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Tomato Ripeness Detection Method Based On Improved YOLOv5 LIU Yang, GONG Zhi-hong, LI Zhen-fa, LIU Tao, ZHAO Zhuo, WANG Teng-ge Chinese Journal of Agrometeorology    2024, 45 (12): 1521-1532.   DOI: 10.3969/j.issn.1000-6362.2024.12.012 Abstract （1133）      PDF（pc） （10145KB）（150）       Knowledge map    Save In order to improve the recognition accuracy of tomato fruit ripeness and to realize online nondestructive automatic detection in tomato planting chain, this study proposes a tomato ripeness detection method based on improved YOLOv5. In the field of agriculture, accurate identification of tomato ripeness is very important, which can help agricultural production to rationalize labor arrangements and timely harvesting, thus improving the yield and quality of agricultural products. Traditional target detection algorithms face some challenges in tomato ripeness recognition, such as misidentification and missed detection, due to factors such as vines and leaf shading between tomato fruits and light interference. Therefore, this study had carried out a series of optimizations of YOLOv5 to address these problems in order to improve the accuracy and robustness of the algorithm. In the first place, an ECA efficient channel attention module was added to its backbone network Backbone, which generated channel weights by one-dimensional convolution and captured small targets that could be easily ignored in tomatoes of different ripening stages by interacting with the k neighboring channels of each channel, thus enhancing the expressiveness and accuracy of tomato features and effectively mitigating the effects of occlusion and light interference on the recognition results. Moreover, the PAFPN in the Neck structure was replaced by BiFPN with bidirectional weighted fusion capability. BiFPN was able to bi-directionally fuse features of different scales, which better handled the occlusion problem between tomato fruits and improves the accuracy of the recognition, and this optimization also mitigated the effect of multi-targets on the recognition accuracy, which enabled the algorithm to perform better in complex scenarios. Finally, a P2 module for small-target detection was added to the Head structure. The P2 module was able to better combine the advantages of shallow and deep tomato features to improve the detection performance of small-target tomatoes, so that it can accurately detect the target even when there are small-target tomatoes and other complex situations in the image. Through a series of ablation experiments, authors obtained the optimal improved algorithm YOLOv5-tomatoA. Compared to traditional target detection networks such as YOLOv3-Tiny, SSD300 and Faster R-CNN, the algorithm performs well in complex scenes such as occlusion and uneven illumination, with an average accuracy mean and F1 score of 97.4% and 95.4%, respectively, and the recognition of an image takes only 14.7ms, which can simultaneously satisfy the high-precision and fast-response tomato fruit recognition. The improved YOLOv5 network structure also optimizes the memory footprint and resource consumption, occupying only 15.9M, making the model more lightweight. This mean that the algorithm had low equipment requirements for realizing online non-destructive testing of tomato ripening, which can provide a more convenient real-time monitoring tool for agricultural activities. This technique can also be applied to the design of automatic tomato picking robots, which provides a strong support to realize the automation and intelligence of the tomato planting process. Therefore, this improved YOLOv5-tomatoA algorithm has important practical value in the field of tomato ripeness detection and is expected to provide more accurate and intelligent management decision support for agricultural production. Related Articles | Metrics | Comments（0）

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Heavy Rains and Floods Impact on Agricultural Product Supply Chain and Countermeasures CHEN Ning-yuan, ZHANG Xi-cai, NI fang-fang Chinese Journal of Agrometeorology    2024, 45 (10): 1236-1246.   DOI: 10.3969/j.issn.1000-6362.2024.10.12 Abstract （947）      PDF（pc） （371KB）（627）       Knowledge map    Save In the context of global climate change, Chinese mainland often faces the threat of heavy rainfall and flooding, and the impact of different regions is different, posing serious challenges to agricultural production and supply chain management. This paper analyzed the spatiotemporal heterogeneity of China's agricultural product supply chain, including complex origin distribution, seasonal production, diversified types of agricultural products, and the close connection of each link of the supply chain; analyzed the impact of heavy rain and flood disasters on the supply chain from planting to final sales, from farmland waterlogging and soil erosion in the production link, to road damage in the logistics and transportation link, the decline in the quality of agricultural products, and then to the price fluctuation and market uncertainty in the sales link. Post-disaster short-term relief operations and post-disaster long-term recovery and reconstruction measures. It aims to improve the resilience of agricultural supply chains, reduce agricultural losses, ensure the sustainability of agricultural product supply, and provide experience for future disaster risk management. Related Articles | Metrics | Comments（0）

