Background As same as the priority and importance of food for being alive for humans, its
science play also a significant role in the world. So, food science, food technology, food …

This research presents a solution that combines deep learning-based image processing,
blockchain technology, and the Internet of Things (IoT) to achieve smarter control and …

Inverse modeling (IM) is a valuable tool in agriculture for estimating model parameters that
aid in decision-making. It is particularly useful when parameters cannot be directly …

Crop yield prediction models are critical tools for evaluating growth performance and
informing decisions during farm management. Develo** yield prediction models that are …

Reference evapotranspiration (ETo) is an essential variable in agricultural water resources
management and irrigation scheduling. An accurate and reliable forecast of ETo facilitates …

Satellite remote sensing is commonly used for large-scale agricultural monitoring, but the
low spatial resolution of its imagery does not allow it to present details of crop growth …

Accurate anticipation of the maize harvest date is important in the agricultural market, as it
ensures the sustainability of food production in response to the increasing global demand …

Accurate daily peak load forecasting (DPLF) is crucial for informed decision-making in
energy management. Deep neural networks (DNNs) are particularly apt for DPLF because …

This study proposed a model that utilized machine learning algorithms to predict the yield of
maize (Zea mays L.) cultivars. This will enable the selection of good cultivars with high yields …

Crop phenology modeling often involves determining variety‐specific growing degree day
thresholds, or parameterizing mechanistic crop models. In this work, we used machine …