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Öğe Analysis of Covariance on The Randomized Plot Factorial Experiment Design(Selçuk Üniversitesi, 2015) Altay, Yasin; Keskin, IsmailThis study isconducted in order to determine the effectiveness of the analysis of variance andcovariance on the randomized plot factorial experiment design for this purpose, comparative analysis of covariance analysisof variance tries to explain, while the created artificial dataset applying to randomized plot factorial experimentdesign respectively. Analysis ofcovariance is an analysis which consists of analysis of variance and regressiontechnique used together. Although the application of this technique consistsof different experiment design analysis of covariance can beapplied to all experimental design. This analysis usedby dividing non-homogeneous materials to sub-blocks or a co-variable (concomitant variable-covariates) toobtain more reliable results and experimental design toincrease sensitivity of experimental design. In thisstudy, in all experimental design covariates error varianceratio was determined that lower values compared to analysis of variance.The decrease of error variance ratio is significant in terms of increasingreliability of findings.Öğe Application of neural network and adaptive neuro-fuzzy inference system to predict subclinical mastitis in dairy cattle(AGRICULTURAL RESEARCH COMMUNICATION CENTRE, 2015) Mammadova, Nazira M.; Keskin, IsmailMastitis is an important problem, while I guess AT is a possible solution to detect subclinical mastitis in Holstein cows milked with automatic milking systems. Mastitis alerts were generated via ANN and ANFIS model with the input data of lactation rank (current lactation number), milk yield, electrical conductivity, average milking duration and season. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the sampling period. Cattle were judged healthy or infected based on somatic cell counts. This study undertook a detailed scrutiny of ANN, and ANFIS AT methodology; constructed and examined models for each; and chose optimal methods based on that examination. The two mastitis detection models were evaluated as to sensitivity, specificity and error rate. The ANN model yielded 80% sensitivity, 91% specificity, and 64% error and the ANFIS, 55%, 91% and 35%. These results suggest the ANN model is better predictor of subclinical mastitis than ANN based on Z-test (the hypothesis control for the difference between rates). AI models such as these are useful tools in the development of mastitis detection models. Prediction error rates can be decreased through the use of more informative parameters.Öğe Application of the Support Vector Machine to Predict Subclinical Mastitis in Dairy Cattle(HINDAWI LTD, 2013) Mammadova, Nazira; Keskin, IsmailThis study presented a potentially useful alternative approach to ascertain the presence of subclinical and clinical mastitis in dairy cows using support vector machine (SVM) techniques. The proposed method detected mastitis in a cross-sectional representative sample of Holstein dairy cattle milked using an automatic milking system. The study used such suspected indicators of mastitis as lactation rank, milk yield, electrical conductivity, average milking duration, and control season as input data. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the control period. Cattle were judged to be healthy or infected based on those somatic cell counts. This study undertook a detailed scrutiny of the SVM methodology, constructing and examining a model which showed 89% sensitivity, 92% specificity, and 50% error in mastitis detection.Öğe DETECTING THE RELATIONSHIP OF CALIFORNIA MASTITIS TEST (CMT) WITH ELECTRICAL CONDUCTIVITY, COMPOSITION AND QUALITY OF THE MILK IN HOLSTEIN-FRIESIAN AND BROWN SWISS CATTLE BREEDS USING CART ANALYSIS(PARLAR SCIENTIFIC PUBLICATIONS (P S P), 2018) Aytekin, Ibrahim; Eyduran, Ecevit; Keskin, IsmailThe aim of this study was to describe the relationship between mastitis and electrical conductivity, milk composition, milk quality in dairy cattle. California mastitis test (CMT) was used to make a diagnosis of mastitis in the cows, and considered as a binary response variable i.e. healthy and unhealthy. Conductivity, color measurement (L* and a*), milk fat, calving month and freezing point were considered as independent variables in the model. All the animals were classified with overall accuracy of 89.6 (%) or the error of 10.4 (%) in diagnosis of mastitis by using Classification and Regression Tree (CART) data mining algorithm. CART algorithm correctly classified unhealthy cows with an accuracy of 77.2%. The algorithm correctly classified healthy cows with a marvelous accuracy of 95.7% and a marvelous area value under ROC curve of 0.924, P=0.000). It was concluded that some measurements i.e. CMT, electrical conductivity, milk color values, milk composition and quality may be used to accurately detect mastitis together with the help of the CART algorithm.