Wheat Stem Rust Detection and Race Characterization in Tunisia

Author:

Abdedayem Wided12ORCID,Patpour Mehran3ORCID,Laribi Marwa2ORCID,Justesen Annemarie F.3,Kouki Hajer2,Fakhfakh Moez4,Hovmøller Mogens S.3,Yahyaoui Amor H.25,Hamza Sonia1,Ben M’Barek Sarrah26

Affiliation:

1. National Agronomic Institute of Tunisia (INAT), 43 Avenue Charles Nicolle, Tunis 1002, Tunisia

2. CRP Wheat Septoria Precision Phenotyping Platform, Tunis 1082, Tunisia

3. Department of Agroecology, Aarhus University, 4200 Slagelse, Denmark

4. Comptoir Multiservices Agricoles, 82, Avenue Louis Brailles, Tunis 1002, Tunisia

5. Borlaug Training Foundation, Colorado State University, Fort Collins, CO 80523-1170, USA

6. Laboratory of ‘Appui à la Durabilité des Systèmes de Production Agricole Dans la Région du Nord-Ouest’, Higher School of Agriculture of Kef (ESAK), Regional Field Crops Research Center of Beja (CRRGC) BP 350, Beja 9000, Tunisia

Abstract

Climate changes over the past 25 years have led to conducive conditions for invasive and transboundary fungal disease occurrence, including the re-emergence of wheat stem rust disease, caused by Puccinia graminis f.sp. tritici (Pgt) in East Africa, Europe, and the Mediterranean basin. Since 2018, sporadic infections have been observed in Tunisia. In this study, we investigated Pgt occurrence at major Tunisian wheat growing areas. Pgt monitoring, assessment, and sampling from planted trap nurseries at five different locations over two years (2021 and 2022) revealed the predominance of three races, namely TTRTF (Clade III-B), TKKTF (Clade IV-F), and TKTTF (Clade IV-B). Clade III-B was the most prevalent in 2021 as it was detected at all locations, while in 2022 Pgt was only reported at Beja and Jendouba, with the prevalence of Clade IV-B. The low levels of disease incidence during these two years and Pgt population diversity suggest that this fungus most likely originated from exotic incursions and that climate factors could have caused disease establishment in Tunisia. Further evaluation under the artificial disease pressure of Tunisian wheat varieties and weather-based modeling for early disease detection in the Mediterranean area could be helpful in monitoring and predicting wheat stem rust emergence and epidemics.

Funder

CGIAR Research Program on wheat (CRP-WHEAT) Precision phenotyping Septoria Platform

United States Agency for International Development (USAID) Bureau for Resilience and Food Security

Publisher

MDPI AG

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

Reference66 articles.

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