Evaluating cotton length uniformity through comprehensive length attributes measured by dual-beard fibrography

Zhou, Jinfeng; Xu, Bugao

doi:10.1007/s10570-020-03326-z

Cited by 9 publications

(4 citation statements)

References 17 publications

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“…Such DBIM used the gray transmission image of beard, narrowed clamping, and Lambert-Beer law and was corrected by empirical formulas of white cotton fibers, which proved to be in high agreement with both HVI and AFIS. In 2018 and 2020, Jin (Jin et al 2018) and Zhou Xu 2020, 2020) estimated algorithms to obtain the fiber frequency distribution using the Lambert-Beer law, respectively. However, the applied L-B law (Strong 1952) only involves absorption light in optical density calculation, resulting in significant errors in colored and thicker fiber beards for the effects of nonnegligible scattered and reflected light.…”

Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Secondary-approximate reflectivity and fluffiness coupled optical correction algorithm for colored cotton fibrogram of random-beard image method

et al. 2022

Preprint

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Fiber length is one of the essential and tricky-to-get characteristics of colored cotton fibers, which affects the spinnability and quality of blending yarns. Based on the optical theory and structure traits of fiber assemblies, an optical method named Random-Beard Image Method (RBIM) was proposed for measuring linear density distribution, fibrogram, of dyed and natural colored cotton fiber beards. This method involves a new two-level prediction model of reflectance and an optical algorithm for beard bulkiness. Fibrograms of 22 different cotton samples in total were tested to verify such algorithms and compared with those by the international standard method, Advanced Fiber Information System (AFIS). The average error between RBIM and AFIS was turned to be lower by 3.22%, and an excellent agreement of fibrograms between the two methods was also confirmed by Bland-Altman analysis. Meanwhile, an exceptionally high linear correlation on the average weight length of these two methods was achieved with insignificant deviation under a significance level of a = 0.01 with the T-test.

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Section: Introductionmentioning

confidence: 99%

WITHDRAWN: Secondary-approximate reflectivity and fluffiness coupled optical correction algorithm for colored cotton fibrogram of random-beard image method

et al. 2022

Preprint

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“…Therefore, this study used multivariate statistical analysis to evaluate high-oleic rape. These methods have been applied in the comprehensive evaluation of rice [ 28 ], rape [ 14 ], cotton [ 29 ], millet [ 30 ], and peanut [ 31 ]. The evaluation results for this research showed that the approved rape varieties, No.1, 3, and 4 were in the top 10 of the evaluation, indicating that the data statistics were stable and reliable.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive evaluation of high-oleic rapeseed (Brassica napus) based on quality, resistance, and yield traits: A new method for rapid identification of high-oleic acid rapeseed germplasm

Chang

et al. 2022

PLoS ONE

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To scientifically evaluate and utilize high-oleic acid rape germplasm resources and cultivate new varieties suitable for planting in the Hunan Province, 30 local high-oleic acid rape germplasms from Hunan were used as materials. The 12 personality indices of quality, yield, and resistance were comprehensively evaluated by variability, correlation, principal component, and cluster analyses. The results of variability showed that except for oleic acid, the lowest coefficient of variation was oil content, which was 0.06. Correlation analysis showed that oil content was positively correlated with main traits such as yield per plant and oleic acid, which could be used in the early screening of high-oleic rape germplasm. The results of principal component analysis showed that the 12 personality indicators were integrated into four principal components, and the cumulative contribution rate was 62.487%. The value of comprehensive coefficient ‘F’ was positively correlated with the first, second, and fourth principal components and negatively correlated with the third principal component. Cluster analysis showed that 30 high-oleic rape germplasms could be divided into four categories consisting of 9 (30%), 6 (20%), 7 (23%), and 8 (27%) high-oleic rape germplasms, each with the characteristics of "high disease resistance", "high yield", "high protein", and "more stability". This study not only provides a reference basis for high-oleic rape breeding but also provides a theoretical basis for their early screening.

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“…Subsequently, many researchers have conducted studies on this method. 26,29,[36][37][38] However, the applied L-B law only involves absorption light in optical density calculation, resulting in significant errors in colored and thicker fiber beards for the effects of nonnegligible scattered and reflected light.…”

mentioning

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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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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Evaluating cotton length uniformity through comprehensive length attributes measured by dual-beard fibrography

Cited by 9 publications

References 17 publications

WITHDRAWN: Secondary-approximate reflectivity and fluffiness coupled optical correction algorithm for colored cotton fibrogram of random-beard image method

WITHDRAWN: Secondary-approximate reflectivity and fluffiness coupled optical correction algorithm for colored cotton fibrogram of random-beard image method

Comprehensive evaluation of high-oleic rapeseed (Brassica napus) based on quality, resistance, and yield traits: A new method for rapid identification of high-oleic acid rapeseed germplasm

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

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