Cotton is an important economic crop in the world, occupying a significant position in the national economy. Cottonseed, as the main product of cotton production, is rich in high-quality protein and oil. Against the backdrop of the current shortage of protein and oil resources, fully exploring and utilizing the protein and oil resources in cottonseed can ensure the safety of edible oil supply and alleviate food security issues. With the increasing attention paid to the comprehensive utilization of cottonseed, the research on the genetic improvement of cottonseed nutritional quality is gradually increasing. This review provides an overview of the common methods for determining cottonseed protein and oil content, and summarizes the genetic characteristics and influencing factors of these traits. The relationships among cottonseed protein and oil content and fiber yield as well as the fiber quality traits were analyzed. A total of 335 quantitative trait locus (QTL) for oil content and 196 QTL for protein content were collected to construct a consistent physical map. In addition, the research progress of cottonseed protein and oil related synthetic pathways and regulatory genes were introduced, and the future research directions of biological breeding for cottonseed nutritional quality was prospected, which can provide a reference for the genetic improvement of nutritional quality in cottonseed.

[Objective] This study aims to monitor the chlorophyll content of cotton leaves by utilizing unmanned aerial vehicle (UAV)-based multispectral technology. [Methods] This study utilized multispectral images of cotton canopies obtained by UAV in southern Xinjiang and employed seven different machine learning methods to estimate the canopy chlorophyll content during the flowering and boll-setting stage which is the critical growth period of cotton. The seven methods include linear regression (LR)-based methods, i.e., simple linear regression, partial least squares regression (PLSR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO) regression, support vector regression (SVR), K-nearest neighbors regression (KNNR), and random forest regression (RFR). [Results] The results showed that compared with the LR method, the RFR, SVR and KNNR can improve the accuracy of prediction model of chlorophyll content in cotton canopies, especially the RFR algorithm, which had the coefficient of determination of 0.742, root mean square error of 1.158 mg·L^-1, residual predictive deviation of 1.969 with the validation dataset. [Conclusion] The use of UAV-based multispectral images with the RFR machine learning method, exhibits the most outstanding performance to estimate the chlorophyll content of cotton leaves and provide essential technical support for precision management in cotton field.

Cotton straw is a by-product of cotton production and an important renewable biomass resource, and the study on its comprehensive utilization is of great significance to optimize energy structure and achieve 'dual carbon' goals. Due to the structural differences, the successful application methods of corn, wheat, and rice straw cannot be directly applied to cotton straw. Traditional treatment and application of cotton straw cause resource waste and environmental pollution. Therefore, it is essential to enhance the comprehensive utilization of cotton straw to improve agricultural waste utilization efficiency, optimize energy structure, and reduce environmental pollution. From the perspective of enhancing the comprehensive utilization efficiency of cotton straw, this article summarizes various utilization modes, including straw returning to the field, using them as feed, energy substrate, and raw material, and prospects the future multiuse of cotton straw which will provide methodological reference and research ideas for the diversified utilization of cotton straw.

[Objective] This research aims to study the effects of delayed sowing on cotton root growth and development characteristics and yield, so as to provide a basis for the timely sowing of cotton in the cotton planting area of the Yellow River Basin. [Methods] A field experiment was carried out at Weixian Experimental Station of Hebei Agricultural University from 2022 to 2023. Two treatments were set as conventional sowing date (15 April) and delayed sowing date (1 May). And the effects of delayed sowing on the root distribution, root growth rate, root-shoot ratio, dry matter accumulation, and yield of a cotton variety Jinongda 23 were analyzed. [Results] Compared with the conventional sowing date, under the delayed sowing condition, the maximum growth rate of cotton root length and root biomass increased by 2.92-5.35 cm·d^-1 and 0.40-0.76 mg·d^-1, respectively. The proportion of cotton roots in deep soil increased, with root length and biomass in the 30-60 cm soil layer increased by 2.99-3.55 percentage points and 3.94-4.42 percentage points, respectively. There was no obvious difference in aboveground biomass and root-shoot ratio in the late growth stage of cotton. The boll capacity of root system significantly decreased by 6.43%-17.69%. There was no significant difference in seed cotton yield in 2022. In 2023, the number of bolls per unit area and seed cotton yield increased significantly by 9.72% and 7.66%, respectively. Correlation analysis showed that root length density in 0-60 cm soil layer, root biomass density in 0-60 cm soil layer, maximum growth rate of root length, and the proportion of root length in 30-60 cm soil layer are extremely significantly correlated with seed cotton yield. [Conclusion] Delaying the sowing date (1 May) in cotton planting area of the Yellow River Basin can enhance the absorption function of cotton roots by increasing the growth rate of roots, the proportion of root length and biomass in deep soil layers, so as to ensure the accumulation of aboveground dry matter and promote the high yield of cotton.

