Progress 06/01/23 to 05/31/24
Outputs
Target Audience:Soil science research community, agricultural engineering research community, and the agricultural community Changes/Problems:As mentioned in the previous section of "What do you plan to do during the next reporting period to accomplish the goals", we are requesting a 2nd no-cost extension for this project. The current end date is May 31, 2024. The requested new end date of the project is May 31, 2025. The project relies on integrating transpiration and N sensors to validate the concept successfully. Although the reliability of the transpiration sensors has improved, there is a performance inconsistency issue that needs to be addressed for the completion of this task. Addressing this issue requires an extension of our timeline.Additionally,one graduate student recently graduated, and another nearing graduation in the Spring semester, dedicating significant time to their thesis. Therefore, the actual time dedicated to this project fell short of previous projections. This shortfall has also impacted our progress on integrating sensor data, further justifying the need for more time. Due to these changes, an additional one-year time beyond the current project expiration is essential to ensure the completion of all project objectives. Our plan: (1)June 1, 2024 - Septemeber 30, 2024:To complete the sensor task:Conduct another round of sensor installation to collect data.The focus will be on deploying water sensors and nitrate sensors. Graduate and undergraduate students will take on the role of sensor installation. (2)June 1, 2024 - December 31, 2024:To complete the data analytics task: Optimize control and analytics tools formergingdiverse sensor data.This unified data can empower us to predict changes in plant and soil nitrogen, along with moisture levels. (3)January 1, 2025- May 31, 2025:To complete the cyber-physical system combining sensors and data analytics tools.This can help us leveragehardware and software to understand data and enhance decision-making for irrigation and fertigation strategies. (4)April 1, 2024- May 31, 2025:To complete data analysis and paper writing for wrapping up the project. What opportunities for training and professional development has the project provided?The project provided research training opportunities to students from computational mathematics, electrical engineering, mechanical engineering, soil sciences and modeling areas.In addition, two postdoctoral researchers received training; one in agronomy with a focus on process-based models for agricultural systems, and the other in engineering. A couple of students previously earned their Ph.D. degrees, concentrating on the innovation of water and nitrate detection technologies. Anothertwo graduate students are expected to earn their Ph.D. degrees this year. Many students went on to pursue engineering careers in the electronic deviceindustry.Furthermore, eight undergraduate students were involved in the project, where they gained crucial experience in testing and assembling sensors, as well as in sensor installation. This practical experience helped them enhance their skills and lay a strong foundation for their career paths. The research program significantly impacted all those involved by providing them with hands-on experience and insight into device testing and creation. Consequently, participants are now well-equipped to thrive in their careers in electrical engineering, agricultural engineering, sensor technology, and manufacturing. How have the results been disseminated to communities of interest?The team disseminated the research results through seven peer-reviewed journal papers, including: (#1) Chen, Y., Tang, Z., Zhu, Y., Castellano, M.J. and Dong, L., 2021. Miniature Multi-Ion Sensor Integrated With Artificial Neural Network. IEEE Sensors Journal, 21(22), pp.25606-25615. (#2) Yin, S., Ibrahim, H., Schnable, P.S., Castellano, M.J. and Dong, L., A FieldDeployable, Wearable Leaf Sensor for Continuous Monitoring of Vapor-Pressure Deficit. Advanced Materials Technologies, p.2001246, 2021. doi.org/10.1002/admt.202001246. (#3) M. T. Rahman, R. R. Khan, Y. Tian, H. Ibrahim, and L. Dong, "High-sensitivity and room-temperature nitrous oxide sensor using Au nanoparticles decorated MoS2," IEEE Sensors Journal. 