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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 （1256）      PDF（pc） （10145KB）（159）       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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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 （988）      PDF（pc） （3065KB）（936）       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 （876）      PDF（pc） （9154KB）（357）       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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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 （872）      PDF（pc） （348KB）（216）       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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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 （790）      PDF（pc） （2227KB）（1067）       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 （773）      PDF（pc） （16431KB）（101）       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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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 （556）      PDF（pc） （16028KB）（159）       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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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 （518）      PDF（pc） （3037KB）（286）       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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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 （463）      PDF（pc） （304KB）（369）       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 （445）      PDF（pc） （4305KB）（413）       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 Meteorological Impacts to Agricultural Production in Autumn 2024 HE Yan-bo, ZHAO Xiao-Feng, WU Men-xin, GUO An-hong, YAN Hao, ZHENG Chang-ling Chinese Journal of Agrometeorology    2025, 46 (3): 432-434.   DOI: 10.3969/j.issn.1000-6362.2025.03.014 Abstract （407）      PDF（pc） （382KB）（211）       Knowledge map    Save  In the autumn of 2024 (September−November), the national average temperature was 11.5°C, which was higher than the average of the same period from 1991 to 2020, and consecutively increased in the sixth year as well as created a new high record since 1961. The national average precipitation was 134.4mm, and 14.4% more than the same period from 1991 to 2020. The national average sunshine hours were 536.5h, and 6.0% less than the same period from 1991 to 2020. In most agricultural areas across the country, the light and heat conditions in autumn were relatively good to the crops. The first frost date in the northeast China was later than usual, and the cold dew wind had little impact on the late rice in the south part of China. The meteorological conditions were conducive to the filling and ripening, harvesting, drying of autumn-harvest crops and sowing of autumn-planted crops. Overall, the harvest and planting activates progressed smoothly in autumn of 2024, excluding the periodic droughts in the eastern part of the Sichuan basin and the middle and lower reaches of the Yangtze river, which affected the quality improvement of economic forest fruits and the sowing and emergence of autumn rapeseed. Nearing to the end of this period, a cold snap weather caused heavy snowfall mainly in the northeastern part of Inner Mongolia and northeast China, which is unfavorable for agricultural and pastoral production.  Related Articles | Metrics | Comments（0）

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Research on Optimized Configuration of Wind/Solar/Precipitation Resources over Guizhou Province under Changing Climate ZHANG Jiao-yan, CHEN Zhen-Hong, LI Zhong-yan, WANG Shuo, LI Yang Chinese Journal of Agrometeorology    2025, 46 (3): 339-349.   DOI: 10.3969/j.issn.1000-6362.2025.03.006 Abstract （382）      PDF（pc） （19740KB）（93）       Knowledge map    Save Based on the monthly near−surface wind speed (sfcWind), surface downwelling short wave radiation (rsds) and precipitation (pr) from the 5 global climate models that participated in the phase 6 of the Coupled Model Intercomparison Project (CMIP6), the ERA−5 reanalysis data and the 83 observational stations over Guizhou, the characteristics of wind/solar/precipitation resources in Guizhou under three scenarios (SSP1−2.6, SSP2−4.5 and SSP5−8.5) were evaluated, using Quantile-Mapping to improve the simulation capabilities. The results showed that compared to the reference period (1995−2014), although there was little change in the relative anomalies of sfcWind under SSP2−4.5 and SSP5−8.5, the relative anomalies of sfcWind under SSP1−2.6 increased statistically significant at the level of 0.01 over Guizhou during 2025−2100, as well as rsds and pr under three scenarios, with growth of 1.22 percent points·10y−1 (sfcWind, SSP1−2.6), 1.32/1.65/1.88 percent points·10y−1 (rsds, SSP1−2.6/2−4.5/5−8.5) and 1.77/1.88/2.97 percent points·10y−1（pr, SSP1−2.6/2−4.5/5−8.5）. Besides, the increases in rsds and pr were found generally in Guizhou during 21st century with respect to 1995−2014, rising from west (near) to east (far) under three scenarios, while sfcWind had different change for different scenarios and areas. Taking the wind/solar/ precipitation resources at the 14 representative stations under SSP2−4.5 in Guizhou during the near−21st century for example, the within and cross−regional complementarity was detected. Citing the case of Weining station from Jan to Dec, the seasonal complementarity was indicated due to making full use of solar/precipitation resources in summer and wind resource in winter/spring. Related Articles | Metrics | Comments（0）

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Development of a Growth Conditions Dataset of Major Crops in China (V2.0) GAO Jing, LIAO Jie, YANG Bing-yu, LIU Yuan-yuan Chinese Journal of Agrometeorology    2025, 46 (5): 725-736.   DOI: 10.3969/j.issn.1000-6362.2025.05.013 Abstract （375）      PDF（pc） （6104KB）（312）       Knowledge map    Save A dataset of the growth conditions of major crops in China was mainly constructed from paper-based annual records before 2012 and electronic annual records after 2013. However, there were problems such as inconsistencies in the observed items and data units，the quality of some data had not been evaluated. To improve the consistency and accuracy of agricultural meteorological data, based on these two types data, a high-quality dataset of the growth conditions China's major crops (including wheat, rice, maize, cotton, oil-seed rape, soybean and peanut) from 1981 to 2022 was developed by using the observation items standardization, integrity checks, cross-year value checks, observation time checks, value range checks, internal consistency checks element limit value check and manual verification. The dataset promoted effective application in agricultural research and decision-making. The results showed that the valid rate of crop common stage from 1981 to 2022 was over 96.0% of the expected observations, while the valid rate for growth status, crop height, stem count and effective stem count were all over 86.0%. The accuracy rate of the above five mentioned elements were above 99.3%. The distribution of observation stations for the seven major crops had obvious spatial and temporal distribution characteristics, with dense stations, uniform spatial distribution and long observation years in eastern China, but sparse and short observation years in northwest China. There were also obvious differences in the number of observation stations between different crops, and the number of observation stations for cotton and oil crops were less than that for staple crops. The valid data was relatively low in the 1980s, but improved significantly after 1994. After quality control and data verification, the valid rate of crop common stage increased from 94.7% to 96.2%, the crop height increased from 88.2% to 92.0%, the stem count increased from 77.1% to 86.7%. The accuracy rate of the common stage data increased from 99.3% to 99.6%. Compared to the "China Major Crops Growth and Development Dataset V1.0"，the overall quality of this dataset has been improved, with the addition of element boundary value checks. This dataset can provide critical fundamental information for studying the impact of climate change on the growth and development of major crops in China. 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 （369）      PDF（pc） （4441KB）（484）       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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Determination of Pure Premium Rates for Huangshan Maofeng Tea Frost Damage Based on ANUSPLIN LIU Rui-na, WANG Xiao-dong, LIU Hong-min, YANG Tai-ming, ZHANG Hui, ZHAO Xing-yu Chinese Journal of Agrometeorology    2025, 46 (01): 122-132.   DOI: 10.3969/j.issn.1000-6362.2025.01.012 Abstract （334）      PDF（pc） （6457KB）（449）       Knowledge map    Save  In order to improve the rationale for determining the premium rate for weather index insurance for tea frost damage in Anhui province. In this paper, authors refined and revised the meteorological index for tea frost damage in Huangshan based on historical disaster data. The ANUSPLIN interpolation software was used to establish the spatial interpolation model of the meteorological indices. Based on historical meteorological data from Huangshan, a refined risk assessment of tea frost damage in Huangshan was conducted with the help of a geographic information system. Taking Huangshan Maofeng tea as the research object, the risk assessment results and tea economic output were comprehensively considered to determine the insurance district and insurance period of tea