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.

Saline-alkali stress is one of the abiotic stresses in the process of plant growth and development, which can cause water deficit, changes in cell membrane permeability, metabolic disorders and blockage of protein synthesis in plants, resulting in crop yield reduction or death. Finding effective methods to reduce the harm of saline-alkali stress and strategies to improve the saline tolerance of plants are of great significance to the comprehensive utilization of saline land. In this paper, the latest researches on the damage and adaptive mechanism of plants under saline-alkali stress in recent years were summarized, and the physiological and molecular mechanisms of plants responding to saline-alkali stress were summed up. Furthermore, the physiological mechanisms of plants under saline-alkali stress were analyzed, which were mainly regulated by accumulating osmotic substances, increasing the activity of antioxidant enzymes and ionic compartmentalization, etc., and the molecular mechanisms were mainly regulated by signal transduction, transcription factor regulation and the expression of plant salt-tolerance-related gene, etc. This study pointed out the trends and urgent problems in the development of plant adaptation to saline-alkali environments, with a view to providing a certain theoretical basis for the selection and cultivation of saline and alkali tolerant plants.

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.

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.

Potassium, a quality element, is one of the essential nutrient elements in the process of plant growth. Too high or too low content of potassium in the environment will affect the normal growth of plants, reduce the yield and quality of plants in a way, even may lead to the death of plants. In order to solve the problem of potassium deficiency in soil and potassium nutrient stress in plants, this paper summarizes the general situation of potassium nutrient stress, the morphological characteristics of potassium nutrient stress, the influence of potassium nutrient stress on plants, the physiological and biochemical changes of potassium nutrient stress as well as the study of potassium nutrient stress in molecular level. The general situation of potassium nutrient stress is summarized from potassium, potassium nutrient stress and symptoms of potassium nutrient stress. The effects of potassium nutrient stress on plants are analyzed from growth and morphological changes, photosynthesis, nutrient absorption, osmotic adjustment and balance of reactive oxygen, yield and quality. It is concluded that the research on potassium nutrient stress in plants mainly focuses on the physiological and biochemical aspect as well as the mechanism of action, while the research on the molecular level is relatively little. The research progress of potassium nutrient stress on molecular level is emphasized, and the paper also clarifies that the research of potassium nutrient stress is important and significant. Three points of view are put forward, namely, future research should focus on the molecular physical and chemical properties of plants coping with plant potassium nutrient stress, suitable fertilizing methods and modes (according to local conditions and plant conditions), and research and development of fertilization tools.

Significance The fruit-picking robot stands as a crucial solution for achieving intelligent fruit harvesting and plays a pivotal role in the realm of smart agriculture. While significant progress has been made in developing foundational methods for picking robots, such as fruit recognition, orchard navigation, path planning for picking, and robotic arm control, the practical implementation of a seamless picking system that integrates sensing, movement, and picking capabilities still encounters substantial technical hurdles. As a result, the widespread commercial adoption of picking robots remains distant. In contrast to current picking systems, the next generation of picking robots aims to replicate the autonomous skills exhibited by human fruit pickers. This involves effectively performing ongoing tasks of perception, movement, and picking without human intervention. To tackle this challenge, this review delves into the latest research methodologies and real-world applications in this field. It critically assesses the strengths and limitations of existing methods and categorizes the essential components of continuous operation into three sub-modules: local target recognition, global mapping, and operation planning. Progress Initially, the review explores methods for recognizing nearby fruit and obstacle targets. These methods encompass four main approaches: low-level feature fusion, high-level feature learning, RGB-D information fusion, and multi-view information fusion, respectively. Each of these approaches incorporates advanced algorithms and sensor technologies for cluttered orchard environments. For example, low-level feature fusion utilizes basic attributes such as color, shapes and texture to distinguish fruits from backgrounds, while high-level feature learning employs more complex models like convolutional neural networks to interpret the contextual relationships within the data. RGB-D information fusion brings depth perception into the mix, allowing robots to gauge the distance to each fruit accurately. Multi-view information fusion tackles the issue of occlusions by combining data from multiple cameras and sensors around the robot, providing a more comprehensive view of the environment and enabling more reliable sensing. Subsequently, the review shifts focus to orchard mapping and scene comprehension on a broader scale. It points out that current mapping methods, while effective, still struggle with dynamic changes in the orchard, such as variations of fruits and light conditions. Improved adaptation techniques, possibly through machine learning models that can learn and adjust to different environmental conditions, are suggested as a way forward. Building upon the foundation of local and global perception, the review investigates strategies for planning and controlling autonomous behaviors. This includes not only the latest advancements in devising movement paths for robot mobility but also adaptive strategies that allow robots to react to unexpected obstacles or changes within the whole environment. Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. The review also identifies a crucial need for further advancements in the dynamic behavior and autonomy of these technologies, emphasizing the importance of continuous learning and adaptive control systems to improve operational efficiency in diverse orchard environments. Conclusions and Prospects The review underscores the critical importance of coordinating perception, movement, and picking modules to facilitate the transition from a basic functional prototype to a practical machine. Moreover, it emphasizes the necessity of enhancing the robustness and stability of core algorithms governing perception, planning, and control, while ensuring their seamless coordination: A central challenge that emerges. Additionally, the review raises unresolved questions regarding the application of picking robots and outlines future trends. These trends include deeper integration of stereo vision and deep learning, enhanced global vision sampling, and the establishment of standardized evaluation criteria for overall operational performance. It provides both technical and theoretical support for the eventual development of robust, autonomous, and commercially viable picking robots in the future.

