Progress 04/01/17 to 03/31/22
Outputs
Target Audience:The COVID-19 pandemic situation eased up some in Fall 2021 and Spring 2022. The principal investigator and the students met virtually as well as face to face once or twice a week to discuss progress and plans and coordinate activities. As in the past, the project team worked closely with the farm personnel on campus and appropriate interfaces were kept with interested undergraduate students from STEAM disciplines and Co-PIs using virtual platforms such as "Google Meet", "Blackboard Collaborate" and "Zoom" to advance project goals. Two undergraduate students were also hired to work with the graduate students in the fields. The project leaders and team members participated in online events on campus, as well as among 1890 institutions and professional societies such as the American Society of Agricultural and Biological Engineers and the American Society of Engineering education. The project team continued to remain in touch with USDA ARS Beltsville research collaborators, local vendors, and the farming community at large primarily using online platforms during the reporting period to ensure the relevance of project goals. Project results were presented at the virtual meetings of the American Society of Engineering Education (ASEE) during July 26-29, 2021, and ASME IDETC/CIE 2021 ( IEEE/ASME Mechatronics and Embedded Systems Application) (Virtual) August17-19. 2021. The mainstream engineering fields are gradually integrating with the advancement in digital agriculture and its promise in solving the food, fiber, and fuel needs of the future and creating high-tech jobs in rural and suburban areas. During this period the project leaders have also continued to maintain ties with the UMES Extension, other universities in Maryland, vendors for farming technologies, and K-12 institutions around the campus using online communications whenever possible. Although the pandemic delayed some of the project plans, the project team worked with the local John Deere Dealer ( Atlantic Tractor) and was able to install and utilize the hardware for variable rate seeding to enhance precision agriculture-related infrastructure on campus consistent with the overall goals of the capacity building efforts. The project leaders collaborated on an NSF-NIFA joint solicitation proposal submitted by the University of Maryland College Park as the lead that involved applications of artificial intelligence to enhance the sustainable intensification of agricultural productivity. Although the proposal was rated very high it was not selected for funding, the project leaders will collaborate with the multi-university team in the next cycle. One of the graduate students supported by the project successfully defended his dissertation and completed all requirements for a doctoral degree at the end of March before the extended completion date of the project ( 3/31/2022). The project team is working on two ASEE conference proceedings articles related to a study related to grid soil sampling and the gradual decline in high phosphorus levels in UMES fields, instrumentation, and education related to FarmBot for which undergraduate engineering students worked alongside food science and technology graduate students. The project team members and one of the other graduate students partially supported by the project attended and presented at the 1890 Association of Research Directors Symposium on April 2-5, 2022. Changes/Problems:As mentioned in previous progress reports despite the COVID 19 related pandemic the broad goals of the project were successfully implemented. The project directors sought no-cost extensions to accommodate the COVID-19-related slowdown. Along with support from synergistic projects supported by Maryland Space Grant, and other USDA/NIFA grants,the no-cost extensions allowed the project director to support a doctoral student throughout his dissertation work ( all requirements were completed by the extended end date of 3/31/2022)who was involved with the project from its inception. The project team has initiated some innovative new aspects that are extensions of the completed project and hopes to develop future proposals to support these initiatives to advance learning and discovery efforts in smart farming and digital agricultural technologies. What opportunities for training and professional development has the project provided?The project utilizes state-of-the-art technologies that are being integrated with the growing field of precision agriculture and smart horticulture. State-of-the-art drones and multispectral camera systems as well as software tools for mapping and geospatial analysis have been utilized by the students involved with the project. The students got an opportunity to interface with vendors such as PIX4D image mapper, Ag leader Technology (SMS Advanced) as well as ESRI (ArcMap) to get exposure to contemporary remote sensing and geospatial information technologies. The project team has recently acquired PIX4Dfields a more user-friendly software for developing ortho-rectified image maps and vegetation indices from drone imagery. The FarmBot autonomous robot is an open-source hardware and software platform. The student team involved with the project is interfacing with the development team and also using the online forums to learn about the new enhancements of the device. The project team is alsoworking closely with the farm personnel to utilize the cloud connectivity and the advanced features of the John Deere combine harvester and sprayer recently acquired by the Ag Experiment Station at UMES, for variable-rate fertilizer application and recording spatial variation