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.
On-field monitoring of fruit ripening evolution and quality parameters in olive mutants using a portable NIR-AOTF device
Mencarelli F;
2016-01-01
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.File | Dimensione | Formato | |
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