Top Read Articles

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

Please wait a minute...


For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails

Select

Characteristics of Climatic Seasonal Variation in Northeast China under the New Standard SHAO Qi-duo, FENG Xi-yuan, REN Hang, TU Gang, LI Shang-feng, LIU Gang, YANG Xu, WU Di Chinese Journal of Agrometeorology    2025, 46 (6): 741-752.   DOI: 10.3969/j.issn.1000-6362.2025.06.001 Abstract （1017）      PDF（pc） （16028KB）（200）       Knowledge map    Save According to the national standard of Climate Seasonal Division (GB\T 42074−2022), the characteristics of seasonal variation in Northeast China (NEC) for the period 1961–2020 were analyzed using CN05.1 gridded data, and the changes caused by the shift of the standards and climatological baselines were investigated. The results showed that the climatic season of NEC was divided into regions with four seasons and non−summer zone regions, and the non−summer regions were mainly located in the northern part of the NEC, high−altitude regions and their surroundings. Spring and summer started from the south to the northeast, from the central plains to the high altitude mountains, and vice versa in autumn and winter. Compared with the 1981–2010 baseline period, parts of the Sanjiang plain and Hulun lake changed from non−summer regions to four−season regions. The starting dates showed a significant advance of 1d·10y−1 in spring over most of the NEC region, and a significant advance of 2−3d·10y−1 in summer over the central and western parts of the Northeastern plains. The starting dates were significantly delayed in autumn over the four-season regions, and in winter over the non−summer regions and the central of Northeastern plains. The summer and winter duration were significantly prolonged and delayed, respectively. Compared to the original standard, there were more areas with significant changes in spring and summer starting dates and summer and winter duration under the new standard. The areas up to the summer standard showed a significant upward trend of 3.9PP·10y−1 and had a significant positive correlation with the area−mean June−July−August NEC temperature. The rating of starting date of seasons obeys the normal distribution law, with a slight advance in summer. Related Articles | Metrics | Comments（0）

Select

Report on Meteorological Condition Impact to Agricultural Production in Winter of 2024/2025 HE Yan-bo, WU Men-xin, ZHAO Xiao-feng, GUO An-hong, LI Sen, HOU Ying-yu Chinese Journal of Agrometeorology    2025, 46 (5): 737-740.   DOI: 10.3969/j.issn.1000-6362.2025.05.014 Abstract （920）      PDF（pc） （310KB）（247）       Knowledge map    Save During the winter of 2024/2025 (December 2024–February 2025), China’s national average temperature was −3.3°C, 0.3°C above the long-term average (1991–2020, hereinafter referred to as perennial). Spatially averaged total precipitation was 23.7mm across the nation, 39.4% less than the perennial , while average sunshine duration reached 519h, 6.1% more than the perennial. In most agricultural regions, favorable light and heat conditions prevailed during the winter, and suitable soil moisture supported the safe overwintering of winter wheat in northern China and the vigorous growth of rapeseed and other crops in southern China. However, persistent snow cover in parts of northern China had posed challenges for livestock farming and conservation protected agriculture. In additionally, the late−season snowmelt and freeze−thaw cycle disrupted grain storage and transportation in northeast China. In east−central of south China, a prolonged precipitation deficits had led to mild to moderate drought, negatively affecting field crops and economic fruit trees. In the latter part of winter, periodic cold and rainy weather in eastern of southwest China, southern Yangtze, and western of south China hampered the steady growth of rapeseed and open−field vegetables. Related Articles | Metrics | Comments（0）

Select

Development of a Growth Conditions Dataset of Major Crops in China (V2.0) GAO Jing, LIAO Jie, YANG Bing-yu, LIU Yuan-yuan Chinese Journal of Agrometeorology    2025, 46 (5): 725-736.   DOI: 10.3969/j.issn.1000-6362.2025.05.013 Abstract （627）      PDF（pc） （6104KB）（439）       Knowledge map    Save A dataset of the growth conditions of major crops in China was mainly constructed from paper-based annual records before 2012 and electronic annual records after 2013. However, there were problems such as inconsistencies in the observed items and data units，the quality of some data had not been evaluated. To improve the consistency and accuracy of agricultural meteorological data, based on these two types data, a high-quality dataset of the growth conditions China's major crops (including wheat, rice, maize, cotton, oil-seed rape, soybean and peanut) from 1981 to 2022 was developed by using the observation items standardization, integrity checks, cross-year value checks, observation time checks, value range checks, internal consistency checks element limit value check and manual verification. The dataset promoted effective application in agricultural research and decision-making. The results showed that the valid rate of crop common stage from 1981 to 2022 was over 96.0% of the expected observations, while the valid rate for growth status, crop height, stem count and effective stem count were all over 86.0%. The accuracy rate of the above five mentioned elements were above 99.3%. The distribution of observation stations for the seven major crops had obvious spatial and temporal distribution characteristics, with dense stations, uniform spatial distribution and long observation years in eastern China, but sparse and short observation years in northwest China. There were also obvious differences in the number of observation stations between different crops, and the number of observation stations for cotton and oil crops were less than that for staple crops. The valid data was relatively low in the 1980s, but improved significantly after 1994. After quality control and data verification, the valid rate of crop common stage increased from 94.7% to 96.2%, the crop height increased from 88.2% to 92.0%, the stem count increased from 77.1% to 86.7%. The accuracy rate of the common stage data increased from 99.3% to 99.6%. Compared to the "China Major Crops Growth and Development Dataset V1.0"，the overall quality of this dataset has been improved, with the addition of element boundary value checks. This dataset can provide critical fundamental information for studying the impact of climate change on the growth and development of major crops in China. Related Articles | Metrics | Comments（0）

Select

Microbial Seed Coating Promote Wheat Seed Germination and Seedling Growth under Drought Stress Condition JIANG Ya-wen, XIE Wen-yan, HE Jiu-xing, GONG Min, HUO Qiu-yan, YANG Xi, HAN Wei, LV Guo-hua Chinese Journal of Agrometeorology    2025, 46 (5): 609-618.   DOI: 10.3969/j.issn.1000-6362.2025.05.002 Abstract （436）      PDF（pc） （1365KB）（311）       Knowledge map    Save Drought stress at the germination and seedling stages is a key factor in reducing crop yields in arid and semi−arid areas. Seeded surrounding microenvironment regulation is one of the important technical measures to improve crop drought resistance. In this paper, wheat (Jimai 22) was selected as the experimental variety, while Bacillus subtilis ACCC 19742 and Bacillus magaterium ACCC 04296 were chosen as the experimental strains. The bacteria were encapsulated using microencapsulation. Wheat seeds coated with bacterial microcapsulation were investigated for seed germination and seedling growth under drought stress. Four treatments were established: Bacillus subtilis coatied (M), Bacillus megaterium coatied (B), Bacillus subtilis and Bacillus megaterium compound coatied (MB), and uncoated treatment (CK). The results showed that the compound bacterial coating had the best effect than the single-strain coatings. The ratio of emergency, above ground dry weight and root-shoot ratio were significantly improved, increased by 12.8 percentage points, 17.8% and 5.3% compared with M treatment, while 15.3 percentage points, 14.7% and 5.7% compared with B treatment. Compared with CK treatment, ratio of emergency was increased by 25.9 percentage points, above ground dry weight increased by 21.8%, root-shoot ratio increased by 9.8%, and total root length, surface area and total volume increased by 37.5%, 34.7% and 84.3% respectively. The activity of superoxide dismutase (SOD), peroxidase (POD), catalase from micrococcus lysodeikticus (CAT) significantly increased, and the content of malondialdehyde (MDA) decreased, but the content of proline (PRO) obviously increased. Fluorescence parameters Fv/Fm and ΦPSⅡ were both larger than that of CK treatment, which showed that coating with composite bacteria could improve the drought resistance significantly. In summary, seed coatied with bacterial microencapsulation can promote seed emergence, root growth, and stress-tolerant enzyme activity in drought stress conditions to increase drought tolerance. Moreover, a compound microbial coating is the optimal method. Related Articles | Metrics | Comments（0）

Select

Characteristics and Causes of Spatiotemporal Variation of Dry-wet Climate in Jilin Province REN Jing-quan, LIU Yu-xi, WU Yu-jie, MU Jia, LIU Cong, GAO Yan, WANG Dong-ni, YU Qing-bo Chinese Journal of Agrometeorology    2025, 46 (10): 1383-1394.   DOI: 10.3969/j.issn.1000-6362.2025.10.001 Abstract （409）      PDF（pc） （6056KB）（184）       Knowledge map    Save In order to study the characteristics and causes of dry−wet climate change in Jilin province, the aridity index (AI) was calculated based on daily meteorological data from 46 meteorological stations in Jilin from 1961 to 2021. Linear tendency estimation and inverse distance weighted spatial interpolation based on ArcGIS 10.2 were used to analyze the spatiotemporal variation characteristics of AI, and contribution rate analysis was used to analyze the cause of AI. The results indicated that the AI values in Jilin province and its western, central and eastern regions exhibited negative trends from 1961 to 2021. There was a significant spatial difference in the average AI values in Jilin province, with a spatial distribution pattern of ‘high−low−high’ from west to east. It was divided into sub arid, sub humid and humid regions in Jilin province. The sub humid region had been expanding over the years, reaching its maximum area in the 2010s. ET0 showed a downward trend, while the precipitation showed an upward trend in Jilin from 1961 to 2021, but the changes trend were not significant. The water vapor pressure and average temperature both showed a significant upward trend, with the climate tendency rate of 0.008kPa·10y−1 (P<0.01) and 0.32℃·10y−1 (P<0.01), respectively. The net solar radiation and wind speed both showed a significant downward trend, with the climate tendency rate of −0.077MJ·m−2·10y−1(P<0.01) and −0.14m·s−1·10y−1(P<0.01), respectively. ET0, net solar radiation, average temperature and wind speed gradually decreased from west to east, while the precipitation showed a gradual increase from west to east and the vapor pressure mainly exhibited a spatial distribution characteristic of ‘low−high−low’. The meteorological factors of vast majority of station had a negative contribution to AI. Precipitation was the dominant factor for the variations in AI values in Jilin province and its west and east, followed by wind speed and ET0, but in the central of Jilin province, wind speed was the dominant factor for the AI change, followed by precipitation and ET0. The research results can provide support for the formulation of strategies to cope with dry−wet climate change and the rational utilization of climate resources in Jilin province.  Related Articles | Metrics | Comments（0）

Select

Effects of Elevated Nutrient Solution Concentration on Growth and Nutrient Absorption of Lettuce under High Temperature Environment in Greenhouse ZHU Huai-wei, FANG Qiao-xian, ZHENG Ze-hua, WANG Guang-lun, FU Ya-ting Chinese Journal of Agrometeorology    2025, 46 (4): 533-545.   DOI: 10.3969/j.issn.1000-6362.2025.04.009 Abstract （398）      PDF（pc） （1403KB）（319）       Knowledge map    Save A hydroponic planting experiment in the southern plastic greenhouse with lettuce was conducted to investigate the effects of two nutrient solution concentrations supply on leaf number, plant height, fresh weight, dry weight and leaf nutrient element content (Ca, Mg, Fe, Mn, Cu, Zn) at different growth stages under high temperature environment. The two levels of temperature environment for lettuce growth were set as high temperature environment (H) and normal temperature environment (N). The nutrient solution concentration was expressed by EC (μS·cm−1), which was set as normal concentration (CK, 1500μS·cm−1) and elevated concentration (C1, 1900μS·cm−1). The results showed that, (1) high temperature environment increased daily average temperature in the growth of lettuce leaves and nutrient solution by 13.9℃ and 12.0℃, daily minimum temperature by 13.9℃and 11.8℃, daily maximum temperature by 14.4℃and 12.7℃, respectively, compared with normal temperature environment. (2) Under normal temperature environment, elevated concentration increased leaf number, plant height, shoot fresh weight, root fresh weight, shoot dry weight and root dry weight at the harvesting stage by 15.2%, 16.9%, 63.2%, 24.4%, 28.5% and 6.6%, respectively, compared with normal concentration. However, under high temperature environment, normal concentration increased above growth indicators by 54.2%, 41.0%, 249.5%, 496.0%, 169.6% and 353.4% at the harvesting stage, respectively, compared with elevated concentration. (3) High temperature environment promoted the contents of Ca, Mg and Fe in lettuce leaves. Under normal temperature environment, elevated concentration significantly promoted the contents of Mn and Cu in lettuce leaves at the harvesting stage by 22.7% and 61.5%, while unsignificant difference occurred in the contents of Ca, Mg, Fe and Zn, compared with normal concentration. Furthermore, under high temperature environment, normal concentration significantly promoted the contents of Ca and Mn in lettuce leaves at the harvesting stage by 34.5% and 44.9%, while didn’t affect the contents of Mg, Cu and Zn significantly, compared with elevated concentration. It is suggested that temperature environment and nutrient solution concentration have significant effects on hydroponic lettuce growth and nutrient absorption, and increasing lettuce yield, quality and fertilizer efficiency can be achieved by adjusting nutrient solution concentration during the actual production of hydroponic lettuce in Summer and Autumn/Winter. Related Articles | Metrics | Comments（0）

Select

Analysis of the Climate Production Potential Characteristics of Rice under the Background of Climate Change in Hilly Area of Central Sichuan LI Jing-rui, LUO Huai-liang, LIU Xiao-ran Chinese Journal of Agrometeorology    2025, 46 (4): 471-482.   DOI: 10.3969/j.issn.1000-6362.2025.04.004 Abstract （381）      PDF（pc） （12307KB）（182）       Knowledge map    Save Based on daily meteorological data in the hilly areas of central Sichuan from 1970 to 2023, the modified FAO climate production potential model was used to analyze the temporal and spatial dynamic characteristics of climate change and rice climate production potential. Then, based on the rice production data over the years, the utilization of climate resources was evaluated, and the sensitivity model was used to explore the impact of climate change on climate production potential. The results showed that: (1) during the study period, the heat resources in the hilly area of central Sichuan increased significantly, the interannual fluctuation of precipitation was large, the sunshine resources were scarce, the heat and light resources were latitudinal distribution, and the water resources were meridional distribution. (2) The climatic production potential of rice in the hilly region of central Sichuan province showed a "increase decrease increase" change, and the annual average value was 15198kg·ha−1, which was high in the southeast and low in the northwest. (3) The annual average utilization rate of climate resources was 50.94%, with great potential for yield increase in the future. (4) Sensitivity analysis shows that an increase in water resources had a positive impact on climate production potential, while an increase in heat resources had a negative impact. In the background of future climate change, the significant warming trend in the region will limit the increase in climate production potential, and the interannual fluctuations in precipitation will seriously affect the stability of climate production potential. In the future, the structure of rice cultivation should be moderately adjusted, climate resources should be explored reasonably, and water resource utilization should be optimized to improve the utilization rate of climate resources in the hilly areas of central Sichuan. Related Articles | Metrics | Comments（0）

Select

Characteristics of Drought Changes and Risk Analysis in Zhaotong Apple ZENG Ting-yu, LU Xing-kai, GAO Ying-ming, YAO Mu-chen, HE Juan, ZHOU Yong-sheng, ZHANG Xiu-ying, SUN Dong-han Chinese Journal of Agrometeorology    2025, 46 (5): 628-639.   DOI: 10.3969/j.issn.1000-6362.2025.05.004 Abstract （381）      PDF（pc） （5302KB）（757）       Knowledge map    Save This study is based on the phenological data of Zhaotong apple from 2010 to 2023, the meteorological data and drought disaster data of Zhaotong from 1960 to 2023, and divided the phenologicals into six growth stages, including dormancy, bud, anthesis, fruitlet, expansion and harvest stage, and used the crop water deficit abnormal index (CWDIa) to analyze the drought frequency and duration of each growth stage, used the cumulative drought intensity (CDI) to identify the drought risk intensity, used the Morlet complex continuous wavelet transform(CCWT) to explore the time−frequency evolution characteristics of cumulative drought intensity, so as to analyze the occurrence law of drought risk in Zhaotong apple. The results showed that drought in the apple growing region of Zhaotong was characterized by a pattern of frequency, seasonality, suddenness, severity and sub−seasonality. The drought in each development stage followed as: there was a large difference in the frequency of occurrence, fruitlet (55y)>harvest and dormancy (49y)> anthesis (20y)> bud(19y)> expansion(8y), and the extreme drought were most likely to occur at the end of the fruiting period and during late harvests. The duration of drought was between 1−4 ten−days, and there were significant differences in CDI, with the mean of fruitlet(335.0%)>dormancy (172.7%)>bud(137.7%)>harvest(137.1%)>anthesis(68.1%)>expansion(8.0%). The thresholds for the classification and identification of drought risk intensity were different, sensitivity to drought stress of stage was expansion>anthesis>harvest> fruitlet>bud>dormancy. The risk of severe drought disasters was seasonal and the fruitlet>bud>harvest>expansion>anthesis>dormancy. Drought risk had shown multi-scale periodic, phased and abrupt changes, with a general trend of increasing drought risk since 1991.  Related Articles | Metrics | Comments（0）

Select

Changes of Main Crops Growth Periods in China and Their Influencing Factors in the Context of Climate Warming GAO Jing, YANG Bing-yu, LIAO Jie, LIU Yuan-yuan Chinese Journal of Agrometeorology    2025, 46 (9): 1261-1276.   DOI: 10.3969/j.issn.1000-6362.2025.09.004 Abstract （347）      PDF（pc） （11434KB）（197）       Knowledge map    Save Based on phenological data of wheat, rice, and maize from 1981 to 2022 collected at 653 agrometeorological stations across China, as well as concurrent meteorological data, trend analysis and correlation analysis methods were used to analyze the characteristics of changes in the growth periods of these three crops. The study also explored the main meteorological factors influencing these changes, aiming to provide a basis for adapting agricultural production to climate change. The results indicated that the mean temperature and growing degree days (except for late double−cropping rice) during the whole growth periods of all three crops showed significant increasing trends (P<0.05). Precipitation during the whole growth period of winter wheat significantly decreased, while it significantly increased for spring wheat and maize. The sunshine duration during the whole growth period of maize and late double−cropping rice significantly decreased. From 1981 to 2022, the whole growth periods of spring wheat, winter wheat and late double−cropping rice mainly shortened, with average decreases of 1.6d per decade, 2.5d per decade, and 2.2d per decade, respectively. In contrast, the whole growth periods of single−season rice, early double−cropping rice, and maize mainly extended, with average increases of 1.9d per decade, 0.01d per decade, and 0.6d per decade, respectively. Compared with the sowing dates in the 1980s, the sowing dates of spring wheat, winter wheat, maize, and late double−cropping rice in the 2010s were delayed by an average of 1.0d, 4.0d, 4.0d and 9.0d, respectively. In contrast, the sowing dates of single−season rice and early double−cropping rice advanced by an average of 2.0d. For spring wheat, winter wheat, and maize, more than 82%, 76% and 85% of the observation stations, respectively, showed a significant positive correlation between the length of each growth stage and sunshine duration. The mean temperature and sunshine duration were key factors influencing the phenological changes of spring wheat, with mean temperature having a particularly significant impact on the duration of the sowing−to−emergence stage of spring wheat. The active accumulated temperature ≥0℃ was the primary factor responsible for the changes in the whole growth period and the vegetative growth period of winter wheat. The mean temperature had the greatest impact on the duration of the sowing−to−tillering stage, while the overwintering period was mainly influenced by sunshine duration.The effective accumulated temperature ≥10℃ was the main factor influencing the changes in the whole growth period of rice (including single−season rice, early double−cropping rice, and late double−cropping rice). The duration from the three−leaf stage to transplanting had the highest correlation coefficient with sunshine duration, while during this stage, the correlation coefficient between precipitation and both early double−cropping rice and late double−cropping rice was the highest.The mean temperature was the primary factor determining the changes in the whole growth period of maize, and the effective accumulated temperature ≥10℃ had the highest correlation coefficient with the duration from the seven−leaf stage to the silking stage. Related Articles | Metrics | Comments（0）

Select

Prediction of Spatial and Temporal Variability of Precipitation in Henan Province Based on CMIP6 Multi-model SSP Scenarios XING Hai-jia, YANG Lian-an, YUAN Xiao-tian, SHANG Xiao-qing, ZHOU Si-cong, XUE Jing Chinese Journal of Agrometeorology    2025, 46 (4): 446-458.   DOI: 10.3969/j.issn.1000-6362.2025.04.002 Abstract （344）      PDF（pc） （13204KB）（201）       Knowledge map    Save Based on daily data from 117 meteorological stations in Henan province (1960-2014) and data from 10 climate models in the Sixth Coupled Model Intercomparison Project (CMIP6), this study evaluated the simulation ability of multi-model ensemble (MME) models for annual precipitation in Henan during the historical period (1960-2014) and analyzed the spatiotemporal changes in precipitation under different SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) for the period 2015-2100, in order to provide a basis for agricultural production in Henan province. The results indicated: (1) from 1960 to 2014, the spatial correlation coefficient (R) between the MME models and observations exceeded 0.95, with a standard deviation (RSD) of 1.05mm and root mean square error (RMSE) of 0.31 mm, indicating that the MME models performed better than individual climate model. (2) Compared to the historical reference period (1960-2014), annual precipitation in Henan under all four scenarios for 2015-2100 showed an increasing trend, with July cumulative precipitation ranging between 150-230mm, higher than in other months. (3) In terms of cyclical changes, all four scenarios exhibited multi-timescale features, with different precipitation cycles at various time scales. The primary periods for scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 were 15y, 25y, 49y, and 26y, respectively. (4) Under all four scenarios, compared to the baseline historical period (1960-2014), the annual precipitation in Henan showed an increasing trend in the near term (2021-2040), mid-term (2041-2060), and late term (2080-2100). Moreover, the higher the emission scenario, the greater the increasing trend. All four scenarios exhibited a spatial distribution feature that increased from northwest to southeast. The findings provide theoretical reference for forecasting future regional precipitation and scientific basis for agricultural production in Henan province. Related Articles | Metrics | Comments（0）

Select

Remote Sensing Monitoring of Wheat Grain Protein Content: A Review LI Meng-xia, LI Jun-ling, LI Shu-yan Chinese Journal of Agrometeorology    2025, 46 (4): 580-591.   DOI: 10.3969/j.issn.1000-6362.2025.04.013 Abstract （335）      PDF（pc） （752KB）（1101）       Knowledge map    Save As an important factor for evaluating wheat quality, grain protein content (GPC) is crucial for guiding agricultural production and enhancing the market value of wheat. To advance the development of GPC remote sensing monitoring techniques, this paper systematically summarized the latest research, with a particular focus on analyzing the strengths, weaknesses, and challenges of diverse GPC remote sensing monitoring models. Results showed that remote sensing data from various platforms−including ground, unmanned aerial vehicles (UAVs), and satellites−each exhibit distinct advantages in monitoring GPC in wheat. However, as data scalability increased, the accuracy of GPC monitoring tends to decrease slightly. In terms of model construction, the development of wheat GPC monitoring models from empirical models to semi−empirical models or coupled remote sensing and crop growth models had increased agronomic parameters and ecological factors, which effectively improved both accuracy and spatio-temporal scalability. It was shown that the semi-empirical models were the preferred option for monitoring GPC. After adding meteorological factors into the Beijing wheat GPC model that integrated spectral information and agronomic parameters, the model's R² increased by 0.242. Currently, there were still many challenges in terms of model accuracy and regionally applications such as the reliability of GPC data, the complexity of the vertical distribution of nitrogen in wheat, and the limitations of regional expansion of the models. To address these issues, this paper proposed to evaluate ground-based GPC, fusing effective data, mine spectral information and explore multi-scale transformation methods in the future. In addition, a multi-scale GPC monitoring model based on collaborative observations from ground stations, UAVs and satellites can be constructed to achieve efficient, accurate and comprehensive monitoring of wheat quality. Related Articles | Metrics | Comments（0）

Select

Progress on Monitoring, Forecasting and Service of Airborne Allergenic Pollen LIU Su-qin, LI Jian-qiang, CHENG Wen-xiu, ZHAO Lin-na, XU Xi, YE Cai-hua Chinese Journal of Agrometeorology    2025, 46 (8): 1095-1110.   DOI: 10.3969/j.issn.1000-6362.2025.08.003 Abstract （332）      PDF（pc） （1951KB）（1028）       Knowledge map    Save The prevention and management of allergy risks caused by airborne allergenic pollen has become a critical concern in safeguarding public health during urban greening. The prevention and management framework covers three main strands from bottom to top: pollen monitoring, pollen forecasting and pollen service. To gain a deeper understanding of this framework, a comprehensive literature review was conducted in this paper. The principles, equipment and station layout of pollen monitoring were analyzed. The development of pollen forecasting methods, spanning from statistical regression to machine learning and deep learning was summarized. Current manifestations and applications of user−friendly pollen service products were summarized. In addition, the challenges faced by each link were discussed, and future research directions were prospected. The results indicated that domestic pollen monitoring equipment primarily relied on gravity settling, which was cost−effective and easy to operate but heavily depended on manual daily monitoring. Pollen forecasting was still mainly based on statistical regression, and future advancements should focus on integrating cutting−edge technologies, such as Artificial Intelligence Large Models, to develop multi−modal factor−driven forecasting methods and support more refined forecasting. Pollen service was launched via WeChat mini−programs, mobile applications, platforms and other products that provide diverse information, including total and classified pollen concentration and medical guidelines. Future developments should prioritize addressing the specific needs of different user groups through personalized and customized solutions. Related Articles | Metrics | Comments（0）

Select

Temporal and Spatial Evolution Analysis of Net Carbon Sink from Cultivated Land Utilization at the County Level in Henan Province MA Wen-bo, ZENG Li-yuan Chinese Journal of Agrometeorology    2025, 46 (5): 593-608.   DOI: 10.3969/j.issn.1000-6362.2025.05.001 Abstract （327）      PDF（pc） （12345KB）（162）       Knowledge map    Save Drawing on statistical data spanning from 2006 to 2020, four key aspects were analyzed in this study: inputs of agricultural production materials, soil conditions, carbon emissions from wheat and rice cultivation, and carbon sequestration by crops. The carbon emission coefficient method was used to calculate the net carbon sink of cultivated land use across 104 counties in Henan province, and its spatiotemporal distribution characteristics were examined. The findings offer scientific insights for the low-carbon transformation of cultivated land use and the pursuit of carbon peaking and neutrality goals in Henan province. The results indicate that: (1) carbon emissions from cultivated land use in Henan province initially rose and then declined, while carbon absorption increased steadily, leading to a fluctuating increase in net carbon sinks. Notably, chemical fertilizers emerged as the primary carbon source. Compared to 2006, by 2020, most counties in Henan province experienced growth in carbon emissions, carbon sinks, and net carbon sinks, with respective county proportions of 65.4%, 78.9%, and 77.9%. In eastern Henan led in increments of carbon emissions, carbon sinks, and net carbon sinks, while northern Henan showed a faster growth rate in carbon emissions. In southern Henan, on the other hand, exhibited significant growth rates in carbon sinks and net carbon sinks. (2) In terms of spatial distribution, the net carbon sink of cultivated land use in Henan province displayed a pattern of “higher in the east and lower in the west.” Spatial agglomeration was evident, with notable regional differences. However, low−value areas of net carbon sinks were gradually transitioning towards high−value areas, indicating a trend of narrowing regional disparities. Most counties fell into the category of moderate net carbon sink areas. Counties exhibiting homogeneity in net carbon sink values accounted for over 95% of the aggregated counties. The center of gravity for net carbon sinks was situated in Yanling county, with a tendency to shift eastward. (3) Natural conditions, including climate, soil, and terrain, as well as national policies, influenced the crop planting structure, the level of agricultural mechanization, and the input of agricultural materials, thereby impacting carbon emissions and carbon absorption from cultivated land use. In the future, crop carbon sinks should be integrated into the decision−making framework for crop planting structure adjustment in Henan province. Efforts should also continue to reduce and enhance the efficiency of chemical fertilizers. Additionally, increasing investment in agricultural machinery technology innovation in Henan province and fostering inter−regional agricultural technology exchange and cooperation will fully harness its potential for emission reduction and carbon sequestration enhancement, ultimately promoting green agricultural development. Related Articles | Metrics | Comments（0）

