[Objective] This study aims to perform genome-wide asscciation study of cotton yield traits, such as lint percentage (LP) and boll weight(BW), and to mine the candidate genes, and may be helpful for improving cotton yield through molecular marker-assisted selection and molecular design breeding. [Methods] Genome-wide association study was performed using 300 upland cotton germplasms resequencing (10×) data and 3 055 642 high-quality single nucleotide polymorphism (SNP) for LP and BW in five environments and best linear unbiased predictive value (BLUP) for two years to detect significant association loci and candidate genes. [Results] The cotton LP and BW showed wide variations in different environments, with an average coefficient of variation of 9.40% and heritability of 92.81% for LP, and an average coefficient of variation of 11.96% and heritability of 86.67% for BW. BW is significantly positively correlated in different environments. It’s the same with LP. Population structure analysis, principal component analysis, and phylogenetic analysis classified the 300 upland cotton lines into six subgroups. Genome-wide association study detected a total of 223 quantitative trait locus (QTL) associated with LP and 89 QTL associated with BW. The three stable QTL qLP_Gh5.18, qLP_Gh12.43, and qLP_Gh17.2 screened in LP were further analyzed, and 17 related candidate genes were found. Two stable QTL qBW_Gh7.5 and qBW_Gh19.5 related to BW were further analyzed, and 8 related candidate genes were identified. [Conclusion] Five stable QTL were identified in 300 up land cotton lines associated with cotton LP and BW, and a total of 25 candidate genes related to LP and BW were mined.

[Objective] This research aims to analyze the resilience level and its influencing factors of China's cotton industrial chain, and to provide reference for the development of cotton industry. [Methods] Based on the resilience theory, a evaluation index system for resilience of cotton industrial chain was constructed from four dimensions of resistance capability, recovery capability, update capability, and government power. And a dynamic evaluation model based on entropy weight-virtual optimal solution technique for order preference by similarity to an ideal solution (TOPSIS) and grey relational analysis was used to measure the resilience level of cotton industrial chain in China from 2007 to 2022. The spatial evolution characteristics of resilience level of cotton industrial chain in China were studied by using the geographic information system (GIS) spatial analysis techniques. Tobit regression model was used to explore the influencing factors of cotton industrial chain resilience. [Results] From 2007 to 2022, the resilience level of China's cotton industrial chain showed a trend of increasing first and then decreasing. In 2007-2016, it was a stable growth period; 2017-2021 was an accelerated growth period; and in 2022, the resilience level decreased, which is a challenging recovery period. From 2007 to 2022, the number of high and higher resilience value area of cotton industrial chain increased, while the number of lower value area decreased. The resilience levels of cotton industrial chain in Xinjiang, Gansu, Shandong, and Hubei were increasing. The levels of opening to the outside world as well as government support showed significant positive impact on the resilience of cotton industrial chain. The impact of scientific and technological innovation level and transportation infrastructure level on the resilience of cotton industrial chain were positive; while the impact of cotton price level was negative. [Conclusion] The resilience level of China's cotton industrial chain is on the rise in general, and the spatial pattern has changed greatly. It is necessary to continue to implement the cotton target price policy, strengthen scientific and technological innovation, and promote infrastructure construction to continuously enhance the resilience of China's cotton industrial chain.

[Objective] This study aims to investigate the regulatory effect of exogenous melatonin (MT) on cotton growth and development under salt stress. [Methods] Guoxinmian 9 was used as the material, and the indoor pot method was adopted with the soil salt content of 0.3%, and after screening out the appropriate MT concentration, four treatments were set: irrigate water + spray water (CK), irrigate salt water + spray water (S), irrigate water + spray MT (MT), and irrigate salt water + spray MT (MS). The plant height, stem diameter, leaf area, relative chlorophyll content (soil and plant analyzer development, SPAD value), biomass per plant, root-shoot ratio, antioxidant enzyme activity, reactive oxygen species content, and osmotic adjustment substance content of cotton under different treatments were studied. And correlation analysis of the above indexes was carried out. [Results] Compared with CK treatment, S treatment significantly reduced plant height, stem diameter, leaf area, SPAD value, aboveground fresh matter mass, underground fresh matter mass, aboveground dry matter mass, and underground dry matter mass, and significantly increased root-shoot ratio of cotton. In the later stage of salt stress treatment, S treatment significantly reduced the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) in cotton leaf; significantly increased the contents of hydrogen peroxide, superoxide anion, and malondialdehyde; and significantly decreased the contents of soluble sugar, soluble protein, and proline. Compared with S treatment, foliar spraying 200 μmol·L^-1 MT under salt stress (MS treatment) significantly increased plant height, stem diameter, leaf area, SPAD value, aboveground and underground fresh matter mass, and aboveground dry matter mass per plant; significantly reduced root-shoot ratio; significantly increased SOD, POD, and CAT activities; significantly reduced the contents of hydrogen peroxide, superoxide anion, and malondialdehyde; and significantly increased the contents of soluble sugar, soluble protein, and proline. Aboveground dry matter mass was significantly and positively correlated with plant height, stem diameter, leaf area, SPAD value, aboveground fresh matter mass, underground fresh and dry matter mass, SOD activity, POD activity, CAT activity, soluble sugar content, soluble protein content, and proline content; while was significantly and negatively correlated with superoxide anion content and malondialdehyde content. [Conclusion] Foliar spray 200 μmol·L^-1 MT can effectively alleviate the oxidative stress and osmotic stress of cotton under high salt environment (soil salt content of 0.3%), promote cotton growth, and improve salt tolerance of cotton.

[Objective] This study aims to analysis the effects of partial organic substitution for chemical fertilizer on soil and cotton root growth in different continuous cotton fields in Xinjiang, and to reveal the optimal proportion of organic fertilizer dosage, so as to provide reference for the rational application of fertilizers in continuous cotton fields in Xinjiang. [Methods] The cotton were planted in the grey desert soil and aeolian sandy soil, two common soil types of cotton fields in Xinjiang, and decomposed farm chicken manure was used as organic fertilizer, and setting up three fertilizer treatments: T1 treatment, 100% chemical fertilizer; T2, 80% chemical fertilizer + 20% organic fertilizer (2 250 kg·hm^-2 organic fertilizer); T3, 60% chemical fertilizer + 40% organic fertilizer (4 500 kg·hm^-2 organic fertilizer). The experiments were conducted using polyvinyl chloride pipes to study the effects of partial organic substitution for chemical fertilizer on the physical and chemical properties of cotton soil at the cotton budding stage and boll-opening stages, the morphological and physiological characteristics of cotton roots, as well as the biomass and yield of cotton. Principal component analysis and regression analysis were conducted on all indicators by using the comprehensive membership function method, to comprehensively evaluate the overall impact of different proportions of organic fertilizer and chemical fertilizer combinations on the soil-cotton system. [Results] Both T2 and T3 treatments significantly increased the total nitrogen content and available phosphorus content in grey desert soil and aeolian sandy soil. For grey desert soil, compared with T1, T2 treatment increased the total phosphorus content of the soil by 14.7% and 30.3%, and increased the available phosphorus content by 138.7% and 202.6% during the budding stage and boll-opening stage, respectively. For grey desert soil, compared with T1, T3 treatment increased the soil total nitrogen content by 39.2% during the budding stage and increased the soil total phosphorus content by 46.2% during the boll-opening stage. In T2 and T3 treatments, the total root length, specific root length, specific surface area, soluble sugar content, and nitrate reductase activity of cotton root were significantly increased, while the root tissue density and aboveground biomass were significantly decreased in gray desert soil. During the cotton budding stage in aeolian sandy soil, the specific root length of cotton were significantly increased by 11.9% and 9.6% under T2 and T3 treatments, respectively. Under T2 and T3 treatments during the cotton boll-opening stage in aeolian sandy soil, the alkaline nitrogen contents in the soil significantly were increased by 51.3% and 97.9%, respectively, while the total root length of cotton were significantly decreased by 26.9% and 21.0%; the specific root length of cotton were significantly decreased by 33.4% and 36.5%. T2 treatment significantly reduced the specific root surface areas by 18.8% and 19.3% during two stages, respectively. T3 treatment significantly increased the average root diameter (65.3%) and aboveground biomass (27.6%) of cotton during the boll-opening stage in aeolian sandy soil. [Conclusion] Partial substitution of chemical fertilizers with organic fertilizers can improve the physical and chemical characteristics of grey desert soil and aeolian sandy soil, increase soil nutrient contents, promote the physiological activity of cotton root, optimize root configuration, and enable cotton root to invest less biomass to obtain higher nutrient absorption benefits, optimize the allocation of biomass, and ultimately alleviate continuous cropping obstacles. In grey desert soil, organic fertilizer replacing 40% chemical fertilizer treatment has the best effect. The effect of partially substituting chemical fertilizers with organic fertilizers in sandy soil varies depending on the proportion of organic fertilizer added and the growth period.

