The harmless and reuse of agricultural waste not only turns waste biomass into treasure, but also reduces pollution to the ecological environment and improves the living environment, which is an effective way to achieve green, circular, low-carbon, efficient and sustainable development. In this article, we conducted bibliometric statistics of the relevant literature on agricultural waste resource utilization published in China and abroad from 1990 to 2022, and comprehensively analyzed the annual trend of the number of articles published in this field and the key words with the help of CiteSpace and VOSviewer bibliometric tools. Domestic research in this area started nearly 10 years earlier than overseas, the research intensity and importance of international research in this field since 2002 have been significantly higher than that of domestic research, the growth trend of the number of annual publications is also significantly higher than that of domestic research, and the gap between the number of publications at home and abroad is also widening year by year. The research hotspots in the field are not exactly the same at home and abroad. We focus more on the use of waste for the production of organic fertilizers to realize the recycling of green and low-carbon agriculture in China; the foreign countries focus more on biomass materialization and energy utilization of waste to compensate for the consumption of non-renewable resources. Based on China's basic condition of having more people and less land, China should strive to broaden the disposal methods of agricultural waste by classifying and disposing of agricultural waste raw materials and subsequently using them for substrate, feed, fertilizer, materialization and energy. And waste gas, heat and residue should be recycled in order to realize the multi-level utilization of harmless, reduced and diversified biomass resources. The results of the study provide a reference for the development of the field of agricultural waste resource utilization in China.

With the increase of global temperature, heat stress has emerged as one of the major factors affecting plant growth and development. The substantial losses caused by heat, particularly for staple crops like rice, pose a significant impact on economic benefits. In order to unravel the molecular mechanisms underlying plant response to heat stress, the adverse effects of heat stress on the morphology, physiology, biochemistry and photosynthesis have been presented. Furthermore, the three molecular mechanisms employed by plants to cope with heat stress, including signal transduction pathways, transcriptional factor regulatory networks and the expression of heat-resistance related genes have been introduced as well. Based on these insights, this review suggests that bioinformatics, genetic engineering, cell biology and molecular biology may be further employed as tools for understanding the molecular mechanisms of heat stress in plants. At last, this review offers a prospective outlook on future research directions in this field.

[Significance] Big Models, or Foundation Models, have offered a new paradigm in smart agriculture. These models, built on the Transformer architecture, incorporate numerous parameters and have undergone extensive training, often showing excellent performance and adaptability, making them effective in addressing agricultural issues where data is limited. Integrating big models in agriculture promises to pave the way for a more comprehensive form of agricultural intelligence, capable of processing diverse inputs, making informed decisions, and potentially overseeing entire farming systems autonomously. [Progress] The fundamental concepts and core technologies of big models are initially elaborated from five aspects: the generation and core principles of the Transformer architecture, scaling laws of extending big models, large-scale self-supervised learning, the general capabilities and adaptions of big models, and the emerging capabilities of big models. Subsequently, the possible application scenarios of the big model in the agricultural field are analyzed in detail, the development status of big models is described based on three types of the models: Large language models (LLMs), large vision models (LVMs), and large multi-modal models (LMMs). The progress of applying big models in agriculture is discussed, and the achievements are presented. [Conclusions and Prospects] The challenges and key tasks of applying big models technology in agriculture are analyzed. Firstly, the current datasets used for agricultural big models are somewhat limited, and the process of constructing these datasets can be both expensive and potentially problematic in terms of copyright issues. There is a call for creating more extensive, more openly accessible datasets to facilitate future advancements. Secondly, the complexity of big models, due to their extensive parameter counts, poses significant challenges in terms of training and deployment. However, there is optimism that future methodological improvements will streamline these processes by optimizing memory and computational efficiency, thereby enhancing the performance of big models in agriculture. Thirdly, these advanced models demonstrate strong proficiency in analyzing image and text data, suggesting potential future applications in integrating real-time data from IoT devices and the Internet to make informed decisions, manage multi-modal data, and potentially operate machinery within autonomous agricultural systems. Finally, the dissemination and implementation of these big models in the public agricultural sphere are deemed crucial. The public availability of these models is expected to refine their capabilities through user feedback and alleviate the workload on humans by providing sophisticated and accurate agricultural advice, which could revolutionize agricultural practices.

[Significance] Agricultural sensor is the key technology for developing modern agriculture. Agricultural sensor is a kind of detection device that can sense and convert physical signal, which is related to the agricultural environment, plants and animals, into an electrical signal. Agricultural sensors could be applied to monitor crops and livestock in different agricultural environments, including weather, water, atmosphere and soil. It is also an important driving force to promote the iterative upgrading of agricultural technology and change agricultural production methods. [Progress] The different agricultural sensors are categorized, the cutting-edge research trends of agricultural sensors are analyzed, and summarizes the current research status of agricultural sensors are summarized in different application scenarios. Moreover, a deep analysis and discussion of four major categories is conducted, which include agricultural environment sensors, animal and plant life information sensors, agricultural product quality and safety sensors, and agricultural machinery sensors. The process of research, development, the universality and limitations of the application of the four types of agricultural sensors are summarized. Agricultural environment sensors are mainly used for real-time monitoring of key parameters in agricultural production environments, such as the quality of water, gas, and soil. The soil sensors provide data support for precision irrigation, rational fertilization, and soil management by monitoring indicators such as soil humidity, pH, temperature, nutrients, microorganisms, pests and diseases, heavy metals and agricultural pollution, etc. Monitoring of dissolved oxygen, pH, nitrate content, and organophosphorus pesticides in irrigation and aquaculture water through water sensors ensures the rational use of water resources and water quality safety. The gas sensor monitors the atmospheric CO₂, NH₃, C₂H₂, CH₄ concentration, and other information, which provides the appropriate environmental conditions for the growth of crops in greenhouses. The animal life information sensor can obtain the animal's growth, movement, physiological and biochemical status, which include movement trajectory, food intake, heart rate, body temperature, blood pressure, blood glucose, etc. The plant life information sensors monitor the plant's health and growth, such as volatile organic compounds of the leaves, surface temperature and humidity, phytohormones, and other parameters. Especially, the flexible wearable plant sensors provide a new way to measure plant physiological characteristics accurately and monitor the water status and physiological activities of plants non-destructively and continuously. These sensors are mainly used to detect various indicators in agricultural products, such as temperature and humidity, freshness, nutrients, and potentially hazardous substances (e.g., bacteria, pesticide residues, heavy metals, etc. Agricultural machinery sensors can achieve real-time monitoring and controlling of agricultural machinery to achieve real-time cultivation, planting, management, and harvesting, automated operation of agricultural machinery, and accurate application of pesticide, fertilizer. [Conclusions and Prospects In the challenges and prospects of agricultural sensors, the core bottlenecks of large-scale application of agricultural sensors at the present stage are analyzed in detail. These include low-cost, specialization, high stability, and adaptive intelligence of agricultural sensors. Furthermore, the concept of "ubiquitous sensing in agriculture" is proposed, which provides ideas and references for the research and development of agricultural sensor technology.

