[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.

[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 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] 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] 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.

[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.