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Against the backdrop of intensifying global climate change, continuous population growth, and increasing pressure on natural resources and the environment, traditional extensive agricultural practices are no longer sustainable [...]

Optimizing aeration, fertilization, and irrigation is vital for improving greenhouse tomato production while mitigating soil greenhouse gas (GHG) emissions. This study investigated the combined effects of three aeration levels (A1: single Venturi, A2: double Venturi, CK: no aeration), two fertilization rates (F1: 180 kg/ha, F2: 240 kg/ha), and two irrigation levels (I1: 0.8 Epan, I2: 1.0 Epan) on tomato yield, CO2, N2O, and CH4 emissions, net GHG emissions, net global warming potential (NGWP), and GHG intensity (GHGI) across Spring–Summer and Autumn–Winter seasons. Results showed that aeration and fertilization significantly increased CO2 and N2O emissions but reduced CH4 emissions. Warmer conditions in Spring–Summer elevated all GHG emissions and yield compared to Autumn–Winter seasons. Tomato yield, net GHG emissions, NGWP, and GHGI were 12.05%, 24.3%, 14.46%, and 2.37% higher, respectively, in Spring–Summer. Combining the Maximal Information Coefficient and TOPSIS models, the optimal practice was A1-F1-I1 in Spring–Summer and A2-F1-I1 in Autumn–Winter seasons. These results provide a theoretical basis for selecting climate-smart management strategies that enhance yield and environmental sustainability in greenhouse tomato systems.

Gross primary productivity (GPP) is a key indicator for assessing carbon uptake capacity and photosynthetic productivity in agricultural ecosystems, playing a crucial role in regional carbon cycle evaluation and sustainable agriculture development. However, traditional mechanistic light use efficiency (LUE) models exhibit variable accuracy under different climatic conditions and crop types. Machine learning models, while demonstrating strong fitting capabilities, heavily depend on the selection of input features and data availability. This study focuses on winter wheat in the Guanzhong region, utilizing continuous field observation data from the 2020–2022 growing seasons to develop five machine learning models: Ridge Regression (Ridge), Random Forest (RF), Support Vector Regression (SVR), Gradient Boosting Regression (GB), and a stacking-based ensemble learning model (LSM). These models were compared with the LUE model under two scenarios, excluding and including solar-induced chlorophyll fluorescence (SIF), to evaluate the contribution of SIF to GPP estimation accuracy. The results indicate significant differences in GPP estimation performance among the machine learning models, with LSM outperforming others in both scenarios. Without SIF, LSM achieved an average R2 of 0.87, surpassing individual models (0.72–0.83), demonstrating strong stability and generalization ability. With SIF inclusion, all machine learning models showed marked accuracy improvements, with LSM’s average R2 rising to 0.91, highlighting SIF’s critical role in capturing photosynthetic dynamics. Although the LUE model approached machine learning model accuracy in some growth stages, its overall performance was limited by structural constraints. This study demonstrates that ensemble learning methods integrating multi-source observations offer significant advantages for high-precision winter wheat GPP estimation, and that incorporating SIF as a physiological indicator further enhances model robustness and predictive capacity. The findings validate the potential of combining ensemble learning and photosynthetic physiological parameters to improve GPP retrieval accuracy, providing a reliable technical pathway for agricultural ecosystem carbon flux estimation and informing strategies for climate change adaptation.

