Top Read Articles

Published in last 1 year |  In last 2 years |  In last 3 years |  All

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Application Effectiveness and Problems of Biodegradable Mulch GUO Bo, YANG Zhen-xing, HE Wen-qing, LIU Jia-lei Chinese Journal of Agrometeorology    2023, 44 (11): 977-994.   DOI: 10.3969/j.issn.1000-6362.2023.11.001 Abstract （1491）      PDF（pc） （625KB）（1029）       Knowledge map    Save Mulch film mulching cultivation technology not only increases agricultural production and income, but also causes serious pollution problems because of the long-term use of polyolefin mulch film and low recovery rates. In areas with serious mulch film residue, the soil structure is seriously damaged, the quality of cultivated land is reduced, agricultural operations are blocked, and crop emergence, nutrient absorption and root growth and development are restricted. Biodegradable mulch film can be degraded by microorganisms such as bacteria, fungi and actinomycetes in the natural environment, and finally decomposed into CO2 and H2O, which not only has no pollution to soil but also promotes the growth and development of crops, and has become one of the effective ways to solve the problem of white pollution. With the deepening of the research on biodegradable mulch film, people found that biodegradable mulch film has different effects on soil environment and crop yield, and these effects are quite different in different regions and crops. It is not possible to directly draw the conclusion that biodegradable mulch film is better than PE mulch film through one or several experiments. In this paper, the effects of biodegradable mulch film on soil environment, crop growth and yield in recent years were summarized, and the experimental effects of biodegradable mulch film (BM) and mulch mulch film (PE) were compared, and their advantages and disadvantages were analyzed, and suggestions were put forward to improve the performance of biodegradable mulch film, so as to continuously improve the performance of biodegradable mulch film and realize the sustainable development of agricultural science and technology. Summary and analysis show that: (1) Biodegradable mulch film can increase soil temperature and humidity, meet the needs of crops in the early stage of growth, accelerate the emergence of seedlings, shorten the growth cycle, and have beneficial effects on soil organic matter, available nitrogen and soil enzyme activity, and improve soil nutrient content. In terms of microorganisms, biodegradable mulch film can promote the growth of soil microbial content and soil respiration rate. At the same time, biodegradable mulch film has better weed control ability than PE mulch film, among which black biodegradable mulch film has the best effect, which can effectively reduce the number of weeds in the field and ensure the supply of nutrients needed by crops. (2) In terms of crops, biodegradable mulch film can promote corn growth, shorten the growth period and increase the yield in the early and middle stages of corn growth. There was no significant difference between the yield of cotton seed cotton covered with biodegradable mulch film and PE mulch film, and the yield of cotton seed cotton covered with mulch film is significantly higher than that of bare land. The potato treated with biodegradable mulch film germinated faster in the early growth stage because of the increase of soil temperature, which significantly shortened the growth cycle and brought it to market earlier, and significantly increased the yield compared with PE mulch film and bare land, among which the black biodegradable mulch film had the most obvious effect. For millet crops, there was no significant difference in yield between the treatment with biodegradable mulch film and the treatment with PE mulch film, and the yield of the treatment with mulch film was significantly improved compared with the treatment with bare land. For vegetable crops such as tomato, eggplant and beet with short growth cycle, biodegradable mulch film can play the role of heat preservation and moisture increase for a long time, and promote the rapid growth of crops. The final yield is not significantly different from that of PE mulch film mulching treatment, even slightly improved, and significantly improved compared with bare land treatment. (3) Put forward the influence of different components of biodegradable mulch film on soil and crops, controllable degradation and cost problems, such as the difficult control of degradation speed, environmental problems caused by incomplete degradation of biodegradable mulch film, low technical maturity and high price, and put forward suggestions for future research and development, so as to modify and innovate biodegradable raw materials, reduce costs and regulate the degradation mechanism of biodegradable mulch film. Strengthen the research on raw materials, formula and production technology of biodegradable mulch film, and develop new biodegradable mulch film with high performance and multifunction, which can meet the regional applicability and crop applicability at the same time, and lay a theoretical foundation for the popularization and application of biodegradable mulch film to more regions and more crop varieties. Related Articles | Metrics | Comments（0）

