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. 2024 Jun 18;103(9):103974. doi: 10.1016/j.psj.2024.103974

Distinct patterns of feed intake and their association with growth performance in broilers

Yuchen Jie *,†, Chaoliang Wen *,†,‡, Qiang Huang *,†, Shuang Gu *,†, Congjiao Sun *,†,‡, Guangqi Li §, Yiyuan Yan §, Guiqin Wu §, Ning Yang *,†,‡,1
PMCID: PMC11264188  PMID: 38972283

Abstract

Improving feed utilization is a vital strategy to meet the growing global demand for meat and promote sustainable food production. Over the past few decades, significant improvements in the feed intake (FI) and feed utilization efficiency of broilers have been achieved through advanced breeding procedures, although dynamic changes in FI and their effects on the feed conversion ratio (FCR) have remained unclear. In this study, we measured individual weekly FI and body weight of 274 male broilers to characterize the dynamic FI patterns and investigate their relationship with growth performance. The broilers were from 2 purebred lines and their crossbreed and measurements were collected from 4 to 6 wk of age. Overall, a continuous increase in the weekly FI occurred from 4 to 6 wk of age, whereas the body weight gain (BWG) reached an inflection point in wk 5. The dynamic change in weekly FI was observed to follow 3 distinct FI patterns: pattern 1, a continuous weekly increase in FI; pattern 2, an increase followed by a plateau; pattern 3, an increase followed by a decrease. The prevalence of these patterns was similar in the purebred and crossbred populations: pattern 2 was most frequent, followed by a moderate proportion of pattern 1, and the lowest proportion of pattern 3. Broilers following pattern 1 displayed significantly better growth performance and feed utilization efficiency than those following pattern 3, emphasizing the importance of maintaining good appetite in the last stage of broiler production. In summary, this study has characterized the dynamic patterns of FI and their association with growth performance. Our results offer a new foundation for improving feed utilization efficiency and investigating feeding regulation in broilers.

Key words: broiler, feed intake pattern, feed utilization efficiency, growth performance

INTRODUCTION

The continued growth of the global population has led to a remarkable increase in the worldwide demand for food. Over the past 50 yr, chicken meat has become the preferred type of meat because of its various advantages, including affordability, health benefits, and absence of religious and cultural restrictions (Aspevik, et al., 2017; Windhorst, 2017; Zampiga, et al., 2021). In 2019, global chicken production comprised 35% of total meat production, surpassing pork to be the most-produced meat (FAO, 2022). By 2030, poultry meat is predicted to account for 41% of all meat-derived protein (OECD-FAO, 2022), highlighting the increasing significance of chicken meat production in global food security. However, worldwide poultry production currently requires over 1,270 million metric tons of feed annually, with broilers accounting for the highest feed consumption among avian species (approximately 364 million metric tons) (Alltech, 2023). The growing demand for meat products, coupled with the decreasing availability of land and food resources, presents a pivotal challenge to the modern chicken industry (Vågsholm, et al., 2020; Zampiga, Calini and Sirri, 2021). Feed can account for up to 70% of the total cost of chicken production, thus, the volatility of feed raw material prices and amount of feed wastage during the production process confers elements of uncontrollability to production efficiency. An effect strategy to address these challenges is to reduce overall feed consumption by enhancing feed utilization (Zampiga, et al., 2018).

The Feed Conversion Ratio (FCR), which is calculated as the change in feed intake (FI) divided by the change in body weight, is often used to assess feed utilization efficiency (Hess, et al., 1941; Wen, et al., 2018). An increase in feed utilization efficiency is reflected by lower FCR values. Genetic selection has led to broilers being over 5 times larger than layers by the age of 6 wk (Zhao, et al., 2004; Buzala and Janicki, 2016; Mai, et al., 2021). The higher body weight of modern commercial broilers is accompanied by improved feed utilization efficiency. Increased body size in commercial chicken has been accompanied by unintended increases in FI (Richards and Proszkowiec-Weglarz, 2007). Thus, high FI is necessary for higher body weight gain (BWG) and better feed efficiency (Wen, et al., 2018; Yan, et al., 2019), whereas low FI is often associated with lower body weight (Dunnington and Siegel, 1997; Dunnington, et al., 2013). Various factors, including appetite, intestinal digestion, and energy metabolism level, can influence feed use (So, et al., 2007; Byrne, et al., 2015). Evidence shows that broilers possess more taste buds than layers and display fewer antigreedy behaviors (preferring foods that require more effort to obtain) (Buzala and Janicki, 2016). As a crucial indicator of broiler production efficiency, FCR plays a pivotal role in individual selection during breeding. However, there is still little understanding of how dynamic FI affects FCR. Therefore, to develop management and breeding strategies that enhance feed utilization efficiency, a deeper understanding of broilers’ feeding regularity, as well as of the intricate connection between FCR and feeding, is essential.

The control of FI is extremely complex. Previous studies have focused primarily on the total feed intake (TFI) throughout the measurement period, aiming to assess the overall efficiency of feed utilization. However, the dynamic changes in FI over time were often neglected (Sun, et al., 2006; Romero, et al., 2011; Prakash, et al., 2020). Consequently, the final FCR data obtained by researchers and breeders reflect the sum of the factors affecting FCR across multiple periods, making it challenging to determine which stage of the growth process has the greatest impact on the overall FCR. In this study, we have pioneered the analysis of broiler FI patterns by investigating dynamic changes in FI during growth. Our research performed a 21-d FI tracking measurement in 274 broiler chickens to explore the dynamic characteristics of FI and their relationship with growth performance at various stages. Our study established a relationship between the patterns of FI and the FCR, showing that FCR selection can be made by selecting individuals with consistently increasing FI, which is instructive for broiler breeding. This study lays the foundation for the analysis of the physiological mechanism of appetite regulation in broilers based on their FI patterns.

MATERIALS AND METHODS

Animals and Housing

The experiment was conducted in accordance with the guidelines established by the Animal Care and Use Committee of China Agricultural University. The 274 male broilers participating in the study were sourced from 2 purebred lines: Cornish (CC group, N = 91), White Plymouth Rock (RR group, N = 88), and their hybrid (CR group, N = 95). The chickens were obtained from Beijing Huadu Yukou Poultry Co., Ltd., where the CC and RR groups serve as the paternal and maternal lines in commercial broiler production. Among these 3 broiler groups, the CC group was the primary focus of the investigation in this trial, with the remaining 2 groups employed to validate the findings related to FI patterns. All broiler chickens were raised in groups until 21 d posthatching and were housed in identical cages from 21 to 42 d of age. Throughout the experiment, the chickens were provided with ad libitum access to feed and water. Rearing was performed in accordance with the Broiler Management Guide of Beijing Huadu Yukou Poultry Co., Ltd.

Measurements of Feed Intake and Feed Conversion Ratio

The weekly feed consumption was recorded for each broiler. The weekly FI for each individual was computed by measuring the difference in feed weight in the trough at the beginning and end of each week. The TFI was the cumulative sum of FI during wk 4 to 6. Broiler weight was measured at 21, 28, 35, and 42 d of age using an electronic scale with a precision of 1.0 g. The BWG for each individual was calculated on the basis of the difference in body weight at the beginning and end of each week. The FCR was determined from the ratio of FI to BWG.

Feed Intake Pattern Analysis

To determine the FI patterns of broilers, the K-means algorithm was employed (Kodinariya and Makwana, 2013). Before the K-means analysis, the FI data for 3 consecutive weeks were arranged chronologically, and individuals with missing data values were excluded. The number of clusters, determined on the basis of the primary characteristic direction of changes in broiler FI. K-means clustering was conducted using cluster package of the R program (Ver 4.3.2). The algorithm was initiated with random initialization and ceased iteration upon achieving convergence. The resulting clusters were evaluated to obtain the within-cluster sum of squares. The results of the K-means analysis were visualized using the R program and considered to indicate the FI patterns.

Statistical Analysis

The phenotypic (Pearson) correlations between FI and growth performance were calculated using SPSS 26.0 software. A P value of <0.05 was considered statistically significant. One-way analysis of variance (ANOVA) was performed to assess the differences in FI and growth performance among the 3 FI patterns. A P value of <0.05 was deemed statistically significant, whereas values between 0.05 and 0.10 were considered to suggest significance. Paired t-tests were performed to examine the differences in FI increments for each week. The result was deemed to make a substantial contribution to feed utilization efficiency if the P values from the 2-tailed t-tests were <0.05.

RESULTS

Descriptive Statistics of Phenotypes

Descriptive statistics of FI and growth performance for each stage are presented in Table 1. The changes in FI and the growth trends for the 3 broiler groups were consistent. For the crossbred (CR) group, the TFI was 3,547.81 ± 263.15 g from d 22 to 42. Throughout the observation period (d 22 to 42), the weekly FI of broilers from the CR group consistently increased, reaching a peak during d 36 to 42 (1,302.53 ± 132.35 g), which accounted for 36.71% of the TFI. However, the BWG peaked during d 29 to 35 (763.88 ± 85.23 g/day) and slightly decreased during d 36 to 42 (662.65 ± 118.79 g/day). In contrast to the observation of the highest FI during the 6 wk, the BWG during this period was not the highest. The fastest growth was found to occur at 5 wk. Notably, the FCR for all the 3 groups increased gradually with age, reaching its maximum value during d 36 to 42 (2.03 ± 0.44), which was significantly higher than that in the other 2 stages (P < 0.05).

Table 1.

Descriptive statistics for FI and growth performance at each stage.

Groups Age N1 FI, g
 BWG, g
 FCR2
Mean ± SD Percentage Mean ± SD Percentage Mean ± SD
CR d 22–28 95 978.79 ± 88.91 27.59% 649.44 ± 67.22 31.28% 1.51 ± 0.09bc
d 29–35 95 1,266.49 ± 90.80 35.70% 763.88 ± 85.23 36.80% 1.67 ± 0.13b
d 36–42 95 1,302.53 ± 132.35 36.71% 662.65 ± 118.79 31.92% 2.03 ± 0.44a
d 22–42 95 3,547.81 ± 263.15 100% 2,075.98 ± 180.95 100% 1.71 ± 0.08
CC d 22–28 95 1,007.92 ± 97.84 26.81% 647.39 ± 90.60 29.44% 1.57 ± 0.15b
d 29–35 93 1,341.53 ± 106.05 35.68% 832.26 ± 102.09 37.87% 1.63 ± 0.14b
d 36–42 91 1,410.01 ± 170.69 37.51% 719.42 ± 152.93 32.71% 2.02 ± 0.40a
d 22–42 91 3,761.95 ± 285.61 100% 2,170.24 ± 387.19 100% 1.71 ± 0.11
RR d 22–28 95 879.37 ± 123.23 28.79% 557.69 ± 98.15 32.39% 1.61 ± 0.30bc
d 29–35 92 1,110.81 ± 108.08 36.37% 647.36 ± 108.90 37.60% 1.81 ± 0.72b
d 36–42 91 1,063.97 ± 149.90 34.84% 510.03 ± 139.27 30.01% 2.11 ± 0.37a
d 22–42 88 3,054.15 ± 284.19 100% 1,721.82 ± 198.74 100% 1.78 ± 0.12
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1

N: number of observations after excluding missing values and outliers that deviate from the mean by 3 standard deviations.

2

a–b values with different superscript letters in a column are significantly different (P < 0.05).

Correlations Between Feed Intake and Growth Performance

As depicted in Figure 1A, the FCR of the CR group exhibited moderate to high negative correlation with BWG at each stage (r < −0.48, P < 0.05), whereas the FI at each stage was positively and highly correlated with the corresponding BWG (r > 0.74, P < 0.05). Similar results were also found for both purebred lines (Figures 1B and 1C).

Figure 1.

Figure 1

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Correlations between feed intake and growth performance. Red and blue represent positive and negative correlations, respectively. The size of the circle and the depth of the color represent the magnitude of the correlation; the number represents the numerical value of the correlation. A blank intersection point indicates no significant correlation between the 2 variables.

There was a strong correlation between weekly FI and TFI in all 3 groups (r > 0.55). Moreover, as the age of the CR and CC populations increased, the correlation coefficient of TFI and weekly FI at each stage gradually declined. Alternatively, for the CR and RR groups, FI21–28 exhibited a positive correlation with total FCR (P < 0.05). However, FI36–42 was negatively correlated with total FCR, suggesting that a larger late-stage FI was associated with a smaller total FCR during d 36 to 42. Remarkably, for all 3 broiler groups, weekly FI and weekly BWG were consistently positively correlated at all stages. Notably, FI36–42 had the strongest correlation with the total BWG (r = 0.87, 0.75, 0.80, respectively, P < 0.05). These results indicate that the FI during d 36 to 42 has an important impact on the final growth efficiency of broilers.

The change in FI between wk 5 and 6 plays a crucial role in shaping FI intake patterns. Consequently, we conducted a detailed analysis of the correlation between FCR and the increase in FI from wk 5 to 6. A moderate negative correlation was observed across all 3 groups. Specifically, the correlation coefficients for the CR, CC, and RR groups were −0.40 (Figure 2A), −0.32 (Figure 2B), and −0.41 (Figure 2C), respectively.

Figure 2.

Figure 2

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Correlation between feed conversion ratio and feed intake increment from wk 5 to 6. FCR22–42 represents for the FCR at 22 to 42 d of age. The red lines in each plot represent linear regression. r and P indicate Pearson correlation coefficients and P values, respectively. FI increment was the change in feed intake from wk 5 to 6.

Characterization of the Feed Intake Patterns

To investigate the changes in FI patterns during growth, we generated a line chart representing the 3 wk of FI data (wk 4–6). The results showed individual FI did not universally increase with age throughout the monitoring period (Figure 3A). In the CR group, the average FI increment from wk 4 to 5 was 328.47 ± 97.29 g from wk 4 to wk 5, which then decreased to 64.29 ± 156.99 g from wk 5 to 6 (Figure 3B). Similar findings were observed in the CC and RR groups (Figures 3C and 3D). From wk 5 to 6, FI exhibited 3 different changes in direction, leading us to categorize the changes in FI into 3 main patterns (Figure 3A). In pattern 1, the FI of broilers increased on a weekly basis. In pattern 2, FI initially increased and then remained relatively stable. In pattern 3, FI initially increased and then decreased. Similar to the CR group, the FI changes in the CC and RR groups were also categorized into 3 patterns. In the CR group, pattern 2 accounted for the highest proportion (44%, Figure 4), indicating its dominance as the primary FI pattern, whereas pattern 3 accounted for the lowest proportion (19%). Consistent with the CR group, we observed pattern 2 as the most prevalent (53% and 38%) and pattern 3 as having the least prevalent (18% and 28%) in the CC and RR groups, respectively (Figure 4).

Figure 3.

Figure 3

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Characteristics of broiler feed intake patterns. (A) The left section displays the weekly change in FI of broilers from wk 4 to 6 of the CR group. Each line represents an individual, color-coded based on FI in the sixth week, with high FI marked in red and low feed intake in blue. Arrows indicate the FI change and the corresponding FI pattern. The right section are the cluster trend plots that depict broiler FI patterns. The Y-axis displays the normalized intake change levels. Yellow and green lines represent the FI trend, while red lines indicate the corresponding trend center. (B, C, and D) are changes in feed intake increment from wk 4 to 6. Histogram of FI increments in the CR, CC, and RR groups from wk 4 to 5 and from wk 5 to 6, respectively.

Figure 4.

Figure 4

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Proportions of the 3 feed intake patterns in the CC, RR, and CR group. The pie plots in red, yellow, and blue represent patterns 1, 2, and 3, respectively.

Differences in the Growth Performance of the 3 Feed Intake Patterns

Regarding growth performance-related weekly changes, we observed major differences among the 3 FI patterns between wk 5 to 6. Between FI patterns 1–3, with the average FI reduction at wk 6, the broiler BWG declined faster, whereas the FCR increased faster at wk 6 (Figure 5).

Figure 5.

Figure 5

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Weekly growth performance of the CR group with different feed intake patterns. Weekly changes in broiler ADG and FCR of the 3 FI patterns from wk 4 to 6 of the CR group. The phenotypes of specific FI pattern are highlighted with the same color background (i.e., red, yellow, and blue backgrounds represent FI patterns 1, 2, and 3, respectively).

To explore the relationship between FI patterns and overall growth performance, we performed ANOVA to explore the differences in growth performance among the 3 feed intake patterns from wk 4 to 6. Sequentially from patterns 1 to 3 in the CR group, the FI and BW of the CR group decreased, with FCR increasing sequentially (Figure 6). Notably, among these patterns, the BW and FI were significantly lower in pattern 3 than in patterns 1 and 2, whereas the FCR was significantly lower in pattern 1 than in patterns 2 and 3(P < 0.05). Broilers following pattern 1 exhibited the largest BW42 and the best feed utilization efficiency, whereas chickens with FI pattern 3 exhibited poor feed utilization efficiency.

Figure 6.

Figure 6

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Feed intake and growth performance of the CR, CC, and RR groups with different feed intake patterns during d 22 to 42. Each row represents the difference between FI22–42, BW42, and FCR22–42 in the 3 feed patterns of a broiler population. We obtained the P values between the different feed intake patterns using ANOVA. * indicates P < 0.05, ** indicates P < 0.01 and *** indicates P < 0.001. Data are expressed as the mean ± SEM and the bar charts in red, yellow, and blue represent FI patterns 1, 2, and 3, respectively.

To confirm the reliability of the method for assessing FCR based on FI patterns, we conducted validation in 2 purebred populations (the CC and RR groups). Consistent with the CR group, in both purebred populations, broilers exhibiting FI pattern 1 had significantly higher BW42 and significantly lower FCR22-42 than those exhibiting FI pattern 3 (P < 0.05).

DISCUSSION

During the observation period of the study, from 21 to 42 d of age, the FI of male broilers steadily increased, whereas the emergence of the BWG growth inflection point led to a significant increase in FCR for broilers aged between 36 and 42 d. This critical stage, spanning from 0 to 4 wk, marks a period of rapid growth in various physiological systems, such as the skeleton, immune system, digestive and cardiovascular systems, and feathers. However, after the fourth week, the growth rate begins to decelerate, eventually reaching an inflection point (Aviagen, 2012; Nogueira, et al., 2019). We observed this BWG inflection point during the fifth week. Among the 3 monitoring stages, the period between 36 and 42 d of age has the greatest impact on final production performance, with broiler chickens consuming the highest amount of feed during this stage, coinciding with peak feeding costs. Enhancing feed use and ensuring uniformity within broiler chickens at this crucial stage is likely to result in a significant improvement in overall production efficiency.

In this study, FI was positively correlated with BW across all stages, whereas FCR and BW were consistently negatively correlated. These findings align with those of previous studies (Yuan, et al., 2015; Begli, et al., 2016; Yan, et al., 2019). No significant correlation was found between BWG and FCR in broiler chickens aged between 21 and 42 d, suggesting that these parameters were independent within each stage. However, a moderate correlation was observed between FI in different growth stages, indicating a mutual influence across various developmental phases. Nonetheless, this influence diminishes over time and may be affected by factors such as gastrointestinal development or nervous system regulation (Richards, 2003; Ferket and Gernat, 2006; Richards and Proszkowiec-Weglarz, 2007). In all stages analyzed, the FI, BW, and FCR from d 36 to 42 demonstrated the strongest correlation with the overall FI, BW, and FCR. This finding aligns with previous studies, which report that FI and growth performance at this stage are the most representative of the overall level (Begli et al., 2016).

At the individual level, diverse patterns of FI were observed, indicating variation responses to dietary changes. Similar variations in FI patterns have been observed in other species, including fish (Dwyer, et al., 2002), pigs (Gregory, et al., 1990), and rats (Latham and Blundell, 1979). The method used in this study to classify FI patterns is similar to those used in research on other species, with clustering used to identify dynamic changes in FI over a continuous period. However, because of the distinct feeding characteristics and production indicators of interest among different species, the specific numbers and changes in FI patterns vary. For example, when studying the relationship between FI patterns and reproductive performance in lactating sows (Rodriguez et al., 2023) divided the FI patterns into 5 categories.

Broiler chickens tend to continue feeding until the upper limit of the intestine without being limited by feed toxicity, environmental factors, management practices, or disease factors (Nitsan, et al., 1991; Siegel, 2000; Renema and Robinson, 2004). In this study, considering the ongoing development of the digestive tract in growing broiler chickens, we inferred that broilers following FI patterns 2 and 3 do not reach the upper limit of their digestive tracts. These groups constitute approximately 70% of the flock, indicating that factors beyond gastrointestinal volume limitations do influence broiler FI. Moreover, there is potential to improve the feed utilization efficiency of broilers with patterns 1.

Although there was no significant correlation between TFI and total FCR, FI pattern analysis identified a correlation between FI increment and FCR. The identification of different FI patterns indicated dynamic variation in broiler FI, suggesting that broilers with sustained FI growth tend to have higher FCR. Broilers with negative growth in FI during the wk 6 exhibited poor performance in both body weight and FCR. Specifically, changes in FI during wk 6 were moderately correlated with total FCR, whereas total FI over wk 3 to 6 was not consistently correlated with total FCR in different broiler groups. This emphasizes the importance of changes in FI as a crucial indicator of production efficiency. As broiler growth enters the finishing period after wk 4, individual differences in growth potential become pronounced during wk 6.

