A meta-analysis of the effects of clay mineral supplementation on alkaline phosphatase, broiler health, and performance

Abstract

The crucial constraint in the broiler production sector is feed efficiency; many feed additives have been widely employed to increase broiler growth. Nonetheless, some of these substances exacerbate health and animal-based food product safety concerns. This meta-analysis examines the effect of clay minerals on alkaline phosphatase (ALP), broiler health, and performance. Metadata was constructed from 369 data items that were harvested from 86 studies. The addition of clay minerals was set as a fixed effect and the difference between experiments was established as a random effect. The metadata were fitted using a linear mixed model. Due to the presence of clay minerals, growth performance as assessed by body weight (BW), average daily gain (ADG), and performance efficiency index (PEI) increased significantly (P < 0.01). In the total period, the increases of BW, ADG, and PEI were 4.12 g, 0.0714 g/d, and 0.648, respectively, per unit of clay minerals added. Clay minerals did not affect blood serum parameters (e.g., ALP and calcium). The IgA and IgM concentrations in the jejunum and ileum were significantly greater (P < 0.01) in the starter phase. Among clay minerals, broilers fed diets with aluminosilicate, halloysite, kaolin, and zeolite consistently exhibited higher (P < 0.05) BW, ADG, PEI, and lower feed conversion ratio (P < 0.05) in the finisher phase. Aluminosilicate was the only clay that increased (P < 0.05) secretory IgA concentration in both jejunum and ileum. In conclusion, clay minerals could be used as a growth promoter, especially during the finisher phase, without adversely affecting feed intake, liver function, and mineral metabolism in broiler chickens. Aluminosilicate was superior in improving the mucosal immunity status of broiler chickens.

INTRODUCTION

The digestive tract ecosystem is crucial for the health of broilers. The composition of intestinal microbiota and environmental parameters of the gastrointestinal tract is closely associated with the intestinal health of broilers. Compared to other avians, broilers have a small digestive system and a high flow rate, resulting in limited bacterial growth and shedding (Pan and Yu, 2014). Based on the most recent scientific studies, gut bacteria improve feed digestion, and their population stability affects the host immune system (Wu et al., 2013a; Yalçın et al., 2017). This mechanism will have a quantifiable effect on feed efficiency.

Recent feed additive technologies, such as antibiotic growth promoters (Maria Cardinal et al., 2019; Cardinal et al., 2020), antimicrobial peptides (Sholikin et al., 2021a), bacteriophages, clay and clay minerals (Slamova et al., 2011), enzymes (Kriseldi et al., 2021; Sjofjan et al., 2021), hyperimmune, phytobiotics, prebiotics, probiotics, and organic acids (Woong Kim et al., 2014), have been widely used to improve the digestive tract ecosystem and subsequently support broiler growth (Gadde et al., 2017). These features include inhibiting pathogenic bacteria (Broom, 2018), improving the digestibility of particular feed ingredients (Cao et al., 2007; Dersjant‐Li et al., 2015), enhancing nonspecific immunity in the gastrointestinal mucosa (Chen et al., 2016b), binding toxic substances in feed (Xu et al., 2018), and regulating the acidity level (Woong Kim et al., 2014). Nevertheless, most of the mentioned compounds still have limitations, particularly food safety. For instance, hyperimmune may result in autoimmunity or conflicting interactions with the host immunity (Gadde et al., 2017). Other substances, such as antimicrobial peptides, may induce allergies and pathogen resistance (Sholikin et al., 2021b). Both clay and clay minerals have inert properties and are rapidly removed from the host body; thus, it is potentially determined as the best candidate as a safe growth enhancer for broilers (Slamova et al., 2011; Gadde et al., 2017).

Clays and clay minerals have been investigated for their potential as growth promoters in the broiler (Rodríguez-Rojas et al., 2015). Clay is a material that occurs naturally in microscopic grains less than 2 or 4 micrometers in size, is composed of phyllosilicates, is malleable, and hardens upon drying (Nadziakiewicza et al., 2019). Clay minerals may be non-phyllosilicate, flexible, and thermally brittle. They are available as natural or synthetic (Rodríguez-Rojas et al., 2015; Moosavi, 2017). Clay minerals consist of one tetrahedral sheet (T) and one octahedral sheet (O). The T and O sheets are appropriately aligned in a straight line (Thiebault, 2020). Clay and clay minerals are often found in nature as a single unit, despite their different names and features. In addition, these substances possess an adsorbent capacity for many toxic molecules (Prabhu and Prabhu, 2018; Thiebault, 2020). It has been demonstrated that clay and clay minerals have a high affinity for adsorbing aflatoxins, enterotoxins, heavy metals, mycotoxins, pathogenic microorganisms, and plant metabolites (Gadde et al., 2017; Nadziakiewicza et al., 2019). Recent research indicates that clay minerals possess antibacterial and immunomodulatory properties (Durán et al., 2016; Dunislawska et al., 2022; Xie et al., 2022). They are often used as feed additives in the form of aluminosilicate, bentonite, diatomaceous earth or diatomite, glauconite, halloysite, kaolin, palygorskite or attapulgite, perlite, sepiolite, and zeolite (Gadde et al., 2017; Nadziakiewicza et al., 2019; Xie et al., 2022).

At 33 to 42 d of age, administering 10 g/kg of halloysite increased ADG and FCR in the finisher phase of broiler chickens (Nadziakiewicz et al., 2021). Halloysite substantially increased carcass weight and lowered liver and gizzard relative weights (Nadziakiewicz et al., 2022). In addition, zeolite is a popular type of clay that is advantageous to increase the expression of cytokines such as interleukin-4 (IL-4), IL-6, and IL-10 (Gall-David et al., 2017; Qu et al., 2019; Dunislawska et al., 2022). Palygorskite enhances performance, gut defense systems, and immunity at 1 g/kg (Zha et al., 2022). Moreover, modified aluminosilicate (hydrated sodium calcium aluminosilicate) is also a promising adsorbent for the detoxification of Trichothecenes (T-2) toxins (Wei et al., 2019). These findings justify the promising growth-promoting effects of many clay minerals suited to be applied as a feed additive for broiler chickens. However, other research failed to establish a significant effect of clay minerals on broiler growth performance (Wu et al., 2013b, c). Discrepancies among empirical studies can potentially lead to subjective bias and nonrobust conclusions. A quantitative and objective analytical methodology is necessary to generate a more robust conclusion about clay minerals as growth enhancers supported by statistical evidence (Sadarman et al., 2021; Adli et al., 2022). Meta-analysis establishes the primary or general summary and validates a treatment effectiveness (Wahyono et al., 2022). This meta-analysis attempts to summarize and predict the optimal dosage of clay minerals in addition to optimizing on broiler growth by looking at the health parameters (such as immunoglobulins and cytokines), liver function via alkaline phosphatase concentration, and growth performance (especially daily body weight gain and feed conversion).

MATERIALS AND METHODS

Animal Ethics Declaration

This meta-analysis utilizes secondary data from published studies without necessarily needing ethical justification for animal use. However, we provide information about the ethics of animal experiments from each article cited source (Table 1).

Table 1.

Literature used in this meta-analysis data.

No.	Article	Level1	Region	Ethic	Clay mineral	Breed	Sex	Age2	Weight3	Reared4
1.	Abaş et al. (2011)	0–20	Turkey		Zeolite	Ross 308		1	47	42
2.	Abbasi Pour et al. (2021)	0–15	Iran	yes	Sodium Bentonite	Ross		11		14
3.	Al-Nass et al. (2011)	0–20	Kuwait		Zeolite	Indian River		1	40	35
4.	Alharthi et al. (2022)	0–4	Saudi Arabia	yes	Bentonite and Zeolite	Ross 308		11		30
5.	Almeida et al. (2014)	0–30	United States	yes	Zeolite	Ross 308	Male	1	41.6	20
6.	Alzueta et al. (2002)	0–20	Spain		Sepiolite	Cobb	Male	1	39	29
7.	Attar et al. (2019)	0–15	Iran	yes	Sodium Bentonite	Ross 308	Male	11		24
8.	Azar et al. (2011)	0–50	Iran		Perlite	Ross 308		1		42
9.	Bailey et al. (2006)	0–5	United States	yes	Bentonite	Cobb	Male	1	35.4	42
10.	Banaszak et al. (2022)	0–20	Poland	yes	Mixed of halloysite and zeolite	Ross 308		1	43.5	7
11.	Bolandi et al. (2021)	0–10	Iran	yes	Zeolite	Cobb	Proper Mix	1		42
12.	Bouderoua et al. (2016)	0–50	Algeria	yes	Sodium Bentonite	Hubbard	Male	12	450	31
13.	Cabuk et al. (2004)	0–25	Turkey		Zeolite		Mix	1	40	42
14.	Cheng et al. (2016)	0–20	China	yes	Palygorskite5	Arbor Acres	Proper Mix	1	40	42
15.	Cheng et al. (2018)	0–10	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	40.1	42
16.	Curtui, (2000)	0–5	Romania		Zeolite			1		28
17.	Gall-David et al. (2017)	0–0.006	France	yes	Zeolite	Ross Pm3	Male	1		21
18.	Grądzki et al. (2020)	0–30	Poland	yes	Zeolite	Ross 308	male	1		42
19.	Denli et al. (2009)	0–5	Italy	yes	Diatomaceous Earth	Ross 308	Male	1	47	42
20.	Dos Anjos et al. (2015)	0–7.5	United States	yes	Diatomaceous Earth	Ross 308	Male	1	41	21
21.	Du et al. (2019)	0–10	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	47.5	42
22.	Dunislawska et al. (2022)	0–5	Poland	yes	Zeolite	Ross 308	Male	1	46.6	42
23.	Durna Aydin et al. (2020)	0–20	Turkey	yes	Glauconite	Ross 308	Male	1	41.3	35
24.	El-Husseiny et al. (2008)	0–5	Egypt		Diatomaceous Earth	Ross 308	Proper Mix	1	39.2	35
25.	Ghazalah et al. (2021)	0–5	Egypt	yes	Bentonite	Arbor Acres	Male	1		35
26.	Hu et al. (2013)	0–0.6	China	yes	Bentonite	Arbor Acres	Male	1		21
27.	Indresh et al. (2013)	0–10	India		Bentonite	Vencobb	Proper Mix	1		35
28.	Joo et al. (2007)	0–3	Korea		Bentonite	Ross 208		1	42	35
29.	Juzaitis-Boelter et al. (2021)	0–5	United States	yes	Hydrated Sodium Calcium Aluminosilicate	Cobb	Male	1	43	21
30.	Karamanlis et al. (2008)	0–20	Greece		Zeolite	Cobb 500		1	39.7	42
31.	Kavan et al. (2013)	0–30	Iran		Zeolite	Ross 308	Male	21		42
32.	Khanedar et al. (2012)	0–15	Iran		Calcium Bentonite and Sodium Bentonite	Ross 308	Male	1		42
33.	Lemos et al. (2015)	0–15	Brazil		Kaolin			15		52
34.	Lim et al. (2017)	0–2	Korea		Silicate	Cobb		1		35
35.	Macháček et al. (2010)	0–40	Czech	yes	Zeolite	Bovan		1
36.	Mallek et al. (2012)	0–10	Tunis	yes	Zeolite	Hubbard	Male	1		45
37.	Miazzo et al. (2005)	0–3	Argentina		Sodium Bentonite	Ross	Male	23		50
38.	Miles and Henry, (2007a)	0–20	United States		Hydrated Sodium Calcium Aluminosilicate	Ross	Male	1		21
39.	Miles and Henry, (2007b)	0–20	United States		Hydrated Sodium Calcium Aluminosilicate	Ross	Male	1		21
40.	Modirsanei et al. (2008)	0–30	Iran	yes	Diatomaceous Earth		male	1	42.0	42
41.	Nadziakiewicz et al. (2021)	0–10	Poland	yes	Halloysite	Ross 308	Proper Mix	1	45	42
42.	Nadziakiewicz et al. (2022)	0–10	Poland	yes	Halloysite	Ross 308	Proper Mix	1	45	43
43.	Neeff et al. (2013)	0–5	United States		Hydrated Sodium Calcium Aluminosilicate	Ross 708	male	1
44.	Nikolakakis et al. (2013)	0–30	Greece		Zeolite	Cobb 500		1		42
45.	Oguz and Kurtoglu, (2000)	0–25	Turkey		Zeolite	Avian		1		21
46.	Ortatatli and Oğuz, (2001)	0–25	Turkey		Zeolite	Avian	Mix	1		21
47.	Ouachem and Kaboul, (2012)	0–30	Algeria		Marl	Isa 15		1		56
48.	Ouhida et al. (2000)	0–20	Spain	yes	Sepiolite		Male	1		22
49.	Owen et al. (2012)	0–30	Nigeria		Kaolin	Hubbard	Mix	1	60	56
50.	Pappas et al. (2010)	0–10	Greece	yes	Palygorskite	Cobb	Proper Mix	1	45	42
51.	Pappas et al. (2014)	0–10	Greece	yes	Bentonite	Ross 308		1	46	42
52.	Pappas et al. (2016)	0–10	Greece	yes	Bentonite	Ross 308		1	45	42
53.	Prvulović et al. (2008)	0–5	Serbia		Aluminosilicate		Mix	1		42
54.	Qu et al. (2019)	0–10	China	yes	Zeolite	Arbor Acres	Male	1		42
55.	Rana et al. (2017)	0–10	Tunis		Zeolite	Hubbard		1	37.6	39
56.	Saçakli et al. (2015)	0–20	Turkey	yes	Zeolite	Ross 308	Male	1	42.6	42
57.	Safaeikatouli et al. (2010)	0–30	Iran		Kaolin and Zeolite	Ross 308	Male	1		42
58.	Safaeikatouli et al. (2012)	0–30	Iran		Bentonite, Kaolin, and Zeolite	Ross 308	Male	1		42
59.	Shannon et al. (2017)	0–5	United States	yes	Bentonite			1	37.4	21
60.	Shi et al. (2009)	0–3	China		Bentonite	Avian	Proper Mix	1		42
61.	Suchý et al. (2006)	0–20	Czech		Zeolite	Ross 308	Proper Mix	1	43	40
62.	Tang et al. (2014)	0–4	China	yes	Zeolite	Arbor Acres		1		42
63.	Tang et al. (2015)	0–4.8	China	yes	Zeolite	Arbor Acres	Proper Mix	1	40	21
64.	Uzunoğlu and Yalçin, (2019)	0–1.5 and 0–15	Turkey	yes	Bentonite and Sepiolite	Ross 308	Male	1	44.1 and 43.9	42
65.	Wawrzyniak et al. (2017a)	0–30	Poland	yes	Zeolite	Ross 308		1	42	40
66.	Wawrzyniak et al. (2017b)	0–30	Poland	yes	Zeolite	Ross 308		1	41	40
67.	Wei et al. (2019)	0–0.5	China	yes	Modified Hydrated Sodium Calcium Aluminosilicate	Cobb 500	male	1	54.2
68.	Wu et al. (2013b)	0–20	China	yes	Zeolite	Arbor Acres	Male	1		42
69.	Wu et al. (2013a)	0–20	China	yes	Zeolite	Arbor Acres	Male	1		42
70.	Wu et al. (2013c)	0–20	China	yes	Zeolite	Arbor Acres		1		21
71.	Wu et al. (2015)	0–20	China	yes	Zeolite	Arbor Acres		1		21
72.	Wu et al. (2016)	0–10	China	yes	Zeolite	Arbor Acres		1		42
73.	Xia et al. (2004)	0–1.5	China	yes	Bentonite	Avian	Male	1		49
74.	Xiaohan Li et al. (2017)	0–10	China	yes	Palygorskite		Male	1	39.8	42
75.	Xu et al. (2003)	0–1	China	yes	Bentonite	Arbor Acres		1	46.2	42
76.	Yalçın et al. (2017)	0–20	Turkey	yes	Sepiolite	Ross 308	Male	1	41.2	42
77.	Chen et al. (2016)	0–10	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	39	42
78.	Chen et al. (2016)	0–10	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	39	21
79.	Chen et al. (2020)	0–10	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	47.3	21
80.	Yan et al. (2019)	1	China	yes	Palygorskite	Ross 308	Male	1	43.2	42
81.	Yang et al. (2016)	0–1.7	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	36.7	42
82.	Yang et al. (2017a)	0–1.7	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	36.7	21
83.	Yang et al. (2017b)	0–1.7	China	yes	Palygorskite	Arbor Acres	Proper Mix	1	36.7	42
84.	Zha et al. (2022)	0–2	China	yes	Palygorskite	Ross 308	Proper Mix	1	46.3	42
85.	Zhang et al. (2017)	0–20	China	yes	Palygorskite	Arbor Acres		1	40.2	42
86.	Zhou et al. (2014)	0–20	China	yes	Attapulgite and Zeolite		Male	1	39.2	42

