Investigation of a Multivariate Correction Method for HVI Fibrogram Measurements

Sayeed, Abu; Kelly, Brendan; Turner, Chris; Héquet, Eric

doi:10.3390/agronomy12020460

Cited by 3 publications

(5 citation statements)

References 26 publications

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“…It was apparent that almost all samples had a lower bias rate using the proposed theoretical reflectance than that adopting the ideal and original reflectance, except for 10# and 18#, with a slightly larger difference of 0.04% and 0.13% than the ideal R 1 . Hence, this method was demonstrated to be effective, and red light was employed in the following study for higher light penetration than the others just as that of the HVI 18,19 and AFIS. 20,22…”

Section: Resultsmentioning

confidence: 99%

“…15 However, HVI cannot provide efficient data for colored cotton and short fiber content because of ignoring material reflectance and scattering in the L–B law. 16–19 In comparison, the AFIS system uses infrared light to measure at least 3000 single fibers, straightened by airflow. 3,20,21 Although its principle was unclear, 22,23 it was proved to have high consistency with HVI using the beard for raw cotton.…”

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confidence: 99%

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Reflectivity and fluffiness coupled optical algorithm for colored cotton fibrogram of random-beard image method

et al. 2023

Textile Research Journal

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Insufficient studies of reflectance and fluffiness effects on optical density caused large derivation and limited the application of fibrogram methods in colored cotton fiber length tests for decades. A coupled optical method was proposed here to solve this issue, named reflectivity and fluffiness coupled optical algorithm of the random-beard image method. In this algorithm, a defined theoretical reflectance was declared with an iteration method for optical linear density on the optical analysis of the derived Kubelka–Munk law, which satisfied its assumption of excluding reflected light at the interface with air. Meanwhile, an apparent polynomial relationship was revealed between the actual density and optical densities of fiber assemblies at different fluffiness. Its accuracy on weighted mean fiber length was demonstrated, referred to as advanced fiber information system, using 10 kinds of dyed cotton slivers and 12 kinds of naturally colored lint fibers whose mean and maximum absolute errors are 0.59 mm and 1.6 mm, respectively. Furthermore, their excellent agreement on fibrograms and the weighted mean length was confirmed by Bland–Altman analysis, correlation analysis and the T-test. Finally, an exceptionally high linear correlation (r2 = 0.93) was achieved on their weighted mean length and had no statistical difference with insignificant deviation under a significance level of a = 0.01. This new algorithm, featured fast and low cost, could provide accurate mean fiber length of colored or dark cotton, exhibiting valuable guidance in the potential application of the fiber trade and the quality control of colored cotton fibers or primaries in blending assemblies and yarn.

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Reflectivity and fluffiness coupled optical algorithm for colored cotton fibrogram of random-beard image method

et al. 2023

Textile Research Journal

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“…In 2021, Sayeed et al demonstrated that the whole fibrogram curve captures additional fiber length information than what is provided by the current HVI length parameters [24]. Later, they developed a method to calibrate the whole fibrogram and showed that the whole fibrogram could be calibrated to bring the measurement to a similar level across multiple HVIs [33]. Addisu et al showed that several span lengths can be calibrated to compare the fibrogram measurements across multiple HVIs [34].…”

Section: Introductionmentioning

confidence: 99%

A New Method to Calculate Cotton Fiber Length Uniformity Using the HVI Fibrogram

et al. 2023

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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.

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“…Using the complete fibrogram curve, they used principal component analysis to extract three independent variables from the fibrogram to represent the variation captured by the entire curve and showed that these three variables predict yarn quality better than the current HVI length parameters. Later, Sayeed et al 15 developed a multivariate correction method to align the fibrogram measurement as a whole curve across multiple HVIs and demonstrated that it is possible to bring the fibrogram measurements at a similar level across many HVIs. Also, Tesema et al 16 showed that the whole fibrogram curve is stable and repeatable over long-and shortterm periods for a single HVI by examining several span lengths along the curve.…”

mentioning

confidence: 99%

“…Later, Sayeed et al. 15 developed a multivariate correction method to align the fibrogram measurement as a whole curve across multiple HVIs and demonstrated that it is possible to bring the fibrogram measurements at a similar level across many HVIs. Also, Tesema et al.…”

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confidence: 99%

Reconstruction of the cotton fiber length distribution from a High Volume Instrument® fibrogram

Turner

Sayeed

Héquet

2022

Textile Research Journal

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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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Investigation of a Multivariate Correction Method for HVI Fibrogram Measurements

Cited by 3 publications

References 26 publications

Reflectivity and fluffiness coupled optical algorithm for colored cotton fibrogram of random-beard image method

Reflectivity and fluffiness coupled optical algorithm for colored cotton fibrogram of random-beard image method

A New Method to Calculate Cotton Fiber Length Uniformity Using the HVI Fibrogram

Reconstruction of the cotton fiber length distribution from a High Volume Instrument® fibrogram

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