Evaluation of models for predicting the preweaning body weight in Holstein calves
سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 129
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_KLST-9-1_006
تاریخ نمایه سازی: 14 دی 1400
چکیده مقاله:
This study compared six non-linear equations [Exponential growth (۴ parameters), Exponential growth (Stirling), Polynomial (Cubic), Quadratic, Brody, and Sinusoidal] for prediction of pre-weaning body weights at different ages in Holstein calves. Thirty-two calves (۱۶ males and ۱۶ females) were randomly divided into two treatment groups and fed with starter diets containing either corn or barley as the grain source. Starter feeding began on the third day of life, and high quality alfalfa hay and fresh cow milk were fed according to the farm schedule. The calves were weighed at birth and weekly thereafter until weaning. In this manner, ten weight records, including the birth and weaning weights, constituted the data set. The results of experiment revealed the fact that all functions mentioned earlier showed good fitness to predict weight gain in relation to age in all groups of calves. However, based on the goodness of the fit of various criteria and the statistical performance, the polynomial (cubic) function was considerably superior to other functions for predicting the calf live weight. The flexible growth functions (more parameters) very often give a closer fit to data points and a smaller residual sum of square (RSS) value than the simpler functions such as the Brody functions.
کلیدواژه ها:
نویسندگان
Ali Moharrery
Department of animal science, faculty of agriculture, Shahrekord University, Shahrekord, Iran.
Hassan Rahmani
Department of Animal Science, Agricultural College, Shahrekord University, Shahrekord, Iran
Mohammad Javad Zamiri
Department of Animal Science, Agricultural College, Shiraz University, Shiraz, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :