Lint Index Research Articles

Heterosis and Inbreeding Depression Studies for Fibre Quality Traits in Upland Cotton (Gossypium hirsutum L.)

Cotton hybrids have its own advantage than varieties in yield and fibre properties. Heterosis breeding helps in identifying F1 hybrids and in creating variability. The chief intention of any hybridization programme is to combine all the desirable genes present in two or more parents into a single genetic background. This investigation helped in identifying the extent of heterosis in crosses among four families in upland cotton (Gossypium hirsutum L.) which was conducted at college Farm during kharif 2021-23. The all 4 hybrids were derived by generation mean analysis study which were analysed for fibre quality traits in a Compact Family Block Design. For traits like Ginning percentage, uniformity index, Upper Half Mean Length, Lint index, and Fibre strength, most of the crosses showed positive and significant relative heterosis. While, heterobeltiosis was also found positive and significant for ginning percentage, uniformity index, Upper half mean length and fibre strength for most of the crosses under study. Most of the crosses under study also showed little inbreeding depression for traits like ginning percentage, uniformity index and fibre strength. Thus, by exploiting the benefits of heterosis while mitigating risks associated with inbreeding depression may lead to the development of superior hybrid varieties with consistently improved fibre quality.

GENETIC INSIGHTS AND BREEDING IMPLICATIONS: ENHANCING COTTON YIELD AND QUALITY THROUGH BIPARENTAL SELECTION

This study was performed in Egypt's Sakha Agriculture Research Station during the seasons 2015–2018 to study the efficiency of biparental progenies derived from inter-population random mating in F2 generation in a cotton cross. Intercrossing is allowed in cotton breeding populations. Although the best lines may include harmful alleles, thus early segregating generation recombination and hybridization are required. The F2 generation of the cotton cross (Giza70 TNB1), which obtained from Agriculture Research Center, Egypt, consisted of five male and eight female plants, was used to test biparental progeny from random interpopulation mating. About 28 and 24 families in BIPS1 and BIPS2 had their original parents were examined. All genotypes were assessed for agricultural and fiber qualities. The mean of families (BIPs2) was higher than BIPs1 for all measured metrics except lint yield, percentage, and uniformity ratio. BIPS2 families had more genotypic coefficients of variation (GCV) for features than BIPS1. Intercrossing affected correlation coefficients of BIPS1 and BIPS2 genotypes. Seed cotton yield and lint index genotypic correlations became considerable. Seed cotton yield estimated by seed index and first fruiting node location were altered from negative to positive. Among them, No.5, No.7, No.8, No.18, and No.19 had large yields and early ripening, as shown by their components. The top five families chosen for fiber length had gain values of 3.373% to 8.961% and 5.919 to 7.781% for fiber strength. The No.18 family exhibited good seed cotton production and fiber length. Intermating and self-pollination (BIPS2) may utilize non-additive gene effects and accumulate trait-influencing alleles. Continuing to select and evaluate families based on their large-scale reproductive performance will enhance the likelihood of producing genotypes with desired features. In conclusion, this study underscores the utility of continued selection based on discerned genetic parameters, genotypic correlations, and observed gains in facilitating the ongoing improvement of cotton breeding programs. By providing valuable insights into the intricacies of genetic variability and trait associations, this research holds implications not only for the advancement of cotton breeding practices but also for the broader agricultural landscape on both national and global scales. Keywords: Biparental, selection efficiency, correlated response, hybridization, self-pollination

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.

GhMYB52 Like: A Key Factor That Enhances Lint Yield by Negatively Regulating the Lignin Biosynthesis Pathway in Fibers of Upland Cotton (Gossypium hirsutum L.).

