Renu Publishers - International Journal of Bioresource Science

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International Journal of Bioresource science

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Title:

International Journal of Bioresource science

Abstract:

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Title:

Exchangeable Acidity Management with Integrated Amendments to Enhance Potato (Solanum tuberosum) Productivity and Nutrient Use Efficiency in Acidic Soils

Abstract:

Potato cultivation is severely hampered by acidic soils, particularly in the Kenyan highlands, where crop growth, yield, and nutrient availability are all impacted. With an emphasis on combining organic and inorganic amendments, this paper looks at how soil additions might improve potato yield and reduce soil acidity. Anthropogenic and natural factors are the main determinants of soil acidity, which is common in the highlands of Kenya. The pH of soil has significantly decreased as a result of the acidic parent material, which is derived from volcanic rocks, as well as human-induced behaviors like constant cultivation and an over-reliance on inorganic fertilizers. The presence of hazardous acidic cations (H? and Al³?) causes exchangeable acidity, which hinders potato root growth and nutrient uptake and lowers crop output. Although a number of amendments, including mineral fertilizers, lime, and organic manure, have demonstrated promise in reducing soil acidity and enhancing soil fertility, little is known about how these amendments work together to affect exchangeable acidity and how that affects potato production. Given that soil acidity changes at different depths and influences nutrient availability, root penetration, and water infiltration, this review emphasizes the need for a greater understanding of soil profile characteristics. Although they provide temporary advantages, traditional supplements like lime efficiently neutralize the pH of soil. Compost, biochar, and farmyard manure are examples of organic amendments that enhance soil structure, water retention, and nutrient cycling, all of which promote long-term soil health. Potato yield has been demonstrated to rise when organic and inorganic additions work in concert to promote soil fertility and nutrient uptake. More focused treatments, including deep liming and subsurface amelioration, can be guided by accurate profiling, improving crop yields and nutrient usage efficiency (NUE). Furthermore, sustainable additives like biochar are becoming more well-known due to their capacity to raise soil pH and sequester carbon. These strategies have potential, but there are still issues with high amendment costs, restricted access to soil testing, and a lack of farmer understanding. In order to support the adoption of sustainable soil management practices for increased potato productivity in acidic soils, this review emphasizes the need for more research into integrated amendment strategies, the creation of affordable and environmentally friendly amendments, and better extension services. Notwithstanding the difficulties, maintaining soil acidity in potato farming appears to have a bright future thanks to the combination of organic and inorganic amendments, improvements in precision agriculture, and simulation models. The purpose of this review is to fill in the information gap about how these changes can boost potato yield and manage exchangeable acidity, which would ultimately increase regional food security.

Title:

Low Cost IoT-enabled Embedded System of Smart Textile for Real-time Health Monitoring of Industrial/Agricultural Worker

Abstract:

The Internet of Things (IoT) can help us better our lives in many ways by rendering real-time information over the Internet via smart network of devices. In this paper, the authors discussed about development of an IoT-enabled embedded system for smart textiles which was developed to monitor the real-time health parameters of industrial/agricultural workers. The developed system encompasses LM 35 body temperature sensor, MAX30100 pulse rate and SpO2 module, NodeMCU ESP 8266 WiFi-enabled microcontroller, Blynk Android app development platform and mobile phone (OS: Android). The developed system was tested in the laboratory measuring the health parameters of ten persons with five replications. Test results shows that the standard deviation and standard error mean (SE mean) in the measured value of temperature were found to be 1.6 °C and 2.22 % respectively. Similarly, standard deviation and standard error mean (SE mean) in the measured value of pulse rate and SpO2 were found as 2.68 BPM and 6.75 % respectively and 5.87 % and 4.60 % respectively. The developed embedded system is easy-to-build, easy-to-use and cost-effective (` 5000/-). The compactness of microcontroller as well as sensor and initial testing shows that the developed system is very much compatible to integrate with the textile product to make a low-cost smart textile for real-time health monitoring of industrial/ agricultural workers.

Title:

Genetic Diversity of Finger Millet Advanced Breeding Lines

Abstract:

Finger millet is an important millet crop known for its three-fold security. The present study was undertaken to assess the associations among various traits and diversity amid 29 finger millet genotypes. All genotypes were evaluated for grain yield, yield components and disease traits at Agricultural Research Station, Vizianagaram, Andhra Pradesh. Association analysis of 14 traits revealed significant positive association between phenological traits and grain yield. It was also observed that longer ears tend to have higher grain yields. The variability of 14 traits was majorly captured by the first principal component where the phenological traits, disease traits and grain yield contributed higher percent compared to others. These traits can serve as reliable selection indices for improving yield potential and adaptability in finger millet breeding programs. Circle plot was also in agreement with association analysis that days to 50% flowering (DFF), days to maturity (DM), ear length (EL), and finger length (FL) were positively associated. Further, the biplot helped to view the grouping of various genotypes into clusters.

Title:

Effect of Detasseling and Organic Nutrient Management on The Growth, Yield attributes and Yield of Baby Corn Under Costal Part of West Bengal

Abstract:

Maize has emerged as an important crop due to its wider adaptability and high yield potential. Baby corn is an off shoot of maize which is grown for it’s young, fresh, finger like green cobs, harvested at the time of silk emergence and before pollination and fertilization. The present study was carried out at the Instructional farm, School of Agriculture and Allied Sciences, the Neotia University Sarisha, Jhinga, South 24 parganas, West Bengal to study the effect of detasseling and organic nutrient management on the growth and yield of baby corn during the Rabi season of 2024-2025. The experiment was carried out in split plot design replicated thrice, having three different level of detasseling time in main plots, viz., D1: no detasseling (control), D2: detasseling immediately after tassel emergence and D3: detasseling at 7 days after tassel emergence, and three different level of organic nutrient management in sub-plots, namely, N1: 4 t vermicompost/ha, N2: 4 t vermicompost/ha + Jeevamruta (at 30 says interval) and N3: 4 t vermicompos/ ha + Jeevamruta + Amrutpani (at 60 says interval). Detasseling time and application of organic nutrient management significantly influenced the growth attributes, yield attributes and yield of baby corn as the detasseling after seven days after tassel emergence and the application of 4 t vermicompost/ha + Jeevamruta (at 30 says interval) resulted in their superiority over other treatment combinations.

Title:

Effect of Crop Booster on Growth, Yield and Quality of Groundnut (Arachis hypogaea L.) under Protective Irrigated Condition

Abstract:

Groundnut is one of the important oilseed crops, which needs a proper nutrient management for its proper growth and development. Based on the above fact, a field experiment was conducted during kharif 2024 at the Zonal Agricultural Research Station, GKVK, UAS, Bangalore, to evaluate the effect of a crop booster on growth, yield and quality of groundnut under protective irrigated condition. The experiment was laid out in a randomized complete block design (RCBD) comprising eight treatments with three replications. The results revealed that the application of recommended dose of fertilizer (RDF) + 1.0 per cent foliar spray of the crop booster significantly improved growth, yield and yield attributes such as plant height (56.46 cm), number of branches per plant(6.89), number of leaves per plant (42.08), leaf area per plant (887 cm²), leaf area index (2.95), total dry matter accumulation per plant (21.95 g), number of pods per plant (49.52), pod weight per plant (21.14 g), pod yield (3629 kg ha-¹) and haulm yield (4583 kg ha-¹) compared to RDF alone. Notably, this treatment also proved the most financial rewarding, generating higher gross returns (` 1,54,745 ha-1), net returns (` 1,01,213 ha-1) and B:C ratio (2.89).

Title:

Constraints in Adoption of Improved Paddy Cultivation Practices among Farmers of Northern Karnataka

Abstract:

The adoption of improved paddy cultivation practices is central to improve the productivity, profitability and sustainability of rice based farming systems in Karnataka. However, the rate of adoption is still limited by a number of farm-level and institutional challenges. The present study was undertaken in the year 2024-25 in order to understand the significant constraints encountered by the paddy farmers in practising improved cultivation practices and to record the farmer derived suggestions for strengthening extension services in Northern Karnataka. Using ex-post facto research design, data was collected from 150 paddy growers selected by using multi stage random sampling from Dharwad, Belagavi and Vijayapura districs Garrett’s ranking technique was used to prioritize the constraints and suggestions. The findings showed that lack of location-specific agro-advisory services, high cost of quality inputs, untimely availability of seed, labour scarcity and poor extension outreach were the most serious constraints for limiting the adoption. Farmers emphasized on time supply, of quality input, strengthening of field level extension services, regular training and demonstrations, stable market prices and improved access to institutional credit as the most important measure for improving adoption. The findings highlight the need for an integrated extension approach combining localized advisory services together with institutional coordination, financial facilitation and farmer-centred learning mechanisms. Strengthening village-level extension systems and input delivery networks will be important for accelerating adoption of improved paddy practices and ensuring sustainable intensification of rice production in the region.

Title:

Spray Drift Pattern Analysis of Different Sprayers

Abstract:

A sprayer is a device used to spray a liquid, where sprayers are commonly used for projection of water, weed killers, crop performance materials, pest maintenance chemicals, as well as manufacturing and production line ingredients. Drift can be defined as spray which unintentionally reaches areas outside the target area, either as droplets, dry particles or vapour, during or after application on the target area. An increase in wind speed from 3 m/s to 5 m/s (at 2 m height) can double spray drift deposition. An experiment was conducted in a closed environment to find the spray drift analysis for different types of sprayers (Battery operated, Hi-tech, Knapsack, Rocker arm & Foot operated) with three different nozzles (Solid cone, flat fan & hallow cone) at different wind speeds (2, 5 & 10 km/hr) and different heights from ground level (50, 60 & 70 cm). Here, Rocker arm & Foot operated sprayers are used only with solid cone nozzle. The highest and lowest discharge rate was observed in battery operated sprayer with solid cone nozzle (1700 ml/min) and knap-sack sprayer with hallow cone nozzle respectively. The highest and lowest droplet size diameter at 50cm height was found in battery operated sprayer with solid cone nozzle (1.5 mm) and battery-operated sprayer with hallow cone nozzle (0.03 mm).

Title:

Impact of Climate Change on Agriculture for Paddy Farmers in Gajapati District

Abstract:

Climate change is one of the most important challenges for agricultural production, particularly in rain-fed irrigations such as Gajapati district of Odisha, where in the people mostly depend on paddy cultivation. The study used purposive sampling impact of irregular rainfall, hot temperatures, cyclones and low moisture in soils and farmer well-being. Used purposive sampling, collected data from 52 paddy farmers through structured questionnaires and personal interviews. The study used descriptive statistcs, chi-square tests and multiple regression analysis to find climate impacts and adaptation responses. The Results reveal that erratic rainfall and heat stress significantly reduce yields, while extreme weather it causes crop losses. While occupation had no clear impact on subsidy, gender was found to influence the adoption of new practices. The most important factor influencing farmer income, according to regression analysis, is the size of the landholding. Despite emerging adaptation strategies such as drought-tolerant varieties, mixed cropping and community water management, limited access to irrigation, credit and institutional support hinders resilience. The study concludes that strengthening irrigation infrastructure, promoting climate-smart agriculture and enhancing institutional interventions are essential to safeguard paddy farming and improve adaptive capacity in Gajapati district. The study finds a significant impact of climate change on paddy farming in Gajapati district, Odisha. The study shows erratic rainfall, rising temperature and extreme weather are directly affecting crop growth, yield and farmers’ livelihood.

Title:

Bio-efficacy of Different Post Emergence Herbicides for Broad Spectrum Weed Management in Transplanted Rice (Oryza sativa L.) in Indo-Gangetic Plain Zone of West Bengal

Abstract:

A field experiment was conducted during two consecutive kharif seasons at AB block Farm, Bidhan Chandra Krishi Viswavidyalaya, Kalyani, Nadia, West Bengal, India during 2019-20 and 2020-21, to study the effect of different post emergence herbicides for broad spectrum weed management in transplanted rice. The experiment was laid out in a randomized block design with ten treatments and replicated thrice. reatments comprises T1 : Bispyribac sodium 38% + Chlorimuron ethyl 2.5 + Metsulfuron methy l 2.5% (43% WG) 34.4 g ai/ha at 20 DAT, T2 : Bispyribac sodium 38% + Chlorimuron ethyl 2.5 + Metsulfuron methyl 2.5% (43% WG) 43 g ai/ha at 20 DAS, T3 : Bispyribac sodium 38% + Chlorimuron ethyl 2.5 + Metsulfuron methyl 2.5% (43% WG) 51.6 g ai/ha at 20 DAS, T4 : Penoxsulam 1.02% + Cyhalofop-butyl 5.1% OD 135 g ai/ha at 20 DAT, T5 : Bispyribac Sodium 10 % SC 25 g ai/ha at 20 DAT, T6 : Bispyribac Sodium 10 % SC 38 g ai/ha at 20 DAT, T7 : Metsulfuron Methyl + Chlorimuron ethyl 10 % WP + Surfactant 4 g ai/ha at 21 DAT, T8 : Metsulfuron Methyl + Chlorimuron ethyl 10 % WP + Surfactant 5 g ai/ha at 21 DAT, T9 : Hand weeding (twice at 20 and 40 DAP), T10 : Weedy check. Among the different herbicidal treatments, T2 and T3 recorded highest weed control efficiency. Two times hand weeding at 20 and 40 days after showing was found highest grain yield and straw yield (4190.18 and 6707.04 kg/ha) and it was on par with chemical application of Bispyribac sodium 38%+ Chlorimuron ethyl 2.5 + Metsulfuron methyl 2.5% (43% WG) 43 g ai/ha WG @ 51.6 & 43 g a.i. ha-1 (4179.06 and 6785.78 kg/ha) and (4152.78 and 6631.88 kg/ha) followed by rest of the treatments excluding control (1523.43 and 3463.70 kg/ha).

Title:

IoT- and Machine Learning-Enabled Early Detection of Rice Stem Borers Using Acoustic and Vibration Sensors

Abstract:

Rice stem borers are among the most destructive pests of rice, causing significant yield losses due to concealed larval feeding within plant stems. Early detection of infestation is difficult using conventional monitoring techniques such as visual scouting or pheromone traps, which often identify the problem only after considerable damage has occurred. This study presents a conceptual framework for an Internet of Things (IoT) and machine learning (ML) enabled system for early and non-invasive detection of rice stem borer activity. The proposed system integrates acoustic and vibration sensors with low-power IoT hardware, wireless communication modules, cloud-based analytics and ML-driven classification models. Micro-acoustic and vibrational signals generated during larval feeding are captured in real time and processed using signal-processing techniques such as filtering, spectral analysis and feature extraction. These processed signals are subsequently analyzed using machine learning models to detect infestation patterns and generate early warning alerts. The architecture includes field sensor nodes installed near rice stems, an IoT gateway for data aggregation and transmission, cloud-based processing units and a farmeroriened mobile interface. This integrated approach enables continuous monitoring of pest activity under field conditions. The system also supports precision pest management by enabling timely intervention and reducing unnecessary pesticide application. The proposed framework highlights the potential of combining modern sensing technologies with intelligent analytics to improve agricultural sustainability and crop protection. The study also discusses challenges related to field deployment, environmental noise, data availability and system scalability. Overall, the integration of acoustic sensing, IoT communication and machine learning offers a promising pathway for developing smart pest surveillance systems in rice production ecosystems.

Title:

Correlation and Path Coefficient Analysis for Yield and Yield- Related Traits in Foxtail Millet (Setaria italica L.)

Abstract:

its component traits in foxtail millet (Setaria italica L.). Twenty genotypes were evaluated during kharif, 2019 at Agricultural Research Station, Vizianagaram, Andhra Pradesh, in a Randomized Block Design with three replications. Mean performance of genotypes show that considerable variation was observed among the genotypes for all the traits studied, indicating the presence of sufficient variability for selection and improvement. Analysis of correlation revealed significant positive association of grain yield with plant height, number of productive tillers per plant and fodder yield, indicating that these traits play a vital role in determining grain yield. Path coefficient analysis revealed that fodder yield exhibited the highest positive direct effect on grain yield, followed by plant height and panicle length, signifying their importance in selection for yield improvement. Traits such as days to maturity and plant height also showed considerable indirect effects through fodder yield. These findings indicate that simultaneous improvement of yield and its related traits can be achieved by selecting for fodder yield, plant height, and panicle length.

Title:

Smart Agriculture Systems: Integrating AI and IoT for Sustainable Crop Production

Abstract:

AI and IoT are changing precision agriculture, process automation, irrigation optimization, predicting the health of crops and animals, improving the supply chain, and making things more sustainable. AI and IoT technology help with big problems like a lack of agricultural supplies and a growing global population. AI, IoT, remote sensing, and GIS-powered precision agriculture goes beyond traditional farming to use data-driven strategies that make the most use of resources, increase crop yields, cut down on waste, and make farming more sustainable. This adjustment not only makes things work better, but it also encourages eco-friendly farming practices, which makes agriculture more resistant to climate change and resource depletion and lowers the growing need for food. Using AI and the Internet of Things (IoT) in precision farming has made it much easier to keep an eye on crops, manage resources, and make decisions. When used on the FAOSTAT dataset, a suggested precision farming (PF) method does better than the current classification methods, getting 98.65% accuracy, 98.32% precision, and 97.65% recall in just 0.23 seconds. This method also shows off the tools and methods that are important for PF and the tools that are used in modern farming in real time. When you combine IoT devices with machine learning, you can look at data in real time. This makes things more efficient, has less of an effect on the environment, and produces more. This is good for the environment and makes money. Using both in situ and mobile sensors is very important for predicting yields and making decisions based on those predictions. Also, radio frequency variables are needed to make wireless sensor networks (WSNs) work better in farming. But they are still worried about privacy issues, the intricacy of the technology, and the high expenses of putting it into practice.

