Cirilli Marco, Bellincontro Andrea, Urbani Stefania, Servili Maurizio, Esposto Sonia, Mencarelli Fabio, Muleo Rosario
Department of Agriculture, Forestry, Nature and Energy (DAFNE), Molecular Ecophysiology of Woody Plant Laboratory, University of Tuscia, Viterbo, Via San Camillo de Lellis snc, 01100 Viterbo, Italy.
Department for Innovation in Biological Agro-food and Forest systems (DIBAF), Postharvest Laboratory, University of Tuscia, Viterbo, Via San Camillo de Lellis snc, 01100 Viterbo, Italy.
Food Chem. 2016 May 15;199:96-104. doi: 10.1016/j.foodchem.2015.11.129. Epub 2015 Nov 30.
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.
本研究优化了便携式近红外声光可调滤光器（NIR）设备的应用，以满足对在橄榄果实发育过程中测量物理和化学性质的经济高效、非侵入性且易于使用的方法日益增长的需求。对来自不同表型品种的果实进行采样，通过高效液相色谱法检测硬度、总酚和特定酚类，通过分光光度法检测总花青素、叶绿素和类胡萝卜素。在相同的果实上，使用漫反射模式的便携式近红外设备进行光谱检测。通过偏最小二乘法分析建立了硬度、叶绿素、花青素、类胡萝卜素和芦丁的预测模型。利用橄榄苦苷、毛蕊花糖苷、3,4-二羟基苯乙醇-乙二胺和总酚建立了验证模型。将内部交叉验证应用于校准模型和预测模型。计算校准、交叉验证、预测的标准误差以及RPD比率（SD/SECV），作为模型有效性的参考。确定最佳收获时间有助于生产高质量的特级初榨橄榄油和食用橄榄。
