Productive Performance and Economic Feasibility of the Inclusion of Biological Silage From Colossoma macropomum By-Products in Diets for Commercial Hens ¹

ABSTRACT

This study evaluated the productive performance and economic feasibility of including biological silage from Colossoma macropomum by-products (BST) in the diets of commercial laying hens at different stages of the production cycle. Two experiments were conducted using young hens (23 weeks old) and older hens (83 weeks old), fed diets containing 0, 1, 2, 3, and 4% BST for 63 days. Productive performance (feed intake, egg production and mass, feed conversion) and economic parameters (feed cost, revenue, profit, break-even point, and profitability index) were analyzed. In young hens, inclusion levels up to 1% BST resulted in performance and profitability similar to the control group, while higher levels significantly impaired egg production and economic indicators. In older hens, inclusion levels of 1% to 2% provided better productive performance and greater financial returns, particularly due to reduced unit egg cost and increased profitability. From 3% onward, negative effects similar to those observed in the first group were noted. It is concluded that BST is a viable alternative ingredient in layer diets, provided its inclusion is adjusted according to the birds’ production phase. The rational use of BST promotes the valorization of regional residues, contributing to the economic and environmental sustainability of poultry farming in the Amazon region.

Keywords:
Alternative food; Amazon; feed efficiency; silage; sustainability

INTRODUCTION

Poultry farming is one of the main pillars of global food production, playing a fundamental role in food security and in the accessible supply of high-quality animal protein (Piccolo et al., 2024). The sector has expanded rapidly in recent decades, driven by population growth, urbanization, and changing dietary patterns, which has intensified the demand for efficient and economically viable production systems (Papageorgiou et al., 2023). However, the continuous rise in input costs, especially those related to feed, undermines the economic and environmental sustainability of the sector (Bowles et al., 2019). This challenge is even more critical in the Amazon region, where logistical constraints, limited infrastructure, and dependence on inputs transported over long distances significantly increase the cost of formulating balanced diets (Cruz et al., 2016). Feed expenses can account for 60% to 80% of the total cost of poultry production, making nutrition the main bottleneck to profitability and driving research into the use of alternative ingredients, particularly those derived from agro-industrial residues (Rufino et al., 2015; Cruz et al., 2016).

In this context, the incorporation of agro-industrial by-products into animal feeding strategies has gained increasing attention worldwide, as it represents a practical approach to simultaneously reduce production costs, mitigate environmental impacts, and promote more sustainable production systems (Van Zanten et al., 2018; Van Hal et al., 2019). Among these alternatives, the use of agro-industrial by-products in animal feed stands out, a practice that helps reduce costs, promotes waste recovery, and integrates principles of circular economy into poultry production (Cruz & Rufino, 2017). Materials often discarded, such as residues from fruit and fish processing, present relevant nutritional value and, when processed into meals or other derivatives, can be incorporated into diets as feed supplements, generating both economic and productive benefits (Guimarães et al., 2021; Silva et al., 2023). Furthermore, these strategies contribute to reducing competition between humans and animals for conventional feed ingredients, such as corn and soybean meal (Van Zanten et al., 2018).

The Amazon region holds great potential in this scenario, with a biodiversity that includes species of recognized nutritional, technological, and economic value (Santos et al., 2024). The sustainable use of these resources, especially through the valorization of residues, can strengthen local production chains and offer technically and economically viable solutions for poultry feeding (Cruz & Rufino, 2017; Costa et al., 2018; Oliveira, 2018). In addition, the regional availability of diverse agro-industrial and fishery residues represents an important opportunity to develop locally adapted feeding strategies that reduce dependence on external inputs (Cruz et al., 2016). The fishing industry, in turn, has grown significantly in recent decades, driven by the global increase in fish consumption (Coppola et al., 2021), which has fostered technological advances throughout the production chain, including the valorization of its by-products (Guimarães et al., 2021). Nevertheless, the large volume of biological waste remains an important environmental challenge, exacerbated by the risk of improper disposal, which may result in pollution, greenhouse gas emissions, and public health concerns (Decker et al., 2016; Coppola et al., 2021).

In this context, biological fish silage emerges as a low-cost and practical technological alternative for transforming these residues into valuable feed ingredients (Guimarães et al., 2021; Santos et al., 2025). Through biomass hydrolysis, a product rich in proteins and fatty acids with high nutritional value is obtained, suitable for use in feed formulations (Rossetto & Signor, 2021), especially for poultry (Guimarães et al., 2019; Guimarães et al., 2021). This technology enables the efficient utilization of residues from Brazilian aquaculture, fishing, and industrial processing (Arruda et al., 2006; Guimarães et al., 2021). Moreover, fish silage production requires relatively simple infrastructure and can be implemented at small and medium scales, making it particularly attractive for developing regions (Guimarães et al., 2021). Among native Amazonian species, tambaqui (Colossoma macropomum) stands out as one of the main candidates for this processing, due to its high productivity and adaptability to tropical conditions, which consequently generates a great amount of residues with high potential for reuse (Aride et al., 2018; Lima et al., 2021; Valenti et al., 2021).

Despite the recognized potential of fish silage as a feed ingredient, information regarding its use as a dietary additive for commercial laying hens, particularly using silage derived from tambaqui by-products, remains limited (Guimarães et al., 2021; Guimarães et al., 2025). Understanding its effects on productive performance and economic outcomes is essential to support its adoption by the poultry industry and to validate its role within sustainable production systems (Santos et al., 2025). Based on these premises, the present study hypothesized that the inclusion of biological silage produced from tambaqui by-products (BST) as a dietary additive for commercial laying hens could improve productive performance while simultaneously enhancing the economic indicators of poultry production. This assumption is supported by consistent evidence demonstrating that fish by-products processed as silage possess high nutritional value and can positively influence poultry performance (Cruz & Rufino, 2017; Guimarães et al., 2019; Guimarães et al., 2021). In addition to their nutritional potential, the reutilization of these residues contributes to waste reduction and promotes environmentally responsible practices by providing a suitable destination for materials that would otherwise be discarded, thereby adding value throughout the production chain (Guimarães et al., 2021; Guimarães et al., 2025). Generating robust scientific evidence regarding the technical and economic feasibility of BST inclusion is essential to support its consolidation as a sustainable feed additive in poultry nutrition. Considering the above, the objective of this study was to investigate the effects of increasing levels of BST in the diets of commercial laying hens on their productive performance and economic feasibility.

MATERIALS AND METHODS

The current experiment was conducted at the Faculty of Agrarian Sciences of the Federal University of Amazonas (UFAM), located in Manaus (AM), Brazil. All experimental procedures were conducted in accordance with the guidelines of the Local Experimental Animal Care Committee and were approved by the UFAM ethics committee (protocol number 005/2022).

Processing of Tambaqui Residues and Silage Production

The residues, consisting of viscera, gills, scales, and fins discarded during the processing of tambaqui (fish weighing between 800 and 1,300 g), were obtained from an industrial fish processing facility in Manaus, Amazonas. These residues were transported to the laboratory in insulated containers and stored in a freezer until further processing. During the initial preparation, the residues were thawed at room temperature and subjected to thermal treatment at 65°C for 5 minutes. Subsequently, they were filtered through a sieve, and the remaining mass was pressed using a hydraulic press. The processed material was then weighed and transferred into 40-liter plastic buckets for later use.

For the production of silage (Figure 1), the residual fish mass was combined with 10% (w/w) cassava trimmings (Manihot esculenta Crantz) obtained from local markets in Manaus. The trimmings were cleaned and ground to serve as a carbohydrate source for the silage. Additionally, 2.5% (v/w) of an inoculum consisting of pure cultures of Lactobacillus plantarum, a proteolytic bacterium, was added, along with 0.1% (w/w) benzoic acid as a fungicidal and bactericidal preservative, and 0.1% (w/w) ascorbic acid as an antioxidant. This process followed the methodology described by Vidotti et al. (2003) and Vidotti et al. (2011).

Figure 1
Processing of biological silage from tambaqui by-products.

All ingredients were thoroughly mixed in the buckets until the silage components were completely uniform. The buckets were then hermetically sealed to ensure anaerobic conditions. To achieve this, a sterilized plastic bag was placed directly over the surface of the ensiled mass before sealing the buckets. The silage was stored and stirred every 24 hours to enhance the fermentation process and maintained for 14 days at room temperature under anaerobic conditions. During this period, the silage was evaluated based on its organoleptic properties, including odor, color changes, texture, pH, and titratable acidity, the latter determined by titration with 0.1 N NaOH.

After fermentation, the silage was transferred to aluminum trays and placed in a forced-ventilation oven at 65 °C (149 °F) for 72 hours, to reduce its moisture content. During drying, the biomass was periodically stirred to ensure uniform dehydration. Once dried, the BST was subjected to proximate composition analysis, following the methodologies described by Van Soest et al. (1991) and AOAC (2019). The results are presented in Table 1.

Table 1
Proximate composition of fresh residual mass and biological silage from tambaqui by-products.

Proximate composition	Fresh waste*	Biological silage*
Dry matter, %	44.61±2.87	87.69±0.17
Crude protein, %	22.67±1.81	44.98±0.59
Fats, %	7.38±0.35	17.89±0.47
Minerals, %	11.70±1.15	21.87±0.69
Crude fiber, %	1.62±0.28	2.44±1.24
Soluble carbohydrates, %	1.23±0.32	0.50±1.06

• * All nutrient values were calculated on a dry matter basis. Values are presented as mean ± standard deviation of three replicates.

Facilities, Animals, and Experimental Design

To evaluate the effects of BST on productive performance and economic viability, two experiments were conducted. The first assessed the inclusion of BST in diets for younger commercial hens (23 weeks old), while the second evaluated its effects in older commercial hens (83 weeks old). A poultry house with structural adaptations aimed at improving bird welfare was used. The facility had natural ventilation provided by open ridge vents and surrounding vegetation (trees and mixed vegetation), artificial lighting system, and no curtain system. The building measured 25 × 8 m, had a ceiling height of 3.25 m, and cement tile roofing. Temperature and relative humidity were monitored using a small digital weather station, which recorded average values of 28.6 °C (83.48 °F) and 54.15%, respectively. Throughout the experimental period, the hens were monitored for potential signs of heat stress caused by environmental conditions, including panting, wing spreading, lethargy, reduced feed intake, and abnormal drinking behavior; however, no such signs were observed during the entirety of either experiment.

In both experiments, 120 commercial hens of the Hissex Brown strain were used. The experimental period lasted 63 days, divided into three 21-day phases, and was preceded by a seven-day adaptation period to the diets and housing. The birds were weighed at the beginning of the experimental period to standardize the experimental units, with an average weight of 1.87 ± 0.181 kg in Experiment 1 and 1.83 ± 0.158 kg in Experiment 2.

The hens were housed in galvanized wire cages (0.45 m high, 0.40 m wide, and 1.00 m long), each housing six birds, arranged in a single row. The cages were equipped with trough feeders and nipple drinkers. Feed and water were supplied ad libitum and birds received 16 hours of light per day (12 hours of natural light and 4 hours of artificial light) throughout the experimental period. Artificial lighting was provided using LED lamps with an average intensity of approximately 10 lux at feeder height, and was controlled by an automatic timer. Eggs were collected twice daily (at 9 a.m. and 3 p.m.), and daily records were kept for all relevant occurrences (mortality, egg production, among others). Bird health was visually inspected at least twice daily, and no vaccinations or therapeutic treatments were applied during the experimental period.

Figure 2
Experimental design showing the evaluation of tambaqui by-product silage (BST) at four inclusion levels (1-4%) in diets for younger (23 weeks) and older (83 weeks) laying hens, with assessment of productive performance and economic viability over a 63-day period.

Both Experiment 1 (younger hens) and Experiment 2 (older hens) were conducted using a completely randomized design. The treatments consisted of a control diet (without BST) and four levels of BST inclusion (1, 2, 3, and 4%), with four replicates per treatment and six birds per replicate. The experimental diets (Table 2) were formulated based on the reference values proposed by Rostagno et al. (2024), except for the BST, which was based on prior compositional analyses. Metabolizable energy values followed the data reported by Guimarães et al. (2019). BST was treated as a fixed component in the diet formulation, and the levels of other feed ingredients were adjusted according to the inclusion levels proposed in the experiments. The diets were formulated using the SuperCrac software (TD Software©, Viçosa, Brazil), and their proximate composition was analyzed to confirm nutrient values, following the methodologies described by Van Soest et al. (1991) and AOAC (2019).

Table 2
Composition of the experimental diets containing biological silage from tambaqui by-products.

Feedstuffs	Biological silage from tambaqui by-products levels, %
	0.00	1.00	2.00	3.00	4.00
Corn (7.88%)1	65.80	65.30	64.42	64.29	63.79
Soybean meal (46%)1	21.41	20.76	20.11	19.46	18.81
BST	0.00	1.00	2.00	3.00	4.00
Limestone	9.78	9.91	10.42	10.17	10.30
Dicalcium phosphate	1.93	1.94	1.95	1.95	1.96
Vit. min. supplement2	0.60	0.60	0.60	0.60	0.60
Salt	0.29	0.29	0.30	0.30	0.30
DL-methionine (99%)3	0.19	0.20	0.21	0.22	0.23
Total	100.00	100.00	100.00	100.00	100.00
Nutrient	Nutritional levels
M.E., kcal.kg-1	2,900.00	2,900.00	2,900.00	2,900.00	2,900.00
Crude protein, %	15.50	15.50	15.50	15.50	15.50
Calcium, %	4.32	4.37	4.42	4.47	4.52
Available phosphorus, %	0.45	0.45	0.45	0.45	0.45
Crude fiber, %	2.55	2.52	2.48	2.45	2.41
NDF, %	10.54	10.39	10.24	10.09	9.94
ADF, %	3.92	3.85	3.78	3.71	3.64
Methionine + Cystine, %	0.70	0.70	0.70	0.70	0.70
Methionine, %	0.43	0.44	0.45	0.45	0.46
Lysine, %	0.76	0.74	0.72	0.70	0.68
Threonine, %	0.60	0.58	0.57	0.56	0.54
Tryptophan, %	0.18	0.17	0.17	0.16	0.16
Sodium, %	0.15	0.15	0.15	0.15	0.15
Price, R$/kg	2.70	2.68	2.66	2.65	2.63

• ¹
  Values in parentheses indicate the protein content of the feedstuffs.
• ²
  Guaranteed levels per kilogram of the product: Vitamin A 2,000,000 IU, Vitamin D3 400,000 IU, Vitamin E 2,400 mg, Vitamin K3 400 mg, Vitamin B1 100 mg, Vitamin B2 760 mg, Vitamin B6 100 mg, Vitamin B12 2,400 mcg, Niacin 5,000 mg, Calcium Pantothenate 2,000 mg, Folic acid 50 mg, Coccidiostat 12,000 mg, Choline 50,000 mg, Copper 1,200 mg, Iron 6,000 mg, Manganese 14,000 mg, Zinc 10,000 mg, Iodine 100 mg. Selenium 40 mg. Vehicle q.s.p. 1,000 g.
• ³
  The value in parentheses indicates the purity of the amino acid.

