Growth Performance and Economic Feasibility of Guarana By-products in Diets for Slow-growing Broilers^I

ABSTRACT

The study evaluated the inclusion of guarana by-products, guarana peel meal (GPEM), and guarana pulp meal (GPUM) in diets for slow-growing broilers to assess their impact on growth performance and economic feasibility. To evaluate the effects of guarana by-products, two experiments were conducted. In both experiments, 240 slow-growing male broilers of the Label Rouge strain were used. Both experiment 1 (testing GPEM) and experiment 2 (testing GPUM) were conducted using a completely randomized design, with treatments consisting of a control diet (without the inclusion of the tested product) and four levels of inclusion of the tested product (2.5%, 5.0%, 7.5%, and 10%) in the diets, each with four replicates of 12 birds. GPEM, with higher fiber content, improved feed efficiency and weight gain at higher inclusion levels (up to 10%), while GPUM, with higher energy content, showed optimal performance at intermediate levels (7.5%). Both by-products enhanced meat production and economic returns compared to the basal diet. The results suggest that GPEM is suitable for systems prioritizing feed efficiency and cost-effectiveness, while GPUM is better suited for phases requiring higher energy intake and weight gain. Additionally, the use of these agro-industrial residues promotes sustainability by integrating circular economy practices into poultry production. The findings highlight the potential of guarana by-products as alternative feed ingredients to improve productivity and reduce costs, particularly in regions with abundant availability of these residues.

Keywords:
Alternative food; Amazon; feed efficiency; Paullinia cupana; sustainability

INTRODUCTION

In various regions of Brazil, especially in the Amazon, logistics for inputs significantly increase the cost of feedstuffs used in the formulation and production of balanced diets (Cruz et al., 2016). This scenario encourages research testing alternative feeds, especially those using agro-industrial residues to reduce feed costs, which can account for 60% to 80% of total production costs in activities such as poultry farming (Rufino et al., 2015; Cruz et al., 2016; Costa et al., 2018a,b; Aride et al., 2016, 2018, 2020; Polese et al., 2022). These residues are often processed into meals and incorporated into poultry diets as nutritional supplements, while also providing competitive advantages for producers (Cruz & Rufino, 2017).

The Amazon region presents numerous native species with economic, technological, and nutritional potential, which have sparked scientific interest in various fields such as food, pharmaceuticals, cosmetics, flavorings, and essences, as well as their potential applications in animal feeding (Clement et al., 2005; Oliveira et al., 2010). In this context, one fruit that is produced intensively and generates a large amount of residue during the harvest season, with potential for use in animal feed, is guarana (Paullinia cupana) (Ferreira et al., 2022). This fruit, native to the Amazon, is cultivated in several parts of Brazil and holds great economic and social importance due to its high demand from the beverage industry for the production of soft drinks and energy drinks (Espinola et al., 1997; Marques et al., 2016; Ferreira et al., 2022).

Among the poultry farming segments that require these alternative feeds, slow-growing broiler production has stood out, particularly for small and medium producers (Machado et al., 2018; Sarica et al., 2020; Cruz et al., 2023). These broilers exhibit greater tolerance to temperature variations and resistance to certain microorganisms (Sarica et al., 2020), along with a more gradual and proportional growth rate compared to fast-growing strains (Machado et al., 2018; Cruz et al., 2023). However, their longer growth period can lead to higher production costs, making these strains less economically attractive for large-scale production, though they remain appealing for alternative production systems (Lusk et al., 2019; Sarica et al., 2020).

References to the use of guarana or its by-products in poultry diets are very scarce in the literature (Santos et al., 2024). However, considering its rich nutritional properties, a high volume of production that generates residues, and its importance to Brazilian agribusiness, guarana by-products may exhibit good biological and productive potential as well as economic viability for inclusion in poultry diets (Cruz & Rufino, 2017; Costa et al., 2018a,b; Santos et al., 2024). Moreover, they contribute to a circular economy within these production chains (Cruz & Rufino, 2017; Oliveira, 2018; Ali et al., 2021). Based on this information, the present study aimed to evaluate the growth performance and economic feasibility of slow-growing broilers fed diets containing increasing levels of guarana by-products.

MATERIALS AND METHODS

The current experiment was conducted at the Faculty of Agrarian Sciences of the Federal University of Amazonas, located in Manaus City, Amazonas State, 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 010/2022).

Acquisition and composition analysis of guarana by-products

The guarana by-products were obtained in the municipality of Maués, Amazonas, located 259 km from Manaus, the state capital. The following steps were performed to obtain guarana peel meal (GPEM): 1) Ripe guarana fruits underwent a manual harvesting process; 2) The harvested fruits were stored in baskets for approximately three days, undergoing a fermentation process; 3) The fruits were separated into seeds and peels; 4) The peels were isolated as residues; 5) The seeds were processed for guarana extract extraction, used in the production of industrialized carbonated beverages; 6) The guarana peels were dried in a closed-circulation oven at 105°C for 24 hours; 7) The dried guarana peels were ground in a grain grinder using sieves with hole diameters similar to those used for corn (4 mm); and 8) the final product, referred to as GPEM, was bagged and stored in a dry and ventilated location for use in the preparation of experimental diets. To obtain guarana pulp meal (GPUM), the following steps were performed: 1) Ripe guarana fruits underwent a manual harvesting process; 2) The harvested fruits were stored in baskets for approximately three days, undergoing a fermentation process; 3) The fruits were separated into seeds and peels; 4) The seeds were processed for guarana extract extraction, used in the production of industrialized carbonated beverages; 5) The residues remaining from the seed extraction were separated and dried in a closed-circulation oven at 105°C for 24 hours; 6) these dried residues were ground in a grain grinder using sieves with hole diameters similar to those used for corn (4 mm); 7) the final product, referred to as GPUM, was bagged and stored in a dry and ventilated location for use in the preparation of experimental diets.

Before conducting the experiment, the proximate composition of both GPEM and GPUM (Table 1) was determined at the Fish Technology Laboratory of UFAM. The dry matter content was determined in an oven at 105 °C following the AOAC 925.10 (2019) method. Mineral content was assessed by incineration in a muffle furnace at 550 °C, in accordance with the AOAC 923.03 (2019) method. Lipid content analysis followed the AOCS Ba 3-38 method. Total protein was determined using the Kjeldahl method, according to AOAC 920.87 (2019). Fiber content (crude fiber, neutral detergent fiber (NDF), and acid detergent fiber (ADF)) was analyzed as described by Van Soest et al. (1991).

Table 1
Composition of guaraná by-products tested.

Variables	Guarana peel meal	Guarana pulp meal
Dry matter, %	89.11	83.93
Crude protein, %	18.72	12.27
Fats, %	5.36	2.41
Minerals, %	5.33	1.01
Crude Fiber, %	44.04	29.17
Neutral detergent fiber, %	61.66	40.84
Acid detergent fiber, %	39.64	26.25
Soluble carbohydrates, %	26.55	55.14
Gross energy, kcal/kg	6,495.65	5,745.42
Metabolizable energy*, kcal/kg	2,258.64	2,828.56

• *Determined using the apparent metabolizable energy calculation method described by Sakomura and Rostagno (2016) and Rostagno et al. (2024).

Facilities, animals and experimental design

To evaluate the effects of guarana by-products on growth performance and economic viability, two experiments were conducted, one for the inclusion of GPEM, and the other for the inclusion of GPUM.

In both experiments, a poultry house with a ceiling height of 3.25 m was used, with structural adaptations to improve bird welfare. Temperature and relative humidity were monitored using a small digital weather station, recording averages of 27.6 °C and 62.3%, respectively. Throughout the experimental period, the broilers were monitored for potential signs of heat stress caused by the environment, a condition that was not observed during the entire experimental period in either experiment.

240 slow-growing male broilers of the Label Rouge strain were used in both experiments, sourced from the Hatchery Center of UFAM’s Poultry Sector. Initially, 1-day-old chicks were housed in a brooder circle with wood shavings as bedding, tray feeders, and cup drinkers, at a density of 50 birds/m², with a central electric heating source, until they reached 7 days of age. Subsequently, they were allocated to their respective treatments in pens measuring 4 m² each, equipped with tubular feeders, pendulum drinkers, and wood shavings bedding on the floor. The experimental stages were divided into an initial (8-28 days) and a final (29-56 days), during which the birds had ad libitum access to feed and water. A lighting program suitable for slow-growing broilers was implemented (Wu et al., 2022).

Both experiment 1 (testing GPEM) and experiment 2 (testing GPUM) were conducted using a completely randomized design, with treatments consisting of a control diet (without the inclusion of the product being tested) and four levels of inclusion of the tested product (2.5%, 5.0%, 7.5%, and 10%) in the diets, each with four replicates of 12 birds. The experimental diets (Tables 2 and 3) were formulated based on the reference values of Rostagno et al. (2024), except for the GPEM and GPUM, which used values from prior compositional analyses of the product. The metabolizable energy values of these guarana by-products were determined using estimation methods described by Sakomura and Rostagno (2016) and Rostagno et al. (2024).

Table 2
Composition of the experimental diets containing guarana peel meal.

Feedstuffs	Pre-initial (1 to 7 days)	Initial (8 to 28 days)					Final (29 to 56 days)
		0	2.5	5	7.5	10	0	2.5	5	7.5	10
Corn 7,88%	58.07	58.07	54.68	51.06	47.45	43.83	63.34	62.88	59.99	56.37	52.75
Soybean meal 46%	38.32	38.35	38.69	39.06	39.44	39.82	32.53	30.64	30.89	31.27	31.64
Guarana peel meal	0.00	0.00	2.50	5.00	7.50	10.00	0.00	2.50	5.00	7.50	10.00
Limestone	0.93	0.82	0.82	0.81	0.80	0.79	1.02	1.02	0.76	0.75	0.74
Dicalcium phosphate	1.79	1.79	1.80	1.81	1.82	1.83	1.55	1.58	1.59	1.60	1.61
Common salt	0.30	0.10	0.27	0.27	0.27	0.28	0.53	0.34	0.28	0.28	0.28
Vit. Min. supplement	0.501	0.501	0.501	0.501	0.501	0.501	0.502	0.502	0.502	0.502	0.502
DL-methionine 99%	0.10	0.10	0.11	0.12	0.12	0.13	0.03	0.04	0.05	0.55	0.06
Soybean oil	0.00	0.27	0.64	1.37	2.09	2.82	0.50	0.50	0.96	1.19	2.41
Total	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00
Nutrients	Guarantee levels3
Metabolizable energy, kcal/kg	3,000.00	3,100.00	3,100.00	3,100.00	3,100.00	3,100.00	3,200.00	3,200.00	3,200.00	3,200.00	3,200.00
Dry matter, %	87.88	87.88	87.76	87.66	87.56	87.46	87.89	87.66	87.49	87.39	87.29
Crude protein, %	22.50	21.00	21.00	21.00	21.00	21.00	19.50	19.50	19.50	19.50	19.50
Calcium, %	0.94	0.90	0.90	0.90	0.90	0.90	0.80	0.80	0.80	0.80	0.80
Available phosphorus, %	0.46	0.45	0.45	0.45	0.45	0.45	0.40	0.40	0.40	0.40	0.40
Sodium, %	0.15	0.19	0.15	0.15	0.15	0.15	0.25	0.18	0.15	0.15	0.15
Crude fiber, %	3.40	3.40	4.39	5.37	6.35	7.33	3.16	4.07	5.06	6.04	7.02
NDF, %	4.76	4.76	6.15	7.52	8.89	10.26	4.42	5.70	7.08	8.46	9.83
ADF, %	3.06	3.06	3.95	4.83	5.71	6.60	2.84	3.66	4.55	5.44	6.32
Total lysine, %	1.21	1.21	1.21	1.21	1.22	1.22	1.06	1.01	1.01	1.01	1.01
Total methionine, %	0.45	0.45	0.45	0.46	0.46	0.47	0.35	0.35	0.35	0.35	0.36
Total methionine + cystine, %	0.80	0.80	0.80	0.80	0.80	0.80	0.68	0.67	0.66	0.66	0.66
Total threonine, %	0.87	0.87	0.87	0.86	0.86	0.85	0.79	0.75	0.75	0.74	0.74
Total tryptophan, %	0.28	0.28	0.28	0.28	0.28	0.29	0.25	0.24	0.24	0.24	0.24

• ¹
  Vitamin/mineral supplement - starter: Content per 1 kg of diet = Folic acid 800 mg, Pantothenic acid 12,500 mg, Antioxidant 0.5 g, Biotin 40 mg, Niacin 33,600 mg, Selenium 300 mg, Vitamin A 6,700,000 IU, Vitamin B1 1,750 mg, Vitamin B12 9,600 mcg, Vitamin B2 4,800 mg, Vitamin B6 2,500 mg, Vitamin D3 1,600,000 IU, Vitamin E 14,000 mg, Vitamin K3 1,440 mg. Mineral supplement - content per 0.5 kg = Manganese 150,000 mg, Zinc 100,000 mg, Iron 100,000 mg, Copper 16,000 mg, Iodine 1,500 mg. ² Vitamin/mineral supplement - finisher: Content per 1 kg of diet = Folic acid 650 mg, Pantothenic acid 10,400 mg, Antioxidant 0.5 g, Niacin 28,000 mg, Selenium 300 mg, Vitamin A 5,600,000 IU, Vitamin B1 550 mg, Vitamin B12 8,000 mcg, Vitamin B2 4,000 mg, Vitamin B6 2,080 mg, Vitamin D3 1,200,000 IU, Vitamin E 10,000 mg, Vitamin K3 1,200 mg. Mineral supplement - content per 0.5 kg = Manganese 150,000 mg, Zinc 100,000 mg, Iron 100,000 mg, Copper 16,000 mg, Iodine 1,500 mg. ³Levels analyzed and calculated on a dry matter basis.

Table 3
Composition of the experimental diets containing guarana pulp meal.

Feedstuffs	Pre-initial (1 to 7 days)	Initial (8 to 28 days)					Final (29 to 56 days)
		0	2.5	5	7.5	10	0	2.5	5	7.5	10
Corn 7,88%	58.07	58.07	56.27	53.17	50.10	47.00	63.34	61.57	58.49	55.40	52.31
Soybean meal 46%	38.32	38.35	35.77	35.66	35.55	35.43	32.53	30.5	30.39	30.28	30.17
Guarana pulp meal	0.00	0.00	2.50	5.00	7.50	10.00	0.00	2.50	5.00	7.50	10.00
Limestone	0.93	0.82	0.83	0.82	0.81	0.81	1.02	0.76	0.75	0.75	0.74
Dicalcium phosphate	1.79	1.79	1.82	1.84	1.85	1.87	1.55	1.58	1.60	1.61	1.63
Common salt	0.30	0.10	0.27	0.28	0.28	0.28	0.53	0.28	0.28	0.28	0.29
Vit. Min. supplement	0.501	0.501	0.501	0.501	0.501	0.501	0.502	0.502	0.502	0.502	0.502
DL-methionine 99%	0.10	0.10	0.14	0.15	0.16	0.18	0.03	0.05	0.06	0.07	0.08
Soybean oil	0.00	0.27	1.90	2.58	3.25	3.93	0.50	2.26	2.93	3.61	4.28
Total	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00	100.00
Nutrients	Guarantee levels3
Metabolizable energy, kcal/kg	3,000.00	3,100.00	3,100.00	3,100.00	3,100.00	3,100.00	3,200.00	3,200.00	3,200.00	3,200.00	3,200.00
Dry matter, %	87.88	87.88	87.86	87.67	87.58	87.50	87.89	87.76	87.59	87.42	87.35
Crude protein, %	22.50	21.00	21.00	21.00	21.00	21.00	19.50	19.50	19.50	19.50	19.50
Calcium, %	0.94	0.90	0.90	0.90	0.90	0.90	0.80	0.80	0.80	0.80	0.80
Available phosphorus, %	0.46	0.45	0.45	0.45	0.45	0.45	0.40	0.40	0.40	0.40	0.40
Sodium, %	0.15	0.19	0.15	0.15	0.15	0.15	0.25	0.15	0.15	0.15	0.15
Crude fiber, %	3.40	3.40	3.94	4.61	5.27	5.93	3.16	4.07	5.06	6.04	7.02
NDF, %	4.76	4.76	5.52	6.45	7.38	8.30	4.42	5.70	7.08	8.46	9.83
ADF, %	3.06	3.06	3.55	4.15	4.74	5.34	4.70	4.54	4.46	4.36	4.27
Total lysine, %	1.21	1.21	1.14	1.12	1.11	1.10	1.06	1,00	0,99	0,98	0,97
Total methionine, %	0.45	0.45	0.47	0.47	0.48	0.49	0.35	0,35	0,35	0,36	0,37
Total methionine + cystine, %	0.80	0.80	0.80	0.80	0.80	0.80	0.68	0,66	0,66	0,66	0,66
Total threonine, %	0.87	0.87	0.82	0.81	0.80	0.79	0.79	0,75	0,73	0,72	0,71
Total tryptophan, %	0.28	0.28	0.27	0.26	0.26	0.26	0.25	0,24	0,23	0,23	0,23

