Chaudhary Charan Singh Haryana Agricultural University

Understanding the spatial variability of soil microbiological properties is essential for optimizing nutrient cycling, enhancing soil fertility and promoting sustainable agriculture. Microbial processes are inherently heterogeneous, making it crucial to study their distribution patterns across cultivated landscapes. Therefore, a study was conducted in 2022–2023 at Deen Dayal Upadhyay Centre of Excellence for Organic Farming, CCS Haryana Agricultural University, Hisar, India in semi-arid region where eighty-nine surface soil samples were collected and subjected to comprehensive laboratory analysis to determine various soil physico-chemical and microbiological properties. The results revealed considerable variability in microbial activity, with microbial biomass carbon ranging from 190.02 to 462.74 mg/kg, dehydrogenase activity from 44.93 to 110.73 μg tri-phenyl formazan (TPF)/(g soil 24 h), phosphatase activity from 117.39 to 252.73 μg p-nitrophenyl phosphate (PNP)/(g soil h) and urease activity from 32.36 to 84.17 μg NH_4^ + -N/(g soil h). Semivariogram analysis through ordinary kriging demonstrated that exponential, gaussian and circular models were the best fit models for different soil microbiological properties with moderate to strong spatial dependence. Nugget values varied from 0 to 0.002 while sill values varied from 0.002 to 0.004. The semivariogram ranges varied markedly, with shorter ranges for dehydrogenase (102.36 m), urease (107.13 m) and phosphatase (123.81 m) activities, while microbial biomass carbon showed notably larger range (170.54 m). Four principal components (eigenvalues ≥ 1), accounting for 75.57

Zinc (Zn) deficiency remains a critical constraint to both wheat productivity and human nutrition, particularly in regions dependent on cereal-based diets. Agronomic biofortification, guided by the 4R Nutrient Stewardship framework Right Source, Right Rate, Right Time, and Right Place offers a pragmatic and scalable solution to enhance grain Zn content while sustaining yield. This review synthesizes current knowledge on Zn dynamics in soil-plant systems, its physiological and biochemical roles in wheat growth, and the agronomic strategies that optimize Zn use efficiency. Emphasis is placed on integrated nutrient management, novel fertilizer technologies (including nano-fertilizers), and genotype-specific responses to Zn application. Furthermore, the review highlights research gaps such as the need for field-scale validation of nanotechnology, microbial interactions, and human health impact assessments. A holistic approach combining precision agronomy, genetic potential, and emerging digital tools for precision zinc application is proposed to ensure sustainable Zn biofortification outcomes. This review demonstrates that integrating Zn biofortification with the 4R nutrient stewardship framework offers a practical and scalable roadmap for increasing zinc concentration in wheat grains, thereby enhancing dietary zinc intake and directly addressing hidden hunger in cereal-dependent populations.

Introduction This study aims to conduct a comprehensive transcriptome analysis of Grewia asiatica (Phalsa) to identify molecular markers and differential gene expression in leaf and root tissues. G. asiatica is recognized for its medicinal properties, attributed to its rich phytochemical profile, including antioxidant, anti-inflammatory, antimicrobial, and hypoglycemic effects. However, genetic insights into the molecular basis of these bioactive properties remain limited.Methodology High-throughput Illumina sequencing was performed, generating 32.97 million clean reads from roots and 33.96 million from leaves. A 98.75% complete de novo assembly yielded 41,678 unigenes. SNP and SSR markers were identified, and transcription factors across 100 families were characterized. Differential gene expression analysis was conducted, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Key differentially expressed genes (DEGs) were validated through qRT-PCR.Results A total of 316,613 SNPs were identified in roots and 247,967 SNPs in leaves. SSR analysis revealed 21,634 markers, with mononucleotide repeats being predominant. A total of 5,781 transcription factors (TFs) were characterized, including members of the C2H2, MYB-HB-like, and bHLH families. Differential expression analysis identified 4,643 DEGs, with flavonoid biosynthesis genes upregulated in leaves and lignin-associated genes upregulated in roots.Discussion GO and KEGG analyses highlighted significant enrichment of metabolic and biosynthetic pathways. The medicinal benefits of G. asiatica are linked to its antioxidant properties, which combat oxidative stress; anti-inflammatory effects, which may aid in arthritis relief; antimicrobial activity against pathogens; hypoglycemic effects for blood sugar regulation; and iron content, which is beneficial for anemia treatment.Conclusion This study provides valuable SNP and SSR markers and offers insights into the genetic mechanisms underlying the medicinal properties of G. asiatica. These findings support future molecular breeding programs and pharmacological research on this underutilized medicinal plant.

Fig (Ficus carica L.) is valued for its high nutritional content, adaptability to marginal environments, and cultural significance. The present study assessed morpho-pomological, yield-related, and nutritional characters of 10 fig genotypes under semi-arid conditions in western India, where high temperature and limited soil moisture impose significant challenges to fruit production, to identify superior accessions for breeding and dryland cultivation. Significant variation was observed in fruit yield (10.2-20.3 kg plant(-1)), total soluble solids (15.2-20.7 degrees Brix), and mineral content, with local genotypes CHESFG-3 and CHESFG-5 outperforming commercial cultivars. Multivariate analyses highlighted distinct trait groupings and the unique adaptability of local genotypes. The first two principal components explained 68.4% of total variation, effectively distinguishing genotypes based on fruit quality and mineral parameters. The integration of morpho-pomological and nutritional traits provided valuable insights into fig genetic resources, emphasizing the breeding potential of local germplasm for enhanced fruit quality, nutritional value, and resilience in dryland horticulture.

This study aimed to assess the genetic variability in Aegle marmelos Correa to develop trait-specific genotypes based on morphological and qualitative traits. The evaluation focused on both morphological and qualitative characteristics within the gene pool of this species. High phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed for traits such as shell weight, fruit weight, and pulp weight, indicating substantial genetic diversity and strong potential for selective breeding within the germplasm. Heritability estimates ranged widely, with fruit weight showing a low 0.07% and shell weight a high 92.23%, reflecting the significant impact of environmental factors on trait expression. Principal Component Analysis (PCA) revealed that the first principal component (PC1) explained 40.19% of the total variation, with an eigenvalue of 8.12. The first six principal components collectively accounted for 80.77% of total variability. Genotypes CHESB-25 and CHESB-29 exhibited the highest positive PC scores for PC1 and PC2, identifying them as superior selections. Cluster analysis identified six distinct clusters of genotypes, with Cluster V being the largest and Cluster VI the smallest. This clustering highlights the genetic diversity among the bael genotypes and provides a basis for breeding and selection strategies. Cluster IV emerged as the most promising, consistently showing the highest values for key attributes such as shell weight, fruit weight, and fruit yield per plant. Therefore, prioritizing Cluster IV is recommended for selecting superior varieties and developing new cultivars. The study also noted that fruit yield per plant positively correlated with traits like shell weight and fruit weight, emphasizing the importance of these traits for yield improvement. Conversely, negative correlations with seed percent, shell percent, and phenolic content suggest these traits may be less beneficial for enhancing yield. The hierarchical clustering heat map of the 101 bael germplasms offers a detailed perspective on the relationships between various traits and germplasms. The results offer vital information for creating A. marmelos cultivars with higher yields and better quality. For breeding programs, targeted selection is made possible by the discovery of important clusters and superior genotypes (CHESB-25 and CHESB-29). Given the high level of genetic variation found, hybridization may be able to improve desired characteristics like fruit output and weight. Overall, the findings offer important insights for selecting elite genotypes and advancing breeding programs.