Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders;however,the results are inconsistent in different studies and regions,as are the interaction effects between environmental factors.We hypo-thesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.AIM To investigate the effects of meteorological factors and air pollution on depressive disorders,including their lagged effects and interactions.METHODS The samples were obtained from a class 3 hospital in Harbin,China.Daily hos-pital admission data for depressive disorders from January 1,2015 to December 31,2022 were obtained.Meteorological and air pollution data were also collected during the same period.Generalized additive models with quasi-Poisson regre-ssion were used for time-series modeling to measure the non-linear and delayed effects of environmental factors.We further incorporated each pair of environ-mental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.RESULTS Data for 2922 d were included in the study,with no missing values.The total number of depressive admissions was 83905.Medium to high correlations existed between environmental factors.Air temperature(AT)and wind speed(WS)significantly affected the number of admissions for depression.An extremely low temperature(-29.0℃)at lag 0 caused a 53%[relative risk(RR)=1.53,95%confidence interval(CI):1.23-1.89]increase in daily hospital admissions relative to the median temperature.Extremely low WSs(0.4 m/s)at lag 7 increased the number of admissions by 58%(RR=1.58,95%CI:1.07-2.31).In contrast,atmospheric pressure and relative humidity had smaller effects.Among the six air pollutants considered in the time-series model,nitrogen dioxide(NO_(2))was the only pollutant that showed significant effects over non-cumulative,cumulative,immediate,and lagged conditions.The cumulative effect of NO_(2) at lag 7 was 0.47%(RR=1.0047,95%CI:1.0024-1.0071).Interaction effects were found between AT and the five air pollutants,atmospheric temperature and the four air pollutants,WS and sulfur dioxide.CONCLUSION Meteorological factors and the air pollutant NO_(2) affect daily hospital admissions for depressive disorders,and interactions exist between meteorological factors and ambient air pollution.

Comparisons of different statistical models for analyzing the effects of meteorological factors on COVID-19

Objective:This general non-systematic review aimed to gather information on reported statistical models examing the effects of meteorological factors on coronavirus disease 2019(COVID-19)and compare these models.Methods:PubMed,Web of Science,and Google Scholar were searched for studies on"meteorological factors and COVID-19"published between January 1,2020,and October 1,2022.Results:The most commonly used approaches for analyzing the association between meteorological factors and COVID-19 were the linear regression model(LRM),generalized linear model(GLM),generalized additive model(GAM),and distributed lag non-linear model(DLNM).In addition to these classical models commonly applied in environmental epidemiology,machine learning techniques are increasingly being used to select risk factors for the outcome of interest and establishing robust prediction models.Conclusion:Selecting an appropriate model is essential before conducting research.To ensure the reliability of analysis results,it is important to consider including non-meteorological factors(e.g.,government policies on physical distancing,vaccination,and hygiene practices)along with meteorological factors in the model.

Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in Yunnan Border Regions

Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever’s temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever’s spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors’influence exhibiting notable spatial and temporal variation.

The Impacts of Mosquito Density and Meteorological Factors on Dengue Fever Epidemics in Guangzhou, China, 2006-2014: a Time-series Analysis

Objective To explore the associations between the monthly number of dengue fever（DF） cases and possible risk factors in Guangzhou, a subtropical city of China. Methods The monthly number of DF cases, Breteau Index （BI）, and meteorological measures during 2006-2014 recorded in Guangzhou, China, were assessed. A negative binomial regression model was used to evaluate the relationships between BI, meteorological factors, and the monthly number of DF cases. Results A total of 39,697 DF cases were detected in Guangzhou during the study period. DF incidence presented an obvious seasonal pattern, with most cases occurring from June to November. The current month＇s BI, average temperature （Tare）, previous month＇s minimum temperature （Train）, and Tare were positively associated with DF incidence. A threshold of 18.25℃ was found in the relationship between the current month＇s Tmin and DF incidence. Conclusion Mosquito density, Tove, and Tmin play a critical role in DF transmission in Guangzhou. These findings could be useful in the development of a DF early warning system and assist in effective control and prevention strategies in the DF epidemic.

