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Research ArticleOpen accessIn the abstractIntegrated ARIMA and Multi-Scale GRU for Crop Recommendation and Yield Prediction in Precision AgricultureVani Vijay Kumar Ballapuram, Gurupraksh Chirathahalli DyamannaAgriculture is the fundamental source of food, income, and livelihood for rural communities in India. Numerous crops are affected due to the lack of technical decision-making support and variations in weather patterns, temperature, rainfall, and atmosphere factors, which play a critical role in defining crop yield. Hence, choosing the appropriate crop to maximize yield is key to enhancing real-time farming … …Journal of Computer Science, Vol. 21, Issue 10 · 26 Nov 2025 · 2,022 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimate of Safe Angle for Cut Slopes Under Different Geology and Rainfall Intensity in Central NepalPrabin Shrestha, Khomendra Bhandari, Mahendra Acharya et al.This research has been carried out on a cut slope of Kathmandu-Terai Fast Track Road near Koppugaon located at Dakshinkali Municipality, Kathmandu. The cutting of the slope without considering the possible effects of geological parameters of slope material may cause unexpected slope failures which may cause loss of lives and properties. This research deals with the effects of rainfall and … …Current Research in Geoscience, Vol. 13, Issue 1 · 26 Nov 2024 · 9,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 accessesView PDFCite
Research ArticleOpen accessIn the abstractSustainable Technology for Agriculture at Extreme Altitudes: Design and Evaluation of a Sprinkler Irrigation System in a Peruvian High Andean CommunityJuan Eduardo Suarez Rivadeneira, Freddy A. Manayay, Daniel Olivier Carranza Lizana et al.In high-altitude agroecosystems, erratic rainfall patterns and steep topography severely constrain crop productivity by exposing plants to soil water deficits during critical phenological stages. This study aimed to enhance the productivity of eleven staple and horticultural crops corn (Zea mays), tomato (Solanum lycopersicum), cucumber (Cucumis sativus), eggplant (Solanum melongena), lettuce (Lactuca sativa), carrot (Daucus carota), barley (Hordeum vulgare), celery (Apium … …OnLine Journal of Biological Sciences, Vol. 26, Issue 4 · 2 Oct 2026 · 645 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractExtended Fuzzy Decision Support Model for Cropland Recommendation of Food Cropping in IndonesiaLucky Christopher Chen, Nurcahyo Wibowo, Ditdit Nugeraha UtamaFood crops are the preferred crops to be cultivated on agricultural land in Indonesia, which has a wide area available for use as agricultural land. Each region’s agricultural lands in Indonesia have distinct features (e.g., water capacity, land porosity, land height, etc.). Rice, maize, red beans and green beans are significant food crops that are commonly cultivated in Indonesia. The … …Journal of Computer Science, Vol. 17, Issue 8 · 8 Sep 2021 · 6,501 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Nonlinear Models for Dry Matter Yield of Brachiaria Hybrid cv Cayman in Drought Season by BootstrappingDanny Villegas Rivas, Nora Valbuena Torres, Manuel Milla Pino et al.The dynamics of biomass accumulation at different seasons of the year is of vital importance in the production of a forage species. In this study nonlinear models (logistic and gompertz) to describe growth dynamics of plants based on dry matter yield of Brachiaria hybrid Cayman at different interval between cuts in drought season were used. Results for logistic and gompertz … …OnLine Journal of Biological Sciences, Vol. 21, Issue 1 · 15 Mar 2021 · 6,640 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Fuzzy Decision Support Model for Cropland Recommendation of Food Cropping in IndonesiaDitdit Nugeraha Utama, Alvali Zaqi Taufan, Al Ghifari Hartzani et al.Indonesia has an incredibly wide area for agriculture. The agriculture area in Indonesia has specific characteristic for each area (e.g., water capacity, land porosity, land height, etc.,). Furthermore, food crop is the most plant planted in Indonesia; rice, corn, red bean, green bean are some important food crops. The study aims to create a Decision Support Model based on fuzzy … …Journal of Computer Science, Vol. 16, Issue 4 · 29 Apr 2020 · 7,504 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 accessesView PDFCite
Research ArticleOpen accessIn the abstractClimate Adaptive Measures Among Smallholder Farmers in Akwa Ibom State, NigeriaObot Akaninyene, Obiekwe NgoziAgricultural production/activities in Nigeria depends on rainfall, which often occurs only at certain times of the year and thus makes agriculture very susceptible to crop failure, insect infestation which causes poor returns on agricultural produce for farmers . Adoption of climate change mitigating strategies is key to coping with variations in weather conditions and the achievement of increased agricultural production … …American Journal of Agricultural and Biological Sciences, Vol. 17, Issue 1 · 19 Sep 2022 · 6,261 accessesView PDFCite