Jeffrey Vitale Gaspard Vognan
Source: ISAAA 2011.
What makes the Burkina Faso story unique? Demonstrates the feasibility of commercially introducing a GM crop in a less developed country Persistence and determination in an environment often hostile to biotechnology and GM crops Collaboration among diverse stakeholders, including smallholder producers, private sector, and public sector
Stagnation Confined Field Trials Ref: Huma et al. 2007;Vitale et al 2006 Demonstration Plots 2007 On-farm trials 2008 Limited Commercial release Large-Scale Commercial release Testing Legal Framework Biosafety Protocols Monitor & Evaluate Ref: Sustainability paper, Sanders et al., Tom Bassett
Summary of Bollgard II® in Burkina Faso: Documented Findings from Surveys Six years of commercial use ( ) – Approaching “full” adoption threshold Higher BGII yields in all years (20.5%) Lower pesticide use (2/3 reduction) Higher economic returns in all years – Consistent with yield increase since no significant change in costs (higher seed cost offset by insecticide cost savings) Health benefits (self-reported) ($1 million annual)
BGII Adoption Profile
Conventional Cotton = “Gray” – “Red”
BGII Adoption Profile Roger’s 80% upper limit Seed Supply Issues Refugia
Ave Yield Increase = 20.5% INERA Producer Surveys b a
Six years of commercial use ( ) Approaching “full” adoption threshold Higher BGII yields in all years (20.5%) Lower pesticide use (2/3 reduction) Higher economic returns in all years Proportional with yield increase since no significant change in costs: higher seed cost offset by insecticide cost savings → Economic Impact ≈ P cott *∆Yield Significant yield impact → Significant economic impact Health benefits (self-reported) ($1 million annual)
Are all farmers benefitting? Does location matter? – Modest regional difference but producers in all zones obtained significantly higher yields growing BGII compared to conventional cotton Does “farm size” matter? – “Larger” farms were found to have higher yields but farms of all size, including smallholder farms, obtained significantly higher yields growing BGII compared to conventional cotton
INERA Farm Type Classification Cotton Production Zone Yield ItemSOFITEX (N BT =109)SOCOMA (N BT =73)Faso Coton (N BT =75)All Zone (kg ha -1 ) Large n BT =66 n CV =77 Med n BT =31 n CV =47 Manual n BT =12 n CV =30 Ave Large n BT =23 n CV =21 Med n BT =42 n CV =32 Manual n BT =8 n CV =9 Ave Large n BT =14 n CV =15 Med n BT =61 n CV =56 Manual n BT =0 n CV =0 Ave n BT =257 n CV =287 BG II 1,293A1,169AB1,297AB1,258A1,192AB1,286A1,088ABC1,235A1,173AB954C-995B1,175a Conventional 1,105B1,084BC870C1,053B948BC964BC1,060ABC972B866C825C-834C981b Average Yield 1,199a1,127a1,083b1,155a1,070a1,125a1,074a1,103a1,019ab890b-914b1,078 Yield inc (kg ha -1 ) Advantage (%) Inc Rev: $ ha Farm Size (ha) BGII Conventional Source: Vitale et al. (2010) AgBioforum
Production Zone: Sample Distribution
Yields by Production Zone b a
Why the Concern over Farm Size/Farm Structure? Welfare of the “smallholder farmer” is explicitly mentioned in Burkina Faso’s biosecurity legal framework Welfare of the smallholder farmer overarching theme of CGIAR and many NARS
How can Farms be Classified by Size? Biosecurity framework provides no specific definition of “smallholder farm” Our analysis has followed the classification used by INERA based on the # of draft animals owned by the household Given the importance of addressing the welfare of smallholders, we have been investigating whether another classification could provide a more accurate depiction of farm size
Farm Size: INERA Classification
Farm Size: Yields by INERA Class. A D C B C E R 2 = 0.198
Farm Size: Planted Area
Farm Size: Yields by Planted Area Small letters: means testing within each land class a b a R 2 = 0.187
Farm Size: Household Labor
Farm Size: Yields by Household Labor R 2 = b a
Summary of Initial Findings BGII provided significantly higher yields and economic returns for all types of farmers, in particular smallholder farmers, using three alternative classifications (#animals, land size, HH labor) All three classifications provided about the same level of explanatory power, 17-20% On-going research: Would using all three farm structure variables provide a better farm classification?
