Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis
Autor: | Ming Chen, Md. Asif Ahsan, Zeeshan Gillani, Md. Matiur Rahaman |
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Jazyk: | angličtina |
Rok vydání: | 2017 |
Předmět: |
0106 biological sciences
0301 basic medicine digital biomass Biomass Biology 01 natural sciences 03 medical and health sciences Digital image Stress Physiological image analysis Image Processing Computer-Assisted plant phenotype Throughput (business) Research Articles Functional ecology drought stress Linear model General Medicine Phenotypic trait Plants Plant phenotyping Linear function Droughts linear model Phenotype 030104 developmental biology Agronomy Biological system TP248.13-248.65 010606 plant biology & botany Biotechnology |
Zdroj: | Journal of Integrative Bioinformatics, Vol 14, Iss 3, Pp 745-55 (2017) Journal of Integrative Bioinformatics |
ISSN: | 1613-4516 |
Popis: | Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately. |
Databáze: | OpenAIRE |
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