23, 18994-19001 (2023) (#4) Ibrahim, H., Moru, S., Schnable, P. and Dong, L., 2022. Wearable Plant Sensor for In Situ Monitoring of Volatile Organic Compound Emissions from Crops. ACS sensors, 7(8), pp.2293-2302. (#5) Ibrahim, H., Yin, S., Moru, S., Zhu, Y., Castellano, M.J. and Dong, L., 2022. In Planta Nitrate Sensor Using a Photosensitive Epoxy Bioresin. ACS Applied Materials & Interfaces, 14(22), pp.25949-25961. (#6)S. Yin and L. Dong, Plant tattoo sensor array for leaf relative water content, surface temperature, and bioelectric potential monitoring, Advanced Materials Technologies (accepted for publication, 2024) (#7)N. Singh, R. R. Khan, W. Xu, S. A. Whitham, and L. Dong, "Plant virus sensor for rapid detection of bean pod mottle virus using virus-specific nanocavities," ACS Sensors, 8(10) 3902-3913 (2023) 2. The team disseminated the research results through two Ph.D. dissertations, including: (#1) Chen, Yuncong. "In-situ soil water potential sensor and nutrient sensor." Iowa State University, 2021. (#2) Hussam Ibrahim, Electrochemical sensors for nutrients, volatile organic compounds, and viral pathogens, Iowa State University. 2022. 3. The team disseminated the research results through several invited talks by PIs.Topics: Smart sensors to improve food security and environmental sustainability. Locations and places:University of Notre Dame, February 2023; University of California, Merced, March 2023; University of Georgia, March 2023.? What do you plan to do during the next reporting period to accomplish the goals?We are requesting a 2nd no-cost extension for this project. The current end date is May 31, 2024. The requested new end date is May 31, 2025. Below is aprojected timetable to complete the portionsof the project for which the extension (June 1, 2024 - May 31, 2025) is being requested June 1, 2024 - Septemeber 30, 2024:To complete the sensor task:Conduct another round of sensor installation to collect data. The focus will be on deploying water sensors and nitrate sensors. Graduate and undergraduate students will take on the role of sensor installation. June 1, 2024 - December 31, 2024:To complete the data analytics task: Optimize control and analytics tools formergingdiverse sensor data. This unified data can empower us to predict changes in plant and soil nitrogen, along with moisture levels. January 1, 2025- May 31, 2025:To complete the cyber-physical system combining sensors and data analytics tools. This can help us leveragehardware and software to understand data and enhance decision-making for irrigation and fertigation strategies. April 1, 2024- May 31, 2025:To complete data analysis and paper writing for wrapping up the project.
Impacts
What was accomplished under these goals?
A critical issue with poor contact between soil particlesand embedded nitrate sensors has been alleviated. We introduceda nanofibrous mat designed to absorb and transport soil water to a soil nutrient sensor surface, thereby enhancing the continuous detection of nitrate ions in the soil. Created through electrospinning, this mat exhibitedhigh hydrophilicity for efficient water absorption and notable chemical corrosion resistance. Its porous design facilitatedwater infiltration while blocking direct contact of the sensor surface with soil particles. Applied to an ion-selective electrode soil nitrate sensor, the mat maintainedthe moisture at the sensor surface, improving the measurement continuity of the sensor under varying soil moisture levels.The composition of the nanofibrous mat includedpolysulfone (PSF), polymethylmethacrylate (PMMA), and polyvinyl alcohol (PVA). We demonstrated the efficacy of the obtained PVA-PSF-PMMA nanofibrous mat in improving water absorption and transport to the ISE nitrate sensor, and in preventing soil particle contamination of the sensor surface. We compared the performance of the sensors with and without the nanofibrous mat. Tests were conducted on various soil samples differing in water content under laboratory and field conditions. These tests validated the capability of the mat to ensure reliable, continuous soil measurements.The performance evaluation of the soil nitrate sensors with and without PVA/PSF-PMMA mat was conducted in the field at three locations. During a continuous test period from August 17 to October 13, 2023, the PVA/PSF-PMMA mat-wrapped sensors monitored variations in nitrate levels more accurately than the pristine sensors. Lab-based validation was employed to detect nitrate in collected soil samples from the field. The laboratory measurements for the collected samples provided analytically consistent results with the responses of both the sensors without and with the PVA/PSF-PMMA mat. However, the sensors without the PVA/PSF-PMMA mat exhibited delayed saturation or higher noise signals at each field location, particularly when the soil has low volumetric water content. The drawback was reduced by introducing the hydrophilic PVA/PSF-PMMA mat, owing to the mat allowing water extraction from soil pores and eliminating direct contact of soil particles with the sensorsurface. It is noteworthy that our PVA/PSF-PMMA mat-integrated sensors could perform for a longer duration compared to the