¹Level in mg/kg as fed.

²Age in day.

³Weight in gram.

⁴Rearing duration of treatment in day.

⁵Palygorskite known as attapulgite.

Article Search

The search retrieved 3,802 items from Google Scholar, PubMed, Science Direct, and Scopus, published between 2000 and 2022. The search terms are: "clay mineral" AND "broiler" with optional keywords such as [("performance" OR "alkaline phosphatase" OR "calcium and phosphor in serum" OR "tibia" OR "immunity")]. The outputs were further selection processes, including scientific articles, book reviews, book excerpts, and books.

Article Selection

The selection procedure followed the latest version of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) protocol (Shamseer et al., 2015; Selcuk, 2019; Page et al., 2021) which considered the previously available review. The protocol helps to minimize the risks of bias in selecting process and guarantees that the selected articles are of high quality and relevant to be included in the meta-analysis (Hayanti et al., 2022). In the first step, the article title and abstract are selected based on their relevance to the topic; acquired 189 publications related to the topic (1). Next, articles were selected when they had the digital object identifier (DOI) (2); were experimental research-based (3); had sufficient information on the materials and methods and well experimentally designed (4); reported addition levels, units, and type of clay mineral (5); the treatment of the clay mineral was not intended as an antitoxin or medication purpose (6); and broiler chickens were used as the subjects of the study (7). The representative flow of the selection process is illustrated in Figure 1. Articles are disregarded if they do not meet the selection process requirements, with the reasons provided.

Figure 1.

Process of literature selection for meta-analysis data. The process of identifying and selecting article resources for a meta-analysis study. Collected 3,802 related articles, then through the selection process, selected 86 articles that are available for data extraction.

Data Compilation and Validation

The vetting procedure produced 86 articles (Table 1). The lists of articles were used for the entire meta-analytical study. The data in a Microsoft Excel spreadsheet file contains units of measurement that were standardized according to International Standard units. The constructed raw dataset resulted in 369 rows and 78 columns. Various clay minerals and their respective frequency were identified and included in the dataset: aluminosilicate (80), bentonite (107), diatomite (7), glauconite (2), halloysite (2), kaolin (28), palygorskite (41), perlite (9), sepiolite (10), and zeolite (165). The database contains information about the level of clay mineral administration in g/kg as a fed basis (i.e., the highest level was 50 and the lowest level was 0) and the 37 observed parameters that were classified into each broiler growing phase, including starter and finisher (Table 2). The parameters examined included body weight (BW, g), average daily gain (ADG, g/h/d), average daily feed intake (ADFI, g/h/d), feed conversion ratio (FCR), mortality (%), productive efficiency index, alkaline phosphatase in serum (ALP, mg/dL), calcium in serum (Ca, mg/dL), the phosphorus in serum (P, mg/dL), the weight of tibia (g). The PEI (1) formula is:

$$PEI=\left[\frac{BW\times V}{FCR\times D}\right]\times 100$$ (1)

Table 2.

Descriptive statistics of the meta-analysis data.

