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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 （1406）      PDF（pc） （625KB）（986）       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）

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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 （1108）      PDF（pc） （359KB）（419）       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）

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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 （1102）      PDF（pc） （10145KB）（150）       Knowledge map    Save In order to improve the recognition accuracy of tomato fruit ripeness and to realize online nondestructive automatic detection in tomato planting chain, this study proposes a tomato ripeness detection method based on improved YOLOv5. In the field of agriculture, accurate identification of tomato ripeness is very important, which can help agricultural production to rationalize labor arrangements and timely harvesting, thus improving the yield and quality of agricultural products. Traditional target detection algorithms face some challenges in tomato ripeness recognition, such as misidentification and missed detection, due to factors such as vines and leaf shading between tomato fruits and light interference. Therefore, this study had carried out a series of optimizations of YOLOv5 to address these problems in order to improve the accuracy and robustness of the algorithm. In the first place, an ECA efficient channel attention module was added to its backbone network Backbone, which generated channel weights by one-dimensional convolution and captured small targets that could be easily ignored in tomatoes of different ripening stages by interacting with the k neighboring channels of each channel, thus enhancing the expressiveness and accuracy of tomato features and effectively mitigating the effects of occlusion and light interference on the recognition results. Moreover, the PAFPN in the Neck structure was replaced by BiFPN with bidirectional weighted fusion capability. BiFPN was able to bi-directionally fuse features of different scales, which better handled the occlusion problem between tomato fruits and improves the accuracy of the recognition, and this optimization also mitigated the effect of multi-targets on the recognition accuracy, which enabled the algorithm to perform better in complex scenarios. Finally, a P2 module for small-target detection was added to the Head structure. The P2 module was able to better combine the advantages of shallow and deep tomato features to improve the detection performance of small-target tomatoes, so that it can accurately detect the target even when there are small-target tomatoes and other complex situations in the image. Through a series of ablation experiments, authors obtained the optimal improved algorithm YOLOv5-tomatoA. Compared to traditional target detection networks such as YOLOv3-Tiny, SSD300 and Faster R-CNN, the algorithm performs well in complex scenes such as occlusion and uneven illumination, with an average accuracy mean and F1 score of 97.4% and 95.4%, respectively, and the recognition of an image takes only 14.7ms, which can simultaneously satisfy the high-precision and fast-response tomato fruit recognition. The improved YOLOv5 network structure also optimizes the memory footprint and resource consumption, occupying only 15.9M, making the model more lightweight. This mean that the algorithm had low equipment requirements for realizing online non-destructive testing of tomato ripening, which can provide a more convenient real-time monitoring tool for agricultural activities. This technique can also be applied to the design of automatic tomato picking robots, which provides a strong support to realize the automation and intelligence of the tomato planting process. Therefore, this improved YOLOv5-tomatoA algorithm has important practical value in the field of tomato ripeness detection and is expected to provide more accurate and intelligent management decision support for agricultural production. Related Articles | Metrics | Comments（0）

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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 （1071）      PDF（pc） （724KB）（1703）       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）

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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 （1053）      PDF（pc） （590KB）（410）       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）

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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 （1034）      PDF（pc） （343KB）（2774）       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）

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Heavy Rains and Floods Impact on Agricultural Product Supply Chain and Countermeasures CHEN Ning-yuan, ZHANG Xi-cai, NI fang-fang Chinese Journal of Agrometeorology    2024, 45 (10): 1236-1246.   DOI: 10.3969/j.issn.1000-6362.2024.10.12 Abstract （943）      PDF（pc） （371KB）（626）       Knowledge map    Save In the context of global climate change, Chinese mainland often faces the threat of heavy rainfall and flooding, and the impact of different regions is different, posing serious challenges to agricultural production and supply chain management. This paper analyzed the spatiotemporal heterogeneity of China's agricultural product supply chain, including complex origin distribution, seasonal production, diversified types of agricultural products, and the close connection of each link of the supply chain; analyzed the impact of heavy rain and flood disasters on the supply chain from planting to final sales, from farmland waterlogging and soil erosion in the production link, to road damage in the logistics and transportation link, the decline in the quality of agricultural products, and then to the price fluctuation and market uncertainty in the sales link. Post-disaster short-term relief operations and post-disaster long-term recovery and reconstruction measures. It aims to improve the resilience of agricultural supply chains, reduce agricultural losses, ensure the sustainability of agricultural product supply, and provide experience for future disaster risk management. Related Articles | Metrics | Comments（0）

