Concrete Mix Design Using Artificial Neural Network

  • Gupta S
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Abstract

Water and ethanolic extracts of four Malaysian local herbs, Tenggek burung (Melicope Iunu-ankenda), Kesum (Polygonum minus), Curry leave (Murraya Koenigii) and Salam (Eugenia polyantha) were investigated for their total phenolic content (TPC), total flavonoids content (TFC) and antioxidant activities (AA). Total phenolic content (TPC) of the herbs was determined using Folin-Ciocalteu reagent assay while the total flavonoid content (TFC) was determined based on aluminium chloride-flavonoid assay. The determination of AA was done using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activitiy and β-carotene bleaching assays (BCB). Different extraction solvents significantly affected the TPC, TFC and AA of all herbs studied (p < 0.05). Both Tenggek burung and Kesum showed highest TPC, TFC and AA regardless of extraction solvents compared to Curry leave and Salam. All herbs showed strong positive correlation between TPC and DPPH assay. However, negative and low correlation between TFC and AA were obtained for all herbs studied. This showed that phenolic compounds of certain structures were responsible for the AA of all the herbs in this study. In conclusion, all herbs in this study except curry leave could be inexpensive sources of good natural antioxidants with nutraceutical potential in food industry.

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APA

Gupta, S. (2013). Concrete Mix Design Using Artificial Neural Network. Journal on Today’s Ideas-Tomorrow’s Technologies, 1(1), 29–43. https://doi.org/10.15415/jotitt.2013.11003

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