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It is possible to predict Sangiovese wine quality through a limited number of variables measured on the vines

机译:通过在葡萄树上测量的有限变量可以预测桑娇维塞葡萄酒的质量

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Aims: The research work aimed at creating and testing a method to evaluate vine performance of Sangiovese (VPS), in particular, a method able to predict the potential oenological result through a limited number of variables measured on the vines.Methods and results: A matching table was created on the basis of literature and the experience acquired over twenty years of research activity on Sangiovese vine and wine quality in Tuscany, which allowed the selection of eight viticultural parameters and three VPS classes. In order to validate the matching table, a specific experiment was conducted during the years 2002 and 2003 in 10 vineyards (selected from 7 farms) representative of the main soils and climates of the vine cultivation areas of the Province of Siena (Italy). The experimental results validated the proposed matching table through a non parametric statistical analysis. A multivariate regression analysis between wine sensory evaluation (score) and viticultural parameters significantly predicted wine quality even with only 4 grape parameters (P < 0.05).Conclusion: It was possible to predict VPS by means of a matching table based upon eight simple viticultural parameters. The reliability of the wine quality prediction increased proportionally according to the number of viticultural parameters, but remained rather high (R2 = 0.606) when taking into account only sugar content, sugar accumulation rate, mean berry weight, and extractable polyphenol index (EPI).Significance and impact of the study: It is now possible to predict the quality of Sangiovese wines with a few selected grape parameters. Because of the wide variability in soil and climatic condition of the viticultural areas of the Province of Siena, where the method was developed, and the strong climatic contrast between the years when the method was validated, the use of both matching table and multiple regression is recommended for VPS prediction in Mediterranean environments.
机译:目的:该研究工作旨在创建和测试一种评估桑娇维塞(VPS)葡萄性能的方法,尤其是一种能够通过在葡萄藤上测量的有限变量来预测潜在酿酒学方法的方法和结果:根据文献和在托斯卡纳的桑娇维塞葡萄和葡萄酒品质研究二十多年的经验创建了一个匹配表,从而可以选择八个葡萄栽培参数和三个VPS类。为了验证匹配表,在2002年和2003年期间对代表锡耶纳省(意大利)葡萄种植区的主要土壤和气候的10个葡萄园(从7个农场中选出)进行了特定实验。实验结果通过非参数统计分析验证了建议的匹配表。酒感官评估(分数)和葡萄栽培参数之间的多元回归分析即使只有四个葡萄参数(P <0.05)也能显着预测葡萄酒质量。结论:可以通过基于八个简单葡萄栽培参数的匹配表来预测VPS 。葡萄酒品质预测的可靠性根据葡萄栽培参数的数量成比例地增加,但仅考虑糖含量,糖积累率,平均浆果重量和可提取的多酚指数(EPI)时,其可靠性仍然很高(R2 = 0.606)。研究的意义和影响:现在可以通过一些选定的葡萄参数来预测桑娇维塞葡萄酒的质量。由于开发该方法的锡耶纳省葡萄栽培区的土壤和气候条件差异很大,并且在验证该方法的年份之间存在强烈的气候对比,因此使用匹配表和多元回归建议用于地中海环境中的VPS预测。

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