scholarly journals SPATIAL DISTRIBUTION OF Chrysodeixis includens EGGS (WALKER, 1858) (LEPIDOPTERA: NOCTUIDAE) IN SOYBEAN CROP

2019 ◽  
Vol 17 (2) ◽  
pp. 51 ◽  
Author(s):  
Leandro Aparecido De Souza ◽  
José Carlos Barbosa ◽  
João Henrique Silva Carvalho ◽  
Leticia Serpa dos Santos ◽  
Diego Felisbino Fraga ◽  
...  

Among pest insects that attack soybean crops, Chrysodeixis includens (Walker, 1858) (Lepidoptera: Noctuidae) looper caterpillar deserves attention due to its key pest status in soybean crops. The spatial distribution of C. includens eggs should be investigated in order to understand the behavior of this species in the area. The aim of this study was to investigate the spatial distribution of C. includens eggs in soybean crops. The experiment was conducted with SYN 9070 RR soybean variety in an experimental area of the Teaching, Research and Extension Farm (FEPE) of FCAV/ UNESP, Jaboticabal, SP, Brazil. The area of 0.6 ha was divided into 60 equidistant plots of 100 m² each. For the study of the spatial distribution of P. includens eggs in the area, the following dispersion indexes were used: variance / mean ratio (I), Morisita index (Id), Green coefficient (Cx), k exponent of the negative binomial distribution for each sampling. Regarding the probabilistic models that describe the spatial distribution of a given variable, the data adjustment to the Poisson and negative binomial distributions was tested. According to values obtained for dispersion indexes, egg distribution occurred in an aggregate way, and the negative binomial distribution was the most appropriate probabilistic model to represent the distribution of C. includens eggs in the study area.

2015 ◽  
Vol 21 (1) ◽  
Author(s):  
Antonio De Souza Silva

<p class="p1"> <strong>RESUMEN</strong></p><p class="p3">El objetivo de este trabajo fue generar informacion acerca de cuál es el modelo de disposición espacial de Vatiga spp. en el cultivo de la yuca. Se realizaron muestreos en dos áreas comerciales de 2500 m<span class="s1">2</span>, divididas en 100 parcelas. Se contaron adultos y de ninfas de Vatiga spp. en las hojas basales y medias de la planta. En total, se realizaron doce muestreos quincenalmente, desde febrero hasta abril de 2014, época de mayor incidencia de esta plaga. De forma general, a través de los índices de dispersión (varianza/media, índice de Morisita y exponente K) y las distribuciones de frecuencia, se observa que la distribución espacial de Vatiga spp. es agregada, es decir, el padrón de distribución Binomial Negativa fue el que resultó de mejor ajuste a los datos obtenidos a campo, con el conteo de los individuos.</p><p class="p1"><strong>ABSTRACT</strong></p><p class="p2">The aim of this study was to generate information about which is the model of spatial distribution of Vatiga spp. in the cassava culture. Sampling was conducted in two commercial areas of 2,500 m<span class="s1">2</span>, divided into 100 plots. Adults and nymphs of Vatiga spp. were counted in the basal and medium plant leaves. In all, twelve samples were taken fortnightly from February to April 2014, when occurs the highest incidence of this pest. Based in the indices of dispersion (variance/mean, Morisita index and K exponent) and the frequency distributions, it was observed that the spatial distribution of Vatiga spp. is aggregate, it means that the standard Negative Binomial distribution was the best fit to the field data obtained, with the counting direction of individuals.</p>


Weed Science ◽  
1992 ◽  
Vol 40 (4) ◽  
pp. 554-557 ◽  
Author(s):  
Lori J. Wiles ◽  
Glenn W. Oliver ◽  
Alan C. York ◽  
Harvey J. Gold ◽  
Gail G. Wilkerson

Spatial distribution of broadleaf weeds within 14 North Carolina soybean fields was characterized by fitting negative binomial distributions to frequency distributions of weed counts in each field. In most cases, the data could be represented by a negative binomial distribution. Estimated values of the parameter K of this distribution were small, often less than one, indicating a high degree of patchiness. The data also indicated that the population as a whole was patchy. Counts of individual species were positively correlated with each other in some fields and total weed count could be represented by a negative binomial for 12 of the 14 fields.


Nativa ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 356
Author(s):  
Emanuel Júnior Pereira da Silva ◽  
Ademária Aparecida de Souza ◽  
Anderson Castro Soares de Oliveira ◽  
Jhonatan David Santos das Neves ◽  
Antônio Lucrécio dos Santos Neto ◽  
...  

