Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective.

ABSTRACT: 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 emerging aspects of computer vision for automated plant phenotyping. Recent advances in image analysis empowered by machine learning-based techniques, including convolutional neural network-based modeling, have expanded their application to assist high-throughput plant phenotyping. Combinatorial use of multiple sensors to acquire various spectra has allowed us to noninvasively obtain a series of datasets, including those related to the development and physiological responses of plants throughout their life. Automated phenotyping platforms accelerate the elucidation of gene functions associated with traits in model plant

SUBMITTER: Mochida K 

PROVIDER: S-EPMC6312910 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature