Progress 05/01/23 to 04/30/24
Outputs
Target Audience:Faculty, scientists, extension agents, graduate and undergraduate students, producers, industry partners, and technical staff are engaged in various aspects of the CEA/indoor agriculture industry. The audience also includes agricultural economics, plant nutrition and physiology, automation, robotics, technology development and adoption, beneficial microbial applications, and workforce/education needs. We also target faculty and students involved in optimization, controls theory, lighting control, and smart building monitoring and control for indoor environments. Other audiences outside academia include current and future industry members (suppliers and producers) to K-12 and extension agents with an interest in CEA. Changes/Problems:Aim 1. Dr. Song Li: (1) we did not host an advisory board meeting in the first year because participating teams have not yet produced enough research output for the advisory board to evaluate. One advisory board member passed away and one industry member disengaged from our activities. Therefore, we plan to recruit a new advisory board in fall 2024 and share the project report with this new advisory board. (2) we originally plan to host all information about this project as a facebook page, however, this approach does not seem to reach enough audience. In the 2nd year of this project, we plan to focus on updating a google sitefor the I2GROW project to disseminate the research results to the public and to engage more collaborators in the research community. (3) we plan to start the first phase of external collaborative grants in Fall 2024. The goal is to find additional partners in academia and industry to extend the impact of I2GROW project. The whole team will draft an RFP before Fall 2024 and release to the public in Fall 2024. The first phase of collaborative projects is expected to start in Spring 2025 and end by Fall 2025. These new projects will serve as preliminary results for new grant applications to be submitted in Fall 2025 or later to local and federal agencies. Dr. Tie Liu and Song Li will be the main lead on this aim. Aim 3. Dr. Blake Johnson: While we did not face any major challenges, we did have to replace a workstation in our lab used for modeling of biosensor response that is planned to be used for validation of experimental measurements made in year 2, which led to a slight delay. Dr. Juhong Chen: Due to Juhong's transfer from Virginia Tech to UC Riverside, a new graduate student (Chulin Cao) needed to be recruited to work on the delaying the development of the CRISPR-based biosensor to detect plant pathogens. Aim 4. Dr. John Bovey: Aim 4.1 outlined a plan for surveying Eastern U.S. hydroponic vegetable growers about the cost of production and practices undertaken to reduce emissions. However, after extensively considering the logistics of implementing such a survey, we have decided not to pursue this Aim. With coauthors (Goodrich et al., 2023), Bovay documents experiences with fraudulent responses to surveys eliciting information from farmers and the small number of valid responses obtained in each of two surveys. Given that the target population of growers under study in this aim would have been so small, we would have been unlikely to obtain a sufficient number of valid responses for statistical inference. Other co-PIs have nothing to report in this period. What opportunities for training and professional development has the project provided?Aim 1. Dr. Eva Colla'kova': We tailor training and professional development of our students and postdocs to their interests and needs. The GRA recruited for this project has medical bioengineering training, so this was a great opportunity for him to learn about plant growth and metabolism as well as about different analytical methods used in plant research. His engineering experience and newly acquired plant knowledge both proved useful in helping with the construction of the gantry/hydroponic system in Li's lab. He also attended the Cold Spring Harbor Laboratory "Frontiers & Techniques in Plant Science" course in summer 2024 to expand his knowledge on the current plant-related methods useful to this project and his planned future career as a NASA scientist. Dr. Song Li: One graduate student (together with Eva's student) was trained to build I2GROW Oasis system. Both students visited CMU robotic lab, and learned