The saline-alkali land is one of the important reserve resources for food production in China. It is important to assess the overall impact of amelioration practices applied to saline-alkali soils from multiple aspects, including crop yield, soil amelioration and climate and environmental impacts. In order to investigate the effects of different soil conditioners on the yield of summer maize, soil carbon sequestration and N₂O emissions in saline-alkali lands in the lower reaches of the Yellow river, a field experiment was carried out in a light-moderate saline-alkali cropland located in Binzhou county, Shandong province, China. Seven treatments were set up in a summer maize field, namely blank control (CK), applying chemical fertilizers according to local practices (F), applying 50% of total nitrogen with manure (M), adding gypsum based on treatment F (G), adding microbial agents on the treatment M (MB), adding gypsum based on the treatment MB (MGB), and applying 70% total nitrogen with manure based on the treatment MGB (HMGB). Among the treatments, M and G were single conditioner treatments, and MB, MGB and HMGB were compound conditioner treatments. Results showed that: (1) application of conditioners had significant effects on both biomass and yield of summer maize compared with the local practice (F). For the crop yield, applying compound conditioners exhibited greater effects than single conditioners where both the number of grains per ear and the 100−grain weight significantly contributed to the increased crop yield under compound conditions. (2) Compared with the local conventional fertilization practice (F), the application of given soil conditioners significantly increased the proportion of 0.250−1.000mm macroaggregates in the soil by 10−20 percentage points, while reducing the clay content (<0.020mm) by 10−30 percentage points. Correspondingly, the contribution of the macro-aggregates to total soil organic carbon content increased by 3.0%−38.7% (0.250− 1.000mm), whereas the contribution of the clay fraction decreased by 3.3%−23.4% (<0.020mm). Notably, treatments applying with gypsum alone (G) and multiple conditioners exhibited significantly greater improvements in aggregate composition and their contributions to soil organic carbon compared to the treatment using organic fertilizer alone (M). (3) The cumulative N₂O emissions during the summer maize growth period for the representative treatments (CK, F, M, MGB) were between 443.8−1416.9gN·ha⁻¹. The treatments M and MGB showed significantly N₂O mitigation by 13.8% and 27.7%, respectively, compared with the treatment F. The results of this study indicated that the conditioner with high-amount manure + gypsum + microbial agent (HMGB) can be applied as a recommended choice for the saline-alkali soil for the multi−objective sustainable development, including increasing the crop yield and SOC, as well as mitigating N₂O emissions in the lower reaches of the Yellow river.

To investigate the effects of direct straw return on soil properties under a facility−based paddy upland rotation system, this study set up five treatments: control (CK), 2y tomato straw return (TS2), 5y tomato straw return (TS5), one year maize straw return (MS1) and 4y maize straw return (MS4). Soil nutrients, enzyme activity and microbial community diversity were analyzed. Results showed that direct straw return significantly reduced the soil organic matter content and pH, with the decrease becoming more pronounced with increasing return years. Meanwhile, the return of straw significantly increased soil available potassium and phosphorus in the soil but decreased the nitrate nitrogen content. Soil bacterial richness and diversity decreased with increasing return years. Additionally, straw return increased the soil phosphatase, cellulase and urease activities, but decreased sucrase and nitrate reductase activities. Correlation analysis indicated that straw return reduced soil bacterial diversity, altered the community composition, making Rhodanobacteraceae and Gemmatimonadaceae the dominant groups and lead to changes in soil enzyme activities and ultimately resulting in alterations in soil physicochemical properties. This study demonstrates that direct straw return under a facility−based paddy−upland rotation system has significant impact on soil properties, providing a scientific basis for optimizing straw return techniques. 

