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Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Daily meteorological data from 1981 to 2022 and citrus growth periods data were used in this paper. The daily mean temperature, daily maximum temperature and their duration were selected as indicators of heat stress in citrus to clarify the spatial distribution characteristic and temporal variation trend of heat stress during citrus growth periods. The spatial and temporal differences of heat stress in different growing periods of citrus were compared using a paired t-test. The results show that (1) the average frequency, times and intensity of heat stress during flowering-fruit expanding stage of citrus are 87.73%, 2.23times•y-1 and 5.28d•times -1, respectively. High-value areas are mainly concentrated in the southeast of Jiangxi province. The average frequency, times and intensity of heat stress during the fruit expanding-fruit coloring stage of citrus are 56.43%, 1.15times•y-1 and 2.74d•times -1, respectively. High-value areas are mainly in the northern and central parts of Jiangxi province. (2) The station ratios, times and intensity of heat stress during the flowering-fruit expanding stage of citrus show a decreasing trend, with an average decrease of 0.90 percent points, 0.02 times and 0.06 d•time -1 every 10 years, respectively. The station ratios, times and intensity of heat stress during fruit expanding-fruit coloring stage of citrus show an increasing trend, with an average increase of 6.80 percent points, 0.26times and 0.50d•times -1 every 10 years, respectively. (3) The paired t-test results show that, the frequency, times and intensity of heat stress during flowering-fruit expanding stage of citrus are significantly higher than that during fruit expanding-fruit coloring stage of citrus. However, the climate tendency of times and intensity of heat stress during flowering-fruit expanding stage of citrus are significantly lower than that during fruit expanding-fruit coloring stage of citrus. The flowering-fruit expanding stage of citrus in Jiangxi province is the most frequent period of heat stress. For now, it is necessary to strengthen citrus defenses against heat stress during the flowering-fruit expanding stage. In the future, we should improve the prevention of heat stress in citrus during the fruit expanding-fruit coloring stage. [ABSTRACT FROM AUTHOR]

Soil denitrification is an important pathway of soil nitrogen loss. The large amount of nitrogen fertilizer applied in agricultural production leads to the increase of soil N2O emission, and it has caused environmental problems such as the enhanced greenhouse effect. At the same time, soil denitrification is also the main way of N2O reduction, so controlling the ratio of soil denitrification products N2O/(N2O+N2) is the key to reduce soil N2O emission. Based on a large quantity of relevant researches, this paper summarized the measurement methods and influencing factors of denitrification product ratio in soil and the mechanism of biochar addition affecting soil denitrification product ratio. The results showed that there was still existing uncertainty about the effect of biochar application on denitrification product ratio, and whether biochar addition could effectively regulate denitrification product ratio and reduce N2O emission was affected by some influencing factors, such as soil physicochemical properties, biochar properties and application amount. Based on the above research status, the future prospects for improving the measurement methods of denitrification products and clarifying the quantitative effects of biochar addition denitrification products ratio and its key influencing factors were proposed. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Droughts are increasing in frequency and intensity as the global climate changes. Risk assessment for agricultural drought disasters is an important approach for disaster prevention and mitigation. Based on the formation mechanism of natural disaster risk, the index system model of agricultural drought risk assessment in North China was constructed, and the robustness of the established risk assessment model was tested by using the internal test method. Then based on the characteristics of agricultural drought risk formation in North China, the paper proposes corresponding risk prevention recommendations. The conclusions were as follows: when adjusting the indices and methods in the risk assessment model, the range of changes in the agricultural drought risk ranking for each city was mostly 1-2.5 places, and the model was relatively robust. With the exception of Beijing and Tianjin, which had the highest disaster prevention and mitigation capacity, central and northern China had the highest agricultural drought risk, which was previously linked to the high risk and vulnerability of these regions. The agricultural drought risk in northern Henan and southern Shandong is low, mainly due to the low risk. The 34 cities in North China can be divided into 6 agricultural drought risk clusters, which are not dispersed in space and cross-city distribution, and have good aggregation. Cluster 4, located in the northernmost mountainous areas, has the highest risk of drought, which is associated with high environmental vulnerability and low capacity for disaster prevention and mitigation, so agricultural areas should be reduced and agricultural input should be increased. Clusters 2, 5 and 6, located in the central and southern regions, have higher grain acreage and yields due to drought, so agricultural drought risk can be further reduced by increasing agricultural input and improving irrigation guarantee rate. [ABSTRACT FROM AUTHOR]

Meteorological disasters are one of the major risks to agricultural production, causing huge losses to agriculture. Agricultural insurance is an important part of the agricultural security system and can effectively spread agricultural risks and losses. Weather index insurance, which emerged in the late 1990s, has received a lot of attention, research, and applications due to its objectivity, standardization, and robust liquidity. In this paper, authors analyzed the advantages and disadvantages of weather index insurance compared to traditional agricultural insurance. The development of weather index insurance technology at home and abroad was reviewed. Authors introduced the development and practical application of weather index insurance model for Anhui grain crops (winter wheat, one season rice, summer corn), and discussed and prospected the future development of weather index insurance. [ABSTRACT FROM AUTHOR]

The extensive use of antibiotics in the medical and aquaculture industries has led to antibiotic resistance, be a global public health concern. Compared with soil and water, there are few reports on antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the air. To provide theoretical support for scientific and effective response to the cross-media migration of microbial resistance, this paper comprehensively reviewed the occurrence status, influencing factors and transmission mechanism of ARB and ARGs in different types of ambient air at home and abroad. The results showed that the abundance of ARB and ARGs in the air was affected by environmental conditions and sampling factors. The pollution was more serious in typical polluted areas such as animal farms, sewage treatment plants and hospitals. The dominant types of ARGs in the above environment were tetracyclines, sulfonamides and β-lactams. Among them, the abundance of ARGs in the air of animal farms was about 2-3 orders of magnitude higher than that in other environments. The highest abundance was found in pig farm compared to other animal houses. At present, there was still no standard for the sampling requirements of ARB and ARGs in the air. The sampling season, duration, particle size and coexisting pollutants all affected their detection. Air pollution, soil water content, rainfall and air mass movement were proved to play a certain role in affecting the spread of ARB and ARGs in the air. Based on it, the research on the migration mechanism of ARB and ARGs at the soil-air interface needs to be further intensified. The review aimed to comprehensively reveal the occurrence characteristics of ARB and ARGs in the air, and provide theoretical support for the scientific and effective response to the cross-media migration of microbial resistance. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an ideal 'indicator' for directly monitoring plant photosynthesis, solar-induced chlorophyll fluorescence(SIF) has a rapid response to variations in plant physiological status. SIF is becoming one of the most active research direction in vegetation remote sensing. This study conducted a systematic literature review on topics of relevance to SIF. To do so, there are 786 SIF-related papers published during 1982-2021 were collected from the Scopus database. Based on VOSviewer, the visual bibliometric analysis was applied to analyze these papers from the perspective of country, institution, author, journal and keyword. The results show that the number of SIF articles published per year is rising rapidly. Among all the countries, United States, China and Germany published 285, 263, and 166, making them the top three countries that have the most SIF papers during the study period. Germany has the highest citations per publication (56.2) and the largest number of cooperative countries(36). Nanjing University, California Institute of Technology, and University of Valencia have made outstanding contributions to the development of this field as they have not only the large number of publications but also the high h-indices Among the scholars in this area, Guanter L(Polytechnic University of Valencia), Zhang Y(Nanjing University), Frankenberg C(California Institute of Technology), Liu L(Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences), and Rascher U(Jülich Research Centre), are currently the most productive, having published more than 40 papers. The Journal Remote Sensing of Environment has the highest number of SIF articles (92) and the highest H-index (40), and Global Change Biology has the highest citations per publication (65.6) in this field. The keyword analysis shows that SIF is a highly multidisciplinary area mainly involving geoscience, ecology, agronomy, plant physiology across a range of spatial and temporal scales. Currently, the most active research topics are the monitor of plant physiological status and stress condition, the acquisition methods of SIF measurements, and the applications of SIF in remote sensing such as terrestrial carbon cycle. China leads the world of overall research focus in this field, which, however, still should have a further improvement of its influence. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Biochar has been recognized as a new exogenous organic substrate and is often used as an important organic resource for carbon reduction because of its stability, adsorption and carbon nutrient richness. The study was conducted in a typical indica rice area of Nanning from 2021 to 2022, against the background of having high early indica rice yields, simultaneous rain and heat, and unique cropping system. In this paper, authors set three treatments: Control treatment (CK): no fertilizer. Inorganic N input (T1, chemical fertilizer) treatment: chemical fertilizer application at conventional fertilizer level, compound fertilizer 800kgha-1, urea 260.87kgha-1, potassium 193.55kgha-1. Inorganic N with organic N (T2, biochar + chemical fertilizer) treatment: biochar 4000kgha-1, compound fertilizer 738.67kgha-1, urea 146.09kgha-1, potassium 34.19kgha-1. The cumulative greenhouse gas emissions, emission equivalents, rice yield traits and the effect of isonitrogen substitution of biochar application on greenhouse gas emissions and rice yield in early southern rice fields were analyzed by regular monitoring of soil greenhouse gas emissions in rice fields during the rice reproductive period using a split static box-meteorological chromatography method 5d after rice transplanting, this study provide a basis for optimizing intensive early rice low-carbon cultivation and reduce fertilizer and increase efficiency. The results showed that: (1) biochar can reduce CH4 and CO2 emissions from paddy soils, and reduce the combined emission equivalent by slowing down CH4 emissions. The application of fertilizer with biochar can mitigate the increase of greenhouse gas carbon emissions caused by fertilizer application alone, and its delayed effect of mitigating CO2 emissions is more obvious. In biochar treatment (T2), compared with the chemical fertilizer treatment (T1), the maximum CH4 emission flux in 2021 was reduced by 41.38% and the cumulative emission was reduced by 31.25%, and the maximum emission flux in 2022 was reduced by 50.50% and the cumulative emission was significantly reduced by 50%, and the combined emission equivalents of 2 years were significantly lower than those of the T1 treatment. The maximum CO2 emission flux and cumulative emission in 2021 were reduced by 57.38% and 37.68%, respectively, compared with the T1 treatment, and the corresponding reduction in 2022 was 16.06% and 35.52% compared to the T1 treatment. (2) Biochar can suppress N2O emissions, significantly reduce cumulative emissions, and reduce nitrogen source emission equivalents. Compared to the T1 treatment, the maximum N2O emission flux was reduced by 5.43% and the cumulative emission was significantly reduced by 33.53% in 2021 in T2 treatment; the maximum emission flux was reduced by 73.75% and the cumulative emission was significantly reduced by 54.33% in 2022, and there was no significant change with the CK treatment. (3) Biochar facilitates the optimization of intensive early indica rice cultivation structure and enhances the productivity of early indica rice. After biochar was put into the paddy field for 2 years, the effect of increasing yield became more and more obvious, and the theoretical yield of T2 treatment was 1.02-1.33 times that of T1 treatment, while the actual yield was 1.06-1.32 times that of T1 treatment. Fertilizer with biochar reduced greenhouse gas emissions and increased rice yield in early indica rice fields, which can be used as an optimization model for low-carbon production of intensive early indica rice in the south. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aims of this paper is to illustrate the importance of grain production in China's food security strategy based on the three Northeastern provinces (NEP) in the new period, which quantitative assessment of climate change under the background of the loss caused by meteorological disasters of regional food production is clarify. In this paper, using grain planting area, yield and agricultural disaster statistics from 1981 to 2020, comparison analysis grain production and disaster characteristics between NEP and the whole country respectively. The disaster-yield assessment model was used to estimate the disaster-yield loss and final yield of the NEP by inputting disaster data in recent 10 years, and the sensitivity and stability of the disaster-yield assessment model were re-tested. The results showed that :(1) from 1981 to 2020, the grain planting area and total output in NEP increased significantly, and the proportion of the total output of NEP increased steadily, and the proportion of the total output of the three northeast provinces reached 1/5 of the total output of the whole country by 2020. (2) The disaster situation in NEP showed a significant trend of first increasing and then decreasing. The incrasing of average grain yield during the past 40 years was 65.96kg⋅ha-1 and 252.5kg⋅ha-1 per year for NEP and the whole country, while the incrasing of average grain yield during the past 10 years was 52.6kg⋅ha-1 per year for NEP significantly. (3) From 2011 to 2020, the average affected area and affected area in China were 23704.5x10³ha and 11204.7x10³ha, respectively, and 3899.1x10³disasters of the whole country and the three northeastern provinces were significantly lower than those of the previous three years, making it the decade with the least severe disasters in 40 years. (4) The simulation accuracy of the disaster-yield assessment model was high. The linear regression coefficients (R²) of simulated grain yield and measured grain yield in Heilongjiang, Jilin and Liaoning provinces were 0.98, 0.90 and 0.88, respectively. The slopes were 1.05, 1.02 and 0.98 (P < 0.01), respectively. The loss rate of grain yield due to agro-disaster was 10.4%, 17.9% and 18.0% respectively in the three province, while which was more than 8.0%, 17.0% and 16.0% for 20a.years. (5) The model slightly overestimated the grain yield of Jilin and Liaoning in recent 10 years due to the overall light disaster situation. Based on the data from 1981 to 2010, the regional grain disaster loss assessment model was proved to be able to evaluate the loss of grain yield caused by meteorological disasters well, and had the performance of predicting grain yield, and has the feasibility of operational application. The impact of meteorological disasters on the grain output in northeast China is higher than the average level of disasters in the whole country. Considering that the grain output in Northeast China accounts for a high proportion of the national grain output, preventing the risk of agro-meteorological disasters in Northeast China in the new period is of great importance to guarantee the national food security. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbon emission from crop production is one of the important sources of greenhouse gas emission in China, and it is a hot issue on agricultural ecological environment in recent years. Based on the statistical data of agricultural production input, crop yield, cultivated land area and crop sowing area in Hebei province from 2010 to 2018, this paper studied the dynamic changes of carbon emission of crop production inputs, and analyzed the proportion of carbon emission for each different crop production inputs, so as to provide a theoretical basis for energy conservation and emission reduction in agricultural production, and in the end to realize the low-carbon agriculture. The results showed that from 2010 to 2018, the carbon emission from crop production in Hebei province took 2015 as the turning point, showing a trend of increasing first and then decreasing. From 2010 to 2018, the total carbon emissions from crop production, carbon emissions per unit yield and carbon emissions per unit cultivated land area in Hebei province were 22.19-104-26.74x104tCO2 eq, 0.21-0.30tCO2eq·t-1 and 3.40-4.10tCO2eq·ha-1, respectively. The total carbon emission of crop production, carbon emission per unit yield and carbon emission per unit cultivated land area in 2018 were the lowest, decreasing by 17.0%, 30.0% and 17.0% respectively compared with the highest value. The 9-year average carbon emission of chemical fertilizer, pesticide, agricultural film, diesel fuel and irrigation electricity accounted for 38.6%, 2.1%, 11.5%, 34.7% and 13.1%, respectively. Chemical fertilizer and diesel fuel were the main sources of agricultural carbon emission, accounting for more than 30%. The dynamic change of carbon emission of crop production inputs was obviously affected by the national policies. It is suggested that the carbon emissions from agricultural production should be guided by national policies, and measures such as formulating mature agricultural management system, strengthening agricultural technology training and promoting the application of advanced cultivation techniques should be taken to reduce the carbon emissions from agricultural sources, so as to promote the green development of agriculture. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The effects of irrigation on winter wheat yield and water use efficiency (WUE) were mostly explored based on site-based experiments in North China Plain (NCP) region. However, due to the influences of contrasting environmental factors (e.g. climate and soil properties), these results cannot be accurately cross-compared among different studies, resulting in the difficulty to get the generalizable pattern at regional scale. Here meta-analysis was conducted to comprehensively evaluate the effects of irrigation on winter wheat yield and WUE in NCP region, with the observation data of 1876 pairs from 186 field experimental papers totally. The differences of the irrigation effects in different regions, precipitation year types, soil texture, and nitrogen (N) application levels were explored, and the corresponding optimal irrigation amounts for reaching high yield and WUE were ascertained. Results showed that compared with non-irrigation during the winter wheat growing period, irrigation increased the yield of winter wheat in NCP by 32.0%-38.3%, and reduced the WUE by 27.1%-30.1%. The yield increment due to irrigation in the northwest of NCP (39.6%-53.5%) with total precipitation during the winter wheat growing period below 150mm was higher than that in the southeast of NCP (24.3%-27.1%) with total precipitation during the winter wheat growing period higher than 150mm, while the decrease of WUE due to irrigation in northwest of NCP (32.4%-37.5%) was higher than that in the southeast of NCP (22.0%-24.3%). The optimum irrigation amount for high yield and WUE of winter wheat was 150-180mm in the northwest and 120-150mm in the southeast. Specifically, for different precipitation year types, the optimum irrigation amounts were 120-150mm with 2 times during jointing and flowering stages for dry year, during jointing and heading stages for normal year, and during jointing and booting stages for wet year. For different soil texture, irrigation under loamy soil had the highest increases in yield, while clay soil had the lowest decreases in WUE; the optimum irrigation amounts of winter wheat with four different soil texture of sandy soil, loam, clay loam and clay were 60-90mm, 120-150mm, 180-210mm, and 150-180mm, respectively. For different N application levels, N application of 120-240kg.ha-1 led to the highest yield and WUE under the irrigation amounts of 80-140mm, of which the higher yield was obtained under irrigation amounts of 110-140mm, and the higher WUE was obtained under the irrigation amounts of 80-110mm. Collectively, the NCP region can achieve the goals of high yield and WUE when irrigation amount was 120-150mm with 2 times but at different stages during different precipitation year types (i.e. dry year, normal year and wet year). Meanwhile, the combination of loam conditions with the N application of 120-240kg.ha-1 can synergistically improve the yield and water use efficiency of winter wheat. [ABSTRACT FROM AUTHOR]

Excessive anthropogenic emissions of greenhouse gas have led to global climate change in recently years. Methane is an important greenhouse gas after carbon dioxide. Methane emissions increase with the global temperature, which further intensifies global warming. Soil is a huge source and sink of methane, and methanotrophic bacteria play a key role in reducing methane emissions. Exploring the effect of temperature on soil methane-oxidizing ability has been a research hotspot in recent years. This paper reviewed the effects of temperature on soil methane oxidation and methanotrophic bacteria; analyzes and compares the soil methane oxidation process and methanotrophic bacteria in various ecosystems at different temperatures, and the growth temperature range of methanotrophic bacteria strains. The results showed that various ecosystems have different temperature ranges for methane oxidation; the rate of methane oxidation increases with increasing temperature in their particular temperature ranges. When the cultivation temperature is closer to the in-situ temperature, the methane oxidation response will be faster. Similar to the effect of temperature on methane oxidation, the diversity and abundance of methanotrophic bacteria also increase with increasing temperature and are closely related to the magnitude of temperature increase and the adaptation temperature of dominant bacteria. Type II methanotrophic bacteria in the soil are more sensitive to temperature. As the temperature rises, the abundance of type II methanotrophs increases. Therefore, temperature affects the abundance and community structure of methanotrophs, thereby affecting the rate of methane oxidation and methane emissions. However, whether temperature can only change the methane oxidation capacity of the soil by regulating the replacement of dominant bacteria is still unconfirmed. This review discussed the response of methane oxidation to temperature and its microbial mechanism, in order to provides a comprehensive analysis for methane oxidation capacity under the context of future climate change. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to explore a simple and easy method to predict the initial flowering stage of rape, the correlation analysis method was used in this paper to determine the winter climate factors significantly related to the first flowering period, and the gray correlation analysis method was also used to determine the pre flowering phenology factors most related to the first flowering period. Then the multiple regression linear equations were established and back substitution test was carried out, and finally the root mean square error (RMSE) and relative error (RE) models were used to evaluate the simulated and measured values. The results showed that: (1) the winter meteorological factors significantly related to the first flowering period were the average minimum temperature in January, the average minimum temperature in February and the sunshine hours in February, and their correlation coefficients were -0.404, -0.556, -0.478, respectively. There was no collinearity between the three independent variables. The regression model was statistically significant and passed the significance test. (2) Among the pre-anthesis phenological stages, there is a high correlation between the sprouting stage, budding stage and the initial flowering stage; and their correlation coefficients were 0.656 and 0.634, respectively. The regression model also showed statistical significance and passed the significance test. (3) The models established by the two methods are tested and evaluated. The back substitution test shows that the fitting accuracy of the models established by the two methods is relatively close on the whole. The RMSE climate factor based on climate factor is 7.16, and the RE climate factor is 11.2%; The phenological factors based on RMSE and RE were 6.50% and 3.87%, respectively. Pearson correlation analysis showed that the correlation coefficients of R phenological factor and R climatic factor were 0.738 and 0.658 respectively, which passed the significance test of 0.01 level. Among them, R phenological factor is higher than R climatic factor. Based on comprehensive analysis of various indicators, the model established by grey correlation analysis is more reliable than the model established by climate factors can be drawn. [ABSTRACT FROM AUTHOR]

