Observed milk quality of different crossbreds under different categories of farm
The daily average milk yield (Liter) and milk constituents based on the farm category and Holstein-Friesian crossbreeds are presented in Table 1. From Table 1, it’s evident that there was a significant difference (P<0.05) in milk yield among crosses and also in the same crosses under different farm categories. Besides, the average milk production was also differed significantly (P<0.05) among the farm categories. Milk yield (Liter/day) of 75% HF×25% L crossbred was the highest, whereas 50%HF×50% L crossbred was the lowest irrespective of the farm categories. Milk yield increased when the proportion of exotic inheritance increased from 50 to 75 per cent was an agreement to
Singh (2016). Significant (P<0.05) difference in production performance of 75% HF × 25% L also may be attributed to the variations in the level of management was an agreement to
Kumar et al., (2017) and
Nath et al., (2016).
Observed milk fat percentage in different farm categories and crossbreds
There was a significant difference (P<0.05) in fat percentage of milk among different crosses and the same crosses under different farm categories. The highest fat percentage was recorded in 50%HF × 50%L and the lowest in 75%HF×25%L crossbred irrespective of farm categories. There were significant (p<0.05) differences in fat percentage among the different crossbreds of HF. Milk fat percentage was highest in 50%HF×50%L and the lowest for 75%HF×25%L crossbred irrespective of farm categories. Our results were similar to the findings of
Haile et al., (2009); Cheruiyot et al., (2018). Farm average fat percentage was significantly (P<0.05) higher in farms belongs to category A compared to farms belongs to category B and C. Regular supply of fodder and experience inefficient feed management might be the cause for average higher fat percentages in farms belongs to category A compared to category B and C.
Yeamkong et al., (2010) findings that variability of fat across farm size could be associated with the availability of roughage and the ability of farmers to manage and utilize feed resources was similar to our results.
Observed milk protein percentage in different farm categories and crossbreds
There was a significant difference (P<0.05) in the average protein percentage of milk among different farm categories. The highest protein percentage was recorded in 50%HF×50%L and lowest in 75%HF×25%L crossbred irrespective of farm categories. Our findings were similar to the results of
Cheruiyot et al., (2018) and
Haile et al., (2009). A non-significant difference was observed in protein percentage between 50% crosses of HF with Local (L) and Sahiwal (SH) under the same and different farm categories. Our findings were an agreement with
Haile et al., (2009). The average protein percentage of different farm categories was differed significantly (P<0.05). The average protein percentage was significantly higher in farms belongs to category A compared to B and C. That difference might be attributed due to differences in management and feed supply of the farms under different categories. The farms belong to B and C have often changed their rations according to availability of roughage and meet the scarcity of forage with non-fiber higher energy concentrate feed compare to farms belongs to category A. Altering the nutrition by changing the proportion of protein in the diet has been shown to affect milk protein composition
Tacoma (2016) was an agreement to us.
Observed milk lactose percentage in different farm categories and crossbreds
There was no significant difference in lactose content among different farms categories and crosses. Comparatively higher lactose content was found in 50%HF×50%L crossbred under farm category A and the lowest in 75%HF×25%L cross under category B farm. Lactose percentage was comparatively higher in the case of 50% Holstein crosses with Local (L) and Sahiwal (SH) compare to 75% crosses of Holstein (HF) under different farm categories. But the differences were non-significant. Our findings were similar to
Shibru et al., (2019) and
Wangdi et al., (2016). The average lactose percentage was higher in farms belongs to category A compared to farms belongs to category B and C. Supply of higher concentrate and imbalance of roughage and concentrate ratio in ration by the farms belong to category B and C and supply comparatively balanced ration with a proper ratio of roughage and concentrate in farms under category A might be the cause for the higher concentration of lactose under category A farms compare to B and C. Our findings were an agreement to
Basset et al., (2012).
Observed milk mineral percentage in different farm categories and crossbreds
The mineral content of same and different HF crosses did not differ in the same and different farm categories (Table 1). The highest percentage of minerals were observed in 50%HF×50%L crossbred and the lowest in 75%HF×25%L crossbred irrespective of farm categories (Table 1). Furthermore, there were no significant differences (P<0.05) observed in the mineral content of milk among different farm categories. Our findings were in agreement to
Noori et al., (2014) and
Gemechu et al., (2015).
Observed milk SNF percentage in different farm categories and crossbreds
In the case of lactose percentage of milk, there was no significant difference (P<0.05) among the farm categories and crossebreds (Table 1). The highest lactose percentage was found in 50%HF×50%L crossbred of farms belong to category A and the lowest in 75%HF×25%L crossbred in farms belong to category B (Table 1). Our findings were similar to
Shibru et al., (2019) and
Wangdi et al., (2016). The average lactose percentage was highest in farms belongs to category A compared to categories B and C (Table 1
). This may be attributed to the energy balance difference among farm categories was an agreement with
Costa et al., (2019).
Correlation with milk yield and other milk constituent
From the correlation regression (Table 2) it was found that correlation with milk production and milk composition (fat, protein, lactose, mineral SNF) has a great impact on dairy cattle in different farm categories. In this study, most of the milk traits showed a negative strong significant (P<0.05) correlation with milk yield, fat (-0.560), protein (-0.307), minerals (-0.602) and SNF (-0.379) and a weak positive significant (P<0.05) correlation were observed between milk yield with lactose (0.06).
Sourabh et al., (2017) also reported that a negative correlation between milk yield and major milk constituents. These findings indicate that selection of crosses with increased blood level of HF for higher milk production may tend to decline milk composition was an agreement with
Alphonsus and Essien (2012).