Machine Learning in Precision Agriculture

Precision agriculture is an advanced farming practice that utilizes modern technologies, such as machine learning and remote sensing, to improve efficiency and productivity in crop production. Machine learning is used to process large amounts of data from various sources, such as satellites and soil sensors, to help farmers identify and monitor trends in crop growth. Machine learning can also be used to detect potential issues such as disease outbreaks and pest infestations, enabling early interventions that can reduce crop loss and yield decline. This technology can also be used to reduce input costs, improve resource utilization, and optimize irrigation and fertilization cycles to boost crop yields. By using machine learning in precision agriculture, farmers can increase the productivity and profitability of their operations while reducing their environmental impact.

← Journal of Precision Agriculture

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24 article(s) found

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The Changing Scenario of Agriculture

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Analyzing Students’ Opinions about their Learning Environments and Study Approaches with Bayesian Modeling

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Effect of a Waterproof Device in the Noninvasive Ventilation Circuit on patient-machine Synchronization

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Towards Precision Rheumatology?

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Scientific and Technological Interventions for Attaining Precision in Plant Genetics and Breeding

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Appropriate Conservation Machinery for Mungbean Cultivation in the Southern Region of Bangladesh

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Towards Implementing the Integrated Technology of Precision Agriculture in Sudan

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Rice Yield Advances Under Precision Agriculture: a Farm Lesson

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The Future Perspectives of Agricultural Graduates and Sustainable Agriculture in Sudan

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Study of The ID3 and C4.5 Learning Algorithms

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Proposed Spray System for Family Agriculture with A Remote-Controlled UAV (Small Drone or Helicopter) and An Economical Sprinkler

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The Impact of Migration and Remittances on Employment in Agriculture in the Gambia

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Statistical Analysis on the Influence of Flipped Classroom Teaching on Students’ Learning Effect During the Coronavirus Disease 2019 Epidemic

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Critical Review of Teaching and Learning Methodologies for Learners with Special Educational Needs in the 21st Century and Beyond

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A Long-Term Polydromic Function to Disentangle Personal Remittance, Migration and Employment in Agriculture in Order to Raise the GDP of the Donor aid Ratio in Five African Countries

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Indian Agriculture needs a Strategic Shift for Improving Fertilizer Response and Overcome Sluggish Foodgrain Production

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Biotechnological application of Cyanobacteria in, Agriculture, Medicine and Environment

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Success Driven: Student Motivation Actions in Teaching and Learning

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Effects of Feedback of Fingertip Force Information with Temporal Coded Vibration Stimulation on Precision Grasping Tasks

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Application of Permaculture Practices to Improve Sustainable Agriculture in the Maltese Islands

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Comparative Study of Deep Learning Techniques for Detecting Corn Plant Leaf Diseases Using Transfer Learning

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Learning and Memory in an Animal Model of Longevity: The Ames Dwarf Mice

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Documenting Interspecific Predation in Odonata: Observations of Ischnura Senegalensis Preying on Agriocnemis Pygmaea in Rice Fields of Faculty of Agriculture, Rajarata University of Sri Lanka, Puliyankulama, Anuradhapura District

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