This study took adjacent deciduous natural broadleaf forest (BF) watershed and evergreen artificial coniferous forest (CF) watershed in the Kuraiyama Experimental Forest of Gifu Prefecture in Japan as research objects. Through comparative analysis of stream temperature, forest air temperature, and soil temperature (at 5cm and 50cm depths) during the deciduous season (November−May of next year) and non−deciduous season (June−October) in 2013−2014 and 2017−2018, effects of different forest types on stream temperature were systematically investigated. The findings could provide a scientific basis for adaptive watershed management and ecological restoration of plantation forests. The results showed that: (1) the annual stream temperature range in the BF watershed (2.76–15.56°C) was approximately 4.56°C narrower than that in the CF watershed (0.07−17.43°C), indicating greater thermal stability. (2) A critical thermal threshold of 10.38℃ was identified in the daily average stream temperatures between the two watersheds. When average stream temperatures in both watersheds were below this threshold, the CF watershed exhibited significantly lower temperatures than the BF watershed by 1.49°C (P<0.05), with the inter−watershed temperature difference increasing as stream temperature decreased. Above the threshold, stream temperatures in the CF watershed became significantly higher than those in the BF watershed by 0.79°C (P<0.05). (3) Soil temperatures at both 5cm and 50cm depths were consistently higher in the BF watershed than in the CF watershed, with the maximum inter−watershed temperature difference reaching 1.00°C in the 5cm soil layer during the deciduous season. (4) Soil temperature showed significantly stronger effects on stream temperature than forest air temperature, with the highest correlations observed between shallow soil temperature (5−15cm) and stream temperature (r=0.907−0.944, P<0.001). The study demonstrated that forest canopy phenology served as the fundamental driver of inter−watershed temperature differences, primarily through its regulation of solar radiation penetration and snow cover dynamics. Based on the research results, authors recommend establishing a stream temperature threshold response system in watershed management, optimizing riparian vegetation composition (e.g., prioritizing deciduous species), and implementing adaptive measures like mixed coniferous−broadleaf forestation to enhance the climate resilience of watershed ecosystems.

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.

Bitter gourd variety 'Jintian 188' were used as test materials in artificial climate chamber. LED pure white light 200μmol·m⁻²·s⁻¹ was taken as control (CK), and red and blue light 200, 300 and 400μmol·m⁻²·s⁻¹ treatments were set up, and the ratio of red and blue light was R7:B3. The photoperiod was day/night = 14h/10h. The purpose of this study was to explore the effects of red and blue light intensity on the growth of bitter gourd seedlings by comparing and analyzing the morphological indices, antioxidant enzyme activities, gas exchange parameters, chlorophyll fluorescence parameters and leaf tissue structure. The results showed that: (1) under red and blue light irradiation, the morphological indices, gas exchange parameters, chlorophyll fluorescence parameters and leaf tissue structure of bitter gourd seedlings were significantly improved compared with those under white light conditions. (2) With the increase of red and blue light intensity, the plant height, stem diameter, leaf area, fresh weight, dry weight and seedling index of bitter gourd seedlings increased gradually, and the plant growth became better. Pn, Gs, Ci and Tr showed increasing trends. Chlorophyll content, Y(II), qP, ETR and Fv'/Fm' were significantly increased. The thickness of leaves, palisade tissue and sponge tissue all increased significantly, and the cells of palisade tissue changed from different lengths and loose arrangement to basically the same length and neat and dense arrangement. The results showed that the morphological indices, photosynthetic efficiency and photosynthetic ability of bitter gourd seedlings were improved under red and blue light irradiation. The performance of 400μmol·m⁻²·s⁻¹ red and blue light treatment was the best, which was the suitable light intensity for bitter gourd seedlings. 

Frequent occurrence of extreme climate adversely affected agricultural production. As foxtail millet had high nutritional value and strong stress resistance, it had played an important role in improving people's dietary structure and ensuring food security. The increasingly severe climate environment had affected the yield and quality formation of foxtail millet seriously. Therefore, it's of importance to strength the research on abiotic stress resistance of foxtail millet. Based on the research progress of domestic and foreign scholars on high temperature, low temperature, drought, salt and alkali of foxtail millet, this paper reviewed the mechanisms on the effects of abiotic stress on the yield and quality formation of foxtail millet, the cultivation techniques and the application of chemical products in the regulation of millet in northern China, and prospected the future in this field. The results showed that high temperature stress affected the translocation and distribution of assimilates and grain formation of foxtail millet, resulting in the decrease of seed setting rate and grain weight. With the extension of high temperature time, the taste and appearance quality of foxtail millet became worse. Low temperature often occured at the seedling stage of foxtail millet, which could cause a large area of rotten seeds and buds, which seriously affected the yield formation. Moderate drought could improve the cooking and processing quality of foxtail millet, but higher degree drought might inhibit the normal growth and development of foxtail millet. Under the saline−alkali environment, the growth of foxtail millet roots and shoots, the accumulation of dry matter decreased, the yield and the processing quality decreased. In conclusion, abiotic stress can inhibit the growth and development of foxtail millet, reduce the efficiency of photosynthesis and limit the absorption of nutrients. These stresses can cause water loss, cell metabolic disorder and physiological dysfunction, and affect the formation of millet yield and quality ultimately. Therefore, it is necessary to focus on research of the influence mechanism of abiotic stress such as high temperature and drought on the growth and development characteristics, yield and quality formation of foxtail millet, mechanisms and explore how to achieve stable and high yield under adverse meteorological environment through breeding technology and cultivation management measures in the future, so as to provide theoretical basis for the research on abiotic stress resistance mechanism and production application for foxtail millet and other crops.

