Lint Percentage Research Articles

Optimization the selection of lint percentage and fiber length in cotton based on the combining effects of parental forms

Forty F1 crosses obtained from 5 × 8 line by tester mating design methodology were studied. The varieties Chirpan-539, Sirius, Darmi (Bulgarian selection), Nazili 954 (Turkish) and FR-H-1002 (Spanish) were used as female parents, selection lines 449, 489, 639, 535, 550, 572, 578 and 678 were used as male parents. The aim of the study was to identify the best F1 crosses for improving lint percentage and fiber length in new cotton varieties, by applying a new approach to select parents with the highest possible general combining ability (GCA) for both traits. Crosses and their parents were sown in one row, randomized in three replications. The highest values of the GCA effects of the two parental forms for each trait were taken as “ideal” and the Euclidean distances between them and the GCA effects of the two parents for each F1 cross were calculated. Combining ability analysis of variance showed that females and males differed in general and specific combining abilities. The cultivars Chirpan-539 and Nazili-954 from the females, and lines 550 (Tiara variety) and 578, from the males, appeared to be very good general combiners for lint percentage. The cultivar FR-H-1002 and Darmi variety, from the females, and lines 449, 572, and 578, from the males, appeared to be very good general combiners for fiber length. Some crosses showed high positive SCA effects and heterosis for both traits. Cross combinations FR-H-1002 × 578, Darmi × 578 and Nazili 954 × 578 had the highest possible GCA for both studied traits and are most valuable for selection programs. A total of seven crosses with short Euclidean distances to the “ideal” population in which desirable segregates are expected to occur were selected.

QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii.

A narrow genetic basis limits further the improvement of modern Gossypium hirsutum cultivar. The abundant genetic diversity of wild species provides available resources to solve this dilemma. In the present study, a chromosome segment substitution line (CSSL) population including 553 individuals was established using G. darwinii accession 5-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. After constructing a high-density genetic map with the BC1 population, the genotype and phenotype of the CSSL population were investigated. A total of 235 QTLs, including 104 QTLs for fiber-related traits and 132 QTLs for seed-related traits, were identified from four environments. Among these QTLs, twenty-seven QTLs were identified in two or more environments, and twenty-five QTL clusters consisted of 114 QTLs. Moreover, we identified three candidate genes for three stable QTLs, including GH_A01G1096 (ARF5) and GH_A10G0141 (PDF2) for lint percentage, and GH_D01G0047 (KCS4) for seed index or oil content. These results pave way for understanding the molecular regulatory mechanism of fiber and seed development and would provide valuable information for marker-assisted genetic improvement in cotton.

Comprehensive analysis of drought tolerance in pure lines derived from half-diallel crosses of upland cotton (Gossypium hirsutum L.)

Drought has a significant impact on plants, affecting their growth, development and survival. This study focuses on evaluating the impact of drought stress, a significant abiotic factor, on the agronomic and fiber parameters of potential cotton (Gossypium hirsutum L.) lines with the aim of developing drought-tolerant varieties. The experiment involved two irrigation regimes—well-watered (100% field capacity) and deficit irrigation (50% field capacity)—conducted on F9–F10 generations. Key fiber parameters, including fiber length, boll weight, fiber strength, and lint percentage, were identified as crucial selection criteria under both well-watered and deficit irrigation conditions. Notably, boll number emerged as the decisive parameter in both F9 and F10 generations. The study employed univariate and multivariate analyses, such as PCA, heat map cluster, correlation analysis, and decision tree, which consistently highlighted fiber length, boll weight, fiber strength and lint (ginning) percentage the key factor. In the F10 generation, the integration of decision tree and heat map cluster results led to the identification of 8 promising lines. These selected genotypes have potential for inclusion in future cotton breeding programmes, offering the opportunity to increase drought tolerance and improve cotton yield and productivity. Their resilience to environmental stresses makes them promising candidates for improving overall cotton performance under challenging conditions.

