Review: Impact of protein and energy supply on the fate of amino acids from absorption to milk protein in dairy cows

Abstract

Making dairy farming more cost-effective and reducing nitrogen environmental pollution could be reached through a reduced input of dietary protein, provided productivity is not compromised. This could be achieved through balancing dairy rations for essential amino acids (EAA) rather than their aggregate, the metabolizable protein (MP). This review revisits the estimations of the major true protein secretions in dairy cows, milk protein yield (MPY), metabolic fecal protein (MFP), endogenous urinary loss and scurf and associated AA composition. The combined efficiency with which MP (EffMP) or EAA (EffAA) is used to support protein secretions is calculated as the sum of true protein secretions (MPY + MFP + scurf) divided by the net supply (adjusted to remove the endogenous urinary excretion: MPadj and AAadj). Using the proposed protein and AA secretions, EffMP and EffAA were predicted through meta-analyses (807 treatment means) and validated using an independent database (129 treatment means). The effects of MPadj or AAadj, plus digestible energy intake (DEI), days in milk (DIM) and parity (primiparous v. multiparous), were significant in all models. Models using (MPadj, MPadj × MPadj, DEI and DEI × DEI) or (MPadj/DEI and MPadj/DEI × MPadj/DEI) had similar corrected Akaike’s information criterion, but the model using MPadj/DEI performed better in the validation database. A model that also included this ratio was, therefore, used to fitting equations to predict EffAA. These equations predicted well EffAA in the validation database except for Arg which had a strong slope bias. Predictions of MPY from predicted EffMP based on MPadj/DEI, MPadj/DEI × MPadj/DEI, DIM and parity yielded a better fit than direct predictions of MPY based on MPadj, MPadj × MPadj, DEI, DIM and parity. Predictions of MPY based on each EffAA yielded fairly similar results among AA. It is proposed to ponder the mean of MPY predictions obtained from each EffAA by the lowest prediction to retain the potential limitation from AA with the shortest supply. Overall, the revisited estimations of endogenous urinary excretion and MFP, revised AA composition of protein secretions and inclusion of a variable combined EffAA (based on AAadj/DEI, AAadj/DEI × Aadj/DEI, DIM and parity) offer the potential to improve predictions of MPY, identify which AA are potentially in short supply and, therefore, improve the AA balance of dairy rations.

The market for amino acids: understanding supply and demand of substrate for more efficient milk protein synthesis

“…Previous lack of evidence regarding this coordination at cellular level resulted in nutrient requirement systems purely based on substrate supply. Including variable efficiencies for individual AA, as proposed by Lapierre and collaborators [14], shifts the approach from substratedefined to incorporating the known ability of the cow itself to alter AA efficiency. A blanket definition of "energy" that includes any source of calories regardless of its metabolic or endocrine signaling capacity is all that nutritionists currently have to work with.…”

“…Modern nutrient requirement systems have started to shift towards using diminishing efficiencies [11][12][13], meaning that the efficiency of utilization of AA for milk protein synthesis decreases in relationship with AA supply, either as absolute amount or as a ratio with energy supply. Lapierre and collaborators have proposed major changes to the NRC system [7], including variable efficiencies for individual essential AA [14]. This is a significant shift in the approach to predicting milk protein yield and reducing N losses because it recognizes the ability of the cow to adjust its own AA efficiency.…”

Rumen bacterial community, indicators of reproduction and milk productivity at different levels of protein concentrate in the diets of dairy cows

“…For cheese production, an important role belongs to the quality of milk in the production process, it must meet the GOST and safety requirements. Thus, one of the milk quality criteria is its suitability for further processing [1,11,13]. Similarly, the qualitative composition of milk is determined by genetic factors (type, breed, line) and at the same time depends on paratypical factors: age, lactation stage, type of feeding, season and climatic conditions [1,2,9,10].…”

“…The main producer of fishmeal on the world stage is Peru (631 thousand tons), Chile (214 thousand tons), and the leader in production is China and South Korea, where, respectively, 56% and 42% of the total production is concentrated. Recently, there has been a stagnation in the production of fish meal, which is the lowest level in the last 40 years [3,13,14].…”

“…Vegetable sources of protein (legumes, oil crop cakes and meal) are rich sources of lipids and energy, but they are significantly inferior to animal feed in terms of the content of non-cleavable protein [3,6,12,13,15].…”