Estimation of Fractional Photosynthetically Active Radiation From a Canopy 3D Model; Case Study: Almond Yield Prediction.

aerial photogrammetry canopy light interception canopy profile feature digital elevation model digital surface model virtual orchard

Journal

Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200

Informations de publication

Date de publication:
2021
Historique:
received: 26 05 2021
accepted: 12 07 2021
entrez: 13 9 2021
pubmed: 14 9 2021
medline: 14 9 2021
Statut: epublish

Résumé

Canopy-intercepted light, or photosynthetically active radiation, is fundamentally crucial for quantifying crop biomass development and yield potential. Fractional photosynthetically active radiation (PAR) (fPAR) is conventionally obtained by measuring the PAR both below and above the canopy using a mobile lightbar platform to predict the potential yield of nut crops. This study proposed a feasible and low-cost method for accurately estimating the canopy fPAR using aerial photogrammetry-based canopy three-dimensional models. We tested up to eight different varieties in three experimental almond orchards, including California's leading variety of 'Nonpareil'. To extract various canopy profile features, such as canopy cover and canopy volume index, we developed a complete data collection and processing pipeline called Virtual Orchard (VO) in Python environment. Canopy fPAR estimated by VO throughout the season was compared against midday canopy fPAR measured by a mobile lightbar platform in midseason, achieving a strong correlation (

Identifiants

pubmed: 34512697
doi: 10.3389/fpls.2021.715361
pmc: PMC8427806
doi:

Types de publication

Journal Article

Langues

eng

Pagination

715361

Informations de copyright

Copyright © 2021 Zhang, Pourreza, Cheung, Zuniga-Ramirez, Lampinen and Shackel.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Front Plant Sci. 2020 Mar 13;11:290
pubmed: 32231679
Plant Methods. 2019 Dec 26;15:160
pubmed: 31889984
Front Plant Sci. 2019 Jul 18;10:809
pubmed: 31379888
PLoS One. 2015 Jun 24;10(6):e0130479
pubmed: 26107174
New Phytol. 2005 Jun;166(3):869-80
pubmed: 15869648

Auteurs

Xin Zhang (X)

Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, United States.

Alireza Pourreza (A)

Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, United States.

Kyle H Cheung (KH)

Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, United States.

German Zuniga-Ramirez (G)

Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, United States.
Kearney Agricultural Research and Extension Center, University of California Agriculture and Natural Resources, Parlier, CA, United States.

Bruce D Lampinen (BD)

Department of Plant Sciences, University of California, Davis, Davis, CA, United States.

Kenneth A Shackel (KA)

Department of Plant Sciences, University of California, Davis, Davis, CA, United States.

Classifications MeSH