Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application

Gerhards R, Gutjahr C, Weis M, Keller M, Sökefeld M, Möhring J & Piepho HP (2011). Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application. Weed Research 52, 6–15. Summary Field experiments using precision farming technology and Geogr...

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Veröffentlicht in:Weed research 2012-02, Vol.52 (1), p.6-15
Hauptverfasser: GERHARDS, R, GUTJAHR, C, WEIS, M, KELLER, M, SÖKEFELD, M, MÖHRING, J, PIEPHO, H P
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container_end_page 15
container_issue 1
container_start_page 6
container_title Weed research
container_volume 52
creator GERHARDS, R
GUTJAHR, C
WEIS, M
KELLER, M
SÖKEFELD, M
MÖHRING, J
PIEPHO, H P
description Gerhards R, Gutjahr C, Weis M, Keller M, Sökefeld M, Möhring J & Piepho HP (2011). Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application. Weed Research 52, 6–15. Summary Field experiments using precision farming technology and Geographic Information Systems, following a so‐called Precision Experimental Design, were conducted in maize, winter barley and winter wheat and compared with two randomised plot experiments in maize to quantify yield effects attributed to weed competition and weed control. Fields were divided into cells, and weed densities for all weed species, soil conductivity and grain yield were measured in each cell. Untreated plots and herbicide treatments against grass weeds or broad‐leaved weeds were included in all three experiments. Chenopodium album, Polygonum spp. and Echinochloa crus‐galli were the dominating weed species in maize. Stellaria media, Veronica hederifolia, Matricaria chamomilla, Alopecurus myosuroides and Galium aparine were the most abundant weed species in the winter barley and winter wheat fields. All species were distributed heterogeneously within the fields with densities ranging from 0 to more than 200 plants m−2. In the Precision Experimental Design, it was found that grass‐weed competition and herbicide application had a significant effect on grain yield, using a linear mixed model with spatial correlation structure to determine the effects of groups of weed species, soil variability and herbicide application on grain yield separately. When a conventional plot experiment was set up in the same field, no statistically significant grain yield difference between the treatments was found. The results highlight the benefits of Precision Experimental Design for studying weed–crop competition. Data can be used to calculate yield loss functions for groups of weed species and to create a decision support system for site‐specific weed control.
doi_str_mv 10.1111/j.1365-3180.2011.00893.x
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Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application. Weed Research 52, 6–15. Summary Field experiments using precision farming technology and Geographic Information Systems, following a so‐called Precision Experimental Design, were conducted in maize, winter barley and winter wheat and compared with two randomised plot experiments in maize to quantify yield effects attributed to weed competition and weed control. Fields were divided into cells, and weed densities for all weed species, soil conductivity and grain yield were measured in each cell. Untreated plots and herbicide treatments against grass weeds or broad‐leaved weeds were included in all three experiments. Chenopodium album, Polygonum spp. and Echinochloa crus‐galli were the dominating weed species in maize. Stellaria media, Veronica hederifolia, Matricaria chamomilla, Alopecurus myosuroides and Galium aparine were the most abundant weed species in the winter barley and winter wheat fields. All species were distributed heterogeneously within the fields with densities ranging from 0 to more than 200 plants m−2. In the Precision Experimental Design, it was found that grass‐weed competition and herbicide application had a significant effect on grain yield, using a linear mixed model with spatial correlation structure to determine the effects of groups of weed species, soil variability and herbicide application on grain yield separately. When a conventional plot experiment was set up in the same field, no statistically significant grain yield difference between the treatments was found. The results highlight the benefits of Precision Experimental Design for studying weed–crop competition. 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Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application. Weed Research 52, 6–15. Summary Field experiments using precision farming technology and Geographic Information Systems, following a so‐called Precision Experimental Design, were conducted in maize, winter barley and winter wheat and compared with two randomised plot experiments in maize to quantify yield effects attributed to weed competition and weed control. Fields were divided into cells, and weed densities for all weed species, soil conductivity and grain yield were measured in each cell. Untreated plots and herbicide treatments against grass weeds or broad‐leaved weeds were included in all three experiments. Chenopodium album, Polygonum spp. and Echinochloa crus‐galli were the dominating weed species in maize. Stellaria media, Veronica hederifolia, Matricaria chamomilla, Alopecurus myosuroides and Galium aparine were the most abundant weed species in the winter barley and winter wheat fields. All species were distributed heterogeneously within the fields with densities ranging from 0 to more than 200 plants m−2. In the Precision Experimental Design, it was found that grass‐weed competition and herbicide application had a significant effect on grain yield, using a linear mixed model with spatial correlation structure to determine the effects of groups of weed species, soil variability and herbicide application on grain yield separately. When a conventional plot experiment was set up in the same field, no statistically significant grain yield difference between the treatments was found. The results highlight the benefits of Precision Experimental Design for studying weed–crop competition. Data can be used to calculate yield loss functions for groups of weed species and to create a decision support system for site‐specific weed control.</description><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>Chemical control</subject><subject>Chenopodium album</subject><subject>competition</subject><subject>crop-weed competition</subject><subject>Cropping systems. Cultivation. Soil tillage</subject><subject>Echinochloa crus-galli</subject><subject>economic weed thresholds</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Galium aparine</subject><subject>General agronomy. Plant production</subject><subject>Generalities. Cropping systems and patterns</subject><subject>Geographic Information System</subject><subject>Herbicides</subject><subject>Hordeum vulgare</subject><subject>Land use</subject><subject>Matricaria chamomilla</subject><subject>mixed linear models</subject><subject>Parasitic plants. Weeds</subject><subject>Phytopathology. Animal pests. Plant and forest protection</subject><subject>Polygonum</subject><subject>precision farming</subject><subject>Stellaria media</subject><subject>Technology</subject><subject>Triticum aestivum</subject><subject>weed control</subject><subject>weed distribution</subject><subject>Weeds</subject><subject>wheat</subject><subject>winter</subject><subject>Zea mays</subject><issn>0043-1737</issn><issn>1365-3180</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNqNkUFr3DAQhUVpodsk_0GX0pPdkWXJNvRSljQtDQ2EhkAuQpZHibZe25Fksv73lbthz9VlxMx7b9AnQiiDnKXzeZczLkXGWQ15AYzlAHXD88MbsjkN3pINQMkzVvHqPfkQwg4ApGyaDZnvghse6eTRuODGgVrt92snonkaxn58XGgc6fOsh-jsQheHfUfRWjQxUB2jd-0csVtFL5iqGfcTRhfXLD109Al964zrkOpp6p3R6-ScvLO6D3jxWs_I3bfL39vv2fXN1Y_t1-vMlKzgWdmKkmnb1YwVbd2BxbJqBWcA2KSnQtdqAaUUhqeOEcArUTRMsqYFW0nd8TPy6Zg7-fF5xhDV3gWDfa8HHOegmgKqRkrBkrI-Ko0fQ_Bo1eTdXvtFMVAraLVTK0-18lQraPUPtDok68fXJToY3Vuvh8Ty5C8EFyWv6qT7ctS9uB6X_85X97eX6ZLs2dHuQsTDya79HyXTvwp1_-tK_axLeNg2t6rifwG8S6Fp</recordid><startdate>201202</startdate><enddate>201202</enddate><creator>GERHARDS, R</creator><creator>GUTJAHR, C</creator><creator>WEIS, M</creator><creator>KELLER, M</creator><creator>SÖKEFELD, M</creator><creator>MÖHRING, J</creator><creator>PIEPHO, H P</creator><general>Blackwell Publishing Ltd</general><general>Wiley-Blackwell</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope></search><sort><creationdate>201202</creationdate><title>Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application</title><author>GERHARDS, R ; GUTJAHR, C ; WEIS, M ; KELLER, M ; SÖKEFELD, M ; MÖHRING, J ; PIEPHO, H P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4123-4b541afd8112b8d0fe47b53100e90110dba50465c300ec50375291619b0f76ad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Agronomy. Soil science and plant productions</topic><topic>Biological and medical sciences</topic><topic>Chemical control</topic><topic>Chenopodium album</topic><topic>competition</topic><topic>crop-weed competition</topic><topic>Cropping systems. Cultivation. Soil tillage</topic><topic>Echinochloa crus-galli</topic><topic>economic