A decision algorithm for patch spraying

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Standard

A decision algorithm for patch spraying. / Christensen, Svend; Heisel, Torben; Walter, Mette; Graglia, Enrico.

I: Weed Research, Bind 43, Nr. 4, 08.2003, s. 276-284.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Christensen, S, Heisel, T, Walter, M & Graglia, E 2003, 'A decision algorithm for patch spraying', Weed Research, bind 43, nr. 4, s. 276-284. https://doi.org/10.1046/j.1365-3180.2003.00344.x

APA

Christensen, S., Heisel, T., Walter, M., & Graglia, E. (2003). A decision algorithm for patch spraying. Weed Research, 43(4), 276-284. https://doi.org/10.1046/j.1365-3180.2003.00344.x

Vancouver

Christensen S, Heisel T, Walter M, Graglia E. A decision algorithm for patch spraying. Weed Research. 2003 aug.;43(4):276-284. https://doi.org/10.1046/j.1365-3180.2003.00344.x

Author

Christensen, Svend ; Heisel, Torben ; Walter, Mette ; Graglia, Enrico. / A decision algorithm for patch spraying. I: Weed Research. 2003 ; Bind 43, Nr. 4. s. 276-284.

Bibtex

@article{f40df05b4a0a4c688424c7e9228bdb65,
title = "A decision algorithm for patch spraying",
abstract = "It has been established that weeds are spatially aggregated with a spatially varying composition of weed species within agricultural fields. Site-specific spraying therefore requires a decision method that includes the spatial variation of the weed composition and density. A computerized decision method that estimates an economic optimal herbicide dose according to site-specific weed composition and density is presented in this paper. The method was termed a {\textquoteleft}decision algorithm for patch spraying{\textquoteright} (DAPS) and was evaluated in a 5-year experiment, in Denmark. DAPS consists of a competition model, a herbicide dose–response model and an algorithm that estimates the economically optimal doses. The experiment was designed to compare herbicide treatments with DAPS recommendations and the Danish decision support system PC-Plant Protection. The results did not show any significant grain yield difference between DAPS and PC-Plant Protection; however, the recommended herbicide doses were significantly lower when using DAPS than PC-Plant Protection in all years. The main difference between the two decision models is that DAPS integrates crop–weed competition and estimates the net return as a continuous function of herbicide dose. The hypothesis tested is that the benefit of using lower herbicide doses recommended by DAPS would disappear after a few years because weed density will increase and thus require higher doses. However, the results of weed counting every year did not confirm this hypothesis.",
author = "Svend Christensen and Torben Heisel and Mette Walter and Enrico Graglia",
year = "2003",
month = aug,
doi = "10.1046/j.1365-3180.2003.00344.x",
language = "English",
volume = "43",
pages = "276--284",
journal = "Weed Research",
issn = "0043-1737",
publisher = "Wiley-Blackwell",
number = "4",

}

RIS

TY - JOUR

T1 - A decision algorithm for patch spraying

AU - Christensen, Svend

AU - Heisel, Torben

AU - Walter, Mette

AU - Graglia, Enrico

PY - 2003/8

Y1 - 2003/8

N2 - It has been established that weeds are spatially aggregated with a spatially varying composition of weed species within agricultural fields. Site-specific spraying therefore requires a decision method that includes the spatial variation of the weed composition and density. A computerized decision method that estimates an economic optimal herbicide dose according to site-specific weed composition and density is presented in this paper. The method was termed a ‘decision algorithm for patch spraying’ (DAPS) and was evaluated in a 5-year experiment, in Denmark. DAPS consists of a competition model, a herbicide dose–response model and an algorithm that estimates the economically optimal doses. The experiment was designed to compare herbicide treatments with DAPS recommendations and the Danish decision support system PC-Plant Protection. The results did not show any significant grain yield difference between DAPS and PC-Plant Protection; however, the recommended herbicide doses were significantly lower when using DAPS than PC-Plant Protection in all years. The main difference between the two decision models is that DAPS integrates crop–weed competition and estimates the net return as a continuous function of herbicide dose. The hypothesis tested is that the benefit of using lower herbicide doses recommended by DAPS would disappear after a few years because weed density will increase and thus require higher doses. However, the results of weed counting every year did not confirm this hypothesis.

AB - It has been established that weeds are spatially aggregated with a spatially varying composition of weed species within agricultural fields. Site-specific spraying therefore requires a decision method that includes the spatial variation of the weed composition and density. A computerized decision method that estimates an economic optimal herbicide dose according to site-specific weed composition and density is presented in this paper. The method was termed a ‘decision algorithm for patch spraying’ (DAPS) and was evaluated in a 5-year experiment, in Denmark. DAPS consists of a competition model, a herbicide dose–response model and an algorithm that estimates the economically optimal doses. The experiment was designed to compare herbicide treatments with DAPS recommendations and the Danish decision support system PC-Plant Protection. The results did not show any significant grain yield difference between DAPS and PC-Plant Protection; however, the recommended herbicide doses were significantly lower when using DAPS than PC-Plant Protection in all years. The main difference between the two decision models is that DAPS integrates crop–weed competition and estimates the net return as a continuous function of herbicide dose. The hypothesis tested is that the benefit of using lower herbicide doses recommended by DAPS would disappear after a few years because weed density will increase and thus require higher doses. However, the results of weed counting every year did not confirm this hypothesis.

U2 - 10.1046/j.1365-3180.2003.00344.x

DO - 10.1046/j.1365-3180.2003.00344.x

M3 - Journal article

VL - 43

SP - 276

EP - 284

JO - Weed Research

JF - Weed Research

SN - 0043-1737

IS - 4

ER -

ID: 47289563