Energy Partition-Based Residual Feed Intake Reveals Efficiency Differences Between White and Brown Laying Hens in Extended Laying Cycles

Abstract

The present research was defined to evaluate the residual feed intake (RFI) of white and brown groups of aged layers, between 85 to 90 weeks of age. A completely randomized design was used, with two treatments and 15 replicates, of one hen per replicate, for individual control. The treatment consisted of two genetic groups, brown and white (W-80), from Hy Line. Performance, egg quality, biometry visceral, body composition, energy partition, RFI, and residual metabolizable energy intake (RMEI) were evaluated. The results showed that egg weight was the main factor responsible for the difference between genotypes, affecting the production of the egg mass, yolk weight, and eggshell weight, as well as measures related to utilization efficiency (p < 0.05). The size of the uterus + vagina was larger for white layers (p < 0.05). The values obtained for RFI and RMEI were lower (p < 0.01) for white layers. While brown layers did not present hens with low RFI, 64.3% of the hens were classified as high RFI. The differences shown in this research between white and brown layers are smaller than in the past and show a tendency towards similarity; however, the economic impacts of the current differences are significant and must be considered.

1. Introduction

The concept of RFI has been consolidated in several areas of animal production [1,2], and poultry science [3,4,5,6,7,8,9,10,11]. Since its methodology conception [12,13], the use of RFI has now been validated with advanced tools [6,14,15]. RFI is defined as the difference between observed and predicted intake [12,13], and has been used to understand differences between individuals of a given genotype [16], between genotypes with the same purpose, environment, and diet [16,17], and their consequences on the utilization efficiency of nutritional resources [18].

The first studies with layers (white Leghorn) showed that hens with the same production for egg mass, weight gain (WG), and body weight (BW) showed a significant difference (10% to 30%) in RFI [12,13,19] and feed efficiency [17]. The factors that constitute the RFI are associated with variability in utilization efficiency between individuals, and can be segregated according to their methodological or biological origin [16]. Factors related to the method to obtain the RFI are associated with feed intake measurement errors (e_im) and adjustment errors in model parameters (e_if), while factors of biological origin are associated with unidentified energy sinks (es), deviation of nutrient digestibility concerning average considered in the nutritional matrix (dd), and variability in metabolic efficiency (e_fm), in addition to a possible part not yet explained (e_i), as demonstrated by [16].

Although the traditional approach allows for the identification of individuals with divergent intake relative to performance, it does not explicitly distinguish how metabolizable energy is partitioned between maintenance and productive functions. In laying hens [4], particularly at advanced ages, this limitation becomes biologically relevant, as age-related changes in maintenance requirements [20], body composition, and metabolic regulation may alter energy allocation patterns, thereby affecting the interpretation of efficiency based solely on intake predictions.

An energy partition-based approach provides a more mechanistic framework by separating metabolizable energy intake into maintenance and production components [21,22]. By explicitly quantifying the energy allocated to egg deposition and maintenance, this method enables a clearer biological interpretation of efficiency differences [22,23]. Recent studies in commercial laying hens have highlighted the complexity of feed efficiency regulation and its association with metabolic status and physiological function [4,15], underscoring the importance of efficiency metrics grounded in energy utilization rather than intake alone.

Therefore, reducing poultry production costs requires an understanding of these factors [24], particularly when selecting genotypes with a lower frequency of high-RFI individuals [25,26]. Commercial layer flocks can now remain productive up to 110 weeks of age, maintaining egg production above 87%, as predicted by Bain, et al. [27]. The extended use of layers contributes to cost dilution and sustainability by reducing non-productive periods and the number of birds required in the production system [27,28]. However, Bédère, et al. [28], highlighted that the laying phase, especially after 80 weeks of age, remains insufficiently explored, with limited information on the physiology, nutrition, and genetics of aged hens. In extended cycles, the maintenance of energy represents an increasing proportion of total metabolizable energy intake [29]; small differences in energy allocation may result in economically relevant effects [29,30].

In addition, commercial white and brown layers differ in body weight, egg weight, and metabolic characteristics, which may influence maintenance requirements and energy partitioning. These differences can affect RFI [17,24,25,26], and overall efficiency, particularly during late laying, when maintenance costs represent a substantial proportion of total energy expenditure. Based on these considerations, the present study aimed to evaluate residual feed intake in white and brown laying hens during the late laying phase by comparing a traditional intake-based model with an energy partition-based approach. By integrating performance data with metabolizable energy partitioning, this study seeks to improve the biological interpretation of genotype differences in feed efficiency under extended production cycles.

2. Materials and Methods

The trial was carried out at the Poultry Science Laboratory (PSL) of the Department of Animal Science, UNESP, Jaboticabal Campus, São Paulo, Brazil. The Animal Ethics and Welfare Committee of São Paulo State University approved all experimental procedures used in this study under Protocol number 2552/23. The trial was conducted at PSL–UNESP, Jaboticabal Campus, from June to August 2023, with the objective of evaluating the feed efficiency of white and brown aged laying hens.

2.1. Hens, Facilities and Management

In this research, commercial layers, brown and white W-80 Hy Line lineage, at 84 weeks of age, were used. The layers used were obtained from the same commercial farm at 18 weeks of age. From the 18th week to the 74th week, the birds were raised in the Poultry Sciences Laboratory, in a conventional open shed, with two half pyramids and a central corridor, equipped with six fans, a galvanized trough feeder, and a nipple drinker. These hens had not been used in any previous experiments and were maintained under standard conditions exclusively for use in the present trial, ensuring no experimental carry-over effects. All management practices were strictly conducted in accordance with the genetic line guideline recommendations, ensuring standardized rearing conditions throughout the pre-experimental period. Based on BW and egg production (EP) of each lineage, Hy Line brown and Hy Line white W-80, a total of 60 layers (30 brown and 30 white W-80), were selected at 74 weeks of age and transferred to a climatic chamber, equipped with temperature and light control and an extractor for air renewal. This standardized selection procedure further minimized potential carry-over effects from the earlier rearing period.

