Non-destructive Phenotypic Analysis of Early Stage Tree Seedling Growth Using an Automated Stereovision Imaging Method.

Abstract

A plant phenotyping approach was applied to evaluate growth rate of containerized tree seedlings during the precultivation phase following seed germination. A simple and affordable stereo optical system was used to collect stereoscopic red-green-blue (RGB) images of seedlings at regular intervals of time. Comparative analysis of these images by means of a newly developed software enabled us to calculate (a) the increments of seedlings height and (b) the percentage greenness of seedling leaves. Comparison of these parameters with destructive biomass measurements showed that the height traits can be used to estimate seedling growth for needle-leaved plant species whereas the greenness trait can be used for broad-leaved plant species. Despite the need to adjust for plant type, growth stage and light conditions this new, cheap, rapid, and sustainable phenotyping approach can be used to study large-scale phenome variations due to genome variability and interaction with environmental factors.

Code and data availability

The paper describes an in-house stereovision phenotyping system with custom software (uEyeDualCam, HeightMap, Acreo Swedish ICT), but no public phenotype dataset, image collection, or code deposit is mentioned. The only URLs are the license, a camera product page, and a vendor whitepaper—none are paper-specific assets.

No evidence-backed public reproduction asset is currently recorded.