Estimating economic thresholds for site-specific weed control using manual weed counts and sensor technology: An example based on three winter wheat trials

Pest Management Science - Tập 70 Số 2 - Trang 200-211 - 2014
Martina Keller1, Christoph Gutjahr1, Jens Möhring2, Martin Weis1, Markus Sökefeld1, Roland Gerhards1
1Department of Weed Science; University of Hohenheim, Institute for Phytomedicine; Germany
2Department of Bioinformatics, University of Hohenheim, Institute of Crop Science, Germany

Tóm tắt

Từ khóa


Tài liệu tham khảo

Rajcan, 2001, Understanding maize-weed competition: Resource competition, light quality and the whole plant, Field Crops Research, 10.1016/S0378-4290(01)00159-9

Seitz, 2006, Herbizide fuer die Landwirtschaft: Chemische Unkrautbekämpfung, Chemie in unserer Zeit, 27, 112

Schwerdtle F Kemmer A Schulz H Gemeinschaftsversuche Baden-Württemberg 1969 Fachgruppe Pflanzenproduktion Stuttgart-Hohenheim 1969

Gerhards R Gemeinschaftsversuche Baden-Württemberg Berichte aus dem Fachgebiet Herbologie der Universität Hohenheim 2011

Giaquinta, 1992, An industry perspective on herbicide-tolerant crops, Weed Technol, 10.1017/S0890037X00035971

Gerhards, 2012, Using precision farming technology to quantify yield effects due to weed competition and herbicide application, Weed Res, 10.1111/j.1365-3180.2011.00893.x

Coble, 1992, The threshold concept and its application to weed science, Weed Technol, 10.1017/S0890037X00034552

Gerowitt, 1990, Weed economic thresholds in the F. R. Germany, Crop Protect, 10.1016/0261-2194(90)90001-N

Zanin, 1993, Estimation of economic thresholds for weed control in winter wheat, Weed Res, 10.1111/j.1365-3180.1993.tb01962.x

Garburg W Investigations to determine the economic thresholds and control thresholds for weeds in cereals Institut für Pflanzenpathologie und Pflanzenschutz der Georg-August-Universiät Göttingen

Beer E Determination of control thresholds and economic thresholds for monocotyledonous and dicotyledonous weeds in winter wheat and winter barley using data from governmental trials Institut für Pflanzenpathologie und Pflanzenschutz der Georg-August-Universiät Göttingen

Niemann, Schadschwellen bei der Unkrautbekämpfung, 257

Gerhards, 2010, Precision Crop Protection-the Challenge and Use of Heterogeneity, 1, 1

Auernhammer, 2001, Precision farming-The environmental challenge, Comput Electron Agric, 10.1016/S0168-1699(00)00153-8

Zhang, 2002, Precision agriculture-A worldwide overview, Comput Electron Agric, 10.1016/S0168-1699(02)00096-0

Adamchuk, 2011, Sensor fusion for precision agriculture, in, Sensor Fusion-Foundation and Applications

Ritter, 2008, An on-farm approach to quantify yield variation and to derive decision rules for site-specific weed management, Precision Agric, 10.1007/s11119-008-9061-5

Corwin, 2005, Apparent soil electrical conductivity measurements in agriculture, Comput Electron Agric, 46, 11, 10.1016/j.compag.2004.10.005

Delin, 2005, Management zones classified with respect to drought and waterlogging, Precision Agric, 10.1007/s11119-005-2325-4

Leithold, 2006, On farm research-A novel experimental design for precision farming, J Plant Dis Protect, XX, 157

Weis, 2008, Precision farming for weed management: Techniques, Gesunde Pflanzen, 10.1007/s10343-008-0195-1

Rumpf, 2012, Sequential support vector machine classification for small-grain weed species discrimination with special regard to Cirsium arvense and Galium aparine, Comput Electron Agric, 10.1016/j.compag.2011.10.018

Weis, 2012, Herbicides-Environmental Impact Studies and Management Approaches

Gutjahr, 2009, European Federation for Information Technology in Agriculture (EFITA), conference 2009, 557

Gutjahr, 2011, Precision Agriculture 2011, 203

Piepho, 2011, Statistical aspects of on-farm experimentation, Crop Pasture Sci, 10.1071/CP11175

Keller, 2011, Precision Agriculture 2011, 491

Piepho, 2004, A mixed modelling approach for randomized experiments with repeated measures, J Agron Crop Sci, 10.1111/j.1439-037X.2004.00097.x

Akaike, 1974, A new look at the statistical model identification, IEEE Transact Auto Contr AC-19, 10.1109/TAC.1974.1100705

R Development Core Team R: A Language and Environment for Statistical Computing Vienna Austria 2008

KTBL Faustzahlen für die Landwirtschaft Achilles W Döhler H Frisch J Fröba N Harder H Hüter J et al

Storkey, 2007, Mini-review managing arable weeds for biodiversity, Pest Manag Sci, 10.1002/ps.1375

Wilson, 1990, Predicting the growth and competitive effects of annual weeds in wheat, Weed Res, 10.1111/j.1365-3180.1990.tb01704.x

Weis, 2009, Book of Abstracts of the European Conference on Precision Agriculture (ECPA) 2009, 349

Eef, 2011, Automatic identification of crop and weed species with chlorophyll fluorescence induction curves, Precision Agric

Burgos-Artizzu, 2009, Improving weed pressure assessment using digital images from an experience-based reasoning approach, Comput Electron Agric, 10.1016/j.compag.2008.09.001

Burks, 2000, Classification of weed species using color texture features and discriminant analysis, Trans Am Soc Agric Engin, 43, 441, 10.13031/2013.2723

Gutjahr, 2012, Evaluation of two patch spraying systems in winter wheat and maize, Weed Res, 10.1111/j.1365-3180.2012.00943.x