In the context of sustainable agriculture and biomaterial development, understanding and enhancing plant secondary cell wall formation are crucial for improving crop fiber quality and biomass conversion efficiency. This is especially critical for economically important crops like upland cotton (Gossypium hirsutum L.), for which fiber quality and its processing properties are essential. Through comprehensive genome-wide screening and analysis of expression patterns, we identified a particularly high expression of an R2R3 MYB transcription factor, GhMYB52 Like, in the development of the secondary cell wall in cotton fiber cells. Utilizing gene-editing technology to generate a loss-of-function mutant to clarify the role of GhMYB52 Like, we revealed that GhMYB52 Like does not directly contribute to cellulose synthesis in cotton fibers but instead represses a subset of lignin biosynthesis genes, establishing it as a lignin biosynthesis inhibitor. Concurrently, a substantial decrease in the lint index, a critical measure of cotton yield, was noted in parallel with an elevation in lignin levels. This study not only deepens our understanding of the molecular mechanisms underlying cotton fiber development but also offers new perspectives for the molecular improvement of other economically important crops and the enhancement of biomass energy utilization.

Land configuration and nutrient management model increased the productivity through improved soil enzyme activities in an organic cotton wheat production system

Suitable land configuration and nutrient approach are essential for sustaining crop production under semi-arid Inceptisols of India. The study aimed to assess the effect of land configuration (raised bed [RB] and flat bed [FB]) and nutrient approach, viz., organic (Organic), inorganic (soil test crop response [STCR]), and integrated nutrient management (STCR-Integrated plant nutrient supply [IPNS]) along with farm yard manure (FYM) and control (CK) on soil’s physicochemical and biological properties after two consecutive cycles of cotton-wheat. Results showed that land configuration did not impact the pH, organic carbon, and its stock at 0–15 and 15–30 cm soil. However, bulk density was reduced (2.03%) and microbial biomass carbon increased (5.12%) significantly under RB at 0–15 cm soil compared to FB planting. The RB significantly increased the available N (4.06%), P (8.40%) and K (4.22%) and urease (8.37%), alkaline phosphatase (6.10%), and dehydrogenase activity (8.28%) of soils compared to FB. Soil physicochemical and biological properties were highly impacted under STCR-IPNS treatment and least under control at both depths. Integrated treatment showed the highest seed cotton (3097 kg ha−1) and wheat grain yield (6085 kg ha−1); however, land configuration did not impact the yield of both crops. Further, RB increased the protein content of wheat by 1.1% and the ginning percentage and lint index of cotton by 2.4% and 5.5%, respectively compared to FB. In terms of nutrient management, cotton and wheat quality parameters were found higher for STCR-IPNS treatment. Thus, the study suggests that RB planting with an integrated nutrient approach could be a sustainable and feasible practice for quality food and fiber production for semi-arid Inceptisols.

Evaluation of Cotton Genotypes Through the Selection Index Technique

Eight upland cotton genotypes introduced from different origins (BA440, FLASH, EDESSA, SPERO, IK259, W888, MONTANA and CANDIA) in addition to the two local cultivars (Coker 310 and Lachata) were cultivated on April 22 and 23, 2022 in the Rahmaniyah region at levels (0, 1, 2, and 3 g/liter). l) of nano-chelated NPK 20-20-20 under drip irrigation conditions, and using a randomized complete block design with three replications, in order to evaluate it by creating multiple selection indices and to estimate the expected increase in seed cotton yield. The results of the analysis of variance for the studied traits (seed cotton yield, plant height, number of fruiting per plant, number of bolls per plant, average boll weight, seed index, and lint index) showed that the mean square of genotypes and levels of nano-fertilizer and their interaction was highly significant for all traits except seed index in case of nano-fertilizer levels. The selection index that included the two traits of plant height and number of bolls per plant was characterized by a high increase in efficiency compared to direct selection of the seed cotton yield, indicating the importance of selection by adopting the selection index for several traits. This selection index in the current study was considered the best due to its high efficiency, and by adopting it in evaluating the genotypes, it was found that the highest mean of the index was 7.689 for the CANDIA genotype, with a significant difference from most other genotypes, followed by the FLASH and BA440 genotypes. The sequence of local varieties adopted in the study (Coker 310 and Lachata) in terms of performance was 10 and 7, respectively. It appeared that six introduced genotypes were superior to the best local cultivars (Lachata), and all introduced genotypes were higher than the least performing local variety (Coker 310).