Based on the Zaozhuang pomegranate yield and the Yicheng national meteorological station data from 2006 to 2020, the pomegranate yield was separated by the sliding average, HP filter and Logistic curve fitting method, and the key meteorological factors were selected to establish a simulation model of pomegranate yield, with a view to providing scientific and technological support for enhancing the Zaozhuang pomegranate brand benefits and helping rural revitalization. The results showed that: (1) the Logistic curve fitting method was the most suitable in separating the yield of Zaozhuang pomegranate from 2006 to 2020, with determination coefficient (R²) of 0.998, the mean relative error (MRE) of 0.389%, the mean absolute error (MAE) of 26.296 kg·ha⁻¹, and the root mean squared error (RMSE) of 29.825 kg·ha⁻¹, the HP filter was second best simulation effect. (2) Zaozhuang pomegranate meteorological yield was positively correlated with the average temperature in early June, the longest consecutive precipitation days in July, the precipitation in mid−August, the longest consecutive precipitation days and the precipitation in August, the sunshine hours and the temperature diurnal variation in late September, which indicated that the high temperature in early June, the sufficient precipitation in July and August, the sufficient sunshine and the larger temperature diurnal variation in late September were all favorable to the improvement of the pomegranate meteorological yield. The negative correlation between the maximum temperature in August, the average relative humidity in September, the average relative humidity in late September and the meteorological yield of pomegranate, which indicated that the hot weather in August and the high humidity in September were unfavorable to the growth of pomegranate. (3) After selection, a simulation model of Zaozhuang pomegranate yield was established using years and seven meteorological factors: the average temperature in early June, the longest continuous precipitation days in July, the maximum temperature and the precipitation in August, the average relative humidity in late September, the sunshine hours and the temperature diurnal variance in late September, with R² of 0.984, MRE of 1.18%, MAE of 82.917kg·ha⁻¹, and an RMSE of 197.770kg·ha⁻¹. The yield simulation model was validated with the pomegranate yield data in 2013, 2017 and 2020, with R² of 0.858, MRE of 8.13%, MAE of 566.983kg·ha⁻¹, and RMSE of 882.967kg·ha⁻¹, indicating that the model can be used for the simulation of Zaozhuang pomegranate yield.

Accurately describing the emission characteristics of nitrous oxide (N₂O) in greenhouse cultivation can effectively support the sustainable development of greenhouse production. This article compared the effects of four nitrogen supply methods on N₂O emission characteristics in greenhouse tomato production in a solar greenhouse in Shunyi of Beijing, using none fertilization as a control. The N₂O emission was measured by static camera obscuring method. The influence characteristics of four nutrient solution supplied on N₂O emission during tomato production in greenhouse were discussed. The influence of air temperature, air relative humidity and substrate temperature on N₂O emission in greenhouse was compared and analyzed. The results showed that: (1) the N₂O emission intensity of the control group and the four nutrient solution supply experimental groups ranged from 0.18−0.33kgN₂O·t⁻¹, the emission factors (EF) was from 1.01% to 1.92%, and the nutrient solution supply of garden type (YS) had the lowest emission factors, and the N₂O emission was reduced while the yield was guaranteed. (2) Compared with air relative humidity and substrate temperature, air temperature in greenhouse had the most significant effect on N₂O emissions (P<0.01). (3) Among the four nutrient solution feeding experimental groups, Yamazaki nutrient solution treatment (SQ) had the highest soluble solids and soluble sugar content, and the tomato fruit quality performance was better, and garden nutrient solution treatment (YS) had the highest tomato yield (68.76t·ha⁻¹), which was significantly different from other experimental treatments. The results of this study can provide a reference for the selection of nutrient solution and the use of more accurate emission factors for N₂O emission accounting of tomatoes cultivated in greenhouse matrix.

