2010
DOI: 10.1111/j.1539-6924.2009.01297.x
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Cocoa Pod Borer (Conopomorpha cramerella Snellen) in Papua New Guinea: Biosecurity Models for New Ireland and the Autonomous Region of Bougainville

Abstract: Cocoa Pod Borer (Conopomorpha cramerella Snellen) (CPB) is an important pest of cocoa. Following its emergence as a pest in East New Britain, Papua New Guinea, in 2006, it was considered relevant to assess its potential spread to other cocoa growing regions. Its likelihood of introduction to the islands of Bougainville and New Ireland from East New Britain Province, Papua New Guinea, was modeled using Monte Carlo simulation. This dispersal model was based around different scenarios, identifying trends rather t… Show more

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Cited by 11 publications
(13 citation statements)
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“…Proper waste recycling strategy has become all the more important with the outbreak of cocoa pod borer (Conopomorpha cramerella Snellen; family: Gracillariidae) (Yen et al 2010). The cocoa pod borer (CPB) larva causes damage to cocoa by boring into the pod and disrupting the development of the beans.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Proper waste recycling strategy has become all the more important with the outbreak of cocoa pod borer (Conopomorpha cramerella Snellen; family: Gracillariidae) (Yen et al 2010). The cocoa pod borer (CPB) larva causes damage to cocoa by boring into the pod and disrupting the development of the beans.…”
Section: Introductionmentioning
confidence: 99%
“…Hence, of cocoa growers abandon CPB-infested pods and opened husks in piles scattered on the farms thus directly contributing to the multiplication of CPB. The husks and pods scattered on the farm, can also harbor and pre-dispose spread of black pod disease (Phytophthora palmivora) inoculum (Yen et al 2010).…”
Section: Introductionmentioning
confidence: 99%
“…The uniform distribution, which gives equal weight to each value within the uncertainty range, is commonly used when the main objective is to understand model behaviour, but more flexible probability distributions are sometimes needed to represent the input and parameter uncertainty. When the model input corresponds to a discrete variable, for example, the number of imported consignments, or number of successful incursions, discrete probability distributions such as the Poisson are often appropriate (e.g., Yen et al 2010). Among continuous distributions, the well-known Gaussian distribution is often convenient, since it requires only the specification of a mean value and a standard deviation.…”
Section: A Four-step Methods For Uncertainty Analysismentioning
confidence: 99%
“…Among continuous distributions, the well-known Gaussian distribution is often convenient, since it requires only the specification of a mean value and a standard deviation. It is often replaced by the truncated Gaussian distribution, triangular, or by beta distributions, which give upper and lower bounds to the possible values (e.g., Peterson et al 2009;Yen et al 2010). When the distribution should be asymmetric, for example, when input factors are likely to be near zero, log-normal, triangular, or beta distributions offer a large range of possibilities (e.g., Peterson et al 2009).…”
Section: A Four-step Methods For Uncertainty Analysismentioning
confidence: 99%
“…Since there was little genetic resistance amongst cultivated varieties, the introduction of the disease had a devastating impact on yields and consequently the economy and employment within the region (Pereira et al, 1996). Other examples of disease and pest movement include the spread of frosty pod rot within Central America (Phillips-Mora et al, 2006) and the spread of the cocoa pod borer within South East Asia (Yen et al, 2010). These examples serve to illustrate the dangers of new pest and disease encounters in a region or country and hence the vital need for quarantine measures.…”
Section: Introductionmentioning
confidence: 99%