Abstract:The digitalization of the aquaculture industry is essential for the modernization of China’s fishery industry.Given that the development of digital aquaculture in China is still in its exploratory stage， there is an urgent need to learn from typical models and summarize international experiences.The paper takes the main ways of integrating current digital technologies with aquaculture as the entry point.By analyzing typical cases empowered by digital technology in China， it dissects the main modes and bottlenecks of digital development of China’s aquaculture industry.It explores the basic path for the digital development of China’s aquaculture industry based on relevant foreign experiences， and puts forward relevant suggestions.This paper argues that to improve the level of digital development in China’s aquaculture industry， it is necessary to increase investment and management of aquaculture data collection and utilization， support research and development as well as the integrated application of digital technologies in aquaculture， enhance farmer participation in the digitalization process， and strengthen the research and formulation of policies related to the digitalization of aquaculture.

Abstract:A non-contact method of measuring the body size of pigs based on stereo-infrared images was established to address the issues of common color images easily affected by environmental lighting and depth images prone to producing holes in the process of measuring the body size of pigs. Infrared images were used to extract foreground of pigs. Ellipse fitting and projection difference methods were used to segment the head and tail of pig. Convex hull analysis and symmetry testing methods were used to select the ideal posture of the pig. Stereo images were used to obtain depth information of the pig， and a homography matrix was used to fuse the advantages of both the infrared and stereo images. A method of measuring the body size of pigs was designed based on these. The results showed that the contours of the pig extracted from the infrared images were clear and smooth. The algorithm of selecting ideal posture had an accuracy of 94.0%. The average relative error of the measurements for body length， body width， hip width， body height， and hip height was 1.78%， 3.26%， 3.20%， 1.92%， and 2.27%， respectively， with an overall average relative error of 2.49% and an average absolute error of 1.42 cm. It is indicated that the algorithm proposed meets the requirements of accuracy for measuring the body size of pigs. It will provide a feasible solution for continuously and automatically measuring the body size of pigs.

Abstract:The dynamic feeding and growth process of breeding pigs during the performance testing was used to solve the problem of accurate segmentation of pigs caused by complex environments in pig farms， dynamic growth of pigs， and changes in body size. A pig video dataset consisting of 234 video sequences was constructed. A XMem-SimAM based semi-supervised video segmentation of pigs was proposed. The ability of model to extract temporal information at different scales was improved and the temporal features of pigs' dynamic movements were captured by introducing SimAM attention for multi-scale feature fusion. The spatial-channel attention module was used to enhance the model's extraction of temporal semantic feature weights. The strategy for multi-scale feature fusion and upsampling module were optimized. The temporal correlation information in video sequences was fully utilized to improve the segmentation accuracy of pigs in videos at a fine-grained level. The results of testing and comparison showed that the Jaccard index， contour accuracy F-score， average metric J&F， and the Dice coefficient of of XMem-SimAM model on the pig video dataset was 96.9， 95.8， 98.0， and 98.0， superior to that of video object segmentation methods including MiVOS， STCN， DEVA， and XMem++， demonstrating its outstanding performance of segmentation. The processing speed reached 58.5 frames per second， with a memory consumption of 795 MB at the stage of reasoning， achieving a good balance between the efficiency of processing and the utilization of resource. The proposed method can be applied to video segmentation of dynamically growing pigs in the complex environments of a pig farm.

Abstract:An automatic supplement system of milk for piglets in the farrowing unit of large-scale pig farms with homeothermia circulation was designed to realize the functions including preparing milk， feeding circularly， and cleaning automatically to solve the problem of low level of automation in nursing piglets in large-scale pig farms. The overall structure and working principle of the supplement system of milk for piglets were explained. The structural design and theoretical analyses of key components including the mixing tanks， stirrers， circulation pipelines， delivery pumps， and auxiliary heaters were conducted. A control system for the supplement of milk was developed with Siemens S7-200 SMART as the core processor. Human-computer interaction through a touchscreen was realized by controlling the flow state of the milk solenoid valves and relays， and monitoring the physical parameters of milk with flow sensors， temperature sensors， liquid level sensors， etc. A prototype was manufactured and the performance of prototype was tested. The results showed that the overall average coefficient of variation for the uniformity of the milk prepared by stirring was 0.435%， and the pipeline pressure ranged from 26.0 kPa to 65.2 kPa. All milk refilling bowls were filled with milk within 6.1 seconds， with the temperature of milk controlled between 40 ℃ and 42 ℃. It is indicated that the designed automatic supplement device of milk for piglets in the farrowing unit has good uniformity of milk， reasonable distribution of pressure， with the temperature of the milk meeting the requirements of supplementing milk for piglets， thereby satisfying the production needs of automatic supplement of milk for piglets in the farrowing unit.

Abstract:An improved YOLOv8n method was used for facial recognition of Angus cattle in captive environments to solve the problem of difficulty in distinguishing facial features caused by Angus cattle's unique black fur and to achieve the accurate and non-contact recognition. A dataset containing 11 000 facial images of 200 Angus cattle at different stages of growth was constructed. Introducing an innovative and enhanced receptive field feature fusion module was introduced to enhance the model's focus on key features. A novel lightweight detection head （LPCDH） was designed for recognizing the facial feature of Angus cattle. The group Taylor pruning method was used to eliminate irrelevant neurons by estimating their importance，thereby reducing computational costs and memory usage，and improving the deployment efficiency of the model. The results showed that the improved model achieved an average recognition accuracy of 92.6%，which was 11.5，3.8，1.8，1.9，5.1，3.9，3.7，and 2.4 percentage higher that of commonly used models including SSDs YOLOv5n，YOLOv8s，YOLOv8m，YOLOv9t，YOLOv10n，RT-Detr，and Mamba-YOLO model，respectively. The designed model was improved by 3.1 percentage in 4-fold cross-validation compared with the original YOLOv8n model. It is indicated that the constructed model is optimized for lightweight memory consumption and computational requirements，making it particularly suitable for real-time recognition on mobile devices and in practical applications，significantly improving the accuracy and efficiency of recognizing the facial feature of Angus cattle. It will have immense potential in individual recognition in the livestock industry.

Abstract:The distribution of the temperature field， relative humidity field， and airflow velocity field in the current layer house was simulated with computational fluid dynamics （CFD） to optimize the thermal environment in a closed cage-rearing layer house under the mode of vertical ventilation in autumn. The accuracy of the numerical model was verified. The average THVI （temperature-humidity-velocity index） and coefficient of variation （CV_THVI） of the cage-rearing areas were calculated for the parameters of ventilation equipment including the angle of the guide plate at the front mountain wall tunnel inlet（θ₁）， the angle of the guide plate at the side wall tunnel inlet（θ₂） and ventilation volume of a suction fan at the end（Q） at three different levels by conducting 17 sets of orthogonal simulation experiments. The results showed that the average relative error of temperature， relative humidity， and airflow velocity at the 24 verification points set on the aisle of cage was 0.38%， 0.52%， and 4.62%， respectively， indicating that the accuracy of the numerical model is high. When the parameters of ventilation equipment θ₁，θ₂ and Q were set to 10°，90° and 42 000 m3/h， the average THVI and coefficient of variation CV_THVI of the airflow field in the cage-rearing areas was 25.65 and 1.64%， 1.61% and 23.93% lower than that of the original scheme of ventilation， beneficial for improving the suitability and balance of the thermal environment in the cage-rearing areas of the layer house.

Abstract:A dynamic correction system consisted of a deviation detection device， a correction execution device， a control system， etc. for the manure cleaning belt was designed to solve the deviation of the manure cleaning belt during the farming of duck with stacked cage. Firstly， the operation status of the manure cleaning belt was monitored in real-time through 6 pressure sensors arranged on both sides of the belt. When the manure cleaning belt deviated， its side pushed the anti-deviation device in the deviation detection device， causing the values of the 3 pressure sensors on the deviated side to change. The direction and offset amount of the cleaning belt was indirectly inferred through the changes. When the STM32 microcontroller determined the deviation of the manure cleaning belt based on the data collected from sensors， it automatically controlled the movement of the stepper motors on both sides， thereby adjusting the forward and backward movement of the drum along the sliding rail to achieve correction. At the same time， the Fuzzy PID control algorithm was introduced to achieve closed-loop control through feedback from displacement sensors to improve the stability and control accuracy of the control system. The results showed that the overall success rate of correction was 85%， with an average deviation of 17 mm and an average relative deviation of 16%. It is indicated that the dynamic correction system designed for the manure cleaning belt basically meets the requirements of the stacked cage-farming duck for automatic correction of the manure cleaning belt， greatly reducing the labor intensity of the farming personnel.

Abstract:The dataset of fish surface pathology was constructed based on four types of fish diseases with high rate of incidence and great harm to fish to improve the accuracy and efficiency of identifying fish surface pathology and solve the problems of heavy reliance on manual labor and low accuracy of identification in the process of identification at present. An improved and optimized DBA_Resnet-18 model with high accuracy of identification based on the Resnet-18 model was constructed by integrating spatial attention and SE channel attention dual attention mechanism. A real-time intelligent visualization system for identifying fish diseases was developed based on this model as well. The improved model incorporates SE channel attention module in the middle of the network and introduces spatial attention mechanism at the end of the network. The results of testing showed that the accuracy of the DBA_Resnet-18 model in classifying fish surface pathology reached 96.75%， which was 1.71， 2.12， 2.37， 2.83， 2.51， 2.23， 2.50， and 3.53 percent points higher than that of the commonly used models including Resnet-18， Resnet-34， Resnet-50， Resnet-101， Swin Transformer， VGG-16， VGG-19， and AlexNet， respectively. It is indicated that the proposed model and the developed intelligent visualization system for identifying fish diseases can quickly and accurately classify and identify different fish surface pathologies， realizing the intelligence of the system for identifying fish diseases， which can be used to diagnose the types of fish surface pathology in practical environments.

Abstract:A method of detecting fish diseases with CEH-YOLOv8 based on dual-channel and hierarchical synergism was developed to solve the problems of the irregular shapes， unclear textures， and scattered disease spots making it difficult to localize the true lesion areas in the detection of fish diseases. A dual-channel feature extraction network was introduced to enhance the ability of model to extract irregular lesion areas with unclear textures. Then， an efficient channel spatial attention （ECSA） mechanism was proposed to improve the capability of model to recognize distributed targets. A hierarchical and balanced feature pyramid network （HBFPN） for was presented to reinforce the improved backbone network and perform hierarchical feature fusion on the information extracted from the backbone network at different levels to enhance the ability of model to express feature. The results showed that the CEH-YOLOv8 network had an accuracy rate of 83.2%， a recall rate of 72.5%， and a mean average precision （mAP） of 76.2% in detecting fish diseases， respectively. Compared with the state-of-the-art （SOAT）YOLOv10 method and the original model， it increased the accuracy rate， recall rate， and mAP by 6.9， 11.6， and 11.9 percent points， and 4.3， 6.9， and 6 percent points， respectively. The inference time for a single frame was 9.1 ms. It is indicated that the improved YOLOv8 network can accurately screen fish with diseases and be used for early detection of fishery diseases to reduce economic losses.

Abstract:A chute mass flowmeter of granular materials was designed based on capacitance method and according to the difference in dielectric properties between granular materials and air to achieve online automatic measurement of the mass flow rate of granular materials in the chute.The device was equipped with an STM32 microcontroller， a capacitance-to-digital Converter chip AD7746， and a plate conversion circuit with MT8816 as the core chip to build a data acquisition system， achieving effective acquisition of capacitance of eight-plate rotary excitation sensors.A test bench of mass flowmeter was built.Maize， wheat and granular compound feed were used to calibrate the relationship between the mass flow rate and the value of cumulative capacitance.The models of predicting the mass flow of three kinds of granular materials were constructed， with determination coefficient R² of 0.990 4， 0.993 9， and 0.987 9， respectively.The results of verifying the accuracy of chute mass flowmeter showed that the average relative error （MRE） of measurement accuracy for maize， wheat and granular compound feed was 3.11%， 3.76%， and 3.75%， when the inclination angle of the chute was 15°， 25°， 35°， 45°， and 55°， the mass of maize and wheat mass was 30， 50 and 70 kg，the mass of granular compound feed was 30， 50， and 65 kg， respectively.It is indicated that it is feasible to use the capacitance method in the online measurement of mass flow rate in the process of transporting granular materials through a chute， which can achieve the automatic online measurement of the mass flow rate of granular materials.

Abstract:A lightweight model of ShuffleNetV2-EH with higher accuracy of identification， lower complexity of computation， and suitable for identifying the types of feed raw material based on the lightweight convolutional neural network model ShuffleNetV2 to achieve rapid identification of warehousing feed raw materials and solve the difficulties in manually identifying the types of feed raw materials with similar crushing degree， color， and shape in currently processing and producing the combined feed raw materials. Firstly， the efficient channel attention（ECA） mechanism was introduced into the structure of ShuffleNetV2 network model， which adaptively adjusts channel weights based on input to enhance the ability of network model to percept important features in images of feed raw materials. Secondly， ReLU was replaced with HardSwish activation function to improve the recognition accuracy of the model without adding additional weights and parameters of bias. Finally， the structure of ShuffleNetV2 network model was adjusted to reduce the number of parameters and the complexity of computation in the model on the basis of ensuring the recognition accuracy of model. The results showed that the recognition accuracy of ShuffleNetV2-EH model on image sets from 8 types of feed raw materials was 99.13%， 1.38% higher than that of the original ShuffleNetV2 model. Its accuracy， recall， and F₁ score increased by 1.45%， 1.63%， and 1.62 %， respectively. The number of model parameters and floating-point operations decreased by 352 092 and 45.27×10⁶， compared to that of the original model. The overall performance was superior to classical convolutional neural network models including AlexNet， VggNet16， GoogLeNet， and ResNet18. It is indicated that the improved ShuffleNetV2 model well balances the complexity of computation and the recognition accuracy of the model， providing an algorithm foundation for online identification of feed raw materials in the warehousing process.

Abstract:A predictive model for detecting the addition of milk to yak milk was established by combining mid-infrared spectroscopy （MIRS） with machine learning algorithms to supervise and regulate the production and sale of yak milk， further quantitatively predict the proportion of adulteration in yak milk and provide new technology of rapid detection. 76 samples of pure yak milk， 76 samples of yak milk adulterated with 10% milk， 76 samples of yak milk adulterated with 25% milk， and 76 samples of yak milk adulterated with 50% milk were used to establish binary qualitative models for distinguishing pure yak milk from yak milk adulterated with milk， and quantitative regression models for predicting the proportion of yak milk adulterated with milk with five spectral preprocessing algorithms， six qualitative and twelve quantitative machine learning algorithms. The results showed that the predictive model for identifying pure yak milk and yak milk adulterated with milk based on support vector machine modeling algorithm and the spectrum without preprocessing had the best performance. The validation set AUC， the accuracy， the sensitivity， and the specificity of the model was 0.95， 0.84， 0.93， and 0.87， which can be used for the identification of pure milk and adulterated milk. The optimal quantitative model for predicting the proportion of milk in yak milk was established using Bayesian regularized neural network modeling algorithm and first-order derivative spectral preprocessing algorithm. The model had R_P²=0.88， RMSEV=6.57%， and RPD=2.89%. It is indicated that the combination of mid-infrared spectroscopy and machine learning algorithms can effectively identify yak milk adulterated with milk and detect the proportion of adulteration.

