Phosphorus in soil directly determines plant growth and crop yields, but phosphorus existing forms in soil are very complex, and those phosphorus forms that can be absorbed and utilized by plants account for only a small part of total phosphorus. Therefore, it is important to study the existing forms and classification methods of phosphorus in soil to improve the phosphorus use efficiency of crops, explore ways to enhance phosphorus availability, and reduce phosphorus loss. In this paper, the existing forms of phosphorus in soil, influencing factors of soil phosphorus availability and phosphorus classification methods were reviewed. The results show that the forms of phosphorus in soil consist of two major categories: inorganic phosphorus and organophosphorus, phosphorus absorbed by plants is mainly water soluble inorganic phosphorus, and other forms of phosphorus are difficult to be absorbed by plants, causing low utilization efficiency of phosphorus in soil. There are many factors that lead to low phosphorus use efficiency, mainly ions like calcium, iron and aluminum, and organic matter, pH, temperature, moisture etc. To study and improve the mechanism of the influencing factors could effectively enhance phosphorus utilization efficiency. At the same time, with the continuous improvement of phosphorus classification methods by domestic and foreign scholars, the effective forms of phosphorus have been studied more in-depth and accurately. Bowman-Cole organophosphorus classification method and Hedley’s phosphorus classification method are the two most widely used methods at present.

Low temperature is an abiotic stress that could affect plant growth and vegetation distribution. Once the environmental temperature is continuously lower than the optimal temperature for plant growth, the plant would suffer low temperature stress, including chilling injury and freezing injury. Chilling injury refers to the damage on plant caused by low temperature of zero degree or above. The cells do not freeze at this temperature, but the cold will have physiological obstacles for thermophilic plants, causing injury or death. Freezing damage refers to the phenomenon that plants are damaged or die because of the low temperature below the freezing point. Previous studies mainly focused on the regulation mechanism of low temperature stress on plants, including the process in plants from the perception of low temperature signal to the expression of functional genes, and to the resistance to low temperature stress. This article reviews the research on cold stress on plants in recent years, analyzes the research status from the aspects of signal perception, signal transduction, functional gene expression, cold-induced physiological and cellular regulatory mechanism, and discusses the prospect of the research on plant cold resistance. It will provide a theoretical basis for cultivating new cold-resistant plant germplasms.

The substitution of chemical fertilizers by organic fertilizers is an effective strategy to reduce the amount and increase the efficiency of chemical fertilizer. It also significantly stimulates crop yield and soil fertility. However, it is worth noting that the substitution of chemical fertilizers by organic fertilizers could contribute to greenhouse gas emissions and pollution loading in soil environment. This paper reviewed the effects of organic fertilizer application on crop quality, soil amelioration, greenhouse gas emissions and agricultural non-point source pollution. Besides, we summarized current research of organic fertilizer application and put forward proposals for further studying the organic fertilizer application. Firstly, constantly optimizing the fermentation process to improve the quality of organic fertilizer is of overarching importance. Secondly, it is suggested to strengthen the quality trait evaluation in assessing the application effect of organic fertilizer, and take full advantage of long-term positioning observation and modern monitoring means to improve the soil fertility monitoring level and accomplish the comprehensive environmental effect evaluation. These suggestions aim at providing guidance for rational and efficient application of organic fertilizers, and for sustainable utilization of soil and water resources.

Agricultural and forestry waste is a valuable biomass resource. If the resource cannot be used efficiently, it will cause serious environmental pollution and even great harm to human health. Therefore, the resource utilization of agricultural and forestry wastes is the important content of controlling agricultural non-point source pollution, saving biomass resources, energy conservation and emission reduction, protecting the ecological environment, achieving the goal of peaking carbon emissions and carbon neutralization, and social and economic sustainable development. In order to promote the resource utilization of agricultural and forestry wastes, this paper summarized the progress achieved in this field at home and abroad in recent years.

