Silicon (Si) enhances maize resistance to drought. While previous studies have mainly focused on the seedling stage, the mediation of drought stress by Si imposed at the vegetative and reproductive stages has been rarely investigated. A soil-column experiment was thus conducted under a rainproof shelter to quantify the effect s of Si application on the physiological and agronomic responses of maize to drought stress imposed at the 6-leaf (D-V6), 12-leaf (D-V12), and blister (D-R2) stages. The observed parameters included plant growth, photosynthesis, osmolytes, antioxidant activity, and grain yield. The results showed that drought stress strongly decreased the leaf area, leaf water content, photosynthetic rate, chlorophyll content, and antioxidant activity (superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT)) and markedly increased lipid peroxidation. D-V6, D-V12, and D-R2 decreased grain yields by 12.9%, 28.9%, and 44.8%, respectively, compared to the well-watered treatment (CK). However, Si application markedly increased leaf area, chlorophyll content, photosynthetic rate, osmolyte content, and enzymatic antioxidant activities (SOD, POD, and CAT), and decreased malondialdehyde (MDA) and superoxide radical accumulation, ultimately improving maize yields by 12.4%, 69.8%, and 80.8%, respectively, compared to the non-Si treated plants under drought stress at the V6, V12, and R2 stages. Furthermore, maize yields had a significant positive correlation with chlorophyll content and SOD and POD activity during the three stages. Our findings suggest that Si-induced changes in chlorophyll content and antioxidant activity might constitute important mechanisms for mitigating drought stress. In conclusion, this study provides physico-biochemical evidence for the beneficial role of Si in alleviating drought-induced yield reduction in maize, particularly during the late vegetative or early reproductive stages. Thus, Si application constitutes an effective approach for improving maize yield in rain-fed agricultural systems.

Optimizing planting structure that balances both high yield and water resources shortage is essential for developing efficient water-saving agriculture. To provide insights about the relationship between planting structure optimization and water resource constraint, crop water requirement, precipitation coupling degree, gross total water requirement and irrigation project metrics were calculated and analyzed with the dataset collected from 16 locations in Xuchang City, China. The strategy of reducing the planting proportion of high water-consumption crops and increasing low consumption and high precipitation coupling degree crops was adopted to determine a suitable water-saving planting scheme based on the IQR (interquartile range) method. Evapotranspiration had a decreasing trend from northwest to southeast areas. There were positive correlations between gross total water requirement (GTWR) and annual total yields (r = 0.825, p = 0.002), and between GTWR and proportion of vegetable planting areas (PVPA) (r = 0.734, p = 0.0101). The GTWR was negatively correlated with the ratio of water-saving irrigated areas to effective irrigated areas (RSEA), proportion of wheat planting areas (PWPA) and proportion of bean planting areas (PBPA), with coefficients of −0.787, −0.936 and −0.828, respectively. The planting proportion of winter wheat, summer maize, vegetables and flowers decreased by 8.8%, 25.8%, 16.2%, and 28.7%, respectively, while oil-beans and tubers increased by 62.4% and 95.6%, respectively. The irrigation water consumption was reduced by 5.2%, saving 3.25 × 10⁷ m³ irrigation water without sacrificing economic benefits after adjusting for the whole region. Consequently, precipitation coupling degree, water-saving technology and historical planting habits should be considered when optimizing cropping distributions. This research provided a new theoretical basis and comprehensive approach for agriculture irrigation water management and regional planting structure optimization from a realistic perspective.

Collecting accurate real-time soil moisture data in crop root zones is the foundation of automated precision irrigation systems. Soil moisture sensors (SMSs) have been used to monitor soil water content (SWC) in crop fields for a long time; however, there is no generally accepted guideline for determining optimal number and placement of soil moisture sensors in the soil profile. In order to study adequate positioning for the installation of soil moisture sensors in the soil profile, six years of field experiments were carried out in North China Plain (NCP). Soil water content was measured using the gravimetric method every 7 to 10 days during six growing seasons of winter wheat (Triticum aestivum L), and root distribution was measured using a soil core method during the key periods of winter wheat growth. The results from the experimental data analysis show that SWC at different depths had a high linear correlation. In addition, the values of correlation coefficients decreased with increasing soil depth; the coefficient of variation (CV) of SWC was higher in the surface layers than in the deeper layers (depths were 0–40 cm, 0–60 cm, and 0–100 cm during the early, middle, and last stages of winter wheat, respectively); wheat roots were mainly distributed in the surface layer. According to an analysis of CV for SWC and root distribution, the depths of planned wetted layers were determined to be 0–40 cm, 0–60 cm, and 0–100 cm during the sowing to reviving stages (the early stage of winter wheat), returning green and jointing stages (the middle stage of winter wheat), and heading to maturity stage (the last stage of winter wheat), respectively. The correlation and R-cluster analyses of SWC at different layers in the soil profile showed that SMSs should be installed 10 and 30 cm below the soil surface during the winter wheat growing season. The linear regression model can be built using SWC at depths of 10 and 30 cm to predict total average SWC in the soil profile. The results of validation showed that the developed model provided reliable estimates of total average SWC in the planned wetted layer. In brief, this study suggests that suitable positioning of soil moisture sensors is at depths of 10 and 30 cm below the soil surface.

Transparent soil (TS) was specifically designed to support root growth in the presence of air, water, and nutrients and allowed the time-resolved phenotyping of roots in vivo. Nevertheless, it is imperative to further optimize the reagent cost of TS to enable its wider utilization. We substituted the costly Phytagel obtained from Sigma with two more economical alternatives, namely Biodee and Coolaber. TS beads from each brand were prepared using 12 different polymer concentrations and seven distinct crosslinker concentrations. A comprehensive assessment encompassing transparency, mechanical characteristics, particle size, porosity, and stability of TS was undertaken. Compared to the Sigma Phytagel brand, both Biodee and Coolaber significantly reduced the transparency and collapse stress of the TS they produced. Consequently, this led to a significant reduction in the allowable width and height of the growth box, although they could still simultaneously exceed 20 cm and 19 cm. There was no notable difference in porosity and stability among the TS samples prepared using the three Phytagel brands. Therefore, it is feasible to consider replacing the Phytagel brand to reduce TS production costs. This study quantified the differences in TS produced using three Phytagel brands at different prices that will better promote the application of TS to root phenotypes.