Heterosis and combining ability for phenological yield and fiber traits of cotton (Gossypium hirsutum L.) genotypes

The seeds of 4 lines, 3 testers, and their 12 F1 hybrids were sown in a randomized complete block design (RCBD) with 3 replications at Botanical Garden, Department of Plant Breeding and Genetics, Sindh Agriculture University, Tandojam during Kharif 2019. F1 hybrids were raised for the estimation of heterotic effects, GCA and SCA for days to 1st squaring, days to 1st boll formation Bolls opened at 90 days after sowing, Sympodial branches plant-1, Bolls plant-1, Boll weight (g), Seed cotton yield plant-1 (g), 100-seed weight (g), Ginning outturn (%) and staple length (mm). Genotypes, parents, crosses, parent's v/s crosses, lines, testers and line × testers were significant for days to 1st squaring and days to 1st boll forming. Bolls unveiled their fissures precisely 90 days post-sowing, while parameters including sympodial branches per plant, bolls per plant, individual boll weight, seed cotton yield per plant, 100-seed weight, ginning outturn, and staple length underwent meticulous evaluation. The statistical scrutiny unveiled the insignificance of both lines and testers concerning the 90-day boll dehiscence. Similarly, the parental influence on boll weight, 100-seed weight, and staple length exhibited a lack of statistical significance. Line CRIS-134, Sindh, and tester FH-901 gave a higher mean performance for all the traits. Among the hybrids, Mehran × FH-901, Sindh-1 × CIM-602, CRIS-134 × CIM-602, CRIS-342 × Koonj, and CRIS-342 × CIM-602 gave a desirable mean performance and heterotic effect for all the traits. CRIS-342 × Koonj produced maximum SCA effects for bolls per plant. Mehran × FH-901 recorded higher SCA effects for seed cotton yield plant-1 and 100-seed weight, CRIS-342 × CIM-602 for lint percentage, and CRIS-342 × FH-901 for staple length. It is suggested that these lines and testers should be utilized in the breeding program to improve these traits.

Evaluating Water Stress Adaptation in Cotton: Multivariate Analysis in F6–F7 Generations for Yield, Fibre Quality and Variety Selection

AbstractThe impact of drought stress on productivity of cotton (Gossypium hirsutum L.) is a well‐known challenge in agricultural production, and concurrently, the question of whether using the same or different selection criteria in well‐watered and water‐deficit conditions to select drought‐tolerant cotton varieties remains unclear. This study aimed to comprehensively assess the single plant progeny lines within the F6 and F7 generations for determine response to DS and select the tolerant lines within the F7 generation. Single plant progeny rows were established, with the deficit water condition comprising 108 and 136 single plants for the F6 and F7 generations, respectively, and the WW condition consisting of 120 and 156 single plants for the F6 and F7 generations, respectively, with four blocks in Augmented experimental design. These progeny rows have length of 12 m, incorporate five control varieties (Karizma, Gloria, Carla, Candia and Claudia) to facilitate a comprehensive comparison. The study findings showed that fibre length, boll number and lint percentage were identified as the most crucial selection criteria under both WW and deficit irrigation conditions through principal component analysis. These indicators are highly beneficial for evaluating cotton's drought tolerance and screening potential drought‐tolerant lines under both irrigation scenarios. According to the decision tree analysis, FL and BN have emerged as the most critical decision‐making parameter in both irrigation conditions. Furthermore, the analysis revealed that each selection criterion has different impact in the comprehensive selection process. Also, as a result of all statistical analysis results and breeder observations, a total of 10 cotton lines were selected in the F7 generation. These selected genotypes hold promise for future cotton breeding programmes, providing an avenue to enhance drought tolerance and elevate cotton yield and productivity.Clinical Trial Registration: This study does not involve a clinical trial, and therefore, clinical trial registration is not applicable.

