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38 results for “Crop Recommendation”
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Research ArticleOpen accessPhrase in the titleIntegrated 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 accessPhrase in the titleDevelopment 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 keywordsDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 481 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 abstractTransforming Saffron Cultivation With Smart Hydroponics: An Artificial Intelligence of Things Approach to Crops and Nutrients ManagementVivek Raj, Gregory Allen, Ananth Prabhu G., Melwin DsouzaAgriculture is changing with the aid of new technologies, particularly in several Asian countries. This research applies Artificial Intelligence (AI) and the Internet of Things (IoT) to traditional farming, particularly focusing on saffron cultivation using hydroponics. Hydroponics is especially useful as a city grows, because it not only saves space but also nourishes the plants directly through the roots - … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 852 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 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 abstractBuilding Resilience in Natural Capital to Reduce Disaster Risks and Adapt to Climate Change: A Case of Wetlands in the Eastern Free State; South AfricaJohanes A. Belle, Nacelle Collins, Andries JordaanWetlands are a form of natural capital which provide services that improve the welbeing of the local community. Unfortunately many wetlands have been degraded before their values and functions were realised. Using a system thing appraoach and a mixed research method, this article collected primary data from 176 respondents using questionnaires. Besides, 21 wetlands were observed using field observation data … …American Journal of Environmental Sciences, Vol. 13, Issue 5 · 12 Oct 2017 · 7,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractCompetition Effects of Date of Sowing and Nutsedge Removal Time on Yield and Yield Contributing Characters of Tef [Eragrostis tef (Zucc.) Trotter]Abdul Shukor Juraimi, Mahfuza Begum, Ahmed Mohammed Sherif, Anuar Abdul RahimProblem statement: Tef [Eragrostis tef (Zucc.) Trotter] is a C4 grass, most important indigenous cereal crop in Ethiopia. The average grain yield of this crop is low; averaging <0.8 Mg ha-1. Under appropriate cultural practices such as the right sowing date, sowing rate, weeding time and fertilizer application, tef could produce grain yields of 2200-4599 kg ha-1. A delay in … …American Journal of Applied Sciences, Vol. 6, Issue 10 · 31 Oct 2009 · 7,137 accessesView PDFCite
Research ArticleOpen accessIn the abstractInvestigating the Effect of Three Nitrate Fertilizers on Nitrate Leaching under the Root Zone in Clay Loam SoilThamer Ahmed Mohammed, M. Nooshin, Megat Johari Megat Mohd. Noor, A. LiaghatProblem statements: Nitrogen fertilizer is recognized as an important factor in crop’s yield level, however more application of N fertilizers in the soil have some adverse effects on environment and especially on groundwater contamination. Perception and recognition the factors influencing nitrate transport through soil profile is helpful for fertilizer management to minimize adverse impacts on environment and nitrate leaching below … …American Journal of Environmental Sciences, Vol. 5, Issue 3 · 30 Jun 2009 · 7,064 accessesView PDFCite