1. Introduction

Copper plays a vital role in the growth of broilers, having significant influences on the maintenance of production performance and regulation of enzymatic activity and on bone growth, glucose metabolism, hemoglobin synthesis, cardiovascular structural integrity, and other physiological functions [1]. According to NRC (1994), the dietary copper requirement of broilers is 8 mg/kg [2], and a higher dose is often given in the production process to obtain better economic benefits yet [3]. It cannot be ignored that excessive copper addition, which occurs because of the cost-effectiveness and easy availability, also causes environmental pollution and waste. Today, the optimum addition of dietary copper is still controversial. Therefore, the level of copper addition urgently needs to be reassessed. Studies have shown that with increasing copper level (100–300 mg/kg), the live performance of broilers is improved [4–6]. Some researchers suggested that feeding 250 ppm of Cu during the starter period had negative consequences on bird performance, and moderate levels of Cu (125 ppm) had beneficial effects on bird performance at market age [7]. Based on studies of the relationship between high levels of dietary copper (100–300 mg/kg) and the performance of broilers, it has been suggested that Cu had an apparent inhibitory effect on the cholesterol content, which can significantly improve the survival rate of broiler offspring [8–9]. In addition, copper oversupply (greater than 300 mg/kg) may inhibit the growth of broilers [10]. Meta-analysis is a kind of statistical method that integrates research results of all types in the same field. The differences between studies are removed by meta-analysis, which can make the corrected data comparable, creating more objective and convincing data [11]. The main goal of this study is to explore the relationship between copper addition and broiler performance reported by different studies through meta-analysis and obtain a reasonable quantitative model to explain the observed value and provide a theoretical reference for the practical process of Cu addition.

2. Materials and methods

2.2. Meta-analysis

The PROC MIXED model (SAS Version 9.4, Cary, NC) was used to analyze the relationship between the copper addition level and broiler performance. The model is as follows:

$$

$Y_{ij}=B_0+B_1{X}_{ij}+B_2{X}_{ij}^2+S_i+b_{1i}{X}_{ij}+b_{2i}{X}_{ij}^2+e_{ij}$

where i is the number of eligible studies and j is the number of observations in each study; B₀ is the overall intercept (fixed effects) of all the studies; B₁ and B₂ are the coefficients of the first and second terms of the polynomial between the different studies (fixed effects), respectively; X_ij is the independent variable of the jth observed value in the ith study; S_i is the random effect intercept of the ith study; b_1i and b_2i are the coefficients of the first and second terms of the polynomial in the ith study (random effects), respectively; and e_ij is the residual, which obeys the N (0, σ²) distribution (random effects).

The differences between the studies are assumed to be random effects. The intercept and slope of the variables (fixed effects) represent the average intercept and average slope of the ADG, ADFI, and FCR as they vary with dietary copper additions in the mixed effects model. The intercept and slope of the variables (random effects) represent important factors not included in the regression analyses in the different studies [12]. The random effects of the y value are adjusted to remove differences between the studies and then a regression analysis performed to calculate the correlation coefficient (i.e., r² ) [13].

The mixed effects model code is shown below.

PROC MIXED data = data;

CLASS Group;

MODEL Y = X X*X/Solution OUTP = Predictionset OUTPM = PredY;

RANDOM intercept X/TYPE = VC SUBJECT = Group SOLUTION;

RUN;

A regression analysis and curve fitting were performed for the relationship between the variables (y-axis) and copper addition (x-axis). The calculation steps are as follows: (i) calculation of the residual, (ii) calculation of PredY, and (iii) determination of the adjusted y value for each independent variable (AdjuestedY = PredY+Residual) to remove the differences between the studies.

We performed meta-analysis of RCTs and reported the pooled weighted mean difference (WMD) with 95% confidence intervals (95% CI) of a total change in ADG, ADFI and FCR. Stratified analysis by geographic areas and published year were also carried out. To assess the effects of each individual study and to verify the stability of the results of the meta-analysis, sensitivity analysis was conducted by removing each study in turn and estimating the overall effect of the remaining studies sequentially. The potential publication bias was evaluated by using Egger's test. All the statistical analyses were performed using STATA (version 11.0; Stata Corp, College Station, TX) and SAS (Version 9.4; SAS Institute, Cary, NC, US) software.

