Plants undergo stress whenever they are subjected to adverse conditions or an element that
inhibits metabolism and growth (Lichtenthaler, 1996). Plants incur irreversible harm, even …

Integrating imaging sensors and artificial intelligence (AI) have contributed to detecting plant
stress symptoms, yet data analysis remains a key challenge. Data challenges include …

Advances in automated and high-throughput imaging technologies have resulted in a
deluge of high-resolution images and sensor data of plants. However, extracting patterns …

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

CONTEXT Paddy crop stress can significantly reduce the quality and quantity of agricultural
goods and severely affect food production safety. Untimely stress and inaccurate crop …

Plant diseases are one of the primary causes of major economic losses in the agriculture
industry worldwide. The continuous monitoring of plant health and early detection of …

In the world economy, agriculture is an essential part among individuals to earn money. But,
the farmers face more obstacles because more diseases naturally affect the health of the …

Data augmentation is a powerful tool for improving deep learning‐based image classifiers
for plant stress identification and classification. However, selecting an effective set of …

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

Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield
under adverse environmental conditions. To achieve this goal and select the most resilient …