Relationships between anthocyanin content and some pomological and colour characteristics of black mulberry (Morus nigra) fruit

Year 2024, Volume: 6 Issue: 1, 55 - 62, 30.06.2024

Osman Nuri Öcalan , Onur Saraçoğlu

https://doi.org/10.53663/turjfas.1440608

Abstract

The analytical method used to determine the total monomeric anthocyanin content of fruits is costly and labour intensive. Researchers are endeavouring to develop prediction models to determine anthocyanin content in a simpler and more accurate way. The aim of this study was to investigate whether there is a relationship between anthocyanin and some fruit characteristics (width, length, weight, L*, a*, b*, chroma, hue) in black mulberry (Morus nigra) fruit. With the outputs of the study, it is aimed to provide preliminary information for the models to be developed for anthocyanin estimation in future studies. The study material, black mulberry fruits, was collected from a single black mulberry tree in Kemalpaşa village of Tokat province in July 2022. Harvesting of the fruits continued for two weeks as raw, semi-ripe and ripe. A total of 586 fruits were individually evaluated and the weight, width, length, colour parameters (L*, a*, b*, chroma, and hue) and total monomeric anthocyanin contents of each fruit were determined. Then, Pearson correlation coefficients between the variables were determined. Stepwise regression analysis was used to find the appropriate model to explain the change in the dependent variable anthocyanin with independent variables (length, width, weight, L*, a*, b*, chroma, hue). After the multiple regression model was established, residual analysis was performed to see the outliers in the full model and to check the accuracy of the model. As a result of the study, it was observed that anthocyanin content could be predicted by colour parameters up to a certain maturity stage. This relationship was found to weaken at the ripeness stage when the fruit colour turns black.

Keywords

Chroma, Hue, Pearson correlation analysis, Stepwise regression analysis

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