The Impact of Different Environments on Productive Performance, Welfare, and the Health of Muscovy Ducks during the Summer Season

Abstract

The objective of this research was to evaluate the influence of the housing system (deep litter [DL] vs. deep litter with swimming pond [DLSP]) on productive performance, carcass traits, body temperature, blood profile, and the element composition of the femur and tibia in Muscovy ducks. At 5 weeks of age, sexed ducklings (264) were divided into 4 equal groups according to housing system and gender (drakes vs. ducks). The groups were as follows: 66 drakes/DL, 66 drakes/DLSP, 66 ducks/DL, and 66 ducks/DLSP. Each of the four groups was divided into three identical replicated subgroups of 22 animals. Regarding external body temperature, the DL birds had higher temperatures compared with the DLSP birds. In addition, drakes had lower temperature values than ducks. Regarding the blood analysis, the birds did not manifest any deviations in the biochemical traits of the blood. The DLSP birds had greater live weight, weight gain, and feed conversion ratio, but a lower proportion of breast meat than the DL birds. The housing conditions did not affect the fracture toughness of the tibia and femur of the birds; however, Muscovy ducks from the DLSP group had more Ca and Mg in the tibia and more Mg in the femur compared with the DL birds.

1. Introduction

Waterfowl rearing, including ducks, plays a significant role in global poultry meat production. The production of duck meat has been steadily increasing worldwide since 2000 [1]. In 2020, the total global production of duck meat reached 4,997,577 tons [2]. Among the various duck breeds, Pekin ducks are the most predominant, followed by Muscovy and Mule ducks [1]. Despite the overall growth in production, there are substantial variations in housing systems, particularly in terms of housing conditions. These discrepancies can be attributed in part to the specific requirements of different duck breeds. Housing systems range from indoor conventional setups to free-range systems [3]. The housing conditions significantly impact animal welfare and, consequently, production performance, along with other relevant parameters [4,5].

The scientific community [6,7,8,9] frequently emphasizes the evaluation of animal welfare with respect to housing conditions, and in the case of waterfowl, the provision of open water areas has shown potential for improvement. Housing systems that incorporate open water areas allow ducks to engage in species-specific behaviors such as swimming, bathing, and head-dipping [3]. Access to open water is also crucial for thermoregulation and maintaining feather hygiene. Ducks require the ability to dip their heads and splash water on their feathers to ensure proper cleanliness [6]. The thermoneutral range for ducks is typically between 7 and 23 °C [8]. When the environmental temperature exceeds this range, it can lead to decreased appetite and reduced feed consumption, ultimately impacting growth rate, body weight, and carcass parameters [10].

Moreover, housing ducks in outdoor systems with access to open water has the potential to positively influence stress levels and enhance bird comfort [6]. Blood parameters serve as reliable indicators of overall health status because any physiological, nutritional, or pathological changes within the organism are reflected in these parameters [11,12]. A study by Kraus et al. [13] investigated the impact of housing systems on biochemical blood parameters, some of which may also be related to stress, in laying hens. Their findings suggested that the housing system is a significant factor influencing biochemical blood parameters.

The intensification of duck farming has reduced production costs but has also raised concerns about the welfare of ducks. To optimize animal well-being while maintaining productive performance, it is crucial to focus on housing conditions [4]. One significant aspect of welfare is bone quality, which has been studied in various animal species, including rabbits [14], laying hens [15], and ducks [8]. Poor bone quality can lead to fractures and osteoporosis, posing a significant challenge in poultry. Housing systems can influence not only fracture toughness but also the mineral composition of bones, which is essential in ensuring bone quality [14,15]. Movement plays a key role in maintaining bone health [16]. However, housing systems with open water access also have some disadvantages. Waterfowl can pose higher health risks, raise concerns about water contamination, and lead to increased manure production [3].

It is known from the literature that ducks spend considerable time in the water and thus have weak legs [3]. Therefore, it is appropriate to monitor the quality of the leg bones of ducks that are fattened under intensive conditions and to possibly optimize their housing. This is a pilot study of Muscovy ducks that seeks to determine the element composition of the tibia and femur in detail in different housing conditions. Apart from the element composition, this study also aims to evaluate productive performance, carcass traits, external body temperature, blood parameters, and bone quality properties of the tibia and femur of ducks reared in different housing conditions. The hypothesis is that housing conditions and the gender of Muscovy ducks will influence their productive performance, carcass traits, body temperature, bone quality, and blood profile. The study follows on from a previous study by Krunt et al. [8], aiming to evaluate the issue in greater detail with regard to meat production in the same housing conditions.

2. Materials and Methods

2.1. Animals and Housing

This study included 264 Muscovy ducks in total. Ducklings were sexed after hatching and were then housed in deep litter in controlled conditions and fed ad libitum (20.5% CP and 12.2 MJ·kg⁻¹ ME). At the age of 5 weeks, they were divided into 4 equal groups according to housing system (deep litter [DL] vs. deep litter with swimming pond [DLSP]) and gender (drakes vs. ducks). The groups were as follows: 66 drakes/DL, 66 drakes/DLSP, 66 ducks/DL, and 66 ducks/DLSP. Each of the four groups was divided into three identical subgroups of 22 animals because of the replication of observations. DL housing systems in closed-sided houses (all animals were protected by the roof of the house against bad weather to keep the housing clean and dry) and DLSP in open-sided houses were used as housing systems. Animals housed in DLSP groups had free access to a swimming pond (10 m × 6 m × 3 m) for the duration of the study. Moreover, the DLSP housing system included vegetation (trees and bushes) close to the swimming pond, which provided much-needed shade. The area around the pond was covered with gravel to prevent vegetation from being eaten, which would affect feed intake and productive parameters. The environmental conditions of the housing were natural (temperature, lighting) and identical in both housing systems. Regarding the temperature, the average measured value (mean day and night) during the study was 19.03 °C (max. 37.7 °C; min. 7 °C; rh. 65%), while lighting consisted of 16 h of light and 8 h of darkness on average. As bedding, wheat straw was used in both housing systems. A density of 4 animals per m² was maintained in all groups. The study took place in summer, specifically from June 2022 to August 2022.