O objetivo desta pesquisa foi estudar a distribuição espacial de Rhinostomus barbirostris (Coleoptera: Curculionidae) (Fabricius, 1775) em coqueiro (Cocos nucifera L.). Foram realizadas 10 amostragens quinzenalmente do número de machos, fêmeas e total (macho + fêmea), de R. barbirostris em armadilhas demarcada com uma tela de náilon envoltas as palmeiras com sintoma característico do ataque dessa praga, totalizando 24 armadilhas. Para o estudo da distribuição espacial de R. barbirostris, foram calculados os índices de dispersão: razão variância/média (I), índice de Morisita (), coeficiente de Green (Cx), expoente k da distribuição binomial negativa (k), índice de grupo por tamanho (IGT), Índice de frequência de agrupamento (IFA) e Índice de Patchiness (IP) para cada amostragem. Foi testado o ajuste dos dados as distribuições Poisson e binomial negativa. Os resultados obtidos nos índices de agregação calculados indicam que a maioria das amostragens apresentou distribuição agregada de R. barbirostris, para todas as variáveis estudadas. A distribuição binomial negativa foi o modelo mais adequado para representar a distribuição de frequência da coleobroca no coqueiro, já que a variância foi superior à média na maioria das amostragens.Palavras-chave: Rhinostomus barbirostris; cocoicultura; índices de dispersão. SPATIAL DISTRIBUTION OF COCONUT BORER ABSTRACT: The objective of this research was to study the spatial distribution of Rhinostomus barbirostris (Coleoptera: Curculionidae) (Fabricius, 1775) in coconut (Cocos nucifera L.). They were made ten samples every two weeks,of males,  females and the total (Male + female), R. barbirostris in marked traps with a nylon screen surrounded with palm trees characteristic symptom of the attack of this pest, totaling 24 traps. To study the spatial distribution of R. barbirostris, dispersion indexes were calculated: variance / mean ratio, Morisita index , Green coefficient (Cx), k exponent of negative binomial distribution, index of de Cluster Size (ICS), index of de Cluster Frequency (ICF) e index of de Patchiness (IP) for each sample. It tested the data fitting the Poisson distribution and binomial negative. The results calculated in aggregation indexes indicate that Most samplings presented aggregated distribution of R. barbirostris for all the variables studied. The negative binomial distribution was the best model to represent the frequency distribution of the coconut borer, since the variance was higher than the average for the majority of the samples.Keywords: Rhinostomus barbirostris; coconut farmin; dispersion indexes.


2019 ◽  
Vol 53 (5) ◽  
pp. 417-422
Author(s):  
P. De los Ríos ◽  
E. Ibáñez Arancibia

Abstract The coastal marine ecosystems in Easter Island have been poorly studied, and the main studies were isolated species records based on scientific expeditions. The aim of the present study is to apply a spatial distribution analysis and niche sharing null model in published data on intertidal marine gastropods and decapods in rocky shore in Easter Island based in field works in 2010, and published information from CIMAR cruiser in 2004. The field data revealed the presence of decapods Planes minutus (Linnaeus, 1758) and Leptograpsus variegatus (Fabricius, 1793), whereas it was observed the gastropods Nodilittorina pyramidalis pascua Rosewater, 1970 and Nerita morio (G. B. Sowerby I., 1833). The available information revealed the presence of more species in data collected in 2004 in comparison to data collected in 2010, with one species markedly dominant in comparison to the other species. The spatial distribution of species reported in field works revealed that P. minutus and N. morio have aggregated pattern and negative binomial distribution, L. variegatus had uniform pattern with binomial distribution, and finally N. pyramidalis pascua, in spite of aggregated distribution pattern, had not negative binomial distribution. Finally, the results of null model revealed that the species reported did not share ecological niche due to competition absence. The results would agree with other similar information about littoral and sub-littoral fauna for Easter Island.


2012 ◽  
Vol 21 (1) ◽  
pp. 78-80 ◽  
Author(s):  
Patricio Peña-Rehbein ◽  
Patricio De los Ríos-Escalante

Nematodes of the genus Anisakis have marine fishes as intermediate hosts. One of these hosts is Thyrsites atun, an important fishery resource in Chile between 38 and 41° S. This paper describes the frequency and number of Anisakis nematodes in the internal organs of Thyrsites atun. An analysis based on spatial distribution models showed that the parasites tend to be clustered. The variation in the number of parasites per host could be described by the negative binomial distribution. The maximum observed number of parasites was nine parasites per host. The environmental and zoonotic aspects of the study are also discussed.


