crop soybeans.a
Table A5. Yield impact assumptions.
Table A6. Cost of technology assumptions (costs/ha).
Table A7. Cost savings (excluding impact of seed premium) assumptions (costs/ha).
Readers should note that the assumptions are drawn from the references listed below. In some cases (trait/crop/country combinations), the authors have not been able to identify specific studies. Where this has occurred, data has been sought from farm advisers and seed-supplying companies in each country. This has been particularly of relevance for some of the HT traits more recently adopted in several developing countries. Accordingly, the authors are grateful to industry sources that have provided information on impact, notably on cost of the technology and impact on costs of crop protection. While this information does not derive from detailed studies, the authors are confident that it is reasonably representative of average impacts; in fact, 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.
Table A8. Data sources.
Suggested citation: Barfoot, P., & Brookes, G. (2007). Global impact of biotech crops: Socio-economic and environmental effects, 1996-2006. AgBioForum, 11(1), 21-38. Available on the World Wide Web: http://www.agbioforum.org.
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