As a key indicator of broiler feed utilization efficiency, the FCR plays a crucial role in individual breeding selection. However, adopting simple selection criteria relating to FCR may lead to individuals with lower FI and slower growth, potentially resulting in reduced group uniformity (Willems, et al., 2013; Yi, et al., 2018). In this study, by analyzing FI patterns, we successfully identified a robust connection between the dynamic shifts in FI and FCR. This linkage was substantiated across the 2 purebred lines and their crossbred lines. Consequently, the FI patterns of broiler chickens can serve as an indirect metric for evaluating the FCR of individual broilers. Therefore, in the process of individual selection, when combined with the change in FI, improved uniformity may be obtained. Notably, due to the earlier growth inflection point in hens, the time points involved in the current research results might be more applicable to roosters.

FI patterns serve as a bridge connecting variations in individuals’ FI to the FCR. This allows for the identification of broiler FI patterns that assist in selecting individual chickens with enhanced feed utilization and stronger genetic potential. Accurate testing cycles for FI and FCR are crucial in poultry production, given that feed accounts for the largest proportion of total production costs. Therefore, streamlining testing costs while maintaining test accuracy and reliability is advantageous. Conventionally, the precise measurement of FCR is a time-consuming and labor-intensive process that involves continuous measurement of feed consumption and body weight throughout the broiler growth cycle. However, using FI patterns to assess FCR enables a shorter testing period, offering an efficient means to assess individual broiler growth. Some studies have indicated that the optimal testing duration for FI and feed utilization efficiency can be shortened to 2 wk without a significant reduction in measurement accuracy (Wang, et al., 2006). This reduction in testing duration can lead to cost savings or facilitate the monitoring of a larger number of individual broilers.

In conclusion, FI during d 36 to 42 exerted the most substantial influence on feed utilization efficiency and growth. FI intake throughout the growth process followed 3 distinct weekly patterns. Broilers exhibiting the different FI patterns had significant differences in body weight, FI, and FCR. In particular, broilers showing a gradual increase in weekly FI had greater weight at slaughter and superior feed utilization efficiency. These findings emphasize the importance of FI patterns as a crucial indicator for assessing feed use efficiency and growth potential in broilers. Furthermore, our results indicate that increasing FI at later stages could help improve broiler body weight and feed conversion ratio, which is of great significance for the optimization of breeding and production management strategies. In the future, it is crucial to further delineate the characteristics of FI patterns across various chicken breeds and throughout longer growth cycles. By introducing the identification of feeding patterns into breeding and production management, it will help to select individuals with better growth performance.

DISCLOSURES

The authors declare no conflicts of interest.

ACKNOWLEDGMENTS

The work was supported by the National Key Research and Development Program of China (2022YFF1000204), the National Natural Science Foundation of China (32102535), the Key Research and Development Program of Hainan province (ZDYF2023XDNY036) and the Guangxi Science and Technology Major Program (GK AA23062049). The authors are grateful to Beijing Huadu Yukou Poultry Co., Ltd. for kindly providing and rearing the experimental birds, and Professor Xianyao Li at Shandong Agricultural University for the assistance in phenotypic determination.