Select

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 （1220）      PDF（pc） （10145KB）（157）       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）

Select

Influence Report of Weather on Agricultural Production in Summer 2022 ZHAO Xiao-feng, HAN Li-juan, LI Sen, HE Liang, LIU Wei Chinese Journal of Agrometeorology    2022, 43 (11): 945-948.   DOI: 10.3969/j.issn.1000-6362.2022.11.008 Abstract （1165）      PDF（pc） （359KB）（425）       Knowledge map    Save In the summer of 2022 (June-August), the national average air temperature was 22.3℃, which was 1.1℃ higher than the same period of the normal year(1991−2020). There were sufficient thermal resources in major agricultural areas. The national average high temperature days reached 14.3d, which was 6.3d more than that in the same period of from 1991 to 2020, and had been the maximum value since 1961. The national average precipitation was only 290.6mm, being the second smallest in the same period since 1961. The national average sunshine duration was 677.4h, which was close to the same period in the normal year and 53.7h more than that in 2021. The weather in most summer-harvesting areas was fine, which was conducive to the full maturity and quality improvement in grain and oil crops. There were two obvious precipitation events in late June, which effectively alleviated the previous drought in the northern summer-sowing areas. However, the deviation of soil moisture was not conducive to timely summer planting in some areas in Shaanxi and Gansu. Most of the agricultural areas were exposed to sufficient light and heat, with no occurrence of obvious cloudy and rainy weather. There was abundant precipitation and suitable soil moisture in the northern agricultural areas, which was in favor of the growth, development and yield formation for local crops such as corn and soybeans. The continuous high temperature and lack of rain in the southern agricultural areas led to the development of agricultural drought and heat stress for crops such as rice and maize. The meteorological conditions limited the stable growth of crops, economic trees and fruits. Superimposed precipitation occurred in Liaoning and Shandong, resulting in waterlogging in some lowland areas. Moreover, periodical low temperature in early June and late August affected the growth, development and grain filling of -harvesting crops in the Northeast. Related Articles | Metrics | Comments（0）

Select

A Review of the Response Characteristics of Soil Respiration to Temperature and Moisture Changes under Global Climate Change RAN Man-xue, DING Jun-jun, SUN Dong-bao, GU Feng-xue Chinese Journal of Agrometeorology    2024, 45 (01): 1-11.   DOI: 10.3969/j.issn.1000-6362.2024.01.001 Abstract （1132）      PDF（pc） （724KB）（1767）       Knowledge map    Save Warming of the climate and changes in precipitation patterns are major manifestations of climate change and abiotic factors affecting soil respiration. Authors presents a systematic analysis of recent research advances on the effects and mechanisms of temperature and moisture on soil respiration. The results show that:（1）there is positive feedback between soil respiration and climate warming, but the temperature adaptation weakens this positive feedback. The effect of temperature on soil respiration varies spatially and temporally due to the different duration of warming and soil carbon storage. The main mechanisms of soil respiration adaptation to temperature include soil microbial adaptation, substrate depletion and soil mineral activation.（2）The effect of precipitation on soil respiration depends on the initial soil water content. When soil water content is lower than the wilting factor, precipitation not only increases soil water content but also promotes soil respiration, reaching a maximum when soil water content is close to the field holding capacity, while soil respiration is inhibited when soil water content reaches saturation value. The main mechanisms by which water affects soil respiration are substitution and blocking effects, substrate supply, microbial stress and root response. （3）The coupling of soil respiration with soil temperature and moisture depends on the ratio of soil water and heat factors. When soil temperature becomes a stress factor, the stimulating effect of increasing soil water content induced by precipitation on soil respiration is suppressed by the negative effect of low temperature. When soil moisture becomes a stress factor, the promoting effect of increased soil temperature due to climate warming on soil respiration is counteracted by the negative impact of drought. The interaction between soil temperature and moisture should be fully considered when studying soil respiration. In order to understand the disturbance factors of soil carbon emissions in terrestrial ecosystems, this paper proposes that future research on the relationship between soil respiration and the environment under climate change. Firstly, strengthen the research on the effects of multi-factor interaction on soil respiration and quantify the soil respiration components. Secondly, continue to pay attention to the characteristics of soil respiration in response to initial soil temperature and temperature fluctuations, and to explore the effects of biodiversity or community structure composition on soil respiration. Related Articles | Metrics | Comments（0）