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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 （870）      PDF（pc） （285KB）（1059）       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）

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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 （807）      PDF（pc） （2053KB）（1057）       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）

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

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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 （708）      PDF（pc） （444KB）（1577）       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）

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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 （705）      PDF（pc） （403KB）（1479）       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）

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Risk Assessment of Frost Damage to Production of Forest Fruit Based on Phenological Phase in Hebei Province WANG Ying, Qiu Xing-lin, LI Yu-xin, Chen Xiao-juan, Chen Xiao-lei Chinese Journal of Agrometeorology    2022, 43 (10): 821-831.   DOI: 10.3969/j.issn.1000-6362.2022.10.005 Abstract （658）      PDF（pc） （16692KB）（252）       Knowledge map    Save The research takes apples and apricots of Hebei province as examples, based on the temperature data of meteorological stations from 1974 to 2015, and calculates accumulated temperature of each region since January, to determine the three phenological periods that are susceptible to frost disasters every year: the starting and the ending of initial budding stage, flowering stage and young fruit stage. Then the research calculates the daily minimum temperature of three phenological periods at different return periods based on the Gumbel distribution, which reveals the dangerous intensity of frost disaster, and evaluates the risk of production reduction due to frost disasters according to the vulnerability curve of the three phenological periods (the yield reduction rate corresponding to the daily minimum temperature) constructed from relevant literature. Taking the once-in-a-hundred-year return period as an example, apples and apricots in northern Hebei province were more likely to be affected by frost during the young fruit period and flowering period. Zhangjiakou city was most affected during each phenological period, with an average yield reduction rate of 47.44%. Among different periods, the risk of flowering period was the highest, the yield was reduced by 59.79%, in the flowering period, the risk of yield reduction of apples and apricots in Chengde city was up to 51.42%, while in the southern region of Hebei province, Xingtai city was relatively special, with the highest yield reduction rate at the initial budding stage, reaching 37.91%. According to the above evaluation results, targeted enhancements at frost disaster monitoring and early warning in each phenological period in these areas can be made. Adjust the planting structure properly, and speed up the development of new environmentally friendly forest and fruit anti-low temperature protection technologies. Related Articles | Metrics | Comments（0）

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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 （656）      PDF（pc） （630KB）（1140）       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）

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Research on the Construction of Knowledge Graphs for Agricultural Meteorological Disasters: A Review QIU Ming-hui, XIE Neng-fu, JIANG Li-hua, WU Huan-ping, CHEN Ying, LI Yong-lei Chinese Journal of Agrometeorology    2024, 45 (10): 1216-1235.   DOI: 10.3969/j.issn.1000-6362.2024.10.11 Abstract （655）      PDF（pc） （1642KB）（2561）       Knowledge map    Save Efficient utilization of massive heterogeneous data is the key factor to enhance the intelligence of agricultural disaster management. Therefore, it is important to explore techniques for constructing multi-source heterogeneous agricultural meteorological disaster knowledge graphs for dynamic monitoring of agricultural meteorological disasters and intelligent management decision making. This paper analyzed the data sources, types, and characteristics required for knowledge graph construction in the agricultural meteorological disaster domain through literature studies and proposed a framework for knowledge graph construction that combined top-down and bottom-up approaches. The paper also examined key techniques and the current application status of knowledge graph construction from the perspective of schema layer construction, entity extraction, relation extraction, and knowledge fusion. In addition, it explored the applications of agricultural meteorological disaster knowledge graphs in the fields of monitoring and early warning, risk assessment, intelligent service, and decision support. It summarized the challenges of constructing agricultural meteorological disaster knowledge graphs and discussed the future development directions. Integrating information from the different modalities could make knowledge graph more comprehensive and accurate in describing and expressing the knowledge and information in the field of agricultural meteorological disasters, which could help to mitigate the losses caused by agricultural meteorological disasters and improve the accuracy and efficiency of decision-making. In the future, agricultural meteorological disaster knowledge graph will be constructed by incorporating large language models, advanced knowledge extraction methods to achieve complex entity and relationship extraction, and multi modal data. Further research is needed to advance the technical study of agricultural meteorological disaster knowledge graph. Related Articles | Metrics | Comments（0）

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Analysis on Change Characteristics of Carbon Footprint of Wheat Life Cycle in Different Provinces from 2015 to 2020 TAN Xin, LI Hao-ru, WANG Zi-jian, GONG Juan-di, HAO Wei-ping Chinese Journal of Agrometeorology    2024, 45 (8): 809-821.   DOI: 10.3969/j.issn.1000-6362.2024.08.001 Abstract （636）      PDF（pc） （1835KB）（394）       Knowledge map    Save In recent years, the carbon footprint of agricultural production has been a hot issue in the research on greenhouse gas (GHG) emissions reduction in China. Based on the statistical data of yield, sown area and agricultural production inputs in 14 wheat-growing provinces from 2015 to 2020, authors calculated the carbon footprint of inputs for wheat life cycle, studied the dynamic changes of carbon footprint of wheat life cycle and analyzed the proportion of carbon footprint for different agricultural inputs, and revealed the change rule of carbon footprint for wheat life cycle and the composition of emission sources. These results can provide a theoretical basis for realizing energy conservation and emission reduction in agricultural production and green low-carbon development. The results showed that the average carbon footprint per unit area and the average carbon footprint per unit yield of wheat life cycle in 14 provinces from 2015 to 2020 were 4315.4 kgCO2eq×ha−1 and 999.4 kgCO2eq×t−1, respectively, which showed a downward trend. The average carbon footprint per unit area and the average carbon footprint per unit yield of wheat life cycle in Shanxi province and Shaanxi province in northern winter (autumn sowing) wheat production region, the Inner Mongolia autonomous region and the Ningxia Hui autonomous region in spring wheat production region, and winter-spring wheat production area (Xinjiang) were higher than the average annual level of the total study regions in this paper. While the average carbon footprint per unit area and the average carbon footprint per unit yield of wheat life cycle in southern winter (autumn sowing) wheat production region (Sichuan, Jiangsu, Anhui and Hubei), Heilongjiang province and Gansu province in spring wheat production region and Shandong province and Henan province in northern winter (autumn sowing) wheat production region were lower than the average annual level of the total study regions of this paper. In the carbon footprint structure of wheat life cycle, the average carbon footprint of irrigation electricity, chemical fertilizer, diesel fuel, wheat seed and pesticides accounted for 34.2%, 51.6%, 7.3%, 3.7% and 3.2%, indicating that chemical fertilizer and irrigation electricity were the main sources of agricultural carbon footprint. Chemical fertilizer was the main source of agricultural carbon footprint in Southern winter (autumn sowing) wheat production region (Jiangsu, Anhui, Hubei and Sichuan), with an average proportion of 76.6%, 71.3%, 69.6% and 70.0%, respectively. Therefore, reducing chemical fertilizer input and increasing utilization efficiency were important emission reduction measures in these regions. Meanwhile, irrigation electricity was the main source of agricultural carbon footprint in Hebei province and Shanxi province in northern winter (autumn sowing) wheat production region and winter- spring wheat production region (Xinjiang), with an average proportion of 45.6%, 54.8% and 65.2%. Therefore, promoting the application of water-saving irrigation and developing low-energy-consuming machinery and equipment were important emission reduction measures in these regions. In short, reducing chemical fertilizer input and promoting water-saving irrigation technology to reduce the carbon footprint of wheat life cycle in study regions were effective management measures, and considering regional socio-economic and agricultural conditions of each province, formulating targeted measures to reduce agricultural greenhouse gas emissions is the key to promote the green and low-carbon development of agriculture.  Related Articles | Metrics | Comments（0）

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Progress of DSSAT-CSM Model Application in Maize Planting Research WANG Yu-ling, XU Chun-xia, BI Ya-qi, FAN Jun, GUO Rui-jia, WANG Jing, FAN Xing-ming Chinese Journal of Agrometeorology    2023, 44 (06): 492-501.   DOI: 10.3969/j.issn.1000-6362.2023.06.004 Abstract （636）      PDF（pc） （448KB）（6099）       Knowledge map    Save Crop models play an important role in the simulation, evaluation and prediction of maize production. Through literature review, the authors systematically summarized the development and application of DSSAT-CSM model in China; the composition, development and shortcomings of DSSAT-CSM model; and the process and results of using crop model to simulate the key factors affecting maize growth. It provided reference and technical support for crop model to optimize maize growth and yield by adjusting crop variety parameters, temperature variation, nitrogen fertilizer measures, irrigation system and key soil factors. Uncertainty and deficiencies of current crop models were the key factors that limited simulation accuracy and efficiency. Therefore, standardizing data collection, coupling multiple types of crop models, optimizing dynamic management processes, and modifying and optimizing models are the future trends of crop models. Related Articles | Metrics | Comments（0）

