Models of kernel number in maize

Crop models that predict kernel number in maize usually do so on the basis of estimated plant growth or radiation interception during a critical period bracketing silking. Yield models without kernel number detail usually use a harvest index concept, the rate of change of harvest index after silking, or plant biomass at silking. The estimation of kernel number, however, is one of the weakest links in accurate crop yield modeling, yet it is the most important single factor influencing yield. In order to estimate field or plot level yields as influenced by weather, genotype, management, and soil properties, models contain relationships influenced by temperature, radiation interception, water and nutrient supply, and genetic coefficients. The genetic coefficients used in models help distinguish differences between genotypes in phenology, kernel numbers, barrenness, and grain growth rate. Recent research has provided information regarding more precise time windows when kernel set occurs, evaluating prolificacy, barrenness, and within-row spatial variability.