the system setup of the I2GROW Oasis at the CMU site. Both students participated in constructing the Oasis testbed at Li Lab in Virginia Tech Cooperate Research Center. The student was trained to assemble the farmbot on top of a NFT hydroponic system and control the robot with an online interface for autonomous image collection. Dr. Jactone Ogejo: One Ph.D. student is working on the project, and the work is expected to be part of their dissertation research for their graduate studies. Dr. Abhisesh Silwal and George Kantor: Under Aim 1, a graduate student was hired and is currently working on his Master's degree in Robotics, building the robot and perception system to perceive and measure plant's physical parameters. One other master's and a undergraduate student are also involved at a robot systems integration level and have received hands on robotics experience through internships. Aim 2. Dr. Javad Velni: One graduate student (working as hourly) is partially working on the project and another one was recruited and will start (pending US visa clearance) in Fall 2024. Dr. Hasan Seyyedhasani: A graduate student was hired and is currently working on her Master's degree in Plant and Environmental Sciences, developing a digital twin to predict and evaluate CO2 supply for indoor agriculture. Another graduate student is also involved at sensing system development level and has received hands-on experience through internships. Dr. Farrokh Jazizadeh: One graduate student was involved with this project that was trained on understanding indoor air quality, specifically CO2 variations in buildings. The student was trained to compile relevant literature, extract, and organize data, and use different machine learning and visualization tools to explore the patterns and opportunities for modeling as well as interpreting model outcomes. Aim 3. Dr. Boris Vinatzer, Blake Johnson, and Juhong Chen: As part of the Smart health objective, two undergraduate students and five graduate students were trained in the PI's respective departments. Aim 4. Dr. John Bovey: nothing to report. Aim 5. Dr. Kaylee South: 1 GRA was recruited to begin his master's degree in Horticulture in the second reporting period. How have the results been disseminated to communities of interest?Aim 1. Dr. Abhisesh Silwal and George Kantor: Seminars: Co-PI Silwa and Kantor shared research methodologies and findings through seminars at multiple institutions including Oregon State University, Iowa State University, Virginia Tech etc.Class lectures: Co-PI Abhisesh Silwal included the robot design and AI concepts as a case study in one of the lectures on the course 16765 Robotics and AI in Agriculture from 2021 through 2024.Demonstrations: We have demonstrated the system design and automated data collection pipeline to several aspiring high school students, undergraduate freshmen seeking degrees in robotics, faculties and researchers from various academic institutions across the country, government officials from the USDA. Dr. Song Li: We have participated in CEA-east conference in Danville in Fall 2023. I presented an overview presentation about the I2GROW project as a short talk to an audience include academic researchers, producers and industry partners. I also presented poster presentation in CAIA big event in Fall 2023 to show case the I2GROW project to researchers in Virginia Tech. I also presented our research as an oral presentation at the PAG 2024 conference in the post harvesting session. I also described our I2GROW project to ~20 high school students participated in summer governor's school of agriculture in summer 2023. Aim 2: Dr. Hasan Seyyedhasani: We presented the initial set-up of this work in an i2GROW-wide meeting (Jiaye Liu & Hasan Seyyedhasani) and are planning to present the generated results in the annual international meeting of American Society of Agricultural and Biological Engineers. Furthermore, another conference paper was submitted and accepted to be presented at ASCE International Conference on Computing in Civil Engineering which has been scheduled to take place July 28th -31st, 2024 in Pittsburgh, PA hosted by Carnegie Mellon University. Although the paper is accepted and the presentation will be in July 2024, the official publication will be later potentially in 2025. Aim 3. Dr. Boris Vinatzer: For objective 3, the undergraduate student shared the experimental design in