Teak (Tectona grandis, Linn.f) is one of the most sought-after tree crops due to the exceptional quality and high market value of its timber. Currently, the Indian subcontinent imports a significant quantity of teak to meet its growing demand. The growth and wood quality of teak are influenced by edaphic and climatic variations across sites, a factor that has been largely underexplored in research. The primary objective of the study is to analyse teak growth, wood quality, and carbon sequestration potential under farmland condition. To address this, the study was conducted across three agroclimatic zones of Tamil Nadu: North Eastern Zone (NEZ), North Western Zone (NWZ), and Cauvery Delta Zone (CDZ), focusing specifically on farmland conditions. The analysis encompassed biometric attributes, volume, and carbon sequestration potential of farm-grown teak across different age classes. The findings of the study reveal that among the three agroclimatic zones, the NEZ (15-20 years age class) recorded the highest biometric attributes, including mid diameter (MD) (0.193 m), volume (0.379 m3), heartwood proportion (0.239 m3), and carbon sequestration (0.683 Mg/acre).. Based on the overall performance, trees in the 15-20 years age class exhibited superior heartwood formation under farmland conditions. Therefore, this age class is recommended for teak cultivation in farmland conditions across Tamil Nadu to maximize growth, wood quality, and carbon sequestration potential.

Biochar is a carbon-rich product that is produced by pyrolysis of organic biomass like forestry waste, animal manure and crop residues in low oxygen conditions using thermochemical processes like pyrolysis, torrefaction, gasification. Slow pyrolysis is most widely utilized among them due to its increased yield and carbon stability. Properties of biochar such as pH, surface area, porosity and nutrient content depend on the feedstock and production conditions. As a green and sustainable solution, biochar finds applications across multiple sectors. In forestry, it enhances soil porosity, water retention capacity, nutrient supply and microbial activity, which stimulates forest regeneration and reduces forest fire risks. In agriculture, biochar enhances soil fertility, agricultural yields, minimizes fertilizer use and leaching of nutrients. Biochar also plays a significant role in climate change mitigation by sequestering carbon in soils for long periods and reducing greenhouse gas emissions such as methane and nitrous oxide. In environmental remediation, its porous structure allows for the adsorption of heavy metals and organic pollutants from soil and water. In the energy industry, biochar is used as a solid renewable fuel or as a byproduct of syngas-producing or bio-oil producing systems. All these multi-variant uses make biochar a powerful instrument for circular economy initiatives, sustainable land management and climate action. With continued research and policy support, biochar presents a potential route toward ecological restoration and stable ecological conditions.

Biomass estimation is pivotal in understanding and managing global carbon stocks, offering vital insights into climate change and environmental ecology. It serves as a critical tool for evaluating carbon sequestration potential, a natural mechanism for regulating atmospheric carbon dioxide levels. Accurate estimation of forest biomass not only aids in quantifying carbon stocks but also provides a basis for sustainable forest management, conservation efforts, and policymaking to mitigate climate change impacts. This article provides a comprehensive review of various biomass estimation methods, including ground-based measurements, remote sensing technologies, and hybrid approaches. Each method's strengths, limitations, and practical applications are critically examined, highlighting their suitability for different spatial scales and ecological contexts. Traditional methods, while precise at small scales, are often labour-intensive and limited in coverage. In contrast, remote sensing technologies such as LiDAR, RADAR, and hyperspectral imaging have revolutionized biomass estimation by enabling large-scale and high-resolution assessments. Additionally, recent advancements in machine learning, data fusion, and satellite-based monitoring systems are transforming the field, offering unprecedented accuracy and efficiency. By presenting these trends and innovations, this article provides valuable insights for researchers, practitioners, and policymakers, emphasizing the importance of integrating advanced technologies into biomass estimation for sustainable development and climate resilience.

Studying the carbon stock of tree plantations is essential for mitigating climate change, as trees act as carbon dioxide sinks by fixing carbon during photosynthesis and storing excess carbon as biomass. With a significant emphasis on the role of carbon in global warming, Afforestation/Reforestation (A/R) activities have the potential to provide a “sink” for carbon from our atmosphere and act as a reservoir. In current study, the sequestered carbon dioxide from atmosphere by Casuarina plantations was calculated and converted into carbon by a particular plantation using the globally accepted formula developed by the IPCC. Simultaneously, the soil organic carbon of the particular Casuarina plantations was also estimated. Finally, the carbon stock of Casuarina equisetifolia plantations were estimated under different management practices. The various management practices like pruning, irrigation and fertilizer application also improves the carbon sink potential of the tree plantations. The mean carbon concentration ranged from 41% (leaf litter) to 46% (wood) in the different components of Casuarina equisetifolia. The plantations recorded a carbon accumulation of 9.12 Mt C ha?¹ year?¹ in biomass components alone at the harvest age of 3 years in the tropical region of Tamil Nadu, India. Proper management practices in tropical regions worldwide have the potential to further enhance carbon stocks in plantations. This data will be ready reckoner for future Clean Development Mechanism (CDM) projects for controlling global warming.

This study investigated the nutritional composition and anti-nutritional factors of Senna spectabilis as a potential fodder for animal feed. Key parameters such as crude protein, crude fiber, dry matter, digestibility and anti-nutritional factors like phenols, tannins, saponins and nitrates were analyzed from the five formulations named from SS1 to SS5. The results showed significant variations across the species in terms of digestibility and energy content, with formulations SS1 and SS4 demonstrating superior digestibility and higher Total Digestible Nutrients (TDN). On the other hand, formulation SS5 exhibited higher crude fiber content and lower digestibility, making it less efficient as a feed source. Anti-nutritional factors such as saponins and nitrates were found to be highest in formulation SS1, which could affect feed intake and livestock health if present in excessive amounts. The study also noted moderate levels of tannins and phenols in several species, which could impact nutrient absorption for animals. Additionally, concentrate feed mixtures were considered in comparison to fodder-based feeds for their influence on livestock growth and performance. These findings suggest that careful selection of feed ingredients, considering both nutritional and anti-nutritional parameters, is essential for optimizing livestock nutrition. Formulations with lower levels of anti-nutritional compounds like SS2, offer more sustainable feed options, while further research is required to understand the effects of these compounds on livestock health and performance.

Background: Melia dubia is a promising tree species in industrial agroforestry and plantation systems across southern India and is popular for its fast growth and economic potential. Choosing a suitable intercrop for an agroforestry system determines the longevity and viability of the system. This study was carried out to explore the feasibility of cluster bean cultivars as an intercrop in Melia dubia -based agroforestry system. Methods: A trial was conducted by comparing three cluster bean varieties such as, Sonali, Pusa Navbahar and MDU 1, under Melia dubia with three treatment conditions representing: open field conditions, as an understorey in three-year-old M. dubia and six-year-old M. dubia plantations. Result: In three-year-old Melia dubia plantation, the light intensity recorded by cluster beans was reduced to 78.12% (65,000 lumen per square metre) for MDU 1, 76.44% (63,600 lumen per square metre) for Pusa Navbahar and 74.51% (62,000 lumen per square metre) for Sonali when compared to the control and the pod yields for the three varieties were recorded as 10.15 t/ha, 9.28 t/ha and 7.86 t/ha, respectively. The benefit cost ratios of cluster bean varieties in three-year-old plantations were 1.43, 1.38 and 1.21, respectively. Overall, the yield attributing parameters such as flowers/cluster, pods/cluster, number of pods, pod length were greater in the MDU1 variety than in the other two varieties. Thus, intercropping cluster bean cv. MDU1 as an understorey in M. dubia plantations can maximize land utilization and yield the greatest returns.