Significance Agricultural environment is dynamic and variable, with numerous factors affecting the growth of animals and plants and complex interactions. There are numerous factors that affect the growth of all kinds of animals and plants. There is a close but complex correlation between these factors such as air temperature, air humidity, illumination, soil temperature, soil humidity, diseases, pests, weeds and etc. Thus, farmers need agricultural knowledge to solve production problems. With the rapid development of internet technology, a vast amount of agricultural information and knowledge is available on the internet. However, due to the lack of effective organization, the utilization rate of these agricultural information knowledge is relatively low.How to analyze and generate production knowledge or decision cases from scattered and disordered information is a big challenge all over the world. Agricultural knowledge intelligent service technology is a good way to resolve the agricultural data problems such as low rank, low correlation, and poor interpretability of reasoning. It is also the key technology to improving the comprehensive prediction and decision-making analysis capabilities of the entire agricultural production process. It can eliminate the information barriers between agricultural knowledge, farmers, and consumers, and is more conducive to improve the production and quality of agricultural products, provide effective information services. Progress The definition, scope, and technical application of agricultural knowledge intelligence services are introduced in this paper. The demand for agricultural knowledge services are analyzed combining with artificial intelligence technology. Agricultural knowledge intelligent service technologies such as perceptual recognition, knowledge coupling, and inference decision-making are conducted. The characteristics of agricultural knowledge services are analyzed and summarized from multiple perspectives such as industrial demand, industrial upgrading, and technological development. The development history of agricultural knowledge services is introduced. Current problems and future trends are also discussed in the agricultural knowledge services field. Key issues in agricultural knowledge intelligence services such as animal and plant state recognition in complex and uncertain environments, multimodal data association knowledge extraction, and collaborative reasoning in multiple agricultural application scenarios have been discussed. Combining practical experience and theoretical research, a set of intelligent agricultural situation analysis service framework that covers the entire life cycle of agricultural animals and plants and combines knowledge cases is proposed. An agricultural situation perception framework has been built based on satellite air ground multi-channel perception platform and Internet real-time data. Multimodal knowledge coupling, multimodal knowledge graph construction and natural language processing technology have been used to converge and manage agricultural big data. Through knowledge reasoning decision-making, agricultural information mining and early warning have been carried out to provide users with multi-scenario agricultural knowledge services. Intelligent agricultural knowledge services have been designed such as multimodal fusion feature extraction, cross domain knowledge unified representation and graph construction, and complex and uncertain agricultural reasoning and decision-making. An agricultural knowledge intelligent service platform composed of cloud computing support environment, big data processing framework, knowledge organization management tools, and knowledge service application scenarios has been built. Rapid assembly and configuration management of agricultural knowledge services could be provide by the platform. The application threshold of artificial intelligence technology in agricultural knowledge services could be reduced. In this case, problems of agricultural users can be solved. A novel method for agricultural situation analysis and production decision-making is proposed. A full chain of intelligent knowledge application scenario is constructed. The scenarios include planning, management, harvest and operations during the agricultural before, during and after the whole process. Conclusions and Prospects The technology trend of agricultural knowledge intelligent service is summarized in five aspects. (1) Multi-scale sparse feature discovery and spatiotemporal situation recognition of agricultural conditions. The application effects of small sample migration discovery and target tracking in uncertain agricultural information acquisition and situation recognition are discussed. (2) The construction and self-evolution of agricultural cross media knowledge graph, which uses robust knowledge base and knowledge graph to analyze and gather high-level semantic information of cross media content. (3) In response to the difficulties in tracing the origin of complex agricultural conditions and the low accuracy of comprehensive prediction, multi granularity correlation and multi-mode collaborative inversion prediction of complex agricultural conditions is discussed. (4) The large language model (LLM) in the agricultural field based on generative artificial intelligence. ChatGPT and other LLMs can accurately mine agricultural data and automatically generate questions through large-scale computing power, solving the problems of user intention understanding and precise service under conditions of dispersed agricultural data, multi-source heterogeneity, high noise, low information density, and strong uncertainty. In addition, the agricultural LLM can also significantly improve the accuracy of intelligent algorithms such as identification, prediction and decision-making by combining strong algorithms with Big data and super computing power. These could bring important opportunities for large-scale intelligent agricultural production. (5) The construction of knowledge intelligence service platforms and new paradigm of knowledge service, integrating and innovating a self-evolving agricultural knowledge intelligence service cloud platform. Agricultural knowledge intelligent service technology will enhance the control ability of the whole agricultural production chain. It plays a technical support role in achieving the transformation of agricultural production from "observing the sky and working" to "knowing the sky and working". The intelligent agricultural application model of "knowledge empowerment" provides strong support for improving the quality and efficiency of the agricultural industry, as well as for the modernization transformation and upgrading.

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.

