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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 （299）      PDF（pc） （625KB）（329）       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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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 （294）      PDF（pc） （724KB）（322）       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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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 （285）      PDF（pc） （343KB）（370）       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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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 （271）      PDF（pc） （2053KB）（364）       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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Effects of High Temperature on Photosynthetic Characteristics and Antioxidant Enzyme Activities of Maize Leaves during Filling Stage YU Meng-qi, LU Meng-li, ZHANG Ya-ting, CHEN Zhi-ying, LI Wen-yang Chinese Journal of Agrometeorology    2023, 44 (07): 599-610.   DOI: 10.3969/j.issn.1000-6362.2023.07.005 Abstract （247）      PDF（pc） （513KB）（175）       Knowledge map    Save The present study was carried out to investigate the effects of high temperature on photosynthetic fluorescence characteristics and antioxidant enzyme activities in maize ear leaves. The pot experiments were carried out at Fengyang Experimental Station of Anhui Science and Technology University June to October 2021. Two maize cultivars, "Anke 985" and "Longping 206", were chosen in this study. The average temperature of high temperature treatment was (37±2)°C during the daytime, and the high temperature duration was 30 days. The indices including contents of yield, chlorophyll relative content (SPAD), photosynthetic parameters, chlorophyll fluorescence parameters, antioxidant enzyme (CAT, SOD, POD) activity and malondialdehyde (MDA) content of maize were measured under different treatments. The results showed that compared with the control, high temperature treatment reduced significantly grain number per row, 100-grain weight, thereby reducing maize yield per plant. The chlorophyll relative content (SPAD), net photosynthetic rate (Pn) and stomatal conductance (Gs) of maize leaves significantly decreased under high temperature treatment, while intercellular carbon dioxide concentration (Ci) increased significantly, indicating that the decreased of net photosynthetic rate (Pn) was mainly affected by non-stomatal factors. High temperature treatment had significant effect on fluorescence parameters of maize. The maximum photochemical efficiency Fv/Fm, actual photochemical efficiency (ΦPSII) and photochemical quenching (qP) of maize ear leaves decreased significantly, but the non-photochemical quenching (qN) increased significantly under high temperature treatment. After high temperature treatment, the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) in maize significantly decreased, but the malondialdehyde (MDA) content increased significantly. In conclusion, high temperature treatment damaged the photosynthetic apparatus of maize leaves, the activity of antioxidant enzymes decreased, the degree of membrane peroxidation increased, the relative content of chlorophyll decreased, and inhibited the photosynthetic performance, which led to the accumulation of photosynthetic assimilates blocked, resulting the maize yield decreased significant. 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 （234）      PDF（pc） （403KB）（268）       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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Establishment of Freezing Injury Index of Camellia oleifera during Flowering Period YUAN Xiao-kang, WU Ding-rong, WANG Pei-juan, WANG Qing-ling, FAN Yu-xian, HE Na Chinese Journal of Agrometeorology    2023, 44 (07): 633-641.   DOI: 10.3969/j.issn.1000-6362.2023.07.008 Abstract （230）      PDF（pc） （462KB）（152）       Knowledge map    Save In order to find out the freezing injury index of Camellia oleifera, a Camellia variety named “Tiecheng No. 1”was used as test material, a artificial control experiment was carried out at the Camellia oleifera base in Changde city, Hunan province in 2020 and 2021, respectively. Taking the natural state as a control, several low-temperature freezers were used to set low-temperature treatments with different intensities at −6℃ to 3℃(or −8℃ to 2℃) for 4 hours, and the Camellia oleifera branches at the flowering stage were placed in the freezers in a non-isolated way. 7 days after treatment, the morphological changes of Camellia oleifera were observed, and the rate of falling flower (fruit) and photosynthetic parameters were determined. The results showed that the morphological indicators of Camellia oleifera, falling flowers (fruit) rate and the light response parameters were clearly changed by low temperature. As the temperature decreased, the symptoms of freezing injury became more obvious, falling flowers (fruit) rate increased, while the maximum net photosynthetic rate, apparent quantum efficiency and saturation irradiation decreased. According to the symptoms of freezing damage and the response of the above physiological indicators to different low temperatures, it was determined that −2℃ was the upper limit of freezing damage of Camellia oleifera during flowering period, −6℃ was the critical temperature for significant aggravation of freezing damage, and −8℃ was the critical temperature for serious freezing damage. It was concluded that the slight freezing injury index of Camellia oleifera during flowering period was: −6℃＜daily minimum temperature≤−2℃, and the moderate freezing injury index was:−8℃＜daily minimum temperature≤−6 ℃, and the severe freezing damage was: daily minimum temperature ≤−8℃. Related Articles | Metrics | Comments（0）

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Variation Trend and Attribution Analysis of Potential Evapotranspiration in Different Climate Regions LIU Wen-hui, ZHANG Bao-zhong, WEI Zheng, HAN Song-jun, HAN Cong-ying, WANG Ya-qi, HAN Xin Chinese Journal of Agrometeorology    2023, 44 (07): 545-559.   DOI: 10.3969/j.issn.1000-6362.2023.07.001 Abstract （214）      PDF（pc） （3706KB）（181）       Knowledge map    Save Based on the daily meteorological data of 710 stations from 1970 to 2017, authors apply the Mann-Kendall test method and contribution analysis method, analyze the variation characteristics of annual ETo (potential evapotranspiration) and its sensitive factors, further quantify the contribution of meteorological factors to ETo variation in different climate regions. The results showed that, (1) among 710 meteorological stations, 177 stations showed a significant increase trend (0.51 to 5.55mm·y−1, P<0.05), 147 stations showed a significant decrease trend (−0.65 to −5.00mm·y−1, P<0.05), and 386 stations showed no-significant change trend. T and U showed an increasing trend, while RH and RN showed a decreasing trend in different climate regions. (2) The sensitivity factors of ETo to meteorological variables were differ in climate regions, in extreme arid region, arid region and semi-arid region ETo was most sensitive to net radiation(RN), and most sensitive factor change to relative humidity(RH) in the semi-humid region and humid region, also the sensitivity of ETo to RH and RN increased with the increase of humidity. (3) The change trend of ETo was influenced by the sensitivity of climate factors and the relative rate of change. The rise of ETo in extreme arid region, arid region, semi-arid region and semi-humid region were mainly caused by the increase of T, while the decrease of ETo was mainly caused by the decrease of U, the change of ETo in humid region was caused by its high sensitivity to RH and RN. In summary, compared with the sensitivity coefficient, the contribution index considering the relative rate of change is more indicative of the influence of climate factors on ETo change. This study is conducive to for scientific understanding of regional climate change and hydrological cycle response mechanism. 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 （209）      PDF（pc） （448KB）（135）       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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Characteristics Analysis on Carbon Reduction of Crop Production in Henan Province Based on the Statistical Yearbook Data LI Jie, NIE Hong-min , XU Guo-zhen Chinese Journal of Agrometeorology    2023, 44 (09): 759-768.   DOI: 10.3969/j.issn.1000-6362.2023.09.001 Abstract （199）      PDF（pc） （535KB）（212）       Knowledge map    Save Based on the statistical yearbook data of Henan province from 2000 to 2020, such as production input, cultivated land area, crop sown area and crop yield, the carbon emission at input end of crop production in Henan province was calculated to analyze the characteristics of carbon reduction in crop production, using the emission factor method that relied on five indexes of fertilizer, pesticide, agricultural film, diesel fuel and irrigation, which provide the theoretical basis for achieving green and low-carbon transformation of agricultural production in Henan province. The results show that, except for the irrigation area, the usage of various inputs in crop production in Henan province showed a trend of first increasing and then decreasing from 2000 to 2020. The total carbon emissions from various