Lameness is a serious disease that affects the health and welfare of dairy cattle whilst also causing yield and economic losses. The primary goal of this study is to determine if lameness can be detected early on in herd management using the Random Forest (RF) algorithm and the surface temperatures of the cows' hoof soles, as well as the digital colour parameters generated by processing these thermal camera images. Ages, hoof sole temperatures, and digital colour characteristics of 40 Simmental cattle were used as independent variables in this study, while lameness was evaluated by scoring and employed as a dependent variable after being updated as a binary variable. The parameters ntree= 100 and mtry= 3 were used to develop the RF algorithm for predicting lameness in animals. As a result, the RF algorithm correctly classified 19 of 22 healthy animals and incorrectly classified 3, while it correctly classified 15 of 18 unhealthy animals and incorrectly classified 3. The classification success of the RF algorithm was 85%, sensitivity, specificity and area under the ROC curve (AUC) were 0.864, 0.833, and 0.848±0.059, respectively, and it was successful in detecting lameness. Also, AUC, which is one of the RF algorithm's classification performances, was found to be statistically significant (P<0.05). As a direct consequence it can be stated that the RF algorithm is a suitable classifier in terms of the use of animal hoof sole temperatures and digital colour parameters obtained through image processing in the detection of lameness in herd management.

In this study, different ratios (A-0%, B-25%, C-50%, D-75%) of kefir were used in the ice cream mix in order to obtain functional ice cream enriched with probiotic bacteria. There was no difference between the chemical and physical properties of the samples (P0.05). Kefir containing samples showed probiotic properties during 90-day storage when the probiotic bacterial counts were considered. In terms of texture and flavor properties, sample D had the lowest scores, while B and C had similar scores compared to sample A in sensory evaluation. As a result, B and C were identified as probiotic products with acceptable properties during 90-day storage.

In order to give detailed information about the characteristics of scientific studies related to the power of the test, a bibliometric analysis of studies in which the power of the tests used in statistical data analysis was determined with the aid of Monte Carlo simulation techniques was carried out. The Web of Science (WoS) database's 1309 scientific studies in which the power of the test was determined by using Monte Carlo simulation techniques served as the study's material of data. The analysis includes the number of studies by year, average citation count by year, the number of articles published in scientific journals, countries of responsible authors, and the most relevant words in the studies. It was observed that Communications in Statistics-Simulation and Computation and Journal of Statistical Computation and Simulation are the journals with the highest number of published articles. The United States of America (USA) takes the lead when considering the countries of corresponding authors, while Türkiye is in 8th place. The most used keywords in the ten-year time period of scientific studies were respectively “power”, “test”, “skewness”, “model” and “inference”. As a result, it can be concluded that test power studies can be obtained safely using the Monte Carlo simulation technique.