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首页> 外文期刊>Australian Journal of Grape and Wine Research >Effect of variety, vintage and winery on the prediction by visible and near infrared spectroscopy of the concentration of glycosylated compounds (G-G) in white grape juice
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Effect of variety, vintage and winery on the prediction by visible and near infrared spectroscopy of the concentration of glycosylated compounds (G-G) in white grape juice

机译:葡萄品种,酿酒厂和酿酒厂对可见和近红外光谱法预测白葡萄汁中糖基化化合物(G-G)浓度的影响

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摘要

The use of visible (Vis) and near infrared (NIR) spectroscopy was explored as a rapid, simple and low cost measurement of the concentration of total glycosylated compounds in white grape juice. The effects of variety (Chardonnay, Riesling and Sauvignon Blanc), winery and vintage (2004 to 2006) on the Vis-NIR spectra were also examined. Juice samples from South Australian wineries were scanned in transmittance mode on a FOSS NIRSystems6500 instrument and subjected to laboratory analyses for the measurement of the concentration of total glycosylated compounds (G-G), total soluble solids (TSS), pH and total phenolics (TP). Partial least squares (PLS) regression method was used to relate the G-G reference data to the Vis-NIR spectra. For all samples, PLS regression resulted in a coefficient of determination in calibration (R~2_(cal)) and standard error of cross validation (SECV) of 0.82 and 49.15 μM, respectively. Splitting the sample set by variety, winery or vintage improved the PLS calibrations for the variety sets. The results show that Vis-NIR spectroscopy has potential for use as a rapid, semi-quantitative technique to predict G-G concentration in white grape juices as 'low', 'medium' or 'high'. This method will be valuable when taking decisions at the winery during vintage to allocate juices according to their aroma potential. Further studies are in progress to validate the robustness and accuracy of the calibration models.
机译:探索了使用可见(Vis)和近红外(NIR)光谱作为快速,简单和低成本的白葡萄汁中总糖基化化合物浓度的测量方法。还检查了品种(霞多丽,雷司令和长相思),酒庄和年份(2004年至2006年)对Vis-NIR光谱的影响。使用FOSS NIRSystems6500仪器以透射模式扫描来自南澳大利亚酒厂的果汁样品,并进行实验室分析,以测量总糖基化化合物(G-G),总可溶性固形物(TSS),pH和总酚类(TP)的浓度。使用偏最小二乘(PLS)回归方法将G-G参考数据与Vis-NIR光谱相关联。对于所有样品,PLS回归得出的校准系数(R〜2_(cal))和交叉验证的标准误差(SECV)分别为0.82和49.15μM。按品种,酿酒厂或年份划分样品组可改善品种组的PLS校准。结果表明,Vis-NIR光谱法有潜力用作一种快速,半定量的技术,将白葡萄汁中的G-G浓度预测为“低”,“中”或“高”。在酿酒期间决定在酒厂根据果汁的香气潜力分配果汁时,此方法非常有用。正在进行进一步的研究以验证校准模型的鲁棒性和准确性。

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