Binomial Sequential Sampling Plans and Decision Support Algorithms for Managing the Russian Wheat Aphid (Homoptera: Aphididae) in Small Grains

Legg, David; Nowierski, Robert M.; Feng, Ming; Peairs, Frank B.; Hein, Gary L.; Elberson, Leslie R.; Johnson, James B.

doi:10.1093/jee/87.6.1513

Cited by 16 publications

(10 citation statements)

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“…Next, we set the theoretical maximum-allowable probability of misclassifying grasshopper densities as being equal to 0.1 (Legg et al, 1994), and calculated sequential sampling stop values with the following equations:…”

Section: Developing the Adult Sequential Sampling Planmentioning

confidence: 99%

“…Legg et al, 1994). Unfortunately, that was not done here as the Weed and Pest Districts and USDA ± APHIS conducted their surveys independently of one another.…”

Section: Checking the Similarity Between Adult Sequential Sampling Anmentioning

confidence: 99%

“…This was done by assuming the outcomes from the USDA ± APHIS method to be`correct'. Typically, there should be > 90% agreement between the two methods (Legg et al, 1994) but, since side-by-side comparisons were not done, and one method produced`generalized' results while the other did not, we felt that > 67% agreement would be acceptable.…”

Section: Checking the Similarity Between Adult Sequential Sampling Anmentioning

confidence: 99%

“…However, if a threshold is expressed in enumerative scale, it can be transformed into a proportion scale through binomial regression (Kono and Sugino, 1958;Gerrard and Chiang, 1970;Legg et al, 1993Legg et al, , 1994Legg and Lockwood, 1995).…”

Section: Introductionmentioning

confidence: 99%

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Binomial sequential sampling plans for rangeland grasshoppers

Legg

Lockwood

2001

International Journal of Pest Management

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Advances in sampling technology have made it possible to develop binomial sequential sampling plans for rangeland grasshoppers. Using this technique, grasshopper infestations can be rapidly classified into`high' or`low' categories relative to a threshold. We have developed a set of binomial sequential sampling tools, or plans, to assess the level of adult and nymphal grasshopper infestations on rangelands. The adult grasshopper plan was used to assess the level of grasshopper infestations throughout Wyoming, USA, in 1998; this resulted in a 79.5% reduction of the sampling effort. In addition, the adult sequential sampling plan was of sufficient scientific rigour to qualify some ranchers for federal disaster relief funds due to excessive grasshopper feeding. Grasshopper managers should consider using binomial sequential sampling plans wherever and whenever efficient surveys are needed to determine if grasshoppers are a threat to the production of rangeland forage and the maintenance of this ecosystem.

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Section: Developing the Adult Sequential Sampling Planmentioning

confidence: 99%

“…Legg et al, 1994). Unfortunately, that was not done here as the Weed and Pest Districts and USDA ± APHIS conducted their surveys independently of one another.…”

Section: Checking the Similarity Between Adult Sequential Sampling Anmentioning

confidence: 99%

Section: Checking the Similarity Between Adult Sequential Sampling Anmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Binomial sequential sampling plans for rangeland grasshoppers

Legg

Lockwood

2001

International Journal of Pest Management

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“…An alternative to enumeration is binomial sampling, which records the presence or absence of mites and relies on the known correlation between mite density and the proportion of samples infested (Legg et al 1984). This has the advantages of being rapid and easily executed in the field with a hand lens.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a brushing machine for estimating density of spider mites on grape leaves

Macmillan

Costello

2015

Exp Appl Acarol

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Direct visual inspection and enumeration for estimating field population density of economically important arthropods, such as spider mites, provide more information than alternative methods, such as binomial sampling, but is laborious and time consuming. A brushing machine can reduce sampling time and perhaps improve accuracy. Although brushing technology has been investigated and recommended as a useful tool for researchers and integrated pest management practitioners, little work to demonstrate the validity of this technique has been performed since the 1950's. We investigated the brushing machine manufactured by Leedom Enterprises (Mi-Wuk Village, CA, USA) for studies on spider mites. We evaluated (1) the mite recovery efficiency relative to the number of passes of a leaf through the brushes, (2) mite counts as generated by the machine compared to visual counts under a microscope, (3) the lateral distribution of mites on the collection plate and (4) the accuracy and precision of a 10% sub-sample using a double-transect counting grid. We found that about 95% of mites on a leaf were recovered after five passes, and 99% after nine passes, and mite counts from brushing were consistently higher than those from visual inspection. Lateral distribution of mites was not uniform, being highest in concentration at the center and lowest at the periphery. The 10% double-transect pattern did not result in a significant correlation with the total plate count at low mite density, but accuracy and precision improved at medium and high density. We suggest that a more accurate and precise sample may be achieved using a modified pattern which concentrates on the center plus some of the adjacent area.

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