poster presentations at university-level research symposia and results were shared at the ICPPB & Biocontrol conference. Other co-PIs have nothing to report in this period. What do you plan to do during the next reporting period to accomplish the goals?Aim 1. Dr. Eva Colla'kova': We will keep evaluating plant growth and nutritional quality grown on different types food waste and will initiate growth experiments in the automated gantry. Dr. Song Li: we plan to recruit a new advisory board and report our progress to the advisory board and seek feedback from the advisory board. We plan to update the project website that can better reach to a broader audience. We plan to host the 2nd I2GROW meeting including all participating PI, co-PI, students, postdocs, potential collaborators, and advisory board members. Dr. Abhisesh Silwal and George Kantor: We plan to use the developed robot system and validate its capability over repeated experiments. The experiment would include cross comparison between closeness of variables measured between the robot system and manual measurements. Dr. Jactone Ogejo. Refine the methods of making biofertilizers from food waste using the ongoing entomocomposting and Bokashi fermentation processes. We also expect to derive fertilizer using the anaerobic digestion process. We are currently setting up the digesters for the work. Dr. Hasan Seyyedhasani's team: Our study will continue by further examining CO2 recycling systems. Also, we aim at developing a low-cost IoT-based sensing system to collect data from various indoor environments and control them remotely. Furthermore, our study will be extended to conduct season-based data acquisition in order to enable us to generate longer prediction horizons for CO2 concentration and the need for the supplements. Dr. Farrokh Jazizadeh's team: We will continue our efforts to further investigate the generalizability of CO2 concentration models and further show the feasibility of modeling for different environments. This may include collecting data locally to augment the available datasets. We are also planning further dissemination. Dr. Javad Velni's team: Our team will examine the interrelation between supplemental CO2 and supplemental lighting and how the two can be co-optimized under the assumption that other variables are regulated. Aim 3. Dr. Boris Vinatzer: For the Smart health objective, we will repeat the experiment done in year 1 to assess the impact of human touch on the leaf microbiome of edible plants grown hydroponically adding additional comparisons to plants grown in soil outdoors, plants grown in commercial CEA settings, and plants sold at the grocery store. Dr. Blake Johnson: We plan to move forward with validation of several biosensing modalities for detection of target food and water-borne pathogens as well as creating a biosensor-integrated hydroponics testbed that can enable us to both assess the performance of biosensors for pathogen detection and the performance of a digital twin to support 'smart' biosensing for hydroponics applications. Dr. Juhong Chen: In the next year, we will catch up to finish the development of CRISPR-based biosensors to detect plant pathogens. Likely, we will have one manuscript submitted and plan to present our discoveries in a national conference. In addition, we will investigate the performance of microneedles to extract pathogenic DNA from plants. Aim 4. Dr. John Bovey: By the end of the next reporting period, Bovay's Ph.D. student should have nearly completed her dissertation, which will include one chapter described in section 5.1 above. Bovay is also planning to hire a scientist with technical expertise and the experience necessary to complete aim 4.2, on the monetary costs and benefits of our production system. Depending on timing, this scientist may also lead work on the life-cycle analysis described in aim 4.3. Aim 5. Dr. Kaylee South: A GRA will begin in the lab and start working on research related to crop production in CEA systems and assist with outreach efforts related to K12 and workforce training. His work will likely result in a poster presentation at a conference. After the testbeds are developed, industry partnerships will be established and workshops will be developed for training and feedback from stakeholders who will utilize the technology/systems developed in this project.
Impacts
What was accomplished under these goals?
