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Prediction Models for Estimation of Pink Disease Development in Acacia Hybrid Plantation


     

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Pink disease (Corticium salmonicolor) of Acacia hybrid was noticed in 5 years old plantations of Hosanagar Division which were raised by Mysore Paper Mill , Bhadravati , Karnataka. An assessment of the disease severity was calculated using 0-3 scale in three plantations of Hosanagar Division. The observed Disease Severity Index (DSI) values were fitted to autoregression method for calculating the disease severity in relation to time. Thus the autoregression model is of the form Yt+1 = 0.761 Yt with autocorrelation coefficient R= 0.976. Similarly , the disease severity was predicted using logistic method and the model is of the form Yt =1001 l+e 5.59+0.16t with coefficient of determination r=0.945 and estimated DSI Y= 5.59+ 0.16x. Since the autocorrelation coefficient value in autoregression method is high (0.967) which is robust method and hence the logistic method is best suited for predicting the disease severity as coefficient of determination r=0.945.
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V. Maheswarappa

Parasurama Janagiri

S. T. Naik


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  • Prediction Models for Estimation of Pink Disease Development in Acacia Hybrid Plantation

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Abstract


Pink disease (Corticium salmonicolor) of Acacia hybrid was noticed in 5 years old plantations of Hosanagar Division which were raised by Mysore Paper Mill , Bhadravati , Karnataka. An assessment of the disease severity was calculated using 0-3 scale in three plantations of Hosanagar Division. The observed Disease Severity Index (DSI) values were fitted to autoregression method for calculating the disease severity in relation to time. Thus the autoregression model is of the form Yt+1 = 0.761 Yt with autocorrelation coefficient R= 0.976. Similarly , the disease severity was predicted using logistic method and the model is of the form Yt =1001 l+e 5.59+0.16t with coefficient of determination r=0.945 and estimated DSI Y= 5.59+ 0.16x. Since the autocorrelation coefficient value in autoregression method is high (0.967) which is robust method and hence the logistic method is best suited for predicting the disease severity as coefficient of determination r=0.945.