Abstract:501 milk samples of healthy Chinese Holstein cows were collected from major milk-producing regions in Northwest，North，and Central China to establish a method that can rapidly，in batch，and efficiently detect the content of β-lactoglobulin in milk from Chinese Holstein cows，high-performance liquid chromatography （HPLC） was used to determine the content of β-lactoglobulin in milk samples，and the mid-infrared spectroscopy （MIRS） data of milk samples were synchronously measured and collected 12 methods of spectra pretreatment were randomly combined twice in a row，and the characteristic bands were manually selected with MIRS as the predictor variable and the content of β-lactoglobulin as the dependent variable.Partial least squares regression （PLSR） was used as a traditional machine learning algorithm to establish an optimal model for the prediction of the content of β-lactoglobulin in milk.The results showed that the R_C² and R_P² of the cross validation set and test set in the established model was 0.812 9 and 0.768 8，with the root mean square errors，RMSE_C and RMSE_P of 0.476 2 g/L and 0.524 9 g/L，the RPD of 2.076 6，meeting the requirements for measuring the production performance of livestock and poultry.It is indicated that MIRS can be used to establish a model for predicting the content of β-lactoglobulin in milk from Chinese Holstein cows.

Abstract:A model for instance segmentation based on improved Mask-Scoring R-CNN was proposed and the efficient segmentation of myofibroblast cells was realized to solve the problems of manual and semi-automatic segmentation with accuracy and efficiency and the inadequate performance of general models for segmentation in encountering various interferences of noisy images.The Convolutional Block Attention Module （CBAM） attention mechanism was introduced into the Mask-Scoring R-CNN model to improve the model.The extraction and expression of feature information by the improved model was enhanced to improve the performance of segmentation and the generalization capability of the model in tasks of segmentation.The results of testing the improved Mask-Scoring R-CNN model on a dataset of 103 test images showed that the root mean square error （RMSE） of phenotype measurement value was smaller than that of the original model，with the RMSE of the total number of myofibers decreased from 2.08 to 1.26，the RMSE of area reduced from 212.21 μm2 to 181.36 μm2，and the RMSE of average diameter decreased from 2.87 μm to 1.47 μm.It is indicated that the improved model can effectively deal with noisy images of myofiber and accurately segment each myofiber even in common noisy environments.

Abstract:Weak gluten wheat is suitable for making biscuits， pastries and other foods. With the continuous growth of consuming biscuits and other foods in China， the demand of weak gluten wheat is gradually increasing. In recent years， the import volume of weak gluten wheat in China has remained high， and it is imperative to improve the yield and quality of weak gluten wheat in China. The current status of weak gluten wheat and the industrial problems in China including insufficient varieties with high-quality， incomplete system of evaluation， poor quality of weak gluten， need for optimizing cultivation techniques， insufficient adaptability of supporting cultivation techniques， and the dependence of importation were analyzed based on the distribution of dominant production areas for weak gluten wheat in China and the achievements of regional scientific research units to enhance the competitiveness of weak gluten wheat and promote the sustainable development of the weak gluten wheat industry in China. We need to optimize the evaluation system， strengthen basic research， breed excellent varieties， and promote innovation and application of cultivation techniques to address these challenges. Therefore， it is proposed to strengthen the basic researches about weak gluten wheat industry， optimize the breeding process of varieties， innovate cultivation techniques， and accelerate the pace of industrial application.

Abstract:The ZmDIR11 gene， a member of the DIR gene family， was cloned from maize and its sequence of gene and structures of protein were predicted to mine key genes involved in regulating the resistance to salt stress in maize. The patterns of gene expression were analyzed to further investigate the regulatory mode of ZmDIR11 in salt stress tolerance in maize B73-EMS mutants. The results showed that ZmDIR11 encoded a peptide containing the Dirigent domain， and its promoter region contained structural elements including ARE， MYB， MYC， STRE， LTR， and MBS， all associated with the regulation of abiotic stress. ZmDIR11 was predominantly expressed in maize roots and upregulated under salt stress， with subcellular localization in the endoplasmic reticulum. It was found that the growth and material accumulation of mutant maize plants after salt stress treatment were significantly lower than those of wild-type B73， and the regulation pathway of oxidative metabolism， the accumulation of proline， the synthesis of chlorophyll， the accumulation of lignin， and the transport pathway of Na⁺/K⁺ were inhibited. Relevant metabolic indexes of mutant maize plants were significantly lower than those of wild-type B73. It is indicated that ZmDIR11 positively regulates the metabolic pathway of salt tolerance in maize， and its mutation reduces the salt tolerance in maize.

Abstract:Cigar-filler variety Chuxue 14 （CX-14） was used to conduct a field experimen to study the effects of sulfur fertilizer dosages including 0， 60， 120 and 180 kg/hm² on the agronomic traits， yield， quality and combustion performance of cigar tobacco.The results showed that the plant height， maximum leaf width， leaf length， effective leaf number， and SPAD value of cigar tobacco during the period of growth， the yield and the rate of superior tobacco under applying sulfur fertilizer was increased compared with no sulfur application， thus the output value of cigar tobacco was increased as well.Among them， the yield and output value were highest under 120 kg/hm² sulfur application， and the rate of superior tobacco was highest under 60 kg/hm² sulfur application.The application of sulfur fertilizer tended to increase the content of total sugar， reducing sugar， and crude protein， the proportion of reducing sugar in cigar tobacco leaves， which in turn helped to improve the intrinsic quality of tobacco leaves.Compared with no sulfur application， the 60 kg/hm² sulfur application increased the activation energy during tobacco combustion， lowered the initial temperature of tobacco combustion， and reduced the content of ash.The maximum heat flux temperature and total heat release increased by 10.9% and 6.3%， respectively， and the frequency factor during combustion decreased by 43.7%， thereby improving the combustion performance of tobacco leaves.It is indicated that the appropriate sulfur fertilizer dosage for cigar tobacco leaves was 60 kg/hm² under the conditions of this experiment.Excessive application of sulfur fertilizer including 120 kg/hm² and 180 kg/hm² can increase the yield and economic benefits of cigar tobacco leaves， but it is not conducive to improving the combustion performance of tobacco leaves.Therefore， it is possible to consider reducing the application of potassium sulfate fertilizer appropriately in the process of planting cigar and replacing it with potassium carbonate and other potassium fertilizers to reduce the negative effects of excessive sulfur fertilizer on the combustion performance of tobacco and soil acidification.

Abstract:The large-scale interlayer soil in heavy saline-alkali land formed by concentrated and continuous sections after the water-saving construction with large-scale and high efficiency in the Weigan River irrigation area was used to solve the practical problems of large quantity of engineering and high cost of production in the existing improvement measures for heavy saline-alkali land.The changes of water and salt in soil under winter irrigation conditions with different improvement measures were studied through field plot experiment.The results showed that the deep-turning treatment had the highest desalination rate of 75.9% among all the treatments， followed by ditching， drilling and sand filling， and drilling and sand filling treatment， accounting for 51.5% and 39.4%， respectively.The desalination rate of ditching and drilling was relatively close， accounting for 38.2% and 37.4% respectively.The lowest desalination rate of ditching was 33.9%.The content of salt under each measure in the 0-20 cm soil layer after two and three times of winter irrigation decreased from 7.06-11.61 g/kg before winter irrigation in 2020 to 2.00-5.91 g/kg after winter irrigation in 2022， with a desalination rate ranged from 76.8% to 382.5%.It is indicated that the surface soil has been improved from the initial medium-heavy saline-alkali soil to light-medium saline-alkali soil， reflecting the retarding effect of clay interlayers on the transport of water and salt.Drilling and sand filling can be used as a simple and practical measure to improve the effect of salt leaching and suppress the return of salt in saline-alkali land.It will provide basic data and technical reference for the rational selection of improvement measures for interlayer soil in the heavy saline-alkali land.

Abstract:The resistance to sesame leaf spot disease of 20 main rice varieties and 5 control varieties in Sichuan Province was evaluated with potted plant disease resistance identification method to study the resistance to sesame leaf spot disease and the physiological and biochemical mechanisms of disease resistance in the main rice varieties in Sichuan Province. The activity of 5 defense enzymes was determined in the leaves of different resistant varieties. The secondary metabolites in the leaves of rice seedlings in resistant and susceptible varieties were analyzed with gas chromatography/mass spectrometry （GC/MS）. The results showed that Yuxiangnuo 1 and Zhejingyou 4 were highly resistant varieties，while 5 varieties including Xiushui 134，Zhehe 622，Zhehexiang No.2，Zhejingyou 77 and Zhejingyou 1578 had moderate resistance，and the rest were susceptible varieties. The activity of 5 enzymes including superoxide dismutase （SOD），polyphenol oxidase （PPO），phenylalanine ammonia lyase （PAL），peroxidase （POD），and catalase （CAT） increased first and then decreased in both resistant and susceptible rice varieties，but the activity of enzyme in resistant varieties was significantly higher than that in susceptible varieties. A total of 18 secondary metabolites were obtained，among which 4 metabolites including ribosyl alcohol，D-glucose，malic acid，and 2，3，4-trihydroxybutyric acid had significant differences in content between resistant and susceptible rice varieties，and between inoculated and non-inoculated treatment of the same variety. It is indicated that rice resistant varieties can resist the invasion of sesame leaf spot disease by increasing the activity of 5 defense enzymes and the content of four secondary metabolites.

Abstract:Paenibacillus polymyxa NBmelon-1 is an efficient biocontrol bacterium isolated from the roots of sweet melons. The third-generation of PacBio sequencing technique was used to sequence the whole genome of strain NBmelon-1 to study the biocontrol mechanisms of P. polymyxa NBmelon-1. The potential functional genes were analyzed and clusters of genes involved in the synthesis of secondary metabolites were predicted. The expression of genes related with antibacterial effect and promoting the growth of plants was detected. The antagonism test of crude extracts was used to identify the main components of antibacterial substances and validate the potential of the bacteria to promote the growth of plants， further clarifying its biocontrol mechanism. The results showed that the genome of P. polymyxa NBmelon-1 was 5.7 Mb， with a GC content of 45.68% and 4 984 coding genes. There were a large number of genes involved in inducing plant disease resistance， hydrolytic enzymes， and promoting plant the growth of plants in the genome. A total of five clusters of genes involved in the synthesis of secondary metabolites of lipopeptides were predicted. The crude extracts isolated from NBmelon-1 culture with acid precipitation method had significant antibacterial activity against a variety of pathogenic fungi from melon， indicating the presence of antibacterial substances. The results of growth potential test showed that the strain was capable of synthesizing growth hormone IAA， producing iron carriers， and providing nitrogen elements for plants. It is indicated that P. polymyxa NBmelon-1 is a multifunctional biocontrol bacterium with broad prospects for development and application in agricultural production.

