Beghi Roberto, Giovenzana Valentina, Tugnolo Alessio, Guidetti Riccardo
Department of Agricultural and Environmental Sciences - Production, Landscape, Agroenergy, Università degli Studi di Milano, Milano, Italy.
J Sci Food Agric. 2018 May;98(7):2729-2734. doi: 10.1002/jsfa.8768. Epub 2017 Nov 29.
The market for fruits and vegetables is mainly controlled by the mass distribution channel (MDC). MDC buyers do not have useful instruments to rapidly evaluate the quality of the products. Decisions by the buyers are driven primarily by pricing strategies rather than product quality. Simple, rapid and easy-to-use methods for objectively evaluating the quality of postharvest products are needed. The present study aimed to use visible and near-infrared (vis/NIR) spectroscopy to estimate some qualitative parameters of two low-price products (carrots and tomatoes) of various brands, as well as evaluate the applicability of this technique for use in stores.
A non-destructive optical system (vis/NIR spectrophotometer with a reflection probe, spectral range 450-1650 nm) was tested. The differences in quality among carrots and tomatoes purchased from 13 stores on various dates were examined. The reference quality parameters (firmness, water content, soluble solids content, pH and colour) were correlated with the spectral readings. The models derived from the optical data gave positive results, in particular for the prediction of the soluble solids content and the colour, with better results for tomatoes than for carrots.
The application of optical techniques may help MDC buyers to monitor the quality of postharvest products, leading to an effective optimization of the entire supply chain. © 2017 Society of Chemical Industry.
水果和蔬菜市场主要由大规模分销渠道(MDC)控制。MDC的买家没有有效的工具来快速评估产品质量。买家的决策主要受定价策略驱动,而非产品质量。因此需要简单、快速且易于使用的方法来客观评估采后产品的质量。本研究旨在利用可见和近红外(vis/NIR)光谱法估算不同品牌的两种低价产品(胡萝卜和番茄)的一些质量参数,并评估该技术在商店中的适用性。
测试了一种无损光学系统(配备反射探头的vis/NIR分光光度计,光谱范围450 - 1650 nm)。研究了在不同日期从13家商店购买的胡萝卜和番茄之间的质量差异。将参考质量参数(硬度、水分含量、可溶性固形物含量、pH值和颜色)与光谱读数进行关联。从光学数据得出的模型取得了积极成果,特别是在预测可溶性固形物含量和颜色方面,番茄的预测结果优于胡萝卜。
光学技术的应用可能有助于MDC买家监测采后产品的质量,从而有效优化整个供应链。© 2017化学工业协会。