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Non-Destructive Quality Evaluation of 80 Tomato Varieties Using Vis-NIR Spectroscopy

  • Lilija Duckena*
  • , Reinis Alksnis
  • , Ieva Erdberga
  • , Ina Alsina
  • , Laila Dubova
  • , Mara Duma
  • *Corresponding author for this work
  • Latvia University of Life Sciences and Technologies

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

Traditional biochemical methods are resource- and time-consuming; therefore, there is a need for cost-effective alternatives. A spectral analysis is one of the non-destructive techniques that are more widely used for fruit quality determination; however, references are needed for traditional methods. In this study, visible and near-infrared (Vis-NIR) spectroscopy was used to analyze the internal quality attributes of tomatoes. For the first time, 80 varieties with large differences in fruit size, shape, color, and internal structure were used for an analysis. The aim of this study was to develop models suitable to predict a taste index, as well as the content of lycopene, flavonoids, β-carotene, total phenols, and dry matter of intact tomatoes based on Vis-NIR reflectance spectra. The content of phytochemicals was determined in 80 varieties of tomatoes. A total of 140 Vis-NIR reflectance spectra were obtained using the portable spectroradiometer RS-3500 (Spectral Evolution Inc.). Partial least squares regression (PLS) and multiple scatter correction (MSC) were used to develop calibration models. Our results indicated that PLS models with good prediction accuracies were obtained. The present study showed the high capability of Vis-NIR spectroscopy to determine the content of lycopene and dry matter of intact tomatoes with a determination coefficient of 0.90 for both parameters. A regression fit of (Formula presented.) = 0.86, (Formula presented.) = 0.84, (Formula presented.) = 0.82, and (Formula presented.).73 was also achieved for the taste index, flavonoids, β-carotene, and total phenols, respectively.

Original languageEnglish
Article number1990
JournalFoods
Volume12
Issue number10
DOIs
Publication statusPublished - May 2023
Externally publishedYes

Keywords

  • partial least squares regression (PLS)
  • phytochemicals
  • Solanum lycopersicumL
  • Vis-NIR spectroscopy

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