crop production inputs also showed a trend of first increasing and then decreasing. The highest point was reached in 2015, reaching 8.6732 million tons, and by 2020, the total carbon emissions had decreased by 10.27% compared to that of 2015. In the average carbon emissions over 21 years, fertilizer had the highest emissions, followed by agricultural plastic film, agricultural diesel, pesticides, and agricultural irrigation, accounting for 73.35%, 9.41%, 8.08%, 7.77% and 1.39% respectively. Therefore, fertilizer is the main source of carbon emissions. The carbon emission intensity of crop production inputs in Henan province showed a trend of first increasing and then decreasing from 2009 to 2020. In 2015, it reached the highest value of 1.0670t·ha−1, but by 2020, the carbon emission intensity had decreased by 2.87% compared to that of 2015. The study found that carbon emissions from crop production inputs are significantly affected by policies. As the main source of carbon emissions in crop production, reducing emissions and increasing efficiency is still an important measure, followed by the rational use of agricultural plastic film. Strengthening policy guidance, controlling the use of fertilizers and pesticides, implementing actions to reduce fertilizer and pesticide use while increasing efficiency, promoting the demonstration and popularization of high-quality and efficient green pest control technologies, and regulating the use and recycling of agricultural plastic film are all effective ways to reduce carbon emissions from crop production in Henan province. Related Articles | Metrics | Comments（0）

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Development Status, Problems and Prospects of Agrometeorological Observation Operation in China ZHANG Quan-jun, HONG Guan, WU Dong-li, HOU Ying-yu, ZHUANG Li-wei, ZHU Yong-chao, YANG Da-sheng, LIU Cong, SHI Yao-hui, HOU Biao, ZHANG Jing, LING Cong-jing, LI Yan Chinese Journal of Agrometeorology    2023, 44 (08): 735-749.   DOI: 10.3969/j.issn.1000-6362.2023.08.008 Abstract （195）      PDF（pc） （5482KB）（172）       Knowledge map    Save Agrometeorological observation is an important cornerstone of agricultural modernization development. This study comprehensively sorted out the development process, business status and existing problems of agricultural meteorological observation in China, and discussed the development prospects of agrometeorological observation in the future, in order to provide a reference for escorting the sustainable development of modern agriculture and national food security. The development of China's agrometeorological observation operation has roughly experienced six stages: theoretical exploration, organization establishment, pilots construction, scale formation, optimization and adjustment, and stable and rapid development. At present, China has established a network of observation stations based on 653 agrometeorological observation stations (including 70 agrometeorological experimental stations) to carry out observation and research on crops, soil moisture, natural phenology, animal husbandry, fruit trees, trees, vegetables and agricultural microclimate. Based on the development of observation business, a national, provincial, municipal and county agrometeorological operational service system with scientific structure and advanced functions has been established. The national agrometeorological monitoring and evaluation, crop yield forecast, agrometeorological disaster monitoring and evaluation and impact forecast, agricultural weather forecast, meteorological grade forecast of occurrence and development of agricultural and forestry diseases and insect pests, agricultural soil moisture, drought relief, and ecological meteorological monitoring and prediction have been relatively mature and service results remarkable. In the past ten years, China's agricultural industry layout, planting structure and planting methods have undergone tremendous changes, and automatic observation technique such as automatic crop meteorological observation and automatic phenology observation have also developed rapidly. The agrometeorological observation operation also gradually shows a series of questions, such as the layout of the network of observation station and the observation tasks needs to be adjusted and optimized, the observation specifications need to be revised and supplemented, the modern technology and automatic observation equipment need to speed up the application and the operational service capacity needs to be improved and strengthened. From the perspective of the strategic deployment of the Party Central Committee of the CPC, the State Council and the China Meteorological Administration for the development of agrometeorological observation operation, the goal of high-quality development of agrometeorological observation, and the demand of modern agricultural development for agrometeorological operation, the future agrometeorological observation operation in China will gradually form a network of observation stations with reasonable layout, perfect specifications, advanced technical equipment, diversified and sophisticated service products, a modern agrometeorological observation and operational service system that can be in line with international standards. Related Articles | Metrics | Comments（0）

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Determination of the Suitable Sowing Date of Fresh Maize Along the Yangtze River of Anhui Province ZHANG Lin, ZHOU Deng-feng, WU Wen-ming, PENG Chen, JI Xue-qin, YANG Tai-ming, WANG Shi-ji Chinese Journal of Agrometeorology    2023, 44 (10): 903-915.   DOI: 10.3969/j.issn.1000-6362.2023.10.004 Abstract （193）      PDF（pc） （654KB）（122）       Knowledge map    Save A field trial was carried out along the Yangtze river in Anhui province to clarify the relationship between growth, yield of fresh maize and meteorological factors under different sowing dates, which would provide a reference to the suitable sowing date of fresh maize. In the study, the fresh maize cultivar “Caitiannuo 100” was used. The treatments consisted of ten sowing dates: April-1, April-16, May-1, May-16, May-31, June-15, June-30, July-15, July-30, and August-14. The growth period, yield, yield component and production value of fresh maize were analyzed. The results showed that the growth duration was shortened when delaying the sowing date from April-1 to June-15. When the sowing date was from June-15 to July-30, the growth duration was extended. The yield was decreased when delaying the sowing date from April-1 to June-30, and the yield was increased. The mean grain yield of fresh ear in the sowing date from April-1 to May-1 and July-30 was 20026.56kg·ha−1, which was significantly higher than that of other sowing dates (P<0.05). The production value of fresh ear planted in July-30 was 70245.00yuan·ha−1, which was significantly increased by 68.66%−123.50% compared with other sowing dates (P<0.05). When the fresh maize was sowed during May-31 to July-15, the days of high temperature ≥32℃ accounted for 56.25%−60.26% in the whole growth duration of the plant, and the accumulation of temperature ≥32℃ increased by 47.78%-54.46% than that of sowing dates from April-1 to May-1 and July-30, which accelerated the fresh maize growing process, shortened the plant height, declined the matter accumulation, ultimately decreased the yield. The fresh maize could not be harvested with the sowing date of August-14 due to the lower temperature during the grain filling stage. The growth duration of maize was negatively correlated with daily mean temperature before silking. The ranking of the correlation coefficients between meteorological factors and fresh maize yield from high to low were effective accumulated temperature >10℃ before silking, precipitation before silking, daily mean temperature before silking, average daily temperature range before silking, precipitation after silking, effective accumulated temperature >10℃ after silking, and sunshine hours before silking. The effective accumulated temperature >10℃ before silking stage mainly influenced the yield by regulating the kernel number per ear. In conclusion, the fresh maize sowed during April-1 to May-1 or July-30 could be prone to extend growth period, increase matter accumulation, and obtain high yield, while might be in danger in the risk of high temperature stress with the sowing date from May-31 to July-15 along the Yangtze river. Related Articles | Metrics | Comments（0）

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Assessment and Re-examination the Disaster-yield Model Based on Regional Grain Yield Loss for Five Provinces across North of China LIU Yuan, LIU Bu-chun, MEI Xu-rong, HE Jin-na, CHEN Di, HAN Rui, ZHU Yong-chang Chinese Journal of Agrometeorology    2023, 44 (11): 1009-1021.   DOI: 10.3969/j.issn.1000-6362.2023.11.003 Abstract （189）      PDF（pc） （1564KB）（214）       Knowledge map    Save Based on statistical data on grain acreage, yields and agricultural disasters from 1961 to 2020, the variability characteristics of grain yields and disasters in China and five northern provinces were compared and analyzed. Disaster yield assessment models for Hebei, Shandong and Henan provinces were used to estimate the loss of grain production due to disasters and grain yields by inputting data on disasters from 2008 to 2020. The sensitivity and stability of the disaster-yield assessment model were examined. Based on the statistical modeling method, the model of grain crop disaster-yield evaluation in Shanxi and Shaanxi was constructed, and the universality of the model construction method was evaluated. The results showed that: (1) the grain planting area and total output of the five northern provinces accounted for 28% and 25% of the national total from 1961 to 2020, respectively. In the five northern provinces, the planting area of summer harvest grain and autumn harvest grain decreased significantly at rates of 3.39ha·a−1 and 106.3ha·y−1(P<0.01) respectively, while the total output increased significantly at rates of 137.3×104t·y−1 and 119.9×104t·y−1(P<0.01), respectively. From 2008 to 2020, the grain planting area and grain yield in the five northern provinces increased significantly at the rates of 209.42ha·y−1 and 258.06×104t·y−1(P<0.01), respectively. (2) From 1961 to 2020, the areas of covered, affected and destroyed disaster in the five northern provinces accounted for 28%, 28% and 23% of the national average, respectively, while the disaster situations in the five northern provinces and the whole country showed a significant trend of first increasing and then decreasing. After reaching historically high values in 2008, 2000 and 2000, the covered disaster, affected disaster and destroyed disaster area had declined year on year. The corresponding disaster situations in the five northern provinces showed a downward turning point in 1990, 1989 and 2004, respectively. Drought and flooding are the main causes of crop disasters in China, with 76 percent of the total area affected by drought and flooding. The disaster in the five northern provinces was mainly caused by drought. The areas affected by drought accounted for 66%, 61% and 58% of the disaster statistics, respectively. From 2008 to 2020, the area affected by drought in Shandong was the largest. The area of drought disaster in Hebei and Shanxi was relatively high. Hebei province has the highest area of flooding and hail. (3) When the data series is extended to 2020, the simulated value of grain yield is significantly correlated with the actual value(R2=0.95, P < 0.01), the simulation accuracy of the model was high. In the past 60 years, the grain loss rates of Hebei, Shandong, Henan, Shanxi and Shaanxi provinces were 8.99%, 18.02%, 9.79%, 12.84% and 20.04%, respectively. In the last 12 years, the grain loss rates of Hebei, Henan, Shanxi and Shaanxi provinces had recorded by 4.4%, 17.4%, 9.65%, 8.14% and 17.9%, respectively, influenced by the reduction of disaster zones and advantage in agricultural science and technology. They all went down. With the verification and construction of the model, the modeling statistical method performs well in evaluating the loss of grain yield due to meteorological disasters, had a promising performance in predicting grain yield, and is feasible for commercial applications. As the five northern provinces account for a high proportion of the country's grain output, it is important to prevent the risk of regional hydrometeorological disasters to ensure the country's food security in the new period. Related Articles | Metrics | Comments（0）

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Spatialization of Spring Maize Yield Area in Northeast China Based on Multiple Linear Regression ZHAO Xue-qing, JIN Tao, DONG Wen-yi, LIU Mei-xia, LIU Qin, LIU En-ke Chinese Journal of Agrometeorology    2023, 44 (11): 1022-1031.   DOI: 10.3969/j.issn.1000-6362.2023.11.004 Abstract （188）      PDF（pc） （6492KB）（215）       Knowledge map    Save Spring maize is the primary food crop in Northeast China. Researching and analyzing the spatial difference in yield under diverse climate and soil models holds immense significance in guiding agricultural production and ensuring food security. In this study, a total of 13 key influencing factors were selected from the three aspects of soil, topography and climate, and a multivariate stepwise linear regression model was constructed for spring maize per unit yield and 13 influencing factors by using multivariate stepwise regression analysis. Then the spatial distribution of spring maize per unit area yield in Northeast China was analyzed by using ArcGIS software to rasterize the spring maize yield per unit area. The results showed that: (1) the spatialized data (with a spatial resolution of 1km) calculated by the multiple linear regression model are basically consistent with the statistical data of spring maize yield per unit area. The spring maize yield in Northeast China is between 2482.49-10147.10kg·ha−1. (2) The spatial distribution map of spring maize yield objectively reflects that the spatial distribution trend of spring maize yield, which generally shows a pattern of decreasing from the central to the surrounding areas. This study accurately obtained the grid-scale simulation results of spring maize yield per unit area spatialization in Northeast China (the average relative error is 1.45%), which provides a method reference for the optimization of agricultural production layout and decision-making in Northeast China. Related Articles | Metrics | Comments（0）

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Spatiotemporal Variation and Risk Zoning of Spring Frost Disaster for Tea Plant in Dabie Mountains CAO Qiang, YANG Xian-gui, DONG Shi-jie, LUO Xiao-dan, LI Hong-fei, CHEN Xi, YUE Wei Chinese Journal of Agrometeorology    2024, 45 (01): 67-78.   DOI: 10.3969/j.issn.1000-6362.2024.01.007 Abstract （188）      PDF（pc） （3420KB）（250）       Knowledge map    Save Based on the daily meteorological data of 35 national meteorological observation stations in Dabie Mountains from 1971 to 2020, the spatiotemporal distribution characteristics of spring frost disaster for tea plant were analyzed with trend surface interpolation and ArcGIS technology. According to the theory of natural disasters risk, the risk of hazard-formation factors, the exposure of hazard-formation environments, the vulnerability of hazard-affected bodies and the capability of hazard prevention and mitigation were taken as the evaluation factors, the weighted comprehensive evaluation method was used to construct the comprehensive risk assessment model of spring frost disaster. The risk zoning had been carried out based by the means of ArcGIS technology. The results showed that: (1) the number of occurrence days of spring frost in different grades decreased significantly from 1971 to 2020, with the average number of occurrence days of total, slight, moderate and severe spring frost being 9.6, 5.2, 3.0 and 1.4d respectively, and the climatic tendency rates being -1.45, −0.61, −0.54 and −0.30d·10y−1. The number of occurrence days was positively correlated with altitude and latitude, and the downward trend of the number of occurrence days in the northern region was much more obvious than that in the southern region. (2) The high risk, medium risk and low risk areas of tea spring frost disaster accounted for 16.67%, 41.88% and 41.45% of the total area in the study region respectively. The high-risk areas were mainly located in the high mountainous regions with an altitude of more than 600m in Jinzhai, Yuexi, Huoshan, Yingshan and Xinyang, as well as scattered shady slopes (northern slopes); the medium-risk areas were mainly located in the mountainous region with an altitude of less than 600m and most of the low-altitude region at the northern foot of Dabie Mountains, and scattered shady slope (north slope) in the low-altitude region at the southern foot of Dabie Mountains; the low-risk region were mainly located in the low-altitude region at the southern foot of Dabie Mountains, and scattered sunny slope (south slope) in the low-altitude areas at the northern foot of Dabie Mountains. The refined assessment of the risk of tea spring frost could provide reference for optimizing the layout of the tea industry and enhancing disaster prevention and mitigation capabilities in Dabie Mountains. Related Articles | Metrics | Comments（0）

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Evaluation on Cold Resistance of Buckwheat Germplasm during Germination Stage in Sichuan Province ZHENG Wen, ZHU Ming-kun, FANG Zhong-yan, CHEN Yu-nan, DU Han-mei, WANG An-hu, ZHOU Yong-hong, WU Dan-dan Chinese Journal of Agrometeorology    2023, 44 (09): 795-804.   DOI: 10.3969/j.issn.1000-6362.2023.09.004 Abstract （188）      PDF（pc） （644KB）（147）       Knowledge map    Save Buckwheat is the major food crop in high altitude areas such as Liangshan district, Sichuan province, China. In order to explore the cold resistance of buckwheat and screen excellent buckwheat germplasm resources adapted to Liangshan district, 5 common buckwheat (Fagopyrum esculentum Moench.) and 13 Tartary buckwheat [Fagopyrum tataricum (L.) Gaertn. ], the most extensive varieties and landrace, were used to evaluate the cold resistance during seed germination stage at 4℃(low temperature condition) and 22℃(control condition). Seven indices related to germination and growth were measured, including radicle length, germination rate and germination potential. Comprehensive cold resistance was reflected by subordinate function analysis, principal component analysis and cluster analysis. The results showed that under low temperature conditions, the seed germination of all buckwheat materials was delayed and the germination rate was retarded. Compared with Tartary buckwheat, seven germination and growth indexes of common buckwheat maintained a higher level, indicating that common buckwheat was more tolerant under low temperature environment. The comprehensive evaluation of the membership function results suggested that Jiuzhaigou common buckwheat had the strongest low temperature tolerance ability at the germination stage, followed by Pintian No.3, whereas Xiqiao No.6 was the most sensitive to low temperature. Related Articles | Metrics | Comments（0）

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Change in Forage Grass Climate Productivity and Response to Meteorological Drought in Sanjiangyuan SANG Chun-yun, WANG Qian, GUO Jian-mao, LI Jian-hua, LI Wen-feng, WANG Yong Chinese Journal of Agrometeorology    2024, 45 (01): 12-22.   DOI: 10.3969/j.issn.1000-6362.2024.01.002 Abstract （187）      PDF（pc） （10091KB）（184）       Knowledge map    Save Based on monthly ground observation data from 18 meteorological stations in Sanjiangyuan region from 1970 to 2020, the SPEI at different time scales was used as the meteorological drought monitoring index. The climate productivity of forage grass was calculated by stepwise correction method. The temporal and spatial characteristics of meteorological drought and climate productivity in the forage grass growing season in the Sanjiangyuan region were analyzed, and the response of climate productivity to meteorological drought was initially revealed. The results show that: in recent 50 years, meteorological drought of forage grass growing season in the Sanjiangyuan region showed an aggravating trend (P<0.01). The climate gradually changed from humid to arid around 1995, drought occurs mainly in the west, south central and northeast regions; The aridification in the northwest of Sanjiangyuan region is more obvious. The climate productivity of forage grass in the growing season was decreased by 7.38kg·ha−1·y−1(P<0.01). The spatial distribution decreases from northwest to southeast, rising in the west and falling in the east. There is a strong positive correlation between climate productivity of forage grass growth season and SPEI in different time periods in the Sanjiangyuan region. Moreover, with the increase of SPEI forward time, the correlation coefficient increases slightly. The response of forage grass climate productivity to meteorological drought in central and western regions was higher than that in other regions. Related Articles | Metrics | Comments（0）

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Evaluation of Rice Affected by Heat Damage in the Sichuan Basin in 2022 Based on Satellite and In-situ Observation WANG Xin, YANG De-sheng, WANG Rui-ting, ZHAO Yi, WANG Ming-tian Chinese Journal of Agrometeorology    2023, 44 (06): 523-534.   DOI: 10.3969/j.issn.1000-6362.2023.06.007 Abstract （186）      PDF（pc） （8606KB）（109）       Knowledge map    Save In order to fully understand the disaster situation of rice high temperature heat damage in the Sichuan basin (SCB) in 2022, this study explores the monitoring and evaluation technology of rice high temperature heat damage suitable for Sichuan by using MODIS data, meteorological data, geographic auxiliary data and agricultural production data. Based on the remote sensing technology, the estimation of daily mean temperature and daily maximum temperature, the extraction of rice area, the identification of rice heading−flowering stage, and the estimation and grade evaluation of high temperature heat damage area during rice heading−flowering stage were studied in the SCB. The evaluation results were verified by high temperature heat damage measured by national meteorological station. The results showed that the mean temperature and maximum temperature can be obtained by merging satellite-retrieved temperature and in-situ observed temperature from dense automatic weather stations with high accuracy. Considering the characteristics of the growth period, the planting area and the key growth period of rice in the SCB could be accurately identified. The high temperature heat damage grade of rice at heading−flowering stage based on satellite-ground fusion data inversion was in good agreement with the measured heat damage grade at the station except for the mountainous region around the basin. The proposed methods can not only rapidly monitor the high temperature heat damage of rice in heading-flowering stage at any time, but also evaluate the distribution of heat damage, frequency distribution and disaster area of rice in heading−flowering stage in the annual study area. It can be applied to operational applications and progressively improved in services. Related Articles | Metrics | Comments（0）

