Nanoscale zerovalent iron (nZVI) has shown great promise for water treatment and soil remediation. However, the rapid aggregation of nZVIs significantly affects their mobility and reactivity, which considerably limits the practical applications. Montmorillonite- (Mt-) supported nZVI (Mt-nZVI) has received increasing attention for the past decade because it can prevent the aggregation of nZVI and incorporate the advantages of both nZVI and Mt in soil and water treatment. This work thus had a comprehensive review on the use of Mt-nZVI for soil and water treatment. We first summarized existing methods used to prepare Mt-nZVI, indicating the advantages of using Mt to support nZVI (e.g., increase of the dispersion and mobility of nZVI, reduction of the size and oxidation tendency of nZVI). We then presented the reaction mechanisms of Mt-nZVI for contaminant removal and evaluated the critical factors that influence the removal (e.g., pH, temperature, and dosage of the adsorbent). We further presented examples of applications of Mt-nZVI for the removal of typical contaminants such as heavy metals and organic compounds in soil and water. We finally discussed the limitations of the use of Mt-nZVI for water treatment and soil remediation and presented future directions for the application of nZVI technology for soil and water treatment.

The application of unmanned aerial vehicle (UAV) remote sensing technology for high-throughput acquisition of phenotypic values of field plant height is of great significance in plant height monitoring of wheat varieties (lines). Based on the UAV, mounted with high-resolution digital cameras, a low-altitude remote sensing platform was built to obtain images of the Berkut/Worrakatta recombinant inbred lines (RIL) wheat population (297 lines). The optimal digital surface model (DSM) for plant height extraction was constructed by combining the actual wheat plant heights measured in the field. Using a wheat 50K SNP chip, quantitative trait locus (QTL) analysis was performed for field plant height of the RIL population using UAV plant height data to detect the locus related to plant height. We verified the effectiveness of QTL analysis using the UAV plant height data. The results of the DSM plant height extraction method showed that the plant height extraction models during the entire growth period had a highly significant correlation (p < 0.001); the measured plant height correlated with the predicted plant height, with prediction model accuracy R² = 0.7527 and verification model accuracy R² = 0.8214. QTL analysis was conducted on the manually and UAV-measured plant height traits. For the manually measured plant height phenotypes, one locus related to plant height was detected on wheat chromosome 6A and explained 13.12% of phenotypic variation. For the UAV-measured phenotypes, one locus related to plant height was also detected on wheat chromosome 6A and explained 9.62% of phenotypic variation. The QPH.xjau-6A locus on chromosome 6A, which featured in the results of the two measurement methods, is a stable locus, indicating that the mapping results obtained using the actual plant height values were in good agreement with those obtained using the UAV extracted values. Three candidate genes related to plant height were screened: they encode protein kinase, NAC domain protein, and cytochrome P450, respectively. Therefore, this study provided reference information for monitoring plant phenotype and growth of wheat and also for the extraction of plant height for wheat breeding in the future.

Oases in arid regions are crucial for sustaining agricultural production and ecological stability, yet few studies have simultaneously examined the coupled dynamics of land use/cover change (LUCC), carbon emissions, and ecosystem service value (ESV) at the oasis–agricultural scale. This gap limits our understanding of how different land use trajectories shape trade-offs between carbon processes and ecosystem services in fragile arid ecosystems. This study examines the spatiotemporal interactions between land use carbon emissions and ESV from 1990 to 2020 in the Wensu Oasis, Northwest China, and predicts their future trajectories under four development scenarios. Multi-period remote sensing data, combined with the carbon emission coefficient method, modified equivalent factor method, spatial autocorrelation analysis, the coupling coordination degree model, and the PLUS model, were employed to quantify LUCC patterns, carbon emission intensity, ESV, and its coupling relationships. The results indicated that (1) cultivated land, construction land, and unused land expanded continuously (by 974.56, 66.77, and 1899.36 km²), while grassland, forests, and water bodies declined (by 1363.93, 77.92, and 1498.83 km²), with the most pronounced changes occurring between 2000 and 2010; (2) carbon emission intensity increased steadily—from 23.90 × 10⁴ t in 1990 to 169.17 × 10⁴ t in 2020—primarily driven by construction land expansion—whereas total ESV declined by 46.37%, with water and grassland losses contributing substantially; (3) carbon emission intensity and ESV exhibited a significant negative spatial correlation, and the coupling coordination degree remained low, following a “high in the north, low in the south” distribution; and (4) scenario simulations for 2030–2050 suggested that this negative correlation and low coordination will persist, with only the ecological protection scenario (EPS) showing potential to enhance both carbon sequestration and ESV. Based on spatial clustering patterns and scenario outcomes, we recommend spatially differentiated land use regulation and prioritizing EPS measures, including glacier and wetland conservation, adoption of water-saving irrigation technologies, development of agroforestry systems, and renewable energy utilization on unused land. By explicitly linking LUCC-driven carbon–ESV interactions with scenario-based prediction and evaluation, this study provides new insights into oasis sustainability, offers a scientific basis for balancing agricultural production with ecological protection in the oasis of the arid region, and informs China’s dual-carbon strategy, as well as the Sustainable Development Goals.