With the rapid development of aquaculture in China, the environmental problems caused by the discharge of aquaculture tailwater are becoming more and more serious. The treatment of aquaculture tailwater has emerged as a crucial research area in recent years. At present, the main methods of aquaculture tailwater treatments include physical, chemical, and biological treatments, which are often combined in practical production. Based on the research status at home and abroad, the physical, chemical and biological technologies of aquaculture tail water treatment were summarized and analyzed, and the development trend of aquaculture tail water treatment technology in China was prospected, aiming to provide some references and directions for aquaculture tail water treatment.

With the intensification of global climate change and land salinization, improving the ability of rice (Oryza sativa L.) to grow in saline and alkaline environments has become a key challenge for agricultural production. The realization of the strategy of " the adaptation of germplasm to land " requires a deep understanding of the salt tolerance mechanism of rice, then breeding improvement on this basis. In this study, we summarized the recent research results on salt tolerance regulatory genes in rice, and classified them functionally according to the biological processes involved. The perception of salt stress in rice and the subsequent activation of various physiological regulatory mechanisms, including osmotic regulation, ion homeostasis, antioxidant defense system and nutrient balance, were analyzed in detail. In this review, we focus on several key Salt stress signaling pathways in rice, including the SOS (Salt Overly Sensitive) pathway, MAPK (Mitogen-Activated Protein Kinase) cascade pathway and hormone regulatory pathway. These pathways play crucial roles in rice adaptation salt stress environment. By reviewing the existing literature, this review aims to provide a comprehensive overview of the salt tolerance regulatory genes and their functions in rice, provide scientific basis on breeding salt-tolerant rice on these grounds, and as a reference in improving the yield and quality of rice under saline and alkaline environments.

Auxin is an important regulatory factor in the process of plant growth and development, and plants achieve their own growth and development through the regulation of auxin. As a member of the early auxin response gene family, the SAUR gene family is one of the indispensable regulatory factors in the auxin signal transduction pathway. In order to study the role of SAUR genes in biological processes such as plant growth and development and stress response, the bioinformatics characteristics, expression patterns, and regulatory mechanisms of the SAUR gene family were analyzed. The functions of SAUR genes in plant cell elongation growth, light-mediated cotyledon and apical hook opening, flower organ formation, fruit development, and stress response were summarized. It was pointed out that SAUR genes not only affected plant growth and development in multiple aspects, but also participated in the response of plants to abiotic stress. This study provides a theoretical basis for future research on the molecular mechanisms of SAUR genes and the cultivation of plant varieties.

产单核细胞李氏杆菌是一种常见的食源性致病菌，其致死率高达30%。该菌能够在高盐度、高酸度和冷藏温度等极端条件下存活和增殖，对人畜健康构成了重大威胁。然而抗生素的滥用导致药物残留和多重耐药性等问题的出现，从而使得李氏杆菌病的防治异常困难。噬菌体相关生物制剂的发展为解决以上问题提供了可行方案。本文综述了李氏杆菌噬菌体在食品保鲜、生物检测、基因工程等方面的应用，同时还探讨了噬菌体与宿主之间的互作机制，旨在为李氏杆菌噬菌体在食品污染防控中提供一定的理论依据。

Wheat is the most important cereal crop, and drought is the most significant abiotic stress factor that severely affects wheat growth and development. Plant root system, as a primary organ for crops to acquire water and nutrients, directly determines the efficiency of soil water utilization. In recent years, increasing evidence has shown that plant root system architecture (RSA) plays an important role in plant tolerance to drought stress. This review summarizes the current research progress on the regulation of wheat drought tolerance determined by RSA. First, we present how root tropism especially root gravitropism shapes the RSA, summarize the relevant genes and molecular regulatory mechanism involved in root gravitropic growth, and explain how the root tropism-regulated RSA is implicated in wheat adaptation to drought stress. In addition to root tropic growth, the root development also participates in the RSA formation and the plant adaptability to drought stress. Therefore, this review further summarizes how wheat regulates root development to alter its root system morphology (including increasing root length, modifying lateral root number and root hair density, etc.), thereby enhancing its water acqusition from the soil and its adaption to drought environment. The identified genes involved in wheat root development under drought stress conditions are also systematically summarized. Furthermore, as the underground part of plants, the revelation of RSA has always been a challenging task, which hinders our understanding of the relationship between RSA and plant drought tolerance. Therefore, this review also summarized the available techniques used to analyze the RSA at two- and three-dimension levels. These techniques can measure and analyze wheat root length, density, growth direction, and morphology parameters, laying technical support for an insightful understanding of the relationship between wheat RSA and drought resistance. Finally, we discuss the prospect of the improvement of RSA in breeding wheat drought-resistant varieties, as well as provide an outlook for how to identify genes regulating wheat RSA and pinpoint their regulatory mechanism. In summary, the relationship between wheat RSA and drought resistant is closely associated. The continuous development of sequencing techniques, along with the deepening research on the regulatory mechanism of wheat RSA, will provide new means and strategies for the further breeding of drought-tolerance wheat varieties.

To improve soil nutrient utilization efficiency and deal with single manure application problems such as dosage, fertilizer efficiency, and nutrient leaching, “biochar”, “compost”, “biochar manure application”, “soil properties” and “crop nutrients” were used as keywords to search and summarize relevant literatures on sources of Web of Science, Google Scholar, China National Knowledge Internet and others. The results showed that: (1) biochar improved the maturity of composting, increased the abundance of microbial communities, and reduced the risk of nutrient leaching in organic fertilizers, thus effectively reducing the environmental impact of traditional composting; (2) manure combined with biochar could improve soil moisture condition, and increase the contents of the available phosphorus and available potassium of different types of soils. Meanwhile, it could also provide better living materials and an environment for soil organisms and microorganisms; (3) the combination of biochar and organic fertilizer could increase the yield of crops and improve the contents of nitrogen, phosphorus and potassium, while different types of crops responded to them differently. The combined application of biochar and organic fertilizer enhanced soil fertility and plant nutrition, and its effect varied with the application rate, type of soil and crop and other factors. Our studies could provide a reference for efficient utilization of livestock and poultry manure resources in agricultural production.

