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

1967 ◽  
Vol 47 (5) ◽  
pp. 461-467 ◽  
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.

scholarly journals SPATIAL DISTRIBUTION AND SEQUENTIAL SAMPLING OF Brevipalpus phoenicis IN CITRUS

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.

SPATIAL PATTERN OF THE IMMATURE STAGES OF HYLEMYA BRASSICAE ON CABBAGE

1970 ◽  
Vol 102 (10) ◽  
pp. 1216-1222 ◽  
Author(s):  
M. K. Mukerji ◽  
D. G. Harcourt
Keyword(s):  
Spatial Pattern ◽  
Poisson Distribution ◽  
Negative Binomial ◽  
Immature Stages ◽  
Expected Number ◽  
Chi Square ◽  
Binomial Series ◽  
Binomial Parameter ◽  
Hylemya Brassicae ◽  
Cabbage Maggot

AbstractCounts of the cabbage maggot, Hylemya brassicae (Bouché), on cabbage did not conform to the Poisson distribution, there being an excess of uninfested and highly infested plants over the expected number. But when the negative binomial series was fitted to the observed distribution, the discrepancies were not significant when tested by chi-square. The negative binomial parameter k tended to increase with density. Using a common k, the distribution of the various stages may be described by expansion of (q − p)−k, when values of k are as follows: egg 0.78, larva 0.71, pupa 0.84. Three different transformations are offered for stabilizing the variance of field counts.

The Stability of Weed Seedling Population Models and Parameters in Eastern Nebraska Corn (Zea mays) and Soybean (Glycine max) Fields

Weed Science ◽  
1995 ◽  
Vol 43 (4) ◽  
pp. 604-611 ◽  
Author(s):  
Gregg A. Johnson ◽  
David A. Mortensen ◽  
Linda J. Young ◽  
Alex R. Martin
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Sequential Sampling ◽  
Mean Value ◽  
Distribution Model ◽  
Ratio Test ◽  
Weed Species ◽  
Sampling Procedures ◽  
Grass Weed

Intensive field surveys were conducted in eastern Nebraska to determine the frequency distribution model and associated parameters of broadleaf and grass weed seedling populations. The negative binomial distribution consistently fit the data over time (1992 to 1993) and space (fields) for both the inter and intrarow broadleaf and grass weed seedling populations. The other distributions tested (Poisson with zeros, Neyman type A, logarithmic with zeros, and Poisson-binomial) did not fit the data as consistently as the negative binomial distribution. Associated with the negative binomial distribution is akparameter.kis a nonspatial aggregation parameter related to the variance at a given mean value. Thekparameter of the negative binomial distribution was consistent across weed density for individual weed species in a given field except for foxtail spp. populations. Stability of thekparameter across field sites was assessed using the likelihood ratio test There was no stable or commonkvalue across field sites and years for all weed species populations. The lack of stability inkacross field sites is of concern, because this parameter is used extensively in the development of parametric sequential sampling procedures. Becausekis not stable across field sites,kmust be estimated at the time of sampling. Understanding the variability in it is critical to the development of parametric sequential sampling strategies and understanding the dynamics of weed species in the field.

scholarly journals Spatial Distribution of Eggs of Alabama argillacea Hübner and Heliothis virescens Fabricius (Lepidoptera: Noctuidae) on Bt and non-BtCotton

2015 ◽  
Vol 87 (4) ◽  
pp. 2243-2253
Author(s):  
TATIANA R. RODRIGUES ◽  
MARCOS G. FERNANDES ◽  
PAULO E. DEGRANDE ◽  
THIAGO A. MOTA
Keyword(s):  
Spatial Distribution ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Heliothis Virescens ◽  
Negative Binomial ◽  
Model Fitting ◽  
Spatial Arrangement ◽  
Distribution Model ◽  
Aggregation Index ◽  
Alabama Argillacea

