ABSTRACT
Dairy cattle excreta are a valuable source of orthophosphate (Ortho-P), an inorganic form of phosphorus (P) that is readily available for microorganisms, plant growth, and development. There is, however, a growing environmental concern about the potential negative environmental impact of excessive amounts of Ortho-P excretion, which can lead to the eutrophication of water bodies. As a result, the development of mathematical equations to quantify and manage Ortho-P excretion on dairy farms could prove valuable for environmental sustainability. This study aimed to use literature data to develop empirical predictions for Ortho-P (g/kg dry matter [DM]) excretion using total P (TP [g/kg DM]) content of dairy cattle feces (Ortho-Pf) and manure (Ortho-Pm). Data sets from studies that evaluated and characterized the different forms of P in feces and manure from dairy cattle were compiled. After outlier exclusion, the final retained database for feces included 37 treatment means from 4 published papers while the manure comprised 23 treatment means from 7 published papers. A linear-mixed model was used to develop the predictive equations, incorporating the random effect of the study. A leave-one-out cross-validation procedure was used to evaluate the predictive ability of the developed models, whereby studies were regarded as folds. The fecal equation was determined as Ortho-Pf (g/kg DM) = -2.447 (0.572) + 0.966 (0.083) × TP (g/kg DM) (R2 = 0.79) and resulted in a root mean square prediction error as a percentage of mean observed value (RMSPE, %) of 32.8% and error due to random sources of 97.6%. Additionally, the manure equation was determined as Ortho-Pm (g/kg) = -0.204 (0.446) + 0.590 (0.065) × TP (g/kg) (R2 = 0.77) and had an RMSPE of 43.3% with a random error of 93.9%. Both models revealed minimal mean and slope biases on feces and manure data. Findings suggest that these sets of equations can be used to estimate excreted Ortho-P from total excreted P, helping nutritionists and farmers to understand the impact of dietary P changes on the environment. Further, these equations can be incorporated into extant models such as the Cornell Net Carbohydrate and Protein System (CNCPS) to aid in understanding and mitigating P and Ortho-P excretion from dairy cattle and to clarify the portion of P that migrates more rapidly into watersheds.
ABSTRACT
Current analytical methods for amino acid (AA) analysis in ruminant nutrition are time-consuming and expensive. This study aimed to develop a method for AA analysis that is faster, more efficient, rugged, and accessible. Four representative matrixes were selected for method development and validation: milk, tissue, feed, and soy flour standard reference material from National Institute of Standards and Technology. Acid and alkaline hydrolysis were used to analyze 18 AA. Separation of AA was performed using a Z-HILIC column in an 18-min run coupled to a triple quadrupole LC/MS system in positive and negative electrospray ionization for identification and quantitation. The method was evaluated for recovery, precision, calibration curve linearity, and limits of detection (LODs) and limits of quantitation (LOQs) and applied to other feed samples. Good quantitation results were achieved for all AA, with coefficients of determination (R2) over 0.995; LODs at 0.2-28.2 and LOQs at 0.7-94.1 ng/mL; intraday and interday precision <14.9% relative standard deviation; blank recovery between 75.6 and 116.2%; and sample recovery between 75.6 and 118.0%. Overall, AA concentrations were similar to literature values, and there was a tendency for higher N recovery as AA. In conclusion, an efficient and robust method was validated to routinely analyze AA for appropriate characterization in diet formulation for dairy cattle.
