County-scale crop yield prediction by integrating crop simulation with machine learning models

Article Computer Science, Artificial Intelligence

Hybrid Deep Learning-based Models for Crop Yield Prediction

Alexandros Oikonomidis et al.

Summary: This article introduces a study on crop yield prediction, where deep learning-based models were developed and experiments were conducted using a public soybean dataset. The results showed that the hybrid CNN-DNN model performed the best, followed by the XGBoost model.

APPLIED ARTIFICIAL INTELLIGENCE (2022)

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Review Cell Biology

A guide to machine learning for biologists

Joe G. Greener et al.

Summary: This passage discusses the application of machine learning in the analysis of biological data and provides guidance for experimentalists. The increasing scale and complexity of biological data have led to a growing use of machine learning in biology.

NATURE REVIEWS MOLECULAR CELL BIOLOGY (2022)

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Article Multidisciplinary Sciences

Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt

Mohsen Shahhosseini et al.

Summary: The study shows that adding simulated crop model variables to machine learning models can reduce prediction errors and that variables related to soil moisture have the biggest impact on predictions. It indicates that more hydrological inputs are needed for improved accuracy in yield predictions.

SCIENTIFIC REPORTS (2021)

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Article Agronomy

Understanding the non-stationary relationships between corn yields and meteorology via a spatiotemporally varying coefficient model

Hao Jiang et al.

Summary: The study develops a novel spatiotemporally varying coefficient (STVC) model to understand the non-stationary relationships between crop yields and meteorological variables. Compared to variant models specialized for time or space, STVC performs the best in simulating corn yield responses towards meteorological conditions, reducing errors and increasing forecasting accuracy.

AGRICULTURAL AND FOREST METEOROLOGY (2021)

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Article Plant Sciences