Iñón Fernando A, Llario Rafael, Garrigues Salvador, de la Guardia Miguel
Laboratorio de Análisis de Trazas, Departamento de Química Inorgánica, Analítica y Química Física, Universidad de Buenos Aires, Pabellón 2, Ciudad Universitaria, Buenos Aires 1428, Argentina.
Anal Bioanal Chem. 2005 Aug;382(7):1549-61. doi: 10.1007/s00216-005-3343-9. Epub 2005 Jul 5.
Near infrared spectroscopy (NIR) has been used to determine important indicators of the quality of beers, for example original and real extract and alcohol content, using a partial least squares (PLS) calibration approach. A population of 43 samples, obtained commercially in Spain and including different types of beer, was used. Cluster hierarchical analysis was used to select calibration and validation data sets. Absorbance sample spectra, in transmission mode, were obtained in triplicate by using a 1-mm pathlength quartz flow cell and glass chromatography vials of 6.5 mm internal diameter. The two methods of sample introduction were compared critically, on the basis of spectral reproducibility for triplicate measurements and after careful selection of the best spectral pre-processing and the spectral range for building the PLS model, to obtain the best predictive capability. For each mode of sample introduction two calibration sets were assayed, one based on the use of 15 samples and a second extended based on use of 30 samples, thus leaving 28 and 13 samples, respectively, for validation. The best results were obtained for 1 mm flow cell measurements. For this method original zero-order spectra data in the ranges 2220-2221 and 2250-2350 nm were chosen. For the real extract, original extract, and alcohol d(x-y) and s(x-y) values of -0.04 and 0.07% w/w, -0.01 and 0.13% w/w, and -0.01 and 0.1% v/v, respectively, were obtained. The maximum errors in the prediction of any of these three indicators for a new sample were 2.2, 1.2, and 1.9%, respectively. This method compares favorably with the automatic reference method in terms of speed, reagent consumed, and waste generated.
近红外光谱法(NIR)已被用于测定啤酒质量的重要指标,例如原始浸出物、真正浸出物和酒精含量,采用的是偏最小二乘法(PLS)校准方法。使用了从西班牙商业采购的43个样品组成的样本集,包括不同类型的啤酒。采用聚类层次分析法选择校准和验证数据集。通过使用1毫米光程的石英流通池和内径为6.5毫米的玻璃色谱瓶,以透射模式一式三份地获取吸光度样本光谱。基于一式三份测量的光谱重现性,并在仔细选择最佳光谱预处理和构建PLS模型的光谱范围后,对两种进样方法进行了严格比较,以获得最佳预测能力。对于每种进样模式,测定了两个校准集,一个基于使用15个样品,另一个基于使用30个样品进行扩展,从而分别留下28个和13个样品用于验证。1毫米流通池测量获得了最佳结果。对于该方法,选择了2220 - 2221纳米和2250 - 2350纳米范围内的原始零级光谱数据。对于真正浸出物、原始浸出物和酒精,分别获得了d(x - y)和s(x - y)值为-0.04和0.07% w/w、-0.01和0.13% w/w以及-0.01和0.1% v/v。对新样品的这三个指标中任何一个的预测最大误差分别为2.2%、1.2%和1.9%。该方法在速度、试剂消耗和产生的废物方面与自动参考方法相比具有优势。