[Objective] This study aims to investigate the potential of cotton carbon credits under the CCER (Chinese Certified Emission Reduction) mechanism, quantitatively evaluate the greenhouse gas reduction potential of cotton production that can participate in the CCER mechanism, predict the economic value it can generate, and explore the possibility of additionality certification for cotton carbon credits based on the CCER mechanism. [Methods] First, a counterfactual analysis framework was constructed through scenario division. Based on the existing mature life cycle assessment boundaries of cotton, components meeting the requirements of the CCER mechanism were identified. The development potential, economic value, and future trends of cotton carbon credit in China's three main cotton regions were estimated and predicted. Furthermore, the additionality of cotton carbon credit was demonstrated using the general proof methods required by the CCER mechanism. [Results] The cotton carbon credit in China's three main cotton regions exhibits significant development potential and economic value. Under the best-line scenario, the annual average carbon credit potential and economic value from 2014 to 2023 were 7.932 4 million tons of CO₂ equivalence and 729 million CNY, respectively, with an upward trend. Under the better-line scenario, the respective figures were 2.412 3 million tons of CO₂ equivalence and 222 million CNY. The Northwest Inland Cotton Region is the primary area for cotton carbon credit development, accounting for over 90% and continuing to increase. Promoting and adopting low-carbon agricultural technologies can help cotton carbon credits pass the additionality certification based on the CCER mechanism. The better-line scenario's technological choices provide a more pragmatic approach. [Conclusion] The three main cotton-growing regions in China, especially the Northwest Inland Cotton Region, have great potential for carbon credit development. Considering the practical context of "increased production equating to increased income", efforts should focus on leveraging the scale advantages of the Northwest Inland Cotton Region and exploring collaborative cooperation models between the upstream and downstream ends of the industry chain to promote the practical development of cotton carbon credit.

[Objective] Accurate identification of cotton species is of great significance for breeding, cultivation management, and pest control. However, the traditional manual identification method is subjective and inefficient. Therefore, this study aims to develop a rapid classification model based on red, green, and blue(RGB) image and random forest (RF) algorithm to realize automatic recognition of cotton species. [Methods] In this study, Gossypium herbaceum, G. arboreum, G. barbadense, and G. hirsutum lines were planted to collect the RGB images of cotton leaves at the squaring stage and the flowering and boll-setting stages, then the color and morphological feature parameters were extracted. Based on the extracted features, three RF models were constructed: one using only leaf features at the squaring stage, another using only leaf features at the flowering and boll-setting stages, and a comprehensive model combined features from both stages. The classification performance of each model was evaluated, and the key features affecting cotton species were identified through feature importance analysis. To assess the superiority of the RF model, the classification effect of the support vector machine(SVM) and K nearest neighbor (KNN) algorithm was conducted for comparison. [Results] The classification model combining the leaf features of the squaring stage and the flowering and boll-setting stages had the highest accuracy, with an overall accuracy of 97.71% and a Kappa coefficient of 0.95, which was superior to the model based only on leaf features from a single growth stage. Feature importance analysis showed that leaf area and roundness played an important role in cotton species recognition. Additionally, the RF model demonstrated better classification performance than SVM and KNN, exhibiting higher stability and accuracy. [Conclusion] The cotton species identification method based on RGB images and the RF algorithm proposed in this study does not require complex image pre-processing and can provide new insights and technical support for crop precision management and the application of machine learning algorithms in agriculture.

