Association between agronomic traits and molecular markers with take-all disease severity in bread wheat Triticum aestivum
Publish place: Journal of Crop Protection، Vol: 11، Issue: 1
Publish Year: 1400
نوع سند: مقاله ژورنالی
زبان: English
View: 111
This Paper With 21 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JCP-11-1_003
تاریخ نمایه سازی: 13 آبان 1402
Abstract:
Identifying resistant genotypes is necessary to control wheat take-all disease Gaeumannomyces graminis var. tritici. In this study, ۳۰ bread wheat genotypes were evaluated under greenhouse and field conditions. The genotypes were evaluated with fifteen molecular markers (SSR and specific primers for translocation wheat-rye). The genotypes were divided into four groups based on disease severity (the greenhouse) and agronomic traits (the field). Chi-square results showed the interactions for these groupings. The correlation between disease severity and agronomic traits indicated that plant resistance is strongly dependent on plant yield. Based on cluster analysis for molecular data (based on simple matching similarity coefficient and UPGMA method), genotypes were separated into resistant and susceptible ones. The correlation between disease severity and amplified loci showed that disease resistance is interactive with xbarc۲۳۲, xbarc۱۲۴, and gpw۹۵۰۰۱ markers. Resistance to take-all disease is probably associated with the interaction of several genes. These results add significant information to our knowledge of the chromosomal location of genes for the take-all disease.
Keywords:
Authors
Roohallah Saberi-Riseh
Department of Plant Protection, Faculty of Agriculture, Vali -e- Asr University of Rafsanjan, Rafsanjan, Iran.
Hossein Dashti
Department of Genetics and Plant Production, Faculty of Agriculture, Vali -e- Asr University of Rafsanjan, Rafsanjan, Iran.
Mozhgan Gholizadeh-Vazvani
Department of Plant Protection, Faculty of Agriculture, Vali -e- Asr University of Rafsanjan, Rafsanjan, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :