Drought stress significantly affects the growth, development, and yield of cotton, triggering the response of multiple genes. Among them, ascorbate peroxidase (APX) is one of the important antioxidant enzymes in the metabolism of reactive oxygen species in plants, and APX enhances the ability of plants to resist oxidation, thus increasing plant stress tolerance. Therefore, enhancing the activity of APX in cells is crucial to improving plant stress resistance. Previous studies have isolated differentially expressed proteins under drought stress (GhAPX7) in drought-resistant (KK1543) and drought-sensitive (XLZ26) plants. Thus, this study analyzed the expression patterns of GhAPX7 in different cotton tissues to verify the drought resistance function of GhAPX7 and explore its regulatory pathways. GhAPX7 had the highest expression in cotton leaves, which significantly increased under drought stress, suggesting that GhAPX7 is essential for improving antioxidant capacity and enzyme activities in cotton. GhAPX7 silencing indirectly affects pronounced leaf yellowing and wilting in drought-resistant and drought-sensitive plants under drought stress. Malondialdehyde (MDA) content was significantly increased and chlorophyll and proline content and APX enzyme activity were generally decreased in silenced plants compared to the control. This result indicates that GhAPX7 may improve drought resistance by influencing the contents of MDA, chlorophyll, proline, and APX enzyme activity through increased expression levels. Transcriptome analysis revealed that the drought-related differentially expressed genes between the control and treated groups enriched plant hormone signal transduction, MAPK signaling, and plant–pathogen interaction pathways. Therefore, the decreased expression of GhAPX7 significantly affects the expression levels of genes in these three pathways, reducing drought resistance in plants. This study provides insights into the molecular mechanisms of GhAPX7 and its role in drought resistance and lays a foundation for further research on the molecular mechanisms of response to drought stress in cotton.

(1) Background: This study aims to analyze the defoliation and boll opening performance of 123 upland cotton germplasm resources after spraying defoliant, using multispectral data to select relevant vegetation indices and identify germplasm resources sensitive to defoliants, providing methods for cotton variety improvement and high-quality parental resources. (2) Methods: 123 historical upland cotton germplasm resources from Xinjiang were selected, and the defoliation and boll opening of cotton leaves were investigated at 0, 4, 8, 12, 16, and 20 days after defoliant application. Simultaneously, multispectral digital images were collected using drones to obtain 12 vegetation indices. Based on defoliation rate, the optimal vegetation index was selected, and defoliant-sensitive germplasm resources were identified. (3) Results: The most significant difference in defoliation rate of cotton germplasm resources occurred 16 days after application. Cluster analysis grouped the 123 breeding materials into three categories, with Class I showing the best defoliation effect. Among the 12 vegetation indices, the Plant Senescence Reflectance Index (PSRI) has the highest correlation coefficient with the defoliation rate; and when the PSRI value is higher, the defoliation effect of the material is better. By comparing the traditional investigation method with the unmanned aerial vehicle multispectral technology, 15 cotton materials sensitive to defoliants were determined, with a defoliation rate of over 85%, a lint percentage ranging from 76.67% to 98.04%, and a PSRI value ranging from 0.1607 to 0.1984. (4) Conclusions: The study found that the vegetation index with sensitive response can be used as an effective indicator to evaluate the sensitivity of cotton breeding materials to defoliants. Using an unmanned aerial vehicle (UAV) equipped with vegetation indices for screening shows a high consistency with the manual investigation and screening method in screening excellent defoliation materials; it proves that it is feasible to screen cotton breeding materials with excellent defoliation effects using UAV multispectral technology.

(1) Background: This study aims to analyze the defoliation and boll opening performance of 123 upland cotton germplasm resources after spraying defoliant, using multispectral data to select relevant vegetation indices and identify germplasm re-sources sensitive to defoliants, providing methods for cotton variety improvement and high-quality parental resources. (2) Methods: 123 historical upland cotton germplasm resources from Xinjiang were selected, and the defoliation and boll opening of cotton leaves were investigated at 0, 4, 8, 12, 16, and 20 days after defoliant application. Sim-ultaneously, multispectral digital images were collected using drones to obtain 12 vegetation indices. Based on defoliation rate, the optimal vegetation index was selected, and defoliant-sensitive germplasm resources were identified. (3) Results: The most significant difference in defoliation rate of cotton germplasm resources occurred 16 days after application. Cluster analysis grouped the 123 breeding materials into three categories, with Class I showing the best defoliation effect. Among the 12 vegetation indices, the Plant Senescence Reflectance Index (PSRI) has the highest correlation coef-ficient with the defoliation rate; and when the PSRI value is higher, the defoliation ef-fect of the material is better. Using drone multispectral technology, 15 defoli-ant-sensitive cotton materials were identified, with defoliation rates exceeding 85%, boll opening rates ranging from 76.67% to 98.04%, and PSRI values between 0.1607 and 0.1984.(4) Conclusions: The study found that vegetation indices with sensitive re-sponses can serve as effective indicators for evaluating the sensitivity of cotton breed-ing materials to defoliants. The combined analysis of traditional survey methods and PSRI classification demonstrates that using drone multispectral technology as a sub-stitute for manual methods in large-scale, rapid monitoring and selection of cotton breeding materials with excellent defoliation effects is feasible.

Background: As a ubiquitous acid-regulating protein family in eukaryotes, 14-3-3 proteins are widely involved in the growth and development of plants. With the development of the third-generation sequencing technology and the smooth completion of the cotton genome work, it is possible to explore the existence and distribution of the 14-3-3 protein family in cotton.Results: In this paper, 33, 33, 17 and 18 members were identified from this family in Gossypium hirsutum((AD)1), G. barbadense((AD)2), G. arboreum(A2) and G. raimondii(D5), respectively. In particular, evolution analysis, structure analysis and functional expression analysis of this protein family in G. hirsutum((AD)1) were carried out. The results showed that compared with Arabidopsis and rice, the phylogenetic tree and gene structure clearly divided the 14-3-3 protein family into two subgroups in G. hirsutum((AD)1), the ε group and the non-ε group; Analysis of transcriptome expression patterns revealed that this family was significantly induced to express under abiotic stress; Most 14-3-3 proteins have a large number of cis-acting elements related to growth, development and abiotic stress in the promoter region, among which elements related to drought stress account for the largest proportion; The results of qRT-PCR showed that the expression of 14-3-3 protein had significant differences under drought stress.Conclusions: In summary, this study signified that the 14-3-3 protein family is relatively conserved in the evolutionary expansion of cotton, and may be involved in the growth and development of plants and the mechanism of stress resistance. These results provide an important theoretical and experimental basis for further analysis and verification of the function of 14-3-3 protein in cotton.