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Canopy architecture assessment of cherry trees by cover photography based on variable light extinction coefficient modelled using artificial neural networks
Indexado
WoS WOS:000706957100024
Scopus SCOPUS_ID:85064413837
DOI 10.17660/ACTAHORTIC.2019.1235.24
Año 2019
Tipo proceedings paper

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



Leaf area index (LAI) is one of the most important parameters in physiological and functional plant models to estimate tree canopy vigor and photosynthesis. However, LAI requires either destructive or indirect methods for accurate assessment, which can be time consuming, costly, and requires specialized instrumentation. Cover photography to estimate canopy architectural parameters has shown to be effective and accurate for several forest species and horticultural tree crops such as apple trees, grapevines and cherry trees. The accuracy of the LAI estimation is highly dependent on the appropriate use of the variable light extinction coefficient (k) parameter per image. Canopy cover photography was tested on a commercial cherry plantation in Maule, Chile during seasons 2011-12 and 2013-14. Two cultivars were assessed, 'Bing' (n=80 images) and 'Sweet Heart' (n=80 images), with 10 trees per cultivar, and 4 photos representing each canopy quadrant per tree. Real LAI (LAI real ) was measured allometrically from every tree photographed for both cultivars. Real k was computed based on the inverted LAI formula and LAI real . Artificial Neural Networks (ANN) modeling for fitting was implemented per cultivar using a customized code written in MATLAB with canopy cover (f f ), crown cover (f c ), canopy porosity (Φ) and clumping index (Ω) obtained from image analysis algorithms as inputs, and real k as target. The ANN fitting model to obtain a variable k showed determination coefficients (R2) for training = 0.98 and 0.92, validation = 0.96 and 0.94, testing = 0.98 and 0.90, and final k model = 0.98 and 0.94, for 'Bing' and 'Sweetheart', respectively, in both seasons studied. This resulted in improvements in the LAI estimation for cherry trees when compared to LAI real with R2 of 0.80 for 'Bing' and 0.90 for 'Sweetheart'. This is a significant improvement in the assessment of canopy vigor and water requirement for tools such as VitiCanopy®, a free LAI estimation App available for iOS and Android devices based on canopy cover photography, which can incorporate a variable k.

Revista



Revista ISSN
Acta Horticulturae 0567-7572

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Disciplinas de Investigación



WOS
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Scopus
Horticulture
SciELO
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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

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Autores - Afiliación



Ord. Autor Género Institución - País
1 Tongson, E. J. Mujer Faculty of Veterinary and Agricultural Sciences - Australia
Univ Melbourne - Australia
2 Fuentes, Sigfredo - Faculty of Veterinary and Agricultural Sciences - Australia
Univ Melbourne - Australia
3 CARRASCO-BENAVIDES, MARCOS RODRIGO Hombre Universidad Católica del Maule - Chile
4 MORA-COFRE, MARCO ANTONIO Hombre Universidad Católica del Maule - Chile
5 Beppu, K -
6 Bessho, H -
7 Haji, T -
8 Yaegaki, H -
9 Matsumoto, D -

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Financiamiento



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