Evaluation of Cotton Genotypes Through the Selection Index Technique

Eight upland cotton genotypes introduced from different origins (BA440, FLASH, EDESSA, SPERO, IK259, W888, MONTANA and CANDIA) in addition to the two local cultivars (Coker 310 and Lachata) were cultivated on April 22 and 23, 2022 in the Rahmaniyah region at levels (0, 1, 2, and 3 g/liter). l) of nano-chelated NPK 20-20-20 under drip irrigation conditions, and using a randomized complete block design with three replications, in order to evaluate it by creating multiple selection indices and to estimate the expected increase in seed cotton yield. The results of the analysis of variance for the studied traits (seed cotton yield, plant height, number of fruiting per plant, number of bolls per plant, average boll weight, seed index, and lint index) showed that the mean square of genotypes and levels of nano-fertilizer and their interaction was highly significant for all traits except seed index in case of nano-fertilizer levels. The selection index that included the two traits of plant height and number of bolls per plant was characterized by a high increase in efficiency compared to direct selection of the seed cotton yield, indicating the importance of selection by adopting the selection index for several traits. This selection index in the current study was considered the best due to its high efficiency, and by adopting it in evaluating the genotypes, it was found that the highest mean of the index was 7.689 for the CANDIA genotype, with a significant difference from most other genotypes, followed by the FLASH and BA440 genotypes. The sequence of local varieties adopted in the study (Coker 310 and Lachata) in terms of performance was 10 and 7, respectively. It appeared that six introduced genotypes were superior to the best local cultivars (Lachata), and all introduced genotypes were higher than the least performing local variety (Coker 310).

STUDIES ON GENETIC VARIABILTY FOR YIELD AND FIBRE QUALITY TRAITS IN UPLAND COTTON (Gossypium hirsutum L.)

Thirty genotypes of cotton were studied to estimate genetic variability, heritability (broad sense) and genetic advance for 15 traits during kharif, 2022. Analysis of variance showed significant amount of variation among the genotypes for traits studied. PCV was greater than GCV for all the traits except days to 50% flowering. High PCV and GCV were recorded for number of monopodial branches, lint index, lint yield and ginning percentage. High heritability coupled with genetic advance as percent of mean was observed for number of monopodial branches, plant height, seed cotton yield, lint index, lint yield, ginning percentage and micronaire indicating preponderance of additive gene action and hence simple selection would be effective for the improvement of these traits.

EVALUATING COMBINING ABILITIES AND HETEROTIC EFFECTS FOR ENHANCED COTTON YIELD

The present research was conducted to evaluate heterosis in diallel crosses, determining general and specific combining abilities for yield-related traits and identifying top-performing genotypes for future breeding programs. A field experiment was conducted using selected genotypes (CIM-599, CIM-602, Shahkar, and NS-181) to produce F1 hybrids through frequent pollinations in a diallel fashion. Twelve F1 hybrids and their four parental genotypes were cultivated in a randomized complete block design with two replications. Yield-related traits including plant height, branches per plant, bolls per plant, lint percentage, boll weight, seed cotton yield, seed index, and lint index were recorded. Analysis of variance and combining ability effects analysis were performed to assess the significance of the genotypes and their interactions. Significant variability among parental genotypes was observed for yield-related traits, indicating genetic variation in the breeding material. Combining ability analysis revealed the predominance of non-additive gene action. General combining ability (GCA) effects were significant for most traits, with CIM-599 exhibiting the highest GCA effects. Specific combining ability (SCA) and reciprocal combining ability (RCA) effects were significant for various traits and hybrid combinations, indicating their potential for trait improvement. Notably, the hybrid combination CIM-599 x Shahkar exhibited substantial mid-parent heterosis for seed cotton yield, boll weight, and lint percentage. This cross also displayed notable SCA effects, indicating its importance for hybrid breeding. These findings highlight the potential of hybrid breeding for trait enhancement. Future breeding programs could leverage the insights gained here to create improved cotton varieties with enhanced yield.

A comprehensive investigation of Genotype-Environment interaction effects on seed cotton yield contributing traits in Gossypium hirsutum L. Using multivariate analysis and artificial neural network

The prediction of seed cotton yield is a critical aspect of cotton breeding. In the present study, an artificial neural network (ANN) and a multiple linear regression (MLR) model were used to predict seed cotton yield based on experimental data obtained from quantitative traits measured under different environmental conditions, including number of bolls per plant (NB), boll weight (BW), 100 seed weight (SI), number of sympodia per plant (NS), lint index (LI), internode length (IL), and seed cotton yield per plant (SCY). The experimental data underwent ANOVA and correlation analysis across different environments. The selected features were utilized for ANN and MLR modeling. The results demonstrated that the ANN model provided precise predictions of SCY, with a root mean square error (RMSE) of 6.63 g/plant and a determination coefficient (R2) of 0.888, which outperformed the MLR model, which showed an RMSE of 8.613 g/plant and an R2 of 0.816. Sensitivity analysis revealed that the number of bolls per plant had the most significant impact on yield estimates, while 100 seed weight had the least impact, as determined by both ANN and MLR models. Furthermore, the ANN model was less influenced by environmental factors than the MLR model, as indicated by R2 values. Overall, this study provides a comprehensive analysis of genotype-environment interaction effects on seed cotton yield and contributes to the development of effective cotton breeding strategies.

GERMPLASM POTENTIAL FOR DIFFERENT ADVANCE LINES OF GOSSYPIUM HIRSUTUM FOR WITHIN BOLL YIELD COMPONENTS

Cotton production per hectare is low in Pakistan due to many biotic and abiotic factors. As boll is the basic determinant for yield in cotton crop, a study on within boll yield parameters was carried out using 24 cotton bulk and 2 check varieties to check their variability for within boll yield components. The experiment was performed in the research area of ​​the Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad. The genotypes were seeded in two replications following a randomized complete block design. Data were subjected to analysis of variance to check significance among different genotypes. Genotypes were significantly different. The genotype PB-132 performed best for most parameters including GOT, lint index, lint mass per seed, and seed density. Correlation analysis was applied to find out the association of these parameters. Seed cotton yield was positively associated with the GOT, boll weight and number of seeds per boll while it negatively correlated with fiber fineness, seed volume, and seed surface area. The first principal component showed 26.37%, the second component showed 17.93%, the third component showed 14.88%, and the fourth component showed 14.40% of total variation. PCA analysis showed the genetic diversity among cotton genotypes. The current study's findings revealed the potential of different bulks of cotton for developing high-yielding varieties. This information may be used to develop breeding strategies to enhance cotton production and variety.

Genotypic and environmental contributions to lint yield, yield components, and fiber quality in upland cotton from Arkansas variety trials over a 19‐year period

AbstractLint yields and their underlying yield components can be substantially influenced by genotype and environment. Thus, the objectives of the current study were to quantify genotypic and environmental contributions to lint yield, yield components, and fiber quality in multi‐site variety trials conducted in Arkansas over a 19‐year period, to identify the traits most strongly associated with lint yield, and to quantify long‐term trends in the aforementioned traits. Annual assessments included lint yield, seeds per hectare (SPH), intra‐boll yield components, and fiber quality parameters. Production environment accounted for a higher percentage of all yield variability in 15 out of 19 years. However, four years were identified in which genotypic contributions were greater than environmental contributions. Genotype was a dominant driver of variability in lint percent, lint index, seed score, seed index, fibers per seed, fiber density, fiber length, strength, and uniformity. Production environment was the dominant driver of variability in SPH, and micronaire. Correlations between yield components and yield varied substantially from year to year, even when genotype was the primary yield driver. A regression function that utilized lint index and SPH was a stronger and more consistent indicator of genotypic variation in lint yield than any single yield component. Finally, long‐term trends show that lint percent has increased significantly over the past 19 years, whereas seed index has declined 19.6% for cotton varieties with the highest lint yields.

Association and path analysis studies for yield contributing and fibre quality traits in the F1 population of Gossypium hirsutum L.

The present investigation on correlation and path analysis studies helps to study the relationship among the yield and yield contributing traits along with the quality parameters. The observations were taken in the F1 population of 35 hybrids along with lines (7 lines) and testers (5 testers) for the traits viz. plant height (cm), number of sympodial branches per plant, the number of bolls per plant, boll weight (g), lint index (g), single cotton yield per plant (g), ginning outturn (%), upper half mean length (cm), elongation percent (%) and micronaire value (µg per inch). The results revealed that seed cotton yield per plant had strong and positive association with the traits namely number of sympodial branches per plant (0.646), number of bolls (0.633) and boll weight (0.652). Path analysis study revealed that number of sympodial branches per plant (1.5396), boll weight (0.6285), lint index (1.3526) and upper half mean length (0.3392) had high direct positive effects on single plant yield and indirect very high positive effects through the traits viz., number of sympodial branches per plant via., number of bolls per plant (1.5125) and boll weight (1.0121). Hence selection based on these traits that are positively associated and direct positive effect with the yield would produce the best outcome in the genotypes in further breeding programmes.

Estimation of mean performance of parents and their hybrids for yield related traits in Gossypium hirsutum L.

Cotton (Gossypium hirsutum L.) is an important fiber crop and plays an important role in Pakistan's economy as a cash crop. Cotton crop is cultivated primarily for fiber. The main objective of all cotton breeders is the production of a new variety with high yield and fiber quality. The current experiment was be conducted in the research area of Department of Plant Breeding and Genetics, University of Agriculture Faisalabad. Crosses were made of four varieties AGC-999, IR-3701, VH-37 and AS-01 by full Diallel mating design in the greenhouse during winter season. Evaluation of 12 crosses and 4 parental varieties were proceeded in the field during Kharif season of 2019 under RCBD (Randomized completely blocked Design) design with three replications. The data for agronomic characters and yield related traits as plant height, number of branches, number of bolls, number of nodes, seed cotton yield, ginning out turn, seed index and lint index was recorded. Mean data of seed cotton yield for all the genotypes indicated that the parent AS-01 provided the maximum yield (93.73 grams) among the parents while AGC-999 × IR-3701 had the maximum yield (82 grams) among the crosses. While VH-37, VH-37 × AS-01 and AS—01 × AGC-999 had the minimum value among parents and crosses respectively. These genotypes

Dispersion Analysis studies in Desi Cotton (Gossypium arboreum L.) based on Wilk’s Criteria and Canonical Vectors

Gossypium arboreum is a native cotton species of India. It is cultivated from extreme north of Punjab to Kanyakumari in the south and Assam in the east to Kutch (Gujarat) in the west of country. G.arboreum genotypes matures in 150 to 180 days and is usually having coarse and short fibred and has high degree of resistance to diseases and insect pests and is very valuable germplasm resources and have great export value. The investigation for fifty-eight desi cotton (Gossypium arboreum L.) genotypes was undertaken to estimate the degree of divergence among the fifty eight genotypes of desi cotton and thereby to identify potential and diverse genotypes for their utilization in hybridization program based on wilk’s criteria and canonical vectors. The analysis of variance revealed significant differences among fifty eight genotypes collected from different cotton growing states in respect of all the twelve morphological characters under study indicating the presence of substantial degree of variability. The canonical root analysis revealed about 80.19 per cent of the total variation was accounted by the first six canonical roots. In root I seed cotton yield per plant, in root II initial plant stand, in root III lint index, in root IV boll weight, in root V number of monopodia per plant and in root VI plant height were important sources of divergence. Among twelve characters studied, seed cotton yield per plant (g) contributed maximum towards divergence followed by initial plant stand, ginning percent, seed index and number of bolls per plant, indicating that yield and yield contributing characters contributed maximum towards divergence. Key words: Canonical roots, D2 analysis, Desi Cotton, Genetic divergence, G. arboreum.

