Validation and Applicability of Single Kernel-Based Cut Grain Dip Method for Amylose Determination in Rice

• Published in: Food analytical methods 2017-02, Vol.10 (2), p.442-448
• Main Authors: Raja, Ramadoss Bharathi, Anusheela, Varadharaju, Agasimani, Somanath, Jaiswal, Sarita, Thiruvengadam, Venkatesan, Chibbar, Ravindra N, Ganesh Ram, Sundaram
• Format: Article
• Language: English
• Subjects: Analytical Chemistry; Chemistry; Chemistry and Materials Science; Chemistry/Food Science; Cooking; Food safety; Food Science; Grain; Microbiology; Size exclusion chromatography
• ISSN: 1936-9751; 1936-976X
• DOI: 10.1007/s12161-016-0607-2

Amylose content (AC) is an important parameter responsible for the cooking quality of rice. Different methods with varied principles are being employed to determine the AC on the basis of their capacity of detection. Recently, our group successfully developed a simple and rapid method for AC determination termed as cut grain dip (CGD) method. In spite of the fact that this method is proved to be user friendly, thorough validation is required for its routine application across laboratories working on rice grain quality. To verify the accuracy of the CGD method, we compared this method with routine Juliano and two pure starch-based methods namely colourimetric and high-performance size-exclusion chromatography. A total of 16 rice varieties with varied amylose contents were used for the estimation of AC using the aforementioned methods. The results indicated that the CGD method showed high correlation ( r ) value of 0.987 ( p <  0.01) with Juliano’s method. This method also showed significant correlation values of 0.849 ( p <  0.01) and 0.869 ( p <  0.01) with pure starch colourimetric and high-performance size-exclusion chromatography (HPSEC) methods, respectively. While the CGD method was able to discriminate the genotypes of all the three amylose classes, the pure starch-based colourimetric method could only discriminate high and low amylose genotypes and failed to detect the intermediate class. The findings of the present investigation indicate that the CGD method is not only rapid enough to screen large germplasm samples, but it also works with acceptable accuracy for its application in rice quality breeding.