Adversity stresses have a significant impact on global crop productivity. Salicylic acid (SA), an endogenous hormone produced through plant metabolism, serves as an important biomarker reflecting plant stress. In-situ detection of SA signaling in plants is crucial for timely understanding of plant's internal status and optimizing growth conditions. Herein, we present a wearable microneedle sensor for in-situ, real-time and nondestructive monitoring of SA concentration in growing plants. The sensing electrode features a high-density microneedle array (494 needles/cm2) fabricated via 3D printing, providing a large specific surface area for sensing. The sensitive film of the sensing electrode is composed of Cu-MOFs/SWCNT/CB/Nafion nanocomposites. This sensor demonstrates high sensitivity (793.4 nA/μM), a low detection limit (1.06 μM), excellent selectivity, and robust anti-interference capability. Integrated with a self-adhesive hydrogel as a flexible substrate, the device forms a stable and biocompatible plant-wearable sensing patch. Furthermore, by combining the sensor with a handheld electrochemical workstation and a smartphone, we have developed a portable intelligent sensing system capable of precise and real-time monitoring of SA concentration within growing plants. The sensor system successfully tracked the dynamic fluctuations of endogenous SA levels in cucumber plants under various stress conditions, such as low temperature and salt stress, demonstrating its potential as a powerful tool for basic research on plant stress physiology. Its practical application holds great potential for advancing smart agriculture and enhancing crop productivity.

Accurately estimating the wheat yield potential under climate changes is essential for assessing food production capacity. However, studies based on crop modeling and imperfect management experiment data frequently underestimate the wheat yield potential. In this study, we evaluated wheat yield potential based on the CERES-Wheat model and a well-managed 10-year (2008-2017) field study in the North China Plain (NCP), and further identified the critical climate and management yield-limiting factors for improving wheat yield potential and closing the wheat yield gap. Our results revealed that wheat yield potential averaged 10.8 t ha-1 in the recent decade. The low growing degree days (GDD) in the pre-winter growing season (592 degrees C d) and solar radiation in the whole growth season (3,036 MJ m-2) are the most critical climatic factors limiting wheat yield potential in the current production system. Nonetheless, wheat yield potential in the NCP is projected to decline during 2040-2059 by 1.8 and 5.1% under the representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios, respectively, without considering the elevated CO2 concentration. However, the positive influence of CO2 fertilization will be sufficient to offset these negative impacts from climatic warming and solar dimming, ultimately leading to an enhancement in wheat yield potential during 2040-2059 by 7.5 and 9.8% compared to the baseline under RCP4.5 and RCP8.5, respectively. To improve the wheat yield potential, we recommend selecting an appropriate planting date (5 October) and planting density (400 plants m-2) that align with light and temperature conditions during the wheat growing season. In addition, optimizing the timing and rate of water application (three times, 270 mm) and fertilizer use (based on in-season root zone nitrogen management) is crucial for closing the wheat yield gap. This study underscores the importance of adopting multiple management practices that account for complex climate-crop-soil interconnections to enhance the wheat yield based on a long-term field experiment under the changing climate.

As the source of data acquisition, sensors provide basic data support for crop planting decision management and play a foundational role in developing smart planting. Accurate, stable, and deployable on-site sensors make intelligent monitoring of various planting scenarios possible. Recent breakthroughs in plant advanced sensors and the rapid development of intelligent manufacturing and artificial intelligence (AI) have driven sensors towards miniaturization, intelligence, and multi-modality. This review outlines the key technologies in developing new advanced sensors, such as micro-nano technology, flexible electronics technology, and micro-electromechanical system technology. The latest technological frontiers and development trends in sensor principles, fabrication processes, and performance parameters in soil and different segmented crop scenarios are systematically expounded. Finally, future opportunities, challenges, and prospects are discussed. We anticipate that introducing advanced technologies like nanotechnology and AI will rapidly and radically revolutionize the accuracy and intelligence of agricultural sensors, leading to new levels of innovation.

