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International Journal of Computer Techniques Volume 12 Issue 3 | Predictive Modeling of Milk Production Using Artificial Intelligence and Machine Learning Techniques

Predictive Modeling of Milk Production Using AI and ML Techniques

Predictive Modeling of Milk Production Using AI and ML Techniques

International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025

ISSN: 2394-2231 | https://ijctjournal.org

Authors

Ms. V. Manibabu – Research Scholar, Dept. of Computer Science, Shrimati Indira Gandhi College, Trichy-2

Dr. M. Gomathy – Research Supervisor, Dept. of Computer Science, Shrimati Indira Gandhi College, Trichy-2

Abstract

This study presents a predictive modeling framework that estimates milk yield using **AI and ML techniques**. Real-world datasets are analyzed using features like **breed, lactation stage, feed intake**, and **environmental conditions**. Models including **Random Forest, SVM, Gradient Boosting**, and **ANN** were evaluated through **R², RMSE**, and **MAE**. Results show that ensemble and neural methods significantly outperform traditional techniques, offering a robust approach to **smart dairy management** and **precision farming**.

Keywords

Dairy Alchemy, Intelligent Herding, Milk Oracle, Farming Synergy, Data-driven Pastures

Conclusion & Future Scope

Artificial Neural Networks and Gradient Boosting Machines excelled in modeling nonlinear relationships in dairy data. Their integration empowers dairy farmers to make **proactive decisions**, reduce resource waste, and increase productivity. Real-time data systems, including sensor feeds for nutrition, health, and weather conditions, should be explored to enhance accuracy and promote **intelligent, adaptive farm ecosystems**. This research positions AI as a transformative force in the future of dairy technology.

References

  1. Suseendran & Duraisamy (2021). Prediction of Dairy Milk Production Using ML Techniques. DOI: 10.1007/978-981-33-6645-0_16
  2. Alwadi et al. (2024). Smart Dairy Farming Based on Deep ML. DOI: 10.1007/s41870-023-01234-5
  3. Khan & Majeed (2022). Milk Yield Prediction Using ML: A Comparative Study. DOI: 10.1016/j.jdst.2021.11.005
  4. Ferreira & Souza (2020). ANN for Milk Yield Prediction. DOI: 10.1186/s40104-020-0410-6
  5. Herrero-Lopez et al. (2023). IoT + ML for Real-Time Milk Yield. DOI: 10.3390/s23052481
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