Journal of Agronomy and Crop Science最新文献

Drought-induced osmotic stress reduces the growth and yield of bread wheat (Triticum aestivum L.) worldwide. Several genotypes of its wild relative, goatgrass (Aegilops biuncialis Vis.) are often tolerant to environmental stresses and used as a gene source for wheat improvement. The Aegilops accessions Ae.b. 382 and Ae.b. 642 collected from contrasted agroecological habitats may represent different defence mechanisms to osmotic stress compared to three bread wheat genotypes with various drought tolerances. The effect of a 1-week 15% polyethylene glycol (PEG) treatment on various physiological and biochemical parameters was compared at the 2-leaf stage. The osmotic stress-induced reduction in shoot length and fresh weight in all genotypes except for Ae.b. 382. This tolerance of Ae.b. 382 can derive from the greater PEG-induced accumulation of the antioxidant hydroxymethyl-glutathione in the shoots compared to other genotypes. It is due to an elevated synthesis of its precursors, cysteine and gamma-glutamylcysteine. In addition, the level of oxidative stress was smaller in Aegilops biuncialis genotypes, shown by the decrease in H₂O₂ and GSSG levels in roots and shoots, respectively. The amount of gamma-glutamylcysteine was greater in their roots than in the wheat genotypes. Furthermore, PEG treatment resulted in a greater level of putrescine, as well as the expression of defence-related genes encoding Glutathione Reductase (GR), cold-regulated protein Wcor and DihydroFlavonol-4-Reductase (DFR) in the shoots of both Aegilops accessions compared to the three wheat genotypes. Based on these differences, certain Aegilops genotypes may serve as a genetic source for the improvement of the stress tolerance of bread wheat.

In order to screen out agronomic traits closely related to drought resistance of cotton, seven agronomic traits were measured, including morphological traits: plant height (PH), first vegetative shoot length of single plant (FVSL) and all vegetative shoot length of single plant (AVSL), and yield traits: boll number (BN), single boll weight (SBW), lint percentage (LP) and seed cotton yield (SCY). All agronomic traits were significantly affected by drought stress, and the morphological traits were significantly correlated, while the yield traits were opposite. Among them, the plant height and seed cotton yield were closely related to drought resistance of cotton. Comprehensive drought resistance coefficient (CDC), comprehensive drought resistance comprehensive evaluation value (D) and weighted drought resistance coefficient (WDC) value are the three comprehensive evaluation indexes of drought resistance. This study is the first to systematically validate that the D value is more scientific to reflect the differences between various agronomic traits and drought resistance of cotton than the CDC value and WDC value. Among the 199 cotton genotypes, there were large differences in drought resistance, and by using cluster analysis, they were divided into five groups: high drought resistance, drought resistance, medium drought resistance, drought-sensitive and high drought sensitivity groups. Four cotton genotypes with high drought resistance were selected; UC072 and UC002 can be widely used as drought resistant genotypes with high yield.

Root system architecture (RSA) is crucial to plant adaptation and the efficiency of soil resource acquisition. However, the RSA variation in okra remains fundamentally uncharacterised. This study aimed to fill this knowledge gap by investigating genetic variability, heritability, and trait associations of RSA characteristics across sixty okra genotypes using a rhizobox-based phenotyping system that evaluated over 30 RSA traits. There was genotypic variation with coefficients of variation ranging from 5% to 70%. Most traits (76%) demonstrated high broad-sense heritability (> 60%), particularly those important for capturing soil resources, including total root length, surface area, and volume. Genetic and phenotypic coefficients of variation were predominantly intermediate (10%–20%) to high (> 20%), except for lateral root angle and primary root length, which showed low variation (< 10%). The first four principal components explained 81.7% of the total genotypic variation, with root perimeter, surface area, and volume as the primary contributors to the diversity in the RSA. There were two genotype groups with contrasting RSA ideotypes independent of the geographical origin of the germplasm. There were moderate to very strong, significant positive associations among many RSA and biomass traits (r = 0.51–0.99; p < 0.001). However, the mean root diameter exhibited weak negative but non-significant correlations with several characteristics. Notable genotypes were identified for specific RSA traits: VI063895 (0.39 and 0.40 g), VI060692 (0.32 and 0.33 g), and GH154 (0.30 and 0.34 g) for superior root biomass allocation; GH108 (2032.28 and 1895.14 cm) for maximum root length; GH111 (25.14 and 20.80 cm³), GH121 (23.56 and 24.59 cm³), and GH157 (18.54 and 19.06 cm³) for enhanced root volume; VI060691 (60° and 62°) and GH125 (61° and 59°) for steep lateral root angles; and V1063895 (10,899 and 10,873), GH135 (9464 and 9330) and GH102 (9303 and 9441) for branching architecture across the two trials. This study advances our understanding of okra RSA diversity, laying the groundwork for trait-based breeding strategies that enhance adaptation to resource-limited environments. The identified genotypes represent diverse RSA ideotypes that offer the potential for improving nutrient and water use efficiency.

Climate change presents challenges to agriculture globally, necessitating to develop resilient production systems to safeguard food security, farm incomes and environmental sustainability. This review synthesises current strategies to raise climate resilience, with a focus on climate-smart agricultural practices, the selection and planting of stress-tolerant crop varieties and efficient water management. The review provides a critical analysis of biotechnological tools including gene editing through CRISPR-cas9 and marker-assisted selection that enable rapid development of region-specific crop improvements. The review also examines the under-explored approaches such as the use of beneficial stress-tolerant microbes, diversified cropping systems, and conservation agriculture. By integrating case studies from multiple geographic regions, it presents a comparative synthesis of context-specific successes and challenges. We suggest a framework to align technological innovation with policy support, farmer education and participatory stakeholder engagement. Special attention is given to the needs of smallholder farmers in climate-vulnerable regions. The review concludes by outlining actionable priorities, including the expansion of climate data services and the integration of ecological management practices to balance productivity with ecosystem health.

Low light conditions, caused by prolonged cloudy and rainy weather during the grain-filling stage, lead to significant reductions in rice quality and yield. However, the molecular mechanisms underlying grain filling under low light remain poorly understood. In this study, two Japonica rice varieties, Xinfeng 6 (Xin 6; low light–tolerant) and Nipponbare (NP; low light–sensitive), were employed to investigate these mechanisms. Under low light conditions, Xin 6 exhibited less pronounced changes in 1000-grain weight, chalkiness, starch and storage protein content, and endosperm starch granule structure compared to NP. Transcriptome analyses revealed that the number of genes regulated by low light in NP grains was approximately threefold higher than that in Xin 6 grains. Notably, a significant number of genes associated with sucrose-starch synthesis, glycolysis, and abscisic acid, calcium, and mitogen-activated protein kinase signalling pathways were downregulated in NP but remained unaffected in Xin 6. Gene network analyses suggest that Tre6P signalling integrates respiration, starch synthesis, low-temperature response and trehalose synthesis in grains under low light. These findings provide novel insights into the molecular mechanisms of low light tolerance in rice.

Physiological and photosynthetic nitrogen use efficiency responses to early drought and their contribution to yields in diverse sugarcane genotypes are understudied. This study examines the physiological responses, photosynthetic nitrogen use efficiency (PNUE), and their relationship with yields in various sugarcane genotypes during early drought and recovery periods, providing information relevant to breeding drought-resistant sugarcane. The experiment was arranged in a split-plot in RCBD with three replications. The main plot was two water regimes (i) well-watered (WW) and (ii) early drought stress (DS), whereas the subplot consisted of six sugarcane genotypes in plant cane and ratoon cane. Relative water content (RWC), SPAD chlorophyll matter reading (SCMR), stomatal conductance (gs), photosynthetic rate (Pn), PNUE, and crop growth rate (CGR) were measured during drought and recovery periods. While cane, sugar, and fiber yield were collected at the final harvest. The results indicated that drought stress reduced RWC, SCMR, gs, Pn, PNUE, and CGR. Furthermore, early drought reduced cane, sugar, and fiber yields, as well as CCS levels. After rewatering, RWC, Pn, gs, PNUE, and CGR quickly recovered in only F03-362 genotype. PNUE significantly contributed to CGR under DS conditions and enhanced cane yield during drought. Under DS conditions, F03-362 maintained high PNUE and GCR, while F03-362 and KK09-0358 sustained high PNUE and cane yield. Interestingly, F03-362 as an F1 hybrid showed a good recovery efficiency for Pn, PNUE, and GCR, resulting in a high cane yield. Breeders can use this genotype as a parent in sugarcane breeding for drought resistance, with PNUE and CGR serving as selection criteria. Understanding the water stress-response mechanisms of diverse genotypes is key to successful drought-resistant breeding.

Canopy resistance (r_c) is a vital parameter for further estimating crop evapotranspiration (ET_c), and Jarvis model is one of the most widely used models to estimate r_c with parameterizations based on the environmental factors and leaf area index (LAI). However, previous researches on the Jarvis model mainly focused on optimising environmental parameters, which could not explain the great fitting disparity for the r_c estimations of distinct crop species and the uncertain model performances in different growing stages. Therefore, we modified the effective leaf area index (LAI_e) in Jarvis model using a multi-layer method in which we measured stomatal resistance (r_s) and LAI at different layers (0–50, 50–100, 100–150 and 150–200 cm of plant height) of greenhouse cucumber to calculate LAI_e to describe the influences of leaf spatial distribution and photosynthesis efficiency. We compared the performances of the improved and the original Jarvis models on r_c estimation and found the coefficient of determination (R²) and root mean squared error (RMSE) of 0.68 and 163 s m⁻¹, 0.64 and 171 s m⁻¹, respectively, the corresponding errors for hourly ET_c calculation were 0.81 and 0.10 mm h⁻¹, 0.88 and 0.098 mm h⁻¹, respectively. The accuracy of both models gradually raised with the increasing in LAI, and an obvious improvement on ET_c estimation appeared when LAI ≤ 1 m² m⁻² with R² = 0.81 for the improved Jarvis model while R² = 0.77 for the original Jarvis model. Although the accuracy of the improved Jarvis model was not prominently increased for all growing stages, the improved Jarvis model is of great significance in considerations of crop physiological and growth diversity to enhance the model adaptability for distinct crops and reduce the uncertainty of model performance for different growing stages.