With the advancement of modern agriculture and increasing scarcity of water and fertilizer resources, determining optimal water and nitrogen (N) management strategies for intercropping systems is critical for ensuring system productivity and enhancing resource-use efficiency. This study employed field experiments to investigate the effects of different water and N treatments on grain yield, aboveground biomass, leaf area index (LAI), photosynthetic parameters, chlorophyll fluorescence characteristics, and radiation use efficiency (RUE) in a maize–soybean intercropping system. The experiment consisted of three cropping systems (maize monoculture, soybean monoculture, and maize–soybean intercropping), two irrigation regimes (rain-fed and supplemental irrigation), and three N-application rates for maize (240, 180, and 120 kgN ha[sup.−1]). The results demonstrated that supplementary irrigation significantly enhanced the LAI and photosynthetic capacity of both maize and soybean during critical growth stages, thereby promoting increases in grain yield and aboveground biomass. Intercropping significantly improved the productivity and photosynthetic performance of maize compared to monoculture, whereas soybean exhibited a reduction under intercropping conditions. Furthermore, irrigation regime and N rate had significant interactive effects on the photosynthetic performance of maize at the tasseling stage. In the intercropping system, a 25% reduction in the conventional application rate of N for maize maintained system productivity, whereas a 50% reduction substantially decreased maize yield and photosynthetic performance. The intercropping system achieved land equivalent ratios (LERs) ranging from 1.06 to 1.11 and RUE advantages (ΔRUE) of 1.52 to 1.64, demonstrating significant superiority in land and light resource utilization. Considering both productivity and resource-use efficiency, supplemental irrigation combined with 180 kgN ha[sup.−1] N application for maize represents the optimal water and N management strategy for achieving high yield and efficiency in maize–soybean intercropping systems in the Guanzhong plain.

The ongoing global warming and changing patterns of precipitation have significant implications for crop yields. Process-based models are the most commonly used method to assess the impacts of projected climate changes on crop yields. In this study, the crop-environment resource synthesis (CERES)-Maize 4.6.7 model was used to project the maize crop yield in the Shaanxi Province of China over future periods. In this context, the downscaled ensemble projections of 17 general circulation models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) were used as input for the calibrated CERES-Maize model. Results showed a negative correlation between temperature and maize yield in the study area. It is expected that each 1.0 °C rise in seasonal temperature will cause up to a 9% decrease in the yield. However, the influence of CO2 fertilization showed a positive response, as witnessed by the increase in the crop yield. With CO2 fertilization, the average increase in the maize crop yield compared to without CO2 fertilization per three decades was 10.5%, 11.6%, TA7.8%, and 6.5% under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. An elevated CO2 concentration showed a pronounced positive impact on the rain-fed maize yield compared to the irrigated maize yield. The average water use efficiency (WUE) was better at elevated CO2 concentrations and improved by 7–21% relative to the without CO2 fertilization of the WUE. Therefore, future climate changes with elevated CO2 are expected to be favorable for maize yields in the Shaanxi Province of China, and farmers can expect further benefits in the future from growing maize.

【Objective】 Deficit irrigation is a technology used widely in most arid and semi-arid regions to increase water use efficiency, but how to optimize the timing of and duration of the deficit remains elusive. The objective of this paper is to fill this gap for summer maize grown in the north of China. 【Method】 The field experiment compared three deficit irrigations by controlling the irrigation water amount at 100% (sufficient), 80% (moderate deficit) and 60% (sever deficit) of the potential evapotranspiration measured from a lysimeter (ETa). Each treatment irrigated the crop at emergence-jointing stage, jointing-tasseling stage, and tasseling-filling stage, respectively. Overall, there were nine treatments: moderate deficit irrigation at the jointing-filling stage (T1), severe deficit irrigation at the jointing-filling stage (T2), moderate deficit irrigation at the emergence-jointing and tasseling-filling stage (T3), moderate deficit irrigation at the emergence-tasseling stage and severe deficit irrigation at the tasseling-filling stage (T4), moderate deficit irrigation at the emergence-jointing stage and severe deficit irrigation at the jointing-tasseling stage (T5), severe deficit irrigation at the emergence-jointing and tasseling-filling stage (T6), severe deficit irrigation at the emergence-jointing stage and moderate deficit irrigation at jointing-tasseling stage (T7), severe deficit irrigation at the emergence-tasseling stage (T8), and moderate deficit at the tasseling-filling stage (T8). Sufficient irrigation in all stages was taken as the control (CK). In each treatment we measured the impact of rewatering on evapotranspiration, grain yield and water use efficiency of the crop. 【Result】 Compared with CK, deficit irrigation led to a decrease in evapotranspiration regardless of the stage it was imposed. Rewatering in T3 increased the evapotranspiration to a level comparable to that in CK. T5, T6 and T7 resulted in a permanent reduction in evapotranspiration even after rewatering. To avoid grain yield loss, the soil water content during the tasseling-filling stage should be maintained above 75% of the field capacity. The critical soil water was 50% of the field capacity, below which the water taken up by the crop was unable to sustain its growth. Deficit irrigation reduced the fruit yield by 5.85%～32.25%, compared to the CK, with T3 reducing the least (5.85%). T3 was thus most water-use efficient (2.81 kg/m3), increasing water use efficiency by 4.07% compared to CK. 【Conclusion】 Moderate water deficit at the seedling stage and full irrigation at the jointing-tasseling stage were optimal to improve water use efficiency without significantly reducing grain yield of the maize.