Anoectochilus roxburghii is a rare and precious medicinal and ornamental plant of the Orchidaceae. It is favored by people for the rich variety of medicinal and nutritional components, and its market demand has been increasing in recent years. In order to promote the industrial development and basic research of A. roxburghii, this paper summarizes previous studies on A. roxburghii research, briefly compares the phylogenetic differences of Anoectochilus, focus on the research results of genomics (structural genomics/functional genomics) and adversity (biotic/abiotic interaction) response, analyzes the main factors affecting the quality of A. roxburghii (processing methods, cultivation models, strains). This paper systematically reviews the studies on germplasm resources, genomics, environmental interaction, quality difference and embryo reproduction that have not been carried out in depth, and puts forward corresponding strategies and prospects for the main problems and the solutions. It provides a feasible reference for the molecular biology research of precious medicinal plants in the era of big data.

Sorghum is the fifth largest grain crop in the world and can be used for food, feed, brewing and bioenergy. Sorghum genetic transformation technology is an essential and important tool in the research of sorghum functional genomics and can also serve as an important complement to traditional breeding methods. In this review, we summarize the research progress of sorghum transformation in recent years, analyze the problems in sorghum genetic transformation and propose strategic solutions to them in order to provide a reference for further improvement of sorghum genetic transformation technology. By summarizing more than 50 literatures on sorghum tissue culture and genetic transformation in recent years, we introduced the current research status of sorghum genotypes, explant sources, and regeneration system construction for genetic transformation, and compared the advantages and disadvantages of four commonly used methods for sorghum genetic transformation: electroporation, pollen-mediated transformation, particle bombardment and Agrobacterium-mediated transformation, summarized the effects of the main components of genetic transformation vectors, including promoters, target genes, selective marker genes and reporter genes, on transformation efficiency, explained the current application status of sorghum genetic transformation, analyzed the main bottleneck problemns in sorghum genetic transformation technology, and studied countermeasures. Sorghum genotypes have a significant influence on tissue culture and P898012 and Tx430 are the most widely used. Gene bombardment and Agrobacterium-mediated transformation are the most commonly used methods for sorghum genetic transformation, and the advantages of Agrobacterium-mediated transformation are gradually emerging. In vector construction, CaMV35S and ubi1 are the most commonly used promoters, and antibiotic resistance genes (nptII, hpt), herbicide resistance genes (bar), and nutrient assimilation genes are the three commonly used selection markers. With the development of sorghum genetic transformation technology and CRISPR/Cas9-mediated gene editing technology, some genes with important agronomic traits have been successfully transferred into sorghum. However, strong genotype dependence, long tissue culture cycle, and poor genetic transformation stability are the main bottlenecks that limit the genetic transformation of sorghum. By introducing morphogenesis regulatory factors, somatic cell generation can be directly performed, which shortens the tissue culture cycle, improves the transformation efficiency, and expands the source of explants. This has become a major breakthrough in sorghum genetic transformation technology. The use of morphogenesis regulatory factors and adoption of cut-dip-budding (CDB) delivery system can further improve the sorghum genetic transformation technology. Combined with the application of CRISPR/Cas9 gene editing technology, they will surely provide an important technical basis for the sorghum molecular breeding and gene function identification.

【Objective】 Livestock production is one of the important emission sources of greenhouse gases, while China is a major country in pig farming. Scientifically assessing the carbon footprint of pig farming system can provide a reference for further promoting carbon emission reduction of animal husbandry. 【Method】 This paper reviewed the research status of carbon footprint assessment of pig breeding system, including model, results and composition. The results of carbon footprint assessment were related to many factors, such as system boundary, emission sources, accounting methods and functional unit. In this study, we considered the main factors which affect the evaluation results, and analyzed the reasons for the difference of results. 【Result】 Through reviewing the domestic and foreign literature on carbon footprint assessment, it was realized that the assessment model of livestock had been constructed well in developed country. The carbon footprint of 1 kg functional unit product was 2.2-10.3 kg CO_2-eq. The assessment results varied due to the different evaluation methods in various studies. Different system boundaries and functional units were the important reasons for different results. The different emission sources, accounting parameters selected for the same emission source, or diverse allocation methods under the same system boundary also led to great differences. For the contribution to the carbon footprint of the pig production system, feed production was the largest link, accounting for 49%-83%; the second was manure management, accounting for 12%-41%. 【Conclusion】 In order to widely precise the carbon footprint of China’s pig production system, the suggestions were as follows: monitoring the key parameters of greenhouse gas emissions for various feeding modes in all regions of China should be carried out; the Chinese carbon footprint assessment database according to the development status of Chinese pig breeding systems should be established; the unified and standardized evaluation methods should be appeared publicly; an carbon footprint assessment model fit for different regions of Chinese production practice should be created to provide data reference support for the sustainable development of Chinese pig production system.

The area of saline alkali land in China accounts for one tenth of the total area of saline alkali land in the world, which seriously restricts agricultural production. It is very important to repair and make good use of saline alkali land. At present, the methods of saline-alkali land remediation include chemical remediation, engineering remediation and bioremediation, among which bioremediation is an economical, efficient, green and sustainable method. Bioremediation improves the soil and environment of saline-alkali land through biological resources such as plants and microorganisms. Halophytes can grow and reproduce in saline-alkali soil and have the ability to repair high concentration saline-alkali soil, while common crops can enhance their salt tolerance through gene mining and variety cultivation to achieve the purpose of repairing saline-alkali soil. Microorganisms can also be used to improve crop salt tolerance or degrade salt and alkaline substances in saline-alkali soil. Bioremediation is a green and environmentally friendly method for the remediation of saline-alkali land, which is in line with the development strategy of sustainable agriculture and circular economy in China.

Pre-harvest sprouting (PHS) refers to the germination of cereal crops on the spike in high humidity conditions before grain harvest. Wheat PHS is a significant problem that affects both the yield and quality of wheat. Seed dormancy level is a major factor influencing the resistance of wheat PHS, and domesticated crops often exhibit reduced seed dormancy levels, making cultivated wheat more prone to PHS compared to its wild ancestors. Wheat PHS is mainly regulated by external environmental factors such as temperature and humidity, as well as internal plant hormones (GAs, ABA, IAA, MeJA, ET, BR). Researchers have identified a range of materials resistant to PHS, cloned key genes regulating PHS resistance, such as PM19, MFT, MKK3, Myb10-3D, Vp1. New wheat materials resistant to PHS have been successfully developed through molecular marker-assisted selection, artificial synthesis of wheat, and CRISPR/Cas9 gene editing technology. This article reviews the genetic mechanism of PHS resistance in wheat and the latest progress in PHS resistance breeding research. In the future, it is necessary to continue exploring key genes related to PHS resistance, and employ biotechnological breeding methods to cultivate new PHS-resistant wheat varieties.

