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 …

Plant stress phenotyping is essential to select stress-resistant varieties and develop better
stress-management strategies. Standardization of visual assessments and deployment of …

Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …

Background Phenotyping is a critical component of plant research. Accurate and precise trait
collection, when integrated with genetic tools, can greatly accelerate the rate of genetic gain …

During the last decade, there has been rapid adoption of ground and aerial platforms with
multiple sensors for phenotyping various biotic and abiotic stresses throughout the …

Current approaches for accurate identification, classification, and quantification of biotic and
abiotic stresses in crop research and production are predominantly visual and require …

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 …

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) …

Plant phenotyping has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …

Key message High-throughput phenotyping (HTP) is in its infancy for deployment in large-
scale breeding programmes. With the ability to measure correlated traits associated with …