METABOLOMIC STUDIES FOR ASSESSMENT OF NUTRITIONAL VALUE OF COCONUT THROUGH DIFFERENT NUT DEVELOPMENTAL STAGES

Abstract

Coconut (Cocos nucifera) is an economically important fruit. The liquid (coconut water) and solid (coconut meat) endosperm of coconut bear tremendous nutritional value in terms of several healthprotective chemical constituents. Nutritional constituents of coconut water and meat change with nut developmental stages. Deciphering the metabolic and nutritional changes during the process of nut development and maturation is of immense scientific and commercial interest owing to their role in making several food products. During the nut development and maturation process, how metabolic and nutritional constituents differ will allow identifying appropriate nut developmental stages for the preparation of nutritionally balanced customized coconut-based edible products. To date, a systematic study on changes in the nutritional profile of coconut with nut developmental stages is not well defined. Furthermore, coconut water is well known for its refreshing test and health-protective properties and is extensively used for the production of value-added products. However, during the production of value-added products from coconut, if there is any spoiled coconut in the batch, its water contaminates the entire pool of collected water at pre-processing stage due to the mixing of spoiled coconut water. As a result, a huge amount of coconut water (Approximately 150 to 160 million liters per year) is wasted without any value addition. To date, any technology for the detection of infected/spoiled coconuts at the pre-processing stage is not available. The main goal of this thesis is to decipher the metabolic and nutritional changes happening in the coconut at defined nut developmental stages and to identify metabolite biomarkers for the prediction of appropriate nut developmental stages. In addition, this thesis works aims to identify some signature volatiles emitting from the spoiled coconuts, which can be used as biomarkers for the non-destructive prediction of coconut quality. The goal was achieved by integrating mass-spectrometry-based metabolomics approaches, multivariate statistical analyses, head-space-enabled volatile profile, and nutritional profile. In this study, two coconut varieties 'Chowghat Orange Dwarf ' (COD) and 'Malayan Yellow Dwarf' (MYD) were used. At first, robust Chromatography-Mass Spectrometry (GC-MS)-based metabolomics technique was optimized for the metabolite profiling from coconut water and coconut meat at four, and using Gas Chromatography-Mass Spectrometry (GC-MS) data analysisacids, minerals, and secondary metabolites from coconuts at different developmental stages was reported. Coconut water from ‘COD’ and ‘MYD’ varieties was collected at four different maturity stages (very young and tender to mature). A gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach was used to identify the metabolites responsible for discriminating the nutrients present in coconut water according to different nut maturity stages. Significant changes in the physicochemical properties, nutritional (free amino acid, protein, sugar, and ascorbic acid), and metabolite profile were observed within each variety during nut maturation. Developmentassociated changes in the mineral composition of coconut water were also observed. Ultraperformance liquid chromatography (UPLC) analyses identified 17 amino acids from coconut water of 'COD' and 'MYD' varieties. Using partial least squares discriminant analysis (PLS-DA) eight metabolites were identified which could be used as biomarkers to distinguish between the nut maturity stages. In addition, detailed metabolite and mineral profiles of coconut meat from ‘COD’ and ‘MYD’ at three different developmental stages from two 'Chowghat Orange Dwarf ' (COD) and 'Malayan Yellow Dwarf' (MYD) varieties, were carried out using GC-MS. GC-MS-based metabolomics analyses identified a total of 43 and 40 metabolites, including all the developmental stages of 'COD' and 'MYD,' respectively. The majority of metabolites showing differential changes during maturation belong to primary metabolites. The multivariate partial least squaresdiscriminant analysis (PLS-DA) together with variable importance in projection scores, identified the top 15 metabolites from each variety which shows the maximum influence on the separation of maturity stages. Furthermore, to non-invasively distinguish healthy coconuts from spoiled coconuts, volatile organic compounds (VOCs) emitted from the intact nuts were profiled and selected signature VOCs were used as non-invasive biomarkers. Solid-phase microextraction (SPME) coupled with GC-MS analysis of intact healthy and spoiled coconuts have identified four volatiles (ethyl butanoate, undecane, ethyl caprylate, and 2-undecanone) as biomarkers for spoiled nut detection. Overall, these highly informative current data sets on the mineral, metabolite, and nutritional profile of coconuts can be used in developing nutritionally balanced customized formulations from coconut water. Proposed metabolite biomarkers can be used in the screening of appropriate nut maturity stages. The proposed volatile biomarkers can be used as targets for the future development of e-nose sensors to facilitate rapid non-destructive quality monitoring of nuts. was optimized. Comprehensive analysis of sugars, sugar alcohols, organic acids, amino acids fatty