Does Farm Size Affect BGII Impact? BG II is a scale neutral technology: – Control effectiveness of BGII independent of field size (~95%) – No new equipment needed (or that could be sold) – Seed cost on a per ha basis (no scale effect) – Insecticide costs on a per ha basis (no scale effect) Farm size and farm structure can affect yield performance …
Empirical Evidence Investigate the effect of farm size and farm structure on BG II yield performance using six years of cotton producer survey data Test whether farm size/farm structure related variables have a significant effect on cotton yield: – Farm size (area) – Household labor – Number of bullocks
Empirical Model Structure Y = α 0 + α 1 Year + α 2 Type + α 3 Zone + α 4 Sprays + β 1 Animals + β 2 Area + β 3 Labor + interactions Variables: – Type BGII or conventional – Year – Zone SOFITEX,SOCOMA, or Faso Coton – Sprays Late season sprays (secondary pests) – Animals # of working animals (bullocks) – Area # hectares of cotton planted by household – Labor # of household members working on-farm
Model Results SourceEstimatePr>FEstimatePr>FEstimatePr>F Intercept853.7< Year…<.0001 Type_Coton (BT=1)139.62< <.0001 Year*Type_Coton… Zone…<.0001 Type_Coton*Zone… Sprays… Type_Coto*Sprays… Labor Land < <.0001 Animals < < <.0001 Labor*Land Land*Animals Labor*Animals Labor/Land Animals/Land R2R2 Model 1 Model 2 Model
Model Results: Estimated BGII Yield Function: Land, Labor, and Animals 3 animals 4 laborers 1,100 kg yield 4 animals 8 laborers 1,250 kg yield
Practical Implication Research findings suggests that the prior definition used to define farm types, based only on # bullocks, is as good as alternative classifications using land and labor. Provide policy makers, and the on-going legal framework, with an alternative approach to define what a “smallholder” producer is, i.e. include a “3-D” definition.
The End
Does Farm Size Affect BGII Impact? BG II is a scale neutral technology: – Control effectiveness of BGII independent of field size (~95%) – No new equipment needed (or that could be sold) – Seed cost on a per ha basis (no scale effect) – Insecticide costs on a per ha basis (no scale effect) Farm size and farm structure can affect yield performance …
How Farm Size Can Matter: Stylized Facts Economy of scale: larger farms can more easily cover fixed costs compared to smaller ones – Higher profits earned by larger farms Wealth Effect: Higher profits enable larger (& better managed) farms to make more investments in equipment (e.g. animal traction) and resources – Bigger farms are wealthier & better equipped than smallholders who remain resource constrained – Greater efficiency, risk mgmt easier, access to capital
How Farm Size Can Matter: Stylized Facts “Rich get richer” while smallholders remain trapped in subsistence farming – Increase land holdings, access to quality lands, and political power while smaller producers are pushed to the margins
Empirical Evidence Investigate the effect of farm size and farm structure on BG II yield performance using six years of cotton producer survey data Test whether farm size/farm structure related variables have a significant effect on cotton yield: – Farm size (area) – Household labor – Number of bullocks
Scale Effects in Cotton Production Farm equipment (+) – Manual farms vs. animal powered vs. mechanized Deeper plowing, increased speed of operation for bigger farms Household farm labor (+/-) – Big farms likely to have larger workforce but also larger field size – Small farms could have more labor per ha but likely have greater labor demand since they are less well equipped – So this variable is difficult to predict a priori and likely to depend on other variables (interaction terms) Farm Size (+/-) – Larger farms are more difficult to manage since they are more complex and have larger area, e.g. pest scouting and nutrient management – Larger farms likely better equipped and more efficient – So this variable is difficult to predict a priori and likely to depend on other variables (interaction terms)
Model Structure Test alternative regression models and identify which variables are significant and which model best fits the data Include interaction terms and create new variables to place farm structure variables on a unit basis, e.g. labor per ha Include other variables to explain cotton yield: – Year – Zone – Insecticide sprays
Empirical Model Structure Y = α0 + α0Zone + α0Zone + α0Sprays + β1Area + β1 + α0Year Variables: – Type (BGII or conventional) – Year – Zone – Insecticide sprays – Village
Model Results SourceEstimatePr>FEstimatePr>FEstimatePr>F Intercept853.7< Year…<.0001 Type_Coton (BT=1)139.62< <.0001 Year*Type_Coton… Zone…<.0001 Type_Coton*Zone… Late_spray_Cat… Type_Coto*Late_spray… Actifs_agricole Surface_parcelle < <.0001 Nombre_animaux_trait < < <.0001 Actifs_ag*Surface_pa Surface_p*Nombre_ani Actifs_ag*Nombre_ani Actifs_ha Animals_ha R2
Results
Two-Dimensional View of Smallholder Farms Lighter colors represent larger residuals
Practical Implication Research findings suggests that the prior definition used to define farm types, based only on # bullocks, is not the best one, but is still consistent with our more general findings. Provide policy makers, and the on-going legal framework, with an alternative approach to define what a “smallholder” producer is, i.e. include a “3-D” defintion.
Conclusions/Policy Implications Smallholder farmers benefit the same as larger, better equipped farms on a proportional basis no matter how “smallholder” is defined Larger, better equipped farms have higher yields and do achieve higher overall yield and economic benefits ALL farm types and size perform significantly better with BGII than conventional cotton Policy makers need to focus assisting farmers to become better equipped and to utilize increased profitability of BGII cotton to invest in farm equipment More efficient farms are expected to improve yields as suggested by the survey results. – Larger farm sizes will be an outcome of the increased farm capital but increasing farm size just for the sake of larger farms will not increase yields.
Farm Type YearManualSmallLargeMotoriseAve BGII1012aC1064aC1207aB(1555A)1094a CONV915aA909bA973bA-933b Diff % Diff BGII978aB1028aB1162aA-1056a CONV882aB863bB947bA-897b Diff % Diff BGII782aD962aC1144aB(1310aA)962a CONV760aC872bB979bA(1000bA)870b Diff (310)92 % Diff (13.1)10.5 Ave BGII953aD1021aC1174aB(1352aA)1049a CONV860bB887bB979bA(1000bA)908b Diff (352)141 % Diff (13.5) / /2015 – Yields*old farm type (animals)*type of cotton Sofitex + Socoma + Faso Coton Notes statistical analyses Mean separation indicated by letters a,b,c is comparing cotton types within same farm type Mean separation indicated by letters A,B,C is comparing farm types within same cotton type ALL FARM TYPES BENEFIT FROM GROWING BOLLGARD II®
2009/2010 – 2013/2014 BGII yield benefit for all field sizes Higher yields More consistent yield
2009/2010 – 2013/2014 BGII yield benefit for all HH Labor Higher yields More consistent yield
Better Way to Classify Farms
Monsanto Company Confidential This presentation focused on cotton yield impact of BGII The close proximity of the average production costs of BGII cotton and conventional cotton indicates that the primary source of the increase in cotton profit from growing Bollgard II across years (2009/2010 – 2011/2012) was from a combination of the yield increase and the higher cotton price that placed a greater value on output compared to the previous two years. Other socio-economic benefits directly linked to yield are available but not discussed in this presentation - Economic return ($/ha) Cotton income – Cotton Production cost - Household income (related to hectares of BGII) - Return to labor ($/day) - more consistent production => this will become visible in presentation (less variable, target pest control) Consistent benefits not directly linked to yield are available but not discussed in this presentation - improved human health (and related reduced health care cost) reduced insecticide exposure (2 treatments vs 6 treatments) chemical storage, preparations spray solutions, exposure during applications waste handling - Reduced environmental impact from reduced insecticide usage - labor saving and the related time spending
Further Research Is there more land available in all villages? Is additional training needed for increasing animal traction