کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4515465 1624890 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Optimisation and standardisation of extraction and HPLC analysis of rice grain protein
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
پیش نمایش صفحه اول مقاله
Optimisation and standardisation of extraction and HPLC analysis of rice grain protein
چکیده انگلیسی


• Standard extraction and HPLC methods for rice grain proteins were developed.
• The most efficient extraction solvent for prolamins was 60% n-propanol.
• The most suitable extraction solvent for glutelins was 5 M acetic acid.
• The developed HPLC gradients allow improved characterisation of rice grain protein composition.

Rice starch composition is considered to be the most important predictor of rice eating quality, however, rice eating quality is not wholly explained by starch since cultivars with very similar starch composition differ in eating quality. Protein constitutes 4%–10% of the milled rice grain and has very diverse properties, suggesting protein composition and not just protein content may contribute to rice grain eating quality. Although many analytical methods have been used to study cereal grain protein, the extraction and analysis of rice grain protein have not been optimised in the context of assessing and improving rice grain quality. In this study, different rice grain protein extraction techniques and high pressure liquid chromatography (HPLC) analysis methods were compared and optimised. The most efficient extraction solvents for prolamins and glutelins were 60% n-propanol and 5 M acetic acid, respectively, and optimised HPLC methods were developed for each of these extracts. These optimised, standardised and reproducible methods distinguish between the proteins of basmati, long, medium and sushi rice grains and quantify differences which might contribute to their different eating qualities.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Cereal Science - Volume 72, November 2016, Pages 124–130
نویسندگان
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