weed thresholds</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Galium aparine</topic><topic>General agronomy. Plant production</topic><topic>Generalities. Cropping systems and patterns</topic><topic>Geographic Information System</topic><topic>Herbicides</topic><topic>Hordeum vulgare</topic><topic>Land use</topic><topic>Matricaria chamomilla</topic><topic>mixed linear models</topic><topic>Parasitic plants. Weeds</topic><topic>Phytopathology. Animal pests. Plant and forest protection</topic><topic>Polygonum</topic><topic>precision farming</topic><topic>Stellaria media</topic><topic>Technology</topic><topic>Triticum aestivum</topic><topic>weed control</topic><topic>weed distribution</topic><topic>Weeds</topic><topic>wheat</topic><topic>winter</topic><topic>Zea mays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>GERHARDS, R</creatorcontrib><creatorcontrib>GUTJAHR, C</creatorcontrib><creatorcontrib>WEIS, M</creatorcontrib><creatorcontrib>KELLER, M</creatorcontrib><creatorcontrib>SÖKEFELD, M</creatorcontrib><creatorcontrib>MÖHRING, J</creatorcontrib><creatorcontrib>PIEPHO, H P</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Weed research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>GERHARDS, R</au><au>GUTJAHR, C</au><au>WEIS, M</au><au>KELLER, M</au><au>SÖKEFELD, M</au><au>MÖHRING, J</au><au>PIEPHO, H P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application</atitle><jtitle>Weed research</jtitle><date>2012-02</date><risdate>2012</risdate><volume>52</volume><issue>1</issue><spage>6</spage><epage>15</epage><pages>6-15</pages><issn>0043-1737</issn><eissn>1365-3180</eissn><coden>WEREAT</coden><abstract>Gerhards R, Gutjahr C, Weis M, Keller M, Sökefeld M, Möhring J &amp; Piepho HP (2011). Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application. Weed Research 52, 6–15. Summary Field experiments using precision farming technology and Geographic Information Systems, following a so‐called Precision Experimental Design, were conducted in maize, winter barley and winter wheat and compared with two randomised plot experiments in maize to quantify yield effects attributed to weed competition and weed control. Fields were divided into cells, and weed densities for all weed species, soil conductivity and grain yield were measured in each cell. Untreated plots and herbicide treatments against grass weeds or broad‐leaved weeds were included in all three experiments. Chenopodium album, Polygonum spp. and Echinochloa crus‐galli were the dominating weed species in maize. Stellaria media, Veronica hederifolia, Matricaria chamomilla, Alopecurus myosuroides and Galium aparine were the most abundant weed species in the winter barley and winter wheat fields. All species were distributed heterogeneously within the fields with densities ranging from 0 to more than 200 plants m−2. In the Precision Experimental Design, it was found that grass‐weed competition and herbicide application had a significant effect on grain yield, using a linear mixed model with spatial correlation structure to determine the effects of groups of weed species, soil variability and herbicide application on grain yield separately. When a conventional plot experiment was set up in the same field, no statistically significant grain yield difference between the treatments was found. The results highlight the benefits of Precision Experimental Design for studying weed–crop competition. Data can be used to calculate yield loss functions for groups of weed species and to create a decision support system for site‐specific weed control.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/j.1365-3180.2011.00893.x</doi><tpages>10</tpages></addata></record>
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subjects Agronomy. Soil science and plant productions
Biological and medical sciences
Chemical control
Chenopodium album
competition
crop-weed competition
Cropping systems. Cultivation. Soil tillage
Echinochloa crus-galli
economic weed thresholds
Fundamental and applied biological sciences. Psychology
Galium aparine
General agronomy. Plant production
Generalities. Cropping systems and patterns
Geographic Information System
Herbicides
Hordeum vulgare
Land use
Matricaria chamomilla
mixed linear models
Parasitic plants. Weeds
Phytopathology. Animal pests. Plant and forest protection
Polygonum
precision farming
Stellaria media
Technology
Triticum aestivum
weed control
weed distribution
Weeds
wheat
winter
Zea mays
title Using precision farming technology to quantify yield effects attributed to weed competition and herbicide application
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