[Objective] Assessing cotton growth status through chlorophyll content offers a swift, accurate, and extensive monitoring of cotton development, which aids in precision farming. [Methods] To enhance the accuracy of chlorophyll content evaluation in cotton, fractional-order differentiation ranging from 0 to 2(with a step size of 0.2) and wavelet transform within scales from 1 to 10 to process the hyperspectral reflectance data collected from both upland cotton and sea island cotton fields were employed. By analyzing the correlation between different spectral processing techniques and chlorophyll content, sensitive spectral bands were identified. Subsequently, support vector machine regression(SVR) and random forest regression (RFR) models were employed to construct hyperspectral estimation models for cotton chlorophyll content. [Results] (1) In the wavelength range from 325 to 1 075 nm, the spectral reflectance curves of the two cotton species show similar overall trends, with reflectance increasing with the increase in chlorophyll content.(2) Following continuous wavelet transform and fractional-order differentiation, the correlationship between hyperspectral data and chlorophyll content improved for both cotton species. Inversion models revealed that using RFR and wavelet energy coefficient 7 had the best results for upland cotton chlorophyll content estimation, with a coefficient of determination (R²) of 0.931, root mean square error (RMSE) of 0.782, and residual prediction deviation (RPD) of 2.162. Similarly, for sea island cotton, employing RFR and wavelet energy coefficient 6 resulted in the most effective chlorophyll content estimation, with the R² of 0.932, RMSE of 1.198, and RPD of 2.687. [Conclusion] This study provides technical insights for remotely estimating chlorophyll content in cotton plants.

[Objective] This study aims to explore the response of Gossypium hirsutum under artificial seawater and NaCl stresses, and to assess the feasibility of using artificial seawater to simulate salt stress for evaluating salt tolerance of cotton germplasms. [Methods] Utilizing 135 distinct G. hirsutum germplasms as the experimental materials, this study investigated the impact of artificial seawater and NaCl stresses on cotton seed germination and seedling growth. Through the integration of principal component analysis, membership function analysis, and cluster analysis methodologies, the comprehensive evaluation of cotton salt tolerance was conducted. The results of two identification methods were verified by field experiments under natural salt stress. [Results] The consistency of the identification results under the two salt stresses were only 52.38%, and there were great differences in the results. The identification results under artificial seawater stress were significantly and positively correlated with the results of field experiments, with a correlation coefficient of 0.720; while that under NaCl stress were not significantly correlated with the field identification results. Under artificial seawater and NaCl stress treatments, 21.90% and 33.33% of the 105 glandless cotton germplasms were resistant or tolerant to salt stress, respectively. Among them, Lu 17 and Handifen 29 showed strong salt tolerance under the two salt treatments. [Conclusion] Using artificial seawater that simulates the composition of coastal soil can identify the salt tolerance of cotton germplasms more accurately. Glandless cotton generally exhibits poorer salt tolerance, but there are still some germplasms with strong salt tolerance that can be used to breed new salt tolerant glandless cotton cultivars.

[Objective] This study aims to investigate the dynamic changes of flavonoids in cotton leaves at different growth and development periods. [Methods] Cotton leaves of sGK156 at seedling stage, flourishing flowering stage, and boll opening stage were used as study materials, and the differential metabolites were analysed and flavonoids abundance was detected by ultra-high-performance liquid chromatography-tandem mass spectrometry. [Results] Differential compounds of cotton leaves at three different periods were mainly enriched in the biosynthesis of flavone and flavonol, and the biosynthesis of flavonoids. Compared with those at the flourishing flowering stage and boll opening stage, kaempferol-3-O-arabinopyranoside and naringenin in cotton leaves were significantly higher at the seedling stage, and the contents of 16 flavonoids such as astragalin, tiliroside, and quercetin in cotton leaves at flourishing flowering stage were significantly higher than those at seedling stage and boll opening stage, and the contents of 5 compounds of epicatechin, kaempferol-3-O-rutinoside, kaempferol-3-O-vicianoside, procyanidin B2, and fraxin were significantly higher at the boll opening stage compared with seedling stage and flourishing flowering stage. [Conclusion] This study further analyses the dynamic changes of flavonoid secondary metabolites in cotton leaves during different growth periods, and discover the dominantly expressed flavonoid metabolites in cotton leaves during different growth periods. It provides a theoretical basis for the further study and utilization of flavonoid metabolites in cotton leaves and the selection and breeding of excellent cotton varieties.

