Cotton (Gossypium hirsutum L.) breeding strategies

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Abstract

This chapter is focused on the achievements and future prospects of cotton breeding and related biotechnology. Traditional plant breeding has been utilized for the development of pure-line selection for high yielding cotton genotypes in segregating generations through the pedigree method. Selection criteria include boll number plant-1, boll mass, sympodial branches and ginning outturn percentage. Plant breeder efforts have been fruitful in releasing cotton cultivars with high yield potential and superior lint quality traits. Traditional breeding efforts resulted in the increase of seed cotton yield and fiber length. The calculated increase in the yield potential was 1.34 kg ha-1 year-1. However, further genetic gains due to selection for high-yield potential reached a plateau in the last two decades and the recent increase in yield was due to better cotton husbandry techniques. Cotton ideotypes specifically for various agronomic and environmental conditions may be developed. Moreover, utilization of wild relatives for the introgression of disease resistance and abiotic stress tolerance is proposed through traditional plant breeding along with molecular markers to reduce linkage drags due to wild relatives. These high yielding cultivars with superior agronomic and adaptability traits may be further used for the development of transgenics. Genome editing technique such as CRISPR/Cas (clustered regularly interspaced short palindromic repeats: associated protein) is one of the emerging technologies to knock out genes or SNP (single nucleotide polymorphism) substitution at specific site with future prospects for the development of disease resistant crop cultivars.

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Rauf, S., Shehzad, M., Al-Khayri, J. M., Imran, H. M., & Noorka, I. R. (2019). Cotton (Gossypium hirsutum L.) breeding strategies. In Advances in Plant Breeding Strategies: Industrial and Food Crops (Vol. 6, pp. 29–59). Springer International Publishing. https://doi.org/10.1007/978-3-030-23265-8_2

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