Spatial and Temporal Variability Management for All Farmers: A Cell-Size Approach to Enhance Coffee Yields and Optimize Inputs

Abstract

Coffee yield exhibits plant-level variability; however, due to operational issues, especially in smaller operations, the scouting and management of coffee yields are often hindered. Thus, a cell-size approach at the field level is proposed as a simple and efficient solution to overcome these constraints. This study aimed to present the feasibility of a cell-size approach to characterize spatio-temporal coffee production based on soil and plant attributes and yield (biennial effects) and to assess strategies for enhanced soil fertilization recommendations and economic results. The spatio-temporal study was conducted using a database composed of yield and soil and plant attributes from four harvest seasons of coffee plantation in the southeast region of Brazil. We used small plots as cells, where soil, leaf, and yield samples were taken, and the average value of each variable was assigned to each cell. The results indicated that macro- and micronutrient contents in the soil and leaves exhibited spatio-temporal heterogeneity between cells, suggesting that customized coffee tree management practices could be employed. The cell-size sampling strategy identified regions of varying yield over time and associated them with their biennial effect, enabling the identification of profitable areas to direct resource and input management in subsequent seasons. This approach optimized the recommendation of potassium and phosphate fertilizers on farms, demonstrating that localized management is feasible even with low spatial resolution. The cell-size approach proved to be adequate on two coffee farms and can be applied in scenarios with limited resources for high-density sampling, especially for small- and medium-sized farms.