StomataScorer: a portable and high-throughput leaf stomata trait scorer combined with deep learning and an improved CV model.

ABSTRACT: To measure stomatal traits automatically and nondestructively, a new method for detecting stomata and extracting stomatal traits was proposed. Two portable microscopes with different resolutions (TipScope with a 40× lens attached to a smartphone and ProScope HR2 with a 400× lens) are used to acquire images of living stomata in maize leaves. FPN model was used to detect stomata in the TipScope images and measure the stomata number and stomatal density. Faster RCNN model was used to detect opening and closing stomata in the ProScope HR2 images, and the number of opening and closing stomata was measured. An improved CV model was used to segment pores of opening stomata, and a total of 6 pore traits were measured. Compared to manual measurements, the square of the correlation coefficient (R

SUBMITTER: Liang X 

PROVIDER: S-EPMC8882810 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature