Prediction of coagulation properties, titratable acidity, and pH of bovine milk using mid-infrared spectroscopy

Abstract

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000-900 cm(-1)) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a(30), mm), TA (SH degrees/50 mL; SH degrees = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm(-1). Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm(-1), 3,040 to 1,700 cm(-1), and 4,000 to 3,470 cm(-1). The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a(30), range 58 mm), 0.25 SH degrees/50 mL (TA, range 3.58 SH degrees/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R(2) = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R(2) = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

Genetic parameters for milk mineral content and acidity predicted by mid-infrared spectroscopy in Holstein–Friesian cows

“…Moreover, mean TA in the present study is similar to reported values of MIRS-predicted TA by De Marchi et al (2009), Colinet et al (2010 and Toffanin et al (2015). The lower pH in first compared with later parity cows corroborates results of Ikonen et al (2004) and could be the consequence, at least partly, of the higher values of P and TA in first lactation cows (Table 2), and the inverse relationships between these minerals and pH (Table 3).…”

Heritability and repeatability of milk coagulation properties predicted by mid-infrared spectroscopy during routine data recording, and their relationships with milk yield and quality traits

“…The use of mid-infrared spectroscopy (MIRS) has been proposed to overcome these limitations and to predict several milk traits such as fatty acid composition (e.g. Soyeurt et al, 2006;De Marchi et al, 2011) andMCP (Dal Zotto et al, 2008;Cecchinato et al, 2009;De Marchi et al, 2009 and. Milk coagulation properties are currently available in several Italian milk laboratories, both for individual and bulk milk samples , since these laboratories have implemented MCP prediction models in Milko-Scan spectrometer (Foss Electric A/S, Hillerød, Denmark).…”

“…foss.dk/industry-solution/products/combifoss-ft). The potential of MIRS to predict milk pH was previously assessed by De Marchi et al (2009), who reported a coefficient of determination in cross-validation of 0.60. SCC was determined with Cell Fossomatic 250 (Foss Electric A/S) and was transformed to SCS according to the formula [SCS 5 3 1 log 2 (SCC/100 000)].…”

New phenotypes for new breeding goals in dairy cattle

“…MIR spectral data are also accurate predictors for parameters related to milk processing properties such as coagulation, acidity and pH (Dal Zotto et al, 2008;De Marchi et al, 2009). Cecchinato et al (2009) demonstrated that selection for milk with better cheese processing ability predicted from MIR data is feasible.…”