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Research Project: OBJECTIVE GRADING AND END-USE PROPERTY ASSESSMENT OF SINGLE KERNELS AND BULK GRAIN SAMPLES

Location: Engineering and Wind Erosion Research Unit

Title: RELATION OF SINGLE WHEAT KERNEL PARTICLE SIZE DISTRIBUTION TO PERTEN SKCS 4100 HARDNESS INDEX

Authors
item Pearson, Tom
item Wilson, Jeff
item Gwirtz, Jeff - KANSAS STATE UNIV
item Mccluskey, Pat - GIPSA
item Dowell, Floyd

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: June 5, 2006
Publication Date: September 17, 2006
Citation: Pearson, T.C., Wilson, J.D., Gwirtz, J., Mccluskey, P., Dowell, F.E. 2006. Relation of single wheat kernel particle size distribution to Perten SKCS 4100 hardness index [abstract]. AACC International Meeting. Poster No. 259.

Technical Abstract: The Perten SKCS 4100 is the current reference method to determine single kernel hardness (AACC Method 55-31). However, some genetically hard wheat has been classed by the SKCS 4100 as soft or mixed; likewise, some genetically soft wheat has been classed as hard or mixed. It is not known whether these classifications are due to the SKCS 4100 hardware or software limitations, or whether the samples are truly classed correctly. The objective of this research is to develop a single kernel hardness reference based on single kernel particle size distributions (PSD). This reference method can then be used to quantify the error in the SKCS 4100, and lead to improved classifications. Material from single kernels crushed on the SKCS 4100 was collected and milled in a fabricated mill, which simulates the last two rolls of a Quadramat Jr. The PSD of each single kernel was then measured using a laser particle counter. It was found that the difference between the maximum and minimum slope of the PSD below 55 µm could distinguish most of the hard and soft kernels. These slopes correspond to a peak in the PSD between 20 to 30 µm. Particle size distributions from soft kernels normally have a peak in this particle size range while hard kernels have a small, or no, peak. SKCS low level data, as well as the raw crush profile, were analyzed to find a correlation with this slope. After stepwise selection, HI, and three normalized crush profile values were used to predict the PSD slope. The predicted slope correctly classified 95% of the hard and soft kernels. These results indicate that a calibration for the SKCS based on single kernel particle size is possible and this may give a better indication of end use quality of a wheat sample.

   

 
Project Team
Pearson, Tom
Dowell, Floyd
Armstrong, Paul
 
Publications
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Related National Programs
  Quality and Utilization of Agricultural Products (306)
 
 
Last Modified: 05/24/2013
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