[Objective] Heat damage is the most important meteorological disaster during the flowering and boll setting stage of cotton, which severely limits the safe production of cotton in Xinjiang. The evolution characteristics of heat damage in this area are clarified, which provides a reference for the scientific formulation of disaster prevention and mitigation measures. [Methods] This research used the daily maximum air temperature of 55 national basic meteorological stations in Xinjiang cotton planting areas from 1961 to 2022, and the observation data during the flowering stage and boll opening stage of 24 cotton meteorological observation stations from 1991 to 2022. Combined with the monitoring indices of high temperature and heat damage during flowering and boll setting stage of cotton, this research revealed the temporal and spatial variation of high temperature and heat damage with different grades during cotton flowering and boll setting stage by climate tendency rate and Mann-Kendall mutation test. [Results] The results showed that the maximum air temperature, extreme high temperature（daily maximum temperature ≥38.0 ℃） and cumulative days of the extreme high temperature during the flowering and boll setting stage of cotton in Xinjiang showed a significant upward trend from 1961 to 2022, with trend rates of 0.16 ℃·(10 a)^-1, 0.07 ℃·(10 a)^-1 and 0.45 d·(10 a)^-1, respectively. The frequency and intensity of high temperature and heat damage during the flowering and boll setting stage of cotton in Xinjiang have increased. From 1961 to 2022, the years of high temperature and heat damage during flowering and boll setting stage with different intensities in the cotton planting area of eastern Xinjiang subregion accounted for more than 96.0%, and the mild and moderate heat damage in the cotton planting area of southern Xinjiang subregion accounted for 88.7% and 51.6%, respectively. And the frequency of mild heat damage during the flowering and boll setting stage of cotton in the northern Xinjiang subregion was 64.5%. [Conclusion] The frequency and intensity of heat damage during flowering and boll setting stage in Xinjiang cotton planting area showed the regional characteristics of "strong in the east and weak in the west, more in the south and less in the north". Therefore, more attention should be paid in Xinjiang cotton planting areas to the breeding and application of high temperature resistant varieties, rationally adjustment of the cotton planting layout, strengthening the monitoring and early warning of meteorological disasters, and ensuring the safe and stable development of cotton production.

[Objective] The effect of nitrogen application on cotton yield and its constituent factors is clarified, aiming to provide theoretical reference for the precise application of nitrogen fertilizer and high cotton yield. [Methods] The comprehensive effects and influencing mechanisms of different nitrogen application rates, nitrogen application schemes, and climatic conditions on cotton yield are studied by meta-analysis and path analysis in Xinjiang. [Results] Compared with no nitrogen application, nitrogen application could significantly increase cotton yield with 43.38%. Nitrogen application of 360-480 kg·hm^-2 had the greatest effect on cotton yield. Nitrogen application exceeding this range no longer increased cotton yield significantly, and the recommended economic nitrogen application rate in this study was 360-420 kg·hm^-2. The nitrogen application scheme of 20% of basic fertilizer, 80% of supplementary fertilizer and 6 times of drip application with water at the rate of 6%, 8%, 22%, 25%, 12%, and 7% had the greatest effect on cotton yield. The greatest yield increase was achieved by the nitrogen fertilization program. The most obvious effect of nitrogen application was found in cotton fields with annual evaporation >2 000 mm, annual precipitation <60 mm, annual sunshine time <2 864 h, annual effective cumulative temperature >4 000 ℃, and frost-free period >200 d, and in fields with sandy soil, initial soil organic carbon content <5.8 g·kg^-1, and initial soil available nitrogen content ≤60 mg·kg^-1. The results of the pathway analysis showed that nitrogen application contributed most significantly to the enhancement of cotton yield by increasing the soil nitrate nitrogen content, thereby increasing the cotton leaf area index. [Conclusion] It is suggested that nitrogen application rate of 360 - 420 kg·hm^-2 with the above optimization scheme should be used in Xinjiang cotton area to achieve high cotton yield and reduce environmental risk in drip irrigation cotton fields under film.

[Objective] Spodoptera litura significantly impacts cotton cultivation, while Rehmannia glutinosa is a prevalent agricultural weed. The exploration and application of R. glutinosa for controlling the S. litura hold crucial relevance for the sustainable production of cotton. [Methods] The effects of root or leaf dry powder of R. glutinosa on the mortality, developmental duration, and body weight of S. litura larvae were preliminarily determined by mixing the dry powder and feed with the mass ratios of 1∶3, 1∶6, 1∶9, and 1∶18, respectively. Additionally, the influence of 95% ethanol extracts of root or leaf powder of R. glutinosa (the ratios of dry powder to solvent were 1∶50, 1∶30, and 1∶10) on the mortality of 1st to 6th instar S. litura larvae were studied by film-coating technique. [Results] The incorporation of R. glutinosa root or leaf dry powder into the larvae's diet notably affected their growth and development. An increase of the root or leaf dry power content in the diet led to higher larval mortality, extended developmental periods, and decreased body weight. The most significant inhibitory effect occurred when the mass ratio of root or leaf dry powder to feed was 1∶3. The ethanol extracts of R. glutinosa root or leaf exhibited a certain inhibitory effect on the younger larvae, while with diminished efficacy on older larvae. As the concentration of R. glutinosa extract increased, the mortality of younger larvae increased at the same testing period. Optimal toxicological effects on 1st to 6th instar larvae were observed when the root or leaf dry power of R. glutinosa to solvent ratio was 1∶10. [Conclusion] R. glutinosa shows a definitive inhibitory effect on S. litura. In a certain range, the greater dosage of R. glutinosa root or leaf dry powder has the stronger inhibitory effect. This finding lays a theoretical groundwork for the strategic utilization of agricultural weed resources in developing plant-derived insecticides.

Cotton is the most important natural fiber crop in the world, as well as also an important cash crop and raw material for textile industry in China. The change of fruit branch angle directly or indirectly affects the canopy structure, light energy distribution, boll formation structure and mechanical characteristics. In order to provide reference for the improvement of cotton plant architecture breeding and further promote cotton breeding, this paper reviews the current research status of cotton fruit branch angle from the perspective of cultivation and molecular, summarizes the previous research results and probes into the research trend of cotton fruit branch angle.

[Objective] This research aims to investigate the sequence structural differences between the mitochondrial genomes of Gossypium harknessii sterile cytoplasm (CMS-D2) and G. trilobum sterile cytoplasm (CMS-D8), which can establish a foundation for the screening and identification of sterility-related genes. [Methods] Based on the sequencing and assembled results of the mitochondrial genome of D2A and D8A, the Synteny and Rearrangement Identifier (SyRI) software was used to identify structural variations, and recombination variation sites containing collinear and non-collinear regions were visualized with Plotsr. The annotation results of the D8A mitochondrial genome were utilized as a reference, and the amino acid sequences encoded by the open reading frame (ORF) annotated in the D2A mitochondrial genome were used for tblastn comparison to screen out the unique ORF in the D2A mitochondrial genome. Subsequently, polymerase chain reaction (PCR) verification, relative expression level analysis, and bioinformatics analysis were performed. [Results] The mitochondrial genomes of the sterile lines D2A and D8A had two partially overlapped and adjacent inverted translocation regions. Seventeen specific ORF were found in D2A mitochondrial genome, and PCR verified the presence of 6 specific ORF (orf114e, orf121b-1, orf121b-2, orf138b-2, orf186a-2, and orf317a-2) in D2A. The relative expression levels of orf121b-1 and orf121b-2 were higher in 3-4 mm flower buds. orf114e, orf186a-2, and orf317a-2 have typical transmembrane domains and chimeric gene structures, which are consistent with some characteristics of sterility genes. [Conclusion] Two adjacent inverted translocation regions were identified between the mitochondrial genomes of D2A and D8A. There are six specific ORF in D2A, among which orf114e, orf186a-2, and orf317a-2 may be potentially related to sporophytic abortion of CMS-D2.

[Objective] This study aims to provide a theoretical basis for molecular breeding of disease-resistant cotton by cloning Gh_D11G050000 gene, and to analyze its function and mechanisms in cotton resistance to Verticillium wilt. [Methods] Bioinformatic method was utilized to analyze the sequence characteristics and phylogenetic relationship of Gh_D11G050000. Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to investigate the expression pattern of this gene, and it's expression level changes after infected by Verticillium dahliae. The function of this gene was validated using virus-induced gene silencing (VIGS) technique. Transcriptome sequencing analysis and the detection of relative expression levels of related genes were conducted to explore the mechanisms of disease resistance. [Results] Gh_D11G050000 exhibited close relationship with Gh_A11G049600 and Gr_11G034620 protein. qRT-PCR analysis revealed that Gh_D11G050000 was highly expressed in cotton roots, and the expression level of Gh_D11G05000 was significantly increased after V. dahliae infection. Gh_D11G050000 silenced cotton plants showed reduced resistance against V. dahliae, characterized by aggravated browning of stem vascular bundles, increased the number of stem segments with bacterial propagation, as well as significantly increased the rate of diseased plants and disease index. Transcriptome analysis combined with qRT-PCR demonstrated that Gh_D11G050000 silenced cotton plants showed decreased transcription levels for several genes in jasmonic acid (JA) signaling pathway, ethylene (ET) signaling pathway, and lignin synthesis pathway. [Conclusion] Gh_D11G050000 positively regulates cotton resistance to Verticillium wilt by influencing the expression of several genes involved in lignin synthesis, JA, and ET signaling pathways.

[Objective] This research aims to investigate the impact of different nitrogen (N) fertilizer rates on cotton under the machine picked with(66 + 10) cm row spacing, so as to provide scientific basis for improving the high-yield cultivation technology of cotton. [Methods] N top-dressing experiments was carried out in Korla of Xinjiang during 2021 and 2022. A field experiment was conducted using Ba 43541 as the test material, and four pure N application levels were set: 0, 112.5, 225.0, and 337.5 kg·hm^-2. Canopy structure characteristics, yield traits, and N use efficiency of cotton in middle position of the wide line (MW), middle position of the narrow line (MN), adjacent to plant (AP) and intermediate position of the adjacent two membranes (MC) were compared under different treatments. [Results] Under different treatments, with the advancement of growth process, leaf area index (LAI) of cotton at the four test sites increased first and then decreased, while photosynthetically active radiation (PAR) decreased first and then increased, but mean leaf angle (MLA) and gap fraction transmission coefficient (GFTC) showed different change trends. During the full budding stage, the LAI was lower, while MLA, PAR, and GFTC were higher in MC. The differences of LAI, PAR, and GFTC among the four test sites gradually decreased from the flowering and boll setting stage to the boll opening stage. During the full boll setting stage and boll opening stage, MLA were higher in MN and AP. Applying N 112.5 kg·hm^-2(N1) obtained appropriate LAI, MLA, PAR, and GFTC during the full boll setting stage, the boll number of per unit area increased. In 2021 and 2022, compared with the other three treatments, seed cotton yield of N1 increased by 1.38%-16.50% and 1.66%-11.57%, and lint yield increased by 1.57%-16.37% and 0.59%-12.40%, respectively; partial productivity and agronomic utilization of N were also increased. In terms of cotton LAI and PAR, there were extremely significant positive correlation among the four test sites. Overall, the best positive correlation of cotton canopy structure index was found among AP and MW, AP and MN. [Conclusion] Under the same N application rate, the change trends of LAI and PAR at four test sites were consistent, while the change trends of MLA and GFTC were inconsistent. The application of 112.5 kg·hm^-2 N could promote the high yield of Ba 43541, and improve the N use efficiency of cotton.

[Objective] This study aims to investigate the regulatory effect of "fertigation adjusted water management" on the physiology and the growth of drip-irrigated cotton in alleviating drought stress, and to enhance cotton yield under limited water resource. [Methods] Using Zhongmian 619 as the test material, two types of irrigation quotas for deficient irrigation (W1: 45 mm) and full irrigation (W2: 54 mm) in combination of three nitrogen input doses, including low nitrogen (F1: 150 kg·hm^-2), medium nitrogen (F2: 225 kg·hm^-2), and high nitrogen (F3: 300 kg·hm^-2) were set. The effects of different irrigation quotas and nitrogen doses on cotton physiological growth indicators and seed cotton yield were analyzed. [Results] The results indicated that increased irrigation quotas promoted cotton growth, enhanced two-year average leaf area index (LAI), relative chlorophyll content (soil and plant analyzer development, SPAD value), and net photosynthetic rate (P_n), while redued the activities of cotton superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and malondialdehyde (MDA) content. With the increase of nitrogen application, LAI, SPAD, P_n, and antioxidant enzyme activity were increased, MDA content was decreased on average, and the influence of water deficiency on cotton development was alleviated. Under W1 treatment, increased nitrogen application improved cotton yield, while under W2 treatment, cotton yield showed the trend of increasing first and then decreasing with the increase of nitrogen application. Under water-nitrogen interaction, the highest two-year average seed cotton yield (6 821.86 kg·hm^-2) was recorded under W2F2 treatment followed by W1F3 treatment (6 717.72 kg·hm^-2). In the technique for order preference by similarity to ideal solution(TOPSIS) analysis, the comprehensive scores of W1F3 and W2F2 were 0.57 and 0.56, respectively, and the differences between the two-year yield of W1F3 and W2F2 treatments were not significant. [Conclusion] Increased nitrogen application under deficit irrigation effectively alleviates the adverse effects of drought on the physiological characteristics and yield in cotton. It is recommended to use 45 mm irrigation quota combined with 300 kg·hm^-2 nitrogen application as the fertigation strategy for the filmless drip-irrigated cotton in southern Xinjiang, to effectively ensure cotton yield under limited water resource.

[Objective] This research aims to investigate the effects of planting density and varieties on the morphological structure of vegetative organs and yield of machine-picked cotton in northern Xinjiang. [Methods] Field trials were conducted in 2022 and 2023 at Wulanwusu Agricultural and Meteorological Experiment Station and Manas Agricultural Experiment Station, respectively. Two varieties, CCRI 127 (V1) and Xinshi 518 (V2), were selected, and three planting densities were designed as 11 plants·m^-2 (D1), 22 plants·m^-2 (D2), and 28 plants·m^-2 (D3), respectively. The effects of different treatments on leaf length, petiole length, petiole diameter, internode length, and internode diameter of cotton main stems and fruiting branches as well as yield traits were compared. [Results] In 2022 and 2023, V1 showed the smallest leaf length, petiole length, and internode length of main stems and fruiting branches under D1 and D2 treatments, respectively. In 2022, V2 showed the smallest leaf length, petiole length, petiole diameter, and internode length of main stems and fruiting branches under D3 treatment. In 2023, V2 showed the smallest petiole length and internode diameter of main stems and fruiting branches under D3 treatment. Leaf length and internode length of main stems and fruiting branches showed V1 ≥ V2 under the same density in 2022. Leaf length, internode length, and internode diameter of main stems and fruiting branches of V1 and V2 were not significantly different under the same density in 2023. The lint percentage of V2 was significantly higher than that of V1 under the same density both in 2022 and 2023. Seed cotton yield and lint yield of V1 and V2 in 2022 as well as that of V2 in 2023 increased with the increase of planting densities. Seed cotton yield of V1D3 treatment was highest in 2022, and relatively higher in 2023. V2D3 treatment had the highest lint yield in 2022 and 2023. [Conclusion] The preferred planting density under the conditions of this experiment was 28 plants·m^-2, and the lint yield of Xinshi 518 was higher. The results of this study can provide a support for the improvement of the CottonXL model, and provide a reference for the selection of appropriate varieties and planting densities of machine-picked cotton in the northern Xinjiang.