Multivariate analysis between meteorological factor and fruit quality of Fuji apple at different locations in China

China has the largest apple planting area and total yield in the world, and the Fuji apple is the major cultivar, accounting for more than 70％ of apple planting acreage in China. Apple qualities are affected by meteorological conditions, soil types, nutrient content of soil, and management practices. Meteorological factors, such as light, temperature and moisture are key environmental conditions affecting apple quality that are difficult to regulate and control. This study was performed to determine the effect of meteorological factors on the qualities of Fuji apple and to provide evidence for a reasonable regional layout and planting of Fuji apple in China. Fruit samples of Fuji apple and meteorological data were investigated from 153 commercial Fuji apple orchards located in 51 counties of 11 regions in China from 2010 to 2011. Partial least-squares regression and linear programming were used to analyze the effect model and impact weight of meteorological factors on fruit quality, to determine the major meteorological factors influencing fruit quality attributes, and to establish a regression equation to optimize meteorological factors for high-quality Fuji apples. Results showed relationships between fruit quality attributes and meteorological factors among the various apple producing counties in China. The mean, minimum, and maximum temperatures from April to October had the highest positive effects on fruit qualities in model effect loadings and weights, followed by the mean annual temperature and the sunshine percentage, the temperature difference between day and night, and the total precipitation for the same period. In contrast, annual total precipitation and relative humidity from April to October had negative effects on fruit quality. The meteorological factors exhibited distinct effects on the different fruit quality attributes. Soluble solid content was affected from the high to the low row preface by annual total precipitation, the minimum temperature from April to October, the mean temperature from April to October, the temperature difference between day and night, and the mean annual temperature. The regression equation showed that the optimum meteorological factors on fruit quality were the mean annual temperature of 5.5-18°C and the annual total precipitation of 602-1121 mm for the whole year, and the mean temperature of 13.3-19.6°C, the minimum temperature of 7.8-18.5°C, the maximum temperature of 19.5°C, the temperature difference of 13.7°C between day and night, the total precipitation of 227 mm, the relative humidity of 57.5-84.0％, and the sunshine percentage of 36.5-70.0％ during the growing period （from April to October）.

Temporal variations of reference evapotranspiration and its sensitivity to meteorological factors in Heihe River Basin, China

On the basis of daily meteorological data from 15 meteorological stations in the Heihe River Basin （HRB） during the period from 1959 to 2012, long-term trends of reference evapotranspiration （ET0） and key meteorological factors that affect ET0 were analyzed using the Mann- Kendall test. The evaporation paradox was also investigated at 15 meteorological stations. In order to explore the contribution of key meteo- rological factors to the temporal variation of ET0, a sensitivity coefficient method was employed in this study. The results show that： （1） mean annual air temperature significantly increased at all 15 meteorological stations, while the mean annual ET0 decreased at most of sites; （2） the evaporation paradox did exist in the HRB, while the evaporation paradox was not continuous in space and time; and （3） relative humidity was the most sensitive meteorological factor with regard to the temporal variation of ET0 in the HRB, followed by wind speed, air temperature, and solar radiation. Air temperature and solar radiation contributed most to the temporal variation of ETo in the upper reaches; solar radiation and wind speed were the determining factors for the temporal variation of ET0 in the middle-lower reaches.

Relationships between temperature-light meteorological factors and seedcotton biomass per boll at different boll positions

Cotton growth and development are determined and influenced by cultivars, meteorological conditions, and management practices. The objective of this study was to quantify the optimum of temperature-light meteorological factors for seedcotton biomass per boll with respect to boll positions. Field experiments were conducted using two cultivars of Kemian 1 and Sumian 15 with three planting dates of 25 April （mean daily temperature （MDT） was 28.0 and 25.4°C in 2010 and 2011, respectively）, 25 May （MDT was 22.5 and 21.2°C in 2010 and 2011, respectively）, and 10 Jun （MDT was 18.7 and 17.9°C in 2010 and 2011, respectively）, and under three shading levels （crop relative light rates （CRLR） were 100, 80, and 60％） during 2010 and 2011 cotton boll development period （from anthesis to boll open stages）. The main meteorological factors （temperature and light） affected seedcotton biomass per boll differently among different boll positions and cultivars. Mean daily radiation （MDR） affected seedcotton biomass per boll at all boll positions, except fruiting branch 2 （FB2） fruting node 1 （FN1）. However, its influence was less than temperature factors, especially growing degree-days （GDD）. Optimum mean daily maximum temperature （MDTmax） for seedcotton biomass per boll at FB11FN3 was 29.9-32.4°C, and the optimum MDR at aforementioned position was 15.8-17.5 MJ m-2. Definitely, these results can contribute to future cultural practices such as rational cultivars choice and distribution, simplifying field managements and mechanization to acquire more efficient and economical cotton management.

Effects of meteorological factors on different grades of winter wheat growth in the Huang-Huai-Hai Plain, China

The sown area of winter wheat in the Huang-Huai-Hai（HHH） Plain accounts for over 65% of the total sown area of winter wheat in China. Thus, it is important to monitor the winter wheat growth condition and reveal the main factors that influence its dynamics. This study assessed the winter wheat growth condition based on remote sensing data, and investigated the correlations between different grades of winter wheat growth and major meteorological factors corresponding. First, winter wheat growth condition from sowing until maturity stage during 2011–2012 were assessed based on moderate-resolution imaging spectroradiometer（MODIS） normalized difference vegetation index（NDVI） time-series dataset. Next, correlation analysis and geographical information system（GIS） spatial analysis methods were used to analyze the lag correlations between different grades of winter wheat growth in each phenophase and the meteorological factors that corresponded to the phenophases. The results showed that the winter wheat growth conditions varied over time and space in the study area. Irrespective of the grades of winter wheat growth, the correlation coefficients between the winter wheat growth condition and the cumulative precipitation were higher than zero lag（synchronous precipitation） and one lag（pre-phenophase precipitation） based on the average values of seven phenophases. This showed that the cumulative precipitation during the entire growing season had a greater effect on winter wheat growth than the synchronous precipitation and the pre-phenophase precipitation. The effects of temperature on winter wheat growth varied according to different grades of winter wheat growth based on the average values of seven phenophases. Winter wheat with a better-than-average growth condition had a stronger correlation with synchronous temperature, winter wheat with a normal growth condition had a stronger correlation with the cumulative temperature, and winter wheat with a worse-than-average growth condition had a stronger correlation with the pre-phenophase temperature. This study may facilitate a better understanding of the quantitative correlations between different grades of crop growth and meteorological factors, and the adjustment of field management measures to ensure a high crop yield.

Relationship of meteorological factors and air pollutants with medical care utilization for gastroesophageal reflux disease in urban area

BACKGROUND Gastroesophageal reflux disease(GERD)is a highly prevalent disease of the upper gastrointestinal tract,and it is associated with environmental and lifestyle habits.Due to an increasing interest in the environment,several groups are studying the effects of meteorological factors and air pollutants(MFAPs)on disease development.AIM To identify MFAPs effect on GERD-related medical utilization.METHODS Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea,while those on MFAPs were obtained from eight metropolitan areas and merged.In total,20071900 instances of GERD-related medical utilizations were identified,and 200000 MFAPs were randomly selected from the eight metropolitan areas.Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends,seasonality,and day of the week.RESULTS Five MFAPs were selected for the prediction model.GERD-related medical utilization increased with the levels of particulate matter with a diameter≤2.5μm(PM2.5)and carbon monoxide(CO).S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants,respectively.The time lag of each variable was significant around nine days after exposure.CONCLUSION Using five MFAPs,the final model significantly predicted GERD-related medical utilization.In particular,PM2.5 and CO were identified as risk or aggravating factors for GERD.

Relationship between NO_2 Concentration and Meteorological Factors in the Urban Area of Wanzhou District

Firstly,the daily variations of NO2 concentration in the urban area of Wanzhou in 2012 were analyzed,and then the relationship between NO2 concentration and meteorological factors（ precipitation,atmospheric pressure,wind speed,temperature,relative humidity and sunshine hours） was discussed. Finally,the multiple linear regression equation was established to predict NO2 concentration. The results showed that NO2 concentration in the urban area of Wanzhou did not exceed 80 μg /m3in most days from January 1 to December 31 in 2012. Among the six meteorological factors,NO2 concentration correlated significantly with three meteorological factors,that is,NO2 concentration correlated negatively with atmospheric pressure and wind speed but positively with relative humidity. NO2 concentration in the urban area of Wanzhou could be predicted using the multiple linear regression model. According to the rose diagram of wind directions,the wind blowing from the NNW was dominant in the urban area of Wanzhou.