2.2. Feeding and Water Access

All groups were fed ad libitum with commercial feed mixture for ducks (pelleted) that contained 20% CP and 11.2 MJ·kg⁻¹ of metabolizable energy (ME), 9 g·kg⁻¹ Ca, 4 g·kg⁻¹ P, 0.6 g·kg⁻¹ Mg, 6.5 g·kg⁻¹ K, 1.6 g·kg⁻¹ Na, 1.2 g·kg⁻¹ Cl, 80 mg·kg⁻¹ Mn, 80 mg·kg⁻¹ Zn, 70 mg·kg⁻¹ Fe, 6 mg·kg⁻¹ Cu, 1.1 mg·kg⁻¹ I, and 0.15 mg·kg⁻¹ Se. Access to fresh water was also unlimited in all groups and replications. In the housing systems that included a swimming pond, fresh water was supplied via channels.

2.3. Body Temperature Analysis

The body temperature analysis consisted of the measurement of external body temperature. Body temperature measurements were taken from 12 randomly selected animals in each replication (36 animals per gender and housing system, 144 animals in total). An assessment of body temperature was made every week, on the same day (Monday) at the same time (between 12:00 and 12:30) from the age of 5 weeks until slaughter (13 weeks of age).

External body temperature was measured using a thermographic camera (Bosch, GTC 400 C Professional, Stuttgart, Germany) at the core of the body, where the temperature was the highest (Figure 1). Three images of each animal were obtained, and the average value was used for further evaluation. Each animal was handled for less than 1.5 min. All birds were treated gently to avoid disrupting their well-being.

2.4. Biochemical Blood Analysis

Biochemical blood analysis included assessment of albumin (ALB), globulin (GLOB), alanine transaminase (ALT), amylase (AMY), aspartate aminotransferase (AST), total cholesterol (CHOL), gamma-glutamyl transferase (GGT), glucose (GLU), glutamate pyruvate transaminase (GPT), triglycerides (TAG), total proteins (TP), creatinine (CR), and urea (U). Moreover, the following elements were examined in the blood serum: calcium (Ca), chlorine (Cl), magnesium (Mg), phosphorus (P), sodium (Na), and potassium (K).

At the age of 13 weeks, all the animals were slaughtered by jugular venesection. Blood samples were taken from 12 animals (randomly chosen) from each replication and each group. The blood for biochemical analysis was collected in empty sterile tubes. In total, 144 tubes were collected for biochemical analysis (36 tubes were collected per housing system and gender). After the collection, blood samples were centrifuged and the obtained serum was stored at −20 °C until the analysis. The evaluation of biochemical traits was made using commercial kits (Erba Lachema, s.r.o., Brno, Czech Republic) on the automatic analyzer XL-200 (Erba Lachema s.r.o., Brno, Czech Republic) at the Department of Veterinary Sciences of the Faculty of Agrobiology, Food, and Natural Resources at the Czech University of Life Sciences Prague.

2.5. Productive Performance and Carcass Traits

The examined productive traits consisted of live weight, average daily weight gain, average daily feed consumption, and feed conversion ratio. The birds’ weight was recorded weekly when every bird was weighed individually, and their feed consumption was noted every day per group and per replication. The fifth week of age was counted as the start of the experiment while the end was 13 weeks of age. Health status was monitored. No animals died during the experiment.

After slaughter, 8 birds per experimental group and per replication (96 birds in total) were randomly selected for carcass analysis. Carcass dissection was conducted according to [17], where SW was slaughter weight, SEW (semi-eviscerated weight) was the manually eviscerated carcass, calculated as carcass weight after removal of the trachea, esophagus, gastrointestinal tract, crop, spleen, pancreas, gallbladder, and gonads. EW (eviscerated weight) was calculated as the SEW after removing the head, feet, heart, liver, gizzard, glandular stomach, and abdominal fat. The DoP (dressing out percentage) was calculated as the SEW divided by SW × 100. The AF (abdominal fat) was measured as a proportion of the SEW. The breast, thigh, and wing yields were calculated as a percentage of EW.

2.6. Bone Quality and Element Composition Analysis

The bone quality analysis involved determining bone weight, length, width, and breaking strength. From a chemical point of view, dry matter, ash, and selected elements, including boron (B), calcium (Ca), cadmium (Cd), cobalt (Co), chrome (Cr), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), sodium (Na), nickel (Ni), phosphorus (P), lead (Pb), sulfur (S), vanadium (V), and zinc (Zn), were assessed. The tibia and femur bones were used for the bone quality and element composition analysis. At the age of 13 weeks, all the animals were slaughtered by jugular venesection. Before slaughter, a 12 h fasting period was applied. Bones were taken from 6 animals from each replication (randomly chosen) and each group, from the right leg. In total, 72 tibia bones and 72 femur bones were used for the analysis.