2016 ◽  
Vol 38 (4) ◽  
Author(s):  
WALTER MALDONADO JR ◽  
JOSÉ CARLOS BARBOSA ◽  
MARÍLIA GREGOLIN COSTA ◽  
PAULO CÉSAR TIBURCIO GONÇALVES ◽  
TIAGO ROBERTO DOS SANTOS

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.


2015 ◽  
Vol 87 (4) ◽  
pp. 2243-2253
Author(s):  
TATIANA R. RODRIGUES ◽  
MARCOS G. FERNANDES ◽  
PAULO E. DEGRANDE ◽  
THIAGO A. MOTA

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.


Crustaceana ◽  
2018 ◽  
Vol 91 (12) ◽  
pp. 1465-1482 ◽  
Author(s):  
Rolando Vega-Aguayo ◽  
Guillermo Figueroa-Muñoz ◽  
Marco A. Retamal ◽  
Patricio De los Ríos

Abstract Our knowledge on the status of Hemigrapsus crenulatus (H. Milne Edwards, 1837) populations along the Chilean coast is scarce. The aim of the present study was to quantitatively estimate the spatial distribution and abundance of Hemigrapsus crenulatus in the Puerto Cisnes estuary (44°S, Aysen region, Chilean Patagonia). The spatial distribution appeared to be aggregated, with 3.64 ± 7.99 ind/m2 as gross density, and 10.50 ± 10.62 ind/m2 as a potential ecological density, i.e., if the quadrants with zero individuals are not taken into consideration. The equation of the negative binomial distribution was: where: . The average density of Hemigrapsus crenulatus under stones is lower if all beach surfaces are considered. Its abundance or dominance on estuarine beaches probably would be due to the fact that this species is one of the crustaceans of the lower intertidal level that can survive under a wide range of salinity values.


2020 ◽  
Vol 80 (2) ◽  
pp. 362-367
Author(s):  
P. De los Ríos ◽  
E. Carreño

Abstract The rocky shores in Chile have a wide invertebrate species diversity, that include species with marked abundances in determined regions. The aim of the present study is to analyse the spatial distribution pattern in different marine invertebrate species in rocky shore of Araucania region, considering if these species have random, uniform or associated patterns, and extrapolate if these patterns have Poisson, binomial or negative binomial distribution respectively. The results revealed the presence mainly of gastropods molluscs that would graze on benthic algae, these species have mainly aggregated pattern that has a robust negative binomial distribution pattern. The obtained results agree with observations for marine benthic fauna that mentioned the presence of aggregated pattern, has negative binomial distribution. Other ecological topics about spatial distribution were discussed.


Author(s):  
Anwer Khurshid ◽  
Ashit B Chakraborty

<p><span>The negative binomial distribution (NBD) is extensively used for the<br /><span>description of data too heterogeneous to be fitted by Poisson<br /><span>distribution. Observed samples, however may be truncated, in the<br /><span>sense that the number of individuals falling into zero class cannot be<br /><span>determined, or the observational apparatus becomes active when at<br /><span>least one event occurs. Chakraborty and Kakoty (1987) and<br /><span>Chakraborty and Singh (1990) have constructed CUSUM and<br /><span>Shewhart charts for zero-truncated Poisson distribution respectively.<br /><span>Recently, Chakraborty and Khurshid (2011 a, b) have constructed<br /><span>CUSUM charts for zero-truncated binomial distribution and doubly<br /><span>truncated binomial distribution respectively. Apparently, very little<br /><span>work has specifically addressed control charts for the NBD (see, for<br /><span>example, Kaminsky et al., 1992; Ma and Zhang, 1995; Hoffman, 2003;<br /><span>Schwertman. 2005).<br /></span></span></span></span></span></span></span></span></span></span></span></span></span></span></p><p><span><span><span><span><span><span><span><span><span><span><span><span><span><span><span>The purpose of this paper is to construct Shewhart control charts<br /><span>for zero-truncated negative binomial distribution (ZTNBD). Formulae<br /><span>for the Average run length (ARL) of the charts are derived and studied<br /><span>for different values of the parameters of the distribution. OC curves<br /><span>are also drawn.</span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></p>


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