Prediction of breakage during roller milling of mixtures of wheat kernels, based on single kernel measurements
Wheat flour milling involves repeated breakage (by roller milling) and separation (by sifting) of flour particles to give efficient recovery of fine flour relatively free from bran contamination. A starting point for modelling the behaviour of mixtures of wheat kernels is to be able to measure the v...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTM Press
2008
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/6759/10/IdaIdayuMuhamad2008_PredictionofBreakageDuringRollerMilling.pdf http://eprints.utm.my/id/eprint/6759/ |
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| Summary: | Wheat flour milling involves repeated breakage (by roller milling) and separation (by sifting) of flour particles to give efficient recovery of fine flour relatively free from bran contamination. A starting point for modelling the behaviour of mixtures of wheat kernels is to be able to measure the variation in kernel properties within the mixture. The Perten Single Kernel Characterisation System (SKCS) gives the distributions of kernel mass, moisture content, diameter and hardness within a mixture, from 300 kernels within 5 minutes. A challenge remains to relate these measured distributions to predictions of milling performance. To this end, a breakage function in terms of these measured parameters for individual kernels has been constructed, and integrated over the distribution of kernel properties using the breakage equation. These models allow prediction of the output particle size distribution delivered by First Break roller milling of kernels varying in size, hardness and variety, based entirely on SKCS characteristics. Predictions have been developed for both sharp-to-sharp and dull-to-dull roll dispositions, and show encouraging agreement with independent data. |
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