Spatial variation of fiber quality and associated loan rate in a dryland cotton field

Spatial variation of fiber quality and associated loan rate in a dryland cotton field A field study was conducted in 2006 in a dryland cotton field in Texas, USA, to explore the spatial variation of cotton fiber quality and the loan rate associated with it. A total of 66 cotton samples were hand-harvested, and the fiber quality properties investigated included the High Volume Instrument measurements of micronaire, length, uniformity, strength, elongation, reflectance (Rd) and yellowness (+b). Conventional statistics showed a generally low level of variation in fiber quality with coefficients of variation <10%. Variogram analysis showed that all fiber quality properties were spatially correlated. Contour maps of individual fiber quality properties were produced from block kriged estimates. Fiber length, uniformity, strength and Rd were positively correlated, and all of these were negatively correlated with +b. The spatial distribution of most fiber quality properties was similar to that of soil apparent electrical conductivity, suggesting that water holding capacity could be a limiting factor for cotton fiber quality. Maps of individual fiber quality properties were combined with the United State Department of Agriculture—Commodity Credit Corporation Loan Schedule for Upland Cotton to create a loan rate map that is associated with fiber quality. A loan rate difference of 20 cents kg–1 was observed within the field. This level of difference indicated that fiber quality at the field level can have a large impact on producers’ revenue. A site-specific management system encompassing both lint yields and fiber quality is strongly recommended for cotton production. Precision Agriculture Springer Journals

Spatial variation of fiber quality and associated loan rate in a dryland cotton field

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Springer US
Copyright © 2008 by Springer Science+Business Media, LLC
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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