[Objective] This research aims to analysis the function of GhWRKY44 gene under drought stress, and to provide candidate gene resources for drought-resistant breeding in cotton. [Methods] The coding sequence of GhWRKY44 gene was obtained by polymerase chain reaction (PCR) from the cDNA of CQJ-5 (Gossypium hirsutum) leaves. And bioinformatics analysis was performed. The expression pattern of GhWRKY44 gene under the treatment of abscisic acid (ABA) and polyethylene glycol (PEG) 6000 were analyzed by quantitative real-time PCR (qRT-PCR). The function of GhWRKY44 genes under drought stress was investigated by using the virus-induced gene silencing (VIGS) technology. [Results] The protein encoded by GhWRKY44 is a member of class Ⅰa WRKY, and is closely related to GbWRKY44. The expression of GhWRKY44 was induced by PEG 6000 and ABA. Compared with the control cotton plants, GhWRKY44 silenced cotton plants showed more severe leaf wilting, and plant survival rate and leaf chlorophyll content (soil and plant analyzer development, SPAD value) were significantly reduced under drought stress. With 6 h and 7 h of dehydration treatment, the leaf water loss rate of GhWRKY44 silenced cotton plants was significantly higher than that of control plants. [Conclusion] Silencing of GhWRKY44 gene reduced drought tolerance of cotton, and GhWRKY44 is a positive regulator of drought tolerance in cotton.

[Objective] This study aims to investigate the effects of nitrogen (N) fertilizer top dressing frequency under drip irrigation on soil N content and cotton yield in southern Xinjiang, and to provide references for the rational N application. [Methods] Field experiments were conducted in Xayar County, Aksu Prefecture, Xinjiang, from 2021 to 2022. With the same total amount of pure N applied (300 kg·hm^-2, 20% basal application, and 80% top dressing with water), four treatments of N fertilizer top dressing frequency were set up (4, 6, 8, and 10; recorded as N4, N6, N8, and N10, respectively). The effects of different treatments on soil total N content and alkali-hydrolyzable N content in the cotton field, cotton dry matter mass and N content, cotton yield, and N partial productivity were analyzed. [Results] The effects of different treatments on soil N content in cotton field changed with cotton growth process. The soil total N and alkali-hydrolyzable N supply under N10 were relatively sufficient at the seedling stage, peak boll-setting stage, and boll opening stage, but was unfavorable to N supply at the squaring stage and peak flowering stage. Whereas soil total N and alkali-hydrolyzable N content were maintained at a higher level during the whole growth stage of cotton under N8. Also under N8, the maximum accumulation rate of dry matter and nitrogen in cotton plants, vegetative organs, and reproductive organs were the highest in 2022; the maximum accumulation rate of N in reproductive organs was the highest in 2021; the dry matter mass and N content of cotton plants, vegetative organs, and reproductive organs were relatively higher in 2021 and 2022. With the increase of N fertilizer top dressing frequency, seed cotton yield and N partial productivity increased firstly and then decreased, and all the highest ones were under N8. Compared with other treatments, seed cotton yield under N8 increased by 3.3%-39.2% and 13.3%-72.8% in 2021 and 2022, respectively; N partial productivity showed the same change range. [Conclusion] Under the water and fertilizer integration mode in the cotton field in southern Xinjiang, top dressing N fertilizer applied with irrigation for 8 times is beneficial to ensure the N supply of the cotton field, and to promote the accumulation of the dry matter and nitrogen in cotton, thus improving cotton yield and N partial productivity.

[Objective] This study aims to investigate the effect of proper postponement of soybean sowing on the productivity of cotton-soybean intercropping system. [Methods] Field experiments were conducted in Linqing City, Shandong Province in 2022 and 2023, and five treatments were set up: cotton monoculture (CM), early-sown soybean monoculture (ESM), late-sown soybean monoculture (LSM), cotton intercropped with early-sown soybean (C||ES), and cotton intercropped with late-sown soybean (C||LS). Various agronomic traits, leaf area index (LAI), canopy photosynthetic rate (CAP), crop yield, harvest index, and land equivalent ratio (LER) were compared among the treatments. [Results] Intercropping is beneficial to reduce the number of rotten bolls per cotton plant at the boll-opening stage. Compared with CM and C||ES treatments, cotton LAI of C||LS at the peak boll-setting stage and boll-opening stage were significantly increased, and the average CAP of cotton under C||LS treatment at the peak squaring stage, peak flowering stage, and peak boll-setting stage were significantly increased. Compared with CM, seed cotton yield of C||LS treatment significantly increased by 11.8%-13.5%, and significantly increased by 21.4%-23.5% in the border row. Compared with C||ES treatment, seed cotton yield of C||LS treatment showed a significant increase of 6.4%-9.4%, with a significant increase of 12.9%-14.8% in the border row. Compared with CM and C||ES treatments, the biological yield of C||LS treatment was increased by 14.6%-18.1% and 8.1%-8.6%, respectively; with an increase of 22.9%-31.3% and 11.9%-21.2% in the border row, respectively. There was no significant difference in harvest index among different treatments. Soybean yield under different treatments was as follows: C||ES > C||LS > ESM > LSM. The biological yield of early sowing soybean was higher than that of late sowing soybean. The soybean harvest index of C||LS treatment was the highest. The LER of C||LS treatment was significantly increased by 4.8% compared with that of C||ES treatment. [Conclusion] Properly delaying the sowing date of soybean can alleviate soybean' competition with cotton in the intercropping system, thereby enhancing the overall productivity of the cotton-soybean intercropping system.