Experimental Analysis

In both experiments, the performance of the hens was assessed following the methodology outlined by Rufino et al. (2021). Every seven days, the following parameters were recorded: feed intake (g/bird/day), egg production (%), feed conversion ratio (kg of feed per kg of eggs produced - kg/kg), feed conversion ratio (kg of feed per dozen eggs produced - kg/dz), and egg mass (g) for each replicate. During the final two days of each 21-day subperiod, four eggs from each replicate were randomly selected for quality analysis.

To determine feed costs and production expenses, only the per-kilogram prices of the feedstuffs used and their updated prices in the region during the experiment were considered. The prices were as follows: corn, R$ 1.66; soybean meal, R$ 3.65; limestone, R$ 0.73; dicalcium phosphate, R$ 4.50; common salt, R$ 0.83; DL-Methionine 99%, R$ 51.00; and mineral and vitamin supplement, R$ 28.35/kg (average price). The cost of BST was calculated considering only transportation and handling expenses (labor), with an estimated price of R$ 1.50 per kilogram. Fixed costs included depreciation of facilities and equipment (maintenance, water, electricity, etc.), while interest on capital remained unchanged in the short term and was considered constant across all treatments. Variable costs included only bird feed expenses and labor.

The feed cost (FC, R$), the only production cost used as an analysis variable, was determined through the acquisition of ingredients and feed preparation, estimated by the formula:

$FC=AFI*AP$

Where:

AFI = accumulated feed intake of the plot (kg)

AP = average price per kilogram of feed (R$/kg)

For total egg production (PO, units), the total units of eggs produced by each pen was considered, as described by Brelaz et al. (2021). To calculate the production cost per egg (PC, R$/unit), the following formula was used:

$PC=\frac{FC}{PO}$

Where:

FC = feed cost (R$)

PO = total production of eggs (units)

The gross revenue (REV, R$) was calculated based on the relationship between egg production and the selling price per egg, using:

$REV=Q*SP$

Where:

Q = quantity of eggs produced by the plot (unit)

SP = selling price per egg produced (R$/unit)

It is important to note that the selling price per egg, applying a gross margin value-added calculation, was determined based on the market price in the region, fixed at R$ 0.75 per egg. Gross profit (PRO, R$) was calculated as the monetary difference between the total revenue from the estimated sale of the eggs and the discounted production cost, which was derived from the feed cost using the formula:

$PRO=REV-FC$

Where:

REV = gross revenue of the plot (R$)

FC = feed cost of the plot (R$)

The profitability index (PI, %), which indicates the capital available after covering costs (in this case, feed costs), was derived from the relationship between gross added value and gross revenue, using the formula:

$PI=(\frac{PRO}{REV})*100$

Where:

PRO = gross profit of the plot (R$)

REV = gross revenue of the plot (R$)

For the break-even point (BE, kg), the quantity of production required to achieve zero return covering all costs was considered. In this case, it represents a partial break-even point, as it reflects the production volume necessary to cover feed costs. The formula used was:

$BE=\frac{FC}{SP}$

Where:

FC = feed cost of the plot (R$)

SP = selling price per egg produced (R$/kg)

Statistical Analysis

The sample size was established based on recommendations for nutritional trials with laying hens, considering experimental precision, housing structure, and logistical feasibility. Each replicate consisted of six birds, in accordance with previous studies evaluating alternative feed ingredients in poultry nutrition and providing adequate experimental sensitivity (Guimarães et al., 2019; Rufino et al., 2021; Guimarães et al., 2021). A total of 120 birds were used per experiment, distributed into 20 experimental units (5 treatments × 4 replicates), which allows for the detection of biologically relevant differences among treatments, while maintaining manageable experimental conditions. Furthermore, preliminary variability data from similar studies conducted under comparable conditions indicated coefficients of variation ranging from 4% to 10% for key performance variables (egg production, feed intake, and feed conversion). Based on these estimates, the adopted sample size provides statistical power greater than 0.80 to detect minimum differences of approximately 5-7% among treatment means at a significance level of 0.05. Therefore, the experimental size was considered adequate to test the proposed hypothesis while respecting ethical principles of animal use by avoiding unnecessary numbers of animals.

The statistical model adopted was as follows:

$Y_{ik}=\mu +{\alpha }_i{ϵ}_{ik}$

Where:

Y_ik = Observed value for the variable under study

μ = Overall experiment mean

α_i = Effect of BST levels

ϵ_ik = Experimental error

Before conducting inferential analyses, all datasets were subjected to pre-analysis procedures to verify compliance with the assumptions of parametric statistics. Data normality was assessed using the Shapiro-Wilk test, while homogeneity of variances among treatments was evaluated using Levene’s test. In addition, residual plots were visually inspected to identify potential outliers and deviations from normality and homoscedasticity. When necessary, data were transformed to meet these assumptions.

In both experiments, all data were analyzed using one-way ANOVA with R software (2021). Commands were executed following the guidelines described by Logan (2010). Tukey’s Honest Significant Difference (HSD) test was used to examine significant differences among the BST levels (independent variable) for each dependent variable evaluated. Results are presented as means, and the significance level for differences was set at 0.05.

Subsequently, results for significant variables (p<0.05) were subjected to correlation and polynomial regression analysis to evaluate the influence of the independent variable on the dependent variables (Chatterjee & Hadi, 2006; Logan, 2010). The mathematical model, either linear (Y = a + bx) or quadratic (Y = c + bx + ax²), was selected based on the influence of the independent variable on the dependent variable analyzed (Dormann et al., 2013). R-squared values were also considered as a criterion to determine the best model (Chatterjee & Hadi, 2006; Dormann et al., 2013).

RESULTS AND DISCUSSION

Experiment 1

The inclusion of BST in the diets of young laying hens significantly influenced productive performance variables (Table 3). First, feed intake exhibited a significant quadratic effect (p=0.004), increasing up to the 2% inclusion level (+4.1% relative to control), and subsequently decreasing at the 3% and 4% inclusion levels (-8.2% and -10.8%, respectively). This result indicates that moderate inclusion levels of BST may favor feed intake, possibly due to improved palatability resulting from compounds generated during silage fermentation (Guimarães et al., 2025). However, the reduced intake at higher inclusion of BST levels in the diets also suggests a lower feed acceptance due to the accumulation of undesirable organoleptic compounds from the BST. Highly hydrolyzed silages may impair animal performance because of the excess of free amino acids and short-chain peptides, which at high concentrations can cause metabolic competition, reducing protein synthesis and growth (Goosen et al., 2016). Moreover, intensified protein degradation during silage processing favors the formation of volatile compounds that negatively affect feed acceptability and palatability (Boitai et al., 2017).

Table 3
Performance of younger commercial hens fed diets containing increasing levels of biological silage from tambaqui by-products¹.