Evaluating the impact and significance of meteorological factors upon dust storm occurrence

In this article, the quantitative impact and significance of factors on dust storm occurrence have been analyzed in detail, based on spring daily data sets of 17 meteorological factors and dust storm records during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China. Results show that daily mean and maximum wind speeds and evaporation have a positive effect on dust storm occurrence, i.e., their increase can result in an increase of dust storm occurrence. Inversely, daily mean and minimum relative humidity, lowest surface air pressure, vapor pressure and number of sunny hours have a negative effect on dust storm occurrence. However, daily mean and highest surface air pressure; mean, highest and lowest surface air temperature; and precipitation of 20：00-08：00, 08：00-20：00 and 20：00-20：00 have a positive effect on dust storm occurrence in some places but negative in other places. On average, daily maximum and mean wind speeds, direction of the maximum wind, number of sunny hours and evaporation have a significant effect on dust storm occurrence in Gansu Province, but precipitation of 20：00--08：00, 08：00-20：00 and 20：00-20：00, and mean surface air pressure and temperature all have a minor influence upon dust storm occurrence.

Coronavirus Disease 2019 (COVID-19) in Conakry, Republic of Guinea: Analysis and Relationship with Meteorological Factors

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), dates back to December 29, 2019, in Wuhan, China. It quickly spreads like wildfire to all continents in the following months. In Guinea, the first case of COVID-19 and death were all reported respectively on March 12 and April 16, 2020. Since then, several studies have found a relationship between certain environmental conditions such as the meteorological factors to have the potential of contributing to the spread of the virus. Thus, this study aims at examining the extent to which observed meteorological factors might have contributed to the spread of the coronavirus disease 2019 (COVID-19) cases in Conakry, from March 1 to May 31, 2020. Meteorological factors such as temperature (Tmin, Tmean and Tmax) and relative humidity (RHmin, RHmean and RHmax) were analyzed together with the data on the COVID-19. The dynamic of the COVID-19 in Guinea was analyzed along with that of some west African countries. The analysis on the dynamic of the COVID-19 pandemic in West Africa indicated Guinea as one of the most affected countries by the pandemic after Nigeria and Ghana. The study found that in general an increase in the temperature is linked to a decline in the COVID-19 number of cases and deaths, while an increase in the humidity is positively correlated to the number of cases and deaths. Nevertheless, from this study it was also observed that low temperature, mild diurnal temperature and high humidity are likely to favor its transmission. The study therefore, recommends that habitations and hospital rooms should be kept in relatively low humidity and relatively higher temperature to minimize the spread of the (SARS-CoV-2).

Spatial Interpolation Method of the Meteorological Factor in Northeast China Based on GIS

[ Objective ] The research aimed to study the best spatial interpolation method of the meteorological factor in Northeast China. [ Method ] Based on geostatistical analysis tool of the Arclnfo GIS software, several spatial interpolation methods were used to estimate the meteorological fac- tore （annual rainfall and monthly average temperature） in Northeast China, such as inverse distance weighted （IDW）, radial basis function （RBF） and Kriging. Then, the best interpolation method of one meteorological factor was selected. [ Result] For monthly average temperature, Kriging method was better than others. For annual rainfall, precision of the evaluated value with RBF method was higher than that of the IDW and Kriging methods. [Conclusion] There was obvious regional difference of the meteorological factor in Northeast China. Monthly average temperature in south was higher than that in north, and annual rainfall in southeast was more than that in northwest in Northeast China.

Preliminary Study on the Temporal Distribution of PM_( 2.5 ) Pollution and Influence of Meteorological Factors in Bengbu City

Based on the data of six automatic air monitoring stations in Bengbu City,the pollution characteristics and temporal distribution of fine particulate matter PM 2.5 in the air in Bengbu City from 2015 to 2019 were studied,and the correlation between meteorological factors and PM 2.5 concentration was analyzed.The results showed that from 2015 to 2019,PM 2.5 pollution in Bengbu City was relatively heavy in winter and spring and relatively light in summer and autumn,and PM 2.5 concentration had two peaks during the day and night.Precipitation,relative humidity,wind direction and wind speed had certain effects on PM 2.5 concentration in Bengbu City.The research provides reference for the monitoring,early warning and prevention of PM 2.5 pollution in the city.

Temporal Variations in Sea of Clouds and Their Relation with Meteorological Factors in Yandang Mountains

Based on data of meteorological elements in the meteorological station in North Yandang Mountains during 1960- 2013,temporal variations in days of sea of clouds over Yandang Mountains in nearly 50 years and their relation with air temperature,precipitation,relative humidity and wind speed were analyzed. The results showed that annual average days of sea of clouds over Yandang Mountains were 164. 92 d,and the maximum and minimum were 215 and 58 d,so there was a big difference between various years. The days of sea of clouds were the most in spring,and average days of sea of clouds（ average days of sea of clouds with low cloud cover ≥80%） were 50. 89 d（ 32. 77 d）,while they were the least in autumn. There was an obvious positive correlation between the days of sea of clouds and relative humidity. Precipitation occurred the day before or on the day when sea of clouds with low cloud cover ≥80% formed. On the day when sea of clouds with low cloud cover ≥80% appeared,average relative humidity was ≥80%,and average wind speed was ≤4. 5 m/s.

Ensemble learning prediction of soybean yields in China based on meteorological data

The accurate prediction of soybean yield is of great significance for agricultural production, monitoring and early warning.Although previous studies have used machine learning algorithms to predict soybean yield based on meteorological data,it is not clear how different models can be used to effectively separate soybean meteorological yield from soybean yield in various regions. In addition, comprehensively integrating the advantages of various machine learning algorithms to improve the prediction accuracy through ensemble learning algorithms has not been studied in depth. This study used and analyzed various daily meteorological data and soybean yield data from 173 county-level administrative regions and meteorological stations in two principal soybean planting areas in China(Northeast China and the Huang–Huai region), covering 34 years.Three effective machine learning algorithms(K-nearest neighbor, random forest, and support vector regression) were adopted as the base-models to establish a high-precision and highly-reliable soybean meteorological yield prediction model based on the stacking ensemble learning framework. The model's generalizability was further improved through 5-fold crossvalidation, and the model was optimized by principal component analysis and hyperparametric optimization. The accuracy of the model was evaluated by using the five-year sliding prediction and four regression indicators of the 173 counties, which showed that the stacking model has higher accuracy and stronger robustness. The 5-year sliding estimations of soybean yield based on the stacking model in 173 counties showed that the prediction effect can reflect the spatiotemporal distribution of soybean yield in detail, and the mean absolute percentage error(MAPE) was less than 5%. The stacking prediction model of soybean meteorological yield provides a new approach for accurately predicting soybean yield.

Individual Cotton Boll Weight as Influenced by Different Production Eco-Regions and Meteorological Factors

In order to explore systematically the physiological mechanism of high yield cotton ( Gossypium hirsutum L.) in Xinjiang, and further improve yield, the yield components were compared between three ecological regions. Boll number per plant was lower in South and North Xinjiang, but the harvested plant population were nearly 1.5 times higher than that in Nangong, so total boll numbers per unit area were greater in South and North Xinjiang. Weight per boll in south and north of Xinjiang was 5.896.50 g and 5.43 6.12 g respectively, 24 to 51% heavier than that in Nangong. The diurnal temperature difference between day and night was relatively greater in Xinjiang than in Nangong, benefitting the accumulation of photosynthetic product in bolls. The temperature difference and total hours of sunshine in boll period are the main reasons for cottons higher boll weight and yield in Xinjiang than in Nangong.

A descriptor for the local dust storm occurrence probability constituted by meteorological factors

Based on daily data sets of 17 meteorological factors during the period of 1954-2005 for 60 gauge stations distributed over Gansu Province of China and the corresponding dust storm records, the dust storm probabilities related to different classes of each factor have been calculated and analyzed. On the basis of statistical analysis, a meteorological descriptor quantifying the daily dust storm occurrence probability for each station, which is referred to as the Dust Storm Occurrence Probability Index （DSOPI）, has been effectively established. According to the statistical characteristics of DSOPI for each station, a feasible judging criterion for a dust storm event has been determined, which can greatly contribute to forecasting dust storms and completing the unavailable historic dust storm records. Meanwhile, the average daily dust storm probability related to each factor on the dust storm day for each station has been specially analyzed in detail, finally disclosing that, in general, the more signifi- cant one factor＇s influence on dust storms, the greater its contribution to them; and each factor＇s contribution clearly varies from place to place. Moreover, on average, maximum and mean wind speeds, maximum-speed wind direction, daily sunny hours, evaporation, mean and lowest relative humidity, lowest surface air pressure and vapor pressure contribute to dust storm events in Gansu Province most greatly in order among all the 17 involved factors.

