Nitrogen Use Efficiency And Sustainable Nitrogen Mangement In High Producing Dairy Farms
The high value of milk protein, increasing feed costs, and growing concerns for the environment have made nitrogen (N) utilization a central component in balancing dairy cow rations. The objectives of this thesis were to evaluate field usable tools to predict N utilization and excretion and help develop protocols to improve N utilization on commercial farms. Specifically this included (1) an assessment of the daily variation in bulk tank milk urea nitrogen (MUN), (2) a computer-based evaluation of the Cornell Net Carbohydrate and Protein System's (CNCPS) ability to predict N excretion, and (3) a farm level evaluation of the ability of the updated CNCPS (v6.1) to develop rations with less environmental impact. In the first study, two data sets (Set A and Set B) containing daily bulk tank (BT) MUN concentrations from commercial farms were obtained from a local cooperative. Milk urea N values were analyzed by source (Set A and B) and by farm (n = 787 and 601 for Set A and B, respectively) across three months (Jan, Feb and March). Mean MUN values from Set A and B followed a normal distribution with the greatest proportion of farms (45% and 42%, respectively) falling within the 11-13 mg/dl range. The majority of variation in both data sets was explained by variability among farms. However, ~10% was attributed to the effect of month while ~20% was unexplained. The unexplained variation could be due to differences in sampling time or technique at the BT, number of milkings, total milk in the BT and/or laboratory error. Significant differences (P less than 0.05) were detected in mean MUN concentrations among months which may be due to seasonal effects. Farmers need to be aware of this variation in order for MUN to be used as an effective management tool. In the second study, CNCPS predictions of fecal N (FN), urinary N (UN), and total manure N (MN) were compared to observed data from published studies (n=32) that completed total collection N balance evaluations on lactating dairy cows. The results showed current CNCPS FN predictions could be improved by using the equation: FN (g/day) = (((NI (g/kg organic matter) x (1 - 0.842)) + 4.3) x organic matter intake (kg/day)) x 1.20. The CNCPS calculates UN as the difference between NI and the sum of FN, scurf N and productive N. Urinary N predictions were improved by incorporating the FN prediction described above into the current CNCPS framework and accounting for N balance biases within the model. The changes to FN and UN predictions translate into an improved prediction of total manure N (Mean square prediction error = 623, coefficient of determination = 0.96, concurrent correlation coefficient = 0.97) and have been incorporated into the latest version of the CNCPS (v6.1). In the final study, the CNCPS was used to adjust the diets of two commercial herds in western NY to improve N utilization and reduce feed costs while maintaining milk production. Crude protein was reduced by approximately 1% DM, MUN was decreased by approximately 2 mg/dl and income over feed cost was improved on both farms. In addition, thirteen herds that were producing 39.3 +/- 5.1 kg of milk/cow/day (mean +/- SD) on low CP diets (14.3-16.5 % DM) were characterized as examples of reachable N utilization targets. This study showed that high milk and milk protein yields can be achieved on diets supplying less than 16% CP and that N use efficiency in commercial herds can be as high as 38%. This study confirms the updated CNCPS can be successfully used to develop diets with enhance N use efficiency under the constraints of a modern commercial dairy farm.
dissertation or thesis