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Reports on Weather Impacts to Agricultural Production in Summer 2024 WU Men-xin, LI Yi-jun, ZHAO Xiao-feng, HE Liang, LIU Wei Chinese Journal of Agrometeorology    2024, 45 (12): 1533-1535.   DOI: 10.3969/j.issn.1000-6362.2024.12.013 Abstract （783）      PDF（pc） （348KB）（205）       Knowledge map    Save The relationship between meteorological factors and agricultural production in China was analyzed using statistical methods, based on daily national meteorological data for the summer of 2024. The results showed that the national average temperature in the summer (June−August) was 22.4°C, 1.2°C higher than the average of the same period from 1961 to 2020 and the maximum value since 1961. The national average precipitation was 342.6mm, which was 20.7mm more than the average of the same period from 1961 to 2020. The national average sunshine duration was 630.0h, 35.1h less than the average of the same period from 1961 to 2020. In most of the agricultural region, the sunshine, heat conditions, and soil moisture content were suitable, and general meteorological conditions were favorable for the growth and production of grain crops. At the same time, the frequent meteorological disasters in the summer had a certain effect on the growth and yield formation of the autumn harvest crops. The North China and Huang-Huai region experienced drought and waterlogging, which affected the growth of summer sowing crops. The heavy rainfall occurred in Jiangnan and south China region, and some early rice suffered from "flowering-stage heavy rain" disaster. There was more precipitation in the central and southern parts of northeast China region, which affected the crop growth and yield formation. The Sichuan basin and the middle and lower reaches of the Yangtze river sustained high temperature weather, which affected the growth of single-season rice and local featured crops in some areas. Related Articles | Metrics | Comments（0）

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Research on the Construction of Knowledge Graphs for Agricultural Meteorological Disasters: A Review QIU Ming-hui, XIE Neng-fu, JIANG Li-hua, WU Huan-ping, CHEN Ying, LI Yong-lei Chinese Journal of Agrometeorology    2024, 45 (10): 1216-1235.   DOI: 10.3969/j.issn.1000-6362.2024.10.11 Abstract （657）      PDF（pc） （1642KB）（2561）       Knowledge map    Save Efficient utilization of massive heterogeneous data is the key factor to enhance the intelligence of agricultural disaster management. Therefore, it is important to explore techniques for constructing multi-source heterogeneous agricultural meteorological disaster knowledge graphs for dynamic monitoring of agricultural meteorological disasters and intelligent management decision making. This paper analyzed the data sources, types, and characteristics required for knowledge graph construction in the agricultural meteorological disaster domain through literature studies and proposed a framework for knowledge graph construction that combined top-down and bottom-up approaches. The paper also examined key techniques and the current application status of knowledge graph construction from the perspective of schema layer construction, entity extraction, relation extraction, and knowledge fusion. In addition, it explored the applications of agricultural meteorological disaster knowledge graphs in the fields of monitoring and early warning, risk assessment, intelligent service, and decision support. It summarized the challenges of constructing agricultural meteorological disaster knowledge graphs and discussed the future development directions. Integrating information from the different modalities could make knowledge graph more comprehensive and accurate in describing and expressing the knowledge and information in the field of agricultural meteorological disasters, which could help to mitigate the losses caused by agricultural meteorological disasters and improve the accuracy and efficiency of decision-making. In the future, agricultural meteorological disaster knowledge graph will be constructed by incorporating large language models, advanced knowledge extraction methods to achieve complex entity and relationship extraction, and multi modal data. Further research is needed to advance the technical study of agricultural meteorological disaster knowledge graph. Related Articles | Metrics | Comments（0）

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Impact Assessment of Extreme Climate Events on Maize Meteorological Yield in Northeast China by Machine Learning TANG Jie, DONG Mei-qi, ZHAO Jin, LI Hao-tian, YANG Xiao-guang Chinese Journal of Agrometeorology    2025, 46 (2): 258-269.   DOI: 10.3969/j.issn.1000-6362.2025.02.012 Abstract （605）      PDF（pc） （3065KB）（814）       Knowledge map    Save In the context of global climate change, the frequency, intensity, and duration of extreme climate events are increasing and strengthening, which greatly affects agricultural production. The three provinces in Northeast China are the main maize-producing areas in the country, and the region most significantly affected by climate change. It is crucial to explore the effects of extreme climate events on maize meteorological yield in the three provinces and safeguard China's food security and economic development. In the current study, a machine learning model was constructed based on the historical meteorological data and statistical maize yield data to clarify the impact extreme climate events on maize meteorological yield in northeast China during the historical (1981−2014) and future (2031−2060) periods. The results showed that high temperature and high- temperature-drought compound events had the greatest impact on maize meteorological yield during the historical period, with meteorological yield decreasing by 13.2% and 15.9%, respectively. Meanwhile, the extreme temperature events had a greater impact on maize meteorological yield compared to extreme precipitation events. In the future, the climate show a warming trend, Compared with the SSP1−2.6 (low−emission) scenario, the magnitude of maize meteorological yield reduction in Northeast China under the SSP5-8.5 (high-emission) scenario is more pronounced, and more attention needs to be paid to the impact of extreme precipitation events on maize meteorological yield in the future. Related Articles | Metrics | Comments（0）