[Significance] The scientific dataset of agricultural pests and diseases is the foundation for monitoring and warning of agricultural pests and diseases. It is of great significance for the development of agricultural pest control, and is an important component of developing smart agriculture. The quality of the dataset affecting the effectiveness of image recognition algorithms, with the discovery of the importance of deep learning technology in intelligent monitoring of agricultural pests and diseases. The construction of high-quality agricultural pest and disease datasets is gradually attracting attention from scholars in this field. In the task of image recognition, on one hand, the recognition effect depends on the improvement strategy of the algorithm, and on the other hand, it depends on the quality of the dataset. The same recognition algorithm learns different features in different quality datasets, so its recognition performance also varies. In order to propose a dataset evaluation index to measure the quality of agricultural pest and disease datasets, this article analyzes the existing datasets and takes the challenges faced in constructing agricultural pest and disease image datasets as the starting point to review the construction of agricultural pest and disease datasets. [Progress] Firstly, disease and pest datasets are divided into two categories: private datasets and public datasets. Private datasets have the characteristics of high annotation quality, high image quality, and a large number of inter class samples that are not publicly available. Public datasets have the characteristics of multiple types, low image quality, and poor annotation quality. Secondly, the problems faced in the construction process of datasets are summarized, including imbalanced categories at the dataset level, difficulty in feature extraction at the dataset sample level, and difficulty in measuring the dataset size at the usage level. These include imbalanced inter class and intra class samples, selection bias, multi-scale targets, dense targets, uneven data distribution, uneven image quality, insufficient dataset size, and dataset availability. The main reasons for the problem are analyzed by two key aspects of image acquisition and annotation methods in dataset construction, and the improvement strategies and suggestions for the algorithm to address the above issues are summarized. The collection devices of the dataset can be divided into handheld devices, drone platforms, and fixed collection devices. The collection method of handheld devices is flexible and convenient, but it is inefficient and requires high photography skills. The drone platform acquisition method is suitable for data collection in contiguous areas, but the detailed features captured are not clear enough. The fixed device acquisition method has higher efficiency, but the shooting scene is often relatively fixed. The annotation of image data is divided into rectangular annotation and polygonal annotation. In image recognition and detection, rectangular annotation is generally used more frequently. It is difficult to label images that are difficult to separate the target and background. Improper annotation can lead to the introduction of more noise or incomplete algorithm feature extraction. In response to the problems in the above three aspects, the evaluation methods are summarized for data distribution consistency, dataset size, and image annotation quality at the end of the article. Conclusions and Prospects The future research and development suggestions for constructing high-quality agricultural pest and disease image datasets based are proposed on the actual needs of agricultural pest and disease image recognition:(1) Construct agricultural pest and disease datasets combined with practical usage scenarios. In order to enable the algorithm to extract richer target features, image data can be collected from multiple perspectives and environments to construct a dataset. According to actual needs, data categories can be scientifically and reasonably divided from the perspective of algorithm feature extraction, avoiding unreasonable inter class and intra class distances, and thus constructing a dataset that meets task requirements for classification and balanced feature distribution. (2) Balancing the relationship between datasets and algorithms. When improving algorithms, consider the more sufficient distribution of categories and features in the dataset, as well as the size of the dataset that matches the model, to improve algorithm accuracy, robustness, and practicality. It ensures that comparative experiments are conducted on algorithm improvement under the same evaluation standard dataset, and improved the pest and disease image recognition algorithm. Research the correlation between the scale of agricultural pest and disease image data and algorithm performance, study the relationship between data annotation methods and algorithms that are difficult to annotate pest and disease images, integrate recognition algorithms for fuzzy, dense, occluded targets, and propose evaluation indicators for agricultural pest and disease datasets. (3) Enhancing the use value of datasets. Datasets can not only be used for research on image recognition, but also for research on other business needs. The identification, collection, and annotation of target images is a challenging task in the construction process of pest and disease datasets. In the process of collecting image data, in addition to collecting images, attention can be paid to the collection of surrounding environmental information and host information. This method is used to construct a multimodal agricultural pest and disease dataset, fully leveraging the value of the dataset. In order to focus researchers on business innovation research, it is necessary to innovate the organizational form of data collection, develop a big data platform for agricultural diseases and pests, explore the correlation between multimodal data, improve the accessibility and convenience of data, and provide efficient services for application implementation and business innovation.

【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.

In order to remove the inherent complex resistance structure of lignocellulose and achieve efficient utilization of lignocellulose, new lignocellulosic pretreatment technologies have been improved continuously. As green solvents, Deep Eutectic Solvents (DESs) have the advantages of low cost, simple preparation, thermal stability, and designability. They have great application potential in promoting the pretreatment of lignocellulose and enzymatic hydrolysis, and have received widespread attention. Based on the analysis and summary of the research status and achievements at home and abroad, the research progress of synthesis and properties of DESs, pretreatment mechanism, enzymatic hydrolysis, and bioethanol conversion were discussed. It was pointed out that different hydrogen bond donors and different pre-treatment conditions had a significant impact on the lignin removal rate and glucose yield. It was believed that pretreatment of lignocellulose with DESs could greatly improve the saccharification rate. Prospects for DESs pretreatment mechanism, recycling, and process parameter optimization were proposed.

Significance The crop phenotype represents the external expression of the interaction between crop genes and the environment. It is the manifestation of the physiological, ecological and dynamic characteristics of crop growth and development and represents a core link within the field of intelligent breeding. Systematic analysis of crop phenotypes can not only provide insight into the function of genes and reveal the genetic factors that affect the key characteristics of crops, but also can be used to effectively utilize germplasm resources and breed varieties with major breakthroughs. The utilization of data-driven, intelligent, dynamic and non-contact crop phenotypic measurement enables the acquisition of key traits and phenotypic parameters of crop growth, thereby furnishing crucial data support for the breeding and identification of breeding materials throughout the entire growth cycle of crops. Progress Crop phenotype acquisition equipment represents the fundamental basis for the acquisition, analysis, measurement and identification of crop phenotypes. Such equipment can be employed monitor the growth status of crops in detail. The functions, performance and applications of the dominant high-throughput crop phenotyping platform, along with an analysis of the characteristics of various sensing and imaging devices employed obtain crop phenotypic information are presented. The rapid development of high-throughput crop phenotyping platforms and perceptual imaging equipment has led to the integration of advanced imaging technology, spectroscopy technology and deep learning algorithms. These technologies enable the automatic and high-throughput acquisition of yield, resistance, quality and other related traits of large-scale crops, as well as the generation of large-scale multi-dimensional, multi-scale and multi-modal crop phenotypic data. This supports the rapid development of crop phenomics. The research progress of deep learning in the intelligent perception of crop agronomic traits and morphological structure, with respect to various phenotypes such as crop plant height, leaf area index, and crop organ detection is presented. Additionally, the main challenges associated with this field are outlined, namely the complexity of environmental influences, the difficulty of large-scale data processing due to data diversity, model generalization issues, and the need for lightweight algorithms. The analysis of crop phenotypes and morphological characteristics based on three-dimensional reconstruction technology is considered to be more accurate than that based on two-dimensional images. A summary and discussion of the three-dimensional reconstruction method for crops is provided, and the main challenges encountered are also outlined, including the complexity of crop structures, the necessity of algorithm optimization and the cost and practicability of the method. Conclusions and Prospects It is devoted to the examination of the difficulties and challenges associated with the intelligent identification of crop phenotypes based on deep learning, from the perspective of research and development of innovative field equipment for the acquisition and analysis of phenotypic data, the establishment of a unified data acquisition and data sharing platform with the objective of improving the efficiency of data utilization, the enhancement of the generality aforementioned approach. A field crop phenotype intelligent identification model must consider multiple perspectives, modalities and points in time. This necessitates a continuous, multi-faceted analysis. It is achieved to identify characteristics in a spatiotemporal context through the fusion of various data sources, such as images, spectral data and weather information. In terms of interpretability models, it explores the potential of deep learning in crop phenotype intelligent recognition. It will be necessary for future research to break through the current bottleneck of high-throughput crop phenomics technology. It is vital to conduct further research into the field of visual perception and deep learning methods. This will allow for the realization of the intelligent acquisition of crop phenotypic information, as well as an intelligent management of phenotypic data.

