Speed breeding in upland cotton (Gossypium hirsutum L): scientific foundations and integrated implementation of a next-generation cotton breeding platform

Abstract

Conventional cotton (Gossypium spp.) variety development requires 8–12 years - a timeline structurally incompatible with the accelerating urgency of climate-change adaptation, soil salinisation, and textile-industry demands for novel varieties within 3–5 years. Speed breeding (SB) compresses the generation interval by 30–80% through synergistic optimisation of LED spectra, temperature, nutrition, and immature embryo rescue (IER). However, SB alone is a temporal accelerator, not a breeding system: its transformative potential is realised only when it functions as the central engine of a genomics-assisted speed breeding (GASB) platform that integrates molecular marker-assisted selection (MAS), genomic selection (GS), CRISPR and New Genomic Technique (NGT) editing, high-throughput phenotyping (HTP), and AI-assisted decision-support tools. Building on previous reviews of cotton speed breeding and genomics-assisted breeding, the present review provides a mechanistic and implementation-oriented synthesis of these complementary technologies within a unified GASB framework. We evaluate: (i) the molecular architecture of photoperiodic flowering in predominantly Gossypium hirsutum, together with currently available evidence from other Gossypium species where appropriate and its manipulation through LED protocol design and CRISPR targeting of flowering suppressors; (ii) the mechanistic basis of multi-channel LED recipe design from SB 1.0 to SB 3.0; (iii) stage-specific thermal management including the operationally critical 33°C pollen safety ceiling; (iv) nutritional physiology, phytohormones, and biochemical monitoring; (v) in vitro biotechnologies—including callus culture, microspore-derived doubled haploids, and immature embryo rescue (IER)—together with the operational coordination of immature embryo rescue and pollen-stage temperature management within speed-breeding facilities; (vi) high-throughput phenotyping technologies experimentally validated in cotton, encompassing five cotton-specific applications reviewed in a dedicated section; and (vii) AI-assisted phenotyping and digital twin architectures for real-time decision support within the GASB pipeline. Critical analysis identifies allotetraploid genome redundancy, genotype × light environment (G×L) interaction with landrace germplasm, IER scalability, bioinformatics infrastructure gaps, SB-to-field correlation uncertainties, and SVT regulatory requirements as the primary barriers to widespread GASB deployment. A structured 2025–2035 roadmap with three time-horizon priorities and measurable KPIs is presented.