Evaluation of the ‘Irish Rules’: The Potato Late Blight Forecasting Model and Its Operational Use in the Republic of Ireland

Abstract

Potato late blight caused by Phytophthora infestans is one of the most important plant diseases known, requiring high pesticide inputs to prevent disease occurrence. The disease development is highly dependent on weather conditions, and as such, several forecasting schemes have been developed worldwide which seek to reduce the inputs required to control the disease. The Irish Rules, developed in the 1950s and calibrated to accommodate the meteorological network, the characteristics of potato production and the P. infestans population at the time, is still operationally utilized by the national meteorological agency, Met Éireann. However, numerous changes in the composition and dynamics of the pathosystem and the risks of production/economic consequences associated with potato late blight outbreaks have occurred since the inception of the Irish Rules model. Additionally, model and decision thresholds appear to have been selected ad hoc and without a clear criteria. We developed a systematic methodology to evaluate the model using the empirical receiver operating curve (ROC) analysis and the response surface methodology for the interpretation of the results. The methodology, written in the R language, is provided as an open, accessible and reproducible platform to facilitate the ongoing seasonal re-evaluation of the Irish Rules and corresponding decision thresholds. Following this initial analysis, based on the available data, we recommend the reduction of the thresholds for relative humidity and an initial period duration from 90% and 12 h to 88% and 10 h, respectively. Contrary to recent reports, we found that the risk of blight epidemics remains low at temperatures below 12 °C. With the availability of more comprehensive outbreak data and with greater insight into the founder population to confirm our findings as robust, the temperature threshold in the model could potentially be increased from 10 °C to 12 °C, providing more opportunities for reductions of pesticide usage. We propose a dynamic operational decision threshold between four and 11 effective blight hours (EBH) set according to frequency of the disease outbreaks in the region of interest. Although the risk estimation according to the new model calibrations is higher, estimated chemical inputs, on average, are lower than the usual grower’s practice. Importantly, the research outlined here provides a robust and reproducible methodological approach to evaluate a semi-empirical plant disease forecasting model.

Research 339: High-resolution climate projections for Ireland. A multi-model ensemble approach

“…The incidences of Lyme borreliosis (Lyme disease), a vector-borne illness caused by the bacterium Borrelia and spread by ticks, increase with high relative humidity; ticks require a minimum 80% humidity to avoid drying out during the early stages of life (Cullen, 2010) and air temperatures greater than 6°C during host questing (Süss et al, 2008). Potato crop failures in Ireland can result when high relative humidity and temperature combine to provide the warm, wet conditions in which the Phytophthora infestans fungi (potato blight) thrive (Cucak et al, 2019). Changes in relative humidity will have an impact on the built and archaeological heritage of Ireland, affecting deterioration mechanisms such as salt weathering, mould growth and corrosion (Daly, 2019).…”

Potatoes in Ireland: Sixty years of potato research and development, market evolution and perspectives on future challenges

“…Whilst these undoubtedly reduce the frequency and quantities of fungicides, they underestimate late blight infection events as reported by Hansen (2017) with an increasing emphasis of the employment of varietal resistance. This scenario, which is an important support tool for Integrated Pest Management (IPM), demonstrated that a substantial reduction in fungicide usage can be achieved without compromising disease control and yield or adversely impacting local P. infestans populations in terms of their aggressiveness (Cucak et al, 2019;Cucak et al, 2021).…”

“…and Cucak et al (2019). BothLeonard et al (2001) andCucak et al (2021) highlight how this results in inadequate protection of the potato canopy and reductions in yield Dowley & Burke (2004).…”

“…have demonstrated that potential does exist for the role of such forecasting or decision support systems, although the methods the authors used were based on infield weather stations which were problematic in Irish potato production given the transient nature of production. More recently,Cucak et al (2019) have revised the rules originally developed byBourke (1955), increasing their accuracy and predictability. It is envisioned this will be used in the future by Met Eireann to provide local disease risk assessments in a graphical map format as shown in Figure4.…”

Application of a modified mathematical model “consumer – resource” to justify the periods of treatment of potato late blight with fungicides

“…There are models that additionally use biological information: a potato variety, a popular oomycete strain in the region and its characteristics [6,7]. Currently, tools are gaining popularity -decision support systems (DSS), which allow recommending fungicidal treatments [8][9][10][11]. Most of these systems assess the favorableness of weather conditions for the development of the disease and, depending on the level of danger, make recommendations for treatment.…”