Using Rapid Chlorophyll Fluorescence Transients to Classify Vitis Genotypes
Abstract
:1. Introduction
2. Results
2.1. Genetic Analysis
2.2. Machine Learning
3. Discussion
4. Materials and Methods
4.1. Plant Material
4.2. Genetic Analysis
4.3. Fluorescence Measurements
4.4. Machine Learning
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Method | Success Rate | Main Parameters |
---|---|---|
K-nearest neighbors | 58.5% | Number of neighbors: 5 |
Decision tree | 51.6% | Split criterion: entropy Maximum tree depth: 19 Minimum number of samples in a node: 5 |
Neural network | 71.8% | Number of neurons: 5000 Activation function: logistic |
Genetic programming | 75.3% | Number of individuals: 250 Number of generations: 100 |
Genotype | Variety | Acession PRT051 | VIVC | Photo (VIVC) * | Leaf Colour | Leaf Bright | Country of Origin |
---|---|---|---|---|---|---|---|
Vitis rupestris Scheele | Rupestris du Lot | 13,821 | 10,389 | Light green | bright | France | |
Vitis riparia Michaux | Riparia Gloire de Montpellier | 13,822 | 4824 | Dark green | dull | France | |
Vitis interspecific crossing | Isabella | 13,619 | 5560 | Dark green | dull | United States of America | |
Vitis vinifera Linné subsp. vinifera | Pinot Noir | 10,918 | 9279 | green | dull | France | |
Vitis vinifera Linné subsp. vinifera | Cabernet Sauvignon | 10,714 | 1929 | Light green | Slightly bright | France | |
Vitis vinifera Linné subsp. vinifera | Riesling Weiss | 13,413 | 10,077 | Dark green | Slightly bright | Germany | |
Vitis vinifera Linné subsp. vinifera | Trincadeira | 11,402 | 15,685 | Dark green | Very bright | Portugal |
SSR Name | Linkage Group | Microsatellite Repeat Motif | Reference |
---|---|---|---|
VVS2 | 11 | (GA)n | Thomas and Scott [42] |
VVMD5 | 16 | (CT)nAT(CT)nATAG(AT)n | Bowers and Meredith [43] |
VVMD7 | 7 | (CT)n | Bowers and Meredith [43] |
VVMD25 | 11 | (CT)n | Bowers et al. [44] |
VVMD27 | 5 | (CT)n | Bowers et al. [44] |
VVMD28 | 3 | (CT)n | Bowers et al. [44] |
VVMD32 | 4 | (CT)n | Bowers et al. [44] |
VRZAG62 | 7 | (GA)n | Sefc et al. [45]/Doligez et al. [46] |
VRZAG79 | 5 | (GA)n | Sefc et al. [45]/Doligez et al. [46] |
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Marques da Silva, J.; Figueiredo, A.; Cunha, J.; Eiras-Dias, J.E.; Silva, S.; Vanneschi, L.; Mariano, P. Using Rapid Chlorophyll Fluorescence Transients to Classify Vitis Genotypes. Plants 2020, 9, 174. https://doi.org/10.3390/plants9020174
Marques da Silva J, Figueiredo A, Cunha J, Eiras-Dias JE, Silva S, Vanneschi L, Mariano P. Using Rapid Chlorophyll Fluorescence Transients to Classify Vitis Genotypes. Plants. 2020; 9(2):174. https://doi.org/10.3390/plants9020174
Chicago/Turabian StyleMarques da Silva, Jorge, Andreia Figueiredo, Jorge Cunha, José Eduardo Eiras-Dias, Sara Silva, Leonardo Vanneschi, and Pedro Mariano. 2020. "Using Rapid Chlorophyll Fluorescence Transients to Classify Vitis Genotypes" Plants 9, no. 2: 174. https://doi.org/10.3390/plants9020174