TY - JOUR
T1 - Electrophoresis and chromatography of wheat proteins
T2 - available methods, and procedures for statistical evaluation of the data
AU - Bietz, J. A.
AU - Simpson, D. G.
PY - 1992/10/30
Y1 - 1992/10/30
N2 - Analysis of gluten proteins from the wheat grain endosperm has long challenged the analytical chemist. Several hundred unique polypeptides are present, many in large polymers. This complexity, plus useful relationships of composition to genotype and quality, encouraged development and application of electrophoresis and chromatography for gluten analysis. We review the methods of polyacrylamide gel electrophoresis, sodium dodecyl sulfate-polyacrylamide gel electrophoresis, isoelectric focusing and high-performance liquid chromatography available for study of wheat proteins. Singly and in combination, they provide rapid, reproducible, high-resolution separations based on size, charge, or surface hydrophobicity. As challenging and important as the analyses themselves, however, is interpretation of data. Subjective evaluation is sometimes possible, but statistical methods such as similarity scores, clustering, principal components, multiple linear regression, and partial least squares now are increasingly used for data analysis. We review the use of these procedures, and precautions necessary to avoid misinterpretation of data. Optimal evaluation of protein analytical data will enhance the value of such analyses in wheat breeding, marketing, and processing.
AB - Analysis of gluten proteins from the wheat grain endosperm has long challenged the analytical chemist. Several hundred unique polypeptides are present, many in large polymers. This complexity, plus useful relationships of composition to genotype and quality, encouraged development and application of electrophoresis and chromatography for gluten analysis. We review the methods of polyacrylamide gel electrophoresis, sodium dodecyl sulfate-polyacrylamide gel electrophoresis, isoelectric focusing and high-performance liquid chromatography available for study of wheat proteins. Singly and in combination, they provide rapid, reproducible, high-resolution separations based on size, charge, or surface hydrophobicity. As challenging and important as the analyses themselves, however, is interpretation of data. Subjective evaluation is sometimes possible, but statistical methods such as similarity scores, clustering, principal components, multiple linear regression, and partial least squares now are increasingly used for data analysis. We review the use of these procedures, and precautions necessary to avoid misinterpretation of data. Optimal evaluation of protein analytical data will enhance the value of such analyses in wheat breeding, marketing, and processing.
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U2 - 10.1016/0021-9673(92)85674-I
DO - 10.1016/0021-9673(92)85674-I
M3 - Review article
C2 - 1494021
AN - SCOPUS:0027070982
SN - 0021-9673
VL - 624
SP - 53
EP - 80
JO - Journal of Chromatography A
JF - Journal of Chromatography A
IS - 1-2
ER -