Drought is one of the most important abiotic stresses affecting the growth and yield of crops. The risk of crops suffering from drought stress is increasing under climate change. In order to cope with drought, crops show a series of resistance mechanisms, including the changes of morphological characteristics, and physiological and biochemical characteristics (antioxidant enzyme, osmotic regulation substances, and endogenous hormone), which play an important role in improving the resistance of crops under drought conditions. This paper summarized the response mechanism of crops to drought stress and introduced the measures to improve the drought resistance ability of crops, including: (1) selecting drought-resistance cultivars to promote the absorption of deep soil water; (2) soil mulching, which could reduce soil evaporation and increase soil water content; (3) water-saving irrigation techniques, such as micro-sprinkler irrigation and drip irrigation, which could precisely control the irrigation application and increase irrigation frequency; in addition, partial root-zone irrigation could reduce luxurious transpiration and soil evaporation by regulating stomatal closure; (4) anti-transpirants, which could inhibit excessive transpiration of water by forming ultrathin transparent protective film on the surface of crop branches and leaves; (5) plant growth regulators, which could enhance crop drought resistance by regulating plant physiological metabolism; (6) nano-fertilizers, which could promote plant growth and development by changing physiological and biochemical reactions of crops and enhance drought resistance of crops; (7) biochar, which is beneficial to soil aeration and water retention, and could improve soil physical properties and soil water retention capacity. In order to provide a theoretical basis and technical reference for coping with drought stress, this paper systematically discussed the action mechanism, application prospect and existing problems of the above 7 measures.

As the byproduct of agricultural production, crop straw is an important renewable resource. Previous studies have shown that the main component of crop straw is lignocellulose. Some microorganisms such as bacteria and fungi can produce certain enzymes that are capable to degrade lignocellulose. The present study summarized the types and degradation mechanisms of lignocellulose-degrading enzymes, and reviewed the reported microbial species which could degrade rice, wheat and corn straw. In addition, this study analyzed the shortcomings of the identified single microorganism strain and microbial complex for commercial application, and discussed the perspectives and directions of future research. The review will provide reference for screening novel high-quality lignocellulose degradation microorganisms and developing cellulose-degrading microorganisms for resource utilization of crop straw.

Iron (Fe) is the earliest discovered and most abundant essential microelement in plants, which is involved in many physiological processes and metabolic pathways, Fe deficiency will seriously affect the growth, development, yield and quality of plants. Fe in plant-derived food is the main source for animal and human to obtain Fe, and insufficient Fe uptake can damage their health. In order to fully understand the metabolic physiology of Fe in plants, and promote the cultivation of iron-rich plants and the development of iron-rich food, in this review, the contents, forms and proportions of Fe in soil and plants were summarized, the distribution and function of Fe in plants were concluded, the different efficient absorption strategies of plants in small amount of soluble Fe environment were compared, and the regulation mechanisms of Fe transport in cells and long-distance in plants were analyzed. Based on the above, some research prospects were discussed in view of the previous research, it is suggested that more attention should be paid to the differences and molecular mechanisms of Fe metabolic pathways among different plant species, the Nramp family genes regulating approach of the docytotic mechanism of Fe deficiency in plants, the oxidation precipitation and reduction release mechanisms of ferritin (Fer) in the plastids, and the biofortification measures for increasing Fe content and bioavailability in plants.

