Great Lakes Dairy Sheep Symposium - the Department of Animal ...

Great Lakes Dairy Sheep Symposium - the Department of Animal ... Great Lakes Dairy Sheep Symposium - the Department of Animal ...

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Table 9 - Coefficients of correlation and statistical significance for simple regressions developed separately for each production class. Production class Milk yield (g/d) < 400 400-799 800-1199 1200-1600 Number of data 63 260 97 20 Dependent Variable Milk fat content (%) Independent Variable Milk yield (g/d) ns - 0.28 c ns - 0.39 a Dietary NDF (% DM) ns - 0.24 c - 0.44 c - 0.60 b NDF intake (% BW) - 0.21 a - 0.35 c - 0.48 c - 0.89 c Energy balance (UFL/d) - 0.24 a - 0.28 c - 0.42 c - 0.79 c a P < 0.10; b P < 0.01; c P < 0.001; ns = P > 0.1 In the ewes with the highest milk yield, one of the major factors affecting milk fat concentration was their EB. In the same class, NDF intake (% of BW) was positively associated with energy intake (% of BW) (r = + 0.92). As energy intake increased, as a result of the increase in pasture (and NDF) intake, the EB improved, probably reducing body fat mobilization and the availability of long chain FA for the mammary gland. As a consequence, milk fat concentration decreased. It is important to highlight that for each experimental treatment the amount of concentrate supplied was the same for all animals, while pasture was fed ad libitum. Therefore, the ewes with the highest milk yield had to eat more pasture (and fiber) than the animals with lower milk yield and requirements. The negative correlation between milk fat concentration and NDF concentration and intake (Table 9 and Figures 4 and 5) is in clear contrast to the positive association between milk fat concentration and NDF previously mentioned (Emery, 1988; Bencini and Pulina, 1997). In the ewes with low milk yield, factors other than precursor availability were important and milk fat concentration was probably largely affected by individual characteristics. This explains why the association between milk fat and the predictors decreased, as milk yield decreased (Table 9). Cannas and Avondo (2002) found that if all the ewes with less than 0.65 kg/d of milk yield were excluded from their database, so that the minimum value was equal to the one of the database of Bocquier and Caja (1993; 2001), the relationship between milk fat concentration and EB would have the same slope of equation [4]: [5] milk fat concentration (%) = 6.99 - 1.22 EB (UFL/d) (r 2 = 0.14; P< 0.0001) The lower coefficient of determination of equation [5] compared to equation [4] is probably the result of a wider range in the data set used for its development (650-1600 g/d of milk in equation [5] vs. 0.65-3.5 l/d in equation [4]). The fact that the slope of the equation was identical in the two equations suggests that the milk fat concentration decreases by 12.2 g/l for each UFL/d of variation in EB regardless the breed considered. The difference in intercept might be due to the different distribution of the data in the two datasets or might suggest breed differences in the average milk fat concentration. Once these differences are accounted for, milk 102

fat concentration can be used as a nutritional indicator to monitor the nutritional status (energy balance) of the ewes. More studies are clearly needed to test the relationship between milk fat and EB and the use of milk fat concentration as a nutritional indicator for different breeds and production levels. The variation in milk fat concentration observed by Bocquier and Caja (1993; 2001) and by Cannas and Avondo (2002), as EB varied, was much larger than that observed in dairy cows by Grieve et al. (1986). This suggests a more important contribution of FA originated from body fat mobilisation in sheep than in cows and supports the advice of using milk fat concentration as a nutritional indicator, at least in ewes in the first months of lactation with medium-high milk yield. Bocquier and Caja (1993; 2001) also reported a positive relationship between EB and milk protein concentration. However, since this relationship is much weaker than that reported for fat concentration, the use of milk protein as a nutritional indicator does not seem feasible. Milk fat (%) Milk fat (%) 14 12 10 8 6 4 2 14 12 10 8 6 4 2 y = -0.22x + 15.57 R 2 = 0.36 30 35 40 45 50 55 Dietary NDF (% DM) y = -0.004x + 11.549 R 2 = 0.151 1100 1200 1300 1400 1500 1600 1700 Milk yield (g/d) Figure 4 - Relationship between milk fat concentration and dietary and animal characteristics for ewes that produced more than 1200 g/d of milk. 103 Milk fat (%) Milk fat (%) 14 12 10 8 6 4 2 14 12 10 y = -2.81x + 10.73 R 2 = 0.79 0.5 1.0 1.5 2.0 2.5 3.0 NDF intake (% BW) 8 6 4 2 y = -2.96x + 6.43 R 2 = 0.63 -1.0 -0.5 0.0 0.5 1.0 Energy balance (UFL/d)

Table 9 - Coefficients <strong>of</strong> correlation and statistical significance for simple regressions<br />

developed separately for each production class.<br />

Production class<br />

Milk yield (g/d) < 400 400-799 800-1199 1200-1600<br />

Number <strong>of</strong> data 63 260 97 20<br />

Dependent Variable<br />

Milk fat content (%)<br />

Independent Variable<br />

Milk yield (g/d) ns - 0.28 c ns - 0.39 a<br />

Dietary NDF (% DM) ns - 0.24 c - 0.44 c - 0.60 b<br />

NDF intake (% BW) - 0.21 a - 0.35 c - 0.48 c - 0.89 c<br />

Energy balance (UFL/d) - 0.24 a - 0.28 c - 0.42 c - 0.79 c<br />

a P < 0.10; b P < 0.01; c P < 0.001; ns = P > 0.1<br />

In <strong>the</strong> ewes with <strong>the</strong> highest milk yield, one <strong>of</strong> <strong>the</strong> major factors affecting milk fat<br />

concentration was <strong>the</strong>ir EB. In <strong>the</strong> same class, NDF intake (% <strong>of</strong> BW) was positively<br />

associated with energy intake (% <strong>of</strong> BW) (r = + 0.92). As energy intake increased, as a result<br />

<strong>of</strong> <strong>the</strong> increase in pasture (and NDF) intake, <strong>the</strong> EB improved, probably reducing body fat<br />

mobilization and <strong>the</strong> availability <strong>of</strong> long chain FA for <strong>the</strong> mammary gland. As a consequence,<br />

milk fat concentration decreased. It is important to highlight that for each experimental<br />

treatment <strong>the</strong> amount <strong>of</strong> concentrate supplied was <strong>the</strong> same for all animals, while pasture was<br />

fed ad libitum. Therefore, <strong>the</strong> ewes with <strong>the</strong> highest milk yield had to eat more pasture (and<br />

fiber) than <strong>the</strong> animals with lower milk yield and requirements. The negative correlation<br />

between milk fat concentration and NDF concentration and intake (Table 9 and Figures 4 and<br />

5) is in clear contrast to <strong>the</strong> positive association between milk fat concentration and NDF<br />

previously mentioned (Emery, 1988; Bencini and Pulina, 1997).<br />

In <strong>the</strong> ewes with low milk yield, factors o<strong>the</strong>r than precursor availability were important<br />

and milk fat concentration was probably largely affected by individual characteristics. This<br />

explains why <strong>the</strong> association between milk fat and <strong>the</strong> predictors decreased, as milk yield<br />

decreased (Table 9).<br />

Cannas and Avondo (2002) found that if all <strong>the</strong> ewes with less than 0.65 kg/d <strong>of</strong> milk<br />

yield were excluded from <strong>the</strong>ir database, so that <strong>the</strong> minimum value was equal to <strong>the</strong> one <strong>of</strong> <strong>the</strong><br />

database <strong>of</strong> Bocquier and Caja (1993; 2001), <strong>the</strong> relationship between milk fat concentration and<br />

EB would have <strong>the</strong> same slope <strong>of</strong> equation [4]:<br />

[5] milk fat concentration (%) = 6.99 - 1.22 EB (UFL/d) (r 2 = 0.14; P< 0.0001)<br />

The lower coefficient <strong>of</strong> determination <strong>of</strong> equation [5] compared to equation [4] is<br />

probably <strong>the</strong> result <strong>of</strong> a wider range in <strong>the</strong> data set used for its development (650-1600 g/d <strong>of</strong><br />

milk in equation [5] vs. 0.65-3.5 l/d in equation [4]). The fact that <strong>the</strong> slope <strong>of</strong> <strong>the</strong> equation was<br />

identical in <strong>the</strong> two equations suggests that <strong>the</strong> milk fat concentration decreases by 12.2 g/l for<br />

each UFL/d <strong>of</strong> variation in EB regardless <strong>the</strong> breed considered. The difference in intercept might<br />

be due to <strong>the</strong> different distribution <strong>of</strong> <strong>the</strong> data in <strong>the</strong> two datasets or might suggest breed<br />

differences in <strong>the</strong> average milk fat concentration. Once <strong>the</strong>se differences are accounted for, milk<br />

102

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