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Temporal and Spatial Variations of Extreme Temperature and Precipitation Events in the Cropping Region across Northeast China LI Hao-tian, DONG Mei-qi, ZHAO Jin, TANG Jie, YANG Xiao-guang Chinese Journal of Agrometeorology    2025, 46 (2): 145-156.   DOI: 10.3969/j.issn.1000-6362.2025.02.002 Abstract （500）      PDF（pc） （9154KB）（340）       Knowledge map    Save  Global warming has led to a significant increase in the frequency of extreme weather and climate events, especially in northeast China, which is bound to affect the grain output of the three northeastern provinces. Based on historical ground meteorological observation data (1981−2014) and future climate change prediction data (2031−2060), this paper systematically analyzed the spatial−temporal distribution characteristics and future occurrence trends of extreme temperature and precipitation events by defining four extreme temperature indices and three extreme precipitation indices related to crop production. The results showed that the number of low temperature days (CD) decreased, the number of high temperature days (HD), low temperature intensity (CSI) and high temperature intensity (HSI) increased, the number of continuous wet days (CWD) decreased, the number of continuous dry days (CDD) increased, the number of heavy precipitation days (R20) decreased, the number of extreme high temperature days increased significantly and the extreme maximum temperature was the same as the historical stage. The extreme minimum temperature is in a state of warming. In the future, the overall temperature in the crop growing areas of the three provinces in northeast China would continue to rise, the number of continuous wet days would increase, the number of continuous dry and heavy precipitation days would decrease, and the precipitation variability and spatial difference would be large and the fluctuation range would be greater than the historical stage, and the uncertainty of abnormal precipitation would be strengthened, showing a trend of warming and drying, especially in the south and southeast. The results can provide reference for agricultural production in Northeast China to cope with climate change. Related Articles | Metrics | Comments（0）

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Monetization Evaluation of Greenhouse Gas Emission Reduction Benefits Based on Corn Stalk Pyrolysis Polygeneration Technology GU Ding-yuan, HUO Li-li, YAO Zong-lu, ZHAO Li-xin, YU Jia-dong, ZHAO Ya-nan Chinese Journal of Agrometeorology    2024, 45 (11): 1253-1264.   DOI: 10.3969/j.issn.1000-6362.2024.11.001 Abstract （497）      PDF（pc） （2086KB）（551）       Knowledge map    Save Biomass energy is a globally recognized renewable energy with zero carbon properties, but its carbon reduction benefits have not been effectively reflected. Based on the whole life cycle evaluation (LCA) method, combined with the economic benefit evaluation method and the environmental impact monetization method, this study built a EGE model for the greenhouse gas emission reduction benefit evaluation (EGE) of straw pyrolysis polygeneration technology. The EGE model took the whole chain of straw collection, off-field storage and transportation, pyrolysis transformation and product utilization as the boundary. The comprehensive economic and environmental benefits of different pyrolysis polygeneration technologies under different production scales was explored. The results showed that the external heating pyrolysis carbon gas co-production technology has the best economic benefits in large-scale application, and at the annual production scale of 0.5×104 ~ 10×104t of straw, each 1t of straw consumption can reduce 1.01−1.07tCO2eq. Greenhouse gas emission reduction could significantly improve the economic benefits of straw pyrolysis polygeneration technology projects, and each 1t of straw consumption could increase the benefit of 57.5−103.1 yuan, which increased the yield rate of straw pyrolysis polygeneration technology projects by 1.6−14.0PP. It is estimated that the utilization potential of straw in 2030 and 2060 would reach 1.24×108t and 1.67×108t respectively, and the emission reduction income of straw pyrolysis polygeneration technology can reach 1.0×1010−3.7×1010 yuan. The results of this study provide technical support for the development of biomass energy industry under the background of realizing the dual-carbon goal. Related Articles | Metrics | Comments（0）

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Characteristics of Climatic Seasonal Variation in Northeast China under the New Standard SHAO Qi-duo, FENG Xi-yuan, REN Hang, TU Gang, LI Shang-feng, LIU Gang, YANG Xu, WU Di Chinese Journal of Agrometeorology    2025, 46 (6): 741-752.   DOI: 10.3969/j.issn.1000-6362.2025.06.001 Abstract （487）      PDF（pc） （16028KB）（148）       Knowledge map    Save According to the national standard of Climate Seasonal Division (GB\T 42074−2022), the characteristics of seasonal variation in Northeast China (NEC) for the period 1961–2020 were analyzed using CN05.1 gridded data, and the changes caused by the shift of the standards and climatological baselines were investigated. The results showed that the climatic season of NEC was divided into regions with four seasons and non−summer zone regions, and the non−summer regions were mainly located in the northern part of the NEC, high−altitude regions and their surroundings. Spring and summer started from the south to the northeast, from the central plains to the high altitude mountains, and vice versa in autumn and winter. Compared with the 1981–2010 baseline period, parts of the Sanjiang plain and Hulun lake changed from non−summer regions to four−season regions. The starting dates showed a significant advance of 1d·10y−1 in spring over most of the NEC region, and a significant advance of 2−3d·10y−1 in summer over the central and western parts of the Northeastern plains. The starting dates were significantly delayed in autumn over the four-season regions, and in winter over the non−summer regions and the central of Northeastern plains. The summer and winter duration were significantly prolonged and delayed, respectively. Compared to the original standard, there were more areas with significant changes in spring and summer starting dates and summer and winter duration under the new standard. The areas up to the summer standard showed a significant upward trend of 3.9PP·10y−1 and had a significant positive correlation with the area−mean June−July−August NEC temperature. The rating of starting date of seasons obeys the normal distribution law, with a slight advance in summer. Related Articles | Metrics | Comments（0）