China's economic construction will rely greatly on U.S. markets and capital. To maintain stability across the Taiwan strait, [Jiang Zemin] also needs U.S. policy restrictions and constraints on Taiwan. Jiang will also seek a clearer commitment to cut back on U.S. weapons sales to Taiwan. If [Bill Clinton] can deliver on these two items, Taiwan independence forces are sure to be suppressed and Jiang will not have to resort to the use of force to resolve the Taiwan question. On this basis, a new Sino-American relationship can be established. Provided that Clinton and Jiang possess the same strategic wisdom, courage and resolve as Mao, [Richard Nixon], [Deng Xiaoping] and [Jimmy Carter] and turn negative factors into positive ones, this meeting could create a new strategic arrangement in which the two countries peacefully co- exist and develop for the next few decades.

【目的】探究不同时间尺度下夏玉米蒸发蒸腾量的变化规律。【方法】试验在夏玉米3个生育阶段（出苗—拔节期、拔节—抽雄期、抽雄—灌浆期）分别设置3个灌水水平（充分灌溉：100%ETa；中度水分亏缺：80%ETa；重度水分亏缺：60%ETa），其中ETa为蒸渗仪实测的充分灌溉条件下的蒸发蒸腾量，采用正交试验设计，共9个处理（CK、T1、T2、T3、T4、T5、T6、T7处理和T8处理），其中CK为充分灌溉处理，其余处理为不同程度的亏缺灌溉处理，研究了不同生育期亏缺-复水对夏玉米不同时间尺度蒸发蒸腾量、产量和水分利用效率的影响。【结果】与CK相比，不同亏缺灌溉处理下夏玉米蒸发蒸散量均有所减少。T3处理复水后蒸发蒸腾量基本可以恢复至正常水平，而T5、T6处理和T7处理复水后均未恢复至正常水平。抽雄—灌浆期土壤含水率应保持在75%田间持水率以上，土壤含水率低于50%田间持水率时，夏玉米将停止生长。不同亏缺灌溉处理的产量相较于CK减少5.85%~32.25%，其中T3处理比CK减少5.85%，且T3处理水分利用效率最高（2.81 kg/m3），比CK增加了4.07%。【结论】在苗期实施中度水分亏缺，拔节—抽雄期充分灌溉，可以提高夏玉米的水分利用效率，同时不造成产量的显著减少。

Richard Nixon's visit to China opened the door to improved Sino-U.S. relations. Deng Xiaoping's visit to the United States established formal diplomatic relations, and he, with Jimmy Carter, mapped out a strategy to contain the Soviet Union. Those two meetings between Chinese...

Richard Nixon's visit to China opened the door to improved Sino-U.S. relations. Deng Xiaoping's visit to the United States established formal diplomatic relations, and he, with Jimmy Carter, mapped out a strategy to contain the Soviet Union. Those two meetings between Chinese...