The global warming rate and the frequency of extreme high temperature weather are continuously increasing, which could bring catastrophic impacts to rice production. To further clarify the response mechanism of rice to high temperature, this article summarized the research progress in the direction of rice heat damage from high temperature, focused on the impact of high temperature on rice production, and deeply analyzed the physiological (photosynthetic characteristics/antioxidant system) and gene molecular mechanisms of rice’s response to high temperature. We concluded that the heat tolerance characteristics of rice were formed by the interaction between varieties and the environment. Results showed that, the photosynthetic characteristics of rice were influenced by both stomatal and non-stomatal limiting factors, and the antioxidant process was achieved by enhancing the activity of antioxidant enzymes and reducing the content of malondialdehyde; rice improved plant heat adaptability by activating the expression of key genes and stimulating the transduction of heat signals within the plant; by optimizing “Before production-During production-After production” comprehensive management and monitoring system, we could explore innovative cultivation systems, and thoroughly investigate the high temperature defense mechanisms of rice. Therefore, this study aimed to clarify the physiological and molecular mechanisms of rice in response to high temperature stress, providing a scientific reference for future heat-tolerant rice breeding work and improving rice sustainable production.

In order to elucidate the response of crop nitrogen absorption and utilization to salt and alkali stress and the regulation mechanisms, based on domestically and internationally research progress, this article summed the effect of salt and alkali stress on crop growth from the aspects of seed germination, seedling growth, root growth, photosynthesis, osmotic regulation system, redox system, and ion balance; discussed the impact of salt and alkali stress on crop nitrogen absorption and utilization and the undying mechanisms from the aspects of soil nitrogen cycling, root nitrogen absorption, and nitrogen assimilation; summarized the regulatory methods on crop nitrogen uptake and utilization under salt alkali stress such as nitrogen efficient variety selection, soil conditioner application, organic matter application, growth regulator application, and endophytic mycorrhizal colonization, and discussed the undying mechanisms. This article pointed out that soil salinization was one of the key soil barrier factors limiting crop production. Increasing nitrogen fertilizer application was an effective way to alleviate salt stress, but improper nitrogen fertilizer application could lead to a decrease in nitrogen utilization efficiency. Further in-depth research on crop nitrogen response mechanisms and regulatory pathways under salt stress from the soil-crop system could be of great significance for crop nutrient management and stable and high crops yield under soil salinization.

[Purpose/Significance] Using the concept of "public cultural space" to refer to various public cultural facilities and places in rural areas is a research trend that has gradually emerged in recent years. Under the background of rural revitalization strategy, clarifying the current research status and existing problems of rural public cultural space in China, exploring future research priorities is of great practical significance and theoretical value to promote the high-quality development of rural public cultural services, prosperous development of rural culture and the spiritual enrichment of farmers in the new era. [Method/Process] This paper reviewed relevant literature on rural public cultural spaces in China from 2012 to 2022, summarized existing research results, analyzed existing problems, and proposed future research priorities. [Results/Conclusions] The existing study mainly focuses on the overall research on rural public cultural space and the research on specific types of rural public culture. The former includes the basic theoretical issues such as the concept connotation, constituent elements, space types, value functions, development and evolution of rural public cultural space, as well as the construction status quo, existing problems and reconstruction path. The latter includes rural traditional cultural space, rural modern cultural space and rural new cultural space construction. The research of rural public cultural spaces puts increasing emphasis on the in-depth and systematic study and is focused on the theoretical value, the problem orientation and policy orientation of the research are becoming increasingly obvious. However, compared with urban public cultural space, specialized research on rural public cultural space is still relatively lacking. At the theoretical research level, research on digital or virtual public cultural spaces in rural areas in the digital and post pandemic era still needs to be improved, and research on the construction and evaluation of rural public cultural space based on the perspective of villagers' participation is still insufficient. At the practical research level, compared with modern cultural space such as township cultural stations and rural libraries, the research on new types of public cultural space such as rural bookstores and homestay bookbars that have emerged in recent years still needs to be further deepened. The innovative practice and advanced experience of traditional rural public cultural space in revitalization and transformation still lack systematic refinement. Faced with the new requirements of rural revitalization strategy and high-quality development of public culture for rural public cultural space, future in-depth research includes comparison of reconstruction paths of various types of rural public cultural space, construction of new rural public cultural space, construction of rural public cultural digital space, service innovation of rural public cultural space, evaluation indicators of rural public cultural space, and international experience and Chinese characteristics of rural public cultural space.

The genus Polygonatum Mill, commonly referred to as "Huang Jing," are plants renowned for their medicinal and edible properties. Their active constituents, including polysaccharides, flavonoids, and saponins, exhibit notable pharmacological effects. Recent studies have predominantly centered on the extraction of saponin components from the genus Polygonatum, which are attributed with anti-fatigue, antioxidant, hypoglycemic, lipid-lowering, and immune-enhancing properties. While there has been some advancement in the structural analysis of the genus Polygonatum saponins, their biosynthetic pathways remain underexplored. The synthesis of saponins in the genus Polygonatum occurs via the mevalonic acid pathway and the 2-C-methyl-D-erythritol-4-phosphate pathway, encompassing multiple enzymatic steps. This research indicates that the genus Polygonatum saponins exert diverse biological effects, including anti-tumor, antibacterial, anti-inflammatory, antiviral, and immune regulatory activities, and hold significant potential in medicine, food, cosmetics, and other sectors. Nonetheless, current studies are limited by inadequate structural analysis, an incomplete understanding of biosynthetic pathways, and ambiguous mechanisms of pharmacological action. Future endeavors should prioritize the isolation, structural analysis, synthetic biology, and pharmacology of the genus Polygonatum saponins to advance their scientific investigation and product development, thereby laying a foundation for the creation of novel therapeutic agents.

Scutellaria baicalensis is a traditional Chinese herbal medicine with high medicinal value. In order to extract and detect flavonoids from Scutellaria baicalensis, the methods of extracting flavonoid compounds from Scutellaria baicalensis roots and aboveground parts are summarized, such as organic solvent extraction, water extraction, etc. The separation and purification methods of flavonoid compounds in Scutellaria baicalensis roots and aboveground parts are analyzed, such as column chromatography, high speed counter-current chromatography, etc. The composition determination methods of flavonoid compounds in Scutellaria baicalensis roots and aboveground parts are sorted out, including high performance liquid chromatography and ultra-high performance liquid chromatography, etc. We also propose suggestions for improving the practical application of Scutellaria baicalensis, such as combining laboratory research with industrial production, improving experimental equipment and extraction process to provide convenience for industrial production, making full use of Scutellaria baicalensis resources to create social benefits, etc. Based on the analysis of flavonoid compounds, this paper reviews the research progress of extraction, separation and determination methods of flavonoid compounds from Scutellaria baicalensis roots and aboveground parts, thus providing technical reference for the large-scale development and application of flavonoids from Scutellaria baicalensis and laying technical foundation for further research and promotion of Scutellaria baicalensis resources.

Citrus is the largest category of fruit in China, which is widely planted and has many cultivars for fresh fruit market. To extend shelf life, promote intensive processing, improve enterprise’s benefit, current research progresses related to fruit storage and processing have been reviewed. At first, new preservation technologies applied in Citrus fruits’ storage were summarized. Subsequently, innovation technologies for processing products and by-products utilization were discussed. Finally, functional components in Citrus with potential application in pharmaceutical industry were also reviewed. Therefore, depending on different cultivars in production areas, fruit sorting system after post-harvest are recommended for orange and lemon varieties. Meanwhile, the non-thermal processing technology and enzymatic digestion for de-peeling is utilized for tradition processing products, such as sweet orange and tangerine. Functional components in Citrus will be extracted and prepared to medicinal and edible food. In conclusion, new technology for storage and processing are used in Citrus to extendindustry chain, which significantly boost industry development in future.

China faces significant challenges of large population and limited arable land resources. In recent years, extreme weather events and ongoing soil degradation have significantly influenced China's agricultural production. With advances in agricultural science and technology, incorporating new materials into agricultural practices has been proven to be an effective strategy for adapting to these developments and environmental shifts. Seaweed extract, specifically seaweed oligosaccharides, are natural active substances derived from seaweed using modern technology. They are employed in agriculture as inducers for plant stress and disease resistance, biostimulants, and fertilizer enhancers. With continuous research progresses on the potential applications of seaweed oligosaccharides in agriculture, significant advancements have been achieved in their study and use. To further systematically understand and apply seaweed oligosaccharides, this paper discussed their sources, classification, and production methods. It summarized their impact on bolstering crop stress and disease resistance, fostering growth and development, and improving nutrient absorption, as well as their effectiveness and mechanisms across various crops. This provided innovative approaches and tools for the sustainable and efficient development of Chinese agriculture in the current context.

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.

Cold stress directly affects plant growth and development, and under extreme conditions, it may result in infertility or even lead to plant mortality. To investigate the molecular mechanisms by which plants respond to cold stress, this review synthesizes the diverse effects of cold stress on plants. It discusses the impact of cold stress on plant plasma membranes, the ICE-CBF-COR signaling pathway, plant hormones, and cellular metabolism. Additionally, recent advancements in understanding the mechanisms underlying plant cold tolerance are examined and discussed. This review aims to provide a foundation for the practical application of these findings in the genetic improvement of crops. Based on the above, the paper suggests that a multidisciplinary approach, incorporating genetic engineering, genetics, biochemistry, molecular biology, and bioinformatics should be employed to further explore the molecular mechanisms behind plant cold tolerance. Furthermore, potential future research directions in this field are proposed.

Sucrose non-fermenting 1-related protein kinase 2(SnRK2) is a ubiquitous protein kinase in plants. It belongs to the Ser/Thr class of protein kinases, and can play a role in various signal transductions. In order to study the role of SnRK2 protein kinase in plant stress resistance, this study analyzed the characteristics and research process of SnRK2 gene family, summarized the functions of SnRK2 gene in regulating stomatal size of plant leaf, responding to drought stress and salt stress, and responding to seed germination and development. It was pointed out that SnRK2 gene played a role in various signal transductions, which could effectively improve plant stress resistance. It is of great significance for ABA response, plant growth and development, and it provides a reference basis for future research on the molecular mechanism of SnRK2 and plant variety cultivation.