The cages had sloped floors to facilitate egg collection. EP was monitored daily, and BW was measured at 84 weeks. Then the group was reduced by half, with 15 brown layers (BW: 1802 g ± 60) and 15 white W-80 layers (BW: 1717 g ± 60), selected for the trial, using the same criteria to standardize the experimental units. At 84 weeks of age, prior to the experimental period, brown hens presented an average egg production of 95% (±6%), while white W-80 hens presented 98% (±8%).

The hens had ad libitum access to water, and feed was offered ad libitum, being supplied twice daily (08:00 and 16:00) in amounts exceeding the expected voluntary intake to always ensure unrestricted access. The reported value of approximately 120 g per hen per day refers to the average amount of feed offered, not to a fixed or restricted allowance, and was intentionally set above observed intake levels. Feed refusals were recorded weekly, confirming that feed intake was not limited during the experimental period.

The lighting program adopted was 17 h of light per day and 7 h of darkness (Lukma electric LK-188, Group Lukma, Sao Jose do Rio Preto, Brazil). Temperature and relative humidity were measured daily using a thermo-hygrometer (Incoterm 7666, Incoterm Induistria de Termometros Ltd., Eduardo Prado, Brazil, accuracy for temperature ±1 °C and ±5% for humidity) during the experimental period. The average, maximum, and minimum temperature were 25.0 °C, 27.6 °C, and 22.7 °C, respectively. The average, maximum, and minimum humidity recorded were 70%, 80%, and 60%, respectively.

2.2. Experimental Design

Thirty Hy-Line brown and white W-80 hens at 85 weeks of age were used, with fifteen hens per treatment housed individually in metabolic cages (45 D cm × 50 W cm × 45 H cm) equipped with an excreta collector under the floor. The cages were fitted with individual galvanized trough feeders and individual nipple drinkers. The feeders were specifically designed to minimize feed spillage, were inspected daily, and any visible feed losses were negligible. Feeders were positioned to prevent contamination of excreta trays and only feed remaining in the feeder was considered as refusal; therefore, feed losses unrelated to actual consumption were minimal and did not affect feed intake calculations.

The experimental design was completely randomized, with two treatments (two genetic groups: brown and white W-80) and fifteen replicates. The treatment consisted of two genetic groups, Hy Line brown and Hy Line white W-80. The feed (Table S1) was formulated according to nutritional recommendations and food composition by Rostagno, et al. [31]. The experimental period lasted five weeks, in accordance with previous studies [4,6]. The first week was designated as an adaptation period due to the handling of the hens for in vivo body composition assessments. Consequently, only data collected from 85 to 90 weeks of age were considered for analysis.

2.3. Performance

The feed was provided twice a day and leftovers were quantified weekly. The daily feed intake (FI, g/bird) was obtained by the difference between the amount of feed supplied and feed leftovers, divided by seven days ([supplied − leftovers] ÷ 7). EP and egg weight (EW) were measured daily. Daily egg mass production (EM) was obtained by the product of EP and EW, (EP × EW] ÷ 100). The feed conversion ratio (FCR) was calculated by the ratio between FI/EM. Feed efficiency was obtained by the reciprocal of FCR (1 ÷ FCR). BW was measured at the beginning (t_i—85 weeks) and at the end (t_f—90 weeks) of the trial. To minimize potential sources of error, body weight was measured under standardized conditions. All birds were housed individually and managed uniformly, ensuring that any residual variability was random rather than systematic. The birds were weighed in the morning (07:00), before feeding. The WG, or daily variation in body weight, was obtained by the difference between BW in t_f-t_i, divided by the experimental period of 28 days.

2.4. Internal and External Egg Quality

Eggs were evaluated in the third week of the trial for seven consecutive days. The variables collected were EW, eggshell weight (ESW), eggshell thickness (EST), yolk weight (YW), albumen weight (AW), albumen height (AH), and Haugh unit (HU). ESW was obtained after removing the albumen residue and drying the shell for 72 h at 55 °C in a forced-air oven (Solab SL-102, Piracicaba, São Paulo, Brazil). The AW was obtained by subtracting the ESW and YW values from the EW. The egg components were weighed using an analytical balance with 0.01 g precision (Bel EngineeringS1002, Bel Engineering S.r.l., Monza, Italy). EST and AH were measured using a digital caliper (Digimess 100-174BL, Digimess Instrumentos de Precisão Ltd., São Paulo, Brazil). The average EST value was the result of three measurements in the equatorial region of the egg; the average value was used for statistical analysis. EST was measured using a calibrated digital caliper with a measurement precision of 0.01 mm. The HU was calculated according to Card and Nesheim [32]. All measuring devices used in the study, including digital calipers and precision scales, were calibrated according to the manufacturers’ specifications before data collection to ensure measurement accuracy and reliability.