Analysis of Meteorological Epidemic Factors and Soil Improvement Controlling Technology of Tobacco Bacterial Wilt (Ralstonia solanacarum)

[Objective] The paper was to analyze the meteorological epidemic factors for occurrence and prevalence of tobacco bacterial wilt （ Ralstonia solanaca- rum）, and to study control effects of different soil conditioners on the bacterial disease in Gacligongshan demonstration area of green, ecological, high quality tobac- co leaf production. [Method] The plots attacked by tobacco bacterial wilt over the years were selected and the incidence of the disease was periodically surveyed in tobacco growth period in 2012, 2103 and 2014, respectively. 10 d Effective accumulated temperature and rainfall were counted according to the meteorological data, and the relationship between meteorological factors and disease index was analyzed. The control effects of three kinds of soil conditioners ＂Zhuanggenfeng＂, refined fulvic acid and lime on tobacco bacterial wilt were tested. [ Result] The analysis results of meteorological factors showed that 10 d effective accumulated temperature and rainfall were positively correlated to disease index. The variation curve of 10 d effective accumulated temperature and rainfall reflected the change trend of disease index. The pH values were increased by 0.57, 0.50 and 0.72 respectively after applying ＂Zhuanggenfeng＂, refined fulvic acid and lime. The aver- age control effects on tobacco bacterial wilt were 60.74% -62. 18%, 53.05% -59.53%, and 48.59% -58.53%, respectively. [ Conclusion] 10 d Effective accumulated temperature and rainfall could be used as important reference for disease forecasting and controUing. The usage of soil conditioner has a certain preven- tion and control effect on tobacco bacterial wilt disease by forming soil conditions conducive to flue-cured tobacco growth but adverse to disease survival, which is an effective auxiliary method against the disease.

Effects of Meteorological Factors on Overwintering Ability,Yield and Quality of Forage Rape

In order to investigate the effects of meteorological factors on rape overwintering ability,forage yield and quality of rape in the North China plain,Brassia campestris L.and Brassica napus L.were used in this study.The results showed that compared with the B.napus L.varieties,the growth period of B.campestris L.was shortened by 10-15 d,the overwintering rate(WR)increased by 50.6%,and the density after winter(PD)increased by 41.5%.The fresh forage yield(FFY)and dry forage yield(DFY)of the B.campestris L.type significantly increased by 40.9%and 38.1%compared with the B.napus L.type.,respectively,while the forage quality of the B.napus L.type rape was significantly better than that of the B.campestris L.type.Compared with the B.campestris L.type,the crude protein(CP),fat,ash and total fatty acid(TFA)contents of the B.napus L.type of rape increased by 27.6%,42.9%,23.9%and 52.3%,respectively,and the milk productivity(HM),relative forage value(RFV)and relative forage quality(RFQ)increased by 14.0%,16.2%and 42.1%,respectively.The light and heat resources before wintering increased the WR and PD(P<0.05),and were positively correlated with FFY and DFY(P>0.05),and lower temperature during the wintering period led to lower WR(P<0.01).The light and heat resources during the overwintering period and after regreening were negatively correlated with FFY and DFY(P>0.05).The contents of CP,fat and TFA of rape had an extremely significant negative correlation with the temperature and sunshine hours before wintering,but an extremely significant positive correlation with the temperature during the wintering period and after regreening,as well as the sunshine hours and rainfall during the wintering period;and HM had an extremely significant positive correlation with the temperature,sunshine hours and rainfall during the wintering period,while RFV and RFQ were only extremely significantly positively correlated with the maximum temperature and rainfall.In summary,in the North China Plain,for autumn sowing rape,the B.campestris L.type can be selected to improve the wintering rate,and the B.napus L.type should be the main choice to improve the forage quality of rape.Therefore,the B.napus L.variety HYZ62 can be selected for autumn sowing in the North China Plain.