Machine learning in agriculture: A comprehensive updated review
The digital transformation of agriculture has evolved various aspects of management into
artificial intelligent systems for the sake of making value from the ever-increasing data …
artificial intelligent systems for the sake of making value from the ever-increasing data …
Google Earth Engine and artificial intelligence (AI): a comprehensive review
Remote sensing (RS) plays an important role gathering data in many critical domains (eg,
global climate change, risk assessment and vulnerability reduction of natural hazards …
global climate change, risk assessment and vulnerability reduction of natural hazards …
[HTML][HTML] Machine learning for large-scale crop yield forecasting
Many studies have applied machine learning to crop yield prediction with a focus on specific
case studies. The data and methods they used may not be transferable to other crops and …
case studies. The data and methods they used may not be transferable to other crops and …
A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
An early and reliable estimation of crop yield is essential in quantitative and financial
evaluation at the field level for determining strategic plans in agricultural commodities for …
evaluation at the field level for determining strategic plans in agricultural commodities for …
Integrating multi-source data for rice yield prediction across China using machine learning and deep learning approaches
Timely and reliable yield prediction at a large scale is imperative and prerequisite to prevent
climate risk and ensure food security, especially with climate change and increasing …
climate risk and ensure food security, especially with climate change and increasing …
[HTML][HTML] Sequential forward selection and support vector regression in comparison to LASSO regression for spring wheat yield prediction based on UAV imagery
Traditional plant breeding based on selection for grain yield is time-consuming and costly;
therefore, new innovative methods are in high demand to reduce costs and accelerate …
therefore, new innovative methods are in high demand to reduce costs and accelerate …
Support vector machine in precision agriculture: a review
Abstract The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which
may be used for acquiring solutions towards better crop management. The applications of …
may be used for acquiring solutions towards better crop management. The applications of …
Wheat yellow rust detection using UAV-based hyperspectral technology
Yellow rust is a worldwide disease that poses a serious threat to the safety of wheat
production. Numerous studies on near-surface hyperspectral remote sensing at the leaf …
production. Numerous studies on near-surface hyperspectral remote sensing at the leaf …
Winter wheat yield prediction at county level and uncertainty analysis in main wheat-producing regions of China with deep learning approaches
Timely and accurate forecasting of crop yields is crucial to food security and sustainable
development in the agricultural sector. However, winter wheat yield estimation and …
development in the agricultural sector. However, winter wheat yield estimation and …
Artificial intelligence in food safety: A decade review and bibliometric analysis
Artificial Intelligence (AI) technologies have been powerful solutions used to improve food
yield, quality, and nutrition, increase safety and traceability while decreasing resource …
yield, quality, and nutrition, increase safety and traceability while decreasing resource …