Challenges and lessons for measuring soil metrics in household surveys
| Autor: | Ayale Abebe, Frédéric Kosmowski, Daglar Ozkan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Soil acidity
Soil texture Soil Science Sample (statistics) Agricultural engineering 010501 environmental sciences 01 natural sciences Article Plot (graphics) immune system diseases Soil pH Range (statistics) Soil organic content Miniaturized spectrometer 0105 earth and related environmental sciences business.industry food and beverages Sampling (statistics) 04 agricultural and veterinary sciences respiratory tract diseases Agriculture Soil water 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Environmental science business Survey experiment |
| Zdroj: | Geoderma |
| ISSN: | 0016-7061 |
| Popis: | Highlights • The accuracy of farmer’s elicitation and miniaturized spectrometers is assessed in rural Ethiopia. • Farmer’s elicitation do not converge with objective metrics. • Miniaturized spectrometers provide accurate data for the identification of soil constraints. • Miniaturized spectrometers provide approximate quantitative predictions. While the importance of soils in agriculture cannot be overlooked, plot level soil data remain scarce in the current data landscape. Large-scale household surveys efforts are increasing in low-income countries and assessing the accuracy, scalability and cost-effectiveness of available methods is crucial. Here, we firstly explore soil data requirements for a set of objectives that include identifying a soil constraint, improving recommendation domain studies and capturing soil metrics as covariates, or as outcomes. We then expose the lessons learned from a methodological experiment in rural Ethiopia, where different approaches – farmer’s self-elicitation and miniaturized spectrometers – are compared against laboratory benchmarks for a set of soil parameters: soil texture, soil pH and soil organic C. With the exception of soil particle sizes, we find that soil parameters captured through farmer’s elicitation do not converge with objective metrics. Miniaturized spectrometers can provide reasonably accurate data for the identification of soil constraints – soil acidity, low organic C or sandy soils. Approximate quantitative predictions can also be delivered for soil pH (R2 = 0.72) and organic C (R2 = 0.60). The additional costs of plot sampling and analysis are in the range of $19–$23 per sample, with the additional percentage of plots with correct data equivalent to 10% for the identification of sandy soils, 75% for low organic C and 89% of acidic soils. |
| Databáze: | OpenAIRE |
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