A decision algorithm for patch spraying
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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 tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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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