Rapid assessment of crop damage is essential for successful management of insect pest outbreaks. In this study, we investigated the use of an unmanned aircraft system (UAS) and image analyses to assess an outbreak of the beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), that occurred in soybean fields in South Korea. A rotary-wing UAS was deployed to obtain a series of aerial images over 31 soybean blocks. The images were stitched together to generate composite imagery, followed by image analyses to quantify soybean defoliation. An economic analysis was conducted to compare the cost of the aerial survey with that of a conventional ground survey. The results showed that the aerial survey precisely estimated the defoliation compared to the ground survey, with an estimated defoliation of 78.3% and a range of 22.4–99.8% in the 31 blocks. Moreover, the aerial survey followed by image analyses was found to be more economical than the conventional ground survey when the number of target soybean blocks subject to the survey was more than 15 blocks. Our study clearly demonstrated the effectiveness of using an autonomous UAS and image analysis to conduct a low-cost aerial survey of soybean damage caused by S. exigua outbreaks, which can inform decision-making for S. exigua management.
Determining the spatio-temporal distribution and association of pests and natural enemies would be useful for implementing biological control of pests and could also be used in site-specific pest management. In this study, the spatio-temporal distribution and association of aphids, plant bugs, and natural enemies were assessed in alfalfa fields using geo-statistics and spatial analysis by distance indices (SADIE). Additionally, the effect of alfalfa hay-harvesting on the spatial and temporal distribution of these insects was investigated for the first time. Geostatistical analysis indicated that the degree of dependence (DD) was ≥75% for 11 out of 39, 9 out of 35, 3 out of 12, 10 out of 29, and 2 out of 20 datasets for pea aphid Acyrthosiphon pisum, spotted alfalfa aphid Therioaphis maculata, cowpea aphid Aphis craccivora, alfalfa plant bug Adelphocoris lineolatus, and tarnished plant bug Lygus rugulipennis, respectively. The results also indicated that DD was ≥75% in 7 out of 45, 18 out of 45, and 3 out of 20 datasets for Coccinella septempunctata, Hippodamia variegata, and Pterostichus melanarius, respectively. Harvesting decreased the aggregation of the ladybirds, which resulted in a decrease in the index of aggregation. The geo-statistics results were confirmed by SADIE in 75% of datasets. These results can be used in biological control and site-specific management of aphids and plant bugs in alfalfa fields.
28 September 2016 in Agricultural and Forest Entomology