Herbicides and Selective Phytotoxicity

Blackman, G. E.; Templeman, Wilfred; Halliday, D.

doi:10.1146/annurev.pp.02.060151.001215

Cited by 30 publications

(10 citation statements)

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“…The principles in toxicology and pharmacology do apply to herbicide research by classifying toxicity according to some standardized methods with sigmoid dose-response models. After World War II, there were several articles on how to assess the toxicity of herbicides in plants (Blackman et al 1951;Woodford 1950), and now, some of those models are being applied easily, thanks to the seamless fitting of nonlinear response curves with high-speed computers. Figure 8.…”

Section: Regression Bmentioning

confidence: 99%

Research Methods in Weed Science: Statistics

2015

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There are various reasons for using statistics, but perhaps the most important is that the biological sciences are empirical sciences. There is always an element of variability that can only be dealt with by applying statistics. Essentially, statistics is a way to summarize the variability of data so that we can confidently say whether there is a difference among treatments or among regression parameters and tell others about the variability of the results. To that end, we must use the most appropriate statistics to get a “correct” picture of the experimental variability, and the best way of doing that is to report the size of the parameters or the means and their associated standard errors or confidence intervals. Simply declaring that the yields were 1 or 2 ton ha−1does not mean anything without associated standard errors for those yields. Another driving force is that no journal will accept publications without the data having been subjected to some kind of statistical analysis.

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Section: Regression Bmentioning

confidence: 99%

Research Methods in Weed Science: Statistics

2015

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“…the capacity of a compound to cause temporary or long-lasting damage to crops, a problem of relevance both in post-emergence but also in pre-emergence treatments (James et al 1991;OEPP/EPPO 2007). As it has known for years, phytotoxicity mainly depends upon the sensitivity of the crop, but also on the doses, the distribution moments and distribution methods of herbicide, and the prevailing environmental conditions such as temperature or moisture (Blackman et al 1951). Phytotoxic effect of a few herbicides were registered in some species such as German chamomile (T oth and Danilovič 2004), a species that in other experiments as well was found to be especially sensitive to chemical treatments (James et al 1991).…”

Section: Chemical Weed Controlmentioning

confidence: 99%

Medicinal and Aromatic Plants of the World

Máthé¹

2015

Medicinal and Aromatic Plants of the World

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“…In consequence much of the work in this field has been empirical, and it has often been impossible to judge the precision, let alone the accuracy, of the results obtained. About the same time, Blackman (1952) and Blackman et al (1951Blackman et al ( , 1958 published papers on the principles of phytotoxicity based on biological assay, the purpose of which was to measure the activity of a biologically active substance by the response of living material. The work of Blackman and colleagues thoroughly discussed the experimental designs, the statistical analysis and the assessment of relative potency.…”

Section: The Logistic Dose-response Curvementioning

confidence: 99%

Joint Action Analysis Utilizing Concentration Addition and Independent Action Models

et al. 2011

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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−1was 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 (ECx) 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.

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Herbicides and Selective Phytotoxicity

Cited by 30 publications

References 0 publications

Research Methods in Weed Science: Statistics

Research Methods in Weed Science: Statistics

Medicinal and Aromatic Plants of the World

Joint Action Analysis Utilizing Concentration Addition and Independent Action Models

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