Deep learning has emerged as a potential tool for crop yield prediction, allowing the model
to automatically extract features and learn from the datasets. Meanwhile, smart farming …

The art of predicting crop production is done before the crop is harvested. Crop output
forecasts will help people make timely judgments concerning food policy, prices in markets …

Rapid population growth, climate change, limited natural resources, and the COVID-19
pandemic contribute to increased global hunger, necessitating intensive efforts to ensure …

A field study was conducted to understand the effectiveness of foliar applications of ZnO-
NPs (0, 50, 100 mg L− 1) and SiO2-NPs (0, 25, 50 mg L− 1) on potato plant growth …

Predicting crop yields is a critical issue in agricultural production optimization and
intensification research. Accurate foresights of natural circumstances a year in advance can …

Droughts and water scarcity represent crucial issues for the agricultural sector, whose water
demand is expected to increase in the next years to ensure food production for a growing …

Current wheat crop management practices in the Nile Delta of Egypt are unsustainable due
to the overuse of limited water resources. Therefore, the aim of this study was to investigate …

Crop yield prediction is one of the crucial components of agriculture that plays an important
role in the decision-making process for sustainable agriculture. Remote sensing provides …

CONTEXT Farming systems face dual pressures of reducing greenhouse gas (GHG)
emissions to mitigate climate change and safeguarding food security to adapt to climate …

Crop simulation models can be effective tools to assist with optimization of resources for a
particular agroecological zone. The goal of this study was to determine the influence of N …