Quantifying the impacts and contributions of nitrogen (N), phosphorus (P), and potassium (K) fertilizer management on the annual and cutting cycle yields of alfalfa can provide guidance for alfalfa cultivation. In this study, 597 sets of alfalfa yield data from the arid and semi-arid regions of China were collected and grouped according to the N, P, K, and NPK rates. Statistical and meta-analyses were employed to explore the response of alfalfa yield to fertilization management. The results indicated that the annual and cutting cycle yields of alfalfa increased and then decreased as the N rate increased; meanwhile, the annual yield increased with the P and K rates, and the cutting cycle yield decreased with increased cutting cycles under P and K treatments. The alfalfa yield at the first cutting cycle was about 30% of the annual yield in the arid and semi-arid regions of China. Moreover, the annual yield increased and then decreased as the NPK rate increased. The Aggregated Boosted Tree (ABT) algorithm-based analysis showed that the NPK rate had the greatest contribution to the annual yield (37.61%), followed by the application rates of P (24.50%), N (22.55%), and K (15.34%). The impacts of the P/NPK, N/NPK, and K/NPK ratios on the annual yield were 38.64%, 31.71%, and 27.65%, respectively. Additionally, an NPK amount > 225–310 kg/ha and ratios of N, P, and K of 14.28–27.72%, 36.36–50%, and below 25%, respectively, resulted in the highest increase in alfalfa yield. This is recommended as the optimal fertilization practice to obtain high alfalfa yields and improve fertilizer use efficiency in the arid and semi-arid regions of China.

Tris(2-chloroethyl) phosphate (TCEP), as an organophosphate contaminant, poses a significant threat to the growth and development of plants, especially roots. This study aimed to clarify the mechanisms of TCEP’s toxicity and damage to root systems, as well as the mechanisms of its damage to the respiration and energy metabolism of alfalfa root cells. The results showed that TCEP obviously affected the root length, root surface area, root volume, and root diameter of alfalfa. With increasing stress intensity, the total mitochondrial respiration rate and Cytochrome C Oxidase (COX) pathway respiration rate progressively declined, while the Alternative Oxidase (AOX) pathway respiration rate and its proportion of total respiration gradually rose. In addition, adenosine triphosphate (ATP) content and root vigor were significantly reduced. Moreover, with an increase in TCEP concentration, root superoxide anion radical content in alfalfa root cells was significantly elevated, while superoxide dismutase (SOD) and catalase (CAT) activities were significantly lowered, and ascorbate peroxidase (APX) and peroxidase (POD) activities were significantly enhanced. The present study indicated that respiration was disrupted, causing a lack of ATP in root cells under TCEP. Both the overproduction of reactive oxygen species (ROS) from the mitochondrial respiratory electron transport chain (mECT) and the deficiency of ROS-scavenging enzymes caused ROS accumulation, which led to the destruction of the cell membrane structure and exacerbated the disruption of the respiratory metabolism. The disruption of the conversion and reuse of energy by TCEP affected root growth and development.