Back to basics: Precision while mixing total mixed rations and its impact on milking performance

Abstract

Abstract:: Details from every mixing load of total mixed ration (TMR) fed to ∼19,000 cows distributed in 92 pens from 21 farms, along with individual milk yield of each cow in every pen and farm, were collected from a feeding and management system (algoMilk; www.algomilk.com) between 2020 and 2022 on a daily basis to assess the impact of quality of mixing TMR on animal performance. Divergence between expected and actual amounts of ingredients mixed in every load was calculated and expressed as a percentage relative to expected amounts. Ingredients were classified as (1) energy grains (i.e., corn, wheat), (2) protein sources (i.e., soybean meal, canola meal), (3) hays (i.e., alfalfa hay), (4) grain silages (i.e., corn silage), (5) nongrain silages (i.e., alfalfa silage), (6) minerals (i.e., salt, sodium bicarbonate), and (7) straw (i.e., wheat straw). Milk yield was averaged within farm and pen on a weekly basis, and mixing divergences were also averaged by load or by ingredient type and week within pen and farm. The weekly standard deviation (SD) of mixing divergences was calculated for every pen and farm. The average divergence of the total amount of TMR prepared was 1.52 ± 0.017% (mean ± SD), which means that, in general, mixing errors were caused by adding an excess of one or more ingredients. Energy grains (1.20 ± 0.037%), grain silages (1.78 ± 0.023%), hays (2.29 ± 0.044%), and protein sources (1.82 ± 0.043%) were mixed in excessive amounts (mean ± SD), whereas nongrain silages (−1.5 ± 0.037%), molasses (−3.05 ± 0.067%), minerals (96.9 ± 0.084%), and straw (−0.6 ± 0.063%) were mixed (mean ± SD) in lower amounts than expected. Divergence in the total amount of TMR was weakly quadratically (concave) correlated (R2 = 0.04) with milk yield. Similarly, divergence in the amounts of grains, protein sources, hay, silages, minerals, and molasses mixed in the TMR wagon in relation to the formulated ration was also weakly and quadratically (concave) with milk yield. Minimizing mixing errors may have positive effects on milking performance.