Inline optimization of cheese making using a near infrared light backscatter sensor technology

Student thesis: Doctoral thesis


Cheese making is the “controlled process of removing water from milk”. This process concentrates the milk protein, fat and other nutrients and increases its shelf life. Cheese manufacture consists of two main steps occurring in the cheese vat, milk coagulation and curd syneresis. Real-time monitoring of milk coagulation, curd firming and syneresis as well as inline prediction of cutting time is essential for cheese making as those factors exert a substantial impact in both cheese yield and quality. Many factors affect the cheese manufacturing process by modifying the quantity, quality, and processing properties of the produced milk. The general objective of this dissertation was to evaluate the impact of milk mixture (i.e., different proportions of goat, sheep and cow milk) and low quality milk (i.e., milk from animals with subclinical mammary infections) in the prediction of clotting time, cutting time, syneresis rate and several other cheese making indexes based on monitoring milk coagulation and syneresis using NIR light backscatter sensor technologies. Several optical devices: a lab-scale coagulation tester (CoAguLab), an inline coagulation sensor and an inline large field of view (LFV) syneresis sensor were used to monitor milk coagulation, cutting time, and whey separation during Manchego cheese manufacture. Optical parameter tmax and several other time-based light backscatter parameters were highly correlated with visually- and rheologically-derived clotting and cutting times as well as cheese yield, yield of whey and SCC. It was observed that milk mixtures and animal breed did not have a significant (P ≥ 0.05) effect on optical and rheological time parameters related to clotting time, while different enzyme concentrations, coagulation temperatures, and subclinical infection had a significant effect on all optical and rheological parameters related to milk clotting time, and gel assembly rate (i.e., aggregation and firming rates). Subclinical mastitis, milk mixtures, temperature, and breed had a significant effect on curd syneresis while cheese yield was affected by subclinical mastitis and breed (note that syneresis effect of enzyme concentration, temperature and milk mixtures was not directly evaluated). Prediction models using light backscatter parameters alone or in combination with protein/solids concentration were successfully obtained for visually determined clotting and cutting times, rheologically derived gelation and cutting times, tanδ at cutting, syneresis rate constant and several cheese yield indicators. Our results confirm the usefulness of light backscatter inline monitoring of milk coagulation and curd syneresis for improved process control of those two critical cheese making steps. The results obtained show that the impact of factors such as milk mixtures and subclinical mastitis in cheese manufacture needs to be considered on cheese making process control operations.
Date of Award21 Nov 2016
Original languageEnglish
SupervisorManuel Castillo Zambudio (Director)


  • Science
  • Food
  • Sensors

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