Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies

Leaf Area index (LAI) is a critical parameter in plant physiology for models related to growth, photosynthetic activity and evapotranspiration. It is also important for farm management purposes, since it can be used to assess the vigor of trees within a season with implications in water and fertiliz...

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Autor principal: Mora, Marco
Formato: Objeto de conferencia Resumen
Lenguaje:Inglés
Publicado: 2018
Materias:
Ciencias Informáticas
leaf area index
image analysis
hand-held sensor
canopy cover
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/71073
http://47jaiio.sadio.org.ar/sites/default/files/CAI-13.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-71073
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
leaf area index
image analysis
hand-held sensor
canopy cover
spellingShingle Ciencias Informáticas
leaf area index
image analysis
hand-held sensor
canopy cover
Mora, Marco
Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
topic_facet Ciencias Informáticas
leaf area index
image analysis
hand-held sensor
canopy cover
description Leaf Area index (LAI) is a critical parameter in plant physiology for models related to growth, photosynthetic activity and evapotranspiration. It is also important for farm management purposes, since it can be used to assess the vigor of trees within a season with implications in water and fertilizer management. Among the diverse methodologies to estimate LAI, those based on cover photography are of great interest, since they are non-destructive, easy to implement, cost effective and have been demonstrated to be accurate for a range of tree species. However, these methods could have an important source of error in the LAI estimation due to the inclusion within the analysis of non-leaf material, such as trunks, shoots and fruits depending on the complexity of canopy architectures. This paper proposes a modified cover photography method based on specific image segmentation algorithms to exclude contributions from nonleaf materials in the analysis. Results from the implementation of this new image analysis method for cherry tree canopies showed a significant improvement in the estimation of LAI compared to ground truth data using allometric methods and previously available cover photography methods. The proposed methodological improvement is very simple to implement, with numerical relevance in species with complex 3D canopies where the woody elements greatly influence the total leaf area.
format Objeto de conferencia
Resumen
author Mora, Marco
author_facet Mora, Marco
author_sort Mora, Marco
title Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
title_short Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
title_full Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
title_fullStr Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
title_full_unstemmed Automated Computation of Leaf Area index from Fruit Trees using Improved Image Processing Algorithms Applied to canopy cover digital photograpies
title_sort automated computation of leaf area index from fruit trees using improved image processing algorithms applied to canopy cover digital photograpies
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/71073
http://47jaiio.sadio.org.ar/sites/default/files/CAI-13.pdf
work_keys_str_mv AT moramarco automatedcomputationofleafareaindexfromfruittreesusingimprovedimageprocessingalgorithmsappliedtocanopycoverdigitalphotograpies
bdutipo_str Repositorios
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