On site monitoring of Grana Padano cheese production using portable spectrometers

L. Marinoni, A. Stroppa, S. Barzaghi, K. Cremonesi, Nicolò Pricca, A. Meucci, Giulia Pedrolini, Andrea Galli, G. Cabassi
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引用次数: 4

Abstract

Author Summary: The GRANIR project founded by the Grana Padano Protection Consortium and developed by CREA-ZA research centre is devoted to the development of a rapid and economic method for the chemical characterisation of Grana Padano PDO cheese based on near infrared (NIR) spectroscopy technology. For this purpose, the Consortium purchased several portable spectrometers XNIRTM (dinamica generale®, Poggio Rusco, MN, Italy), to be assigned to the Consortium staff for screening operations of production batches in the fire-branding step, in warehouses and at the packaging step, on cheese paste. To develop predictive models and to evaluate the performance of the portable instruments, 195 samples of Grana Padano were scanned directly on the whole open wheel, scanning both rind and cheese paste. Robust models were built for the prediction of dry matter, fat, fat/dry matter, proteins and proteins/dry matter content using average spectra of rind and paste and chemical data of cheese paste. Additional spectra acquired with two other instruments were included in order to make the models less sensitive to different instruments. Spectra of the same samples acquired at different temperatures (10, 16 and 25 °C) were also added to the dataset in order to reduce the influence of temperature on prediction results. The obtained results showed a satisfactory predictive ability of the models built with portable NIR spectrometers, with respect to the chemical composition of Grana Padano cheese, showing root mean square errors in prediction comparable to that obtained with a Fourier-Transform NIR benchtop instrument. This allows the estimation of average cheese composition, at batch level, using multiple scans taken on a high number of wheels.
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利用便携式光谱仪对帕达诺干酪生产进行现场监测
GRANIR项目由Grana Padano保护协会发起,由CREA-ZA研究中心开发,致力于开发一种基于近红外(NIR)光谱技术的快速经济的Grana Padano PDO奶酪化学表征方法。为此,联盟购买了几台便携式光谱仪XNIRTM (dinamica generale®,Poggio Rusco, MN,意大利),分配给联盟工作人员,用于在仓库和包装阶段对奶酪膏进行生产批次的筛选操作。为了建立预测模型并评估便携式仪器的性能,对195个Grana Padano样品在整个开放式车轮上进行了直接扫描,同时扫描了皮和奶酪酱。利用干酪糊的皮和糊平均光谱和化学数据,建立了预测干物质、脂肪、脂肪/干物质、蛋白质和蛋白质/干物质含量的稳健模型。为了降低模型对不同仪器的敏感性,还包括了用另外两种仪器获得的附加光谱。为了减少温度对预测结果的影响,还将在不同温度(10、16和25°C)下获得的相同样品的光谱添加到数据集中。结果表明,便携式近红外光谱仪建立的模型对Grana Padano奶酪的化学成分具有令人满意的预测能力,其预测的均方根误差与傅里叶变换近红外台式仪器的预测结果相当。这允许估计平均奶酪成分,在批级,使用多次扫描采取了大量的车轮。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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