Accurate detection and recognition of plant diseases is the key technology to early diagnosis and intelligent monitoring of plant diseases, and is the core of accurate control and information management of plant diseases and insect pests. Deep learning can overcome the disadvantages of traditional diagnosis methods and greatly improve the accuracy of diseases detection and recognition, and has attracted a lot of attention of researchers. This paper collected the main public plant diseases image data sets all over the world, and briefly introduced the basic information of each data set and their websites, which is convenient to download and use. And then, the application of deep learning in plant disease detection and recognition in recent years was systematically reviewed. Plant disease target detection is the premise of accurate classification and recognition of plant disease and evaluation of disease hazard level. It is also the key to accurately locate plant disease area and guide spray device of plant protection equipment to spray drug on target. Plant disease recognition refers to the processing, analysis and understanding of disease images to identify different kinds of disease objects, which is the main basis for the timely and effective prevention and control of plant diseases. The research progress in early disease detection and recognition algorithm was expounded based on depth of learning research, as well as the advantages and existing problems of various algorithms were described. It can be seen from this review that the detection and recognition algorithm based on deep learning is superior to the traditional detection and recognition algorithm in all aspects. Based on the investigation of research results, it was pointed out that the illumination, sheltering, complex background, different disorders with similar symptoms, different changes of disease symptoms in different periods, and overlapping coexistence of multiple diseases were the main challenges for the detection and recognition of plant diseases. At the same time, the establishment of a large-scale and more complex data set that meets the specific research needs is also a difficulty that need to face together. And at further, we point out that the combination of the better performance of the neural network, large-scale data set and agriculture theoretical basis is a major trend of the development of the future. It is also pointed out that multimodal data can be used to identify early plant diseases, which is also one of the future development direction.

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.

Copper (Cu) is an essential metal for human body, animals and plants, and participates in various morphological, physiological and biochemical processes. Copper is a cofactor of many enzymes and plays an important role in photosynthesis, respiration and electron transport chain. It is also a structural component of defense genes. In order to provide more systematic theoretical reference for the future study of copper stress on plants, based on the adverse effects of excessive copper on physiological processes such as plant germination, growth, photosynthesis and anti-oxidation summarized in previous studies, this paper reviews the biological functions of copper, the toxicity of excessive copper to plant growth and development, the role of copper transporters and chaperone proteins, and the tolerance mechanism of plants to copper stress. The future research direction is prospected, which provides a basis for formulating effective strategies to maintain copper homeostasis.

The SWEET gene family of plant sugar transporters is a class of important sugar transporters discovered in recent years, which plays an important role in plant growth and development, physiological metabolism, and resistance to stress by regulating the transport and distribution of sugar in plants. SWEET gene has different biological functions in different species and plays an important role in plant life activities. In this study, we reported the research status of the protein structure, transport mechanism and biological function of the SWEET gene family in plants, aiming to provide a theoretical basis for further study on other structures and functions of SWEET gene family.

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.

Direct seeding is an important rice planting method. It is widely used at home and abroad due to its advantages of saving labor, time and cost and significantly improving the comprehensive benefits of rice planting. In this paper, the research status and progress of direct seeding rice at home and abroad were elaborated, and three main direct seeding rice planting methods, namely wet direct seeding, water direct seeding and dry direct seeding, were introduced. Main problems in direct seeding rice production were analyzed from the aspects of yield, weed control and lodging resistance, and countermeasures were proposed as cultivating suitable varieties, appropriate nitrogen application, lodging resistance, weed control, and integrated development of agronomic practices and agricultural machinery. The paper also discussed the development trend of direct seeding rice, in order to provide reference for the cultivation and promotion of direct seeding rice with high yield and lodging resistance.

Alternative splicing is widespread in plants and is the main source of transcriptome and proteome diversity in organisms. With the development of science and technology, the research methods of alternative splicing have gradually become simple, convenient and efficient, and more and more alternative splicing events have been discovered in plants. The article mainly introduces the mechanism and research methods of alternative splicing in plants, as well as the latest research progress of alternative splicing in several plants, and puts forward suggestions on the research direction in the future.

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.

Botanical insecticides are secondary metabolites produced by plants, which provide rich resources for research and development of insecticides because of their specific biological activities. They are alternatives to organic synthetic chemical pesticides. In this study, a brief history and current status of plant-based insecticides, and their active ingredients and modes of action were reviewed in detail, and the problems and development prospects of plant-based insecticide research were discussed. This study will provide reference for the development of more botanical insecticides.

Wastewater from aquaculture has attracted wide attention as one of the sources of agricultural non-point source pollution, and the management of aquaculture wastewater has become a current research hotspot. In order to understand the mechanism of aquaculture wastewater purification and enhance the purification technology efficiency, this paper introduces the current status, hazards, and related control policies of aquaculture pollution in China, and reviews the aquaculture wastewater purification technologies developed in the past two decades. Finally, the research direction of aquaculture wastewater is discussed to put forward the possibility of strengthening the sedimentation unit, and using new materials and microorganisms to intensify the purification system.

Rice husk is a kind of agricultural waste produced after rice processing, and one of the important biomass resources. Discarding, burying or burning of rice husk in open field directly will cause not only waste of resources but also environmental problems. Resource utilization is the development trend of effective utilization of rice husk, which is in line with the requirements of the sustainable agricultural development and green and circular agricultural development. Material utilization is a new way of rice husk resource utilization, which has become the focus of research at home and abroad. Therefore, on the basis of analyzing the properties of rice husk, this paper took rice husk board, rice husk-polymer composite and rice husk-cement composite as examples, reviewed the research progress on the performance of the composites and the material utilization of rice husk resources. Finally, the development direction of material utilization of rice husk resource was discussed, so as to provide reference for further research.

The article introduced the symptoms of grapevine downy mildew and the process of infestation cycle. Moreover, it summarized the formation and development of oospores, the production and changes of the relevant secretory proteins after the infection of the fungus, and the pathogenic mechanism of grapevine downy mildew. At the same time, the control methods of grapevine downy mildew were reviewed from the aspects of the selection of resistant varieties, physical control, biological control, chemical control and integrated control, aiming to provide reference for subsequent research and disease control of grapevine downy mildew.

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.

Selenium is one of the trace elements required by human body, and it is very important for the survival and development of human beings. As a new type of bio-nanotechnology, the method of researching and preparing nano-selenium has attracted more and more attention and has broad application prospects. This article summarizes three methods of preparing nano-selenium, which are physical method, chemical method and biological method. It also introduces the synthesis of nano-selenium by biological method. This synthesis method has mild reaction conditions and fast reaction, and is pollution-free and sustainable, which is the best synthesis method among the three. This article also summarizes the common methods for characterizing nano-selenium in the past five years at home and abroad, such as transmission electron microscopy, Fourier infrared spectroscopy, X-ray diffraction and ultraviolet-visible absorption spectroscopy, and discusses the application direction of the selenium industry such as plant selenium supplementation, animal selenium supplementation and drug development, aiming to provide new ideas for the preparation of nano-selenium, and to explore the application prospects of nano-selenium.

The brand building of agricultural products is an important symbol of the construction of modern agriculture, which is conducive to promoting the transformation and upgrading of traditional agriculture to modern agriculture, and can provide a huge space for the development of regional agriculture and other industries. This study aims to fully discuss the research status of brand building of agricultural products in China by elaborating the role of branding of agricultural products and reviewing related studies. The study summarized the function of branding in improving the quality and competitiveness of Chinese agricultural products, promoting the industrialization development of agricultural products and boosting the revitalization of rural industries. It also discussed the brand building of ‘three products and one indication’ agricultural products (pollution-free agricultural products, green food, organic agricultural products and geographical indication of agricultural products), the brand building of characteristic agricultural products, and the regional public brand building of agricultural products; and explored the regional characteristics and existing problems of agricultural products’ brand building. Suggestions were put forward targeting the existing problems in order to provide reference for brand building of agricultural products, agricultural revitalization through quality and rural revitalization.

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.

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.

Leaf, as the material basis for constructing the rice organs, is closely related to the quality of the light environment and the utilization rate of light energy. The leaf area index (LAI) is an important indicator related to rice yield, and is significantly correlated with the light and effective radiation absorption coefficient in rice canopy. In this paper, we reviewed the relationship between the LAI in different growth periods of rice and the yield, and pointed out that the optimal LAI could be increased based on variety selection and cultivation measures, to achieve the high yield. The study could provide a theoretical basis for developing a predicting system of the optimal LAI and for regulating the rational canopy structure of rice.

