Geostatistical techniques to account for the heterogeneity of Fusarium wilt inoculum distribution in upland cotton field screening studies

Variable and uncontrollable environmental factors have a wide range of influence on crop field screening programs, with the potential to cause significant experimental errors in phenotypic data collection. These factors can be additive and negatively confound genetic studies. When field screening upland cotton for genetic resistance to Fusarium wilt caused by Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4), the distribution and concentration of fungal inoculum in the field directly impact the disease severity, affecting the results of these studies. Variability among FOV4 screening fields and protocols has influenced the search for durable genetic resistance. To account for this spatial variability, rigorous use of check plots with predictable responses to FOV4 were planted throughout a screening nursery in Clint, TX, and scored for percent survival within each plot. The scores and locations were used to generate a predicted surface via kriging interpolation and conditional simulation, which estimate FOV4 inoculum pressure at every plot location in the field. These predictions created FOV4 pressure‐adjusted disease severity ratings in F3 generations of bi‐parental crosses between FOV4‐resistant and susceptible upland cotton lines. Environment‐adjusted phenotypes allow breeders to consider the environmental variance associated with the heterogenous distribution of the pathogen in the field. The techniques presented here are transferrable to any field screening program that needs to account for spatial variation of environmental factors. Core Ideas Geostatistics can be used with field check varieties to model the distribution of environmental factors in fields. Kriging predicts an overly smooth surface and conditional simulation refines the surface with more spatial variation. Crop trait measurements adjusted by predicted environmental factors can lead to more accurate analyses.