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Joint Action Analysis Utilizing Concentration Addition and Independent Action Models

  • Julie A. Abendroth (a1), Erin E. Blankenship (a2), Alex R. Martin (a3) and Fred W. Roeth (a3)
Abstract

In weed science literature, models such as concentration addition, independent action, effect summation, and the parallel line assay technique have been used to predict and analyze whole-plant response to herbicide mixtures. Although a joint action reference model is necessary for determining whether the herbicide mixture provides less than (antagonistic), equal to (zero-interaction or additive), or greater than (synergistic) expected control, model selection often occurs with little regard to the model's underlying biological assumptions. The joint action models of concentration addition (CA) and independent action (IA) are the appropriate models to consider for analysis of herbicide mixtures of two active components. CA assumes additivity of dose, with herbicides differing only in potency, whereas IA assumes multiplicativity of effects, in which herbicides behave independently and sequentially within the plant. CA and IA predicted mixture responses were computed for a sample mixture data set of mesotrione plus atrazine. IA predicted lower mixture responses than CA; for example, mesotrione at 17.5 g ha−1 + atrazine at 140 g ha−1 was predicted to provide 45% (IA) compared with 53% (CA) control of Palmer amaranth. Joint action claims of synergism and antagonism were shown to be dependent on the reference model selected. Although mesotrione plus atrazine combinations were synergistic under IA assumptions, analysis under CA assumptions indicated mesotrione plus atrazine to be synergistic, additive, and antagonistic according to the selected effective concentration (EC x ) level and fixed-ratio mixture. Because it is not possible to determine the appropriate joint action model on the basis of fit of predicted to observed mixture data, the appropriateness of underlying biological assumptions was considered for the sample mixture data set. Additionally, we provide decision criteria to aid researchers in their selection of an appropriate joint action reference model.

En la literatura de la ciencia de las malezas, modelos tales como el de adición de concentración, acción independiente, la suma de los efectos y la técnica de prueba de líneas paralelas se han usado para predecir y analizar la respuesta de toda la planta a la mezcla de herbicidas. Mientras que se necesita un modelo de acción conjunta de referencia para determinar si la mezcla de herbicida proporciona menos que (antagónico), igual a (cero interacción o aditivo) o mayor que (sinérgico) el control esperado, frecuentemente la selección del modelo se hace considerando poco las suposiciones biológicas subyacentes del modelo. Los modelos de acción conjunta de adición de concentración (CA) y acción independiente (IA) son los apropiados a considerar para los análisis de mezclas de herbicidas de dos componentes activos. El CA supone un efecto aditivo de dosis, con herbicidas que difieren solamente en potencia, mientras que IA supone un efecto multiplicativo en el que los herbicidas se comportan independientemente y secuencialmente dentro de la planta. Las respuestas de las mezclas predichas en los modelos CA e IA se computaron para una muestra de datos de una mezcla de mesotrione + atrazine. IA pronosticó respuestas a la mezcla más bajas que CA; por ejemplo, se estimó que mesotrione a 17.5 g/ha + atrazine a 140 g/ha proporcionaría un control de Amaranthus palmeri de 45% (IA) versus 53% (CA). Las predicciones de acción conjunta como sinergismo y antagonismo mostraron depender del modelo de referencia seleccionado. Mientras las combinaciones de mesotrione + atrazine resultaron ser sinérgicas, de acuerdo a las suposiciones IA, el análisis bajo las suposiciones CA indicó que mesotrione + atrazine sería sinérgico, aditivo y antagónico según el nivel de concentración efectiva (ECx) seleccionada y la proporción fija de mezcla utilizada. Debido a que no es posible determinar el modelo adecuado de acción conjunta basado en el ajuste de los datos pronosticados a los observados, se tomó en cuenta lo apropiado de las suposiciones biológicas subyacentes para el conjunto de datos muestra de la mezcla. Adicionalmente, los autores proporcionan criterios de decisión para ayudar a los investigadores en la selección de un modelo de acción conjunta de referencia apropiado.

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Corresponding author's E-mail: julie.abendroth@pioneer.com
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Weed Technology
  • ISSN: 0890-037X
  • EISSN: 1550-2740
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