UNIVERSIDADE ESTADUAL PAULISTA - UNESP 

CÂMPUS DE JABOTICABAL 

 

 

 

 

 

 

 

 

NET ENERGY FOR MAINTENANCE IN POULTRY 

 

 

 

 

 

 

Freddy Alexander Horna Morillo 

Zootecnista 

 

 

 

 

 

 

 

 

 

2022 



 

UNIVERSIDADE ESTADUAL PAULISTA 

CÂMPUS DE JABOTICABAL 

 

 

 

 

 

NET ENERGY FOR MAINTENANCE IN POULTRY 

 

 

 

 

 

Mg. Sc. Freddy Alexander Horna Morillo 

 Orientadora: Profª. Drª. Nilva Kazue Sakomura  

Coorientador: Prof. Dr. Marcos Macari  

 

 

Tese de Doutorado apresentada à Faculdade de 
Ciências Agrárias e Veterinárias Unesp, Câmpus 
de Jaboticabal, como parte das exigências para a 
obtenção do título de Doutor em Zootecnia. 

 

 

2022 

  



 

FICHA CATALOGRÁFICA 

 

 

 

 

 

 

 

 

 

 

  



 

 

 

 

 



 

DADOS CURRICULARES DO AUTOR 

FREDDY ALEXANDER HORNA MORILLO, nascido no dia 21 de abril de 1989 

em Nuevo Chimbote, Ancash, Peru. Ingressou no curso de Zootecnia na Universidad 

Nacional Agraria de La Molina em março de 2006. Em novembro de 2011 obteve o 

título de Zootecnista. Ingressou no Programa de Mestrado na Universidad Nacional 

Agraria de La Molina em abril de 2012. Em novembro de 2017 obteve o título de Mestre 

em Nutrição. Trabalhou 2 anos em uma integradora avícola no Peru e em agosto de 

2018 ingressou no Doutorado do Programa de Pós-Graduação em Zootecnia da 

Universidade Estadual Paulista – “Júlio de Mesquita Filho” (UNESP) – Faculdade de 

Ciências Agrárias e Veterinárias, Campus de Jaboticabal, sob orientação da Profª. Drª. 

Nilva Kazue Sakomura, submetendo-se à defesa da tese em outubro de 2022.  

  



 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Dedico 

Ao meu pai Miguel e a minha mãe Maria, pela força e compreensão desde o 

início dessa caminhada e por sempre acreditarem em mim. Às minhas irmãs 

Karina e Luz Maria pelo amor e carinho. À Andrea pelo amor e por estar 

sempre ao meu lado me apoiando. 

  



 

AGRADECIMENTOS 

A vida académica inclui inúmeros desafios e incertezas. Trilhar esse caminho só foi 

possível com o apoio, energia e força de algumas pessoas, a quem agradeço do fundo 

do meu coração: 

Aos meus pais Miguel e Maria, pois mesmo nos momentos mais difíceis estão 

sempre presentes oferecendo seu amor e carinho. Às minhas irmãs Karina e Luz Maria 

pela amizade, apreço e companheirismo. 

À Andrea, pois apesar da distância, cada passo neste caminho foi ao seu lado. 

Ao meu mentor, Professor Doutor Víctor Guevara Carrasco, pela amizade e pelos 

ensinamentos que me foram e serão úteis no meu desenvolvimento profissional e 

pessoal. 

Aos amigos que fiz durante essa caminhada: Thaila, Gabriela, Torcido, Palloma, 

Guilherme, Dami, Bárbara, Larissa, e Matheus que espero levar para a vida toda. 

Aos ex-moradores da república Myzheria, especialmente ao baby, pois mesmo 

longe de casa, consegui encontrar uma segunda família. 

À Professora Doutora Nilva Kazue Sakomura, pela orientação pautada por um 

elevado e rigoroso nível científico, os quais contribuíram para enriquecer, com grande 

dedicação, todas as etapas subjacentes ao trabalho realizado. 

Ao meu coorientador, Professor Marcos Macari pela ajuda, compreensão e 

ensinamentos. A sua contribuição foi essencial nessa caminhada. 

Ao Jaap Van Milgen, pelas críticas construtivas que contribuíram para o 

aperfeiçoamento desse trabalho. 



 

À professora Doutora Kênia Cardoso, Flávio Bello da Embrapa e Barbara Joss da 

Sable System, pelo suporte científico. 

Aos membros da banca de qualificação e defesa. 

Aos meus amigos latinos que fiz durante esse período. 

Aos colegas do aviário que participaram incondicionalmente e contribuíram 

positivamente na realização dos experimentos e elaboração dos artigos científicos que 

compõem a tese. Muito obrigado pela inestimável ajuda. 

A Faculdade de Ciências Agrárias e Veterinárias, pela estrutura e acolhimento, 

sendo minha segunda casa nos quatro anos. 

O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento 

de Pessoal de Nível Superior - Brasil (CAPES) – 88887.338773/2019-00 

 



i 

TABLE OF CONTENTS 

Page 
 

Chapter 1 – CONSIDERAÇÕES GERAIS ........................................................................ 1 

1.1. Introduction ......................................................................................................... 1 

1.2. Energy metabolism.............................................................................................. 3 

1.3. Energy for maintenance ...................................................................................... 6 

1.3.1. Metabolizable energy for maintenance ............................................................ 6 

1.3.2. Net energy for maintenance ............................................................................. 7 

1.3.3. The fasting metabolism .................................................................................... 8 

1.4. Energy for physical activity ................................................................................ 10 

1.4.1. Physical activity .............................................................................................. 10 

1.4.2. Methodologies to assess the physical activity ................................................ 10 

1.5. Calorimetry technique ....................................................................................... 11 

1.5.1. Indirect calorimetry ......................................................................................... 11 

1.6. References ........................................................................................................ 14 

Chapter 2 – Fasting heat production as affected by body weight and environmental 
temperature in group-housed pullets and laying hens .................................................... 19 

ABSTRACT ............................................................................................................. 21 

Introduction ............................................................................................................. 23 

Materials and methods ............................................................................................ 24 

Results .................................................................................................................... 28 

Discussion ............................................................................................................... 29 

Conclusion .............................................................................................................. 33 

References .............................................................................................................. 34 

Chapter 3 – Energy requirements for maintenance as a function of body weight and 
critical temperature in broiler chickens ........................................................................... 49 

ABSTRACT ............................................................................................................. 51 

1. Introduction .................................................................................................... 53 

2. Materials and methods ................................................................................... 54 

3. Results ........................................................................................................... 58 

4. Discussion ...................................................................................................... 59 

5. Conclusion ..................................................................................................... 64 



ii 

REFERENCES ........................................................................................................ 65 

Chapter 4 – Feather covering and environmental temperature affects energy for 
maintenance in broiler chickens ..................................................................................... 83 

Abstract ................................................................................................................... 85 

Implications ............................................................................................................. 87 

Introduction ............................................................................................................. 88 

Material and methods .............................................................................................. 90 

Results .................................................................................................................... 94 

Discussion ............................................................................................................... 95 

References ............................................................................................................ 100 

Chapter 5 – Energy cost of physical activities in growing broilers ................................ 110 

Abstract ................................................................................................................. 112 

INTRODUCTION ................................................................................................... 113 

MATERIALS AND METHODS .............................................................................. 115 

RESULTS .............................................................................................................. 120 

DISCUSSION ........................................................................................................ 122 

ACKNOWLEDGMENTS ........................................................................................ 125 

REFERENCES ...................................................................................................... 126 

Chapter 6 – Implications ............................................................................................... 140 

 

  



iii 

 

  



iv 

NET ENERGY FOR MAINTENANCE IN POULTRY 

 

 

