Paper
12 May 1993 Digital image analysis of starch granules for recognizing hard red and soft red winter wheats
Inna Y. Zayas, D. B. Bechtel, J. D. Wilson, Richard E. Dempster
Author Affiliations +
Proceedings Volume 1836, Optics in Agriculture and Forestry; (1993) https://doi.org/10.1117/12.144019
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
The relationship between isolated starch granule morphometry and wheat hardness was studied. Starch granule size and shape may relate to grain millability, rheological properties of dough, and baking quality. Twenty four Kansas wheats were studied: 14 hard red winter (HRW) and 10 soft red winter (SRW). Isolated starch granules were viewed with light microscopy to obtain black and white images which were recorded on video tape. A program was designed to keep track of the taped images and measure starch granules without operator intervention. The data base of starch granule size and shape features of the 24 samples contained 152,237 granule observations. The number of observations per sample varied from 3,238 to 14,671. Distinguishing HRW from SRW wheat samples was accomplished by evaluation of starch granule morphometry. Several data manipulations and transformations were performed in analysis of the data. Information carried in two shape descriptors, which reflect aspect ratio and equivalent diameter distribution, was used to distinguish starch granules of HRW and SRW wheats. The percentage of starch granules in the aspect ratio range of 1.65 - 1.95 was 25.8 - 31.5% for HRW and 19.9 - 25.4% for SRW.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Inna Y. Zayas, D. B. Bechtel, J. D. Wilson, and Richard E. Dempster "Digital image analysis of starch granules for recognizing hard red and soft red winter wheats", Proc. SPIE 1836, Optics in Agriculture and Forestry, (12 May 1993); https://doi.org/10.1117/12.144019
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KEYWORDS
Agriculture

Forestry

Image analysis

Near infrared

Video

Microscopy

Shape analysis

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