[Objective] This research aims to explore the impact of planting pattern and irrigation quota on the growth, yield, and fiber quality of cotton in southern Xinjiang. [Methods] Using Xinluzhong 67 as the experimental material, field trial was conducted in Tumxuk City, Xinjiang in 2023. Two planting patterns were set: (66 cm + 10 cm) wide and narrow row configuration (M1), and 76 cm equal row spacing configuration (M2). Three irrigation quotas were set: 3 600 m³·hm^-2 (W1), 4 500 m³·hm^-2 (W2), and 5 400 m³·hm^-2 (W3). The differences in soil moisture content, cotton plant height, stem diameter, leaf area index, photosynthetic performance, yield, irrigation water use efficiency, and fiber quality under different treatments were compared. Additionally, the entropy weight technique for order preference by similarity to ideal solution (TOPSIS) was applied for a comprehensive evaluation to identify the optimal treatment. [Results] All treatments showed the largest increase in average soil moisture content in 0-30 cm soil layer after irrigation during the flowering and boll-setting stage (12.18-15.13 percentage point), followed by 30-60 cm soil layer. Under the same irrigation quota, the average soil moisture content in 0-30 cm soil layer after irrigation of M2 treatment was higher than that of M1 treatment. Under the same irrigation quota, plant height, stem diameter, and leaf area index under M2 treatment were higher than those under M1 treatment. Under the same planting pattern, plant height, stem diameter, and leaf area index of cotton all increased with the increasing of irrigation quota. During the flowering and boll-setting stage, the net photosynthetic rate and water use efficiency of leaf under M2W2 treatment were significantly higher than other treatments. The seed cotton yield of M2W2 treatment was the highest, which was significantly increased by 3.26%-17.70% compared with other treatments, and its irrigation water use efficiency was significantly higher than that of M1W2, M1W3, and M2W3 treatments. M2W1 treatment had the highest irrigation water use efficiency. The cotton fiber of M2W2 treatment showed the largest uniformity index, the upper half mean length and breaking elongation were also higher. The evaluation results of entropy weight TOPSIS method indicated that M2W2 treatment had the optimal overall performance. [Conclusion] Adopting the planting pattern of 76 cm equal row spacing with an irrigation quota of 4 500 m³·hm^-2 can effectively promote the growth and development of cotton, and improve the seed cotton yield and fiber quality in southern Xinjiang.

[Objective] This study aims to reveal the effects of different irrigation treatments at the flowering and boll setting stage on the photosynthetic characteristics and yield of cotton, and to provide a reference for the optimization of irrigation system in cotton planting areas of northern Xinjiang. [Methods] A field experiment was conducted in Changji, Xinjiang in 2023, with CCRI 125 as the test variety. Three lower limits of irrigation were set at the flowering and boll setting stage, which were 55% field capacity (T1), 60% field capacity (T2), and 70% field capacity (T3), respectively. The local conventional drip irrigation mode was used as the control (CK). The effects of different treatments on the soil moisture content, photosynthetic characteristics, and yield traits of cotton during the flowering and boll setting stage were analyzed. And the correlation and regression relationships between the photosynthetic index, foliar temperature, and the meteorological factors were also explored. [Results] The soil moisture content of 0-60 cm soil layer of T3 treatment was maintained in a relatively high and stable range (18.5%-21.6%) during the flowering and boll setting period. During the early flowering and boll setting period (11 July), the daily average of net photosynthesis rate of T3 treatment was the highest, showing a daily trend of increasing-decreasing-ascending-decreasing. Correlation analyses showed that net photosynthetic rate and transpiration rate were positively correlated with 0-60 cm soil moisture content, foliar temperature, solar radiation intensity, and ambient temperature. Seed cotton yield and irrigation water use efficiency were the highest under T3 treatment, which were significantly increased by 26.46% and 71.43%, respectively, compared with that of CK. The multi-objective evaluation based on the rank-sum ratio method showed that T3 treatment had the best overall effect. [Conclusion] In the northern Xinjiang where water resources are scarce, the lower and upper limits of irrigation at the flowering and boll setting stage setting at 70% and 90% field capacity, respectively, is a reasonable water-saving and high-yield irrigation mode for cotton fields under the drip irrigation with plastic-film mulching.

