Abstract
Agricultural production relies on soils. Even though many indicators of soil quality have been proposed, a unique consensus on the best indicator is not reached. This contribution proposes a methodology to aggregate quantitative soil characteristics through the use of economic theory. This aggregation method, which is general and can be applied to any production context, yields a soil-quality measure that summarizes soil characteristics in output terms, among Kenyan maize (Zea mays L.) farmers situated on different types of soils (FAO, 2015). Our methodology, developed at the University of Maryland in 2011, uses simple linear programming to obtain a measure of soil quality. We hypothesize that carbon and clay might have negative marginal effects on soil quality. Our results confirm this hypothesis by demonstrating that soil carbon has a negative impact on soil quality for concentrations above 40gkg−1, depending on clay concentration.
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