Perspective: common errors in dose–response analysis and how to avoid them

Keshtkar, Eshagh; Kudsk, Per; Mesgaran, Mohsen B.

doi:10.1002/ps.6268

Cited by 23 publications

(16 citation statements)

References 48 publications

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“…Model Y represents the growth response (dry weight, survival or enzyme activity) to dose x of the herbicide; d is the upper limit of the curve; c is the lower limit (fixed at 0); b is the slope at the inflection point (i.e., GR 50 , LD 50 or I 50 ); x is the herbicide dose; e the herbicide concentration required to inhibit shoot growth, lethal dose and enzyme activity by 50% [31,32]. The resistance factors (RF = R/S).…”

Section: Discussionmentioning

confidence: 99%

Confirmation of Multiple Resistant Chloris radiata Population, Harvested in Colombian Rice Fields

et al. 2021

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This paper reports the first C. radiata population with resistance to glyphosate and multiple resistance to the acetolactate synthase (ALS) inhibitor, imazamox. Two populations, one putative resistant (R) and one susceptible (S), were used in the studies. Dose–response experiments were performed to evaluate the resistance factor (RF). Shikimic acid accumulation, 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) and ALS enzyme activities were studied together with chemical integrated weed management (adjuvants and alternative herbicides). The resistance to glyphosate and imazamox was confirmed based on the dry weight reduction, visual evaluation and survival. The results of dose–response curve assays showed for the R population intermedium RF for glyphosate (5.1 and 9.7 for amount of herbicide needed to reduce the dry weight by 50% GR50 and lethal dose of 50% LD50, respectively) and high RF for imazamox (34.9 and 37.4, respectively). The low shikimic acid accumulation in R population confirmed the glyphosate resistance. The glyphosate concentration which inhibited the EPSPS enzyme in 50% (I50) was approximately 20 times higher for R population than the S population, while the imazamox I50 in ALS enzyme for the R plants was 89 times greater than the S plants. In the chemical integrated weed management, the foliar retention and effectivity assays showed that the use of adjuvants improves the retention of glyphosate and imazamox, and the reduction in dry weight of weeds. The alternative herbicides study showed that the acetyl-CoA carboxylase (ACCase) inhibitors, paraquat and glufosinate, had better results for control in this species. However, poor control was observed with bispyribac-sodium, metsulfuron-methyl and quinclorac, indicating possible cross-resistance for ALS-inhibitors and also multiple resistance for auxinic herbicides (quinclorac). Nevertheless dose–response experiments are required to confirm this assumption.

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Section: Discussionmentioning

confidence: 99%

Confirmation of Multiple Resistant Chloris radiata Population, Harvested in Colombian Rice Fields

et al. 2021

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“…The concept of quantiles for time-to-event studies is closely related to the concept of effective doses (ED) in dose-response assays, although we discourage the use of this term for time-toevent studies, as the main predictor is not, in strict terms, a dose, but rather time. As a general suggestion for time-to-event assays, quantiles should be calculated for the whole sample, and they should not be restricted to the fraction of individuals that have experienced the event, especially when the purpose is to make comparisons across treatment groups (Bradford 2002;Keshtkar et al 2021).…”

Section: Quantilesmentioning

confidence: 99%

A unified framework for the analysis of germination, emergence, and other time-to-event data in weed science