After slaughter, the bones were de-fleshed without boiling, afterward individually packed into plastic bags, sealed, and frozen at a temperature of −20 °C in the freezer until the beginning of the analysis. Before the analysis, the bones were taken out of the freezer, thawed for 24 h, and cleaned again of all excess tissue. Length and width were measured using an electronic sliding caliper (DIN 862; IP54; Shut Geometrical Metrology; Gröningen, The Netherlands) with 0.01 mm precision. The measurements were made in the middle of the bones, and each bone was measured three times. Fracture toughness was determined using the Instron device (Instron Universal Testing Machine; model 3342; Instron Ltd., Norwood, MA, USA), which calculates the required force (in N) to break the bone. The analysis involved a 50-kg-load cell at a 50-kg-load range with a crosshead speed of 50 mm·min⁻¹ with bone supported on a 3.35-cm span, according to [18].

Chemical analysis (dry matter, ash, and element composition) was performed as follows: the dry matter content of bones was determined by drying the samples in the oven at a temperature of 105 °C for 24 h. After drying, the bones were weighed on the Ohaus (Model: Traveler TA502, Parsippany, NJ, USA) digital laboratory scale with 0.01 g precision to calculate dry matter content. The ash content was determined by burning the samples in the oven at a temperature of 550 °C. The ashed samples were subsequently treated with concentrated HCl and HNO₃ acids and the determination of element composition was analyzed using the ICP-OES iCAP 7000 (Thermo Fisher Scientific, Waltham, MA, USA). The limit of detection (LD) was calculated using the equation: LD = 3.29 σ0 (where σ0 is a blank sample standard deviation). The samples and standards were matrix matched. Several procedural blanks were included throughout the analysis.

The bone quality analysis was conducted in the laboratory of the Department of Animal Science of the Faculty of Agrobiology, Food, and Natural Resources at the Czech University of Life Sciences Prague. The chemical analysis (dry matter, ash, and element composition) was conducted in the laboratory of the Department of Soil Science and Soil Protection of the Faculty of Agrobiology, Food, and Natural Resources at the Czech University of Life Sciences Prague.

2.7. Statistical Analysis

The effect of gender and housing system was assessed using a mixed model and the MIXED procedure recommended by SAS (SAS Institute Inc., Cary, NC, USA, 2011):

Y_ijk = µ + HS_i + G_j +(HS × G)_ij + e_ijk,

where Y_ijk is the value of the trait, µ is the overall mean, HS_i is the effect of the housing system (deep litter, deep litter with swimming pond), G_j is the effect of gender (drakes, ducks), (HS × G)_ij is the effect of the interaction between housing system and gender, e_ijk is the random residual error. The significance of the differences among groups was tested using Duncan’s multiple-range test. The value of p ≤ 0.05 was considered significant for all measurements.

3. Results

3.1. Body Temperature

The statistically evaluated results of external body temperature are listed in

Table 1. External body temperature in relation to housing system and gender of 13-week-old Muscovy ducks.

Housing System	Gender	External Body Temperature (°C)
DL 1		36.6 a
DLSP 2		36.1 b
	Drakes	35.9 b
	Ducks	36.8 a
p-Value
Housing system		0.0231
Gender		0.0001
SEM 3		0.019

¹ DL, deep litter; ² DLSP, deep litter with swimming pond; and ³ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

. Figure 1 is an image taken by the thermographic camera to show how external body temperature was measured. Furthermore, since the interactions are superior to the individual effects, the interactions between the housing system and gender are displayed in Figure 2 for external body temperature. The effect of gender and housing system was calculated as significant (p < 0.001; p < 0.05) for external body temperature. Regarding the housing system, the animals with the highest values were those kept on litter compared with animals that had access to the water area. When considering the effect of gender, ducks had a higher temperature than drakes. The interaction between the housing system and gender was statistically significant for external body temperature.

Figure 1. Measurement of external body temperature using a thermographic camera.

Figure 1. Measurement of external body temperature using a thermographic camera.

3.2. Biochemical Blood Composition

In terms of biochemical blood traits (

Table 2. Effect of housing system and gender on biochemical properties and element composition of 13-week-old Muscovy duck blood.

Housing System	Gender	ALB 1 (g·L−1)	GLOB 2 (g·L−1)	ALB/GLOB 3	TP 4 (g·L−1)	Ca 5 (mmol·L−1)	P 6 (mmol·L−1)	Na 7 (mmol·L−1)	K 8 (mmol·L−1)	Mg 9 (mmol·L−1)	Cl 10 (mmol·L−1)
DL 11		15.8	15.9	0.997	32.3	2.95 a	2.37	156.9	3.55	0.884	105.2
DLSP 12		15.8	15.7	1.005	32.2	2.94 b	2.36	156.8	3.54	0.881	105.3
	Drakes	15.8	15.8	0.999	32.2	2.94 b	2.36	156.9	3.53	0.871	105.2
	Ducks	15.8	15.8	1.003	32.3	2.96 a	2.37	156.8	3.56	0.894	105.4
p-Value
Housing system		0.5089	0.1038	0.4980	0.5089	0.0446	0.8310	0.6793	0.6729	0.7836	0.4975
Gender		0.4120	0.8968	0.4079	0.2659	0.0095	0.3563	0.6675	0.3870	0.1040	0.3417
SEM 13		0.040	0.053	0.002	0.081	0.003	0.009	0.115	0.014	0.005	0.107

¹ ALB, albumin; ² GLOB, globulin; ³ ALB/GLOB, albumin/globulin ratio; ⁴ TP, total protein; ⁵ Ca, calcium; ⁶ P, phosphorus; ⁷ Na, sodium; ⁸ K, potassium; ⁹ Mg, magnesium; ¹⁰ Cl, chlorine; ¹¹ DL, deep litter; ¹² DLSP, deep litter with swimming pond; and ¹³ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

and

Table 3. Effect of housing system and gender on biochemical properties of 13-week-old Muscovy duck blood.

Housing System	Gender	CHOL 1 (mmol·L−1)	GLU 2 (mmol·L−1)	CR 3 (µmol·L−1)	U 4 (mmol·L−1)	TAG 5 (mmol·L−1)	AMY 6 (IU·L−1)	AST 7 (IU·L−1)	ALT 8 (IU·L−1)	GPT 9 (IU·L−1)	GGT 10 (IU·L−1)
DL 11		4.51	12.85 a	18.3	1.54	0.921	51.1	52.0	40.8	20.2	2.50
DLSP 12		4.43	12.16 b	18.6	1.49	0.884	52.5	52.2	40.0	19.8	2.47
	Drakes	4.50	12.14 b	18.7 a	1.53	0.883	50.3 b	51.1	40.0	19.7 b	2.46 b
	Ducks	4.44	12.87 a	18.2 b	1.50	0.922	53.3 a	53.1	40.8	20.3 a	2.51 a
p-Value
Housing system		0.0626	0.0466	0.2372	0.4661	0.0780	0.3257	0.8473	0.1265	0.0846	0.2734
Gender		0.1630	0.0388	0.0491	0.6460	0.0688	0.0357	0.0745	0.2659	0.0141	0.0442
SEM 13		0.023	0.180	0.147	0.035	0.011	0.750	0.589	0.269	0.116	0.012

¹ CHOL, cholesterol; ² GLU, glucose; ³ CR, creatinine; ⁴ U, urea; ⁵ TAG, triglycerides; ⁶ AMY, amylase; ⁷ AST, aspartate aminotransferase; ⁸ ALT, alanin aminotransferase; ⁹ GPT, glutamate pyruvate transaminase; ¹⁰ GGT, gama glutamyl transferase; ¹¹ DL, deep litter; ¹² DLSP, deep litter with swimming pond; and ¹³ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

), the housing system was confirmed as significant in concentrations of Ca (p < 0.05) and GLU (p < 0.05), where higher values were found for the DL group compared with the DLSP group. Gender influenced concentrations of Ca (p < 0.05), GLU (p < 0.05), CR (p < 0.05), AMY (p < 0.05), GPT (p < 0.05), and GGT (p < 0.05). Except for CR, higher values were detected in ducks compared with drakes.

3.3. Growth Performance and Carcass Value

The results of productive performance and growth performance are displayed in

Table 4. Effect of housing system and gender on productive performance of 13-week-old Muscovy ducks.

Housing System	Gender	LW5 1 (g)	LW13 2 (g)	ADWG 3 (g)	ADFC 4 (g)	FCR 5
DL 6		1167 a	3874 b	48.34 b	177.59 a	3.79 a
DLSP 7		1114 b	3932 a	50.30 a	172.30 b	3.52 b
	Drakes	1258 a	4851 a	64.16 a	212.07 a	3.31 b
	Ducks	1024 b	2955 b	34.48 b	137.82 b	4.00 a
p-Value
Housing system		0.0004	0.0002	0.0003	0.0024	0.0001
Gender		0.0001	0.0001	0.0001	0.0001	0.0001
SEM 8		36.374	285.910	4.486	11.237	0.113

¹ LW5, live weight at 5 weeks of age; ² LW13, live weight at 13 weeks of age; ³ ADWG, average daily weight gain; ⁴ ADFC, average daily feed consumption; ⁵ FCR, feed conversion ratio; ⁶ DL, deep litter; ⁷ DLSP, deep litter with swimming pond; and ⁸ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

and Figure 3.

Table 5. Effect of housing system and gender on carcass value characteristics of Muscovy ducks at 13 weeks of age.

Housing System	Gender	SW 1 (g)	SEW 2 (g)	EW 3 (g)	DoP 4 (%SEW)	AF 5 (%SEW)	Wings (%EW)	Thighs (%EW)	Breasts (%EW)
DL 6		3742	2810	2407	74.73	0.97 a	17.53	21.55	33.45 a
DLSP 7		3723	2780	2392	74.50	0.75 b	17.33	21.80	32.34 b
	Drakes	4825 a	3644 a	3123 a	75.54 a	0.93	16.95 b	22.02 a	31.85 b
	Ducks	2640 b	1945 b	1675 b	73.68 b	0.78	17.91 a	21.33 b	33.94 a
p-Value
Housing system		0.7330	0.4915	0.7062	0.3915	0.0181	0.4951	0.3653	0.0021
Gender		0.0001	0.0001	0.0001	0.0001	0.1126	0.0017	0.0153	0.0001
SEM 8		123.110	95.647	81.722	0.167	0.047	0.155	0.143	0.216

¹ SW, slaughter weight; ² SEW, semi-eviscerated weight; ³ EW, eviscerated weight; ⁴ DoP, dressing out percentage; ⁵ AF, abdominal fat; ⁶ DL, deep litter; ⁷ DLSP, deep litter with swimming pond; and ⁸ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

shows the results of selected carcass traits. According to the live weight of birds at 5 weeks of age (start of the experiment), the significant differences between the DLSP and DL groups are caused by sexual dimorphism between drakes and ducks because the live weight of the groups was counted as an average. Figure 3 shows that groups were created based on similar weight. Birds from the DLSP group had significantly higher live weight (p < 0.001) at the end of the experimental period, higher average daily weight gain (p < 0.001), lower feed consumption (p < 0.001), and lower feed conversion ratio (p < 0.001). All selected parameters were significantly higher for drakes than for ducks. However, the productive traits differed significantly between the groups, and were not reflected in most of the monitored carcass traits. A higher value (p < 0.05) of the AF proportion from SEW was found in DL birds compared with DLSP birds. In addition, the breast meat was significantly affected by housing conditions (p < 0.05) in the DL birds compared with the DLSP birds. As expected, drakes had a significantly higher SW (p < 0.001), SEW (p < 0.001), and EW (p < 0.001) than ducks. Furthermore, drakes were characterized by higher DoP (p < 0.001) and higher (p < 0.05) thigh proportions compared with ducks. However, ducks had a higher wing (p < 0.001) and breast (p < 0.001) proportion compared with drakes.

3.4. Bone Quality and Element Composition

The results for basic bone quality parameters, including fracture toughness, bone length, width, and weight, are displayed in

Table 6. Effect of housing system and gender on basic tibia properties of 13-week-old Muscovy ducks.

Housing System	Gender	Fracture Toughness (N)	Length (mm)	Width (mm)	Weight (g)
DL 1		383.4	112.1	8.12	11.1
DLSP 2		378.8	113.6	8.10	11.3
	Drakes	482.3 a	124.0 a	9.5 a	15.3 a
	Ducks	278.9 b	102.4 b	7.3 b	7.5 b
p-Value
Housing system		0.3674	0.4672	0.8834	0.6228
Gender		0.0001	0.0001	0.0001	0.0001
SEM 3		17.157	3.235	0.301	0.563

¹ DL, deep litter; ² DLSP, deep litter with swimming pond; and ³ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

for the tibia and in

Table 7. Effect of housing system and gender on basic femur properties of 13-week-old Muscovy ducks.

Housing System	Gender	Fracture Toughness (N)	Length (mm)	Width (mm)	Weight (g)
DL 1		367.3	68.9	9.5	8.5
DLSP 2		359.5	70.4	9.6	8.0
	Drakes	455.2 a	76.0 a	11.1 a	10.2 a
	Ducks	278.0 b	63.5 b	8.7 b	4.9 b
p-Value
Housing system		0.5614	0.2876	0.9554	0.4654
Gender		0.0001	0.0001	0.0001	0.0001
SEM 3		15.878	1.618	0.311	0.583

¹ DL, deep litter; ² DLSP, deep litter with swimming pond; and ³ SEM, standard error of the mean. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

for the femur. Only the effect of gender was statistically significant. Gender significantly affected all evaluated parameters in both the tibia and the femur, with drakes having significantly higher values (p < 0.001) in all evaluated parameters than ducks in both of the observed bones.

The element composition, dry matter, and ash results are shown in detail in

Table 8. Effect of housing system and gender on tibia element composition and chemical attributes of 13-week-old Muscovy ducks.

Housing System	Gender	B 1 (mg·kg−1)	Ca 2 (g·kg−1)	Cd 3 (mg·kg−1)	Co 4 (mg·kg−1)	Cr 5 (mg·kg−1)	Cu 6 (mg·kg−1)	Fe 7 (mg·kg−1)	K 8 (g·kg−1)	Mg 9 (g·kg−1)	Mn 10 (mg·kg−1)
DL 11		91.5	271.4 b	0.13	1.19	2.66 b	20.2 a	62.1	3.2 b	4.3 b	9.98 b
DLSP 12		101.9	277.0 a	0.13	1.21	3.41 a	17.5 b	60.0	3.5 a	4.6 a	11.45 a
	Drakes	90.3 b	274.9	0.13	1.21	3.36 a	18.1	65.7 a	3.4	4.7 a	10.22 b
	Ducks	103.1 a	273.8	0.13	1.18	2.75 b	19.6	56.7 b	3.4	4.2 b	11.25 a
p-Value
Housing system		0.0208	0.0142	0.6182	0.7895	0.0002	0.0171	0.5859	0.0418	0.0001	0.0063
Gender		0.0006	0.5899	0.6182	0.7895	0.0016	0.1907	0.0415	0.9837	0.0001	0.0495
SEM 13		9.853	1.149	0.003	0.044	0.105	0.565	2.204	0.081	0.040	0.282
Housing System	Gender	Na 14 (g·kg−1)	Ni 15 (mg·kg−1)	P 16 (g·kg−1)	Pb 17 (mg·kg−1)	S 18 (g·kg−1)	V 19 (mg·kg−1)	Zn 20 (mg·kg−1)	DM 21 (%)	Ash (%)
DL		8.6	0.49	114.4 a	1.55	7.3 b	0.67 b	411.6	88.7	56.7
DLSP		8.8	0.57	107.8 b	1.92	7.8 a	1.02 a	428.9	88.8	56.1
	Drakes	8.9 a	0.63 a	108.9 b	1.40 b	7.7 a	0.78	404.7 b	86.1 b	58.5 a
	Ducks	8.4 b	0.43 b	112.8 a	2.07 a	7.4 b	0.92	435.4 a	91.3 a	54.5 b
p-Value
Housing system		0.7854	0.4021	0.0001	0.0983	0.0009	0.0016	0.3129	0.2708	0.2015
Gender		0.0001	0.0237	0.0004	0.0044	0.0014	0.1865	0.0017	0.0001	0.0001
SEM		0.216	0.044	0.621	0.121	0.106	0.060	19.037	0.261	0.412

¹ B, boron; ² Ca, calcium; ³ Cd, cadmium; ⁴ Co, cobalt; ⁵ Cr, chrome; ⁶ Cu, copper; ⁷ Fe, iron; ⁸ K, potassium; ⁹ Mg, magnesium; ¹⁰ Mn, manganese; ¹¹ DL, deep litter; ¹² DLSP, deep litter with swimming pond; ¹³ SEM, standard error of the mean; ¹⁴ Na, sodium; ¹⁵ Ni, nickel; ¹⁶ P, phosphorus; ¹⁷ Pb, lead; ¹⁸ S, sulfur; ¹⁹ V, vanadium; ²⁰ Zn, zinc; and ²¹ DM, dry matter. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

for the tibia and in

Table 9. Effect of housing system and gender on femur element composition and chemical attributes of 13-week-old Muscovy ducks.

