Cotton Quality Research Articles

Cotton is a globally important crop, with fiber quality traits governed by complex quantitative trait loci (QTL). However, the utility of QTL data is often limited due to inconsistencies across studies. This study conducted a comprehensive Meta-QTL (MQTL) analysis by integrating 2864 QTLs from 50 independent studies published between 2000 and 2024. Of these, 2162 high-confidence QTLs were projected onto a consensus genetic map using BioMercator V4.2.3, resulting in the identification of 75 MQTLs across the cotton genome. These MQTLs exhibited significantly reduced confidence intervals and enhanced statistical support, with 14 MQTLs reported for the first time. Several MQTLs, including MQTLchr7-1, MQTLchr14-1, and MQTLchr24-1, were identified as stable clusters harboring key fiber quality and stress tolerance traits. Candidate gene analysis within select MQTL regions revealed 75 genes, 38 of which were annotated with significant gene ontology terms related to lignin catabolism, flavin binding, and stress responses. Notably, GhLAC-4, GhCTL2, and UDP-glycosyltransferase 92A1 were highlighted for their potential roles in fiber development and abiotic stress tolerance. These findings provide a refined genomic framework for cotton improvement and offer valuable resources for marker-assisted selection (MAS) and functional genomics aimed at enhancing fiber quality, yield, and stress resilience in cotton breeding programs.

Cotton production is a crucial agricultural industry, a raw material source for the textiles sector and a major source of livelihood for more than 30 million farmers globally. The yield and quality of cotton (Gossypium) are influenced by different types of stress and diseases. Deep Learning as a solution for disease prevention, detection, and management can increase the yield, reduce the cost and improve the quality of crop. This study presents a robust method using 10-fold cross-validation with the YOLOv8 DL model for precise cotton leaf disease recognition. The k-fold cross-validation mitigates overfitting by training the model on diverse data subsets, which leads to enhanced generalizability while ensuring reliable performance. The proposed method achieved 99.60% and 100% as Top_1 and Top_5 accuracy, respectively. The method also achieved a recall of 99.53%, a precision of 99.53%, and an F1 score of 99.60%. During 10 trials, the method consistently performed with an average. Top_1 and Top_5 accuracy of 98.41% and 100% respectively, recall 98.53%, precision 98.39% and F1 score 98.42%.This study is among the first to apply YOLOv8 classification with 10-fold cross-validation for multi-class cotton leaf disease identification using field-captured images.

Comparative effects of ZnSO4 and ZnO-NPs in improving cotton growth and yield under drought stress at early reproductive stage.

Mechanical specimen preparation method for next-generation cotton quality testing using HVIs

Changes in atmospheric CO₂ concentration strongly affect the photosynthetic performance of C₃ plants. Cotton (Gossypium hirsutum L.), a major global cash crop, provides a suitable model to study CO₂ fertilization effects. While moderate CO₂ enrichment can promote growth and yield, the optimal regime for field-scale application remains unclear. In this study conducted in Xinjiang, China, CO₂ gas was dissolved in irrigation water at four concentrations (0.04, 0.08, 0.12, 0.16 kg·m-³) and applied via a drip irrigation system. The effects on canopy CO₂ distribution, plant physiological responses, yield, and fibre quality were assessed. Drip-applied CO₂ solutions increased canopy CO₂ concentration by gradually releasing CO₂ from the soil, which in turn enhanced plant growth indicators (SPAD, AGB, LAI, plant height). Growth promotion followed a dose–response trend, with effects rising at lower concentrations and declining at higher levels. Yield analysis showed that lint yield increased by 1.9% and 8.4% under 0.04 and 0.08 kg·m-³ treatments, respectively, compared with the control (p < 0.05). In contrast, 0.12 and 0.16 kg·m-³ treatments reduced yield by 13.4% and 5.4%, respectively (p < 0.05). Fibre quality indicators remained within the optimal range across all treatments. Overall, 0.08 kg·m-³ was identified as the most effective concentration, producing the highest yield while maintaining fibre quality. These findings provide a scientific basis for the field application of CO₂-enriched irrigation, offering a promising approach to enhance cotton productivity and the ecological sustainability of farmland systems.

