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Predictive weed emergence models and biocenomic models as a tool for integrated weed management

Maja Šćepanović orcid id orcid.org/0000-0003-4661-5417 ; Sveučilište u Zagrebu, Agronomski fakultet
Valentina Šoštarčić orcid id orcid.org/0000-0002-6887-7680 ; Sveučilište u Zagrebu, Agronomski fakultet
Roberta Masin ; University of Padova, DAFNAE
Klara Barić ; Sveučilište u Zagrebu, Agronomski fakultet


Puni tekst: hrvatski pdf 1.031 Kb

str. 397-409

preuzimanja: 256

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Puni tekst: engleski pdf 1.031 Kb

str. 397-409

preuzimanja: 660

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Sažetak

In Integrated Weed Management herbicide use is justified only when the economic damage caused by the weed population is greater than the cost of the treatment which is known as economic threshold. The competitiveness of the weeds must be known beforehand in order to be able to forecast the potential damage. Economic optimum threshold models give more precise indication because they predict the long–term effects (seed bank) of weed competition and management techniques on population dynamics and annualized net return. Because of the multispecies nature of the weed population and completely different biology and ecology of weed species regarding pests and pathogens, adoption of this threshold approach to weed management has been much slower. In recent years many decision models have been developed to assist growers in weed control decision–making for several crops. The most used one are decision support system (DSS) models and predictive weed emergence models. DSS models integrate biology of weed with economy of crops and give to producers information “if” and “how” to treat. Information “when” to treat is possible while using predictive weed emergence models because they calculate the percentage of weeds that have already emerged out of the total number of plants that may potentially emerge during the season. This information is useful for optimizing application time.

Ključne riječi

Integrated Weed Management; economic threshold; bio–economic models; DSS; predictive weed emergence models

Hrčak ID:

166561

URI

https://hrcak.srce.hr/166561

Datum izdavanja:

13.7.2016.

Podaci na drugim jezicima: hrvatski

Posjeta: 2.098 *