Housing System	Gender	B 1 (mg·kg−1)	Ca 2 (g·kg−1)	Cd 3 (mg·kg−1)	Co 4 (mg·kg−1)	Cr 5 (mg·kg−1)	Cu 6 (mg·kg−1)	Fe 7 (mg·kg−1)	K 8 (g·kg−1)	Mg 9 (g·kg−1)	Mn 10 (mg·kg−1)
DL 11		124.5 a	276.6	0.13 b	1.14 b	3.40	87.7	106.9 b	4.8 b	4.51 b	10.5 b
DLSP 12		94.9 b	277.9	0.17 a	1.44 a	3.44	18.9	122.3 a	5.3 a	4.62 a	13.3 a
	Drakes	93.4 b	280.0	0.16 a	1.44 a	3.49	19.3	129.7 a	5.3 a	4.61	12.3
	Ducks	126.1 a	274.5	0.13 b	1.37 b	3.34	87.3	99.5 b	4.9 b	4.52	11.5
p-Value
Housing system		0.0048	0.6499	0.0055	0.0055	0.8175	0.1227	0.0459	0.0019	0.0134	0.0001
Gender		0.0020	0.8679	0.0224	0.0055	0.4225	0.1269	0.0001	0.0079	0.0733	0.0879
SEM 13		9.391	1.496	0.007	0.058	0.092	22.563	4.108	75.560	0.024	0.264
Housing System	Gender	Na 14 (g·kg−1)	Ni 15 (mg·kg−1)	P 16 (g·kg−1)	Pb 17 (mg·kg−1)	S 18 (g·kg−1)	V 19 (mg·kg−1)	Zn 20 (mg·kg−1)	DM 21 (%)	Ash (%)
DL		9.40 a	0.67	116.2 a	1.34 b	8.3 a	0.83	489.1	88.5 b	62.2
DLSP		8.96 b	0.64	109.2 b	2.07 a	8.0 b	0.75	452.5	89.9 a	62.2
	Drakes	9.14	0.67	112.0	1.25 b	8.0 b	0.59 b	447.7 b	87.5 b	62.9 a
	Ducks	9.21	0.64	113.4	2.16 a	8.3 a	0.99 a	493.9 a	91.1 a	61.5 b
p-Value
Housing system		0.0399	0.8437	0.0001	0.0024	0.0030	0.4258	0.0877	0.0001	0.9923
Gender		0.7499	0.8544	0.2419	0.0002	0.0010	0.0001	0.0317	0.0001	0.0389
SEM		0.180	0.086	0.699	0.139	0.075	0.058	18.73	0.053	17.515

¹ B, boron; ² Ca, calcium; ³ Cd, cadmium; ⁴ Co, cobalt; ⁵ Cr, chrome; ⁶ Cu, copper; ⁷ Fe, iron; ⁸ K, potassium; ⁹ Mg, magnesium; ¹⁰ Mn, manganese; ¹¹ DL, deep litter; ¹² DLSP, deep litter with swimming pond; ¹³ SEM, standard error of the mean; ¹⁴ Na, sodium; ¹⁵ Ni, nickel; ¹⁶ P, phosphorus; ¹⁷ Pb, lead; ¹⁸ S, sulfur; ¹⁹ V, vanadium; ²⁰ Zn, zinc; and ²¹ DM, dry matter. Values marked with different superscript letters in each column are significantly different (p ≤ 0.05).

for the femur. For the tibia, the statistically significant effect of the housing system was calculated for the following elements: B (p < 0.05), Ca (p < 0.05), Cr (p < 0.001), Cu (p < 0.05), K (p < 0.05), Mg (p < 0.001), Mn (p < 0.05), P (p < 0.001), S (p < 0.001), and V (p < 0.05). Furthermore, the significant effect of gender was found to be significant in B (p < 0.001), Cr (p < 0.05), Fe (p < 0.05), Mg (p < 0.001), Mn (p < 0.05), Na (p < 0.001), Ni (p < 0.05), P (p < 0.001), Pb (p < 0.05), S (p < 0.05), and Zn (p < 0.05) and also for dry matter (p < 0.001) and ash contents (p < 0.001). For the femur, the effect of the housing system was significant in B (p < 0.05), Cd (p < 0.05), Co (p < 0.05), Fe (p < 0.05), K (p < 0.05), Mg (p < 0.05), Mn (p < 0.001), Na (p < 0.05), P (p < 0.001), Pb (p < 0.05), and S (p < 0.05) and for dry matter contents (p < 0.001). The effect of gender was calculated as statistically significant in B (p < 0.05), Cd (p < 0.05), Co (p < 0.05), Fe (p < 0.001), K (p < 0.05), Pb (p < 0.001), S (p < 0.05), V (p < 0.001), and Zn (p < 0.05) and also for dry matter (p < 0.001) and ash content (p < 0.05).

4. Discussion

4.1. Body Temperature

The duration of time that animals spend in the water plays a crucial role in regulating their body temperature [8]. This behavior enables animals to cool their bodies, enhance evaporation, and mitigate heat stress [7]. Furthermore, outdoor-reared ducks with free access to water have shown improved stress levels and enhanced bird comfort [6]. However, the use of open water sources can lead to increased waste production and negatively impact the condition of the litter used in the housing system [19].

In the present study, the housing system had a significant influence on external body temperature, although the temperature decline between the DL and the DLSP groups was relatively modest. It was particularly intriguing to note the differences in external temperature between genders. Krunt et al. [8] found significant variations in internal body temperature between drakes and ducks, with lower values observed in drakes. They proposed that these gender differences could be attributed to hormonal activity, considering that progesterone, for example, inhibits vasodilation in women [20] and domestic mammals [21].

Moreover, the higher body temperature in females compared with males has been confirmed in various species, including mice [22], Japanese quails [23], and farm-reared emus [24]. The authors of these studies attributed the temperature oscillations to differences in circadian modulation of the hypothermic response [22], variations in calorie intake and body weight [23], and metabolic changes [24], which can increase heat production capacity. The normal range of body temperature for Muscovy ducks typically falls between 38 and 42 °C [25]. Naturally, when measuring temperature using external methods that do not interfere with the body, the recorded values were lower.

4.2. Biochemical Blood Composition

Serum analysis is commonly used to determine and predict disease and infection; it can also be used to track the health status of animals [26]. The results of the blood composition in the present paper are shown in Table 3 and Table 4. According to our data, the type of housing system only significantly influenced the concentration of GLU and Ca in the blood. However, studies such as [27] or [28] proposed that greater movement or swimming in ducks reduces serum triacylglycerol and cholesterol. The birds in the present study did not differ in terms of these traits. Glucose is the main energy source of mammals and birds [29]. In our study, higher values of GLU were found in the DL group, which could mean a reduced need for energy due to lower physical activity [8] compared with the DLSP group, where birds could swim, thereby expending greater energy. Moreover, gender appeared as significant in the present paper. The differences could be linked to body size and different energy needs, as reported by [30]. Differences in Ca between housing systems were very low, varying only by 0.01 mmol·L⁻¹; they were also low between genders, varying only by 0.02 mmol·L⁻¹. Calcium is typically presented in three fractions—the ionized fraction, the protein-bound fraction, and the fraction complexed to anions [31]. Similar concentrations of Ca serum in birds could indicate similar levels of parathormone and vitamin D or the hormone, calcitonin, which influence the level of Ca in the blood. Other investigated elements were sodium, chlorine, and potassium. ATP pump based on sodium and potassium is important for balancing water in cells and maintaining biomass energy metabolism [32]. It is known that the concentration of these elements can be reduced by heat stress [33]. According to our results, it is clear that summer temperatures did not reduce these elements in both groups of birds. In addition, the concentration of creatinine differs significantly according to gender, with higher concentrations of serum in males than in females. Conversely, serum CR is found in the muscles and is described as a waste product, which is attributed to higher muscle mass [34]. Therefore, the higher body weight and muscle mass of males led to increased CR. Moreover, serum amylase is typically used to assess pancreas activity. It reflects stability in the rate of entry and removal from the blood. A small increase does not usually indicate pancreatitis, but some other condition [35]. Liver enzymes (GPT, GGT) serve as indicators of the pathological state that appears in hepatocytes and symbolizes abnormal (declining or rising) liver function [36].

4.3. Growth Performance and Carcass Value

Based on the findings, birds from the housing system with access to the swimming pond (DLSP) exhibited higher final live weight, average daily weight gain, and lower feed conversion rates compared with birds in standard deep litter housing (DL). These results align with the findings of Abo Ghanima et al. [28], who also reported improved productive performance in swimming birds, attributing it to the beneficial effects of natural swimming behavior for ducks. Similarly, Rehman et al. [26] concluded that the presence of swimming ponds enhanced feed efficiency and resulted in higher final weights compared with birds without access to swimming facilities.

However, contrasting results were reported by Damaziak et al. [37], who found superior weight gain and feed conversion ratios in intensively fattened birds compared with those provided with space for running. These discrepancies suggest that the type of movement may play a crucial role in the observed variations among birds. Based on the collective findings of the aforementioned studies, it can be inferred that swimming appears to be a more natural activity for waterfowl, generally leading to improved performance, while running may require additional energy expenditure and potentially hinder the growth of birds.

The differences observed between drakes and ducks can be attributed to significant sexual dimorphism, characterized by larger body dimensions in drakes [8]. However, while the final weight was higher in DLSP birds compared with DL birds, there was no statistical difference in eviscerated weight. This could be explained by the presence of a greater number of feathers on the bodies of DLSP birds, as it is known that birds from outdoor runs with access to swimming ponds tend to exhibit improved hygiene, cleaner feathers, and overall better feather condition when compared with birds in intensive housing conditions, where cleanliness and hygiene issues may arise. Additionally, feather growth is significantly enhanced in outdoor systems [3].

The absence of exercise opportunities, such as swimming in this case, in intensive housing conditions had an impact on the proportion of abdominal fat in birds. Birds from the DL group had a higher proportion of abdominal fat compared with the DLSP birds. Similar results were reported by Farghly et al. [38], who observed higher levels of abdominal fat in groups of birds without access to swimming compared with groups where swimming was allowed for varying durations as per the experimental design. Conversely, DLSP birds exhibited reduced breast muscle compared with DL birds due to increased water-based movement and related activities.

In other studies [28,39], the researchers did not observe a decline in breast muscle, possibly because they focused on comparing intensive, semi-intensive, and extensive systems without considering the factor of swimming in their investigations. The variations observed between genders in terms of DoP, the percentage of wings, thighs, and breasts could be attributed to the higher carcass weight of drakes compared with ducks. This is a factor that is considered when calculating the share of each body part, influencing its proportion. Thus, there is a relationship with overall body size. As a result of different growth patterns, drakes exhibited particularly well-developed thighs, surpassing the corresponding ratio in ducks. Additionally, when expressed in grams, drakes displayed greater length and weight across all body parts [40].

4.4. Bone Quality and Element Composition

In the case of poultry, particularly laying hens, the focus often lies on examining the impact of various nutritional factors on bone composition [15]. Nevertheless, specific attention has been paid to the influence of duck nutrition on bone quality in certain studies [41], while other research endeavors [8] have explored the potential effect of physical activity, as observed in fattened ducks, on bone quality—a relationship that has been demonstrated in other animal species [14].

