Dergiler / Livestock Studies / 2020 / Cilt: 60 - Sayı: 2

Use of Multiple Regression Modeling for the Evaluation of Lactation Characteristics of Awassi Sheep

Sayfa
46–53
Yayın Tarihi
2021-01-06
DOI
—
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In an analysis of the HO, R2 and r parameters together, the fourth-order Legendre polynomial (LEG4) model was found to best predict the lactation curves of the Awassi sheep in the present study.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This study was conducted to identify the best model characterizing the lactation curves of Awassi sheep, and to calculate the estimated lactation milk yield (ELMY) per sheep based on the model parameters.
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Temel Bulgular & Veri:The study also investigated the factors affecting the observed lactation milk yield (OLMY) and ELMY, as well as the identified model parameters.
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Sonuç & Katkı:In an analysis of the HO, R2 and r parameters together, the fourth-order Legendre polynomial (LEG4) model was found to best predict the lactation curves of the Awassi sheep in the present study.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Awassi sheep · lactation curve · LEG4

Abstract

This study was conducted to identify the best model characterizing the lactation curves of Awassi sheep, and to calculate the estimated lactation milk yield (ELMY) per sheep based on the model parameters. The study also investigated the factors affecting the observed lactation milk yield (OLMY) and ELMY, as well as the identified model parameters. OLMY was 111.47±3.504 kg, with a lactation period of 133.70±1.714. In an analysis of the HO, R2 and r parameters together, the fourth-order Legendre polynomial (LEG4) model was found to best predict the lactation curves of the Awassi sheep in the present study.

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Bu Makaleye Atıf Yap

GÜNGÖR, İ., ATASOY, F. (2021). Use of Multiple Regression Modeling for the Evaluation of Lactation Characteristics of Awassi Sheep. Livestock Studies, Cilt: 60 - Sayı: 2, 46–53. https://ajindex.com/articles/228301

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Kaynakça (14)

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