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The main goal of this paper is to detail the challenges and factors taken into consideration when implementing a hyperspectral imaging system in an agricultural environment for blend grade verification of cured tobacco. Cultivated tobacco plants are harvested and cured before using in the manufacture of tobacco products. Processed tobacco leaves are graded by Subject Matter Experts (graders). Hyperspectral imaging can be used to optimize the grading process in an efficient, cost-effective and commercially applicable manner. VNIR (Visible- Near Infrared) range of 400 -1000 nm was used for imaging the samples and developing the algorithm. Development of the grade verification system consisted of multiple years of data collection, along with iterative design changes. This paper details the challenges in both developing the initial control method for grading cured tobacco as well as adapting to the changing needs of those who ultimately utilize the technology.
Amrita Sahu,Henry Dante,Evan Haase, andJerry W. Morris
"Hyperspectral imaging using CCD imager and broadband energy source for agricultural grading: implementation", Proc. SPIE 10754, Wide Bandgap Power and Energy Devices and Applications III, 107540G (26 April 2019); https://doi.org/10.1117/12.2323721
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Amrita Sahu, Henry Dante, Evan Haase, Jerry W. Morris, "Hyperspectral imaging using CCD imager and broadband energy source for agricultural grading: implementation," Proc. SPIE 10754, Wide Bandgap Power and Energy Devices and Applications III, 107540G (26 April 2019); https://doi.org/10.1117/12.2323721