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At first, linear multiple regression was fitted for the estimation of open days on Holstein cows using 52 parturition records. Independent variables were year (X<SUB>1</SUB>) and month of parturition (X<SUB>2</SUB>), parity (X<SUB>3</SUB>), body weight at conception (X<SUB>4</SUB>), milk production for the first 30 days (X<SUB>5</SUB>), body weight loss from pre-partum to 30th day post-partum (X<SUB>6</SUB>) and a derived variable (X<SUB>7</SUB>=X<SUB>5</SUB>•X<SUB>6</SUB>/1000). The multiple correlation coefficient by the equation was low.<BR>Then, curvilinear multiple regression was fitted taking quadratic and cubic terms of independent variables (X<SUB>1</SUB>, X<SUB>2</SUB>, X<SUB>5</SUB>, X<SUB>6</SUB>, and these derivatives) into account. This time, the regression equation explained over one third of the variation in open days (adjusted R<SUP>2</SUP>=0.362). In that equation, the quadratic and cubic effects of year and month of parturition were significant. Milk production (X<SUB>5</SUB>), body weight loss (X<SUB>6</SUB>) and derived variables from these two had a rather complicated effect on open days. The estimated open days by the regression for all possible combinations in value of X<SUB>5</SUB> and X<SUB>6</SUB> showed bowl-shaped surface. When X<SUB>5</SUB> and X<SUB>6</SUB> took values 550 and 115kg, minimum estimate of open days was obtained as the bottom of the bowl.
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