Predicting nitrogen excretion from cattle

Abstract

Manure nitrogen (N) from cattle production facilities can lead to negative environmental effects, such as contribution to greenhouse gas emissions, leaching and runoff to aqueous ecosystems leading to eutrophication, and acid rain. To mitigate these effects and to improve the efficiency of N use, accurate prediction of N excretion and secretions are required. A genetic algorithm was implemented to select models to predict fecal, urinary, and total manure N excretions, and milk N secretions from 3 classes of animals: lactating dairy cows, heifers and dry cows, and steers. Two tiers of model classes were developed for each category of animals based on model input requirements. A total of 6 models for heifers and dry cows and steers and an additional 2 models for lactating dairy cattle were developed. Evaluation of the models using K-fold cross validation based on all data and using the most recent 6 yr of data showed better prediction for total manure N and fecal N compared with urinary N excretion, which was the most variable response in the database. Compared with extant models from the literature, the models developed in this study resulted in a significant improvement in prediction error for fecal and urinary N excretions from lactating cows. For total manure production by lactating cows, extant and new models were comparable in their prediction ability. Both proposed and extant models performed better than the prediction methods used by the US Environmental Protection Agency for the national inventory of greenhouse gases. Therefore, the proposed models are recommended for use in estimation of manure N from various classes of animals.

Short communication: Evaluation of nitrogen excretion equations from cattle

“…The equations developed by Reed et al (2015b) for lactating cows resulted in less prediction error and bias compared with other extant equations evaluated here. The equation development procedure implemented by Reed et al (2015b) differs from other studies in size and quality of the data used for equation development and the rigorous equation-selection process implemented.…”

“…Data collection was limited to studies published between 1994 and 2015 to ensure current data were used for evaluation. Data were collected for 3 animal classes, lactating cows, heifers and nonlactating cows, and steers, to be able to evaluate equations for the 3 animal classes reported by Reed et al (2015b). The majority of articles collected did not report the ME content of the feed, which is a predictor in several of the equations being evaluated.…”

“…Fecal (FN) and urinary N (UN) excretions have different effects on the environment, so equations predicting UN and FN separately improve estimation of N partitioning to air and soil. Several equations have been developed to estimate FN and UN excretion separately and have been reported to improve the accuracy of estimation (Reed et al, 2015b). Most extant equations predicting N excretion from cattle were developed from a small pool of potential covariates and selected based on either biological knowledge or a stepwise selection method, both of which are subject to criticism.…”

“…However, when the number of possible covariates is large, equation selection can be a time-and computation-intensive process. The genetic algorithm used by Reed et al (2015b) facilitated the selection process and reduced the time required to identify the best possible equation based on a given criteria. Although the equations developed by Reed et al (2015b) performed well in internal evaluation, the most recent observation in the data used for equation development and evaluation was collected in 1994, so the prediction accuracy of the equations for modern cows is uncertain.…”

“…The genetic algorithm used by Reed et al (2015b) facilitated the selection process and reduced the time required to identify the best possible equation based on a given criteria. Although the equations developed by Reed et al (2015b) performed well in internal evaluation, the most recent observation in the data used for equation development and evaluation was collected in 1994, so the prediction accuracy of the equations for modern cows is uncertain. Thus, the objective of this study was to evaluate the accuracy and precision of existing N excretion prediction equations for 3 animal classes and 3 forms of N excretion using N balance data collected from recently published studies.…”