An empirical method for prediction of cheese yield

Area of Science:

• Dairy Science
• Food Chemistry
• Agricultural Economics

Background:

• Classical formulae like VanSlyke estimate theoretical cheese yield from milk fat and casein content.
• Accurate milk component analysis is crucial for yield prediction but often too costly for small factories.
• Dairy farmers desire milk payment based on cheese yield, reflecting milk quality and composition.

Purpose of the Study:

• To develop a cost-effective empirical test for predicting cheese yield in small factories.
• To establish a practical method for milk payment based on cheese yield potential.
• To correlate simple dry weight yield measurements with theoretical cheese yield.

Main Methods:

• Developed a miniature cheese-making process using basic laboratory equipment.
• Measured dry weight yield gravimetrically after a controlled drying process.
• Performed linear regression analysis comparing theoretical yield with measured dry weight yield.

Main Results:

• A regression equation (y = 1.275x + 1.528) was developed for Cheddar cheese with high correlation (r² = 0.981).
• Cross-validation showed a low standard deviation of the difference (0.194) and coefficient of variation (1.95%).
• The empirical test provides a reliable and practical alternative to expensive milk component analysis.

Conclusions:

• The developed empirical test accurately predicts cheese yield, offering a viable solution for small-scale dairy operations.
• This method facilitates fair milk payment to farmers based on actual yield potential and milk quality.
• Direct correlation of dry weight yields can be used for cheeses lacking established theoretical yield equations.