Accurate prediction of the initial flowering date (IFD) of cherry blossoms holds significant importance for tourism planning and park management. It serves as a scientific basis for park authorities to implement protective measures in advance. Thus, the Gui'an Cherry Blossom Garden was considered to analyze the IFD of cherry blossoms in combination with the meteorological data from 2013 to 2024. Pearson correlation coefficients were employed to evaluate the relationships between meteorological factors and the IFD, for identification of significant factors from 18 meteorological variables for model construction. Based on the extracted key factors, a BP neural network model and a multiple linear stepwise regression (MLSR) model were developed. The BP neural network underwent six−fold cross−validation, and its results were compared with those of the MLSR model. The IFD results of cherry blossoms in the Gui'an Cherry Blossom Garden exhibited a general trend of "advancement followed by a slight delay," with significant interannual fluctuations. The IFD mainly occurred in the first half of March and was  highly influenced by climate fluctuations, particularly in mid−January and late February. Accumulated temperature (especially low−threshold temperatures, such as ≥3°C) played a critical role in advancing the IFD and was designated as a key reference indicator for prediction. Validation of the established models using RMSE and R² revealed that the BP neural network model significantly outperformed the MLSR model in both accuracy and stability. The BP model achieved an average root mean square error (RMSE) of 0.2636 days, markedly lower than the 2.92 days of the MLSR model. Furthermore, the BP model's coefficient of determination (R²) reached as high as 0.9961 during cross-validation, whereas the R² of the MLSR model was much lower. Overall, the integration of BP neural network model with multiple meteorological factors, represented better nonlinear relationships, thereby providing a robust scientific foundation for park management and tourism planning. Additionally, it offered an effective technical approach for the accurate prediction of the IFD of cherry blossoms.

In order to reveal the influence of meteorological factors on the quality of Shanghang tobacco, based on the daily meteorological data of Shanghang from 2009 to 2024 and the tobacco quality data of Shanghang tobacco in the same period, a variety of mathematical statistical methods were used to analyze the change characteristics of Shanghang tobacco quality, to reveal the key meteorological factors and sensitive periods affecting the quality of tobacco leaves, and then build a response model and validate the model. The results showed that: (1) from 2009 to 2024, the nicotine content of Shanghang tobacco leaves in Fujian was 1.7%−3.1%, the total sugar content was 22.4%−38.7%, the total nitrogen content was 1.5%−2.4%, the potassium content was 1.9%−3.0%, except the total sugar and reducing sugar contents were slightly higher, the other contents were all within the suitable range. (2) From 2009 to 2024, the total sugar content of Shanghang tobacco leaves showed a significant upward trend (P<0.01), the total nitrogen content showed a significant downward trend (P<0.01), and the other quality changes were not significant. (3) In terms of the transplanting period, the average temperature on the transplanting day and the extreme low temperature after transplanting for 40d were the key meteorological factors that affected nicotine. The relative humidity after transplanting for 15d was the key meteorological factor affecting total sugar and total nitrogen. Precipitation after transplanting for 15d and after transplanting for 50d were respectively the key meteorological factors affecting reducing sugar and potassium. For the picking period, the average temperature in the first 5d of picking was the key meteorological factor affecting nicotine. Extreme low temperature on the picking day was the key meteorological factor affecting total sugar and reduction of sugar. Total nitrogen were comprehensively affected by the average temperature 20d before picking, the extreme high temperature 20d before picking, the extreme low temperature on the picking day and the relative humidity 15d before picking. Extreme low temperature 40d before picking was the key meteorological factor affecting potassium. (4) The prediction model of tobacco leaf quality during the transplanting period and picking period was verified by the meteorological factor and tobacco leaf quality data from 2022 to 2024. It showed that the root mean square error between the simulated values and the actual values of nicotine, total nitrogen and potassium contents was between 0.29% and 0.71%, and the mean absolute error (MAE) was between 0.28% and 0.71%. The simulation model effect was good. It indicates that the model can guide the growth of characteristic tobacco leaves, respond to meteorological disasters during the production process, and predict the quality of tobacco leaves.

