Research Papers

Chemical characterization and biological activity of Curvularia Lunata, an endophytic fungus isolated from lemongrass (Cymbopogon citratus). Braz J Microbiol

Kaur Mehak, Mishra Rahul C., Lahane Vaibhavi, Kumari Anita, Yadav Akhilesh K., Garg Monika, Barrow Colin J., Goel Mayurika

Exploration of medicinal plants for bioactive-producing endophytic fungi is a relatively unmapped source of pharmaceuti¬cally important compounds. In this study, the endophytic fungus Curvularia lunata AREF029 isolated from the medicinal plant Cymbopogon citratus (known as lemongrass) was assessed for its biological activity. The methanolic extract of AREF029 had minimum inhibition concentration (MIC) ranging from 38 to 174 μg/ml against phytopathogenic fungi Alteranria solani, Fusarium oxysporum and Rhizoctonia solani.

An Overview of Pigmented Bioactive Products from the Genus Cordyceps

Kaur Mehak , Goel Mayurika

| 2025

The demand for natural colorants in the food, textile, cosmetic, pharmaceutical, and other industries has increased due to the adoption of environmentally friendly alternatives to non-sustainable resources. Microorganisms are preferred over other biological resources because of their high stability, water solubility, year-round availability, and cost-effectiveness. Fungi are prolific producers of a myriad of pigments with therapeutic benefits.

Artificial Intelligence in Climate Resilience: Evaluating Contributions to SDG 13

Sharma Reeta, Shekar Alpana C

| 2024

In recent years, there has been a significant increase in artificial intelligence (AI) approaches for Sustainable Development Goals (SDGs), particularly SDG 13: Climate Action. Several AI technologies, such as machine learning, deep learning neural networks, and big data analytics present new tactics to tackle the complex problems of climate change.

Spatial variation of biochar production potential from surplus crop residues in India

Datta Arindam , Dutta Sutapa , Sharma Shivani , Rahman Md.Hafizur

| 2025

India faces environmental issues due to large-scale seasonal in situ burning of crop residues, leading to air pollution and nutrient loss. Biochar application can increase soil carbon content, moisture, and nutrient content while reducing air pollution. India produces 156 Mt. of annual in situ surplus crop residues from ten major crops, with the highest potential for rice residue biomass in Sangrur, Punjab. Biochar could reduce greenhouse gas emissions by 405 Tg annually and its application to soil could sequester 7.5 Tg of carbon.

GIS and ML-Driven Insights into Forest Vulnerability and Climate Hotspots in Assam, India

Ghosh Sayanta , Warman Aakash , Chauhan Pranjul , Soni Aniruddh , and Sharma Jitendra Vir

| 2025

This study assesses the impact of regional climate variability on forest vulnerability in Assam using a GIS and Machine Learning (ML)-based approach. A grid-based Forest Vulnerability Index (FVI) was developed using eight key indicators, and climate change hotspots were mapped using temperature and precipitation anomalies. The results revealed that 87 forested grids are highly vulnerable, with significant overlaps between climate hotspots and biodiversity risk zones.

Remote Sensing and Machine Learning-based assessment of Forest Biomass Changes in Pench Tiger Reserve, Maharashtra, India

Ghosh, S., Zaidi, A., Chauhan, P., Soni, A., & Vir Sharma, J. V

| 2024

This study evaluates spatio-temporal variations in forest biomass in the Pench Tiger Reserve, Maharashtra, India, using a combination of remote sensing, field-based observations, and machine learning approaches. Fractional Vegetation Cover (FVC) layers were generated using the Linear Spectral Unmixing (LSU) Algorithm applied to multi-temporal LANDSAT data (2001-2022). A Linear Regression Model (LRM) was developed to estimate forest biomass across three forest strata: Very Dense Forest (VDF), Moderate Dense Forest (MDF), and Open Forest (OF), based on field sampling plots.

Technical note on steps in baseline quantification for ARR carbon finance projects using remote sensing and GIS.

Ghosh Sayanta, Sharma Jitendra Vir

| 2024

This technical note outlines a systematic approach to baseline quantification for ARR (Afforestation, Reforestation, and Revegetation) carbon finance projects using advanced remote sensing (RS) and GIS methodologies. This approach particularly addresses India's fragmented landscapes, aiming to integrate small and marginal farmers into carbon finance markets, thus enhancing agroforestry potential and providing additional income generation.

Advancing India’s Agroforestry Potential: Leveraging Technology and Community Approaches for Sustainable Development

Ghosh Sayanta, Sharma Jitendra Vir

| 2024

Agroforestry, a sustainable land management practice integrating trees with crops and livestock, holds immense potential for climate change mitigation and enhancing rural livelihoods in India. This article explores the synergy between advanced Remote Sensing (RS) technologies, such as vegetation indices like NDVI, and participatory approaches involving Farmer Producer Organizations (FPOs), cooperatives, and other farmer collectives.

Assessing forest biomass changes in Pench Tiger Reserve, Maharashtra, India with remote sensing and machine learning approaches

Ghosh, Sayanta, Zaidi, A., Chauhan, P., Soni, A., & Sharma, J. V.

| 2024

This study explores the use of remote sensing and machine learning approaches to monitor forest biomass changes in the Pench Tiger Reserve, Maharashtra, India. It integrates Earth observation data and advanced computational models to assess biomass dynamics, providing critical insights into forest management and conservation efforts. The research underscores the potential of geospatial technologies in supporting sustainable practices, biodiversity conservation, and carbon sequestration initiatives, aligning with India's commitments to environmental sustainability.

Turning trash into treasure: conversion of agroresidue rice straw into carboxymethylcellulose biopolymer

Kaur Prabhpreet , Bohidar Himadri B., Williams Richard , Pfeffer Frederick M. , Agrawal Ruchi

| 2024

In the present study, rice straw-derived cellulose was converted into carboxymethylcellulose (CMC) using alkalization followed by an etherification reaction. The synthesis conditions for this chemical modification were optimized such that CMC with a high degree of substitution (1.02) was obtained. Infrared spectra of the synthesized CMC clearly showed an increased intensity of the C═O bond at 1600cm−1, confirming successful carboxymethylation.