نوع مقاله : مقاله پژوهشی
نویسندگان
1 بخش تحقیقات هوشمندسازی کشاورزی - موسسه تحقیقات فنی و مهندسی کشاورزی - سازمان تحقیقات، آموزش و ترویج کشاورزی - کرج - ایران.
2 بخش تحقیقات حشرهشناسی کشاورزی - موسسه تحقیقات گیاهپزشکی کشور - سازمان تحقیقات، آموزش و ترویج کشاورزی - تهران - ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Introduction
The apple codling moth, Cydia pomonella (Lep.: Tortricidae), is one of the key pests of the apple trees. This pest attacks apple trees in significant numbers every year, causing damage that always exceeds the level of economic loss. Therefore, apple codling moth forecasting is very important to determine the most appropriate time for spraying to control the pest, which plays a major role in apple orchard management. Using modern and smart methods for pest forecasting is very important to succeed in chemical control and reducing the number of spraying times in the orchard. Internet of Things (IoT) technology and its smart solutions, based on the basic principles of sensor networks, can enable smart environments and data-based decision-making. In this research, a smart system based on the Internet of Things and a Wireless Sensor Network (WSN) technologies was developed for forecasting of the apple codling moth in the orchard. The effectiveness of using the designed system was also investigated in an apple orchard located in Tehran province (Damavand County).
Materials and Methods
A wireless sensor node was used to collect on-line data of the ambient temperature in the orchard. The data was transported to the gateway through LoRa radio protocol, a long-range and low-power protocol for the Internet of Things. They were sent from the gateway to the network server and then made available to the software designed for the system. The main heart of the software for decision-making was the apple codling moth forecasting model, which was determined based on the hour-degree Celsius. For this purpose, the biofix of apple codling moth pest was determined using pheromone traps and the ambient temperature was recorded hourly using the wireless sensor node installed in the orchard to calculate the total effective environmental temperature. Based on the temperature data and using a phenological forecasting model, the most appropriate spraying time for controlling the apple codling moth was determined and included in the designed software of the system. A dashboard was also designed to display the results. The efficiency of the designed smart system and its forecasting model for controlling apple codling moth pest in the orchard was evaluated over two years.
Results and Discussion
The Internet of Things-based smart system designed for apple codling moth forecasting pest in the orchard could announce the appropriate time for spraying, along with the type and dosage of the pesticide. This smart system has excellent reliability in data transmission with zero data loss and has excellent accuracy (100%) in terms of timely warning announcements. Evaluations showed that the designed system reduces the damage caused by the apple codling moth pest by reducing the number of spraying times from four to two, which will increase the yield and improve the quality of the product. The results of the two-year investigation indicated that the damage caused by the apple codling moth pest at the harvest time in the control trees was more than 70% greater than in trees that were sprayed based on the forecasting model of the designed system. This is even though according to the orchard manager's statements, the average number of spraying times in previous years, based on predictions made with pheromone traps, has been four, and the damage caused by the codling moth has exceeded the amount estimated in this research. Spraying times for controlling the apple codling moth was reduced to twice a year in the orchard by using the smart system developed based on the hour-degree Celsius forecasting model.
Conclusion
Given the high efficiency of the smart system designed based on the determined forecasting model in controlling the apple codling moth pest and reducing the use and costs of pesticides by 50%, and consequently a 50% reduction in labor costs and pesticide spraying equipment required for each time of spraying in the orchard, the use of this Internet of Things-based system is recommended for forecasting of this pest in apple orchards. Reducing the risk of contamination for the workers who spray pesticides and reducing the amount of pesticide residue in the product are indirect positive effects of using the designed smart system. Future work in the continuation of this research is to pay attention to making the biofix determination process smarter by developing smart traps that can be connected to the system's Wireless Sensor Network.
Acknowledgment
We would like to thank Future Wave Ultratech Company for the cooperation and providing the necessary equipment and infrastructure to conduct this research. We are also grateful to the manager of the apple orchard for his cooperation.
کلیدواژهها [English]
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