• Journal of Drive and Control
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• v.21 no.2
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• pp.53-64
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• 2024

Global population growth has resulted in an increased demand for food production. Simultaneously, aging rural communities have led to a decrease in the workforce, thereby increasing the demand for automation in agriculture. Drones are particularly useful for unmanned pest control fields. However, the current method of uniform spraying leads to environmental damage due to overuse of pesticides and drift by wind. To address this issue, it is necessary to enhance spraying performance through precise performance evaluation. Therefore, as a foundational study aimed at optimizing drone-based pest control technologies, this research evaluated water-sensitive paper (WSP) via density map estimation using convolutional neural networks (CNN) with a encoder-decoder structure. To achieve more accurate estimation, this study implemented multi-task learning, incorporating an additional classifier for image segmentation alongside the density map estimation classifier. The proposed model in this study resulted in a R-squared (R²) of 0.976 for coverage area in the evaluation data set, demonstrating satisfactory performance in evaluating WSP at various density levels. Further research is needed to improve the accuracy of spray result estimations and develop a real-time assessment technology in the field.

• Journal of Drive and Control
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• v.20 no.3
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• pp.25-34
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• 2023

In this study, we conducted a research on optimizing the spraying performance of agricultural drones and predicted the spraying performance in various flight conditions using the multi-layer perceptron (MLP). Data was collected using a test device for pesticide spraying performance according to the water sensitive paper (WSP) evaluation. MLP training involved supervised learning to achieve a coefficient of variation (CV), which indicates the degree of uniform spraying. The performance evaluation was conducted using R-squared (R²), the test samples showed an R² of 0.80. The results of this study showed that drone spraying performance can be predicted under various flight environments. In addition, the correlation analysis between flight conditions and predicted spraying performance will be useful for further research on optimizing the spraying performance of agricultural drones.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.137-150
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• 1997

To investigate the feasibility of a boom sprayer in the paddy field, an experimental boom sprayer for both broadcast and directed spraying to the lower part of rice plants was developed. The droplet deposition characteristics of the boom sprayers were experimentally compared to those of power sprayer. Water sensitive papers(WSP) and a machine vision system were used to evaluate the coverage rate and droplet density. It was shown that the broadcast application by the boom sprayer was the best coverage among the tested sprayers. Coverage tate and droplet density were affected by the distance between nozzles and the sprayer ground speed, The best result was obtained when the distance of 30cm and the speed of 1.7km/hr. The directed application showed inconsistency in overall droplet distribution. The inconsistency was judged to be caused by conflict between plants and boom extenders. The power sprayer showed a very wide range of droplet size distribution, relatively larger droplets and inconsistency in cove The power sprayer was judged to be inadequate for the low-volume precision application because of inconsistency in performance and difficulty in adjusting the spraying rate. Based on the droplet coverage characteristics, it was concluded that the self-propelled boom sprayer for the broadcast application was feasible for an alternative to the power sprayer in case of low volume, precision application in paddy condition.

• Korean journal of applied entomology
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• v.60 no.2
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• pp.229-234
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• 2021

This study investigated spray patterns and coverage generated by three types of commercial nozzles for spraying pesticides with Unmanned Aerial Vehicles (UAVs) using a multi-copter. Flufenoxuron+metaflumizone SC and bifenthrin EC were sprayed. The falling particles of the spraying agent were measured using WSP (Water and oil Sensitive Paper) and the coverage was determined. The results showed that the uniformity of falling particles was different according to the difference in wind strength, and there was no difference for different formulations. The injection amount for each nozzle was found to be different from the official information provided by the manufacturers. These results could be used to establish guidelines for the control of UAVs and pesticide registration testing.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.350-357
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• 2014

We studied on pesticide residue and pest control effect when using various types of sprayers on paprika cultivation. Additionally, a test was conducted to optimize chemical content per unit area in condition of optimum pest control. Two types of sprayer were tested (three times) on paprika cultivation which was divided into seven sections. Blind spots were also examined using a water sensitive paper when spraying chemical pesticide, remote controlled sprayer were confirmed to be not effective in terms of its spraying capacity. However, a U-shaped sprayer was confirmed that it sprayed enough on all the parts of a plant in green house including the blind spots. Additionally, it does not exceed the minimum residue limits on the all parts of pesticides residue conditions. When using remote controlled sprayer, water sensitive paper were changed to blue color (82.5% and 81.2%) in terms of controlling Bemisia tabaci and Aphis gossypii based on the two spraying manners. 53.0% and 42.6% of control effect were shown on the fair parts of the plants. However, on the poor parts on which pesticides were not well-sprayed, thus, not-remained, more number of pests increased. Meanwhile, on farming that only one type of pesticide has been used, resistance pests present with very low control effect, even though sufficient amount of pesticide was well-sprayed. On the test of the optimum amount of spraying per a unit area, which shows no differences in the two cases of using 5L and 2.5L of chemical pesticides on 9 plants of paprika that has 81.8% and 84.5% control effect, respectively.