Title:

Remote Sensing and Its Role in Shaping Forest Crescendos under Climate Change

Abstract:

Forests serve as critical regulators of the global climate through carbon sequestration, biodiversity conservation, and ecosystem services. Nonetheless, climate change is fundamentally disrupting these

functions by driving shifts in species distributions, reducing biomass productivity, altering carbon storage capacity, and intensifying disturbance regimes such as wildfires, pest outbreaks, droughts, and storms.

Such transformations threaten forest resilience and challenge sustainable management, necessitating advanced monitoring tools capable of capturing complex, multi-scale ecological responses. Remote sensing technologies, including satellite-based optical sensors (Landsat, Sentinel, MODIS), radar systems, LiDAR, hyperspectral imaging, and unmanned aerial vehicles (UAVs), provide indispensable insights into forest canopy structure, phenological cycles, biomass dynamics, and physiological stress indicators like chlorophyll fluorescence and water deficits. Integration of these technologies with machine learning (ML), artificial intelligence (AI), and ecological models enables unprecedented detection of subtle climatedriven impacts and predictive capacity for ecosystem shifts. Key advances include Sentinel-1/2 fusion for cloud-free deforestation monitoring, GEDI-Landsat integration, enhancing biomass estimation accuracy by 30% and convolutional neural networks (CNNs) achieving >90% accuracy in early pest outbreak detection. Despite persistent challenges such as tropical cloud cover, scaling mismatches, computational demands, and ground-validation gaps, remote sensing has become fundamental for informing climate adaptation strategies, conservation planning, and policy frameworks like REDD+. This chapter synthesizes technological innovations, regional case studies, and emerging opportunities to advance predictive monitoring and strengthen forest resilience under accelerating climate change, bridging critical gaps between scientific research and actionable management solutions.

Title:

Ecosystem Services by Insect Pollinators, Their Crisis and Climate Change Effects

Abstract:

Insects provide indispensable ecosystem services that sustain biodiversity, agricultural productivity, and

ecological resilience. This literature explores the multifaceted roles of insects in ecosystem functioning,

emphasizing pollination, decomposition, natural pest control, and aquatic ecosystem maintenance. Pollinators such as bees, butterflies, and flies contribute significantly to global food security and plant reproduction, while decomposer and predatory insects enhance soil fertility and pest regulation. The chapter highlights how insect diversity underpins ecosystem stability and how its decline poses severe risks to food systems and environmental health. It examines the growing threats from habitat loss, monoculture farming, pesticide overuse, climate change, and invasive species, which collectively disrupt ecological balance and diminish pollination efficiency. Additionally, it discusses the innovative potential of bio-inspiration derived from insect physiology and behavior in advancing sustainable technologies and climate adaptation. Current global initiatives, including those led by IPBES and FAO, are also reviewed for their efforts in promoting insect conservation and policy integration. The chapter concludes by emphasizing the urgent need for ecosystem-based management, landscape diversification, and strengthened institutional support to safeguard insect-mediated services essential for global sustainability, climate resilience, and human well-being.

Title:

Ecosystem Services by Insect Pollinators, Their Crisis and Climate Change Effects

Abstract:

Insects provide indispensable ecosystem services that sustain biodiversity, agricultural productivity, and ecological resilience. This literature explores the multifaceted roles of insects in ecosystem functioning, emphasizing pollination, decomposition, natural pest control, and aquatic ecosystem maintenance. Pollinators such as bees, butterflies, and flies contribute significantly to global food security and plant reproduction, while decomposer and predatory insects enhance soil fertility and pest regulation. The chapter highlights how insect diversity underpins ecosystem stability and how its decline poses severe risks to food systems and environmental health. It examines the growing threats from habitat loss, monoculture farming, pesticide overuse, climate change, and invasive species, which collectively disrupt ecological balance and diminish pollination efficiency. Additionally, it discusses the innovative potential of bio-inspiration derived from insect physiology and behavior in advancing sustainable technologies and climate adaptation. Current global initiatives, including those led by IPBES and FAO, are also reviewed for their efforts in promoting insect conservation and policy integration. The chapter concludes by emphasizing the urgent need for ecosystem-based management, landscape diversification, and strengthened institutional support to safeguard insect-mediated services essential for global sustainability, climate resilience, and human well-being.