RESUMO 

O sistema energia líquida (EL) tem sido bem sucedido na nutrição de suínos e bovinos; 
no entanto, a nutrição avícola apresentou dificuldades na adoção do EL. Para o 
sucesso do sistema EL em aves, é necessário quantificar a energia necessária por ave 
e os valores energéticos dos alimentos no sistema EL. Com base na abordagem 
fatorial, a necessidade de energia EL pode ser dividida em energia para mantença 
(produção de calor em jejum, FHP) e produção (energia retida no corpo ou ovo). 
Fatores internos e externos são comumente considerados como um aumento na 
necessidade de energia de manutenção. Além disso, tem sido sugerido que a taxa 

metabólica se ajusta com a lei dos ¾ segundo a função potência (𝑦 = 𝑎 ∗ 𝑥𝑏), porém, 
nas últimas décadas, a universalidade deste expoente tem sido enfraquecida e a 
relevância deste escalar para algumas espécies de aves deve ser testado. Além disso, 
existem muitas discrepâncias no ajuste da quantidade de energia usada para atividade 
física (AF). Devido à AF abranger comportamentos múltiplos e complexos, este estudo 
utiliza a metodologia do time-energy budget como uma tentativa de quantificar a energia 
necessária para a AF. Portanto, os objetivos deste estudo são: (1) determinar um 
escalar alométrico adequado para frangas e galinhas poedeiras bem como quantificar o 
efeito da T no FHP, (2) determinar como o peso corporal e a temperatura ambiente 
afetam o FHP em frangos de corte, (3) Explorar o efeito do grau de empenamento (F) e 
T sobre FHP, e (4) Determinar o custo energético de AF para alguns tipos de atividade 
física. Câmaras calorimétricas foram utilizadas para realizar esses experimentos e, com 
base nas trocas gasosas e na equação de Brouwer, foi calculado o calor produzido 
durante o jejum. Os resultados desses experimentos são os seguintes: (1) O escalar 
mais adequado para galinhas poedeiras foi 0,67 enquanto 89 foi a energia necessária 
para mantença (kcal/kg0,67) e a equação descreve a relação entre T e FHP é definida 
por: 0,247*T2-11,9*T+220. (2): FHPkcal/ave = BW0,75*[85 + 2,65*(CT-T)*(T<CT) + 4,41*(T-
CT)*(T≥CT)]; onde CT=22,46+(35,83-22,46)*e-0,4906*BW, BW é o peso corporal (kg) e T é 
a Temperatura (°C). (3) A relação entre FHP, F e T foi descrita da seguinte forma: FHP 
= 100,7 + U*[CT-T]*[T<CT] + V*[T-CT]*[T≥CT], em que, CT = 30,48+1,06*F, U=6,94-
6,44*F e V=2,06+4,21*F. O custo energético para comer, beber e movimentação foi 
calculado como 0,607, 0,352 e 0,938 cal.kg-0,75.s-1, respectivamente. 

Palavras-chave: Produção de calor em jejum, temperatura ambiental, atividade física, 
empenamento, calorimetria indireta. 

  



v 

NET ENERGY FOR MAINTENANCE IN POULTRY 

 

ABSTRACT 

The NE system has been fully implemented in swine and cattle nutrition; despite that, 
the poultry industry has been slower to adopt the NE. For the successful implementation 
of NE system, it is necessary to quantify the energy required per bird and the energy 
values of feedstuffs in the same system. Based on the factorial approach, the NE energy 
requirement can be divided into energy for maintenance (Fasting heat production, FHP) 
and production (retained energy in body or egg). Internal and external factors are 
commonly considered to result in an increase in the maintenance energy requirement. 
Moreover, it has been suggested that the metabolic rate scales with ¾ law according to 

the power function (𝑦 = 𝑎 ∗ 𝑥𝑏), however, in the last decades, the universality of this 
exponent has been weakened and the relevance of this scalar for some poultry species 
needs to be tested. Also, there are many discrepancies in the adjustment of energy 
used for physical activity (PA). Due to PA covering multiple and complex behaviors, this 
study uses the time-energy budget approach as an attempt to quantify the energy 
required for PA. Therefore, the objectives of this study are: (1) to determine an 
appropriate allometric scalar for pullets ad laying hens, and, also, to quantify the effect 
of T on FHP, (2) To determine how body weight and environmental temperature affect 
the FHP in broilers, (3) Explore the effect of feathering degree (F) and T over FHP, and 
(4) Determine the energy cost of PA for further adjustment of total energy expenditure 
PA. Calorimetry chambers were used to perform these experiments, and, based on gas 
exchange and the Brouwer equation, the heat produced during fasting status was 
calculated. The results of these experiments are as follows: (1) The most appropriate 
scalar for laying hens was 0.67 and 89 was the energy required for maintenance 
(kcal/kg0.67), also, the following equation describes the relationship between T and FHP: 
above CT is described by: 0.247*T2-11.9*T+220. (2) FHPkcal/bird = BW0.75*[85 + 2.65*(CT-
T)*(T<CT) + 4.41*(T-CT)*(T≥CT)]; where CT=22.46+(35.83-22.46)*e-0.4906*BW, BW is 
body weight (kg) and T is Temperature (°C). (3) The relationship between FHP, F, and T 
were described as follows: FHP = 100.7 + U*[CT-T]*[T<CT] + V*[T-CT]*[T≥CT], in which, 
CT = 30.48+1.06*F, U=6.94-6.44*F, and V=2.06+4.21*F. The energy cost for eating, 
drinking, and motion was calculated as 0.607, 0.352, and 0.938 cal.kg-0.75.s-1, 
respectively. 
 
Keywords: Fasting heat production, temperature, physical activity, feathering, indirect 
calorimetry.



1 

Chapter 1 – CONSIDERAÇÕES GERAIS  

 

1.1. Introduction 

The primary goal of poultry nutritionists is to formulate diets to supply energy and 

nutrients that meet the objective of production. In this regard, given that birds eat 

primarily to meet their energy requirements mainly, it is necessary to first implement an 

energy system that allows a better understanding of energy partitioning; secondly, 

define energy requirements under the energy system implemented; and, thirdly, be 

aware of the energy value of the feedstuffs. This knowledge will allow the formulation of 

efficient and economic diets. The metabolizable energy (ME) system has been widely 

used as it is a simple method to assess both energy requirements and energy value for 

feedstuffs; however, it has been suggested that the net energy (NE) system is more 

reliable due to the differences in metabolic utilization between nutrients, so this 

characteristic avoids under or overestimation of energy values for poultry diets. 

In contrast to the ME system, the NE system has been fully implemented in swine 

and cattle nutrition, despite that, the poultry industry has been slower to adopt the NE. 

This is plausible because, in the ME system, there is a high amount of information about 

the energy requirements and the energy values of feedstuffs. Under the ME system, the 

energy requirements of birds were well defined based on corn-soybean diets, so these 

energy requirements are appropriate for birds fed corn-soybean diets. However, a future 

change to non-conventional feedstuffs could result in a different response because the 

metabolic utilization may be different due to variations in the chemical composition of 

feedstuffs. Due to the NE system considering differences in metabolic utilization of 

nutrients, an expression of energy requirements and feed energy values based on the 

NE system should be independent of feed composition. Thus, for future implementation 

of the NE system, it is necessary to define the energy values of feedstuffs and bird 

energy requirements; however, published data on this subject is limited or scarce. The 

present research will therefore focus on studying the energy requirements of birds under 

the NE system. 



2 

Traditionally, energy and nutrient requirements have been determined using a 

dose-response approach, in which the energy or nutrient under analysis is related to the 

response criteria using regression analyses. On the other hand, the factorial approach is 

been used to study how animals use the energy and nutrients from feed for vital 

processes, so that, based on the additive assumption, the energy and nutrient are 

divided into maintenance and production, thus the energy and nutrient requirements are 

obtained by combining them. The factorial approach is widely used in mathematical 

modeling to predict energy and nutrient requirements, body composition, and growth 

under multiple conditions. Due to these characteristics, the factorial approach allows 

nutritional corrections to animals subjected to environments with constant changes. 

Based on this approach, it has been demonstrated that environmental factors have no 

effects on the efficiency of energy used for production; consequently, it is common 

practice to conduct studies on factors that influence maintenance in order to make 

further adjustments to maintenance requirements. Moreover, under the NE system, the 

estimation of maintenance is a crucial point to estimate the NE values of feedstuffs. 

In the absence of feed, the vital functions of the animal can be supported at the 

expense of the body reserves, so, fasting animals in resting status allows for quantifying 

the energy to maintain the vital processes, eliminating the thermal effect produced by 

the digestion and absorption processes or by requirements for growth. In the present 

study, birds subjected to fasting conditions were used to quantify the NE for 

maintenance and the factors affecting it. Moreover, as birds age, their body size 

increases; however, the metabolic rate does not increase at the same proportional rate. 

As a result, the metabolic rate, between and within animal species, scales with the 

power function (𝑦 = 𝑎 ∗ 𝑥𝑏) had been suggested. The 3/4 exponent has been proposed 

as a universal scaling; however, in the last decades, the universality of this exponent 

has been weakened. Therefore, this study aims to propose the most appropriate 

allometric scale for laying hens. 

There are some challenges to including the energy used for physical activity for 

further calculation of the energy required per day. This is probably a consequence of the 

lack of a robust definition of what maintenance means. Most mathematical modelers 



3 

consider the energy required for physical activity as a fixed portion of maintenance while 

others do not consider it in their calculations; however, considering the arbitrary time 

frame of physical activity, it is difficult to define how to insert this energy under the 

factorial approach. Due to physical activity covering multiple and complex behaviors, this 

study uses the time-energy budget approach as an attempt to quantify the energy 

required for physical activity. Finally, to perform these studies, indirect calorimetry was 

used to measure the heat production from oxygen consumption and carbon dioxide 

production. This technique allows for measuring the oxidation of carbohydrates, 

proteins, and fats, which releases the energy to fuel metabolic processes. 

 

1.2. Energy metabolism 

In the metabolism of living animals, the oxidation of macromolecules releases the 

energy stored in the chemical bonds, then this chemical energy is transferred to the 

bonds between phosphate groups of the adenosine triphosphate (ATP), so the energy 

stored in ATP molecules is further used for many purposes, viz., active transport of ions, 

synthesis of macromolecules, mechanical work in muscle contraction, etc (Haynie, 

2001). The energy from foods is released in two main stages. The first stage is related to 

digestion processes, in which macromolecules like protein and carbohydrates are 

broken down into smaller units, while fats are hydrolyzed to glycerol and fatty acid for 

further absorption by the intestinal cells, then these smaller units are degraded to 

simpler units (glucose, glycerol, amino acids, free fatty acids) for further metabolic 

processes (McDonald et al., 2011). In the second step, these molecules can be used to 

produce ATP in the major pathways to produce energy. Glucose is predominantly 

oxidized via glycolysis, free fatty acids via β-oxidation, and proteins via deamination 

(Swanson et al., 2010). 

NRC (1994) stated that “energy is not a nutrient but a property of energy; yielding 

nutrients when they are oxidized during metabolism”. Poultry diets consist of a mixture of 

feedstuffs such as cereal grains, vegetable and animal proteins, oil and fats, and vitamin 

and mineral premixes. This mixture provides nutrients required for essential vital 

processes such as growth or reproduction; however, due to the limitation in digestion 



4 

processes, it is not possible to use the total energy stored in feedstuffs. This energy is 

termed “gross energy”, and, it can be simply defined as the total chemical energy 

measured from the complete combustion of the food in a bomb calorimeter (Hall et al., 

2013). Nevertheless, depending on the peculiarities of the digestive system in animals, 

the energy value of a feed can be expressed in several ways. “Digestible energy” refers 

to the quantity of gross energy intake minus energy lost in feces. Metabolizable energy 

(ME) refers to digestible energy minus energy lost in the urine and that lost in gases. 

The energy loss in gases is usually neglected in poultry experiments. As a result, the 

protein is not catabolized and excreted, whereas, in adult animals, a portion of the 

protein tissues is oxidized and excreted. Based on this, the ME value is often corrected 

for zero nitrogen retention (Sibbald, 1982). 

Following feed intake, there is an increase in heat production (HP) due to 

mastication, digestion, absorption, and metabolism of feed. This increase in HP is 

named heat increment (HI), and terms like “calorigenic effect” and “specific dynamic 

action” are also commonly used (Smith et al., 1978). The subtraction of the HI from the 

ME value gives the NE of a diet. The NE value is the amount of energy that is available 

for useful purposes such as body maintenance and growth and product formation. It 

should be clear that the NE for maintenance will leave the animal as heat, while that 

used for growth is stored in the body, and this is referred to as energy retention (ER). 

Figure 1 illustrates a general overview of energy partitioning. 



5 

 

Figure 1. Partition of ingested energy (Sibbald, 1982) 

 

The energy balance can be simply defined as the difference between energy 

intake and energy expenditure. Thus, a non-zero energy balance (positive energy 

balance) must implicate an equal change in the energy content of the body in the form of 

Ingested energy 

Apparent 

digestible energy 

Apparent 

metabolizable 

energy 

Fecal energy 

Fecal 

energy 

of feed 

Metabolic 

fecal 

energy 

Gaseous energy 

Urinary energy 

Endogenous 

urinary 

energy 

Urinary 

energy 

of feed 

True Metabolizable 

energy 

Heat of fermentation 
Heat of digestion and 

absorption 

Heat of product 

formation 

Heat of waste formation 

and excretion 

Heat Increment 

fermentation 

Net energy for maintenance 

Basal metabolism 

Heat of activity 

Heat of thermal regulation 

Metabolic fecal energy 

Endogenous urinary energy 

Tissue growth 

Fat accretion 

Carbohydrate storage 

Eggs 

Semen 

Net energy for production 



6 

changes in the weight of some body constituent; however, there is a persistent deviation 

from energy equilibrium. Many factors can affect this equilibrium such as metabolic 

adaptation or adaptative thermogenesis, variation in feed intake and/or amount of feed 

as well as variations in body mass (Lam and Ravussin, 2016). Based on energy 

balance, the evaluation of efficiencies of animal growth is based on the partition of the 

energy for maintenance and production; then, it should be clear that the separation of 

metabolism into maintenance and production is superficial. However, this energy 

partitioning has been convenient and useful to study the whole animal metabolism 

allowing the development of recommendations for feeding standards for practical 

purposes (Koong et al., 1985). 

 

1.3. Energy for maintenance 

The energy required for maintenance can be expressed both in the ME and NE 

system. Based on energy partitioning, the estimation of energy for maintenance is very 

important for the NE system because it will influence the NE value of feedstuffs. For both 

systems, the choice of methodologies and experimental conditions can affect these 

energy values. 

 

1.3.1. Metabolizable energy for maintenance 

Traditionally, maintenance has been defined as the amount of energy or sufficient 

feed to maintain the essential processes of life when doing no work and yielding no 

material product (Armsby, 1917). In the ME system, some definitions were proposed 

according to physiological state; typically, this value is named ME for maintenance 

(MEm). For adult and non-productive animals, maintenance could be defined as the 

amount of energy required to balance anabolism and catabolism, which comprises the 

energy retention of around zero (Chwalibog, 1991); nevertheless, this concept does not 

include the variation in body composition (fat and protein), i.e. it is probably that a 

reduction in one of the components occurs while the other increase its deposition rate. 

As a result, in total, the energy retention could be equal to zero. Chwalibog (1985) has 



7 

suggested another definition of MEm for growing or producing animals: “the amount of 

energy to maintain a dynamic equilibrium of protein and fat turnover, to maintain a 

constant body temperature, and to maintain a “normal” level of locomotor activity”, so, 

this modification implies that the energy balance in each component equals to zero. 

The values of MEm can be estimated from experiments with animals feeding with 

different feed intakes with greater variations in energy intake and retained energy. This 

approach assumes that there is a linear relationship between energy intake and energy 

retention, and, also, the energetic efficiencies are constant between feeding levels. 

Based on this, regression analyses can be performed to find the feeding level or energy 

intake does not produce variations in body size regardless; also, assuming a constant 

energy efficiency for fat (kf) and protein (kp), a multiple linear regression model can be 

performed to obtain the EMm, kf, and kp as suggested by kielanoswki (1965): 

𝐸𝑀𝑖 = 𝐸𝑀𝑚 + 𝑅𝐸𝑝/𝑘𝑝 ∗ +𝑅𝐸𝑓/𝑘𝑓 

Where Emi is the metabolizable energy intake, EMm is metabolizable energy for 

maintenance, ERp and ERf are the retained energy as protein and fat, respectively, kp 

and kf are the efficiencies for protein and fat deposition, respectively. 

According to Chwalibog (1991), this regression equation of ME in relation to 

protein and fat requires that the ratio between protein and fat retention is not constant; 

also, the estimate of MEm over a longer period of growth will provide a MEm being 

probably underestimated for younger animals and overestimated for older animals. 

Moreover, the multiple regression assumes that EMm, kp, and kf are independent 

variables; however, the energy output in bird (REp and REf) depends on the energy 

input (EMi), but not vice versa; thus, a high degree of multicollinearity exists between 

body size and rates of protein and fat retention. 