Öğe Estimation of Cold Carcass Weight and Body Weight from Several Body Measurements in Sheep through Various Data Mining Algorithms(ZOOLOGICAL SOC PAKISTAN, 2017) Karabacak, Ali; Celik, Senol; Tatliyer, Adile; Keskin, Ismail; Erturk, Yakup Erdal; Eydurans, Ecevit; Javed, YasirThe goal of the present study was to compare the predictive performance of three data mining algorithms viz., CHAID, Exhaustive CHAID, and CART implemented in the estimation of cold carcass weight (CCW) and body weight (BW) from several body measurements (withers height (WH), chest depth (CD), body length (BL), hearth girth (HG) and leg circumference (LC)) measured from five sheep breeds (Akkaraman (9), Daglic (10), Kivircik (10), Merinos (10) and Karacabey Merino (8)) reared in Konya province conditions located in the Central Anatolia Region of Turkey. For measuring the predictive performance of three algorithms in Models I and II, goodness of fit criteria (coefficient of determination (R-2%), adjusted coefficient of determination (Adj.R-2%), coefficient of variation (CV%), SD ratio, Root Mean Square Error (RMSE), Relative Approximation Error (RAE), and Pearson correlation coefficient between actual and predicted values were calculated. For both Models, CHAID and CART were chosen as the best algorithms in the estimation of CCW trait, whereas only CHAID was the ideal tree-based algorithm in the estimation of BW trait. In conclusion, the determination of the best data mining algorithm on the estimation of BW and CCW traits might be utility for further researches linked with characterization of sheep breeds, and sheep breeding in very large flocks.Öğe Fatty Acid Composition and Conjugated Linoleic Acid Content in Various Carcass Parts of Kivircik Lambs(ZOOLOGICAL SOC PAKISTAN, 2016) Karabacak, Ali; Guler, Ozmen-Gokalp; Keskin, Ismail; Javed, Yasir; Tariq, Mohammad MasoodThis investigation was conducted to determine the fatty acid composition of lamb meat. For this purpose, Kivircik lambs fattened intensively were slaughtered at the end of two-month fattening period. The fatty acid composition of the samples from leg, shoulder, rib, and breast parts of cold carcasses after slaughtering were analyzed for total saturated fatty acid (SFA), unsaturated fatty acid (MUFA), polyunsaturated fatty acid (PUFA), and conjugated linoleic acid (CLA). In the legs SFA, MUFA, PUFA and CLA were found to be 42.96, 40.80, 5.61, and 1.18%, respectively. In the shoulder these were 43.48, 43.21, 3.59, and 0.85%; in ribs 40.61, 45.36, 4.67, and 1.09% and in breast 37.88, 51.39, 3.89, and 1.20%, respectively. The results showed that the breast part of a carcass was the most advantageous part in terms of fatty acids.Öğe Fitness of four different mathematical models to the lactation curve of Brown Swiss cows in Konya Province of Turkey(AGRICULTURAL INST CANADA, 2009) Keskin, Ismail; Dag, Birol; Sariyel, VahdettinKeskin, I., Dag, B. and Sariyel, V. 2009. Fitness of four different mathematical models to the lactation curve of Brown Swiss cows in Konya Province of Turkey. Can. J. Anim. Sci. 89: 195-199. The aim of this study was to investigate the fitness of Incomplete Gamma (WD), Exponential (WIL), Mixed Log (MIL) and Polynomial Regression (AS) models to the lactation curve of Brown Swiss Cows. Data were collected from 143 Brown Swiss cows raised on the Altinova State Farm in Konya Province, Turkey. Milk yield was recorded monthly, and milk records were started at the third week of lactation (mean = 16.9 day, SD = 0.7). Total milk yields estimated by the four models were very close to real total milk yield. The models were found to be adequate for estimation of milk yield. The MIL model underestimated the peak yield significantly. The differences between peak yields of the models and real peak yields were not significant and ranged from 27.70 to 29.01 L. All models forecasted peak time earlier than real peak time. The differences for the persistency values of the four models were significant. The AS model's persistency value was nearly equal to the real persistency value (77.56 vs. 77.59%). R-2 values of the models changed from 86.05 to 97.95%. The AS model gave the best R-2 and the least MSPE values. Consequently, the AS model showed the best fit to the lactation data of Brown Swiss cows and allowed a suitable definition of the lactation curve.Öğe Investigation of Relationship Amongst Milk and Wool Yield Traits of Awassi Sheep by Using Canonical Correlation Analysis(MEDWELL ONLINE, 2009) Keskin, Ismail; Dag, BirolThis study was carried out to investigate the relationship between milk and wool yield traits of Awassi sheep by using canonical correlation analysis. Data were collected from 108 Awassi sheep maintained at the state farm of Gozlu in Konya Province. The 2 data sets were formed for the analysis. One of the set (X set) was consisted of wool traits that were Fleece Weight (FW), Staple Length (SL), Fibre Length (FL), average number of crimps over a length of 5 cm (ANC) and Wool Fineness (WF) and the other set (Y set) was constituted of Milk Yield (MY), Lactation Period (LP), Milking Period (MP), Average Daily Milk Yield (ADMY) and Maximum Daily Milk Yield (MDMY). The first canonical correlation coefficient between the 2 sets was 0.4473 (p>0.05) and the 2nd was 0.3203 (p>0.05).Öğe Lactation curve traits of holstein cows raised at polatli state farm(KAFKAS UNIV, VETERINER FAKULTESI DERGISI, 2009) Keskin, Ismail; Cilek, Sueleyman; Ilhan, FatmaThis study was done to determine lactation curves traits of Holstein cows raised at Polatli State Farm. Gamma curve parameters (Yt = at(b)e(-ct)) of Wood were used in determination of the types of lactation curve. In this study, values of parameters a, b, c were used in determination of the shape and type of lactation curve. All parameters in typical lactation curves are positive. As one of these parameters is negative, curve is atypical lactation curve. If both b and c parameter are negative, lactation curves are concave. If b parameter is negative and c parameter is positive, lactation curve have negative slope (decreasing type). In total 2581 lactation curves were investigated in this study, 2049 lactation curves were determined as typical (79.39%), 253 lactation curves were determined as concave (9.80%). 279 lactation curves were determined as decreasing type (10.81%). For typical lactation curves, a (beginning yield), b (coefficient of rising), c (coefficient of decreasing), persistency (S), the time after parturition when the peak yield occurs (T-max), maximum daily peak yield (Y-max) and coefficient of determination of variation (R-2) were 27.5 +/- 0.18, 0.47 +/- 0.008, 0.178 +/- 0.0023, 2.7 +/- 0.001, 81 +/- 2.1, 26.7 +/- 0.15, 68.0 +/- 0.50, respectively. For concave lactation curves, values of a, b, c, Tmax, Ymax and R-2 were found as 23.5 +/- 0.42, -0.37 +/- 0.016, -0.062 +/- 0.0038, 744 +/- 159, 16.5 +/- 0.42 and 47.8 +/- 1.68, respectively. For decreasing typical lactation curves, values of a, b, c, Tmax, S and R-2 were found as 27.6 +/- 0.41, -0.13 +/- 0.007, 0.051 +/- 0.0023, -567 +/- 327, 2.9 +/- 0.05 and 65.8 +/- 1.33, respectively.Öğe Oestrus detection by fuzzy logic model using trait activity in cows(KAFKAS UNIV, VETERINER FAKULTESI DERGISI, 2011) Memmedova, Nazire; Keskin, IsmailThe aim of this study was the accurately oestrus detection of cows by fuzzy logic model, where the traits activity, movement behavior of cows and period since last oestrus was used simultaneously. The animal material of the study formed the 117 Holstein cows in different ages grown up in private farm. The trait activity was measured by pedometer, which were attached at the left foreleg of each cow. The trait period since last oestrus include information about previous inseminations and oestrus cases. It was also used the certain input named cow's type which determined the cow's movement behavior. As the result of the study, the rate of the detection of cows in oestrus by using fuzzy logic system was considerable quite high as 98.0% was determined.Öğe SUBCLINICAL MASTITIS PREDICTION IN DAIRY CATTLE BY APPLICATION OF FUZZY LOGIC(UNIV AGRICULTURE, FAC VETERINARY SCIENCE, 2015) Mikail, Nazire; Keskin, IsmailThe main purpose of this study was to detect subclinical mastitis in a large sized dairy herd milked using automated milking systems. Recording of data was performed on the private dairy farm Karapinar of the province of Konya, Turkey. A data set of 346 milkings from 170 cows was used. Mastitis alerts were generated via a Fuzzy Logic (FL) model with the input data of lactation rank (current lactation number), milk yield, electrical conductivity, average milking duration and season. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the sampling period. Cattle were judged healthy or infected based on somatic cell counts. The evaluation of the model was carried out according to sensitivity, specificity and error rate. The FL model yielded 82% sensitivity, 74% specificity, and 60% error. Fuzzy logic seems one of the useful tools to develop a detection model for mastitis. With more informative parameters, the error rate can be decreased.
