A phenotyping method to predict β-carotene content of cassava tuberous root using ImageJ

Abstract

Cassava (Manihot esculenta) tuberous roots are crucial in carbohydrate production, serving as a staple food and industrial material for decades. High β-carotene content is essential for nutrition and stress tolerance, conserving in yellow-fleshed cassava tuberous roots. However, the complex and costly laboratory analysis of the β-carotene content is an obstacle. This study aims to develop a simple and precise phenotyping method for predicting the β-carotene content of cassava tuberous root using grayscale analysis with ImageJ. This study was conducted at the Research Centre for Genetic Engineering, Bogor, in October 2021 for the training set and October 2022 for the validating set. The training set used six yellow and three white-fleshed cassava cultivars as genetic materials. Seven other white-fleshed cassava cultivars were added to the validating set. The grayscale analysis accurately distinguished the white and yellow-fleshed cassava cultivars, reflecting variation in the β-carotene content. This phenotyping method showed a stable result in the validating set. Additionally, a robust correlation was found between β-carotene content and grayscale values, showing the ability of grayscale analysis to predict β- carotene content. Thus, this method could be advantageous in a massive and early selection of the β-carotene content in segregated cassava populations.