ที่มา:วิทยาสารเกษตรศาสตร์ สาขา วิทยาศาสตร์

หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : Fitness of Lactation Curve Functions to Daily and Monthly Test-Day Milk Data in an Ethiopian Multi-Breed Dairy Cattle Population)

ผู้เขียน:Gebregziabher Gebreyohannes, ดร.ศกร คุณวุฒิฤทธิรณ, รองศาสตราจารย์, Mauricio A. Elzo, ดร.ธนาทิพย์ สุวรรณโสภี, รองศาสตราจารย์

สื่อสิ่งพิมพ์:pdf

Abstract

The objectives of this study were to identify the lactation curve function that had the best fi t to daily and monthly test-day milk data and to evaluate the factors affecting parameters of the best fi t lactation curve function for an Ethiopian dairy cattle population. An incomplete gamma (IG), a modifi ed incomplete gamma (MIG; b = 1) and an inverse polynomial (IP) function were compared using 6,717 lactation milk records of 2,064 cows from the Bako, Holetta and Debre Zeit Research Centers, Ethiopia. Breed groups were Horro (H), Boran (B), B ? Friesian, H ? Friesian, B ? Simmental, H ? Simmental, B ? Jersey and H ? Jersey. The MIG and IG were log-transformed to linear form before fi tting. The functions were compared based on the least squares means (LSM) of R2 (LSM R2) and adjusted R2 values and on the accuracy of lactation milk yield prediction. The statistical model included herd-year-season of calving, parity, data type, breed group, lactation curve function, and the interactions of data type ? function and breed ? data type ? function as fi xed effects, and the residual as a random effect. The MIG, IP and IG functions ranked from the best to the worst fi t based on LSM R2 and adjusted R2. The LSM R2 and adjusted R2 were signifi cantly (P < 0.001) different among all classes of fi xed effects considered in the model. The LSM R2 and adjusted R2 for the MIG function were 0.90 and 0.89, respectively. All functions fi tted to monthly test-day better than to daily milk data. The MIG function had the best fi t (P < 0.001) to daily milk data, but both the MIG and IP functions had a similar fi t to monthly test-day milk data based on the LSM of adjusted R2. The ln(a) and c from the MIG function with daily and monthly test-day milk data, and the A0, A1 and A2 from the IP function with monthly test-day data were different among breed groups, parities and herd-year-season classes (at least P < 0.05). The MIG function predicted the lactation milk yield from the monthly test-day milk with the lowest prediction error (P < 0.001) compared to the IP and IG functions. Thus, the MIG function could be recommended to model lactation milk data from monthly test-day milk in the studied dairy cattle population.

Article Info

Agriculture and Natural Resources -- formerly Kasetsart Journal (Natural Science), Volume 047, Issue 1, Jan 13 - Feb 13, Page 60 - 73 |  PDF |  Page

ที่มา:วิทยาสารเกษตรศาสตร์ สาขา วิทยาศาสตร์

หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : Comparison of Five Mathematical Functions for Prediction of Monthly Yield in Thai Multibreed Dairy Cattle Population)

ผู้เขียน:Warangkana Kitpipit, ดร.พรรณวดี โสพรรณรัตน์, รองศาสตราจารย์, Sayan Buaban, ดร.ศรเทพ ธัมวาสร, ศาสตราจารย์

สื่อสิ่งพิมพ์:pdf

Abstract

Monthly yields of 32,583 records from 3,523 first lactation cows, collected by the bureau of Biotechnology in Livestock Production, Department of Livestock Development (DLD) were used in this study. These dataset were obtained between 1993 and 2003 in 777 farms throughout the country. The objective was to evaluate five mathematical models for describing the phenotypic lactation curve of dairy cattle in Thai multibreed population. In the previous analysis, monthly milk yields were adjusted by the variation of herd-year-season of calving, Holstein Friesian (HF) fractions, calving age and first test-day after calving. The adjusted monthly milk yields were used to fit five mathematical functions. Five functions, i.e. Ali and Schaeffer polynomial (A&S), Schaeffer and Dekkers (S&D) logarithm, Wilmink exponential (WIL), Wood incomplete gamma (WD) and Legendre polynomials (LEG) functions were used in this study. For the whole data analysis, all functions showed few differences in comparison criteria. A&S fitted the actual yield better than other functions according to the adjusted coefficient of determination (R2 adj=0.39) and mean square error (MSE=6.84). For individual lactation analysis, A&S provided the smaller value of residual errors including means of absolute error (RES), means of mean square error (MMSE) and means of square prediction error (MSPE) than other functions. Ranking all functions from the best to the worst were A&S, WD, S&D, WIL and LEG, respectively. The results indicated that A&S function could be fitted well for the whole and individual data. Therefore, A&S could be applied to describe the phenotypic lactation curve in this dairy population.

Article Info

Agriculture and Natural Resources -- formerly Kasetsart Journal (Natural Science), Volume 042, Issue 2, Apr 08 - Jun 08, Page 246 - 255 |  PDF |  Page