Maintaining soil health and crop productivity in the semi‐arid Vertisols of central India poses a significant challenge under intensive agricultural practices. This 6‐year field study assessed the combined impact of different tillage methods, maize‐based crop rotations, and nitrogen management on soil's physical, chemical, and biological characteristics, soil quality indices (SQI), and crop yields. The experiment used a split‐split‐plot design, featuring no‐till (NT) and conventional tillage (CT) as the main treatments, maize‐wheat and maize–chickpea rotations as sub‐treatments, and four nitrogen levels (0%, 50%, 100%, and 150% of the recommended dose) as sub‐sub treatments. Compared to CT, NT significantly increased soil organic carbon by 13%–21%, the mean weight diameter of aggregates by 29%–32%, available phosphorus by up to 110% in surface soils, and microbial activity, as evidenced by a 15% rise in dehydrogenase activity and a 5%–16% increase in
β
‐glucosidase activity in the 0–5 cm layer. There were strong positive correlations between SOC and aggregate stability (
r
= 0.78) and nutrient availability (
r
= 0.70–0.78), underscoring the crucial role of organic matter in soil function. The maize‐wheat rotation consistently surpassed maize‐chickpea in soil quality metrics due to higher residue retention, while nitrogen fertilization showed a dose‐dependent enhancement in soil properties and crop yields. Grain yields of maize, wheat, and chickpea under NT were 21%, 15%, and 31% higher, respectively, than under CT. Although the highest yields were achieved at 150% N, the 100% N rate offered a favorable balance between improving soil health and sustaining yields. Overall, the study illustrates that long‐term use of no‐till, combined with a residue‐rich maize‐wheat rotation and optimized nitrogen management, significantly enhances soil quality, carbon sequestration, and crop productivity in semi‐arid Vertisols, providing a viable approach for sustainable intensification in similar agroecological areas.
N. K. Sinha, M. Mohanty, S. Jayaraman et al.· Land Degradation & Devel...· 0 citations
Climate change is intensifying drought, salinity, heat, chilling, flooding, and heavy-metal stresses across major fruit-producing regions, threatening yield stability and fruit quality in economically vital, perennial crops such as apple, grapevine, citrus, banana, strawberry, and peach. Because these species are long-lived, highly heterozygous, and polyploid, conventional breeding for climate resilience remains slow and often inadequate, necessitating molecular strategies informed by systems-level understanding. This review synthesizes recent advances in multi-omics research spanning genomics, transcriptomics, proteomics, metabolomics, epigenomics, ionomics, and phenomics that have collectively decoded the regulatory architecture underlying abiotic stress perception, signaling, and tolerance in fruit crops. Hormonal networks, particularly abscisic acid (ABA) crosstalk with jasmonate, salicylic acid, ethylene, and brassinosteroids, emerge as central integrators of stress responses, coordinating stomatal regulation, osmolyte accumulation, antioxidant defense, and secondary metabolite biosynthesis. Genomic and pangenomic approaches have identified stress-associated loci and cultivar-specific structural variants, while transcriptomic and proteomic studies reveal transcription factor networks (MdERF38–MdMYB1, MaMYB4–MaHDA2, VvDREB1, CsNAC29) and post-translational regulatory switches governing tolerance mechanisms across drought, cold, salinity, and flooding stress. Metabolomic and ionomic profiling link biochemical reprogramming to fruit quality traits, whereas epigenomic mechanisms including DNA methylation, histone modifications, and small RNA regulation provide a chromatin-level layer mediating stress memory across growing seasons. Integration of these omics layers through systems biology, machine learning, and high-throughput phenomics is enabling functional validation via CRISPR-Cas9 and marker-assisted selection, translating correlative associations into causally validated breeding targets. Despite this progress, challenges including batch effects, tissue heterogeneity, and methodological inconsistencies in data integration continue to constrain translational applications. This highlights convergent regulatory hubs across stress types and species, underscoring multi-omics-guided precision breeding as the most promising pathway toward developing climate-resilient, high-quality fruit crop cultivars for sustainable global production.
