Comparison between Univariate and Multivariate Optimisations on Wet Digestion of Almond Nuts Prior To Determination of Magnesium

Tan Jun Hao, Azli Sulaiman

Abstract


Optimisation is the act of improving the efficiency of a certain product, process or system to obtain the best response for measurement. There are two types of optimisation method, which are univariate and multivariate optimisation, for the latter is more effective and efficiency as it considers interactions between parameters. However, univariate optimisation is still being use more frequently than multivariate in certain cases. The purpose of this study is to compare univariate optimisation and multivariate optimisation, hence, to determine the presence of significant difference between both methods. The comparison was done using the analysis of magnesium in almond nuts where the parameters of temperature, volume of nitric acid and time of digestion were optimised. A two-sample assuming unequal variances t-test was then used to determine the difference between both univariate and multivariate optimisation. It was found that there was a significance difference between both methods, whereby based only on the best responses, univariate optimisation method was superior. However, taking all the factors and interactions, multivariate optimisation was, overall, the more efficient and superior method.

Keywords


Univariate; multivariate; optimisation; Almond nuts; determination of Magnesium

Full Text:

PDF

References


Araujo, P.W. and R.G. Brereton, Experimental design III. Quantification. TrAC Trends in Analytical Chemistry. 15(3) (1996) 156-163.

Bezerra, M.A., R.E. Santelli, E.P. Oliveira, L.S. Villar, and L.A. Escaleira, Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta. 76(5) (2008) 965-977.

Lundstedt, T., E. Seifert, L. Abramo, B. Thelin, Å. Nyström, J. Pettersen, and R. Bergman, Experimental design and optimization. Chemometrics and intelligent laboratory systems. 42(1-2) (1998) 3-40.

Myers, R.H. and D.C. Montgomery, Response surface methodology: process and product optimization using designed experiments. (1995) 1-15.

Carley, K.M., N.Y. Kamneva, and J. Reminga, Response surface methodology. (2004) 13-27.

Vera Candioti, L., M.M. De Zan, M.S. Cámara, and H.C. Goicoechea, Experimental design and multiple response optimization. Using the desirability function in analytical methods development. Talanta. 124 (2014) 123-138.

Tung, C.Y., Spectrophotometric Method for the Determination of Saccharin in Preserved Fruits and Beverages, in Faculty of Science. 2009, Universiti Teknologi Malaysia: Faculty of Science.

Moodley, R., A. Kindness, and S.B. Jonnalagadda, Elemental composition and chemical characteristics of five edible nuts (almond, Brazil, pecan, macadamia and walnut) consumed in Southern Africa. Journal of Environmental Science and Health Part B. 42(5) (2007) 585-591.

Hormozi-Nezhad, M.R., M. Jalali-Heravi, H. Robatjazi, and H. Ebrahimi-Najafabadi, Controlling aspect ratio of colloidal silver nanorods using response surface methodology. Colloids and Surfaces A: Physicochemical and Engineering Aspects. 393 (2012) 46-52.

Lobo, F.A., D. Goveia, A.P.d. Oliveira, E.R. Pereira-Filho, L.F. Fraceto, N.L.D. Filho, and A.H. Rosa, Comparison of the univariate and multivariate methods in the optimization of experimental conditions for determining Cu, Pb, Ni and Cd in biodiesel by GFAAS. Fuel. 88(10) (2009) 1907-1914.

Caldas, L.F.S., B.B.A. Francisco, A.D.P. Netto, and R.J. Cassella, Multivariate optimization of a spectrophotometric method for copper determination in Brazilian sugar-cane spirits using the Doehlert design. Microchemical Journal. 99(1) (2011) 118-124.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 eProceedings Chemistry

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright © 2016 Department of Chemistry, Universiti Teknologi Malaysia.

Disclaimer : This website has been updated to the best of our knowledge to be accurate. However, Universiti Teknologi Malaysia shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.
Best viewed: Mozilla Firefox 4.0 & Google Chrome at 1024 × 768 resolution.