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DOI:10.31220/agriRxiv.2022.00162
声明:预印本系统所发表的论文仅用于最新科研成果的交流与共享,未经同行评议,因此不建议直接应用于指导生产实验。

Early prediction of Shiraz wine quality based on small volatile compounds in grapes.

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    Abstract: Abstract Traditionally, wine producers perform early wine quality prediction on-site based on the berry morphological and sensory characteristics together with the measurement of basic chemical parameters. Incorporating analysis on grape and wine volatiles could potentially achieve accurate prediction of wine quality, but forming these models requires careful selection of grapes, controlled fermentations and standardised quality assessment. Here, we present 3 models for the prediction of quality in Shiraz wine. Modelling was done by general regression analysis with 4-fold cross-validation. Model 1 (R 2 = 99.97% and 4-fold R 2 = 97.61%) for prediction of wine quality from wine volatiles, Model 2 (R 2 = 99.89% and 4-fold R 2 = 98.42%) for early prediction of wine quality from free- and glycosidically- bound grape volatiles, and Model 3 (R 2 = 91.62% and 4-fold R 2 = 80.21%) for prediction of wine quality from free grape volatiles only. The accuracy of these models presents an advancement in the early prediction of wine quality and provide a valuable tool to assist grape growers and winemakers in understanding quality in the vineyard to better direct scarce resources.

    Key words: wine quality; prediction; fold; model; models; grap

    提交时间:2022-01-01

    版权声明:作者本人独立拥有该论文的版权,预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
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引用格式

Jiaqiang Luo, Jamie Selby‐Pham, Kimber Wise, Yin-hao Wu, Jiacan Sun, Ya-meng Qu, Tian Cao, Pangzhen Zhang, Philip J. Marriott, Kate Howel. Early prediction of Shiraz wine quality based on small volatile compounds in grapes.. 2022. agriXiv.2022.00162

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