ABSTRACT This study explores and discusses the fiber quality from pre-production cotton waste, spun using rotor technology, on fabrics for use in home textiles or denim. The shortage of primary cotton on the market and changes in cotton quality due to organic farming have prompted producers to find optimal ways to recover cotton from waste. However, the reuse of cotton fibers from cotton waste is limited due to fiber quality degradation. Specific cleaning channels C and A on the Rieter R 37 were used to compare the effect of contamination on the quality of the final products. The quality of fibers, yarns, and fabrics in the gray state and after bleaching was analyzed, and the influence of fiber contamination was evaluated. The yarn spun in cleaning channel C was of comparable quality to that spun in cleaning channel A but with better fiber utilization at the expense of contamination. No significant degradation of the final treated fabric was observed. Fabric contamination, mainly due to seed coat fragments, correlated with contamination levels in yarn spun from different fiber blends and decreased as the treatment process progressed.

Agricultural is the primary source of essential provisions almost all nation and remains as a vital survival tool for human race for past, present and future. The agriculture which remains as the bedrock of the civilizations is frequently being affected by devastating plant diseases leading to the loss of economy and food shortage. The manual testing requires high expertise, time and often leads to human error. Recent advancements in computer vision and AI models have highlighted the potential for building automatic plant disease detection models based on visible signs using image classification tasks. However, the task becomes complex and erroneous due to the complex nature of data. Consequently Deep Learning (DL) models tend to outperform others traditional methods through utilizing network topology with convolution layers in core. Projected system uses high quality Cotton Disease dataset sourced by Kaggle and provide a suitable solution to the aforementioned problem using advanced DL neural network namely Blend Unity Resqueeze Resnet approach which yields high accuracy with modification including Resqueeze layer and blend unity weights applied to do the tedious job of diagnosing plant diseases on image based classification. The proposed research outperforms the conventional methods achieving better accuracy of 92% with better precision and reliability. The outcome of the respective research is analyzed with suitable metrics and compared with the recent developed conventional algorithms in which the proposed model proves to be a better suited for the efficient plant disease classification. Hence, the proposed method is intended to contribute in the plant disease classification and assist the agriculturists significantly to prevent the losses due to crop diseases.

The elongation period of cotton fiber development is crucial for ensuring cotton quality. However, the molecular mechanisms underlying fiber elongation remain unclear. This study reveals that SER02_A11, which is preferentially expressed during the fiber elongation period, encodes serine protease inhibitors (serpins). A previously uncharacterized SNP517th is localized in the gene's coding region between Gossypium barbadense and G. hirsutum, leading to the premature translation termination and low expression of GhSER02 in G. hirsutum. However, in G. barbadense, normal protein translation and high expression of GbSER02 are observed. Ectopic GbSER02 expression or site‐directed GhSER02' mutagenesis (but not GhSER02) promotes trichome and root cell elongation in Arabidopsis, indicating that SNP517th causes the dysfunction of GhSER02. Overexpressing GbSER02 in G. hirsutum increases fiber length. GbSER02 interacts with the transcription factor GhVOZ1 (vascular one‐zinc‐finger protein) in the cytoplasm, alleviating the inhibitory effect of GhVOZ1 on GhGA3ox1 expression, thereby promoting gibberellin synthesis. Subsequently, the cell wall loosening‐related genes GhXTH2 and GhEXPA1 are significantly upregulated whereas the flavonoid metabolism‐related gene GhCHS1 is significantly downregulated, ultimately improving fiber length. Collectively, this study reveals the essential role of the GbSER02‐GhVOZ1‐GhGA3ox1 module in regulating fiber quality and provides novel insights into the mechanism of fiber development in cotton.

Effect of natural extracts alone or combined with a recommended herbicide on weed control, productivity and quality of cotton under different nitrogen levels

BackgroundVerticillium dahliae, a soil-borne fungi, can cause Verticillium wilt, and seriously diminish the yield and quality of cotton. However, the pathogenic mechanism of V. dahliae is complex and not clearly understood at the moment. This study aimed to identify the high-affinity nicotinic acid transporter genes in V. dahliae. The gene expression profiles in V. dahliae following sensing of root exudates from susceptible and resistant cotton varieties were analyzed. The function of VdNAT1 in the pathogenic process of V. dahliae was studied using the tobacco rattle virus (TRV)-based host-induced gene silencing (HIGS) technique.ResultsEight high-affinity nicotinic acid transporter genes were identified from V. dahliae through the bioinformatics method. Each protein contains a conserved major facilitator superfamily (MFS) domain, which belongs to the MFS superfamily. Evolutionary relationship analysis revealed that all 8 genes belong to the anion: cation symporter (ACS) subfamily. All proteins have transmembrane domains, ranging from 7 to 12. The expression levels of most VdNAT genes were significantly increased after induction by root exudates from susceptible cotton varieties. Silencing VdNAT1 gene by HIGS significantly inhibited the accumulation of fungal biomass in cotton plants, and alleviated the disease symptoms of cotton.ConclusionsEight VdNAT genes were identified from V. dahliae, and most VdNAT genes was up-regulated after induced by root exudates from susceptible cotton variety. In addition, VdNAT1 is required for the pathogenicity of V. dahliae. Overall, these findings will facilitate the pathogenic molecular mechanism of V. dahliae and provide candidate genes.

