Abstract. In this study, we aimed to determine the slaughter-carcass characteristics, meat quality, and fatty acid composition in lambs raised under intensive and extensive conditions. The animal material consisted of 30 Norduz male lambs, with an average age of 171 days. The lambs were divided into two groups: concentrate-fed lambs (CO) and pasture-fed lambs (PS). The results showed that the CO lambs had heavier carcasses (p< 0.001), a higher dressing percentage (p< 0.001), and higher intramuscular fat (p< 0.01) than the PS lambs. It was determined that the longissimus thoracis muscle of the CO lambs had a lower ultimate pH and higher L * and water-holding capacity than the PS lambs. In this study, intramuscular fat (longissimus thoracis, semimembranosus, triceps brachii), subcutaneous and tail fat samples were used to evaluate the effect of feeding system on fatty acid composition. The polyunsaturated fatty acid to saturated fatty acid ratio (PUFA / SFA) of intramuscular fat was found to be significantly higher in the CO group than in the PS lambs, while similar subcutaneous and tail fat results were found in both groups. Moreover, the PS lambs had a lower n6 / n3 ratio and higher percentage of omega-3 than the CO lambs in all tissues studied (p< 0.05). Overall, the CO lambs have heavier and fattier carcasses with better meat quality traits than the PS lambs. However, the effects of feeding system have varying results based on the fatty acid composition of different types of fat deposits.

The aims were to identify the body weight of the several age groups in Norduz lambs and its correlations between these traits were to determine the best non-linear growth curve models for the growth performance of the Norduz sheep breed. A total of 91 male and female of Norduz lambs were evaluated under extensive system conditions. The least square means for weights at birth and at 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195 and 210 days of age periods were 4.51±0.56, 9.28±0. 25, 11.14±0.29, 14.99±0.37, 18.21±0.43, 22.54±0.54, 22.33±0.25, 23.59±0.54, 25.58±0.55, 28.07±0.58, 29.45±0.60, 29.98±0.84, 32.44±0.61, 32.03±0.59 and 31.45±0.57 kg, respectively. There were differences in favor of lambs of four-year old dams at 15 days of age and also lambs born single at 90 days of age for the body weight. The effect of weight of dam at birth, 30, 45, 60 days of age was significant (P< 0.05-P<0.01) and the birth weight in lambs importantly effected the weights at 15, 30, and 45 days of age.All correlations between the body weights of several age periods were significant as statistical (P<0.01). As for the growth models, distinguished models were compared using the coefficient of determination and mean square error for both sexes. As a result, we concluded that von Bertalanffy model were the best model in comparison with the other models for biological growth curves in Norduz male and female lambs.

Generalized Procrustes Analysis (GPA) is a multivariate statistic method that is used at the evaluation of sensory analyses in the food industry. GPA provides benefit in terms of decreasing the difference between the panellists and bringing the data obtained from different panellists together. In this study, the aim was to determine the effect of a pre-slaughter fasting period on sensory characteristics of lambs fed with different rations using GPA. Semi-trained panellists formed from twenty-six persons were requested for evaluation of the meat samples such as tenderness, juiciness, flavour and overall liking rated on a scale of 1(extremely dislike) to 9 (extremely good). The first two factors obtained by GPA explained 66.74% of total variability. As a result of the analysis, it was determined that 12 h and 24 h fasting of lambs fed barley supplemented with alfalfa hay were less preferable when compared to lambs fed alfalfa hay only. In addition, lambs in both groups with 48 h fasting were preferred less by the panellists. In conclusion, GPA analysis provides useful data concerning the sensitivity of each panellist in a sensory panel test.

-The objective of this study was to determine the sexual parameters in young bucks with different sexual activity and the effect of experience (age) on sexual parameters in bucks. Fifteen young, sexually inexperienced (SI) and five adult, sexually experienced (SE) Saanen × Hair goat crossbred bucks were used in this study. Bucks were individually exposed to three estrus does for 15-min periods during four sexual performance tests, which were carried out every other day to determine some sexual behavior traits such as flehmen response, reaction time, and ejaculation efficiency. Sexually inexperienced young bucks were evaluated based on their sexual activity (active (AC) vs inactive (IA)) and presence of horn. It was found that AC bucks had significantly higher serum testosterone concentrations (31.5 vs 21.5 ng/mL) and weight loss (114.2 vs 51.2 g/day) than IA bucks. In addition, weight loss was significantly correlated with ejaculation efficiency in young bucks. On the other hand, horned bucks tended to have higher ejaculation efficiency with significantly longer reaction time than polled bucks. For experience (age) classes, SE bucks had higher testosterone concentration (76.0 vs 31.5 ng/mL) and weight loss (16.7 vs 8.6%) than SI active young bucks. However, the effect of experience on other sexual performance traits was found to be limited. Overall, these results indicate that testosterone concentration may affect sexual performance of young bucks in the mating season. Age-related sexual experience is not a determining factor for sexual performance in bucks. However, sexual performance data alone may not reflect reproductive outcomes without semen data.

Bu çalışma, derin sinir ağlarında en iyi sınıflandırma modelini bulmak amacıyla gerçekleştirilmiştir. Bu amaçla, optimizasyon yöntemi (Sgd, Adagrad, Rmsprop, Adam ve Nadam), aktivasyon fonksiyonu (Tanh ve ReLU) ve nöron sayılarının kombinasyonları kullanılarak 20 farklı model oluşturulmuştur. Oluşturulan model kombinasyonlarının performansları karşılaştırılarak, sınıflandırma için en iyi model belirlenmiştir. Sonuçlara göre; modellerin performanslarının parametrelere bağlı olarak değişkenlik gösterdiği, en başarılı modelin gizli katmanında 64 nöron bulunduğu, aktivasyon fonksiyonunun ReLU olduğu ve optimizasyon yöntemi olarak da Rmsprop kullanıldığı belirlenmiştir (%92 doğruluk). Bununla beraber, en düşük başarı oranıyla sınıflandırma yapan modelin 32 nöronlu, ReLU aktivasyon fonksiyonlu ve Sgd optimizasyon yöntemli model olduğu belirlenmiştir (% 70 doğruluk). Ayrıca tüm sonuçlar göz önüne alındığında; Rmsprop, Adam ve Nadam optimizasyon yöntemlerinin diğer iki yönteme göre, ReLU aktivasyon fonksiyonunun ise Tanh'a göre daha başarılı olduğu belirlenmiştir. Sonuç olarak derin öğrenme çalışmalarında model oluşturulurken; optimizasyon algoritmalarının, aktivasyon fonksiyonlarının ve nöron sayılarının farklı seçeneklerine göre model performanslarını denemek mümkündür. Ayrıca oluşturulan modelde, optimizasyon yöntemlerinin farklı parametrelerinin kombinasyonlarıyla çalışıldığında, veri setine daha uygun mimari elde edilmektedir.