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Öğe A Sound-Based Monitoring and Evaluation System for Small-Scale Dairy Operations(2022) Kızıl, Ünal; Aksu, Sefa; Kınacı, Ahmet Cumhur; Bilgücü, Ertuğrul; Senturklu, SongulContinuous monitoring of livestock operations is vitally important for a sustainable production system. Monitoring systems based on cameras are not sufficient in livestock barns since they require visual inspection and ignore vocal conditions within the barn. These systems are also quite expensive for most small family operations. A prototype device that costed $ 470 developed to remotely monitor the barn based on sound sensors (microphones) data. This device also warns the operator by sending an SMS at sound intensities exceeding the predetermined durations and threshold values. It also makes it possible to listen to the barn by phone if needed. The device and associated web database was tested in this study. The main challenge was the determination of threshold values at which sensors are to generate warning SMS messages. As a method, Z-score of 2.33 which corresponds to area left of the 99% of the normally distributed data curve was determined representing the highest values with a possibility of 1% observation for each sensor. An average value of 97 dB was determined to be a threshold suggestion for future studies. A customizable web-based MySQL database was created to monitor and evaluate the long term data collected via the system.Öğe E-nose identification of milk somatic cell count(Çanakkale Onsekiz Mart Üniversitesi, 2016) İnalpulat, Melis; Kızıl, Ünal; Bilgücü, Ertuğrul; Genç, LeventMastitis is a common disease among dairy animals which causes serious economic losses. It can be diagnosed via diverse clinical findings, while milk somatic cell count (SCC) is accepted as a key indicator. However, determination of SCC with traditional methods is time consuming and laborious. This paper focuses on the ability of electronic nose (e-nose) system containing 12 different metal oxide sensors (MOS) to discriminate milks with somatic cell counts (SCC) above a threshold value. Milk samples were collected from dairy farms around Biga district of Çanakkale province, Turkey. Forty-six samples were analyzed using standard protocols in laboratory, then exposed to DiagNose II e-nose system. Artificial Neural Networks (ANNs) was used to discriminate between Non-Mastitic (N-M) / Mastitic (M) samples depending on sensor responses. Results showed that 8 of 12 sensors were responded to milk samples. Thus, performances of several ANNs models with different topologies were tested using 8 sensor responses. ANNs was trained using 28 samples, and remaining 18 samples were used in validation step. Among tested models, the results of the lowest overall errors for training and validation steps were found to be 35.71 % and 38.89 % respectively. To improve the performance, Principal Components Analysis (PCA) performed for dimension reduction and three components were selected to be included in ANNs model instead of 8 sensors. Performing of PCA prior to ANNs provided decreased overall errors for training (10.7 %) and validation (0 %). However, the actual performance of the system should be tested using new dataset.Öğe Effect of somatic cell count of cow’s milk on the lipolysis and fatty acid profile of farmer cheese(Universiti Putra Malaysia, 2021) Ivanov, Galin Y.; Bilgücü, Ertuğrul; Balabanova, T. G.; Ivanova, Ivelina V.The objective of the present work was to investigate the effect of somatic cell count (SCC) of raw cow’s milk on the lipolysis and oxidative processes in farmer cheese. The farmer cheesesamples were produced from three different batches of raw cow’s milk of low (about 100,000cells/mL, batch L), medium (between 500,000 and 600,000 cells/mL, batch M), and high(above 1,500,000 cells/mL, batch H) SCC. The farmer cheese samples were aged andcold-stored at 4 ± 1°C for three and ten months, respectively. Lipolysis in the farmer cheesesamples was evaluated by monitoring the changes in cheese fatty acid values and peroxidevalues, as well as the changes in the fatty acid profile. Results indicated intensive lipolysisduring aging and cold storage of batch H; increased concentrations of short-chain fatty acidsas well as a higher percentage of saturated fatty acids were observed. It can thus be concludedthat the accelerated lipolysis in farmer cheese samples made from raw cow’s milk with highSCC could cause some quality defects, and reduce cheeses’ shelf life.Öğe Effect of somatic cells count in cow milk on the formation of biogenic amines in cheese(Springer, 2021) Ivanova, Ivelina; Ivanova, Mihaela; Ivanov, Galin; Bilgücü, ErtuğrulComparative studies on physicochemical characteristics of milk with different somatic cells count (SCC) (L-low < 400,000 cells/ml, M-medium between 500,000 and 600,000 cells/ml and H-high > 1,000,000 cells/ml) and obtained cheeses, were conducted. No significant differences between samples were found. The H SCC milk was characterized by the highest total viable count. Higher levels of proteolysis were established in cheeses made from milk with SCC exceeding 500,000 cells/ml. After 10 months of ripening and cold storage the water-soluble nitrogen in total nitrogen (WSN/TN), noncasein nitrogen in total nitrogen (NCN/TN), nonprotein nitrogen in total nitrogen (NPN/TN) and free amino groups values of the sample with the highest SCC reached 28.4 +/- 0.8%, 24.8 +/- 0.9%, 18.3 +/- 0.9% and 83.6 +/- 0.3 mg/kg respectively. The biogenic amine concentration in the cheese samples from the L and M batches remained below 10 mg/kg throughout the ripening and cold storage period. The present study established an increase in the biogenic amine content during the ripening period and the cold storage of the cheeses made from milks with high SCC (batch H). The main amines accumulated at the end of the storage period (10th month) were tyramine (31.7 +/- 0.3 mg/kg), putrescine (20.5 +/- 0.2 mg/kg) and cadaverine (14.6 +/- 0.2 mg/kg). Histamine was not found in any of the studied cheese samples.Öğe Spatial Noise Modeling in Dairy Operations(2022) Kızıl, Ünal; Aksu, Sefa; Kınacı, Ahmet Cumhur; Bilgücü, Ertuğrul; Senturklu, SongulA prototype sound monitoring and evaluation system was used to measure the noise level in a medium-sized dairy barn. In addition, the distribution of noise from the shelter was also modeled in order to determine how much the barn, where only the animals, mechanical tools and working workers in the barn were the sound source, affect the neighboring operations in terms of sound intensity. Considering that the intensity of the sound fluctuates according to the activities during the day, the equal noise level (Leq), which is a cumulative indicator, was used. The data recorded by 7 sensors placed inside the barn were modeled separately for day and night conditions in CadnaA software, and the distribution of Leq values both inside and outside the barn was modeled numerically and visually. As a result of the modeling study, Leq levels in the shelter were determined by averaging the values of 7 sensors. Accordingly, the Leq values for day and night in the barn were calculated as 69.0 and 64.2 dB, respectively. It was determined that these values were considerably lower than the maximum allowable values for dairy cattle. In addition, the spatial distribution modeling of the sound emitted from this establishment was at levels that would not cause disturbance for the neighboring operations.
