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The Role of Biotechnology in Sustainable Agriculture of the Twenty-First Century: The Commercial Introduction of Bollgard II in Burkina Faso

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Convergence of Food Security, Energy Security and Sustainable Agriculture

Part of the book series: Biotechnology in Agriculture and Forestry ((AGRICULTURE,volume 67))

Abstract

In the broader context of West African cotton production, we present empirical evidence of how Bt cotton has impacted the Burkina Faso cotton industry based on household surveys that encompass the first 3 years of commercial production, 2009 through 2011. The surveys document the impact of Bt cotton on household income, production costs, pesticide use, and associated health issues. Briefly, over 3 years, a mean yield increase of 22 % was observed with Bt cotton over conventional cotton with a reduction of insect sprays by at least two-thirds, resulting in significantly reduced human pesticide exposure. Roughly equivalent production costs enabled growers to retain the value of the extra yields, which led to mean income benefits of about $65 per ha and contributed heavily to a national level economic benefit of approximately $53 million over the 3 years surveyed. These data are discussed in the context of West African cotton production, its history, current issues, and potential sustainability.

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Notes

  1. 1.

    In most years West Africa exports 97 % of its cotton production to the world market (ICAC 2006).

  2. 2.

    Most of West Africa’s cotton lint is of medium to medium-high grade. Quality issues would be further enhanced if contamination was reduced and segregation improved. Moreover most West African cotton has been bred to provide seed cotton with a high lint percentage by weight (gin turnout). The 42 % gin turnout seen in Mali is much higher than most US varieties (ICAC 2006).

  3. 3.

    This chapter only reports on the occurrences of pesticide poisonings. Additional questions elicited information on the handling, application, disposal, and other safety issues related to pesticide use.

  4. 4.

    However, the successful efforts to encourage producers to follow recommended practices precluded the opportunity to statistically test the effect of late season sprays in 2010 or 2011 since the number of producers who did not spray was too small for ANOVA models. The low numbers of producers who sprayed once were also small, and while the number of producers who sprayed once were large enough to be included in ANOVA models, the small sample sizes created wide statistical confidence intervals for comparing means in the second and third years and were not well suited for appropriate balanced statistical analyses using weighted averages.

  5. 5.

    Production costs were nearly constant across the three years, varying only modestly between 2009 and 2011. Because of the low inter-year variability, only 3-year average values for production costs are presented in Table 11.4 and Fig. 11.10.

  6. 6.

    Average production costs are calculated as production costs divided by yield. Average production costs provide a useful measure of profitability since they indicate how much profit is made per unit produced, i.e., profit is given by the difference between selling price and average production cost. Hence, to break even average production costs must be less than selling price.

  7. 7.

    In the 2010 report, returns to labor were calculated using 76 days of labor per ha to maintain consistency with the INERA report. This value of labor was not obtained from the survey data, but appears to have been obtained from previous research. Returns to labor calculated as profit divided by the days of labor per ha.

  8. 8.

    The extrapolation calculated the aggregate impact using per ha economic returns reported in the figures. The national impacts reported in Fig. 11.14 are based on the cotton price paid to producers. Additional benefits could accrue to the cotton companies from the increased quantity of cotton sold on world markets. Since the cotton companies marketing margins were not available, those benefits could not be assessed.

  9. 9.

    There is a 1-year lag in the reporting of pesticide poisonings since the households ask about incidents that occurred in the previous year. For example, in the first year of the surveys, 2009, producers were asked for poisoning incidents that occurred in 2008. This is necessary since surveys occur during the production period, before all of the insecticides have been applied. The 2009 surveys also asked producers to self-report pesticide poisoning incidents that had occurred over the previous 5 years, 2004–2008.

  10. 10.

    The producer surveys collected the number of self-reported poisoning incidents that occurred within the household. For each incident reported, respondents listed the type of insecticide used, symptoms incurred, extent of illness, medical expenses, lost wages, and background information on the poisoned individual.

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Authors and Affiliations

  1. Department of Agricultural Economics, Oklahoma State University, 418 Ag Hall, Stillwater, OK, 74078, USA

    Jeff Vitale

  2. Monsanto, 800 N. Lindbergh Blvd, Saint Louis, MO, 63167, USA

    John Greenplate

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  1. Director of Research/Cell Biology, Cibus LLC, San Diego, California, USA

    David D. Songstad

  2. National Laboratory for Agriculture and, USDA-ARS, Ames, Iowa, USA

    Jerry L. Hatfield

  3. Grimes, Iowa, USA

    Dwight T. Tomes

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Vitale, J., Greenplate, J. (2014). The Role of Biotechnology in Sustainable Agriculture of the Twenty-First Century: The Commercial Introduction of Bollgard II in Burkina Faso. In: Songstad, D., Hatfield, J., Tomes, D. (eds) Convergence of Food Security, Energy Security and Sustainable Agriculture. Biotechnology in Agriculture and Forestry, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55262-5_11

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