Select

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 （1128）      PDF（pc） （371KB）（668）       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）

Select

Effects of Duck Manure Replacing Chemical Fertilizer on Soil Nutrient Characteristics and Pear Quality in Pear Planting XUE Peng-ying, CHEN Yong-xing, ZHU Zhi-ping, HAO Dong-min, SONG Man Chinese Journal of Agrometeorology    2022, 43 (12): 1015-1024.   DOI: 10.3969/j.issn.1000-6362.2022.12.006 Abstract （1112）      PDF（pc） （590KB）（437）       Knowledge map    Save The purpose of this study was to explore the effects of duck manure application on soil environmental quality and pear quality and to promote the scientific application of duck manure to partially replace chemical fertilizers in pear planting. Under the condition of equal nitrogen substitution, the duck manure alternative fertilizer program in this study was divided into five groups including the control group (CK), 30% (DM1), 40% (DM2), 50% (DM3), and 60% (DM4). The duck manure was applied to the pear tree soil in April and July. Soil and pear samples were collected in October. The soil environmental quality (soil pH, soil nutrients, heavy metals, antibiotics) and pear quality parameters (soluble solids, soluble sugars, vitamin C) were also analyzed. The results showed that all the duck manure replacement treatments (DM1-DM4) could significantly increase the soil pH (6%−21%) compared with the control group, and the organic matter of deeper soil (40−60cm) was improved. The most significant effect on increasing the content of available phosphorus and available potassium in the soil was also found in the DM3 group. Fortunately, the contents of heavy metals in different soil layers of each treatment fully meet the requirements of pollution-free and green food producing areas for soil environment. The results also indicated that the application of duck manure improved the pear quality, and the soluble solids, soluble sugars, and vitamin C of pear were increased by 5.21%−17.44%, 2.50%−8.45%, and 0.39%−11.01%, respectively. The results showed that 30% duck manure replacing had the best effect on improving pear quality, while 50% duck manure replacing had the best effect on improving soil environment quality. Related Articles | Metrics | Comments（0）

Select

Application of Deep Learning Technology in Monitoring, Forecasting and Risk Assessment of Agricultural Drought HUANG Rui-xi, ZHAO Jun-fang, HUO Zhi-guo, PENG Hui-wen, XIE Hong-fei Chinese Journal of Agrometeorology    2023, 44 (10): 943-952.   DOI: 10.3969/j.issn.1000-6362.2023.10.007 Abstract （1094）      PDF（pc） （343KB）（2857）       Knowledge map    Save The development of artificial intelligence technology, especially the emergence of deep learning, has promoted new developments of agriculture, and is regarded as a new direction of modern agricultural production. Deep learning has the advantages of strong learning ability, wide coverage, strong adaptability, and great portability. Considering that its development of simulated datasets can solve real-world problems, it is more and more widely used in monitoring, forecasting and risk assessment of agricultural drought. This paper used the method of literature review to summarize the development and application of monitoring, forecasting and risk assessment of agricultural drought, and summarized the principles, advantages and disadvantages of the deep learning model. The practical applications of depth learning model in monitoring, prediction and risk assessment of agricultural drought were systematically summarized. The existing problems of large dataset requirements, long data preprocessing time, narrow predefined category range, and complex remote sensing images were discussed, and the future research directions were prospected. The results showed that in recent years, the technologies of monitoring, prediction and risk assessment of agricultural drought had made important progress. However, due to the nonlinearity of agricultural system and the complexity of disasters, existing technologies were still difficult to meet the needs of actual agricultural production in the new situation in terms of applicable regions, objects and accuracies. The deep learning technology provided a new means for agricultural drought research. However, the deep learning model could not accurately express the specific process and mechanism of crop growth, so coupling of crop growth model with deep learning model could ensure the interpretability of deep learning model. For correcting the prediction sequence, coupling models based on general circulation model and depth learning model could be established to further improve the prediction ability of deep learning model for medium and long-term agricultural drought. Aiming at the problem of limited disaster sample size, strengthening the research on agricultural drought monitoring and evaluation based on migration learning could further improve the precisions in fine monitoring and evaluation of agricultural drought. In view of the fact that the factors affecting agricultural drought formation was characterized by large amount of data, diverse types and nonlinearity, the method of combining deep learning and information fusion was adopted to further improve the accuracies in regional monitoring, prediction and risk assessment of agricultural drought. Therefore, the coupling of deep learning models and crop growth models, agricultural drought prediction by integrating deep learning models and general circulation models, fine monitoring and evaluation of agricultural drought based on deep learning and migration learning, regional monitoring, prediction and risk assessment of agricultural drought based on deep learning and information fusion were considered as the development trends of applicating deep learning technologies in monitoring, prediction and risk assessment of agricultural drought in the future. Related Articles | Metrics | Comments（0）