[Objective] GbTMEM214 transgenic Gossypium hirsutum line, obtained using Agrobacterium-mediated method, was used to clarify the sequence characteristics and detection methods of the T-DNA insertion site, and further promote its biosafety evaluation. [Methods] Based on the genome resequencing technology, the sequencing data was compared with the G. hirsutum standard line TM-1 genome sequence by BLASTn, and specific primers were designed to verify the insertion site by polymerase chain reaction (PCR). [Results] The T-DNA carrying the target gene GbTMEM214 was integrated into the position of 57 019 068-57 019 106 bp on chromosome D13 of G. hirsutum genome, resulting in 37 bp deletion of cotton genome. Combined with the flanking sequence of T-DNA insertion site obtained by PCR amplification, the specific detection method for GbTMEM214 transgenic cotton was established. [Conclusion] The T-DNA insertion site and flanking sequence of GbTMEM214 transgenic cotton was obtained based on genome resequencing technology, which can provide technical reference for biosafety evaluation of the transgenic cotton.

[Objective] This study aims to systematically identify the chemical constituents of cotton stalk, laying the basis for in-depth exploitation and utilization of cotton stalk. [Methods] The ultra-high-performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry (UHPLC-Q-Exactive orbitrap MS) was performed with a Thermo Scientific Hypersil GOLD^TM aQ (100 mm × 2.1 mm, 1.9 μm) chromatographic column using gradient elution consist of 0.1% formic acid (A)-acetonitrile (B) as the mobile phase at a flow rate of 0.3 mL·min^-1, while the column temperature was set at 40 ℃, and the injection volume was 2 μL. The MS used electrospray ionization(ESI) source to gain the high-resolution mass data in positive or negative models by full MS scan with data dependence MS²(full MS/dd-MS²) involved in parallel reaction monitoring (PRM). [Results] A total of 102 components from cotton stalk were identified, including 13 flavonoids, 48 organic acids, 8 nucleotides, 10 terpenoids, 8 amino acids, 3 coumarins, 2 alkaloids, and 10 other compounds. Among them, 92 were found in cotton stalk for the first time. [Conclusion] The method based on UHPLC-Q-Exactive orbitrap MS combined with PRM was established, which is easy to operation, with high sensitivity, good specificity and rapid analysis. By this method, 102 compounds were identified in cotton stalks, and 92 compounds were identified for the first time, laying the foundation for the further development and utilization of cotton stalk. It provides reference for the in-depth exploitation and utilization of cotton stalk.

[Objective] This study aimed to clarify the effect of N-life Ⅱ (the main active ingredient is nitrapyrin) on soil nutrient contents and soil nitrogen (N) cycle-related enzyme activities under different application levels of N, so as to provide a basis for the application of N-life Ⅱ in cotton production. [Methods] Field experiments were carried out at Sanya, Hainan province in 2021 and 2022 with Zheda 12 as the experimental material. The field experiment was designed with two factors split-pot. The main plot was N-life Ⅱ application level: 22.5 kg and 0 kg (control) per hectare, respectively; the secondary plot was pure N application level: 285.0 kg (conventional level), 256.5 kg (10% N reduction), 228.0 kg (20% N reduction), and 199.5 kg (30% N reduction, 2022 only) per hectare, respectively. N, phosphorus and potassium contents as well as urease, ammonia monooxygenase (AMO), hydroxylamine oxidoreductase (HAO), nitrite oxidoreductase (NXR), nitrate reductase (NR), and nitrite reductase (NiR) activities in soil were analyzed at the seedling stage, flowering and boll setting stage, and boll opening stage of cotton under different treatments. [Results] Compared with the respective control treatments at the same N application level, soil ammoniacal N content increased at the flowering and boll setting stage and boll opening stage under the N-life Ⅱ treatment; soil nitrate N content decreased at the seedling stage and flowering and boll setting stage, and increased at the boll opening stage; and there were no significant differences in the contents of soil total N, P₂O₅ and K₂O at the seedling stage, flowering and boll setting stage, and boll opening stage. Compared with the mean values of all control treatments, the average soil total N content under N-life Ⅱ treatments was significantly increased by 6.10% to 6.63% at the boll opening stage; the average soil P₂O₅ and K₂O contents under N-life Ⅱ treatments were significantly reduced during the flowering and boll setting stage and boll opening stage. Application of N-life Ⅱ reduced the activities of soil urease, AMO, NR, and NiR at the seedling stage and flowering and boll setting stage; reduced soil NXR activity at the seedling stage; enhanced soil urease activity at the boll opening stage; and enhanced soil NiR activity at the boll opening stage under the normal N application level; while had no significant effect on soil HAO activity at different growth stages. [Conclusion] Under different application levels of N, N-life Ⅱ reduced soil nitrate N content at the seedling stage and flowering and boll setting stage, and increased soil ammoniacal N content at the flowering and boll setting stage and boll opening stage by inhibiting the activities of urease, AMO, NXR, NR, and NiR in soil.