Abstract:Pinellia ternata diseases pose a significant obstacle to the industrial development of P. ternata.To screen for superior strains of beneficial microorganisms that promote growth and enhance resistance to P. ternata diseases，strains were isolated and screened from the rhizosphere soil of P. ternata.Nine strains exhibiting antagonistic effects against various pathogens of P. ternata，including Fusarium oxysporum，Aspergillus，Fusarium，Phytophthora capsici and Fusarium solani，were successfully isolated.These strains were identified，and their antimicrobial activities were assessed.Subsequently，the strains were formulated into microbial fertilizers，and their effects on promoting growth promotion and controlling disease in P. ternata were evaluated.The results showed that strain 21-2 exhibited the strongest antimicrobial activity，and identification confirmed that the strain was Paenibacillus polymyxa.Strain 21-2 demonstrated notable inhibitory effects against five common pathogens of P. ternata and significantly promoted the germination of P. ternata seeds.The bacterial suspension of strain 21-2 exhibited a disease control efficacy of 45.83% against diseases affecting P. ternata and significantly enhanced the plant’s height，fresh weight，bulb weight，and chlorophyll content .The bio-organic fertilizer，which consists of P. polymyxa 21-2，straw-derived biochar，and organic fertilizer from chicken manure，exhibited a disease control efficacy of 61.90% against diseases affecting P. ternata.The results indicated that the P. polymyxa strain 21-2 could be effectively utilized for controlling diseases in P. ternata，promoting its growth，and demonstrating significant potential for further development and application.

Abstract:A method for simultaneously detecting the concentrations of Prochloraz and Imazalil at relatively high concentrations was established with high performance liquid chromatography （HPLC） to scientifically standardize the use of Prochloraz and Imazalil in the preservation of citrus fruits.The results showed that the linear relationship between Prochloraz and Imazalil was good within the range of 5-300 μg/mL， indicating that this method has high sensitivity and accuracy.Prochloraz was stable at room temperature and Imazalil had a high rate of degradation in the post-harvest sorting line of Satsuma mandarins.The concentration of Prochloraz and Imazalil after 6 hours of processing 15 tons of Satsuma mandarins decreased by 98.6 μg/mL and 290.3 μg/mL， respectively.It is indicated that this method can be applied to detect the concentration of Prochloraz and Imazalil during the post-harvest processing of citrus fruits， which is beneficial for improving the efficiency of using fungicide and reducing costs of production.

Abstract:The efficient and stable genetic transformation system of plants is an important technical support for the analysis of gene function and molecular breeding. However， the imperfect tissue culture system seriously hinders its application in many plants， especially in crops. In recent years， many efficient genetic transformation systems of plants with non-tissue culture have been established to solve the problems mentioned above. This article focuses on the genetic transformation system of plants with non-tissue culture mediated by Agrobacterium tumefaciens in terms of the current status of application， factors affecting transformation efficiency， and applications of gene editing with flower organ infection， cut-dip-budding （CDB） delivery， regenerative activity dependent in plant injection delivery （RAPID）， seed inoculation， development regulatory （DR） assisted transformation， and virus delivery in plants. The application of pollen tube channel method， particle bombardment method and nano delivery method in plants independent of Agrobacterium tumefaciens was summarized. It will provide reference for establishing efficient， simple and genotype-independent genetic transformation system with non-tissue culture in more species and assisting the studies on plant functional genes and the practices of molecular breeding.

Abstract:‘Zaohong’navel orange ［Citrus sinensis （L.） Osbeck + C. unshiu Marc.］ is a grafted chimaera of ‘Robertson’ navel orange ［C. sinensis （L.） Osbeck］ and ‘Guoqing 1’ satsuma mandarin ［C. unshiu Marc.］.The ‘Zaohong’ navel orange has the peels of a navel orange and the flesh of a tangerine.It has a good flavor that has made it a favorite in recent years.The effects of different rootstocks on the growth of tree and fruit quality of ‘Zaohong’ navel orange were evaluated to provide a scientific basis for growers of ‘Zaohong’ navel orange species to select the optimal combinations of rootstock.The ‘Zaohong’ navel orange was used to study the effects of three different combinations of rootstock including C. reticulata Blanco cv. Red tangerine （Rt）， Poncirus trifoliata Raf.（Pt）， and originally Poncirus trifoliata and then red tangerine（Pt+Rt） on the growth and the fruit quality of the oranges.The results showed that there were differences in photosynthesis and its products， the growth of tree， fruit yield and quality of ‘Zaohong’ navel oranges grafted on different rootstocks.The content of soluble sugar in leaves， the concentration of intercellular CO₂ and the stomatal conductivity were in the decreasing order of Pt>Pt+Rt>Rt.The growth of tree and fruit yield， plant height， crown diameter， shoot length， leaf size and fruit yield were in the decreasing order of Rt>Pt+Rt>Rt.The fruit quality including the content of soluble solids and total acid in Pt was higher than that in the other two combinations.There was no significant difference in the solids-acid ratio of the different combinations of rootstocks.The fruit weight of Rt and Pt+Rt was larger than that of Pt.The fruit size of Pt was unstable among different years.It is indicated that Rt has stronger growth of tree， higher yield of fruit and weight of single fruit， with acid fixation ratio not inferior to that of Pt. Rt has better economic benefits and is suitable for promotion and use in the Three Gorges Reservoir area.

Abstract:To clarify the cause of mortality in Pelophylax nigromaculatus， a pathogenic bacterial strain designated B20200824 was isolated from the brain， spine， liver， and kidney of diseased P. nigromaculatus. The strain was identified through physiological and biochemical assays， 16S rRNA sequencing， and phylogenetic analysis.. Subsequently， the susceptibility and minimal inhibitory concentrations （MICs） were determined using the Kirby-Bauer （K-B） and broth micro-dilution methods， respectively. After identification， the strain was characterized as a Gram-negative short bacillus with biochemical properties consistent with those of Proteus vulgaris. Moreover， 16S rRNA sequencing and phylogenetic analysis revealed that the strain exhibited a close genetic relationship with P. vulgaris， which shared over 99% genetic homology. Consequently， strain B20200824 was identified as P. vulgaris. The results of the drug susceptibility test showed that the strain was resistant to norfloxacin， amoxicillin， enrofloxacin， and 3 other drugs； it showed intermediate resistance to doxycycline and erythromycin， and susceptible to azithromycin， cefotaxime， florfenicol， and 2 other drugs. The MIC of florfenicol was 0.25 μg/mL， while the MICs for imipenem， levofloxacin， and azithromycin were 0.125 μg/mL， and for cefotaxime it was 0.061 25 μg/mL， respectively. These results were consistent with those obtained from the susceptibility assay. Taken together， these findings demonstrate that P. vulgaris can cause disease in P. nigromaculatus， and florfenicol is recommended for controlling infections caused by P. vulgaris in clinical practice.

Abstract:To explore the etiology of a serious infectious disease affecting Rana grylio at a farm in Sichuan Province，pathological examinations and pathogen isolation were conducted on the diseased frogs.The isolated pathogen was identified using transmission electron microscopy，PCR detection，and phylogenetic analysis.External clinical signs included limb swelling and ulcerations on the body surface.The dead frog exhibited an enlarged liver，spleen and kidney.Histopathological observations revealed that the liver，spleen，kidney and other organs exhibited damage characterized by significant degeneration and necrosis foci.The carp epithelioma papulosum cyprini （EPC） cell line，inoculated with diseased samples at 25 ℃，demonstrated typical cytopathic effects （CPE） after four days，including rounding and shedding，with a TCID₅₀ of 10^4.12/0.1 mL.Transmission electron microscopic observation showed that the virus exhibited a regular hexagonal shape with a crystalline array of its capsid，and the diagonal diameter measured approximately 165 nm.PCR by using specific primers for the major capsid protein （MCP） gene was performed on the internal tissues of infected frogs and on EPC cells with CPE，yielding positive results.Phylogenetic analysis based on MCP gene sequences indicated that the sequences of isolated virus shared over 99% identity with ranavirus and was classed as FV3-like.This study confirmed that the isolated virus，designated TSL210813，is a ranavirus，responsible for the disease observed in R. grylio.

Abstract:A seedling picking and chain breaking device for a chain paper pot seedling transplanter was designed with conventional hexagonal cross-section chain pot seedlings to solve the problems of continuous chain transplanting with unadjustable spacing of plant and inability to meet the requirements of transplanting crops with large spacing of plant in the existing chain paper pot seedling transplanters. The structure of key components and the range of working parameters were determined through theoretical analyses of the working process based on explaining the working principle of the seedling picking and chain breaking device. An experiment bench was set up for the experiment with single factor. The orthogonal combination experiment of three factors including the opening of the pinch finger， the inclination angle of the seedling chute and the planting frequency and three levels with the success rate of seedling taking and the rate of matrix loss as the evaluation indexes was conducted to analyze and optimize the effect of each factor on the evaluation index. The results showed that the effect was better when the opening of the pinch finger was 52 mm， the inclination angle of the seedling chute was 20°， and the planting frequency was 45 plants/min. The success rate of seedling taking and the rate of matrix loss in the bench experiment and the soil trough verification experiment was 91.3% and 14.2%， and 87.5% and 17.4% under this combination of parameters. It will provide reference for the development of the whole chain pot seedling transplanter.

