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ARS Home » Southeast Area » Stoneville, Mississippi » Cotton Ginning Research » Research » Publications at this Location » Publication #257467
Title: Cotton revenue apportioned between lint yield and fiber quality: a precision agriculture perspective

Author
item GE, YUFENG - Texas A&M University
item THOMASSON, J. ALEX - Texas A&M University
item MORGAN, CRISTINE L.S. - Texas A&M University
item STANISLAV, SCOTT - Texas A&M University
item Sui, Ruixiu

Submitted to: Journal of Cotton Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/7/2011
Publication Date: 1/26/2012
Citation: Ge, Y., Thomasson, J., Morgan, C., Stanislav, S., Sui, R. 2012. Cotton revenue apportioned between lint yield and fiber quality: a precision agriculture perspective. Journal of Cotton Science. 15:274-281.

Interpretive Summary: Cotton fiber quality was emphasized by breeders, ginners, and textile processors, but it has not aroused much attention among producers. A producer’s view of cotton loan rates (determined by several fiber quality parameters, such as color and micronaire) is mostly in terms of a price adjustment applied to a cotton bale, rather than a revenue component that may be spatially variable in the field. Many believe that cotton fiber quality is determined by genetics, but a number of recent studies have shown that in-field variation of cotton fiber quality existed and was significantly related to soil properties, pointing to the possibility of site specific management for fiber quality improvement. One critical question that has not been answered by these studies is: Is it economically advantageous for cotton growers to manage fiber quality variability? Unlike lint yield, which is directly proportional to a grower’s revenue, fiber quality parameters have a rather complex and non-linear relationship with revenue. It would thus be useful to convert the fiber quality variation into an economic term (namely, $ ha-1) so that the importance of fiber quality can be directly compared with that of lint yield. Such a comparison would help growers to better understand the factors affecting their revenue, and whether and how it would be worthwhile to implement site specific management according to fiber quality. Field studies were conducted in two cotton fields near College Station, TX. Lint yield and fiber quality data were collected. Loan rate maps were produced by integrating fiber quality parameter maps with the USDA-CCC Loan Schedules; and gross revenue maps were produced by combining lint yield and loan rate maps. In-field variation of revenue was decomposed into two components: one associated with in-field variation of lint yield and the other associated with in-field variation of fiber quality. It was found that while lint yield was the primary factor in determining overall revenue, the contribution from fiber quality was quite significant and should not be overlooked, especially when high input costs and small profit margins are considered.

Technical Abstract: The issue of cotton fiber quality has been emphasized by breeders, ginners, and textile processors but has not aroused much attention among growers. Whereas many studies have shown in-field variation of cotton fiber quality, the variation observed is usually small compared to that of lint yield, casting doubt on the usefulness of site specific management for fiber quality improvement. The overall goal of this study was to elucidate the inter-related effects of lint yield and fiber quality on in-field revenue variation. With more clarity in this regard, growers can better understand how to improve revenue, and whether and how it would be worthwhile for them to manage fiber quality site specifically. Field studies were conducted in two cotton fields near College Station, TX. Lint yield and fiber quality data were collected. Loan rate maps were produced by integrating fiber quality parameter maps with the USDA-CCC Loan Schedules; and gross revenue maps were produced by combining lint yield and loan rate maps. By using an empirical method, in-field variation of revenue was decomposed into two components: one associated with in-field variation of lint yield and the other associated with in-field variation of fiber quality. The results showed that, for the first field, the standard deviation (SD) of revenue was 181 $ ha-1, of which 23 $ ha-1 was attributable to fiber quality variation. In the second field, the SD of revenue was 216 $ ha-1, of which 55 $ ha-1 was attributable to fiber quality variation. While lint yield was the primary factor in determining overall revenue, the contribution from fiber quality was quite significant and should not be overlooked, especially when high input costs and small profit margins are considered.