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利用振动光谱法测定面食中的水分含量。

Determining moisture content in pasta by vibrational spectroscopy.

机构信息

Department of Chemistry, University of Wrocław, 14F. Joliot-Curie, 50-383 Wrocław, Poland.

Engineering and Cereals Technology Department, University of Life Sciences in Lublin, Skromna 8, 20-704 Lublin, Poland.

出版信息

Talanta. 2018 Feb 1;178:294-298. doi: 10.1016/j.talanta.2017.09.050. Epub 2017 Sep 19.

Abstract

Pasta aside from bread is the most consumed cereal-based product in the world. Its taste and cooking ease makes it the basis of many cuisines. The pasta dough formed by mixing flour and water is extruded through an extrusion die to mould the appropriate pasta form and is dried to obtain a stable product. The concentration of moisture in the pasta dough is a one of key parameters determining the final quality of the product. Monitoring the moisture content of pasta after extrusion is also critically important. It enables a selection of suitable drying conditions that ensure the appropriate parameters of pasta, such as texture, color and taste, are met. A method for the quantitative determination of moisture content in pasta dough and in pasta based on the partial least squares treatment of infrared spectra registered using a single-reflection attenuated total reflectance diamond accessory is described. Results of a similar quality were found using models derived from near infrared spectra obtained in a diffuse reflectance mode and slightly worse based on Raman spectra. Relative standard errors of prediction calculated for moisture quantification by ATR/NIR/Raman techniques amounted to 2.54/3.16/5.56% and 2.15/3.32/5.67%, for calibration and validation sets, respectively. The proposed procedures can be used for fast and efficient pasta moisture quantification and may replace the current, more laborious methods used.

摘要

除面包外,面条是世界上消费最多的谷类产品。它的口感和烹饪便利性使其成为许多菜系的基础。将面粉和水混合形成的面团通过挤出模具挤压成适当的面条形状,并进行干燥以获得稳定的产品。面团中的水分浓度是决定产品最终质量的关键参数之一。监测挤出后面条的水分含量也至关重要。它可以选择合适的干燥条件,确保面条达到适当的参数,如质地、颜色和口感。本文描述了一种基于近红外漫反射光谱和拉曼光谱建立的定量分析方法,用于测定面团和面条中的水分含量。基于单反射衰减全反射(ATR)附件的红外光谱的偏最小二乘(PLS)处理,结果发现模型质量相似,但基于拉曼光谱的模型稍差。ATR/NIR/Raman 技术预测水分含量的相对标准误差(RSEP)分别为 2.54%、3.16%、5.56%和 2.15%、3.32%、5.67%,适用于校准和验证集。所提出的方法可用于快速、高效地定量测定面条水分,有望替代当前更繁琐的方法。

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