Stefano Calvo, Mattia Barezzi, D. Demarchi, U. Garlando
{"title":"基于茎电阻抗的植物水分胁迫和生物活性体内近端监测系统","authors":"Stefano Calvo, Mattia Barezzi, D. Demarchi, U. Garlando","doi":"10.1109/IWASI58316.2023.10164553","DOIUrl":null,"url":null,"abstract":"Population growth and global warming are the main threats to food production. Food security, producing enough food for the entire population, is becoming harder, and new strategies must be applied. Smart agriculture tackles this problem by integrating field sensors and data with the farmers’ knowledge to increase crop yield and reduce resource waste.This paper proposes a system to monitor the plant water stress status. This system monitors the plant directly and does not rely on environmental sensors. Acquired data are sent to a remote server thanks to LoRa communication. The designed system is low-power and relies on a single battery with more than five years of expected lifetime. The system monitors the trunk electrical impedance of plants thanks to a relaxation oscillator with a portion of the trunk in the feedback loop. This way, changes in the impedance are reflected in changes in the oscillator frequency.Two systems were installed directly in the fields and connected to apple trees. Statistical analyses were performed on the acquired data. The correlation between the trunk frequency values and the soil water potential is above 75% for both plants.The proposed system is low-power and low-cost and could be directly adopted in the fields. It can detect the water status of plants directly, avoiding environmental sensors.","PeriodicalId":261827,"journal":{"name":"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In-vivo proximal monitoring system for plant water stress and biological activity based on stem electrical impedance\",\"authors\":\"Stefano Calvo, Mattia Barezzi, D. Demarchi, U. Garlando\",\"doi\":\"10.1109/IWASI58316.2023.10164553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Population growth and global warming are the main threats to food production. Food security, producing enough food for the entire population, is becoming harder, and new strategies must be applied. Smart agriculture tackles this problem by integrating field sensors and data with the farmers’ knowledge to increase crop yield and reduce resource waste.This paper proposes a system to monitor the plant water stress status. This system monitors the plant directly and does not rely on environmental sensors. Acquired data are sent to a remote server thanks to LoRa communication. The designed system is low-power and relies on a single battery with more than five years of expected lifetime. The system monitors the trunk electrical impedance of plants thanks to a relaxation oscillator with a portion of the trunk in the feedback loop. This way, changes in the impedance are reflected in changes in the oscillator frequency.Two systems were installed directly in the fields and connected to apple trees. Statistical analyses were performed on the acquired data. The correlation between the trunk frequency values and the soil water potential is above 75% for both plants.The proposed system is low-power and low-cost and could be directly adopted in the fields. It can detect the water status of plants directly, avoiding environmental sensors.\",\"PeriodicalId\":261827,\"journal\":{\"name\":\"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWASI58316.2023.10164553\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWASI58316.2023.10164553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In-vivo proximal monitoring system for plant water stress and biological activity based on stem electrical impedance
Population growth and global warming are the main threats to food production. Food security, producing enough food for the entire population, is becoming harder, and new strategies must be applied. Smart agriculture tackles this problem by integrating field sensors and data with the farmers’ knowledge to increase crop yield and reduce resource waste.This paper proposes a system to monitor the plant water stress status. This system monitors the plant directly and does not rely on environmental sensors. Acquired data are sent to a remote server thanks to LoRa communication. The designed system is low-power and relies on a single battery with more than five years of expected lifetime. The system monitors the trunk electrical impedance of plants thanks to a relaxation oscillator with a portion of the trunk in the feedback loop. This way, changes in the impedance are reflected in changes in the oscillator frequency.Two systems were installed directly in the fields and connected to apple trees. Statistical analyses were performed on the acquired data. The correlation between the trunk frequency values and the soil water potential is above 75% for both plants.The proposed system is low-power and low-cost and could be directly adopted in the fields. It can detect the water status of plants directly, avoiding environmental sensors.