Sugar beet yield loss predicted by relative weed cover, weed biomass and weed density
Roland Gerhards, Kostyantyn Bezhin, Hans-Joachim Santelhttps://doi.org/10.17221/57/2016-PPSCitation:Gerhards R., Bezhin K., Santel H. (2017): Sugar beet yield loss predicted by relative weed cover, weed biomass and weed density. Plant Protect. Sci., 53: 118-125.
Sugar beet yield loss was predicted from early observations of weed density, relative weed cover, and weed biomass using non-linear regression models. Six field experiments were conducted in Germany and in the Russian Federation in 2012, 2013 and 2014. Average weed densities varied from 20 to 131 with typical weed species compositions for sugar beet fields at both locations. Sugar beet yielded higher in Germany and relative yield losses were lower than in Russia. Data of weed density, relative weed cover, weed biomass and relative yield loss fitted well to the non-linear regression models. Competitive weed species such as Chenopodium album and Amaranthus retroflexus caused more than 80% yield loss. Relative weed cover regression models provided more accurate predictions of sugar beet yield losses than weed biomass and weed density.Keywords:
crop–weed interaction; weed competition; yield loss functionReferences:
Ali Asif, Streibig Jens C., Andreasen Christian (2013): Yield loss prediction models based on early estimation of weed pressure. Crop Protection, 53, 125-131 https://doi.org/10.1016/j.cropro.2013.06.010BERTI A., ZANIN G. (1994): Density equivalent: a method for forecasting yield loss caused by mixed weed populations. Weed Research, 34, 327-332 https://doi.org/10.1111/j.1365-3180.1994.tb02001.xCOUSENS ROGER (1985): A simple model relating yield loss to weed density. Annals of Applied Biology, 107, 239-252 https://doi.org/10.1111/j.1744-7348.1985.tb01567.xCousens R., Brain P., O’Donovan J.T., O’Sullivan A. (1987): The use of biologically realistic equations to describe the effects of weed density and relative time of emergence on crop yield. Weed Science, 35: 720–725.Gummert A., Ladewig E., Märländer B. (2012): Guidelines for integrated pest management in sugar beet cultivation – weed control. Journal für Kulturpflanzen, 64: 105–111.HESS M., BARRALIS G., BLEIHOLDER H., BUHR L., EGGERS TH., HACK H., STAUSS R. (1997): Use of the extended BBCH scale - general for the descriptions of the growth stages of mono- and dicotyledonous weed species. Weed Research, 37, 433-441 https://doi.org/10.1046/j.1365-3180.1997.d01-70.xHydrometcentre of Russia (2015): Weather in the cities of Russia. Available at http://meteoinfo.ru/climate/klimatgorod/1705-1246618396 (accessed July 24, 2015).ICUMSA (2013): ICUMSA Methods Book 2013. Berlin, Verlag Dr. Albert Bartens KG.Jalali Amir Houshang, Salehi Foroud (2013): Sugar beet yield as affected by seed priming and weed control. Archives of Agronomy and Soil Science, 59, 281-288 https://doi.org/10.1080/03650340.2011.608158Jursík M., Holec J., Soukup J., Venclová V. (2008): Competitive relationships between sugar beet and weeds in dependence on time of weed control. Plant Soil and Environment, 54: 108–116.Kapustin A. (2012): Analysis of field weed seed contamination. [Dissertation.] Tomsk, Tomsk State Polytechnical University. (in Russian)KROPFF M. J., SPITTERS C. J. T. (1991): A simple model of crop loss by weed competition from early observations on relative leaf area of the weeds. Weed Research, 31, 97-105 https://doi.org/10.1111/j.1365-3180.1991.tb01748.xKunz C., Schröllkamp C., Koch H.-J., Eßer C., Schulze Lammers P., Gerhards R. (2015): Potentials of post-emergent mechanical weed control in sugar beet to reduce herbicide inputs. Landtechnik – Agricultural Engineering, 70: 67–81.LOTZ L. A. P., CHRISTENSEN S., CLOUTIER D., QUINTANILLA C. FERNANDEZ, LEGERE A., LEMIEUX C., LUTMAN P. J. W., IGLESIAS A. PARDO, SALONEN J., SATTIN M., STIGLIANI L., TEI F. (1996): Prediction of the competitive effects of weeds on crop yields based on the relative leaf area of weeds. Weed Research, 36, 93-101 https://doi.org/10.1111/j.1365-3180.1996.tb01805.xMarlander B., Hoffmann C., Koch H.-J., Ladewig E., Merkes R., Petersen J., Stockfisch N. (2003): Environmental Situation and Yield Performance of the Sugar Beet Crop in Germany: Heading for Sustainable Development. Journal of Agronomy and Crop Science, 189, 201-226 https://doi.org/10.1046/j.1439-037X.2003.00035.xMay M.J., Wilson R.G. (2006): Weeds and weed control. In: Draycott P. (ed,): Sugar Beet. Oxford, Blackwell Publishing Ltd: 359–386.Milberg P, Hallgren E (2004): Yield loss due to weeds in cereals and its large-scale variability in Sweden. Field Crops Research, 86, 199-209 https://doi.org/10.1016/j.fcr.2003.08.006Nichterlein Henrike, Matzk Anja, Kordas Leszek, Kraus Josef, Stibbe Carsten (2013): Yield of glyphosate-resistant sugar beets and efficiency of weed management systems with glyphosate and conventional herbicides under German and Polish crop production. Transgenic Research, 22, 725-736 https://doi.org/10.1007/s11248-012-9678-zPetersen J. (2008): A review on weed control in sugar beet. In: Inderjit (ed.): Weed Biology and Management. Dordrecht, Kluwer Academic Publishers: 467–483.R Core Team (2015): R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Available at www.R-project.org (accessed July 24, 2015).Vislobokova L., Ivanova O. (2013): Optimal sugar beet fertilizing guidelines in Tambov region. Sugar Beet, 4: 7–14. (in Russian)