Select

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 （958）      PDF（pc） （3065KB）（888）       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）

Select

Current Situation and Research Prospect of Agrometeorology in the New Stage PAN Zhi-hua Chinese Journal of Agrometeorology    2023, 44 (04): 327-332.   DOI: 10.3969/j.issn.1000-6362.2023.04.007 Abstract （901）      PDF（pc） （285KB）（1099）       Knowledge map    Save At present, China has been entering a new stage of building an agricultural power, and agrometeorology is facing unprecedented challenges and opportunities for development. In view of the new situation of smart agricultural production, food security, green development and climate change, it is urgent for agrometeorology to establish the quantitative relationship between climate factors and agricultural production, make scientific and rational use of climate resources, and improve the utilization rate of climate resources. The major tasks of agrometeorology are to deepen the research content, expand the research field and innovate the theory and method, and the key research directions include agrometeorological basis, climate change adaptation, greenhouse gas emission reduction, efficient utilization of agro-climatic resources, agro-microclimate regulation, and climate-smart agriculture. Agrometeorology needs to accelerate its development and stay ahead of other basic agricultural disciplines. Related Articles | Metrics | Comments（0）

Select

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 （856）      PDF（pc） （9154KB）（350）       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）

Select

Analysis of Annual Compound Events of Heat and Drought in North China Based on Copula Function YU Xin, ZHANG Qi, YANG Zai-qiang Chinese Journal of Agrometeorology    2023, 44 (08): 695-706.   DOI: 10.3969/j.issn.1000-6362.2023.08.005 Abstract （846）      PDF（pc） （2053KB）（1088）       Knowledge map    Save The Copula function was used to analyze the annual compound events of heat and drought in North China, which can provide reference for agricultural water management and disaster prevention and mitigation in North China. Based on the daily maximum temperature and precipitation data of 36 meteorological stations in North China from 1960 to 2019, the year-by-year heat intensity and drought intensity were identified, the Copula function was introduced to construct a two-dimensional joint cumulative probability distribution function of heat intensity and drought intensity, and the return period of compound events of heat and drought in different grades were analyzed to assess the occurrence characteristics of the compound events. The results showed that when fitting the marginal distributions of annual number of heat days and drought intensity, the GEV function worked best at more stations; the most applied Copula function was the Symmetrised Joe-Clayton function when combining annual number of heat days and drought intensity in two dimensions; compared with high temperature intensity, drought intensity had a greater effect on the magnitude of the joint return period of compound events. North China is more prone to compound events with high heat intensity in the southwest and drought intensity in the south-central part of the country. The leading factors of compound events in North China vary from region to region, and different measures need to be taken to mitigate the damage caused by compound events in different regions. Related Articles | Metrics | Comments（0）

Select

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 （841）      PDF（pc） （348KB）（210）       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）

Select

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 （769）      PDF（pc） （2227KB）（1028）       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）