In order to provide new treatment methods and strategies for clinical prevention and treatment of Pseudomonas aeruginosa infection, the inherent resistance, acquired resistance and adaptive resistance of Pseudomonas aeruginosa are summarized in this paper. With the mechanisms of different resistance, the characteristics, development trends and treatment methods of Pseudomonas aeruginosa resistance under different situations are also analyzed. This paper points out that Pseudomonas aeruginosa resistance mainly depends on its high level of inherent and acquired resistance, while its adaptive resistance mainly depends on the formation of biofilm mediation and quorum sensing. It is proposed that clinical Pseudomonas aeruginosa resistance is not the result of a single resistance. In all, the most effective treatment strategy in the future is to carry out combination therapy based on traditional treatment and new treatment.

Cotton is the most important cash crop in Xinjiang, and southern Xinjiang is the main cotton production area, which yield accounts for 80% of the whole Xinjiang. For a long time, the planting mode of "wet sowing and dry emergence" was widely adopted in the cotton areas of southern Xinjiang, which meant that in addition to conventional irrigation during the cotton growth period, winter irrigation and spring irrigation were also needed to play a role in pressing salt and improving soil moisture during the sowing period. However, with the continuous expansion of cultivated land area and the increasing shortage of water resources, the cotton production of southern Xinjiang began to try the cultivation method in northern Xinjiang of "dry sowing and wet emergence" to grow cotton, but the overall effect was not ideal. Through the literature review, this paper tries to explore the reasons for the ineffective implementation of the "dry sowing and wet emergence" cultivation method in southern Xinjiang, and puts forward possible solution strategies on this basis.

Chalkiness is one of the important indexes to evaluate the appearance quality of rice. It is a bad character that seriously affects the grinding, appearance and taste quality of rice, and plays an important role in the market value evaluation of rice. This paper summarized the effects of environmental factors, physiological mechanisms and genetic mechanisms on the formation of chalkiness in rice, and pointed out the difficulties existing in the improvement of chalkiness in rice breeding. Based on the current research results and the development of related technologies, some suggestions for improvement were put forward to provide a certain research basis for the production of high-quality rice.

随着测序技术的发展，大量组学测序技术不断涌现并得以推广，产生了包括基因组、表观基因组、转录组、蛋白质组、代谢组、微生物组等大量的组学数据。这些数据对深入研究和揭示畜禽重要经济性状(生长性状、繁殖性状、肉质性状、抗病性状等)的复杂调控过程具有重要意义。仅通过单一层面的组学无法揭示畜禽重要经济性状的复杂性，而多组学技术可以系统解析畜禽重要经济性状的机理和表型，并逐渐成为研究畜禽重要经济性状的主要方法。本文综述了多组学技术的方法、优点及其在畜禽重要经济性状研究中的应用，旨在对畜禽重要经济性状的研究提供参考和思路。

[Objective] It is of great significance to improve the efficiency and accuracy of crop pest detection in complex natural environments, and to change the current reliance on expert manual identification in the agricultural production process. Targeting the problems of small target size, mimicry with crops, low detection accuracy, and slow algorithm reasoning speed in crop pest detection, a complex scene crop pest target detection algorithm named YOLOv8-Entend was proposed in this research. [Methods] Firstly, the GSConv was introduecd to enhance the model's receptive field, allowing for global feature aggregation. This mechanism enables feature aggregation at both node and global levels simultaneously, obtaining local features from neighboring nodes through neighbor sampling and aggregation operations, enhancing the model's receptive field and semantic understanding ability. Additionally, some Convs were replaced with lightweight Ghost Convolutions and HorBlock was utilized to capture longer-term feature dependencies. The recursive gate convolution employed gating mechanisms to remember and transmit previous information, capturing long-term correlations. Furthermore, Concat was replaced with BiFPN for richer feature fusion. The bidirectional fusion of depth features from top to bottom and from bottom to top enhances the transmission of feature information acrossed different network layers. Utilizing the VoVGSCSP module, feature maps of different scales were connected to create longer feature map vectors, increasing model diversity and enhancing small object detection. The convolutional block attention module (CBAM) attention mechanism was introduced to strengthen features of field pests and reduce background weights caused by complexity. Next, the Wise IoU dynamic non-monotonic focusing mechanism was implemented to evaluate the quality of anchor boxes using "outlier" instead of IoU. This mechanism also included a gradient gain allocation strategy, which reduced the competitiveness of high-quality anchor frames and minimizes harmful gradients from low-quality examples. This approach allowed WIoU to concentrate on anchor boxes of average quality, improving the network model's generalization ability and overall performance. Subsequently, the improved YOLOv8-Extend model was compared with the original YOLOv8 model, YOLOv5, YOLOv8-GSCONV, YOLOv8-BiFPN, and YOLOv8-CBAM to validate the accuracy and precision of model detection. Finally, the model was deployed on edge devices for inference verification to confirm its effectiveness in practical application scenarios. [Results and Discussions] The results indicated that the improved YOLOv8-Extend model achieved notable improvements in accuracy, recall, mAP@0.5, and mAP@0.5:0.95 evaluation indices. Specifically, there were increases of 2.6%, 3.6%, 2.4% and 7.2%, respectively, showcasing superior detection performance. YOLOv8-Extend and YOLOv8 run respectively on the edge computing device JETSON ORIN NX 16 GB and were accelerated by TensorRT, mAP@0.5 improved by 4.6%, FPS reached 57.6, meeting real-time detection requirements. The YOLOv8-Extend model demonstrated better adaptability in complex agricultural scenarios and exhibited clear advantages in detecting small pests and pests sharing similar growth environments in practical data collection. The accuracy in detecting challenging data saw a notable increased of 11.9%. Through algorithm refinement, the model showcased improved capability in extracting and focusing on features in crop pest target detection, addressing issues such as small targets, similar background textures, and challenging feature extraction. [Conclusions] The YOLOv8-Extend model introduced in this study significantly boosts detection accuracy and recognition rates while upholding high operational efficiency. It is suitable for deployment on edge terminal computing devices to facilitate real-time detection of crop pests, offering technological advancements and methodologies for the advancement of cost-effective terminal-based automatic pest recognition systems. This research can serve as a valuable resource and aid in the intelligent detection of other small targets, as well as in optimizing model structures.

