Abstract
Monitoring and measuring the phenotypic traits of plants to understand their growth using computer vision techniques are becoming increasingly important in agriculture. These techniques are expected to replace destructive and labor-intensive traditional plant investigation methods. In this chapter, we first introduce several innovative computer vision-based techniques developed to measure the growth dynamics of plants under outdoor conditions, with the aim of understanding plant formation under dynamic interaction between genotype and environment. Then, the potential possibilities of adapting such techniques to plant factory industries to maximize productivity are discussed.
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Acknowledgments
Part of the approaches introduced in this chapter are partially funded by the CREST Program “Knowledge Discovery by Constructing AgriBigData” and the SICORP Program “Data Science-based Farming Support System for Sustainable Crop Production under Climatic Change,” Japan Science and Technology Agency.
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Guo, W. (2018). Automated Characterization of Plant Growth and Flowering Dynamics Using RGB Images. In: Kozai, T. (eds) Smart Plant Factory. Springer, Singapore. https://doi.org/10.1007/978-981-13-1065-2_23
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DOI: https://doi.org/10.1007/978-981-13-1065-2_23
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