Food scarcity, population growth, and global climate change have propelled crop yield
growth driven by high-throughput phenotyping into the era of big data. However, access to …

Employing computer vision to extract useful information from images and videos is
becoming a key technique for identifying phenotypic changes in plants. Here, we review the …

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of
genomics and environment on plants, limiting the progress of smart breeding and precise …

The breeding of forest trees is only a few decades old, and is a much more complicated,
longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle …

The complex interaction between a genotype and its environment controls the biophysical
properties of a plant, manifested in observable traits, ie, plant's phenome, which influences …

Today there is a rapid development taking place in phenotyping of plants using non-
destructive image based machine vision techniques. Machine vision based plant …

Maize (Zea mays L.) is one of the three major cereal crops in the world. Leaf angle is an
important architectural trait of crops due to its substantial role in light interception by the …

Computer vision technology is moving more and more towards a three-dimensional
approach, and plant phenotyping is following this trend. However, despite its potential, the …

High throughput image-based plant phenotyping facilitates the extraction of morphological
and biophysical traits of a large number of plants non-invasively in a relatively short time. It …

A model for estimating the area of individual leaves (LA) by employing their dimensions was
developed for chrysanthemum. Further hypotheses were tested:(a) LA estimation is …