Prediction of Salicornia europaea L. biomass using a computer vision system to distinguish different salt-tolerant populations.

ABSTRACT:

Background

Salicornia europaea L. is emerging as a versatile crop halophyte, requiring a low-cost, non-destructive method for salt tolerance classification to aid selective breeding. We propose using a computer vision system (CVS) with multivariate analysis to classify S. europaea based on morphometric and colour traits to predict plant biomass and the salinity in their substrate.

Results

A trial and validation set of 96 and 24 plants from 2 populations confirmed the efficacy. CVS and multivariate analysis evaluated the plants by morphometric traits and CIELab colour variability. Through Pearson analysis, the strongest correlations were between biomass fresh weight (FW) vs. projected area (PA) (0.91) and anatomical cross-section (ACS) vs. shoot diameter (Sd) (0.94). The PA a

SUBMITTER: Cardenas-Perez S 

PROVIDER: S-EPMC11568609 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature