Variation in nutrients formulated and nutrients supplied on 5 California dairies

Abstract

Computer models used in ration formulation assume that nutrients supplied by a ration formulation are the same as the nutrients presented in front of the cow in the final ration. Deviations in nutrients due to feed management effects such as dry matter changes (i.e., rain), loading, mixing, and delivery errors are assumed to not affect delivery of nutrients to the cow and her resulting milk production. To estimate how feed management affects nutrients supplied to the cow and milk production, and determine if nutrients can serve as indexes of feed management practices, weekly total mixed ration samples were collected and analyzed for 4 pens (close-up cows, fresh cows, high-milk-producing, and low-milk-producing cows, if available) for 7 to 12 wk on 5 commercial California dairies. Differences among nutrient analyses from these samples and nutrients from the formulated rations were analyzed by PROC MIXED of SAS (SAS Institute Inc., Cary, NC). Milk fat and milk protein percentages did not vary as much [coefficient of variation (CV) = 18 to 33%] as milk yield (kg; CV = 16 to 47 %) across all dairies and pens. Variability in nutrients delivered were highest for macronutrient fat (CV = 22%), lignin (CV = 15%), and ash (CV = 11%) percentages and micronutrients Fe (mg/kg; CV = 48%), Na (%; CV = 42%), and Zn (mg/kg; CV = 38%) for the milking pens across all dairies. Partitioning of the variability in random effects of nutrients delivered and intraclass correlation coefficients showed that variability in lignin percentage of TMR had the highest correlation with variability in milk yield and milk fat percentage, followed by fat and crude protein percentages. But, variability in ash, fat, and lignin percentages of total mixed ration had the highest correlation with variability in milk protein percentage. Therefore, lignin, fat, and ash may be the best indices of feed management to include effects of variability in nutrients on variability in milk yield, milk fat, and milk protein percentages in ration formulation models.

Deviation from the formulated target weight of ingredients loaded into high milk yield cow recipes on California dairies

“…It has been reported that dayto-day variability in nutrient composition was not as large as the variability observed between the fed and formulated recipe (Sova et al, 2014). The observed variability in TMR nutrient composition might have implications in regard to milk yield (Rossow and Aly, 2013;Sova et al, 2014). Due to these uncertainties associated with the feeding process, nutrition consultants often times add a safety margin by formulating rations that exceed requirements for critical nutrients such as CP.…”

Greenhouse gas, water, and land footprint per unit of production of the California dairy industry over 50 years

“…Two scenarios were considered for data collection. Model 1 was based on primary data from 5 commercial dairies located in Tulare and Kings Counties, California (Rossow and Aly, 2013), and these were used to determine the average milk production and composition for this model. The average milk production representing 2014 model 1 levels was 39.8 kg/d, with milk fat and protein percentages of 4 and 3.3%, respectively.…”

“…Two different diets with respective milk production were considered for 2014 using IPCC assessment report 5 characterization factors (AR5; IPCC, 2014). Model 1 was based on highproducing cows in Rossow and Aly (2013), whereas model 2 was the average cow based on CDFA cost of milk production reports from 2013 to 2015.…”

“…California representative diets were collected from published data for 1964 and 2014 (NRC, 1958;Mead and Ronning 1961;Palmquist et al, 1964;Hutton and Bath, 1967a,b;Rauch et al, 2012Rauch et al, , 2014Rossow and Aly 2013;Swanepoel et al, 2014;Havlin et al, 2015;CDFA, 2014). In 1964, separate diets were used for calves, heifers, pregnant heifers, close-up heifers, and lactating and dry cows (Table 1).…”

Liver mitochondrial oxygen consumption and efficiency of milk production in lactating Holstein cows supplemented with copper, manganese and zinc

“…Faecal, diet and diet refusal samples used in the determination of DMI were collected over the last 4 days of the 28‐days dosing period. Diet samples were collected once daily and subsampled from three tubs set along the feed bunk during feed delivery (Rossow & Aly, ). Refusal samples were collected once daily before the a.m. feeding, and average diet sample compositions were corrected with average residual compositions.…”