References

  1. Alltech. 2023. Alltech Agri-Food Outlook 2023.
  2. Aspevik T., Oterhals A., Ronning S.B., Altintzoglou T., Wubshet S.G., Gildberg A., Afseth N.K., Whitaker R.D., Lindberg D. Valorization of proteins from co- and by-products from the fish and meat industry. Top Curr Chem (Cham) 2017;375:53. doi: 10.1007/s41061-017-0143-6. [DOI] [PubMed] [Google Scholar]
  3. Aviagen 2012. Avian growth profile poster. https://aviagen.com/assets/Tech_Center/BB_Resources_Tools/Avian-Growth-Profile-Poster.pdf. Accessed April, 2012.
  4. Begli H.E., Torshizi R.V., Masoudi A.A., Ehsani A., Jensen J. Longitudinal analysis of body weight, feed intake and residual feed intake in F2 chickens. Livest. Sci. 2016;184:28–34. [Google Scholar]
  5. Buzala M., Janicki B. Review: Effects of different growth rates in broiler breeder and layer hens on some productive traits. Poult. Sci. 2016;95:2151–2159. doi: 10.3382/ps/pew173. [DOI] [PubMed] [Google Scholar]
  6. Byrne C., Chambers E., Morrison D., Frost G. The role of short chain fatty acids in appetite regulation and energy homeostasis. Int. J. Obes. 2015;39:1331–1338. doi: 10.1038/ijo.2015.84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Dwyer K.S., Brown J.A., Parrish C., Lall S.P. Feeding frequency affects food consumption, feeding pattern and growth of juvenile yellowtail flounder (Limanda ferruginea) Aquaculture. 2002;213:279–292. [Google Scholar]
  8. Dunnington E., Siegel P. Anorexia in chickens selected for low juvenile body weight. Archiv. Fur. Geflugelk. 1997;61:201–204. [Google Scholar]
  9. Dunnington E.A., Honaker C.F., McGilliard M.L., Siegel P. Phenotypic responses of chickens to long-term, bidirectional selection for juvenile body weight–historical perspective. Poult. Sci. 2013;92:1724–1734. doi: 10.3382/ps.2013-03069. [DOI] [PubMed] [Google Scholar]
  10. FAO . World Food and Agriculture – Statistical Yearbook 2022. FAO; Rome, Italy: 2022. [Google Scholar]
  11. Ferket P.R., Gernat A.G. Factors that affect feed intake of meat birds: a review. Int. J. Poult. Sci. 2006;5:905–911. [Google Scholar]
  12. Gregory P.C., McFadyen M., Rayner D.V. Pattern of gastric emptying in the pig: relation to feeding. Br. J. Nutr. 1990;64:45–58. doi: 10.1079/bjn19900008. [DOI] [PubMed] [Google Scholar]
  13. Hess C.W., Byerly T.C., Jull M.A. The efficiency of feed utilization by barred plymouth rock and crossbred broilers. Poult. Sci. 1941;20:210–216. [Google Scholar]
  14. Kodinariya T.M., Makwana P.R. Review on determining number of cluster in K-means clustering. Int. J. 2013;1:90–95. [Google Scholar]
  15. Latham C.J., Blundell J.E. Evidence for the effect of tryptophan on the pattern of food consumption in free feeding and food deprived rats. Life Sci. 1979;24:1971–1978. doi: 10.1016/0024-3205(79)90307-2. [DOI] [PubMed] [Google Scholar]
  16. Mai C., Wen C., Xu Z., Xu G., Chen S., Zheng J., Sun C., Yang N. Genetic basis of negative heterosis for growth traits in chickens revealed by genome-wide gene expression pattern analysis. J. Anim. Sci. Biotechnol. 2021;12:52. doi: 10.1186/s40104-021-00574-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Nitsan Z., Dunnington E., Siegel P. Organ growth and digestive enzyme levels to fifteen days of age in lines of chickens differing in body weight. Poult. Sci. 1991;70:2040–2048. doi: 10.3382/ps.0702040. [DOI] [PubMed] [Google Scholar]
  18. Nogueira B., Reis M., Carvalho A., Mendoza E., Oliveira B., Silva V., Bertechini A. Performance, growth curves and carcass yield of four strains of broiler chicken. Braz. J. Poult. Sci. 2019;21:1–8. [Google Scholar]
  19. OECD-FAO. 2022. OECD-FAO Agricultural Outlook 2021-2030.
  20. Prakash A., Saxena V.K., Singh M.K. Genetic analysis of residual feed intake, feed conversion ratio and related growth parameters in broiler chicken: a review. Worlds Poult. Sci. J. 2020;76:304–317. [Google Scholar]
  21. Renema R., Robinson F. Defining normal: comparison of feed restriction and full feeding of female broiler breeders. Worlds Poult. Sci. J. 2004;60:508–522. [Google Scholar]
  22. Richards M., Proszkowiec-Weglarz M. Mechanisms regulating feed intake, energy expenditure, and body weight in poultry. Poult. Sci. 2007;86:1478–1490. doi: 10.1093/ps/86.7.1478. [DOI] [PubMed] [Google Scholar]