[Objective] This paper aims to solve the problem of accurate recognition and localization of cotton with different postures and grades by cotton picker under the requirement of high-quality cotton picking. A cotton detection method YOLOX-Cotton based on the improved YOLOX is proposed. [Methods] YOLOX-Cotton uses YOLOX as the main framework, including a recognition module and a localization module, and incorporates coordinate attention (CA) module and SIoU loss function, and takes various posture and grade cotton pictures as data sets to train and test. [Results] The detection module of YOLOX-Cotton was capable of detecting cotton with different postures and grades, and the model precision, recall and average precision reached 92.9%, 86.8% and 92.4%, which were improved by 5.2, 5.5 and 6.1 percentage points, compared with the original YOLOX, respectively. The localization module of this model was capable of accurately obtaining the location of the cotton, the measurements were kept within the threshold range of the validated results of the field trial, and the standard deviation of all samples was less than 0.01. [Conclusion] The experiment proves that the YOLOX-Cotton can effectively solve the problem of cotton detection and localization by cotton picker under the requirement of high-quality cotton picking, and provides strong technical support for the realization of high-quality cotton picking.

[Objective] This study aims to explore the impact of diverse mulching techniques and irrigation quota on each application on cotton production. [Methods] Field experiments were conducted in Aral City, Xinjiang from 2017 to 2019. For the experiments under drip irrigation with plastic-film mulching in 2017 and 2018, Xinluzhong 46 was used as the test material, and three irrigation quotas on each application of 24 mm (M1), 30 mm (M2), and 36 mm (M3) were set. For the experiments under drip irrigation without plastic-film mulching in 2018 and 2019, Zhongmian 619 was used as the test material, and three irrigation quotas on each application of 36 mm (W1), 45 mm (W2), and 54 mm (W3) were set. The effects of different treatments on the soil temperature and water content in 10 cm, 20 cm and 40 cm soil layers, seed cotton yield, and irrigation water use efficiency were analyzed. [Results] The soil water content in 10 cm, 20 cm, and 40 cm soil layers of cotton fields, and seed cotton yield under the two mulching modes showed an increasing trend with the increase of irrigation quota on each application. Notably, the seed cotton yield of M2 and M3 treatments were significantly increased by 8.82%-11.47% and 14.24%-18.96% compared with M1 treatment, respectively. The seed cotton yield of W2 and W3 treatments were increased significantly by 15.18%-22.61% and 32.53%-46.29%, respectively, in comparison to W1 treatment. Both soil temperature and irrigation water use efficiency showed a declining trend with the increasing of irrigation quota on each application. The irrigation water use efficiency of M2 and M3 treatments were significantly declined by 10.82%-12.94% and 20.70%-23.84%, respectively, in comparison to M1 treatment. The irrigation water utilization efficiency of W2 and W3 treatments also showed a reduction, ranging from 1.91%-7.85% and 2.47%-11.65%, respectively, in comparison to W1 treatment. When the irrigation quota on each application were the same in 2018, the soil water content, soil temperature in 0-40 cm soil layer, seed cotton yield, and irrigation water use efficiency of M3 treatment were higher than that of W1 treatment. The comprehensive evaluation based on the technique for order preference by similarity to ideal solution (TOPSIS) indicated that superior outcomes could be obtained by aligning 30 mm irrigation quota on each application with the drip irrigation with plastic-film mulching treatment, and 54 mm irrigation quota on each application with the drip irrigation without plastic-film mulching treatment. [Conclusion] An increase in irrigation quota on each application can serve to offset the reduction in seed cotton yield resulting from the filmless planting mode to a certain extent, albeit at the cost of reduced irrigation water use efficiency. The findings of this study may provide reference for the promotion of drip irrigation without plastic-film mulching cotton planting technology in the local area.

