Carlos Quilcate
Papers
1
Total Citations
13
H-Index
1
About
Carlos Quilcate is a rising researcher at the intersection of artificial intelligence and agri-food technology, with a focused expertise in applying computer vision and sensor-based AI to enhance meat quality assessment and supply chain traceability. His most-cited work, "Implementing artificial intelligence to measure meat quality parameters in local market traceability processes" (2024, 13 citations), introduces a novel framework that leverages AI-driven sensors to quantify and qualify meat products from various domestic species, addressing critical gaps in local market transparency and food safety. This contribution is particularly significant for developing regions where traditional quality control methods are limited. Quilcate’s research not only advances the practical deployment of AI in agricultural settings but also supports the broader goals of sustainable food systems and consumer protection. As an emerging voice in precision livestock farming, his work is gaining traction among researchers and industry stakeholders interested in scalable, low-cost digital solutions for meat traceability. With a clear trajectory toward integrating machine learning with real-world agricultural challenges, Quilcate is positioned to make lasting impacts on how local markets ensure product integrity and quality.
Research Focus
Key Achievements
Top Papers
- 1