ABSTRACT Among the options to control Alabama argillacea (Hübner, 1818) and Heliothis virescens (Fabricius, 1781) on cotton, insecticide spraying and biological control have been extensively used. The GM'Bt' cotton has been introduced as an extremely viable alternative, but it is yet not known how transgenic plants affect populations of organisms that are interrelated in an agroecosystem. For this reason, it is important to know how the spatial arrangement of pests and beneficial insect are affected, which may call for changes in the methods used for sampling these species. This study was conducted with the goal to investigate the pattern of spatial distribution of eggs of A. argillacea and H. virescens in DeltaOpalTM (non-Bt) and DP90BTMBt cotton cultivars. Data were collected during the agricultural year 2006/2007 in two areas of 5,000 m2, located in in the district of Nova América, Caarapó municipality. In each sampling area, comprising 100 plots of 50 m2, 15 evaluations were performed on two plants per plot. The sampling consisted in counting the eggs. The aggregation index (variance/mean ratio, Morisita index and exponent k of the negative binomial distribution) and chi-square fit of the observed and expected values to the theoretical frequency distribution (Poisson, Binomial and Negative Binomial Positive), showed that in both cultivars, the eggs of these species are distributed according to the aggregate distribution model, fitting the pattern of negative binomial distribution.

scholarly journals Sampling Hazelnuts for Aflatoxin: Effect of Sample Size and Accept/Reject Limit on Reducing the Risk of Misclassifying Lots

2007 ◽  
Vol 90 (4) ◽  
pp. 1028-1035 ◽  
Author(s):  
Guner Ozay ◽  
Ferda Seyhan ◽  
Aysun Yilmaz ◽  
Thomas B Whitaker ◽  
Andrew B Slate ◽  
...  
Keyword(s):  
Sample Size ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Food Additives ◽  
Sampling Plan ◽  
Test Results ◽  
Sampling Plans ◽  
Wide Range ◽  
Sample Test

Abstract About 100 countries have established regulatory limits for aflatoxin in food and feeds. Because these limits vary widely among regulating countries, the Codex Committee on Food Additives and Contaminants began work in 2004 to harmonize aflatoxin limits and sampling plans for aflatoxin in almonds, pistachios, hazelnuts, and Brazil nuts. Studies were developed to measure the uncertainty and distribution among replicated sample aflatoxin test results taken from aflatoxin-contaminated treenut lots. The uncertainty and distribution information is used to develop a model that can evaluate the performance (risk of misclassifying lots) of aflatoxin sampling plan designs for treenuts. Once the performance of aflatoxin sampling plans can be predicted, they can be designed to reduce the risks of misclassifying lots traded in either the domestic or export markets. A method was developed to evaluate the performance of sampling plans designed to detect aflatoxin in hazelnuts lots. Twenty hazelnut lots with varying levels of contamination were sampled according to an experimental protocol where 16 test samples were taken from each lot. The observed aflatoxin distribution among the 16 aflatoxin sample test results was compared to lognormal, compound gamma, and negative binomial distributions. The negative binomial distribution was selected to model aflatoxin distribution among sample test results because it gave acceptable fits to observed distributions among sample test results taken from a wide range of lot concentrations. Using the negative binomial distribution, computer models were developed to calculate operating characteristic curves for specific aflatoxin sampling plan designs. The effect of sample size and accept/reject limits on the chances of rejecting good lots (sellers' risk) and accepting bad lots (buyers' risk) was demonstrated for various sampling plan designs.

POPULATION ASSESSMENT DURING THE LARVAL STAGE OF THE ALFALFA WEEVIL, HYPERA POSTICA (COLEOPTERA: CURCULIONIDAE)

1975 ◽  
Vol 107 (8) ◽  
pp. 785-792 ◽  
Author(s):  
J. C. Guppy ◽  
D. G. Harcourt ◽  
M. K. Mukerji
Keyword(s):  
Larval Stage ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Sampling Plan ◽  
Variance Analysis ◽  
Alfalfa Weevil ◽  
Hypera Postica ◽  
Total Cost ◽  
Sample Unit

AbstractThis paper presents a sampling plan for estimating numbers of H. postica larvae in the spring growth of alfalfa. A 6-stem bouquet of foliage formed an appropriate sample unit. The pattern of counts for all four instars conformed to the negative binomial distribution, and variance analysis for 89 sets of data revealed that differences between block, plots, and quadrats generally were not significant. For moderate levels of infestation (ca. 12 larvae per bouquet), estimates with acceptable precision may be obtained by taking a single 6-stem bouquet from each of 16 randomly selected ft2 (0.9m2) quadrats within a field, at a total cost of 120 man-minutes.

