Methods for predicting the energy value of pet foods

Castríllo, C.; Hervera, M.; Baucells, M. D.

doi:10.1590/s1516-35982009001300001

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…The present study agrees with previous results where cats had a greater risk for weight gain when fed HF v. HC diets either ad libitum ( 5 , 19 ) or to energy requirements ( 4 , 6 ) . In addition, these results further support the hypothesis that using calculated values of ME systemically underestimates the true ME content of commercially available HF diets for cats ( 20 ) ; therefore, it is unclear as to whether the increase in BW and body fat with HF dietary feeding was driven by fat or energy intake or both. Furthermore, the trend in a reduction in LBM + BMC require further investigation as the mechanism for a loss in structural protein is surprising and may suggest that, compositionally, more protein as a function of energy content should be considered.…”

Section: Resultssupporting

confidence: 73%

Dietary fat and carbohydrate have different effects on body weight, energy expenditure, glucose homeostasis and behaviour in adult cats fed to energy requirement

et al. 2015

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The effects of dietary carbohydrate and fat on feline health are not well understood. The effects of feeding diets moderately high in fat (HF; n 10; 30 % fat, 26 % carbohydrate as fed) or carbohydrate (HC; n 10; 11 % fat, 47 % carbohydrate), for 84 d, were investigated in healthy, adult cats (3·5 (sd 0·5) years). Data on indirect calorimetry, blood biomarkers, activity, play and cognition were collected at baseline, and at intervals throughout the study. Body composition was measured by dual-energy X-ray absorptiometry at baseline and on day 85. There were no significant main effects of diet on body weight and composition. When data were analysed over study day within diet, cats fed HF diets experienced a significant increase in body fat (P = 0·001) and body weight (P = 0·043) in contrast to cats consuming the HC diet that experienced no change in body fat or body weight (P = 0·762) throughout the study. Overall, energy expenditure was similar between diets (P = 0·356 (fasted), P = 0·086 (postprandial)) and respiratory quotient declined with exposure to the HF diet and increased with exposure to the HC diet (P < 0·001; fasted and postprandial). There was no difference in insulin sensitivity as an overall effect of diet (P = 0·266). Activity declined from baseline with exposure to both diets (HC: P = 0·002; HF: P = 0·01) but was not different between diets (P = 0·247). There was no effect of diet on play (P = 0·387) and cats consuming either the HF or HC diet did not successfully learn the cognitive test. Overall, cats adapt to dietary macronutrient content, and the implications of feeding HC and HF diets on risk for adiposity as driven by metabolic and behavioural mechanisms are discussed.

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Section: Resultssupporting

confidence: 73%

Dietary fat and carbohydrate have different effects on body weight, energy expenditure, glucose homeostasis and behaviour in adult cats fed to energy requirement

et al. 2015

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“…Overall, the MA equation performed worst of all, 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. These results clarify and extend previous work assessing performance of predictive equations for ME content in dog and cat food [7,8,10,15], emphasising the superiority of the NRC 2006 tdf equations over all other methods [13].…”

Section: Discussionsupporting

confidence: 87%

“…In the current study, we have analysed data from 355 feeding studies in dogs and cats, which were performed according to AAFCO guidelines [3] over a period of 5 years. Our aim was to compare accuracy of various predictive equations for estimating ME [2,4–9,12,13,16]. Overall, the MA equation performed worst of all, 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.…”

Section: Discussionmentioning

confidence: 99%

“…As a result, this equation tends to underestimate energy content of highly-digestible foods whilst, at the same time, overestimating the energy content of foods of a lesser digestibility [11]. For this reason, others have recommended methods based on GE [6,7], fat (F) [6], crude protein (CP) [12], a method using near infrared reflectance spectroscopy [12] and the fibre content [9,13]. These latter studies prompted the NRC in 2006 to recommend equations that are based upon either crude fibre (CF) or total dietary fibre (TDF) [2,14], methods since adopted by FEDIAF, the European Pet Food Federation, in their guidelines [15].…”

Section: Introductionmentioning

confidence: 99%

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Metabolisable energy content in canine and feline foods is best predicted by the NRC2006 equation

Calvez¹,

Weber²,

Ecochard³

et al. 2019

PLoS ONE

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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 2006cf) and total dietary fibre (NRC 2006tdf), 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 2006cf and Hall equations were intermediate in performance, whilst the NRC 2006tdf 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 2006tdf equations and using measured rather than predicted GE.

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“…In dogs, the modified Atwater equation underestimated the ME value of low-ash poultry meal by 15% [ 36 ]. Furthermore, predicted ME values underestimated in vivo values of dog food with ME values above 3.6 kcal ME/g DM, which corresponds to most dry extruded pet foods currently on the market [ 37 , 38 , 39 ]. Conversely, the modified Atwater equation has accurately predicted ME value in some studies.…”

Section: Discussionmentioning

confidence: 99%

Digestibility Is Similar between Commercial Diets That Provide Ingredients with Different Perceived Glycemic Responses and the Inaccuracy of Using the Modified Atwater Calculation to Calculate Metabolizable Energy

Asaro

Guevara²,

Berendt

et al. 2017

Veterinary Sciences

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Dietary starch is required for a dry, extruded kibble; the most common diet type for domesticated felines in North America. However, the amount and source of dietary starch may affect digestibility and metabolism of other macronutrients. The objectives of this study were to evaluate the effects of 3 commercial cat diets on in vivo and in vitro energy and macronutrient digestibility, and to analyze the accuracy of the modified Atwater equation. Dietary treatments differed in their perceived glycemic response (PGR) based on ingredient composition and carbohydrate content (34.1, 29.5, and 23.6% nitrogen-free extract for High, Medium, and LowPGR, respectively). A replicated 3 × 3 Latin square design was used, with 3 diets and 3 periods. In vivo apparent protein, fat, and organic matter digestibility differed among diets, while apparent dry matter digestibility did not. Cats were able to efficiently digest and absorb macronutrients from all diets. Furthermore, the modified Atwater equation underestimated measured metabolizable energy by approximately 12%. Thus, the modified Atwater equation does not accurately determine the metabolizable energy of high quality feline diets. Further research should focus on understanding carbohydrate metabolism in cats, and establishing an equation that accurately predicts the metabolizable energy of feline diets.

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Methods for predicting the energy value of pet foods

Cited by 12 publications

References 28 publications

Dietary fat and carbohydrate have different effects on body weight, energy expenditure, glucose homeostasis and behaviour in adult cats fed to energy requirement

Dietary fat and carbohydrate have different effects on body weight, energy expenditure, glucose homeostasis and behaviour in adult cats fed to energy requirement

Metabolisable energy content in canine and feline foods is best predicted by the NRC2006 equation

Digestibility Is Similar between Commercial Diets That Provide Ingredients with Different Perceived Glycemic Responses and the Inaccuracy of Using the Modified Atwater Calculation to Calculate Metabolizable Energy

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