Effects of Milking System Operating Conditions on the Milk-Fat-Percentage Measuring Accuracy of an Inline Light-Scattering Sensor

Abstract

Contamination of the inner surface of milk hoses of milking systems with milk residues, water residues and pathogenic microflora has a negative impact on milk quality and can affect the accuracy of light-scattering sensors measuring milk quality parameters. A three-stage study of the influence of milking system operating conditions on the accuracy of a light-scattering sensor is presented. The growth of pathogenic microflora on the inner surface of milk hoses was studied, the flow of milk and milk hoses rinsing was simulated and the accuracy of the light-scattering sensor was tested under conditions of low-quality rinsing of the milking system. A significant difference in the total microbial count was detected between the milk residues of healthy animals and the milk residues of animals with subclinical mastitis (1.2 × 104 CFU/mL and 9.2 × 104 CFU/mL). The presence of Staphylococcus (aureus and epidermidis) was detected in quantities much lower than those that could interfere with the analysis of milk quality parameters. Simulation modeling allowed us to prove that even when rinsing with hot water (80 °C) without chemical solutions, pathogenic microflora in milk hoses of the milking system will be suppressed. Modeling of the milk flow in the measuring chamber of the device showed the stable replacement of milk in the measuring chamber and provided actual measurements of milk quality parameters. It has been determined that low-quality rinsing and water residues in milk hoses lead to a significant increase in measurement error up to 15–20% during the first 30–40 s after the milking system starts operating. The study results confirm that the light-scattering sensors are resistant to such factors of the milking system operation as contamination by pathogenic microflora (S. aureus and S. epidermidis) and low-quality rinsing of milk hoses.

Keywords

• milking systems
• food quality control
• milk
• non-destructive food analysis
• optical sensors