【目的】试验旨在研究抗鸭甲肝病毒基因3型(Duck hepatitis A virus genotype 3,DHAV-3)的北京鸭专门化品系(即抗性品系Z7-R)与DHAV-3易感品系(Z7-S)的脂质代谢轮廓,并筛选品系间差异脂质标志物。【方法】选取2日龄Z7系DHAV-3抗性北京鸭和易感北京鸭各6只,采集血液与肝脏组织,进行血液生化指标测定与基于液相色谱-质谱联用技术(LC-MS)的非靶向肝脏脂质组检测。采用t检验、偏最小二乘分析(PLS-DA)和差异倍数(FC)综合筛选品系间显著差异脂质。【结果】Z7-R系北京鸭血浆总胆固醇、低密度脂蛋白和磷脂含量均显著高于Z7-S系(P<0.05)。脂质组分析共鉴定到1 532个脂质代谢物,涵盖了脂肪酰(FA)、甘油酯(GL)、甘油磷脂(GP)、鞘脂(SP)、固醇脂(ST)5个大类。共筛选到84个显著差异脂质,其中甘油酯类主要为甘油三酯(TG),且Z7-R系含量均高于Z7-S系(P<0.05);甘油磷脂类主要为溶血磷脂酰胆碱(LPC)、溶血磷脂酰乙醇胺(LPE)和游离脂肪酸(FFAs),且Z7-R系含量均低于Z7-S系(P<0.05)。共筛选到10个显著差异的脂质显著富集到鞘脂代谢、甘油磷脂代谢、甘油酯代谢、亚油酸代谢和α-亚麻酸代谢通路中。【结论】脂质组学技术可用于区分北京鸭Z7-R系与Z7-S系,筛选到的10个显著差异脂质物质可作为潜在的DHAV-3抗性与易感性状相关生物标志物。

Agro-ecosystem is not only one of the important contributors to greenhouse gases, but also plays an important role in carbon sequestration and emission reduction. Under the background of “CO₂ emission peak” and “carbon neutrality”, agro-ecosystem has great potential for carbon sequestration and emission reduction. In this paper, we mainly reviewed the sources, fixed pathways, and influencing factors of main greenhouse gases in China’s typical agro-ecological types. Meantime, the specific contents were discussed including the existing research results, emission reduction potential and existing problems of carbon sequestration and emission reduction in agro-ecosystem. New research directions and exploration approaches were summarized to promote the research in the field of carbon sequestration in the entire agroecological system. It provided an important theoretical reference for China to further carbon sequestration and emission reduction, sustainable development of agriculture, and the realization of the “double carbon” goal as soon as possible.

[Objective] To effectively tackle the unique attributes of wheat leaf pests and diseases in their native environment, a high-caliber and efficient pest detection model named YOLOv8-SS (You Only Look Once Version 8-SS) was proposed. This innovative model is engineered to accurately identify pests, thereby providing a solid scientific foundation for their prevention and management strategies. [Methods] A total of 3 639 raw datasets of images of wheat leaf pests and diseases were collected from 6 different wheat pests and diseases in various farmlands in the Yuchong County area of Gansu Province, at different periods of time, using mobile phones. This collection demonstrated the team's proficiency and commitment to advancing agricultural research. The dataset was meticulously constructed using the LabelImg software to accurately label the images with targeted pest species. To guarantee the model's superior generalization capabilities, the dataset was strategically divided into a training set and a test set in an 8:2 ratio. The dataset includes thorough observations and recordings of the wheat leaf blade's appearance, texture, color, as well as other variables that could influence these characteristics. The compiled dataset proved to be an invaluable asset for both training and validation activities. Leveraging the YOLOv8 algorithm, an enhanced lightweight convolutional neural network, ShuffleNetv2, was selected as the basis network for feature extraction from images. This was accomplished by integrating a 3×3 Depthwise Convolution (DWConv) kernel, the h-swish activation function, and a Squeeze-and-Excitation Network (SENet) attention mechanism. These enhancements streamlined the model by diminishing the parameter count and computational demands, all while sustaining high detection precision. The deployment of these sophisticated methodologies exemplified the researchers' commitment and passion for innovation. The YOLOv8 model employs the SEnet attention mechanism module within both its Backbone and Neck components, significantly reducing computational load while bolstering accuracy. This method exemplifies the model's exceptional performance, distinguishing it from other models in the domain. By integrating a dedicated small target detection layer, the model's capabilities have been augmented, enabling more efficient and precise pest and disease detection. The introduction of a new detection feature map, sized 160×160 pixels, enables the network to concentrate on identifying small-targeted pests and diseases, thereby enhancing the accuracy of pest and disease recognition. Results and Discussion The YOLOv8-SS wheat leaf pests and diseases detection model has been significantly improved to accurately detect wheat leaf pests and diseases in their natural environment. By employing the refined ShuffleNet V2 within the DarkNet-53 framework, as opposed to the conventional YOLOv8, under identical experimental settings, the model exhibited a 4.53% increase in recognition accuracy and a 4.91% improvement in F₁-Score, compared to the initial model. Furthermore, the incorporation of a dedicated small target detection layer led to a subsequent rise in accuracy and F₁-Scores of 2.31% and 2.16%, respectively, despite a minimal upsurge in the number of parameters and computational requirements. The integration of the SEnet attention mechanism module into the YOLOv8 model resulted in a detection accuracy rate increase of 1.85% and an F₁-Score enhancement of 2.72%. Furthermore, by swapping the original neural network architecture with an enhanced ShuffleNet V2 and appending a compact object detection sublayer (namely YOLOv8-SS), the resulting model exhibited a heightened recognition accuracy of 89.41% and an F₁-Score of 88.12%. The YOLOv8-SS variant substantially outperformed the standard YOLOv8, showing a remarkable enhancement of 10.11% and 9.92% in accuracy, respectively. This outcome strikingly illustrates the YOLOv8-SS's prowess in balancing speed with precision. Moreover, it achieves convergence at a more rapid pace, requiring approximately 40 training epochs, to surpass other renowned models such as Faster R-CNN, MobileNetV2, SSD, YOLOv5, YOLOX, and the original YOLOv8 in accuracy. Specifically, the YOLOv8-SS boasted an average accuracy 23.01%, 15.13%, 11%, 25.21%, 27.52%, and 10.11% greater than that of the competing models, respectively. In a head-to-head trial involving a public dataset (LWDCD 2020) and a custom-built dataset, the LWDCD 2020 dataset yielded a striking accuracy of 91.30%, outperforming the custom-built dataset by a margin of 1.89% when utilizing the same network architecture, YOLOv8-SS. The AI Challenger 2018-6 and Plant-Village-5 datasets did not perform as robustly, achieving accuracy rates of 86.90% and 86.78% respectively. The YOLOv8-SS model has shown substantial improvements in both feature extraction and learning capabilities over the original YOLOv8, particularly excelling in natural environments with intricate, unstructured backdrops. Conclusion The YOLOv8-SS model is meticulously designed to deliver unmatched recognition accuracy while consuming a minimal amount of storage space. In contrast to conventional detection models, this groundbreaking model exhibits superior detection accuracy and speed, rendering it exceedingly valuable across various applications. This breakthrough serves as an invaluable resource for cutting-edge research on crop pest and disease detection within natural environments featuring complex, unstructured backgrounds. Our method is versatile and yields significantly enhanced detection performance, all while maintaining a lean model architecture. This renders it highly appropriate for real-world scenarios involving large-scale crop pest and disease detection.

