Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions
To overcome the environmental changes occurring now and predicted for the future, it is essential that fruit breeders develop cultivars with better physiological performance. During the last few decades, high-throughput plant phenotyping and phenomics have been developed primarily in cereal breeding...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/11/3/329 |
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| author | Gustavo A. Lobos Alejandro Escobar-Opazo Félix Estrada Sebastián Romero-Bravo Miguel Garriga Alejandro del Pozo Carlos Poblete-Echeverría Jaime Gonzalez-Talice Luis González-Martinez Peter Caligari |
| author_facet | Gustavo A. Lobos Alejandro Escobar-Opazo Félix Estrada Sebastián Romero-Bravo Miguel Garriga Alejandro del Pozo Carlos Poblete-Echeverría Jaime Gonzalez-Talice Luis González-Martinez Peter Caligari |
| author_sort | Gustavo A. Lobos |
| collection | DOAJ |
| description | To overcome the environmental changes occurring now and predicted for the future, it is essential that fruit breeders develop cultivars with better physiological performance. During the last few decades, high-throughput plant phenotyping and phenomics have been developed primarily in cereal breeding programs. In this study, plant reflectance, at the level of the leaf, was used to assess several physiological traits in five <i>Vaccinium</i> spp. cultivars growing under four controlled conditions (no-stress, water deficit, heat stress, and combined stress). Two modeling methodologies [Multiple Linear Regression (MLR) and Partial Least Squares (PLS)] with or without (W/O) prior wavelength selection (multicollinearity, genetic algorithms, or in combination) were considered. PLS generated better estimates than MLR, although prior wavelength selection improved MLR predictions. When data from the environments were combined, PLS W/O gave the best assessment for most of the traits, while in individual environments, the results varied according to the trait and methodology considered. The highest validation predictions were obtained for chlorophyll <i>a/b</i> (R<sup>2</sup><sub>Val</sub> ≤ 0.87), maximum electron transport rate (R<sup>2</sup><sub>Val</sub> ≤ 0.60), and the irradiance at which the electron transport rate is saturated (R<sup>2</sup><sub>Val</sub> ≤ 0.59). The results of this study, the first to model modulated chlorophyll fluorescence by reflectance, confirming the potential for implementing this tool in blueberry breeding programs, at least for the estimation of a number of important physiological traits. Additionally, the differential effects of the environment on the spectral signature of each cultivar shows this tool could be directly used to assess their tolerance to specific environments. |
| first_indexed | 2024-12-20T06:56:43Z |
| format | Article |
| id | doaj.art-38ba3a5ccfbf4b52a55ead8abb9f2d87 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T06:56:43Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-38ba3a5ccfbf4b52a55ead8abb9f2d872022-12-21T19:49:20ZengMDPI AGRemote Sensing2072-42922019-02-0111332910.3390/rs11030329rs11030329Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat ConditionsGustavo A. Lobos0Alejandro Escobar-Opazo1Félix Estrada2Sebastián Romero-Bravo3Miguel Garriga4Alejandro del Pozo5Carlos Poblete-Echeverría6Jaime Gonzalez-Talice7Luis González-Martinez8Peter Caligari9Plant Breeding and Phenomics Center, Facultad de Ciencias Agrarias, Universidad de Talca, Casilla 747, Talca, ChilePlant Breeding and Phenomics Center, Facultad de Ciencias Agrarias, Universidad de Talca, Casilla 747, Talca, ChilePlant Breeding and Phenomics Center, Facultad de Ciencias Agrarias, Universidad de Talca, Casilla 747, Talca, ChileDepartamento de Ciencias Agrarias, Universidad Católica del Maule, Casilla 684, Curicó, ChilePlant Breeding and Phenomics Center, Facultad de Ciencias Agrarias, Universidad de Talca, Casilla 747, Talca, ChilePlant Breeding and Phenomics Center, Facultad de Ciencias Agrarias, Universidad de Talca, Casilla 747, Talca, ChileDepartment of Viticulture and Oenology, Stellenbosch University, Matieland 7602, South AfricaDepartamento de Producción Forestal y Tecnología de la Madera, Facultad de Agronomía, Universidad de la República, Av. Gral. Eugenio Garzón 780, Montevideo 12900, UruguayDepartamento de Ciencias Agrarias, Universidad Católica del Maule, Casilla 684, Curicó, ChileBioHybrids International Ltd., Woodley, Reading RG6 5PY, UKTo overcome the environmental changes occurring now and predicted for the future, it is essential that fruit breeders develop cultivars with better physiological performance. During the last few decades, high-throughput plant phenotyping and phenomics have been developed primarily in cereal breeding programs. In this study, plant reflectance, at the level of the leaf, was used to assess several physiological traits in five <i>Vaccinium</i> spp. cultivars growing under four controlled conditions (no-stress, water deficit, heat stress, and combined stress). Two modeling methodologies [Multiple Linear Regression (MLR) and Partial Least Squares (PLS)] with or without (W/O) prior wavelength selection (multicollinearity, genetic algorithms, or in combination) were considered. PLS generated better estimates than MLR, although prior wavelength selection improved MLR predictions. When data from the environments were combined, PLS W/O gave the best assessment for most of the traits, while in individual environments, the results varied according to the trait and methodology considered. The highest validation predictions were obtained for chlorophyll <i>a/b</i> (R<sup>2</sup><sub>Val</sub> ≤ 0.87), maximum electron transport rate (R<sup>2</sup><sub>Val</sub> ≤ 0.60), and the irradiance at which the electron transport rate is saturated (R<sup>2</sup><sub>Val</sub> ≤ 0.59). The results of this study, the first to model modulated chlorophyll fluorescence by reflectance, confirming the potential for implementing this tool in blueberry breeding programs, at least for the estimation of a number of important physiological traits. Additionally, the differential effects of the environment on the spectral signature of each cultivar shows this tool could be directly used to assess their tolerance to specific environments.https://www.mdpi.com/2072-4292/11/3/329spectroscopyspectrometerspectroradiometerphenotypegas exchangestem water potential<i>V. corymbosum</i><i>V. ashei</i> |
| spellingShingle | Gustavo A. Lobos Alejandro Escobar-Opazo Félix Estrada Sebastián Romero-Bravo Miguel Garriga Alejandro del Pozo Carlos Poblete-Echeverría Jaime Gonzalez-Talice Luis González-Martinez Peter Caligari Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions Remote Sensing spectroscopy spectrometer spectroradiometer phenotype gas exchange stem water potential <i>V. corymbosum</i> <i>V. ashei</i> |
| title | Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions |
| title_full | Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions |
| title_fullStr | Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions |
| title_full_unstemmed | Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions |
| title_short | Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions |
| title_sort | spectral reflectance modeling by wavelength selection studying the scope for blueberry physiological breeding under contrasting water supply and heat conditions |
| topic | spectroscopy spectrometer spectroradiometer phenotype gas exchange stem water potential <i>V. corymbosum</i> <i>V. ashei</i> |
| url | https://www.mdpi.com/2072-4292/11/3/329 |
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