3. Results

3.2. Results of the meta-analysis

Based on the results of the random-effects method, the pooled WMD of the ADG, ADFI and FCR was -0.166 (95% CI: -1.587 to 1.254), -0.844 (95% CI: -1.536 to -0.152) and -0.029 (95% CI: -0.057 to 0.000), respectively. The forest plots are shown in Figs 1–3

Fig 1

Forest plot of ADG.

Fig 2

Forest plot of ADFI.

Fig 3

Forest plot of FCR.

3.3. Subgroup analyses

The subgroup analysis was stratified by area and showed that the pooled WMD of the ADG was 1.365 (95% CI: 1.246 to 1.484) in Israel, -0.271 (95% CI: -2.605 to 2.063) in the US, -0.381 (95% CI: -2.388 to -2.374) in Iran, -0.348 (95% CI: -1.649 to 0.952) in China, and 1.838 (95% CI: 1.8 to 1.877) in India (Table 1). When stratified by publication years, the pooled WMD of the ADG was -1.565 (95% CI: -7.307 to 4.177) from 1980 to 1990, 0.636 (95% CI: -0.803 to 2.075) from 1990 to 2000, 0.483 (95% CI: -0.348 to 1.315) from 2000 to 2010, and -0.831 (95% CI: -4.134 to 2.473) from 2010 to 2020 (Table 1). The results of subgroup analysis for the ADFI and FCR are detailed in Table 1.

Table 1

Stratified analyses by different factors.

	Stratified factors	No. of studies	WMD	95% CI (lower limit)	95% CI (upper limit)	Heterogeneity (I2)	Heterogeneity test P value	Model
ADG
Country
	Israel	1	1.365	1.246	1.484	-	-	Random
	US	4	-0.271	-2.605	2.063	100%	0	Random
	Iran	1	-0.381	-2.388	-2.374	-	-	Random
	China	5	-0.348	-1.649	0.952	99.9%	0	Random
	India	1	1.838	1.800	1.877	-	-	Random
Years
	1980–1990	2	-1.565	-7.307	4.177	100%	0	Random
	1990–2000	2	0.636	-0.803	2.075	99.3%	0	Random
	2000–2010	5	0.483	-0.348	1.315	99.9%	0	Random
	2010–2020	3	-0.831	-4.134	2.473	100%	0	Random
ADFI
Country
	Israel	1	0.437	-1.03	1.905	-	-	Random
	US	4	-0.572	-3.485	2.341	99.7%	0	Random
	Iran	1	-4.29	-4.946	-3.634	-	-	Random
	China	5	-0.995	-1.67	-0.320	99.9%	0	Random
	India	1	1.017	0.888	1.146	-	-	Random
Years
	1980–1990	2	-2.225	-7.345	2.894	97.8%	0	Random
	1990–2000	2	0.255	-2.894	3.404	98.7%	0	Random
	2000–2010	5	0.045	-0.633	0.724	99.4%	0	Random
	2010–2020	3	-2.149	-5.588	1.290	99.8%	0	Random
FCR
Country
	Israel	1	-0.070	-0.111	-0.029	-	-	Random
	US	4	0.006	-0.086	0.097	99.9%	0	Random
	Iran	1	-0.030	-0.054	-0.007	-	-	Random
	China	5	-0.046	-0.083	-0.008	99.9%	0	Random
	India	1	-0.043	-0.047	-0.039	-	-	Random
Years
	1980–1990	2	0.024	-0.158	0.205	98.7%	0	Random
	1990–2000	2	-0.022	-0.050	0.005	95.1%	0	Random
	2000–2010	5	-0.050	-0.088	-0.012	96.3%	0	Random
	2010–2020	3	-0.033	-0.049	-0.018	99.9%	0	Random

3.4. Relationship between performance and Cu addition

Cu addition was used as the independent variable, and the performance indices (ADG, ADFI, and FCR) of the broiler were used as the dependent variables. The results indicated a quadratic relationship between the adjusted performance index (ADG, ADFI, and FCR) and Cu addition. The maximum values of the ADG (31.84 g/d) and ADFI (47.69 g/d) were reached when Cu addition was 158 mg/kg (Y_ADG = 31.49+0.005X-0.00002X², n = 86, P<0.05) and 0 mg/kg (Y_ADFI = 47.27–0.00001X², n = 86, P<0.05), respectively. However, the minimum value of the FCR (1.53) was reached when Cu addition was 217 mg/kg (Y_FCR = 1.55–0.0003X+0.0000006X², n = 86, P <0.05) (Figs 4–6). The statistical results are shown in Table 2.

Fig 4

Relationship between copper supplementation and adjusted ADG.

Fig 5

Relationship between copper supplementation and adjusted ADFI.

Fig 6

Relationship between copper supplementation and adjusted FCR.

Table 2

Regression relationships inferred using mixed effects models.

Dependent variable	Independent variable	Intercept	SE	P value	Quadratic	SE	P value	R2
ADG	Cu addition	31.49	1.02	<0.05	-2.00E-05	4.18E-06	<0.05	0.54
ADFI		47.27	1.97	<0.05	-1.00E-05	4.68E-06	<0.05	0.55
FCR		1.55	0.06	<0.05	6.12E-07	0	<0.05	0.51

3.5. Sensitivity analysis and publication bias

To assess the effects of each individual study and to verify the stability of the results of the meta-analysis, sensitivity analysis was conducted by removing each study in turn and estimating the overall effect of the remaining studies sequentially. After removing each individual study, the pooled estimates of the remaining studies were all located in the range of the overall effect, indicating that the results of the meta-analysis showed low sensitivity and high stability (Figs 7–9). There was little indication of publication bias for studies on the ADG, ADFI or FCR (P values for Egger's test were 0.81, 0.71 and 0.14, respectively).

Fig 7

Sensitivity analysis of ADG.

Fig 8

Sensitivity analysis of ADFI.

Fig 9

Sensitivity analysis of FCR.

4. Discussion

The NRC (1994) recommended 8 mg/kg Cu for broiler diets. However, in practice, an excessive amount of copper was added for a long time. This is because studies have found that increasing the supply of copper in poultry production can effectively improve the live performance of the birds, mainly because of the antibacterial or bacteriostatic properties of copper [17]. In addition, a study on laying hens also showed that an increase in copper addition was effective in changing the lipid composition of eggs and reducing the cholesterol content in eggs [26]. Many studies have also indicated that supplementation in excess of the current recommendations (8 mg/kg) caused growth-promoting effects in broilers, and the copper supplementation at 150 mg/kg was found to have a positive effect on live weight gain in broilers, which might be a consequence of the significant reduction in the total number of pathogenic organisms in the gut [1, 9, 21, 27, 28, 29, 30].

In this study, with the increase in Cu addition, the average daily gain (ADG) of broilers showed a significant negative quadratic relationship, reaching an extreme value when the Cu addition amount was 158 mg/kg (Fig 4). The FCR of the broilers also showed a significant positive quadratic relationship and the lowest FCR value was found when 217 mg/kg of Cu was added (Fig 6). Although there is a quadratic relationship between the ADFI and copper addition (Fig 5), the extreme value of the ADFI is not reached in the interval in which the copper addition is greater than zero, which may be related to a difference in the data. In the modern poultry industry, the amount of copper added has been much higher than 8 mg/kg as the minimum requirement for broiler recommended by NRC. We have also reached a similar conclusion through meta-analysis. To achieve the maximum ADG and the minimum FCR, we believe that the amount of copper added should be 158mg/kg and 217mg/kg, respectively. According to Samanta et al ., the result was found to be commercially beneficial for the chickens receiving 150mg/kg of diet. There are also studies showed that the addition of 200 or 250mg/kg copper could promote the growth of broilers [19, 28]. These experimental results were considered to have some support for our study. The amount of copper added was often not accurate in the previous studies, most of which only had two or three treatment levels and often showed a multiple relationship between the treatment levels. While meta-analysis integrated the results of various studies, and the final result was more statistically significant. In addition, the copper addition levels obtained in this study are not consistent when the ADG or FCR reach an extremum (maximum or minimum). The addition of copper at 150mg/kg is widely accepted in commercial poultry nutrition, however, we believed that the copper addition might be more appropriate when FCR reached the extreme value. FCR is an important determinant of profitability for broiler producers. Because the feed constitutes 70–80% of the cost of raising broiler chickens, changes in the feed-conversion ratio can have a major impact on the profitability of an operation [31]. Therefore, the recommended copper addition amount is 217mg/kg in this study, but not all studies support this result. According to the positive quadratic relationship between FCR and copper addition, the FCR gradually increased after the copper addition was higher than 217mg/kg. The results of one study suggest that no effect on weight gain and feed conversion even with 500 mg/kg level of copper sulfate in broiler [32], which may indicate that there is not a simple quadratic relationship between copper addition and broiler performance, additionally, more experimental data are needed to support the meta-analysis. In the analysis of different countries, some of the data included only one study; therefore, the result may not be accurate. There was no significant difference between the experimental and control data in the US. For China, while there was no significant change in the ADG data, both the ADFI and FCR declined, suggesting that the copper additive had a positive effect on performance. In the analysis of different years, none of the data showed significant differences, except for the FCR data. From 2000 to now, there was a significant reduction in the FCR, indicating that the use of copper additives has been more accurate in the 21^st century, making it possible to avoid the production performance degradation caused by copper contents that are either too high or too low. On the other hand, the rising price of copper has also promoted the broiler industry to seek more reasonable copper additives in the 21^st century.

