Dinesh Kumar

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.

Currently, agroecosystems sustainability is mainly challenged by unsustainable agricultural practices that lead to land degradation and amplified climate change. About 25% of the World's total land area has deteriorated due to improper agricultural land management, resulting in ~24 billion tonnes of annual soil loss. Globally, soil erosion, mainly caused by high‐frequency tilling, crop residue removal or burning, poor pasture management, and inefficient crop rotations, is responsible for >40% of total land deterioration problems. Conservation agriculture (CA) seeks minimum soil disturbance, permanent soil cover, and crop rotation, which are indispensable for soil fertility restoration, carbon stabilization, increased soil biodiversity, and sustainable food production. In the last decades, the global annual adoption rate of CA was 7 M ha yr⁻¹. CA‐based soil and crop management practices enhanced water productivity, soil organic carbon, crop productivity, and energy use efficiency by 18%–66%, 12%–93%, 3.8%–76.2%, and 8.9%–40.2%, respectively, over conventional practices under diverse agroecosystems in India. Hence, adopting CA can avert/minimize the problem of land degradation and food insecurity by improving crop productivity and decreasing soil erosion, energy use, and carbon emission, besides maintaining soil physicochemical and biological health. Moreover, CA can be a sustainable way to ensure global food demand, achieve sustainable development goals (SDGs), and restore soil health, and multiple agroecosystem services. This study aims to provide in‐depth insights into the role of CA in restoring agroecosystem services, attaining SDGs, and ensuring global food security.

Various faulty farming practices and low-performance cultivars selection are reducing crop yields, factor productivity, and soil fertility. Therefore, there is an urgent need to achieve better nutrient dynamics and sustainable production by selecting more nutrient-responsive cultivars using efficient nutrient management. The present experiment aimed to enhance crop productivity, seed quality, nutrient efficiency, and soil nutrient dynamics through efficient nutrient management under different lentil cultivars. The experiment was laid out in a split-plot design, assigning three cultivars (viz. Sapna, Garima, and HM-1) in the main plots and ten nutrient management practices in the sub-plots, replicating them thrice. Results revealed that cultivar HM-1 recorded significantly higher seed yield (1.59–1.61 Mg ha^-1) and the uptake of N (67.2–67.6 kg ha^-1), P (6.8–7.0 kg ha^-1), K (13.8–13.9 kg ha^-1), Zn (60.4–61.1 g ha^-1), and Fe (162.5–165.2 g ha^-1) in seed compared to Sapna and Garima. Also, the cultivar HM-1 was more efficient in terms of partial factor productivity for NPK (PFP; 24.27–24.59 kg kg^-1), partial nutrient balance (PNB; 2.09–2.13 kg kg^-1) and internal utilisation efficiency (IUE; 11.64–11.85 kg kg^-1). The study showed that the lentil cultivar HM-1 could be successfully grown by substituting 50% RDN with organic manures,i.e., vermicompost, without compromising crop productivity and soil fertility, thereby sustaining soil-human-environment health.

Stray/wild animals can cause serious damages to crops, leading to accusations and counter accusations among villagers. In the Bundelkhand region of India, this problem is more severe due to “Anna Pratha,” that is, letting loose animals to open graze. Protective measures employed by farmers (barbed wire fencing, conventional fencing, etc.) are not fully effective and also require periodical maintenance, which involves additional costs and manpower. This necessitates the evolution of a cost-effective and long-term solution to minimize the problem. The current study seeks to evaluate the potential of thorny bamboo (Bambusa bambos) as a bio-fence creating deterrence to stray/wild animals at the ICAR—IISWC RC, the research farm of Datia, Madhya Pradesh, India. After 21 months of planting, bamboo plants attained the maximum plant height up to 4.47 m with the highest clump spread diameter of 30.50 cm. However, the growth of the bamboo bio-fence to be effective depends on the edaphic and management conditions. The findings revealed that planting bamboo at a distance of 80.00 cm in the continuous trench can be an effective bio-fence to avoid man–animal conflict. Huge crop losses were reported before the establishment of a bio-fence. In 2021–2022 (when bamboo plants turned into a closely spaced thicket, making a bio-fence), only two incidents of the invasion of animals were reported with no crop damage. The initial cost to develop a bamboo bio-fence was estimated at INR 5,796 for a length of 100 m. Therefore, the present study suggests that bamboo bio-fencing is an economical and effective crop protection measure against damage by wild/stray animals.

Due to the shifting course of the Brahmaputra River, the fluvial landforms of the Brahmaputra Valley of Assam, India, are prone to changes in landform and land use. For sustainable soil management under such conditions, it is crucial to have information about soil physicochemical and biological properties for different land uses. Therefore, the present study was conducted to investigate the soil physicochemical properties and soil microbial population across five major land uses under different landforms, such as paddy fields, banana systems, and arecanut cultivations in the alluvial plains; and rubber plantations and sal forests in the uplands, with varying slope gradients and soil depths (0–25 cm and 25–50 cm) in the lower Brahmaputra Valley. The results of the analysis of variance revealed that the effects of different landforms and land uses were found to be statistically significant on very labile soil organic carbon (VLSOC), available K, B, Fe, Mn, Zn, and Cu, and soil moisture content across two different soil depths. Paddy cultivated systems recorded the highest (1.23%) soil organic carbon (SOC), but these levels were statistically at par with other land use scenarios except for banana systems; whereas, forests and rubber plantations showed the highest VLSOC (0.38% and 0.34%, respectively,) and were significantly different from other land use scenarios. All soil microbial populations (bacteria, fungi, and actinomycetes) studied varied significantly in different land uses across varying soil depths. Perennial land uses under arecanut, rubber, and forest cultivations showed significantly higher microbial populations than paddy and banana systems. The principal component analysis (PCA) identified SOC, VLSOC, Cu, K, B, P, and the bacteria count as the major soil quality parameters of the study area. The results showed that landforms, land use, and management practices collectively affect soil properties. Therefore, soil management choices should take into consideration the landforms and land use for maintaining soil health and its sustainability.