?Objective 1: Smart Growth Dr. Song Li:As the PI of the project, I primarily organized the I2GROW project. I sent weekly or bi-weekly updates to the entire team to ensure everyone was informed about the project's activities. I organized sub-aim meetings to discuss project progress, including student recruitment, research design, updates, and coordination between different sub-aims. I managed the budget, set up the I2GROW Facebook page, and presented our project at several local and national conferences. Additionally, I participated in the GROW conference as a panelist and reviewer for urban CEA projects. Lead on Robotics and Automation--Dr. Abhisesh Silwal and George Kantor: We've developed a fully integrated prototype of the I2GROW-Oasis at CMU. This prototype consists of a 3-axis gantry robot system with a growth bed for crops, LED lighting to facilitate growth, an NFT-based irrigation system, an RGB camera to image the plants, and sensors such as CO2 and humidity sensors to measure environmental variables. The robot system, along with the sensors, is housed inside a large growth tent to isolate it from external environmental influences. The current level of autonomy includes a data acquisition pipeline where the robot can navigate to known plant locations and capture images from multiple views. Environmental sensory data are captured simultaneously with the images for precise data alignment. To aid in data collection, processing, and visualization, we've also developed robust data acquisition and storage protocols, along with a graphical user interface to monitor and display processed spatiotemporal information. Lead on Plant Science--Dr. Eva Collakova: We developed a small-scale hydroponic system to test the growth and nutritional quality of lettuce and tomato plants under different nutrient conditions. Using chromatography-mass spectrometry-based methods, we assessed levels of nutritionals and antinutritionals, including mineral macro and micronutrients, antioxidants, and other specialized metabolites through 10 different assays. Our initial experiments with lettuce and processed liquid food waste revealed that sugar content needs to be reduced by exploring different methods of preparing food waste, such as compost tea. In parallel, a functional automated gantry system, mirroring the one at CMU, was established in Dr. Li's lab with an NFT hydroponic system. Dr. Jactone Ogejo: We tested methods to produce nutrient solutions for hydroponic growth systems from food waste. Three potential pathways were explored: hydrothermal carbonization, compost tea from entomocomposted frass, and solid-state fermented food waste using a commercially available process called Bokashi fermentation. The hydrothermal approach seems to generate solutions high in sugars, posing challenges for growing systems. The fermentation-based processes reduced the sugar levels in the solutions and provided suitable nutrient profiles. Objective 2: Smart Building Lead--Dr. Javad Velni: Leveraging our preliminary results from another NIFA grant, we developed an optimal supplemental lighting control method using LED lamps in greenhouses. Our past work, which provides the only available optimal lighting tools in the literature, did not account for supplemental light distribution and multi-crop cultivation in greenhouses. To address these challenges, we proposed sectioning LED lamp control sources and formulated an optimization problem to minimize electricity costs, regulate light intensity, and minimize the peak of supplemental lights. This was achieved under both supplemental light distribution and multi-crop conditions, using a learning-based algorithm with sunlight prediction. The next step is to deploy and demonstrate the benefits of these tools in commercial greenhouses, beyond laboratory settings. Dr. Hasan Seyyedhasani: To control CO2 levels within a sealed chamber, we explored CO2 Capture & Release through recycling the CO2 delivered to outdoor air handling units.We focused on chemical absorption and identified a collaborator to adapt this method for indoor agriculture. We developed a simulator/digital twin to predict and evaluate CO2 supply. We have started data collection from two indoor agriculture environments--a greenhouse at Virginia Tech and vertical farming facilities at the IALR in Danville, VA. Relative humidity, temperature, and atmospheric pressure are being collected to predict CO2 concentrations. Learning-based models were developed to predict CO2 levels. Time series models, like long short-term memory (LSTM), were developed to predict CO2 concentrations for the next hour and day based on the previous six hours of data. Dr. Farrokh Jazizadeh: We investigated methods to monitor and infer CO2 variations in educational buildings, where higher occupant numbers result in CO2 accumulation. We focused on scalable, generalizable models that do not require instrumenting each subspace. Using publicly available datasets and literature, we studied CO2 concentration variations under different conditions, including buildings with natural and mechanical ventilation. Our machine learning models estimated and predicted CO2 concentrations for various subspaces, showing