Determination of DPPH free radical scavenging activity: Application of artificial neural networks

Food Chemistry

Volumn 194, Issue , 2016, Pages 705-711

  Musa, Khalid Hamid ^a   Abdullah, Aminah ^a   Al Haiqi, Ahmed ^a  

^a UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Artificial neural network; DPPH free radical scavenging activity; Image classification; Machine learning

Indexed keywords

IMAGE CLASSIFICATION; LEARNING SYSTEMS; METEOROLOGICAL INSTRUMENTS; NEURAL NETWORKS; SPECTROPHOTOMETERS;

2 ,2-DIPHENYL-1-PICRYLHYDRAZYL; BROWN RICE; COMPUTATIONAL APPROACH; DPPH FREE RADICAL SCAVENGING ACTIVITIES; DPPH RADICALS; FREE RADICAL SCAVENGING ACTIVITY; QUANTITATIVE RESULT; TEA EXTRACTS;

FREE RADICALS;

1,1 DIPHENYL 2 PICRYLHYDRAZYL; TROLOX C; 2,2-DIPHENYL-1-PICRYLHYDRAZYL; BIPHENYL DERIVATIVE; PICRIC ACID; SCAVENGER;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BEAN; BLACK RICE; BROWN RICE; CINNAMON; CLOVE; CONCENTRATION (PARAMETERS); CONTROLLED STUDY; DPPH RADICAL SCAVENGING ASSAY; MACHINE LEARNING; MUNG BEAN; RED BEAN; RED RICE; RICE; SPECTROPHOTOMETRY; TEA; CHEMISTRY;

BIPHENYL COMPOUNDS; FREE RADICAL SCAVENGERS; NEURAL NETWORKS (COMPUTER); PICRATES;

EID: 84940473397     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2015.08.038     Document Type: Article

References (18)

1. J.R. Anderson, R.S. Michalski, J.G. Carbonell, and T.M. Mitchell Machine learning: An artificial intelligence approach II 1986 Morgan Kaufmann California
2. J.A. Balejko, Z. Nowak, and E. Balejko Artificial neural network as the tool in prediction rheological features of raw minced meat Acta Scientiarum Polonorum Technologia Alimentaria 11 2012 273 281
3. W.G. Baxt Application of artificial neural networks to clinical medicine The Lancet 346 1995 1135 1138
4. W. Brand-Williams, M.E. Cuvelier, and C. Berset Use of a free radical method to evaluate antioxidant activity Lebensmittel-Wissenschaft und Technologie 28 1995 25 30
5. A. Bucinski, H. Zieliński, and H. Kozłowska Artificial neural networks for prediction of antioxidant capacity of cruciferous sprouts Trends in Food Science and Technology 2004 161 169
6. A.C. Cabrera, and J.M. Prieto Application of artificial neural networks to the prediction of the antioxidant activity of essential oils in two experimental in vitro models Food Chemistry 118 2010 141 146
7. C. Cimpoiu, V.M. Cristea, A. Hosu, M. Sandru, and L. Seserman Antioxidant activity prediction and classification of some teas using artificial neural networks Food Chemistry 127 2011 1323 1328
8. Clark, J., Koprinska, I., & Poon, J. (2003). A Neural Network Based Approach to Automated E-Mail Classification. In Web Intelligence, IEEE/WIC/ACM International Conference on (pp. 702-702). IEEE Computer Society.
9. K. Di Scala, G. Meschino, A. Vega-Gálvez, R. Lemus-mondaca, S. Roura, and R. Mascheroni An artificial neural network model for prediction of quality characteristics of apples during convective dehydration Food Science Technology (Campinas) 33 2013 411 416
10. Eaton, J. W. Gnu Octave (2015) URL http://www.gnu.org/software/octave. Accessed 23/02/2015.
11. R.P. Guine, M.J. Barroca, F.J. Goncalves, M. Alves, S. Oliveira, and M. Mendes Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments Food Chemistry 1 168 2015 454 459
12. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I.H. Witten The Weka Data Mining Software: An update ACM SIGKDD Explorations Newsletter 11 1 2009 10 18
13. S.B. Kotsiantis Supervised machine learning: A review of classification techniques Informatica 31 2007 249 268
14. T.M. Mitchell Machine learning and data mining Communications of the ACM 42 1999 30 36
15. T.M. Mitchell The discipline of machine learning 2006 Carnegie Mellon University, School of Computer Science, Machine Learning Department
16. P. Molyneux The use of the stable free radical diphenylpicryl-hydrazyl (DPPH) for estimating antioxidant activity Songklanakarin Journal of Science and Technology 26 2004 211 219
17. K.H. Musa, A. Abdullah, B. Kuswandi, and M.A. Hidayat A novel high throughput method based on the DPPH dry reagent array for determination of antioxidant activity Food Chemistry 141 2013 4102 4106
18. G.P. Zhang Neural networks for classification: A survey systems, man, and cybernetics, Part C: Applications and reviews IEEE Transactions 30 2000 451 462