Studying the risk propagation mechanisms in agricultural systems is crucial for maintaining agricultural stability and promoting sustainable development. This research analyzes the risk effects and risk propagation mechanisms in agricultural systems using the DCC-t-Copula-CoVaR model, multi-layer network structures, and the mixed-frequency regression MIDAS model. The study finds that there is significant heterogeneity in risk spillover and absorption in agricultural systems; the risk propagation in agricultural systems is stable, and the stronger the connectivity of industry nodes, the greater the risk. Taking the seed industry as an example, its structural indicator values consistently range between 1.0 and 1.1, with fluctuations closely linked to industry development and policy adjustments. Major risks are caused by risk resonance across multiple industries, not triggered by a single industry alone; the interconnections between industries within the agricultural system can disperse risks, forming a collective risk-sharing mechanism. Understanding these dynamics is essential for developing resilient agricultural practices that support long-term sustainability, ensuring food security, and mitigating environmental impacts. By addressing risk propagation and fostering interconnected risk-sharing mechanisms, agricultural systems can better adapt to challenges such as climate change, resource scarcity, and market volatility, ultimately contributing to a more sustainable and stable global food system.

Agricultural insurance is instrumental in consolidating the gains of poverty alleviation and advancing rural revitalization. It significantly aids in the efficient allocation of agricultural production factors, which in turn enhances agricultural output and bolsters the evolution of modern agriculture. Therefore, utilizing data from 583 household surveys and employing endogenous transformation and intermediary effect models, this paper analyzes the production factor allocation effect and specific mechanism of agricultural insurance. It focuses on small-scale farmers and new agricultural operators, exploring how insurance contributes to the advancement of modern agricultural practices. The results show the following: (1) Agriculture insurance can significantly affect the agricultural scale input behavior of farmers such as land input scale and input scale, agricultural machinery application behavior such as the degree of mechanization and water conservancy application, agricultural technology adoption behavior, and planting structure selection behavior, thereby helping to modernize agriculture. (2) There is heterogeneity in the impact of agriculture insurance on the allocation of production factors for small farmers and new agricultural operators. For small farmers, agriculture insurance has a significant promoting effect on their agricultural machinery application behavior, agricultural technology adoption behavior, and planting structure selection behavior. For new agricultural operators, agriculture insurance significantly promotes their agricultural scale input behavior, agricultural machinery application behavior, and agricultural technology adoption behavior. (3) In terms of the mechanism of action, agriculture insurance mainly promotes agricultural scale input behavior through land transfer, facilitates agricultural machinery application behavior by purchasing agricultural machinery equipment and services, encourages agricultural technology adoption behavior by strengthening agricultural technology training, and enhances professional production levels by increasing the scale of insured planting, thereby contributing to the development of modern agriculture. Based on this, several policy suggestions have been proposed. These include enhancing the directionality of agriculture insurance policies, improving the collaborative interaction mechanism between agriculture insurance and agricultural credit financing, and adopting certain reward and punishment measures to curb moral hazard.

This study aimed to identify warning thresholds that can guide sellers in achieving reasonable profits while reducing buyer payment costs. Monthly price data from January 2009 to June 2023 and the two-regime threshold regression model were used for an empirical analysis of the asymmetric effects of the changes in household consumption under different pork price fluctuation levels to verify that the changes in household consumption have significant pork price fluctuation thresholds and threshold effects. It was found that as the fluctuation of pork prices approached the threshold, the temporary price-intervention policy (e.g., reference price) effect of adjusting prices diminished. An empirical analysis was conducted from the perspective of asymmetric effects of the upstream (feed and piglets), midstream (live pigs), and downstream (pork) of price transmission. The impacts of the products in the upstream and midstream of the industry chain on pork prices declined gradually, and among the products, the impact of the prices of feeds for fattening pigs on pork prices was found to be the weakest. Thus, the price intervention policy (e.g., reference price) based on the pork price threshold suggests that strengthening the supervision of the price fluctuations of midstream products (e.g., controlling the profit margin) when the pork price fluctuation is near the threshold (8.24%) would have more significant effects on all sides.

