Climatic risk for potato late blight in the Andes region of Venezuela

Abstract

Potato is an important crop for Venezuelan agriculture. However, its production is highly affected by late blight (Phytophtora infestans), since weather is commonly favorable for this disease. The aim of this study was to determine the sowing dates of low climatic risk for potato late blight in the Andes region of Venezuela, with an agrometeorological disease model and geographical information system (GIS) tools. The disease model used in this study was developed by Hyre (1954) which requires daily rainfall and temperature data which were obtained from 106 weather stations, located at the States of Mérida, Táchira, and Trujillo, for a period of 31 years. Hyre's model was applied for all stations obtainig the following variables: number of disease favorable days (DFD); number of periods with ten consecutive favorable days, named disease occurrence (O); and number of sprays required for disease control (S). These variables were used to calculate the Maximum Risk Index (MRI) and the Probable Risk Index (PRI). The interpolation of these indexes was used to generate maps of climatic risk for each sowing date. MRI and PRI maps showed that the highest climatic risk for potato late blight occurrence was during the rainy season, from May to July, decreasing during dry and mid seasons. However, high disease risk variability was observed for all seasons. The maps generated by coupling an agrometeorological disease model and GIS also show that in great part of potato areas of Andes region the number of sprays could be reduced, but more investigations about that must be carried out.

Impact of drought stress on simultaneously occurring pathogen infection in field-grown chickpea

“…In another instance, Garcia et al . (2008) developed an agro-meteorological disease model to predict the sowing dates with the least risk for the potato late blight disease infection 55 . We, in this direction, attempted a case study to predict chickpea seed yield under drought stress based on the parameter similar to the field experiment using the DSSAT (Decision Support System for Agrotechnology Transfer) simulation-modeling tool.…”

Impact of Combined Abiotic and Biotic Stresses on Plant Growth and Avenues for Crop Improvement by Exploiting Physio-morphological Traits

“…Similarly, a number of plant disease prediction models have also been developed and evaluated. For example, Garcia et al (2008) developed and applied a geographical information system (GIS) based agro-meteorological disease model to determine the sowing dates with low climatic risk for the infection of potato late blight disease in the Andes region of Venezuela ( Garcia et al, 2008 ).…”

A system to map the risk of infection by <i>Puccinia kuehnii</i> in Brazil

“…This study allowed for the quantification of disease severity, both spatially between different state regions and temporally during the study period, adequately differentiating the areas studied. Garcia, Sentelhas, Tapia, and Sparovek (2008) evaluated the climatic risk of potato late blight in the Andes (Venezuela) and developed maps showing that the highest risk of proliferation of the disease occurred during the rainy season (from May to July) and decreased during the dry and transition seasons. Moraes, Peixoto, Jesus Junior, and Cecílio (2011) developed space-time mapping of areas of climatic favorability to coffee rust infection in Brazil using historical averages of temperature and relative humidity data from 1961 to 1990 provided by the Climate Research Unit (CRU).…”

“…There are particular features on each map created by Lopes et al (2008), Hamada et al (2008), Garcia et al (2008), Moraes et al (2011), andSentelhas et al (2016) in terms of the methodology, meteorological data, climatic data and mathematical models used, mainly due to differences in favorability among the maps for different diseases and crops, as different environmental and genetic factors influence the pathogen-host relationship and determine the complexity of each different pathosystem. The development and dissemination of these maps on a monthly or weekly basis could contribute toward monitoring and epidemiological studies of orange rust occurrence in sugarcane, as well as to the evaluation of the necessity for disease control, including methods such as avoiding planting susceptible varieties in zones favorable to the disease and promoting the use of chemical control in locations and during time periods of high favorability.…”