2.5. Metabolizable Energy of the Diet

To precisely determine metabolizable energy intake, the total excreta collection method was used. Collections were collected in the fourth week of trial, for five consecutive days. To mark the beginning and end of the total excreta collection period, ferric oxide (1%) was used. Total excreta collection began when the ferric oxide marker first appeared and finished when the marker reappeared at the end. After removing feathers, feed residues, and other contamination sources, excreta from each experimental unit were collected twice daily to avoid fermentation. The excreta were stored in identified plastic bags, weighed according to each repetition, and stored at −20 °C pending analysis.

At the end of the trial, the excreta samples were thawed and homogenized per experimental unit and pre-dried in a forced-air oven at 55 °C for 72 h. Before analysis, feed and excreta samples were ground through a 1 mm screen in an animal nutrition laboratory mill for the analysis of dry matter (oven-dried: SOLAB SL-100, SOLAB-Equipamentos para Laboratórios Ltd., Piracicaba, Brazil) using an oven at 105 °C for 16 h (AOAC-930.15). The total nitrogen (N) content was determined using the Kjeldahl (TecnalTE-036/1, Piracicaba, São Paulo, Brazil) method (AOAC-2001.11); the crude protein (CP) value was obtained considering (N × 6.25). The gross energy (GE) was determined by bomb calorimetry (IKA Works Inc., Staufen, Germany). After laboratory analysis, calculations were carried out to determine the apparent metabolizable energy and nitrogen-corrected apparent metabolizable energy for the nitrogen balance (ME_n) using the equations proposed by Matterson, et al. [33]. The ME_n were applied because, in laying hens, continuous protein export in eggs and variation in protein turnover affect nitrogen balance, making ME_n a more biologically comparable estimate for energy intake and partitioning [3,4].

2.6. Determination of Body Composition

Body composition in vivo, at the beginning and end of the trial, was measured using the DXA method, dual-energy X-ray absorptiometry (DXA, Hologic-QDR^® model 13.4.2., Marlborough, MA, USA). As a pre-anesthetic procedure, the hens were kept fasting for 5 h. To completely immobilize the hen during scanning, inhalation anesthesia was used, keeping the concentration of isoflurane (2%), diluted in 100% oxygen in the inhalation chamber during scanning. The hens were positioned in dorsal recumbency with their wings and legs flexed to be scanned, following the procedure described by Alves [34]. The measurements of bone mineral content, bone mineral density, fat mass, lean mass, and total mass obtained from DXA for each hen were used in the equations proposed by [34] to obtain the respective values of protein, fat, water, and ash deposition.

2.7. Biometric Measurements: Visceral

After the end of the trial, all hens were fasted for 12 h and were then sacrificed using cervical dislocation for subsequent biometric evaluation of the main organs of the gastrointestinal and reproductive tract and organs of the immune system. The collected organs were weighed (ToledoAR2140, Toledo do Brasil Indústria de Balanças Ltd., São Bernardo do Campo, Brazil) on a precision scale (0.1 mg); their length was measured using a measuring tape (Incoterm 35246, Incoterm Induistria de Termometros Ltd., Eduardo Prado, Brazil) with a precision of 0.1 cm. The viscera of the gastrointestinal tract were measured after removing the remaining residues. The variables evaluated were weight and length of heart, liver, oviduct (infundibulum, magnum, isthmus, uterus, and vagina), duodenum, jejunum, ileum, pancreas, and cecal handles. The selection of organs for biometric analysis was based on their known involvement in energy utilization, nutrient digestion and absorption, metabolic regulation, and egg formation, which are central to the objectives of this study.

2.8. Determination of Tradicional Residual Feed Intake (Method 1)

The RFI was defined as the difference between the observed or actual feed intake (aFI), and the estimated feed intake (eFI), obtained for everyone. The eFI was estimated by multiple linear regression, using as input variables: metabolic weight, (BW^0.67), WG, and EM, according to model 1:

eFI₁ = β0 + β1 × BW^0.67 + β2 × WG + β3 × EM ± e, g/day

(1)

where β0, is the regression intercept; β1, is the regression coefficient for BW^0.67; β2, is the regression coefficient for WG; β3, is the regression coefficient for EM; and e, is the random error.

The RFI₁ was obtained as follows: RFI₁ = aFI − eFI₁, where aFI and eFI₁ were previously defined. The standard deviation of the RFI₁ (σRFI₁) was calculated for each hen and used to interpret the homogeneity of individuals in relation to the group mean. Individuals were categorized into three groups: high, medium and low RFI₁, using the σRFI₁ values, according to the following criteria: high RFI when the σRFI₁ value is >+0.5σ; average RFI₁ when the σRFI₁ value was >−0.5σ and <+0.5σ; and low RFI₁, when the σRFI₁ value is <−0.5σ.

2.9. Partition of Metabolizable Energy (Method 2)

The model used to consider the partition of metabolizable energy intake (aMEI or Φ) was based on description from Sakomura [21], which assumes the utilization for maintenance (τ), and production (ξ), as follows: Φ = τ + ξ. In this research, the parameters Φ, τ, and ξ were obtained separately, using the input variables, FI, BW, and EM, respectively, as follows:

Φ = FI × ME_n, kcal/day,

(2)

τ = [Φ − ξ] ÷ BW^0.67, kcal/kg^0.67,

(3)

ξ = [λ ÷ EW] × EM, kcal/day,

(4)

λ = [(−19.70 + 1.810 × EW), kcal, obtained from [35].

Based on the energy partition, the expected FI (eFI₂) was calculated according to model 2:

eFI₂ = [τ + ξ]/ME_n, g/day,

(5)

The expected metabolizable energy intake (eMEI), was calculated as follows:

eMEI = τ + ξ, kcal/day,

(6)

RMEI = aMEI − eMEI, kcal/day,

(7)

The eFI₂ was used to calculate RFI₂, considering the energy partition.