Casein kinase GhCKA1 positively regulates cotton resistance to Verticillium wilt.

High yield and fiber quality of upland cotton has been remained main focus of breeding programs. Breeders use various methods like interspecific hybridization, conventional hybridization with exotic germplasm, production of transgenic plants and mutagenesis in order to introduce variation in cotton, so that, they can use this change for development of cotton. This can only be possible with developments in the fields of biotechnology and molecular biology and exploring quantitative trait loci (QTL). To explore QTLs which has strong linkage to yield, agronomic, morphological and fiber quality traits, 80 SSR markers have been used in present study to find out the QTLs in the genetic structure of 100 Gossypium hirsutum accessions. Among the 80 SSR markers only 20 showed strong association with traits under study. The range of P value was 1.66E-13 to 2.69E-04 and of R2 was 0.13-0.44. Three markers, CIR0307, NAU5383 and NAU5499 were linked with fiber fineness; MGHES0034 and NAU5480 with fiber uniformity; BNL3594 and JESPR0153 with fiber strength and seed cotton yield; NAU2038 and BNL1066 showed their association with fiber elongation. Structure analysis was conducted with the aid of model-based software STRUCTURE of 100 cotton genotypes which showed a little admixture. The highest ..K value was observed at K = 6 which divided the genotypes into two subgroups; Group I had 45 cotton genotypes and Group II carried 55 cotton genotypes. The QTLs having strong linkage with desire traits will help the breeders to use information of QTLs for cotton improvement by marker assisted selection (MAS) program.. KEYWORDS :SSR markers, Gossypium hirsutum, QTLs, Fiber, Yield traits.

BackgroundHigh temperatures significantly impair the yield and quality of cotton. Ankyrin-repeat proteins (ANKs) are among the largest superfamilies of proteins in plants and play vital roles in both biotic and abiotic stress responses.ResultsIn this study, we identified and characterized members of the cotton ankyrin repeat protein (ANK) gene family, focusing on the ANK-TM subfamily member GhANK169, which was highly upregulated in the RNA-seq data of cotton plants exposed to 42 °C. Overexpression of GhANK169 in tobacco at 42 °C resulted in improved phenotypic resilience, enhanced antioxidant enzyme activity, and reduced relative electrolyte leakage (REL) and malondialdehyde (MDA) content. Conversely, silencing GhANK169 in cotton via virus-induced gene silencing (VIGS) renders plants highly susceptible to heat stress, with symptoms including accelerated water loss, reduced relative water content (RWC), elevated superoxide anion (O2-) and hydrogen peroxide (H2O2) levels, and diminished reactive oxygen species (ROS) scavenging capacity. Transcriptome sequencing revealed that crucial genes associated with ABA signaling, ROS response, endoplasmic reticulum protein quality control, cytoskeleton maintenance, and substance transport were affected in the treated plants.ConclusionThis study enhances our understanding of the cotton ANK gene family and offers valuable genetic resources for improving cotton heat tolerance mechanisms and breeding strategies.

The aim of this study is to precisely elucidate the control efficacy of drip irrigation herbicide application against broadleaf weeds and comprehensively assess its safety to cotton. Broadleaf weeds were managed through the application of herbicide in the cotton field. The herbicide was dispensed from a fertilizer tank in tandem with water droplets. A field investigation was conducted via a fixed-point investigation method to assess the herbicide residue levels and the safety of the cotton crop from 2022 to 2023. When 100.8 g a.i./hm2 of 48% Flumioxazin SC was applied via drip irrigation, it had no adverse effect on cotton safety at the mature stage. During the fruit-setting stage, it exhibited a significant weeding effect on annual broadleaf weeds such as Solanum nigrum L. and Chenopodium album L. Analysis revealed no pesticide residues in cotton and cottonseeds. Soil pesticide residues were found to be at a low level. The cotton yield reached 5618.1 kg/hm2, and the cotton quality met the national standard requirements. For the control of broadleaf weeds in cotton fields, the application of 100.8 g a.i./hm2 of 48% Flumioxazin SC via drip irrigation can effectively control broadleaf weeds. This method can suppress annual broadleaf weeds, with S. nigrum and C. album being the dominant weed communities, without compromising the safety and quality of cotton. Although drip irrigation technology offers advantages such as time savings and reduced labor demands, it is essential to adopt appropriate weed control techniques tailored to the specific conditions of different cotton fields.

