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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #272082
Title: Cotton fiber quality prediction based on spatial variability in soils

Author
item WANG, RUI - Mississippi State University
item THOMASSON, J - Texas A&M University
item COX, MICHAEL - Mississippi State University
item Sui, Ruixiu
item MARLEY-HOLLINGSWORTH, ELIZABETH - Texas A&M University

Submitted to: Journal of Cotton Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2017
Publication Date: 12/17/2017
Citation: Wang, R., Thomasson, J.A., Cox, M.S., Sui, R., Marley-Hollingsworth, E.G. 2017. Cotton fiber quality prediction based on spatial variability in soils. Journal of Cotton Science. 21:220-228.

Interpretive Summary: High quality cotton at the farm level enhances price and makes the crop more marketable. Previous research found that cotton fiber-quality variation exhibits some correlation with soil-property variation. However, there has been no solid evidence that fiber-quality variation could be effectively predicted by soil parameters. Two years’ data of soil nutrient content and texture for two fields in Brooksville, Mississippi were studied with respect to their predictive capabilities in regard to fiber quality. Multiple regression analyses were conducted to determine whether fiber-quality factors could be effectively estimated from soil parameters, and spatial autocorrelation was considered. Kriging maps were produced for all measured parameters and for predicted micronaire values. It was found that a notable amount of variation existed in most of the soil parameters and in some cotton fiber-quality factors. Cotton fiber micronaire exhibited relatively large variability among fiber-quality parameters. An intelligent information system that can store and analyze multi-year and multi-field data sets might be useful in finding a more effective prediction method for micronaire.

Technical Abstract: Maintaining cotton fiber quality is crucial for the continued success of the U.S. cotton (Gossypium hirsutum L.) industry. Previous studies have indicated that spatial variability of fiber-quality parameters exists in cotton fields. Site-specific fiber-quality prediction could conceivably enable in-harvest fiber segregation in order to increase a producer’s overall crop price, or the crop could be managed to optimize fiber quality with respect to profitability. Micronaire (related to fiber maturity and fineness) was identified as the target parameter for quality segregation because of its relative importance to the textile industry and moderate variation at the farm-field level. Two years’ cotton and soil data from two fields in Brooksville, Mississippi were used to investigate the extent to which soil parameters could explain spatial variation in cotton fiber-quality. Multiple-linear regression was employed, and spatial autocorrelation was considered but found not to be a factor. Spatial variability existed in both soil and cotton-quality parameters, and micronaire was found to have relatively large variability compared to other quality parameters. Soil variability explained only about a fourth to a third of the variation in micronaire. Site-specific prediction of micronaire based on soil parameters alone thus appears impractical according to the results of this study.