Maize and soybean are important grain and oil crops in China. Being the first grain crop in China, maize is important feed and raw materials for industrial uses, while soybean constitutes the major raw materials for animal protein feed. Hence, both are essential and strategic agricultural products related to people’s livelihood worldwide. This paper mainly analyzed the changes in production, consumption, trade and price of maize and soybean in China, and applied the CAMES model to predict the trends in maize and soybean production, consumption, trade and price in the next decade (2024-2033) based on certain hypotheses of economic and social conditions and agricultural production conditions. According to the study, supply and demand of maize in China will witness regional balance in the foreseeable future, when maize imports will constantly decrease and the maize self-sufficiency rate will exceed 97%. In the meantime, imported soybeans will still be the major source for domestic feed use, with Brazil and the United States as the major importers. Despite the high imports, the self-sufficiency rate of soybean in China will keep rising and soybean imports will decrease due to the decline in feed processing and the increase in domestic soybean production capacity. In addition, this study also introduced the domestic and international uncertainties facing the supply and demand of maize and soybean in China in the future.

Understanding the effects of climatic factors on maize yield will benefit tactical decisions for future agricultural forecasting. In this study, the relationship between maize yield and meteorological factors has been estimated on the basis of daily meteorological data during the growing season and maize yield observation data from 1970 to 2022 on the island of Nguazidja. The specific maize growth stages most sensitive to meteorological factors were divided into six stages: emergence, jointing, tasseling, flowering, filling and harvesting. First, a simple regression is carried out with the tendency model. Yield and years are included. We then analysed the effect of meteorological factors on each stage of maize growth using the orthogonal Chebyshev polynomial regression. It was found that rainfall has a generally positive influence on yield growth. Temperature has a significant negative effect on yield during the emergence and filling stages. The key point is that meteorological factors have an effect on maize yield throughout the growth season. The degree of impact of each meteorological factor during the growing season is not the same. The first step is to understand that maize needs higher temperatures, especially during the emergence period. On the other hand, rainfall sometimes provides more water than is needed. The aim of this research is to provide clear information on the impact of climatic factors on maize yields. This is a study that has not yet been carried out in the country. And the results are important for forecasting maize yields in the Comoros.

当前中国数字普惠金融快速发展,逐步取代传统融资方式,并成为一种更加多样化以及更具包容性和可靠性的融资方式.基于2011—2021年农业上市公司数据和数字普惠金融指数构建面板模型,并进行稳健性检验与异质性检验,探讨数字普惠金融对农业上市公司融资约束的影响机制.研究发现:数字普惠金融的发展有助于缓解农业上市公司面临的融资约束,数字普惠金融与农业上市公司融资约束存在明显的负相关性;农业上市公司信贷可得性作为传导机制发挥了重要作用;经过内生性检验发现,数字普惠金融对农业上市公司融资约束具有改善作用的结果较为稳健.另外,数字金融对农业上市公司的融资约束存在异质性,即规模越大的上市公司受到数字金融发展的影响越显著.最后,提出了推动数字普惠金融缓解农业上市公司融资约束的对策建议.

为合理评价我国粮食安全状态,基于2001-2021年我国6个省份(湖北、湖南、江西、安徽、河南和山西)的面板数据,构建粮食安全评价指标体系,通过TOPSIS熵权法从数量安全、环境安全、质量安全、生态安全和贸易安全等5个子系统角度对粮食安全状态进行评估,并提取出单位耕地面积粮食产量、农业机械化水平和粮食生产财政支出等5项关键影响因素.结果表明,(1)在整体层面,中部6个省份的粮食安全状态经历了先下降再缓慢上升最后快速上升的3个阶段;(2)在子系统层面,数量安全和质量安全子系统呈稳定上升趋势,生态安全和环境安全子系统变化相对平缓,且存在下降趋势,贸易安全子系统回调后迅速上升;(3)在关键因素层面,单位耕地面积粮食产量、农业机械化水平和粮食生产财政支出是影响粮食安全状态的关键因素.通过对粮食安全评价体系的研究,提出了相应的改进措施,使其更加客观、科学、全面,在具有代表性的中部地区进行了实证研究,为深入理解我国粮食安全问题提供了有价值的参考.

