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Constructing a three-dimensional resource database of plants using situ-measured morphological data

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2016 ASABE Annual International Meeting  162449020.(doi:10.13031/aim.20162449020)
Authors:   Weiliang Wen, Xinyu Guo, Yongjian Wang, Chunjiang Zhao, Weihua Liao
Keywords:   three-dimensional, database, plants, morphological.

Abstract. Three-dimensional (3D) modeling of plants is the basis of Functional-Structural Plant Modeling (FSPM) and Digital Plant research, and also plays important role in crop phenomics research and plant germplasm resources protection. In order to provide high fidelity 3D models with complete agronomic information for these research and applications, a 3D visual database of plants was constructed. Firstly, situ-measured morphological data, including 3D digital data, 3D point clouds and texture mapping images, were acquired for different precision requirements. In order to set a unified access rule for the database, a morphological data acquisition standard of plants was promoted. The standard constraints the way of acquiring 3D digital data, 3D point cloud and texture imaging features of plants and organs. It also specifies the agronomic information which has to be recorded to guarantee the completeness of the morphological data, such as the plant cultivar, growth period, planting density, water and fertilizer treatment. Then geometric models of plants and organs were modeled by parametric plant modeling methods and geometric modeling based on point clouds using the acquired data. Finally, the 3D resource database of plants was constructed by collecting these plant resources with two aspects of database keywords: agronomy attribute keywords and 3D attribute keywords. The constructed database contains a large number of plant models of different species, cultivars and multiple growth period with agronomic parameters and high level of details. The construction of the database would promote the digital plant playing a greater role on the research and production in agriculture.

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