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Decreased aquifer water in the Texas High Plains has increased the risks associated with irrigation, including lower irrigation volume and the need to balance seasonal water demands among crops, requiring management of both irrigation rate and timing. Boll distribution measurements in cotton (Gossypium hirsutum L.) can be used to quantify the effects of irrigation on productivity and were used in a study of irrigation rate × timing from 2011 to 2013 in Halfway, TX. Field experiments quantified cotton boll distribution using three in-season irrigation levels (maximums of 0 , 3.2 , and 6.4 mm d -1 ) during three different irrigation periods determined by accumulated growing degree days (GDD) based on the threshold of 15.6°C: period 1 (P1, <525 GDD), period 2 (P2, 525-750 GDD), and period 3 (P3, >750 GDD). Combinations of these factors resulted in 27 irrigation treatments, applied with a low energy precision application (LEPA) pivot. Heavy irrigation early in the growing season used more water, did not increase boll number, and was often detrimental to yield. Mid-and late-season irrigation improved yield and fiber quality, with P2 irrigation influencing yield in the middle of the plant and P3 irrigation controlling yield at the top of the plant. Moderate irrigation later in the season minimized effects of short-term water deficit observed in other similar studies. These results provide insight into optimizing cotton water use in a region with declining crop water availability, increased pumping restrictions, and a challenging climate.
Variation in cotton fiber length impacts processability at the mill and the quality of spun yarns. The High Volume Instrument (HVI) and Advanced Fiber Information System (AFIS) are cotton fiber quality assessment instruments able to quickly assess a myriad of fiber quality characteristics. HVI testing provides the fiber length parameters most widely utilized by the cotton industry, Upper Half Mean Length and Uniformity Index. However, HVI fiber length parameters do not account for the complete within-sample variation in fiber length, such as the shortest fibers in the sample. AFIS testing is able to characterize the complete within-sample distribution of fiber length within a sample of cotton by evaluating individual fibers. Within-sample variation in fiber length is an important cotton fiber quality concern because it impacts processing performance and yarn quality. In this paper, the fiber length for 9127 commercial cotton bales was evaluated on both HVI and AFIS. The AFIS length distributions are used to characterize the complete distribution of fiber length within each bale. A novel statistical technique is introduced and is used to characterize a set of multivariate axes that characterize the total within-bale variation in fiber length among the complete set of commercial bales. These results suggest that less than half of the variation in cotton fiber length captured by the AFIS length distributions is captured by the two length parameters provided by HVI testing. If an experimental factor has no significant impact on an HVI fiber quality parameter, an alternative cotton fiber length measurement such as the AFIS length distribution should be considered.
Within-sample variation in cotton fiber length is important when explaining variation in yarn quality. However, typical High Volume Instrument (HVI) length parameters, the Upper Half Mean Length (UHML) and Uniformity Index (UI), do not characterize the total within-sample variation in fiber length. HVI fiber length measurements are based on the fibrogram principle where the HVI generates a curve called a fibrogram and reports the UHML and UI. Our results, based on 19,628 commercial bales, reveal that the typical HVI length measurements do not characterize unique types of length variation. Fibrograms from a subset of 538 commercial samples suggest that the fibrograms capture additional within-sample variation in fiber length that is not being currently reported. Two additional sets of samples were then used to evaluate the importance of this additional length variation. Partial Least Square Regression models and leave-one-out cross-validation reveal that the HVI fibrogram explains yarn quality better than current HVI length parameters and is comparable with the Advanced Fiber Information System (AFIS) length distribution by number. The validation results show that the models built with the HVI fibrogram are better than models with the current HVI length parameters and at least as good as the AFIS length distribution by number when predicting yarn quality. Fiber length variation captured by the whole fibrogram could provide a new tool to breeders for selecting breeding lines and spinners for purchasing cotton bales.
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