Predicting plant biomass accumulation from image-derived parameters.

ABSTRACT:

Background

Image-based high-throughput phenotyping technologies have been rapidly developed in plant science recently, and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologists. However, it is a great challenge to find a predictive biomass model across experiments.

Results

In the present study, we constructed 4 predictive models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to 3 consecutive barley (Hordeum vulgare) experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based paramet

SUBMITTER: Chen D 

PROVIDER: S-EPMC5827348 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature