CLASSIFICATION OF THE MATURITY OF TEA LEAVES USING HYPERSPECTRAL IMAGING
DOI:
https://doi.org/10.48047/943qvg84Keywords:
Hyperspectral Imaging, HIS in tealeavesAbstract
Technologies for the food industry to enhance product quality through precise and efficient analysis methods have been driven by advancements in the food industry, which have in turn led to the adoption of cutting edge technologies. HSI, which was first developed for remote sensing, has also been used for food commodity classification because it is a non-invasive technology that can analyze multiple chemical properties at a single time. Black tea production, the tender leaves (bud and first two leaves) must be harvested, but since manual plucking involves mature leaves, the quality of the product is reduced. A machine learning based classification model using hyperspectral imaging to identify tender tea leaves is presented in this research with the aim of improving productivity and minimizing plucking errors.
Downloads
References
“Benelli, A., Cevoli, C., & Fabbri, A. (2020). In-field hyperspectral imaging: An overview on the ground based applications in agriculture. Journal of
Agricultural Engineering, 51(3), 129-139.” “ElMasry, G., & Sun, D. W. (2010). Principles of hyperspectral imaging technology. In Hyperspectral
imaging for food quality analysis and control (pp. 343). Academic Press.”
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