POPULATION AND MORTALITY ASSESSMENT DURING THE COCOON STAGE OF THE ALFALFA WEEVIL, HYPERA POSTICA (COLEOPTERA: CURCULIONIDAE)

1975 ◽  
Vol 107 (12) ◽  
pp. 1275-1280 ◽  
Author(s):  
D. G. Harcourt ◽  
J. C. Guppy
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Sampling Plan ◽  
Mortality Factors ◽  
Alfalfa Weevil ◽  
Hypera Postica ◽  
Total Cost ◽  
Sample Unit

AbstractThis paper presents a sampling plan for estimating populations of Hypera postica (Gyll). cocoons in alfalfa, and of the principal mortality factors during this stage. The plan provides for samples in foliage and ground litter. For samples in foliage, where two-thirds of the cocoons are found, the most appropriate sample unit is a bouquet of 6 stems; for typical weevil densities, estimates with acceptable precision may be obtained by taking 25 bouquets at random from within a field. For litter samples, the appropriate sample unit is a quarter ft2 (232 cm2); acceptably precise estimates may be obtained by taking 20 such units at random from within a field. Total cost for a combined sample is 3.9 man-hours.The pattern of counts, both in foliage and ground litter, was well described by the negative binomial distribution.

Sequential Sampling for the Imported Cabbageworm, Pieris rapae (L.)

1966 ◽  
Vol 98 (7) ◽  
pp. 741-746 ◽  
Author(s):  
D. G. Harcourt
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Pieris Rapae ◽  
Sequential Sampling ◽  
Sampling Time ◽  
Field Conditions ◽  
Population Estimates ◽  
Population Means ◽  
Considerable Saving

AbstractSequential sampling, in which decisions depend upon the accumulated results of a series of observations, leads to considerable saving of time and money. A sequential plan, based on the negative binomial distribution and providing for population estimates in three infestation categories, was drawn up for use in control of the imported cabbageworm, Pieris rapae (L.), on cabbage. An appraisal of the plan under field conditions showed that it reduced the sampling time by 75% while rating the infestation correctly in 94 of 100 cases. With the six discrepancies, population means lay between the limits set for the infestation categories.

scholarly journals Risk Assessment for Tomato Fruitworm in Processing Tomato Crop-Egg Location and Sequential Sampling

Insects ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 13
Author(s):  
Elisabete Figueiredo ◽  
Catarina Gonçalves ◽  
Sónia Duarte ◽  
Maria C. Godinho ◽  
António Mexia ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Sequential Sampling ◽  
Sampling Plan ◽  
Random Pattern ◽  
Growth Stages ◽  
Data Sets ◽  
Tomato Crop ◽  
Sample Number ◽  
Sequential Sampling Plan ◽  
Fixed Sample

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.

The spatial pattern of Cyprideis torosa (Jones, 1850)(Crustacea: Ostracoda)

1976 ◽  
Vol 56 (1) ◽  
pp. 179-189 ◽  
Author(s):  
Carlo Heip
Keyword(s):  
Spatial Pattern ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial

The spatial pattern of the ostracod Cyprideis torosa (Jones, 1850) is aggregated and can be described by the negative binomial distribution. The fit of the observed distribution to the negative binomial is less well for the total number of females because females that are not carrying eggs tend to be independently distributed from both females carrying eggs and males. The aggregations are roughly circular with a radius of about 13 cm and may be themselves aggregated. A method to picture the aggregations is described.

Sign in / Sign up

Export Citation Format

Share Document