frost damage, and the weather index trigger value and premium rate during some period were also designed considering daily tea frost risk and actual needs of agricultural insurance operation, and the insurance pure premium rates of tea frost damage at different periods and altitudes were calculated. The results showed as follows: the extreme minimum temperature (Td) 3°C was used as the threshold value of tea frost damage index, according to the interval of 1℃, the tea frost damage index were divided into 2℃<Td≤3℃, 1℃<Td≤2℃, 0<Td≤1℃, −1℃<Td≤0, −2℃<Td≤−1℃, −3℃<Td≤−2℃ and Td≤−3℃ 7 disaster grades, the corresponding average loss rates of tea buds were 5%, 15%, 25%, 35%, 50%, 70% and 90% respectively. The distribution of frost damage risk in Huangshan had an obvious regional characteristics, with higher the altitudes having a higher risk of frost damage, and the time series showing a decreasing trend with time. The insurance region of the weather index of tea frost damage of Huangshan Maofeng was 400−1000m above sea level, and the insurable period was from March 16 to April 15, when the extreme minimum temperature reached 2℃ to trigger the compensation. The insurance pure premium rates at 400−500m, 500−600m, 600−700m, 700−800m, 800−900m and 900−1000m above sea level were 1.4%, 1.9%, 2.7%, 3.7%, 4.9% and 6.4% respectively. The insurance pure premium rates for the four periods of coverage from March 16 to March 30, March 21 to April 4, March 26 to April 9, March 31 to April 15 were 1.2%−5.0%, 0.9%−3.8%, 0.6%−2.2% and 0.3%−1.5% respectively. The insurance-only premium rate for tea frost damage in Huangshan Maofeng shows an increasing trend with altitude and a decreasing trend with time delay.  Related Articles | Metrics | Comments（0）

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Risk Assessment of Low-temperature Disaster on Peony in Heze, Shandong Province ZHANG Cui-ying, GUO Jian-ping, ZHAI Jian-qing, HAO Xiao-lei, WANG Jun-lin, CAO Jie Chinese Journal of Agrometeorology    2025, 46 (2): 249-257.   DOI: 10.3969/j.issn.1000-6362.2025.02.011 Abstract （332）      PDF（pc） （4583KB）（353）       Knowledge map    Save Peony is an important specialty cash crop in Heze city, Shandong province. Low temperature and freezing damage in spring is the main meteorological disaster faced by peony in Heze city, which not only affects the flowering time and yield of peony, but also affects the local characteristic tourism and economic benefits. This study was based on the observational data of 9 national meteorological stations from 1978 to 2020 and 150 regional automatic stations since 2005, as well as the phenology and disaster data of peony in Heze, Shandong province. Firstly, the cold air and frost processes were identified, and a single-disaster hazard assessment was carried out by selecting typical disaster factors for example the duration days, maximum the drop of daily minimum temperature, extreme minimum temperature of cold air processes and the days, mean temperature, minimum temperature of frost disaster. Secondly, the risk index of low temperature disaster was obtained by weighted sum of the single disaster hazard. Finally, the low temperature disaster risk of Mudan in Heze was quantitatively assessed based on the three-factor methodology of hazard, exposure and vulnerability. The results showed that Juye county and Yuncheng county of Heze city had the largest proportions of high level hazard areas of low temperature disaster, which were 9.8% and 9.5% respectively. The proportions of areas with high level hazard in Caoxian county and Mudan district were the smallest, both less than 0.3%. Affected by low temperature risk and peony exposure, the high risk areas of low temperature disaster mainly distributed in the northeast and southeast of Heze city. In addition, the urban area of Mudan, where peonies were mainly planted, had a higher risk of low temperature disaster leading to a greater risk of peony disaster. The central and western areas were low risk areas, especially the western, southern and eastern parts of peony area, where the risks of low temperature disaster were lower. This research suggested that the planting area of ornamental peony can be expanded to increase the economic benefits of flower farmers. The results can provide basic support for optimizing the planting structure and sustainable development of peony in Heze. Related Articles | Metrics | Comments（0）