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Study on Frost Risk during Apple Blossom in Northern China under Different Climate Change Scenarios QIU Xing-lin, LIN Ze-quan, LI Can, YU Hai-yang, WANG Ying Chinese Journal of Agrometeorology    2024, 45 (01): 33-44.   DOI: 10.3969/j.issn.1000-6362.2024.01.004 Abstract （185）      PDF（pc） （11528KB）（231）       Knowledge map    Save The main apple-producing areas in northern China are located in the North China plain and the loess Plateau, and the apple blossom frost hazard events have had a severe impact on the income of fruit growers and the economy of the production areas. Future climate change will exacerbate the frequency and intensity of extreme weather and climate events. In this study, based on the climate model data shared by NEX-GDDP, the seven models with the best fitting ability for the minimum temperature during apple blossom were selected using Taylor diagrams, and the annual encounter values of the minimum temperature during apple blossom were calculated and revised using the transfer function correction method of the extreme value distribution, so as to predict the risk of frost disaster and yield reduction of apples in northern China under climate change. Taking the intensity of the apple blossom frost disaster with a 30-year occurring period event across the study area as an example, in the near and distant future under the RCP4.5 scenario, the regions of Henan, Shanxi, northern Shaanxi and, northern Ningxia were the main affected areas, dominated by the minimum temperature of −3 to −2°C, and the highest yield reduction rates were in the northern regions of Henan, Ningxia, Shanxi, and northern Shaanxi provinces, with the yield reduction rate of apples in northern China ranging from 2.47% to 5.22%. Under the RCP8.5 scenario, the frost disaster area with a minimum temperature of −3°C or less expands to the whole of Henan, central Shandong and other places, and the yield reduction rate of apples in northern China is 4.57%−12.39%. In the future, apple cultivation in these areas needs to strengthen the prevention of frost disaster risk. Related Articles | Metrics | Comments（0）

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Construction of A Tomato Growth Rate Simulation Model Based on Climate Suitability Index GUO Shen-bo, LIU Fu-hao, WANG Di, HUANG Bo, CAO Yan-fei Chinese Journal of Agrometeorology    2023, 44 (07): 611-623.   DOI: 10.3969/j.issn.1000-6362.2023.07.006 Abstract （183）      PDF（pc） （1024KB）（134）       Knowledge map    Save The microclimate of the facility is an important influencing factor for tomato growth and is characterized by complex parameters and rapid changes. In order to scientifically grasp the microclimate characteristics and explore the relationship between microclimate suitability index and tomato growth rate, two experiments were conducted in 2021 using tomatoes as the test material in insulated plastic greenhouses, with ‘Provence’ as the test tomato variety for the spring crop (January 18-May 24, 2021) and ‘Baolufuqiang’as the test tomato variety for the autumn crop (August 27-December 31, 2021), both in substrate bags. Authors adopt conventional field management methods. Microclimate including temperature, relative humidity, solar radiation, CO2 concentration and vapor pressure deficit (VPD) were monitored in the facility, and tomato morphological indicators and growth rate were measured every 7 days. Authors proposed a method for calculating the microclimate suitability index for facilities using factor analysis, and constructed a tomato growth rate simulation model based on the microclimate suitability index using multiple linear regression method to simulate and verify tomato growth rate in autumn crop. The results showed that the microclimate suitability identified based on the computational method matched 75% with that based on manual empirical judgment, and the correlation between microclimate suitability and the growth amounts of fresh tomato weight (r=0.690), dry weight (r=0.623), and plant height (r=0.748) reached significant levels (P<0.05). In the simulation results of the growth rate of autumn crop, the fitting degree and accuracy of the growth rate simulation were better. The results of autumn crop tomato growth rate simulations showed good fit and accuracy, with simulated relative growth rate at seedling stage with measured values R2=0.875 and RMSE=0.048d−1, and simulated absolute growth rate at flowering and fruiting stage with measured values R2=0.785 and RMSE=0.877g·d−1. In summary, this study provides a new method for quantitative facility microclimate analysis, which is more comprehensive than temperature determination, and also provides a new way of thinking for the construction of tomato growth rate model. Related Articles | Metrics | Comments（0）