  23. Richards M.P. Genetic regulation of feed intake and energy balance in poultry. Poult. Sci. 2003;82:907–916. doi: 10.1093/ps/82.6.907. [DOI] [PubMed] [Google Scholar]
  24. Rodriguez M., Diaz-Amor G., Morales J., Koketsu Y., Pineiro C. Feed intake patterns of modern genetics lactating sows: characterization and effect of the reproductive parameters. Porc. Health Manag. 2023;9:6. doi: 10.1186/s40813-022-00300-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Romero L.F., Zuidhof M.J., Renema R.A., Naeima A., Robinson F.E. Effects of maternal energy efficiency on broiler chicken growth, feed conversion, residual feed intake, and residual maintenance metabolizable energy requirements. Poult. Sci. 2011;90:2904–2912. doi: 10.3382/ps.2011-01665. [DOI] [PubMed] [Google Scholar]
  26. Siegel P.B. Social behavior and husbandry of the fowl - an essay. Arch. Anim. Breed. 2000;43:347–350. [Google Scholar]
  27. So P.-W., Yu W.-S., Kuo Y.-T., Wasserfall C., Goldstone A.P., Bell J.D., Frost G. Impact of resistant starch on body fat patterning and central appetite regulation. PLoS One. 2007;2:e1309. doi: 10.1371/journal.pone.0001309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sun J.M., Richards M.P., Rosebrough R.W., Ashwell C.M., McMurtry J.P., Coon C.N. The relationship of body composition, feed intake, and metabolic hormones for broiler breeder females. Poult. Sci. 2006;85:1173–1184. doi: 10.1093/ps/85.7.1173. [DOI] [PubMed] [Google Scholar]
  29. Vågsholm I., Arzoomand N., Boqvist S. Food security, safety, and sustainability–getting the trade-offs right. Front. Sustain Food Syst. 2020;4:16. [Google Scholar]
  30. Wang Z., Nkrumah J.D., Li C., Basarab J.A., Goonewardene L.A., Okine E.K., Crews D.H., Jr., Moore S.S. Test duration for growth, feed intake, and feed efficiency in beef cattle using the GrowSafe System1. Anim. Sci. J. 2006;84:2289–2298. doi: 10.2527/jas.2005-715. [DOI] [PubMed] [Google Scholar]
  31. Wen C., Yan W., Zheng J., Ji C., Zhang D., Sun C., Yang N. Feed efficiency measures and their relationships with production and meat quality traits in slower growing broilers. Poult. Sci. 2018;97:2356–2364. doi: 10.3382/ps/pey062. [DOI] [PubMed] [Google Scholar]
  32. Willems O.W., Miller S.P., Wood B.J. Aspects of selection for feed efficiency in meat producing poultry. Worlds Poult. Sci. J. 2013;69:77–88. [Google Scholar]
  33. Windhorst H.-W. In: Pages 1–25 in Poultry Quality Evaluation. Petracci M., Berri C., editors. Woodhead Publishing; Cambridge: 2017. Chapter 1 - dynamics and patterns of global poultry-meat production. [Google Scholar]
  34. Yan W., Sun C., Wen C., Ji C., Zhang D., Yang N. Relationships between feeding behaviors and performance traits in slow-growing yellow broilers. Poult. Sci. 2019;98:548–555. doi: 10.3382/ps/pey424. [DOI] [PubMed] [Google Scholar]
  35. Yi Z., Li X., Luo W., Xu Z., Ji C., Zhang Y., Nie Q., Zhang D., Zhang X. Feed conversion ratio, residual feed intake and cholecystokinin type A receptor gene polymorphisms are associated with feed intake and average daily gain in a Chinese local chicken population. J. Anim. Sci. Biotechnol. 2018;9:50. doi: 10.1186/s40104-018-0261-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Yuan J., Wang K., Yi G., Ma M., Dou T., Sun C., Qu L.J., Shen M., Qu L., Yang N. Genome-wide association studies for feed intake and efficiency in two laying periods of chickens. Genet. Sel. Evol. 2015;47:82. doi: 10.1186/s12711-015-0161-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Zampiga M., Calini F., Sirri F. Importance of feed efficiency for sustainable intensification of chicken meat production: implications and role for amino acids, feed enzymes and organic trace minerals. Worlds Poult. Sci. J. 2021;77:639–659. [Google Scholar]
  38. Zampiga M., Flees J., Meluzzi A., Dridi S., Sirri F. Application of omics technologies for a deeper insight into quali-quantitative production traits in broiler chickens: a review. J. Anim. Sci. Biotechnol. 2018;9:1–18. doi: 10.1186/s40104-018-0278-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Zhao R., Muehlbauer E., Decuypere E., Grossmann R. Effect of genotype-nutrition interaction on growth and somatotropic gene expression in the chicken. Gen. Comp. Endocrinol. 2004;136:2–11. doi: 10.1016/j.ygcen.2003.11.009. [DOI] [PubMed] [Google Scholar]

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