Select

Temporal and Spatial Variations of Drought in the Yellow River Basin from 1980 to 2020 GU Yang-yang, ZHAO Wen-ji, WU Shu-qi Chinese Journal of Agrometeorology    2025, 46 (8): 1192-1205.   DOI: 10.3969/j.issn.1000-6362.2025.08.011 Abstract （324）      PDF（pc） （8259KB）（162）       Knowledge map    Save The Yellow river basin, as an ecological barrier zone in northern China, experiences frequent drought events with significant spatiotemporal differentiation. However, its large−scale evolution pattern and atmospheric oceanic driving mechanisms are not yet clear, which hinders the optimal allocation of regional water resources and drought risk management. This study was based on monthly precipitation and temperature data from 340 meteorological stations in and around the Yellow river basin from 1980 to 2020. The Thornthwaite model was used to calculate the Standardized Precipitation Evapotranspiration Index (SPEI), and linear trend estimation, Mann−Kendall trend/mutation test, continuous wavelet transform and wavelet coherence analysis were combined to reveal the spatiotemporal evolution of drought in the Yellow river basin and its multi−scale coupling mechanism with the Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), El Niño−Southern Oscillation (ENSO) and East Asian Summer Monsoon (EASM), in order to provide scientific basis for regional basin drought warning and adaptive regulation. The results showed that from 1980 to 2020, the spring SPEI−3 in the Yellow river basin significantly decreased at a rate of 0.021·y−1 (P<0.01), and mild or above drought occurred 30% of the time in spring. In autumn of 1997, the detection of SPEI−3 mutation identified a significant jump point, with a 20% increase of droughts within five years thereafter. There was no significant sustained trend of drought in the Yellow river basin during summer and winter, which manifested as short−term random fluctuations. From 1980 to 2020, the annual scale SPEI−12 in the Yellow river basin showed a slight downward trend of 0.005·y−1 (P=0.06). From 1997 to 2002, there were a total of eight occurrences of mild to moderate drought in the Yellow river basin, accounting for 65% of the total annual drought events. In 1986, it suddenly changed to a sustained drought. Spatially, from 1980 to 2020, the high−frequency drought zone in the Yellow river basin migrated from the middle and lower reaches of the northeast to the southwest, forming a radiation belt of "frequent occurrence in the northeast and weakening in the southwest" covering 35.23% of the middle and lower reaches. The Arctic Oscillation (AO) caused a 2−4 month lag in drought in the Yellow river basin through a 3−60 month resonance. The bimodal effect of Pacific Decadal Oscillation (PDO) caused drought to advance or lag by 3−8 months. ENSO multi−cycle alternation caused drought to lag by 3−9 months or advance by 12−18 months. The coupling of short period negative phase and medium to long period positive phase in the East Asian Summer Monsoon (EASM) caused drought to lag by 1−15 months. In summary, the periodic fluctuations of multi−scale weather and climate events were the key driving mechanism for the meteorological drought evolution in the Yellow river basin from 1980 to 2020 through the cross scale synergistic effects of AO suppressing soil moisture, PDO weakening water vapor transport and EASM driving changes. This study can provide reference for regional drought warning and adaptive regulation. Related Articles | Metrics | Comments（0）

Select

Research Progress of Crop Water and Fertilizer Management Decision-making Models Based on Bibliometrics CAI Meng-ting, SU Zhen-juan, ZHANG Peng, LIU Xue-zhi , XU Li-gang, YANG Hao, WANG Jiao, LIU Wei-lun Chinese Journal of Agrometeorology    2025, 46 (5): 704-714.   DOI: 10.3969/j.issn.1000-6362.2025.05.011 Abstract （322）      PDF（pc） （4342KB）（697）       Knowledge map    Save Based on the Web of Science (WoS) core database and the China National Knowledge Infrastructure (CNKI) database, this paper retrieved the literature related to crop water and fertilizer management decision-making models, and analyzed the changes in the number of publications, publishing country and keywords of the papers in this field from 2003 to 2023, as well as the research progress of crop water and fertilizer management decision- making models at home and abroad, with the help of CiteSpace and VOSviewer visualization software, and understood the research status and trend of crop water and fertilizer management decision-making models. The results indicated that the overall publication volume of crop water and fertilizer management decision-making model research had shown an upward trend from 2003 to 2023. The main research focus on water and fertilizer management, model optimization, etc., and the United States and China dominated the research in this field. The main keywords in publications from 2003 to 2023 concentrated on nitrogen, water, management as well as water−fertilizer coupling, yield, water and fertilizer integration, respectively. Currently, the widely used crop water and fertilizer management decision−making models included APSIM, DSSAT, RZWQM, and AquaCrop. With the advantages of modularity and soil−centered design, APSIM model could accurately assess the dynamic changes in soil moisture and nutrients in agricultural land by setting up different scenarios of crops, soil types and climatic conditions, etc., thus providing important support for the development of more rational agricultural water and fertilizer management strategies. Integrating the current research progress in crop water and fertilizer management decision making, future research should pay more attention to agro-ecological effects and combine with new remote sensing technologies to establish, optimize or couple crop models to provide technical support for the assessment of agricultural water and fertilizer dynamics and the efficient use of resources. Related Articles | Metrics | Comments（0）

Select

Research on Weather Index Insurance Pricing of Apple in Qingyang, Gansu Province Based on XGBoost Method LI Jin-rong, XIAO Hong-min Chinese Journal of Agrometeorology    2025, 46 (5): 715-724.   DOI: 10.3969/j.issn.1000-6362.2025.05.012 Abstract （322）      PDF（pc） （1017KB）（321）       Knowledge map    Save Weather index insurance based on machine learning algorithms represents a significant innovation in agricultural insurance research. Since crop yields are primarily influenced by weather-related disasters, developing a robust data analysis model that accurately captures the relationship between yield losses and adverse weather conditions is crucial for pricing crop weather index insurance. This paper focuses on Qingyang apples in Gansu province, utilizing daily precipitation and temperature data during the growing season (April-October) and apple yield data from five counties (or districts) in Qingyang city spanning 1996–2020. Indices of low−temperature freezing, drought and continuous cloudy rainfall were constructed, and a regression model linking these indices to the meteorological yield reduction rate of apples was established using the XGBoost algorithm. The kernel density estimation method was applied to determine the pure rate of weather index insurance for apples in Qingyang. The findings of the study were as follows: (1) meteorological disasters caused significant fluctuations in the apple cimate yield reduction rates across counties (or districts) in Qingyang city. A nonlinear relationship was observed between the cimate yield reduction rate and seven types of apple disaster weather indices. (2) Regression models for the climate yield reduction rate-weather indices in Ning county, Qingcheng county, Zhengning county, Huan county, and Xifeng district (1996–2020) were constructed using the XGBoost algorithm. These models demonstrated superior fitting accuracy compared to multivariate stepwise regression models, with coefficients of determination (R²) improving by 0.157, 0.125, 0.190, 0.115 and 0.117, uhile root mean square errors (RMSE) decreasing by 0.045, 0.026, 0.335, 0.126, and 0.039 percentage points, respectively. (3) The climate yield reduction rate payout triggers for apple weather index insurance were 11.88%, 3.37%, 4.33%, 9.21%, and 17.70% in Ning county, Qingcheng county, Zhengning county, Huan county, and Xifeng district, respectively. The corresponding pure insurance rates were 4.00%, 3.64%, 4.91%, 1.94% and 4.98%.   Related Articles | Metrics | Comments（0）

Select

Study on the Causes of Chilling Dew Wind in Hubei by Atmospheric Circulation and Its Beginning Date Simulation Model XIE Jia-xu, LIU Zhi-xiong, DU Liang-min, LIU Kai-wen, DENG Ai-juan, YUAN Zheng-xuan Chinese Journal of Agrometeorology    2025, 46 (4): 558-568.   DOI: 10.3969/j.issn.1000-6362.2025.04.011 Abstract （320）      PDF（pc） （3756KB）（543）       Knowledge map    Save Based on the temperature and precipitation data from the late rice region of Hubei, spanning the period from 1970 to 2022, this paper delves into the characteristics of chilling dew wind in Hubei, encompassing its climate characteristics, atmospheric circulation pattern and sea surface temperature background. A simulation model for the beginning date of chilling dew wind was constructed using the Hyperparameters Tuning of Random Forest method and previous circulation indices, in order to provide a reference for preventing and mitigating the impact of the chilling dew wind. The results showed that: (1) over the past 53 years, the chilling dew wind had shown a trend of delayed beginning date and reduced total number of days, with a delay rate of nearly 0.4d·10y−1 and a reduction rate of nearly 44d·10y−1. The decade with highest cumulative number of stations was 1970−1980, the lowest in 2001−2010. Since 1990s, the proportion of severe station occurrence had been increasing, indicating a shift towards fewer but more intense occurrences of the chilling dew wind. (2) The typical circulation pattern associated with chilling dew wind in Hubei was characterized by a "− + −" anomalous distribution of geopotential height from west to east over the mid-to-high latitudes of Eurasia, accompanied by the northward transport of warm and humid air from the southern regions. (3) The beginning date of chilling dew wind was significantly correlated with the large−scale meridional circulation anomaly in Eurasia and the anomalous sea surface temperature (SST) in the western Pacific warm pool and the north of the South Atlantic. The beginning date of chilling dew wind was earlier (later) when the geopothetic height near the Ural mountains increases (decreases). When SST over western Pacific warm pool was abnormally cold (warm), and the north of the South Atlantic SST showed cold to warm (warm to cold) distribution from north to south, the beginning date of chilling dew wind tend to be earlier (later). (4)The simulation error using hyperparameters tuning of random forest method was minimal. The historical fitting rate from 1970 to 2007 was 91%, and average absolute error of sample test from 2008 to 2020 was 2.9d, indicating that the model had a good ability to simulate the beginning date of chilling dew wind in Hubei.  Related Articles | Metrics | Comments（0）

Select

Prediction of Climatical Suitable Areas for Rape in China Based on Optimized MaxEnt Model ZHAO Chen-yu, ZHANG Fang-min, YIN Si-yi, CAO Wen Chinese Journal of Agrometeorology    2025, 46 (5): 660-668.   DOI: 10.3969/j.issn.1000-6362.2025.05.007 Abstract （313）      PDF（pc） （7044KB）（159）       Knowledge map    Save This study optimized the parameter settings of the MaxEnt model by using the ENMeval package in R, selected dominant climatic factors based on the data of 255 rape sample points of China and 19 climatic factors, and further predicted the distribution and change characteristics of climatical suitable areas for rape in China under the climate change scenarios for historical period (1970−2000) and future period (2041−2060) by optimized MaxEnt model. Results indicated that: (1) the optimal parameter setting of MaxEnt for rape in China was a linear combination of Linear, Quadratic, Hinge, Product and Threshold functions with a regularization multiplier of 4.0. This setting achieved the highest simulation accuracy. (2) The dominant climatic factors affecting the distribution of rape climatical suitable areas were minimum temperature of the coldest month, mean temperature of the wettest quarter, and precipitation of the driest month. (3) During the historical period, the low climatical suitable areas were mainly located in the western regions, central Inner Mongolia and Liaoning. The medium and high climatically suitable areas were primarily distributed in the central and eastern regions of China. Compared to the historical period, the future changes in climatical suitable areas were mainly reflected in the transition of unsuitable areas to low suitable areas, low suitable areas to medium suitable areas, and medium suitable areas to high suitable areas. The climatical unsuitable areas will decrease, the climatically suitable areas will increase, and the low, medium, and high climatical suitable areas will expand northward. Related Articles | Metrics | Comments（0）

