Yield Loss Assessment from Leaf Rust in Bread Wheat (Triticum aestivum L.) Across Different Seasons and Locations

Sayed, O. A.; Elsayed, Mona I.E.; El-Gammal, Y. H.; Khalifa, Neamat A.M.; Yahya, A. I. A.; Harb, Alshimaa H.

doi:10.21608/jpp.2025.416066.1502

Yield Loss Assessment from Leaf Rust in Bread Wheat (Triticum aestivum L.) Across Different Seasons and Locations

Document Type : Original Article

Authors

¹ Wheat Diseases Research Department, Plant Pathology Research Institute, A.R.C., Giza, Egypt.

² Central Laboratory for Design & Statistical Analysis Research, A.R.C., Giza. Egypt.

³ Microorganisms Identification Unit, Plant Pathology Research Institute, A. R. C., Giza, Egypt.

⁴ Wheat Dept., wheat Research Institute, Agricultural Research Center, Giza, 12619, Egypt.

⁵ Agronomy Department, Faculty of Agriculture, Cairo University, Giza, Egypt.

10.21608/jpp.2025.416066.1502

Abstract

In the context of climate change and evolving pathogen populations, wheat leaf rust (Puccinia triticina) remains one of the most damaging cereal diseases worldwide, threatening food security through significant yield and quality losses. This study evaluated nine bread wheat genotypes over two consecutive seasons (202/2024 and 2024/2025) at two locations to examine the relationship between disease severity and yield loss. Disease development was measured using final rust severity (FRS%), area under disease progress curve (AUDPC), and relative AUDPC ( rAUDPC). Differences in 1000-kernel weight, kernels per spike, and grain yield per plot were evaluated between protected and infectedplants.Thehighest disease levels were detected by Sids1, Gemmeiza7, and Gemmeiza11(FRS up to 41.67%, AUDPC > 500, rAUDPC > 6, and yield reductions in some traits exceeded 35%. In contrast, Shandweel2 (FRS 10–18.33%, rAUDPC < 25%), Nubaria2 (FRS 12.5–21.67%, rAUDPC 18–30%), and Misr3 (FRS 18.33–28.33%, rAUDPC 25–35%) consistently exhibited low disease parameters and minimal yield losses, indicating strong partial resistance. Significant correlations between AUDPC, rAUDPC, and yield losses confirm their value as reliable indicators for resistance screening. The integration of multi-parameter disease assessment with yield loss analysis offers a robust and updated basis for identifying high-yielding, rust-resistant genotypes and guiding global breeding and integrated disease management strategies .

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