نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه علوم دامی، دانشکدگان کشاورزی و منابع طبیعی دانشگاه تهران، کرج، البرز، ایران
2 گروه علوم دامی، دانشکدگان کشاورزی و منابع طبیعی دانشگاه تهران،کرج، البرز، ایران.
3 مدیر تولید دامپروری هلدینگ کشاورزی و دامپروری فردوس پارس، تهران، ایران
4 بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی آذربایجان شرقی، سازمان تحقیقات و آموزش و ترویج کشاورزی، تبریز،
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The purpose of the current study was to investigate the relationship between fecal starch concentration and other fecal components in early Holstein lactating Cows. In current study, correlation coefficients between fecal starch concentration and other fecal components was studied and then univariate and multivariate regression approach used to select the best fecal starch fitting model using other fecal compositions in early Holstein lactating Cows. The present study conducted to estimate fecal starch excretion using other fecal components on 76 industrial dairies. The model fitting was performed based on univariate and multivariate regression. The results of univariate regression and correlation between fecal parameters showed an inverse relationship between fecal pH, fecal protein and fecal neutral detergent fiber with fecal starch excretion. Furthermore, based on univariate regression, it was shown that fecal pH had the highest coefficient of determination in estimating fecal starch (R² = 0.48). It was also demonstrated that the best estimation of fecal starch excretion is possible with high accuracy and precision using multiple regression with three factors: fecal pH, fecal protein percentage, and neutral detergent fiber percentage. Finally, the results of the present study showed that there is a significant correlation between excreted starch through feces and other compounds of feces, and also, it is possible to predict the concentration of excreted starch through feces using multivariate regression models with high accuracy.
کلیدواژهها [English]