Scopus
🔓 Açık Erişim YÖKSİS DOI Eşleşti
SJR Q4
Prediction of fattening final live weight from some body measurements and fattening period in young bulls of crossbred and exotic breeds using MARS data mining algorithm
Pakistan Journal of Zoology · Şubat 2018
YÖKSİS Kayıtları
Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm
Pakistan Journal of Zoology · 2018 SCI-Expanded
Prof. Dr. İSMAİL KESKİN →
Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm
Pakistan Journal of Zoology · 2018 SCI-Expanded
Prof. Dr. İBRAHİM AYTEKİN →
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Fatty Acid Composition and ConjugatedLinoleic Acid Content in Various Carcass Partsof Kivircik Lambs
2016 ISSN: 0030-9923 SCI-Expanded
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Fatty Acid Composition and Conjugated Linoleic Acid Content in Various Carcass Parts of Kivircik Lambs
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Prediction of Fleece Weight from Wool Characteristics of Sheep Using Regression Tree Method Chaid Algorithm
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Prediction of Fleece Weight from Wool Characteristics of Sheep Using Regression Tree Method Chaid Algorithm
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Estimation of Cold Carcass Weight and Body Weight from Several Body Measurements in Sheep through Various Data Mining Algorithms
2017 ISSN: 0030-9923 SCI-Expanded
Prof. Dr. İSMAİL KESKİN →
Prediction of Fattening Final Live Weight from some Body Measurements and Fattening Period in Young Bulls of Crossbred and Exotic Breeds using MARS Data Mining Algorithm
2018 ISSN: 0030-9923 SCI-Expanded Q3
Prof. Dr. İBRAHİM AYTEKİN →
Description of Factors Affecting Wool Fineness in Karacabey Merino Sheep using Chaid and Mars Algorithms
2021 ISSN: 0030-9923 SCI-Expanded Q4
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Description of Factors Affecting Wool Fineness in Karacabey Merino Sheep using Chaid and Mars Algorithms
2021 ISSN: 0030-9923 SCI-Expanded Q4
Prof. Dr. SAİM BOZTEPE →
Identification of Chlamydophila abortus in Abomasum Content of Aborted Sheep and Goats by PCR
2021 ISSN: 0030-9923 SCI-Expanded Q4
Prof. Dr. ZAFER SAYIN →
Makale Bilgileri
ISSN00309923
Yayın TarihiŞubat 2018
Cilt / Sayfa50 · 189-195
Scopus ID2-s2.0-85041050365
Erişim🔓 Açık Erişim
Özet
The aim of this investigation was to develop a prediction equation for fattening final live body weight from several body measurements and fattening period of native, crossbred and exotic breeds. For this aim, a total of 103 young bulls were used. In the prediction of fattening final live weight as an output variable, several continuous predictors evaluated in the current study were: withers height (WH), back height (BH), front rump height (FRH), back rump height (BRH), body length (BL), back rump width (BRW), chest depth (CD) and chest circumference (CC). Also, the breed factor was considered as a nominal predictor and fattening period (FP) was accepted as an ordinal predictor. To obtain the prediction equation, the results of Multivariate Adaptive Regression Splines (MARS) data mining algorithm as a non-parametric regression technique was implemented. To measure predictive accuracy of MARS, model evaluation criteria such as coefficient of determination (R2), adjusted coefficient of determination (R2 ADJ), SDRATIO and Pearson coefficient (r) between actual and predicted values in fattening final live weight were calculated. To reveal the highest predictive ability in the MARS algorithm, numbers of terms and basis functions were set at 21 and 45 where order of interactions was three. Except for CD, other predictors were entered into MARS model. MARS showed very high predictive capability (R2=0.9717, R2 ADJ=0.9643, SDRATIO= 0.168 and r=0.986) for the data evaluated in the investigation. Also, GCV value of the MARS prediction equation was found as 409.83. In conclusion, it could be suggested that a very reliable prediction equation with the predictive accuracy of nearly 100 (%) was developed in practice by using MARS data mining algorithm, which a quite remarkable tool in the prediction of fattening final live weight with interaction effects of predictors and in description of breed standards, in the development of breeding strategies and especially in the detection of ideal fattening period for each breed under the condition.
Yazarlar (5)
1
Ibrahim Aytekin
2
Ecevit Eyduran
3
Koksal Karadas
4
Rifat Aksahan
5
İsmail Keskin
Anahtar Kelimeler
Beef cattle
Data mining
Fattening performance
Live weight prediction
MARS algorithm
Kurumlar
Bolvadin District Ministry of Food
Afyon Turkey
Iğdır Üniversitesi
Igdir Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Pakistan Journal of Zoology
Q4
SJR Skoru0,202
H-Index36
YayıncıUniversity of Punjab (new Campus)
ÜlkePakistan
Animal Science and Zoology (Q4)
Metrikler
44
Atıf
5
Yazar
5
Anahtar Kelime