[Objective] This study aims to explore the effects of applying different amounts of 1,1-dimethyl piperidinium chloride (DPC) through drip irrigation on cotton plant architecture characteristics and yield traits under dry-sowing and wet-emergence planting mode, and to screen the optimal amount of DPC, so as to promote the simplified chemical manipulation of cotton. [Methods] Field experiments were conducted in Shawan City, Xinjiang, from April 2023 to October 2024. The control treatment (CK) was established with foliar application of 315 g·hm^-2 DPC. Four treatments were set up with different drip application rates of DPC: 315 g·hm^-2 (D1), 630 g·hm^-2 (D2), 1 260 g·hm^-2 (D3), and 1 890 g·hm^-2 (D4). The effects of drip-applied DPC on cotton plant height, plant width, stem diameter, and other plant architecture characteristics, as well as leaf area index (LAI), and yield traits were investigated. [Results] In 2023 and 2024, cotton plant height, internode length of main stem, cotyledon node height, plant width, fruiting branch length, number of fruiting branches per plant, height of the first fruiting branch node, and LAI all decreased with the increasing amount of DPC through drip irrigation. There were no significant differences between D2 and CK treatment in plant height, cotyledon node height, plant width, vegetative shoot length, stem diameter, fruiting branch number per plant, first fruiting branch node and its height, plant height-width ratio, fruiting node number-fruiting branch number ratio, and LAI (except for peak boll-setting stage in 2023). There were no significant difference in harvest density and lint percentage among different treatments. Compared with CK treatment, the boll weight of D1-D4 treatment and the boll number per plant of D1 and D2 treatment were no significant difference, and the boll number per plant of D3 and D4 treatment were significantly reduced. The seed cotton yield of D2 treatment showed no significant difference with CK, and it was higher than that of D1 treatment, and significantly increased by 19.7% to 20.0% and 27.1% to 49.6%, respectively compared with D3 and D4 treatments. [Conclusion] The application of 630 g·hm^-2 DPC through drip irrigation under the dry-sowing and wet-emergence planting mode in cotton fields of northern Xinjiang can effectively regulate the plant architecture of cotton, ensuring high cotton yield.

[Objective] With the adjustment of planting structure and the change of planting area of cotton in China, the main diseases and pests are constantly evolving, especially in the case of the sharp fluctuation of cotton planting area in the Yellow River Basin. Clarifying the evolution characteristics of diseases and pests in this area can provide reference for scientific control. [Methods] Based on the relevant data of National Bureau of Statistics and National Plant Protection Statistics released by National Agro-Tech Extension and Service Center, the changing trends of cotton planting area, occurrence and control of disease and pest, and yield loss in the cotton planting region of the Yellow River Basin were analyzed. [Results] From 1998 to 2023, the cotton planting area of the Yellow River Basin and its proportion to the cotton planting area of the whole country increased first and then decreased. The occurrence area, control area, recover loss, and actual loss showed an overall trend of decreasing-increasing-decreasing. The total control area of disease and pest in cotton planting area of the Yellow River Basin is larger than the occurrence area. The occurrence area, control area, recover loss, and actual loss of pest are greater than that of disease. In order of average annual occurrence area from large to small, the major pests and diseases were Helicoverpa armigera, Aphis gossypii, cotton mirid bug, Tetranychus cinnabarinus, seedling disease, boll disease, Bemisia tabaci, Fusarium wilt, cotton thrips, and Ostrinia furnacalis. Over all, the occurrence area ratio of A. gossypii, cotton mirid bug, B. tabaci, cotton thrips, and boll disease showed an increasing trend, while the occurrence area ratio of H. armigera, seedling disease, and Fusarium wilt showed a decreasing trend, and the occurrence area ratio of T. cinnabarinus and O. furnacalis showed no obvious change. The actual losses of H. armigera, A. gossypii, and boll disease accounted for a large proportion. [Conclusion] The main pests and diseases in the cotton planting area of the Yellow River Basin were identified, which provided theoretical support for the prediction and prevention of cotton diseases and pests in production.

[Objective] This study aims to clarify the flight capacity of adults of Sylepta derogata. [Methods] Using an insect flying mill system, the flight capacity for 24 h of male and female adults of S. derogata at 1 day old, and flight parameters for 12 h of adults in different genders and ages of S. derogata were measured; the flight distance, flight time, and flight speed of S. derogata under different mating states, ambient temperatures, and complementary nutrition conditions were also measured in the laboratory. [Results] The adults of S. derogata can be divided into three types: short flying type, intermediate flying type, and long flying type. The dividing points of 24 h cumulative flight time of short and intermediate flying type, intermediate and long flying type were 0.90 h and 2.02 h, respectively. The 1- or 2-day-old adults of S. derogata had relatively weak flight capacity, while the 5-day-old adults had the strongest flight capacity. And there is no significant difference in flight parameters between female and male adults of S. derogata at the same ages. Compared with unmated adults, the flight distance, flight time, and flight speed of 5-day-old mated female adults of S. derogata decreased by 49.85%, 35.63%, and 31.97%, respectively; as for 5-day-old mated male adults, the flight distance, flight time, and flight speed significantly decreased by 82.28%, 66.58%, and 53.65%, respectively. The 5-day-old adults of S. derogata were able to fly normally under the temperature of 22-28 ℃. Under different ambient temperatures, the average flight distance and speed of male and female adults were 26 ℃ > 28 ℃ > 22 ℃. The flight time is the longest under 26 ℃. In addition, after feeding on 8% honey water, the flight capacity of 5-day-old unmated male and female adults of S. derogata was significantly better than that of those fed on water or sugar-vinegar solution. [Conclusion] The adults of S. derogata had a certain level of flight capacity, and the ages, mating status, ambient temperature, and complementary nutrition have important effects on its flight capacity.

