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

Abstract

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 implication on survey budget, implementation speed and respondent and interviewer burden. In this paper, six alternative methods of crop residue coverage measurement are tested among the same sample of rural households in Ethiopia. The relative accuracy of these methods are 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 (i.e., >30% 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. Results deliver a ranking of measurement options that can inform survey practitioners and researchers.

Phenotyping Conservation Agriculture Management Effects on Ground and Aerial Remote Sensing Assessments of Maize Hybrids Performance in Zimbabwe

“…The reason for this is assumed to be the added noise derived from the crop residue coverage of the soil. According to the FAO definition, the soil surface has to be covered at least by 30% to qualify as CA in principle [ 61 ], which may have influenced remote sensing readings under CA. Due to this fundamental difference between CA and CP, it is difficult to segregate the biomass from the plant and residue cover.…”

The Challenge of Tracking the Reach of Post-Green Revolution Crop Breeding

“…Table 1 reports the rate of correct classification and identification for each of the 16 case studies (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).…”

“…And while sample size and representativity differ across studies, it is notable that the subset of studies presenting nationally representative data, on average, show a larger degree of misclassification and misidentification, confirming the generalizability of the findings. Misclassification is moreover often correlated to farmers' characteristics, and this non-classical measurement error therefore invalidates conclusions from common analyses of the correlates of adoption (8,9,12,14,15,17).…”

“…2 Authors in (6) performed a further cluster analysis to identify the variety type of 1,538 initially unidentified samples. Finally, missing data, due to sample damage or losses during transit were also excluded from the calculationsamong the 16 datasets analyzed, only two experienced significant losses (15,16).…”

Maize yield gaps and their mitigation in Ethiopia: an integrated assessment

“…The main drivers of maize yield increase have been linked to input intensification (mainly fertiliser use and improved varieties) and the agricultural extension system Sheahan and Barrett, 2017). One of the maize intensification promotion strategies has been breeding for improved and stress-tolerant varieties that can increase maize yield and minimize yield loss from abiotic and biotic stresses (Collinson et al, 2022;Jones-Garcia and Krishna, 2021;Kosmowski et al, 2020). Since 1990, fifty-three improved maize varieties have been released in Ethiopia (Kosmowski et al, 2020).…”