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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
    Abstract1125)      PDF(pc) (625KB)(919)       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.
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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
    Abstract987)      PDF(pc) (359KB)(396)       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.
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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
    Abstract980)      PDF(pc) (590KB)(387)       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.
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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
    Abstract938)      PDF(pc) (724KB)(1479)       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.
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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
    Abstract928)      PDF(pc) (343KB)(2529)       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.
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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
    Abstract903)      PDF(pc) (10145KB)(108)       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.

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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
    Abstract824)      PDF(pc) (285KB)(995)       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.
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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
    Abstract761)      PDF(pc) (371KB)(568)       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.
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    Evaluation and Projection of Temperature in Southwestern China by CMIP6 Models
    JIN Cheng-xiu, JIANG Chao, ZHANG Xi-yue
    Chinese Journal of Agrometeorology    2022, 43 (08): 597-611.   DOI: 10.3969/j.issn.1000-6362.2022.08.001
    Abstract748)      PDF(pc) (5094KB)(824)       Save
    Using on the CN05.1 monthly average temperature observation data set from 1961 to 2014 and the output data from 19 global climate models from Coupled Model Intercomparison Project Phase 6 (CMIP6), the simulation ability of CMIP6 models on the climatology spatial distribution and interannual variability of temperature in Southwestern China was systematically evaluated by means of Taylor diagram, Taylor index and interannual variability skill score. The variation characteristics of future temperature in this area were predicted under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios. The results showed that: (1) compared with other seasons, most CMIP6 models had the best performance in simulating the spatial distribution of autumn temperature climatology during 1961-2014; and CMIP6 models underestimated the interannual variability of seasonal and annual average temperature. Among the 19 models, the best models simulated the temperature in Southwestern China were ACCESS-CM2, CMCC-CM2-SR5 and CMCC-ESM5. (2) The multi-model ensemble mean(MME) of 3 best-fit models simulated the climatology spatial distribution and interannual variability of average temperature better than the MME of 19 models. (3) Compared with the multi-year average temperature observed in the same period during 1961−2014, the seasonal and annual average temperature in Southwestern China showed an upward trend in the future under the four climatic scenarios, seasonal and annual average temeprature increased by 0.94−3.48℃. Under the four scenarios, the increase of average temperature in summer was the largest(2.17−3.48℃) and the interannual fluctuation range was the smallest, the increase of temperature in winter was the smallest(0.94−2.24℃) and the interannual fluctuation range was the largest. (4) In the early of 21st century, there was little difference in the increase of seasonal and annual average temperature under 4 scenarios. During the middle of the 21st century, the upward trend of seasonal and annual average temperature in high radiation forcing scenarios was gradually larger than that in low radiation forcing scenarios. (5) Under the four scenarios, the anomaly values of multi-year average temperature at the early (2015−2034), middle (2045−2064) and end (2081−2100) period of 21st century and the historical(1961−2014) observed temperature showed the spatial distribution characteristics that the northwest was greater than southeast of this region, and the high latitude and high altitude areas were greater than the low latitude and low altitude areas. With the passage of time, at the end of 21st century, the temperature anomaly in the same region was significantly higher under high forcing scenarios than that in low forcing scenarios.
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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
    Abstract742)      PDF(pc) (2053KB)(988)       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.
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    Physiological Characteristics of Soybean Leaves at Different Growth Stages
    LIU Jiang, LI Ming-qian, CHANG Jun-fei, CHENG Xi-han, WANG Li-wei, LIU Qing, GAO Xi-ning
    Chinese Journal of Agrometeorology    2022, 43 (08): 622-632.   DOI: 10.3969/j.issn.1000-6362.2022.08.003
    Abstract720)      PDF(pc) (387KB)(692)       Save
    The impacts of drought on agricultural production is a hot topic in agrometeorological research field. Soybean is an important economic crop. Clarifying its responses and adaptation characteristics to drought would be helpful to predict the soybean yields and improve agricultural production technology under global climate change. Therefore, authors conduct water control experiments in the scientific observing and experimental station of crop cultivation in northeast China. The soybean cultivar "Liaodou 15" was used and the drought and rewatering control experiments were conducted. At the flowering and full seed stage, the light drought (relative soil moisture 65%±5%), heavy drought (relative soil moisture 50%±5%), and control (relative soil moisture 80%±5%) treatments were set, respectively and the treatments lasted for 7, 14 and 21 days, respectively. After the droughts, the rewatering treatments were conducted to make the relative soil moisture recover to the control level. When the water stress reached the set levels, the indexes including contents of soluble protein, malondialdehyde (MDA) and the activities of superoxide dismutase (SOD) and peroxidase (POD) in the leaves were measured. These indices were also measured on the seventh day after rewatering to clarify the effects of drought and the compensation effects of rewatering. The results showed that the contents of soluble protein, malondialdehyde (MDA) and the activity of peroxidase (POD) increased significantly under light and heavy drought conditions at the flowering stage. The activity of superoxide dismutase (SOD) increased significantly under light drought condition. At the full seed stage, the soluble protein content, MDA content and SOD activity increased, but the POD activity decreased significantly. Rewatering showed compensation effects on soluble protein content, MDA content and SOD activity of soybean leaves, but did not show obvious compensation effect on POD. In conclusion, drought would probably induce peroxidation damage to soybean leaves, represented by the increase of antioxidant enzyme and osmotic regulation substance content. Rewatering can alleviate the peroxidation damage caused by drought, showing different degrees of compensation effect.