Variables2	Biological silage from Colossoma macropomum by-products levels, %				p-value 3	CV4, %	MM5		R²
	0.00	1.00	2.00	3.00	4.00
FI	118.69±12.25a	121.79±16.13a	123.61±10.12a	108.94±11.25b	105.90±12.12b	0.004	7.51	Y = 119.36 + 4.377x - 2.055x2	0.82
EP	88.24±5.32a	90.02±9.97a	80.05±7.74b	70.38±6.64c	68.00±12.19c	0.032	6.71	Y = 91.362 - 6.012x	0.90
FEKG	2.61±0.63b	2.81±0.52a	2.80±0.45a	2.54±0.41b	2.31±0.25c	0.006	8.76	Y = 2.6294 + 0.2301x - 0.0793x2	0.95
FEDZ	1.60±0.32c	1.61±0.41c	1.84±0.52b	1.91±0.43a	1.91±0.22a	0.049	5.77	Y = 1.59 + 0.092x	0.85
EM	39.98±4.12a	38.94±8.12a	35.30±7.33ab	30.10±10.12b	31.27±11.11b	0.043	7.22	Y = 40.37 - 2.626x	0.88

• ¹
  All data represent the average of 24 replicates (hens) per treatment. ² FI = Feed intake (g/bird/day). EP = Egg production (%). FEKG = Feed efficiency, kg/kg (Quantity of feed (kg) to produce one kilogram (kg) of egg). FEDZ = Feed efficiency, kg/dz (Quantity of feed (kg) to produce one dozen (dz) of eggs). EM = Egg mass (g). ³ The means followed by lowercase letters in the lines differ using the Tukey test (p<0.05). Not significant = p>0.05. ⁴ CV = Coefficient of variation. ⁵ MM = Mathematical model adjusted according to the influence of the independent variable on the dependent variable.

Egg production declined linearly with increasing BST levels (p=0.032), decreasing by 2.0% at 1%, 9.3% at 2%, 20.2% at 3%, and 22.9% at 4% compared with the control. This decrease may be associated with nutritional imbalances or the presence of secondary metabolites generated during fermentation, which may negatively affect the birds’ reproductive physiology (Guimarães et al., 2021; Guimarães et al., 2025). Similar results were reported by Batalha et al. (2017), who observed reduced crude protein digestibility in lightweight laying hens fed acid silage from Arapaima gigas (pirarucu) at inclusion levels of 3% or higher. These findings suggest that even moderate inclusion levels of silage may impair the utilization of essential nutrients, directly impacting egg production.

Feed efficiency per kilogram of eggs was significantly affected (p=0.006), exhibiting a quadratic response. Considering that this variable represents the kilograms of feed required to produce 1 kg of eggs, lower values indicate better feed conversion. Under this criterion, the inclusion levels of 1% and 2% BST resulted in poorer feed efficiency, with increases of 7.7% and 7.3%, respectively, relative to the control. Conversely, feed efficiency improved at 4% inclusion, with a reduction of 11.5% compared with the control. This result indicated that an inclusion level of 4% of BST optimized the conversion of feed into eggs. This positive response may be attributed to greater nutrient bioavailability resulting from the fermentation process used in silage preparation. According to Goosen et al. (2014), fish silage is highly digestible and has a favorable nutritional profile, making it a promising ingredient in animal nutrition. During fermentation, proteins are hydrolyzed into simpler compounds such as free amino acids and short-chain peptides, which are more readily absorbed in the digestive tract (Ozyurt et al., 2017).

On the other hand, feed efficiency per dozen eggs increased linearly (p=0.049), rising by 19.5% and 20.1% at 3% and 4% BST, respectively, indicating that larger amounts of feed were required to sustain egg production at higher levels of silage inclusion. This finding aligns with the observed decline in egg production and may suggest a reduction in the metabolic responses due to excessive silage levels. In the same way, egg mass showed a linear decreasing trend (p=0.043), decreasing by 11.7% at 2%, 24.7% at 3%, and 21.8% at 4% compared with the control, indicating impaired nutrient deposition into the egg content as silage levels increased. The reduction in egg mass may be associated with lower intake of essential nutrients such as sulfur-containing amino acids and calcium, or with the presence of metabolites produced during fermentation. Although the hydrolysis process releases functional peptides with bioactive properties and potential benefits for animal health (Dadkhodazadeh et al., 2024), the excessive accumulation of these compounds may lead to adverse metabolic effects (Goosen et al., 2014). In this scenario, the birds’ metabolic energy may be redirected toward maintenance and detoxification processes, compromising nutrient deposition in the eggs. Therefore, the reduction in egg mass constitutes a direct indicator of reproductive physiological dysfunction.

The economic analysis of including BST in diets for young laying hens, based on the performance results, is presented in Table 4 and revealed progressively adverse effects on the main financial viability indicators as inclusion levels increased. Feed cost exhibited a significant quadratic trend (p=0.001), increasing by 2.9% at 1% BST and decreasing by 12.8% at 4% BST relative to control. This may be related to adjustments in feed intake in response to palatability or dietary energy density. A similar result was reported by Rufino et al. (2015), who observed a reduction in feed cost after 5% inclusion of tucumã residue meal. Likewise, Melo et al. (2017) found that including 5% of yam (Dioscorea spp.) resulted in the lowest feed cost, representing the optimal level. Batalha et al. (2019), using acid silage from pirarucu (Arapaima gigas) residues, also reported a significant reduction in feed cost with 3% inclusion. In the same way, egg production peaked (p=0.037) at the 1% inclusion level (+2.0%) and declined by 22.9% at 4%. This response may be linked to a possible reduction of nutrient availability or the presence of compounds that impair birds’ physiological performance at higher inclusion levels of BST. Similar findings were reported by Melo et al. (2017), who observed a sharp drop in production after 10% inclusion of yam, and by Batalha et al. (2019), who reported maximum productive performance at 2.63% inclusion of acid silage meal, suggesting a trend toward alternative food inclusion in poultry diets, whereas excessive inclusion leads to metabolic and productive limitations that compromise both biological performance and economic return (Santos et al., 2025).

Table 4
Economic analysis of the performance of younger commercial hens fed diets containing increasing levels of biological silage from tambaqui by-products¹.

Variables2	Biological silage from Colossoma macropomum by-products levels, %				p-value 3	CV4, %	MM5		R²
	0.00	1.00	2.00	3.00	4.00
FC	161.57±8.26a	164.57±5.72a	166.27±7.47a	145.67±5.27b	140.80±8.94b	0.001	8.06	Y = 162.43 + 4.8246x - 2.7171x2	0.85
PO	444.75±13.72a	453.75±23.79a	403.50±30.34b	354.75±76.65c	342.75±84.26c	0.037	6.71	Y = 454.71 + 18.729x - 2.8929x2	0.90
PC	0.36±0.01b	0.36±0.02b	0.41±0.02a	0.42±0.10a	0.42±0.07a	0.049	5.31	Y = 0.358 = 0.018x	0.82
RE	333.56±10.29a	340.31±17.84a	302.62±22.76b	266.06±57.49c	257.06±63.19c	0.032	6.71	Y = 345.37 - 22.725x	0.89
PR	171.98±10.55a	175.49±22.58a	136.34±17.35b	120.38±53.63bc	116.26±55.34c	0.049	9.02	Y = 177.4 - 16.655x	0.87
PI	51.54±2.41a	51.42±3.81a	44.92±2.74b	43.02±13.75b	43.34±10.21b	0.048	7.37	Y = 51.808 - 2.48x	0.84
BE	215.43±11.01a	219.75±7.63a	221.70±9.96a	194.23±7.03b	187.73±11.92b	0.001	8.06	Y = 216.66 + 6.4966x - 3.6471x2	0.85

• ¹
  All data represent the average of 24 replicates (hens) per treatment. ² FFC = Feed Cost (R$). PO = Total Egg Production (units). PC = Production Cost per egg (R$/unit). RE = Gross Revenue (R$). PR = Gross Profit (R$). PI = Profitability Index (%). BE = Break-even point (units). ³ The means followed by lowercase letters in the lines differ using the Tukey test (p<0.05). Not significant = p>0.05. ⁴ CV = Coefficient of variation. ⁵ MM = Mathematical model adjusted according to the influence of the independent variable on the dependent variable.

Consequently, gross revenue declined linearly (p=0.032), with a 23.0% reduction at 4% BST relative to control, following the trend of reduced egg production. This relationship was also observed by Rufino et al. (2017), who reported higher revenue in diets with up to 5% inclusion of buriti flour, followed by a decline. Similarly, Batalha et al. (2019) reported the highest revenue (R$ 185.17) at 2.63% inclusion of acid silage. The production cost per unit increased significantly (p=0.049) from R$ 0.36 to R$ 0.42 (+16.7%) at ≥3% inclusion, indicating reduced productive efficiency. This pattern was also noted by Melo et al. (2017), who reported economic unfeasibility beyond 15% inclusion of yam, and by Batalha et al. (2019), who found the lowest cost per unit with 3.11% inclusion of acid silage from pirarucu. All these studies converge in demonstrating that although alternative feed ingredients may reduce diet formulation costs, their economic viability is strongly dependent on maintaining productive performance. Santos et al. (2025) also reported that when inclusion levels of alternative foods exceed the physiological capacity of birds to efficiently utilize the ingredient, declines in egg output and feed efficiency outweigh potential savings, resulting in higher unit production costs and reduced profitability.

Finally, gross profit (p=0.049) and the profitability index (p=0.048) declined linearly, with profitability index decreasing from 51.5% (control) to 43.3% at 4% BST (-15.9%), reflecting the combined effect of higher costs and reduced economic returns. According to Rufino et al. (2017), inclusion levels above 10% of buriti flour led to a significant drop in profitability, supporting the findings of Batalha et al. (2019), who reported maximum profitability (58.56%) with 3.1% inclusion of acid silage. These authors reinforce the concept that moderate inclusion of alternative food may improve or maintain economic efficiency, whereas excessive inclusion levels reduce productive efficiency and erode profit margins, thereby limiting the economic feasibility of such strategies in commercial hens’ diets.

The break-even point, in turn, increased significantly (p=0.001) with higher silage inclusion levels, indicating greater production requirements to achieve economic sustainability. A similar situation was described by Rufino et al. (2015) for tucumã meal, and by Batalha et al. (2019), who estimated the optimal break-even point at 1.17% inclusion. Therefore, the use of BST in diets for young laying hens should be approached with caution, as inclusion levels above 1% result in economic, productive, and operational losses, compromising the profitability of poultry systems during the early laying phase.

Experiment 2

Based on the data presented in Table 5, which evaluates the productive performance of older commercial laying hens fed diets containing different levels of BST, a dose-dependent adverse effect was observed on the main productive indicators. Feed intake initially increased with the inclusion of 1% silage, reaching 111.48 ± 11.25 g/bird/day, compared to the control group, which consumed 97.63 ± 10.13 g/bird/day. However, from the 2% inclusion level onward, a progressive and significant reduction in intake was observed, with the lowest value recorded at 4% inclusion (57.29 ± 10.49 g/bird/day; p=0.001). These results suggested that high silage concentrations may compromise diet palatability or alter energy density, directly affecting voluntary intake, especially in older hens, which are reported as more sensitive to organoleptic and energetic changes introduced by silage, which negatively affects their feed intake at higher inclusion levels (Batalha et al., 2017; Guimarães et al., 2025).

Table 5
Performance of older commercial hens fed diets containing increasing levels of biological silage from tambaqui by-products¹.

Variables2	Biological silage from Colossoma macropomum by-products levels, %				p-value 3	CV4, %	MM5		R²
	0.00	1.00	2.00	3.00	4.00
FI	97.63±10.13ab	111.48±11.25a	89.05±13.15b	71.28±10.28b	57.29±10.49c	0.001	2.30	Y = 93.4459 - 4.0473x	0.38
EP	67.25±3.58a	69.00±6.28a	66.50±6.12a	40.75±4.96b	36.25±5.12b	0.044	3.87	Y = 57.9 - 0.975x	0.24
FEKG	2.08±0.45c	2.17±0.43c	2.43±0.33c	3.36±0.66b	3.95±0.52a	0.038	5.35	Y = 3.73 - 0.164984x	0.17
FEDZ	1.36±0.44c	1.59±0.52c	1.99±0.33b	2.70±0.42a	2.95±0.36a	0.047	5.25	Y = 2.24 - 0.0587018x	0.15
EM	35.57±9.12a	37.49±8.33a	39.40±8.42a	29.86±7.77b	17.83±7.66c	0.021	4.41	Y = 30.0825 - 0.0236312x	0.17

• ¹
  All data represent the average of 24 replicates (hens) per treatment. ² FI = Feed intake (g/bird/day). EP = Egg production (%). FEKG = Feed efficiency, kg/kg (Quantity of feed (kg) to produce one kilogram (kg) of egg). FEDZ = Feed efficiency, kg/dz (Quantity of feed (kg) to produce one dozen (dz) of eggs). EM = Egg mass (g). ³ The means followed by lowercase letters in the lines differ using the Tukey test (p<0.05). Not significant = p>0.05. ⁴ CV = Coefficient of variation. ⁵ MM = Mathematical model adjusted according to the influence of the independent variable on the dependent variable.

Regarding egg production, the results showed stability across treatments with 0, 1, and 2% BST inclusion, with production rates ranging from 66.50% to 67.25%. However, significant reductions were observed at the 3% and 4% inclusion levels, with values of 40.75 ± 4.96% and 36.25 ± 5.12%, respectively (p=0.044). This result suggests that high levels of BST inclusion may compromise the laying capacity of birds, in addition to amplifying age-related effects, since older birds exhibit physiological changes that reduce their ability to adequately respond to the use of alternative ingredients (Şekeroğlu et al., 2024; Tainika et al., 2024). In older hens, there is a progressive decline in digestive efficiency, characterized by reduced enzyme secretion, decreased intestinal motility, and lower absorptive capacity of the intestinal epithelium (Şekeroğlu et al., 2024). These factors may explain the more pronounced decline in performance observed in older birds fed diets containing high levels of BST inclusion (Tainika et al., 2024; Shahid et al., 2026).

Consistent with the reductions in egg production, feed efficiency, expressed both per kilogram of eggs produced and per dozen eggs, showed improvement at low inclusion levels (1% and 2%) but deteriorated markedly at 3% and 4% BST. Feed efficiency was best in the control and 1% groups (2.08 and 2.17 kg/kg; 1.36 and 1.59 kg/dz) and poorest at 4% inclusion (3.95 kg/kg and 2.95 kg/dz), with significant differences per kilogram and per dozen eggs (p=0.038 and p=0.047, respectively). These increases indicate that greater amounts of feed were required to sustain egg output, reflecting a reduction in the efficiency of nutrient utilization. Egg mass followed a similar pattern to egg production, remaining stable up to 2% BST inclusion and declining significantly from 3% onward. While the control group presented an average egg mass of 35.57 ± 9.12 g, the lowest value was recorded at 4% inclusion (17.83 ± 7.66 g; p=0.021).

The concurrent decline in egg production and egg mass, together with the deterioration in feed efficiency at higher BST inclusions, suggests that excessive inclusion of silage impairs the birds’ capacity to convert ingested nutrients into productive output (Batalha et al., 2017; Guimarães et al., 2025). In older laying hens, physiological priorities progressively shift toward body maintenance rather than egg formation, particularly under conditions of reduced nutrient availability or utilization efficiency (Shahid et al., 2026). Thus, when combined with age-related digestive and metabolic constraints, high BST inclusion levels likely exacerbate limitations in nutrient assimilation (Tainika et al., 2024; Shahid et al., 2026), resulting in poorer productive performance.

In the final phase of the production cycle, the inclusion of BST, according to the data presented in Table 6, demonstrated a positive effect on economic indicators at moderate inclusion levels, highlighting its potential as a viable alternative ingredient for older laying hens. This response pattern suggests that BST can partially offset age-related declines in productive efficiency when included within physiologically tolerable limits (Şekeroğlu et al., 2024). Feed cost increased significantly (p=0.001) up to the 3% inclusion level, followed by a reduction at 4%. This variation may reflect both formulation costs and adjustments in birds’ feed intake. At moderate inclusion levels, the incorporation of BST may increase formulation complexity and ingredient cost, whereas at higher inclusion levels, the observed reduction in feed intake and productive performance may indirectly reduce total feed expenditure (Guimarães et al., 2025). Batalha et al. (2019), using acid silage from pirarucu, observed a similar pattern, with the lowest feed cost estimated at 3% inclusion. Similarly, Rufino et al. (2015), when evaluating tucumã meal, reported a reduction in feed cost starting from the optimal inclusion point of 5%.

Table 6
Economic analysis of the performance of older commercial hens fed diets containing increasing levels of biological silage from tambaqui by-products¹.

Variables2	Biological silage from Colossoma macropomum by-products levels, %				p-value 3	CV4, %	MM5		R²
	0.00	1.00	2.00	3.00	4.00
FC	96.46±12.46c	119.79±15.27b	132.91±22.52ab	149.07±33.45a	76.18±47.52c	0.001	13.91	Y = 90.081 + 52.986x - 13.529x2	0.76
PO	217.98±11.17b	338.94±98.88a	347.76±70.91a	360.36±103.49a	182.70±41.63c	0.001	14.68	Y = 214.6 + 164.65x - 42.39x2	0.92
PC	0.61±0.03a	0.30±0.09c	0.35±0.07c	0.44±0.16b	0.43±0.12b	0.001	13.33	Y = 0.5614 - 0.2049x + 0.0457x2	0.71
RE	163.48±8.38b	254.20±74.16a	260.82±53.18a	270.27±77.62a	137.02±31.22b	0.001	14.68	Y = 160.94 + 123.49x - 31.794x2	0.92
PR	30.57±8.38c	157.74±64.15a	141.02±45.19a	121.20±57.25b	60.84±11.29c	0.025	8.54	Y = 43.451 + 110.45x - 27.011x2	0.87
PI	18.53±4.37c	59.21±13.11a	52.61±9.55a	40.19±21.86b	41.49±17.04b	0.013	5.26	Y = 24.943 + 26.856x - 6.0414x2	0.70
BE	177.21±21.15b	128.61±17.52c	159.72±22.35b	198.75±15.15a	101.57±13.66c	0.001	13.13	Y = 156.65 + 17.383x - 6.3743x2	0.71

• ¹
  All data represent the average of 24 replicates (hens) per treatment. ² FFC = Feed Cost (R$). PO = Total Egg Production (units). PC = Production Cost per egg (R$/unit). RE = Gross Revenue (R$). PR = Gross Profit (R$). PI = Profitability Index (%). BE = Break-even point (units). ³ The means followed by lowercase letters in the lines differ using the Tukey test (p<0.05). Not significant = p>0.05. ⁴ CV = Coefficient of variation. ⁵ MM = Mathematical model adjusted according to the influence of the independent variable on the dependent variable.

Egg production increased significantly (p=0.001) from 1% to 3% inclusion, with a peak observed at the 3% level. This result indicates that the silage contributed positively to the productive performance of older birds. This improvement may be associated with the additional supply of highly digestible protein, peptides, and bioactive compounds present in BST, which can enhance nutrient availability and metabolic efficiency in aged birds (Libonatti et al., 2023). A similar trend was reported by Melo et al. (2017) with 5% yam inclusion, and by Batalha et al. (2019), who observed an estimated production of 462.93 eggs with 2.63% inclusion of acid silage from pirarucu residues.

The unit production cost per egg was significantly (p=0.001) reduced at the 1% and 2% inclusion levels, indicating greater economic efficiency. This reduction reflects a favorable balance between feed cost and productive response, in which modest BST inclusion enhances performance without substantially increasing diet cost. This result aligns with the findings of Rufino et al. (2015) and Batalha et al. (2019), who identified the lowest production cost per unit at 3.11% inclusion of acid silage. Gross revenue increased (p=0.001) from 1% to 3% inclusion levels, consistent with the rise in productivity. Studies by Rufino et al. (2017) and Batalha et al. (2019) also reported increased revenue at moderate inclusion levels (up to 5%), reinforcing the economic potential of protein-rich fish by-products in poultry feeding during the late laying phase.

Gross profit (p=0.025) and the profitability index (p=0.013) improved significantly at 1% and 2% inclusion levels. These findings indicate that moderate BST inclusion not only reduces production costs but also enhances financial return per unit of output, as observed for alternative foods by Rufino et al. (2020) and Brelaz et al. (2021). The highest profit and PI values observed in the present study are consistent with findings by Melo et al. (2017), who reported greater economic return with 5% yam inclusion, and by Batalha et al. (2019), who obtained 58.56% profitability with 3.1% inclusion of acid silage from pirarucu.

Finally, the break-even point was significantly (p=0.001) reduced at the 1% inclusion level, indicating a lower production requirement to cover variable costs, thus favoring the financial viability of the system. From a practical standpoint, a lower break-even point provides greater economic resilience, particularly under conditions of market price fluctuation and increased feed costs (Brelaz et al., 2021). Batalha et al. (2019) estimated the optimal break-even point at 1.17% inclusion, reinforcing the importance of respecting physiological limits to maximize profitability. Therefore, the inclusion of BST in the diets of older laying hens proved to be economically viable and productively promising at inclusion levels of 1 to 2%, representing an efficient and sustainable alternative for the valorization of fishery residues in late-phase poultry farming. These results demonstrate that economic advantages are maximized when BST is used as a functional supplement rather than as a major dietary component (Rufino et al., 2017; Rufino et al., 2020; Brelaz et al., 2021).

CONCLUSION

The results of this study demonstrate that BST can be used as a functional dietary additive for commercial hens, provided that its inclusion level is adjusted according to the birds’ production phase. In young hens, BST inclusion above 1% negatively affected productive performance and economic indicators, indicating limited tolerance to higher inclusion levels during the early laying phase. In contrast, older hens exhibited a more favorable response to moderate BST inclusion, with levels between 1% and 2% improving productive performance, reducing unit production cost, increasing profitability, and lowering the break-even point. However, inclusion levels ≥3% consistently impaired feed intake, egg production, egg mass, and feed efficiency in both age groups, reflecting physiological and metabolic constraints associated with excessive silage intake. Therefore, BST represents a technically and economically viable alternative ingredient when used at low inclusion levels, contributing to the valorization of fishery by-products and promoting more sustainable poultry production systems in the Amazon region. This study was limited to a single silage processing method, one genetic strain of laying hens, and a fixed experimental period under specific environmental conditions. Additionally, potential effects of BST inclusion on egg quality attributes and long-term bird health were not evaluated and should be addressed in future research.

ACKNOWLEDGEMENTS

We acknowledge Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and the Programa de Pós-Graduação em Ciência Animal e Recursos Pesqueiros (PPGCARP) of the Universidade Federal do Amazonas (UFAM) for the support in developing this study.

REFERENCES

• AOAC. Official Methods of Analysis of AOAC International. 21st ed. Rockville: AOAC; 2019.
• Aride PHR, Oliveira AM, Batista RB, et al. Changes on physiological parameters of tambaqui (Colossoma macropomum) fed with diets supplemented with Amazonian fruit Camu camu (Myrciaria dubia). Brazilian Journal of Biology 2018;78(2):360-7. https://doi.org/10.1590/1519-6984.169442
  » https://doi.org/10.1590/1519-6984.169442
• Arruda LFD, Borghesi R, Brum A, et al. Nutritional aspects of Nile tilapia (Oreochromis niloticus) silage. Food Science & Technology 2006;26:749-53. https://doi.org/10.1590/S0101-20612006000400006
  » https://doi.org/10.1590/S0101-20612006000400006
• Batalha OS, Alfaia SS, Cruz FGG, et al. Análise econômica da farinha de silagem ácida de resíduos de pirarucu em rações de poedeiras comerciais leves. Revista em Agronegógio e Meio Ambiente 2019;12(2):363-75. https://doi.org/10.17765/2176-9168.2019v12n2p363-375
  » https://doi.org/10.17765/2176-9168.2019v12n2p363-375
• Batalha OS, Alfaia SS, Cruz FGG, et al. Digestibility and physico-chemical characteristics of acid silage meal made of pirarucu waste in diets for commercial laying hens. Acta Scientiarum. Animal Sciences 2017;39(3):251-7. https://doi.org/10.4025/actascianimsci.v39i3.35112
  » https://doi.org/10.4025/actascianimsci.v39i3.35112
• Boitai SS, Babu LK, Pati PK, Pradhan CR, Tanuja S, Kumar A, Panda AK. Effect of dietary incorporation of fish silage on growth performance, serum biochemical parameters and carcass characteristics of broiler chicken. Indian Journal of Animal Research 2018;52(7):1005-9. https://doi.org/doi:10.18805/ijar.B-3315
  » https://doi.org/doi:10.18805/ijar.B-3315
• Bowles N, Alexander S, Hadjikakou M. The livestock sector and planetary boundaries: a 'limits to growth' perspective with dietary implications. Ecological Economics 2019;160:128-36. https://doi.org/10.1016/j.ecolecon.2019.01.033
  » https://doi.org/10.1016/j.ecolecon.2019.01.033
• Brelaz KCBTR, Cruz FGG, Rufino JPF, et al. Viabilidade econômica do óleo do resíduo de pescado na alimentação de poedeiras comerciais leves. Revista em Agronegógio e Meio Ambiente 2021;14(1):27-35. https://doi.org/10.17765/2176-9168.2021v14n1e007618
  » https://doi.org/10.17765/2176-9168.2021v14n1e007618
• Chatterjee S, Hadi AS. Regression analysis by example. 4th ed. Hoboken: John Wiley; 2006.
• Coppola D, Lauritano C, Palma Esposito F, et al. Fish waste: from problem to valuable resource. Marine Drugs 2021;19(2):116. https://doi.org/10.3390/md19020116
  » https://doi.org/10.3390/md19020116
• Costa APGC, Cruz FGG, Rufino JPF, et al. Tucumã meal in diets for broilers on performance, carcass traits and serum biochemical profile. Archivos de Zootecnia 2018;67:137-42. https://doi.org/10.21071/az.v67i257.3501
  » https://doi.org/10.21071/az.v67i257.3501
• Cruz FGG, Rufino JPF, Melo RD, et al. Perfil socioeconômico da avicultura no setor primário do estado do Amazonas, Brasil. Revista em Agronegógio e Meio Ambiente 2016;9:371-91. https://doi.org/10.17765/2176-9168.2016v9n2p371-391
  » https://doi.org/10.17765/2176-9168.2016v9n2p371-391
• Cruz FGG, Rufino JPF. Formulação e fabricação de rações: aves, suínos e peixes. Manaus: EDUA; 2017.
• Dadkhodazadeh V, Shabanpour B, Pourashouri P. Quality evaluation of produced silage and extracted oil from rainbow trout (Oncorhynchus mykiss) wastes using acidic and fermentation methods. Applied Food Research 2024;4:100534. https://doi.org/10.1016/j.afres.2024.100534
  » https://doi.org/10.1016/j.afres.2024.100534
• Decker AT, Rodrigues EA, Almeida JC, et al. Avaliação dos possíveis impactos ambientais dos resíduos de pescado na localidade de Pelotas/RS. Revista Brasileira de Engenharia e Sustentabilidade 2016;2(1):1-10. https://doi.org/10.15210/rbes.v2i1.6186
  » https://doi.org/10.15210/rbes.v2i1.6186
• Dormann CF, Elith J, Bacher S, et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 2013;36(1):27-46. https://doi.org/10.1111/j.1600-0587.2012.07348.x
  » https://doi.org/10.1111/j.1600-0587.2012.07348.x
• Goosen NJ, De Wet LF, Görgens JF. Rainbow trout silage as immune stimulant and feed ingredient in diets for Mozambique tilapia (Oreochromis mossambicus). Aquaculture Research 2016;47:329-40. https://doi.org/10.1111/are.12497
  » https://doi.org/10.1111/are.12497
• Guimarães CC, Silva AJI, Cruz FGG, et al. Digestibility and physicochemical characteristics of tambaqui waste biological silage meal included in commercial layer diets. Brazilian Journal of Poultry Science 2019;21:eRBCA-2018. https://doi.org/10.1590/1806-9061-2018-0869
  » https://doi.org/10.1590/1806-9061-2018-0869
• Guimarães CC, Maciel IV, Silva AF, et al. Biotechnological aspects of biological silage of tambaqui residues. Revista em Agronegógio e Meio Ambiente 2021;14(1):1-12. https://doi.org/10.17765/2176-9168.2021v14n1e006861
  » https://doi.org/10.17765/2176-9168.2021v14n1e006861
• Guimarães CC, Nóbrega TC, Santos ANA, et al. Biological silage from tambaqui (Colossoma macropomum) by-products on the productive performance, hematological parameters and egg quality of older commercial hens. Tropical Animal and Health Production 2025;57:20. https://doi.org/10.1007/s11250-024-04273-8
  » https://doi.org/10.1007/s11250-024-04273-8
• Libonatti CC, Agueria DA, Breccia J. Fish waste silage, a green process for low feedstock availability: a review. Agronomía Mesoamericana 2023;34(2):51077. https://doi.org/10.15517/am.v34i2.51077
  » https://doi.org/10.15517/am.v34i2.51077
• Lima CAS, Bussons MRFM, Oliveira AT, et al. Análise socioeconômica e lucratividade da piscicultura do tambaqui (Colossoma macropomum) no estado do Amazonas, Brasil. In: Santos A, organizador. Aquicultura na Amazônia: estudos técnico-científicos e difusão de tecnologias. Ponta Grossa: Atena Editora; 2021. p.86-102.
• Logan M. Biostatistical design and analysis using R: a practical guide. Chichester: John Wiley; 2010.
• Melo RD, Rufino JPF, Feijó JC, et al. Viabilidade econômica da farinha de cará na alimentação de poedeiras comerciais leves. Revista Brasileira de Saúde e Produção Animal 2017;18(2):221-30. https://doi.org/10.1590/S1519-99402017000200001
  » https://doi.org/10.1590/S1519-99402017000200001
• Oliveira Filho PA, Cruz FGG, Rufino JPF, et al. Inovações na formação e manejo dos ciclos de produção das poedeiras. Revista Científica de Avicultura e Suinocultura 2018;4:1-11.
• Ozyurt G, Özkütük AS, Boga M, et al. Biotransformation of seafood processing wastes fermented with natural lactic acid bacteria; the quality of fermented products and their use in animal feeding. Turkish Journal of Fisheries and Aquatic Sciences 2017;17:543-55. https://doi.org/10.4194/1303-2712-v17_3_11
  » https://doi.org/10.4194/1303-2712-v17_3_11
• Papageorgiou M, Goliomytis M, Tzamaloukas O, et al. Positive welfare indicators and their association with sustainable management systems in poultry. Sustainability 2023;15(14):10890. https://doi.org/10.3390/su151410890
  » https://doi.org/10.3390/su151410890
• Piccolo EA, Duval HC, Gallo Z, et al. A contemporaneidade da avicultura: da pré-história à liderança concorrencial brasileira. Revista Políticas Públicas & Cidades 2024;13(2):e947. https://doi.org/10.23900/2359-1552v13n2-102-2024
  » https://doi.org/10.23900/2359-1552v13n2-102-2024
• R Core Team. R: a language and environment for statistical computing [computer program]. Version 4.1.2. Vienna: R Foundation for Statistical Computing; 2021. Available from: https://www.R-project.org/
• Rossetto JF, Signor A. Technological innovations used in coproducts generated by fish processing. Pubvet 2021;15(4):1-11. https://doi.org/10.31533/pubvet.v15n04a796.1-11
  » https://doi.org/10.31533/pubvet.v15n04a796.1-11
• Rostagno HS, Albino LFT, Calderano AA, et al. Tabelas brasileiras para aves e suínos: composição dos alimentos e exigências nutricionais. 5th ed. Viçosa: Ed. UFV; 2024.
• Rufino JPF, Cruz FGG, Brasil RJM, et al. Relationship between the level and the action period of fiber in diets to laying hens. Acta Scientiarum. Animal Sciences 2021;43:e49033. https://doi.org/10.4025/actascianimsci.v43i1.49033
  » https://doi.org/10.4025/actascianimsci.v43i1.49033
• Rufino JPF, Cruz FGG, Miller WPM, et al. Análise econômica da inclusão de farinha do resíduo de tucumã (Astrocaryum vulgare Mart.) na alimentação de poedeiras comerciais. Revista Brasileira de Saúde e Produção Animal 2015;16(1):1-9. https://doi.org/10.1590/S1519-99402015000100001
  » https://doi.org/10.1590/S1519-99402015000100001
• Rufino JPF, Cruz FGG, Oliveira Filho PA, et al. Análise de viabilidade econômica do farelo do resíduo de açaí na alimentação de poedeiras comerciais leves. Revista em Agronegócio e Meio Ambiente 2020;13(3):867-82. https://doi.org/10.17765/2176-9168.2020v13n3p867-882
  » https://doi.org/10.17765/2176-9168.2020v13n3p867-882
• Rufino JPF, Melo RD, Cruz FGG, et al. Análise econômica da inclusão de farinha do resíduo de buriti na alimentação de poedeiras comerciais. Revista Ciência Agronômica 2017;48(4):732-8. https://doi.org/10.5935/1806-6690.20170085
  » https://doi.org/10.5935/1806-6690.20170085
• Santos ANA, Rufino JPF, Viana AL, et al. Paullinia cupana peel meal on the growth performance, meat quality, and haematological and serum biochemical parameters of slow-growing broilers. Animal Production Science 2024;64:AN24137. https://doi.org/10.1071/AN24137
  » https://doi.org/10.1071/AN24137
• Santos ADN, Rufino JPF, Beltrão PHSP, et al. Potential of alternative feeds in poultry nutrition: a systematic review. Worlds Poultry Science Journal 2025;1-28. https://doi.org/10.1080/00439339.2025.2540284
  » https://doi.org/10.1080/00439339.2025.2540284
• Sekeroglu A, Sentürk Y, Tainika B, et al. The impact of laying hen age, egg-laying time, cage tier, and cage direction on egg quality traits in hens in an enriched cage system. Brazilian Journal of Poultry Science 2024;26(2):eRBCA-2024-1902. https://doi.org/10.1590/1806-9061-2024-1902
  » https://doi.org/10.1590/1806-9061-2024-1902
• Shahid MAH, Jha R, Mishra B. Changes in the gut microbiome, metabolic pathways, and intestinal gene expression during the peak, mid, and decline egg production phases in laying hens. Poultry Science 2026;105(3):106372. https://doi.org/10.1016/j.psj.2026.106372
  » https://doi.org/10.1016/j.psj.2026.106372
• Silva AF, Cruz FGG, Rufino JPF, et al. Substituição do milho pelo farelo de tucumã em rações para poedeiras comerciais leves. Revista em Agronegógio e Meio Ambiente 2023;16:e7619. https://doi.org/10.17765/2176-9168.2023v16n2e7619
  » https://doi.org/10.17765/2176-9168.2023v16n2e7619
• Tainika B, Sekeroglu A, Akyol A, et al. Effects of age, housing environment, and strain on physical egg quality parameters of laying hens. Brazilian Journal of Poultry Science 2024;26(3):eRBCA-2024-1911. https://doi.org/10.1590/1806-9061-2024-1911
  » https://doi.org/10.1590/1806-9061-2024-1911
• Valenti WC, Barros HP, Moraes-Valenti P, et al. Aquaculture in Brazil: Past, present and future. Aquaculture Reports 2021;19:100611. https://doi.org/10.1016/j.aqrep.2021.100611
  » https://doi.org/10.1016/j.aqrep.2021.100611
• Van Hal O, De Boer IJM, Muller A, et al. Upcycling food leftovers and grass resources through livestock: impact of livestock system and productivity. Journal of Cleaner Production 2019;219:485-96. https://doi.org/10.1016/j.jclepro.2019.01.329
  » https://doi.org/10.1016/j.jclepro.2019.01.329
• Van Soest PV, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and non-starch polysaccharides in relation to animal nutrition. Journal of Dairy Science 1991;74(10):3583-97. https://doi.org/10.3168/jds.S0022-0302(91)78551-2
  » https://doi.org/10.3168/jds.S0022-0302(91)78551-2
• Van Zanten HHE, Herrero M, Van Hal O, et al. Defining a land boundary for sustainable livestock consumption. Global Change Biology 2018;24:4185-94. https://doi.org/10.1111/gcb.14321
  » https://doi.org/10.1111/gcb.14321
• Vidotti RM, Pacheco MTB, Gonçalves GS. Characterization of the oils present in acid and fermented silages produced from Tilapia filleting residue. Revista Brasileira de Zootecnia 2011;40:240-4. https://doi.org/10.1590/S1516-35982011000200002
  » https://doi.org/10.1590/S1516-35982011000200002
• Vidotti RM, Viegas EMM, Carneiro DJ. Amino acid composition of processed fish silage using different raw materials. Animal Feed Science and Technology 2003;105(1-4):199-204. https://doi.org/10.1016/S0377-8401(03)00056-7
  » https://doi.org/10.1016/S0377-8401(03)00056-7

• FUNDING
  None.
• DATA AVAILABILITY STATEMENT
  The data of this study are available from the corresponding author upon reasonable request.
• DISCLAIMER/PUBLISHER’S NOTE
  The published papers’ statements, opinions, and data are those of the individual author(s) and contributor(s). The editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.

Edited by

• Section Editor:
  Rodrigo Garófallo Garcia

Data availability

The data of this study are available from the corresponding author upon reasonable request.

Publication Dates

• Publication in this collection
  10 Aug 2026
• Date of issue
  2026

History

• Received
  29 June 2025
• Accepted
  11 Mar 2026