Evaluating empirical models to predict yield loss of winter wheat (Triticum aestivum L.) cultivars in interference with feral rye (Secale cereale)

Saadatian, Bijan; Kafi, Mohamad; Soleymani, Fatemeh; Ahmadvand, Goudarz

Evaluating empirical models to predict yield loss of winter wheat (Triticum aestivum L.) cultivars in interference with feral rye (Secale cereale)

Document Type : Research Paper

Authors

¹ Ph. D. Student, Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad

² Prof., Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad

³ Ph. D. Student, Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan

⁴ Assoc. Prof., Dept. of Agronomy and Plant Breeding, Faculty of Agriculture, Bu-Ali Sina University, Hamedan

Abstract

To evaluate the empirical models of competition in predicting yield loss of winter wheat, a factorial trial based on a randomized complete block design with three replications was carried out. Experimental factors were four wheat cultivars (Sayson, Alvand, Chamran and Sepahan) and feral rye densities at five levels (0, 20, 40, 60 and 80 plants m^־²) at exemplary form of Dargaz, in 2010-2011 crop year. Feral rye caused a biological and grain yield reduction of studied wheat cultivars. Wheat cultivars did not have similar reaction for yield loss of biological and grain in interference with feral rye. Maximum and minimum of initial slop of biological and grain yield loss (I parameter) obtained in Chamran (6.19 and 13.12 percent) and Sepahan (1.24 and 2.62 percent) cultivars, respectively. Competition effect on biological yield of wheat cultivars was less than grain yield. Obtained relative damage coefficients (q parameter) of one and two-parameter models based on relative leaf area and relative dry matter were indicative of high competitive ability of feral rye than wheat cultivars. Models based on relative leaf area and relative dry matter of feral rye had more efficiency in predict of wheat grain yield loss in compared with yield loss-density model. Minimum regression root mean square error of observed and predicted quantities resulted of two-parameter models based on leaf area and relative dry matter of weed. Regarding to simplicity of dry matter measuring than leaf area, the two-parameter model of weed relative dry matter introduced a favorite model for predicting of wheat yield loss.

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