Scientific Research Publishing

Crane-Droesch, A. (2018) Machine Learning Methods for Crop Yield Prediction and Climate Change Impact Assessment in Agriculture. Environmental Research Letters, 13, Article ID ...

ABSTRACT: Accurate prediction of water travel time in drip irrigation systems is essential for efficient water and nutrient delivery. This study develops a predictive model for travel time by ...
IEEE

In-Season Corn Yield Prediction Using Satellite-Derived Solar-Induced Chlorophyll Fluorescence and Machine Learning Algorithms

Abstract: Accurate in-season crop yield prediction is critical for timely agricultural decision-making, food security, and climate-resilient farm management. This study presents a framework for ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Frontiers

Integrating meteorological and breeding data to predict maize yields using machine learning algorithms

Introduction: Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods ...
Frontiers

Almond yield prediction at orchard scale using satellite-derived biophysical traits and crop evapotranspiration combined with machine learning

Accurate almond yield prediction is essential for supporting decision-making across multiple scales, from individual growers to international markets. This is crucial in the Mediterranean region, ...
IEEE

Enhancing Crop Yield Prediction using Machine Learning Techniques

Abstract: The advanced machine learning technique is important in enhancing the accuracy of crop yield forecasting, which is crucial for advancing agricultural productivity and ensuring global food ...