Using Infrared Spectroscopy for Tracking and Estimating Antioxidant in Tomato Fruit Fractions

Ayman Ibrahim, Hussin Daood, Zsuzsanna Bori and Lajos Helyes
Additional contact information
Ayman Ibrahim: Agricultural Engineering Research Institute (AEnRI), Agricultural Research Center (ARC), Dokki, Giza, Egypt
Hussin Daood: Regional Knowledge Centre, Szent Istvan University, Gödöllő, Hungary
Zsuzsanna Bori: Regional Knowledge Centre, Szent Istvan University, Gödöllő, Hungary
Lajos Helyes: Regional Knowledge Centre, Szent Istvan University, Gödöllő, Hungary

European Journal of Engineering and Technology Research, 2018, vol. 3, issue 5, 21-30

Abstract: Infrared technology has brought a quantum leap in the specialization of non-destructive systems for internal quality inspection of agricultural and food products. Applying near-infrared spectroscopy technique (NIRs) for tracking and estimating some antioxidants such as (Lycopene, ?-carotene, Phytoene and Phytofluenxe) in tomato fruit fractions (Exocarp, Mesocarp, Endocarp and Tomato pomace) with prediction model. High-performance liquid chromatography (HPLC) device showed the antioxidant concentrations values within tomato fractions. Where, the maximum and minimum values observed in the mesocarp and exocarp fractions. Also, tomato fractions color analysis confirmed these results. Meanwhile, mesocarp fraction within range dark red color with h°? 31.7°, due to increased lycopene concentration, whereas, exocarp fraction was 77.29° for h°, within yellow range. In addition to HPLC and color reference methods were consensus significantly with the different of spectral transformations by the regression of partial least square (PLS). NIR spectra and antioxidant in tomato fractions were taken to establish calibration models for tracking and estimating antioxidant in tomato fractions by using partial least squares (PLS) model. The obtained Coefficients of prediction model (R2p) were 0.95, 0.91, 0.93 and 0.94 for Lycopene, ?-Carotene, Phytoene and Phytofluenxe respectively. The values of (RPD) ratio obtained from the standard deviation to the standard error of prediction and also (RER) obtained from the standard error range of prediction model were varied for different tomato fractions and antioxidant content, and found that the NIR model suitable not only for screening the different concentrations values of antioxidants for tomato fractions, but also suitable for most applications including quality assurance.

Keywords: Near-Infrared Spectroscopy; HPLC; Tomato Anatomy; Color Analysis; Antioxidant; Partial Least-Squares (PLS) (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://eu-opensci.org/index.php/ejeng/article/view/60736 Abstract page (text/html)
https://eu-opensci.org/index.php/ejeng/article/download/60736/11891 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:3:y:2018:i:5:id:60736

DOI: 10.24018/ejeng.2018.3.5.736

Access Statistics for this article

More articles in European Journal of Engineering and Technology Research from European Open Science
Bibliographic data for series maintained by Support ().