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首页> 外文期刊>Journal of the Institute of Brewing >Enhanced NIR Calibration for Wort Fermentability Using Orthogonal Signal Correction
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Enhanced NIR Calibration for Wort Fermentability Using Orthogonal Signal Correction

机译：使用正交信号校正增强了麦芽发酵性的近红外校准

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摘要

An enhanced method for the calibration of Near Infra Red (NIR) reflectance spectra to wort fermentability is proposed using a signal pre-processing algorithm called orthogonal signal correction (OSC). Pre-processing NIR spectra prior to partial least squares Project to Latent Structures (PLS) regression modelling is becoming commonplace in multivariate calibration. A set of twenty wort samples subjected to a replicated 2~2 factorial design with a centre point and nine production samples were used to construct multivariate prediction models. The experimental design factors were the mash tun saccharification temperature and time used to purposely provide a sample set with significant leverage in the fermentability responses. Calibration PLS models for both wort apparent degree of fermentation (ADF) and final attenuation apparent extract (Final AE) values with and without OSC corrected spectra were compared demonstrating significant improvements in prediction capability with the prior (Q~2 = 0.90 versus Q~2 = 0.28). The OSC algorithm removed almost 60% of the variance in the NIR spectra, which was independent or orthogonal to the fermentability measures. By cleaning up the spectra, the standard errors of prediction (SEP) for ADF and Final AE were improved by 50 and 90%, respectively, illustrating not only the enhancement in calibration but also the aptness for process control applications. Various model validation tests, including an external validation example and random response permutation, verify the validity of the models using OSC. Furthermore, interpretation of the important wavelengths related to wort fermentability is provided and demonstrates that some key wavelengths are related to both carbohydrate overtones as well as nitrogen functional groups. The application of OSC prior to developing calibration models with NIR demonstrates promising results for brewers interested in real time control of wort fermentability.
机译：提出了一种被称为正交信号校正（OSC）的信号预处理算法，用于校准近红外（NIR）反射光谱以改善麦汁发酵性能。在部分最小二乘之前对NIR光谱进行预处理在多变量校准中，投影到潜在结构（PLS）回归建模正变得司空见惯。一组二十个麦芽样品经过一个具有中心点的重复2〜2因子设计，九个生产样品用于构建多元预测模型。实验设计因素是糖化糖化糖化温度和时间，目的是故意为可发酵性响应提供显着杠杆作用的样品组。比较了在有和没有经过OSC校正的光谱的情况下，麦芽表观发酵度（ADF）和最终衰减表观提取物（最终AE）值的校准PLS模型，证明了预测能力与先前（Q〜2 = 0.90 vs Q〜2 = 0.28）。 OSC算法消除了NIR光谱中几乎60％的方差，该方差与发酵性指标无关或正交。通过清理光谱，ADF和最终AE的标准预测误差（SEP）分别提高了50％和90％，这不仅说明了校准的增强，而且说明了过程控制应用的适用性。各种模型验证测试（包括外部验证示例和随机响应排列）使用OSC验证了模型的有效性。此外，提供了与麦芽汁发酵能力有关的重要波长的解释，并证明了一些关键波长与碳水化合物的泛音以及氮官能团有关。在开发具有NIR的校准模型之前，OSC的应用为对麦芽汁发酵能力实时控制感兴趣的啤酒商展示了可喜的结果。

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