Callipogon relictus, a natural monument, is an insect whose life cycle was assumed to take more than 5 years in nature. Winter is a very harsh season, but it is known to be a crucial condition for many insects’ growth. However, no information is known about the overwintering condition and its effects on C. relictus. To understand the overwintering effects on the growth of C. relictus, we investigated the growth patterns of its larvae in indoor conditions after chilling treatment. The larvae were induced to dormancy at low temperature (4°C) for two months, and put them into 10°C for two weeks to break dormancy. After awakening, the temperature was increased 15°C, 20°C to 25°C at a time, and the larvae were kept for two weeks at each temperature. The larvae were divided into 3 groups (3rd to 5th instar, 6th to 8th instar, 9th to last instar). Lastly, head width and weight of the larvae were measured every 30 days under 25°C condition, and mortality and deformity were counted as well. The mortality and deformity rates were the highest in the first group, and the rates decreased toward the last group. On the other hands, growth rate appeared opposite to mortality and deformity rate of each larval group.

The fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera: Noctuidae), which is native to tropical and subtropical regions of the Western Hemisphere is now annually arrives in Korea. In this study, we developed loop-mediated isothermal amplification (LAMP) assay, one of the main merits of which is a rapid identification of target species. Five among 11 FAW-specific loci tested successfully provided a consistent reaction when ten FAWs, which were collected from eight localities in four countries were tested, whereas the 13 non-target species were not amplified. To increase in-field applicability of the method all life stages, reaction time, and different periods after death was tested using the quick extracted DNA. Our FAW diagnostic protocol can be completed within 30 min, from the process of extracting genomic DNA from an egg or a 1st instar larva to species determination.

Non-destructive estimation of leaf area is a more efficient and convenient method than leaf excision. Thus, several models predicting leaf area have been developed for various horticultural crops. However, there are limited studies on estimating the leaf area of strawberry plants. In this study, we predicted the leaf areas via nonlinear regression analysis using the leaf lengths and widths of three-compound leaves in five domestic strawberry cultivars (‘Arihyang’, ‘Jukhyang’, ‘Keumsil’, ‘Maehyang’, and ‘Seollhyang’). The coefficient of determination (R2) between the actual and estimated leaf areas varied from 0.923 to 0.973. The R2 value varied for each cultivar; thus, leaf area estimation models must be developed for each cultivar. The leaf areas of the three cultivars ‘Jukhyang’, ‘Seolhyang’, and ‘Maehyang’ could be non-destructively predicted using the model developed in this study, as they had R2 values over 0.96. The cultivars ‘Arihyang’ and ‘Geumsil’ had slightly low R2 values, 0.938 and 0.923, respectively. The leaf area estimation model for each cultivar was coded in Python and is provided in this manuscript. The estimation models developed in this study could be used extensively in other strawberry-related studies.