of the yield data. The project team also interfaced with local John Deere dealers to get updates on the capabilities of the advanced machinery and the John Deere Operations Center. Recently the campus has developed capabilities for variable rate seeding of soybean and corn. The project team will develop prescription maps for variable rate seeding using previous harvest data using tools available in the John Deere Operations Center in the near future for field trials to improve productivity. For the grid soil sampling and mapping the students utlized the MagicTec autonomous sampler mounted on an ATV and utlize the "Soil Test Pro" app on their mobile phones. Since the GIS lab( with the ESRI ArcMAP software) was not easily accessible during the COVID 19 lockdown phase the students used the open access QGIS software and used the online forums to navigate the software environment successfully to map the grid soil sampling data. The vendors for the subsurface drip irrigation set-up (TORO) and the wireless soil moisture sensor network (IRROMETER) also provided the project team with significant support as the team navigated the nuanced capabilities of the advanced technology systems. How have the results been disseminated to communities of interest?The project team has worked with farm personnel on campus and disseminated project-related information to organizations such as STEAM onward for the small farms' community and K-12 students particularly focused on underrepresented minorities. The project team also provided demonstrationsto the local K-12 students and faculty when they visited campus ( February 2022) as well as on other occasions. The project director serves as a technical committee member of IEEE/ASME Mechatronics and Embedded Systems Applications ( MESA) and chaired the sessionon Mechatronics and Embedded Systems Agriculture 4.0 atthe virtual conference of MESA 2021 held in conjunction with ASME/IDETC 2021. The project director also worked with the members of the project team to publish a refereed article and presented the same at the virtual conference -"Nagchaudhuri, A., Hartman, C., Ford, T., and Pandya, J., " Recent Field Implementation Of Contemporary And Smart Farming Technologies at University of Maryland Eastern Shore Proceedings of the ASME IDETC/CIE 2021 ( IEEE/ASME Mechatronics and Embedded Systems Application) (Virtual) August17-19. 2021". The project team also developed a refereed article for the 2021 Proceedingsof the American Society for Engineering Education (ASEE) and presented the same at their virtual conference on July 26-July 29 ---(Nagchaudhuri, A., Mitra, M., Ford, T, and Pandya, J., "Towards efficient Irrigation Management with Solar Powered Wireless Soil Moisture Sensors and Real-time Monitoring Capability", Proceedings of American Society for Engineering Education Annual Conference and Exposition, July26-29, 2021(Virtual) https://peer.asee.org/37921) The project team has also provided demonstrations of aspects of the project to the campus community at large as well as members of other Maryland universities that participate in the Maryland Space Grant Consortium/NASA ( MDSGC). MDSGC has continued a synergistic project titled AIRSPACES annually. UMES graduate school and the interested members of the entire campus community was invited to participate in the open session of the dissertation defense of Mr. Travis Ford ( doctoral student supported by project funds) titled "Remote Sensing and In Situ Observation of Field Experiments with Cereal Crops" in December 2021, based on broad goals of the project. One of the graduate students involved with the project also attended the 1890 Research Symposium of the Association of Research Directors held in Atlanta, April 2-5 and presented his work and other projected related efforts undertaken by the team. Besides dissemination efforts reported above for the final year, the prior progress reports have delineated dissemination efforts undertaken by the project team throughout the duration of the project. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
As evidence of climate change and drought occurrences mount, the necessity for water use efficiency and fertilizer use efficiency for sustainable intensification of agricultural productivity increases to feed a growing world population on limited arable land. As outlined in prior progress reports the project funds facilitated the installation of subsurface drip irrigation (SDI) capability on a modest-sized production agriculture field on campus for corn, wheat, and soybean rotation. The SDI field was utlized to conduct field experiments to determine high water productivity irrigation strategies under variable seeding and fertilizer (N) application rates. The project has also enabled the enhancement of remote sensing capabilities that were initiated on campus earlier on a NASA and Maryland Space Grant supported project using an advanced six-band camera system on a drone capable of imaging in color, color-infrared, and thermal bands. These capabilities and the existing precision agriculture-related infrastructure on campus, largely supported by prior capacity building projects led by the project director allowed one of the FDST graduate students to design and conduct field trials, as well as gather and analyze data for the 2017-2020 growing season on the SDI field. STEM undergraduates, farm personnel, and collaborators from NASA and USDA assisted and advised the graduate student along with the UMES project leaders. During the project, the grid soil sampling efficiency for the campus was also enhanced using an autonomous sampler mounted on John Deere Gator ( All-Terrain Vehicle). Grid