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Potential Distribution Region for Chinese Ampelopsis grossedentata Based on the MaxEnt Model ZHOU Wei, ZHONG Yan-wen, CHEN Yu-gui, LI Yan Chinese Journal of Agrometeorology    2025, 46 (2): 213-225.   DOI: 10.3969/j.issn.1000-6362.2025.02.008 Abstract （318）      PDF（pc） （8157KB）（164）       Knowledge map    Save Based on the current 193 geographical distribution data and 34 environmental variables such as bioclimate, altitude, and radiation, the maximum entropy model (MaxEnt) was used to simulate potential distribution areas and change characteristics of Ampelopsis grossedentata under three kinds of future climate scenarios. In order to make full use of climate resources and provide scientific basis for Ampelopsis grossedentata planting, protection and industrial development. The results showed that: (1) the prediction accuracy of the MaxEnt model was relatively high, with an AUC value of 0.928 to 0.956. (2) The six key environmental variables that affect Ampelopsis grossedentata distribution were precipitation in the driest month, precipitation of driest quarter, annual rainfall, monthly average radiation in May, altitude, and minimum temperature of coldest month. The thresholds of key environmental variables in the highly suitable region were 30-90mm, 130-300mm, 1600-2450mm, 14000-15200KJ·m−2·d−1, ＜1100m and 4.0-9.0℃, respectively. (3) Under the SSP126 scenario, the area of highly and moderately suitable region for Ampelopsis grossedentata could be increased. The area of suitable region from 2081 to 2100 was the largest at 1.822 million km2. SSP245 scenario was not as effective as SSP126 scenario in increasing the region of suitable region. However, it was stronger than SSP585 scenario, which was mainly reflected by an increase in the highly suitable regions of Guangdong, Guangxi, Fujian, Yunan, and Hunan that had degenerated, and an increase in the moderately suitable regions of southeastern Sichuan. Under the SSP585 scenario, some high-probability regions in Guizhou, Fujian, Guangdong and Jiangxi had gradually degenerated into medium-probability regions, and the middle-probability region in Hainan had degenerated into low-probability regions, and the total number of suitable regions in China from 2081 to 2100 was the lowest in history. (4) From 2041 to 2100, the total suitable region of Ampelopsis grossedentata only increased under the SSP126 climate scenario, and decreased under the SSP245 and SSP585 climate scenarios. Regardless of the climate scenario, the centroid of the total suitable area will move away from the current junction of Hunan and Guangxi, and it would move 46 to 80 km to the south of Hunan, slightly to the north and east. Related Articles | Metrics | Comments（0）

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Wind and Rain Disaster Loss Separated Methods from Typhoon in Guangdong Province LIU Wei-qin, TANG Li-sheng, XIE Li-jiang, HE Yan Chinese Journal of Agrometeorology    2025, 46 (01): 80-88.   DOI: 10.3969/j.issn.1000-6362.2025.01.008 Abstract （304）      PDF（pc） （672KB）（279）       Knowledge map    Save  The lack of separate statistics on wind and rain damage by disaster-causing factors in the typhoon disaster data in Guangdong is a contributing factor to the existence of typhoon catastrophe index insurance basis risk. To mitigate this basis risk, this paper proposes a method to separate typhoon wind and rain damage. An analysis was conducted on the typhoon disaster data from 2014 to 2022 for 36 counties (districts) in nine coastal cities in Guangdong, focusing on wind and rain indicators. A multiple regression method was employed to construct a typhoon wind and rain disaster loss separation model, which separated the disaster loss due to wind and rain in the typhoon disaster statistics of each county (district). Furthermore, the typhoon observation data and direct economic loss data from Jiangmen Taishan city and Xiangqiao district of Chaozhou were presented as case studies to illustrate the model's validation. Linear correlation analysis showed that eliminating or reducing the effect of multicollinearity on the regression equation at the beginning of modeling may result in the loss of some valid information. The Gamma distribution was found to appropriately fit the distribution pattern of typhoon wind, rain, and damage in Guangdong. The results indicated that 22 counties (districts) passed the significance test at the 0.05 level. The model successfully separated wind- and rain- related damage in Guangdong's typhoon disaster loss statistics, providing a valuable reference for categorizing and analyzing typhoon disaster data by cause. Related Articles | Metrics | Comments（0）

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Variation and Relationship between Tea Tree Canopy Temperature and Atmospheric Temperature TAO Yao, YU Yan-wen, YANG Ai-ping, WU Wen-xin , CHEN Jiao-jiao, CAI Zhe, ZHANG Xiao-fang Chinese Journal of Agrometeorology    2024, 45 (12): 1438-1449.   DOI: 10.3969/j.issn.1000-6362.2024.12.005 Abstract （300）      PDF（pc） （1065KB）（258）       Knowledge map    Save The difference of canopy-air temperature can indirectly monitor the variation of tea tree heat and moisture. However, the time lag effect between the tea tree canopy temperature and atmospheric temperature of tea plantation will affect the monitoring effect. In order to explore the time lag effect and the variation law between canopy temperature and atmospheric temperature, the variation characteristics of tea tree canopy temperature and atmospheric temperature of tea plantation during different tea picking seasons and different weather types were analyzed based on the monitoring data of microclimate station in tea plantation and near national meteorological station in Wuyuan from March to September in 2020. The simulated models of daily average canopy temperature and atmospheric temperature of tea plantation according to different weather types were established through the linear regression method and tested to provide data support for tea meteorological service. The results showed that: (1) the diurnal variation of tea tree canopy temperature and atmospheric temperature of tea plantation showed an obviously single-peak trend during different tea picking seasons and different weather types, while the change intensity of canopy temperature was greater than that of atmospheric temperature of tea plantation, and the peak time of canopy temperature was generally about 1h earlier than that of atmospheric temperature of tea plantation. (2) The point temperature difference of tea tree canopy and atmospheric temperature of tea plantation within 24h a day were generally ranked as spring tea＞autumn tea＞summer tea, sunny days＞cloudy days＞rainy days. In general, the canopy temperature was above or near to the atmospheric temperature of tea plantation around noon, while the canopy temperature was lower than the atmospheric temperature of tea plantation at all times in rainy days. (3) From the aspects of daily average temperature, it showed that the canopy was generally lower (1-2℃) than which in the atmosphere, but the changing trend was the same. (4) All kinds of daily average temperature prediction models were approved by 0.01 level significant test, which meaned the simulation effect were good generally. What’s more, the simulation effect of the atmospheric temperature of tea plantation prediction models were better than that of canopy temperature. In addition, under different weather types, the optimal effect of the prediction models were demonstrated in rainy days, followed by sunny days, and relatively poor in cloudy days. Related Articles | Metrics | Comments（0）

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Evolution Characteristics Analysis of Drought and Flood in Nanjing from 1470 to 2012 YUAN Yuan, SHI Yi, ZHANG Lu, DONG Jin-fang, LU Rong, XIA Bin, LIN Yan, CAI Dan-ping Chinese Journal of Agrometeorology    2025, 46 (3): 281-289.   DOI: 10.3969/j.issn.1000-6362.2025.03.001 Abstract （298）      PDF（pc） （1797KB）（338）       Knowledge map    Save Re-establishing a current rule on the grading of drought and flood in Nanjing from 1470 to 2012, based on historical drought and flood grades data in Nanjing from 1470 to 1950, monthly precipitation data from Nanjing National Basic Meteorological Station from 1951 to 2012 and the drought and flood grades standards for precipitation classification in "Chinese Map Collection of Drought and Flood Distribution in the Past Five Hundred Years". Morlet wavelet analysis and moving mean t-test were used as the research methodology to analyze the evolution characteristics of the drought and flooding grade series in Nanjing from 1470 to 2012. The result showed that between 1470 and 2012, it experienced 160 years of drought, 167 years of flooding and 216 years of normal conditions in Nanjing. Severe floods, severe droughts occur frequently and intensively. The occurrence of droughts and floods in Nanjing showed distinct phases. Drought dominated from 1470 to 1554, 1625 to 1652, and 1912 to 2012. From 1653 to 1805 and from 1849 to 1912, the normal dominated. Between 1806 and 1848 there was a significant alternating pattern of droughts and floods, and the region had experienced more droughts than floods over the past century. The drought and flood levels in Nanjing also exhibit multi−scale periodic oscillations, with the most significant oscillations occurring on time scales of 2−8y and 10−20y. Following these, there were long-period oscillations on the scales 64y, 32y, and 16y. At the present, the Nanjing region had entered a period of oscillation within the 2−8y period. In different time series, significant drought−flood mutations occurred around the years in 1554, 1615 and 1914, characterizing the climatic evolution of dry periods-pluvial periods-dry periods. Since the 20th century, the duration of moderate flood in Nanjing had been shortened by a trend towards aridity.  Related Articles | Metrics | Comments（0）