 

1.3.2. Net energy for maintenance 

The metabolic rate of animals can be measured by measuring several variables, 

including oxygen consumption, carbon dioxide production, and the heat produced; 

however, due to the fact that metabolic rate varies according to many factors, to facilitate 



8 

scientific comparisons, it became necessary to define a set of conditions for its 

measurement. This is the reason for the origin of the concept of basal metabolic rate 

(BMR), which was believed to represent the minimum energy cost of living (Hulbert and 

Else, 2004). The concept of BMR is defined as the HP of an animal in a thermoneutral 

temperature (temperature range that does not produce an increase in metabolism), in a 

post-absorptive state (when the digestion and absorption of the last feed have ended) 

under resting status (NRC, 1981). However, the measurement of BMR is complicated by 

the fact that the heat produced comes not only from body tissues but also from the 

digestion and metabolism of food components, known as heat increment of feeding 

(HIF), as well as from the voluntary muscular activity of the animal (McDonald et al., 

2011). 

It is difficult to measure the BMR mainly by complications of the HIF. In the 

absence of feed, with water and sufficient oxygen supply, the life of the animal can be 

supported for a considerable period by its body reserves. Therefore, the fasting animal 

in a state of rest allows for studying the demands of the fundamental vital processes 

uncomplicated by the functions of digestion and resorption or by the requirements of 

growth, fattening, or reproduction (Armsby, 1917). However, there is much confusion 

and disagreement as to when resting metabolism ends and basal metabolism begins for 

each species because the period of fast required for the digestion and metabolism of 

previous meals to be completed varies considerably between species; thus, the length 

of time for the fast is an important criterion to specify in all cases (NRC, 1981; Sartori et 

al., 1995). Thus, fasting heat production (FHP) is commonly used to characterize the 

BMR in many species under specified conditions (Koong et al., 1985; Noblet et al., 

2015). 

1.3.3. The fasting metabolism 

In quails subjected to 21 days of fasting, the fasting can be divided into three 

phases or stages. Phase-I is characterized by a rapid decrease of body weight and high-

fat mobilization. Phase-II is longer and characterized by a slow and steady decline in the 



9 

rates of body weight loss and nitrogen excretion. Phase-III is marked by an abrupt 

increase in the rates of body weight loss and nitrogen excretion (Sartori et al., 1995). 

Following feed deprivation, the first stage of fasting is the postabsorptive period, 

which begins once all of the nutrients ingested at the last meal have been absorbed 

from the small intestine (Maughan et al., 2010). Factors such as body size, feed 

composition, length of the digestive system, and rate of feed passage (Hillerman et al., 

1953; Noy and Sklan, 1995) affect the length and characteristics phase-I. In this stage of 

fasting, the body adjusts its metabolism progressively to the absence of nutrients, i.e., 

blood glucose is maintained during this time by the liver glycogen, but the liver content is 

highly variable (López‐Soldado et al., 2020). Also, as fasting became prolonged, there is 

a reduction in the rate of carbohydrate oxidation due to limited storage of carbohydrates 

while the mobilization of triglycerides increases, resulting in increased fat oxidation 

(Horton and Hill, 2001). 

Under fasting conditions, due to the reduction in the heat provided by digestion 

and metabolism of nutrients, there are some adaptations in the thermoregulatory 

system. To preserve body temperature, adaptive changes in heat loss or thermal 

conductance can occur, but some studies suggest that birds reduce body temperature to 

induce a hypometabolic state to afford energy conservation (Hohtola, 2012). The 

hypometabolic state (or metabolic depression) can be achieved by the downregulation 

of cellular processes, including the depression of ion pumps, a decrease in ion leakage, 

and suppression of RNA and protein synthesis (Secor and Carey, 2011).  

The FHP can be affected by a great number of factors such as metabolic body 

size, circadian variation (Macleod et al., 1980), physiological state (Yan et al., 1997), 

environmental temperature (O’Neill et al.,1971), feather covering (Lee et al., 1983), 

feeding regime and duration of starvation (Koonn et al., 1982), age and early feed 

restriction (Zubair and Leeson, 1994), and body composition (Tess et al., 1984). 

 



10 

1.4. Energy for physical activity 

1.4.1. Physical activity 

Physical activity (PA) can be defined as any bodily movement produced by 

skeletal muscles that result in energy expenditure (Caspersen et al., 1985). Any bodily 

movement requires energy as produced by muscles, so there is a complicated 

interaction between PA, body weight, body composition, and energy expenditure 

(Westerterp, 2013). Differences in PA represents the largest source of variability in 

energy requirements, both within and between animals, thus, changes in PA patterns 

can produce changes in energy requirements. If energy is not adjusted to this new 

energy steady, it can lead to changes in body size and body composition with time (Hill 

et al., 1995). Differences in duration, frequency, and intensity of PA may create 

considerable variations in total energy expenditure (Van Baak, 1999). It is important to 

note some differences between PA and exercise. The term "exercise" has been used 

interchangeably with PA; however, exercise is a planned, structured, and repetitive type 

of PA aimed at improving or maintaining the physical fitness component (Caspersen et 

al., 1985). 

The patterns of PA are completely understood, in large part, because it is affected 

by numerous factors. It is generally reported that PA reduces as body size or age 

increases (Bokkers and Koene, 2003). The lighting schedule affects the PA patterns; 

consequently, the HP (Apeldoorn et al., 1999). Stock density is negatively related to the 

locomotor activity (Simitzis et al., 2012). Birds reared in battery cages had a reduced PA 

compared to birds with free access to aviary environments (Duncan, 2001; Fleming et 

al., 2006). On daily basis, the amount and characteristics of PA can be varied 

considerably between individuals (Murphy and Preston, 1988). 

1.4.2. Methodologies to assess the physical activity 

The PA has been studied to understand energy losses and their relationship with 

energy requirements; however, due to PA covering multiple and complex behaviors, 

precise quantification can be difficult. Accelerometers are devices that measure the body 

acceleration in one of the three orthogonal planes (anteroposterior, mediolateral, and 



11 

vertical) which can be used to estimate the intensity of PA over time. The raw output of 

accelerometers is known as counts; however, it is often unclear what a count truly 

means, physically or physiologically (Chen and Bassett, 2005). Despite that, there are 

attempts to use the accelerometer as a tool for behavior classification in ruminants 

which cannot be directly translated to birds (Yang et al., 2021). 

An index of PA can also be estimated by determining the percentage of pixels of 

moving animals to the total number of pixels within the image including animals and 

background (Bloemen et al., 1997). Compared to accelerometers, this is a non-

invasiveness method that does not require bird manipulation but a digital analysis 

technique for further estimation of PA. Although this technique will allow assessing the 

PA for a set of birds (or animals), this technique is not yet ready for large-scale practical 

use, and also, there are no studies relating this PA index with energy expenditure yet. 

The time-energy budget method is commonly used to calculate energy 

expenditure in free-living animals. The pattern of PA (type and duration) is recorded in 

the field and the duration of these activities are multiplied by their respective energy cost 

to calculate the total energy expenditure (Goldstein, 1988). Based on the definition of 

PA, this approach seems more to relate the PA with duration, frequency, and intensity. 

This technique requires previous determination of the energy cost of each type of PA; 

however, information about the energy cost of each type of PA in commercial birds is 

limited or non-existent. 

 

1.5. Calorimetry technique 

1.5.1. Indirect calorimetry 

In the history of calorimetry, both indirect and direct methods are of merit. 

Although direct calorimetry was first employed, indirect chemical procedures introduced 

by Regnault and Reiset in 1849 attained wider use mainly because such measurements 

were less expensive and more convenient (Benzinger and Kitzinger, 1949). The rate of 

HP in an individual is directly proportional to energy expenditure and, therefore, 

metabolic rate. The energy expenditure can be accurately quantified by measuring heat 



12 

release with direct calorimetry and/or estimated from the quantitative measurement of 

the chemical by-products of metabolism (Figure 2). Since biochemical pathways to 

generate energy depend on oxygen, there exists a relationship between oxygen 

consumed and HP, thus the measurement of oxygen consumption provides an estimate 

of energy expenditure (Kenny et al., 2017). Over the years, indirect calorimetry has been 

a well-established technique to measure the HP of men and animals for many years 

based on the measurement of oxygen consumption and carbon dioxide production for 

further calculation of HP. 

 

 

Figure 2. Indirect versus direct calorimetry (Kenny et al., 2017). 

 

According to Mtaweh et al. (2018), the indirect calorimetry methods for energy 

expenditure measurements are based on the following assumptions: 

a. Any fuel consumed has an intrinsic energy content that upon metabolic 

modifications in the living system will result in heat or energy production. 

b. The combustion or synthesis of carbohydrates, fat, or protein is the end result 

of all the biochemical reactions occurring in the body. 

c. The oxidation of glucose, fat, or protein results in a substance-specific fixed 

ratio between the quantities of O2 consumed and CO2 produced. 

d. Loss of substrates is negligible in feces and urine 

 

Foodstuffs + O2 Heat + CO2 + O2 

Indirect 
calorimetry 

Direct 
calorimetry 



13 

Several indirect calorimeters (or calorimetry chambers) are manufactured across 

the world. The indirect calorimeters can classify as open or closed-circuit systems. In the 

open-circuit design, the animal breathes chamber air supplied by a mechanical ventilator 

or external pump. Air inlets and outlets are usually positioned in the back and front of the 

chambers while ventilators are used to homogenize the gas in the chamber. The 

difference between inspired and expired gas concentration is used to calculate oxygen 

consumption and carbon dioxide production (Miller and Koes, 1988; Johnson et al., 

2019; Tøien, 2013). 

Closed-circuit systems usually are simpler in design than open system. An air 

pump circulated chamber air through a screw-capped plastic bottle containing KOH 

solution and a bubbler assembly to absorb CO2 expired by the birds. The air is passed 

through a dried silica gel to absorb humidity before being returned to the chamber. The 

O2 is provided by a cylinder allowing replenishing of the consumption of O2 in the 

chamber by the birds. Oxygen consumption is calculated by the weight loss in the O2 

cylinder. The CO2 can be recovered from the KOH solution by precipitation techniques 

(Lighton, 2008). 

  



14 

1.6. References 

 
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Archiza B, Welch JF, Sheel AW (2017) Classical experiments in whole-body 
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15 

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glucose tolerance after a normal mixed meal. Journal of Applied Physiology 90(1): 
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Kenny GP, Notley SR, Gagnon D (2017) Direct calorimetry: a brief historical review of its 
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Kielanowski J (1965) Estimates of the energy cost of protein deposition in growing 
animals. Energy metabolism 3: 13. 
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Koong LJ, Ferrell CL, Nienaber JA (1985) Assessment of interrelationships among 
levels of intake and production, organ size and fasting heat production in growing 
animals. The Journal of Nutrition 115(10): 1383-1390. 
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Koong LJ, Nienaber JA, Pekas JC, Yen JT (1982) Effects of plane of nutrition on organ 
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19 

Chapter 2 – Fasting heat production as affected by body weight and 

environmental temperature in group-housed pullets and laying hens 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Este capítulo é apresentado segundo as normas da revista Animal Production Science



20 

  20 

 

Running head: Fasting heat production in pullets and laying hens 

 

Fasting heat production as affected by body weight and environmental temperature in 

group-housed pullets and laying hens  

 

F. HornaA, M. MacariA, J. Van MilgenB, M. P. ReisA, C. C. N. NascimentoA, N. K. 

SakomuraA, * 

 

ASchool of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), 

Jaboticabal, São Paulo, Brazil. 

BPEGASE, INRAE, Institut Agro, 35590 Saint-Gilles, France. 

*Corresponding author: Nilva Kazue Sakomura, Email: nilva.sakomura@unesp.br  



21 

  21 

 

ABSTRACT 

 

Context. Fasting heat production (FHP) is typically used to represent the net energy (NE) 

requirement for maintenance. To implement a net energy (NE) system for pullets and 

laying hens, it is important to determine how the FHP varies with body weight (BW) and 

external factors (e.g., environmental temperature). 

Aims. This study aims to assess the suitability of 0.75 allometric scaling to express the FHP 

relative to BW in pullets and laying hens and to quantify the impact of environmental 

temperature of the FHP during the laying period using an open-circuit indirect calorimetry 

system.  

Methods. To determine the allometric scaling for the effect of BW on FHP, forty-eight 

measurements were obtained in different groups of White Lohmann pullets and laying hens 

with BW ranging between 0.08 and 1.60 kg. Recorded data of FHP and BW were used to 

fit the linear-log model: log10 (FHP) = log10 (a) + b*log10 (BW), where a is the constant 

term representing the FHP (kcal/(BWb*d)), and b is the allometric scalar. To quantify the 

effect of temperature on the FHP in laying hens, thirty-seven measurements were obtained 

from different sub-groups of six birds (56 to 67 weeks old) subjected to temperatures 

ranging from 15 to 35°C. 

Key results. The results indicate that a value of 0.67 for b is appropriate to describe the 

allometric relationship between FHP and BW and that 90 kcal NE/(BW0.67*d) is thus 

required for maintenance in pullets and laying hens. In laying hens, the FHP was minimal 

at 24°C and the effect of temperature (T) can be described by the model FHP 

(kcal/(kg0.67*d)) = 0.247*T2-11.9*T+220. 



22 

  22 

 

Conclusion. The most appropriate allometric BW scalar for FHP in growing pullets is 0.67, 

while the energy correction above maintenance during the laying period can be done by the 

quadratic model. 

Implications. The choice of 0.67 or 0.75 allometric scalings will affect the estimate of the 

NE requirement for maintenance and thus the partitioning of NE above maintenance at 

different BW. In laying hens, the FHP varied little between 20 and 28°C but was 

considerably higher at lower and higher temperatures. 

 

Keywords: Allometric scaling, net energy for maintenance, critical temperature, 

thermoneutral zone, indirect calorimetry. 

  



23 

  23 

 

Introduction 

As energy accounts for the greatest portion of feed costs, accurate estimates of both 

energy requirements and energy values of feeds are required to optimize poultry 

production. The factorial approach has commonly been used to quantify the contribution of 

metabolic processes like maintenance and production to define energy requirements 

(Chwalibog, 1992). External factors are commonly considered to result in an increase in the 

maintenance energy requirement (NRC, 1981). In the net energy (NE) system, energy is 

partitioned into NE for maintenance (NEm) and production (NEp). The fasting heat 

production (FHP) is typically used to estimate NEm while NEp is the energy retained in the 

body or in products (Zuidhof, 2019). 

The concept of metabolic body weight (Kleiber, 1947) has been used to express 

energy requirements for maintenance per kilogram body weight (BW) raised to the power 

of 0.75 (BW0.75). Although this scaling is appropriate to express the maintenance energy 

requirement of different species over a wide range of BW, it appears less appropriate for 

growing animals within a species. Consequently, the universality of the scalar 0.75 has 

been questioned and values of 0.60, 0.70, and 0.77 have been proposed for commercial 

poultry species (Lopez and Leeson, 2005; Noblet et al., 2015; Rivera-Torres et al., 2011). A 

too-high and inappropriate scalar may lead to an underestimation of maintenance at lower 

BW and an overestimation at higher BW (Lopez and Leeson, 2005). This affects the 

availability and efficiency of energy for production (Lopez and Leeson, 2008). 

It is generally accepted that there is a range of ambient temperatures, known as the 

thermoneutral zone (TNZ), over which the heat production is minimum or constant 

(O'Neill et al., 1971). Below the lower critical temperature (LCT), the heat production is 

expected to increase because the animal spends more energy to maintain homeothermy 



24 

  24 

 

(NRC, 1981) while, above the upper critical temperature (UCT), additional energy is 

required for panting. Based on the ME system, Hurwitz et al. (1980) reported that the 

metabolizable energy requirement for maintenance (MEm) ranges between 24 to 28°C. 

In contrast to other livestock species, the NE system has not been fully implemented 

for poultry. Although the 0.75 allometric scalar is widely used in poultry nutrition, it 

originates from the comparison of the maintenance energy expenditure in mature, non-

productive animal species, and the relevance of this scalar for growing pullets and laying 

hens needs to be tested. Furthermore, it is important to quantify how the energy expenditure 

for maintenance and thermoregulation is affected by ambient temperature. Therefore, the 

primary objective of this study is to determine an appropriate allometric scalar relating the 

FHP to BW in pullets and laying hens. A secondary objective is to quantify the FHP over a 

wide range of temperatures in laying hens. 

Materials and methods 

All procedures involving animals were approved by the Animal Care and Use 

Committee of São Paulo State University (Protocol n°5397/20). 

Birds, Housing, and Management 

The study was conducted in two successive experiments, for which 350 one-day-old 

Lohmann LSL Lite NA pullets were purchased from a commercial hatchery (Planalto, 

Brazil). Birds were housed in a temperature-controlled semi-commercial facility for up to 

18 weeks of age. For the rearing phase, groups of four birds each were housed in cages (0.5 

m x 0.5 m) equipped with one feeding trough and one drinking nipple per cage. The 

environmental temperature was set at 32°C on arrival and gradually decreased to 21°C at 

the end of the rearing period on week 18. At 19 weeks of age, the hens were transferred to 



25 

  25 

 

2-tier layer cages with a capacity of four birds per cage (0.5 m x 0.45 m x 0.4 m). For both 

stages, a diet based on corn and soybean meal was formulated to meet or exceed the 

nutrient requirements according to the feeding program of the breeder (Lohmann LSL-

LITE, 2019). Birds were offered feed ad libitum. Lighting, vaccination programs, and 

general bird management were carried out according to the recommendations of the 

breeder. 

Measurement of energy expenditure by indirect calorimetry 

The trials were performed in an open-circuit indirect calorimetry unit with six 

respiration chambers of 0.7 m3 (0.9 m x 0.9 m x 0.85 m). Air inlets and outlets were 

positioned at the back and front of the chambers respectively, and ventilators in the 

chambers were used to homogenize the air in the chamber. The respiration chambers were 

equipped with a thermostat for temperature control (15 - 36°C; ±1°C) and a lighting 

controller system. For the rearing period, the birds were housed in a cage. For the laying 

period, a 3-compartment-cage of two birds per compartment was used. Cages were 

equipped with a feeding trough, three drinking nipples chamber, and a tray excreta 

collector. 

Gases were extracted continuously from the respiration chamber by an air pump (FK-

100, Sable Systems, Las Vegas, NV, USA). A sample (500 ml/min) of the outgoing air was 

connected to a gas flow multiplexer (RM-8, Sable Systems, Las Vegas, NV, USA), which, 

at regular intervals, sequentially directed air from each chamber to a gas analysis system. 

The eighth port on the multiplexer was used to direct the in-going air to the gas analysis 

system. The sampled air was passed through a relative humidity and dew point analyzer 

(RH-300, Sable Systems, Las Vegas, NV), scrubbing columns to remove water vapor 



26 

  26 

 

(Drierite, W. A. Hammond Drierite Co., LTD), a CO2 analyzer (CA-10A, Sable Systems, 

Las Vegas, NV, USA), an O2 analyzer (PA-10, Sable Systems, Las Vegas, NV, USA), and, 

finally, a subsample pump (SS4; Sable Systems) in pull mode to subsample 155 ml/min 

from multiplex excurrent gas. Voltage outputs from the analyzers were digitized using an 

analog-digital converter (UI-2, Sable Systems, Las Vegas NV, USA) and recorded with a 

sampling interval of 1/second using Expedata software (Sable Systems) for further analysis. 

At the beginning of each trial, both CO2 and O2 analyzers were calibrated to a zero 

point (pure N2) and a gas of known composition (a standard gas mixture with 21% O2 and 

1% CO2). At the end of each trial, these gases were passed again through analyzers to 

correct deviations during the measurement period. The ingoing and outgoing O2 and CO2 

(L/min) were calculated by multiplying the O2 and CO2 concentrations measured in the 

ingoing and the outgoing air streams. The O2 consumption and CO2 production were 

calculated by the difference between them. For a detailed explanation of the calculations of 

O2 consumption and CO2 production, see the Excel spreadsheet cited in Alferink et al. 

(2015). 

Fasting heat production measurements 

To measure FHP, a group of birds was placed in the chambers and fed under the 

aforementioned feeding program for three days (adaptation period). On the fourth day, the 

feeder was removed from 8:00 until 8:00 the next day to measure the FHP. For each 

measurement, a group of birds in the poultry house was selected from those that were not 

used in the preceding weeks. During the adaptation period, the temperature was set 

according to the recommendations for each age. The flow rate of the air pump was set to 

obtain CO2 concentrations ranging from 0.5% to 1.5%. Birds had continuous access to 



27 

  27 

 

water during the fasting period and were kept under a continuous light schedule. They were 

weighed at the beginning and end of the fasting, and the average weight was used to 

represent the BW during the fasting day. The Brouwer equation (1965) was used to 

calculate the heat production (HP) per hour and the asymptotic HP was used to estimate the 

plateau FHP according to a broken line with a descending quadratic portion: if R<time then 

HP = L + U* (R-time)2 else HP=L. This model fits a descending quadratic curve for times 

before R, followed by a plateau HP (L) at times greater than R. 

To determine the allometric coefficient and the FHP, 48 groups of pullets and laying 

hens between 0.08 and 1.60 kg BW were used. Birds that reached the target BW according 

to guideline of Lohmann LSL-LITE (2019) were taken for the FHP measurement. On the 

fasting day, the chamber temperature was set according to guideline recommendations for 

each age. The number of birds per measurement unit was reduced as the age of the birds 

increased. For the ages of 1, 2, 3-4, 5-7, 8-13, 14-18, and 20-34 weeks, groups of 16, 12, 

10, 8, 6, 5, and 4 birds per chamber were used, respectively. 

To describe the effect of ambient temperature on FHP, 37 groups of 56 to 67-week-

old animals with six laying hens per chamber were used at ambient temperatures of 15, 20, 

22, 25, 27, 29, 30, 32, and 35°C. During the adaptation period, the chamber temperature 

was set to 22°C, whereas during the fasting period the temperature treatments were applied. 

Statistical analysis 

The allometric equation (𝑦 = 𝑎 ∗ 𝑥𝑏) proposed by Huxley (1924) in its linear form 

obtained by logarithmic transformation (Kleiber, 1947) was used to describe the FHP as a 

function of BW. Before the adjustment of the linear equation, recorded data of FHP and 

BW were logarithmically transformed: 



28 

  28 

 

𝑙𝑜𝑔10⁡(𝐹𝐻𝑃) ⁡⁡= 𝑎⁡⁡ + 𝑏 ∗ 𝑙𝑜𝑔10⁡(𝐵𝑊)⁡⁡… [1] 

Where a is the FHP (kcal/(BWb*d)) and b is the allometric scalar. The model was 

fitted using the NLMIXED procedure of SAS (Version 9.4, SAS Institute Inc., Cary, NC, 

2012). Additionally, the ESTIMATE statement of NLMIXED was used to test if the b 

parameter differed significantly from the allometric scalars proposed by others for avian 

species (i.e., 0.60, 0.67, 0.70, and 0.75). 

To explore the effect of temperature on FHP, the FHP per bird was expressed per unit 

of metabolic BW (MBW) using the allometric scaling of 0.67 and 0.75. Subsequently, a 

quadratic regression analysis was performed to explain the variation in FHP relative to 

temperature according to the model: 

𝐹𝐻𝑃⁡⁡ = 𝑎 ∗ 𝑇2 + 𝑏 ∗ 𝑇 + 𝑐 … [2] 

Where FHP is the fasting heat production (kcal/(MBW*d)) and T the environmental 

temperature (°C). The model [2] was fitted using the NLMIXED procedure of SAS 

(Version 9.4, SAS Institute Inc., Cary, NC, 2012). The temperature at which the FHP was 

minimum was obtained by solving for T when the first derivative of equation [2] equals 

zero: 

𝐶𝑇⁡⁡ = −𝑏/2𝑎… [3] 

Results 

For both experiments, the birds appeared to be in good health and the egg production 

continued in laying hens despite the fasting conditions. For the allometric scaling study, the 

BW losses averaged 7% during the fasting day (Table 1). During fasting, the RQ was lower 

for pullets (0.72) than for laying hens (0.77). For the study of the effect of temperature on 

FHP, the RQ was 0.73 while the BW loss averaged 12%. 



29 

  29 

 

Allometric regression equations and estimates of fixing the allometric scalar b are 

shown in Table 2. The log-linear model estimates a value of 0.671 as the most appropriate b 

scalar. For simplicity, this value was further considered as 0.67 and the value of a was re-

estimated. This procedure was carried out with an allometric scaling of 0.75. The 

ESTIMATE statement of NLMIXED showed that the scalar 0.67 differed significantly 

from 0.75 and 0.70. Figure 1 illustrates the allometric relationship between FHP and BW 

with the 0.67 and 0.75 allometric scalings, respectively. Using the 0.75 scaling as a 

reference, the expected FHP with the 0.67 scalar is greater for lighter birds (≤ 0.72 kg) 

while it is lower for heavier birds. 

The results of fitting a quadratic equation to express the effect of T (°C) on 

FHP(kcal/kgb) using 0.67 and 0.75 as allometric scalars are 0.247*T2-11.9*T+220 and 

0.241*T2-11.6*T+215, respectively. For both modes of expression, the first derivative 

indicated that the minimum FHP was attained at 24°C. The effect of ambient temperature 

on the FHP is shown in Figure 2 using 0.75 as an allometric scalar. The FHP increased by 

about 40% in both a low (15°C) and high (35°C) ambient temperatures.  

Discussion 

Allometric scaling and energy for maintenance 

It has been suggested that the energy loss of different-sized species should be related 

to their surface area and that the surface area of an animal is proportional to BW raised to 

the power of 0.67 or 2/3 (Chapell and Mordenti, 1991). Since Kleiber proposed that the 

metabolic rate was related closely to 0.75 or 3/4, many researchers have assumed that 

raising BW to the power 3/4 can be applied to all species and animals of different BW 

within a species. However, distinctions should be made between intraspecific and 



30 

  30 

 

interspecific scaling (Heusner, 1982; Glazier, 2005). In birds, numerous allometric 

relationships relating metabolic rate to body weight have been developed (Table 3). The 

proposed scalars for interspecific comparisons range from 0.60 to 0.81. The majority of 

these relationships concern different species of adult wild and captive birds. Only a few 

studies have been carried out with growing birds within a species. 

In the last decades, genetic selection has increased the growth rate and feed efficiency 

significantly in meat-type broilers, reducing the market age (Zuidhof et al., 2014). Also, the 

lay persistency and egg quality have been improved in laying hens (Bain et al., 2016), 

which may be accompanied by a lower metabolic rate (Denbow and Kuenzel, 1978; Buzała 

et al., 2015). In intraspecific studies for commercial birds, the proposed scalars range from 

0.61 to 0.77, which encompasses the allometric scalar found in this study. Therefore, it 

appears that the metabolic BW in birds does not scale well with 3/4, but depends on the 

strain and the characteristics of their growth rate. 

Considering that maintenance energy requirement represents a large portion of the 

energy intake in poultry (Gous, 2007), the use of different scalars has a considerable impact 

on the estimated energy requirement and energy partitioning as illustrated in Figure 1. The 

lines with scalars 0.67 and 0.75 intersect at 0.72 kg but, with the 0.75 scalars, the estimated 

maintenance requirement is lower than that with the 0.67 for lighter birds and higher for 

heavier birds. Consequently, the partitioning of energy between maintenance and 

production depends on the scalar that is used to estimate maintenance. 

Thermoneutral zones and critical temperatures 

The establishment of a TNZ in commercial birds is a matter of discussion, especially 

when associated with the energy requirements for maintenance. There is no consensus 



31 

  31 

 

among poultry nutritionists about the position and shape of TNZ, due to variations in feed 

intake, degree of feathering, and physical activity (Leeson and Summers, 2009). In a classic 

article, Barott and Pringle (1941) indicated that the “metabolism is at a minimum” between 

24 to 27°C while a “point of flexure” occurs around 25°C. The data of our study suggest a 

minimum FHP at 24°C, but the FHP is only slightly affected between 20 to 28°C (Figure 

2). Consequently, laying hens seem to be able to minimize their FHP over a relatively wide 

range of temperatures. 

Although the quadratic model used in the current study fitted the data well, it 

assumed that the increase in heat production is the same regardless of cold or hot 

environments. However, the physiological mechanisms for thermogenesis and cooling are 

different. The response to cold consists of initial vasoconstriction followed by an increase 

in HP by shivering (Dietz et al., 1997). The response to hot conditions consists of the 

activation of heat loss mechanisms by vasodilatation (Wolfenson et al., 1981) and panting 

(Dawson, 1982). In fed conditions, the thermal effect of feeding is not to be considered as 

an energy loss if it is used to preserve the body temperature (Bech and Præsteng, 2004). 

However, in hot conditions, the thermal effect of feeding is an energy loss and can even be 

a burden if the bird has difficulties dissipating the generated heat. The bird can then only 

reduce its heat production by decreasing its feed intake. Thus, the thermoregulatory 

mechanisms between cold and hot temperatures are different. During fasting, there is no 

thermal effect of feeding, and heat production is only due to the FHP. Due to the lack of 

thermal effect of feeding, it is anticipated that both the LCT and UCT are higher in fasted 

birds than in fed birds, resulting in a shifted TNZ towards higher temperatures. The 

minimum heat production at 24°C observed in this study may therefore be somewhat higher 

than the minimum heat production and TNZ in the fed state. 



32 

  32 

 

Corrections over energy for maintenance 

In some studies, it may be possible to describe negative linear correlations between 

energy requirements at cold temperatures. In the study of Farrell and Swain (1977) with 

broilers, it is possible to observe a constant decrease in starvation HP in their data. This 

inverse relationship between energy for maintenance and a cold environment was also 

reported in laying hens (Balnave et al.,1978), pullets (Sakomura et al., 2003), and broiler 

breeders (Sakomura et al., 2003; Reyes et al.,2012). Nevertheless, in some studies, it is 

possible to identify an increase in energy for maintenance at T greater than the critical 

point. In the study of Hurwitz et al. (1980) using broilers and turkeys, they observed a 

quadratic effect over MEm by T also, at 16°C, it is possible to observe an increase of 40% 

in MEm. In 1-to-10-old chickens and turkeys, subjected to 1 hour of cold and hot 

temperatures, a cubic trend in HP was found to allow determining a CT for each age 

(Tzschentke and Nichelmann, 1999.). In the study of Neme et al. (2005), carried out with 

feathered and defeathered laying type pullet hens, there is a constant increase in MEm of 

6.73 and 0.88 kcal/(kg0.75*°C) at T below and above CT regardless of feathering degree. 

Although it is well known that animal responses are nonlinear (Almquist, 1953; 

Roush et al, 1994; Rosen, 2007), statistical simplification is commonly used to obtain 

important estimates for practical use by ignoring some biological considerations. 

Nevertheless, the mathematical approach is commonly used to adjust the energy for 

maintenance within an operational range of temperatures in commercial poultry production 

according to the physiological state (NRC, 1981). Rostagno et al. (2017) pointed out that 

the energy correction of 2.6 kcal ME/(BW0.75*°C) can only be applied within a range of ± 6 

of CT because extreme T impairs bird performance and overestimate corrections for feed 

intake and nutritional levels. Based on our data, we suggest that the energy corrections 



33 

  33 

 

above maintenance by temperature can be applied below and above 4°C assuming the 

presence of a single CT. 

Conclusion 

In conclusion, this study indicated that the most appropriate allometric BW scalar for 

FHP is 0.67 so the maintenance NE requirement for pullets and laying hens is 90 

kcal/(kg0.67*d). Because of the wide range in BW, the choice of an appropriate scalar is 

more important for pullets than for laying hens, because of the wide range in BW. The FHP 

in laying hens varies relatively little between 24 and 28°. However, this temperature range 

should not be considered as the TNZ for birds that are fed, because the thermal effect of 

feeding will likely shift the TNZ to somewhat lower temperature values.  

Acknowledgments 

The authors thank the Coordination for the Improvement of Higher Education 

Personnel (CAPES, Process 88887.338773/2019-00) for the scholarship grant. 

Declaration of funding 

This work is supported by the Sao Paulo Research Foundation (FAPESP), grant 

2019/26575-6. 

Data Availability Statement 

The data that support this study will be shared upon reasonable request to the 

corresponding author. 

Conflict of Interest Statment 

The authors declare no conflict of interest. 



