## 3 Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Milk Yield (/Day)**} \\ \hline Models & P(M) & P(M! data) & BF10 & Signif \\ \hline Breed & 0.0769 & \(3.53\times 10^{-30}\) & 503.38 & *** \\ Age class & 0.0769 & \(3.88\times 10^{-32}\) & 5.54 & ** \\ DIM 2 class & 0.0769 & \(2.01\times 10^{-8}\) & \(2.86\times 10^{24}\) & *** \\ \hline \multicolumn{4}{c}{**Fat (\%)**} \\ \hline Breed & 0.0769 & \(5.29\times 10^{-8}\) & 0.19 & Ns \\ Age class & 0.0769 & \(4.53\times 10^{-7}\) & 1.64 & Ns \\ DIM 2 class & 0.0769 & \(0.31\) & \(1.11\times 10^{6}\) & *** \\ \hline \multicolumn{4}{c}{**Protein (\%)**} \\ \hline Breed & 0.0769 & \(2.34\times 10^{-11}\) & 0.66 & Ns \\ Age class & 0.0769 & \(3.22\times 10^{-9}\) & 90.83 & ** \\ DIM 2 class & 0.0769 & \(0.01\) & \(4.37\times 10^{7}\) & *** \\ \hline \multicolumn{4}{c}{**Lactose (\%)**} \\ \hline Breed & 0.0769 & \(4.31\times 10^{-31}\) & 170.17 & *** \\ Age class & 0.0769 & \(4.19\times 10^{-33}\) & 1.65 & Ns \\ DIM 2 class & 0.0769 & \(1.24\times 10^{-7}\) & \(4.91\times 10^{25}\) & *** \\ \hline \multicolumn{4}{c}{**Fat/Protein**} \\ \hline Breed & 0.0769 & \(6.75\times 10^{-10}\) & 0.13 & Ns \\ Age class & 0.0769 & \(4.52\times 10^{-10}\) & 0.09 & Ns \\ DIM 2 class & 0.0769 & \(0.81\) & \(1.56\times 10^{8}\) & *** \\ \hline \multicolumn{4}{c}{**Fat/Lactose**} \\ \hline Breed & 0.0769 & \(9.09\times 10^{-5}\) & 0.13 & Ns \\ Age class & 0.0769 & \(3.39\times 10^{-4}\) & 0.49 & Ns \\ DIM 2 class & 0.0769 & \(0.55\) & 785.59 & *** \\ \hline \multicolumn{4}{c}{**log\({}_{9}\)SCC 1**} \\ \hline Breed & 0.0769 & \(3.63\times 10^{-9}\) & 2.85 & Ns \\ Age class & 0.0769 & \(9.47\times 10^{-7}\) & 744.22 & *** \\ DIM 2 class & 0.0769 & \(1.20\times 10^{-4}\) & 94,248.97 & *** \\ \hline \end{tabular} \({}^{\dagger}\) SCC—somatic cell count; 2 SD—standard deviation.  
\end{table} 
Table 4: Bayesian ANOVA results for milk variables. Significance symbols were derived from the BF10 values as reported in the text. The different asterisks indicate different levels of statistical significance: very strong (**), decisive (***). \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \(\mathbf{BF_{10}}\) & **Milk Yield** & **Fat** & **Protein** & **Lactose** & **F/P 2 Ratio** & **F/L 3 Ratio** & **log\({}_{10}\)SCC 1** \\ \hline \multirow{2}{*}{**Milk Yield**} & r & — & & & & & \\  & BF\({}_{10}\) & — & & & & & \\ \hline \multirow{2}{*}{**Fat**} & r & \(-0.41\) & — & & & & \\  & BF\({}_{10}\) & *** & — & & & & \\ \hline \multirow{2}{*}{**Protein**} & r & \(-0.31\) & \(0.29\) & — & & & \\  & BF\({}_{10}\) & ** & * & — & & & \\ \hline \multirow{2}{*}{**Lactose**} & r & \(0.17\) & \(0.41\) & \(0.02\) & — & & \\  & BF\({}_{10}\) & * & *** & * & — & & \\ \hline \multirow{2}{*}{**F/P 2 Ratio**} & r & \(-0.28\) & \(0.88\) & \(-0.18\) & \(0.38\) & — & \\  & BF\({}_{10}\) & * & *** & ns & *** & — & \\ \hline \multirow{2}{*}{**F/L 3 Ratio**} & r & \(-0.49\) & \(0.97\) & \(0.31\) & \(0.17\) & \(0.85\) & — \\  & BF\({}_{10}\) & *** & *** & ** & ns & *** & — \\ \hline \multirow{2}{*}{**log\({}_{10}\)SCC 1**} & r & \(-0.41\) & \(0.21\) & \(0.27\) & \(-0.49\) & \(0.12\) & \(0.3\) & — \\  & BF\({}_{10}\) & *** & ns & ns & *** & ns & *** & — \\ \hline \end{tabular} \({}^{\dagger}\) SCC—somatic cell count; 2 F/P ratio—fat to protein ratio; 3 F/L ratio—fat to lactose ratio. The different asterisks indicate different levels of statistical significance: strong (*), very strong (**), decisive (***).  
\end{table} 
Table 5: Bayesian correlation coefficients for milk variables in Alpine goat breed. Asterisks evidence the significance of BF\({}_{10}\) as reported in the text. Figure 1: Patterns of milk variables in Alpine and Nera di Verzasca goat breeds for age and days in milk (DIM), respectively. The effects of breed, age and DIM have been evaluated on milk yield **(a,b)**, milk fat % **(c,d)**, milk protein % **(e,f)**, milk lactose % **(g,h)**, milk fat/protein ratio (i,j)**, milk fat/ lactose ratio (**k,l**) and on somatic cell count **(m,n)**.