Postharvest Characterization of Olive Oil Fruits Texture by NIR and Vis/NIR Spectroscopy

Abstract

For olive oil fruits, textural properties could be used as indices of ripeness to meet requirements for technological process and oil characterization. Texture measuring instruments are time consuming and envisage high cost for devices. Increasing demand for rapid, cost-effective and non-invasive measurement of texture remains a challenge in the food process. This work studied the applicability of vis/NIR (400-1,000 nm) and NIR (1,000-2,000 nm) spectroscopy as rapid techniques for the characterization of olives texture, directly at the mill just before oil extraction process. Mechanical analyses (breaking point force, total deformation energy, stiffness) were performed on fruit flesh using a laboratory dynamometer. Moreover, a firmness (N) analysis was done using a digital penetrometer. The destructive analyses and the optical acquisitions were carried out on 100 olives harvested in November 2012. Principal component analysis (PCA) was performed on vis/NIR and NIR spectra to examine sample groupings and a partial least square (PLS) regression algorithm was used to correlate samples spectra and physical properties. Regarding the vis/NIR results, PCA pointed out a good separation among samples according to texture parameters; the best PLS models, in validation, were elaborated for stiffness (R2 = 0.85 and RPD = 2.53) and firmness (R2 = 0.86 and RPD = 2.67). Slightly better results were obtained for NIR spectroscopy. PCA showed a fairly good separation among classes and the best PLS models were achieved again for stiffness (R2 = 0.86 and RPD = 2.72) and firmness (R2 = 0.87 and RPD = 2.62). The study provides the sector with postharvest methods and sorting systems for a quick evaluation of olive oil fruits texture. Therefore, the vis/NIR and NIR spectroscopy could give support to producers for preliminary decisions about the destination of olives before the oil extraction process.