Applying crop modelling tools to identify drought adaptation options for rainfed rice in Senegal (CropModAdapt)

Proyecto: Investigación

Detalles del proyecto

Descripción

In Senegal, there is a huge unexploited land available for expansion of rainfed rice as only 20% of the area potentially cultivated has been exploited (Villar et al, 2019). Eighty per cent of the rice consumed in Senegal is imported, thus there is potentially a large market for an increase production of this cereal (Mendez Del Villar and Dia, 2019). Creating irrigated paddy areas is a costly investment and maintenance is rarely well-managed, opening opportunities to develop rainfed upland rice. In Senegal, the cultivation of upland rice in the Casamance region seems to be an opportunity to ensure the increasing demand for rice. Rice is a major strategic commodity in Senegal government's options, it accounts for 34% of national cereal consumption. Recently, the government created incentives to increase upland rice yield as it might have a huge impact on smallholders that depend on rice production and do not have resources to convert to irrigated systems (Projet d¿Appui à la Production Durable du riz pluvial (PRIP) maer.gouv.sn)). However, several constraints such as inadequate water availability, poor soil, suboptimal crop management and lack of adapted germplasm limits the adoption of upland rice (Saito et al 2018). The lack of sufficient knowledge on management practices and varieties available for increasing rainfed rice productivity and resilience to climate change constrains upland rice adoption in Senegal. Recent crop model simulations studies suggest that rainfed rice yields in Senegal will fall by 50% in 2100, due to climate change (Gérardeaux et al 2021), hence adaptation options need to be designed to maintain (or even increase) its production. Rainfed upland rice is grown in rainfed naturally well drained soils without surface water accumulation, usually without phreatic water supply and not bounded. One factor affecting rainfed rice production is the frequency and duration of droughts. In this context, breeding for new plant traits and adapting management practices to specific environments could address frequent drought problems in upland rice and contribute to mitigate yield loss and maintain yield stability under a changing climate. To identify the best genetic material, plant traits and management practices, traditional breeding and agronomic field trials is often time and resource intensive. Thus, crop simulation models can be used as a tool to synthetize cropping information, determine breeding objectives and suggest climate adaptation strategies. Even though, there are many rice crop models available, they have different methods for accounting drought stress impact (Li et al. 2015), and they should be adapted to simulate rainfed upland rice. Crop models, integrate growth and development of plants and take into account soil properties including soil water holding capacity and fertility, helping characterize Genotype-byEnvironment interactions for drought and high temperature stress (see e.g., Heinemann et al., 2015; Ramirez-Villegas et al., 2018; van Oort et al., 2015). Crop models can help map areas according to their drought risk (i.e., drought-induced yield reductions and their likelihood, Adam et al., forthcoming), and also devise adaptation strategies such as varieties and cropping calendars (e.g., Heinemann et al., 2020). In the past, our crop modelling studies helped to identify the plant traits for upland rice breeding and established clear targets for rainfed rice crop management in Brazil (RamirezVillegas et al 2018; Heinemann et al., 2021). Further, we have a strong collaboration with the DSSAT modelling team (Adam et al. 2018, 2020) and DSSAT model was already calibrated for upland rice in Senegal (Gerardeaux et al. 2021). Finally, our team developed a more detailed crop model (Samara, Uttam et al. 2016, Akinseye et al 2017) for rice and sorghum, which was already used to design sorghum ideotypes best adapted to different drought stress patterns in the drylands of West Africa (Adam et al (2020). In collaboration with local partners in Senegal (AfricaRice, ISRA, and Sodagri) we identified key regions and data available for crop modelling studies for upland rice in Senegal. Using annual average data for precipitation and temperature for the 38 sites three potential environments for upland rice were identified: a dry environment with 648 mm/year precipitation, a wet ¿ cool environment and a wet-hot environment both with 1000 mm/year. A clear question arising from the present analysis is whether the classification of trial sites presented here reflects the yield response of upland rice varieties. Such analysis can be conducted through a deeper exploration of the trial data, or through crop simulation models, or both. Building on this work and the team experience, this PhD will develop a modelling framework and explore drought risk management options and breeding targets that could be performed to estimate the potential of the upland rice region in Senegal.
EstadoActivo
Fecha de inicio/Fecha fin01/01/2401/01/26

Financiación de proyectos

  • Internacional
  • CENTRE DE COOPÉRATION INTERNATIONAL EN R