Abstract
This study investigates the genetic contribution and decision-making coefficients of agronomic traits of upland cotton parents, and their F1 crosses to provide a scientific basis for breeders to select and improve certain traits. Therefore, Genetic contribution and decision-making coefficients analysis were conducted on 4 agronomic traits and 4 yield traits of 130 upland cotton varieties (lines) and their 206 F1 crosses using the additive-dominance genetic model and its interaction effect with the environment. The results showed that these traits had rich genetic diversity, and the coefficient of variation (CV) for these eight traits in the parents ranged from 4.68 to 50.83%, while that of the F1 crosses was between 3.96 and 55.87%. The contribution rate of the additive effects of agronomic traits to yield, except for the first fruiting branch position and the lint percentage, was highly significant, ranging from 4 to 100%. Moreover, the additive contribution rate of the five petal boll rate and plant height to boll number and boll weight and the contribution rate of the dominance × environment interaction reached a positive and extremely significant level of more than 0.01. The additive variance, dominance × environment interaction, and residual variance among different models of genetic variation, as well as generalized heritability, significantly contributed to the total phenotypic variation in traits. The contribution of the dominance effect to the total phenotypic variation was highly significant, except for the boll number, and the contribution of the additive × environment interaction effect to the total phenotypic variation was highly significant, except for the lint yield. The main decision-making traits and limiting traits responsible for improving the yield of upland cotton hybrids were identified. The dominance decision-making coefficients of the lint yield, the decision-making coefficients of the dominance × environment interaction, the phenotypic decision-making coefficients, and the genotypic decision-making coefficients played a major role in determining the boll number. The decisive factors influencing boll weight, controlled by the additive effect, were the first fruiting branch position, plant height, and the five petal boll rate. The boll number was the most limiting trait affecting boll weight by influencing dominance decision-making coefficients, decision-making coefficients of the additive × environment interaction, decision-making coefficients of the dominance × environment interaction, phenotypic decision-making coefficients, and genotypic decision-making coefficients. Plant height and five petal boll number were the decision-making traits of lint percentage controlled by additive effects, while lint yield and boll weight were the major limiting traits.
Similar content being viewed by others
Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
References
Chattha WS, Ahmad HB, Farooq MA, Shafqat W, Yaseen M, Ihsan MZ, Alghabari F, Alzamanan SM (2021) A novel parent selection strategy for the development of drought-tolerant cotton cultivars. Plant Genet Resour 19(4):299–307
Chen XH (2012) Analysis of Bt and EPSPS gene related agronomic, biochemical and proteomic difference in glandless cotton and genetic effects for biochemical and economic traits in Bt hybrid cotton. Zhejiang: Zhejiang University
Fan DR, Wang XY, Liu LJ, Ge Q, Gong JW, Li XH, Li JW, Liu AY, Shi YZ, Gong WK, Shang HH, Pan JT, Yuan YL (2022) Genetic diversity analysis of fiber yield and quality in segregating populations of upland cotton with high quality. China Cotton 49(4):10–17 (in Chinese)
Feng HJ, Sun JL, Wang J, Jia YH, Zhang XY, Pang BY, Sun J, Du XM (2011) Genetic effects and heterosis of the fiber color and quality of brown cotton (Gossypium hirsutum L.). Plant Breed 130(4):450–456. https://doi.org/10.1111/j.1439-0523.2010.01842.x
Feng CH, Jiao CH, Zhang YC, Bie Y, Qin HD, Wang QS, Zhang JH, Wang XG, **a SB, Lan JX, Chen QQ (2022) Genetic analysis for yield and fiber quality traits in upland cotton based on partial NCII mating design. Crops 5:13–21 (in Chinese)
Guo H, Yu JW, Pei WF, Guan YH, Li H, Li CX, Liu JW, Wang W, Dong ZP, Wang BQ, Mei YJ (2023a) Analysis of the main effect clustering and decision-making coefficients for F2 generation of upland cotton in Southern **njiang. Euphytica 219:32. https://doi.org/10.1007/s10681-023-03164-7
Guo JC, Cao XC, Song J, Zhao YL, Shao YJ, He LR (2023b) Combining ability and stability analysis of yield and quality traits of upland cotton hybrid F1 in different years. Shandong Agric Sci 55(2):36–43 (in Chinese)
** SQ, Liu FJ, Liu Y, Yang FX (2014) Discussions on the conventional cotton breeding direction in the yellow river region in recent years. China Cotton 41(1):8–11 (in Chinese)
Li BT, Shi YZ, Gong JW, Gong JW, Li JW, Liu AY, Shang HH, Gong WK, Chen TT, Ge Q, Jia CY, Lei YS, Hu YS, Yuan YL (2016) Genetic effects and heterosis of yield and yield component traits based on Gossypium barbadense chromosome segment substitution lines in two Gossypium hirsutum backgrounds. PLoS ONE 11(6):e0157978. https://doi.org/10.1371/journal.pone.0157978
Li HQ, Yu Y, Wang P, Liu J, Hu W, Lu LL, Qin WQ (2019) Genetic diversity analysis of the main agronomic and fiber quality characteristics in 270 upland cotton germplasm resources. J Plant Genet Resour 20(04):903–910 (in Chinese)
Luan MB, Guo XM, Zhang YS, Yao JB (2008) Genetic effect on yield and fiber quality traits of 16 chromosome substitution lines in upland cotton. Agric Sci China 7(11):1290–1297. https://doi.org/10.1016/S1671-2927(08)60177-7
Mei YJ, Zhu J, Zhang LL, Guo WF, Hu SL (2006) Analysis on contribution of yield components to main fiber traits in upland cotton (Gossypum hirsutum L.). Chin J Agric Sci 04:848–854 (in Chinese)
Mei YJ, Guo WF, **ong RC (2007) Analysis on genetic contribution of yield components to lint yield in upland cotton (Gossypium hirsutum L.). Cotton Sci 02:114–118 (in Chinese)
Nusreti USM, Yu SX, Fan SL, Mei YJ, Yuan RH (2012) Analysis of genetic contribution of mechanical harvesting traits to lint yield in upland cotton. Cotton Sci 24(1):10–17 (in Chinese)
Nyombayire A, Derera J, Sibiya J, Ngaboyisonga C (2018) Genotype x environment interaction and stability analysis for grian yield of diallel cross maize hybrids across tropical medium and highland ecologies. J Plant Sci 6(3):101–106. https://doi.org/10.11648/j.jps.20180603.14
Qi HK, Zuo YL, Zhang BQ, Du MW, Tian XL, Xu DY, Lu HY, Li ZH (2020) Analysis of the main decision characters of cotton yield in heilonggang cotton region of the yellow river basin. Cotton Sci 32(6):483–490 (in Chinese)
Reddy KB, Reddy VC, Ahmed ML, Naidu TCM, Srinivasarao V (2016) Combining ability study for yield and its component traits through diallel mating design in upland cotton (Gossypium hirsutum L.). J Cotton Res Dev. 30(2):180–184
Riaz M, Farooq J, Ahmed S, Amin M, Chattha WS, Ayoub M, Kainth RA (2019) Stability analysis of different cotton genotypes under normal and water-deficit conditions. J Integr Agric 18(6):1257–1265
Song MZ, Fan SL, Pang CY, Wei HL, Yu SX (2014) Genetic analysis of the antioxidant enzymes, methane dicarboxylic aldehyde (MDA) and chlorophyll content in leaves of the short season cotton (Gossypium hirsutum L.). Euphytica 198(1):153–162. https://doi.org/10.1007/s10681-014-1100-x
Song MZ, Fan SL, Pang CY, Wei HL, Liu J, Yu SX (2015) Genetic analysis of yield and yield-related traits in short-season cotton (Gossypium hirsutum L.). Euphytica 204(1):135–147. https://doi.org/10.1007/s10681-014-1348-1
