2016
DOI: 10.1016/j.jfoodeng.2016.03.001
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A compositional breakage equation for wheat milling

Abstract: The compositional breakage equation is derived, in which the distributions of botanical components following milling of wheat are defined in terms of compositional breakage functions and concentration functions. The forms of the underlying functions are determined using experimental data for Outer Pericarp, Intermediate Layer, Aleurone and Starchy Endosperm generated from spectroscopic analysis of milled fractions of a hard and a soft wheat milled under Sharp-to-Sharp (S-S) and Dull-to-Dull (D-D) dispositions.… Show more

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Cited by 10 publications
(6 citation statements)
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“…The soft variety, GK F eny produces much larger bran particles compared to the hard variety. This finding confirmed the consequences of Galindez-Najera et al (2016).…”
Section: Results and Their Assessmentssupporting
confidence: 84%
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“…The soft variety, GK F eny produces much larger bran particles compared to the hard variety. This finding confirmed the consequences of Galindez-Najera et al (2016).…”
Section: Results and Their Assessmentssupporting
confidence: 84%
“…In milling technology, the degree of kernel hardness is proportional to the energy used for grinding, since the grinding of harder kernel requires far more energy than soft ones. The broken particles distribute differently in hard and soft cultivars (Galindez-Najera et al, 2016). In addition, the kernel hardness specifies the conditioning parameters, the flour particle size, the density, the starch damage rate and through this the flour water absorption ability and the flour extraction rate.…”
Section: Introductionmentioning
confidence: 99%
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“…Previous studies have modeled particle size distribution throughout the mill grinding and separation process (Campbell, Bunn, et al, 2001;Campbell et al, 2007;Fang & Campbell, 2003;Galindez-Najera et al, 2016). These results demonstrated that the particle size distribution was impacted by conditioning level and roll gaps in the break system along with other factors such as grain size and hardness.…”
Section: Introductionmentioning
confidence: 87%
“…They further extended the dataset for this model (Fuh et al, 2014). Galindez-Najera et al (2016) further demonstrated that the continuous crushing function can also be defined as a crushing function related to particle composition for predicting particle size distribution. The experimental data they generated enriched the practical implications of this theory.…”
Section: Building Mathematical Modelsmentioning
confidence: 99%