Select

Model of Field Population Abundance of Rice Leaffolder in Guizhou Province Based on Meteorological Conditions SUN Si-si, YANG Shi-jun, WANG Ke-xin, TANG Pi-ru, ZENG Xiao-shan, YU Fei Chinese Journal of Agrometeorology    2025, 46 (4): 512-523.   DOI: 10.3969/j.issn.1000-6362.2025.04.007 Abstract （312）      PDF（pc） （1305KB）（636）       Knowledge map    Save Taking Yuqing county of Guizhou province as the study area, data from the rice leaffolder (RLF) field surveys and meteorological stations during the main local RLF occurrence period (June-August) from 2011 to 2020 and methods such as correlation analysis, mathematical statistics, and machine learning were used to analyze the effects of meteorological conditions on the population abundance of larvae and adults of RLF in Guizhou province, screen for key meteorological influence factors, and explored the predictive effects of different modeling methods. The results showed that: (1) meteorological factors that favored the increase in RLF larvae were mean minimum temperature, precipitation, mean relative humidity, and minimum relative humidity. Mean temperature, minimum temperature, mean precipitation, mean relative humidity, mean minimum relative humidity, sunshine hours, and mean 0cm ground temperature were found to favor an increase in RLF adults. (2) The lagged effect of meteorological conditions on RLF’s field populations in Guizhou province was greater. The RLF field population abundance was mainly influenced by mean temperature, mean minimum temperature, precipitation, minimum relative humidity, mean wind speed, and mean 0cm ground temperature, which were per-five-day daily averaged between June to August each year. The longest lag effect could be up to about 30d, with significant effect period of 3, 4, and 5 pentads in advance. (3) The results of the model simulation varied considerably between the different modeling schemes. Non-linear models (R2=1.00, MAE=2.62 individual, RMSE=3.89 individual) were more effective than linear models (R2=0.46, MAE=164.98 individual, RMSE=240.66 individual), and the simulation effect for the adult population (R2=0.68, MAE=81.29 individual, RMSE=117.98 individual) was better than that for the larva population (R2=0.67, MAE=118.78 individual, RMSE=173.92 individual). Related Articles | Metrics | Comments（0）

Select

Effect of LED Light Irradiation on the Growth, Development, and Spectral Characteristics of Pleurotus citrinopileatus Singer LIU Yi-han, CHEN Xiao-li, ZHENG Wen-gang, ZHANG Xin, GAO Yi-nan, GUO Wen-zhong Chinese Journal of Agrometeorology    2025, 46 (4): 524-532.   DOI: 10.3969/j.issn.1000-6362.2025.04.008 Abstract （307）      PDF（pc） （1510KB）（269）       Knowledge map    Save Edible fungi has certain photo−sensitivity during the mushroom emergence stage, but the optimal light environment parameters for the formation of the morphology and color of Pleurotus citrinopileatus Singer are not clear. Pleurotus citrinopileatus Singer were planted in in an environmentally controllable growth chambers with different light qualities that were respectively pure white light (CK), pure green light (G), pure red light (R), pure blue light (B), and far red light (Fr). The optimal light formula suitable for the growth and development of Pleurotus citrinopileatus Singer was investigated by analyzing the physical and spectral characteristics of mushroom exposed to different light treatments. The results showed that the number of mushroom buds in Pleurotus citrinopileatus Singer exposed to R and Fr treatments increased by 0.87% and 1.73% respectively, compared to the control. However, R and Fr treatments caused deformation of Pleurotus citrinopileatus Singer fruiting bodies, showed as soft stipe, thin pileus, and lighter colors in the later stage of growth. B treatment decreased the number of mushroom buds and stipe length of Pleurotus citrinopileatus Singer, but significantly promoted the increase in stipe diameter, pileus diameter, and fruiting body weight of Pleurotus citrinopileatus Singer, with a increase of 35.52%, 18.30%, and 23.66% respectively (P<0.05), compared to the control. The spectral parameters color saturation (C value) and hue angle (Hue value) of Pleurotus citrinopileatus Singer exposed to B treatment increased by 2.72% and 1.64% respectively, compared to the control, while the color index (CCI value) and color ratio (a*/b* value) decreased by 44.62% and 80.00% respectively. Meanwhile, smaller chromatism (∆E value) and deepened simulated color were detected in Pleurotus citrinopileatus Singer treated with B in relative to the control. In addition, the reflectance in the 400-700 nm wavelength range of the Pleurotus citrinopileatus Singer pileus exposed to B treatment was lower than that of the control, indicating that the pileus of Pleurotus citrinopileatus Singer under B treatment absorbed more blue light. Therefore, based on the comprehensive characteristics and spectral characteristics of Pleurotus citrinopileatus Singer, blue light was more suitable for industrial cultivation of Pleurotus citrinopileatus Singer, which provided a reference for the regulation of light environment in the industrial production of Pleurotus citrinopileatus Singer in future. Related Articles | Metrics | Comments（0）