Effects of Clariva Complete Beans Seed Treatment on <i>Heterodera glycines</i> Reproduction and Soybean Yield in Iowa

Bissonnette, Kaitlyn M.; Marett, Christopher C.; Mullaney, Mark P.; Gebhart, Gregory D.; Kyveryga, Peter; Mueller, Tristan; Tylka, Gregory L.

doi:10.1094/php-08-17-0043-rs

Cited by 11 publications

(12 citation statements)

References 19 publications

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“…Pasteuria penetrans can strongly reduce Meloidogyne density (e.g., > 80% in Bhuiyan et al, 2018 ) and reduce crop damage (e.g., Timper et al, 2016 ). In field trials, however, P. penetrans and other Pasteuria species vary substantially in their ability to control nematode populations (Bissonnette et al, 2018 ; Kariuki & Dickson, 2007 ).…”

Section: Introductionmentioning

confidence: 99%

A diverse parasite pool can improve effectiveness of biological control constrained by genotype‐by‐genotype interactions

Mundim

Gibson

2022

Evolutionary Applications

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The outcomes of biological control programs can be highly variable, with natural enemies often failing to establish or spread in pest populations. This variability has posed a major obstacle in use of the bacterial parasite Pasteuria penetrans for biological control of Meloidogyne species, economically devastating plant‐parasitic nematodes for which there are limited management options. A leading hypothesis for this variability in control is that infection is successful only for specific combinations of bacterial and nematode genotypes. Under this hypothesis, failure of biological control results from the use of P. penetrans genotypes that cannot infect local Meloidogyne genotypes. We tested this hypothesis using isofemale lines of M. arenaria derived from a single field population and multiple sources of P. penetrans from the same and nearby fields. In strong support of the hypothesis, susceptibility to infection depended on the specific combination of host line and parasite source, with lines of M. arenaria varying substantially in which P. penetrans source could infect them. In light of this result, we tested whether using a diverse pool of P. penetrans could increase infection and thereby control. We found that increasing the diversity of the P. penetrans inoculum from one to eight sources more than doubled the fraction of M. arenaria individuals susceptible to infection and reduced variation in susceptibility across host lines. Together, our results highlight genotype‐by‐genotype specificity as an important cause of variation in biological control and call for the maintenance of genetic diversity in natural enemy populations.

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Section: Introductionmentioning

confidence: 99%

A diverse parasite pool can improve effectiveness of biological control constrained by genotype‐by‐genotype interactions

Mundim

Gibson

2022

Evolutionary Applications

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“…It contains Pasteuria nishizawae ‐Pn1 for seed treatments against Heterodera glycines and H. schachtii on soybean and sugar beet, respectively. Despite decade‐long marketing, little is known about the efficacy of the treatments (Bissonnette et al., 2018; Jensen et al., 2018).…”

Section: Discussionmentioning

confidence: 99%

Performance of biological and chemical nematicides in different soils to control Meloidogyne incognita in tomato plants

Loffredo,

Edwards,

Ploeg

et al. 2023

Journal of Phytopathology

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Three fluorinated, one carbamate nematicide, as well as two biological control agents were tested in greenhouse trials to determine their efficacy against Meloidogyne incognita on tomato plants in three different soils. Each soil was treated with one of the following chemical nematicides at the labelled rate: fluensulfone, fluopyram, fluazaindolizine, and oxamyl. The biocontrol agents used were Metacordyceps chlamydosporia and Pasteuria penetrans. In one additional treatment, a combination of the biocontrol agents was applied. After 60 days, root‐knot nematode population data, tomato plant growth, and root galling were assessed. Of the chemical nematicide treatments, fluazaindolizine had the strongest effect on M. incognita J2 in soil, with a 99% reduction relative to the untreated control. More than 99% reduction in the number of eggs per root system was achieved by all three fluorinated nematicides. The strongest effect on M. incognita J2 in soil by a biological control agent was in a combined M. chlamydosporia + P. penetrans treatment that resulted in an 87% reduction. This combined treatment was also the most effective on the eggs per root system, reducing the number of eggs by 69% relative to the untreated control. The different soils affected the efficacy of the biocontrol agents more than the efficacy of the fluorinated nematicides. For example, the percentage reduction in M. incognita J2 by the biocontrol treatments ranged from 40% to 65% for the three soils. For the fluorinated nematicides this range was 96% to 97%. These trials demonstrate the influence of the growth substrate on the efficacy of the biocontrol treatments. Overall, the tested biological control agents did not match the novel nematicides' early protection of tomato transplants.

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“…For example, Kyveryga et al (2013a) combined on‐farm, weather and soil data to analyze the risk of yield losses resulting from a reduction of farmer normal N fertilizer rates applied to corn ( Zea mays L.). Bissonnette et al (2018) used on‐farm data from 18 strip‐trial experiments located in the northern half of Iowa over 3 yr to study the effect of nematicide seed treatment, Clariva Complete Beans (CCB) ( Pasteuria nishizawae, sedaxane, thiamethoxam, fludioxonil and mefenoxam as active ingredients) compared with CruiserMaxx Advanced plus Vibrance (CMV) ( thiamethoxam, mefenoxam, fludioxonil and sedaxane as active ingredients), on soybean cyst nematode ( Heterodera glycines ) reproduction and soybean [ Glycine max (L.) Merr.] yield.…”

Section: Developing Research Networkmentioning

confidence: 99%

A Framework for Visualization and Analysis of Agronomic Field Trials from On‐Farm Research Networks

et al. 2019

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An on‐farm research network is an organization of farmers that conducts agronomic experiments under local conditions. It is common that an elementary statistical analysis be conducted for individual studies. However, there is unexplored potential in detecting yield response variability patterns for better decision making. We developed a data‐analytics framework and web‐application program that allows users to analyze multiple studies that use a common protocol and can identify the conditions where an imposed treatment may or may not be effective. The development of this data‐analytics framework is needed to improve predictions at the farm level that can lead to more cost‐effective, sustainable and environmentally sound agricultural production. Data visualization is an important part of data‐analytics. In this paper, we have developed and tested a Bayesian hierarchical model that can be used to assess the general agronomic performance of different management practices. Decision making related to new management practices should be based on the complete evidence, local conditions and economic considerations. The web‐application includes dynamic data visualization features to enhance communication and sharing of information with the goal to reach a broader audience. Core Ideas We develop a data‐analytics framework and web‐application for on‐farm research trials. A Bayesian hierarchical model quantifies the uncertainty in yield response. The model helps assess alternative practices, products, and technologies among trial locations. The framework provides a reactive break‐even economic analysis of alternative management practices.

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Effects of Clariva Complete Beans Seed Treatment on Heterodera glycines Reproduction and Soybean Yield in Iowa

Cited by 11 publications

References 19 publications

A diverse parasite pool can improve effectiveness of biological control constrained by genotype‐by‐genotype interactions

A diverse parasite pool can improve effectiveness of biological control constrained by genotype‐by‐genotype interactions

Performance of biological and chemical nematicides in different soils to control Meloidogyne incognita in tomato plants

A Framework for Visualization and Analysis of Agronomic Field Trials from On‐Farm Research Networks

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