Investigating mineral affecting alkaline phosphatase activity and feed efficiency of broiler chickens using meta analytical and machine learning approaches

Document Type : Research Paper

Authors

Department of Poultry Science, Faculty of Agriculture Science, Tarbiat Modares University, Tehran, Iran

Abstract

This study aims to develop two separate models to predict serum alkaline phosphatase (ALP) activity in broiler chickens based on dietary mineral intake and to forecast feed conversion ratio (FCR) based on their mineral intake and serum ALP activity. A meta-analysis method was employed to aggregate data from 29 articles spanning years 1998 to 2020. This resulted in a dataset of 185 rows containing variables such as serum ALP activity, calcium, phosphorus, zinc of the diet, and FCR in broiler chickens. Machine learning techniques, specifically artificial neural network models (ANN), were utilized for data analysis and predictive modeling. The ANN demonstrated high accuracy in predicting ALP activity and FCR, achieving R2 values of 97% and 95%, respectively. Sensitivity analysis revealed that serum ALP activity is more responsive to changes in calcium, whereas FCR is more sensitive to changes in zinc. Furthermore, through optimization of the ANN model, the minimum attainable FCR was found to be 1.41. This corresponded to ALP activity of 1190 U/L, and daily intake of zinc of 11.21 mg, phosphorus of 0.46 g, and calcium of 0.70 g. These findings provide insights into optimizing broiler chicken nutrition for improved performance. The developed model not only accurately predicts ALP activity and FCR in broiler chickens but also enhances broiler breeding by offering an easy-to-use tool for optimizing mineral intake and accurately predicting bird performance. To facilitate accessibility for readers and nutritionists, an Excel® calculator was created for predicting ALP activity and FCR in broilers using the developed ANN.

Keywords

Main Subjects

Extended Abstract

Introduction

Broiler metabolism relies heavily on various enzymes present in their plasma. Any alterations in these enzymes can significantly impact broiler performance. Alkaline phosphatase (ALP) is a vital enzyme found in broiler blood serum, with four isoenzymes expressed in different tissues including intestines, placenta, and nonspecific tissues like liver, bone, and kidney. This study aims to explore the relationship between ALP enzyme activity, mineral consumption, and feed conversion ratio in broiler chickens through meta-analysis.

Materials and methods

Data collection involved a systematic search from diverse sources without language restrictions, focusing on indexed publications between 1998 and 2020 presenting in vivo experimental results on broilers. Key search terms included blood serum ALP, broiler mineral intake, feed conversion, and feed efficiency. A total of 29 articles encompassing 11,392 broiler chickens were included, yielding a dataset of 185 rows of information. Variables included ALP activity (U/L), daily mineral intake (calcium, phosphorus, and zinc), and feed efficiency at 42 days. Artificial neural network (ANN) models were constructed using JMP PRO version 14 software, with one model incorporating all four input parameters and another with only mineral intake variables.

 

Results

Employing two ANN models significantly enhanced prediction accuracy, achieving R2 values of 97% and 95% for ALP activity and feed conversion ratio, respectively. Sensitivity analysis underscored calcium and FCR as more responsive to ALP activity changes compared to zinc levels. Further optimization of the ANN model revealed the minimum attainable feed conversion ratio (FCR) to be 1.41 g/g. This corresponded to an ALP activity of 1190 U/L, with daily intake levels of zinc at 11.21 mg, phosphorus at 0.46 g, and calcium at 0.70 g. These findings offer insights into optimizing broiler nutrition for enhanced performance. The developed model facilitates optimized broiler breeding by predicting performance based on mineral intake, offering a user-friendly Excel® calculator for easy implementation by readers and nutritionists.

 

Conclusion

The established model provides a precise estimation of feed conversion ratio and serum ALP activity in broiler chickens, enhancing breeding practices and performance prediction accuracy.

Author Contributions

For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used “Conceptualization, X.X. and Y.Y.; methodology, X.X.; software, X.X.; validation, X.X., Y.Y. and Z.Z.; formal analysis, X.X.; investigation, X.X.; resources, X.X.; data curation, X.X.; writing—original draft preparation, X.X.; writing—review and editing, X.X.; visualization, X.X.; supervision, X.X.; project administration, X.X.; funding acquisition, Y.Y. All authors have read and agreed to the published version of the manuscript.” Please turn to the CRediT taxonomy for the term explanation. Authorship must be limited to those who have contributed substantially to the work re-ported.

All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.

Data Availability Statement

In this section, please provide details regarding where data supporting reported results can be found, including links to publicly archived datasets analyzed or generated during the study (see examples). Data available on request from the authors.

If the study did not report any data, you might add “Not applicable” here.

 

Acknowledgements

The Acknowledgments section should be a few sentences at the end, but it is important to recognize those people (organizations and individuals) who made considerable impact on the research, provided significant help to the author to formulate and complete the experiment, and improved the research at any stage (from providing access to equipment or field sites to editing the manuscript). However, this is an optional section.

In this section, you can acknowledge any support given which is not covered by the author contribution or funding sections. This may include administrative and technical support, or donations in kind (e.g., materials used for experiments).

The authors would like to thank all participants of the present study.

Ethical considerations

The study was approved by the Ethics Committee of the University of ABCD (Ethical code: IR.UT.RES.2024.500). The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares no conflict of interest.

 

Conflict of interest

The author declares no conflict of interest.

 

References

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Iranian Journal of animal Science
Volume 56, Issue 1
March 2025
Pages 193-211

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History

  • Receive Date: 30 November 2023
  • Revise Date: 27 June 2024
  • Accept Date: 29 June 2024

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