TY - GEN
T1 - Modelling chemical thinning in peach
AU - Szafran, E.
AU - Kizner, Z.
AU - David, I.
AU - Zilkah, S.
PY - 1999
Y1 - 1999
N2 - A statistical model was developed to make chemical thinning possible in the peach growing industry. The new concept behind this model is that, in addition to the obvious factors - active compound, concentration, volume and timing of the thinning application -an accurate prediction of the tree response should consider the plant's physiological status, and the environmental conditions following the application. The method of model building is presented as a factor analysis on three different sets of parameters - chemical thinning application, environmental conditions and physiological status of the tree -followed by a multivariate linear regression. The number of fruitlets remaining on the trees two weeks after the application was used as the predicted variable, while the predictors were the factors resulting from the factor analysis. Unnecessary variables were taken out of the factor analysis by a repetitive method. The influence of their removal was evaluated by checking the linear regression: prediction coefficient R2, Marlow's total squared error Cp, and regression significance p. The correlations between the predictions of the model and observed results were highly significant. They varied between r=0.66 and r=0.85 when the model equation was applied on same-year observations, and between r=0.42 and r=0.81 when it was applied to those from another year or to data from the whole study.
AB - A statistical model was developed to make chemical thinning possible in the peach growing industry. The new concept behind this model is that, in addition to the obvious factors - active compound, concentration, volume and timing of the thinning application -an accurate prediction of the tree response should consider the plant's physiological status, and the environmental conditions following the application. The method of model building is presented as a factor analysis on three different sets of parameters - chemical thinning application, environmental conditions and physiological status of the tree -followed by a multivariate linear regression. The number of fruitlets remaining on the trees two weeks after the application was used as the predicted variable, while the predictors were the factors resulting from the factor analysis. Unnecessary variables were taken out of the factor analysis by a repetitive method. The influence of their removal was evaluated by checking the linear regression: prediction coefficient R2, Marlow's total squared error Cp, and regression significance p. The correlations between the predictions of the model and observed results were highly significant. They varied between r=0.66 and r=0.85 when the model equation was applied on same-year observations, and between r=0.42 and r=0.81 when it was applied to those from another year or to data from the whole study.
KW - Factor analysis
KW - Multivariate linear regression
KW - Prunus
UR - http://www.scopus.com/inward/record.url?scp=84879570673&partnerID=8YFLogxK
U2 - 10.17660/ActaHortic.1999.499.12
DO - 10.17660/ActaHortic.1999.499.12
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AN - SCOPUS:84879570673
SN - 9789066057623
T3 - Acta Horticulturae
SP - 123
EP - 128
BT - V International Symposium on Computer Modelling in Fruit Research and Orchard Management
PB - International Society for Horticultural Science
ER -