Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Weather/Irrigation Management Data Acquisition
2.2. Physicochemical Analysis
2.3. Gas Chromatography–Mass Spectroscopy
2.4. Statistical Analysis and Machine Learning Modeling
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Year | Solar Exposure (V-H; MJ m2 −1) | Solar Exposure (S-H; MJ m2 −1) | MJSE (MJ m2 −1) | DD-S-H (days) | MJT (°C) | MeanMaxT V-H (°C) | Mean MinTV-H (°C) | Water Balance (mm) |
---|---|---|---|---|---|---|---|---|
2011 | 15.6 | 19.1 | 24.6 | 1066.8 | 18.6 | 19.7 | 9.44 | 673.7 |
2012 | 17.9 | 20.2 | 26.3 | 1147.3 | 19.4 | 22.6 | 10.75 | 255.9 |
2013 | 21.8 | 21.8 | 28.9 | 1234.2 | 19.8 | 26.1 | 12.05 | −117.5 |
2014 | 19.0 | 20.0 | 27.6 | 1223.7 | 20.3 | 25.8 | 11.31 | −61.9 |
Volatile Compound | Aroma * |
---|---|
Ethyl hexanoate | Apple/Green banana/Pineapple |
Phenylethyl alcohol | Rose/Bread/Honey |
Diethyl succinate | Cooked apple |
Ethyl octanoate | Apple/Banana/Pineapple |
Ethyl nonanoate | Cognac/Apple/Winey/Nutty |
Ethyl-9-decenoate | Fruity/Fatty/Roses |
Ethyl decanoate | Waxy/Apple/Grape |
Ethyl laurate | Floral/Soapy/Sweet |
Ethyl palmitate | Waxy/Fruity/Creamy/Milky |
Stage | Samples | Observations | R | Slope (b) | Performance (MSE) |
---|---|---|---|---|---|
Model 1 | |||||
Training | 40 | 360 | 0.99 | 0.98 | 0.003 |
Validation | 13 | 117 | 0.97 | 0.98 | 0.03 |
Testing | 13 | 117 | 0.97 | 0.92 | 0.03 |
Overall | 66 | 594 | 0.99 | 0.97 | / |
Model 2 | |||||
Training | 40 | 560 | 0.96 | 0.91 | 0.02 |
Validation | 13 | 182 | 0.93 | 0.83 | 0.05 |
Testing | 13 | 182 | 0.90 | 0.94 | 0.06 |
Overall | 66 | 924 | 0.94 | 0.90 | / |
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Fuentes, S.; Tongson, E.; Torrico, D.D.; Gonzalez Viejo, C. Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence. Foods 2020, 9, 33. https://doi.org/10.3390/foods9010033
Fuentes S, Tongson E, Torrico DD, Gonzalez Viejo C. Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence. Foods. 2020; 9(1):33. https://doi.org/10.3390/foods9010033
Chicago/Turabian StyleFuentes, Sigfredo, Eden Tongson, Damir D. Torrico, and Claudia Gonzalez Viejo. 2020. "Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence" Foods 9, no. 1: 33. https://doi.org/10.3390/foods9010033