The RMEI was obtained as follows: RMEI = aMEI − eMEI, where aMEI and eMEI were previously defined. The standard deviation (sd or σ) of the RMEI (sdRMEI) was calculated for each hen and used to interpret the homogeneity of individuals in relation to the group mean. Individuals were categorized into three groups: high, medium and low RMEI, using the σ RMEI values, according to the following criteria: high RMEI when the σ RMEI value is >+0.5σ; average RMEI when the σ RMEI value was >−0.5σ and <+0.5σ; and low RMEI when the σ RMEI value is <−0.5σ.

2.10. Analysis Statistics

All biometric, performance, and egg quality measurements were conducted by the same trained operator to minimize observer-related variability. When additional assistance was required, a trained team followed standardized laboratory protocols to ensure procedural consistency. The performance variables, egg quality, body composition, and biometrics were analyzed for the assumptions of homoscedasticity of variance and normality of errors. Then, the variances were analyzed using the F test and, when the null hypothesis was rejected, multiple linear regression analysis. was applied. First, regression analysis was specifically applied for the estimation of residual feed intake (RFI), using BW^0.67, EM, and WG as independent variables to predict expected feed intake, as described in the RFI model (method 1). The averages of RFI, RMEI and their respective standard deviations sdRFI and sdRMEI, were calculated for each method. The traditional method was based on FI (method 1, and the second method was obtained via energy partitioning (method 2), in which FI is an estimate based on the energy requirement and energy concentration in the diet. Thus, RFI₁, RMEI₁, σRFI₁ and σRMEI₁ were obtained by method 1 and RFI₂, RMEI₂, sdRFI₂ and sdRMEI₂ were obtained by method 2. These variables were subjected to ANOVA and absolute and cumulative frequency analysis, based on the low, medium and high RFI groups obtained by each method. The level of statistical significance was defined as α = 0.05. Differences were considered significant at p < 0.05, and trends were discussed when 0.05 ≤ p ≤ 0.10, when applicable. All statistical analyses were performed using SAS software (SAS Institute Inc., Cary, NC, USA, 2014, version 9.4).

3. Results

3.1. Performance, Egg Quality, Biometry, and Body Composition

The results obtained for performance are presented in

Table 1. Results to related to the performance of white and brown hens, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
Diet MEn, kcal/kg	2.749	2.778	2.763	0.009	29	1.65	0.090
Actual feed intake, g/day	114.5	114.0	114.3	4.4	28	3.86	0.779
Egg production, %	94.5	93.3	93.88	4.39	28	4.68	0.465
Egg weight, g	66.0 a	61.3 b	63.7	4.1	29	6.45	0.004
Egg mass, g/day	62.4 a	57.1 b	59.8	4.2	28	6.98	0.002
Feed conversion ratio, g/g	1.847 b	2.020 a	1.931	0.153	28	7.94	0.005
Feed efficiency, g/kg	546 a	496 b	521	41	28	7.94	0.003
Daily weight gain, g/day	1.30	2.06	1.69	1.42	29	84.52	0.156
Body weight, kg	1.675 b	1.842 a	1.759	0.060	29	3.44	0.001

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

. The main characteristics related to RFI did not differ between the genotypes p > 0.05. Therefore, white and brown hens presented similar overall values for aFI, determined ME_n, EP, and WG (Table 1). The other variables differed (p < 0.01), especially BW, EW, and EM (Table 1). Measures related to utilization efficiency (FCR and FE) differed significantly between genotypes (p < 0.01).

The egg quality variables are presented in

Table 2. Mean of the egg quality in white and brown hens, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
Yolk weight, g	17.9 a	15.8 b	16.8	1.2	29	6.67	0.001
Shell weight, g	6.4 a	5.9 b	6.2	0.5	29	7.58	0.016
Egg shell thickness, μm	398.8	389.9	394.3	20.1	29	5.09	0.236
Albumen weight, g	48.3	45.5	46.9	4.4	29	9.35	0.094
Height albumen, mm	8.5	8.6	8.5	1.1	29	13.2	0.649
Haugh unity, %	92.7	94.8	93.8	1.1	29	6.30	0.338

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

. There was a significant effect (p < 0.05) between the genotypes only for yolk weight and shell weight, which are directly related to EW. The other variables related to albumen, weight, height, Haugh unit, and eggshell thickness did not differ. The average difference in body weight between the genotypes was 167 g. Based on this result, differences in biometrics between the genotypes were expected. However, a significant effect (p < 0.05) was recorded specifically for some viscera, such as the heart, duodenum, jejunum, and cecal handles, favoring brown hens. Regarding the uterus + vagina segment, brown hens presented greater segment weight (p ≤ 0.05), whereas white hens showed greater segment length (p ≤ 0.05) (

Table 3. Biometry (g and cm) of visceral organs, in white and brown hens, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
Weight, g
Heart	7.0 b	8.2 a	7.6	1.2	29	15.5	0.012
Liver	35.4	36.0	35.7	6.2	29	17.4	0.779
Oviduct	67.1	66.2	66.6	7.4	29	11.2	0.732
Magnum + Isthmus	36.3	33.8	35.0	5.1	29	14.6	0.193
Uterus + Vagina	30.8	32.4	31.6	4.2	29	13.2	0.318
Reproductive System	134.2	132.3	133.2	14.9	29	11.2	0.733
Duodenum	11.1 b	14.0 a	12.6	1.9	29	15.3	0.001
Jejunum	26.2 b	31.9 a	29.1	4.9	29	16.9	0.004
Ileum	4.7	5.0	4.9	1.0	29	21.5	0.310
Digestive System	42.0 b	51.0 b	46.5	6.3	29	13.6	0.001
Pancreas	3.2	3.5	3.4	0.6	29	18.9	0.165
Cecal Handles	12.3 b	15.7 a	14.0	2.7	29	19.4	0.002
Length, cm
Oviduct	71.9	69.8	70.9	5.9	29	8.4	0.343
Magnum + Isthmus + Infundibulum	47.4	47.6	47.5	4.9	29	10.4	0.907
Uterus + Vagina	24.5 a	22.2 b	23.4	2.4	29	10.3	0.014
Intestine (Digestive System)	132.3	138.6	135.5	14.5	29	10.7	0.249
Duodenum	22.6	24.2	23.4	2.9	29	12.4	0.138
Jejunum	93.7	98.7	96.2	12.4	29	12.7	0.279
Ileum	16.0	15.7	15.9	1.8	29	11.4	0.616
Cecal Handles	26.4	26.1	26.3	2.7	29	10.2	0.712

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

). These results indicate morphological differences between genotypes in this reproductive tract segment.

The body composition of the layers was evaluated at 84 and 90 weeks of age. The values of protein, fat, water, and minerals content were significantly different (p < 0.05) between the genotypes (

Table 4. Initial (i—84 weeks old) and final (f—90 weeks old) weight for protein, fat, water and minerals and gain or change in body composition (g/day) in white and brown hens, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
iProtein, g/hen	248.1 b	275.9 a	262.0	12.8	29	4.9	<0.001
fProtein, g/hen	263.3 b	294.8 a	279.0	15.1	29	5.4	<0.001
Change in body composition	0.5	0.7	0.6	0.54	29	89.5	0.5161
iFat, g/hen	176.6 b	217.8 a	197.2	34.8	29	17.6	0.003
fFat, g/hen	196.3 b	246.1 a	221.2	30.4	29	13.7	<0.001
Change in body composition	0.7	1.1	0.8	0.7	29	89.5	0.280
iWater, g/hen	843.3 b	940.8 a	892.1	38.5	29	4.3	<0.001
fWater, g/hen	889.3 b	1004.3 a	946.8	31.2	29	3.2	<0.001
Change in body composition	1.6	2.3	1.95	1.1	29	56.8	0.134
iAsh, g/hen	51.2 b	57.4 a	54.3	2.7	29	5.1	<0.001
fAsh, g/hen	51.1 b	59.3 a	55.2	2.8	29	5.1	<0.001
Change in body composition	−0.004	0.07	0.03	0.11	29	355.2	0.094

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

), while the mean values of change in body weight varied; random error was responsible for the results obtained (p > 0.05) (Table 4).

3.2. Energy Partition

The energy partition results are presented in

Table 5. Mean of the actual energy metabolizable intake (aMEI, kcal/day), gross energy whole eggs (kcal/g), deposition (kcal), maintenance (kcal/kg^0.67), utilization efficiency for egg and utilization efficiency total, in white and brown hens, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
aMEI	314.9	319.0	316.9	2.6	29	4.39	0.427
Gross energy whole eggs	1.511 a	1.487 b	1.499	0.004	29	1.38	0.005
Deposition	94.3 a	84.9 b	89.7	1.6	29	8.05	0.002
Maintenance	156.1	155.8	155.9	2.0	29	7.05	0.942
Utilization efficiency for egg	0.301 a	0.266 b	0.558	0.009	29	6.17	0.001
Utilization efficiency total	0.796 a	0.754 b	0.776	0.005	29	1.79	0.001

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

. The aMEI and maintenance partition values did not differ between white and brown hens. The gross energy whole eggs and deposition values are related to the respective EW and EM values of the genotypes and differ significantly (p < 0.01). The results for partial (egg energy deposition) and total utilization efficiency differed between genotypes, as expected, since aMEI was similar between genotypes and the deposition differed significantly (Table 5).

3.3. Residual Feed Intake and Residual Energy Metabolizable Intake

To adjust the parameters of the equation, the intercept was removed and the model obtained was as follows: eFI = 60.3 * (±6.05) × BW^0.67 +1.08^NS (±0.7) × WG + 0.42 ** (±0.14) × EM ± 4.08 g/day, R² = 0.998.

The parameters BW^0.67 (* p < 0.05) and EM (** p < 0.01) were significant in the model, while the contribution of WG was non-significant (NS). Therefore, WG was removed from the equation, and the parameters for BW^0.67 and EM were readjusted, obtaining the following model: eFI₁ = 62.1 ** (±6.09) × BW^0.67 + 0.40 * (±0.14) × EM ± 4.19 g/day, R² = 0.998. The adjusted parameters for BW^0.67 (** p < 0.05) and EM (* p < 0.01) were significant, without relevant changes in the adjustment statistics.

This model was used to obtain RFI₁ (aFI − eFI1) and RMEI₁ was obtained by multiplying RFI₁ × Diet ME_n. The results obtained for this method of calculation (method 1) are presented in

Table 6. Mean of the estimated daily feed intake (eFI₁ and eFI₂), residual feed intake (RFI₁ and RFI₂), and residual energy metabolizable intake (RMEI₁ and RMI₂), obtained by two methods to hens white and brown, from 85 to 90 weeks old.

Variables	White	Brown	Mean	SEM	DF	CV	p-Value
Method 1—Considering the traditional method
eFI1, g/hen	112.7 a	116.2 b	114.4	0.6	29	2.55	0.003
RFI1, g/hen	1.8	−1.2	0.3	0.9	29	1311.3	0.085
RMEI1 kcal/hen	5.1	−3.4	1.0	2.4	29	1293.4	0.081
Method 2—Considering the energy partition
eFI2, g/hen	91.1 a	86.7 b	89.0	0.7	29	3.27	0.004
RFI2, g/hen	23.4 b	28.2 a	25.8	0.6	29	8.76	0.001
RMEI2, kcal/hen	64.5 b	78.4 a	71.2	1.8	29	9.24	0.001

SEM, standard error of the mean; DF, degree of freedom; CV, coefficient of variation. ^a,b Means within a row followed by different lowercase letters differ significantly according to the F test at p < 0.05.

and indicate that only eFI₁ was significantly different between genotypes (p < 0.01), while RFI₁ and RMEI₁ were similar between genotypes (p-Value = 0.085).

The values obtained for eFI₂, RFI₂, and RMEI₂, using the energy partition calculations by method 2, presented in Table 6, indicated significant differences (p < 0.01) between the genotypes, with white hens having lower RFI₂ and RMEI₂ values. White hens, therefore, were more efficient in the use of feed and energy intake.

The equations to relate total utilization efficiency (k_t) and RFI₂ were adjusted for both genotypes (k_t = 0.96 − 0.007 × RFI₂, R² = 0.93), for white hens (k_t = 0.94 − 0.006 × RFI₂, R² = 0.92), and brown hens (k_t = 0.90 − 0.005 × RFI₂, R² = 0.78). The adjusted models indicated a negative relationship between k_t and RFI₂, with the maximum value of utilization efficiency being close to 94% and 90% for white and brown hens, respectively, for a scenario with RFI₂ = 0.

Table 7. Frequency of the absolute and cumulative of the within-animal variation in residual feed intake (sdRFI) obtained by two methods to white and brown hens, from 85 to 90 weeks old.

sdRFI	White			Brown
	Absolute	Absolute %	Cumulative %	Absolute	Absolute %	Cumulative %
Method 1—Considering the traditional method
1 High	7	46.7	46.7	1	7.1	7.1
2 Low	2	13.3	60.0	6	42.9	50.0
3 Medium	6	40.0	100.0	7	50.0	100.0
Method 2—Considering the energy partition
High	1	6.7	6.7	9	64.3	64.3
Low	8	53.3	60.0	0	0
Medium	6	40.0	100	5	35.7	100.0

¹ High residual feed intake; ² Low residual feed intake; ³ Medium residual feed intake.

shows the frequency of individuals with high, low, and medium RFI classified by two methods, RFI₁ and RFI₂, and the respective sdRFI₁ and sdRFI₂ for white and brown hens. The methods must be considered when defining the RFI. While the first method classified 86.7% of the white hens as high and medium RFI, for brown hens, only 57.1% were classified in this way. There was, therefore, a biased interpretation according to all the others results obtained. In the classification obtained with the second method, using RFI₂ and sdRFI₂, approximately 46.7% of the white hens were classified as high and medium RFI, and 53.3% presented as low RFI, while the brown hen category did not present hens with a low RFI and 64.3% of the individual hens were classified as high RFI.

4. Discussion

This study evaluated residual feed intake (RFI) and residual metabolizable energy intake (RMEI) in two commercial layer genotypes (white and brown) at an advanced production stage (85–90 weeks). The results obtained allowed us to understand some differences between white and brown birds that have a relevant position in the housing of commercial laying hens. Under individual housing and a controlled environment, white and brown hens showed similar daily feed intake and egg production; however, white hens produced heavier eggs and a higher egg mass, leading to superior feed conversion and feed efficiency. These results (Table 1) reinforce the idea that, when intake and egg production are similar, relatively small differences in egg weight and egg mass become major drivers of apparent feed efficiency and energy utilization.

This result allowed us to accurately measure the conversion between input (feed) and output (egg mass), especially since the first publications [19,36] attributed part of the variability between individuals and the results obtained in this research support this hypothesis. Despite the similarity in egg production between genotypes, the egg weight of white layers was 4.7 g higher, increasing the difference to 5.3 g when calculating egg mass. In this research, egg weight was considered as the main characteristic responsible for the difference in egg mass, which in turn affected other variables associated with the efficiency of utilization of nutritional resources (Table 1). White hens showed a reduction of 50 g of feed intake per kilogram of egg mass produced compared with that of brown hens (p ≤ 0.05).

The heavier eggs produced by white hens directly increased egg mass output and egg energy deposition, improving conversion metrics without requiring higher intake. Previous studies [21] that directly compared genotypes under the same objective, environment, and diet also found consistent responses in the efficiency of utilization in hens. In extended laying cycles, even small differences in egg mass accumulate into meaningful differences in total output and margin, because feed remains the dominant variable cost of production. A key practical implication is that efficiency comparisons between genotypes in late layers should emphasize egg mass and egg energy output, rather than just the egg production. Industry and scientific discussions on long-cycle hens consistently highlight that sustaining egg mass and shell quality to 90–100+ weeks is central to profitability and sustainability.

The difference in daily weight gain of −0.76 g/day per hen was not significant due to the high coefficient of variation. In part, the variability in body weight can be attributed to the presence, or lack, of the egg in the reproductive tract at the time of weighing, since a fasting period of 5 h was defined before weighing to mitigate the influence of residue feed in the digestive tract. According to research carried out, brown birds anticipate oviposition by 1 h to 2 h compared to genotypes that produce eggs with white shells [37,38,39].

However, non-observance to observe the individual’s characteristics in oviposition may have contributed to this variation, since weighing followed the principle of randomization. Therefore, we believe that studies with individuals should maintain the sequence of weighing hens at the beginning and end of the test, especially when involving genotypes with specific characteristics at the time of oviposition, so that possible variations from this cause can be mitigated. This limitation makes any inference about the effects found for body weight at the end of the trial impossible (Table 1). The weight of chemical components (Table 4: fprotein, ffat, and fwater), when related to the measurement at the beginning of the test, suggests the occurrence of a gain or change in body weight; however, as reported, the coefficient of variation limits exploring any hypothesis related to the protein, fat, and water components.

Ash (iAsh and fAsh) presented the highest coefficient of variation (Table 4) and can add to the arguments about the presence or absence of the egg at the time of weighing and body composition analysis, since the gain composition is, mostly, in water, fat, and protein, with ash being an insignificant part. When considering the difference between fAsh and iAsh, there was no change in the hens’ body weight.

Measurements of weight and size of the viscera should follow in proportion to the body (Table 3). In this sense, the weight of the heart, digestive system (duodenum and jejunum), and cecal handles were consistent with this premise and presented differences in the genotype (p < 0.05) favoring brown layers (Table 3), while other viscera did not differ in weight. For example, liver from white layers corresponded to 2.11% concerning their body weight, while that of brown layers was close to 1.95%—8% smaller than that of white layers.

Therefore, although the weight of the livers did not differ, the proportions concerning the body were significantly different (p = 0.046), which is considered relevant and related to the demand for the synthesis of egg components, and which registered a greater weight for white layers. The liver has a significant role in the lipid metabolism of birds [40,41] and increases its proportion within the body during sexual maturation [42,43] for the synthesis of egg yolk components [40,41]. Another result obtained in biometrics that demonstrates the relevance of egg weight was the length of the uterus + vagina of white layers (Table 3), which was approximately 2 cm greater (p < 0.05), while the proportion in relation to the body was greater—1.84% versus 1.76%—but not significant (p = 0.315).

Although brown hens had larger digestive segments (duodenum and jejunum), which may suggest greater digestive capacity, this did not translate into superior feed or energy efficiency in the present conditions. This indicates that post-absorptive metabolic efficiency and energy partitioning likely played a larger role than digestive capacity alone in determining net efficiency differences. Conversely, white hens showed a higher proportional liver size and longer uterus + vagina length. These findings are physiologically consistent with their higher egg output in terms of egg weight and energy deposition, because hepatic lipid metabolism is central to yolk precursor synthesis (e.g., VLDL and vitellogenin production) and represents a major metabolic investment during laying [44]. Importantly, liver function and oxidative status may change with age, potentially affecting yolk precursor formation and thereby influencing egg size and consistency in late laying [45]. Therefore, the larger relative liver in white hens may reflect either (i) greater capacity for yolk precursor synthesis; (ii) different lipid metabolic regulation; or (iii) different physiological strategies for sustaining egg mass late in the cycle.

Overall, the biometric results highlight the importance of evaluating organs proportionally to body weight when comparing genotypes. Although brown hens had larger digestive segments, this did not translate into superior efficiency, indicating that digestive capacity alone did not explain the differences observed. In contrast, white hens showed a greater proportional liver size and longer uterus + vagina length, traits consistent with their higher egg weight and energy deposition. Thus, the evaluation of metabolic and reproductive organs was essential to biologically interpret genotype differences, suggesting that post-absorptive metabolic allocation, rather than digestive size, played a central role in efficiency divergence during late laying.

The variables in yolk and eggshell weight (Table 2) are directly related to egg weight and were different between genotypes, while others, such as eggshell thickness, albumen height, and Haugh unity, did not differ between genotypes. It was expected that the albumen weight would follow the proportionality of the egg weight and that, therefore, it would be different between the genotypes. However, the probability value found (p = 0.094) showed uncertainty regarding the main effect, genotype, due to the process of albumen removal, which depends on the integrity of the membranes and can generate loss of content and add variability to the sampled values.

The values of current metabolizable energy intake (Table 5) were obtained by the relationship between daily feed intake and diet ME_n concentration; none of these variables differed (p > 0.05) between the genotypes. However, the correlation between the variables in the database showed that the values obtained in diet ME_n determined with white layers were positively correlated with daily feed intake (0.65%; p = 0.009), current metabolizable energy intake (0.78%; p = 0.006), and ileum (0.62%; p = 0.014). For brown layers, the values obtained for diet ME_n did not show significance for correlation with these variables (daily feed intake, actual energy metabolizable intake and ileum). A hypothesis to justify this may be related to the greater digestive capacity. As shown in Table 3, the duodenum and jejunum differed significantly (p < 0.05), favoring brown layers with greater use of dietary energy, at approximately 29 kcal/kg (Table 1), indicating a trend of effect (p = 0.090).

The results obtained for gross energy for whole eggs reinforce the findings of Sibbald [35], which show that the variation in gross energy of the egg is directly related to the weight of the egg (Table 5). Energy deposition in the egg (Table 5) was calculated by relating the gross energy of whole eggs and the egg mass produced. For this, Sibbald’s equation [35] was modified (GrossEnergyWholeEggs kcal/g = [−19.70 + 1.810 × EggWeight]/EggWeight) to obtain the values in kcal/g and to allow for the use of egg mass as an input variable.

