David Elmouttie

Improving detection probabilities for pests in stored grain.

BACKGROUND The presence of insects in stored grain is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspection of bulk grain commodities is essential to detect pests and thereby to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grain, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper, a sampling methodology is demonstrated that accounts for the heterogeneous distribution of insects in bulk grain. RESULTS It is shown that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling programme to detect insects in bulk grain. The results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. It is also demonstrated that the probability of detecting pests in bulk grain increases as the number of subsamples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION This study underlines the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Are insect frugivores always plant pests? The impact of fruit fly (Diptera: Tephritidae) larvae on host plant fitness

Herbivory is generally regarded as negatively impacting on host plant fitness. Frugivorous insects, which feed directly on plant reproductive tissues, are predicted to be particularly damaging to hosts. We tested this prediction with the fruit fly, Bactrocera tryoni, by recording the impact of larval feeding on two direct (seed number and germination) and two indirect (fruit decay rate and attraction/deterrence of vertebrate frugivores) measures of host plant fitness. Experiments were done in the laboratory, glasshouse and tropical rainforest. We found no negative impact of larval feeding on seed number or germination for three test plants: tomato, capsicum and eggplant. Further, larval feeding accelerated the initiation of decay and increased the final level of fruit decay in tomatoes, apples, pawpaw and pear, a result considered to be beneficial to the fruit. In rainforest studies, native rodents preferred infested apple and pears compared to uninfested control fruit; however, there were no differences observed between treatments for tomato and pawpaw. For our study fruits, these results demonstrate that fruit fly larval infestation has neutral or beneficial impacts on the host plant, an outcome which may be largely influenced by the physical properties of the host. These results may contribute to explaining why fruit flies have not evolved the same level of host specialization generally observed for other herbivore groups.

Host use and crop impacts of Oribius Marshall species (Coleoptera: Curculionidae) in Eastern Highlands Province, Papua New Guinea

Oribius species are small flightless weevils endemic to the island of New Guinea and far northern Cape York, Australia. The adults feed externally on leaves, developing fruit and green bark, but their impact as pests and general host use patterns are poorly known. Working in Eastern Highlands Province, Papua New Guinea, we carried out structured host use surveys, farmer surveys, shade-house growth trials and on-farm and on-station impact trials to: (i) estimate the host range of the local Oribius species; (ii) understand adult daily activity patterns; (iii) elucidate feeding habits of the soil dwelling larvae; and (iv) quantify the impacts of adult feeding damage. Oribius inimicus and O. destructor accounted for nearly all the Oribius species encountered locally, of these two O. inimicus was the most abundant. Weevils were collected from 31 of 33 plants surveyed in the Aiyura Valley, and a combination of farmer interviews and literature records provided evidence for the beetles being pestiferous on 43 crops currently or previously grown in the Highlands. Adult weevils had a distinct diurnal pattern of being in the upper plant canopy early in the morning and, to a lesser extent, again late in the afternoon. For the remainder of the day, beetles resided within the canopy, or possibly off the plant. Movement of adults between plants appeared frequent. Pot trials confirmed the larvae are root feeders. Quantified impact studies showed that the weevils are damaging to a range of vegetable and orchard crops (broccoli, capsicum, celery, French bean, Irish potato, lettuce, orange and strawberry), causing average yield losses of around 30-40%, but up to 100% on citrus. Oribius weevils pose a significant and, apparently, growing problem for Highlands agriculture.

Sampling stored‐product insect pests: a comparison of four statistical sampling models for probability of pest detection

BACKGROUND Developing sampling strategies to target biological pests such as insects in stored grain is inherently difficult owing to species biology and behavioural characteristics. The design of robust sampling programmes should be based on an underlying statistical distribution that is sufficiently flexible to capture variations in the spatial distribution of the target species. RESULTS Comparisons are made of the accuracy of four probability-of-detection sampling models - the negative binomial model,(1) the Poisson model,(1) the double logarithmic model(2) and the compound model(3) - for detection of insects over a broad range of insect densities. Although the double log and negative binomial models performed well under specific conditions, it is shown that, of the four models examined, the compound model performed the best over a broad range of insect spatial distributions and densities. In particular, this model predicted well the number of samples required when insect density was high and clumped within experimental storages. CONCLUSIONS This paper reinforces the need for effective sampling programs designed to detect insects over a broad range of spatial distributions. The compound model is robust over a broad range of insect densities and leads to substantial improvement in detection probabilities within highly variable systems such as grain storage.

A review of current statistical methodologies for in-storage sampling and surveillance in the grains industry.

Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, integrated pest management (IPM), to determine grain quality and to satisfy importing nations biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in-storage sampling strategies concentrating on detection of pest insects within a grain bulk; however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in-storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in-storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in-storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in-storage sampling systems.