Prediction of the competitive effects of weeds on crop yields based on relative leaf areas of weeds

Autor: Svend Christensen, D. Cloutier, A. Pardo Iglesias, A. Legere, P. J. W. Lutman, L. Stigliani, J. Salonen, Claudel Lemieux, Maurizio Sattin, C. Fernandez Quintanilla, L.A.P. Lotz, Francesco Tei
Rok vydání: 1996
Předmět:
Zdroj: Weed Research 36 (1996)
Scopus-Elsevier
Weed research (Online) 36 (1996): 93–101. doi:10.1111/j.1365-3180.1996.tb01805.x
info:cnr-pdr/source/autori:Lotz L.A.P., Christensen S., Cloutier D., Fernandez Quintanilla C., Légère A., Lemieux C., Lutman P.J.W., Pardo Iglesias A., Salonen J., Sattin M., Stigliani L., Tei F./titolo:Prediction of the competitive effects of weeds on crop yield based on the relative leaf area of weeds/doi:10.1111%2Fj.1365-3180.1996.tb01805.x/rivista:Weed research (Online)/anno:1996/pagina_da:93/pagina_a:101/intervallo_pagine:93–101/volume:36
ISSN: 0043-1737
DOI: 10.1111/j.1365-3180.1996.tb01805.x
Popis: Summary For implementation of simple yield loss models into threshold-based weed management systems, a thorough validation is needed over a great diversity of sites. Yield losses by competition wsth Sinapis alba L. (white mustard) as a model weed, were studied in 12 experiments in sugar beet (Beta vulgaris L.) and in 11 experiments in spring wheat (Triticum aestivum L.). Most data sets were heller described by a model based on the relative leaf area of the weed than by a hyperbolic model based on weed density. This leaf area model accounted for (part of) the effect of different emerging times of the S. alba whereas the density model did not. A parameter that allows the maximum yield loss to be smaller than 100% was mostly not needed to describe the effects of weed competition. The parameter that denotes the competitiveness of the weed species with respect to the crop decreased the later the relative leaf area of the mustard was determined. This decrease could be estimated from the differences in relative growth rate of the leaf area of crop and S. alba. However, the accuracy of this estimation was poor. The parameter value of the leaf area model varied considerably between sites and years. The results strongly suggest that the predictive ability of the leaf area model needs to be improved before it can be applied in weed management systems. Such improvement would require additional information about effects of abiotic factors on plant development and morphology and the definition of a time window for predictions with an acceptable level of error.
Databáze: OpenAIRE
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