Electrical Conductivity as an Indicator of Milk Spoilage for Use in Biosensor Technology
Li, Xingyi

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Li, X. (2016). Electrical Conductivity as an Indicator of Milk Spoilage for Use in Biosensor Technology (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/6788
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http://hdl.handle.net/10523/6788
Abstract:
Milk is characterised as a perishable food. It is vulnerable to microbial contamination and has a limited shelf life, even when stored in a cold environment. Rapid milk spoilage is a sustained problem that restrains the shelf life of milk, and it consistently burdens the global food waste. Thus, there is a continuous interest in seeking better means of milk quality control and management. Recently, the development of biosensing technology offers a potential solution for better managing strategies of milk quality. Biosensors have been developed from growing demand for a reliable, cost-effective and rapid chemical detection tool. Many disciplines including clinical medicine, food industry, and environment monitoring employ biosensors as analytical tools. In particular, the use of electrical conductivity (EC) as a biosensing approach has frequently been studied in the dairy sector. However, its application to milk spoilage has yet to be fully explored.
The scope of this study was to investigate the use of EC as a parameter to aid in the prediction of milk spoilage. A portable conductivity meter was used to measure the EC in milk; the total bacterial count (TBC), lactic acid (LA) concentration and pH were assessed using standard plate count methods, titratable acidity and digital pH meter, respectively. Commercial pasteurized skim and whole milk were used in the study. The variations of EC, TBC, LA concentration and pH were measured over an extended storage of milk that held at either 4 or 8℃ in the trial experiment. The change in EC was comparatively examined with the change of other measured parameters, and the interrelationship between EC and parameters was analysed by correlation analysis. In addition, several laboratory-controlled model systems were used to assess the impacts of every individual parameter on the change of EC. The results of trial and model systems were compared with each other.
The trial experiment showed that EC progressively increases with an increase in TBC, LA concentration and pH during spoilage of skim and whole milk under storing at 4 and 8℃. The change in EC was found to have moderate to strong correlations with the measured parameters in spoilt milk. A statistically significant difference in EC value was observed before the complete spoilage of milk, when either the flavour defects or textural changes occurred. Moreover, the model systems revealed that the increase in EC is proportional linear to an increased LA concentration and decreased pH. By comparing the results between trial experiment and model systems, it showed that LA approximately contributed one-quarter of the total proportion of changed EC in spoiled milk. Furthermore, a number of bacteria present in milk with more than 〖10〗^7 colony forming units (CFU)/ml significantly decreased the mean EC value of milk. In addition, the ‘best before date’ (BBD) underestimated the correct shelf life of milk at both 4 and 8℃.
The fixed nature of BBD restrains its use as a suitable indicator. In comparison, EC can be a potential alternative to predict milk spoilage. Since it is a direct measurement of spoilage of milk, and changes simultaneously with the growth of bacteria, production of LA and acidity in milk held at either the optimal (4℃) or the inappropriate (8℃) temperatures. Further investigations are needed to obtain a better understanding of the interrelationship between EC and milk spoilage preceding the valid application of biosensing technology.
Date:
2016
Advisor:
Azam, Ali; Sarah, Wakes; Phil, Bremer
Degree Name:
Master of Science
Degree Discipline:
Centre for materials science and technology
Publisher:
University of Otago
Keywords:
milk; spoilage; biosensor; electrical; conducitivity; shelf life; detection; method
Research Type:
Thesis
Languages:
English
Collections
- Thesis - Masters [3379]
- Bioengineering [4]
- Applied Science [16]