Suitability of Early Blight Forecasting Systems for Detecting First Symptoms in Potato Crops of NW Spain

TY - JOUR

T1 - Suitability of Early Blight Forecasting Systems for Detecting First Symptoms in Potato Crops of NW Spain

AU - Meno, Laura Fariñas

AU - Abuley, Isaac Kwesi

AU - Escuredo, Olga

AU - Carmen, Seijo-Coello Maria

PY - 2022/7/4

Y1 - 2022/7/4

N2 - In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later.

AB - In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later.

KW - Alternaria spp.

KW - Growing Degree Days

KW - Solanum tuberosum

KW - disease forecasting

KW - physiological age

UR - http://www.scopus.com/inward/record.url?scp=85133703937&partnerID=8YFLogxK

U2 - 10.3390/agronomy12071611

DO - 10.3390/agronomy12071611

M3 - Journal article

SN - 2073-4395

VL - 12

JO - Agronomy

JF - Agronomy

IS - 7

M1 - 1611

ER -