[Objective] To improve the yield of summer direct seeding cotton in the Yangtze River basin, this study focuses on the effects of nitrogen (N) and potassium (K) application frequency on cotton. [Methods] Field experiment was conducted in 2021 and 2022 under a randomized complete block design in a split-plot arrangement, where K fertilizer (210 kg·hm^-2) application frequency K1 [pre-plant fertilizer (PP) 100%] and K2 [PP 50% + first flowering fertilizer (FF) 0 d 50%] were kept in the main plot, and the sub-plots were allocated with N fertilizer (210 kg·hm^-2) application frequency: N2 [PP 20% + FF 0 d 80%], N3 [PP 20% + FF 0 d 60% + FF 21 d 20%], and N4[PP 10% + FF 0 d 50% + FF 7 d 30% + FF 21 d 10%]. The effects of different treatments on cotton dry matter accumulation and allocation, N and K accumulation and allocation, yield and yield components, and nutrient utilization efficiency were studied. [Results] The dry matter mass and the accumulation of N and K at plant removal stage, and the duration and average accumulation rate of the rapid accumulation period of dry matter in cotton plant, source, flow, and sink organs under K2N3 treatment were lower than those of K2N4 treatment, but the distribution ratio of dry matter, N, and K in the sink organs were higher than those of K2N4 treatment. K2N3 resulted in higher seed cotton yield and lint cotton yield, which were 31.4% and 31.9% significantly higher than the lowest yield treatment K1N2, respectively. However, further increase of N application times (K2N4 treatment) did not result in significantly higher cotton yield. There is no significant difference in the partial productivity of N and K between K2N3 and K2N4 treatments, but both are significantly higher than the other treatments. Principal component analysis showed that the main difference in cotton yield comes from the number of bolls, and promoting the allocation of biomass, N and K nutrients to sink organs is beneficial for improving yield. [Conclusion] For the direct seeding cotton after wheat in the Yangtze River basin, two times of K application combined with three times of N application can increase the absorption of N and K, promote dry matter as well as N and P distribution to sink organs, thus increase the number of bolls, and improve cotton yield.

[Objective] Cotton is a relatively tolerant crop to cadmium (Cd) stress. It is of great significance to breeding and extending the Cd tolerant cotton cultivars for remediation of Cd contaminated soil. This study aims to analysis the inheritance of cotton tolerance to Cd stress and to map the quantitative trait locus (QTL) related to Cd stress. [Methods] In this study, 188 recombinant inbred lines (RIL) called HM188 derived from an intraspecific hybrid between HS46 and MARCABUCAG8US-1-88 were used to study the phenotypic data of germination rate, germination potential, chlorophyll content, plant height, dry and fresh weight at seedling stage under Cd stress, and the Cd stress coefficient of each material was calculated as well. QTL mapping was conducted for each trait and Cd stress coefficient of HM188 population by using complete interval mapping method. [Results] According to the performance and Cd stress coefficient of each trait under Cd stress, MARCABUCAG8US-1-88 was the Cd tolerant parent, while HS46 was a sensitive one. The Cd tolerance of 188 RIL was basically normal distribution, including 23 strong Cd tolerant lines, 49 Cd tolerant line, 67 medium tolerant lines, and 49 sensitive lines. A total of 28 QTL for Cd stress coefficient was identified, which were distributed on 14 chromosomes with explaining of variation of 1.58%~8.41%. Among them, qRFW-13-1 related to root fresh weight was detected in both environments, which explained variation of 7.66% and 7.71%, respectively. [Conclusion] Cd tolerance in upland cotton is a quantitative trait controlled by multiple genes, which was greatly affected by the environment. However, qRFW-13-1 for Cd tolerance may be a stable QTL, which has some application values in molecular breeding for Cd tolerant cotton.

[Objective] This study aims to understand the changes in the agglomeration level of cotton production in China and its influencing factors. These findings hold practical significance for optimizing the layout of the cotton industry, promoting high-quality development of the cotton industry, and enhancing regional economic development. [Methods] Using the location quotient index to measure the agglomeration level of cotton production in China from 2001 to 2022, comparing the agglomeration growth and competitive status changes of cotton production in major producing provinces using the competitive state model, and finally empirically analyzing the factors affecting agglomeration changes. [Results] From 2001 to 2022, the cotton production aggregation level in inland regions of Northwest China has been consistently higher than that in the Yangtze River basin and the Yellow River basin, and has continued to rise. The production aggregation level and competitiveness of cotton in Xinjiang have been continuously strengthened. However, the production aggregation level and comprehensive competitiveness of cotton in other major cotton-producing provinces have notably declined. Factors affecting the changes in cotton production aggregation in China include conflicts between grain and cotton for land, water resources, the quantity of agricultural labor, agricultural technology levels, transportation costs, the synthetic fiber industry, and cotton target price policy. [Conclusion] For the sustainable development of the cotton industry, it is recommended to scientifically promote the allocation of resources for cotton production, implement the cotton industrial policies in accordance with local conditions, improve the technical level of cotton production, improve the cotton production infrastructure, promote the development of related industries and improve target price subsidy policies.