• ¹
  Vitamin/mineral supplement - starter: Content per 1 kg of diet = Folic acid 800 mg, Pantothenic acid 12,500 mg, Antioxidant 0.5 g, Biotin 40 mg, Niacin 33,600 mg, Selenium 300 mg, Vitamin A 6,700,000 IU, Vitamin B1 1,750 mg, Vitamin B12 9,600 mcg, Vitamin B2 4,800 mg, Vitamin B6 2,500 mg, Vitamin D3 1,600,000 IU, Vitamin E 14,000 mg, Vitamin K3 1,440 mg. Mineral supplement - content per 0.5 kg = Manganese 150,000 mg, Zinc 100,000 mg, Iron 100,000 mg, Copper 16,000 mg, Iodine 1,500 mg. ² Vitamin/mineral supplement - finisher: Content per 1 kg of diet = Folic acid 650 mg, Pantothenic acid 10,400 mg, Antioxidant 0.5 g, Niacin 28,000 mg, Selenium 300 mg, Vitamin A 5,600,000 IU, Vitamin B1 550 mg, Vitamin B12 8,000 mcg, Vitamin B2 4,000 mg, Vitamin B6 2,080 mg, Vitamin D3 1,200,000 IU, Vitamin E 10,000 mg, Vitamin K3 1,200 mg. Mineral supplement - content per 0.5 kg = Manganese 150,000 mg, Zinc 100,000 mg, Iron 100,000 mg, Copper 16,000 mg, Iodine 1,500 mg. ³Levels analyzed and calculated on a dry matter basis.

The guarana by-products were a fixed component in the diet calculations, with other feedstuffs values being adjusted based on the inclusion levels proposed in the experiments. The diets were formulated using the SuperCrac software (TD Software©, Viçosa, Brazil). The composition of these diets was analyzed to confirm their proximate composition according to the methods described by AOAC (2019), where moisture content was determined following method 925.10, mineral content according to method 923.03, lipid content analyses followed method Ba 3-38, total protein content was determined using method 920.87, and fiber content (crude fiber, NDF, and ADF) was determined according to the methods described by Van Soest et al. (1991).

Experimental analysis

In both experiments, during 56 days, performance data (feed intake and weight gain) were collected from the birds for use in the economic feasibility analysis following the methodological procedures described by Costa et al. (2018a,b) and Rufino et al. (2018). At 56 days of age, after a 12-hour fasting period, 12 birds from each treatment group were randomly selected for weighing, stunning by electric shock (40 V; 50 Hz), and slaughter by cutting of the jugular vein. The carcasses were then scalded in hot water (60 °C for 62 seconds), defeathered, and eviscerated following the recommendations of Mendes & Patricio (2004).

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 supplements (F1 - starter; F2 - grower; and F3 - finisher), R$ 28.35/kg (average price). The cost of GPEM and GPUM was calculated considering only transportation and handling expenses (labor), with estimated prices of R$ 0.30 and R$ 0.35 per kilogram, respectively. Fixed costs included depreciation of facilities and equipment (maintenance, water, electricity, etc.), where 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 variables were calculated based on the production of each plot. The Productive Efficiency Index (PEI) was determined using the formula:

$PEI=\frac{DWG\ast VIA{B}^{\ast }100}{FCR}$

Where:

DWG = daily weight gain of the plot (kg)

VIAB = viability of the plot (%)

FCR = feed conversion ratio of the plot (kg/kg).

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, considering both stages (R$/kg).

For total meat production (kg) and meat production per square meter (kg/m²), the carcass yield of slaughtered, scalded, defeathered, and cleaned animals was considered, as described by Costa et al. (2018b) and Rufino et al. (2018). To calculate the production cost per kilogram of meat (PCKG, R$/kg), the following formula was used:

$PCKG=\frac{CA}{PRODKG}$

Where:

FC = feed cost of the plot (R$)

PRODKG = meat production of the plot (kg).

To determine the production cost per square meter of meat (PCPSM, R$/m²), the following formula was used:

$PCPSM=\frac{CA}{PRODSM}$

Where:

FC = feed cost of the plot (R$)

PRODSM = meat production per square meter of the plot (kg/m²).

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

$REV=Q*SP$

Where:

Q = quantity of meat produced by the plot (kg)

SP = selling price per kilogram of meat produced (R$/kg).

It is important to note that the selling price per kilogram of chicken, applying a gross margin value-added calculation, was determined based on the market price in the region, fixed at R$ 8.00 per kg. Gross profit (PRO, R$) was calculated as the monetary difference between the total revenue from the estimated sale of the chickens (kilograms of chicken meat) and the discounted production cost, which 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:

$PI=\left(\frac{PRO}{REV}\right)\ast 100$

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:

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

Where:

REV = gross revenue of the plot (R$)

SP = selling price per kilogram of meat produced (R$/kg).

Statistical analyses

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 GPEM or GPUM levels

ϵ_ik = Experimental error.

All data were analyzed using one-way ANOVA with R software (2021). Commands were executed following Logan’s (2010) guidelines. Tukey’s Honest Significant Difference (HSD) test was used to examine significant differences among the GPEM or GPUM 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 AN DISCUSSION

Experiment 1

The growth performance analysis of slow-growing broilers in the starter stage indicated a significant effect (p<0.05) of GPEM inclusion on feed intake and weight gain (Table 4), with the increasing inclusion of GPEM causing a linear increase in these variables; that is, the 10% inclusion level of GPEM provided higher results. However, in the final stage, feed intake and feed efficiency showed an opposite behavior, with the increasing inclusion of GPEM reducing (p<0.05) the broilers’ feed intake, and the 10% inclusion level of GPEM providing a better feed efficiency result. In this sense, weight gain in this stage increased (p<0.05) linearly as the inclusion of GPEM in the diets increased.

Table 4
Growth performance of slow-growing broilers fed diets containing increasing levels of guarana peel meal¹.

Stage	Variables2	Guarana peel meal levels, %				p-value 3		CV4, %	COR5	MM6	R2
		0.00	2.5	5.00	7.5	10.00
Starter	FI	1.43b	1.48b	1.69a	1.71a	1.74a	<0.01	7.52	0.47	Y = 1.44 + 0.034x	0.96
	WG	0.87b	0.94b	0.98ab	1.01a	1.06a	<0.01	2.33	0.42	Y = 0.882 + 0.018x	0.94
	FE	1.64	1.57	1.72	1.69	1.64	0.10	8.28	-	-	-
Final	FI	2.95a	3.01a	2.98a	3.01a	2.63b	0.05	12.64	-0.08	Y = 2.9269 + 0.0681x - 0.0094x2	0.95
	WG	1.03b	1.04b	1.01b	1.03b	1.16a	0.05	10.69	0.20	Y = 1.004 + 0.01x	0.92
	FE	2.86a	2.89a	2.95a	2.92a	2.27b	0.05	4.59	-0.36	Y = 2.8049 + 0.1197x - 0.0166x2	0.93
General	FI	4.38	4.49	4.67	4.72	4.37	0.09	5.35	-	-	-
	WG	1.90b	1.98b	1.99b	2.04ab	2.22a	<0.01	4.69	0.29	Y = 1.886 + 0.028x	0.89
	FE	2.31a	2.27a	2.35a	2.31a	1.97b	<0.01	4.58	-0.34	y = 2.262 + 0.058x - 0.0083x2	0.91

• ¹
  All data represent the average of 48 replicates (broilers) per treatment. ² FI = Feed intake (kg/bird). WG = Weight gain (kg/bird). FE = Feed efficiency (kg/kg). 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 COR = correlation coefficient between the independent variable (GPEM levels) and the dependent variable analyzed. ⁶ MM = Mathematical model adjusted according to the influence of the independent variable (Guarana peel meal levels) on the dependent variable.

When observing the cumulative growth performance, it was found that the inclusion of GPEM did not significantly affect (p>0.05) the cumulative feed intake in the entire evaluated period. However, the cumulative results of weight gain and feed efficiency showed that these variables were significantly influenced (p<0.05) by the inclusion of GPEM, with weight gain increasing linearly, and feed efficiency improving as the levels of GPEM in the diets increased, that is, the 10% inclusion level of GPEM led to better cumulative weight gain and feed efficiency results.

The inclusion of GPEM positively impacted most growth performance variables, notably producing heavier broilers with improved feed efficiency. This result is particularly significant given that GPEM contains a considerable amount of fiber, which increased the dietary fiber levels from 4% to 7%. Despite this increase in fiber contents, broiler performance was not adversely affected by the progressive inclusion of GPEM. Fiber in poultry diets has traditionally posed challenges for researchers and industry, as the avian gastrointestinal tract exhibits limited enzymatic activity for fiber digestion, particularly in broilers, potentially restricting nutrient utilization (Azizi et al., 2021). Nonetheless, studies by González-Alvarado et al. (2010), Mateos et al. (2012), Rufino et al. (2021) and Santos et al. (2024) suggest that moderate fiber levels in poultry diets play a crucial role in enhancing physiological responses, nutrient utilization, and overall growth performance. Jiménez-Moreno et al. (2009a,b) and Svihus (2011) further emphasized that the beneficial effects of moderate fiber levels are linked to improved digestibility through continuous gizzard stimulation, enhanced small intestine activity, and a positive impact on intestinal microbiota due to the prebiotic effects of fiber.

In this sense, Pushpakumara et al. (2017) found that including up to 15% palm kernel meal in broiler diets improved feed efficiency and weight gain. Malhado et al. (2022) reported no significant effects (p>0.05) on weight gain, final weight, or feed efficiency when using barley residues in slow-growing broilers but noted a linear increase (p<0.05) in feed intake with higher barley levels. Similarly, Costa et al. (2018a) observed improved weight and production efficiency with tucumã meal inclusion, though levels above 25% negatively affected these indices.

The high fiber content in many alternative feeds derived from food processing residues can challenge nutrient metabolism and growth performance (Rufino et al., 2015; Cruz & Rufino, 2017; Liu et al., 2018; Rufino et al., 2021; Cho et al., 2024). However, residues from guarana processing like GPEM may provide additional benefits due to bioactive compounds with antioxidant, antimicrobial, and stimulating properties, potentially enhancing nutrient utilization and physiological responses (Marques et al., 2016; Yonekura et al., 2016; Cruz & Rufino, 2017).

According to the economic analysis on the performance of slow-growing broilers fed diets containing GPEM (Table 5), no significant difference (p>0.05) was observed among the treatments for the breakeven point variable. However, all other variables were significantly affected by the inclusion of GPEM.

Table 5
Economic analysis of the performance of slow-growing broilers fed diets containing increasing levels of guarana peel meal¹.

Variables2	Guarana peel meal levels, %				p-value 3		CV4, %	COR5	MM6	R2
	0.00	2.5	5.00	7.5	10.00
PRE-INI, R$/kg	3.09	3.11	3.14	3.18	3.21	-	-	-	-	-
PRE-FIN, R$/kg	2.97	2.90	2.91	2.94	2.97	-	-	-	-	-
PEI	169.91b	204.82a	204.74a	207.05a	208.47a	<0.01	6.19	0.76	Y = 173.9 + 10.556x - 0.7382x2	0.86
FC, R$	132.95b	135.05b	141.61a	144.86a	135.71b	0.03	5.45	0.48	Y = 131.28 + 3.5629x - 0.295x2	0.71
PRODKG, kg	22.92c	23.76b	23.88b	24.60b	26.76a	<0.01	7.23	0.92	Y = 22.68 + 0.3408x	0.85
PCKG, R$/kg	5.80a	5.68b	5.93a	5.89a	5.07c	0.03	8.24	-0.56	Y = 5.6826 + 0.1431x - 0.0193x2	0.73
PRODSM, kg/m²	5.73c	5.94b	5.97b	6.15a	6.69a	<0.01	7.23	0.92	Y = 5.67 + 0.0852x	0.85
PCPSM, R$/m²	33.24b	33.76b	35.40a	36.21a	33.93b	0.03	5.45	0.48	Y = 32.823 + 0.8881x - 0.0735x2	0.71
REV, R$	160.44c	166.32c	167.16c	172.20b	187.32a	<0.01	7.23	0.92	Y = 158.76 + 2.3856x	0,85
PRO, R$	27.49b	31.27b	25.55b	27.34b	51.61a	0.01	5.25	0.64	Y = 30.717 - 3.7693x + 0.5542x2	0.78
PI,	17.13b	18.80b	15.28b	15.88b	27.55a	0,03	4,86	0.56	Y = 18.79 - 2.0398x + 0.2757x2	0.73
BE, kg	18.99	19.29	20.23	20.69	19.39	0.51	5.45	-	-	-

• ¹
  All data represent the average of 48 replicates (broilers) per treatment. ² PRE-INI = Price of initial diets. PRE-FIN = Price of final diets. PEI = Productive Efficiency Index; FC = Feed Cost; PRODKG = Total Meat Production (kg); PCKG = Production Cost per kg; PRODMQ = Meat Production per m²; PCPSM = Production Cost per m²; REV = Gross Revenue; PRO = Gross Profit; PI = Profitability Index; BE = Break-even point. 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 COR = correlation coefficient between the independent variable (GPEM levels) and the dependent variable analyzed. ⁶ MM = Mathematical model adjusted according to the influence of the independent variable (Guarana peel meal levels) on the dependent variable.

In the variables of productive efficiency, total production of chicken meat in kilograms, and meat production per square meter, all broilers fed diets containing GPEM showed better results, with a gradual improvement in efficiency as the inclusion level of this alternative product increased. These findings align with results obtained by Costa et al. (2018a, b), who reported improved broiler productivity when including increasing levels of tucumã residue flour in their diets.

As mentioned above, the use of alternative foods in broiler diets often presents challenges related to the balance between their composition and the effects on bird productivity. Many of these feeds are by-products of the food processing industry, often comprising peels and seeds, which naturally contain high fiber levels (Cruz & Rufino, 2017; Rufino et al., 2021). However, depending on the specific feed used, its fiber content may vary and can be outweighed by other nutrients of nutritional interest, such as proteins and soluble carbohydrates, which affect feed efficiency and, consequently, productivity (Rufino et al., 2021; Rufino et al., 2023).

These results of productive indexes directly influence economic variables, such as feed cost, production cost per kilogram, and production cost per square meter, which were higher in several treatments that included GPEM. According to Rufino et al. (2015), higher inclusion levels of alternative foods can result in fluctuations in the production volume required to cover feed costs, affecting production costs either by increasing them, as seen in this study, or lowering them as compensation for using cheaper ingredients.

Feed cost represents a significant component of production expenses, and the use of agricultural residues in diets can impact these costs by replacing or reducing conventional ingredients (Nogueira et al., 2014; Cruz & Rufino, 2017). Economic analyses of alternative foods for poultry show that factors such as procurement logistics, production volume, and price fluctuations are crucial in deciding whether to use alternative ingredients (Silva et al., 2009; Rufino et al., 2015; Melo et al., 2017; Costa et al., 2018a,b; Batalha et al., 2019). These parameters confirm the economic viability of alternative feeds, which is closely tied to performance results (Pelizer et al., 2007; Costa et al., 2009).

In terms of gross income, gross profit, and profitability index, higher inclusion levels of GPEM yielded better results, demonstrating a positive economic impact. Despite apparent increases in production costs, productivity improvements effectively compensated for these, leading to favorable economic outcomes. According to Furtado et al. (2011), Rufino et al. (2015), Cruz & Rufino (2017), and Brelaz et al. (2021), including alternative foods in poultry diets can offer positive effects by utilizing regional agro-industrial by-products unsuitable for human consumption, reducing production costs without compromising bird performance, or enhancing productivity to offset costs. These impacts are especially significant for small and medium-scale poultry operations.

Conducting an economic and financial feasibility analysis of investments is essential, as it estimates and analyzes financial performance perspectives based on production outcomes (Rufino et al., 2018). If alternative feeds fail to achieve comparable productive and economic results to conventional feeds, they must be excluded from feed formulations or reconsidered for use under different conditions (Rufino et al., 2015).

According to Cruz & Rufino (2017), an alternative feed must meet four essential criteria to validate its use in animal production diets: (1) Proven biological composition with potential for use without anti-nutritional factors; (2) Accessible logistics, sufficient production volume, and year-round availability; (3) Cost similar to or lower than conventional feeds; and (4) A positive impact on productivity, comparable to or exceeding that of conventional diets. These criteria ensure effective technical decisions regarding the use of alternative feeds in poultry diets (Melo et al., 2017; Rufino et al., 2021; Rufino et al., 2023).

Experiment 2

The growth performance analysis (Table 6) of slow-growing broilers in the starter stage showed that increasing GPUM levels significantly (p<0.05) influenced feed intake and weight gain, with 7.5% GPUM inclusion yielding higher results for these parameters. Regarding feed efficiency, GPUM inclusion had a positive effect, as all slow-growing broilers fed diets containing GPUM demonstrated better feed efficiency than those fed the basal diet, with 5% GPUM inclusion providing the best results for feed efficiency. Similarly, in the final stage, slow-growing broilers fed diets with 7.5% GPUM inclusion exhibited higher (p<0.05) feed intake. However, in this stage, broilers fed diets with 2.5% GPUM inclusion achieved better feed efficiency. Cumulatively, all slow-growing broilers fed diets containing GPUM showed higher (p<0.05) feed intake and weight gain compared to those fed the basal diet, with 7.5% inclusion providing optimal results. Feed efficiency during this period exhibited significant (p<0.05) improvement up to 7.5% inclusion, beyond which no further improvements were observed.

Table 6
Growth performance of slow-growing broilers fed diets containing increasing levels of guarana pulp meal¹.

Stage	Variables2	Guarana peel meal levels, %				p-value 3		CV4, %	COR5	MM6	R2
		0.00	2.5	5.00	7.5	10.00
Starter	FI	1.30c	1.51b	1.52b	1.63a	1.50b	0.04	10.72	0.47	Y = 1.3051 + 0.0871x - 0.0066x2	0.89
	WG	0.50c	0.75b	0.78ab	0.82a	0.74b	<0.01	8.31	0.60	Y = 0.5151 + 0.0963x - 0.0074x2	0.95
	FE	2.61a	1.99b	1.94b	2.00b	2.02b	<0.01	14.93	-0.53	Y = 2.5446 - 0.2057x + 0.0159x2	0.87
Final	FI	2.83b	2.95b	3.10a	3.16a	3.04ab	<0.01	5.17	0.59	Y = 2.8086 + 0.0903x - 0.0065x2	0.93
	WG	1.13	1.20	1.19	1.19	1.05	0.10	8.34	-	-	-
	FE	2.49c	2.45c	2.59b	2.65b	2.90a	0.02	8.62	0.65	Y = 2.412 + 0.0408x	0.82
General	FI	4.13c	4.46b	4.63b	4.80a	4.55b	<0.01	6.44	0.57	Y = 4.1123 + 0.1798x - 0.0133x2	0.95
	WG	1.64c	1.96a	1.98a	2.01a	1.80b	<0.01	9.42	0.30	Y = 1.654 + 0.1348x - 0.012x2	0.95
	FE	2.52a	2.27c	2.33b	2.38b	2.53a	<0.01	5.67	0.13	Y = 2.276 + 0.2908x - 0.0488x2	0.82

• ¹
  All data represent the average of 48 replicates (broilers) per treatment. ² FI = Feed intake (kg/bird). WG = Weight gain (kg/bird). FE = Feed efficiency (kg/kg). 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 COR = correlation coefficient between the independent variable (GPUM levels) and the dependent variable analyzed. ⁶ MM = Mathematical model adjusted according to the influence of the independent variable (Guarana pulp meal levels) on the dependent variable.

When comparing the results of experiment 2 (GPUM) with those obtained in experiment 1 (GPEM), it stands out that GPUM promoted higher feed intake across all stages, especially at the 7.5% inclusion level, whereas GPEM showed a reduction in consumption during the final stage. This reduction may be associated with the higher fiber content, which, although potentially limiting intake, stimulates gizzard function and enhances nutrient digestibility (Sacranie et al., 2012; Jiménez-Moreno et al., 2019; Santos et al., 2024). In terms of weight gain, both guarana by-products had positive impacts, but the effect of GPEM was linear and more pronounced at higher inclusion levels (10%), while GPUM showed optimal results at 7.5%, suggesting that its nutritional profile effectively supports growth at moderate inclusion levels. Regarding feed efficiency, GPEM showed significant improvements across all stages, with the best cumulative performance at 10% inclusion, whereas GPUM achieved peak efficiency at moderate inclusion levels (5%-7.5%).

These observed differences can be primarily attributed to the fiber profile of each by-product. The higher fiber content in GPEM may have stimulated increased gizzard activity, promoting more efficient digestibility and consequently better feed efficiency, as reported in studies highlighting the benefits of moderate fiber levels in poultry diets (Sacranie et al., 2012; Abdollahi et al., 2019; Jiménez-Moreno et al., 2019; Santos et al., 2024). In contrast, GPUM, with its lower fiber content and higher metabolizable energy (2,828.56 kcal/kg for GPUM versus 2,258.64 kcal/kg for GPEM), favored more consistent feed intake and higher weight gains, which aligns with findings from other studies using agricultural by-products with moderate fiber levels (Jiménez-Moreno et al., 2009; Costa et al., 2018b; Oliveira, 2018; Rufino et al., 2024).

These results reinforce important insights reported in the literature, which suggest that the impact of fiber in poultry diets depends not only on its quantity, but also on its composition and interaction with other nutrients (Sanchez et al., 2021; Tejeda & Kim, 2021; Santos et al., 2024). Previous studies indicate that insoluble fibers, such as those in GPEM, may be more effective at stimulating gastrointestinal motility and improving digestibility in slow-growing broilers, whereas soluble fibers, present in smaller proportions in GPUM, tend to have a lesser effect on gastrointestinal function (Mateos et al., 2012; Sanchez et al., 2021; Tejeda & Kim, 2021; Machado et al., 2022).

Thus, the cumulative effects observed in both experiments underscore the importance of energy balance and nutrient profile when choosing a guarana by-product for the diet of slow-growing broilers. Overall, while GPEM demonstrated a greater ability to sustain performance throughout the production cycle, GPUM exhibited superior performance during the early and intermediate stages. This difference could have significant practical implications depending on the production system’s objectives. In systems prioritizing feed efficiency and cost reduction, GPEM emerges as a more advantageous choice (Willems et al., 2013; Zampiga et al., 2021). Conversely, GPUM may be better suited for systems aiming to maximize feed intake and weight gain during critical growth periods, particularly in nutritional strategies focused on accelerating initial growth (Willems et al., 2013; Prakash et al., 2020; Zampiga et al., 2021).

In the results of the economic analysis (Table 7), all variables evaluated in experiment 2 were statistically significant (p<0.05). Overall, the economic results from experiment 2 showed interesting differences compared to those observed in experiment 1, reflecting the distinct nutritional characteristics of the guarana by-products evaluated. Increasing levels of GPUM inclusion resulted in a proportional rise in feed cost, reaching the highest value at the 7.5% inclusion level. This was also reflected in the cost per kilogram of meat produced, which significantly increased at higher inclusion levels. These results contrast with those of experiment 1, where GPEM demonstrated greater stability in production costs, even at higher inclusion levels. As mentioned above, this difference can be partly attributed to the positive effects of GPEM’s insoluble fibers, which optimized digestibility and offset costs through superior feed efficiency (Sacranie et al., 2012; Abdollahi et al., 2019; Jiménez-Moreno et al., 2019).

Table 7
Economic analysis of the performance of slow-growing broilers fed diets containing guarana pulp meal.¹

Variables2	Guarana peel meal levels, %				p-value 3		CV4, %	COR5	MM6	R2
	0.00	2.5	5.00	7.5	10.00
PRE-INI, R$/kg	3,16	3,18	3,20	3,24	3,25	-	-	-	-	-
PRE-FIN, R$/kg	3,04	3,06	3,08	3,10	3,12	-	-	-	-	-
PEI	186.55b	214.01a	187.38b	184.17b	164.62c	0.02	12.12	-0.47	Y = 192 + 5.1206x - 0.8069x2	0.72
FC, R$	153.96c	167.25bc	174.60b	182.84a	173.69b	<0.01	7.06	0.66	Y = 153.17 + 7.2294x - 0.5027x2	0.95
PRODKG, kg	19.70c	23.59a	23.85a	24.22a	21.65b	<0.01	9.42	0.30	Y = 19.866 + 1.6452x - 0.1464x2	0.95
PCKG, R$/kg	7.82ab	7.08c	7.32bc	7.56b	8.04a	<0.01	5.87	0.29	Y = 7.7286 - 0.2421x + 0.0279x2	0.87
PRODSM, kg/m²	4.92c	5.89a	5.96a	6.05a	5.41b	<0.01	9.42	0.30	Y = 4.9609 + 0.4113x - 0.0366x2	0.95
PCPSM, R$/m²	38.49c	41.81bc	43.65b	45.70a	43.42b	<0.01	7.06	0.66	Y = 38.294 + 1.806x - 0.1256x2	0.95
REV, R$	162.78c	188.76a	190.82a	193.78a	173.20b	0.01	9.12	0.22	Y = 163.52 + 11.574x - 1.0539x2	0.96
PRO, R$	8.81b	21.50a	16.21ab	10.94b	-0.48c	0.03	9.51	-0.39	Y = 10.338 + 4.343x - 0.5509x2	0.91
PI,	4.92b	11.38a	8.46a	5.47b	-0.57c	0.02	9.75	-0.42	Y = 5.7286 + 2.1895x - 0.2865x2	0.92
BE, kg	19.24c	20.90bc	21.82b	22.85a	21.71b	<0.01	7.06	0.66	Y = 19.142 + 0.903x - 0.0627x2	0.95

• ¹
  All data represent the average of 48 replicates (broilers) per treatment. ² PRE-INI = Price of initial diets. PRE-FIN = Price of final diets. PEI = Productive Efficiency Index; FC = Feed Cost; PRODKG = Total Meat Production (kg); PCKG = Production Cost per kg; PRODMQ = Meat Production per m²; PCPSM = Production Cost per m²; REV = Gross Revenue; PRO = Gross Profit; PI = Profitability Index; BE = Break-even point. 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 COR = correlation coefficient between the independent variable (GPUM levels) and the dependent variable analyzed. ⁶ MM = Mathematical model adjusted according to the influence of the independent variable (Guarana pulp meal levels) on the dependent variable.

In terms of meat production and gross revenue, both by-products showed positive gains compared to the control, but with distinct patterns. GPUM inclusion led to higher meat production and gross revenue at intermediate levels, from 2.5% to 7.5%, reflecting its higher soluble carbohydrate content and metabolizable energy, which favored short-term productive performance (Jiménez-Moreno et al., 2009; Costa et al., 2018b; Oliveira, 2018; Rufino et al., 2024). In contrast, GPEM exhibited consistent increases in meat production and revenue across all inclusion levels.

Gross profit and profitability index indicators also highlighted important economic differences between the two by-products. GPUM showed better economic performance at intermediate levels, but its viability was compromised at extreme levels, particularly at 10% inclusion, where additional costs were not offset by increased production. This contrasts sharply with GPEM results, which maintained consistent economic outcomes across the entire range of inclusion levels, with the best results observed at 10%. This reflects GPEM’s ability to sustain stable productive and economic performance throughout the production cycle.

In general, the key point in the contrast observed in the economic results of both experiments lies in the relationship between the nutritional profiles and the economic costs of the products and their productive responses. Although the higher fiber content of GPEM may limit feed intake at certain times, it also promotes more efficient nutrient utilization, offsetting the additional costs associated with diet formulation (Mateos et al., 2012; Melo et al., 2017; Lusk et al., 2019). Conversely, GPUM, with its lower fiber content and higher energy density, is more sensitive to higher inclusion levels, as energy saturation can lead to reduced feed efficiency, directly affecting economic viability (Sacranie et al., 2012; Oliveira, 2018; Abdollahi et al., 2019).

Additionally, the difference in profitability results also reflects the composition of the by-products. GPUM, with a lower protein content (12.27%) and mineral content (1.01%), lacks some structural benefits provided by GPEM, such as greater metabolic stability and support for intestinal microbiota development (Jiménez-Moreno et al., 2019; Sanchez et al., 2021; Tejeda & Kim, 2021). This may explain why GPUM’s profitability is more affected at extreme inclusion levels, while GPEM maintains positive results due to the broader support provided by its nutritional profile. It is also important to highlight that both options contribute to a more sustainable approach to poultry production, promoting the use of agro-industrial residues and potentially reducing indirect costs (Rufino et al., 2015; Costa et al., 2018b; Batalha et al., 2019; Brelaz et al., 2019).

CONCLUSION

he inclusion of guarana by-products (GPEM and GPUM) in diets for slow-growing broilers has proven to be a viable alternative to enhance growth performance and economic feasibility, promoting the sustainable use of agro-industrial residues. GPEM, despite its higher fiber content, delivered better results in feed efficiency and weight gain at higher inclusion levels (up to 10%), while GPUM was more efficient at intermediate levels (7.5%). Both by-products contributed to greater meat production and economic returns compared to the basal diet, with positive impacts varying according to inclusion levels. The results highlight the importance of considering the specific goals of the production system when selecting the most suitable by-product. The use of GPEM is recommended for systems prioritizing feed efficiency and cost-effectiveness, while GPUM appears to be more appropriate for phases that require higher energy intake and weight gain.

ACKNOWLEDGEMENTS

We acknowledge the support of 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) in the development of this study.

REFERENCES

• Abdollahi MR, Zaefarian F, Hunt H, et al. Wheat particle size, insoluble fibre sources and whole wheat feeding influence gizzard musculature and nutrient utilisation to different extents in broiler chickens. Journal of Animal Physiology and Animal Nutrition 2019;103:146-11. https://doi.org/10.1111/jpn.13019
  » https://doi.org/10.1111/jpn.13019
• Ali A, Ponnampalam EN, Pushpakumara G, et al. Cinnamon: a natural feed additive for poultry health and production - a review. Animals (Basel) 2021;11:2026. http://doi.org/10.3390/ani11072026
  » http://doi.org/10.3390/ani11072026
• AOAC - Association of Official Agricultural Chemists. Official methods of analysis of AOAC international. 21st ed. Rockville: AOAC; 2019.
• Aride PHR, Oliveira AM, Ferreira MS, et al. Growth and hematological responses of tambaqui, Colossoma macropomum fed different levels of rice, Oryza spp.. Brazilian Journal of Biology 2020;81:1-7. https://doi.org/10.1590/1519-6984.232560
  » https://doi.org/10.1590/1519-6984.232560
• Aride PHR, Oliveira AM, Baptista 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;78:360-7. https://doi.org/10.1590/1519-6984.169442
  » https://doi.org/10.1590/1519-6984.169442
• Aride PHR, Oliveira AT, Oliveira AM, et al. Growth and hematological responses of tambaqui fed different amounts of cassava (Manihot esculenta). Arquivo Brasileiro de Medicina Veterinária e Zootecnia 2016;68:1697-704. https://doi.org/10.1590/1678-4162-8704
  » https://doi.org/10.1590/1678-4162-8704
• Azizi MN, Loh TC, Foo HL, et al. Is palm kernel cake a suitable alternative feed ingredient for poultry? Animals (Basel) 2021;11:338. https://doi.org/10.3390/ani11020338
  » https://doi.org/10.3390/ani11020338
• 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 Agronegócio e Meio Ambiente 2019;12:363-75. https://doi.org/10.17765/2176-9168.2019v12n2p363-375
  » https://doi.org/10.17765/2176-9168.2019v12n2p363-375
• Brelaz KCBTR, Cruz FGG, Rufino JPF, et al. Viabilidade econômica do óleo do resíduo de pescado na alimentação de poedeiras comerciais leves. Revista em Agronegócio e Meio Ambiente 2021;14:e007618. 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. New Jersey: John Wiley & Sons; 2006.
• Cho S, Shi H, Sureshkumar S, et al. The effects of the dietary inclusion of by-products obtained after the extraction of vitamin B2 from fermented soybean on the performance and meat quality of growing-finishing pigs. Applied Sciences 2024;14:803. https://doi.org/10.3390/app14020803
  » https://doi.org/10.3390/app14020803
• Clement CR, Lleras PE, van Leeuwen J. O potencial das palmeiras tropicais do Brasil: acertos e fracassos das últimas décadas. Agrociencias 2005;9(1/2):67-71. Available from: http://www.alice.cnptia.embrapa.br/alice/handle/doc/678989
  » http://www.alice.cnptia.embrapa.br/alice/handle/doc/678989
• Costa FGP, Goulart CC, Costa JS, et al. Desempenho, qualidade de ovos e análise econômica da produção de poedeiras semipesadas alimentadas com diferentes níveis de raspa de mandioca. Acta Scientiarum. Animal Sciences 2009;31(1):13-8. https://doi.org/10.4025/actascianimsci.v31i1.457
  » https://doi.org/10.4025/actascianimsci.v31i1.457
• 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 2018a;67:137-42. https://doi.org/10.21071/az.v67i257.3501
  » https://doi.org/10.21071/az.v67i257.3501
• Costa APGC, Cruz FGG, Rufino JPF, et al. Viabilidade econômica da farinha do resíduo de tucumã na alimentação de frangos de corte. Agropecuária Técnica (UFPB) 2018b;38(4):225-33. https://doi.org/10.25066/agrotec.v38i4.28894
  » https://doi.org/10.25066/agrotec.v38i4.28894
• Cruz FGG, Rufino JPF, Melo RD, et al. Perfil socioeconômico da avicultura no setor primário do Estado do Amazonas, Brasil. Revista em Agronegócio e Meio Ambiente 2016;9(2):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.
• Cruz FL, Carvalho FP, Marçal JO, et al. Fatty acid profile of slow-growing broilers supplemented with biocomplexed minerals. Ciência Rural 2023;53(5):e20210525. https://doi.org/10.1590/0103-8478cr20210525
  » https://doi.org/10.1590/0103-8478cr20210525
• 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;36:27-46. https://doi.org/10.1111/j.1600-0587.2012.07348.x
  » https://doi.org/10.1111/j.1600-0587.2012.07348.x
• Espinola EB, Dias RF, Mattei R, et al. Pharmacological activity of Guaraná (Paullinia cupana Mart) in laboratory animals. Journal of Ethnopharmacology 1997;55:223-9. https://doi.org/10.1016/s0378-8741(96)01506-1
  » https://doi.org/10.1016/s0378-8741(96)01506-1
• Ferreira FAM, Ferreira BB, Bragança VAN, et al. Guaraná (Paullinia cupana Kunth), marapuama (Ptychopetalum olacoides Benth.), gentian (Gentiana lutea L.), quassia (Quassia amara L.) and their properties: a brief review. Research, Society and Development 2022;11(2). https://doi.org/10.33448/rsd-v11i2.24592
  » https://doi.org/10.33448/rsd-v11i2.24592
• Furtado DA, Carvalho Junior SB, Lima ISP, et al. Desempenho e características de carcaça de aves caipiras alimentadas com feno de erva-sal (Atriplex nummularia lindl.). Revista Caatinga 2011;24:182-91.
• González-Alvarado JM, Jimenez-Moreno E, González-Sanchez D, et al. Effect of inclusion of oat hulls and sugar beet pulp in the diet on productive performance and digestive traits of broilers from 1 to 42 days of age. Animal Feed Science and Technology 2010;162:37-46. https://doi.org/10.1016/j.anifeedsci.2010.08.010
  » https://doi.org/10.1016/j.anifeedsci.2010.08.010
• Jiménez-Moreno E, González-Alvarado JM, Coca-Sinova A, et al. Effects of source of fibre on the development and pH of the gastrointestinal tract of broilers. Animal Feed Science and Technology 2009;154:93-101. https://doi.org/10.1016/j.anifeedsci.2009.06.020
  » https://doi.org/10.1016/j.anifeedsci.2009.06.020
• Jiménez-Moreno E, González-Alvarado JM, Lázaro R, et al. Effects of type of cereal, heat processing of the cereal, and fiber inclusion in the diet on gizzard pH and nutrient utilization in broilers at different ages. Poultry Science 2009;88:1925-33. https://doi.org/10.3382/ps.2009-00193
  » https://doi.org/10.3382/ps.2009-00193
• Jiménez-Moreno E, González-Alvarado JM, de Coca-Sinova A, et al. Insoluble fiber sources in mash or pellets diets for young broilers. 2. Effects on gastrointestinal tract development and nutrient digestibility. Poultry Science 2019;98(6):2531-47. https://doi.org/10.3382/ps/pey599
  » https://doi.org/10.3382/ps/pey599
• Liu CW, Zhou HS, Kim MY, et al. Impacts of rapeseed meal, canola meal and their mixture substitute for soybean meal on performance of lactating sows and their offspring. Indian Journal of Animal Research 2018;53:124-8. https://doi.org/10.18805/ijar.B-837
  » https://doi.org/10.18805/ijar.B-837
• Logan M. Biostatistical design and analysis using R: a practical guide. New Jersey: John Wiley & Sons; 2010.
• Lusk JL, Thompson NM, Weimer SL. The cost and market impacts of slow-growth broilers. Journal of Agricultural and Resource Economics 2019;44(3):536-50. https://doi.org/10.22004/ag.econ.292330
  » https://doi.org/10.22004/ag.econ.292330
• Machado NJB, Lima CAR, Brasil RJM, et al. Digestible threonine for slow-growing broilers: performance, carcass characteristics, intestinal mucin, and duodenal morphometry. Revista Brasileira de Zootecnia 2018;47:e20170193. https://doi.org/10.1590/rbz4720170193
  » https://doi.org/10.1590/rbz4720170193
