Metabolite Profiling to Predict Tongar Avocado’s Maturity

Accurate methods are needed to find fruit maturity stages, preserve quality, and prolong postharvest shelf life. Metabolomics helps analyze postharvest fruit development. Essential clues are also provided to analyze biomarkers in enhancing postharvest fruit technology by observing significant changes. Therefore, this analysis conducts a sequence-based metabolome analysis of high-quality fruit Tongar avocado, produced in West Sumatra, Indonesia. It was carried out on samples collected at 180, 210, and 240 days after flowering using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). The results indicate that LC-HRMS identified 31 metabolites, including fatty alcohols, furan derivatives, phenolics, and fatty acids (FAs). Furthermore, the identified metabolites were most abundant at the 180-day harvest time. Avocadene and AcO d–avocadyne were suspected as potential marker metabolites, differentiating the three different harvesting times. A PLSR (partial least square regression) model was improved according to the 31 metabolites and physicochemical parameter correlation, including ethylene production (EP) and TSS (total soluble solids). The identified metabolites can help to predict EP and TSS. These results provided a thorough understanding of changes in metabolite profiling and reported the ability to predict the Tongar avocado maturity.