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Integrating Morphological, Pathogenic, and Molecular Approaches to Characterize Fusarium Root Rot Pathogens of Common
Taghrid A Kamel1, Manal M Yasser2, Naglaa A Taha1
1Plant Pathology Research Institute, Agricultural Research Center, Giza 12619, Egypt.
Abstract:
Fusarium root rot (FRR) is a major disease affecting common bean (Phaseolus vulgaris L.) production worldwide. In Egypt, FRR has recently become more prevalent, threatening crop yields. Fusarium species are considered the primary causal agents of this disease. To identify the pathogens associated with FRR and evaluate host resistance, Fusarium isolates were obtained from diseased common bean plants collected in different Egyptian governorates. Morphological identification, pathogenicity assays on six cultivars (Alpha, Samantha, Giza 6, Giza 12, Cambo, and Nebraska), and molecular identification using TEF-1α gene sequencing were conducted. Thirteen isolates exhibited pathogenicity, and five isolates (FP33, FP24, FP26, FP21, and FP11) were classified as highly aggressive. Isolate FP33 caused the highest disease severity, reaching 90% on Giza 6 and 80% on Cambo, while Nebraska showed the highest resistance (30% disease severity). Similarly, FP24 led to 85% and 75% severity on Giza 6 and Cambo, respectively. Nebraska and Giza 12 showed the greatest resistance, while Giza 6 and Cambo were most susceptible. Molecular analysis identified FP33 and FP24 as F. equiseti, FP26 and FP21 as F. oxysporum, and FP11 as F. solani. The study demonstrates the genetic and pathogenic variability among Fusarium isolates causing root rot in common bean. Nebraska and Giza 12 were identified as the most resistant cultivars, while Giza 6 and Cambo were highly susceptible. These findings highlight the importance of selecting resistant cultivars and implementing integrated disease management strategies to mitigate FRR in Egypt. The results also contribute valuable data for breeding programs aimed at developing durable resistance. The integration of morphological, molecular, and pathogenicity data provides a framework for future epidemiological studies and sustainable disease management strategies.
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