Coordinates: 18°37′22.62″N 73°53′14.43″E / 18.6229500°N 73.8873417°E / 18.6229500; 73.8873417Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth, formerly Konkan Krishi Vidyapeeth, is an agricultural university at Dapoli in Ratnagiri district of the Indian state of Maharashtra. It was established on 18 May 1972 as Konkan Krishi Vidyapeeth, and got its present name on 12 February 2001 in memory of third Chief Minister of Maharashtra Shri. P. K. Sawant. Its research centre at Karjat has developed some patented varieties of rice. Its major focus areas are rice, horticulture and fisheries. In 1997, it received the Best Institute Award of the Indian Council of Agricultural Research.Dr. SD Sawant is the 14th Vice Chancellor of this University, he was appointed by Chancellor Ch. Vidyasagar Rao on 7 March 2019..
The production of activated carbon (AC) from biomass has gained significant research interest due to its dual benefits of environmental sustainability and promotion of the circular bioeconomy. Among various biomass sources, banana crop residues including pseudo stem, peel, leaves, and rachis have emerged as promising, renewable precursors for the synthesis of high-performance activated carbon. This review provides a comprehensive and integrated analysis of the production processes and emerging applications of banana waste-derived activated carbon. It covers the latest advancements in carbonization and activation techniques, along with key factors influencing the physicochemical, textural, morphological, functional, thermal and adsorption properties of the resulting materials. Special emphasis is placed on the use of banana-derived activated carbon in environmental pollutant adsorption to advanced fields such as energy storage, biosensing, catalysis, composite materials, electromagnetic shielding, and construction materials. A comparative evaluation of recent studies is presented, detailing preparation parameters, adsorption capacities, and product yields. The review concludes with insights into current challenges, research gaps, and future directions, highlighting the potential of banana crop waste as a sustainable feedstock for activated carbon production and its critical role in advancing environmental remediation and circular bioeconomy strategies.
Mangrove ecosystems are central to global climate mitigation and coastal resilience, yet their monitoring remains inherently complex due to tidal inundation, spectral ambiguity and persistent cloud cover across tropical regions. The emergence of cloud-based geospatial platforms, particularly the Google Earth Engine (GEE), has transformed mangrove remote sensing from scene-based analysis to scalable, multi-sensor, time-series frameworks operating at planetary scale. This study presents a systematic review and critical synthesis of 162 peer-reviewed studies published between 2017 and 2025, examining the structural evolution, methodological foundations and ecological implications of GEE-enabled mangrove research. Bibliometric assessment indicates rapid expansion of the field, reflecting a transition from early methodological experimentation to widespread application. Thematic evolution reveals a clear shift from two-dimensional extent mapping to increasingly dynamic and process-oriented analyses, including disturbance monitoring, hydroperiod assessment, biomass estimation and blue carbon quantification. Methodologically, the literature is strongly anchored in ensemble machine learning approaches, particularly Random Forest, supported by multi-sensor integration of optical time-series (Landsat, Sentinel-2) and Synthetic Aperture Radar (SAR) to mitigate atmospheric and tidal constraints. Despite these advances, critical structural limitations persist. Research output and study-area focus remain geographically concentrated in a limited number of countries, whereas several ecologically significant mangrove regions remain underrepresented, indicating a mismatch between research capacity and ecosystem distribution. Furthermore, although classification accuracy has improved substantially, persistent uncertainties arising from tidal variability, spectral similarity, training data bias and limited model transferability constrain ecological interpretation. These findings indicate that GEE has successfully enabled large-scale mangrove monitoring but has not yet fully translated computational advances into ecological understanding or operational decision-making. Future research should prioritize cross-regional model validation, the integration of structural datasets such as spaceborne light detection and ranging (LiDAR), and the development of interpretable, process-based frameworks to better connect remote sensing outputs with ecosystem functioning. Strengthening these directions is essential to ensure that GEE-based monitoring systems effectively contribute to global mangrove conservation, blue carbon accounting and climate-resilient coastal management.
Thrips parvispinus (Karny), a polyphagous thrips species, has recently emerged as an important pest threatening horticultural and agricultural crop production in several regions worldwide. Owing to its invasive nature, this species has expanded rapidly across different geographic regions and is now recognized as a serious pest affecting a wide range of crops in many countries. The successful establishment and spread of T. parvispinus have been associated with several factors, including its broad host range, high reproductive potential, reduced effectiveness of insecticidal control, limited natural enemy complexes, and dispersal facilitated through international trade and movement of plant materials. Although several studies have investigated different aspects of the biology, ecology, and management of this pest, consolidated information on T. parvispinus remains scarce in the available literature. A clear understanding of its biology, ecological adaptability, damage potential, and available management options is essential for developing effective preventive and curative strategies against this emerging pest in the future. This review synthesizes information on the taxonomy, global distribution, bioecology, host range, economic importance, preferred habitats, and environmental factors that influence the occurrence and population dynamics of T. parvispinus. By synthesizing existing knowledge, this review offers a clearer perspective on the challenges of managing these pests. This highlights the importance of integrated and sustainable management strategies for effective control.
A field experiment was carried out in the Tarai region of Uttar Pradesh during Kharif 2022 and 2023 to evaluate the effect of balanced fertilization and biofertilizer application on growth, yield attributes, yield, and profitability of maize ( Zea mays L.). The experiment was laid out in a split plot design with five balanced fertilization treatments nitrogen-phosphorus (NP), nitrogen-phosphorus-potassium (NPK), nitrogen-phosphorus-potassium-sulfur (NPKS), nitrogen-phosphorus-potassium-zinc (NPKZn), nitrogen-phosphorus-potassium-sulfur-zinc (NPKSZn)) in main plot and four biofertilizer treatments (Control, Azotobacter , Azotobacter + phosphate-solubilizing bacteria (PSB), and NPK consortia) in sub plot. The combined application of NPKSZn markedly enhanced physiological performance of maize, as reflected in improved plant height, dry matter accumulation, and chlorophyll content, which ultimately resulted in higher grain yield and superior economic returns. Among biofertilizer treatments, NPK consortia further strengthened yield attributes, grain productivity, and profitability, demonstrating the role of microbial inputs in improving nutrient use efficiency. The findings indicate that integrating balanced fertilization with biofertilizer consortia not only enhances crop productivity and farm income but also supports resource-use efficiency and soil health. This integrated nutrient management approach has wider implications for sustainable maize production and aligns with global efforts toward climate-resilient and environmentally sustainable agricultural systems.
Small-scale fisheries sustain approximately 90