[目的]乡村振兴是中国新时代经济社会发展的重要战略,粮食安全是乡村振兴的重要方面之一.[方法]从生产资料、生产投入、生产效率、经济效益、产出效率和生态环境六个层面构建了粮食安全监测指标体系.通过对2000-2021年时间序列数据的分析,合成了中国粮食安全监测预警指数,并根据指数确定了粮食安全的警戒等级和警线标准,以此来评估粮食安全的发展水平.[结果]乡村振兴战略与粮食安全监测预警之间相互支撑;农业、农村和农民三个层面均得到了有效改善;粮食产能提升的效果显著.[结论]2000-2009年间,中国粮食监测预警指数处于高风险和较高风险区间,2009-2012年处于中等风险区,2013-2016年处于较低风险区,2017至2021年处于低风险区;根据预测结果未来五年中国粮食安全监测预警指数仍然处于低风险区.

[目的]文章旨在介绍人工智能技术在种植业领域的应用现状和发展方向,分析当前面临的挑战,并提出相应的建议.[方法]首先,将人工智能技术在种植业中的应用分为农情智能感知技术、农情信息通信技术、农情信息处理技术、农情智能装备和农情智能管理.其次,针对应用中存在的问题进行分析,并指出当前中国人工智能技术在种植业领域发展所面临的挑战.最后,提出相关建议以应对这些挑战.[结果]人工智能技术在种植业领域的应用已经取得了显著成效,可以优化种植策略,提高效率,降低成本,减少浪费和损失.然而,在应用中仍面临一些挑战,主要集中在数据资源掌握与应用、技术开发与核心技术以及认知理念与管理方式三方面.[结论]为了进一步推动人工智能技术在种植业中的应用,实现农业高质量发展,该文提出以下建议:一是重视数据管理与保护,确保数据的质量和安全;二是强化关键技术研发能力,加强人工智能在种植业中的核心技术研究;三是完善监管与复合人才的培养机制,建立健全的政策法规和培训体系.

Context: China produces more than 20 % of maize grain in the world, and Northeast China (NEC) accounts for similar to 30 % of the nation's total maize production. Previous studies have used either climate data, satellite data, or crop growth model (CGM) to predict or forecast maize yield. However, maize is highly susceptible to the effect of extreme climate events (such as drought, heat) in NEC, and there is a lack of studies to predict/forecast maize yield by integrating climate data, satellite data, extreme climate events, and CGM-simulated data. Objective: We aim to develop a hybrid approach with machine learning to blend different sources of data (climate data, satellite data, extreme climate events) and process-based modelling results to improve predictive accuracy of maize yield in NEC. Methods: Using maize data from 44 sites during the period of 2000-2013 in NEC, we firstly optimized Agricultural Production System sIMulator (APSIM) using Differential Evolution Adaptive Metropolis combined with Gaussian likelihood function and Bayesian multiplication method. Next, we divided the growing season into five phases, and selected variables of different phases using exploratory data analysis and Random Forest. Then, we developed a hybrid model using Random Forest by blending of multiple sources of data and APSIM simulations to predict maize yield from the start to the end of the growing season, and quantified the relative contribution of predictors. Results and conclusions: A hybrid model developed with random forest by combining climate data, NDVI, extreme climate events and APSIM simulations can achieve high performance for predicting yield toward the end of the growing season. The accuracy of in-season yield prediction showed a linear increase with MAPE/KGE changing from 19 %/0.05 to 13 %/0.53 from start to end of the growing season. Yield forecasts are acceptable with RMSE/MAE of 1.20/1.01 Mg ha(-1) (16 %/13 % of the observed mean yield) approximately one-month prior to harvest. The most important predictor that affect yield forecast was APSIM-simulated biomass or yield, and the most important extreme climate event was drought during early grain-filling stage. Significance: With the increasing availability of crop-related data, we expect that the in-season forecasting capacity of the proposed methodology could be further improved, and the methodology can be extended to other crops and other regions for yield forecast.

为准确判断我国饲料粮消费需求及其变化趋势,本研究结合饲养规模和结构变化,科学测算了主要动物性产品的饲料粮转化系数,并采用需求法对我国饲料粮消费量和消费结构进行了重新测算.结果表明:1)肉类产品单位耗粮数量明显高于鸡蛋、牛奶和水产品,其中猪肉最高.从饲料粮转化系数来看,我国耗粮型家畜比重逐步减少,节粮型产品产量迅速增长,畜禽产品供给结构逐步优化.2)养殖规模对不同畜禽品种的影响差异较大,生猪规模化养殖的单位耗粮数量高于散养户,肉牛、肉羊、蛋鸡和奶牛规模化养殖更加节约用粮,肉鸡中等规模养殖耗粮最低.3)2000-2020年我国饲料粮消费先快速增长后有所下降,2020年7种动物性产品生产预计消耗3.06亿t饲料粮.从结构来看,生猪饲料粮消费量最大,但其占比由2000年的57.54％下降至2020年的42.89％.从空间格局来看,我国饲料粮消费量大致呈"东高西低".

In 2013, the government officially approved the construction task of developing high-standard farmland, which had been written into the outline of the “12th Five-Year Plan”, the “13th Five-Year Plan” and the “14th Five-Year Plan”, effectively ensuring the sustainable development of farmland with high and stable yield in China. Moreover, with the rapid progress of urbanization and industrialization, the quality and usage of cultivated land have changed greatly, and the relationship between the economic value, social value and ecological value of land has become increasingly prominent. Whether the development of high-standard farmland, especially the high-standard farmland used for grain production, has achieved the goals of increasing farmers’ income, agricultural output and rural development is not clear. Therefore, it is necessary to evaluate the comprehensive benefits of high-standard farmland development in grain production, so as to scientifically measure the results of the development. From the perspective of economic, social and ecological benefits, this paper establishes an entropy weight evaluation index system and a model to evaluate the level and effectiveness of high-standard farmland development from 2013 to 2020 in China. The results show that the high-standard farmland development project has improved the yield of grain and the basic productivity of cultivated land, effectively increased the yields of land in the project area and promoted the protection and improvement of cultivated land quality, which includes soil quality improvement, soil fertility enhancement, pollution control and soil remediation. The project also helped raise the farmers’ income levels and improved farmers’ agricultural knowledge and skills in the project area. The projects are very beneficial for agricultural production, the farmers’ income and rural development. However, there is still a certain gap between the national average level of improvement and the original goal set in the policy. The average grain yield per mu (Note: 1 mu ≈ 0.0667 ha, similarly hereinafter) was expected to be increased by less than 100 kg (the national average was a 40 kg increase), and the degrees of improvement in economic, social, ecological and comprehensive benefits in different project types were also different. In the future, we suggest that the project should be implemented according to local conditions and the features of each region. We should pay attention to the protection of basic farmland quality and further improve grain output to achieve the goal of stabilizing and increasing production.