Plant root system architecture is the growth and distribution of the root system in its growth medium, include root length, number, branch and biomass, etc, which can fix plants in the soil and effectively absorb water and mineral nutrients, which directly affect the growth and development of plants. The root system architecture is affected by many factors, including soil moisture, nutrients and rhizosphere microorganisms. Conventional root ameliorated practices often rely on chemical fertilizers, which have immense and adverse effects on environments. Therefore, it is necessary to propose alternatives to chemical fertilizers. The rhizosphere of the plant is an essential niche with abundant microorganisms residing in it, those rhizospheric microbes link the interaction of plants and soil to promote nutrient solubilization and they possess the properties of the primary root, lateral root and root hair growth ameliorated as the second genome of the plant. The application in the techniques of multi-omic analysis (genomics-metabolomics, genomics-transcriptomics, etc) can explore deeply related mechanisms for beneficial microbes affect root development. These mechanisms are of great importance in improving soil fertility and plant growth, thus reducing the negative impact of chemical fertilizers on the environment. Therefore, the aim of this paper was to review the research methods, effects and mechanisms of root system architecture regulated by plant rhizosphere microorganisms. The results indicated that AMF, PGPR and rhizobium increased root length, root diameter, root branch and promoted root hair and lateral root development through four mechanisms (nitrogen fixation, phosphate solubilization, regulation of plant secretion of plant hormones, and release of volatile organic compounds). Above all, plant rhizosphere microorganisms can improve root system architecture, but the effect of plant rhizosphere microorganism's application still needs to be further studied. Quantifying the relative contributions of different mechanisms and improving the stability of microbial inoculants in practical applications are the focus of follow-up research. These conclusions will provide a theoretical basis for the development of microbial inoculants. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate estimation of reference crop evapotranspiration (ET0) is essential for water resources planning and irrigation scheduling. However, the absence of solar radiation (Rs) data is a common problem affecting the estimation of ET0. This study investigates the feasibility of employing temperature-based models to estimate Rs and proposes effective methodologies for obtaining more convenient and accurate ET0 estimates. To evaluate the effectiveness of different approaches, authors compared nine empirical models (M1-M9) and three machine learning algorithms (RF, GRNN and ANN) for daily Rs estimation. This analysis utilized data from 339 national basic meteorological stations in China, spanning the period from 2001 to 2018. Subsequently, authors proposed two strategies for estimating daily ET0 in regions where solar radiation data is limited or unavailable. The results showed that (1) temperature-based models exhibited satisfactory accuracy (R² > 0.6) for daily Rs estimation, with machine learning algorithms outperforming their empirical counterparts. The machine learning accuracies are ranked as follows: Artificial Neural Network (ANN) > Generalized Regression Neural Network (GRNN) > Random Forest (RF). And empirical models are ranked in descending order of accuracy: M9 > M8 > M6 > M7 > M5 > M2 > M3 > M1 > M4. The accuracies of twelve models in the four climatic zones are indicated as follows: the temperate continental zone (TCZ) > the temperate monsoon zone (TMZ) > the subtropical monsoon zone (SMZ) > the mountain plateau zone (MPZ). (2) The comprehensive assessment for nine empirical models indicates that the Hargreaves-Samani model (M1) is the most reliable for solar radiation estimation. Its estimated results are close to those of the other models, and the coefficient of variation of the parameters (0.10) is much lower than that of the other empirical models. Thus, combining the model with the nationally calibrated parameters computed by the Kriging interpolation method allows for reliable values of the daily solar radiation. (3) Machine learning techniques show variations in estimating daily ET0 across different climate zones. The machine learning accuracies are ranked as ANN>GRNN>RF, and TCZ>TMZ>MPZ>SMZ in the four climate zones. (4) The accuracies of the two daily ET0 estimation strategies, with or without actual Rs calibration, are very close. Both strategies provide accurate daily ET0 estimates (R² >0.95) with an average R² improvement of only 0.39% for strategy I compared to strategy II. In conclusion, this study provides new ideas to address the scarcity of solar radiation data and highlight the potential of machine learning in ET0 estimation. This approach can be effectively applied to reference crop evapotranspiration estimates in regions where solar radiation data is scarce. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Agrometeorology is the property of Editorial Board of Chinese Journal of Agrometeorology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)