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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
    Abstract652)      PDF(pc) (348KB)(182)       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.

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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
    Abstract640)      PDF(pc) (403KB)(1403)       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.
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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
    Abstract626)      PDF(pc) (444KB)(1257)       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.
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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
    Abstract595)      PDF(pc) (630KB)(1036)       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.
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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
    Abstract593)      PDF(pc) (4230KB)(613)       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.
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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
    Abstract588)      PDF(pc) (5405KB)(1274)       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.
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    Progresses of Crop Model Application and Its Integration with Remote Sensing Technology
    PENG Hui-wen, ZHAO Jun-fang, XIE Hong-fei, FANG Shi-bo
    Chinese Journal of Agrometeorology    2022, 43 (08): 644-656.   DOI: 10.3969/j.issn.1000-6362.2022.08.005
    Abstract587)      PDF(pc) (379KB)(1956)       Save
    Crop model remote sensing and play important roles in agricultural production monitoring, evaluation, and future prediction with their unique advantages. The integration technologies of crop model and remote sensing information have obvious application advantages and broad development prospects in monitoring, evaluation and prediction of large-scale and high-precision agricultural production. In order to promote the wider applications of these technologies in crop yield prediction, impact assessments of agrometeorological disaster, and agricultural decision-making to deal with climate change on a regional scale, the method of literature review were adopted in this paper. The development and application of crop models in Europe, United States, Australia and China were systematically summarized. The principle, characteristics and shortcomings of the current mainstream data integration methods were concluded. The practical applications of integration technologies of crop model and remote sensing information were summarized. The existing problems in improving the accuracy of data integration were discussed, and the future research direction was prospected. The results showed that the research and application of crop model and its integration with remote sensing data were extensive and intensive at home and abroad. The assimilation method could effectively improve the simulation accuracies of crop model, providing technical support for crop growth and yield evaluation on regional scales, impacts of climate change on yield, farmland management decision-making, etc. The uncertainties from crop model simulation results and remote sensing inversion data, diversities of data assimilation strategies, and scale effects were the limiting factors to further improve the accuracy and efficiency of integrated systems. Therefore, multi-source fusion of remote sensing data, multivariable cooperation in assimilation process, multi-type coupling of crop models, and high-performance parallel computing of data were the development trends of integrating crop models and remote sensing research in the future.
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    Spatiotemporal Patterns of Seasonal Mean Temperature Variations in China During 2001−2100
    FU Da-rong, CHEN Xiao-die, LIU Yi-ting, LIU Li, PENG Shou-zhang
    Chinese Journal of Agrometeorology    2022, 43 (09): 681-691.   DOI: 10.3969/j.issn.1000-6362.2022.09.001
    Abstract586)      PDF(pc) (5662KB)(656)       Save
    Based on the 1-km resolution long time series temperature data set, the spatial and temporal patterns of the magnitude and trend of the four-season mean temperature changes in the historical period (2001−2020), and in the future period (2021−2100) under the low forcing scenario (SSP119), medium forcing scenario (SSP245) and high forcing scenario (SSP585) are analyzed using the distance level method, Mann-Kendall trend test method and Sen's slope estimation method, with a view to providing a basis for developing detailed regional adaptation strategies in the context of climate warming. The results show that: (1) compared with the historical period, the average temperature of the four seasons in the future will increase in general under the three scenarios, and the area with the largest increase in summer is 66.70% under SSP119, 37.37% and 99.06% under SSP245 and SSP585, respectively. At the same time, the overall variation range of seasonal mean temperature under the three SSP scenarios is significantly different, which is moderated under SSP119, followed by SSP245, and the largest increase range under SSP585. (2) In the historical period, compared with other seasons, the significant rise in mean temperature in spring had the fastest rate (0.68±0.24℃∙10y−1) and the largest area share (14.44%), mainly distributed in North China, Yunnan, Guizhou, Jiangsu and Zhejiang provinces. (3) In the future period, the regional seasonal mean temperature in China shows an overall rising trend with significant spatial differences; among them, under the SSP119 scenario, the regions with significantly rising mean temperature in spring and winter are mainly concentrated in southern China and the local area of the Qinghai-Tibet Plateau, accounting for 29.03% and 25.58% of the area, respectively; under the SSP245 and SSP585 scenarios, the seasonal mean temperature in all regions of China shows a significant upward trend; under the SSP585 scenario, the seasonal mean temperature in the north increases at a faster rate than that in the south, and the national region has the fastest significant rate of increase in winter (0.66±0.09℃∙10y−1).
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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
    Abstract569)      PDF(pc) (4326KB)(742)       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.
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