A Non-destructive Method to Quantify Leaf Starch Content in Red Clover.

ABSTRACT: Grassland-based ruminant livestock production provides a sustainable alternative to intensive production systems relying on concentrated feeds. However, grassland-based roughage often lacks the energy content required to meet the productivity potential of modern livestock breeds. Forage legumes, such as red clover, with increased starch content could partly replace maize and cereal supplements. However, breeding for increased starch content requires efficient phenotyping methods. This study is unique in evaluating a non-destructive hyperspectral imaging approach to estimate leaf starch content in red clover for enabling efficient development of high starch red clover genotypes. We assessed prediction performance of partial least square regression models (PLSR) using cross-validation, and v

SUBMITTER: Frey LA 

PROVIDER: S-EPMC7593268 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature