In this study, 737 individual sheep milk samples were collected 2 times from morning milkings to evaluate the relationships between Brix refractometer measurements and milk constituentsd protein and fat percentages to verify its ability to predict milk constituents. The Pearson's simple (rSP) and partial (rPP) correlations between milk constituents were calculated, and several first- and second-order regressions were tested to predict the protein and fat percentages. The rSP coefficients between the Brixrefractometer measurement and fat (rSP ¼ 0.46) and protein (rSP ¼ 0.87) contents were different fromthe rPP coefficients, particularly for fat percentage (rPP ¼ 0.04 and rPP ¼ 0.82, for fat and protein per-centages, respectively). The results of the forecasts can be considered satisfactory only for the first order regression that predicted the percentage of milk protein, while the regression that predicted the percentage of fat milk protein presented a weak forecasting capacity.
Massimo Todaro, Riccardo Gannuscio, Isabella Mancuso, Barbara Ducato, Maria Luisa Scatassa (2024). The use of Brix refractometer as a simple and economic device to estimate the protein content of sheep milk. INTERNATIONAL DAIRY JOURNAL, 154, 105940 [10.1016/j.idairyj.2024.105940].
The use of Brix refractometer as a simple and economic device to estimate the protein content of sheep milk
Massimo TodaroPrimo
;Riccardo Gannuscio
Secondo
;
2024-01-01
Abstract
In this study, 737 individual sheep milk samples were collected 2 times from morning milkings to evaluate the relationships between Brix refractometer measurements and milk constituentsd protein and fat percentages to verify its ability to predict milk constituents. The Pearson's simple (rSP) and partial (rPP) correlations between milk constituents were calculated, and several first- and second-order regressions were tested to predict the protein and fat percentages. The rSP coefficients between the Brixrefractometer measurement and fat (rSP ¼ 0.46) and protein (rSP ¼ 0.87) contents were different fromthe rPP coefficients, particularly for fat percentage (rPP ¼ 0.04 and rPP ¼ 0.82, for fat and protein per-centages, respectively). The results of the forecasts can be considered satisfactory only for the first order regression that predicted the percentage of milk protein, while the regression that predicted the percentage of fat milk protein presented a weak forecasting capacity.File | Dimensione | Formato | |
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