Developing and verifying a fumigant loss model for bulk stored grain to predict phosphine concentrations by taking into account fumigant leakage and sorption

Plumier, Benjamin M.; Schramm, Matthew W.; Maier, Dirk E.

doi:10.1016/j.jspr.2018.05.006

Cited by 13 publications

(2 citation statements)

References 9 publications

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“…It is a well-established fact that phosphine resistance develops in a pest population mainly due to failure to maintain the recommended concentration within the storage enclosure, resulting in selection for resistance, given that resistance genotypes are present (15,24). Several factors can contribute to inadequate fumigation, including leaky storage structures, underdosing, and fumigation temperatures that are lower than that recommended for phosphine fumigation (20,24,76,90,110). Repeated fumigation in an attempt to control surviving populations in leaky storage is a typical example of selection for resistance (41).…”

Section: Reducing Selectionmentioning

confidence: 99%

Resistance to the Fumigant Phosphine and Its Management in Insect Pests of Stored Products: A Global Perspective

Nayak

Daglish

Phillips

et al. 2020

Annu. Rev. Entomol.

236

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Development of resistance in major grain insect pest species to the key fumigant phosphine (hydrogen phosphide) across the globe has put the viability and sustainability of phosphine in jeopardy. The resistance problem has been aggravated over the past two decades, due mostly to the lack of suitable alternatives matching the major attributes of phosphine, including its low price, ease of application, proven effectiveness against a broad pest spectrum, compatibility with most storage conditions, and international acceptance as a residue-free treatment. In this review, we critically analyze the published literature in the area of phosphine resistance with special emphasis on the methods available for detection of resistance, the genetic basis of resistance development, key management strategies, and research gaps that need to be addressed.

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Section: Reducing Selectionmentioning

confidence: 99%

Resistance to the Fumigant Phosphine and Its Management in Insect Pests of Stored Products: A Global Perspective

Nayak

Daglish

Phillips

et al. 2020

Annu. Rev. Entomol.

236

View full text Add to dashboard Cite

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“…The 3D MLP (Maier, Lawrence, Plumier) finite element model has been previously used to investigate stored grain ecosystems in a variety of situations [8,[16][17][18]. It has the capacity to analyze the effects that changing sensor distributions have on aeration results by running multiple simulations with sensors distributed in ways consistent with the existing temperature cable technology and the randomized wireless sensor technology.…”

Section: Introductionmentioning

confidence: 99%

Effect of Temperature Sensor Numbers and Placement on Aeration Cooling of a Stored Grain Mass Using a 3D Finite Element Model

Plumier

Maier

2021

Agriculture

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Grain stored in silos in the United States of America is generally cooled with an aeration system to limit mold spoilage and insect infestation. Monitoring efficacy of aeration and real-time conditions of stored grain is generally done using temperature cables with fixed-spaced sensor locations that are hung from the roof of the silo. Numerous placement options exist in terms of the number of cables and their positions. However, little investigation has been done into the effects of cable placement on aeration system operation decisions and real-time monitoring of stored grain conditions. For a one-year period, the temperatures predicted by sensors in three recommended temperature cable configurations were evaluated for conditions in Ames, IA, USA. The average temperatures of each of the cable sensor configurations were lower than the average temperatures of the entire silo, with as much as an 11.4 °C difference. When sensor locations were used as inputs for aeration control, all cable sensor configurations predicted similar average temperatures. However, the temperature averages varied by as much as 3.6 °C depending on the temperature cable distribution chosen. Results demonstrated that temperature cables near the center or near the edges of the silos produce results that are not representative of the grain mass, resulting in less efficient aerations. Simulations were also conducted with randomized horizontal “wireless” sensor locations at fixed grain depths. The average temperatures were similar, but an increase in the number of sensors reduced variability between simulated storage years as the number of randomized sensors increased.

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Alternative and emerging storage practices and technologies

Thorpe¹

2022

Storage of Cereal Grains and Their Products

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Developing and verifying a fumigant loss model for bulk stored grain to predict phosphine concentrations by taking into account fumigant leakage and sorption

Cited by 13 publications

References 9 publications

Resistance to the Fumigant Phosphine and Its Management in Insect Pests of Stored Products: A Global Perspective

Resistance to the Fumigant Phosphine and Its Management in Insect Pests of Stored Products: A Global Perspective

Effect of Temperature Sensor Numbers and Placement on Aeration Cooling of a Stored Grain Mass Using a 3D Finite Element Model

Alternative and emerging storage practices and technologies

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