Research Article

Evaluation of the Physicochemical Properties of an Extruded Cattle Feed Added with Huizache (Vachellia Schaffneri) and its Impact on In Vitro Digestibility

García Domínguez María Fernanda1, Páez Lerma Jesús Bernardo1, Reyes Jáquez Damián1, Carrete Carreón Francisco Oscar2, Rosas Guerra María Inés1, Araiza Rosales Elia Esther2*

1Tecnológico Nacional de México/Instituto Tecnológico de Durango, Blvd. Felipe Pescador 1830, Nueva Vizcaya, 34080 Durango, Dgo; 2Universidad Juárez del Estado de Durango, Facultad de Medicina Veterinaria y Zootecnia. Carretera al Mezquital Km 11.5. Durango, Dgo.

Received | August 28, 2024; Accepted | January 14, 2025; Published | February 01, 2025

*Correspondence | Araiza Rosales Elia Esther, Universidad Juárez del Estado de Durango, Facultad de Medicina Veterinaria y Zootecnia. Carretera al Mezquital Km 11.5. Durango, Dgo; Email: [email protected]

Citation | Fernanda GDM, Bernardo PLJ, Damián RJ, Oscar CCF, Inés RGM, Esther ARE (2025). Evaluation of the physicochemical properties of an extruded cattle feed added with huizache (Vachellia schaffneri) and its impact on In vitro digestibility. J. Anim. Health Prod. 13(1): 29-37.

DOI | https://dx.doi.org/10.17582/journal.jahp/2025/13.1.29.37

ISSN (Online) | 2308-2801

Copyright © 2025 Kumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Copyright: 2025 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

The current population growth requires increases in livestock production to meet the food demand (INEC, 2018). According to the FAO (2017), by 2050, the population will exceed the alarming figure of 9 billion people. However, the increase in agricultural production implies a greater exploitation of natural wealth (Carro et al., 2018), which is increasingly constrained by the increase in greenhouse gases that cause climate change (Garcia et al., 2020). In the search for alternatives to avoid competition to produce food for consumption, the limitations of planting areas, in addition to reducing the environmental impact, developing non-conventional livestock feeds has been chosen by incorporating plants with little or no use in cattle feed (Holguín et al., 2020). Using these tree or shrub plants to develop livestock feed could benefit arid areas susceptible to food shortages without becoming competition for human food (Pámanes et al., 2021). Huizache (HUI) is a shrubby legume distributed in Mexico, whose leaves and pods are used as a nutritional supplement in animal feed (Zarza et al., 2020) for its protein content that allows it to be used in diets to produce livestock species (Gómez, 2019). The use of plants such as HUI could reduce dependence on the use of external ingredients, thus minimizing damage to natural resources. Technologies such as extrusion make possible to explore the use of various inputs for feed formulation (Verhelts, 2019). Extrusion is a versatile and modern process that can transform agricultural products into fully cooked food products (Cotacallapa et al., 2021) using high processing temperatures in relatively short times (da Silva et al., 2018), without significantly altering the nutritional value of the food (Leonard et al., 2020). Therefore, this research aimed to evaluate the effect of temperature, moisture content and HUI content of an extruded cattle feed on its physicochemical properties and in vitro digestibility.

MATERIALS AND METHODS

Ingredients

HUI (Vachellia schaffneri) was collected from Francisco I. Madero, Durango, México in March 2021. The branches were sampled to collect leaves; the leaves were dried in a forced-air oven until constant weight at 55 °C, and the leaves were ground in a knife mill fitted with a 1 mm mesh to obtain a homogeneous sample for further analysis. Flour, soybean paste, soybean husks, distillers’ dried grains, ground corn (MM) and molasses were purchased from commercial feed stores in Durango, Mexico.

Formulation/Experimental Treatments

A balanced feed of 12% crude protein (CP) was formulated for fattening cattle (NRC, 2001) with the inclusion of HUI (X3) in percentages of 0-10%, according to the experimental design. The ingredients used for the formulation of the feed are shown in Table 1. The proportion of ingredients that remained constant in the formulation consisted of 21% soybean husks, 4% distillers’ dried grains, 6% cane molasses, 5% soybean paste, 3.5% flour, and 3.5% wheat bran. The HUI substituted ground corn (GC) so that eight different treatments with different HUI and GC ratios were evaluated: 57:0, 56.94:0.06, 53.62:3.38, 53.43:3.57, 51.07:5.93, 51.01:5.99, 50.84:6.16 and 47:10.

Chemical Composition

The determination of CP, dry matter (DM), ash (ASH) and ether extract (EE) of ingredients and feeds was performed using AOAC (2019) standard methods. Cell wall components such as neutral detergent fibre (NDF), acid detergent fibre (ADF) and lignin (LIG) were determined using an ANKOM Fiber Analyzer (ANKOM Technologies, USA) and according to the calculations proposed by Van Soest et al. (1991). Non-structural carbohydrates (NSC) were determined by difference using Equation 1.

NSC=[100-(PC+EE+ASH+NDF)]

Extrusion Process

The extrusion of the treatments was conducted using a Brabender single-screw extruder (Duisburg Germany) with a 1:1 compression ratio, screw speed at 150 rpm, feed speed at 45 rpm, a 6 mm output die and four heating zones, with the first three at constant temperatures of 90, 100 and 110 °C, respectively, while the fourth temperature (X1) was varied according to the experimental design. The treatments’ moisture content (X2) was adjusted before the extrusion process following the experimental design. The desired humidity level was adjusted by sprinkling distilled water into the ingredients and mixing it by hand for 15 minutes. Moistened mixtures were refrigerated at 4 °C and stored in sealed polyurethane bags for at least 12 hours before being extruded. Upon completion, the extruded samples were placed in trays to cool down at room temperature for 1 hour. They were then packed in polyurethane bags and refrigerated for further analysis.

 

Table 1: Chemical composition of ingredients in experimental treatments [g/100 g].

Ingredients	MS	CE	PC	USA	FDN	FDA	LIG
Huizache	93.41± 2.769	6.61± 0.002	14.01± 0.263	1.34±0.265	39.54±1.981	32.86±1.91	8.15±0.685
Ground corn	89.34± 0.417	0.74± 0.377	6.53± 0.304	1.89±0.0003	13.13±0.125	3.18±0.079	-
Wheat bran	89.72± 0.876	6.44± 0.312	15.23± 0.195	1.46±0.021	36.83±1.25	13.35±0.566	1.69±0.142
Soybean husks	89.31± 2.838	4.41± 0.375	12.39± 0.287	1.01±0.012	58.39±0.075	44.47±0.395	1.34±0.169
Soybean paste	90.51± 0.257	7.14± 0.551	40.57± 0.922	0.98±0.036	5.31±0.483	3.34±0.243	0.34±0.056
Distiller's grains	90.51± 0.257	7.16± 0.169	27.49± 0.103	4.61±0.079	40.65±0.221	14.23±0.221	1.93±0.444
Flour mill	87.82± 0.278	6.94± 0.291	41.93± 0.855	3.82±0.078	27.15±0.936	17.77±0.646	4.23±1.082
Molasses	76.25± 2.756	10.72± 0.397	5.36± 0.359	-	-	-	-

 

MS: dry matter; PC: crude protein; EE: ethereal extract; CE: ash; NDF: neutral detergent fiber; FDA: acid detergent fiber; LIG: lignin. Results are expressed as the mean ± standard deviation.

 

Experimental Design and Data Analysis

A D-optimal experimental design with three independent variables was conducted using the Design-Expert 13.0 software (State-Ease Inc., Minneapolis, MN, USA), and 15 experimental treatments were obtained. The evaluated factors were X1 = die outlet temperature [90-150 °C], X2 = moisture content [14-18%] and X3 = HUI content [0-10%]. The responses of the experimental design were expansion index (EI), bulk density (BD), hardness (H), water absorption index (WAI), water solubility index (WSI), total phenols (TP), condensed tannins (CT) and in vitro dry matter digestibility (IVDMD. The results were analyzed by multiple quadratic regressions (Equation 2). Regression coefficients were obtained by fitting the experimental data to the quadratic model. The statistical significance of the coefficients (p<0.05) was evaluated through an analysis of variance for each response. A numerical optimization was performed through the methodology of overlapping response surfaces for each treatment.

