2026-04-02
Sudha Verma, Manpreet Kour, Vijay Kumar, Simrandeep Kour, Bhim Singh
An experiment was carried out during the Kharif season of 2023 in the sub- tropical climate of Jammu in the Siwalik foothills ofnorth-west Himalaya. The soil was sandy clay loam, slightly alkaline, low in organic carbon, available nitrogen, zinc and mediumin accessible potassium and phosphorus. A factorial randomized block design with three replications was used with two factors,i.e, Factor A, which included two varieties, viz., V1- SSG and V2- CSV 33 MF and Factor B consisting of eight zinc fertilizationtreatments. N:P2O5:K2O @ 60:40:20 kg ha-1 was applied uniformly to all the treatments. CSV 33 MF (V2) variety had the noticeablygreatest crop growth metrics and crude protein at all the harvesting intervals. However, RDF + soil application of ZnSO4 @ 20 kgha-1and foliar application of ZnSO4 at 0.5% at 40 DAS and 80 DAS (F8) proved superior in terms of growth parameters and crudeprotein which was statistically at par with F6 at first cut and F7 at second and third cut. With regard to quality traits, numericallylowest NDF, ADF, hemicellulose, crude fibre and highest values of ether extract, ash content, DDM, DMI, RFV, RFQ and TDNwas recorded under CSV 33 MF (V2) and RDF + soil application of ZnSO4 @ 20 kg ha-1 and foliar application of ZnSO4 at 0.5% at40 DAS and 80DAS (F8). The findings indicate that variety CSV 33 MF with RDF + soil application of ZnSO4 @ 20 kg ha-1 + foliarapplication of ZnSO4 at 0.5% at 40 DAS and 80 DAS is more suitable for increased fodder quality.
2026-03-24
Rudragouda, G. K. Girijesh, J. S. Nagaraja, H. K. Veeranna, Adivappar Nagarajappa, G. M. Devagiri, Somshekargouda Patil, Kishore Mote, M. Dinesh Kumar
In coffee-based agroforestry systems under diverse shade tree patterns in Kodagu, Central Western Ghats, India, tree diversity and carbon stock were investigated in both Coffea arabica and Coffea canephora plantations spanning 4106 km2 during 2023-24 and 2024-25. Six distinct shade patterns in coffee agroforestry systems were identified in this study based on the combination of coffee species and shade-tree composition. Two coffee species (C. arabica and C. canephora) were evaluated under three shade-tree types: native species, mixed species (native + exotic) and exotic species (Grevillea robusta). These six shade patterns were assessed under three management regimes: low, medium, and high. Field enumeration recorded tree density, basal area, species richness and structural attributes using nested sampling approaches. Biodiversity indices such as the Shannon-Wiener index (SWI) and Simpson’s index (SI) evaluated species diversity and dominance, revealing maximum biodiversity in native and mixed shade systems than in exotic species-dominated systems. The carbon stock distribution was studied across above-ground biomass (AGB), below-ground biomass (BGB) and soil organic carbon (SOC). Arabica plantations recorded higher total biomass (362.43 Mg ha-¹) than Robusta (215.50 Mg ha-¹), with native and mixed shade systems outperforming exotic systems. SOC contributed over 50% to the total carbon stock, with significant variations across shade patterns and management regimes. Arabica systems showed higher carbon stock (353.06 Mg ha-¹) and CO₂ sequestration potential (1294.57 Mg C ha-¹) than Robusta systems (272.97 Mg ha-¹ and 1000.88 Mg C ha-¹, respectively). Native and mixed shade systems exhibited superior SOC accumulation and carbon sequestration potential (1212.02 Mg C ha-¹ and 1194.81 Mg C ha-¹) compared to exotic systems (1036.34 Mg C ha-¹). These findings highlight the ecological importance of native and mixed shade systems in enhancing biodiversity, carbon storage and soil health. The study advocates integrating native tree species for long-term sustainability and resilience in coffee agroforestry systems.
2026-03-24
S. K. Jain, Omprakash, Rajdeep Jajoriya, Vikas Khandelwal, S. K. Sharma, Vaibhav Vaibhav Sharma, B. L. Dhaka
An experiment was conducted during two seasons (summer and kharif 2024) to evaluate general and specific combining ability and heterosis in pearl millet using a line × tester mating design comprising 15 female lines, 9 male testers, 135 hybrids, and one check. The study aimed to identify superior parental lines and cross combinations for grain and fodder yield, along with micronutrient traits (iron and zinc content). Significant genetic variation was observed among parents, indicating diverse genetic potential. The variance due to specific combining ability (SCA) was higher than that of general combining ability (GCA), highlighting the predominance of non-additive gene action for most traits. Among the parents, ICMB-04888 and ICMB-97111 (females) and RIB-13 and RIB-1501 (males) emerged as good general combiners for multiple traits. Crosses such as ICMA-04999 × RIB-3135-18, ICMA-97111 × RIB-494, ICMA-88004 × RIB-15S076, and ICMA-94333 × RIB-192 showed superior grain yield. For fodder yield, ICMA-05999 × RIB-15S076 and ICMA-05999 × RIB-20K86 were the most promising. Hybrids ICMA-99444 × RIB-1501, ICMA-02333 × RIB-13, and ICMA-94333 × RIB-15177 recorded high iron content, while ICMA-94333 × RIB-15177, ICMA-04888 × RIB-1501, and ICMA-96666 × RIB-192 showed high zinc content. Notably, ICMA-97111 × RIB-494 was best for both grain yield and plant height; ICMA-05999 × RIB-15S076 for plant height and fodder yield; and ICMA-94333 × RIB-15177 for dual micronutrient content. These superior hybrids hold significant potential for grain, fodder and biofortified pearl millet breeding programmes, especially under dryland and agroforestry-based farming systems.
2026-03-24
Mech A., Letha Devi G, M. Sivaram, A. P. Kolte, P. K. Malik, N. M. Soren, S. B. N. Rao, A. Dhali, Maya G
Feed management plays a crucial role in mitigating greenhouse gas (GHG) emissions from livestock production systems. Despite India possessing one of the largest sheep populations globally, information on the environmental impacts of sheep production remains limited. The present study was conducted in Karnataka, South India, where over 400 sheep from 18 semi-intensive flocks were monitored over a two-year period. A cradle-to-farm-gate life cycle assessment (LCA) approach was employed in accordance with ISO 14040/44 standards, using IPCC Tier 2 methodologies to quantify GHG emissions. Feed carbon footprint (CF) varied significantly across seasons, with the highest CF during winter (0.89 kg CO₂-eq day⁻¹ sheep⁻¹) and declining during the monsoon and post-monsoon (0.30–0.38 kg CO₂-eq day⁻¹ sheep⁻¹). Common grazing lands contributed 15 to 56% of total nutrient intake, depending on season, substantially reducing reliance on purchased feeds. Strategic incorporation of seasonal green fodder and crop byproducts lowered feed-related emissions by up to 55 to 65% and reduced per day per sheep feed costs up to 12.2%. The findings highlight the critical role of seasonal forage availability in reducing both emissions and production costs, particularly in dryland regions.
2026-03-24
Monica Tundwal, Ravish Panchta, Satyawan Arya, Neeraj Kharor, Sonu Langaya, Dalvinder Pal Singh
Precise selection of superior genotypes for yield and its attributing traits is of utmost importance for a successful breeding program, but the complex nature of yield makes this selection difficult. The present study was conducted at dry land research area, CCSHAU, Hisar, Haryana, India, during Kharif 2022 to measure the genetic diversity among the cluster bean genotypes and to select the diverse parents for recombination breeding. Data were recorded on 17 quantitative traits using 50 cluster bean genotypes. D2 analysis distributed all the genotypes into five clusters. Cluster IV had the maximum intra-cluster distance. The crossing among the genotypes of clusters I and III, III and IV, and I and IV would result in novel recombinants, as they showed high inter-cluster distance. In the PCA study, the first five principal components (PCs) had eigenvalues greater than one, and they cumulatively explained 83.29% of the total variation present in the original dataset. The first principal component (PC 1) explained 37.87%, while PC 2, PC 3, PC 4, and PC 5 explained 18.04, 12.90, 8.23, and 6.25% of the total variability, respectively. PC 1 has captured maximum variability for seed yield and its attributing traits, along with gum content. The genotypes, RGr 20-15, X 25, RGr 18-1, HG 884, RGr 20-7, HG 2-20, HG 19-4, HG 563, GD 567, and GG 1806, were the top-ranking genotypes upon PC analysis with high positive PC 1 scores.