Cluster and Principal Component Analysis for Seed Coat Resistibility and Its Related Traits of Cotton (Gossypium spp.) Genotypes

Authors: Fatih KILLI; Tahsin BEYCİOGLU
DIN
IJOEAR-JUN-2025-16
Abstract

During the ginning of seed cotton, the seeds can be broken and mixed into the fibers. The number of seed coat particles passing into the fibers and the amount of neps caused by the seed coatis an important factor that negatively affects the yarn quality and creates problems in dyeing. In this study, 200 different cotton genotypes were evaluated in terms of 100-seed weight, seed coat ratio, seed coat thickness and seed coat resistibility. As a result of the study, it was determined that 100-seed weights of genotypes varied between 7.23-15.43 g, seed coat ratios between 15.53-38.27%, seed coat thickness between 0.41-1.00 mm and seed coat resistibility between 41.07-107.21 newton. TxNo:142 genotype had the highest seed coat resistibility. In addition, it was determined that there was a positive and significant relationship between seed coat resistibility and 100-seed weight. In principal components analysis, two out of 4 principal components were selected with Eigenvalue >1. The two principal components contributed 59.3% towards variability. In cluster analysis, 200 genotypes were allocated in five clusters. Cluster IIwas the largest by having 90 genotypes while cluster V, cluster III, cluster I and cluster IVhaving 54, 28, 20 and 8 genotypes, respectively.

Keywords
Cotton seed traits seed coat
Introduction

Cotton, which constitutes the raw material of more than fifty industries, especially the textile and food industries, is one of the most important industrial plants. Cotton is the raw material of the textile and cellulose industry with its fiber, of the vegetable oil industry with the oil obtained from the kernel, and of the feed industry with its seed and meal. Approximately 90% of the fiber crops cultivation areas in the world are cotton. In our country, according to 2024 data, cotton was cultivated on approximately 467 000 hectares and 2.24 million tons of seed cotton was produced (Anonymous, 2024). According to Aydın Commodity Exchange data, in the 2023/2024 season, Turkey is the fourteenth country in terms of cultivation area, sixth in terms of fiber cotton yield obtained from unit area, seventh in terms of fiber cotton production amount, fifth in terms of fiber cotton consumption and fourth in terms of fiber cotton imports in the world cotton market (Anonymous, 2023). Seed cotton harvested from the field contains fibers and kernels before processing. In order for the seed cotton to be sent to spinning mills, it must be cleaned from the kernels and other foreign materials (vegetable parts, dust, etc.). The process of separating cotton into kernel and fiber is called ginning (Kıllı, 2001). After the ginning process, fiber cotton is obtained as the main product and cottonseed is obtained as a by-product. On average, 35-40% of the seed cotton consists of fiber and 60-65% of seed.

The seed cotton obtained after harvesting is separated from the seeds by ginning. During ginning, the seeds may break and mix with the fiber cotton. After ginning, the number of seed coat particles and the amount of neps caused by seed coatis an important problem that negatively affects the yarn quality, creates problems in dyeing and reduces the quality and value of textiles (yarn and fabric). In our country, approximately 40% of baled cotton has seed coat problem (Özbek, 2017). The cottonseed coat has a 5-layered structure (Figure 1) (Yan et al., 2009).

FIGURE 1: Cottonseed coat structure a)Light microscope image of seed coat sectionb) Schematic view of seed coat anatomical structure. 1) epidermis layer, 2) outer pigment layer, 3) colorless layer, 4) palisade layer, 5) inner pigment layer, 6) cotton fiber, 7) cutin (Yan et al., 2009).

Cellulose and pectin are the main components of the epidermal layer surrounded by cutin and wax; pectin, hemicellulose and lignin are the main components of the palisade layer; and lignin-like compounds are the main components of the inner and outer pigment layer (Yan et al., 2009). During the ginning of seed cotton after harvest, seed coats can be broken and mixed into the fibers. Approximately 30% of the negative effects in textile products are attributed to seed coat particles and it is emphasized that seed coat particles in ginned fiber cotton can vary by 50% depending on cotton varieties (Bel and Xu, 2011). Principal component analyses (PCA) and biplot approaches are an approach that provides the opportunity to visually present and evaluate the relationships between the examined parameters and genotypes at the same time (Kahraman et al., 2021). There is a need to use principal component analysis to demonstrate the results of cotton breeding research. Therefore, many researchers (Abasianyanga et al., 2017; Nandhini et al., 2018; Shah et al., 2018; Vinodhana and Gunasekaran, 2019; Abdel-Monaem et al., 2020; and Yehia and El-Hashash, 2021) have used PCA to know the relationships among yield and yield components, as well as to evaluate the relationship and diversity among various cotton germplasms. This study aimed to evaluate the genotypes and the relationship between seed coat breaking resistance and seed weight, seed coat ratio and seed coat thickness traits in 200 different cotton genotypes.

Conclusion

The analysis of variance revealed that there were sufficient variations among cotton genotypes for seed coat resistibility and its related traits. The results showed the presence of significant differences (P ≤ 0.01) among the tested genotypes for all traits. Cluster analysis revealed that the 200 cotton genotypes were grouped into 5 clusters. The principal component analysis extracted two principal components PCA1 to PCA2 from the original data having Eigenvalues greater than one accounting nearly 59.3% of the total variation. Cluster analysis classified the 200 cotton genotypes into five distinct clusters contained 8-90 genotypes. This indicated the presence of diversity among the tested cotton genotypes. The relationships between traits identified through biplot analysis were consistent with Pearson’scorrelation coefficients, showing positive correlations between 100-seed weight and seed coat resistibility. A significant count of cotton genotypes are used in the study, and this diversity provides the opportunity to select genetic types with desirable seed coat resistibility trait for use inbreeding programs.

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