• Machado ALN, Alves JR, Lima HJD, et al. Barley residue levels in the diet of Label Rouge broilers. Revista Acadêmica Ciência Animal 2022;20:e20002. https://doi.org/10.7213/acad.2022.20002
  » https://doi.org/10.7213/acad.2022.20002
• Marques LLM, Panizzon GP, Aguiar BAA, et al. Guaraná (Paullinia cupana) seeds: Selective supercritical extraction of phenolic compounds. Food Chemistry 2016;212:703-11. https://doi.org/10.1016/j.foodchem.2016.06.028
  » https://doi.org/10.1016/j.foodchem.2016.06.028
• Mateos GG, Jiménez-Moreno E, Serrano MP, et al. Poultry response to high levels of dietary fiber sources varying in physical and chemical characteristics. Journal of Applied Poultry Research 2012;21:156-74. https://doi.org/10.3382/japr.2011-00477
  » https://doi.org/10.3382/japr.2011-00477
• Melo RD, Cruz FGG, 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
• Mendes AA, Patrício IS. Controles, registros e avaliação do desempenho de frangos de corte. In: Mendes AA, Nääs IA, Macari M. Produção de frangos de corte. Campinas: FACTA; 2004.
• Nogueira MA, Cruz FGG, Tanaka ES, et al. Suplementação de óleo de dendê (Elaeis guineensis Jaquim) na alimentação de poedeiras leves em clima tropical. Revista Acadêmica Ciência Animal 2014;12(2):103-111.
• Oliveira PR, Costa CA, Bem GF, et al. Effects of an extract obtained from fruits of Euterpe oleracea Mart. in the components of metabolic syndrome induced in C57BL/6J mice fed a high-fat diet. Journal of Cardiovascular Pharmacology 2010;56(15):619-26. https://doi.org/10.1097/fjc.0b013e3181f78da4
  » https://doi.org/10.1097/fjc.0b013e3181f78da4
• Oliveira DHR. Alternative food for broiler chickens: an overview. Scientific Electronic Archives 2018;11:112-7. https://doi.org/10.36560/1152018691
  » https://doi.org/10.36560/1152018691
• Pelizer LH, Pontieri MH, Moraes IO. Utilização de resíduos agroindustriais em processos biotecnológicos como perspectiva de redução de impacto ambiental. Journal of Technology Management & Innovation 2007;2(1):118-27. Available from: https://www.jotmi.org/index.php/GT/article/view/art41
  » https://www.jotmi.org/index.php/GT/article/view/art41
• Prakash A, Saxena VK, Singh MK. Genetic analysis of residual feed intake, feed conversion ratio and related growth parameters in broiler chicken: a review. World's Poultry Science Journal 2020;76(2):304-17. https://doi.org/10.1080/00439339.2020.1735978
  » https://doi.org/10.1080/00439339.2020.1735978
• Polese MF, Polese MF, Radael MC, et al. Zootechnical parameters of Corn feed particle size in performance, digestibility and rate of passage in juvenile tambaqui Colossoma macropomum. Brazilian Journal of Biology 2022;82:1-13. https://doi.org/10.1590/1519-6984.232612
  » https://doi.org/10.1590/1519-6984.232612
• Pushpakumara DMS, Priyankarage N, Nayananjalie WAD, et al. Effect of inclusion of palm (Elaeis guineenses) kernel cake in broiler chicken rations. International Journal of Livestock Research 2017;7:103-9. http://doi.org/10.5455/ijlr.20170201053413
  » http://doi.org/10.5455/ijlr.20170201053413
• Rostagno HS, Albino LFT, Calderano AA, et al. Tabelas brasileiras para aves e suínos: composição dos alimentos e exigências nutricionais. 5th ed. Viçosa: Editora da Universidade Federal de Viçosa; 2024.
• 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, Feijó JC, et al. Análise econômica de patos submetidos a diferentes planos nutricionais fásicos e densidades de alojamento. Revista em Agronegócio e Meio Ambiente 2018;11(3):767-81. https://doi.org/10.17765/2176-9168.2018v11n3p767-781
  » https://doi.org/10.17765/2176-9168.2018v11n3p767-781
• 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, Oliveira Filho PA, et al. Farelo de açaí (Euterpe precatoria) como alimento alternativo em dietas para poedeiras comerciais leves. Revista em Agronegócio e Meio Ambiente 2023;16:e11466. https://doi.org/10.17765/2176-9168.2023v16n4e11466
  » https://doi.org/10.17765/2176-9168.2023v16n4e11466
• Sacranie A, Svihus B, Denstadli V, et al. The effect of insoluble fiber and intermittent feeding on gizzard development, gut motility, and performance of broiler chickens. Poultry Science 2012;91(3):693-700. https://doi.org/10.3382/ps.2011-01790
  » https://doi.org/10.3382/ps.2011-01790
• Sakomura NK, Rostagno HS. Métodos de pesquisa em nutrição de monogástricos. Jaboticabal: Funep; 2016.
• Sanchez J, Barbut S, Patterson R, et al. Impact of fiber on growth, plasma, gastrointestinal and excreta attributes in broiler chickens and turkey poults fed corn- or wheat-based diets with or without multienzyme supplement. Poultry Science 2021;100(8):101219. https://doi.org/10.1016/j.psj.2021
  » https://doi.org/10.1016/j.psj.2021
• 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
• Sarica M, Yamak U, Boz M, et al. Performance of fast, medium and slow growing broilers in indoor and free-range production systems. South African Journal of Animal Science 2020;49:1127-38. https://doi.org/10.4314/sajas.v49i6.16
  » https://doi.org/10.4314/sajas.v49i6.16
• Silva EP, Rabello CBV, Dutra Júnior WM, et al. Análise econômica da inclusão dos resíduos de goiaba e tomate na ração de poedeiras comerciais. Revista Brasileira de Saúde e Produção Animal 2009;10(4):774-85.
• Svihus B. The gizzard: function, influence of diet structure and effects on nutrient availability. World's Poultry Science Journal 2011;67:207-24. https://doi.org/10.1017/S0043933911000249
  » https://doi.org/10.1017/S0043933911000249
• Tejeda OJ, Kim WK. Effects of fiber type, particle size, and inclusion level on the growth performance, digestive organ growth, intestinal morphology, intestinal viscosity, and gene expression of broilers. Poultry Science 2021;100(10):101397. https://doi.org/10.1016/j.psj.2021.101397
  » https://doi.org/10.1016/j.psj.2021.101397
• Van Soest PJ, Robertson JB, Lewis BA. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. Journal of Dairy Science 1991;74:3583-97. https://doi.org/10.3168/jds.s0022-0302(91)78551-2
  » https://doi.org/10.3168/jds.s0022-0302(91)78551-2
• Willems OW, Miller SP, Wood BJ. Aspects of selection for feed efficiency in meat producing poultry. World's Poultry Science Journal 2013;69(1):77-88. https://doi.org/10.1017/S004393391300007X
  » https://doi.org/10.1017/S004393391300007X
• Wu Y, Huang J, Quan S, et al. Light regimen on health and growth of broilers: an update review. Poultry Science 2022;101:101545. https://doi.org/10.1016/j.psj.2021.101545
  » https://doi.org/10.1016/j.psj.2021.101545
• Yonekura L, Martins CA, Sampaio GR, et al. Bioavailability of catechins from guaraná (Paullinia cupana) and its effect on antioxidant enzymes and other oxidative stress markers in healthy human subjects. Food & Function 2016;7:2970-8. https://doi.org/10.1039/c6fo00513f
  » https://doi.org/10.1039/c6fo00513f
• Zampiga M, Calini F, Sirri F. Importance of feed efficiency for sustainable intensification of chicken meat production: implications and role for amino acids, feed enzymes and organic trace minerals. World's Poultry Science Journal 2021;77(3):639-59. https://doi.org/10.1080/00439339.2021.1959277
  » https://doi.org/10.1080/00439339.2021.1959277

• 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:
  Irenilza A. Nääs

Data availability

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

Publication Dates

• Publication in this collection
  30 June 2025
• Date of issue
  2025

History

• Received
  09 Jan 2025
• Accepted
  27 Feb 2025