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[学术文献 ] Multi-modal feature integration from UAV-RGB imagery for high-precision cotton phenotyping: A paradigm shift toward cost-effective agricultural remote sensing 进入全文
COMPUTERS AND ELECTRONICS IN AGRICULTURE
Cost-effective remote sensing solutions are critically needed to democratize precision agriculture technologies. While hyperspectral and LiDAR systems deliver high accuracy, their prohibitive costs limit widespread adoption. This study demonstrates that systematic multi-modal feature integration transforms standard UAV-based RGB imagery into a powerful phenotyping instrument, achieving crop trait prediction accuracy comparable to systems costing 10-50 times more. We developed a comprehensive framework integrating spectral indices, geometric parameters, and texture metrics from commodity RGB sensors to predict five critical cotton traits: leaf area index (LAI), intercepted photosynthetically active radiation (IPAR), above-ground biomass, lint yield, and seed cotton yield. The progressive integration approach employed Random Forest regression with four feature configurations: baseline color indices (CIbase), refined color indices (CIref), geometric parameters (CIref + GP), and texture metrics (CIref + GP + T). Field experiments across three trials over two growing seasons (2022-2023) with varying genotypes, planting densities, and sowing dates provided 2,126 ground truth measurements for model development and validation. The optimal multi-modal model achieved R2 = 0.97 for IPAR (rRMSE = 6 %), R2 = 0.91 for LAI (rRMSE = 15 %), and R2 = 0.85 for biomass (rRMSE = 32 %), with lint yield and seed cotton yield demonstrating R2 values of 0.92 and 0.77, respectively. Variance partitioning analysis revealed texture features as the dominant contributor (16.2 % +/- 7.1 %), followed by spectral indices (9.1 % +/- 4.2 %) and geometric parameters (8.0 % +/- 2.8 %), with substantial shared variance (45-65 %) indicating strong feature complementarity. Phenological analysis demonstrated that flowering-stage imagery outperformed boll opening stage measurements, while stage-general models showed superior robustness. Cross-temporal validation confirmed model generalizability, with trial-general models achieving R2 values of 0.91-0.97 for IPAR across diverse environmental conditions. The framework enables sub-meter spatial resolution trait mapping while maintaining operational simplicity and cost-effectiveness, demonstrating that systematic feature engineering can democratize high-precision phenotyping technologies for broader agricultural applications.
[学术文献 ] Mapping the Phosphorylation Regulatory Network of Single-Celled Fibre Elongation Mediated by GhBIN2 in Cotton 进入全文
PLANT BIOTECHNOLOGY JOURNAL
Protein phosphorylation plays a pivotal role in cellular signal transduction and plant development. The plant steroid hormone Brassinosteroids (BRs) signal transduction relies primarily on protein kinase-mediated phosphorylation cascades. However, the specific mechanisms of phosphorylation regulation in BR signalling remain to be fully elucidated. This study focuses on BIN2, an indispensable protein kinase in the BR signalling pathway, utilising single-celled cotton fibre to investigate the mechanisms by which phosphorylation regulates cell elongation. Firstly, we confirmed the inhibitory role of GhBIN2 in fibre elongation through its overexpression. Subsequently, we employed 4D-fastDIA quantitative phosphoproteomics and proteomics analysis to map the GhBIN2-mediated phosphorylation regulatory network. Through a comprehensive analysis of this network, we identified six credible substrates of GhBIN2. Further investigation revealed that GhBIN2 interacts with substrate GhIQD14 and increases its abundance through phosphorylation to negatively regulate fibre elongation. This study deepens the understanding of BR signalling in cotton fibre elongation and provides experimental evidence and new insights for comprehending the regulatory role of protein phosphorylation in plant cell elongation processes.
[学术文献 ] Examining photosynthetic induction variation among historical cotton cultivars through time-integrated limitation analyses 进入全文
PLANT PHYSIOLOGY
A thorough understanding of the biochemical, stomatal, and mesophyll components that limit photosynthetic induction is crucial for targeted improvement of crop productivity. However, compared with biochemical activation and stomatal conductance (gs), mesophyll conductance (gm) remains underexplored in induction studies. The fluorescence method (the variable J method) is a valid and widely accessible tool for gm measurement under steady-state conditions. Here, we experimentally validated the applicability of the fluorescence method under nonsteady-state conditions, demonstrating comparable induction kinetics of gm with the well-established carbon isotope method. Building on this validation, we combined the fluorescence method with gas-exchange measurements to comprehensively examine the induction kinetics of photosynthetic rate (A) and its associated components in a set of historical cotton (Gossypium hirsutum L.) cultivars. Our results showed no significant effect of the year of cultivar release on A during induction, suggesting that dynamic photosynthesis has not benefited from past selection efforts in cotton. Nonetheless, significant among-cultivar variations were observed in all measured induction traits, hinting at breeding opportunities for leveraging dynamic photosynthetic variation to boost crop productivity. Through induction-period-integrated limitation analysis, we further identified gs as the single most important limiter of photosynthetic induction across all cotton cultivars. Moreover, the analysis also demonstrated that accurately accounting for gm kinetics is essential for the unbiased acquisition of mechanistic insights into nonsteady-state photosynthetic physiology. We recommend that future induction studies incorporate gm measurements whenever possible to strengthen the knowledge base necessary for genetically enhancing dynamic carbon gain and crop yield in the field. Time-integrated limitation analyses incorporating mesophyll conductance reveal stomatal conductance as the primary limitation of photosynthetic induction among historical cotton cultivars.
[学术文献 ] Patterns of domestication in upland cotton (Gossypium hirsutum): a perspective from multielement stoichiometry 进入全文
BMC Plant Biology
Upland cotton (Gossypium hirsutum) is one of the most important cash crops in the world, but few studies have investigated its chemical and physiological changes during domestication, especially changes in chemical element stoichiometry. We investigated the concentrations of 15 chemical elements (carbon, nitrogen, calcium, potassium, sulfur, phosphorus, magnesium, iron, silicon, manganese, boron, zinc, nickel, copper, and molybdenum) in the leaves of 41 genotypes of semiwild and domesticated upland cotton. Principal component analysis, network analysis and domestication effect analysis were used to explore the changes in multielement stoichiometry during the domestication of upland cotton. Analysis of the multielement network indicated that calcium became a more important element after domestication. Across the studied genotypes, the concentrations of carbon and phosphorus decreased after domestication, whereas the concentrations of calcium, magnesium and zinc increased. These alterations resulted in significant domestication effects on some elemental ratios. Combined with changes in plant aboveground biomass, a genetic dilution effect of phosphorus was found. We proposed and tested the “elemental domestication effect” (EDE) in upland cotton (the higher the concentration of elements, the easier it is to be changed during domestication), which may provide new directions for potential crop breeding. We suggest further increasing the calcium, magnesium, and zinc concentrations to enhance the potential for cotton yield and quality, and to reverse the continuous decrease in phosphorus concentration through biological fortification.
[学术文献 ] Biochemical defense responses in cotton: secondary metabolite and antioxidant shifts under thrips infestation 进入全文
PHYTOPARASITICA
Thrips are among the most destructive pests of cotton, causing significant losses in yield and fiber quality through direct feeding. This study aimed to investigate the biochemical responses associated with thrips resistance in two cotton genotypes- LH 2107 (susceptible) and LD 491 (tolerant). Key defense-related parameters, including phenolic metabolism, antioxidant activity, and volatile compounds, were analyzed under both uninfested and thrips-infested conditions. Activities of phenylalanine ammonia-lyase and tyrosine ammonia lyase increased significantly in LD 491 during an infestation, indicating enhanced phenolic biosynthesis. Both genotypes exhibited increased levels of total phenols, o-dihydroxy phenols and total flavanols from 15 days post-infestation, with LD 491 showing significantly higher concentrations than LH 2107. Antioxidant assays revealed a marked rise in DPPH free radical scavenging activity, FRAP activity, total reducing power, superoxide anion radical scavenging activity, and hydroxyl radical scavenging activity, with LD 491 demonstrating the greatest enhancement. GC-MS analysis of volatile compounds showed genotype-specific differences, with the compound palmitin, 2-mono- uniquely present in LD 491 under both conditions. These findings suggested that elevated phenolic content, antioxidant activity, and specific volatiles contribute to thrips resistance in cotton. The identified biochemical markers may serve as valuable tools for screening and breeding thrips-resistant cotton genotypes.
[学术文献 ] Fiber Quality and Stability of Partially Interspecific Cotton Lines Under Irrigation and Nitrogen Environments 进入全文
APPLIED SCIENCES-BASEL
Cotton is one of the most important crops worldwide, having considerable economic importance in Greece. This study aimed to evaluate the fiber quality traits of partially interspecific cotton lines under contrasting irrigation and nitrogen environments within a strip-split block field design. Experiments conducted over two consecutive years include a control (commercial cultivar Celia) and four partially interspecific lines of the Pa7 generation (Gossypium hirsutum x G. barbadense). Three irrigation and two nitrogen fertilization levels were applied. Significant differences were observed among genotypes and environments for all fiber quality traits, with some year-to-year variation. Genotypic response for yellowness was influenced by fertilization. Across the two experimental years, a strong Fertilization x Environment interaction was observed, and in the second year, a Genotype x Fertilization x Environment interaction was detected for the uniformity index. Pa7 lines consistently outperformed Celia in fiber length (approximate to 33 vs. 30 mm) and elongation (approximate to 7.0 vs. 5.5%), while exhibiting higher yellowness values. Fiber strength, micronaire, uniformity, and reflectance varied between years but remained within acceptable ranges. Overall, Pa7 lines demonstrated superior fiber quality and stability under variable conditions, highlighting their potential for breeding programs. These findings support the importance of integrating interspecific germplasm with suitable irrigation-nitrogen management to improve cotton fiber performance and resilience under diverse cultivation environments.
