Proteomics may help to detect subtle pollution-related changes, such as responses to mixture pollution at low concentrations, where clear signs of toxicity are absent. Also proteomics provide potential in the discovery of new sensitive biomarkers for environmental pollution. We utilized SELDI-TOF MS (surface enhanced laser desorption. / ionization time-of-flight mass spectrometry) to analyze the proteomic profile of Heterocypris incongruens exposed to several heavy metals (lead, mercury, copper, cadmium and chromium) and pesticides (emamectin benzoate, endosulfan, cypermethrin, mancozeb and paraquat dichloride). Several highly significant biomarkers were selected to make a model of classification analysis. data sets obtained from H. incongruens exposed to pollutants were investigated for differential protein expression by SELDI-TOF MS and decision tree classification. Decision tree model was developed with training set, and then validated with test set from profiling data of H. incongruens. Machine learning techniques provide a promising approach to process the information from mass spectrometry data. Even thought the identification of protein would be ideal, class discrimination does not need it. In the future, this decision tree model would be validated with various levels of pollutants to apply field samples.

Biological control of greenhouse whitefly, Trialeurodes vaporariorum in greenhouse tomatoes with the parasitoid Encarsia formosa has been evaluated in Korea. However implementation of biological control program is retarded due to the reasons that lacks of site specific strategies. Aims of the present research are: (1) To develop an effective biological control method of the whitefly in tomato plants; the following were studied: (a) development of proper introduction rate of parasitoid, E. formosa, for the control of whiteflies, and (b) development of the effective control method of American serpentine leafminers with a parasitoid, Diglyphus isaea. (2) To build a computer-simulation model in which all factors are incorporated which have been studied in the relationship between whitefly and the parasitoid. The computer-simulation models would be used to estimate the effect of future developments in the greenhouse industry on the biological control of the greenhouse whitefly using E. formosa. More general goals are to develop reliable evaluation techniques to test the pest-control ability of natural enemies prior to their use in practical situations and to determine which role simulation models may play in estimating the results of biological control in new situations.

In this study, we examined the spatial dependence and association of Ambrosia beetle, Platypus koryoensis, which is the vector of oak wilt disease caused by Rafaelea sp. using two geostatistical methods. Two adjacent sampling plots were selected and named as "Sector A" and "Sector B". Sector A area was 63 ha and Sector B area was 420 ha, respectively. We arbitrarily separated each sampling plot by 50m×50m grids. Sector A and B were separated by 19×15 and 43×41 grids, respectively. The oak wilt disease damage level of tree was classified by amount of frass of Ambrosia beetle near target oak tree as follows: Lost tree (LT), Severe damage (SD), Intermediate damage (ID), and Light damage (LD). Number of each damage level of oak tree was counted and recorded in each sampling grid. Spatial dependence and association of oak wilt damage was analyzed and compared using mathematical variogram models and spatial analysis by distance indices (SADIE). Variogram model ranges were 179~368m in Sector A and 634~1073m in Sector B, respectively. The damage levels of all trees in each sector were indicated as aggregated distribution by aggregation indices of SADIE (Ia > 1). Each damage level pair had strong association in the consecutive orders than in any random order based on the results of SADIE association test. The spatial dependence and association of oak wilt damage levels presented here provide the baseline information necessary to understand and manage oak wilt disease in Korea.

Two cherry tomato plant cultivars (Lycopersicon esculentum Miller, cultivars ‘Koko’ and ‘Pepe’) were supplied with high (395 ppm), medium (266 ppm) and low (199 ppm) concentrations of nitrogen to determine the influence of nitrogen fertilization on development, cultivar preference and honeydew production by greenhouse whiteflies, Trialeurodes vaporariorum (Westwood) (Hemiptera: Aleyrodidae). The nitrogen, protein, andchlorophyll content of tomato leaves were higher in the high nitrogen supplied plants than in the medium or low nitrogen supplied plants, but the sugar content showed an inverse relationship. The developmental times of eggsand nymphs decreased as the nitrogen concentrations increased in both cultivars. The preference of T. vaporariorum was compared by counting the number of eggs deposited on leaves in choice and non-choice tests. In the non-choice test, no significant nitrogen treatment effects were observedbut the upper plant stratum was preferred for egg laying. In the choice test, there were significant main effects of cultivar and nitrogen concentration. T. vaporariorum laid eggs more on leaves of plants with higher nitrogen at the upper stratum. In both experiments, T, vaporariorum preferred the ‘Koko’ cultivar to the ‘Pepe’ cultivar. The honeydew production of T. vaporariorum nymphs increased with decreasing nitrogen treatment concentrations. The largest honeydew production was detected in the ‘Pepe’ cultivar grown at low nitrogen concentration. It is concluded that cultivar ‘Pepe’ had an advantage over ‘Koko’ in term of T. vaporariorum management program in tomato greenhouses.