Spatial Analysis of Environment Factors for Modeling Plant Hopper Potential Risk Prediction

Abstract

Agricultural insect pests reduce crop productivity, causing a gap between global food demand and production. Early detection and early response can improve pest control efficiency. The study aimed to investigate the spatial correlations between Brown Plant Hopper (BPH) occurrence and affected factors using field data collection in Can Tho City, Vietnam. The data on cultivation practices and meteorological conditions at 120 sites every week during the rice cropping season of 2016–2017 were collected to find the correlation between the occurrence frequency and density of BHP. Besides, GIS and spatial interpolation were applied to assess the current status of harmful situations, predict the impact trends of crop pests or diseases in space and time to serve a community's needs, and forecast plant protection. As a result, in the 2nd rice cropping stage, the population of brown planthoppers were found to be highly significantly influenced by factors: (1) planthopper age, (2) natural enemy density, (3) air temperature, (4) field water level, and (5) number of leaves, which is highly positively correlated with brown hopper density. There is a lower correlation between leaf color code (6) and air humidity (7) and a negative correlation between pesticides used (8). The variables of rice leaf color code (6) and air humidity (7) correlate with the BHP population, although the field water level (4) and leaf count (5) do not correlate for the whole crop. It can be used to predict the changing trend of BHP in rice fields. However, the factors influencing the brown planthopper would determine the prognosis's accuracy.

Keywords

• geographic information system (gis)
• potential risk
• geostatistic
• interpolation
• brown plant hopper