[Significance] Plant active small molecules play a key role in regulating plant growth and resisting environmental stress. Accurate detection of these molecules is of great significance for achieving precise management of agriculture and promoting the development of smart agriculture. Various detection methods have been used for the detection of plant active small molecules, among which electrochemical sensors have attracted much attention due to their sensitivity, portability, and low cost. [Progress] By reviewing relevant literature, this article deeply analyzes the research status of electrochemical sensors in the field of detecting plant active small molecules, and provides a detailed analysis of the sensing principles, signal amplification strategies, and application potential of each sensor. The development trend of sensors from in vitro to in vivo and in situ detection, the important role of nanomaterials in the sensing process, and the combination of sensors with flexible electronics and artificial intelligence technology are discussed. [Conclusion] This article summarizes the technical challenges currently faced by electrochemical sensors in the field of detecting plant active small molecules and analyzes the next development direction, including improving sensing performance, optimizing electrolyte materials, and integrating sensors with microelectronics and artificial intelligence technology, providing a reference for the technical research and application of plant small molecule electrochemical sensors.

Field environmental sensing can acquire real-time environmental information, which will be applied to field operation, through the fusion of multiple sensors. Multi-sensor fusion refers to the fusion of information obtained from multiple sensors using more advanced data processing methods. The main objective of applying this technology in field environment perception is to acquire real-time environmental information, making agricultural mechanical devices operate better in complex farmland environment with stronger sensing ability and operational accuracy. In this paper, the characteristics of sensors are studied to clarify the advantages and existing problems of each type of sensors and point out that multiple sensors can be introduced to compensate for the information loss. Secondly, the mainstream information fusion types at present are outlined. The characteristics, advantages and disadvantages of different fusion methods are analyzed. The important studies and applications related to multi-sensor information fusion technology published at home and abroad are listed. Eventually, the existing problems in the field environment sensing at present are summarized and the prospect for future of sensors precise sensing, multi-dimensional fusion strategies, discrepancies in sensor fusion and agricultural information processing are proposed in hope of providing reference for the deeper development of smart agriculture.

农业供应链是我国现代农业市场体系建设中不可或缺的组成部分。建立现代化的农业供应链体系,对推进农村一二三产业融合发展、提高流通现代化水平、提升农业竞争力和国际话语权等具有重要意义。自加入WTO以来,我国农业高度开放,受到全球农业供应链的影响越来越大。加强农业供应链管理已成为学术界研究的热点,也是新冠肺炎疫情全球蔓延新形势下政府关切和管理调控的难点、农业生产经营者关注的焦点。我国在农业供应链管理研究方面起步晚,但近10年来发展较快。本文通过文献研究并结合相关科研实践,分析比较了不同方面对农业供应链的定义,阐述了农业供应链管理的概念和内涵,重点综述了农业供应链管理在理论研究、流通模式、风险管理和技术创新等方面的研究应用进展。最后,结合国内外新形势及我国实际,指出了突发事件下的农业供应链应急管理、经济全球化背景下农业供应链治理能力、绿色农业供应链体系构建及管理、智慧农业供应链的创新等有待继续深入研究的方向与热点问题,为促进我国农业供应链管理领域发展提供建议。

High molecular weight glutenin subunits (HMW-GS) are the most important components in the storage protein of wheat grains. Their compositions, expressions and contents determine the dough elasticity and baking quality. This article summarized the progress of cloning, molecular characterization and functional studies of HMW-GS as well as their marker development and application in wheat breeding. Update status of different HMW-GS effects on flour processing quality, genetic transformation of several HMW-GS genes, small-scale mixograph analysis by adding prokaryotic expressed HMW-GS, and mutant developing on HMW-GS loci, were also reviewed. Besides, crucial issues in current studies on wheat HMW-GS were discussed. It is suggested that the key point on HMW-GS in the future will be to pyramid some desirable HMW-GS genes by marker assisted selection and transgenic strategies for the development of wheat varieties with good bread-making quality and the functional dissection of each HMW-GS gene accurately.

The article systematically reviewed the research status of Chinese Clematis plants in germplasm resource investigation, cultivation and reproduction, pharmacology and garden applications, analyzed the regional representative distribution of Clematis germplasm resources due to different climatic conditions, and discussed the relationship between Clematis breeding and eco-geographical response. It was concluded that temperature control, light, appropriate amount of plant growth regulator and good culture medium were effective means to improve the breeding technology of Clematis, and the medicinal chemical composition, efficacy and landscaping forms of different species Clematis from the aspect of resource value utilization were further analyzed. It was suggested that the resources of Clematis with little development potential should be protected, and cross-breeding and utilization of the germplasm with good performance in the existing Clematis resources should be done.

Graphene-based materials have been widely used in the fields of electronics, biomedicine and environmental protection due to their unique structural characteristics and excellent physical and chemical properties. With the continuous breakthroughs in basic research on graphene, its industrial applications are expanding and have been gradually extended to the agricultural field. This paper reviewed the research progress of graphene-based materials in improving the utilization of agricultural chemicals, promoting crop growth and agricultural sensors. The authors analyzed the applications and action mechanism of graphene-enhanced compound fertilizers and nano-pesticides, and summarized that graphene-based materials could affect crop growth by stimulating the secretion of growth hormones, enhancing the stress resistance of crops and improving the soil environment. In agriculture, the application of graphene-based materials has shown great potential, but is still in the exploration stage. It is considered that the mechanism and influencing factors of graphene-based materials on crops should be further explored, their biosecurity should be evaluated comprehensively, and a complete application database should be established to realize the sustainable development after the integration of graphene and agriculture.

The flavor substances of cigar tobacco leaves play a decisive role in the stylistic characteristics of cigars. Fermentation is an important process to improve the quality of cigar tobacco, which can affect the type, content and composition ratio of flavor substances in cigar tobacco, thus determining the quality of cigar tobacco leaves and cigar tobacco quality. This paper reviews the mechanism of fermentation and flavor perception of cigar tobacco leaves and the progress of flavor analysis of cigar tobacco leaves under different fermentation conditions, summarizes their effects on cigar tobacco leaves, and looks forward to the future research on cigar flavors to provide theoretical support for related research.

Vicia faba is an important food resource for human and livestock, and China is the largest producer around the world. Bruchus rufimanus Boheman is the most important pest of V. faba, with infestation rates of 3%-100%, which causes significant economic losses. Semiochemical is a kind of chemical substance released by creature which causes behavior modification or physiological reaction of other biological organisms. It is vital in insect feeding, seeking mate, orienting host and laying eggs. Here, we present a comprehensive review of B. rufimanus from distribution, morphological feature, life cycle, developmental strategy and chemical ecology based on published domestic and foreign research. Emphasis is placed on semiochemical application prospect in integrated pest management, which provides a new perspective to green prevention and control technology of B. rufimanus.

As a kind of plant functional food, edible plant enzymes have received wide attention in the fields of food and health products, and the related production processes have made progress in terms of raw materials, fermentation microorganisms and fermentation conditions. A review was conducted to analyze the current research status of edible plant enzymes. The main fermentation methods, main active ingredients, main functional roles, and the risks and challenges faced by edible plant enzymes were summarized. The fermentation of edible plant enzymes generally adopted natural fermentation and artificial inoculation fermentation. The use of artificial inoculation technology had the significant advantages of effectively reducing the time required for fermentation and improving the production efficiency. The main active ingredients of edible plant enzymes were polysaccharides, polyphenols, vitamins, etc., which had certain preventive and therapeutic effects in lowering blood lipids, antioxidant and cardiovascular diseases. In the production process of edible plant enzymes, artificial inoculation and fermentation required the selection of the right strain, control of fermentation conditions, and prevention of environmental pollution. The analysis results showed that the development prospect of edible plant enzymes was very promising. The aspects needed to be focused on in the futurewas proposed, and the mechanism of edible plant enzymes was made a prospective, aiming to provide a more valuable reference for the further research and development and promotion of edible plant enzymes.

Strigolactones (SLs) is a new type of plant hormone, which is involved in regulating plant branching, reproductive development, leaf senescence and other biological processes. D53/SMXLs is an inhibitor of monolactone signal transduction pathway, and plays an important role in monolactone signal transduction. The previous studies about strigolactones inhibitory factor D53/SMXLs at home and abroad were reviewed. The discovery, structure, signal transduction mechanism, molecular biological functions and other functions of D53/SMXLs were summarized. At last, it was pointed out that the three aspects of strigolactones signal transduction pathway should be further improved and studied.

Bacillus thuringiensis (Bt) is a widely distributed Gram-positive bacterium that can produce a series of insecticidal proteins during its vegetative growth and sporulation phases. It is commonly used as a biocontrol agent in agriculture, forestry and public health practice. The Bt crops developed based on genetic engineering technology provide an efficient and environmentally friendly biological control method for agricultural pest management. However, the extensive and prolonged cultivation of Bt crops has led to the gradual development of Bt resistance in pests, which has greatly reduced the insecticidal effect of Bt proteins and the long-term benefits of Bt crops. In order to gain a deeper understanding of the relationship between the mechanism of action of Bt proteins and the occurrence of Bt resistance in insects, this paper summarized the structural and functional characteristics of various Bt toxins, and elaborated the molecular mechanism of Bt resistance in insects from three main aspects: immune system regulation, changes in toxin activation, and mutations in toxin receptor genes. In addition, two insect resistance management strategies, gene stacking and ‘high dose/shelter’ were also introduced. Finally, the future research directions of Bt crops were pointed out, including further in-depth analysis of the mode of action of Bt toxins and the mechanism of Bt resistance in insects, exploration of new Bt proteins, strengthening the popularization and publicity of Bt crops, and establishing resistance monitoring network as well as early warning system.

[Purpose/Significance] The spread of misinformation on social media has caused serious harm and attracted attention from various disciplines. This study aims to systematically examine the factors associated with the propagation of misinformation. It contributes to the existing literature by providing an integrated model of the factors influencing misinformation propagation, which is crucial for understanding and mitigating the spread of misinformation. [Method/Process] The search strategy, developed with the help of librarians, was searched in six Chinese and foreign databases. Four researchers coded the information back-to-back to ensure the accuracy of the analysis. Our literature screening criteria were rigorous to ensure that only high quality and relevant research was included. A total of 108 empirical studies related to misinformation propagation were included. The factors were summarized and sorted from multiple perspectives such as disciplinary field, theoretical foundation, research methods and different roles. [Results/Conclusions] Research on this topic has grown rapidly in recent years. Scholars from a variety of disciplines have used survey and experimental methods to study misinformation in the areas of politics and health. Pedictors of misinformation propagation are mainly studed from the perspective of users and information, including objective characteristics of information, perceptual characteristics of information, as well as individual characteristics, cognitive characteristics, and perceptual characteristics of users. The results show that individual characteristics play a critical role in shaping users' intention and behavior to propagate misinformation. Individual characteristics are the most frequently studied factors, while information and situational characteristics have received less attention. Psychological and behavioral variables, including users' cognitive, emotional, and behavioral responses play key mediating roles in this process. In addition, the types of information, individual attributes, cognitive characteristics, social interactions, personal knowledge, behavior and emotions play moderating roles. This study constructs an integrated model of the influencing factors for misinformation propagation, which can provide direction for targeted interventions and algorithm design to mitigate the spread of misinformation. The study also identified some limitations of current studies, including an excessive focus on the political and health issues, a lack of attention to how information characteristics, intervention factors, and platform characteristics play a role, and the relative simplicity of the research methods. Future studies should focus on misinformation propagation in other scenarios, explore more information characteristics suitable for algorithmic intervention, examine the differences in misinformation propagation on different platforms, and use mixed research methods to reach more credible conclusions. This study provides directions and goals for multi-agent collaborative misinformation management.

Theaflavins are the main components of black tea, which have great potential and promising applications in the fields of foods and medicines. Base on the synthesis mechanism of theaflavin, the advance of the main preparation methods of theaflavin was summerized, such as direct extraction and preparation in vitro which can be divided into chemical oxidation method, enzymatic oxidation method and biomimetic synthesis method. The primal problem of the above synthesis methods, such as the inability to achieve industrialization, were also addressed, possible future research fields were reviewed in this paper, with the aim of providing a reference for the research and development of preparation of theaflavins.

