Literature DB >> 32180619

Control of ascorbic acid in fortified powdered soft drinks using near-infrared spectroscopy (NIRS) and multivariate analysis.

Monique Carvalho de Santana1, Marcia Miguel Castro Ferreira2, Juliana Azevedo Lima Pallone1.   

Abstract

Powdered soft drinks (PSDs), fortified with antioxidants such as ascorbic acid (AA), are normally controlled by titration or chromatographic methods. This study evaluated the feasibility of using near-infrared spectroscopy (NIRS) and multivariate analysis to predict AA contents in PSDs as an alternative not-destructive method. The AA content of sixty-seven samples of commercial fortified grape and passion fruit PSDs was analyzed by the standard method (titration) and showed significant variance between flavors within the same brand. In addition, 75% of the samples required from 0.3 to 10.2 more cups of grape than passion fruit flavor to supply the AA Reference Nutrient Intake for children and adults. Spectral and reference data sets were split into calibration and validation sets. Partial least squares regression models were built and validated for the determination of AA in both PSDs. The model's basic statistics for grape flavor PSDs (RMSEC = 0.49 mg g-1, Rcal 2 = 0.84; RMSECV = 0.67 mg g-1, RCV 2 = 0.70; RMSEP = 0.50 mg g-1, Rpred 2 = 0.84), and that for passion fruit flavor PSDs (RMSEC = 0.24 mg g-1, Rcal 2 = 0.95; RMSECV = 0.56 mg g-1, RCV 2 = 0.76; RMSEP de 0.57 mg g-1, Rpred 2 = 0.72) indicated that NIRS-PLS methodology produced reasonable results. The limits of detection and quantification obtained showed that the method is useful to detect and quantify AA in the studied samples. A new set of grape drinks was used for external prediction and the RMSEP was 0.62 mg g-1, Rpred 2 was 0.72. Based on the results, NIRS-multivariate analysis proved to be useful for quality control of AA in commercialized grape and passion fruit in PSDs and a faster, objective and environmentally friendly method alternative to standard methods. © Association of Food Scientists & Technologists (India) 2019.

Entities:  

Keywords:  Alternative green method; Food quality control; PLS regression

Year:  2019        PMID: 32180619      PMCID: PMC7054581          DOI: 10.1007/s13197-019-04154-1

Source DB:  PubMed          Journal:  J Food Sci Technol        ISSN: 0022-1155            Impact factor:   2.701


  1 in total

1.  Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics.

Authors:  Priscila D Alamar; Elem T S Caramês; Ronei J Poppi; Juliana A L Pallone
Journal:  Food Res Int       Date:  2016-04-30       Impact factor: 6.475

  1 in total
  2 in total

Review 1.  QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs.

Authors:  David K Bwambok; Noureen Siraj; Samantha Macchi; Nathaniel E Larm; Gary A Baker; Rocío L Pérez; Caitlan E Ayala; Charuksha Walgama; David Pollard; Jason D Rodriguez; Souvik Banerjee; Brianda Elzey; Isiah M Warner; Sayo O Fakayode
Journal:  Sensors (Basel)       Date:  2020-12-07       Impact factor: 3.576

Review 2.  Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview.

Authors:  Balkis Aouadi; John-Lewis Zinia Zaukuu; Flora Vitális; Zsanett Bodor; Orsolya Fehér; Zoltan Gillay; George Bazar; Zoltan Kovacs
Journal:  Sensors (Basel)       Date:  2020-09-24       Impact factor: 3.576

  2 in total

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