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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Grain Quality and Structure Research » Research » Publications at this Location » Publication #162872
Title: MEASURING WHEAT STARCH SIZE DISTRIBUTION USING IMAGE ANALYSIS AND LASER DIFFRACTION TECHNOLOGY

Author
item Wilson, Jeff
item Bechtel, Donald

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/10/2004
Publication Date: 9/19/2004
Citation: Wilson, J.D., Bechtel, D.B. 2004. Measuring wheat starch size distribution using image analysis and laser diffraction technology. Presented to the symposium titled "Starch: Size Does Matter" for the American Association of Cereal Chemists held in San Diego, CA, Sept. 19-22, 2004. Meeting Abstract.

Interpretive Summary:

Technical Abstract: Particle size and shape has long been recognized as an important variable in a range of processes including predicting rheology and flow behavior. Wheat, barley, rye and triticale have starch populations with multimodal distributions; large A-type granules lenticular in shape and smaller B- and C-type granules spherical in shape. A wide range in particle size creates difficulties in accurately measuring starch populations. Starch, isolated from flour of four classes of wheat, was analyzed by digital image analysis (IA) and laser diffraction sizing (LDS) to measure starch size distributions. IA data was converted to volume percent to be compared to LDS data. IA errors were detected, corrected, and compared with size distributions obtained from LDS. LDS resulted in a ~40% underestimation of the A-type granule diameter and a ~50% underestimation of the B-type granule diameter in comparison to IA. Laser diffraction data correlated to IA data, with R2 values ranging from 0.02ns to 0.55***. A correction factor was used to adjust LDS and IA data for better correlations. After the adjustment, correlations improved (R2 = 0.79*** to 0.93***) dependent on the class of wheat starch evaluated. This work represents a step towards combining IA and LDS technologies to study non-spherical particles.