In this pape, AHP-entropy weight method is used to evaluate the state of food security in China. The "dual carbon" target will be incorporated into the evaluation system of food security, and a food security index system including "dual carbon", production security,structural benefit, technological input and sustainable development was constructed. Centering on the internal logic of "emission reduction-production-consumption", China’s food security situation during the "13th Five-Year Plan" was evaluated. The results showed that during the "13th Five-Year Plan" period, the overall coordination capacity of China’s food security showed a steady upward trend. The "dual carbon" target and environmental protection were firstly decreased then increased, consumption was stable, the surplus was slightly increased, and financial and technological input has strongly supported China’s food security. Trade development appeared W-shaped fluctuation, there was a high degree of uncertainty.

信息化的发展程度已经成为决定农业现代化水平的重要标志.新一代信息技术正在全球范围内引发新一轮科技革命,加快与现代农业深度融合.基于Web of Science核心合集数据库,采用专业数据分析工具DDA和VOSviewer引用分析功能,重点分析了国内外农业信息化领域近10年发展态势和技术热点.研究表明,全球和中国农业信息技术论文数量均呈现出整体增长态势,近3年加快增长;国际上影响力较强的机构主要有美国农业部农业研究院、荷兰瓦赫宁根大学、法国国家农业研究院等;技术方面,遥感技术和农业通信技术研究最多,遥感技术和信息化设备联系更为紧密;从新兴趋势看,人工智能趋势明显,分类算法、深度学习、卷积神经网络、随机树分类器等作为新兴技术热点应该引起重点关注.基于此,未来中国推动农业信息技术发展应着眼全球,借鉴国际经验,与高水平机构加强国际合作,引领农业信息科技创新.

开展农业废弃物资源化利用,是推动农业绿色发展的重大任务和举措.目前中国的秸秆综合利用和畜禽粪污资源化利用已经取得较大进展,标准化工作获得积极推进,但仍存在制约农业废弃物资源高效利用与管理的标准化难题.从秸秆、畜禽粪污的利用现状出发,梳理了农业废弃物标准化研制现状,发现在农业废弃物资源化利用中存在标准实用性集成性不足、标准体系不完善两大问题.基于此,为进一步推动农业废弃物资源化高效利用,提升利用效率评价的科学化和程序化,为农业废弃物资源化高效利用和管理能力提升提供支撑,从构建科学合理的标准体系、加强数据监测与评价管理规范、加大科技创新与应用等方面提出了标准需求建议.

Real-time noninvasive monitoring of crop water information is an important basis for water-saving irrigation and precise management. Nano-electronic technology has the potential to enable smart plant sensors to communicate with electronic devices and promote the automatic and accurate distribution of water, fertilizer, and medicine to improve crop productivity. In this work, we present a new flexible graphene oxide (GO)-based noninvasive crop water sensor with high sensitivity, fast responsibility and good bio-interface compatibility. The humidity monitoring sensitivity of the sensor reached 7945 Ω/% RH, and the response time was 20.3 s. We first present the correlation monitoring of crop physiological characteristics by using flexible wearable sensors and photosynthesis systems, and have studied the response and synergistic effect of net photosynthetic rate and transpiration rate of maize plants under different light environments. Results show that in situ real-time sensing of plant transpiration was realized, and the internal water transportation within plants could be monitored dynamically. The synergistic effect of net photosynthetic rate and transpiration of maize plants can be jointly tested. This study provides a new technical method to carry out quantitative monitoring of crop water in the entire life cycle and build smart irrigation systems. Moreover, it holds great potential in studying individual plant biology and could provide basic support to carry out precise monitoring of crop physiological information.

大豆作为国际上主要的农产品,其发展情况在期货市场和现货市场都具重要意义.大豆指数的编制情况与编制方法一直广受关注.以推动大豆产业发展为主要目标,从产业链视角出发,探讨各指标要素在大豆产业发展中的权重,通过平衡不同权重,编制了涵盖大豆产量、大豆面积、大豆进口量、大豆价格、大豆消费量等指标的大豆发展指数.此外,在2000—2020年大豆发展指数的基础上,预测了2021—2025年的大豆产业发展情况,根据大豆发展指数,未来中国大豆产业发展趋势将逐渐好转.