To comprehensively understand the current status and development trend of quinoa research at home and abroad in the past decade, this paper used bibliometric methods to comprehensively study the relevant literature on quinoa research, which were retrieved from the China National Knowledge Infrastructure (CNKI) Chinese Journal Full-text Database and Web of Science (WOS) Core Collection Database from 2012 to 2022. The year of publication, research institutions, journal distribution, and subject field distribution of the literature were statistically analyzed, and the main research frontiers and hotspots of quinoa at home and abroad were summarized by keyword co-occurrence network analysis. The results show that quinoa research has been growing rapidly since 2013, “The International Year of Quinoa”, and has been in a period of rapid growth in the past three years. Although the research on quinoa started late in China, the number of published papers has surpassed that of the European and American countries, ranking first in the world. However, the paper quality needs to be further improved, and the average citation frequency is ranked after Germany, Italy, Chile, the United States and Spain. Foreign research institutions are mainly distributed in the origin area of quinoa in South America and developed countries in Europe and North America, while domestic research institutions are mainly concentrated in the quinoa planting areas such as Northwest China and North China. The distribution of journals is mainly in the field of food science, and the research hotspots are mainly focused on breeding and cultivation, nutritional quality, and processing characteristics. As a kind of healthy grain, quinoa is emerging in China, and promoting its industrialization has broad development prospects and application space.

Crop variety identification is an important guarantee for breeding and promoting excellent varieties, and the appropriate detection method is the key for the accurate identification of varieties. With the development of molecular marker techniques, the third-generation molecular marker SNP has gradually been applied in the field of variety identification. This paper outlines the characteristics of SNP molecular markers, analyses the features and applicability of five commonly used high-throughput detection methods in crop research, including high resolution melting, competitive allele specific PCR, gene chips, sequencing and genotyping by target sequencing. The research and application of SNP markers in the identification of variety authenticity, purity testing, and analysis of genetic relationships and classification are summarized as well, in order to provide technical reference for subsequent variety identification.

The basement membrane is a specialized structure of extracellular matrix, which exists in most tissues. It not only provides supporting structure for various cell types such as epithelial cells, endothelial cells, nerve cells, muscle cells, but also plays an important role in maintaining the tissue structure and function. Matrigel is the soluble basement membrane preparation extracted from the mouse Engelbreth-Holm-Swarm (EHS) tumors rich in extracellular matrix protein. It contains almost all components of the basement membrane and can mimic its biological properties, which becomes the crucial biological material for many experimental models in life science research, especially the important media of organoids. In this review, the biological characteristics of matrigel, its extraction and preparation technology, and its main uses are summarized, and its potential application fields and values are discussed. Additionally, the current status of its production both at home and abroad and the existing problems are analyzed, and the future development trend of matrigel production is prospected. This study aims to provide reference for the development and application of matrigel in China.

Digital soil mapping is a novel and efficient soil mapping technique that utilizes 3S technology and is theoretically based on soil formation science, geography and mathematics. Domestic and foreign scholars had conducted extensive research on the generation of environmental collaborative variables, the acquisition of sample data, the selection of digital soil mapping models or methods, and the generation and validation of soil maps, especially on mapping methods. This paper introduced five categories of digital soil mapping techniques, including geostatistical methods, deterministic interpolation, mathematical statistics, machine learning, and expert knowledge models. At the same time, the mapping method suitable for the study area was chosen based on the merits of various approaches, from the aspects of target variables, topography and geomorphological features, sample density and distribution status and more. The future development direction of digital soil mapping included incorporating human activity factors into environmental synergistic variables; establishing more effective sampling methods based on machine learning and data mining; the application of new modeling methods (deep learning and multimodal methods).

遗传评估软件在动物领域的应用极大地提高了育种工作效率。随着基因组测序技术不断完善和人工智能技术的兴起，动物遗传评估软件也得到了快速的发展。本文首先介绍了常规育种和基因组育种在动物育种领域的应用，然后重点回顾了GBLUP方法、贝叶斯方法和机器学习以及深度学习方法的全基因组遗传评估软件的特点和发展历史，最后展望了计算机软件在动物遗传评估育种中的未来发展趋势，旨为动物育种领域的研究人员提供相关遗传评估软件的参考。

As the main matters of polyphenolic compounds in tea, catechins have free radical elimination, anti-aging, anti-radiation, weight loss, blood lipid reduction, cancer prevention and other active functions, accounting for 12%~24% of the tea. Due to the special variety and processing technology, the catechin content in Pu 'er tea is higher than other tea varieties, which shows excellent efficacy in terms of nutritional value and health care. This paper mainly describes the types of catechin, extraction measurement methods, content variations and efficacy researches of Pu 'er tea, so as to provide reference for the further development and utilization of functional catechin products in Pu' er tea.

In order to analyze the research progress and dynamics of denitrifying bacteria, we analyzed the research overview and development trend of denitrifying bacteria from 1990 to 2022 based on the core database of Web of Science, using tools such as VOSviewer and Citespace. The field has experienced three processes of origin, exploration and development. There are many countries involved but the cooperation is weak, among which the European countries have stronger regional cooperation and higher quality of publications; although China started late, it has developed rapidly, with a large number of publications but insufficient influence; among the core authors, academician Peng Yongzhen of China has published the most articles; and there is less cooperation and communication among the core authors. The keywords present three types of "tool-object-method", and the current research is mainly concerned with the performance of biological denitrification and dedicated to improving the denitrification efficiency of wastewater. Future research will pay more attention to the deepening and expansion of nitrogen oxide emission, the screening of new denitrifying bacteria, the development and application of denitrifying agents, research on simultaneous nitrification and denitrification, and removal of nitrate nitrogen.

