The paper 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 solid 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.

Assessing the Feasibility of a Miniaturized Near-Infrared Spectrometer in Determining Quality Attributes of San Marzano Tomato

Malegori C.;
2019-01-01

Abstract

The paper 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 solid 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1027237
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