A case study to test an early warning technology to detect enteric dysbiosis in broiler production and to reduce the use of antibiotics

This study presents a case study of a novel early-warning system for detecting enteric dysbiosis in broiler chickens using Volatile Organic Compounds (VOCs) analysis. The system combines metal oxide semiconductor (MOS) sensors with PCA–KNN algorithms to identify metabolic air-profile changes associated with enteric diseases. Field validation was conducted in two broiler houses in Northern Italy using oocyst counts as the diagnostic gold standard. The monitoring system issued alerts up to four days before clinical signs appeared, enabling timely intervention with organic acids instead of antibiotics. Early treatment reduced mortality, maintained feed conversion efficiency, and preserved antibiotic-free certification. The model achieved over 80% accuracy in early detection, while organic acid intervention (€88) was substantially more cost-effective than antibiotic treatment (€180). Overall, this technology offers a non-invasive, real-time tool to support antimicrobial reduction strategies in poultry production, aligning with EU objectives to minimize antibiotic use. Limitations of the study include reliance on oocyst count alone, and need for IoT connection. Nonetheless, this approach represents a scalable and sustainable alternative to antibiotics in broiler production systems.