Mid-Infrared Spectroscopy for Predicting Goat Milk Coagulation Properties

Area of Science:

• Dairy Science
• Analytical Chemistry
• Agricultural Technology

Background:

• Milk coagulation properties (MCPs) are vital for goat cheese production and quality.
• Traditional MCP assessment uses time-consuming lactodynamographic analysis.
• Mid-infrared spectroscopy (MIRS) presents a rapid, large-scale alternative for evaluating milk's technological traits.

Purpose of the Study:

• To evaluate the potential of MIRS for predicting MCPs in goat milk.
• To assess MIRS's accuracy in classifying milk samples based on coagulation aptitude.
• To determine if MIRS can be a viable tool for the dairy-goat sector.

Main Methods:

• Collected 501 bulk goat milk samples from various farms.
• Paired reference MCP measurements with mid-infrared spectra.
• Developed prediction models using partial least squares regression and partial least squares discriminant analysis.

Main Results:

• The MIRS model for rennet coagulation time achieved sufficient accuracy for screening (R²CrV = 0.68, R²Ext = 0.66, RPD = 2.05).
• Models for curd-firming time and curd firmness showed lower performance.
• Classification of high coagulation aptitude yielded balanced accuracy values of 0.81 (calibration) and 0.74 (validation).

Conclusions:

• MIRS shows promise for predicting certain MCPs, particularly rennet coagulation time, in goat milk.
• Further model refinement and larger datasets are needed for broader application.
• MIRS could become a valuable tool for monitoring and enhancing milk suitability for cheesemaking in the dairy-goat industry.