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System Theory, Resource Theory and Solution Ideas of the Current Problems Related to Agrometeorology PAN Zhi-hua, HOU Ying-yu Chinese Journal of Agrometeorology    2025, 46 (2): 270-274.   DOI: 10.3969/j.issn.1000-6362.2025.02.013 Abstract （429）      PDF（pc） （304KB）（343）       Knowledge map    Save In recent years, there has been a "wandering phenomenon" in the development of agrometeorology, and some key questions need to be answered effectively. Based on system theory and resource theory, this paper deeply analyzed the connotation of agrometeorology, and expanded the relationship between meteorological conditions and agricultural (crop) production, and provided ideas and solutions to related problems. The results showed that the elements such as atmosphere, soil, crops and technical conditions make up the agrometeorological system. Climatic factors were not only natural, but also productive, and were involved in the whole process of agricultural production. The functional relationship between crop production and meteorological conditions could be established. Agrometeorological indices were the dynamic combinations of meteorological elements. Technological conditions could change the availability of climatic conditions and the sensitivity of agricultural production to climate. There were three properties of climate resources: quantity, space-time potential and quality. Different combinations of elements of the hydrometeorological system determine different objectives. This research could play important role in promoting agro meteorology. Related Articles | Metrics | Comments（0）

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Immobiliaztion Effect of Arsenic in Contaminated Red Soils and Its Enzyme Activities after Application of Lanthanum-modified Biochar XIE Jin-ni, LI Lian-fang, LV Peng, WANG Zi-han, YAN Ao, KANG Meng-qi, ZHOU Xue, YE Jing Chinese Journal of Agrometeorology    2024, 45 (12): 1391-1404.   DOI: 10.3969/j.issn.1000-6362.2024.12.001 Abstract （410）      PDF（pc） （4305KB）（391）       Knowledge map    Save Biochar pyrolysis at high temperature with limited oxygen plays an important role in the resource utilization of agricultural waste, carbon sequestration and emission reduction, indicating the great potential of biochar for remediating contaminated environment. As a functional material for soil remediation, its ability of adsorption and fixation for heavy metals is still insufficient, which limits the large-scale promotion and application of biochar. Nowadays, it has been an increasingly important research area to enhance the adsorption and fixation capacity of biochar through modification design of engineered materials. In this study, wood chips were used as raw materials to prepare biochar (BC), and then lanthanum modified biochar (LBC) was manufactured. Aiming to remediate arsenic contaminated red soil and compare the immobilization difference, these two kinds of amendments (LBC, BC) were applied into the experimental soils separately, and the blank soil without material addition was used as control treatment. All these above treatments was cultivated for 30days under the soil moisture content with 30%, 70%, and 100% field water capacity respectively, and the corresponding remediation effects of arsenic contaminated red soil by using LBC and BC were investigated. The results were as following: (1) LBC addition was beneficial for alleviating the acidification of southern red soils. When the cultivation experiment was finished, soil pH treated by LBC was enhanced obviously and the increased pH ranged from 0.86 to 1.20 units under three kinds of soil moisture content with 30%, 70%, and 100% field water capacity. In comparison with BC treatment, the soil pH also increased by 0.09−0.44 units after LBC addtion. (2) LBC application led to the obvious immobilization effect of arsenic in red soils, and the related fixation efficiency under three kinds of soil water content was up to 54.7%−90.0% during the whole soil cultivation period, and the immobilization efficiency reached 81.0%−85.8% after 30days of cultivation. On the contrary, soil treated by BC resulted in the arsenic activation of soils with the increased percent 135.4%−895.9% compared to the control. (3) The immobilization effect of LBC on soil arsenic is mainly related to the transformation of arsenic in various speciation, especially from non-specialized adsorption forms to more stable ones such as residue forms. In the meanwhile, BC resulted in the enhancement of non-specialized adsorption arsenic and promoted the activation of soil arsenic. (4) LBC was capable of immobilizing arsenic in red soils with high efficiency, and did not obviously excert negative influence on soil enzyme activity. The application of LBC was able to improve the activity of soil urease and catalase although it led to a slight decrease in soil phosphatase and sucrase activities. It is worth mention that LBC treatment remained higher soil sucrase activities than those for BC treatments. Overall, it manifest that LBC has great potential for remediating arsenic contaminated red soil. Related Articles | Metrics | Comments（0）