Within the scope of this study, the authors conducted a comparative analysis between deep litter housing and an alternative housing system that offered swimming opportunities in ponds. Although only numerical differences were observed across the treatments, no significant variations were detected in terms of tibia and femur length, width, weight, or fracture toughness. Rodenburg et al. [3] noted that ducks inherently possess weaker leg and thigh joints, but swimming enables them to alleviate the weight-bearing burden on their joints. Interestingly, our findings indicate that the inclusion of swimming did not exert any adverse effects on tibia or femur strength. Moreover, housing treatment did not produce any discernible impacts on length, width, or weight parameters, aligning with the findings of Farghly and Mahmoud [8]. The findings suggest that the use of swimming ponds by ducks may not have notably reduced terrestrial locomotion, thereby having a limited impact on bone development or fragility. Furthermore, the study supports the assertion made by previous researchers regarding the influence of gender, as observed in Muscovy ducks exhibiting sexual dimorphism, with males displaying significantly larger physical dimensions than females.

Bone quality is influenced by various factors, including its architectural structure, organic composition, and mineral constituents. The mineral content, predominantly composed of calcium and phosphorus, is commonly assessed through bone ash analysis [42]. In the context of housing conditions for laying hens, studies have shown that bones from hens housed in cages exhibit lower ash content compared with those from floor pens [43] or free-range systems [44], which provide greater opportunities for animal mobility. The ash content and percentage of dry matter in bones also play a significant role in the incidence of osteoporosis in adult animals [44]. Additionally, when considering the effect of gender, factors such as live weight (which can vary substantially between genders) and growth rate, are likely to be the primary influencing factors [45]. In a study conducted by Corr et al. [46], it was observed that lighter broiler chickens exhibited higher mineral content in their bones compared with their heavier counterparts. However, in the current investigation, it was found that heavier males displayed a higher ash content in both bones studies compared with females. As highlighted by González-Cerón et al. [45], ash content can serve as an indicator of bone mineralization.

Interestingly, Rath et al. [42] reported contrasting findings, noting that fast-growing birds tend to exhibit lower levels of bone mineralization compared with slower-growing birds. Additional studies [46,47] have also suggested that slower-growing birds demonstrate superior bone mineralization and density compared with their faster-growing counterparts. These differences between males and females in our study could potentially be attributed to the divergent growth rates, with females experiencing faster growth and reaching physical maturity earlier than males [3].

The structure of the bone is determined by the minerals that are involved in the whole process. Calcium (Ca) and phosphorus (P) play a leading role and are the key elements markedly influencing bone strength. However, regarding the quality of the bone matrix, other elements are also involved, namely, sodium (Na), magnesium (Mg), potassium (K), copper (Cu), zinc (Zn), manganese (Mn), chrome (Cr), iron (Fe), and lead (Pb), all of which influence bone strength [48]. A mutual relationship between Ca and P is widely recognized, and Mg is connected to these as an antagonist of Ca [49]. The importance of Mg was mentioned in a study by Krunt et al. [14], with the authors believing that Mg plays a key role in bone strength. A study by Shastak and Rodehutscord [50] confirmed that rats with a deficiency of Mg in their diet showed a worse bone growth rate and lower bone strength than their counterparts with a normal diet. In addition, a deficiency of Na results in increased activity of osteoclasts and bone resorption [51]. In contrast, a surplus of Na in the feed mixture negatively affects Ca excretion from the organism. Moreover, osteoporosis is exposed to Na [52]. K is considered an element that favorably affects bone homeostasis by influencing the acid–base balance [53]. However, the benefits of Cu for bone health are not consistent in the scientific literature [48]. There could be a link with the inhibition of osteoclastic resorption through lysine crosslinks in collagen and elastin, which are affected by Cu as an enzymatic cofactor [54]. Another cofactor is Zn, which influences the proliferation and bone mineralization via protein gene expression (e.g., alkaline phosphatase or osteocalcin) [55]. Cr, Al, Pb, Cd, and Co could have a potential negative effect on bone health, while B, Si, Fe, and Sr could have a positive effect. Manganese (Mn) may influence the bone positively or negatively, depending on its content [48]. Furthermore, vanadium (V) plays an important role in the organism, such as the regulation of the glucose metabolism [56]. It also has an osteogenic effect; hence it influences the differentiation and mineralization of components in the cell bone extracellular matrix or in the formation of collagen [19]. In addition, it has been found that cobalt (Co) affects both angiogenesis and osteogenesis through alkaline phosphatase or osteocalcin alone; alternatively, the effect could be influenced by other trace elements [57].

5. Conclusions

During the fattening period, the birds exhibited a decline in their external body temperature when provided with unrestricted access to swimming ponds. Remarkably, the birds residing in the housing systems offering swimming opportunities demonstrated superior productive performance and a lower proportion of abdominal fat compared with birds in standard deep litter housing. These findings provide a compelling argument in discussions on the potential disparity in production outcomes between alternative and intensive systems.

Despite discernible variations in the elemental composition of the tibia and femur between birds housed under different systems, the present study suggests that the housing system itself did not exert a substantial influence on bone quality, and specifically fracture toughness, at the investigated age. Nevertheless, it is imperative to exercise caution when interpreting these results, particularly if birds were reared under identical conditions until reaching the reproductive phase. This investigation has provided novel insights into the bone quality of waterfowl raised under intensive conditions.

In future research endeavors, we recommend focusing attention on evaluating the meat quality of ducks fattened in accordance with the housing conditions examined in this study. By focusing on these aspects, we will further enhance our understanding of the broader implications associated with the studied housing systems.