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.
Cotton fiber length parameters are used across the cotton industry to select elite germplasm, purchase cotton bales and manage mill throughput. The High Volume Instrument (HVI) provides the most commonly used fiber length parameters, upper half mean length (UHML) and uniformity index (UI). UI is the ratio of mean length (ML) to the UHML expressed as a percentage. These length parameters, UHML and ML, are generated following the fibrograph principle and are highly correlated with two span lengths on the fibrogram curve. These two length parameters represent a small part of the fibrogram and do not characterize the total within-sample variation. In previous studies, we found that fiber length variation captured by the whole fibrogram improves the prediction of yarn quality. However, HVIs are currently calibrated for UHML and UI. In this study, we investigated a correction method using a set of 461 commercial samples to correct the whole fibrogram curve across HVIs and validated the method using an independent set of 932 commercial samples. The correction procedure lowers the Euclidian distance between fibrograms as much as 35%, bringing the fibrogram measurements into agreement across multiple HVIs. This indicates that the whole fibrogram could be used to improve HVI fiber length measurements across the cotton industry.
Fiber length is a crucial property throughout many textile processing steps. The high volume instrument (HVI) is the most commonly used tool to assess the properties of cotton fibers. The HVI currently reports two length parameters, the upper-half mean length (UHML) and uniformity index (UI). The UI is the ratio of mean length (ML) to the UHML expressed as a percentage. UHML and ML are extracted from the fibrogram. These parameters are used in the current U.S. cotton classification and global cotton marketing systems. The two values are highly correlated and characterize only the longer fibers in a sample. The fibrogram holds more descriptive information than the two measurements provided by the HVI. However, limited information is available about the stability and repeatability of the fibrogram measurement. This study aims to investigate the stability of the fibrogram, assess the reproducibility across multiple instruments, and determine if corrective actions are required. Three different raw cotton sample sets were tested for this three-stage experiment. The obtained results demonstrate that for a given HVI, the entire fibrogram is stable over both the short term and long term; however, differences among HVIs were observed. The proposed correction procedure effectively reduces the differences among the four HVI lines.
Fiber length is an important parameter to spin cotton fibers. Cotton breeders work to improve length, and research samples may be machine-harvested, resulting in variability for trash content between samples within the same experiment. There is evidence that trash may directly or indirectly affect the measurement of some fiber quality parameters like micronaire and strength. We hypothesize that the presence of trash particles in the samples may compromise the quality of the length measurement and screening decisions in breeding programs. In order to test this hypothesis, we developed an experiment to evaluate the heritability of length parameters for entries with the same genetic background and affected by the same environment with different trash content. The heritability estimates for samples with high trash content are different from the estimates for samples with native low trash content. Cleaning trashy samples with a laboratory-scale lint cleaner brings the heritability estimates closer to the calculated values for samples with native low trash content. Although the values are similar, the types of variation are not the same. These results indicate that breeders must avoid making decisions based on samples with high trash content. Breeders should base their decisions on samples with low original trash content because this type of sample provides research results closer to the native length distribution.
Cotton fiber length is one of the most critical parameters of fiber quality for ring-spun and air-jet-spun yarns. Currently, two of the most common instruments for testing cotton fiber length are the USTER High Volume Instrument (HVI) and the USTER Advanced Fiber Information System (AFIS). The HVI bases its length measurement on the fibrogram concept. It is fast but reports only two length measurements—the upper half mean length (UHML) and the uniformity index (UI), where the UI is the percentage ratio of mean length (ML) to UHML. The AFIS is slower and more costly per test because it individualizes fibers to provide a complete fiber length distribution per sample. This paper presents a method that can reconstruct a complete fiber length distribution from an HVI fibrogram based on established fibrogram theory. Results show that the algorithm can accurately recover different types of distributions based on synthetically generated data. Results also show that reconstructed distributions of three different types of samples—upland, pima, and viscose—differ in ways that make sense based on known characteristics of their length distributions. Finally, a variety of statistics computed from the reconstructed distributions are compared to the HVI-reported length parameters. Results show a good correlation with HVI output with R2 ranging from 0.730 to 0.965 across nine different methods of calculating the ML, UHML, and UI. Interestingly, statistics calculated from an approximation of the length distribution by weight are the most closely related to the HVI length parameters.
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