Spatial Econometric Modeling for Site-Specific Nematode Management

Management of nematodes infested within cotton field has eluded farmers and researchers for decades. Nematode control has primarily relied upon nematicide application. Recent advances in precision agriculture technologies and spatial statistics allow the feasibility of site-specific nematode management which rely upon applying nematicides at a variable rate across fields only in locations where economically justified. The estimation of profitability of site-specific management and the development of application recommendation are based on the clear establishment and estimation of yield potential (penalty) function. Due to the existence of spatial dependency in the crop yield monitor data, spatial econometric techniques with modeling correlation among neighboring observations should be considered to use to obtain more reliable estimates.

This paper reviewed and applied spatial econometric modeling to determine the potential of site-specific nematicide application. Spatial autoregressive error model, spatial autoregressive lag model, spatial Durbin model and spatial panel model with fixed and random effect extension were used to estimate cotton lint yield as a function of nematode population, soil texture, nematicide application and other environmental factors using on-farm experiments data collected in southeastern Arkansas.

The results from both cross-sectional and panel data analysis support following findings: 1) spatial econometric models are the proper alternative to aspatial model for site-specific nematode management study; 2) post-treatment nematode population at bloom season and percent sand fraction are significant factors in explaining cotton yield variability; 3) yield penalty resulting from a given nematode infestation vary with different soil texture;  4) yield response for nematicide application differs by soil texture. The results provide evidence to support the potential of site-specific nematicide application and can be used to develop efficient site-specific nematode management strategies.