Open AccessMetabolisable energy content in canine and feline foods is best predicted by the NRC2006 equation
Author(s) -
Juliane Calvez,
M. Weber,
Claude Ecochard,
Louise Kleim,
John G. Flanagan,
Vincent Biourge,
Alexander J. German
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0223099
Subject(s) - pet food , zoology , energy density , medicine , mathematics , limits of agreement , regression analysis , statistics , food science , biology , nuclear medicine , physics , theoretical physics
Although animal trials are the most accurate approach to determine the metabolisable energy (ME) content of pet food, these are expensive and labour-intensive. Instead, various equations have been proposed to predict ME content, but no single method is universally recommended. Data from canine and feline feeding studies, conducted according to Association of American Feed Control Officials recommendations, over a 6-year period at a single research site, were utilised to determine the performance of different predictive equations. Predictive equations tested included the modified Atwater (MA equation), NRC 2006 equations using both crude fibre (NRC 2006 cf ) and total dietary fibre (NRC 2006 tdf ), and new equations reported in the most recent study assessing ME predictive equations (Hall equations; PLoS ONE 8(1): e54405). Where appropriate, equations were tested using both predicted gross energy (GE) and GE measured by bomb calorimetry. Associations between measured and predicted ME were compared with Deming regression, whilst agreement was assessed with Bland-Altman plots. 335 feeding trials were included, comprising 207 canine (182 dry food; 25 wet food) and 128 feline trials (104 dry food, 24 wet food). Predicted ME was positively associated with measured ME whatever the equation used ( P <0.001 for all). Agreement between predicted and actual ME was worst for the MA equation, for all food types, with evidence of both a systematic bias and proportional errors evident for all food types. The NRC 2006 cf and Hall equations were intermediate in performance, whilst the NRC 2006 tdf equations performed best especially when using measured rather than predicted GE, with the narrowest 95% limits of agreement, minimal bias and proportional error. In conclusion, when predicting ME content of pet food, veterinarians, nutritionists, pet food manufacturers and regulatory bodies are strongly advised to use the NRC 2006 tdf equations and using measured rather than predicted GE.