Modeling of crop loss caused by Puccinia striiformis f. sp. tritici in three common wheat cultivars in southern Iran | ||
| Journal of Crop Protection | ||
| Article 8, Volume 5, Issue 3, 2016, Pages 389-395 PDF (373.74 K) | ||
| DOI: 10.48311/jcp.2016.1282 | ||
| Authors | ||
| Mohammad Reza Eslahi* 1; Shideh Mojerlou2 | ||
| 1Plant Protection Research Department, Khuzestan Agricultural and Natural Resources Research Center, AREEO, Ahvaz, Iran. | ||
| 2Department of Horticulture and Plant Protection, College of Agriculture, Shahrood University of Technology, Shahrood, Iran. | ||
| Abstract | ||
| Stripe rust cause by Pucciniastriiformis f. sp. tritici is one of the most important diseases of wheat and can cause severe yield loss in many wheat growing regions of the world including Iran. To determine yield loss caused by this disease and evaluate the effect of some chemical components on reduction of yield loss in south of Iran, field experiments were carried out in split plot design with three replications at Ahvaz research station during 2014-2015. Three cultivars; Chamran, Virinak and Boolani, were used and artificial inoculation was performed using an isolate which was collected from south of Iran and designated as Yr27 race variant. Meanwhile the effects of propiconazole and some herbicides on yield loss reduction were studied. In this study, grain yield and area under disease progress curve (AUDPC) were measured. Statistical analysis showed that the level of the yield reduction was significantly different in the three studied cultivars and different treatments. Propiconazole could control the disease significantly. The highest yield loss was observed for cv. Boolani in both with (9%) and without (54%) fungicide treatments. Combined application of propiconazole and herbicides significantly reduced yield loss compared with using them separately. The results of crop loss modeling using integral and multiple point regression models showed that the integral model (L = 0.017AUDPC-17.831) could explain more than 69% of AUDPC variations in relation to crop loss in all cultivars. In multiple point models, disease severity at various dates was considered as independent variable and crop loss percentage as dependent variable. This model with the highest coefficient of determination had the best fitness for crop loss estimation. The results showed that the disease severity at GS39, GS45, GS50 and GS60 stages (Zadok's scale) were more important for crop loss prediction than those in other phenological stages. | ||
| Keywords | ||
| AUDPC; Crop loss; Modeling; Stripe rust; Wheat | ||
| References | ||
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