Y= B0+B1 X1+B2 X2+B3 X3+B11 X12+B22 X22+B33 _32+B12 X1 X2+B13 X1 X3+B23 X2 X3

Physicochemical Properties

Expansion index and bulk density: The technique described by Oke et al. (2013) was used to determine EI and BD. For BD, ten extruded samples were randomly selected and then the average value of the diameter (d) was obtained with three measurements of each extruded. After that, the length (l) was measured, and each extruded sample (Pm) was weighed. The BD was obtained using Equation 3. For EI, the average value of the diameter was divided by the diameter of the outlet die hole.

Hardness: H was evaluated using a Universal Texture Analyzer TA-XT2 (Texture Technologies Corp., Scarsdale, NY/Stable MicroSystems, Haslemere, Surrey, UK) with the Warner Bratzler blade. Fifteen extruded samples were measured per treatment, at a speed of 1 mm/s, recording the average of the maximum hardness.

Water absorption index and water solubility index: WAI and WSI were evaluated as described by Ding et al. (2005). One gram of ground product was sifted into a No. 40 mesh (0.420 mm). The sample was mixed in 10 mL of distilled water, then stirred for 30 min and centrifuged at 3000 x for 15 min. The resulting supernatant was decanted into a previously tared vessel. With the gel’s weight obtained after the supernatant removal, the WAI was calculated as the unit weight of the solids on a dry basis and expressed as grams of water retained per gram after removal of the sample supernatant (g/g), while WSI was obtained by evaporating the supernatant and was expressed as the weight of the dry solids in the supernatant as a percentage of the original weight of the sample (%).

Phenolic compounds: To obtain the extracts, 0.5 g of sample was mixed and agitated in 45 mL of 70% ethanol for 24 h at room temperature. The extracts were filtered and dried until the ethanol was removed in the extraction hood. Yields were calculated based on the dry sample.

Total Phenols and Condensed Tannins

TP were determined using the Folin-Ciocalteu method, and CT were determined using the vanillin method, both described by Heimler et al. (2005), using gallic acid and catechin as standards, respectively.

In Vitro Dry Matter Digestibility

IVDMD was determined with a Daisy digester (ANKOM Technology, Fairport, NY, USA) according to the manufacturer’s manual of techniques (ANKOM, 2017) using an inoculum prepared from buffer solutions and liquid extracted from a fistulated bovine in a 2:1 ratio.

RESULTS AND DISCUSSION

Chemical Composition of Ingredients

Table 1 shows the chemical composition of the feed ingredients. The CP content of the HUI was 14%, which differs from other authors (Zapata et al., 2020: Araiza et al., 2022a), who analyzed the foliage of the huizache and found a CP content of 17%. However, these variations in CP content may be due to the place of origin of the collected material (Velázquez et al., 2011). According to Mamani and Cotacallapa (2018), the CP content is variable in different harvest sites, attributed to factors related to soil fertility and the phenological state of the plant, so, based on its collection, it still needs to have its maximum nutritional potential. On the other hand, the CP content of HUI was higher than that of ground corn, so the substitution of HUI for ground corn makes a protein contribution to the feed.

Physicochemical Properties

Table 2 shows the regression coefficients obtained from the responses of the extruded samples.

Expansion Index and Bulk Density

EI and BD are related to product expansion and are inversely related since the increase in EI results in a decrease in BD and vice versa. According to the regression coefficients in Table 2, X2 had a significant negative effect on the IE (p<0.05) in its linear term, which is consistent with Lourenço et al. (2016), who found that EI decreased due to

 

Table 2: Regression coefficients of responses of extruded HUI treatments.

	Coefficients
Responses	Intercept	Linear			Interaction			Quadratic			R2
	b0	X1	X2	X3	X1 X2	X1 X3	X2 X3	X12	X22	X32
EI	1.1	-0.003	-0.022	0.001	0.010	-0.009	0.008	-0.005	0.023	0.003	0.489
BD	1175.13	-39.24	26.95	19.98	-13.16	-13.09	-37.2	-10.55	8.91	14.01	0.801
H	126.13	-7.24	11.52	5.45	-5.9	7.21	-6.56	6.98	6.77	-1.02	0.603
WSI	9.78	-0.235	-0.004	-0.215	-0.097	-0.514	0.509	0.015	-0.377	-0.466	0.628
WAI	3.55	0.203	0.177	-0.108	-0.098	-0.065	-0.003	0.063	-0.044	0.033	0.656
IVDMD	89.26	0.986	-1.45	1.61	-0.219	-0.608	-0.641	1.6	0.056	-1.39	0.882
TC	0.118	-0.005	-0.001	0.054	0.002	-0.004	0.005	0.003	0.004	0.01	0.917
TF	0.199	-0.007	-0.003	0.078	-0.001	-0.022	-0.001	-0.003	-0.013	0.008	0.986

 

X1: temperature (°C); X2: humidity (%); X3: Huizache content (%). EI: expansion index (-); BD: bulk density kg/m3; H: hardness (N); WSI: water solubility index (%); WAI: water absorption index (g/g); IVDMD: in vitro dry matter digestibility (%); TC: condensed tannins (%); TF: total phenols (%).

 

an increase in humidity, showing that humidity was a factor with a predominant effect on EI and, therefore, on BD (Ding et al., 2005). In turn, X2 had a positive effect on BD (p<0.05). In addition, the elasticity of the dough is reduced as there is higher moisture content through the plasticization of the molten material, which consequently results in less gelatinization (Nkubana et al., 2020), thus reducing expansion and, in turn, increasing density and hardness. On the other hand, during the extrusion process, there is a sudden pressure drop when the treatment comes out of the extruder, due to the change from high pressure to atmospheric pressure conditions (Altan et al., 2008). In this process, the water nucleates, causing the formation of bubbles in the extruded material, generating an expansion due to the sudden evaporation of moisture caused by the pressure drop (Kamarudin et al., 2018). However, an increase in X2 causes the bubbles within the extruded to collapse after expansion at the matrix outlet due to reduced viscosity (Kantrong et al., 2018), as it has been reported that in products with lower humidity, being more viscous, they have a more significant expansion than those with higher humidity (Delgado et al., 2021). As the pressure differential is higher for products with low moisture due to the drag generating more pressure on the die (Oke et al., 2013), EI decreases when the moisture content increases. X1 showed a significant negative effect on BD (p<0.05), while X3 had a positive effect (p>0.05) on BD (both in their linear terms), which is consistent with previous researches (Bisharat et al., 2013; Sharma et al., 2017). The increase in X3 increased BD, as the protein and rigid fiber of the HUI flour prevented the expansion of the air bubbles and reduced the formation and retention of expanded air pockets due to the rupture of the cell walls (Ravindran et al., 2011; Pérez et al., 2017), which was probably caused by the increased friction between the fed material and the surface of the barrel as a result of the increase in viscous dissipation of the mass (Martinez et al., 2011). As fibre- and protein-rich materials are added to extruded products, density is expected to increase. As for X1, the high extrusion temperature and shear force generate heat that causes the water to overheat as the extruded exits the die (Gopirajah and Muthukumarappan, 2018), which encourages the formation of bubbles and generates a lower viscosity, forming a lighter structure and therefore less dense and hard (Fletcher et al., 1985; Jiangping et al., 2017).

Hardness

H is a property defined as the maximum force needed to penetrate a product by a probe (Charunuch et al., 2014). According to the analysis, X2 has a significant positive effect on its linear term on H (p<0.05), which indicates that as humidity increases from 14 to 18%, hardness increases, which is consistent with the positive effect of humidity on BD and the negative effect on EI that was previously described. Sharma et al. (2017) found that higher humidity significantly increased H since this factor participates as a plasticizer of the matter found within the extruder, which results in lower viscosity and a decrease in energy dissipation. Therefore, bubble growth is compressed at the outlet, generating a more rigid product.

Water Absorption Index and Water Solubility Index

The WAI describes the degree of starch gelatinization as it relates to the amount of water that is absorbed by starch granules when they are in excess water (Alcázar and Almeida, 2015), so it depends on the hydrophilic groups that are free to bind to water molecules and also on the ability of macromolecules to form a gel (Néder et al., 2016). WSI is defined as the number of soluble polysaccharides released from the granules after the addition of excess water and indicates the degree of degradation of the molecular components (Rodríguez et al., 2011). A high WSI reflects the presence of solutes from gelatinization and is sometimes attributed to starch dextrinization. In contrast, a high WAI indicates the presence of large starch fragments due to lower starch degradation (Ravindran et al., 2011). The positive coefficients of X1 and X2 in their linear terms had a significant effect on WAI (p < 0.05), while X3 had a negative effect on WAI (p < 0.05).

The effect of X1 on the WAI is consistent with other reports (Singh and Muthukumarappan, 2014; de Cruz et al., 2015). At elevated temperatures, the crystalline structure of the starch is destroyed, which allows it to retain more water (Pérez et al., 2019) due to an increase of exposed hydroxyl groups (Zhang et al., 2014), forming an expanded matrix that absorbs more water by separating the amylopectin and amylose branches (Jiangping et al., 2017). On the other hand, the positive linear coefficient of humidity indicates that the increase in humidity from 14 to 18% also increases WAI, which is consistent with other researches where the WAI increases with a higher moisture content (Kothakota, 2013; Gat and Ananthanarayan, 2015). Leonard et al. (2015) and Gulati et al. (2016) explained that higher humidity coupled with higher temperature causes the viscosity of the material to be lower, which promotes extensive internal mixing and uniform heating that improves starch gelatinization and increases WAI.

A lower WAI due to the increase in X3 in the extrudates may be attributed to the higher fiber input by the HUI and the reduction of starch, which was observed by Ajita and Jha (2017), where they found a lower WAI in extruded plants with a higher percentage of wheat bran, since the substitution of starch for the fiber component, decreases starch gelatinization. In addition, starch gelatinization was probably limited by an increased interaction between the hydrophilic groups available in the protein with the starch caused by the increase in HUI (Sharma et al., 2017).

Regarding WSI, the interaction of the X1X3 and X2X3 factors had a negative and positive effect on the WSI (p < 0.05), respectively. For WSI, its decrease could be attributed to an increase in temperature since starch depolymerization did not occur at high temperatures (Atienzo-Lazos et al., 2011). Reyes-Jáquez et al. (2012) reported that high temperatures reduce solubility as hydrophobic groups within the protein structure are exposed due to denaturation. On the other hand, an increase in WSI due to a higher moisture content in the treatment could be attributed to the reduction of lateral expansion because of the melting of the material, as observed by Kothakota (2013). However, it has also been found that there is an increase in WSI at lower moisture content because of more significant starch degradation (Singh et al., 2007). An increase in WSI with a higher moisture content was observed by Prabhakar et al. (2017) in extruded citrus residues.

Total Phenols and Condensed Tannins

The extrusion process uses short-term cooking. However, the phenolic compounds in the treatments are subjected to varying degrees of heating and moisture content (Yaĝci y Göĝůş, 2009), which are enough to cause changes in those compounds.

Table 2 shows that X1 and X3 in their linear terms had a significant effect on TP (p<0.05), just as interaction X1X3 and X2 in their quadratic term had a significant effect on TP (p<0.05). Polyphenols are compounds that are very susceptible to oxidation/degradation during extrusion due to the thermomechanical conditions involved in the process (Obradovic et al., 2015), because high temperatures accelerate the degradative oxidation of TP (Chaparro et al., 2009) since phenolic compounds are thermolabile. Their nature can be altered at temperatures above 80 °C (Sharma et al., 2012). Extrusion can alter the molecular structure of these compounds as well as reduce their chemical reactivity (Patterson, 2017), as phenolic compounds can undergo decarboxylation of phenolic acids during extrusion (Brennan et al., 2011) due to higher melting temperature and moisture content (Pedrosa et al., 2021), which can reduce their extractability by promoting the polymerization of phenols (Wang et al., 2014), such as the formation of a complex protein matrix that makes the difficult to extract (Almirudis, 2018). The extrusion process denatures proteins that lead to open structures that promote tannin-protein interaction, thus causing the formation of complexes that reduce their extractability (Brennan et al., 2011). The negative effect of X2 on TP content may be due to the increased generation of moist heat, which is more destructive and produces a synergistic effect with temperature (Yaĝci and Göĝůş, 2009).

X3 had a positive effect on CT (p<0.05) since increasing the HUI content from 0 to 10% has a more significant contribution to the CT content due to the presence of these compounds in the plant. In cattle feed, CT is desired when seeking to reduce the emission of gases such as methane, as long as they do not exceed 5.5% of the diet, due to possible harmful effects to the animal, such as reducing the voluntary consumption of food and the digestibility of nutrients (Núñez and Rodríguez, 2019). According to the obtained results, the extrudates are below this limit.

In Vitro Dry Matter Digestibility

X1, X2 and X3 in their linear terms, had significant effects on the IVDMD (p<0.05), as well as the interaction of X1X3 and X2X3 and X1 and X3 in their quadratic terms (p<0.05) (Table 2). IVDMD of the extrudates ranged between 86.6-94.4%, with similar values in extruded cattle feed from other studies (Reyes-Jáquez et al., 2011; Delgado et al., 2020) and extruded pig feed (Araiza-Rosales et al., 2022b). Gelatinization of starch by the influence of temperature and humidity in the extrusion process (Donmez et al., 2021) makes it more susceptible to enzymatic hydrolysis due to the severity of the treatment, as it makes the starch granules easier to break down (Sun et al., 2019). In addition, the contact surface between the microbial enzymes and the substrate is enhanced by gelatinized starch and by mechanical breakdown of the plant cell wall (Sun et al., 2006). On the other hand, the degradability of the protein in the rumen is decreased by the partial denaturation of the protein (Reyes-Jáquez et al., 2011), which increases the amount of absorbable amino acids in the small intestine of cattle (Jenko et al., 2018), which is of utmost importance since the microbial protein does not meet all the requirements of the animal (Barchiesi et al., 2018). Razzaghi et al. (2016) compared the degradability of starch and protein in the rumen in unprocessed diets and diets processed by extrusion and pelletization in corn, wheat and soybean mixtures, whereby extrusion improved the digestibility value of feeds.

Numerical Optimization

Numerical optimization was performed by superimposing response surfaces (EI, BD, H, WAI, WSI, TP, CT, IVDMD). The optimal processing conditions were determined to obtain a high WAI, a lower WSA, a high IVDMD and a higher content of TF and CT, establishing as processing parameters the use of a high temperature, a low moisture content and a high HUI content. The optimal processing conditions for the feed were X1=150 °C, X2=14% moisture content and X3=10% HUI content, with an EI of 1.107, BD of 1060.79 kg/m3, H of 145.2 N, WAI of 3.51 g/g, WSI of 7.58%, TP of 0.246%, CT of 0.173% and IVDMD of 93.82%. The optimization results have similar values to commercial products shown in previous research (Reyes-Jáquez et al., 2011) or other optimizations in livestock feed (Delgado et al., 2020) so that extruded feed with the addition of HUI could be incorporated into the cattle feed with the addition of other forages. The chemical analysis was performed in the optimal extruded treatment with percentages of DM=89.24±0.485, ASH=4.44±0.038, CP=11.66±0.573, EE=1.48±0.107, NDF=26.288±0.591, ADF=15.97±0.604, LIG=1.34±0.084, NSC=56.07±0.225 and IVDMD of 94.46±0.652.

CONCLUSIONS AND RECOMMENDATIONS

The optimal processing conditions were obtained and according to the obtained results, the inclusion of HUI in cattle feed could replace conventional raw materials such as corn for food processing since the IVDMD did not show significant differences compared to commercial feeds, which suggests that HUI could be added to the formulation of extruded diets for bovine feed.

ACKNOWLEDGEMENTS

The authors would like to thank the funding provided by Consejo Nacional de Humanidades, Ciencias y Tecnologías, through the Graduate Scholarship with number 1107116.

NOVELTY STATEMENT

It is necessary to continue producing food for livestock in the face of the climate crisis and without compromising nutritional health. This study proposes the use of HUI as a non-conventional ingredient in the formulation of livestock feed with the use of extrusion to improve its nutritional quality.

AUTHOR’S CONTRIBUTIONS

Garcia Dominguez Maria Fernanda: Draft writing, investigation, analysis, data collection and curation.

Páez Lerma Jesús Bernardo: Conceptualization, Project management, supervision.

Reyes Jáquez Damián: Data analysis, methodology, visualization)

Carrete Carreón Francisco Oscar: Supervision, draft editing.

Rosas Guerra Maria Inés: Methodology, formal analysis)

Araiza Rosales Elia Esther: Data interpretation, conception, supervision.

Conflict of Interest

The authors declare that there is no conflict of interest related to the published article.

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