Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - Scopus: 20Estrus Detection and Dairy Cow Identification With Cascade Deep Learning for Augmented Reality-Ready Livestock Farming(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Arıkan, İ.; Ayav, T.; Seçkin, A.Ç.; Soygazi, F.Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming. © 2023 by the authors.Article Citation - WoS: 13Citation - Scopus: 13Multi-Scale Benchtop 1h Nmr Spectroscopy for Milk Analysis(Academic Press, 2021) Söyler, Alper; Çıkrıkçı, Sevil; Çavdaroğlu, Çağrı; Bouillaud, Dylan; Farjon, Jonathan; Giraudeau, Patrick; Öztop, Mecit H.Benchtop NMR systems offers various advantages such as being easy to use, not requiring constant maintenance and being available at affordable prices. In this study, multiple aspects of benchtop NMR spectroscopy were explored to analyze milk in an industrial context, either regarding the quality of production or regarding the differentiation of the final product. The first part focuses on the production conditions of lactose hydrolysis in milk and quantitative online NMR spectroscopy was adapted to follow lactose hydrolysis in milk in continuous flow mode. The second part focuses on differentiating milk samples having different properties. 36 milk samples from France and Turkey were analysed and glycerol, fat and sugar contents were measured from the NMR spectra. Combination of spectroscopic data with a proposed Artificial Neural Network model enabled to classify milk of different origins and different properties. This study shows that benchtop NMR spectroscopy is a versatile non-destructive control method that can help controlling milk quality both during and after production. © 2020 Elsevier Ltd