Grouping of Bulgarian and foreign cotton varieties by cluster analysis

Abstract. During the period 2016-2019, 21 Bulgarian and 10 foreign cotton varieties were included in a trial set by the block method design in four replicates and a harvest plot of 20 m2. A cluster analysis was applied to the most important economic traits. It was found that based on the clustering by individual years and on average for four years, the varieties were divided into two or three main clusters, mainly on the traits of seed cotton yield, fiber length and lint percentage. The year conditions have influenced the phenotypic manifestation of the studied traits and have had a significant impact on the genotypes clustering by the individual years. The clustering of the varieties based on the average data for four years showed different degrees of genetic similarity and distance between them and with the standard variety – Chirpan-539. The varieties Helius, Trakia, Philipopolis and Plovdiv, which were highly productive, were genetically very similar and it is appropriate to include them in one selection program together with the varieties Natalia, Dorina, Vega, Perla-267, Kolorit, (Bulgarian selection), Stoneville 112, Deltapine 30 (American) and 791-169 (Greek), which were genetically more distant from them and have shown other valuable traits.

Pyramiding effects of favorable haplotypes of loci on major fiber yield and quality traits in Upland Cotton (Gossypium hirsutum L.)

Enhancing both fiber yield and quality is crucial in cotton breeding programs. Typically, a negative correlation exists between fiber yield and quality, and the strategy to decouple this relationship remains obscure. In this study, we generated three multi-parent intercross populations, encompassing 2,852 F2:3 lines, which represent fiber yield potential (FY), fiber quality potential (FQ), and a combination of both potentials (FYQ), derived from sixteen diverse Upland cotton cultivars. We utilized twenty-four kompetitive allele specific PCR (KASP) molecular markers, based on previously identified loci associated with fiber quality (FL5/FS1, FL3/FS2, and FL2) and fiber yield (BW1, BW2, and LP1), for genotyping purposes. The pyramiding of favorable haplotypes from three fiber quality-associated loci resulted in an increase exceeding 10% in fiber length (FL5+FL3+FL2+LP1) and in an increase exceeding 17% in fiber strength (FL5+FL3+FL2). Notably, our findings suggest that the combination of FL3+FL2+BW1+LP1 alleles has the potential to disrupt the negative correlation between fiber yield and quality. Lines harboring these alleles simultaneously exhibited an elevated lint percentage (LP), as well as enhanced fiber length and quality. This study offers robust molecular markers for the efficient selection of superior progeny with desired phenotypes in the early stages of cotton breeding. Furthermore, the allelic combination that concurrently improves fiber quality and yield sheds light on for further exploration the molecular basis of breaking unfavorable linkages in crop breeding.

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.)

Key messageA Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton.Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP). A multi-parent population consisting of 256 recombinant inbred lines, derived from four elite cultivars with distinct combinations of traits, was used in the analysis of QTLs for lint percentage, seed index, lint index and seed oil content and their interrelations. All four traits were moderately heritable and correlated but with no large influence of genotype × environment interactions across multiple seasons. Seven to ten major QTLs were identified for each trait with many being adjacent or overlapping for different trait pairs. A fivefold cross-validation of the model indicated prediction accuracies of 0.46–0.62. GP results based on any two-season phenotypes were strongly correlated with phenotypic means of a pooled analysis of three-season experiments (r = 0.83–0.92). When used for selection of improvement in lint, seed and oil yields, GP captured 40–100% of individuals with comparable lint yields of those selected based on the three-season phenotypic results. Thus, this quantitative genomics-enabled approach can not only decipher the genomic variation underlying lint, seed and seed oil traits and their interrelations, but can provide predictions for their simultaneous improvement. We discuss future breeding strategies in cotton that will enhance the entire value of the crop, not just its fibre.

Genomic insights into local adaptation of upland cotton in China and Pakistan.

Different kinship and resistance to cotton leaf curl disease (CLCuD) and heat were found between upland cotton cultivars from China and Pakistan. 175 SNPs and 82 InDels loci related to yield, fiber quality, CLCuD, and heat resistance were identified. Elite alleles found in Pakistani accessions aided local adaptation to climatic condition of two countries. Adaptation of upland cotton (Gossypium hirsutum) beyond its center of origin is expected to be driven by tailoring of the genome and genes to enhance yield and quality in new ecological niches. Here, resequencing of 456 upland cotton accessions revealed two distinct kinships according to the associated country. Fiber quality and lint percentage were consistent across kinships, but resistance to cotton leaf curl disease (CLCuD) and heat was distinctly exhibited by accessions from Pakistan, illustrating highly local adaption. A total of 175 SNP and 82 InDel loci related to yield, fiber quality, CLCuD and heat resistance were identified; among them, only two overlapped between Pakistani and Chinese accessions underscoring the divergent domestication and improvement targets in each country. Loci associated with resistance alleles to leaf curl disease and high temperature were largely found in Pakistani accessions to counter these stresses prevalent in Pakistan. These results revealed that breeding activities led to the accumulation of unique alleles and helped upland cotton become adapted to the respective climatic conditions, which will contribute to elucidating the genetic mechanisms that underlie resilience traits and help develop climate-resilient cotton cultivars for use worldwide.

Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype

G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.

A novel nondestructive detection approach for seed cotton lint percentage using deep learning

BackgroundThe lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consuming; thus, an efficient and accurate measurement method is needed. In recent years, classification-based deep learning and computer vision have shown promise in solving various classification tasks.ResultsIn this study, we propose a new approach for detecting the lint percentage using MobileNetV2 and transfer learning. The model is deployed on a lint percentage detection instrument, which can rapidly and accurately determine the lint percentage of seed cotton. We evaluated the performance of the proposed approach using a dataset comprising 66 924 seed cotton images from different regions of China. The results of the experiments showed that the model with transfer learning achieved an average classification accuracy of 98.43%, with an average precision of 94.97%, an average recall of 95.26%, and an average F1-score of 95.20%. Furthermore, the proposed classification model achieved an average accuracy of 97.22% in calculating the lint percentage, showing no significant difference from the performance of experts (independent-sample t-test, t = 0.019, P = 0.860).ConclusionThis study demonstrated the effectiveness of the MobileNetV2 model and transfer learning in calculating the lint percentage of seed cotton. The proposed approach is a promising alternative to traditional methods, providing a rapid and accurate solution for the industry.

UDP-glucosyltransferase 71C4 controls the flux of phenylpropanoid metabolism to shape cotton seed development

Seeds play a crucial role in plant reproduction, making it essential to identify genes that affect seed development. In this study, we focused on UDP-glucosyltransferase 71C4 (UGT71C4) in cotton, a member of the glycosyltransferase family that shapes seed width and length, thereby influencing seed index and seed cotton yield. Overexpression of UGT71C4 results in seed enlargement owing to its glycosyltransferase activity on flavonoids, which redirects metabolic flux from lignin to flavonoid metabolism. This shift promotes cell proliferation in the ovule via accumulation of flavonoid glycosides, significantly enhancing seed cotton yield and increasing the seed index from 10.66 g to 11.91 g. By contrast, knockout of UGT71C4 leads to smaller seeds through activation of the lignin metabolism pathway and redirection of metabolic flux back to lignin synthesis. This redirection leads to increased ectopic lignin deposition in the ovule, inhibiting ovule growth and development, and alters yield components, increasing the lint percentage from 41.42% to 43.40% and reducing the seed index from 10.66 g to 8.60 g. Our research sheds new light on seed size development and reveals potential pathways for enhancing seed yield.

Elucidating the phenotypic basis of multi-environment stability for fiber yield and quality traits of cotton (Gossypium hirsutum L.) using 498 recombinant inbred lines

Understanding genotype-environment interactions and trait relationships is pivotal for guiding breeding efforts aimed at stabilizing cotton varieties across diverse environments while boosting yield and fiber quality. The study aimed to assess genotypic variability and stability in 10 agronomic and fiber quality traits across four environments (Anyang in 2020 and 2021 and Weixian in 2020 and 2021) for three parental lines (ZR014121, CCRI60, and EZ60) and their corresponding 498 recombinant inbred lines (RILs) populations. The results indicated that the analysis of variance showed significant genotype and genotype-by-environment effects for all measured traits. Analysis of correlation revealed highly significant positive correlations between seed cotton yield and each of boll weight (r = 0.95), lint yield (r = 0.90), and between boll weight and lint yield (r = 0.90), while highly significant negative correlations were noticed between fiber maturity and fiber elongation (r = −0.52) and between fiber length and lint percentage (r = −0.38). Furthermore, the weighted average of absolute scores (WAASB) was calculated for each trait, revealing moderate to high stability for some yield traits and fiber quality parameters. Also, the multi-trait stability index (MTSI) applied to these RILs populations identified G13 as the most stable line (MTSI = 5.5) and S23 as the least stable (MTSI = 12.1). Selecting 25 RILs with the lowest MTSI values (5.5–6.47) revealed elite stable lines with favorable trait values, providing a valuable genetic resource for developing high-performance cotton cultivars in diverse environments.