The CRISPR/Cas9 system is a simple and efficient targeted gene editing technology, which has important application value in plant genetic improvement and crop genetics and breeding. This research mainly introduced the principle and construction method of CRISPR/Cas9, discussed the application and research progress of CRISPR/Cas9 in plant gene function and gene expression regulation, plant genome site-specific editing and crop molecular breeding in recent years. We analyzed the main influencing factors and the optimizing methods of this gene editing technology, as well as problems in its application and the solutions to the problems, and discussed the future development direction of the technology, thus providing reference for the application of CRISPR/Cas9 in plant genome editing and crop genetics and breeding.

Pesticide residues, as one of the key factors affecting the quality of Chinese herbal medicines, seriously affect the efficacy of medication, human health, and the development of the Chinese herbal medicine industry. The authors briefly summarized the status of pesticide residues in Chinese herbal medicines, including the types of Chinese herbal medicines examined, the types of pesticides frequently detected, and the types of pesticide residues. The authors also sorted out the advantages and disadvantages of the main analytical detection techniques for pesticide residues in Chinese herbal medicines, and the specific applications of chromatography and chromatography-mass spectrometry in the domain of pesticide residues in Chinese herbal medicines. The causes of pesticide residues in Chinese herbal medicines, such as indiscriminate use of pesticides and incomplete registration, different degrees of contamination in the cultivation and processing, and the imperfect residue limit standards of relevant pesticides, were reviewed, and certain suggestions for improvement were given for different causes, such as building green planting bases to guarantee the quality of Chinese herbal medicines from the source, enhancing pesticide registration management norms, developing pesticide residue detection methods with wide applicability, strengthening the knowledge of growers about pesticides, and improving pesticide residue limit standards.

The main active ingredient of Silybum marianum L. Gaertn is the flavonoid silymarin, which can inhibit damage, treat cardiovascular and cerebrovascular diseases, and has antitumor effect. It is especially effective in liver injury treatment. In this study, the current research progress of the medicinal plant Silybum marianum L. Gaertn is reviewed in terms of botanical characteristics, cultivation techniques, active ingredients and pharmacological effects. The study aims to provide reference for further improving the cultivation technology and developing the medicinal value of Silybum marianum L. Gaertn. It is found that Silybum marianum L. Gaertn can regulate plant growth and development under abiotic stress by affecting secondary metabolites, antioxidant enzyme activities and osmoregulatory substance content. In addition, the application of exogenous plant growth hormone can resist the external stress and promote the plant growth and development of Silybum marianum L. Gaertn. Moderate abiotic stress such as drought and salinity and alkalinity can improve the accumulation of active ingredients in Silybum marianum L. Gaertn.

Phytoplasmas are important prokaryotic pathogenic bacteria of many plant diseases, and can cause serious diseases in important food crops, vegetables, fruit trees, ornamental plants and trees, resulting in huge economic losses. In order to deeply understand the status, distribution and diversity of phytoplasma diseases in China and scientifically control phytoplasma diseases, this paper summarizes the research history, economic importance, symptom characteristics, epidemic and transmission, identification methods, geographical distribution and diversity of phytoplasma diseases in China. It is suggested that the research on phytoplasma diseases should be carried out from the aspects of screening resistant resources, identifying resistant genes, genome characteristics, pathogenic mechanism, disease epidemiology, control methods and mechanism of insect vector transmission.

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.

Accurate and efficient monitoring of animal information, timely analysis of animal physiological and physical health conditions, and automatic feeding and farming management combined with intelligent technologies are of great significance for large-scale livestock farming. Deep learning techniques, with automatic feature extraction and powerful image representation capabilities, solve many visual challenges, and are more suitable for application in monitoring animal information in complex livestock farming environments. In order to further analyze the research and application of artificial intelligence technology in intelligent animal farming, this paper presents the current state of research on deep learning techniques for tag detection recognition, body condition evaluation and weight estimation, and behavior recognition and quantitative analysis for cattle, sheep and pigs. Among them, target detection and recognition is conducive to the construction of electronic archives of individual animals, on which basis the body condition and weight information, behavior information and health status of animals can be related, which is also the trend of intelligent animal farming. At present, intelligent animal farming still faces many problems and challenges, such as the existence of multiple perspectives, multi-scale, multiple scenarios and even small sample size of a certain behavior in data samples, which greatly increases the detection difficulty and the generalization of intelligent technology application. In addition, animal breeding and animal habits are a long-term process. How to accurately monitor the animal health information in real time and effectively feed it back to the producer is also a technical difficulty. According to the actual feeding and management needs of animal farming, the development of intelligent animal farming is prospected and put forward. First, enrich the samples and build a multi perspective dataset, and combine semi supervised or small sample learning methods to improve the generalization ability of in-depth learning models, so as to realize the perception and analysis of the animal's physical environment. Secondly, the unified cooperation and harmonious development of human, intelligent equipment and breeding animals will improve the breeding efficiency and management level as a whole. Third, the deep integration of big data, deep learning technology and animal farming will greatly promote the development of intelligent animal farming. Last, research on the interpretability and security of artificial intelligence technology represented by deep learning model in the breeding field. And other development suggestions to further promote intelligent animal farming. Aiming at the progress of research application of deep learning in livestock smart farming, it provides reference for the modernization and intelligent development of livestock farming.

Biochar is an adsorption material with porous structure, which has a very wide application prospect in improving soil quality and repairing soil pollution. To explore the research layout and future development trend in the application field of waste biochar at home and abroad, relevant documents in the application field of waste biochar from 2000 to 2021 downloaded from the core collection database of Web of Science and the core database of China National Knowledge Infrastructure Network were taken as the research objects. Using CiteSpace and VOSviewer visual analysis software, WOS and CNKI’s own analysis tools, visual analysis was carried out from different angles, such as annual publication volume and publication trend, important research institutions, important journal sources and authors, keyword co-occurrence map and keyword emergence etc., to provide a theoretical basis for the preparation and application of biochar from waste. The results showed that the application of waste biochar was widely concerned at home and abroad. China had the largest proportion of publications in foreign language, indicating that China attached great importance to this field. At present, the focus of this field is agricultural and forestry waste, pyrolysis temperature, adsorption mechanism and so on.

Water-retaining agent, also known as superabsorbent polymer, has the ability of absorbing water and controlling the release of fertilizer, and can promote the growth of plants. Water-retaining agents can be synthesized from synthetic polymers, natural polymers, and combinations of organic and inorganic materials. The synthesis of water-retaining agent includes physical, chemical and hybrid bonding, which is mainly realized by bulk polymerization, solution polymerization, inverse suspension polymerization, radiation polymerization and other methods. Based on this, the basic concept, properties, mechanism of action, synthesis methods and classification of water-retaining agents are reviewed, and some existing problems are also discussed in this paper. It is pointed out that the future research focus of water-retaining agent should be on high salt resistance, reusable property and mass production potential.

Plant growth promoting rhizobacteria (PGPR) is a type of beneficial bacteria that can effectively alleviate the damage of salinity to plant, promote the absorption of mineral nutrients by plants and have a significantly antagonistic effect on pathogenic bacteria. Rational application of PGPR has extremely important application potential in stress resistance mechanism of plant, soil ecological remediation and breeding strategy improvement. In this review, we summarize the research progress of PGPR in promoting plant nutrient absorption, regulating plant hormone homeostasis and alleviating the damage of salinity to plant, and provide a theoretical basis for analyzing the application prospect of PGPR in future breeding improvement research.

Intelligent equipment is necessary to ensure stable, high-quality, and efficient production of facility agriculture. Among them, intelligent harvesting equipment needs to be designed and developed according to the characteristics of fruits and vegetables, so there is little large-scale mechanization. The intelligent harvesting equipment in Japan has nearly 40 years of research and development history since the 1980s, and the review of its research and development products has specific inspiration and reference significance. First, the preferential policies that can be used for harvesting robots in the support policies of the government and banks to promote the development of facility agriculture were introduced. Then, the development of agricultural robots in Japan was reviewed. The top ten fruits and vegetables in the greenhouse were selected, and the harvesting research of tomato, eggplant, green pepper, cucumber, melon, asparagus, and strawberry harvesting robots based on the combination of agricultural machinery and agronomy was analyzed. Next, the commercialized solutions for tomato, green pepper, and strawberry harvesting system were detailed and reviewed. Among them, taking the green pepper harvesting robot developed by the start-up company AGRIST Ltd. in recent years as an example, the harvesting robot developed by the company based on the Internet of Things technology and artificial intelligence algorithms was explained. This harvesting robot can work 24 h a day and can control the robot's operation through the network. Then, the typical strawberry harvesting robot that had undergone four generations of prototype development were reviewed. The fourth-generation system was a systematic solution developed by the company and researchers. It consisted of high-density movable seedbeds and a harvesting robot with the advantages of high space utilization, all-day work, and intelligent quality grading. The strengths, weaknesses, challenges, and future trends of prototype and industrialized solutions developed by universities were also summarized. Finally, suggestions for accelerating the development of intelligent, smart, and industrialized harvesting robots in China's facility agriculture were provided.

【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.

Crop maturity is the comprehensive performance reflection of crop growth, development and maturation. It is usually expressed by the growth period or life cycle from seedling emergence to harvest. It is also a critical indicator of crop ecological adaptability. The selection of cotton varieties with appropriate maturity is an important prerequisite to ensure normal maturity, high yield, superior fiber quality, and timely harvest. Accurate evaluation of cotton crop maturity is an important basis for cotton cultivation management and genetic improvement. Due to the indeterminate growth characteristic of cotton, the evaluation of cotton crop maturity is complicated, and there are still controversies so far. This manuscript clarifies the concept of cotton crop maturity, and discusses its main influencing factors (genetic factors, environmental factors, and cultivation measures), and reviews predictors and methods used for cotton crop maturity evaluation based on growth characteristics (the first fruit branch node, fruit branch occurrence speed and flowering time interval, pre-frost seed cotton rate, etc.), growth process (growth period, physiological termination period, the number of fruit branches above cracked boll, early maturity index, etc.) and the comprehensive index. In the end, the following suggestions have been given: enhancing the innovation of evaluation predictors for cotton crop maturity, establishment of the evaluation system for cotton crop maturity, and creation of an innovative information collection system, which will provide theoretical and technical support for cotton simplified and mechanized production.

Aiming at the application of transgenic technology in the improvement of staple food crops in China, this study described the principles and advantages of transgenic technology. The research progress of transgenic technology in the improvement of staple food crops (maize, wheat and rice) in China was reviewed. Moreover, the main application of transgenic technology in disease resistance, insect resistance, herbicide resistance and quality improvement of staple food crops in China was summarized. At last, the study put forward future research directions, expecting that people can better understand transgenic plants and treat the application and development of transgenic plants with a scientific attitude.

Salt stress is one of the most important abiotic stresses, which seriously threatens the growth and development of plants. Understanding the adaptive mechanisms of plant to salt stress is beneficial for the breeding of salt tolerant crops and the effective use of saline land to meet the increasing demand of food supply. Salt stress causes ion imbalance, osmotic derangement, and accumulation of toxic substances, especially reactive oxygen species (ROS), in plants. To adapt to salt stress, the plants have to balance cellular ions, remodel osmotic potential and maintain ROS. The former researches on the genetic, physiological and biochemical subjects have revealed a large number of plant regulators responding salt stresses, which might modulate plant salt tolerance through multiple and complex stress signal pathways. This paper reviews the salt sensing, signal transduction, gene expression regulation, phytohormone regulation and adaptive response of plants under salt stress, and provides a relatively complete summary of plant salt stress response mechanisms.

[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.