Cold plasma technology has gained significant traction in agriculture due to its advantages, including low operational temperature, green, residue-free, high efficiency, and remarkable effectiveness in seed treatment, as well as in activating the internal physiological and biochemical processes of plants to improve resistance and yield. This paper reviews the progress of cold plasma technology in seed disinfection, breaking seed dormancy to promote germination, enhancing plant resistance, and increasing yield, etc. Furthermore, this paper provides a comprehensive analysis of the primary active ingredients of this technology and elucidates their mechanisms of action at the physicochemical, physiological and biochemical levels. In view of the differences in physical, chemical and physiological effects of different treatment objects after discharge by different types of cold plasma equipment, the future research direction is proposed: optimizing and establishing cold plasma treatment system, and clarifying the long-term effect of cold plasma treatment on the phenotypic genetic changes of plant growth cycle.

Microalgae, as the third generation biomass energy, has great potential in wastewater treatment. In order to seek more economical treatment methods, the co-culture of microalgae with other microorganisms can promote the flocculation harvest of microalgae and increase biomass and lipid production, thus reducing the cost of microalgae wastewater treatment. In this paper, the types of microalgae co-culture systems and the mechanisms, system settings, and influencing factors of microalgae co-culture treatment of wastewater were summarized. The current research of microalgae using wastewater as a growth substrate to produce high-value by-products was described, and the prospects and challenges of wastewater treatment and reutilization by microalgal co-culture were pointed out.

[Purpose/Significance] In the rapidly evolving digital landscape, generative artificial intelligence (GenAI) has emerged as a transformative force in information literacy (IL) education, presenting unprecedented opportunities and challenges for library-based learning environments. This scoping review comprehensively examines the integration of GenAI within IL education, moving beyond theoretical frameworks to provide a nuanced analysis of practical applications and strategic implementations. In contrast to existing research that primarily emphasizes technological capabilities, this study explores the profound implications of GenAI on educational paradigms and provides critical insights into the systematic transformation of library IL services in the AI era. [Methods/Process] Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, 51 key literature sources selected from the SSCI, A\&HCI, and CSSCI databases were systematically analyzed. The comprehensive analytical framework encompassed four key dimensions: technology acceptance, educational framework construction, AI literacy cultivation, and the integration of artificial intelligence with IL education. This methodological approach enabled a thorough exploration of current practices while identifying critical gaps in existing research. [Results/Conclusions] The results show that GenAI significantly enhances IL education through personalized learning experiences and improved digital teaching effectiveness. Tools such as ChatGPT have significant potential to promote adaptive learning environments and improve student engagement. The research identifies four primary areas of impact: 1) creating dynamically adaptive learning environments tailored to individual needs, 2) enhancing critical thinking through interactive scenarios, 3) facilitating cross-disciplinary knowledge integration, and 4) generating innovative educational content and resources. However, the study also identifies several critical challenges, including concerns about data accuracy concerns, inherent algorithmic biases, risks to academic integrity, and the potential weakening of independent thinking skills due to over-reliance on AI systems. To address these challenges, the research proposes a comprehensive framework that includes: 1) robust ethical guidelines for the implementation of GenAI, 2) systematic assessment mechanisms to monitor learning outcomes, 3) critical thinking training programs, and 4) strategies to maintain academic integrity and intellectual autonomy. The study emphasizes that the integration of GenAI is more than a technological change - it represents a fundamental shift towards AI literacy education. This evolution will require learners to develop skills beyond traditional IL skills, including understanding AI ethics, legal frameworks, and using AI technologies to solve problems. Future research directions should focus on conducting empirical studies in different educational contexts, developing adaptive teaching frameworks that balance technological innovation with traditional educational values, and investigating the long-term impact of GenAI integration on learning outcomes. By systematically examining the opportunities, challenges, and development trajectories of generative AI, this study provides valuable insights for libraries and educational institutions seeking to optimize their IL programs in the AI era. The findings not only contribute to the theoretical understanding of the role of GenAI in education, but also provdie practical guidance for integrating advanced technologies into traditional educational frameworks, ultimately fostering a more adaptive, intelligent, and personalized learning ecosystem.

To provide a reference for the in-depth research and utilization of coumarin compounds in the genus Heracleum, this review summarized the types and chemical structures of the identified coumarin compounds in the genus Heracleum, concluded the research progress in aspects of anti-bacteria, anti-oxidation, anti-cell proliferation, anti-inflammation, toxicity, etc, and comparatively analyzed the difference between relevant domestic and foreign researches. It revealed the diversity of coumarin compounds in the genus Heracleum and their values in medical and food industries. It proposed during the drug development process, there are problems, such as the research in its function is not deep or systemic enough, active ingredients are unclear, etc. It suggested fortifying research on its toxicity and efficacy and promoting the development and utilization of the genus Heracleum as a plant resource for foods and medicine.

To further promote the application of intelligent management technology in vegetable production and management, this paper puts forward the overall framework of vegetable production intelligent technology, analyzes the vegetable data sources and acquisition means under the background of big data age, summarizes the latest research technology of vegetable disease diagnosis, environment and water and fertilizer regulation, cultivation management decision, intelligent production operation, and the intelligent information service. Then, by analyzing the challenges of vegetable intelligent management technology, the development suggestions for vegetable intelligent management technology are put forward. Intelligentization is an essential factor of modern agricultural development. And the use of intelligent information technology to improve the comprehensive productivity and benefit of the vegetable industry is the ultimate goal. It is necessary to dig into the actual demand, integrate the data of the whole vegetable industry chain, promote the deep integration of intelligent information technology and the vegetable industry, and support the transformation and upgrading of the vegetable industry.