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  • Author or Editor: S. Tamhankar x
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Ten dicoccum wheats were analyzed for their physico-biochemical and milling properties to evaluate the pasta making potential. Dicoccums showed higher protein content and mixograph midline peak values compared to durum variety MACS2846. Mixographic properties of dicoccums were poor compared to durums, due to lower functional visco elastic gluten content. Dicoccums were poorer in milling properties compared to durums, due to lower test weight and thousand-grain weight. Among dicoccums, DDK 1025 showed high micro SDS sedimentation volume and strong mixographic properties, but values were still lesser compared to durum MACS 2846. HMW glutenin subunits in recently developed/released dicoccums were similar to durum parents and were different from the older dicoccums. LMW glutenin subunits, however, were similar to dicoccum parents, except in DDK 1025 which showed LMW glutenin subunits similar to durum wheat. To breed high quality dicoccum wheat for pasta products, breeders should select superior glutenin subunits composition, along with better mixograph properties, keeping morpho-botanical characteristics of dicoccum wheat.

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An ingredient of ‘Dasamoola’ and ‘Laghupanchamoola’ group of drugs, the source of ‘Brihati’ has been controversial. Although the dried root of Solanum anguivi is considered as the source of the drug ‘Brihati’ according to the Ayurvedic Pharmacopoeia of India, closely related and morphologically similar few species like Solanum torvum, Solanum melongena, Solanum incanum, and Solanum insanum are known as its substitutes. In the present study, a high-performance thin-layer chromatography (HPTLC) method was developed and validated for the chemoprofiling and quantitative estimation of glycoalkaloid solamargine from 5 species of the genus Solanum as well as market samples. The developed method was precise, accurate, robust, specific, and linear. The results showed that S. incanum has the highest content of solamargine, followed by S. insanum. Out of the 9 market samples analyzed, solamargine was detected only in 3 samples. Unsupervised pattern recognition techniques, such as principal component analysis and hierarchical cluster analysis, were used to analyze the complex fingerprint patterns and to predict the grouping of samples. The method clearly segregated the field and market samples. Our study is the first attempt to evaluate the drug ‘Brihati’ and the market samples using HPTLC.

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