A machine learning-coupled APSIM model pipeline for projected oil palm yield in Surat Thani, Thailand. [PDF]
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Crop Yield Prediction Using Python
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Application of crop growth models in crop yield assessment. [PDF]
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Advancing Soybean Improvement: Multi-Omics Strategies, Cutting-Edge Techniques, and Bioinformatics Innovations. [PDF]
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Improving genomic prediction in wheat with random regression models with genotype-specific phenology-driven environmental covariates. [PDF]
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A review of remote sensing-based crop yield estimation: machine learning techniques and environmental, algorithmic, and hardware limitations. [PDF]
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Predicting water status, growth and yield of tomato under different irrigation regimes using the RGB image indices and artificial neural network model. [PDF]
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A novel approach for efficient crop yield prediction
Computers and Electronics in Agriculture, 2019Abstract Crop yield prediction is one of the challenging task in agricultural domain. Extensive research in agricultural domain has been carried out to predict better crop yield using the machine learning algorithm Artificial Neural Network (ANN) and statistical model Multiple Linear Regression (MLR).
R Bhargavi
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An Ensemble Algorithm for Crop Yield Prediction
2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), 2021Machine learning is a pivotal viewpoint for grasping real-world and purposeful use cases for yield prediction of crops. Machine learning is a supportive tool for the agricultural sector which helps us to decide which plant to grow and when to grow the desired plant.
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An Approach by Computer to the Prediction of Crop Yields
International Journal of Pest Management: Part B, 1968(1968). An Approach by Computer to the Prediction of Crop Yields. Pest Articles & News Summaries. Section B. Plant Disease Control: Vol. 14, No. 4, pp. 347-352.
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