Based on daily meteorological data and forest fire information from 2006 to 2014 in Yanbian county of Panzhihua, this paper analyzed the correlation between meteorological conditions and forest fires occurrence, and screend out the main meteorological factors that contributed to forest fires occurrence. By applying the principal component analysis method of SPSS software, a meteorological grade model of forest fire danger was constructed. Forest fire data from 2015 to 2019 were used to test the model, which was expected to provide a basis for local forest fire danger prediction and serve the ecological construction of Panzhihua city. The results showed that forest fires in Yanbian county of Panzhihua city, mainly occured from January to June, with February to May being the months with the highest rate of forest fires. The meteorological factors that had a correlation with the occurrence of forest fires of Yanbian county, in descending order of correlation degree, were the average 10min wind speed, average 2min wind speed, average temperature, maximum temperature, sunshine hours, maximum wind speed and daily precipitation. Using the above 7 meteorological factors to construct a meteorological grade evaluation model for forest fire danger in Yanbian. The inspection found that the new mode had a 94.0% hit rate in predicting level 5 when a fire occurred. The hit rate of the new mode increased by 11.9 percentage points compared with the original mode, and the false alarm rate decreased by 20.2 percentage points. In terms of the normal distribution of meteorological grade predictions of fire risks at all levels, the new model was closer to the local objective reality and the accuracy in the results was higher. It can provide services for local forest fire risk forecasting.   

To provide a reference for addressing the adverse effects of drought heat wave compound events under climate change, promoting agricultural development, protecting the ecological environment and rationally using water resources, an analysis was conducted using daily meteorological data from 80 national meteorological stations spanning the period from 1971 to 2023. This study aimed to investigate the temporal and spatial variability characteristics of drought heat wave compound events within the province. Additionally, the correlation between these compound events and agricultural drought was analyzed and evaluated. The results indicated that: (1) from 1971 to 2023, the cumulative drought days, times of heat waves and drought heat waves compound events at 80 stations in Guizhou exhibited increasing trends following abrupt changes in 2019, 2008 and 2020, respectively. In addition, the oscillation strength of these events intensified over time, with notable period variations of approximately 17 and 11 years. Notably, times of heat waves fluctuated significantly at a rate of 11 per decade (P<0.01), whereas drought days and times of drought heat wave compound events did not display significant trend changes. (2) From 1971 to 2023, the distribution of drought days, times of heat waves and drought heat waves compound events in Guizhou exhibited similar west-to-east characteristics, with a notable increase in the number of drought heat waves compound event from west to south. Specifically, 12.5% of the stations observed a statistically significant increase in drought days (P<0.05), 26.3% of the stations experienced a significant rise in times of heat waves (P<0.05), and 5.0% of the stations reported a significant increase in times of drought heat waves compound events (P<0.05). (3) The occurrence of times of drought heat waves compound events in Guizhou from 1971 to 2023 was positively affected by the same intensity of drought days and times of heat waves.The spatial distribution of these events followed a southwest-to-northeast pattern and an elevation gradient from high to low. The risks associated with these three disasters (drought, heat waves and their composite events) increased significantly. (4) From 2010 to 2022, the drought-affected crop area in Guizhou exhibited a significant positive correlation with the drought days and times of heat waves recorded at 80 stations within the province (P<0.05). Furthermore, an extremely significant positive correlation was observed between the drought-affected crop area and times of drought heat waves compound events (P < 0.01). It is important to note that the number of drought heat wave compound event had a more profound impact on agricultural drought compared to the drought days or heat waves number alone.

In order to improve the monitoring ability of wheat meteorological diseases, based on the historical meteorological data and observation data of wheat scab in Jiangsu province, from the aspect of the scab infection process, the appropriate meteorological conditions were analyzed for the development of scab, the disease promotion indices of wheat key growth stages were given. A comprehensive humidity and heat index model was then constructed to classify the meteorological suitable level of the occurrence of wheat scab. In addition, meteorological suitable level prediction techniques were studied and their accuracy was tested. The results showed that the disease promoting indicators for wheat growth stages include booting to heading, heading to flowering and flowering to milk ripening were T≥14℃ and RH≥70%, T≥16℃ and RH≥68%, T≥18℃ and RH≥70%, respectively. Site−scale tests found that the model’s accuracy was more than 70% in the simulating levels of Fusarium head blight, and that it was in high agreement with observations of moderate to severe outbreaks of Fusarium head blight in 2002, 2003 and 2012. At the same time, the regional scale test showed that model could also accurately predict the epidemic areas and occurrence levels of diseases in typical years well, indicating it was more prevalent along the Huai river and the southern part of the Yangtze river in Jiangsu province, and spatially presented a "heavy in the south and light in the north" characteristic. Combined with refined weather forecasting products, this model had a good ability to predict and identify the spatiotemporal changes in the occurrence and development of typical Fusarium head blight epidemics. As the comprehensive humidity and heat index model well reflects the typical occurrence year and the variations in region and degree of the disease, it could be used to determine the meteorological suitability level for wheat Fusarium head blight in Jiangsu province, thereby potentially reducing the risk of disease occurrence more effectively.