Surur Khorramdel; Parviz Rezvani Moghaddam; Abdollah Mollafilabi; Sahar Valizadeh
Abstract
Weedy flora of agroecosystems is composed of many species that have evolved in response to cropping system practices by occupying the niches left available in agroecosystems. In order to study weed species diversity and community structure in the saffron fields of Khorasan province, a survey trial was ...
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Weedy flora of agroecosystems is composed of many species that have evolved in response to cropping system practices by occupying the niches left available in agroecosystems. In order to study weed species diversity and community structure in the saffron fields of Khorasan province, a survey trial was carried out in seven counties (including Mashhad, Neyshabur, Birjandn, Ghaen, Gonabad, Torbat-e Jam and Torbat-e Heydari) during 2014 and 2015 from vegetative growth, dormant to flowering stages of saffron randomly dropped 1×1 m2 quadrates in 50 fields based on a systematic method as W pattern. The counties were clustered by the hierarchical complete linkage method based on Euclidean. Biodiversity indices such as stability coefficient, Simpson, Shannon–Wiener, Margalef and Menhinick were computed. The results indicated that the dominant weeds in saffron fields belong to 19 families and 50 species. Poaceae, Brassicaceae, Asteraceae and Fabaceae were dominant families with 11, 9, 8 and 6 species, respectively. The majority of weed species were dicotyledonous, C3, noxious and annual plants. The highest stability coefficients in the stages of growth of saffron were calculated in Alhagi camelorum, Avena fatua and Achillea millefolium to be 30.81, 24.11 and 12.14, respectively. All weed species except for Alhagi camelorum (sustainable species) and Avena fatua (temporary species) were recognized as causal species. The maximum diversity indices for weed species were recorded at the vegetative phase of saffron. Correlation coefficient between weed density and yield loss of saffron was computed as R2=0.98. Based on diversity indices for weed species, different counties were clustered in three groups at 75% similarity level.