2022

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Summary Germination and emergence assays represent the most notable examples of time-to-event data in agriculture and related disciplines. In spite of the peculiar characteristics of this type of data, there has been little effort to establish a specific and comprehensive framework for their analyses. Indeed, a brief survey of literature shows that germination and emergence data, along with other phenological measurements such as flowering time, have been analyzed through a myriad of approaches giving rise to confusion and uncertainty among scientists and practitioners as to what may represent the best statistical practice. This lack of a coherence in statistical approach may reduce the efficiency of research, while making the communication of results and the cross-study comparisons extremely challenging. Here, we attempt to provide a coherent framework and protocol for the analyses of germination/emergence and other time-to-event data in weed science and related disciplines, together with a software implementation in the form of a new R package. We propose a similar approach to biologic assays in ecotoxicology, based on: (i) fitting a time-to-event model to describe the whole time-course of events; (ii) comparing time-to-event curves across experimental treatments, and (iii) deriving further information from the fitted model to better focus on some traits of interest. The most appropriate methods to accomplish the above procedure were carefully selected from the framework of survival analysis and related sources and were modified to comply with the specific needs of weed, seed, and plant sciences. Finally, they were implemented in the new R package ‘drcte’. In this manuscript we describe the procedure and its limitations by way of providing examples of several types of germination/emergence assays. We highlight that our proposed procedure can also serve as the first step of data analyses where its output are subsequently submitted to traditional or meta-analytic approaches.

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“…At 28 days after treatment (DAT), visual control was assessed (0%, no control to 100%, complete plant death) and aboveground biomass was harvested (clipped at the potting mix level) and dried to constant weight in a forced-air oven at 60 C. For dose-response, the raw biomass weight (grams per Cone-tainer) was subjected to statistical analysis, as suggested by Keshtkar et al (2021). As for the herbicide screen, dry biomass weight was converted to the percentage of biomass reduction (BR) compared to the nontreated check of each accession using the equation:…”

Section: Data Collectionmentioning

confidence: 99%

Target site resistance to acetolactate synthase inhibitors in a fall panicum (Panicum dichotomiflorum Michx.) accession from Wisconsin and its response to alternative herbicides

et al. 2022

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Due to the lack of effective POST herbicide options, producers typically rely on nicosulfuron as the main POST grass herbicide in sweet corn production systems. In 2019, a Wisconsin sweet corn producer reported fall panicum control escapes after spraying nicosulfuron. Seeds from mature plants were collected to i) measure fall panicum response to acetolactate synthase [ALS]-inhibiting herbicides, ii) elucidate the resistance mechanism, and iii) evaluate its response to alternative POST herbicides. Greenhouse and laboratory investigations were conducted to assess fall panicum response to ALS-inhibiting herbicides and elucidate the resistance mechanism. Dose-response results showed that fall panicum was highly resistant to nicosulfuron with a resistance ratio of >12.9-fold (survived rates >254 g ai ha−1 or 8X the field label rate). Molecular and genetic studies indicated that there are multiple ALS gene copies in fall panicum and resistance was due to a mutation in one copy, resulting in an Asp-376-Glu amino acid substitution. Additional greenhouse experiments indicate that clethodim (105 g ai ha−1), quizalofop-p-ethyl (70 g ae ha−1), glyphosate (864 g ae ha−1), and glufosinate (650 g ai ha−1) are effective POST options to manage the ALS-resistant fall panicum (>90.0% control and 96.8% biomass reduction) in rotational years. The 4-hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting herbicides isoxaflutole (105 g ai ha−1), mesotrione (105 g ai ha−1), tembotrione (92 g ai ha−1), and tolpyralate (39 g ai ha−1) did not provide effective POST fall panicum control. Because these herbicides are commonly used for POST weed control in sweet corn, more investigations are required to evaluate combinations of HPPD-inhibiting herbicides with herbicides from other sites of action for POST fall panicum control. Herein we confirm the first case of herbicide resistance in fall panicum in the United States.

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Perspective: common errors in dose–response analysis and how to avoid them

Cited by 23 publications

References 48 publications

Confirmation of Multiple Resistant Chloris radiata Population, Harvested in Colombian Rice Fields

Confirmation of Multiple Resistant Chloris radiata Population, Harvested in Colombian Rice Fields

A unified framework for the analysis of germination, emergence, and other time-to-event data in weed science

Target site resistance to acetolactate synthase inhibitors in a fall panicum (Panicum dichotomiflorum Michx.) accession from Wisconsin and its response to alternative herbicides

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