## 4 Conclusions  
The number of farmers using spraying drones is increasing owing to its various advantages. However, spray drift has been a challenge in aerial spraying systems. To address this issue, an AI nozzle with an effective drift reduction capacity was used. However, there are few research works that installed AI nozzles to drones and analyzed their effectiveness. In this study, AI and flat fan nozzles were installed on drones to evaluate their spray performance. Moreover, the pest control performance was also evaluated. The deposition and penetration ratios were measured using a flat fan nozzle and an AI nozzle. Pest control efficacy was analyzed based on the type of target crops (rice and soybean). The crops used were rice and soybean. The study results are listed as follows:  
1. For both crops, coverage was more than 2.3 times higher when using AI nozzles compared with that when using flat fan nozzles. The larger size droplets of the AI nozzle apparently reduced drift, which was attributed to increased deposition of the sprayed droplets. A two-way analysis of variance showed that the effect of the nozzle on the coverage was significant (\(p<0.05\)). For the effect of the plant on coverages, there was no significant difference. 2. The penetration ratios of both nozzles were analyzed. A two-way analysis of variance showed no significant difference due to the treatment method. It seems that weather conditions may have affected the results of the experiment. Previous studies of vertically growing maize, which has a similar morphology to rice, have yielded different results than this study, and additional analysis is required. 3. The crop production rate was investigated. [PERSON]'s test showed no significant difference between the experimental groups. Environmental and genetic factors seem to have influenced production. Also, it seemed that the decreased surface area reduced the effectiveness. 4. For the control efficacy, [PERSON]'s test showed no significant difference between the experimental groups. As the results of the production investigation, similar PR values between treatments made no difference in control efficacy. 5. When measuring aerial spray performance, penetration rates must be measured at the same time. The analysis of the aforementioned results showed that using AI nozzles instead of flat fan nozzles for aerial pest control increased the droplet deposition of the sprayed droplets. However, there was no significant difference in production and control efficacy. Thus, this study showed that aerial control with AI nozzles delivers more spray droplets to the field and the effect on control efficacy needs further study. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Damaged Leaf Ratio**} & \multicolumn{2}{c}{**Damaged Grain Ratio**} \\ \hline  & **Disease (\%)** & **Pest (\%)** & **Disease (\%)** & **Pest (\%)** \\ \hline AI nozzle & 0.5a & 11.8a & 2.2a & 3.6a \\ Flat fan nozzle & 0.7a & 15.9a & 2.4a & 4.7a \\ Control & 2.3b & 49.7b & 8.0b & 18.4b \\ \hline \hline \end{tabular} a,b: the same letter note indicates no significant difference at the \(p=0.05\) significant level, different letters indicate significant differences at \(p=0.05\) significant level.  
\end{table} 
Table 7: Control efficacy of soybean after spraying. In this study, a single flight condition (2 m/s forward speed at 3 m height) was used to compare the effect of nozzle type on control performance. In the future, it is necessary to conduct experiments under various flight conditions and/or to compare UAV loadings over time to drift. However, since it is difficult to control various conditions in the field, the primary analysis is performed through Computational Fluid Dynamic (CFD) simulations and supplemented with field experiments. Conceptualization, C.-G.L. and S.-H.Y. ; methodology, C.-G.L. and S.-H.Y. ; software, C.-G.L. ; validation, C.-G.L., Y.K. and S.-H.Y. ; formal analysis, C.-G.L. and Y.K. ; investigation, C.-G.L. and Y.K. ; resources, S.-H.Y. ; data curation, C.-G.L.