Analysis of Farmer Field Data for Soybean

Average crop yields will need to increase substantially during the next 33 years to meet expected food demand increase while avoiding massive expansion of cropland area (Alexandratos and Bruinsma, 2012; Grassini et al., 2013). This challenge can be achieved by increasing the rate at which best management practices are identified and adopted for a particular soil-climate context. Replicated eld experiments are used in agricultural research to test new technologies and management practices. Farmer survey data can be utilized as a cost-effective source of information to identify yield constraints and fine-tune management practices so that these yield limitations can be ameliorated or eliminated (e.g., Lobell et al., 2005; Tittonell et al., 2008). An advantage of using farmer data is that it allows examination of opportunities for yield increase within the range of current management practices that are both cost-effective and logistically feasible in farmer fields. Another advantage of using farmer data is that, when they are properly contextualized relative to their biophysical environment, it is possible to explore and quantify management × environment interactions (Rattalino Edreira et al., 2017). Such assessment would allow identification of suites of management practices that perform best for a given environment and provide a focus to traditional, costly field experiments so that they can target those management practices with the most likely impact on crop productivity and input-use efficiency.