Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2764


Predicting the microbial safety of irrigation water and fresh produce: A collaborative approach

    1Department of Biotechnology and Food Technology, Durban University of Technology, South Africa. 2Department of Information Technology, Durban University of Technology, South Africa.  
Email: [email protected]

  •  Accepted: 31 May 2013
  •  Published: 30 June 2013




Outbreak of food borne illnesses as a result of consumption of fresh vegetables and fruits is occurring regularly. In USA for example, it has become business as usual to hear and read about fresh produce recalls. Although, the increase has been attributed to many factors it is however more important to find solution to the problem. An effective solution will be a proactive approach such as prediction and forecasting which are not new in the field of meteorology. For many years now, meteorologists have been predicting the weather. It is indeed high time that food scientists in collaboration with other professionals found out dependable and realistic methods to predict the presence of pathogens in irrigation water and fresh produce. In this review, several prediction tools such as factor analysis, artificial neural network, support vector machine, logistic regression analysis, partial least square and ‘nanosensing’ were discussed. The problem of produce safety may in fact be solved when food scientist collaborate with I.T professionals, biotechnologists and others.


Key words: Listeria monocytogenes, neural network, nanosensing, partial least squares, food safety.