Abstract:The mechanical properties of stalks of water chestnut at the stage of transplanting were studied to provide a theoretical basis for the mechanization of transplanting.Experiments of radial compression，shearing，and bending on the stalks of Hubei water chestnut No.1 and Dahongpao water chestnut from Tuanfeng County，Huanggang City，Hubei Province，China，were carried out with TMS-PRO textrometer.The results showed that the capacity of radial bearing in the stalks increased from the top to the bottom，with the average value of the lower part ranged from 4.0 N to 4.1 N.The longer the shelving time （within 4 hours），the lower the content of moisture in the stalks and the smaller the capacity of radial bearing.The effect of loading rate on the capacity of radial bearing was not significant.The lower part of the stalks had the highest force of shearing，with an average of 120 N to 165 N and a strength of shearing about 6 MPa.The effect of a 4-hour resting time on force of shearing was not significant.The upper part of the stalk had the smallest stiffness of bending，with an average between 1.4×10^-3 N·m² and 1.6×10^-3 N·m²，the middle part had the largest bending modulus of elasticity，with an average between 290 MPa and 405 MPa，and the lower part had the largest cross-sectional moment of inertia，with an average between 33 mm⁴ and 35 mm⁴，and the force of the lower part was significantly higher than that of the upper and middle parts，with an average of the maximum load less than 2 N.It will provide a basis for the design of the machine tools for cutting，handling and transplanting of seedlings.

Abstract:The XAG P20-2019 quadcopter UVA was used to spray foliar fertilizer on Acanthopanax trifoliatus to study the feasibility and optimal combination of working parameters for spraying foliar fertilizer on Acanthopanax trifoliatus with unmanned aerial vehicle （UAV）. The orthogonal experiment with three factors and three levels was designed to investigate the effects of the concentration of spraying， the speed of flight and the height of working on the quality of spraying， the yield of Acanthopanax trifoliatus and the quality of leaf. The results showed that the speed of flight and the height of working had significant effects on the quality of spraying， and the density of droplet deposition had a strong positive correlation with the amount of droplet deposition. The effects of the concentration of spraying， the speed of flight and the height of working on the yield and quality of leaf in Acanthopanax trifoliatus were significant. The density and the amount of droplet deposition was 188.212/cm2 and 0.269 μg/cm2 when the concentration of spraying， the speed of flight and the height of working was 5 times the concentration recommended，1.0 m/s and 2.0 m. At this time， the effect of spraying foliar fertilizer on Acanthopanax trifoliatus with UAV was the best， with a 27.46% increase in the yield of Acanthopanax trifoliatus and a 33.23% increase in the content of chlorophyll in Acanthopanax trifoliatus compared with that of the control. It is indicated that it is feasible to use UAV to spray foliar fertilizer with high concentration on Acanthopanax trifoliatus. It will provide references for using the same type of UVA to spray foliar fertilizer.

Abstract:Industrial syngas contains a large amount of CO₂， and the utilization of CO₂ resources is of great significance to the current improvement of environment. The homoacetogenesis in the process of anaerobic fermentation has characteristics of autotrophy and heterotrophy. It can use CO₂ and H₂ to produce acetic acid， and degrade glucose to produce volatile fatty acids （VFAs）. The autotrophic characteristics of homoacetogenic bacteria were used to study its ability to convert CO₂ into resources and the effects of headspace H₂/CO₂ ratio， the type of carbon sources and pH on the synthesis of homoacetogenic reaction products. The results showed that high pH was beneficial for homoacetogenic bacteria to utilize H₂/CO₂ mixed gas for autotrophic reactions. When pH=5 and H₂/CO₂=3∶1， the yield of VFAs including acetic acid， propionic acid and butyric acid was the highest， reaching 3 369.89 mg/L， and the proportion of acetic acid was 76.1%. When glucose and H₂/CO₂ mixed gas were used as a common carbon source， the homoacetogenic bacteria preferentially used glucose for heterotrophic reaction， and then the H₂/CO₂ mixed gas began to be utilized. The results of correlation analysis showed that there was a weak positive correlation between the content of VFAs and the value of pH， but a negative correlation with H₂/CO₂， indicating that the content of CO₂ has a greater impact on the autotrophic pathway of homoacetogens. A prediction model with BP neural network for homoacetogenic reaction was established， which accurately predicted the yield of VFAs synthesized by homoacetogenic bacteria with H₂/CO₂ mixed gas as the carbon source（R²=0.966）.

Abstract:A heterogeneous network-based on interactions between plants was constructed，and a graph neural network-based method for predicting interactions between plants was proposed to solve the problem of accurately predicting inhibitory and promotive interactions between plants based on prior knowledge.The method is primarily composed of three modules including a representation learner，an interaction identifier，and a type classifier.The representation learner is responsible for extracting representations of interactions.The interaction identifier collaborates with the representation learner to predict whether an interaction exists on types of targeted plant and applies perturbations to the type classifier to maximally acquire transferable features across different types of interaction.The type classifier is designed to accurately distinguish types of interactions between plants to avoid being affected by the interaction identifier.The inter adversarial relationship among the three modules is leveraged to enhance robustness against the differences in the types of inhibitory and promotive interactions between plants，thereby effectively solving the problem of accurately predicting targeted interactions between plants.The AUC，precision，and accuracy of this method on the dataset of companion plant improved by 7.74，1.61，and 8.62 per cent，respectively compared with the best method SVM that of existing methods including SEAL，GATNE，HeGAN，PME，SVM，and RF，reaching 92.00%，80.12%，and 86.21%，respectively.The results indicate that the proposed method effectively mitigates the interference caused by target interaction type differences，enabling accurate prediction of plant interactions.This approach can be applied to optimize agricultural production practices.