Scientists and food researchers have created a device that allows users to monitor the intricacies of cheese production. Using data collected while measuring backscattering of cheese using an Ocean Optics spectrometer and light source, the researchers have developed algorithms to predict the optimal cutting time, fermentation endpoint, whey fat losses, cheese yield and curd moisture of various cheeses.
Cheese-making has long been an art, but it is now becoming a science as well. The process of cutting coagulated milk in vats causes moisture to be released from the curd in the form of whey, and it is the size and moisture of that curd that plays a large role in determining the quality of the finished product. Monitoring the process of curd syneresis is difficult, however, as most methods are disruptive to the cheese-making process.
Researchers from University College, Dublin, Ireland; the University of Kentucky in Lexington, USA; and the Moorepark Food Research Center in Cork, Ireland, have developed an online Vis-NIR optical sensor to monitor various characteristics of the cheese-making process. This type of on-line monitoring of coagulation and syneresis, along with the application of special algorithms to the data, allows instant feedback, improving the consistency of curd moisture and texture from batch to batch.
Three experiments, each comprising unique experimental variables and designs, were undertaken in this study. In each experiment a unique mix of whole milk, skim milk powder, distilled water, cream and calcium chloride (firming agent) was prepared. The milk was heated to a temperature of 32 +/- 0.1 °C. In each experiment, the cutting blades were replaced after gel cutting and stirring at a certain speed for 4 minutes over the course of syneresis. Then curd and whey samples were measured for fat content.
The syneresis sensor comprised a tungsten halogen light source, an optical fiber, a vertical polarizer, and a glass window. Backscattered light was collected over a large area through the glass window. Reflected light was then transmitted through a second fiber and a collimating lens focused the scattered light onto an optical fiber and transmitted it to the HR2000CG-UV-NIR miniature spectrometer.
Raw spectra obtained from the online sensor during syneresis is shown in Figure 1.
The on-line sensor was able to predict whey production and fat content in whey. In general terms, the light backscatter sensor will work in different cheese production plants but a model developed at the laboratory level or for a specific plant may need to be adapted to the needs of that plant, depending on the range of milk composition, cheese type and vat design in use.
Validation of a curd-syneresis sensor over a range of milk composition and process parameters. Mateo, M.J. et al. Journal of Dairy Science , Volume 92 , Issue 11 , 5386 – 5395.
Segments of this material were derived from open-access media published in the Open Access Journals section of ScienceDirect.com.