【Objective】 This study aimed to investigate the impact of cover crops (wheat and common vetch) on the growth of Chinese cabbage seedlings and the structure of the soil microbial community. The findings could provide the theoretical and technical support for using wheat and common vetch cover crops to alleviate continuous cropping obstacles in Chinese cabbage production. 【Method】In this experiment, there were four treatments: wheat cover crop treatment (W), common vetch cover crop treatment (P), mixture of wheat and common vetch treatment (WP), and no cover crop treatment (CK). The effects of different cover crop treatments on the growth of Chinese cabbage seedlings were studied. Moreover, the effects of wheat and common vetch cover crops on the microbial community of Chinese cabbage rhizosphere were also investigated through qPCR and Illumina MiSeq techniques. In addition, Spearman correlation analysis was conducted to identify the key soil microbial taxa related to Chinese cabbage growth. Then, the changes in soil chemical properties on soil microbial community structure were explored by environmental factor correlation analysis. 【Result】Compared with CK, the cover crop treatments had positive effects on Chinese cabbage growth and decreased soil electrical conductivity (EC) value. The mixed cover crop treatment significantly decreased soil available potassium content, whereas wheat cover crop treatment increased soil pH. The qPCR results showed that the abundance of soil bacterial community was not significantly affected by the cover crop treatment, but increased the abundance of soil fungal community. Both common vetch cover crop treatment and mixed wheat and common vetch cover crop treatment significantly reduced the abundances of Bacillus spp. and Pseudomonas spp. communities. The Illumina MiSeq analysis showed that the relative abundance of genus TM7a was significantly increased by cover treatments, while the relative abundances of Leptolyngbya_EcFYyyy-00, Lophotrichus, Acaulium, and Sodiomyces were decreased. The mixed cover crop treatment significantly increased the relative abundance of Sphingomonas and Massilia and significantly decreased the relative abundance of Fusarium. Spearman correlation analysis showed that Sphingomonas, TM7a, Massilia, and Gemmatimonas were positively correlated with growth. Leptolyngbya_EcFYyyy-00, Acaulium, Lophotrichus, Sodiomyces, and Fusarium were significantly negatively correlated with the growth of Chinese cabbage. Moreover, these cover crop treatments influenced bacterial and fungal diversity indices. The Shannon index and inverse Simpson index for soil bacterial community and Shannon index of soil fungal community significantly decreased in cover common vetch treatment. In contrast, the inverse Simpson index of soil fungal community was increased. The mixed cover crop treatment increased the fungal Shannon index, while the inverse Simpson index of soil fungal community decreased. Principal Coordinates Analysis (PCoA) showed significant differences in soil microbial community structure, with soil EC value as a major environmental factor affecting the structure.【Conclusion】The cover crop treatments exhibited growth-promoting effects on Chinese cabbage seedlings, and the best effect was found in the mixed cover crop treatment. The relative abundances of some Sphingomonas, TM7a, Massilia, other potential growth-promoting bacteria were increased in the cover crop treatments. The relative abundances of some potential plant pathogens Leptolyngbya_EcFYyyy-00 and Fusarium were decreased and the relative abundance of potential biocontrol agent Chaetomium was increased in the mixed cover crop treatment.

In order to understand current status and hot issues of rural habitat environment at home and abroad, using CiteSpace literature analysis software, an analysis of those research literatures about rural habitat environment selected from 2002 to 2022 China Knowledge Network (CNKI) and Web of Science core collection database was carried out, and a knowledge map of rural habitat environment research at home and abroad was drawn. The results show that: (1) the number of publications abroad is more than that in China, and the research theories are richer; the cooperation network of research between authors abroad is closer than that in China, indicating more interdisciplinary exchanges; the main publishing institutions at home and abroad are concentrated in universities; the US and China are the main publishing countries. (2) The domestic researches mainly focus on the hard and soft environment of rural areas, including those topics around "rural revitalization", "new rural areas", "rural governance" and "rural development". While the researches abroad focus on the impact of rural habitat on villagers, the topics are mainly around "climate change", "mental health", "physical activity" and "infectious diseases". In the future, the combination of theory and practice in rural habitat research should be further strengthened, and both qualitative and quantitative research methods should be emphasized. Moreover, the depth and breadth of rural habitat research will be expanded based on a multidisciplinary perspective.

【Objective】 Mining the key drought-resistant genes of maize, revealing its drought-resistant molecular mechanism, and providing genetic resources and theoretical guidance for the cultivation of new drought-resistant maize varieties.【Method】Transcriptome data combined with weighted gene co-expression network (WGCNA) and screening methods for physiological and biochemical indicators of drought resistance were used to identify ZmPAL genes associated with drought resistance and rewatering. Genome-wide analysis of the genes encoding PAL was performed using bioinformatics methods. Quantitative real-time fluorescence PCR (qRT-PCR) was used to detect the expression of ZmPAL genes under drought treatment conditions, as well as the expression characteristics of ZmPAL5 among different inbred lines and the expression patterns in different tissues. Finally, genetic transformation was used to analyze the drought resistance function of ZmPAL5 in maize, and the deletion-type Arabidopsis mutant was analyzed for drought resistance with the help of CRISPR/Cas9 technology for the PAL5 homologous gene.【Result】Nineteen maize ZmPAL genes were identified, six of which were clustered on chromosome 5 and encoded proteins that were mostly hydrophilic acidic proteins and relatively evolutionarily conserved in the PAL family of genes. The promoter region of ZmPAL genes contained a large number of cis-acting elements associated with hormonal and abiotic stress responses. Six core genes were identified, four of which were significantly up-regulated for expression after drought treatment. In particular, ZmPAL5 showed an 8.57-fold increase in expression after drought stress. The expression level of ZmPAL5 was found to be significantly higher in the drought-resistant inbred line Zheng 8713 than in the drought-sensitive inbred line B73 under both drought stress and rewatering treatments. Meanwhile, ZmPAL5, a constitutively expressed gene, showed a high level of expression in young stems. Overexpressed ZmPAL5 maize grew well under drought stress, and its relative water content, lignin, chlorophyll, soluble protein, proline content, and activities of superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase were 1.52, 1.49, 1.47, 1.43, 1.44, 1.41, 1.53, 1.41, and 1.35 times, but the malondialdehyde content was 0.65 times that of the wild type. The PAL5-deficient Arabidopsis mutant was sensitive to drought. Under drought stress, its physiological and biochemical indexes showed the opposite trend to those of overexpression of ZmPAL5 maize. 【Conclusion】 Six core genes (ZmPAL3, ZmPAL5, ZmPAL6, ZmPAL8, ZmPAL11, and ZmPAL13) were screened in response to drought stress, in which the expression of ZmPAL5 was positively correlated with drought resistance. ZmPAL5 positively regulated the drought resistance and resilience of the plant by influencing the content of osmotically regulated substances and antioxidant enzyme activities.