Parameter1	Data summary2
	NDP	Mean	SD	Max	Min	Q25	Q50	Q75
Level, mg/kg as fed
Clay mineral	369	8.69	10.1	50	0	0	5	15
Performance3
Starter
BW, g	180	711	289	1918	236	517	671	820
ADG, g/h/d	236	33.5	15.4	101	11.7	22.6	30.1	37.7
ADFI, g/h/d	241	48.9	23.3	187	19.5	35.2	44.7	52.2
FCR	238	1.5	0.218	2.99	0.99	1.36	1.46	1.58
Finisher
BW, g	119	2128	430	3233	711	1897	2090	2431
ADG, g/h/d	152	69.7	20.1	155	22.7	58.2	70.3	80.7
ADFI, g/h/d	159	127	32.6	185	50.4	101	135	154
FCR	156	1.9	0.345	3.3	1.11	1.71	1.89	2.09
Total
BW, g	198	2,087	459	3,384	1,104	1,781	2,090	2,403
ADG, g/h/d	195	50.9	13.8	95.2	19.5	39.8	50.8	58.1
ADFI, g/h/d	192	93.6	26.1	225	37.3	77.1	93.4	104.6
FCR	198	1.84	0.246	2.99	1.3	1.69	1.81	1.94
Mortality, %	56	3.9	3.29	15	0	2	3.33	5.33
PEI	184	264	73.9	498	85.6	215	268	316
Serum, mg/dL
Starter
ALP	34	108	32.5	194	61.1	80.9	105	132
Ca	70	10.1	1.02	12.3	5.1	9.63	10.1	10.7
P	70	6.07	1.97	8.88	1.48	5.62	6.5	7.5
Finisher
ALP	45	188	97.9	334	65.9	92.8	167	308
Ca	60	10.4	1.84	16.1	8.03	9.01	10.2	10.8
P	54	7.07	3.53	19.8	2.06	4.92	6.98	7.8
Tibia
Starter
Weight, g	41	2.07	0.836	3.82	0.45	1.77	2.2	2.37
Ash, g	37	0.778	0.342	1.41	0.164	0.452	0.898	1.02
Ash, %	99	41.9	8.07	57.1	22.3	37.2	40.9	46
Ca, %	31	17.3	5.7	27.3	5.9	12.6	18.9	20.2
P, %	31	9.03	2.88	13.9	2.8	7.94	9.68	10.4
Ca/P	31	1.93	0.181	2.2	1.37	1.91	1.95	2.03
Finisher
Weight, g	12	6.82	0.392	7.43	6.22	6.58	6.83	7.07
Ash, g	12	2.62	0.144	2.89	2.43	2.52	2.6	2.69
Ash, %	34	45.2	7.41	60.3	36	39.4	43.7	46.6
Ca, %	13	22.4	1.77	25	19.8	20.5	22.3	24.1
P, %	13	11.2	0.66	11.9	10.2	10.6	11.5	11.6
Ca/P	13	1.99	0.078	2.12	1.88	1.95	1.97	2.07
Immunity, µg/mg protein
Starter
Jejunum IgG	12	20.4	13.9	42	1.38	6.4	20.9	32.9
Jejunum IgM	8	2.41	1.05	3.51	0.94	1.3	2.97	3.13
Jejunum IgA	14	1.06	0.917	3.48	0.116	0.328	1.03	1.17
Ileum of IgG	12	24.7	14.7	43	5.65	6.41	29.6	35.8
Ileum IgM	8	2.46	0.864	3.22	1.19	1.66	2.96	3.11
Ileum IgA	14	1.12	0.797	3.02	0.105	0.377	1.25	1.38
Finisher
Jejunum IgG	9	25.2	18.9	48.9	4.53	6.04	33.7	39.8
Jejunum IgA	9	0.836	0.657	1.53	0.117	0.145	1.22	1.46
Ileum IgG	9	25.8	18.9	50	4.56	6.87	36.2	40.9
Ileum IgA	9	0.865	0.726	1.63	0.097	0.104	1.33	1.45
Cytokines, pg/mL
Starter
Serum IL–1β	11	157	57.6	261	102	117	128	193
Ileum IL–1β	11	105	39.3	165	52	77.5	106	124
Finisher
Jejunum IL–1β	11	101	39	161	49	73.5	101	121

¹ADFI = average daily feed intake; ADG = average daily gain; ALP = alkaline phosphatase; BW = body weight; Ca = Calcium; FCR = feed conversion ratio; IgA = immunoglobulin A; IgG = immunoglobulin G; IgM = immunoglobulin M; IL = interleukin; P = phosphor; PEI = productive efficiency index.

²Max = maximum the feature data value; Min = minimum the feature data value; NDP = number of data points; Quantile statistics are expressed as follows: Q25: 25%; Q50: 50%; and Q75: 75%; SD = standard deviation.

³The period or phase of treatment.

Where D = total days of growth and V = proportion of living broilers (one hundred percent minus mortality percentage) (Hubbard, 1999; Tauqir and Nawaz, 2001; Modirsanei et al., 2008).

Statistical Modelling

The objective of the statistical modeling was to determine the response variables affected by adding clay minerals. The studies were referred to as random effects, and the clay minerals addition was a fixed component. Then, using a linear mixed model (LMM), these 2 components were computed (St-Pierre, 2001; Sauvant et al., 2008). The LMM Equation (2) provides the foundation for metadata modeling.

$$Y_{ijk}=\mu +S_i+{\tau }_j+S{\tau }_{ij}+{\beta }_1{X}_{ij}+b_i{X}_{ij}+{\beta }_2{X}_{ij}^2+b_i{X}_{ij}^2+e_{ijk}$$ (2)

Notation: $Y_{ijk}$ = dependent variable, $\mu$ = overall mean value, $S_i$ = random effect of the ith study, assumed to be $\sim N_{iid}\left(0,{\sigma }_S^2\right)$, ${\tau }_j$ = fixed effect of the jth of $\tau$ factor, $S{\tau }_{ij}$ = random interaction between the ith and jth level of $\tau$ factor, also assumed to be $\sim N_{iid}\left(0,{\sigma }_{S\tau }^2\right)$, ${\beta }_1$ = overall value of the linear regression coefficient of Y to X (a fixed effect), ${\beta }_2$ = overall coefficient value of the quadratic regression of Y to X (a fixed effect), $X_{ij}$ dan $X_{ij}^2$= continuous values of the predictor variable (in linear and quadratic form, respectively), $b_i$ = random effect of the study on the regression coefficient of Y to X, assumed to be $\sim N_{iid}\left(0,{\sigma }_b^2\right)$, and $e_{ijk}$ = residual value from unpredictable error. The interaction between the broiler strain (B) and the type of clay minerals (C) was also examined in the model. The different types of clay minerals were compared using the lsmeans package available in R software (Lenth, 2016). The least-square means of control and clay minerals groups were contrasted following the procedure of the R documentation.

A validation and significance test were conducted on the model. The significance effect was determined using a one-way analysis of variance. It is significant if the P value is < 0.05 and tends to be significant when P value is between 0.05 and 0.10. P_l represents the P value for the linear constant (${\mathbf{\beta }}_1$) and P_q represents the P value of the quadratic constant (${\mathbf{\beta }}_2$). The validation test was conducted using the root mean square error (RMSE) and Nakagawa determination coefficient (R2) or $R_{GLMM}{\left(c\right)}^2$ (Nakagawa and Schielzeth, 2013; Nakagawa et al., 2017; R Core Team, 2022). Below is the equation for RMSE (3) and R² (4).

$$RMSE=\sqrt{\frac{\sum {\left(O-P\right)}^2}{NDP}}$$ (3)

$$R_{GLMM}{\left(c\right)}^2=\frac{\left({\sigma }_f^2+\sum \left({\sigma }_l^2\right)\right)}{\left({\sigma }_f^2+\sum \left({\sigma }_l^2\right)+{\sigma }_e^2+{\sigma }_d^2\right)}$$ (4)

Note: $O$ = actual value, $P$ = estimated value, $NDP$ = number of data point, ${\sigma }_f^2$ is the variant of a fixed factor, $\sum \left({\sigma }_l^2\right)$is the sum of all variants of the component, ${\sigma }_e^2$ is the variant due to the predictor dispersion, and ${\sigma }_d^2$ is the specific distribution of the variant. R version 4.2.0, also known as "Vigorous Calisthenics", and accompanying libraries, such as lme4 (for LMM construction) and lsmeans (for least-squares means test), are used to model and statistically test LMM. In addition, using mixed models methodology, categorical analysis was performed to evaluate the effects of clay minerals type on the response variables. The number of replications was used as a weighting factor and Tukey was used for multiple comparisons of the least-square means (Irawan et al., 2022). The Pearson correlation matrix between mineral clay types and growth performance (BW, ADG, ADFI, FCR, and PEI) is then given as a heatmap (Figure 2) (Brownstein et al., 2019; Sholikin et al., 2019).

Figure 2.

Matrix correlation of clay mineral on broiler performance at starter, finisher, and total period of treatment. Body weight (BW, g), average daily gain (ADG, g/h/d), average daily feed intake (ADFI, g/h/d), feed convertion ratio (FCR), and performance efficiency index (PEI).

RESULTS

Table 3 displays the effects of clay minerals supplementation on broiler performance, blood serum, tibia, and immunity. Clay additives significantly increased body weight (P_l = 0.044 and P_q = 0.027) and decreased FCR (P < 0.01) during the starter period. In the finisher phase, performance parameters such as BW, ADG, ADFI, and FCR experienced significant (P < 0.01) improvements. In total period, the administration of clay minerals resulted in a significant (P < 0.01) improvement in growth performance, as reflected by the increase in BW, ADG, and PEI. For every gram of clay minerals added, improvement rates of BW, ADG, and PEI were 4.12 g, 0.0714 g/h/d, and 0.648, respectively, based on the linear model. In contrast, for every gram of clay minerals added, the FCR was decreased (P_l = 0.003 and P_q < 0.001) by 0.00223 units. The application of clay minerals in the diet did not affect other performance parameters such as ADFI and mortality.

Table 3.

Determine the impact of adding clay mineral on broiler performance, blood serum, tibia, and immunity.

Parameter1	Mathematical models2							C × B3
	Intercept ($\mu$)		Gradient (${\beta }_1$ or ${\beta }_2$)		P values	RMSE	R2
	Value	SE	Value	SE
Performance4
Starter
BW, g	747	28.5	0.668	0.331	0.044	29.8	0.98	0.962
			−0.0106	0.00476	0.027
ADG, g/h/d	34.5	1.34	0.0012	0.0106	0.91	1.72	0.982	0.873
ADFI, g/h/d	50.5	2.17	0.0331	0.0197	0.095	3.24	0.975	0.991
FCR	1.48	0.019	0.00162	0.000388	<0.001	0.064	0.873	0.296
Finisher
BW, g	2095	60.2	5.86	1.2	<0.001	67.3	0.97	0.003
			−0.082	0.0224	<0.001
ADG, g/h/d	66.9	2.44	0.298	0.0738	<0.001	3.5	0.95	0.462
			−0.00567	0.00197	0.005
ADFI, g/h/d	126	4.03	0.12	0.051	0.018	5.47	0.96	0.41
FCR	1.98	0.043	−0.00517	0.00157	0.001	0.076	0.93	0.02
			0.000114	0.0000421	0.007
Total
BW, g	2,106	48.1	4.12	0.681	<0.001	53.2	0.98	<0.001
			−0.0527	0.0116	<0.001
ADG, g/h/d	51.3	1.45	0.0714	0.0208	0.001	1.72	0.98	0.061
			−0.00087	0.00031	0.005
ADFI, g/h/d	95.9	2.765	0.0372	0.0219	0.091	3.56	0.974	0.004
FCR	1.87	0.024	−0.00223	0.000749	0.003	0.064	0.89	<0.001
			0.0000402	0.000011	<0.001
Mortality, %	3.87	0.57	0.0174	0.0221	0.433	2.06	0.511	0.875
PEI	262	8.12	0.648	0.176	<0.001	13.2	0.96	<0.001
			−0.00958	0.00292	0.001
Serum, mg/dL
Starter
ALP	106	8.31	−0.0222	0.532	0.967	17.5	0.567	0.946
Ca	10.1	0.178	0.00205	0.00927	0.826	0.684	0.403	0.885
P	6.07	0.406	−0.035	0.0142	0.018	0.403	0.94	0.741
			0.000678	0.000322	0.041
Finisher
ALP	197	23.3	−0.0263	0.402	0.948	20.8	0.917	0.005
Ca	10.4	0.408	0.00831	0.00481	0.092	0.44	0.915	0.16
P	7.04	0.847	−0.00668	0.00372	0.081	0.301	0.989	0.003
Tibia
Starter
Weight, g	2.11	0.248	0.00461	0.00369	0.221	0.322	0.789	<0.001
Ash, g	0.809	0.108	0.00209	0.00141	0.146	0.122	0.818	0.964
Ash, %	44.5	1.65	−0.0176	0.0422	0.678	2.96	0.845	0.001
Ca, %	18.9	1.53	−0.134	0.113	0.246	3.03	0.525	0.829
P, %	9.77	0.73	−0.0638	0.0407	0.13	1.06	0.713	0.106
Ca/P	1.94	0.047	−0.00107	0.00551	0.847	0.167	0.074	0.012
Finisher
Weight, g	6.78	0.254	0.0019	0.00232	0.437	0.126	0.884	0.929
Ash, g	2.65	0.075	−0.0127	0.00269	0.002	0.036	0.91	0.001
			0.000292	0.0000516	<0.001
Ash, %	46.2	2.48	0.0327	0.0155	0.047	1.02	0.977	0.227
Ca, %	21.3	0.75	0.0569	0.0148	0.006	0.462	0.885	0.179
P, %	11.1	0.327	0.00349	0.00515	0.52	0.16	0.914	0.277
Ca/P	1.93	0.024	0.00446	0.00127	0.008	0.047	0.542	0.082
Immunity, µg/mg protein
Starter
Jejunum IgG	16.9	9.04	0.869	0.449	0.089	2.89	0.951	0.319
Jejunum IgM	2.05	1.08	0.0375	0.0281	0.238	0.161	0.983	0.738
Jejunum IgA	1.05	0.496	0.0516	0.00517	<0.001	0.067	0.993	0.149
Ileum IgG	22.2	9.52	0.689	0.371	0.1	2.38	0.97	0.736
Ileum IgM	2.11	0.933	0.0543	0.0161	0.02	0.092	0.992	0.992
Ileum IgA	1.03	0.38	0.056	0.00515	<0.001	0.067	0.99	0.418
Finisher
Jejunum IgG	22.1	18.1	0.979	1.47	0.53	4.03	0.963	0.04
Jejunum IgA	0.66	0.626	0.184	0.0753	0.058	0.067	0.99	0.29
			−0.0393	0.0191	0.095
Ileum IgG	22.1	18.3	1.45	1.22	0.279	3.34	0.976	0.287
Ileum IgA	0.768	0.695	0.0172	0.0265	0.541	0.073	0.992	0.235
Cytokines, pg/mL
Starter
Serum IL–1β	164	38.5	0.269	0.802	0.747	15	0.923
Ileum IL–1β	108	29	−0.377	0.358	0.327	6.63	0.973
Finisher
Jejunum IL–1β	105	28.6	−0.421	0.401	0.329	7.45	0.965

¹ADFI = average daily feed intake; ADG = average daily gain; ALP = alkaline phosphatase; BW = body weight; Ca = Calcium; FCR = feed conversion ratio; IgA = immunoglobulin A; IgG = immunoglobulin G; IgM = immunoglobulin M; IL = interleukin; P = phosphor; PEI = productive efficiency index.

²${\beta }_1$= The first row of each parameter is a linear coefficient; ${\beta }_2=$ the second row is a quadratic coefficient; R2 = R squared Nakagawa for validate linear mixed model; RMSE = root mean square error; SE = standard error.

³B = broiler breed; C = level of clay mineral (g/kg as fed).

⁴The period or phase of treatment.

The P content of the serum linearly decreased (P_l = 0.018 and P_q = 0.041) when supplemented during the starter phase up to 0.035 mg/dL. In the finisher phase, serum Ca concentration tended to increase (P = 0.092) and P concentration in blood serum tended to lower (P = 0.081). ALP concentration was not affected by adding clay minerals at the starter and finisher. The tibia ash composition was increased (P = 0.047). Similarly, the composition of Ca and the ratio of Ca to P were considerably increased (P = 0.006 and P = 0.008, respectively). In the starter and finisher phases, other tibia characteristics such as weight, ash, Ca, P, and Ca/P were not significant (except for ash, Ca, and Ca/P in the finisher phase).

During the starter phase, the clay minerals administration linearly increased (P < 0.01) the IgA concentration in the jejunum and ileum. Ileal IgM concentration was also linearly increased (P = 0.02), while jejunal IgG tended to increase (P = 0.089). In the finisher phase, jejunal IgA was the only variable found to be quadratically affected (P_l = 0.058 and P_q = 0.095) by the levels of clay minerals. In addition, increasing levels of clay minerals did not affect the expression of cytokines based on the concentration of IL-1β in serum, jejunum, and ileum. The lack of significant effect from LMM regression analysis on many parameters could be associated with variations from different clay minerals within studies.

Table 4 summarizes the different effects of clay minerals on the response variables. Clay minerals did not impact ADG, ADFI, and FCR during the starter phase (P > 0.05). However, more excellent (P < 0.05) BW in the starter and finisher phases was associated with some clay minerals treatment, including aluminosilicate, diatomaceous, halloysite, kaolin, smectite, and zeolite, compared to broiler chickens fed basal ration. ADFI and FCR were higher (P < 0.05) when broiler chickens were treated with aluminosilicate, while the other clay minerals did not affect those parameters. Compared to all treatments, the control exhibited the highest level of P in blood serum (6.15 mg/dL; P = 0.004) at the starter phase. Compared to other treatments (such as calcium bentonite and sodium bentonite), calcium concentration in blood serum at the finisher phase was considerably more significant in the bentonite treatment (11.3 mg/dL; P = 0.003). Compared to other clay mineral treatments, bentonite treatment tended to have a more significant ALP activity (219 mg/dL; P = 0.063). Other blood serum values relating to Ca, P, and ALP were insignificant. The weight and mineral makeup of the broiler tibia were not significantly affected by the type of clay mineral. The IgA was significantly higher in the jejunum and ileum (P < 0.01 and P = 0.003, respectively) at starter phase after the aluminosilicate treatment (e.g., hydrated sodium calcium aluminosilicate and silicate). In addition, these parameters concentration become 2.22 and 2.3 µg/mg protein, respectively. Moreover, other immunity characteristics were not significant owing to the various clay mineral types.

Table 4.

The type of clay mineral affects the performance, blood serum, tibia, and immunity of broilers.

Parameter1	Treatment2											SEM3	P values
	Con	Clay 1	Clay 2	Clay 3	Clay 4	Clay 5	Clay 6	Clay 7	Clay 8	Clay 9	Clay 10
Performance4
Starter
BW, g	812b	835a	816b	841a	798b	846a	844a	833ab	815b	837a	836a	36.9	<0.001
ADG, g/h/d	39.1	40.7	39.3	40.2	38.4	40.8	42.3	38.3	38.5	40.2	39.7	5.3	0.225
ADFI, g/h/d	55.7	56.5	57.2	57.2	57.5	58.5	48.3	53.6	55.6	56.5	56.3	9.9	0.844
FCR	1.46	1.46	1.47	1.47	1.48	1.48	1.26	1.47	1.48	1.44	1.45	0.11	0.346
Finisher
BW, g	2,193c	2,516a	2,198c	2,280a	2,098c	2,300a	2,407a	2,264b	2,235b	-	2,254b	157	<0.001
ADG, g/h/d	70.7b	87.5a	72b	74.6a	67b	73.8a	79a	70.2b	71.2b	-	72.7b	10.1	<0.001
ADFI, g/h/d	130b	152a	131b	137b	126b	119b	131b	127b	130b	-	132b	16.5	<0.001
FCR	1.92a	1.65c	1.89a	1.91b	1.97a	1.74b	1.83b	1.9a	1.9a	-	1.9a	0.141	<0.001
Total
BW, g	2,263b	2,339a	2,282b	2,248b	2,166b	2,346a	2,347a	2,322a	2,297b	-	2,341	108	<0.001
ADG, g/h/d	56.2	58.1	57.4	55.6	53.6	58.2	57.2	55.6	56.2	-	57.5	4.9	0.22
ADFI, g/h/d	95.8	97.7	97.6	97.9	99.7	86.9	94.1	95.6	-	95.8	96.8	1.54	0.368
FCR	1.87	1.88	1.86	1.93	1.98	1.69	1.77	1.89	-	1.85	1.84	0.014	0.33
Mortality, %	4.15	2.46	4.3	3.99	-	3.4	-	2.05	-	-	4.33	0.349	0.84
PEI	261a	266ab	263ab	253ab	220ab	307ab	272ab	268ab	249ab	277ab	274b	4.49	0.001
Serum, mg/dL
Starter
ALP	105	104	92.6	77.2	-	-	-	-	-	-	133	5.57	0.106
Ca	10.2	10.1	10.2	10.8	-	-	-	-	8.54	-	10.1	0.122	0.564
P	6.15a	5.74ab	5.24b	-	-	-	-	-	6.05ab	-	5.98ab	0.236	0.004
Finisher
ALP	200ab	-	219a	-	-	212ab	211ab	-	-	209ab	166b	14.6	0.063
Ca	10.3b	-	11.3a	-	-	11.5ab	10.5ab	-	9.98ab	10.6ab	10.2b	0.237	0.003
P	6.96	-	6.94	-	-	7.75	7.35	-	6.84	6.94	6.86	0.48	0.8
Tibia
Starter
Weight, g	2.13	2.14	2.11	2.15	-	-	-	-	-	-	2.26	0.131	0.967
Ash, g	0.84	0.82	0.84	0.88	-	-	-	-	-	-	0.84	0.056	0.999
Ash, %	44. 7	44.9	43.8	44. 6	-	-	-	-	45.6	-	44.1	0.81	0.965
Ca, %	18.8	19.4	19	-	-	-	-	-	-	-	16	1.03	0.346
P, %	9.71	9.38	9.73	-	-	-	-	-	-	-	8.52	0.518	0.221
Ca/P	1.95	2.01	1.95	-	-	-	-	-	-	-	1.9	0.033	0.888
Finisher
Weight, g	6.83	-	-	-	-	-	-	-	-	-	6.82	0.113	0.936
Ash, g	2.66	-	-	-	-	-	-	-	-	-	2.6	0.42	0.434
Ash, %	46.2	-	47.5	-	-	-	47.5	-	-	46.8	46.3	1.27	0.642
Ca, %	21.4	-	22.6	-	-	-	23.2	-	-	-	22.3	0.49	0.266
P, %	11.0	-	11.4	-	-	-	11.3	-	-	-	11	0.18	0.485
Ca/P	1.95	-	1.97	-	-	-	2.05	-	-	-	2.03	0.027	0.279
Immunity, µg/mg protein
Starter
Jejunum IgA	1.06b	2.22a	-	-	-	-	-	1.21b	-	-	1.13b	0.245	<0.001
Jejunum IgM	2.09	-	-	-	-	-	-	2.18	-	-	-	0.37	0.632
Jejunum IgG	16.5	-	-	-	-	-	-	20.3	-	-	19.4	4.02	0.495
Ileum IgA	1.08b	2.3a	-	-	-	-	-	1.20b	-	-	1.06b	0.213	0.003
Ileum IgM	2.13	-	-	-	-	-	-	2.31	-	-	-	0.305	0.286
Ileum IgG	22.8	-	-	-	-	-	-	25.2	-	-	22.5	4.25	0.738
Finisher
Jejunum IgA	0.68	-	-	-	-	-	-	0.88	-	-	0.7	0.218	0.342
Jejunum IgG	22.9	-	-	-	-	-	-	25	-	-	21.8	6.29	0.927
Ileum IgA	0.82	-	-	-	-	-	-	0.75	-	-	0.81	0.242	0.846
Ileum IgG	22.7	-	-	-	-	-	-	24	-	-	24.5	6.28	0.928
Cytokines, pg/mL
Starter
Serum IL–1β	168	-	-	-	-	-	-	148	-	-	175	17.4	0.599
Jejunum IL–1β	107	-	-	-	-	-	-	95.4	-	-	99.5	11.8	0.374
Finisher
Ileum IL–1β	110	-	-	-	-	-	-	102	-	-	102	11.9	0.507