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  34 

 

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Tables 

Table 1. Respiratory quotient and body weight loss during the experiment 

Type N Mean Std Error 

Allometric scaling 

 --------- Respiratory quotient --------- 

Pullet 38 0.72 0.003 

Laying 10 0.77 0.014 

Pooled 48 0.73 0.004 

 --------- Body weight loss (%) --------- 

Pullet 38 6.7 0.26 

Laying 10 7.7 0.14 

Pooled 48 7.0 0.22 

Effect of temperature 

 --------- Respiratory quotient --------- 

Laying 37 0.73 0.004 

 --------- Body weight loss (%) --------- 

Laying 37 12.0 0.21 

 

  



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Table 2. Regression parameters log(a) and b for the allometric equation and estimation of 

log(a) fixing allometric scaling b. 

Parameter Estimate Std Error Pr > |t| 

------------ Parameter Estimates ------------ 

log(a) 1.95 0.004 <.0001 

b 0.671 0.012 <.0001 

---------------- fixing b = 0.75 ---------------- 

log(a) 1.971 0.006  

    

---------------- fixing b = 0.67 ---------------- 

Log(a) 1.9537 0.004   

a: FHP (kcal/BWb); b: allometric scaling. 

 

  



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Table 3. Body weight range, basal metabolic rate (a), and allometric scaling (b) of different 

avian species (Based on Bushuev et al., 2018) 

Source Classification BW range (kg) b1 a1,2 

---------------- Interspecific studies3 ---------------- 

Brody and 

Proctor (1932)4,5 
Avian species  0.640 90.11 

Bennett and 

Harvey (1987)4 
All birds 0.01 - 1006 0.670 57.54 

Tieleman and 

Williams (2000) 
All birds 0.0037 - 95.4 0.638 73.69 

McKechnie and 

Wolf (2004) 
All birds 0.0029 - 100 0.669 72.60 

Speakman 

(2005) 
All birds  0.671 83.75 

McNab (2009) All birds 0.0052 - 92.4 0.652 75.16 

Lasiewski and 

Dawson (1967) 
Passeriformes 0.0061 - 0.866 0.724 129.00 

 Non-passerines 0.003 - 100 0.723 78.30 

 All birds 0.0061 - 100 0.668 86.40 

Daan et al. 

(1990) 
All birds 0.0108 - 1.253 0.677 86.88 

McKechnie et 

al. (2006) 

Captive-raised 

birds 
0.01 - 10d 0.670 66.67 

 Wild-caught birds 0.01 - 10d 0.744 75.32 

Zar (1969) Passerines  0.724 129.00 

 Non-passerines  0.728 76.70 

 All birds  0.667 83.90 

Ballesteros et al. 

(2018) 
Flying birds  0.657 76.73 

 Flightless birds  0.744 60.68 



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Flightless birds, 

without outliers 
 0.805 61.15 

Johnson and 

Farrell (1985) 
All birds 0.7 - 4.35 0.614 96.25 

 Mature birds  0.602 96.92 

 Immature birds  0.646 95.59 

Hudson et al. 

(2013) 
avian species  0.710  

White et al. 

(2006) 
Pooled  0.640 58.16 

---------------- intraspecific studies3 ---------------- 

Noblet et al. 

(2015) 
Broiler 0.6 - 2.8 0.700 100.38 

Berman and 

Snapir (1965) 
Pooled 1.5 - 4.0d 0.610 91.58 

Rivera-Torres et 

al. (2010) 
Growing turkeys 0.2 - 13.77 0.770 105.40 

This study 
Pullet and laying 

hens 
0.08 - 1.60 0.670 89.89 

1a is the constant term and represents FHP (kcal/BWb); b is the scaling exponent from 

equation FHP = a*BWb. 

2The constant term a was recalculated from logarithmic back transforming, based on 1000g 

of body mass, 24 hours, and/or 1kcal = 4.184 kJ. 

3Birds were post-absorptive, thermoneutral surrounding, and nearly rested as possible. 

4Literature review. 

5Cited by Johnson and Farrell (1985). 

6Not reported. 

7based on equation 1L of O2 = 20.083 kJ (Schmidt-Nielsen, 1997). 

  



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Figure 1. Allometric relationship between body weight mass and fasting heat 

production for pullets and laying hens.  



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Figure 2. Observed and Predicted data of Fasting heat production per metabolic body 

weight as a function of temperature. Allometric scaling fixed at 0.75. 

  



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Summary text for the table of contents 

The BW0.75 was developed to express energy requirement however the validity of 

0.75 in pullets in laying hens needs to be tested. The results suggest that the most 

appropriate scalar for pullets and laying hens is 0.67; nevertheless, the choice of 0.67 or 

0.75 allometric scalings will affect the estimate of the energy required for maintenance for 

growing pullets than laying hens.  For laying hens, the maintenance energy varied a little 

between 20 and 28°C but was considerably higher outside this range. 



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Chapter 3 – Energy requirements for maintenance as a function of body weight 

and critical temperature in broiler chickens 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Este capítulo é apresentado segundo as normas da revista Livestock Science 



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Main Document 

Energy requirements for maintenance as a function of body weight and critical 

temperature in broiler chickens 

F. Hornaa , M. Macaria, M.P. Reisa, G.F.S. Teofiloa, R.S. Camargosa, N.K. Sakomuraa, * 

a School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp) 

Jaboticabal, São Paulo, Brazil. 

* Corresponding author: Nilva Kazue Sakomura e-mail: nilva.sakomura@unesp.br 

  

mailto:nilva.sakomura@unesp.br


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ABSTRACT 

The rate of heat loss (HL) reduce as body weight (BW) increases, also this rate of HL is 

affected by environmental temperature (T) thus interactions between BW and T on energy 

metabolism are highly expected; then quantification of these interactions over maintenance 

requirements is important to get a better adjust of energy requirements. Therefore, this 

study aimed to explore the interaction of BW and T on fasting heat production (FHP) 

assuming a single critical temperature (CT). A procedure used in this study assumed two 

main stages: (i) how the CT (°C) is affected by BW size and (ii) how the FHP change 

according to T. To solve the first stage (i), it was used the one-phase exponential decay to 

relate CT as a function of BW (CT = c + (d-c)*e-R*BW … [1]). To solve the second stage 

(ii), a line-line regression was used to describe the amount of energy used (kcal/(kg0.75*°C)) 

above FHP assuming a single CT (FHPkcal/bird = BWb*[L + U*(CT-T)*(T<CT) + V*(T-

CT)*(T≥CT)] … [2]). The CT term in equation [2] was replaced by equation [1] allowing 

for the building of a simultaneous model. To fit the full model, a total of seventy-six 

observations of FHP from group-housed broilers placed in six respiratory chambers were 

used. Data were taken weekly with broilers ranging from 0.20 and 3.30 kg of BW (1 to 45 

days old) while the environmental chambers were adjusted to temperatures below and 

above the recommendation of the broiler management guide for each age (15, 18, 21, 24, 

27, 30, 33, and 36°C). A previous analysis showed that FHP was proportional to BW raised 

to the power of 0.75, so this allometric scaling was used to adjust the full model. The fitted 

model was as follows: FHPkcal/bird = BW0.75*[84.98 + 2.65*(CT-T)*(T<CT) + 4.41*(T-

CT)*(T≥CT)]; where CT = 22.46 + (35.83 - 22.46)*e-0.4906*BW, BW is body weight (kg) and 

T is Temperature (°C). In the current study, the simultaneous regression analysis indicated 



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that the CT reduces as BW increases while the energy corrections outside CT are 2.70 and 

4.07 kcal/kg0.75(°C*d) for temperatures below and above CT, respectively.  

 

Keywords: Fasting heat production, critical temperature, indirect calorimetry, modelling, 

net energy.  



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1. Introduction 

The net energy (NE) has been proposed as the most accurate system to express the 

energy needed for the animals because the energy requirements and diet energy values are 

expressed on the same basis which should theoretically be independent of the feed 

characteristics (Noblet, 2007). In the NE system, the energy is usually partitioned into NE 

for maintenance and NE for production (Latshaw and Moritz, 2009). The NE for 

maintenance is related to the energy level required to support the metabolic basal functions 

in the animal (Koong et al., 1985), consequently, the fasting heat production (FHP) of 

animals is used as indicative of their basal metabolic rate to estimate their maintenance 

energy requirements (Noblet et al., 2015). The NE for production is related to the energy 

required for body weight gain or products (Zuidhof, 2019). 

The requirement for m