Work

Non-destructive assessment of quality parameters in Javadi cv. Peach fruits using Vis/NIR spectroscopy and multiple regression analysis

Year: 2025

Type: article

Abstract: This study aimed to non-destructively identify quality parameters in Javadi peaches. In this context, a capacitive array (CCD) spectroradiometer ranging from 350 to 1150 nm was employed for the nondestructive prediction of pH, titrable acid (TA), soluble solid-state (SSC), total phenol (TP), extract anthocyanin (Prance and Nesbitt). Utilizing multivariate partial least squares (PLS) regression models, both reference and degradation measurements were considered. Various spectral data processing techniques such as Savitsky-Goley smoothing (SG), first derivative (D1), incremental diffusivity correction (MSC), standard normal variate (SNV), and Baseline correction were applied individually and in combination (SG + MSC + D1) and (SG + Baseline) to forecast peach quality attributes. Model performance was assessed using the root mean square error of prediction (RMSEP), correlation coefficient (rp), and standard deviation ratio (SDR). Optimal models showed high accuracy for pH (raw spectra: RMSEP = 0.15, rp = 0.94, SDR = 3.0), moderate for TA (first derivative: RMSEP = 0.07, rp = 0.86, SDR = 2.29) and SSC (MSC: RMSEP = 1.17, rp = 0.85, SDR = 1.88), but lower for TP and EA (SDR < 1.5). This non-destructive approach offers rapid, cost-effective quality assessment compared to destructive methods.

Source: Food Chemistry

DOI: 10.1016/j.foodchem.2025.146401

Authors: Vali Rasooli Sharabiani, Nadia Saadati, Fatemeh Alizadeh, Mariusz Szymanek

Institutions: University of Mohaghegh Ardabili, University of Life Sciences in Lublin

Language: English

Topic: Spectroscopy and Chemometric Analyses

Subfield: Analytical Chemistry

Field: Chemistry

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: hybrid

Estimated APC paid: $4,930