Application of the Non-Destructive NIR Technique for the Evaluation of Strawberry Fruits Quality Parameters

Abstract

The determination of strawberry fruit quality through the traditional destructive lab techniques has some limitations related to the amplitude of the samples, the timing and the applicability along all phases of the supply chain. The aim of this study was to determine the main qualitative characteristics through traditional lab destructive techniques and Near Infrared Spectroscopy (NIR) in fruits of five strawberry genotypes. Principal Component Analysis (PCA) was applied to search for spectral differences among all the collected samples. A Partial Least Squares regression (PLS) technique was computed in order to predict the quality parameters of interest. The PLS model for the soluble solids content prediction was the best performing—in fact, it is a robust and reliable model and the validation values suggested possibilities for its use in quality applications. A suitable PLS model is also obtained for the firmness prediction—the validation values tend to worsen slightly but can still be accepted in screening applications. NIR spectroscopy represents an important alternative to destructive techniques, using the infrared region of the electromagnetic spectrum to investigate in a non-destructive way the chemical–physical properties of the samples, finding remarkable applications in the agro-food market.

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

“…Several properties of fruits such as water content, sugar content, chlorophyll, carotenoid, soluble solid, acidity, and firmness are measured for fruit quality assessment. The spectroscopy/spectral imagery are non-destructive and highthroughput methods to estimate these qualitative parameters (Berardo et al, 2004;ElMasry et al, 2007;Shao and He, 2008;Wu et al, 2008;Nishizawa et al, 2009;Penchaiya et al, 2009;Ecarnot et al, 2013;Guo et al, 2013;Dykes et al, 2014;Wang et al, 2015;Mancini et al, 2020). However, a robotic system can be presented to monitor the dynamics of these attributes for hundreds of growing fruits per day.…”

Nondestructive monitoring of polyphenols and caffeine during green tea processing using Vis‐NIR spectroscopy

“…Therefore, chemometric techniques were needed for spectral analysis. PCA was employed to assess the ability of Vis‐NIR spectroscopy to qualitatively classify samples according to their variety and processing step (Mancini et al., 2020).…”

“…Therefore, chemometric techniques were needed for spectral analysis. PCA was employed to assess the ability of Vis-NIR spectroscopy to qualitatively classify samples according to their variety and processing step (Mancini et al, 2020). Figure 6 shows the result of PCA on the first 3 principal components (PC1, PC2, and PC3) of tea samples that indicated the correlations between the Vis-NIR spectra and different classes.…”

Rapid Quality Control of Woodchip Parameters Using a Hand-Held Near Infrared Spectrophotometer

“…MicroNIR has been already used in various fields, such as agrifood and seafood sectors, microbiological, petrochemical and pharmaceutical sectors, and bioenergy along with forestry and wood industry. In the agrifood and seafood sectors, portable NIR spectroscopy plays a fundamental role in continuous and rapid quality control of products [18][19][20][21]. Likewise, the increasing of NIR spectroscopy in industrial applications, for instance in the microbiological, petrochemical and pharmaceutical sectors, is determined by the possibility to analyze a significant amount of samples quickly and cost-effectively [22,23].…”