Current Issue http://journals.caass.org.cn/mhxb EN-US http://journals.caass.org.cn/mhxb/EN/current.shtml http://journals.caass.org.cn/mhxb 5 2SO₄ stress is a major type of salt stress in Xinjiang and has seriously restricted the cotton production in Xinjiang. This study aims to explore the effect of Na₂SO₄ stress on cotton metabolism and to investigate the key metabolites and metabolic pathways in the stress response of cotton. [Method] The metabolic analysis was applied in cotton roots and leaves under two treatment settings, including control (CK) and sulfate stress (Na₂SO₄, SS), to explore the changes of metabolite content and metabolic pathways in cotton under Na₂SO₄ stress. [Result] Sulfate stress significantly inhibited the growth of cotton. Compared with CK, the dry mass of leaves, stems, and roots, and total mass of plant under SS treatment decreased by 46.9%, 50.9%, 43.0% and 47.9%, respectively. Under sulfate stress, there were 42 up-regulated and 10 down-regulated organic acids, 32 up-regulated and 16 down-regulated amino acids and amino acid derivatives, 23 up-regulated and 1 down-regulated carbohydrate in root. There were 37 up-regulated organic acids and 7 down-regulated organic acids, 16 up-regulated and 17 down-regulated amino acids and amino acids derivatives, 16 up-regulated and 4 down-regulated carbohydrate in leaves. A total of 30 differential metabolic pathways were selected in roots, including 9 pathways related to amino acid metabolism, 7 pathways related to organic acid metabolism, and 7 pathways related to carbohydrate metabolism. A total of 17 differential metabolic pathways were selected in leaves, including 7 pathways related to amino acid metabolism, 4 pathways related to organic acid metabolism, and 3 pathways related to carbohydrate metabolism. [Conclusion] Cotton responded to sulfate stress by accumulating organic acids, carbohydrate and alcohols in roots and leaves. The up-regulation of citric acid, succinic acid, pyruvic acid and linoleic acid in leaves suggested the enhanced tricarboxylic acid (TCA) cycle and β-enhanced oxidation. And up-regulation of citric acid, succinic acid and pyruvic acid in roots indicated the enhanced TCA cycle. This study explored the mechanism of Na₂SO₄ stress response in cotton and provided a theoretical basis for cotton cultivation in Xinjiang.]]> -1 1-methylcyclopropene (1-MCP), 0.01, 0.02, 0.05 μmol·L^-1 coronidine (COR) and 0.5, 1.0, 2.0 μmol·L^-1 2, 4-epibrassinolide (EBR) spraying treatments were set at the seedling stage. Water and 400 μmol·L^-1 1-MCP spraying treatment were set at the flowering and boll setting stage. The effects of different plant growth regulators on the dry mass, leaf photosynthetic characteristics, chlorophyll content, antioxidant enzyme activity, yield and fiber quality of cotton under the normal temperature and high temperature conditions were explored. [Result] The results showed that the suitable concentrations of three plant growth regulators could improve the high temperature tolerance of cotton. Under high temperature stress at the seedling stage, compared with water treatment, spraying 400 μmol·L^-1 1-MCP could significantly increase the dry mass of aboveground and underground parts of cotton, and increase the net photosynthetic rate, the contents of chlorophyll a and chlorophyll b, and the activities of antioxidant enzymes (superoxide dismutase, peroxidase, glutathione peroxidase and ascorbate peroxidase), and decrease malondialdehyde content in newly expanded cotton leaves. Principal component analysis proved that 400 μmol·L^-1 1-MCP could effectively improve the high temperature tolerance of cotton. Meanwhile, under high temperature stress at the flowering and boll setting stage, spraying 400 μmol·L^-1 1-MCP could significantly improve the net photosynthetic rate, stomatal conductance and transpiration rate of subtending leaves to cotton bolls, the number of bolls per plant, boll weight, seed cotton yield per plant and fiber quality compared with spraying water. [Conclusion] 400 μmol·L^-1 1-MCP can increase the chlorophyll content, photosynthetic capacity and antioxidant enzyme activity, and reduce the accumulation of malondialdehyde and other harmful substances in cotton leaves, thus enhancing the high temperature tolerance of cotton, and finally improve the cotton yield and fiber quality to a certain extent.]]> 4 plant·hm^-2), medium density (D2, 13.8 × 10⁴ plant·hm^-2) and high density (D3, 24 × 10⁴ plant·hm^-2). The UAV images were obtained on the 25 days old cotton seedlings, and the vegetation indices (VIs) of red, green, and blue (RGB) and target morphological features were extracted from the acquired UAV images. Based on the selected independent variable according to the correlation analysis, the model to estimate the quantity of cotton seedlings was constructed using stepwise multiple regression, followed by the model validation. [Results] (1) Comparing the segmentation effects of extracting cotton targets by triangular greenness index (TGI), excess greenness index (ExG), and green-blue difference + modified excess greenness index (GBDI + MExG), all these three VIs had relatively good segmentation effects, while TGI showed the highest precision of segmentation of cotton targets. (2) Comparing the two cotton plant quantity estimation models constructed with the two feature parameters, the estimation model based on the target