In-Line Technologies for the Analysis of Important Milk Parameters during the Milking Process: A Review

Abstract

Considering automatized and robotic milking systems substantially decreasing the contact between producers and the herd, milk analysis is crucial to maintain the quality and safety of all dairy products. These systems naturally also decrease the possibility of health problems and illness identification. Abnormalities in milk can be caused by several factors. Milk quality can be affected by external conditions, such as temperature and contamination in the feedstock; by management practices, such as hygiene, milking frequency, treatment, and feedstuff quality; and by diseases, genetics, or age. Somatic cell count, electric conductivity, and contents of urea, fat, protein, and lactose were reviewed as likely parameters of milk representing its quality with respect to feedback for consumers and breeders. Methods for evaluating milk constituents and parameters are still being developed to provide in-line information. These methods allow the avoidance of enormous economic losses every year caused by milk discard, health treatments, or cow replacements. In addition, individual and in-line milk analysis provides information in terms of nutritional status or lactation period and fertility. The objective of this study is to identify trends and potential methods focusing on in situ and in-line techniques for the analysis of milk parameters during the automatized and robotic milking process. Four methods are described and compared: near-infrared spectroscopy (NIRS) and mid-infrared spectroscopy (MIRS), optical analysis, milk conductivity analysis, and milk leukocyte differential test. The versatility and accessibility of these methods were also evaluated, showing a considerable range of possible related problems.

Near-infrared spatially-resolved spectroscopy for milk quality analysis

“…The implementation of in-line measurements is necessary when considering the increasing automation of the dairy sector and the food industry (Rodenburg, 2017). Non-destructive sensors integrated into a milk pipeline can enable high-frequency and autonomous composition monitoring, which can have measurable positive impacts on dairy quality control and processing efficiency, animal health and welfare, and dairy production economics (Kunes et al, 2021). In-line milk quality analysis can further benefit dairy processing systems by enabling milk sorting infrastructures to classify milk into different batches at the point of production (Augustin et al, https://doi.org/10.26434/chemrxiv-2023-kswct ORCID: https://orcid.org/0000-0001-6178-0088 Content not peer-reviewed by ChemRxiv.…”

Bulk and Surface Acoustic Wave Biosensors for Milk Analysis

“…Furthermore, the viscosity is affected by mechanical and thermal treatments to which the milk was subjected. Consequently, a comprehensive analysis of milk samples requires both the specific detection of milk components, be it natural ingredients or contaminants, and the determination of the physical parameters of the milk as a whole [ 1 , 2 , 3 , 4 ].…”

“…LFAs are mainly being used for sample screening or field tests since they are associated with the least experimental effort but may lack sufficient accuracy. In addition, the polymerase chain reaction (PCR) is applied to identify and detect bacterial DNA in milk [ 1 , 2 , 3 , 4 , 5 , 6 ].…”