Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

Assessing the feasibility of a miniaturized near infrared spectrometer in determining quality attributes of San Marzano tomato

Academic Article
Publication Date:
2019
abstract:
The paper is aimed to assess the feasibility of using a miniature near infrared (NIR) spectrometer to determine quality attributes of tomato fruits. To reach this objective, a total of 300 tomato fruits of San Marzano variety coming from two different fields, cropped under two different regimes (integrated and organic), were collected and analyzed using a handheld spectrometer (MicroNIR 1700 by Viavi Solutions® working between 908 and 1650 nm). Simultaneously, several quality attributes were determined using reference methods: fresh weight, pH, dry matter, chromatic values, electrical conductivity, titratable acidity and soluble solids content. Combining the spectra with chemical attributes, it was possible to understand that the best way for acquiring NIR data on tomato fruits is scanning the whole equatorial area, due to fruit heterogeneous internal structure. Moreover, after a proper data pre-processing, accurate predictive models were obtained using partial least square (PLS) regression to estimate physico-chemical properties of tomato in a rapid and non-destructive way. An impact of this comprehensive study is the possibility of determining tomato chemical attributes in real time, leading to a high quality San Marzano tomato according to the Protected Designation of Origin (PDO) legislation.
Iris type:
01.01 Articolo in rivista
Keywords:
Tomato; Protected Designation of Origin (PDO); near-infrared spectroscopy; partial least square regression (PLS)
List of contributors:
Buttafuoco, Gabriele
Authors of the University:
BUTTAFUOCO GABRIELE
Handle:
https://iris.cnr.it/handle/20.500.14243/350726
Published in:
FOOD ANALYTICAL METHODS
Journal
  • Overview

Overview

URL

https://link.springer.com/journal/12161
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)