Tang FY, **ao WJ (2014) Genetic association of within-boll yield components and boll morphological traits with fiber properties in upland cotton (Gossypium hirsutum L.). Plant Breed 133(4):521–529. https://doi.org/10.1111/pbr.12176
Tang FY, Mo WC, Wang XF, **ao WJ (2010) Analysis on genetic contribution of plant type traits to lint yield in upland cotton (Gossypum hirsutum L.). Chin Agric Sci Bull 26(23):151–156 (in Chinese)
Wang HT, Li XH, Cai X, Tang LY, Zhang SJ, Liu CJ, Zhang XY, Zhang JH (2022a) Genetic diversity analysis of agronomy and fiber quality characters in 314 upland cotton germplasm resources. Shandong Agric Sci 54(05):16–23 (in Chinese)
Wang RM, Zhao WC, Zhang AM, Qi HX, Dong LY, Zhang DL, Li FR, Yang XF, Shi JL (2022b) Analysis of heritability and combining ability of 18 parents and combination main characters of upland cotton. Cotton Sci 44(3):47–53 (in Chinese)
Wu JX, Jenkins JN, McCarty JC, Zhu J (2004) Genetic association of yield with its component traits in a recombinant inbred line population of cotton. Euphytica 140:171–179. https://doi.org/10.1007/s10681-004-2897-5
Wu K, Yu Y, He LR, Liu WH, Wang XW, Li H, Zhao FX (2023) Analysis of the combining ability and heterosis of upland cotton quality and yield traits. Jiangsu Agric Sci 51(6):67–73 (in Chinese)
Yang DG (2011) Genetic effects and expression profiling analysis of upland cotton double row hybridization. Bei**g, Chinese Academy of Agricultural Sciences in Chinese
Ye ZH, Mei YJ, Zou KQ, Fu XS, Jiang LS (2008) Genetic dissection of net effects between yield and its components in sea island cotton (Gossypium barbadense L.). Agric Sci China. 7(9):1052–1060
Yu SX, Wei XW, Zhao XH (2000) Cotton production and technical development in China. Cotton Sci 06:327–329 (in Chinese)
Yu SX, Fan SL, Wang HT, Wei HL, Pang CY (2016) Advances in high yield breeding of cotton in China. Sci Agric Sin 49(18):3465–3476 (in Chinese)
Yuan ZF, Zhou JY, Guo MC, Lei XQ, **e XL (2001) Decision coefficient: the decision index of path analysis. J Northwest a&f Univ 29(5):131–133 (in Chinese)
Zeng LH, Pettigrew WT (2015) Combining ability, heritability, and genotypic correlations for lint yield and fiber quality of upland cotton in delayed planting. Field Crop Res 171:176–183. https://doi.org/10.1016/j.fcr.2014.10.004
Zhang JF, Wu M, Yu J, Yu JW, Li XL, Pei WF (2016) Breeding potential of introgression lines developed from interspecific crossing between upland cotton (Gossypium hirsutum L.) and Gossypium barbadense: heterosis, combining ability and genetic effects. PLoS ONE 11(1):e0143646. https://doi.org/10.1371/journal.pone.0143646
Zhao CS, Zhao XW, Sun LP, Li SN, Guo BF, Wang RZ (2021) Field identification and selection of excellent soybean germplasm resources from different origins. Acta Agric Boreali-Occidentalis Sin 30(11):1638–1647 (in Chinese)
Acknowledgements
This study was supported by the National Natural Science Foundation of China Genome-wide Mining of Specific Yield Traits (QTs) in Upland Cotton from Southern **njiang (31560408). We thank Zhu J of Zhejiang university and Yuan ZF of Northwest F&A University, China for providing the test method used in this research.
Funding
This study was supported by the National Natural Science Foundation of China Genome-wide Mining of Specific Yield Traits (QTs) in Upland Cotton from Southern **njiang (31560408).
Author information
Authors and Affiliations
Contributions
CL planned the experiments and wrote the manuscript. YG and ZD provided advice for experiments and manuscript writing. JY conceived and designed the research and manuscript revision. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Li, C., Guan, Y., Dong, Z. et al. Genetic contribution and decision-making coefficients analysis of agronomic components of upland cotton in Southern **njiang to yield traits. Euphytica 220, 86 (2024). https://doi.org/10.1007/s10681-024-03346-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10681-024-03346-x