Spatial Pattern and Sequential Sampling Plan forMeloidogyne haplain Muck-Grown Carrots

Helicoverpa armigera is one of the key pests affecting processing tomatoes and many other crops. A three-year study was conducted to describe the oviposition preferences of this species on determinate tomato plants (mainly the stratum, leaf, leaflet, and leaf side) and the spatial pattern of the eggs in the field, to form a sequential sampling plan. Eggs were found mainly in the exposed canopy, on leaves a (upper stratum) and b (upper-middle stratum) and significantly fewer eggs on leaf c (middle-lower stratum) below flower clusters. This vertical pattern in the plant was found in all phenological growth stages. The spatial pattern was found to be aggregated, with a trend towards a random pattern at lower densities. A sequential sampling plan was developed, based on Iwao’s method with the parameters of Taylor’s power law, with minimum and maximum sample size of 20 and 80 sample units (plants), respectively (two leaves/plant). For its validation, operating characteristic (OC) and average sample number (ASN) curves were calculated by means of simulation with independent data sets. The β-error was higher than desirable in the vicinity of the economic threshold, but this sampling plan is regarded as an improvement both in effort and precision, compared with the fixed sample plan, and further improvements are discussed.

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SPATIAL ARRANGEMENT OF THE EGGS OF HYLEMYA BRASSICAE (BOUCHÉ), AND A SEQUENTIAL SAMPLING PLAN FOR USE IN CONTROL OF THE SPECIES

Canadian Journal of Plant Science ◽

10.4141/cjps67-086 ◽

1967 ◽

Vol 47 (5) ◽

pp. 461-467 ◽

Cited By ~ 2

Author(s):

D. G. Harcourt

Keyword(s):

Spatial Pattern ◽

Negative Binomial Distribution ◽

Binomial Distribution ◽

Negative Binomial ◽

Sequential Sampling ◽

Spatial Arrangement ◽

Sampling Plan ◽

Chi Square ◽

Sequential Sampling Plan ◽

Hylemya Brassicae

Counts of eggs of Hylemya brassicae (Bouché) in cabbage did not conform to the Poisson distribution owing to a preponderance of uninfested and highly infested plants. But when the negative binomial series was fitted to the observed distribution, the discrepancies were not significant when tested by chi-square. The spatial pattern may be described by expansion of (q—px)−k with a common k of 0.95.Three methods of transformation stabilized the variance of field counts. A sequential sampling plan based on the negative binomial distribution and providing for two infestation classes was drawn up for use in control of the insect in the stem brassicas.

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A Fixed-Precision Sequential Sampling Plan for the Potato Tuberworm Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae), on Potato Cultivars

Neotropical Entomology ◽

10.1007/s13744-017-0487-1 ◽

2017 ◽

Vol 46 (4) ◽

pp. 388-395 ◽

Cited By ~ 4

Author(s):

M Shahbi ◽

A Rajabpour

Keyword(s):

Sequential Sampling ◽

Sampling Plan ◽

Potato Cultivars ◽

Phthorimaea Operculella ◽

Sequential Sampling Plan ◽

Potato Tuberworm Moth ◽

Potato Tuberworm

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Within-plant distribution and binomial sequential sampling plan for Tetranychus evansi (Acari: Tetranychidae) in greenhouse tomato: implications for management.

10.31220/agrirxiv.2020.00011 ◽

2020 ◽

Author(s):

Willis Ndeda Ochilo ◽

Gideon Nyamasyo ◽

John Agano

Keyword(s):

Sequential Sampling ◽

Sampling Plan ◽

Plant Distribution ◽

Tetranychus Evansi ◽

Sequential Sampling Plan ◽

Red Spider Mite ◽

Mite Density ◽

Density Analysis ◽

The Tropics ◽

Best Fit

Abstract The red spider mite, Tetranychus evansi is a critical pest of tomato in the tropics. Control of T. evansi has traditionally depended on acaricide treatments. However, it is only in a handful of crops where monitoring techniques for mites, using statistical methods, have been developed to help farmers decide when to spray. The objective of this study, therefore, was to develop a sampling plan that would help farmers increase accuracy, and reduce the labor and time needed to monitor T. evansi on tomato. The distribution of T. evansi within-plant was aggregated, and intermediate leaves (YFL) was the most appropriate sampling unit to evaluate the mite density. Analysis based on Taylor's Power Law showed an aggregated pattern of distribution of T. evansi, while assessment of the fitness of the binomial model indicated that a tally threshold of 5 mites per YFL provided the best fit. Consequently, binomial sequential sampling plans premised on three action thresholds (0.1, 0.2 and 0.3) were developed. The binomial sequential sampling plan for T. evansi developed in this study has the potential to significantly increase the chance for targeted acaricide applications. This judicious use of pesticides is especially crucial within the context of integrated pest management (IPM).

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Analysis and Design of the Sequential Sampling Plan by Attributes Based on the Minimal Lattice Paths

Frontiers in Statistical Quality Control ◽

10.1007/978-3-662-11787-3_4 ◽

1987 ◽

pp. 52-66

Author(s):

H. Ohta ◽

M. Furukawa

Keyword(s):

Sequential Sampling ◽

Sampling Plan ◽

Lattice Paths ◽

Analysis And Design ◽

Sequential Sampling Plan ◽

Minimal Lattice

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SPATIAL DISTRIBUTION AND SEQUENTIAL SAMPLING OF Brevipalpus phoenicis IN CITRUS

Revista Brasileira de Fruticultura ◽

10.1590/0100-29452016085 ◽

2016 ◽

Vol 38 (4) ◽

Author(s):

WALTER MALDONADO JR ◽

JOSÉ CARLOS BARBOSA ◽

MARÍLIA GREGOLIN COSTA ◽

PAULO CÉSAR TIBURCIO GONÇALVES ◽

TIAGO ROBERTO DOS SANTOS

Keyword(s):

Spatial Distribution ◽

Negative Binomial Distribution ◽

Binomial Distribution ◽

Negative Binomial ◽

Sequential Sampling ◽

Sampling Plan ◽

Goodness Of Fit Test ◽

Control Plan ◽

Sequential Sampling Plan ◽

Brevipalpus Phoenicis

ABSTRACT Among the pests of citrus, one of the most important is the red and black flat mite Brevipalpus phoenicis (Geijskes), which transmits the Citrus leprosis virus C (CiLV-C).When a rational pest control plan is adopted, it is important to determine the correct timing for carrying out the control plan. Making this decision demands constant follow-up of the culture through periodic sampling where knowledge about the spatial distribution of the pest is a fundamental part to improve sampling and control decisions. The objective of this work was to study the spatial distribution pattern and build a sequential sampling plan for the pest. The data used were gathered from two blocks of Valencia sweet orange on a farm in São Paulo State, Brazil, by 40 inspectors trained for the data collection. The following aggregation indices were calculated: variance/ mean ratio, Morisita index, Green’s coefficient, and k parameter of the negative binomial distribution. The data were tested for fit with Poisson and negative binomial distributions using the chi-square goodness of fit test. The sequential sampling was developed using Wald’s Sequential Probability Ratio Test and validated through simulations. We concluded that the spatial distribution of B. phoenicis is aggregated, its behavior best fitted to the negative binomial distribution and we built and validated a sequential sampling plan for control decision-making.

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