[Objective] The aim of this study was to investigate the niche mechanism of weeds in drip-irrigated and machine-harvested cotton fields in North Xinjiang, China. [Methods] A seven-stage visual survey was conducted to investigate the degree of dominance about weeds in 25 cotton fields under drip-irrigated and machine-harvested in 5 regions (143rd corps, 145th corps, and 147th corps of the 8th Division of The Xinjiang Production and Construction Corps, Changji city, Kuytun city) of North Xinjiang. According to the degree of dominance, the important value, the niche breadth, and niche overlap values of 20 main weeds were calculated. The ecological similarity were revealed by detrended correspondence analysis (DCA) sorting. And minimum spanning tree of graph theory cluster analysis were drawn on the basis of the niche overlap value. [Results] The results show that Convolvulus arvensis, Chenopodium album, Amaranthus retroflexus, Solanum nigrum, Phragmites australis, Setaria viridis (L.) Beauv., Abutilon theophrasti Medicus, Hibiscus trionum, and Echinochloa crusgalli with wide niche breadth are the dominant species (malignant weeds) in drip-irrigated and machine-harvested cotton fields in North Xinjiang. The niche overlap values of S. nigrum and C. album, A. theophrasti and A. retroflexus, H. trionum and E. crusgalli, A. retroflexus and E. crusgalli are higher, implying that these weeds may fiercely compete for resources. Based on the relationship between niche overlap values, minimum spanning tree were produced to reflect the similar ecological needs of related weeds. The 20 kinds of main weeds were divided into 4 groups in the minimum spanning tree. In the 25 sites, the integrated ecological demands of 20 kinds of main weeds were sorted by DCA. The results showed that the 9 kinds of malignant weeds clustered in the center of DCA, which are obviously different from those general weeds around DCA. DCA results corresponded well to the minimum spanning tree. [Conclusion] With the increase of years of drip irrigation, there was a extremely significant or significant regression relationship between the dominance values of above mentioned 9 kinds of malignant weeds and years of drip irrigation. There were significant nonlinear regression relationships between their dominant values of C. arvensis and S. viridis and years of drip irrigation, while there were extremely significant linear regression relationships between the dominant values of other 7 kind of malignant weeds and years of drip irrigation.

[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 research aims to explore the effects of adjuvants during pesticide spraying by plant protection unmanned aerial vehicle (UAV) on droplet deposition characteristics and control efficiency on Aphis gossypii. [Methods] Dajiang T30 UAV was selected to conduct a field spray experiment during the cotton budding stage. The effects of 6 adjuvants (Yaketou, Beidatong, Zhiwusancan, Nongjianfei, Qigong, and Beibeijia) in 39% spirotetramat buprofezin on the size, density, coverage, and deposition amount of droplets and control efficiency on A. gossypii were compared. [Results] Compared with the control without adjuvant, treatments with the adjuvants increased the droplet density, coverage, and deposition amount on the upper, middle, and lower leaves of cotton plant. The droplet size, density, coverage, and deposition amount treated with Beibeijia and Beidatong were all higher; of which the density, coverage, and deposition amount on the upper, middle, and lower leaves of cotton plants were significantly higher than those of the control treatment. The control efficiency on A. gossypii of treatments with adjuvants in the upper, middle, and lower parts of cotton plant was higher than that of the control treatment at 1 d, 3 d, 7 d, and 14 d after application. The control efficiency of the treatment with Beibeijia was the best, followed by the treatment with Beidatong. [Conclusion] The addition of Beibeijia and Beidatong can improve the deposition characteristics of droplets and has a good control effect on A. gossypii. It also has a good synergism on the control of A. gossypii with 39% spirotetramat buprofezin suspension.

[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.