{"title":"Biofeedback-Based Closed-Loop Phytoactuation in Vertical Farming and Controlled-Environment Agriculture.","authors":"Serge Kernbach","doi":"10.3390/biomimetics9100640","DOIUrl":null,"url":null,"abstract":"<p><p>This work focuses on biohybrid systems-plants with biosensors and actuating mechanisms that enhance the ability of biological organisms to control environmental parameters, to optimize growth conditions or to cope with stress factors. Biofeedback-based phytoactuation represents the next step of development in hydroponics, vertical farming and controlled-environment agriculture. The sensing part of the discussed approach uses (electro)physiological sensors. The hydrodynamics of fluid transport systems, estimated electrochemically, is compared with sap flow data provided by heat-based methods. In vivo impedance spectroscopy enables the discrimination of water, nutrient and photosynthates in the plant stem. Additionally to plant physiology, the system measures several air/soil and environmental parameters. The actuating part includes a multi-channel power module to control phytolight, irrigation, fertilization and air/water preparation. We demonstrate several tested in situ applications of a closed-loop control based on real-time biofeedback. In vertical farming, this is used to optimize energy and water consumption, reduce growth time and detect stress. Biofeedback was able to reduce the microgreen production cycle from 7 days to 4-5 days and the production of wheatgrass from 10 days to 7-8 days, and, in combination with biofeedback-based irrigation, a 30% increase in pea biomass was achieved. Its energy optimization can reach 25-30%. In environmental monitoring, the system performs the biological monitoring of environmental pollution (a low concentration of O<sub>3</sub>) with tomato and tobacco plants. In AI research, a complex exploration of biological organisms, and in particular the adaptation mechanisms of circadian clocks to changing environments, has been shown. This paper introduces a phytosensor system, describes its electrochemical measurements and discusses its tested applications.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"9 10","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11506309/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomimetics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/biomimetics9100640","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This work focuses on biohybrid systems-plants with biosensors and actuating mechanisms that enhance the ability of biological organisms to control environmental parameters, to optimize growth conditions or to cope with stress factors. Biofeedback-based phytoactuation represents the next step of development in hydroponics, vertical farming and controlled-environment agriculture. The sensing part of the discussed approach uses (electro)physiological sensors. The hydrodynamics of fluid transport systems, estimated electrochemically, is compared with sap flow data provided by heat-based methods. In vivo impedance spectroscopy enables the discrimination of water, nutrient and photosynthates in the plant stem. Additionally to plant physiology, the system measures several air/soil and environmental parameters. The actuating part includes a multi-channel power module to control phytolight, irrigation, fertilization and air/water preparation. We demonstrate several tested in situ applications of a closed-loop control based on real-time biofeedback. In vertical farming, this is used to optimize energy and water consumption, reduce growth time and detect stress. Biofeedback was able to reduce the microgreen production cycle from 7 days to 4-5 days and the production of wheatgrass from 10 days to 7-8 days, and, in combination with biofeedback-based irrigation, a 30% increase in pea biomass was achieved. Its energy optimization can reach 25-30%. In environmental monitoring, the system performs the biological monitoring of environmental pollution (a low concentration of O3) with tomato and tobacco plants. In AI research, a complex exploration of biological organisms, and in particular the adaptation mechanisms of circadian clocks to changing environments, has been shown. This paper introduces a phytosensor system, describes its electrochemical measurements and discusses its tested applications.