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Analysis of Spatial-temporal Variation Characteristics of Meteorological Drought in the Hexi Corridor Based on SPEI Index XUE Hua-zhu, LI Yang-yang, DONG Guo-tao Chinese Journal of Agrometeorology    2022, 43 (11): 923-934.   DOI: 10.3969/j.issn.1000-6362.2022.11.006 Abstract （633）      PDF（pc） （5405KB）（1362）       Knowledge map    Save Using the daily meteorological data of 21 meteorological stations in the Hexi corridor from 1965 to 2017, SPEI at different time scales was calculated based on the Penman-Monteith evapotranspiration model, and the temporal and spatial variation characteristics of meteorological drought in the Hexi corridor, such as the change trend, occurrence frequency and duration, were analyzed. The results showed that: (1) in the past 53 years, the SPEI of the Hexi corridor showed a significant upward trend on the monthly, seasonal and annual scales, which indicated that the drought had a significant weakening trend, but the drought lasted for a long time at individual stations, and the drought lasted for 11 months in 2013 in Wuwei. (2) The Hexi corridor had a trend of wetting in four seasons, and it was significantly wet in winter. Among them, the in spring, summer and autumn presented unstable drought changes, while the sudden change in winter around 1989 indicated the trend from drought to wet. (3) The spatial distribution of drought in the Hexi corridor had obviously regional characteristics. The arid area was mainly concentrated in the northwest, and the humid area was mainly concentrated in the south. (4) The frequency variety law of different grades drought occurance at different time scales was consistent .The frequency of mild to moderate droughts was much higher than that of severe and extreme droughts, and the spatial distribution characteristics of relatively high frequency areas of severe and extreme droughts on the annual and seasonal scales were opposite to those of mild to moderate droughts. Generally, the drought in the Hexi corridor had weakened in the past 53 years, which was beneficial to the local agricultural production and ecological environment. However, the climate change in this region is complex, and local drought needs to be paid attention to. Related Articles | Metrics | Comments（0）

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Effects of Low Temperature Stress during the Anther Differentiation Period on Leaf Anatomical Structure and Photosynthetic Characteristics of Wheat LIU Lv-zhou, ZHANG Yan, ZHANG Lin, CAI Hong-mei, YU Min, WEI Feng-zhen, CHEN Xiang, LI Jin-cai Chinese Journal of Agrometeorology    2023, 44 (01): 58-70.   DOI: 10.3969/j.issn.1000-6362.2023.01.006 Abstract （632）      PDF（pc） （4230KB）（652）       Knowledge map    Save Two wheat varieties differing in spring cold-sensitivity Yannong 19 (YN19) and Xinmai 26(XM26) were used as experimental materials. During the anther differentiation period, two temperature treatments of 4℃ and−4℃were set up in the smart climate box. At the same time, the average temperature of the ambient temperature was 10℃ as the control (CK). After the treatment, effects of low temperature stress during the anther differentiation period on leaf anatomical structure and photosynthetic characteristics of wheat were observed. The results showed that: (1) low temperature stress during the anther differentiation period significantly increased the SOD, POD, CAT enzyme activities and MDA content of functional leaves of the two wheat varieties, and the CAT enzyme activity increased the most. Compared with CK, XM26 increased by 48.68% and 87.55% at 4℃ and −4℃, while YN19 increased by 76.59% and 110.39%, respectively. Overall, the increase in antioxidant enzyme activity of YN19 was greater than that of XM26, and it had a strong ability to eliminate reactive oxygen species. (2) Low temperature stress destroys the chloroplast structure of wheat functional leaves. Compared with CK, the chloroplast number and chloroplast area of XM264℃ and −4℃ decreased by 12.43%, 24.97% and 57.68%, 5.88%, respectively, and YN19 decreased by 14.56%, 16.69% and 25.88%, 61.90%, respectively. With the decrease of temperature (4℃→−4℃), the number and thickness of grana lamellae in the leaves of the two tested wheat varieties also decreased significantly, the cell membrane was damaged to different degrees, and the grana lamella began to disintegrate. (3) With the deepening of low temperature stress, the contents of chlorophyll a (Chla), chlorophyll b (Chlb) and Chla+Chlb of the two tested wheat varieties decreased, and XM26 decreased by 26.97%, 27.39%, 31.78% compared with CK under −4℃ low temperature stress, while YN19 decreased by 34.36%, 23.81%, and 26.91%, respectively, indicating that low temperature stress destroyed the internal structure of leaves and reduces chlorophyll content. (4) Compared with CK, the net photosynthetic rate (Pn) of functional leaves of wheat under low temperature stress decreased gradually, and the intercellular CO2 concentration (Ci) increased gradually. The Pn of XM26 decreased by 31.84% and 92.04%, while that of YN19 decreased by 17.42% and 89.62% on the day of low temperature stress at 4℃ and −4℃, respectively, indicating that the decrease of Pn in wheat leaves was mainly caused by non-stomatal limiting factors. To sum up, the low temperature stress during the anther differentiation period will damage the wheat leaf function and reduce its photosynthetic capacity. Therefore, the cultivation and management measures should be strengthened in field production to improve the cold resistance of wheat and reduce the damage caused by late spring cold to wheat. Related Articles | Metrics | Comments（0）

