In this study, we investigated the effects of water stress on the growth and yield of summer maize (Zea mays L.) over four phenological stages: Seedling, jointing, heading, and grain-filling. Water stress treatments were applied during each of these four stages in a water-controlled field in the Guanzhong Plain, China between 2013 and 2016. We found that severe water stress during the seedling stage had a greater effect on the growth and development of maize than stress applied during the other three stages. Water stress led to lower leaf area index (LAI) and biomass owing to reduced intercepted photosynthetically active radiation (IPAR) and radiation-use efficiency (RUE). These effects extended to the reproductive stage and eventually reduced the unit kernel weight and yield. In addition, the chlorophyll content in the leaf remained lower, even though irrigation was applied partially or fully after the seedling stage. Severe and prolonged water stress in maize plants during the seedling stage may damage the structure of the photosynthetic membrane, resulting in lower chlorophyll content, and therefore RUE, than those in the plants that did not experience water stress at the seedling stage. Maize plants with such damage did not show a meaningful recovery even when irrigation levels during the rest of the growth period were the same as those applied to the plants not subjected to water stress. The results of our field experiments suggest that an unrecoverable yield loss could occur if summer maize were exposed to severe and extended water stress events during the seedling stage.

Aerated irrigation (AI) is a method to mitigate rhizosphere hypoxia caused by the wetting front from subsurface drip irrigation (SDI). This study evaluated the impacts of AI on soil aeration, plant growth performance, fruit yield (tomato), irrigation water use efficiency (IWUE), fruit nutrition (lycopene and Vitamin C (VC)) and taste (soluble sugar, organic acid and sugar–acid ratio) quality. A three-factorial experiment including AI and SDI at three irrigation levels (W_0.6, W_0.8 and W_1.0, corresponding with crop-pan coefficients of 0.6, 0.8 and 1.0) and two dripper depths (D₁₅ and D₂₅, burial at 15 and 25 cm, respectively), totaling 12 treatments overall, was conducted in a greenhouse during the tomato-growing season (April–July) in 2016. The AI improved soil aeration conditions, with significantly increased soil oxygen concentration and air-filled porosity relative to SDI. Moreover, the AI improved crop growth performance, with increased root morphology (diameter, length density, surface area and volume density), delayed flowering time, prolonged flowering duration and increased shoot (leaf, stem and fruit) dry weight, and harvest index. Fruit yield per plant, fruit weight, IWUE, the contents of lycopene, VC and soluble sugar, and sugar–acid ratio significantly increased under AI treatments (P < 0.05). As the irrigation level increased, fruit yield, number, and weight increased (P < 0.05), but IWUE and fruit lycopene, soluble sugar, and organic acid content decreased (P < 0.05). The dripper depth had no significant impact on fruit yield, nutrition and taste quality. Principal component analysis revealed that the optimal three treatments in terms of fruit yield, IWUE, and nutrition and taste quality were the treatments W_0.6D₂₅AI, W_1.0D₂₅AI and W_1.0D₁₅AI. These results suggest that AI can improve tomato growth performance and increase fruit yield, nutrition and taste quality, and IWUE through enhancing soil aeration conditions.

In this study, the crop environment resource synthesis maize (CERES-Maize) model was used to explore the effects of declining sunshine hours (SSH), decreasing daily maximum temperature (T_max), and cultivar replacements on growth processes and yields of maize in Northern China, a principal region of maize production. SSH were found to decrease at 189 of 246 meteorological stations in the northern provinces of China over the period of 1994–2012, and a decrease in T_max was also seen at many of these stations. The most significant decrease in these two climate variables occurred during June to September, a period for summer maize growth. For this study, seven crop field stations in the ShaanXi province, in the Guanzhong Plain, were selected, all of which showed a downward trend in SSH and T_max over the period of 1994–2012. The CERES-Maize model was first calibrated and validated against yield observations for these stations over the same period, and the yield simulations matched very well with observations. The model was then driven by the detrended SSH and T_max data, and the simulations were compared with those with a trend in these two input variables. The decline in SSH was found to reduce the maize yield by 8% on average over these stations due mostly to limited root growth, and the decline for shorter SSH reduced the yield more than that for longer SSH. Meanwhile, the decrease in higher T_max increased the yield by extending the growth period, while the decrease in lower T_max reduced the yield by lowering the thermal time. In addition, the observed yield showed a significant upward trend, and our modeling results indicate that this increase can be attributed mainly to the frequent cultivar replacements over our study period. The replaced cultivars usually had a longer growth period than the prior ones, which compensated for the yield loss due to fewer SSH. Net maize production decreased with the combined effects of the declines in SSH and T_max on yields. This study quantifies the contribution of changes in climate and cultivars to maize growth processes and yields and provides strong insights into maize production under a complex dynamic climate system.