Efficient and rational monitoring of plant health is an essential prerequisite for ensuring
optimal crop production and resource management in the field of agriculture. Computer …

Agriculture has undergone a remarkable transformation, transitioning from traditional
methods that were used for centuries to technology-driven practices. The advent of image …

As advancements in agricultural technology unfold, machine learning and deep learning
approaches are gaining interest in robust plant disease identification. Early disease …

Globally, all the major crops are significantly affected by diseases every year, as manual
inspection across diverse fields is time-consuming, tedious, and requires expert knowledge …

In order for a country's economy to grow, agricultural development is essential. Plant
diseases, however, severely hamper crop growth rate and quality. In the absence of domain …

AI branches many areas including computer vision and machine learning which are growing
in a variety of application sectors. In this perspective, the agriculture sector is a promising …

With the COVID-19 pandemic outbreak, most countries have limited their grain exports,
which has resulted in acute food shortages and price escalation in many countries. An …

Plant pathogens can decimate crops and render the local cultivation of a species
unprofitable. In extreme cases this has caused famine and economic collapse. Timing is vital …

Background Abiotic stressors impair crop yields and growth potential. Despite recent
developments, no comprehensive literature review on crop abiotic stress assessment …

Precise identification of plant diseases facilitates effective agricultural management.
However, classifying plant diseases poses formidable challenges due to various factors …