There are several reasons why the addition of Cu in feed can promote the performance of broiler chickens. First, the inhibitory effect of copper on the reproduction of harmful bacteria in the intestines of broilers indirectly promotes the growth process of broilers. Furthermore, copper also controls the microbes in the feed, reducing the microbial consumption of the feed [33]. Second, copper can increase the activities of certain related enzymes, such as GSH-Pox, CuZn-SOD, and intestinal lipase [25]. Third, copper stimulates growth hormone secretion. Yang et al . reported that copper reduced hypothalamic somatostatin secretion by regulating catecholamine metabolism [34]. Therefore, the addition of 8mg/kg copper addition is no longer suitable for the broiler breeding industry, and there is currently an urgent need to redefine the amount of Cu needed.

However, our results showed that there was a quadratic relationship between the copper supply and growth performance, which implies that excessive copper addition has certain disadvantages. The remarkable effects of high level of copper sulfate in diets for poultry is the gizzard erosion which means ulceration of the lining of gizzard. It is most likely that the acidic nature of Cu or sulfate dissociated from copper sulfate or even both may be responsible [28]. Growth suppressive effects, which are mainly due to the biological toxicity of excess copper, have been reported in some studies using extremely high amounts of copper additives (>300 ppm) [22,35]. Copper, as a trace element, has a low content in tissues but a high content in the liver, so copper poisoning mainly affects the liver. Typical copper poisoning results in liver cirrhosis, accompanied by hemolysis and kidney damage, which can seriously affect animal growth performance [36]. Almost all of the unabsorbed copper is excreted in feces or urine, and may subsequently lead to environmental contamination [37–38]. In addition, there are no unified management measures for the treatment of animal feces, which is generally used as fertilizer and is in direct with the soil. Although, the mobility of metal in the soil is relatively low, it will gradually accumulate and cause pollution to the natural environment. The accumulation of copper has a significant impact on agricultural ecosystems and is thought to lead to a decline in soil fertility and water quality [39]. Some studies have suggested that excessive copper in the soil has a negative effect on soil microbial community function [40]. Furthermore, studies have also shown antagonism between trace elements (Cu and Zn, Fe, Mo, and S) in chicks and other animals [41,42]. The antagonism between trace elements is mainly due to the formation of insoluble complexes in the gastrointestinal tract by unexcreted metallic substances [42].

Through meta-analysis, this study attempts to synthesize existing research and provide a theoretical basis for the quantitative analysis of new copper demand. Meta-analysis is greatly influenced by the literature sources; however, the main sources of literature in this study are mainly from Chinese and English databases. Literature in other languages, papers in conference proceedings, and some unpublished results may have an impact on the meta-analysis. In addition, the number of studies included was limited. Although there was no publication bias in these studies, only one study was included in some subgroups, which does not lead to robust results. Thus, the results of this paper may have some limitations.

5. Conclusions

The demand for copper in modern broiler feeding far exceeds the NRC standard. Through mate-analysis, we found that the adjusted ADG, ADFI, and FCR showed a clear quadratic relationships with the amount of Cu added. The maximum ADG (31.84 g/d) was reached when 158 mg/kg of copper was added, and the minimum FCR (1.53) was reached when 217 mg/kg of copper was added. We suggest that the addition of copper in the broiler feeding process should be 217 mg/kg which may have a positive effect on broiler performance and improve economic benefits.