Scientific innovation in agriculture: image processing for livestock management and empowering Indian youth for global leadership in Viksit Bharat
Year: 2025
Type: article
Abstract: Modern livestock management relies heavily on image processing, which allows for advances in body weight prediction, breed recognition, and individual animal identification. It entails transferring visual data to a digital format for analysis, using techniques such as picture thresholding, segmentation, and feature extraction. The technique uses a variety of picture formats, including binary, grayscale, depth, RGB, and infrared. Body condition grading, breed categorization, and early illness diagnosis are among the most important uses. Recent research have shown that 3D cameras and convolutional neural networks (CNNs) can accurately identify breeds and estimate physical condition in animals. While image processing has various advantages, including less labor and improved decision-making, difficulties remain, such as high starting costs, reliance on high-quality photos, and technological complexity. To reach its full potential, further research, training, and scalable solutions are required. By tackling these difficulties, image processing has the potential to significantly enhance sustainable livestock management techniques, resulting in more efficient, data-driven agricultural systems.
Author: Tarun Kumar*, Pranaw Kumar Tripathi
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W6949740978
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