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Image‐based thresholds for weeds in maize fields
Author(s) -
Ali A,
Streibig J C,
Christensen S,
Andreasen C
Publication year - 2015
Publication title -
weed research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 74
eISSN - 1365-3180
pISSN - 0043-1737
DOI - 10.1111/wre.12109
Subject(s) - weed , weed control , context (archaeology) , agronomy , economic threshold , biology , infestation , mathematics , horticulture , pest analysis , paleontology
Summary Recent development of site‐specific weed management strategies suggests patch application of herbicides to avoid their excessive use in crops. The estimation of infestation of weeds and control thresholds are important components for taking spray decisions. If weed pressure is below a certain level in some parts of the field and if late germinating weeds do not affect yield, it may not be necessary the spray such places from an economic point of view. Consequently, it makes sense to develop weed control thresholds for patch spraying, based on weed cover early in the growing season. In D anish maize field experiments conducted from 2010 to 2012, we estimated competitive ability parameters and control thresholds of naturally established weed populations in the context of decision‐making for patch spraying. The most frequent weed was C henopodium album , accompanied by C apsella bursa‐pastoris, C irsium arvense, L amium amplexicaule, T ripleurospermum inodorum, P oa annua, P olygonum aviculare, P olygonum persicaria, S tellaria media and V eronica persica . Relative leaf cover of weeds was estimated using an image analysis method. The relation between relative weed leaf cover and yield loss was analysed by nonlinear regression models. The competitive ability parameters and economic thresholds were estimated from the regression models. The competitive ability of weed mixtures was influenced by the increasing proportion of large size weeds in the mixtures. There was no significant effect of weeds which survived or established after the first herbicide application, indicating that early image analysis was robust for use under these conditions.