Biometrical Letters

ISSN:1896-3811

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Volume (54) Number 1 pp. 25-42

Stefano Di Blasi 2, Federico Mattia Stefanini 1

1Department of Statistics, Computer Science, Applications – University of Florence, , Florence, Italy
2R&D wine and sensory consultant – Marchesi Antinori, , Florence, Italy

A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes

Summary

In this paper, a Conditional Linear Gaussian Network (CLGN) model is built for a two-year experiment on Tuscan Sangiovese grapes involving canopy management techniques (number of buds, defoliation and bunch thinning) and harvest time (technological and late harvest). We found that the impact of the considered treatments on the color of wine can be predicted still in the vegetative season of the grapevine; the best treatments to obtain wines with good structure are those with a low number of buds; the best treatments to obtain fresh wines suitable for young consumers are those with technological rather than late harvest, preferably with a high number of buds, and anyway with both defoliation and bunch thinning not performed.

Keywords: Canopy management, Conditional independence, Directed acyclic graphs, Late grape harvest, Polyphenolic content, Potential alcohol

DOI: 10.1515/bile-2017-0002

For citation:

MLA Blasi, Stefano Di, and Federico Mattia Stefanini. "A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes." Biometrical Letters 54.1 (2017): 25-42. DOI: 10.1515/bile-2017-0002
APA Blasi, S. D., & Stefanini, F. M. (2017). A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes. Biometrical Letters 54(1), 25-42 DOI: 10.1515/bile-2017-0002
ISO 690 BLASI, Stefano Di, STEFANINI, Federico Mattia. A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes. Biometrical Letters, 2017, 54.1: 25-42. DOI: 10.1515/bile-2017-0002
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