Forecasting Late Blight in Potato Crops of Southern Idaho Using Logistic Regression Analysis

Abstract

Previously published late blight forecasts which predict the threat of disease based on the presence or absence of favorable weather have not been effective in semi-arid potato-producing areas of the Pacific Northwest (Idaho, Oregon, and Washington). Research was conducted to identify weather variables useful for forecasting late blight in southern Idaho. The objectives of this research were to (i) determine if regional weather variables could be related to the occurrence of late blight in southern Idaho, (ii) determine if disease severity (scale of 0 to 4) could be predicted using variables found to be correlated with the annual occurrence of late blight, and (iii) validate the efficacy of this model in predicting disease incidence in regions of the Columbia Basin. Weather data were collected from five locations over a 9-year period (1995 to 2003). A binary logistic regression model (0 = no disease and 1 = disease) indicated that the number of hours with favorable conditions (10°C ≤ temperature ≤ 27°C, relative humidity ≥ 80%) in April and May (HF80m) was a significant disease predictor. Logistic regression analysis using an ordinal disease scale (0 = no disease and 4 = severe disease) indicated amount of precipitation (APj) and favorable hours (HF80j) with extended periods from April to June as significant disease predictors. The binary model predicted disease occurrence more accurately, with 67.5% accuracy (27/40 years correctly predicted), 75% sensitivity (12/16 late-blight years predicted), and 62.5% specificity (15/24 non-late-blight years predicted) using a leave-1-year-out error estimate. The binary model was validated with data (1995 to 2003) from the semi-arid Columbia Basin regions, predicting disease with 80.8% accuracy (21/26 years predicted), 84% sensitivity (21/25 outbreak years predicted), and 0% specificity (0/1 non-outbreak years predicted).

Metalaxyl-M-Resistant Pythium Species in Potato Production Areas of the Pacific Northwest of the U.S.A.

“…Metalaxyl applications to manage P. infestans were reduced in 1995 in the Columbia Basin due to the development of MR strains of P. infestans in 1993 (Deahl et al 1993;Hamm et al 1994). In contrast to the high use of metalaxyl in the Columbia Basin (Johnson et al 1997), metalaxyl applications were not as common in the early 1990s in Idaho since widespread late blight outbreaks were infrequent (Henderson et al 2007). However, the widespread and common use of metalaxyl to manage potato late blight undoubtedly exposed the Pythium soil population in the Columbia Basin to metalaxyl which may account for the higher incidence of MR Pythium found there, compared to soil populations in Idaho.…”

Ordinal regression models for predicting deoxynivalenol in winter wheat

“…These are also the two main reasons why ordinal scales are encountered for assessing disease severity in plant disease prediction (Isebaert et al, 2009). Other application domains include ecology (Guisan & Harrell, 2000;Minetos & Polyzos, 2010), bioinformatics and agriculture in general (Henderson et al, 2007).…”

Accuracy of Rain Forecasts for Use in Scheduling Late Blight Management Tactics in the Columbia Basin of Washington and Oregon

“…blight is weather dependent (2,7,10,11,15,17,19,20,26,32), and the goal of this study was to evaluate rain forecasts for accuracy, which could be used to schedule fungicide applications for managing potato late blight. The disease control strategy desired is to forecast and pre vent future infection periods versus forecasting disease symptoms after infection periods (24).…”