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 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.

Knowledge of cotton fiber length uniformity is important for the cotton industry. The accurate and reliable measurement of fiber length uniformity would allow cotton breeders to release new cotton varieties with improved fiber length variation. This knowledge would also help spinning mills to optimize their machine setup, which would improve yarn processing performance. Currently, the high volume instrument (HVI) is most commonly used to characterize the cotton fiber length variation. The HVI length measurement is based on the fibrogram principle. The HVI length measurement characterizes 2 points, 1.8% as the upper half mean length (UHML) and 7.8% span length as the mean length (ML) from the fibrogram, and reports UHML and uniformity index (UI). The ratio of ML to the UHML is used to calculate the UI and is expressed as a percentage. UI measurement does not represent the shorter fibers as the above two span lengths only represent the longest fibers within a sample. We propose to calculate the uniformity of the cotton fiber length using the complete fibrogram as an alternative. First, the area of the measured fibrogram curve is calculated. Second, the area of a theoretical mono-length fibrogram with a length equal to the maximum length of the fibers for the same sample is calculated. Finally, we calculate a new length uniformity as the ratio of the measured fibrogram area to the mono-length fibrogram area expressed as a percentage. Based on the results obtained using a set of 991 commercial samples, the new length uniformity shows promise. We also applied this new length uniformity to a set of 60 commercial-like samples and developed partial least square regression (PLSR) prediction models to predict yarn quality. The results obtained demonstrate that the new length uniformity predicts yarn quality better than the current UI.

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.