On-field monitoring of fruit ripening evolution and quality parameters in olive mutants using a portable NIR-AOTF device. (15th May 2016)

• Record Type: Journal Article
• Authors: Cirilli, Marco; Bellincontro, Andrea; Urbani, Stefania; Servili, Maurizio; Esposto, Sonia; Mencarelli, Fabio; Muleo, Rosario
• Is Part Of: Food chemistry. Volume 199(2016)
• Page Start: 96
• Page End: 104
• Publication Date: 2016-05-15
• Subjects: AOTF Acousto Optically Tunable Filter -- cv. cultivar -- DAD diode-array detector -- FLD fluorescence detector -- NIR near infrared -- PCA Principal Component Analysis -- PLS Partial Least Square -- RMSEC Root Mean Standard error in Calibration -- RMSECV Root Mean Standard error in Cross-Validation -- RMSEP Root Mean Standard error in Prediction -- RPD residual predictive deviation -- 3, 4-DHPEA-EDA 3, 4-DHPEA-Elenolic acid Di-Aldehyde (Oleuropein-aglycone di-aldehyde); Chlorophyll a (PubChem CID: 6449992) -- Chlorophyll b (PubChem CID: 46173742) -- Oleuropein (PubChem CID: 5281544) -- Oleuropein-aglycone di-aldehyde (3, 4-DHPEA-EDA) (PubChem CID: 56842347) -- Quercetin-3-O-rutinoside (rutin) (PubChem CID: 5280805) -- Verbascoside (PubChem CID: 5281800); Olive fruits -- Total phenols -- Oleuropein -- Verbascoside -- Rutin -- NIR-AOTF spectroscopy -- Firmness -- Partial Least Square regression (PLSR); Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2015.11.129
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Feasibility of NIR-AOTF as a spectral tool to predict olive firmness has been established. NIR-AOTF portable device can be used on-field non-destructive prediction of olive attributes. The knowledge of optimal harvesting time improves high quality extra virgin olive oil production. Abstract: This study optimizes the application of portable Near Infrared-Acousto Optically Tunable Filter (NIR) device to meet the increasing demand for cost-effective, non-invasive and easy-to-use methods for measuring physical and chemical properties during olive fruit development. Fruits from different phenotypically cultivars were sampled for firmness, total and specific phenols detection by HPLC, total anthocyanins, chlorophyll and carotenoids detection by spectrophotometry. On the same fruits, a portable NIR device in diffuse reflectance mode was employed for spectral detections. Predictive models for firmness, chlorophyll, anthocyanins, carotenoids and rutin were developed by Partial Least Square analysis. Oleuropein, verbascoside, 3, 4-DHPEA-EDA, and total phenols were used to develop a validation model. Internal cross-validation was applied for calibration and predictive models. The standard errors for calibration, cross-validation, prediction, and RPD ratios (SD/SECV) were calculated as references for the model effectiveness. The determination of the optimal harvesting time facilitates the production of high quality extra virgin olive oil and table olives.