Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as ...
As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. Recently, there have been many studies ...
The agricultural industry is experiencing revolutionary changes through the latest advances in artificial intelligence and deep learning-based technologies. These powerful tools are being used for a variety of tasks including crop yield estimation, c...
Crop yield is a significant factor in world income and poverty alleviation as well as food production through agriculture. Conventional crop yield forecasting approaches that employ subjective estimates including farmers' perceptions are imprecise an...
The development of machine learning algorithms, along with high-resolution satellite datasets, aids in improved agriculture monitoring and mapping. Nevertheless, the use of high-resolution optical satellite datasets is usually constrained by clouds a...
Precise pest classification plays an essential role in smart agriculture. Crop yields are severely impacted by pest damage, which poses a critical challenge for agricultural production and the economy. Identifying pests is of utmost importance, but m...
Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for...
Early automation in identifying plant diseases is crucial for the precise protection of crops. Plant diseases pose substantial risks to agriculture-dependent nations, often leading to notable crop losses and financial challenges, particularly in deve...
The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy crop production. Adva...
A verifiable and regional level method for mapping crops cultivated under organic practices holds significant promise for certifying and ensuring the quality of farm products marketed as organic. The prevailing method for the identification of organi...