[Objective] This study aimed to explore the impact of drought stress, lower canopy shading, and their interaction on the light energy utilization capacity of cotton leaves. [Methods] The photosynthetic physiological indexes, such as plant height, leaf area, leaf thickness, chlorophyll content, and chlorophyll fluorescence parameters, were measured in an artificial climate chamber under drought stress and lower canopy shading conditions using the cotton variety Xinluzao 80 as the material. [Results] Under moderate and severe drought stress, the shading treatment of the lower canopy in cotton significantly increased the plant height and leaf area of lower leaves, significantly decreased the leaf area of upper leaves and leaf thickness of lower leaves, and simultaneously increased the chlorophyll content of upper and lower leaves, which were conducive to the enhancement of the light energy capture capacity, compared with those under the non-shading treatment. Under moderate and severe drought stresses, the actual quantum efficiency of photosystem Ⅱ (Φ_PSⅡ), electron transport rate (ETR), photochemical quenching coefficient (q_P), and non-photochemical quenching (NPQ) of the lower leaves under the shading treatment were reduced compared with those under the non-shading treatment. Φ_PSⅡ of upper leaves under the shading treatment was increased by 19.4% and 31.4%, respectively; ETR was increased by 19.5% and 31.4%, respectively; and q_P was increased by 26.2% and 34.7%, respectively. When shading treatment was applied to the lower leaves, the photochemical reaction in the upper leaves was enhanced under both moderate and severe drought stress. Meanwhile, the heat dissipation capacity of the upper leaves decreased under moderate drought stress but increased under severe drought stress. [Conclusion] The effects of shading treatment on the photosynthetic apparatus of upper leaves were different under different drought stress conditions. Under moderate drought stress, systemic regulation helped to improve the light energy utilization capacity of upper leaves in cotton.

[Objective] This study aimed to screen the single-guide RNA (sgRNA) for gene editing of GhOMT1 (encoding flavonoid 3-O-methyltransferase) and GhPGF (related to gland formation) in cotton, laying the foundation for rapid detection of mutant plants. [Methods] Based on the Cas9-overexpressing cotton Jin668, sgRNAs targeting GhOMT1and GhPGF genes were designed. The editing efficiency and specificity of the sgRNAs were detected by using the cotton leaf crumple virus (CLCrV) vector-mediated gene editing system and high-throughput tracking of mutations (Hi-TOM) technology. [Results] GhOMT1-sgRNA2 and GhPGF-sgRNA induced mutations at the target sites of GhOMT1 and GhPGF, respectively. Hi-TOM sequencing revealed that 12 out of 15 cotton plants transformed with GhOMT1-sgRNA2 exhibited mutations, with a mutation efficiency of 80%. The editing efficiency in single plants ranged from 7.90% to 43.72% for the A subgenome and from 9.60% to 56.32% for the D subgenome. The mutation efficiency of GhPGF-sgRNA was 80%, with an editing efficiency ranging from 10.23% to 30.27%. No off-target effects were observed at the three potential off-target sites of GhOMT1-sgRNA2, and GhPGF-sgRNA had no potential off-target sites in the coding regions of the genome, indicating the high specificity of these sgRNAs. [Conclusion] One sgRNA targeting GhOMT1 and one sgRNA targeting GhPGF were screened using the CLCrV-mediated gene editing system.