This study focuses on evaluating the application of anaerobic digestion technology in the treatment of organic waste, conversion into renewable energy and organic fertilizers, and exploring the mitigation effects of that on the environment. The effects of temperature, carbon to nitrogen ratio, organic loading rate, volatile fatty acids, hydraulic residence time and pH on the efficiency and stability of anaerobic digestion were analyzed by literature review. The results show that these parameters have significant effects on promoting microbial activity, accelerating organic decomposition and maintaining stable operation of the system. The effectiveness of anaerobic digestion technology is verified by the typical studies of organic wastes such as corn stalks, livestock manure and food waste, and the structure and function of key microbial communities in the process are elaborated, including the mechanisms of action of bacteria and archaea at different stages such as hydrolysis, acidification, acetogenesis and methanogenesis. In addition, the generation of toxic substances and its management strategies are also discussed. Finally, the findings of this study suggest that improving the efficiency of anaerobic digestion, developing new reactor technologies, and strengthening research on microbial population will help make anaerobic digestion technology more efficient, stable, and widely applied in the future.

Chitosan is a natural, safe, and cheap product of chitin deacetylation, which is widely used in industry production due to its own features. In this paper, the function and application of chitosan and its nanoparticles in seed treatment, soil remediation and increasing efficiency of fertilizer and pesticide synergy were reviewed. Chitosan can be used for seed treatment and soil amendment, promoting plant growth and inducing plant tolerance to abiotic and biological stresses. In recent years, chitosan has also been used to synthesize chitosan nanoparticles, as carriers of fertilizers, pesticides, fungicides and microelements, in order to achieve the purpose of reducing stockpiles and increasing efficiency, and promote the sustainable development of agriculture. Finally, future research directions of chitosan and its nanoparticles in agriculture were prospected.

To enhance the efficient application of water-soluble fertilizers containing amino-acids in agricultural production, and to promote green, high-quality development of agriculture. The study reviewed the source and production technology of amino-acids raw material, the functional characteristics, the development status, the application in agricultural production and the future development trend of water-soluble fertilizers containing amino-acids. The results showed that water-soluble fertilizers containing amino-acids were widely used in food crops, vegetable crops, fruit crops and cash crops, had positive effects on crop growth, formation of fruit quality and soil improvement. However, the application of fertilizer on different crops needed to be further explored according to the growth and development rules and nutritional requirements of the plant. The water-soluble fertilizers containing single amino-acids cannot satisfy the market demand, it is necessary to develop new types of fertilizers combining function and nutrition of amino acids.

【Objective】The study investigated the impact of salicylic acid (SA) priming on the germination vigor and physiological response of rice seeds under low temperatures. It aimed to reveal the expression patterns of genes related to abscisic acid (ABA) and gibberellin (GA) metabolic pathways as well as cell wall relaxation genes by SA priming. This research provided a theoretical basis for the study of rice seed germination at low temperatures.【Method】Using indica three-line hybrid rice Taifengyou 208 seeds as materials, the effects of SA on seed germination vigor and physiology responses under low temperature were analyzed through seed priming treatment, and the expression patterns of genes related to ABA, GA and expansin in response to SA were analyzed by qRT-PCR.【Result】Low temperature (15 ℃) significantly delayed the germination process of rice seeds. In seeds germinated at low temperatures for one day, the endogenous SA concentration was 1.7 times higher than that at normal temperatures (28 ℃). However, for five-day-old seedlings, the SA concentration under low temperature was only 0.6% of that at normal temperatures. SA could effectively enhanced germination vigor of seeds at low temperature, with the most significant effects observed at 2 000 μmol·L^-1 SA. This concentration significantly increased the germination index, vigor index, shoot length, root length, fresh weight, and dry weight of seeds under low temperature conditions. Notably, the vigor index was three times that of non-primed seeds (CK1) and two times that of water-primed seeds (CK2). In terms of physiological indexes, SA priming increased the contents of soluble sugar, proline and active oxygen, enhanced the activities of total amylase, β-amylase, superoxide dismutase (SOD) and catalase (CAT), and decreased the content of malondialdehyde (MDA). Compared with CK1, 2 000 μmol·L^-1 SA decreased the ABA content by 79%, and increased the IAA and GA₁ contents by 32.2% and 2.66 times, respectively. In terms of gene expression, the expression levels of ABA synthesizing genes OsNCED2 and OsNCED3 were decreased by 94.26% and 90.24% compared with CK1 in seeds primed by 2 000 μmol·L^-1 SA, respectively, whereas the expression levels of ABA decomposing genes OsABA8’ox2 and OsABA8’ox3 were 5.9 and 3.9 times higher than that of CK1, respectively. Compared with CK1, SA priming significantly upregulated the expression of GA synthesizing genes OsCPS1, OsKAO and OsGA20ox1, while it significantly downregulated the expression of GA decomposing genes OsGA2ox2 and OsGA2ox6. In several candidate genes encoding cell wall relaxation protein, e.t. expansin, all but OsEXPB11 were significantly upregulated to some extent by priming. Compared with CK1, 2 000 μmol·L^-1 SA increased the expression levels of OsEXPA2, OsEXPB4 and OsEXPB6 to 12.2, 5.9 and 6.1 times, respectively.【Conclusion】SA priming can significantly alleviate the impact of low temperatures on rice seed germination and seedling growth, which is likely due to SA enhancing the activity of antioxidant enzymes such as SOD and CAT, reducing the production of MDA, and increasing the content of soluble sugars and proline, thereby strengthening the tolerance of seeds and seedlings to low temperatures. On the other hand, SA priming decreases endogenous ABA content, increases GA₁ content, enhances the activities of total amylase and β-amylase, and promotes the expression of genes related to cell wall relaxation, thus facilitating seed germination and seedling growth at low temperature.

Polyethylene (PE), as one of the most used plastics in the world, has widely existed in the natural environment because of its wear-resistant, high molecular weight and indestructible properties. PE would break down into microplastics (MPs) and accumulate in large quantities, and currently MPs has become an important pollutant that affects the ecosystem. Currently, many studies have been demonstrated that PE could be partially degraded, but further research is needed in screening of microorganisms or enzymes that could completely degrade PE and construct a complete biodegradation pathway for PE. Therefore, this paper summarizes the classification, recycle methods and characterization methods of PE, microorganisms and enzymes that degrade PE, biodegradation pathways and influencing factors, and proposes future research directions of PE biodegradation. These findings provide theoretical basis for the degradation mechanism of PE.