Estimation of Combining Ability and Heterosis on Seed Cotton Yield and its Attributing traits in American Cotton Gossypium hirsutum L. Genotypes

An experiment was executed during Kharif 2021 at Regional Agricultural Research Station, Lam, Guntur in randomized block design (RBD) in two replications for estimation of combining ability of the parents and gene effects and also the extent of heterosis using line × tester fashion design. Statistical data were collected on the biometrical observations viz., days to 50% flowering, plant height (cm), number of monopodia/ plant, number of sympodia/plant, number of bolls per plant, boll weight (g), seed index (g), lint index (g), Ginning Out Turn (GOT %), seed cotton yield (kg/ha) and lint yield (kg/ha). The lines GISV298 and SCS1207; the testers, Lam GPC 501 and Lam GPC 355 exhibited positive General Combining Ability (GCA) effects for the traits Ginning Out Turn (GOT%), Seed Cotton Yield (SCY) and Lint Yield (LY) signifying that these were good general combiners. The cross combinations viz., TCH1837/GP117, GISV298/GP274, and SCS1207 / GP117 expressed significant specific combining ability (SCA) effects for Seed Cotton Yield (SCY) and Lint Yield (LY). The cross combination, SCS1207/ Lam GPC 355 was identified as the best hybrid combination with high GCA and SCA for important traits like GOT, seed cotton yield, and lint yield coupled with significant positive heterosis which can be further tested in multi-location testing at the station and all India level.

Variability studies and genetic divergence in cotton (Gossypium hirsutum L.) germplasm using multivariate analysis

Two hundred germplasm lines of upland cotton (Gossypium hirsutum L.) were evaluated for genetic variability and divergence for seed cotton yield attributing traits and fibre quality traits at Regional Agricultural Research Station, ANGRAU, Lam, Guntur. The analysis of variance indicated significant genetic variability among the germplasm lines. The close symmetry between the phenotypic and genotypic coefficient of variances and lower values of environmental coefficient variance for all the studied attributes indicated that the traits were genetically controlled and under less influence of the environment.   Higher broad sense heritability and genetic advance for all seed cotton yield attributing traits indicated that these attributes were governed by additive genes and early phenotypic selection for their improvement might be effective. Five principal components (PCs) were depicted as having Eigen value >1 and cumulative variability of 66.17%, out of which PC1 accounted for 26.81% and  PC2  for 14.08% of variability. The attributes of significance depicted in PC1 were seed index, lint index, upper half mean length, uniformity index, and staple length. Bi-plot revealed that Lam GPC232, Lam GPC223, Lam GPC225, Lam GPC135, Lam GPC62, Lam GPC85, Lam GPC168, and Lam GPC203 were the most divergent germplasm. These genetically diverse genotypes with the absolute and significant association of attributes could be utilized in a future cotton breeding program. Keywords: Genetic variability, Genetic advance, Heritability, PCA

Registration of Arkot 1005, Arkot 1015, and Arkot 1019 cotton germplasm lines

AbstractArkot 1005 (Reg. no. GP‐1127, PI 700852), Arkot 1015 (Reg. no. GP‐1128, PI 700853), and Arkot 1019 (Reg. no. GP‐1129, PI 700854) are conventional cotton (Gossypium hirsutum L.) germplasm lines released by the Arkansas Agricultural Experiment Station in April 2022. The lines were compared with UA48 and UA222 (check cultivars) in replicated field tests at four Arkansas sites over 5 yr. Over these tests, lint yields of the three lines did not differ from each other and were greater than UA48. Lint yield of Arkot 1015 was greater than UA222, while lint yields of Arkot 1005 and Arkot 1019 were equal to UA222. Performance in regional tests indicates that the lines have wide adaptation. The lint yields of Arkot 1015 and Arkot 1019 were attributed to producing more (and smaller) seed per area and less lint per seed (lint index) than UA222. Arkot 1005 produced higher lint index than the other two lines and the two check cultivars. Seed per area for Arkot 1005 was higher than UA48, equal to UA222, and lower than Arkot 1015 and Arkot 1019. Leaf pubescence, stem pubescence, and bract trichome density of the three lines were intermediate between UA222 and UA48. All three lines displayed high resistance to bacterial blight and were similar to UA222 and UA48 in their response to other diseases. Arkot 1015 was more resistant to tarnished plant bug (TPB) than Arkot 1005, Arkot 1019, and UA48, but all were more susceptible to TPB than UA222. Compared with the other lines and check cultivars, Arkot 1005 and Arkot 1019 displayed higher and lower, respectively, resistance to seed deterioration. Fiber quality of Arkot 1019 was superior to UA48, UA222, and the other lines. Fiber quality of Arkot 1005 and Arkot 1015 was superior to UA222.

