Kizil, ÜnalYapici, Ali NailYapici, Binnur MeriçliBilgi, Sadi TurgutInalpulat, Melis2025-01-272025-01-2720141583-4433https://doi.org/10.24264/lfj.14.2.3https://hdl.handle.net/20.500.12428/13132In this study it was aimed to design a metal oxide gas sensor array to determine the bacterial load in soaking float of wet-salted domestic sheep skin for garment leather production. The results showed that an array of 4 metal oxide gas sensors employed with Artificial Neural Networks (ANNs) can predict the 2 bacterial population in soaking float of leather manufacturing. The relationship between predicted and observed bacterial populations yielded a R value of 0.95 in model testing. Design procedures, gas sensors and other materials and techniques were explained in this paper.eninfo:eu-repo/semantics/openAccessArtificial neural networks; Bacteria; Gas sensors; Leather; OdorEvaluation of the relationship between bacterial population and associated gas generation in soaking float of sheep skin using a sensor array systemEvaluarea rela?iei dintre popula?ia de bacterii şi generarea de gaze asociate în flota de înmuiere a pieilor de oaie folosind un sistem de senzoriArticle1429310610.24264/lfj.14.2.32-s2.0-84905487838Q4