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Report on Growing Season Agrometeorological Conditions of Autumn Harvest Crops in 2024 HAN Li-juan, SONG Ying-bo, ZHAO Xiao-feng Chinese Journal of Agrometeorology    2025, 46 (2): 275-280.   DOI: 10.3969/j.issn.1000-6362.2025.02.014 Abstract （408）      PDF（pc） （2227KB）（876）       Knowledge map    Save According to the observed meteorological data in 2024 and the historical data from 2467 meteorological stations and 653 meteorological stations in China, the agrometeorological evaluation index, climate suitability models, grid estimation methods for soil moisture and agrometeorological disaster index model were used to evaluate the agrometeorological effects on yield of major autumn-harvest crops, such as corn, single rice, later rice, soybean and cotton. The results showed that water conditions and thermal conditions were sufficient for the crop growth and development during the growing season. The impact of agricultural drought, continuous rain, sunless, rainstorm and flood disasters during the main growth season was light, while the meteorological conditions were favorable for crop development growth and yield. However, in Heilongjiang and Jilin, there was continuous low temperature and waterlogging from mid-May to June seriously affected the growth process of crops. In Henan and Liaoning, heavy rainfall was concentrated from July to August, and the waterlogging disaster was severe, resulting in reduced corn and soybean yields. In the Yangtze and Sichuan river basins from July to September, high temperature persisted for a long time, and heat damage to single rice plants yields. Related Articles | Metrics | Comments（0）

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Flood Loss Assessment for Crops Based on Hydrodynamic Modeling: A Case Study in the Jianghan Plain QIN Peng-cheng, ZHOU Yue-hua, LIU huo-sheng, XIA Zhi-hong Chinese Journal of Agrometeorology    2025, 46 (3): 420-431.   DOI: 10.3969/j.issn.1000-6362.2025.03.013 Abstract （392）      PDF（pc） （16431KB）（80）       Knowledge map    Save Crop loss assessment is critical for decision making in flooding management. From the perspective of disaster chain, flooding damage is a complex interaction of hazard factors (e.g., extreme precipitation), local topographic attributes and vulnerability of affected bodies, and thus characterized by large temporal and spatial variations. Developing a physically based modelling chain that can capture the dynamic evolution and spatial heterogeneity of the disaster process is critical for timely and efficient emergency response to flooding prevention. This study presented a modelling framework for estimating crop loss due to flooding, by coupling the flooding vulnerability curves with the Rainfall−Runoff−Inundation (RRI) model developed by the International Center for Water Hazard and Risk Management. The flooding vulnerability curve was shown as a function of inundation depth, duration and crop stage. A quantitative assessment of crop loss at gridded scale was established by integrating the inundation maps, crop distribution, and flooding vulnerability curves. The framework was applied to two representative flooding events on the Jianghan plain to demonstrate its capability to estimate crop losses due to rainstorm−induced flooding. The results showed that the RRI model could reasonably simulate the formation and retreat of the flooding peak as well as the surface inundation dynamics in accordance with the rainstorm, with the simulation error ranging from −14.8% to 11.5% for the runoff, the simulation accuracy exceeding 80% for the inundation area, the matching rate ranging from 84.2% to 87.1% for the inundation depth, and the estimated deviation of crop loss rate were −33.8% to 6.4%, −10.8% to −9.5%, and −6.0% to 1.8% for areas covered, areas affected and areas of total crop failure, respectively. The method proposed in this study provides a fundamental support for the rapid assessment and risk early warning for flooding mitigation and post−disaster reconstruction. Related Articles | Metrics | Comments（0）

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Optimization of Crop Planting Structure in Guizhou Based on the Water-Energy- Food Nexus HAN Shun-li, ZHANG Peng-fei, LU Yuan, ZHANG Jiao-jiao, LIU Geng, DAI Yan-yan, ZHANG Lei, GUO Li-gang Chinese Journal of Agrometeorology    2024, 45 (12): 1426-1437.   DOI: 10.3969/j.issn.1000-6362.2024.12.004 Abstract （370）      PDF（pc） （3037KB）（260）       Knowledge map    Save  The water and energy consumption characteristics of five crops (rice, corn, potato, rape and soybean) in Guizhou from 2010 to 2020 were analyzed using a water footprint and energy consumption accounting model based on relevant statistical data. Additionally, a multi-objective optimization model with constraints on water resources, energy, land, and food supply was developed to achieve optimal economic and ecological benefits, aiming to scientifically optimize the planting structure of five crops in Guizhou. The results showed: (1) there were significant differences in the water footprint and energy consumption per unit area of major crops in Guizhou during the period from 2010 to 2020. Specifically, rice, potato, soybean, corn, and rape were classified as extremely high water and energy-consuming crops, high water and energy-consuming crops, high water but medium energy-consuming crops, medium water and low energy-consuming crops, and low water and energy-consuming crops, respectively. (2) The water footprints of five crops were primarily dominated by green water consumption. Among them, rice, corn, and potato were the major contributors to the water footprint, accounting for 85% of the total. The energy consumption structure of five crops differed, with rice mainly consuming electricity, corn and potato mainly consuming chemical fertilizers, and rape and soybean primarily consuming fuel. Notably, rice and potato were the major contributors to the energy consumption, accounting for 69% of the total. (3) There were significant spatial variations in the crop planting structure in Guizhou due to differences in natural conditions. Specifically, rice was primarily distributed in the flat areas below 600m in altitude in southern Guizhou, corn was planted across the province but with varying qualities, potato was mainly cultivated in areas with altitudes ranging from 100 to 2900m, rape was primarily planted in central Guizhou, and soybean was cultivated in all regions with small differences in the proportion of each region. (4) After optimization, there was a slight decrease in the total planting area of five crops in Guizhou province. Notably, the planting area of rape and potato increased by 14000 and 146000ha respectively, resulting in their shares increasing by 0.6 and 1.6 percentage points, respectively. Conversely, the planting area of rice and corn decreased by 171000 and 386000ha, respectively, causing their shares to decrease by 0.3 and 1.5 percentage points, respectively. Following the optimization in Guizhou, there was a reduction in water footprint of 3.06 billion m³, a decrease in chemical fertilizer usage of 150 million tons, and a reduction in energy consumption of 2459000 GJ. Consequently, the ecological benefits have been significantly improved, while the economic benefits have remained stable. The optimized planting structure, based on the water-energy-food nexus, considers both economic and ecological benefits, exhibiting characteristics of low water consumption, low energy consumption, and low pollution. This further promotes the sustainable development of agriculture in Guizhou. Related Articles | Metrics | Comments（0）