Response of optimization and sufficiency index in Bt cotton (Gossypium spp.) through optical sensor based nitrogen management

To break the productivity barriers in Bt cotton (Gossypium spp.), adoption of optical sensor based nitrogen (N) management practices is the need of the hour. In light of this, a field experiment was conducted at the main Agricultural Research Station, Dharwad, Karnataka during rainy (kharif) season 2019 and 2020 to optimize the response index (RI) and sufficiency index (SI) for real time nitrogen management in Bt cotton through optical sensors. Experiment was conducted in split plot design with 16 treatment combinations having 2 genotypes (main plot) and 8 N management practices (subplot). Pooled data indicated that non-significant (P=0.3480) difference in seed cotton yield was observed with genotypes (First Class and Ajeet 155 recorded 3313 and 3159 kg/ha, respectively). Seed cotton yields varied significantly (P<.0001) due to different optical sensor-based N management practices. N supplementation at 1.1–1.5 RI and 81–90% SI (4460 and 4412 kg/ha, respectively) produced higher but on par yields with RDF (4386 kg/ha) with saving of 15 kg N through sensors during both the years. Interactions were found non-significant (P>.9999). Similarly, N supplementation at 1.1–1.5 RI and 81–90% SI recorded significantly (P<.0001) higher number of good and bad opened bolls, total number of bolls, sympodials, seed cotton yield per plant, boll weight, lint index and harvest index but was found on par with RDF.

Genetic analysis of yield traits in Egyptian cotton crosses (Gossypium barbdense L.) under normal conditions

To generate high-yielding cultivars with favorable fiber quality traits, cotton breeders can use information about combining ability and gene activity within a population to locate elite parents and potential F1 crosses. To this end, in the current study, twelve cotton parents (eight genotypes as female parents and four testers) and their F1 crosses obtained utilizing the linex tester mating design were evaluated for their general and specialized combining abilities (GCA and SCA, respectively) of yield traits. The findings showed that for all the investigated variables, variances owing to genotypes, parents, crosses, and parent vs cross showed extremely significant (P ≤ 0.01) differences. Additionally, throughout the course of two growing seasons, the mean squares for genotypes (parents and crosses) showed strong significance for all the variables under study. The greatest and most desired means for all the examined qualities were in the parent G.94, Pima S6, and tester G.86. The best crossings for the qualities examined were G.86 (G.89 × G.86), G.93 × Suvin, and G.86 × Suvin. The parents' Suvin, G89x G86 and TNB were shown to have the most desired general combining ability effects for seed cotton yield/plant, lint yield/plant, boll weight, number of bolls/plants, and lint index, while Suvin, G.96 and pima S6 were preferred for favored lint percentage. For seed cotton yield, lint percentage, boll weight, and number of bolls per plant per year, the cross-G.86 x (G.89 × G.86) displayed highly significant specific combining ability impacts. The crosses G.86 × Suvin, Kar x TNB, G.93 × Suvin, and G.93 × TNB for all the studied traits for each year and their combined were found to have highly significant positive heterotic effects relative to better parent, and they could be used in future cotton breeding programs for improving the studied traits.