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Continuous Cropping Years Affect the Rhizosphere Soil Microbial Community Structure and Functional Taxa of Celery LIU Su, WU Hong-liang, CHEN Zhuo, FENG Hai-ping, ZHANG Hai-yu, KANG Jian-hong Chinese Journal of Agrometeorology    2023, 44 (05): 372-385.   DOI: 10.3969/j.issn.1000-6362.2023.05.003 Abstract （630）      PDF（pc） （4326KB）（794）       Knowledge map    Save Celery is a characteristic vegetable in Ningxia cold region, and its large-scale planting inevitably leads to the prominent obstacle of continuous cropping. In order to reveal the diversity characteristics of microbes in celery rhizosphere soil and the difference of community structure with planting years, author used Illumina Novaseq-PE250 sequencing platform to sequence 16S V3V4 region and ITS1 region of celery rhizosphere soil samples after planting for one year (CA), continuous cropping for two years (CB) and continuous cropping for three years (CC), and made bioinformatics analysis.The results showed that the soil bacterial diversity decreased gradually with the extension of continuous cropping years. The Chao 1 index decreased from 8509.41 in the first year to 6314.09 in the third year.The CA Shannon index was the highest at 11.48 and the CC was the lowest at 11.08.The abundance of beneficial bacteria such as Deltaproteobacteria and Gemmatimonadetes in soil bacteria and Rokubacteriales, Blastococcus and Solirubrobacter in them decreased. The diversity index and richness index of soil fungi first decreased and then increased with the increase of continuous cropping years, which showed that the Chao 1 index of CA and CB was 505.44 and 264.66, while CC was 443.92, the Shannon index of CA and CB was 5.98, 4.93, and CC was 5.61, and there were significant differences between continuous cropping years. At the same time, there are significant differences among soil fungi, such as Sordariomycetes, Lophotrichus, Melanospora and other dominant genera. The results of microbial principal coordinate component analysis showed that there was strong heterogeneity between CC and other treatments. The function prediction analysis of PICRUSt2 showed that bacteria in the rhizosphere soil of celery mainly had 7 major categories of primary functional layers, with the highest relative abundance of Amino Acid Biosynthesis, fungi had 5 major categories of primary functional layers, and the highest relative abundance of Nucleoside and Nucleotide Biosynthesis. At the same time, there were significant differences between multiple metabolic pathways in different years of continuous cultivation of celery. To sum up, celery continuous cropping will reduce the richness and diversity of rhizosphere soil flora, change the flora structure, and lead to the imbalance of rhizosphere micro-ecological environment, thus causing related continuous cropping obstacle diseases. Among them, the microbial indices changed the most when celery was continuously cropped for three years. Therefore, it is recommended that the celery industry in the southern mountainous areas of Ningxia should be continuously cropped for no more than two years as a field planting mode. Related Articles | Metrics | Comments（0）