Farklı Orijinli Holştaynların Döl ve Süt Verimi Özellikleri 1.Döl Verimi Özellikleri

Alkoyak, Kürşat; Çetin, Orhan

doi:10.15312/eurasianjvetsci.2018.176

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“…In this study, when we subtract the gestational age from the average gestational age (FPA), which was calculated as 23 months for the Holstein breed, the gestational dates for the first of the animals can be determined as an average of 14 months. These values are in agreement with the averages reported by the mean for the same breed (16.5, 18.3 months, and 16.8 months, 14.9, respectively (Alkoyak, 2016;Asan, 2021;Çetin and Alkoyak, 2018;Eyduran et al, 2008;Omar, 2022).The found service period obtained in this study was found to be 123 days and this value was 127 days in the study conducted by (Gürses and Bayraktar, 2012). Gürses and Bayraktar (2012) in TİGEM Ceylanpınar, Dalaman, Koçaş and Tahirova Agricultural Enterprises, on the same breed, while it was 127 days in Aydın province In the study conducted by the company Gürses (2019), ( Gürses, 2019) it is shorter as 144 days; In the study conducted by Sarar and Tapkı (2017) (Sarar and Tapkı, 2017) in Koçaş Agricultural Enterprise, 106 days; In a study conducted by Arı (2019) in a private enterprise in Aydın province, 109 days, (Arı, 2019, Kopuzlu et al, 2008.…”

Section: Discussionsupporting

confidence: 92%

Creating a Lactation Model for 305-Day Milk Yield with Different Resampling Techniques (Bagging Mars) in Mars Modeling

Çanga Boğa

2024

Karadeniz Fen Bilimleri Dergisi

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The main purpose of this research is to obtain a prediction model for milk yield by using Multivariate Adaptive Regression Splines (MARS) and Bagging MARS algorithms as a non-parametric regression technique. For this purpose, the effects on milk yield of 305 days were investigated by using lactation parameters in dairy cattle. In the study, 9337 lactation milk yield records belonging to 37 animals belonging to the 2022-2023 period were used and the data set was created by randomly ordering the animals. Data on milk yield results were analyzed with MARS and Bagging MARS algorithms. For dairy cattle; it was modeled with explanatory variables such as lactation month (month), service period (SP), last 7 days average milk yield (L7DMMY), animal's first birth age (FP), animal's age (Age), number of lactations (LN).Correlation coefficient (r), coefficient of determination (R2), Adjusted R2, Root of Square Mean Error (RMSE), standard deviation ratio (SD ratio), mean absolute percent error (MAPE), mean absolute for MARS algorithm estimating total average milk yield deviation (MAD) and Akaike Information Criteria (AIC) values are 0.9986, 0.997, 0.977, 0.142, 0.052, 0.2389, 0.086 and -88, respectively. Similar statistics for the Bagging MARS algorithm are 0.754, 0.556, 0.453, 1.8, 0.666, 3.96, 1.47, and 115, respectively. It has been observed that MARS and Bagging MARS algorithms provide correct results according to the goodness of fit statistics. In this study, it was revealed that MARS algorithm gave better results in milk yield modeling of 305-day lactation.

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Section: Discussionsupporting

confidence: 92%

Creating a Lactation Model for 305-Day Milk Yield with Different Resampling Techniques (Bagging Mars) in Mars Modeling

Çanga Boğa

2024

Karadeniz Fen Bilimleri Dergisi

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Farklı Orijinli Holştaynların Döl ve Süt Verimi Özellikleri 1.Döl Verimi Özellikleri

Cited by 1 publication

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Creating a Lactation Model for 305-Day Milk Yield with Different Resampling Techniques (Bagging Mars) in Mars Modeling

Creating a Lactation Model for 305-Day Milk Yield with Different Resampling Techniques (Bagging Mars) in Mars Modeling

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