morphological features for cotton seedling (R²=0.935 5) is better than the estimation model based on the VI of RGB (R²=0.903 6). (3) The estimation accuracy of the VIs-based seedling quantity estimation model were 96.77%, 99.55%, and 95.95% at D1, D2 and D3 densities respectively, and the overall estimation accuracy was 98.47%; the estimation accuracy of the plant estimation model based on the target morphological features at D1, D2 and D3 densities were 99.98%, 99.21%, and 97.92% respectively, and the overall estimation accuracy was 99.21%. The accuracy of the plant number estimation model based on the target morphological characteristics was slightly higher than that of the plant number estimation model based on VIs, but both models had good estimation outcome under different planting densities. [Conclusion] Using the UAV based low-altitude remote sensing platform with the integration of high-resolution sensors, the quantity estimation models for the drip-irrigated cotton seedlings were constructed by color vegetation indices and morphological features of target plants. Both models can effectively and accurately identify and quantify the drip-irrigated cotton plants under mulching, providing technical support for subsequent precision management in cotton fields.]]> Lygus pratensis in cotton field, so as to provide a theoretical basis for the ecological control of L. pratensis. [Method] A total of 20 cotton fields in Aral Reclamation Area of Xinjiang were selected as experimental sites from 2019 to 2021. The methods of net trapping and sex attracter combined with yellow plate trapping were used to investigate the population dynamics of L. pratensis adults, and the land use status around the cotton field within a radius of 2 000 m was also investigated. A linear mixed model was fitted to the landscape parameters of farmland landscape patterns at 500 m, 1 000 m, 1 500 m and 2 000 m scales and the population number of the L. pratensis adults of the second- and third-generation. [Result] L. pratensis had 4 generations in Aral Reclamation Area every year, and the second and third generations were the main populations in cotton fields. At the four scales, host crop habitat (Host) accounted for the highest area (64.14%-69.85%), followed by single crop (Cotton) habitat (51.21%-55.26%), while the area ratio of forest belt and desolate sands habitat (FBDS), shrub habitat (Shrub), building land habitat (Building), other crop habitat (Other crops) and water habitat (Water) were relatively low. The results of model fitting showed that the control effect of landscape variables on the population number of the second-generation adults in the cotton field gradually weakened with the increase of the scale. There were extremely significant or significant positive correlation between the population number of the second-generation adults and the area ratio of Building (500 m scale) and FBDS (1 500 m scale), and a strong and extremely significant negative correlation between the population number of the second-generation adults and the area ratio of Host (1 000 m scale). There was a strong and extremely significant positive correlation between the population number of the third-generation adults of L. pratensis and the area ratio of Building (500 m scale). The population number of the third-generation adults was negatively correlated with the area ratio of Host (1 000 m), Other crops (1 000 m, P < 0.01) and Water (1 000 km, P < 0.05), and positively correlated with the perimeter area ratio (1 500 m, P < 0.05; 2 000 m, P < 0.01). [Conclusion] The farmland landscape pattern had an obvious regulatory effect on the population number of L. pratensis adults in cotton field. The increase of the area ratio of Host, Other crops and Water in farmland landscape had a certain control effect on the population number of L. pratensis in cotton field. The increase of the area ratio of FBDS and Building promoted the occurrence of L. pratensis in cotton fields.]]> Gossypium hirsutum × G. barbadense. [Method] In this study, CSSL MBI7561 with excellent fiber quality selected from BC₄F_3:5 of CCRI 45 (G. hirsutum) × Hai 1 (G. barbadense) was used to construct the secondary segregating populations of two generations BC₅F₂ and BC₅F_2:3. Then two populations (BC₆F₂ and BC₆F_2:3) were obtained through backcrossing with the recurrent parents and selfing. Four simple sequence repeat markers, CGR6894a, PGML02608, NAU5408 and NAU3594, linked to three major QTL for fiber length (qFL-16-1, qFL-16-4, qFL-16-5) and three major QTL for fiber strength (qFS-16-1, qFS-16-4 and qFS-16-5) on chromosome 16, were used to screen individuals of BC₆F₂ and BC₆F_2:3. [Result] Four markers related to qFL-16-1, qFL-16-4, qFL-16-5, qFS-16-1, qFS-16-4 and qFS-16-5 indicated obvious and significant single marker selection effect and pairwise marker pyramiding effect for fiber length and fiber strength in the two populations of BC₆F₂ and BC₆F_2:3. Furthermore, the excellent individual which contain more than two QTL was screened. [Conclusion] The analyzed QTL related to fiber length and fiber strength on chromosome 16 had significant genetic effects in different generations of the CSSLs, and the fiber length and fiber strength of individuals were significantly increased by pyramiding two QTL. This study laid an important foundation for molecular marker to assist the pyramiding selection of fiber length and strength.]]>