Non-destructive determination of color, titratable acidity, and dry matter in intact tomatoes using a portable Vis-NIR spectrometer

• Published in: Journal of food composition and analysis Vol. 107; p. 104288
• Main Authors: Arruda de Brito, Annelisa, Campos, Fernanda, dos Reis Nascimento, Abadia, Damiani, Clarissa, Alves da Silva, Flávio, de Almeida Teixeira, Gustavo Henrique, Cunha Júnior, Luis Carlos
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-04-2022
• Subjects: Chemometrics; Partial least square; Portable Vis-Nir; Principal component analysis; Quality food; Portable Vis-Nir; Quality food; Chemometrics; Partial least square; Principal component analysis
• ISSN: 0889-1575; 1096-0481
• DOI: 10.1016/j.jfca.2021.104288

•The spectra were collected in optical geometry interactance.•The samples varied in origin and planting season.•Portable Vis-NIR spectrometer were used for spectra collection.•The Vis-NIR models allowed the prediction of color and dry matter parameters.
Fruit color and chemical composition, particularly dry matter and titratable acidity (TA), are important tomato-quality parameters for consumers. Therefore, a single test allowing for the evaluation of these parameters simultaneously would improve the efficiency of this analysis. Vis-NIR spectroscopy has been used to identify many compounds in fruits and vegetables, therefore, here, a portable Vis-NIR spectrometer was used to collect the spectra of fresh tomatoes produced from November 2018 to November 2019, in five tomato cropping regions in Brazil, namely, Goiás, Bahia, Santa Catarina, Minas Gerais, and São Paulo states. Calibration and prediction models were developed using the 396–1,131 nm spectral region, through principal component analysis (PCA), and partial least square regression (PLS). Strong prediction results (root mean square of error prediction, RMSEP; coefficient of prediction, Rp²; and standard deviation ratio, SDR) were obtained for the color parameter a*, representing red (RMSEP = 2.89, Rp² = 0.94, SDR = 4.11), and the amount of dry matter (RMSEP = 0.46 %; Rp² = 0.59 % SDR = 1.92). However, poor prediction results were obtained for titratable acidity (RMSEP = 0.07 %; SDR = 1.15). These findings indicate that color (a*) and dry matter of intact tomatoes may be predicted using a portable Vis-NIR spectrometer.