The relationship between egg gross energy and egg weight is well established, supporting the use of egg energy deposition as a meaningful biological output when comparing efficiency [44]. Thus, a difference (p < 0.05) close to 10% in energy deposition in the egg was found favoring white layers. The energy partition for daily weight gain was not considered due to variability, as mentioned above. The partition of energy ingested for maintenance (Table 5) did not differ between genotypes (p > 0.05), with 156 kcal/kg^0.67 being used to maintain metabolic weight.

This value was higher than the average maintenance requirement presented in the publication by Luiting [46], which was close to 120 kg/kg^0.67, varying between 102–143 kg/kg^0.67. Therefore, we believe that there was energy deposition in the body, but the variability did not allow us to isolate the effect of body deposition. Therefore, the value found of 156 kcal/kg^0.67 has some contribution, especially in the form of lipids in the body. The maintenance value observed in this study was higher than classical reports [30] for adult hens, which may reflect age-related changes in metabolic costs and body composition dynamics (e.g., lipid turnover) that become more relevant after 80 weeks. Studies in “long-life” hens likewise emphasize that energy requirements and nutrient supply strategies need re-optimization in extended cycles, as the balance between production, maintenance, and body reserves changes with age [20].

The RFI obtained by method 2 was consistent in the segregation of individuals (Table 6). The methods must be considered when defining the RFI. While the first method classified 86.7% of the white hens as high and medium RFI, for brown hens, only 57.1% were classified in this way. Therefore, this was a biased interpretation according to all the other results obtained. For the classification (Table 7) obtained with the second method, using RFI₂ and sdRFI₂, approximately 46.7% of the white hens were classified as high and medium RFI and 53.3% presented as low RFI. The brown hen category did not present birds with a low RFI, and 64.3% of individuals were classified as high RFI.

A central contribution of this work is the demonstration that the traditional regression approach (method 1) did not clearly separate genotypes, whereas the energy partition approach (method 2) yielded biologically coherent differences in RFI₂ and RMEI₂, classifying a higher proportion of white hens as low-RFI and most brown hens as high-RFI. Conceptually, this is expected when the underlying biology changes with age: aged laying hens (85–90 weeks) may exhibit altered maintenance costs, shifts in nutrient partitioning, and changes in body lipid turnover, all of which are imperfectly captured by a purely regression-based prediction using BW^0.67, WG, and EM. In contrast, partition models explicitly allocate metabolizable energy to maintenance and production, which aligns more directly with physiological energy sinks and enables RMEI to reflect “true” deviations in energy use.

Recent work in aged laying hens in the late production phase supports this interpretation by showing that RFI divergence is associated with measurable differences in metabolic status and physiological regulation, indicating that RFI captures more than simple intake–output relationships [4]. In addition, broader poultry studies in the literature emphasize that RFI is influenced by multiple biological components, such as digestive efficiency, basal metabolism, physical activity, body composition dynamics, and metabolic efficiency, whose relative importance can vary by life stage [3].

The utilization efficiency values for energy deposition in the egg and in the total differed between genotypes (p < 0.05), with white layers being 12% more efficient in using energy for egg production. When considering total efficiency, the difference between white and brown hens was reduced to 5.3% (Table 5). The partial (egg deposition) and total efficiency values are supported by previous findings [46,47,48]. The equations to relate total utilization efficiency (k_t) and RFI₂ were adjusted for both genotypes (k_t = 0.96 − 0.007 × RFI₂, R² = 0.93) for white hens (k_t = 0.94 − 0.006 × RFI₂, R² = 0.92), and brown hens (k_t = 0.90 − 0.005 × RFI₂, R² = 0.78). The adjusted models indicated a negative relationship between k_t and RFI₂, with the maximum value of efficiency of utilization close to 94% and 90% for white hens and brown hens, respectively, for a scenario with RFI₂ = 0. The differences revealed in this research between white and brown hens are smaller than in the past and show a tendency towards similarity; however, the economic impacts of the current differences are significant and must be considered.

Future studies aiming to partition energy into egg vs. body deposition in late laying-phase hens may benefit from tighter control of weighing relative to oviposition or repeated BW measures to reduce random error. Nonetheless, because the genotype differences in RFI₂/RMEI₂ were robust and consistent with egg energy deposition differences, the conclusions regarding energy-partition efficiency are supported. Even though genetic and management advances have narrowed the performance gap between white and brown commercial layers, the remaining differences in egg mass and energy utilization can be economically relevant when extrapolated to long cycles. From a breeding and management perspective, this study supports the use of RFI, especially energy-partition derived indices (RFI₂/RMEI₂), as practical tools with which to identify more efficient individuals and genotypes in late laying-phase production. This aligns with recent reviews emphasizing RFI as a criterion that can reduce feed costs and the environmental footprint when incorporated into selection and decision-making frameworks.

5. Conclusions

The study demonstrated that residual feed intake and residual metabolizable energy intake, particularly when estimated using energy partition models, are reliable indicators of feed and energy efficiency in laying hens at 85–90 weeks of age. Although white and brown hens showed similar feed intake and egg production, white layers produced heavier eggs, greater egg mass, and higher egg energy deposition, resulting in better feed conversion and more efficient use of metabolizable energy. The traditional regression method did not clearly differentiate genotypes, whereas the energy partition approach revealed lower RFI and RMEI values in white hens, indicating superior biological efficiency. Differences in visceral measurements, body composition, and reproductive tract size supported these results. Despite reduced genetic gaps compared with previous studies, the remaining differences remain economically important in extended laying cycles, supporting the inclusion of efficiency traits in selection programs.