Cotton production plays an important role in India’s farming and industry, supporting the country’s economy, jobs and textile exports. This review looks at the Strengths, Weaknesses, Opportunities and Threats (SWOT) of cotton farming in India. Some key strength includes suitable weather, large areas of farmland and help from research centres like CICR (Central Institute for Cotton Research) and ICAR (Indian Council of Agricultural Research). Government support through subsidies and minimum price guarantees also adds value. On the other hand, there are several weaknesses such as too much reliance on rain, insufficient irrigation, low crop yields, pest problems, high costs for seeds and fertilizers, small land sizes and limited use of machines. These problems reduce the quality and quantity of cotton thereby makes it harder to compete globally. Still, there are many opportunities to improve. Using better seeds, modern farming tools and smart practices like precision farming can boost production. There is also growing demand for organic and eco-friendly cotton, which India can take advantage of adding value through better processing, branding amidst government initiatives that augment farmers’ earnings. However, there are threats that need attention viz; climatic changes, water shortages, vermin pests and price swings in the market that could impact farmers. The rise of synthetic fibres and unclear policies also bring challenges. Environmental concerns and the need for standards like Fair Trade and GOTS (Global Organic Textile Standard) are becoming more important. To face these issues, the focus should be on saving water, reducing waste and employing better technological advancements. In the end, the cotton sector in India needs a careful mix of modern tools, strong policies and eco-friendly steps to stay strong and succeed in the future. This review underscores the need for a balanced approach integrating technological advancements, policy support and sustainable practices to navigate challenges and leverage opportunities that ensuring the long-term viability and competitiveness of India’s cotton industry.

The continuous provision of nitrogen (N) to the crop is critical for optimal cotton production; however, the constant and excessive application of synthetic fertilizers causes adverse impacts on soil, plants, animals, and human health. The current study focused on the short-term effects (one-year study) of adding different rates of clinoptilolite zeolite, as part of an integrated nutrient management plan, and different rates of inorganic N fertilizer to improve soil and crop performance of cotton in three locations (ATH, MES, and KAR) in Greece. Each experiment was set up according to a split-plot design with three replications, three main plots (zeolite application at rates of 0, 5, and 7.5 t ha−1), and four sub-plots (N fertilization regimes at rates of 0, 100, 150, and 200 kg N ha−1). The results of this study indicated that increasing rates of the examined factors increased cotton yields (seed cotton yield, lint yield, and lint percentage), with the greatest lint yield recorded under the highest rates of zeolite (7.5 t ha−1: 1808, 1723, and 1847 kg ha−1 in ATH, MES, and KAR, respectively) and N fertilization (200 kg N ha−1: 1804, 1768, and 1911 kg ha−1 in ATH, MES, and KAR, respectively). From the evaluated parameters, most soil parameters (soil organic matter, soil total nitrogen, and total porosity), root and shoot development (root length density, plant height, leaf area index, and dry weight), fiber maturity traits (micronaire, maturity, fiber strength, and elongation), fiber length traits (upper half mean length, uniformity index, and short fiber index), as well as color (reflectance and spinning consistency index) and trash traits (trash area and trash grade), were positively impacted by the increasing rates of the evaluated factors. In conclusion, the results of the present research suggest that increasing zeolite and N fertilization rates to 7.5 t ha−1 and 200 kg N ha−1, respectively, improved soil properties (except mean weight diameter), stimulated crop development, and enhanced cotton and lint yield, as well as improved the fiber maturity, length, and color parameters of cotton grown in clay-loam soils in the Mediterranean region.

Late embryogenesis abundant gene GhLEA-5 of semi-wild cotton positively regulates salinity tolerance in upland cotton.

Boron (B) plays significant roles in the growth, development, yield and quality of cotton. However, there exists a very narrow gap between plant deficiency and toxicity limits of B. We conducted this field study, following a thrice replicated randomized complete block split-plot design (main: B levels and sub: genotypes), to evaluate the growth, yield, and boron-use-efficiency of five cotton genotypes (Sohni, Chandi, Reshmi, Qalandri and CRIS-443) of Sindh under deficient (0 kg B ha-1) and adequate (2.0 kg B ha-1) levels of soil applied B (Borax, 11.5% B). The crop also received a blanket dose of 120-60-60 kg NPK ha-1. The soil used was clay loam, alkaline in nature (pH: 8.2), slightly saline (EC: 1.7dS m-1), while low in organic matter (0.79%) and diluted HCl-B (0.42 mg kg-1). Both the sources of variance (B and cotton genotypes) (G) significantly (p <0.001) affected all the traits. Cotton genotypes significantly differed for their B accumulation. Boron × genotypes interaction significantly (p <0.05) affected the number of bolls and seed cotton yield. Qalandari produced maximum number of sympodia, bolls, seed cotton yield, and accumulated maximum B concentration under both the levels of B. Sohni had maximum ginning out turns and B accumulation under both the B levels. Reshmi produced maximum boll weight under both the B conditions. Qalandari appeared to be a potential genotype to perform both under low and high B input agriculture, being most efficient-responsive genotype. We concluded that the adequate B nutrition significantly affect most of the growth traits and seed yield of cotton genotypes, though independent of boron accumulation. Hence, a wide range of cotton genotypes may be involved to exploit their variation for B accumulation in quest of identifying B-use-efficient cotton genotypes.

During the cotton harvesting stage, the application of chemical harvest aids, such as thidiazuron and ethephon, facilitates cotton defoliation and boll maturation, serving as a crucial management tool in modern cotton cultivation systems. This paper reviews recent advancements in cotton defoliation and ripening research; delves into the physiological mechanisms underlying defoliation, boll maturation, and cotton fiber development; and summarizes the effects of major defoliants and herbicide-type desiccants on plants. It also explores the roles of hormones and genes that are involved in the defoliation process and identifies the key factors influencing the effectiveness of harvest aids. Additionally, this paper offers recommendations and scientific prospects for optimizing cotton defoliation and ripening technologies in the future. Through these contributions, it aims to provide valuable insights for the research and application of efficient harvesting of mature cotton, stimulate innovation in cotton defoliation and ripening technologies, enhance the quality and yield of cotton, reduce labor costs, and contribute to the sustainable development of the cotton industry.

BackgroundZinc (Zn), being the most deficient micronutrient, can largely limit plant growth and development on alkaline calcareous soil. Crop species and varieties within species differently require Zn for optimum productivity. The current study aimed to optimize Zn level and mode of application for better growth, yield, and fiber quality of cotton (Gossypium hirsutum L.). The experimental plan comprised a control group with no Zn application, three Zn levels through soil application, i.e. 5 mg·kg−1 (SZn5), 10 mg·kg−1 (SZn10), and 15 mg·kg−1 (SZn15), two levels of foliar application including 0.5% (FZn0.5) and 1% (FZn1) Zn solution, and various combinations of soil plus foliar application. Two cotton cultivars, CIM-663 (Bt) and Cyto-124 (non-Bt) were used, and each treatment was replicated thrice.ResultsZinc nutrition caused a significant (P ≤ 0.05) improvement in growth, yield, physiological, and fiber quality characteristics of both cotton cultivars. All levels and modes of Zn application were found effective in improving cotton productivity on alkaline calcareous soil. However, integrated soil application and foliar spray showed superiority over sole soil or foliar application. Among different treatments, SZn15 + FZn1 caused the highest improvement in most of the observed growth and yield traits. The said treatment maximally increased the leaf Zn concentration by 270.5% and 218.4% with a subsequent increase in plant height 23.2% and 28.0%, monopodial branches 40.7% and 42.1%, sympodial branches 37.2% and 35.2%, seed cotton yield 32.5% and 36.6%, and lint yield 30.0% and 34.6% in CIM-663 and Cyto-124, respectively, compared with the control. SZn15 + FZn1 also caused the highest increase in relative water contents 32.6% and 22.4%, chlorophyll contents 92.0% and 67.1%, and stomatal conductance 112.8% and 100.8% in CIM-663 and Cyto-124, respectively, compared with the control. Among the fiber quality characteristics, fiber fineness was maximally improved by 19.7% and 15.9% in CIM-663 and Cyto-124, respectively, with SZn15 + FZn1 compared with the control. Leaf Zn concentration was positively correlated with fiber length (R2 = 0.717 3), fiber strength (R2 = 0.548 3), and fiber fineness (R2 = 0.637 9) of both cotton cultivars grown with different levels and application modes of Zn. The benefit-cost ratio was remarkably improved with Zn nutrition, and the highest value of 1.64 was found in CIM-663 at SZn10 + FZn1 and SZn15 + FZn1.ConclusionThe plant growth, physiological, yield, and fiber quality characteristics of cotton cultivars were significantly improved with Zn supply at different levels and modes of application. SZn15 + FZN1 could be recommended to get optimum seed cotton yield and fiber quality of cotton on alkaline calcareous soil.