ascotraceR: An R Package Resource to Simulate the Spatiotemporal Spread of Ascochyta Blight in a Chickpea Field Over a Growing Season

ascotraceR: An R Package Resource to Simulate the Spatiotemporal Spread of Ascochyta Blight in a Chickpea Field Over a Growing Season

Chickpea is the second most widely grown legume crop globally, and is known for its high fiber, protein, and vitamin content (Wallace et al. 2016). Ascochyta blight, caused by Ascochyta rabiei (syn. Phoma rabiei), is one of the most devastating diseases of chickpea, and severe infection can cause up to 100% yield loss (Nene and Reddy 1987; Pande et al. 2005). Management of Ascochyta blight in chickpea is challenging, in part due to the significant spatial and temporal variations in disease severity among growing regions because of variable weather conditions. As Ascochyta blight development depends on weather conditions (e.g., rainfall and temperature), and significant variations in weather exist among different chickpea-growing regions, management decisions need to be customized to be location specific. A weather-driven spatiotemporal model is required to predict spatial disease risk based on location-specific weather conditions at a paddock scale. Ascochyta blight risk can then be made available to different stakeholders for making customized decisions. This study is the first to develop a spatiotemporal model, ascotraceR, as an R package that simulates the pathogen-related processes of conidial production, dispersal, deposition on chickpea, infection, and host-related processes of growth, in terms of the development of growing points (terminal and lateral shoot apices, branches, inflorescence, and flowers). The package provides a single function to simulate Ascochyta blight spread on a daily time-step and convenient functions have been provided to calculate a paddock-level summary of the model output, including area under the disease progress curve (AUDPC).

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