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Electronic tongue: a versatile tool for mineral and fruit-flavored waters recognition

机译:电子舌:矿物质和水果味水识别的多功能工具

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Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity,sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate water’s pH (25 sensors: R2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification.
机译:天然矿泉水(蒸馏水),泡腾的天然矿泉水(汽泡水)和带有水果味的芳香化水(蒸馏水或起泡水)是新兴市场。在这项工作中,评估了带有脂质聚合物膜的电位电子舌头定量评估常规质量理化参数(pH和电导率)以及根据水的类型定性分类水样的能力。研究表明,基于通过模拟退火算法选择的21个传感器的线性判别模型可以正确地对100%的水样品进行分类(留出一个交叉验证)。通过应用重复的K倍交叉验证(确保至少15%的独立样本仅用于内部验证),进一步证明了这种潜力,为此可以实现96%的正确分类。电子舌的令人满意的识别性能可以归因于所研究的水的pH,电导率,糖和有机酸含量,结果表明甜味感知指数和总酸味存在显着差异。此外,基于模拟退火算法选择的传感器子集,电子舌与多元线性回归模型相结合,可以准确估算水的pH值(25个传感器:R2等于0.99和0.97,留一出或重复使用) K折交叉验证)和电导率(23个传感器:R2等于0.997和0.99,留一法或重复的K折交叉验证)。因此,所获得的总体令人满意的结果允许设想将来在瓶装水分析和分类中使用电子舌头装置的潜在应用。

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