Data for: Challenges and lessons for measuring soil metrics in household surveys

Used in the article "Challenges and lessons for measuring soil metrics in household surveys

Ansätze zur Modellierung von Schaumströmungen

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Part III : Social changes in rural populations : introduction

International audienc

The seeds of misallocation: fertilizer use and maize varietal misidentification in Ethiopia

Optimal input allocation in agriculture leverages production complementarities. For example, improved seeds are generally more responsive to fertilizer than traditional seeds. Thus, inaccurate beliefs about whether seeds are improved may result in sub-optimal fertilizer application. We document precisely this pattern using data from Ethiopia that allows us to compare farmer beliefs about their maize seeds with genotyping data that identify the true genetics of these seeds. We find that 15 percent of farmers believe incorrectly that they are using improved varieties and use far more fertilizer than farmers who correctly believe that they sowed traditional varieties. Conversely, we find that about 15 percent of farmers believe incorrectly that they are growing traditional material and use far less fertilizer than those farmers who correctly believe that they are growing improved material. We extrapolate from our nationally representative sample to estimate the national-level magnitude of fertilizer misallocation due to incorrect seed beliefs

On the Ground or in the Air? A Methodological Experiment on Crop Residue Cover Measurement in Ethiopia

Maintaining permanent coverage of the soil using crop residues is an important and commonly recommended practice in conservation agriculture. Measuring this practice is an essential step in improving knowledge about the adoption and impact of conservation agriculture. Different data collection methods can be implemented to capture the field level crop residue coverage for a given plot, each with its own implications for the survey budget, implementation speed, and respondent and interviewer burden. This study tests six alternative methods of crop residue coverage measurement among the same sample of rural households in Ethiopia. The relative accuracy of these methods is compared against a benchmark, the line-transect method. The alternative methods compared against the benchmark include: (i) interviewee (respondent) estimation; (ii) enumerator estimation visiting the field; (iii) interviewee with visual-aid without visiting the field; (iv) enumerator with visual-aid visiting the field; (v) field picture collected with a drone and analyzed with image-processing methods; and (vi) satellite picture of the field analyzed with remote sensing methods. Results of the methodological experiment show that survey-based methods tend to underestimate field residue cover. When quantitative data on cover are needed, the best estimates are provided by visual-aid protocols. For categorical analysis (such as greater than 30 percent cover or not), visual-aid protocols and remote sensing methods perform equally well. Among survey-based methods, the strongest correlates of measurement errors are total farm size, field size, distance, and slope. The results deliver a ranking of measurement options that can inform survey practitioners and researchers. This work is a part of the SIAC (2013-2016) program to develop robust methods to routinely track adoption of CGIAR research outcomes. You can find a bit more information on the collaboration with LSMS-ISA here (http://impact.cgiar.org/methods/lsms-isa). This research was supported by ISPC-SPIA under the grant “Strengthening Impact Assessment in the CGIAR (SIAC).” (https://cas.cgiar.org/spia/news/strengthening-impact-assessment-cgiar-siac-2013-2016

Varietal Identification in Household Surveys: Results from an Experiment Using DNA Fingerprinting of Sweet Potato Leaves in Southern Ethiopia

Sweet potato (Ipomoea batatas) varieties have important nutritional differences and there is strong interest to identify nutritionally superior varieties for dissemination. In agricultural household surveys, this information is often collected based on the farmer's self-report. However, recent evidence has demonstrated the inherent difficulties in correctly identifying varieties from self-report information. This study examines the accuracy of self-report information on varietal identification from a data capture experiment on sweet potato varieties in southern Ethiopia. Three household-based methods of identifying varietal adoption are tested against the benchmark of DNA fingerprinting: (A) elicitation from farmers with basic questions for the most widely planted variety; (B) farmer elicitation on five sweet potato phenotypic attributes by showing a visual-aid protocol; and (C) enumerator recording observations on five sweet potato phenotypic attributes using a visual-aid protocol and visiting the field. The reference being the DNA fingerprinting, about 30 percent of improved varieties were identified as local or non-improved, and 20 percent of farmers identified a variety as local when it was in fact improved. The variety names given by farmers delivered inconsistent and fuzzy varietal identities. The visual-aid protocols employed in methods B and C were better than method A, but still way below the adoption estimates given by the DNA fingerprinting method. The findings suggest that estimating the adoption of improved varieties with methods based on farmer self-reports is questionable, and point toward a wider use of DNA fingerprinting, likely to become the gold standard for crop varietal identification. This work is a part of the SIAC (2013-2016) program to develop robust methods to routinely track adoption of CGIAR research outcomes. You can find a bit more information on the collaboration with LSMS-ISA here (http://impact.cgiar.org/methods/lsms-isa). This research was supported by ISPC-SPIA under the grant “Strengthening Impact Assessment in the CGIAR (SIAC).” (https://cas.cgiar.org/spia/news/strengthening-impact-assessment-cgiar-siac-2013-2016

Varietal identification in household surveys: results from three household-based methods against the benchmark of DNA fingerprinting in southern Ethiopia

Accurate crop varietal identification is the backbone of any high-quality assessment of outcomes and impacts. Sweetpotato (Ipomoea batatas) varieties have important nutritional differences, and there is a strong interest to identify nutritionally superior varieties for dissemination. In agricultural household surveys, such information is often collected based on the farmer's self-report. In this article, we present the results of a data capture experiment on sweet potato varietal identification in southern Ethiopia. Three household-based methods of identifying varietal adoption are tested against the benchmark of DNA fingerprinting: (A) Elicitation from farmers with basic questions for the most widely planted variety; (B) Farmer elicitation on five sweet potato phenotypic attributes by showing a visual-aid protocol; and (C) Enumerator recording observations on five sweet potato phenotypic attributes using a visual-aid protocol and visiting the field. In total, 20% of farmers identified a variety as improved when in fact it was local and 19% identified a variety as local when it was in fact improved. The variety names given by farmers delivered inconsistent and inaccurate varietal identities. Visual-aid protocols employed in methods B and C were better than those in method A, but greatly underestimated the adoption estimates given by the DNA fingerprinting method. Our results suggest that estimating the adoption of improved varieties with methods based on farmer self-reports is questionable and point towards a wider use of DNA fingerprinting in adoption and impact assessments