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ThesisItem Open Access Statistical study on pre-harvest forecasting of apple yield(2014) PROMILA, DEVI; CHAUDHARY, V.K.The present study entitled “Statistical study on pre-harvest forecasting of apple yield” was undertaken in the Department of Basic Science, Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan 173230 (H.P.) during 2012-2014. The primary data were collected on the S yield and biometrical characters of apple trees of five blocks (Kullu, Nagar, Banjar, Anni and Nirmand) of Kullu district of H.P. Maximum yield was observed in Nagar block & minimum in Banjar block during the study. Yield was found to be significantly and positively correlated with age, height, girth, diameter, canopy (N-S), canopy (E-W) and number of branches biometrical characters of apple tree. In Kullu block, cubic model was best fitted for tree age to predict apple yield. S- curve model was best fitted for height, girth, diameter and volume to predict apple yield. Quadratic model best fitted for canopy (N-S), canopy (E-W) and number of branches to predict apple yield. In Nagar block, power model was best fitted for tree age to predict apple yield. S model was best fitted for height, girth, diameter and volume to predict apple yield. Exponential model was best fitted for canopy (N-S) and canopy (E-W) to predict apple yield. Growth model was best fitted for number of branches to predict apple yield. In Banjar block, cubic model fitted best for tree age to predict apple yield. Logarithmic model fitted best for girth, diameter and volume to predict apple yield. Quadratic model fitted best for height, canopy (E-W) and number of branches to predict apple yield. Linear model fitted best for canopy (N-S) to predict apple yield. In Anni block, power model was best fitted for girth, diameter, canopy (N-S) and volume to predict apple yield. Quadratic model was best fitted for height and number of branches to predict apple yield. Cubic model was best fitted for tree age to predict apple yield. S model was best fitted for canopy (E-W) to predict apple yield. In Nirmand block, cubic model was best fitted for tree age, height and diameter to predict apple yield. Linear model fitted best for girth, canopy (N-S) and canopy (E-W) to predict apple yield. Quadratic model fitted best for volume and number of branches to predict apple yield. Whereas, forecasting model based on multiple regression analysis for Kullu district is Y=1.1272+0.9638X1+2.6485X2+3.5237X3+0.2138X4+0.4467X5+0.8395X6+1.3490X7+1.0280X8 found to be fitted well based on R 2 , adjusted R 2 , SSE and RMSE in the data of biometrical characters of apple tree