Cotton Fiber-Quality Prediction Based On Spatial Variability In Soils

Maximizing cotton fiber quality is crucial for the continued success of the U.S. cotton industry. Previous studies have indicated that spatial variability of fiber-quality properties exists and is a factor in revenue variability across a field. Site-specific fiber-quality prediction potentially could be managed on the farm to optimize fiber quality with respect to profitability, or the harvest could be segregated according to fiber quality to increase a producer's overall crop price. Fiber micronaire was identified as the target property for study because of its moderate variation at the farm-field level and its importance to producers and the textile industry. Two years' cotton and soil data from two fields near Brooksville, MS, were used to investigate the extent to which soil parameters could explain spatial variation in cotton fiber quality. Spatial variability existed in both soil and fiber-quality properties, and as expected from prior research, micronaire was found to have relatively large variability compared to other quality properties. Spatial autocorrelation in the data was considered by using Moran's I but found not to be a factor. When simple linear regression was employed, the individual soil-related factors most closely related to overall micronaire variability were clay content, pH, and relative site elevation. Multiple linear regression was also employed, and one soil variable, pH, accounted for 42% of the overall variability in micronaire for the south field in year one; whereas pH, magnesium, and sodium together accounted for more than 41% of the micronaire variability for the north field in year two. Site-specific prediction of micronaire based on soil parameters alone continues to be a challenge according to the results of this study.