Select

Review on the Impacts of Climate Change on Highland Barley Production in Tibet Plateau HAO Shuai, SONG Yan-ling, SUN Shuang, WANG Chun-yi Chinese Journal of Agrometeorology    2023, 44 (05): 398-409.   DOI: 10.3969/j.issn.1000-6362.2023.05.005 Abstract （756）      PDF（pc） （444KB）（1720）       Knowledge map    Save The Tibet plateau is strongly sensitive to global climate change and the ecosystem is very fragile. Highland barley is a major crop on Tibetan plateau and sensitive to climate change. Authors reviewed the studies on the impact of current and future climate change on barley production over the Tibetan plateau and summarized the changes of agro-meteorological resources and agro-meteorological disasters, as well as the impact of climate change on barley cropping systems, fertility and yield. The results of studies have shown that a significantly warmer trend was observed on the Tibet plateau compared to the trend in other regions, together with increasing precipitation, reduced sunshine hours, and more frequent agro-meteorological disasters such as drought and floods under climate change. The potential planting boundary of highland barely moved to higher latitudes and altitudes under climate change, which led to the potential cultivated region increasing. The climate change shortened the growth period and showed a potentially positive impact on highland barley growth. Cultivar renewal combined with technological advances boosted highland barley yields and the ability to climate change adaption. The future climate change would shorten the growth period of highland barley, which posed a big threat to highland barley production and food security on the Tibet plateau. Existing reports are limited in terms of the study area and there are few studies on climate compounding impacts and integrated risk assessment. Therefore, it is necessary to gain a deeper understanding of the mechanism of climate change impact on barley production, the technology of dynamic assessment of meteorological disaster impact and comprehensive risk, and to develop effective measures to promote the adaptation of highland barley to climate change, which can ensure food security for Tibetans over Tibet plateau. Related Articles | Metrics | Comments（0）

Select

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 （748）      PDF（pc） （16431KB）（95）       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）

Select

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 （747）      PDF（pc） （2086KB）（574）       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）

Select

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 （737）      PDF（pc） （1642KB）（2795）       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）

Select

Hyperspectral Remote Sensing of Crop Information Based on Machine Learning Algorithm: State of the Art and Beyond ZHAO Jin-long, ZHANG Xue-yi, LI Yang Chinese Journal of Agrometeorology    2023, 44 (11): 1057-1071.   DOI: 10.3969/j.issn.1000-6362.2023.11.007 Abstract （735）      PDF（pc） （403KB）（1573）       Knowledge map    Save Machine learning, as a new technique combining statistics and computer science, has been widely used in crop information acquisition tasks in recent years. Traditional methods for obtaining crop information mainly rely on chemical detection methods, which is time-consuming and labor-intensive. Based on machine learning algorithms and hyperspectral remote sensing techniques, crop appearance and internal physical and chemical parameters can be quickly sensed in a non-destructive way, which has obvious application advantages and development prospects. First, the researches related to the hyperspectral remote sensing of crop information were systematically reviewed in this paper. Second, the application, advantages and disadvantages and uncertainties of different machine learning algorithms in hyperspectral sensing crop information were summarized. Finally, it was pointed out that the future development trends of hyperspectral sensing crop information were as follows: (1) complementary crop information acquisition methods could be realized through multi-source remote sensing collaborative observations. (2) The assimilation technologies of hyperspectral remote sensing and crop model as well as the deep integration technologies of hyperspectral remote sensing and artificial intelligence could be developed. (3) The intelligent acquisition of key information oriented to the whole growth period of crops and decision-making could be realized. Related Articles | Metrics | Comments（0）

