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Microbial quality assessment of minimally processed pineapple using GCMS and FTIR in tandem with chemometrics.

ABSTRACT: Microbial quality is the critical parameter determining the safety of refrigerated perishables. Traditional methods used for assessing microbial quality are time consuming and labour intensive. Thus rapid, non-destructive methods that can accurately predict microbial status is warranted. Models using partial least square regression (PLS-R) from chemical finger prints of minimally processed pineapple during storage obtained by Headspace Solid Phase Microextraction Gas Chromatography Mass Spectrometry (HS-SPME-GCMS), Fourier Transform Infrared (FTIR) spectroscopy and their data fusion are developed. Models built using FTIR data demonstrated good prediction for unknown samples kept under non-isothermal conditions. FTIR based models could predict 87 and 80% samples within?±1?log CFU/g for TVC and Y&M, respectively. Analysis of PLS-R results suggested the production of alcohols and esters with utilization of sugars due to microbial spoilage.

SUBMITTER: Adiani V

PROVIDER: S-EPMC7148306 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Microbial quality assessment of minimally processed pineapple using GCMS and FTIR in tandem with chemometrics.

Adiani Vanshika V Gupta Sumit S Variyar Prasad S PS

Scientific reports 20200410 1

Microbial quality is the critical parameter determining the safety of refrigerated perishables. Traditional methods used for assessing microbial quality are time consuming and labour intensive. Thus rapid, non-destructive methods that can accurately predict microbial status is warranted. Models using partial least square regression (PLS-R) from chemical finger prints of minimally processed pineapple during storage obtained by Headspace Solid Phase Microextraction Gas Chromatography Mass Spectrom ...[more]

PMID: 32277084

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