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1 May 2003 Yield loss in spring-sown cereals related to the weed flora in the spring
Ullalena Boström, Per Milberg, Håkan Fogelfors
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Yield loss was related to weed species composition and density in permanent plots, recorded several weeks after sowing of spring cereals in southern Sweden. A range of agronomic situations was included by experimentally varying fertilizer application and sowing density in 33 field trials in different locations during 3 yr. Direct gradient analysis, using yield loss as the sole predictor, arranged weed community composition in the spring along a gradient of small to large yield losses. Yield loss could be explained, to some extent, by the species composition in the spring. Species associated with situations with large losses were hempnettle and wild radish, whereas several benign species were identified based on their association with lack of yield loss. The results suggest that possible predictive tools using spring species composition would be improved if they also considered soil type and seed rate. Some agronomically important weed species were not identified as associated with yield loss when assessed in terms of their abundance in the spring, which may limit the possibilities of basing management decisions on weed plant density in the spring.

Nomenclature: Hempnettle, Galeopsis spp.; wild radish, Raphanus raphanistrum L. RAPRA; nightflowering catchfly, Silene noctiflora L. MELNO; scarlet pimpernel, Anagallis arvensis L. ANGAR; spurge species; Euphorbia spp.; Polygonum spp.; prostrate knotweed, Polygonum aviculare L. POLAV; wild buckwheat, Polygonum convolvulus L. POLCO; common lambsquarters, Chenopodium album L. CHEAL; field violet, Viola arvensis Murr. VIOAR; spring barley, Hordeum distichum L.; spring wheat, Triticum aestivum L.

Ullalena Boström, Per Milberg, and Håkan Fogelfors "Yield loss in spring-sown cereals related to the weed flora in the spring," Weed Science 51(3), 418-424, (1 May 2003).[0418:YLISCR]2.0.CO;2
Received: 17 December 2001; Accepted: 17 December 2002; Published: 1 May 2003
multivariate analysis
redundancy analysis
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