Select

Assessment of Extreme Temperature Simulation Ability of CMIP6 Global Climate Model in Shandong Province LIU Shan-shan, LIU Bu-chun, LIU Yuan, HAN Rui, YANG Fan, LIU Guan-zhi, CHE Hong-lei Chinese Journal of Agrometeorology    2024, 45 (01): 91-100.   DOI: 10.3969/j.issn.1000-6362.2024.01.009 Abstract （709）      PDF（pc） （7111KB）（388）       Knowledge map    Save The scenario data of Coupled Model Intercomparison Project Phase 6 (CMIP6) are processed by Delta method in statistical downscaling method.Based on the centralized root mean square error (RMSE), correlation coefficient (R), standard deviation (STD) and interannual variability skill score (Ts), comprehensively evaluate the simulation ability of scenario data from 10 CMIP6 models on the extreme temperature index in Shandong,and select models with better simulation results. The results indicate that:In the simulation of extreme temperature indices TXx and TNx that characterize intensity,after downscaling,more than 50% of the models simulate that the median absolute deviation of extreme temperature index in Shandong is closer to the observed value than before downscaling, in the simulation of extreme temperature indices TR, SU, FD and ID that characterize frequency,more than 60% of the models absolute deviation medians are closer to the observations than before downscaling.Using the ranking method, the simulation ability of the 10 models was compared.The CMCC-ESM2 score was 178 points, NorESM2-MM score was 191 points,and TaiESM1 score was 191 points.Therefore, these three models are preferred models. The error percentage of extreme temperature indices simulated by the ensemble mean of optimized models is lower than that of all models.After optimization,the absolute value of error percentage of TXx, TNx, TR and ID decreased from 4.2%, 2.2%, 28.67% and 14.3% to 3.3%, 1.8%, 23.58% and 9.7%, the error percentage of SU was within ± 1% before and after optimization. Related Articles | Metrics | Comments（0）

Select

Effects of Short-term High Temperature on Spikelet Opening Dynamics and Yield of Different Rice Varieties during Flowering Period XU Peng, HE Yi-zhe, HUANG Ya-ru, WANG Hui, YOU Cui-cui, HE Hai-bing, KE Jian, WU Li-quan Chinese Journal of Agrometeorology    2023, 44 (01): 25-35.   DOI: 10.3969/j.issn.1000-6362.2023.01.003 Abstract （692）      PDF（pc） （630KB）（1168）       Knowledge map    Save Under the background of global warming, high temperature weather occurs frequently in the Yangtze River Basin, which has become the primary problem seriously affecting the safe production of rice in this region. In order to clarify the effects of short-term high temperature on the spikelet opening dynamics and yield of different rice varieties during flowering period, the heat-resistant rice variety N22 and heat-sensitive rice variety YR343 were used as experimental materials and planted in pots. From the day of heading and blooming, the artificial climate chamber was used for temperature treatment, with 32℃/25℃ (day/night) as the control, 38℃/30℃ as the high temperature treatment, and continuous treatment for 7 days. Samples were taken on the 1st, 3rd, 5th, and 7th days of treatment to study the effects of high temperature stress on the opening dynamics, physiological characteristics of spikelets and yield of rice in different days of flowering. The results showed that: (1) the yield and seed setting rate of rice showed a decreasing trend after high temperature stress, and the reduction range was related to the duration of high temperature. After 7 days of high temperature treatment, the yield and seed setting rate of N22 decreased by 49.1% and 37.4%, and that of YR343 decreased by 85.1% and 65.3%, respectively. (2) The anther dehiscence rate and pollen activity of rice decreased to varying degrees after high temperature stress during flowering, and the longer the high temperature lasted, the greater the decrease. (3) The total amount of spikelet opening of rice was significantly reduced under high temperature stress, in N22 and YR343, by 33.3% and 65.5%, respectively. The flowering peak and peak appearance time of rice changed under high temperature stress. Compared with the control, the flowering peak ratio of N22 and YR343 decreased by 0.5% and 2.8%, respectively, and the flowering peak of N22 appeared 1 h earlier, while that of YR343 did not change. And under the high temperature coercion, YR343 has a shortened flowering period. (4) The changes of the physiological indices of rice spikelets under high temperature stress were as follows: the contents of soluble protein, soluble sugar and proline generally decreased; the contents of malondialdehyde and hydrogen peroxide increased; the activity of antioxidant enzymes showed a trend of first increasing and then decreasing. In summary, the low seed setting rate is the main reason for the reduction in rice yield. High temperature stress leads to the reduction of rice yield, mainly by changing the spikelet opening dynamics and its physiological characteristics, reducing the anther dehiscence rate and pollen activity, and thus reducing the seed setting rate. Related Articles | Metrics | Comments（0）