[Objective] Low temperature is one of the main agrometeorological disasters during the cotton seedling period in Aksu Prefecture of Xinjiang, which seriously limits the stability and safety of cotton production. Clarifying the risk areas of cotton low temperature disaster during cotton seedling period in Aksu Prefecture can effectively improve the defense ability of this region to cope with low temperature. [Methods] Based on the meteorological data of Aksu Prefecture from 1961 to 2020, the changing trends of daily maximum temperature, daily minimum temperature, daily average temperature, and the changing frequency of low temperature disasters (cold wave and late frost injury) during the seedling period of cotton were analyzed by using the climatic tendency rate. The time distribution characteristics of cold wave and late frost injury in April to May were also analyzed. A comprehensive risk assessment model for low temperature disaster was established, and the risk regionalization of low temperature disaster during cotton seedling stage was carried out by analyzing the hazard index of low temperature disaster-inducing factors, and combining the exposure index of the hazard-bearing body, and local the disaster prevention and mitigation capacity. [Results] From 1961 to 2020, the daily minimum temperature, daily maximum temperature, and daily average temperature during the cotton seedling period in Aksu Prefecture showed a significant increasing trend, and the frequency of cold wave and late frost injury showed a decreasing trend. The incidence of cold wave and late frost injury in Aksu Prefecture is below 20% after 10 April and 12 April, respectively. The risk level of spring low temperature disaster-causing factors in Aksu Prefecture showed the spatial distribution characteristics of “high in the north and low in the south, high in the west and low in the east”. The results of comprehensive risk regionalization indicated that the central and east-central areas of Aksu Prefecture, which including Aral City, the central part of Aksu City, the north-eastern part of Awati County, the eastern edge of Kalpin County, the eastern part of Xinhe County, the south-western and central part of Kuqa City, the northern part of Xayar County, and the south-eastern part of Wensu County are the highest or higher level risk zones of low temperature disaster. [Conclusion] Although the spring temperature increased, and the frequency of cold wave and late frost injury decreased in Aksu Prefecture, the risk of low temperature disaster is still high in the central and east-central cotton growing areas in Aksu Prefecture, and targeted measures are needed to be taken to mitigate the impact of low temperature disasters on cotton production.

[Objective] This research aims to measure the digital development level of cotton field in Xinjiang, analyze the obstacle factors and the main issues of the digital transformation, and propose corresponding countermeasures, so as to provide reference for promoting the modernization development of cotton industry in Xinjiang. [Methods] The evaluation index system was constructed from four dimensions: digital foundation, digital support, digital application, and digital efficiency. Analytic hierarchy process-entropy combination assigning method and the obstacle factor analysis method were used to analyze the digital development level and main obstacles of cotton field in Xinjiang from 2012 to 2021. [Results] The digital development level of cotton field in Xinjiang is increasing year by year. The composite score was raised from 1.68 in 2012 to 28.42 in 2021. The main obstacles to the digital development of Xinjiang cotton field have changed from the digital foundation, digital support, and digital applications in 2012 to digital applications and digital efficiency in 2021. Xinjiang cotton field has shortcomings in digital technology application, capital investment, large-scale development, technical personnel and so on. [Conclusion] The digital development of cotton field in Xinjiang has achieved some results, but there are still some problems. By strengthening the research and promotion of digital technology, promoting the scale and organization of cotton field, increasing policy support, and cultivating composite technical talents, it is expected to promote the digital transformation and upgrading of cotton field in Xinjiang.

[Objective] This study aims to explore the prediction effects of different models on cotton plant height under high dense planting conditions in the Aral Reclamation Area, Xinjiang. [Methods] Xinluzhong 81 and Tahe 2, which are different in plant type, were used as experimental materials for field experiment under the high dense planting condition of 16 000·hm^-2 in Aral Reclamation Area. Prediction models for plant height growth were established using logistic, Gompertz, Richards growth equations, and decision tree machine learning methods using Python language. In addition, the prediction accuracy of the models was analyzed. [Results] For the logistic, Gompertz, and Richards models, the root mean square error (RMSE) of Xinluzhong 81 was 8.38%, 7.49%, and 7.52%, respectively, and the mean absolute error(MAE) was 6.80%, 5.79%, and 5.82%, respectively; the RMSE of Tahe 2 was 6.09%, 4.77%, and 4.85%, while the MAE was 4.52%, 3.34%, and 3.36%, respectively. The RMSE of Xinluzhong 81 and Tahe 2 by using decision tree machine learning method were 6.91% and 3.27%, respectively, and the MAE were 5.04% and 2.16%, respectively. The results indicated that logistic, Gompertz, and Richards growth equations and decision tree machine learning methods can effectively reflect the growth of cotton plant height under high dense planting condition. However, in terms of prediction accuracy, decision tree machine learning methods was generally superior to the three growth equations. [Conclusion] The machine learning method based on decision tree does not require mathematical and statistical knowledge to explain the model, training the model requires less data, and can achieve higher simulation accuracy. It has certain advantages in simulating cotton plant height, and is a beneficial supplement to the traditional growth equations.