A Quick Analysis Method for Protein Quantification in Oilseed Crops: A Comparison With Standard Protocol - Langyan, Sapna; Bhardwaj, Rakesh; Radhamani, J.; Yadav, Rashmi; Gautam, Raj Kumar; Kalia, Sanjay; Kumar, Ashok (Frontiers in Nutrition, 2022)
Protein is one of the most abundant substances in plants and plays a major role in human health hence standardization of its analytical quantification method is essential. Various methods for protein quantification exist, such as Kjeldahl, Bradford, Lowry, bicinchoninic acid assay (BCA), Biuret, and total amino acid content methods. These methods are widely applied; however, the development of the rapid and efficient method is the need of the time hence the objective of this research was to analyze and comparing compare the modification of the Kjeldahl method for the determination of protein content in oilseed crops. The study was performed to improve the sample preparation method for protein quantification. Generally, the method initially requires homogenization of grains to a fine flour, which involves time and increases the risk of sample cross-contamination and partial loss of oil from the sample during grinding. Moreover at times, it becomes challenging to homogenise oil seeds to fine flour due to high oil content. However, in the present research, the whole grain was digested to accomplish quick protein quantification and compared it with the flour matrix of different oil seeds. To further reduce the digestion time, we have used the modified digestion mixture. The developed method was statistically validated using ANOVA, Pearson correlationreliability test, paired T-test, and different types of plot analysis. The validation of the sample preparation method in protein quantification demonstrated non-significant differences that the protein content from whole grain of all the five oilseed crops shows non-significant results compared with the flour matrix in both the digestion mixtures. The developed novel method could be used to prepare the sample for protein analysis and reduces the overall analysis time while ensuring the accuracy of the results.