¹ADFI = average daily feed intake; ADG = average daily gain; ALP = alkaline phosphatase; BW = body weight; Ca = Calcium; FCR = feed conversion ratio; IgA = immunoglobulin A; IgG = immunoglobulin G; IgM = immunoglobulin M; IL = interleukin; P = phosphor; PEI = productive efficiency index.

²Con = control; Clay 1 = aluminosilicate (e.g., hydrated sodium calcium aluminosilicate and silicate); Clay 2 = bentonite (e.g., calcium bentonite and sodium bentonite); Clay 3 = diatomaceous earth (diatomite); Clay 4 = glauconite; Clay 5 = halloysite; Clay 6 = kaolin; Clay 7 = palygorskite (attapulgite); Clay 8 = perlite; Clay 9 = sepiolite; Clay 10 = zeolite.

³SEM = Standard error of the mean (n = NDP in Table 2).

⁴The period or phase of treatment.

^a,b,ab,cDifferent letters in the same row have a significant difference with a 5% error degree.

DISCUSSION

Previous research has demonstrated that mineral clay has a high absorption capacity due to its fine particle size (some are nano-sized, 5–50 nm) (Ganguly et al., 2011; Al-Beitawi et al., 2017; Ujilestari et al., 2019), thin particle shape (Slamova et al., 2011), and vast surface area (Ouachem et al., 2015). Clay can absorb substances or materials to get rid of things like antinutrients, heavy metals, pathogenic microorganisms, poisonous compounds, and viruses, as illustrated in Figure 3 (Slamova et al., 2011). As a growth promoter, the advantages of clay and clay minerals are more focused on conditioning the digestive tract environment, such as boosting the quality of intestinal health by absorbing toxic chemicals or bacteria (Rodríguez-Rojas et al., 2015), enhancing the performance of various digestive enzymes (Zabiulla et al., 2021), and regulating pH (Gadde et al., 2017).

Figure 3.

Mode of action of clay and clay mineral in the small intestine (modified from Gadde et al., 2017). Clay and clay minerals bind antinutrients, pathogens, and toxins in the broiler small intestine by absorbing and expelling them. This condition will improve the gut health, as shown by a rise in increased enzyme activity and lactic acid bacteria.

In addition, clay minerals catalyze the digestive process (Zhang et al., 2021). Zeolite plays an active role in triggering enzyme activation and enhancing the performance of digestive enzymes (Smeets et al., 2020). The pores of clays are rich in metal ions that can help to maintain enzyme stability (thermal and pH) and act as an activating agent for lipases, proteases, and xylanase (Naseri et al., 2018; Smeets et al., 2020; Dashtestani et al., 2021). Such favorable effects on enzyme secretion and activation can explain the improvement of growth performance in broiler chickens, as confirmed by the increase in ADG and the decrease in FCR values. This meta-analysis also validated that ADFI was not affected by the clay minerals, indicating that they did not interfere with palatability. Compared to other clay minerals, zeolite significantly affected the phenotypes parameter, such as an increase in BW and ADG. Digestive enzymes, including lipase, protease, and xylanase are actively catalyzed by zeolite and activated by it (Smeets et al., 2020; Dashtestani et al., 2021; Zhang et al., 2021). As a result, the zeolite treatment absorption process operates more effectively, leading to excellent production performance.

Clay enhances the PEI value; the quantity of PEI influences broiler performance; as the PEI value grows, so does the productivity and efficiency of the broiler. Santurio et al. (1999) study on bentonite administration in aflatoxin stress treatment showed that it might increase BW, ADG, FCR, PEI, and decrease mortality rate over the control. The meta-analysis revealed that the highest PEI was formed by zeolite (PEI = 274). This result causes zeolite capacity to promote digestion and absorption. Zeolite stimulates the formation of beneficial bacteria in the intestine during digestion (Lebedynets et al., 2004; Ferreira et al., 2012; Durán et al., 2016; Bolandi et al., 2021). Similarly, clays such as clinoptilolite (zeolite) and sodium bentonite are used (Modirsanei et al., 2008; Attar et al., 2019).

Fascinatingly, clay mineral does not influence broiler meat mineral (Abaş et al., 2011). Following a meta-analysis of ALP investigations, adding clay minerals did not affect the serum concentration of ALP. This remark implies that clay does not interfere with the metabolism of serum phosphorus. ALP is a member of the class of metalloenzymes that act as catalysts or biomineralizing agents in blood serum (Turan et al., 2011; Bhattarai et al., 2014; Abalymov et al., 2020). This metalloenzyme is responsible for the feed derived inorganic pyrophosphate release of phosphate ions and the crystallization of that compound into hydroxyapatite (de Souza Nakagi et al., 2013; Abalymov et al., 2020). The amount of ALP in the blood serum was unaffected by adding clay minerals. This implies that although serum P metabolism is unaffected by clay, P levels drop during the starter phase. The rate of P deposition in the tibia, the balance of Ca:P in the diet, and the pace of bone formation during the starter phase were assumed to be the causes of the drop in P (Kalantar-Zadeh et al., 2010; Abaş et al., 2011; Saçakli et al., 2015). Aluminosilicates, such as kaolin and zeolite, are minerals resistant to nutrient absorption in addition to these factors (Lemos et al., 2015; Wu et al., 2015; Yang et al., 2015).

Zeolite treatment often resulted in lower serum ALP and Ca levels and higher P levels than the other classes of clays. Conversely, bentonite treatment led to greater ALP, Ca, and reduced P. It was suggested that the distinction between the two clays stems from their chemical structure, attraction for metal ions, and mineral homeostasis in serum (Dos Anjos et al., 2015; Du et al., 2019; Alharthi et al., 2022). The aluminosilicate crystal structure of zeolite comprises SiO₄ and AlO₄ tetrahedra and takes on a 3-dimensional shape (Nadziakiewicza et al., 2019). The zeolite primary charge is a negative charge caused by aluminum silicate (Narayanan et al., 2020). Additionally, zeolites feature honeycomb-shaped holes (microspores or nanoporous in size) that may hold metal ions and organic molecules (Shariatmadari, 2008; Wattanawong and Aht-Ong, 2021). Meanwhile, bentonite has a flexible, uneven heterogeneous structure that serves as a colloid (Prabhu and Prabhu, 2018). Na⁺ and Ca²⁺ ions comprise most of the bentonite exchangeable positive charge (Nadziakiewicza et al., 2019). With this knowledge, it is clear that bentonite contains Ca²⁺ and has the potential to swap this ion for other valence ions, allowing Ca²⁺ to be taken into the body. Additionally, increased serum Ca²⁺ concentration increases ALP concentration and a reduction in P concentration (Amer et al., 2018; Al-Zghoul et al., 2019; Kriseldi et al., 2021). Administration of clay minerals for more than 21 d of maintenance (finisher period) increased blood minerals, leading to a rise in tibia mineral content.

Due to the clay minerals addition, the tibia macromineral composition varies naturally, and ash as a biomineral composition predictor was changed. Clay minerals impact calcium deposition in the tibia. According to recent research by Safaeikatouli et al. (2012), bentonite, kaolin, and zeolite enhance the amount of Ca deposition in the tibia. The presence of clay-derived Ca²⁺ minerals, such as calcium bentonite, which are also absorbed in the small intestine, may cause an increase in Ca deposition, as seen in the tibia. The Ca²⁺ ions of bentonite may readily be exchanged for metal ions or other cationic substances (Moosavi, 2017). As a result, cells and other structures like the tibia will retain extra calcium ions in the blood. In addition, clays such as attapulgite, bentonite, and zeolite feature holes that are effective for inducing the binding and release of calcium carbonate from inorganic sources, thus increasing Ca²⁺ bioavailability (Moosavi, 2017; Hubadillah et al., 2018; Liu et al., 2018a; Nadziakiewicza et al., 2019; Hartati et al., 2020; Sandomierski et al., 2020). High Ca levels can cause a reduction in P absorption in the small intestine and may block parathyroid hormone action as the following mechanism to maintain body homeostasis (Kalantar-Zadeh et al., 2010; Turan et al., 2011; Wilkens and Muscher-Banse, 2020). The implication is that; 1) several mechanisms regulate calcium balance, including calcium distribution into cells (e.g., through transcellular and paracellular channels); 2) increase bone density in tibia; and 3) induce the synthesis of vitamin D, which is vital for P absorption (Behera et al., 2020; Kim et al., 2020; Wilkens and Muscher-Banse, 2020). Clays such as aluminosilicates, bentonite, kaolin, and zeolite in broiler feed might enhance Ca deposition (Safaeikatouli et al., 2012; Bouderoua et al., 2016; Attar et al., 2019).

According to previous research, changes in IgA and IgM levels indicate that the use of clay minerals impacts the immunity of broiler chickens. IgA and IgM are primarily responsible for inhibiting microorganisms or antigens in the small intestinal lumen. Antigens are deposited by IgM so that phagocytic cells may promptly consume them. Additionally, B cell-produced activated IgA acts as the primary mucosal effector and shields the intestinal epithelium from hazardous substances and pathogenic microbes (Corthésy, 2013). IgA also produces antigen-absorbing mucus, inhibits antigen access at epithelial receptors, and facilitates antigen removal with the help of peristaltic mechanisms and mucociliary activity (Peng et al., 2005; Racine and Winslow, 2009; Zhou et al., 2014; Bolandi et al., 2021). According to Chen et al. (2016a) results, adding palygorskite into the feed caused IgA and IgM levels to rise during the starter phase. Similar results were found by Tang et al. (2014), who found that the addition of clinoptilolite, which binds to zinc minerals, boosted IgA levels in the lumen of the jejunum of 21-day-old broiler chickens. The rise in IgA and IgM levels in the intestinal lumen indicates that clay minerals are efficient immunomodulatory agents, according to the prior explanation and metadata findings (e.g., jejunum and ileum). Thus, clay minerals directly contribute to maintaining the microflora ecology and improving broiler health by enhancing the immunological condition in the intestinal lumen, particularly the aluminosilicates and zeolite types of clay minerals, which enhance broiler immunological response. Most of the clay referred to in this meta-analysis has been activated by altering the clay pores (Wei et al., 2019). Clay minerals used various treatments to enhance the alterations, including acids, bases, ionic surfactants, mechanical (nano/micro grinding), polyhydroxy cation, and heat (Tole et al., 2019; Thiebault, 2020). The primary goal of activating clay minerals is to improve the adsorbent surface area and adsorption capacity for more effective use as an adsorbent (Tole et al., 2019). The immune system is strongly impacted by zeolite. Similar to superantigens, aluminosilicates, and silicates operate as nonspecific immunomodulators (SAgs). SAgs are sensitive to bacterial toxins and viruses that bind to proteins from T-cell receptors, create major histocompatibility, and drive the development of protein antigen-presenting cells (Ivkovic et al., 2004; Tang et al., 2022). This hypothesis is consistent with meta-analysis results showing that clay minerals could boost immunoglobulin levels and broiler health (surpress mortality percentage). In agreement with the results of Neeff et al. (2013), hydrated sodium calcium aluminosilicate lowers mortality from an aflatoxin B₁ contaminated diet. Smectite and sodium bentonite may increase broiler performance and lessen the toxicological impact of aflatoxin on the liver, according to the results of another trial (Magnoli et al., 2011; Zabiulla et al., 2021). Moreover, Liu et al. (2018b) and Nadziakiewicz et al. (2022) stated that clay minerals might increase the production of significant quantities of IgA and alleviate intestinal, also gizzard damage caused by aflatoxin when employed as detoxifying agents.

CONCLUSION

Clay minerals positively affect body weight gain, feed conversion, performance index, IgA, and IgG of broilers. Additionally, clay minerals do not affect macromineral metabolism and blood serum absorption. According to FCR, the optimal amount of clay minerals was 22.6 g/kg for the finisher period and around 27.6 g/kg for the total period. Recommended clay minerals might nicely combine with other feed additives to enhance adsorption. Also, it can be an active form for specific applications, such as enhancing the absorption of Ca and P in the ileum.