previously reported nitrate sensors.We also examined 6 pairs of salt extract and sensor-based measurements, both with and without the PVA/PSF-PMMA membrane, at field location 2. The slopes of the linear regression models for the sensors with and without the mat differed from 1. With the mat, the sensor linear equation is y = 0.8577x - 4.8137, with an r2 value of 0.85. This slightly lower slope value suggests that the mat may absorb some NO3- during delivery into the sensor surface. Conversely, when there is no mat on the sensor, the linear equation becomes y = 0.1270x - 16.9040, with an r2 value of 0.12. This very low r2 value indicates that the pristine NO3- sensor fails to adequately detect the relationship between the variables due to the hydrophobic sensor surface and the adsorption of negatively charged soil particles.Furthermore, a time series analysis revealed lab-validated and sensor-based measurements, with and without the PVA/PSF-PMMA membrane, conducted at variable water content levels at field location 2. Soil water content ranged from 12% at its lowest to 25% at its highest over the observed period. Overall, these results suggest that the hydrophilic mat facilitates the transport of soil water containing dissolved nitrate for diffusion to the nitrate sensor surface under field conditions. The mat remained structurally intact even after the sensors were continuously inserted into the field for 57 days, as evidenced by the significantly more soil particles attached to the surface of the mat-wrapped sensors than the counterpart without the mat. For our water content tattoo sensors,we made it possible to monitorimpedance changes of the sensor once every minute. After the irrigation, the relative water content increased, prompting the plants to transpire and release water from the leaf through the stomata. An additional amount of water was applied shortly after the first irrigation. Possibly because of the overwatering condition, there was a minimal impact on the relative water content. As a result, only a small change in the RH of the surrounding air was observed. At night there wasa decline in the relative water content, attributed to reduced photosynthesis and transpiration, as indicated by the lowered RH in the air surrounding the plant. Detailed analysis of the impedance changes when the light was turned on and off revealed meaningful dynamics. Specifically, it was noticed that there was a lag of about 5 minutes following the light off, attributed to the gradual closing process of the stomata. On the contrary, when the light was back on, the leaf's relative water content and the RH near the leaf increased, as the stomata reopened to facilitate transpiration. This reaction to light features the capacity of the plant to manage photosynthesis and gas exchange in response to changing light conditions. In the 2023 field experiment focusing on the deployment of water sensors, we found that around 65% of these sensors successfully provided valuable data for the duration of nearly two and a half months, demonstrating their resilience and operational efficiency in field conditions. These sensors effectively monitored leaf surface relative humidity and temperature, offering critical insights into the environmental conditions. However, the experiment also showed challenges impacting sensor performance. A notable 25% of the sensors encountered severe operational difficulties, functioning for merely a week or less. These issues were primarily attributed to an overheating problem in the circuitry of the on-chip sensor within the datalogger. This overheating issue points to a critical design flaw that needs addressing to enhance sensor longevity and reliability. Additionally, a small fraction of sensors experienced power supply interruptions due to inconsistencies with the solar panel energy source. Despite these challenges, the sensors demonstrated an improved level of operational integrity over a span of two months. This year the use of cellular wireless transmission capabilities in several sensors aimed to improve data transmission reliability. Yet, ensuring a stable cellular connection emerged as a critical challenge, indicating the need for further optimization of wireless communication protocols. This mixed success highlighted the importance of addressing both the technical and environmental challenges field sensors face. Enhancing circuit design to prevent overheating, improving power management to handle environmental triggers effectively, and stabilizing cellular connections are key areas. By overcoming these challenges, we can significantly improve the performance and reliability of field sensors, making them more effective tools for environmental monitoring and data collection.
Publications
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2024
Citation:
S. Yin and L. Dong, Plant tattoo sensor array for leaf relative water content, surface temperature, and bioelectric potential monitoring, Advanced Materials Technologies (in press)
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Singh, N., Khan, R.R., Xu, W., Whitham, S.A. and Dong, L., 2023. Plant Virus Sensor for the Rapid Detection of Bean Pod Mottle Virus Using Virus-Specific Nanocavities. ACS sensors, 8(10), pp.3902-3913.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Rahman, M.T., Khan, R.R., Tian, Y., Ibrahim, H. and Dong, L., 2023. High-sensitivity and room-temperature nitrous oxide sensor using Au nanoparticles-decorated MoS 2. IEEE Sensors Journal, 23(17), pp. 18994-19001
|
Progress 06/01/22 to 05/31/23
Outputs
Target Audience:Soil science research community, agricultural engineering research community, and the agricultural community. Changes/Problems:The USDA has recently approved a no-cost extension for this project, extending its duration by another year. Due to the recent graduation of two students involved, the actual time they were able to dedicate to the project was significantly less than originally anticipated. As a result, our progress was impacted. Fortunately, with the granted extension, we have an opportunity to address these challenges effectively without altering the project's scope. Two new students will be joiningthe team in Fall 2023, bringing assistance in tackling these issues. What opportunities for training and professional development has the project provided?The project aimed to impart scientific and professional training to several students across various disciplines. Specifically, six graduate students, specializing in electrical engineering and sensor development, sensor networks, agronomy, and computational mathematics were among the beneficiaries. Additionally, one postdocin agronomy, working on agricultural systems process-based models, and the other postdoc in engineering also received scientific training through this project. Two engineering students successfully obtained their Ph.D. degrees. Their primary focus was on the development of water and nitrate sensors. Leveraging the expertise gained from this program at Iowa State University, both of these graduates secured employment as engineers in the industry, specializing in flexible electronics and semiconductor devices. Furthermore, eight undergraduate researchers actively participated in the project, gaining invaluable experience in sensor testing and assembly, and sensor installation. These hands-on opportunities allowed them to grow and develop their skills, setting a solid foundation for their future careers. Notably, one of these undergraduate researchers is now employed at a start-up company in Iowa, where he focuses on developing agricultural sensors and measurement systems for water and nitrate monitoring. Overall, the research program had a profound impact on all participants, offering them real-world experience and exposure to various aspects of device testing and fabrication. As a result, they are now better prepared to excel in their respective fields, including electrical engineering, agricultural engineering, sensor engineering, and manufacturing How have the results been disseminated to communities of interest?1. The team disseminated the research results through five peer-reviewed journal papers, including (#1) Chen, Y., Tang, Z., Zhu, Y., Castellano, M.J. and Dong, L., 2021. Miniature Multi-Ion Sensor Integrated With Artificial Neural Network. IEEE Sensors Journal, 21(22), pp.25606-25615. (#2)Yin, S., Ibrahim, H., Schnable, P.S., Castellano, M.J. and Dong, L., A Field-Deployable, Wearable Leaf Sensor for Continuous Monitoring of Vapor-Pressure Deficit. Advanced Materials Technologies, p.2001246, 2021. doi.org/10.1002/admt.202001246. (#3)Md Tawabur Rahman, Raufur Rahman Khan, Yang Tian, Hussam Ibrahim, and Liang Dong, 2023. High-sensitivity and room-temperature nitrous oxide sensor using Au nanoparticles-decorated MoS2, IEEE Sensors Journal, DOI: 10.1109/JSEN.2023.3296504. (#4)Ibrahim, H., Moru, S., Schnable, P. and Dong, L., 2022. Wearable Plant Sensor for In Situ Monitoring of Volatile Organic Compound Emissions from Crops. ACS sensors, 7(8), pp.2293-2302. (#5)Ibrahim, H., Yin, S., Moru, S., Zhu, Y., Castellano, M.J. and Dong, L., 2022. In Planta Nitrate Sensor Using a Photosensitive Epoxy Bioresin. ACS Applied Materials & Interfaces, 14(22), pp.25949-25961. 2. The team disseminated the research results through two Ph.D. thesises, including(#1) Chen, Yuncong. "In-situ soil water potential sensor and nutrient sensor." Iowa State University, 2021. (#2)Hussam Ibrahim, Electrochemical sensors for nutrients, volatile organic compounds and viral pathogens, Iowa State University. 2022. 3. The teamdisseminated the research results through several invited talks given by PIs. What do you plan to do during the next reporting period to accomplish the goals?We plan to continue developing control and analytics tools for the integration of various sensor data. This integration will enable us to make accurate predictions regarding the temporal and spatial fluctuations in plant and soil nitrogen as well as water content. Our primary objective is to utilize this valuable data to offer insights for decision-making concerning irrigation and fertigation processes. Moreover, our commitment extends to providing education and workforce development opportunities.Through these efforts, we aim to strengthen the graduate program in sustainable agriculture while actively encouraging the enrollment of underrepresented minority groups and women students. Furthermore, we are dedicated to sharing our knowledge with the wider public to promote awareness and understanding in sustainable agriculture practices.
Impacts
What was accomplished under these goals?
A novel and multifunctional plant sensor was recently developed and put into operation, specifically designed to provide real-time data about parameters such as leaf water content, relative humidity on leaf surfaces, and temperature. Traditional sensing technologies often rely on adhesives or substrates to anchor and support the sensing components. However, these can potentially inhibit the growth of the plants being monitored and are incapable of facilitating uninterrupted, long-term measurements.In contrast, our multifunctional plant tattoo sensing array, based on a gold thin film, offers a multitude of advantages for concurrently monitoring several parameters including water content, temperature, and bioelectric potential. The innovative sensing array is fabricated on an ultra-thin PET film using a simple cut-and-paste method, and then gently transferred onto the leaf surface without the need for any chemical adhesives. This approach ensures excellent conformity and minimal weight of the sensor, offering noninvasive properties and good gas permeability for long-term monitoring. The sensing elements facilitate extended measurement of parameters related to essential plant functions such as photosynthesis and transpiration. This critical information aids in the efficient management of water resources. Comprehensive long-term measurements of the multifunctional sensor were carried out. As part of this, the sensors were affixed to a maize leaf and irrigation was administered twice, with the objective of observing the plant's responses and potential fluctuations in leaf water content. During the daytime, the plant's stomata, or pores, opened up, leading to the release of water vapor as a cooling mechanism. An increase in the plant's biopotential was noticed upon irrigation, which indicated the absorption of water and nutrients from the soil by the plant. This process resulted in the formation of an ion concentration gradient, which subsequently led to the change in biopotential. During the night, an increase in biopotential was again observed, which later dropped back down due to the plant's inherent self-regulation mechanism. It was also observed that in the absence of sufficient nutrients in the soil due to lack of fertilization, there was a decrease in biopotential. This decrease was followed by a subsequent rise due to reduced water absorption. Additionally, changes in leaf water content were found to be associated with changes in relative humidity. Following irrigation, an increase in leaf water content was noted, confirming that the plant was drawing water from the soil. The absorbed water was then used in the photosynthesis and transpiration processes. This rise in RH aligned with the observed results. A second round of irrigation was carried out, but it didn't yield any discernible change in leaf water content. This observation suggests that both the plant and the soil had adequate water, eliminating the need for further irrigation. We improved wireless nitrate sensors using water-absorbing hydrogel incorporated with nitrate-selective polypyrene (ppy) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate. Molecularly imprinted technology was used to create nitrate selective coating for the wireless sensor. This innovative approach allowed for precise molecular recognition, enhancing the sensor's capacity to detect nitrate ions accurately. The ppy-PEDOT:PSS hydrogel underwent an electrical polymerization process that was carried out in a solution composed of 0.2 Molar sodium nitrate and 0.2 Molar pyrrole, under an applied potential of 0.8 Volts for a duration of 30 minutes. This polymerization process resulted in a doped Ppy hydrogel with a unique set of properties, the most prominent being its elevated sensitivity to nitrate ions. In terms of selectivity, the nitrate sensor performed remarkably well. Its selectivity was maintained even under conditions with multiple interfering ions. The variations in the signal amplitude when exposed to a mixture of nitrate and various interference ions were less than 12% as compared to its exposure to nitrate alone. This degree of fluctuation in the sensor's amplitude under these challenging conditions indicates an acceptable selective capacity of the nitrate sensor. To enhance the sensor's utility, a wireless circuit was constructed using the ppy-PEDOT:PSS hydrogel as the primary sensitive material. This construction was strategic, as the hydrogel's sensitivity allowed for an accurate and rapid frequency response to changes in nitrate ion concentration. A concrete relationship between the nitrate ion concentration and the frequency response of the circuit was established, further demonstrating the sensor's utility and functionality. To assess the consistency and reliability of this nitrate sensor, fifty individual units were produced and tested. These sensors underwent a drift test to measure the stability of their frequency over time. The results revealed a frequency drift of 5.3% over a period of 30 days and 13.6% over 60 days relative to the resonance frequency, which was set at 378 MHz. While the sensors were observed to maintain their functionality over 60 days, there were certain challenges encountered in the implementation of this technology. The most prominent issue was maintaining a stable wireless connection to the central station, an integral part of the system that required a substantial amount of time to rectify. Power consumption also posed a significant challenge. Despite implementing a sleep mode for the circuit, environmental conditions like rainfall and high temperatures would occasionally trigger the sensor, waking it from sleep mode. This unexpected activation led to an increased and unforeseen consumption of power. These challenges were thoroughly analyzed, and potential solutions were identified. Efforts are currently being channeled into resolving each of these issues, to enhance the efficiency, reliability, and overall performance of the nitrate sensor system. In the field experiment in 2022, it was observed that 72%or approximately 42 water sensors were capable of delivering effective and valuable data for crop management. Looking further into the specifics, a majority, constituting around 58% demonstrated exceptional resilience and robustness by maintaining their functionality throughout the entire growth season, which spans approximately two and a half months. These sensors proved their reliability by operating ceaselessly, without any instances of failure. In the next tier, about 14% of the sensors had an operational span ranging from 20 to 60 days. The limited functionality of these sensors can be attributed to intermittent power outages that affected the solar panels responsible for their energy supply. These power-related complications hindered the continuous functioning of these sensors, restricting their active period to less than the full crop season. Lastly, an unfortunate 28% of the sensors exhibited significant issues as they only managed to function for a brief period of between 0 and 5 days. The primary reasons for this poor performance were notably poor connections with the battery systems, including issues like broken cables and the failure of batteries.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Ibrahim, H., Yin, S., Moru, S., Zhu, Y., Castellano, M.J. and Dong, L., 2022. In Planta Nitrate Sensor Using a Photosensitive Epoxy Bioresin. ACS Applied Materials & Interfaces, 14(22), pp.25949-25961.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Ibrahim, H., Moru, S., Schnable, P. and Dong, L., 2022. Wearable Plant Sensor for In Situ Monitoring of Volatile Organic Compound Emissions from Crops. ACS sensors, 7(8), pp.2293-2302.
- Type:
Journal Articles
Status:
Awaiting Publication
Year Published:
2023
Citation:
Md Tawabur Rahman, Raufur Rahman Khan, Yang Tian, Hussam Ibrahim, and Liang Dong, 2023. High-sensitivity and room-temperature nitrous oxide sensor using Au nanoparticles-decorated MoS2, IEEE Sensors Journal, DOI: 10.1109/JSEN.2023.3296504
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2022
Citation:
Hussam Ibrahim, Electrochemical sensors for nutrients, volatile organic compounds and viral pathogens, Iowa State University. August 2022.
|
Progress 06/01/21 to 05/31/22
Outputs
Target Audience:Soil science research community, agricultural engineering research community, and the agricultural community. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project provided scientific and professional training to one graduate student in electrical engineering and sensordevelopment, one graduate student in sensor network, and another graduate student in computational mathematics. The project provided scientific and professional training to a postdoc in agronomy who works on agriculturalsystems process-based models. One electrical engineering Ph.D. studentrecentlygraduated from this project. His research was to develop sensors for the project. He now worksin a company that manufactures sensors. How have the results been disseminated to communities of interest?1. The team disseminated the research results through one peer-reviewed journal paper published in IEEE Sensors Journal (Chen, Y., Tang, Z., Zhu, Y., Castellano, M.J. and Dong, L., 2021. Miniature Multi-Ion Sensor Integrated With Artificial Neural Network.IEEE Sensors Journal,21(22), pp.25606-25615.) 2. The result on the nitrate sensors was disseminated through a Ph.D. thesis (Chen, Yuncong. "In-situ soil water potential sensor and nutrient sensor." Iowa State University, 2021). What do you plan to do during the next reporting period to accomplish the goals?We will use a control and analytics tool to integrate andfuse field sensor point data and remote sensor data topredict temporal and spatial variations inplant and soil nitrogen and water. We will focus ono using the generated data toprovide feedback to decision-making for irrigation and fertigation. We will continue to provide diverse STEM workforce training and mentorship activities,enhancing the graduate program in sustainable agriculture, recruiting underrepresented minority groups and women students,and transmitting knowledge to the public.
Impacts
What was accomplished under these goals?
To improve nitrogen sensor selectivity, weincorporated artificial neural network (ANN) algorithms with ourmulti-ion sensor to reduce cross-sensitivity between multiple sensing elements of the sensor for improving accuracy in measuring nitrate (NO3-), phosphate (H2PO4-), and potassium (K+) ions in agricultural soil solution, plant sap, and tile drainage water. An array of three ISE-based sensing elements were formed on one side of a printed circuit board (PCB). Each ISE element was coated with an ISM that ideally can target a specific NO3-, H2PO4-, or K+ ion (Fig. 1a and 1b). On the other side of the PCB was an Ag/AgCl-based RE. The sensor was shaped to a needle that helped to insert into the stalk of plants for in-situ measurement of target ions, while for ion sensing in soil solution and tile drainage water, the needle shape was not required. An ANN model was constructed to reduce the cross-sensitivity of the three ISEs through modeling the relationship between the input and output data of the neural network. The ANN was trained using the responses of the three ISEs to prepare mixed-ion solutions with known NO3-, H2PO4- and K+ concentrations. Key parameters of the ANN were optimized to improve performance in predicting NO3-, H2PO4- and K+ ion concentrations. Prediction performance of the ANN was evaluated by root mean squared error (RMSE) and coefficient of determination (R2). The three ISE-based sensing elements had different sensing characteristics and could probe differential interactions with ion species. The ANN analyzed these interactions and learned a model based on a part of the data to perform data classification and regression. The multi-ion sensor, in conjunction with the optimal ANN, was demonstrated to identify and quantify NO3-, H2PO4- and K+ ions in different samples obtained from agriculture cropland. We installed 18 soil nitrate sensors, 18 plant nitrate sensors, 18 leaf transpiration sensors, and 6 soil water potential sensors. These sensors were distributed between the two sites in Nebraska and Iowa. All sensors were powered by solar panels. Data wasinstalled on the SD card of eachsensor. The data logger of each sensorwasplaced inside a waterproof container on the ground.Allsensors were left in the fields for about one and half months after theirinstallation. However, due to the parts shortage and backorder, the installation started in early July, which was quite late.Data analysis is ongoing.We have noticed that7out of18 soil nitrate sensors, 8 out of 18plant nitrate sensors, 15 out of 18 leaf transpiration sensors, and 2 out of 6 soil water potential sensors could producewater and nitrate concentration data continuously from the sensor installation to retrieving.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Chen, Yuncong, Zheyuan Tang, Yunjiao Zhu, Michael J. Castellano, and Liang Dong. "Miniature Multi-Ion Sensor Integrated With Artificial Neural Network." IEEE Sensors Journal 21, no. 22 (2021): 25606-25615.
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2021
Citation:
Chen, Yuncong. "In-situ soil water potential sensor and nutrient sensor." Iowa State University. Ph.D. Disseratation (2021).
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Progress 06/01/20 to 05/31/21
Outputs
Target Audience:Soil science research community, agricultural engineering research community, andthe agricultural community. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?1. The project provided scientific and professional training to one graduate student in electrical engineering and sensor development, one graduate student in sensor network, and another graduate students in computational mathematics. 2. The project provided scientific and professional training to a postdoc in agronomy who works on agricultural systemsprocess-basedmodels. 3. One graduate student gave a presentation on the topic of plant VOC sensors atthe IEEENano/Micro Engineered and Molecular Systems (IEEE-NEMS),2020, virtual conference. The title of the presentation is "Wearable Sensors for On-Leaf Monitoring of Volatile Organic Compounds Emissions from Plants." 4. One graduate student gave a presentation on the topic of plant growth sensors atthe IEEENano/Micro Engineered and Molecular Systems (IEEE-NEMS),2020, virtual conference. The title of the presentation is "Capturing subtle changes during plant growth using wearable mechanical sensors fabricated through liquid-phase fusion." How have the results been disseminated to communities of interest?The team disseminated the research results through one peer-reviewed journal paper published in Advanced Materials Technologies (Adv. Mater. Technol. 2021, 2001246) and two presentations at the IEEE NEMS 2020 (virtual conference). What do you plan to do during the next reporting period to accomplish the goals? We plan to develop a control and analytics tool that can fuse field sensor point data (temporally-continuous, direct, detailed, individual-plant) and remote sensor data (spatially-continuous, indirect, entire field), predict temporal and spatial variations in plant and soil nitrogen and water, and provide feedback to decision-making, specifically targeted irrigation and fertigation. We will start to validate the proposed CPS for irrigation and fertilization optimization through empirical demonstrations using existing in-house and in-field testbeds, and to model, predict, and explain interactions and tradeoffs between NUE and WUE for production. At the same time, we will continue to provide diverse STEM workforce training and mentorship activities, enhancing the graduate program in sustainable agriculture, recruiting underrepresented minority groups and women students, and transmitting knowledge to the public.
Impacts
What was accomplished under these goals?
We optimized the nitrate sensor, leaf sensor, and soil water potential sensor to make them more rugged and robust for field deployment. The nitrate sensor was improved to achieve stable working and reference electrodes. The working electrode was formed with a thin layer of Ag deposited on a patterned Au electrode and covered with the ion-to-electron transducing layer and the nitrate-selective membrane. The reference electrode comprised a screen-printed silver/silver chloride electrode covered by a protonated polymer layer to prevent chloride leaching in long-term measurements. A waterproof epoxy covered the entire surface of the sensor and allows only the center area of the membrane to be exposed to the soil solution. The sensors provided long-term, continuous measurement of soil solution nitrate concentration at a specific point in space where they were deployed. The wearable transpiration sensor was improved to realize real-time on-leaf monitoring of relative humidity, temperature, and vapor-pressure deficit of plants in both controlled environments and under field conditions. This sensor became flexible and conformable to the leaf surface. By integrating a graphene-based RH sensing element and a gold-based thin-film thermistor on a polyimide sheet, the sensor allowed accurate and continuous determination of vapor-pressure deficit at the leaf surface, thereby providing information on plant transpiration. A greenhouse experiment validated the ability of the sensor to continuously and simultaneously monitor both the leaf RH and temperature of maize plants over more than two weeks. The sensor output also demonstrated the influences of light and irrigation on maize transpiration. By attaching multiple sensors onto different locations of a plant, it was possible to estimate the time required for water to be transported from the roots to each of the measured leaves along the stalk, as well as longitudinally from one position on a leaf toward the leaf tip. The sensors were also deployed in crop production fields where they demonstrated the ability to detect difference in transpiration between fertilized and unfertilized maize plants. The improved soil water potential sensor filled with an osmotic solution for continuous, in-situ monitoring of water potential with self-compensation of temperature. The sensor consisted of an active sensing element filled with an osmotic solution, and a reference element that was identical to the active element except for being sealed to prevent the embedded osmotic solution from transportation. The active element responded to both external soil water potential and environmental temperature changes, but the reference element only responded to temperature changes since the reservoir is sealed and the water transport was prevented. Therefore, the integration of the active and reference elements into a single water potential sensor could effectively compensate for temperature variation induced measurement errors that otherwise would be observed with the active element alone. When the environmental temperature changed, the volume of the osmotic solution in both active and reference elements change, leading to a displacement on the diaphragm. This displacement was then detected by the optical detector. Since the displacements on the active and reference elements were simultaneous, the temperature influence could be compensated by subtracting the output of the reference element from the output of the active element. Thus, there was no need for calibrating the response of the sensor to temperature. The improved soil water potential sensor extended the dynamic range of water potential to -1.1 MPa with almost no response to temperature variation. The sensor has been validated, demonstrating the ability to continuously monitor dynamic changes in water potential for about two weeks, conservatively. We used commercial wireless communication technology LoRaWAN for data collection from the sensor. All the field sensors will use rechargeable batteries powered by solar panels. The sensors, data collection units, and solar panels are currently being installed.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Yin, S., Ibrahim, H., Schnable, P.S., Castellano, M.J. and Dong, L., A Field-Deployable, Wearable Leaf Sensor for Continuous Monitoring of Vapor-Pressure Deficit. Advanced Materials Technologies, p.2001246, 2021. doi.org/10.1002/admt.202001246
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