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Potential Impacts of Climate Change on Rice Yield in Sichuan-Chongqing Area YANG Man-shan, GUAN Kai-xin, ZHANG Wen-meng, JIANG Chao-yue, LIU Zhi-juan, YANG Xiao-guang Chinese Journal of Agrometeorology    2024, 45 (10): 1146-1159.   DOI: 10.3969/j.issn.1000-6362.2024.10.005 Abstract （351）      PDF（pc） （24714KB）（133）       Knowledge map    Save  The cultivation of the double-cropping systems involving early and late rice was investigated within the Sichuan-Chongqing area, and a panel model was constructed based on historical meteorological data (1981−2020) and rice yield data (1997−2020) to analyze the impacts of future climate (2021−2060, SSP1−2.6 and SSP5−8.5) on rice yield in study area. The results showed that: (1) from 2021 to 2060, the rice yield in most areas of Sichuan and Chongqing would increase by 10.0% to 30.0% compared with the historical yield, and the southern and southeastern areas of Sichuan would decrease by 0 to 10%. (2) Under future climate change, the change of mean climate (precipitation and radiation) and extreme climate (high temperature and drought) would reduce rice yield by 0 to 2.0% in most areas of Sichuan and Chongqing, and the change of extreme state of precipitation would reduce rice yield by 0 to 2.0% in Chongqing and Dazhou. The impact of temperature on yield of early and late rice was very different. The impact of precipitation and radiation on yield of early and late rice was basically the same. During 2021−2060, the temperature, precipitation and radiation in most areas showed an upward trend, while the precipitation in a few areas (Chongqing and Panzhihua) showed a downward trend. While the change of precipitation and radiation, drought and high temperature led to the decrease of rice production in study area. The mean climate of radiation and the extreme climate of drought contributed most to rice yield under future SSP1−2.6 and SSP5−8.5, respectively. Under future climate change, the high and stable yield of rice should be ensured under extreme drought and high temperature events in Sichuan-Chongqing area. Related Articles | Metrics | Comments（0）

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Trend and Influencing Factors of Green Development of Sichuan Planting Industry LIN Xu, QI Yan-bin, XIE Wei Chinese Journal of Agrometeorology    2024, 45 (11): 1265-1275.   DOI: 10.3969/j.issn.1000-6362.2024.11.002 Abstract （323）      PDF（pc） （1566KB）（333）       Knowledge map    Save Ensuring food security and while achieving low-carbon development is a practical issue for the agricultural economy and the priority for carbon neutrality in the planting industry. Based on the time series data of Sichuan planting industry, the change of carbon emission and emission intensity was reviewed, and the input-output super-efficiency model was applied to evaluate the green development efficiency of Sichuan planting industry, and the influencing factors were analyzed by Tobit regression model. The results showed that carbon intensity of Sichuan planting industry decreased from 0.717 t to 0.208 t per 10000 yuan of GDP over the 2010−2022 period, with the continued expansion of the planting area being the core driver of the increase. At the same time, the green development trend of Sichuan planting industry showed the evolution characteristics of "continuous low efficiency− rapid stretching−stable development". In terms of influencing factors, the unique agricultural industrial structure and climate environment, as well as technological investment, have driven the green development of planting industry in Sichuan, while the high proportion of grain and oil crop cultivation was an objective challenge. The fiscal policy had improved the utilization level of planting industry to climate resources, but there was also a significant inhibitory effect. Therefore, while actively adapting to global warming, achieving a long-term balance between food security and green development of the planting industry, and guiding the green development willingness of planting entities with policy orientation, should be a direction that the government should continue to focus on. Related Articles | Metrics | Comments（0）

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Current Status and Development Trend of Food Life-cycle Carbon Emissions Research LIU Chang, SHANG Jie Chinese Journal of Agrometeorology    2024, 45 (10): 1131-1145.   DOI: 10.3969/j.issn.1000-6362.2024.10.004 Abstract （321）      PDF（pc） （5706KB）（443）       Knowledge map    Save The impact of food production and consumption processes on the environment has become increasingly apparent in the context of ongoing economic development and the environment. Especifically, the issue of greenhouse gas emissions in the life cycle of food has emerged as a major challenge in the realm of climate change and ecological balance. A comprehensive analysis of international and domestic research progress on food life cycle carbon emissions can reveal the research trends and frontier hotspots in this area. By conducting searches in English and Chinese literature databases, including the Web of Science (WoS) and China National Knowledge Infrastructure (CNKI), utilizing the scientific knowledge graph and the CiteSpace literature visualization tool, an in-depth analysis and visual representation were carried out. The results showed that research on carbon emissions from food lifecycle began to emerge internationally in 2003, while domestic attention to the issue began in 2009, and both had exhibited steady growth in their respective research activities. While Chinese research had largely emphasized the food production aspect, international research had taken a more holistic approach, encompassing research on both food production and consumption, the entire food system, and the supply chains. In addition, there was a greater emphasis internationally on the management of carbon emissions within food systems and supply chains, whereas Chinese research was more skewed towards the study of regional disparities. In the future, research on carbon emissions in the food lifecycle was likely to place increased emphasis on the equilibrium between food production and consumption, with emerging industries like food delivery services gaining attention. Regional disparities in food lifecycles’ carbon emissions were crucial for the sustainable development of regional food production and consumption. Hybrid life cycle assessment was poised to become a mainstream research method, with future research comprehensively evaluating multiple aspects of food life cycle carbon emissions. The effectiveness of policies is also set to be a key focus of future research aimed at driving carbon reduction in the food life cycle. Related Articles | Metrics | Comments（0）

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Climate and Land Use Change Effect on Natural Runoff in Shiyang River Basin CAO Jin-jun, MA Hai-hua Chinese Journal of Agrometeorology    2024, 45 (11): 1290-1301.   DOI: 10.3969/j.issn.1000-6362.2024.11.004 Abstract （320）      PDF（pc） （5279KB）（384）       Knowledge map    Save  Climate warming and human activities have a major impact on the spatial and temporal characteristics of surface runoff in the Shiyang river basin, and the adaptive management of water resources in the basin is facing serious challenges. With three independent drainage Dajinghe river system, Liuhe river system and Xidahe river system as the research object, the statistical method analyzed the average flow evolution in 1960−2020, using Mann-Kendall test and Pettitt test to determine the runoff sequence mutation point, set the combination of climate and land use change, and used SWAT model to identify the runoff variation in Shiyang river basin, addressing the unequal allocation of water resources. The results showed that: (1) from 1960 to 2020, the annual average runoff decline rate of Xidahe river, Liuhe river and Dajing river system was 0.01m3·s−1, 0.07m3·s−1, 0.01m3·s−1 respectively. The runoff years for the Liuhe river and Xidahe river were in 1973 and 2002, respectively, while the Dajing river system was in its natural state. (2) The SWAT model had a good adaptability to the Shiyang river basin, and the determination coefficient and the Nash efficiency coefficient were both higher than 0.50. (3) From 1960 to 2020, the contribution of precipitation, average temperature, relative humidity, solar radiation and average wind speed to the annual average runoff were 75%, 53%, 55%, 55%, and 52%, respectively. The contribution of land use change to the annual average runoff was 17%. The coupled contribution of six influence factors to annual average runoff reduction was 67%, indicating that climate change had great influence on runoff in Shiyang river basin. The research results could provide a reference for the adaptive management of watershed water resources. Related Articles | Metrics | Comments（0）

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Design and Evaluation on Meteorological Index Insurance Product of Rice High Temperature Heat Damage in Jiangsu Province REN Yi-fang, CHEN Si-ning, ZHAO Yan-xia Chinese Journal of Agrometeorology    2025, 46 (01): 1-13.   DOI: 10.3969/j.issn.1000-6362.2025.01.001 Abstract （311）      PDF（pc） （4441KB）（451）       Knowledge map    Save Based on an accurate assessment of the risks of agricultural production, together with the information required for insurance policies, the reasonable design and evaluation of insurance products is an important guarantee for the sustainable development of China's agricultural insurance policies. According to historical meteorological data as well as rice growth stage and yield data, based on the construction of meteorological index for rice high temperature disaster insurance, combined with comprehensive regionalization and assessment of insurance risk in Jiangsu province, by setting different deductible amounts, insurance pure rates were set and corresponding products were designed. In addition, a comprehensive evaluation of the effectiveness of the application of the rice heat damage meteorological index insurance product has been achieved by using three methods: index evaluation, historical retrospective analysis, and analysis of typical heat damage events. The study found that under different deductible amounts for yield reduction rates, the determined pure insurance rates for rice high-temperature heat damage in various counties in Jiangsu province exhibited a distribution pattern of "high in the southwest and low in the northeast". The deductibles were ultimately determined to be 2.5% for low-risk, 2.5% for medium-risk and 7.5% for high-risk areas, after taking into account the incentives for farmers to participate and the level of coverage. The corresponding pure insurance rates were determined to be 5.09%, 5.27% and 5.26% respectively. The designation of this index insurance product was relatively reasonable from the point of view of the company's operational efficiency, loss compensation pressure, level of risk transfer and coverage of the farmer's production. In low-risk, medium-risk, and high-risk areas, the operational sustainability indices of insurance companies were 14%, 37%, and 76%, respectively, while the stability indices of farmer production security were 6%, 9%, and 21%, respectively, and the average compensation rates for high-temperature heat damage events were 111%, 122% and 303%, respectively. In typical high-temperature heat damage years, the average compensation amount in Jiangsu province exceeded 1800 yuan·ha−1, and the number of compensation counties accounted for more than 50%. The results of this study may serve as references for the evaluation of the operational characteristics of meteorological index insurance products, as well as for the adjustment of insurance product design schemes, and the promotion and implementation of insurance products.       Related Articles | Metrics | Comments（0）

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Different Varieties and Planting Densities Influence on the Transpiration Rate of Xinjiang Cotton ZHAO Ming-ze, ZHANG Ze-shan, WANG Xue-jiao, SONG Yan-hong, SUN Shuai, HU Yan-ping, PARHAT Maimaiti, ZHANG Li-zhen, BAKE Batur, LI Jie Chinese Journal of Agrometeorology    2024, 45 (11): 1357-1368.   DOI: 10.3969/j.issn.1000-6362.2024.11.010 Abstract （297）      PDF（pc） （6725KB）（288）       Knowledge map    Save To study the impact of different varieties and planting densities on the transpiration rate of cotton in Xinjiang, a field experiment was conducted in 2022 in Wulanwusu, Xinjiang. Three cotton varieties (' Zhongmian 979'  ' Zhongmian 703'  and 'Guoxin cotton' ) and two planting densities (D1:22 plants·m−2; D2:11 plants·m−2) were establish for treatment. The transpiration rate was measured using a heat ratio stem flow meter, and the differences in daily average transpiration, daily transpiration change, and cumulative transpiration of cotton under different weather conditions (sunny, rainy) and time scales were compared to clarify the water consumption rules of cotton under different varieties and densities in northern Xinjiang. The results showed that: (1) planting density had a significant impact on the cumulative and daily transpiration rates of cotton population. The cumulative and daily transpiration rates of cotton increased significantly under D1 planting density. Under D1 planting density treatment, the cumulative and daily transpiration rates of three varieties were significantly higher than those under D2 planting density treatment (an average increase of 51.2%). (2) Cotton varieties had a significant impact on individual and group transpiration, with ' Zhongmian 703'  higher stem flow rate, daily transpiration rate, and cumulative transpiration than other varieties. (3) The transpiration of a single cotton plant showed a "几" shaped variation pattern on a daily scale. During the day (9：00−21：00), the transpiration was relatively stable, but there was still a slight stem flow at night due to root pressure. (4) The transpiration rate and amount of cotton decreased month by month from July to September. The daily transpiration curve of cotton in September gradually transitioned to a unimodal pattern, and the daytime transpiration starts later (10：00) and ends earlier (20：00). (5) Accumulated transpiration had a positive correlation with both seed cotton yield and average leaf area, but it was not significant. Related Articles | Metrics | Comments（0）

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Report on Agrometeorological Conditions Analysis during Growing Season of Summer Harvest Crops in 2024 ZHENG Chang-ling, GUO An-hong, ZHAO Yun-cheng, ZHAO Xiao-feng, HE Yan-bo Chinese Journal of Agrometeorology    2024, 45 (10): 1247-1252.   DOI: 10.3969/j.issn.1000-6362.2024.10.13 Abstract （278）      PDF（pc） （429KB）（507）       Knowledge map    Save Based on the measured data of about 1800 meteorological observation stations and 295 agrometeorological stations in the main production region of summer grain and oil crops in China from 2023 to 2024, the climate suitable index and disaster index were used to analyze the agrometeorological conditions in the growing season of major summer harvest crops, including winter wheat and rape. The results showed that there were sufficient thermal conditions and sunlight in the main production region during the winter wheat and rape growing season. At the same peirod, precipitation was excessive, while soil moisture conditions were suitable for crop growth and development. In addition, agricultural meteorological disasters such as late frosts, waterlogging damage and drought had relatively light effects. Crop diseases and pests were closely and effectively guarded against, so that they only occurred on a small scale. The weather during maturity stage was clear and favorable for mechanized wheat harvesting operations. The wheat harvest progresses faster than usual and ahead of the previous year （1991-2020）, resulting in a high harvest quality. However, the increase in rapeseed yields had been affected by multiple rounds of rain, snow and freezing damage in winter, periodic cloudy rain in mid spring, and strong convective weather in the middle and lower reaches of the Yangtze river, especially in Hunan and Hubei provinces. Overall, the winter wheat growing season was generally better than the previous with the higher climate suitability, while the meteorological conditions during the rape growing season were close to the 2023. Related Articles | Metrics | Comments（0）