the feasibility of developing generalizable models despite some challenging cases. Objective 3: Smart Health Lead--Dr. Boris Vinatzer: We assessed the plant and human health aspects of growing edible plants in public spaces. In the first year, we focused on the impact on the plant leaf microbiome by varying degrees of student interaction with hydroponically grown lettuce in a classroom. The experimental design included four sets of lettuce plants: (1) plants grown in a rarely occupied room, and plants grown in a frequently occupied classroom,(2) without student contact, (3)with students invited to approach but not touch the plants, and (4)with students encouraged to touch the plants frequently. No significant differences were found between the microbiomes of the four plant sets, suggesting that growing plants in public spaces may not significantly increase the risk of contamination with human-associated bacteria. Dr. Blake Johnson: Our group established a high-throughput platform for optimizing the working electrode surface functionalization approach for biosensor-based pathogen detection using electrochemical and electromechanical biosensors. We developed physics-guided machine learning models to improve biosensor performance in practical applications, enhancing measurement confidence and reducing false negatives and positives. We also created a digital twin for the hydroponics-integrated biosensing system to interface with surface-based biosensors for pathogen detection. This digital twin model helps guide the identification of pathogen entry points and optimization of hydroponic system parameters. Dr. Juhong Chen: We are developing a CRISPR-based biosensor to detect plant pathogens. So far, we have optimized the CRISPR system to detect a biomarker gene (avr) for plant pathogens, demonstrating high specificity for the detection of the avr gene. Objective 4: Analysis of Economic Feasibility and Social Benefits Lead--Dr. John Bovey: We developed a methodology to explore hydroponics technology adoption rates and their impacts on market supply and producer surplus. Our ongoing research simulates the adoption rates for various crops in the U.S. and measures the impacts on producer welfare. Objective 5: Outreach and Extension Lead--Dr. Kaylee South: We host the CEA Summit East to bring together various stakeholders to discuss CEA-related topics. At the 2023 event, we networked with industry members and presented the I2GROW project. We also conducted a survey to identify workforce training needs for CEA, which will aid in developing training programs. We established relationships with a Virginia Governor School program for K12 outreach, providing hands-on experience with our technologies.
Publications
- Type:
Websites
Status:
Published
Year Published:
2023
Citation:
https://www.facebook.com/profile.php?id=61550880821913
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
The I2GROW project. A testbed of climate-smart technologies for indoor and controlled environment agriculture. 2023. CEA-EAST conference, Danville, VA, Invited talk. by Song Li
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Application of AI and hyperspectral imaging in quality assessment of agricultural products. PAG 2024, by Song Li, Invited Talk.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
I2GROW: Intelligent and Integrated Greenhouse gas RemOval With Indoor and Controlled Environment Agriculture. Poster presentation. Fall 2023, By Song Li
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Robotics Institute Special Seminar: Title: Robotics and AI for Sustainable Agriculture. May 9th, 2024. Pittsburgh, PA, invited talk, Abhisesh Silwal
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Kaur S, Karuppasamy T, Liu H, Li S, Vinatzer BA (2024) An investigation of the effect of human touch on the taxonomic composition of the lettuce leaf microbiome. Poster presentation at ICPPB & Biocontrol 2024, July 7-12, Blacksburg, VA, USA.
- Type:
Websites
Status:
Published
Year Published:
2024
Citation:
https://sites.google.com/vt.edu/i2grow/home
- Type:
Journal Articles
Status:
Under Review
Year Published:
2024
Citation:
S. S. Alaviani, M. W. van Iersel, and J. Mohammadpour Velni, Optimal Supplemental Lighting Control Using Light-Emitting Diode (LED) Lamps in Greenhouses for Multi-Crops Considering Light Distribution, IEEE Trans. on Control Systems Technology, submitted in Feb. 2024, revision submitted in May 2024 and still under review. From a previous project (also supported by NIFA), we extracted some preliminary results and submitted the following manuscript with a former postdoc. Proper acknowledgement to i2GROW will be given once the paper is accepted.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Seyyedhasani, Bio-Automation and Smart Farming. Nov 8, 2023. School of Plant and Environmental Sciences, Virginia Tech. Blacksburg, VA. Invited Talk
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2025
Citation:
Meimand, M., Jazizadeh, F., 2024 Toward Generalized CO2 Prediction in Educational Buildings , ASCE International Conference on Computing in Civil Engineering, July 28-31, 2024, Pittsburgh, PA, USA
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