Comparative Transcriptomic Analysis of Gossypium hirsutum Fiber Development in Mutant Materials (xin w 139) Provides New Insights into Cotton Fiber Development.

Cotton is the most widely planted fiber crop in the world, and improving cotton fiber quality has long been a research hotspot. The development of cotton fibers is a complex process that includes four consecutive and overlapping stages, and although many studies on cotton fiber development have been reported, most of the studies have been based on cultivars that are promoted in production or based on lines that are used in breeding. Here, we report a phenotypic evaluation of Gossypium hirsutum based on immature fiber mutant (xin w 139) and wild-type (Xin W 139) lines and a comparative transcriptomic study at seven time points during fiber development. The results of the two-year study showed that the fiber length, fiber strength, single-boll weight and lint percentage of xin w 139 were significantly lower than those of Xin W 139, and there were no significant differences in the other traits. Principal component analysis (PCA) and cluster analysis of the RNA-sequencing (RNA-seq) data revealed that these seven time points could be clearly divided into three different groups corresponding to the initiation, elongation and secondary cell wall (SCW) synthesis stages of fiber development, and the differences in fiber development between the two lines were mainly due to developmental differences after twenty days post anthesis (DPA). Differential expression analysis revealed a total of 5131 unique differentially expressed genes (DEGs), including 290 transcription factors (TFs), between the 2 lines. These DEGs were divided into five clusters. Each cluster functional category was annotated based on the KEGG database, and different clusters could describe different stages of fiber development. In addition, we constructed a gene regulatory network by weighted correlation network analysis (WGCNA) and identified 15 key genes that determined the differences in fiber development between the 2 lines. We also screened seven candidate genes related to cotton fiber development through comparative sequence analysis and qRT-PCR; these genes included three TFs (GH_A08G1821 (bHLH), GH_D05G3074 (Dof), and GH_D13G0161 (C3H)). These results provide a theoretical basis for obtaining an in-depth understanding of the molecular mechanism of cotton fiber development and provide new genetic resources for cotton fiber research.

Combining ability of Egyptian cotton (Gossypium barbadense L.) reveals genetic potential for improved yield and fiber quality

BackgroundAs the most widely cultivated fiber crop, cotton production depends on hybridization to unlock the yield potential of current varieties. A deep understanding of genetic dissection is crucial for the cultivation of enhanced hybrid plants with desired traits, such as high yield and fine fiber quality. In this study, the general combining ability (GCA) and specific combining ability (SCA) of yield and fiber quality of nine cotton parents (six lines and three testers) and eighteen F1 crosses produced using a line × tester mating design were analyzed.ResultsThe results revealed significant effects of genotypes, parents, crosses, and interactions between parents and crosses for most of the studied traits. Moreover, the effects of both additive and non-additive gene actions played a notably significant role in the inheritance of most of the yield and fiber quality attributes. The F1 hybrids of (Giza 90 × Aust) × Giza 86, Uzbekistan 1 × Giza 97, and Giza 96 × Giza 97 demonstrated superior performance due to their favorable integration of high yield attributes and premium fiber quality characteristics. Path analysis revealed that lint yield has the highest positive direct effect on seed cotton yield, while lint percentage showed the highest negative direct effect on seed cotton yield. Principal component analysis identified specific parents and hybrids associated with higher cotton yield, fiber quality, and other agronomic traits.ConclusionThis study provides insights into identifying potential single- and three-way cross hybrids with superior cotton yield and fiber quality characteristics, laying a foundation for future research on improving fiber quality in cotton.

Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton.

Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

Genotypic variation in functional contributors to yield for a diverse collection of field‐grown cotton

AbstractYield improvement in cotton could be accelerated through selection for functional yield drivers such as interception of cumulative photosynthetically active radiation (∑IPAR), radiation use efficiency (RUE), and harvest index (HI). However, information on the extent to which these traits vary in cotton in the southeastern United States is limited. It was hypothesized that functional yield drivers would vary significantly within a diverse cotton collection. This study was conducted in Tifton and Athens, GA, and included a total of 4 site‐years. Lint yield, total biomass production, ∑IPAR, RUE, and HI were all affected by genotype. Biomass was more strongly correlated with RUE than ∑IPAR. Even among the highest yielding genotypes, values for functional yield drivers (biomass and harvest index) differed significantly, indicating that high yields could be achieved by differentially manipulating these underlying traits. However, when considered for all genotypes, only HI exhibited a significant positive correlation with yield. Boll production and intra‐boll yield components were also affected by genotype. When considered across upland genotypes, lint per boll, lint per seed, and lint percent were strongly associated with HI and lint yield, whereas boll mass and seed number per boll were not. We conclude that the genotypes evaluated in the current study achieve high lint production per boll and lint yields by manipulating different yield drivers. However, lint yield was primarily maximized through an increase in HI due to increases in boll production and within‐boll distribution of biomass to fiber, not due to increases in total biomass production or boll size.

Map-based cloning of qLPA01.1, a favorable allele from the Gossypium tomentosum chromosome segment line

Cotton is an important natural fiber crop worldwide which plays a vital role in our daily life. High yield is a constant goal of cotton breeding, and lint percentage (LP) is one of the important components of cotton fiber yield. A stable QTL controlling LP, qLPA01.1, was identified on chromosome A01 from Gossypium hirsutum introgressed lines with G. tomentosum chromosome segments in a previous study. To fine-map qLPA01.1, an F2 population with 986 individuals was established by crossing G. hirsutum cultivar CCRI35 with the chromosome segment substitution line HT_390. A high-resolution genetic map including 47 loci and spanning 56.98 cM was constructed in the QTL region, and qLPA01.1 was ultimately mapped into an interval corresponding to an ~80 kb genome region of chromosome A01 in the reference genome, which contained six annotated genes. Transcriptome data and sequence analysis revealed that S-acyltransferase protein 24 (GoPAT24) might be the target gene of qLPA01.1. This result provides the basis for cotton fiber yield improvement via marker-assisted selection (MAS) and further studies on the mechanism of cotton fiber development.

Genetic Analysis of Cotton Fiber Traits in Gossypium Hybrid Lines.

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr-A07, chr-D06, and chr-D07. Notably, chr-D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker-assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker-assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production.

Registration of Arkot 1102ne cotton germplasm line

AbstractArkot 1102ne (Reg. no. GP‐1142; PI 702558) is a conventional, nectariless cotton (Gossypium hirsutum L.) germplasm line released by the Arkansas Agricultural Experiment Station in October 2022. The germplasm line represents an ongoing effort to develop improved genotypes with enhanced yield, yield components, seed traits, earliness, host plant resistance, and fiber properties. Arkot 1102ne was compared to ‘UA48’ and ‘UA222’ over 5 years and four test sites in Arkansas. Across all the test sites, lint yields of Arkot 1102ne were 7.9% and 20.8% higher than those of UA222 and UA48, respectively, due to its higher lint percentage, seed per area, and fiber density. Arkot 1102ne produced the highest average yield of 21 genotypes over 10 locations in the 2019 Regional Breeders’ Network Test (RBTN). Arkot 1102ne produced the highest oil and protein percentages at four 2019 RBTN locations where seed were evaluated. Host plant resistance traits that have been measured on Arkot 1102ne include bacterial blight resistance and Verticillium wilt tolerance. Leaf pubescence and bract trichome density of Arkot 1102ne were intermediate between UA48 and UA222, but stem pubescence was lower. This combination of host plant resistance and yield components should lead to more stable yield production over contrasting environments. The fiber quality of Arkot 1102ne was lower than UA48 and was similar to that of UA222.