Paper
4 August 2009 Digital TAcy: proof of concept
Annie Bubel, Jean-François Sylvain, François Martin
Author Affiliations +
Proceedings Volume 7386, Photonics North 2009; 73861G (2009) https://doi.org/10.1117/12.839484
Event: Photonics North 2009, 2009, Quebec, Canada
Abstract
Anthocyanins are water soluble pigments in plants that are recognized for their antioxidant property. These pigments are found in high concentration in cranberries, which give their characteristic dark red color. The Total Anthocyanin concentration (TAcy) measurement process requires precious time, consumes chemical products and needs to be continuously repeated during the harvesting period. The idea of the digital TAcy system is to explore the possibility of estimating the TAcy based on analysing the color of the fruits. A calibrated color image capture set-up was developed and characterized, allowing calibrated color data capture from hundreds of samples over two harvesting years (fall of 2007 and 2008). The acquisition system was designed in such a way to avoid specular reflections and provide good resolution images with an extended range of color values representative of the different stages of fruit ripeness. The chemical TAcy value being known for every sample, a mathematical model was developed to predict the TAcy based on color information. This model, which also takes into account bruised and rotten fruits, shows a RMS error of less than 6% over the TAcy interest range [0-50].
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Annie Bubel, Jean-François Sylvain, and François Martin "Digital TAcy: proof of concept", Proc. SPIE 7386, Photonics North 2009, 73861G (4 August 2009); https://doi.org/10.1117/12.839484
Lens.org Logo
CITATIONS
Cited by 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Calibration

Chemical analysis

Cameras

Data modeling

Light sources and illumination

RGB color model

Statistical modeling

Back to Top