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Developing a high‐throughput micromilling protocol for evaluating durum wheat milling performance and semolina quality
Author(s) -
Wang Kun,
Taylor Dale,
Pozniak Curtis,
Fu Bin Xiao
Publication year - 2019
Publication title -
cereal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 100
eISSN - 1943-3638
pISSN - 0009-0352
DOI - 10.1002/cche.10181
Subject(s) - bran , fraction (chemistry) , chemistry , gluten , grinding , roller mill , yield (engineering) , food science , mill , agronomy , chromatography , raw material , materials science , composite material , biology , organic chemistry
Background and objectives Effective and efficient selection of key quality traits is crucial to develop new durum varieties with improved end‐use quality. This study was undertaken to develop a rapid micromilling protocol using a single Brabender Quadrumat Jr. (QJ) semolina mill without purification to predict milling performance and generate semolina for quality analysis. Findings After grinding 200 g of durum wheat with a QJ mill with the reel sifter removed, the resulting wholemeal was sifted through a laboratory sifter equipped with a bottom screen of 180 µm to remove flour and a top screen of 630 µm to retain bran‐rich fraction. Semolina materials between the two screens were collected. A model for predicting semolina yield ( R 2 = 0.81) was developed based on the amounts of semolina and bran‐rich fraction, thus eliminating the need for additional milling to recover semolina in the bran‐rich fraction. There were highly significant correlations ( r > 0.86) for semolina ash, yellowness, yellow pigment content, protein content, wet gluten, and gluten index between semolina prepared with this proposed protocol and those generated with a Allis‐Chalmers mill. Conclusions The micromilling protocol developed in this study is rapid and reliable for assessing durum milling performance and for preparing semolina for quality characterization. Significance and novelty The proposed protocol modified QJ mill and optimized milling conditions. A robust and simplified model was developed for predicting semolina yield with one‐step milling. It is a useful tool for breeding programs or genetic mapping studies that are usually large in sample number but very limited in sample size.