Genetic selection for wool quality.

Jafari, Seyyed Asghar

doi:10.1079/pavsnnr201510017

Cited by 3 publications

(3 citation statements)

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“…However, in the present paper a novel ‘To To’ simple numerical method was used to solve the polynomial equations of degree n,

y = P_{n} (x) = \sum_{i = 0}^{i = n} a_{i} x^{i} = 0

(where a is any real number). To convert the equation of degree n to a system of n equations of degree one, Equation is suggested:

y_{m} - a_{m} = x \sum_{i = m + 1}^{n} a_{i} x^{i - m - 1}

where n is an integer, y m are a series of lines from m = 0 to m = n − 2 and include the line corresponding to m = n − 1 which are called the reflection lines and the criteria line respectively. Both extreme roots are found by periodic reflections between the reflection lines and the criteria line until they embrace each other at a certain point, which is the approximate root of the equation.…”

Section: Theory and Calculationsmentioning

confidence: 99%

“…Interested readers are referred to the original paper for the pure mathematics of the ‘To To’ numerical method. However, from an analytical point of view, it must be stated that the ‘To To’ method is capable of solving algebraic equations by finding the most extreme roots firstly by any initial assumptions (unlike most other numerical methods, e.g.…”

Section: Theory and Calculationsmentioning

confidence: 99%

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A novel utilisation of principal component analysis to optimise sorption isotherms and determine diffusion coefficients of five naphthalimide disperse dyes on polyester fibres

et al. 2013

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Experimental data was gathered from more than 700 dyeings of polyester fibres with five naphthalimide disperse dyes. The dyeing process which was the same for all the dyes was carried out separately at five different temperatures, namely: 40°, 60°, 80°, 100° and 120° centigrade. Dye sorption was measured at 10 min time intervals at each temperature until the completion of the dyeing process. Additionally, the raw data was modified by the principal components analysis (PCA) in order to extract the highly informative part of the raw data (i.e. principal components). Such modified data was correlated with the six main sorption models. The results illustrate that unmodified raw data fit a dual combination of sorption models of the Nernst–Freundlich or Nernst–Scatchard type. However, the novel utilisation of PCA‐modified data illustrate that a linear Nernst type sorption model is appropriate, making it less dependent on dye structure and aggregation. The validity of this approach was confirmed by sensitivity analysis, affinity calculations and diffusivity determination. Furthermore, a novel ‘To To’ numerical method worked extremely well in determining diffusion coefficients based on the Hill's approximate solution.

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“…However, in the present paper a novel ‘To To’ simple numerical method was used to solve the polynomial equations of degree n,

y = P_{n} (x) = \sum_{i = 0}^{i = n} a_{i} x^{i} = 0

(where a is any real number). To convert the equation of degree n to a system of n equations of degree one, Equation is suggested:

y_{m} - a_{m} = x \sum_{i = m + 1}^{n} a_{i} x^{i - m - 1}

Section: Theory and Calculationsmentioning

confidence: 99%

Section: Theory and Calculationsmentioning

confidence: 99%

A novel utilisation of principal component analysis to optimise sorption isotherms and determine diffusion coefficients of five naphthalimide disperse dyes on polyester fibres

et al. 2013

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“…As a new breed of fine-wool sheep, the body weight and wool production-related traits of Alpine Merino sheep are essential and complex quantitative traits with polygenic inheritance [ 20 – 24 ]. With the continuous improvement and cost reduction of NGS (Next Generation Sequencing) technologies [ 25 ], QTL analysis using SNPs from WGR has become an emerging approach [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR

Zhang,

Lu,

Guo

et al. 2024

BMC Genomics

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Background The Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program. Results In this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers). Conclusions The first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.

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A review on some factors affecting wool quality parameters of sheep

Gelaye¹,

Sandip²,

Mestawet³

2021

AJFAND

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Wool is a natural fibre with a unique amalgamation of properties that are exploited in garment industry. The wool industry, in particular the production of fine wool, has a notable role in world trade and the price of the wool is dependent on quality. Accordingly, wool characteristics have direct impact on wool prices set by processors and industry. These properties can particularly benefit the wearer of the garment during exercise. There are different factors affecting wool quality parameters both with direct and indirect involvement. The environmental and genetics are the main factors affecting quality and quantity of wool from sheep. Infections related to skin and parasitic infestations have direct influence on the quality of wool. Breed or genotype is one of the main genetic factors that influences the product and productivity as well as quality of wool from sheep that is fleece from different sheep breeds is different in its both physical and chemical characteristics. Hormonal changes in relation to sex of sheep also have effect on the wool quality traits. The main objective of this review was to define and explore key wool characteristics, such as staple length, number of crimp, fibre type, fibre diameter, wool wax and scouring yield in regards to quality and interventions approaches for improving. In most of studies, non-genetic factors such as age, season, shearing period, shearing frequency and nutrition have a significant effect on traits viz. staple length, wool wax, scouring yield, fibre diameter and for other traits as well. Conducting a research on wool quality characteristics is an operative way of defining and differentiating the quality of wool. Acquiring knowledge of the wool quality characteristics can help to manage the end use products, consumers comfort and processing intensity. Therefore, an understanding of the factors affecting physical and chemical properties of wool traits is important to improve the quality of wool through genetics and management interventions. This article reviews some important quality attributes of wool for the product and productivity development and value addition.

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Genetic selection for wool quality.

Cited by 3 publications

References 0 publications

A novel utilisation of principal component analysis to optimise sorption isotherms and determine diffusion coefficients of five naphthalimide disperse dyes on polyester fibres

A novel utilisation of principal component analysis to optimise sorption isotherms and determine diffusion coefficients of five naphthalimide disperse dyes on polyester fibres

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR

A review on some factors affecting wool quality parameters of sheep

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