Effect of different levels of rapidly degradable carbohydrates calculated by a simple rumen model on performance of lactating dairy cows.

Aggregating rumen degradation characteristics of different carbohydrate components into the term modeled rapidly degradable carbohydrates (mRDC) can simplify diet formulation by accounting for differences in rate and extent of carbohydrate degradation within and between feedstuffs. This study sought to evaluate responses of lactating dairy cows to diets formulated with increasing levels of mRDC, keeping the supply of other nutrients as constant as possible. The mRDC content of feedstuffs was calculated based on a simple rumen model including soluble, washable, and nonwashable but potentially degradable fractions, as well as the fractional degradation and passage rates, of sugar, starch, neutral detergent fiber, and other carbohydrates. The mRDC term effectively represents the total amount of carbohydrates degraded in the rumen within 2 h after ingestion. Fifty-two lactating Holstein cows (of which 4 were rumen fistulated) were assigned to 4 treatments in a 4 × 4 Latin square design. Treatments were fed as a total mixed ration consisting of 25.4% corn silage, 23.1% grass silage, 11.6% grass hay, and 39.9% concentrate on a dry matter basis. Differences in mRDC were created by exchanging nonforage neutral detergent fiber-rich ingredients (mainly sugar beet pulp) with starch-rich ingredients (mainly wheat) and by exchanging corn (slowly degradable starch) with wheat (rapidly degradable starch) in the concentrate, resulting in 4 treatments that varied in dietary mRDC level of 167, 181, 194, or 208 g/kg of dry matter. Level of mRDC did not affect dry matter intake. Fat- and protein-corrected milk production and milk fat and lactose yield were greatest at 181 mRDC and decreased with further increases in mRDC. Milk protein yield and concentration increased with increasing mRDC level. Mean rumen pH and diurnal variation in ruminal pH did not differ between treatments. Total daily meal time and number of visits per meal were smaller at 181 and 194 mRDC. Despite milk production responses, increasing dietary mRDC levels, while maintaining net energy and intestinal digestible protein as well as other nutrients at similar levels, did not influence rumen pH parameter estimates and had minor effects on feeding behavior. These results indicate that aggregating rapidly degradable carbohydrate content into one term may be a simple way to further improve predictability of production responses in practical diet formulation for lactating dairy cows.

Technical note: Evaluation of an ear-attached movement sensor to record cow feeding behavior and activity.

The ability to monitor dairy cow feeding behavior and activity could improve dairy herd management. A 3-dimensional accelerometer (SensOor; Agis Automatisering BV, Harmelen, the Netherlands) has been developed that can be attached to ear identification tags. Based on the principle that behavior can be identified by ear movements, a proprietary model classifies sensor data as "ruminating," "eating," "resting," or "active." The objective of the study was to evaluate this sensor on accuracy and precision. First, a pilot evaluation of agreement between 2 independent observers, recording behavior from 3 cows for a period of approximately 9h each, was performed. Second, to evaluate the sensor, the behavior of 15 cows was monitored both visually (VIS) and with the sensor (SENS), with approximately 20 h of registration per cow, evenly distributed over a 24-h period, excluding milking. Cows were chosen from groups of animals in different lactation stages and parities. Each minute of SENS and VIS data was classified into 1 of 9 categories (8 behaviors and 1 transition behavior) and summarized into 4 behavioral groups, namely ruminating, eating, resting, or active, which were analyzed by calculating kappa (κ) values. For the pilot evaluation, a high level of agreement between observers was obtained, with κ values of ≥ 0.96 for all behavioral categories, indicating that visual observation provides a good standard. For the second trial, relationships between SENS and VIS were studied by κ values on a minute basis and Pearson correlation and concordance correlation coefficient analysis on behavior expressed as percentage of total registration time. Times spent ruminating, eating, resting, and active were 42.6, 15.9, 31.6, and 9.9% (SENS) respectively, and 42.1, 13.0, 30.0, and 14.9% (VIS), respectively. Overall κ for the comparison of SENS and VIS was substantial (0.78), with κ values of 0.85, 0.77, 0.86, and 0.47 for "ruminating," "eating," "resting," and "active," respectively. Pearson correlation and concordance correlation coefficients between SENS and VIS for "ruminating," "eating," "resting," and "active" were 0.93, 0.88, 0.98, and 0.73, and 0.93, 0.75, 0.97, and 0.35, respectively. In conclusion, the results provide strong evidence that the present ear sensor technology can be used to monitor ruminating and resting behavior of freestall-housed dairy cattle. Our results also suggest that this technology shows promise for monitoring eating behavior, whereas more work is needed to determine its suitability to monitor activity of dairy cattle.