Plant stresses have been monitored using the imaging or spectrometry of plant leaves in the
visible (red-green-blue or RGB), near-infrared (NIR), infrared (IR), and ultraviolet (UV) …

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

Remote detection and monitoring of the vegetation responses to stress became relevant for
sustainable agriculture. Ongoing developments in optical remote sensing technologies have …

Optical technologies can be developed as practical tools for monitoring plant health by
providing unique spectral signatures that can be related to specific plant stresses …

Agricultural production is limited by a wide range of abiotic (eg drought, waterlogging) and
biotic (pests, diseases and weeds) stresses. The impact of these stresses can be minimized …

Societal Impact Statement Advancements in our ability to rapidly detect plant responses to
stress are necessary to improve crop management practices and meet the global challenge …

Reducing agricultural losses is an effective way to sustainably increase agricultural output
efficiency to meet our present and future needs for food, fiber, fodder, and fuel. Our ever …

Current methods of in-house plant phenotyping are providing a powerful new tool for plant
biology studies. The self-constructed and commercial platforms established in the last few …

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 …

Effective crop protection requires early and accurate detection of biotic stress. In recent
years, remarkable results have been achieved in the early detection of weeds, plant …