soil sampling and mapping were done on an annual basis on the SDI field to observe the gradual decline of phosphorus levels on UMES fields. The project team is developing an article for refereed publication related to the comprehensive data results from the grid soil sampling over an extended period and would also form a chapter in the dissertation work of the FDST graduate student. The No-Cost-Extension of the project allowed the graduate student supported by project funds to complete all dissertation requirements prior to the extended completion date of the project ( 3/31/2022). The results for the 2017-2020 field trials have been reported in prior progress reports and the extensive analysis of the field data forms the basis of the dissertation work completed by Mr. Travis Ford ( FDST graduate student supported by project funds) titled "Remote Sensing and In Situ Observation of Field Experiments with Cereal Crops"). Although the 2021 field experiment conducted during this reporting period was not part of the dissertation work of Mr. Travis Ford it provided an opportunity to introduce another graduate student to precision agriculture-related field trials in the SDI field. The field experiment was conducted as a split-plot experimental design with two nitrogen fertilizer rates as the main plot factor and 4 irrigation treatments as the sub-plot factor. The N fertilizer treatments were 180lbs/ac and 220lbs/ac, while the irrigation treatments consisted of 0 in, 1/8 in, ¼ in, and 1/3 in, per irrigation event. Each irrigation treatment received the same total number of irrigation events, and the irrigation events were triggered when the soil was below 50% plant available water. Soil moisture sensors were placed in each treatment area at a depth of 6 inches and 12 inches, to monitor the change in soil moisture and how it is impacted by the subsurface drip irrigation. Harvest results indicate that irrigation had a statistically significant impact on yield. N fertilizer did not have a statistically significant impact on yield, but the high fertilizer treatment averaged over 1,000kg/ha more than the low N treatment. Thermal and multispectral images are currently being processed and correlation studies, linear regression, and the root-mean-square error analysis is being performed for each treatment area to compare yields. During the later stages of the project ( 2020/2021) the agriculture experiment station on campus acquired a John Deere Combine harvester and sprayer. Variable-rate seeding capability for corn and soybean has also recently been installed. These capabilities will continue to involve STEM graduate and undergraduate students on campus in learning, discovery, and engagement in the growing field of precision farming that is strongly aligned with the campus land grant mission.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Nagchaudhuri, A., Mitra, M., Ford, T, and Pandya, J., Towards efficient Irrigation Management with Solar Powered Wireless Soil Moisture Sensors and Real-time Monitoring Capability , Proceedings of American Society for Engineering Education Annual Conference and Exposition, July26-29, 2021(Virtual) https://peer.asee.org/37921
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
Nagchaudhuri, A., Hartman, C., Ford, T., and Pandya, J., Recent Field Implementation Of Contemporary And Smart Farming Technologies at University of Maryland Eastern Shore Proceedings of the ASME IDETC/CIE 2021 ( IEEE/ASME Mechatronics and Embedded Systems Application) (Virtual) August17-19. 2021
- Type:
Theses/Dissertations
Status:
Submitted
Year Published:
2022
Citation:
Ford, Travis, "Remote Sensing and In Situ Observation of Field Experiments with Cereal Crops", Dissertation Submitted to UMES Graduate School, March 2022
|
Progress 04/01/20 to 03/31/21
Outputs
Target Audience:The COVID-19 pandemic situation, restricted access to campus, and social distancing mandates impacted some of the planned activities during this reporting period. Two graduate student advisees of the primary author who had initiated field experiments in the spring continued with their work and completed their efforts over the summer while maintaining the pandemic-related safety precautions enforced by campus administration with support from farm personnel and the aviation coordinator. The principal investigator and the students met virtually as well as face to face once or twice a week to discuss progress and plans and coordinate activities. As in the past, the project team worked closely with the farm personnel on campus and appropriate interfaces were kept with interested undergraduate students from STEAM disciplines and Co-PIs using virtual platforms such as "Google Meet", "Blackboard Collaborate" and "Zoom" to advance project goals. The project leaders and team members participated in online events on campus, as well as among 1890 institutions and professional societies such as the American Society of Agricultural and Biological Engineers and the American Society of Engineering education. The project team continued to remain in touch with USDA ARS Beltsville research collaborators, local vendors, and the farming community at large primarily using online platforms during the reporting period to ensure the relevance of project goals. Project results were presented at the virtual meetings of the Northeast Agricultural and Biological Engineers Conference (NABEC 2020) held virtually on July 31st and Virtual annual meeting of the American Society of Engineering Education (ASEE) during June 22-26, 2020 by participating graduate, undergraduate students, and the PI. Overview of Smart Agriculture and Unmanned systems efforts that have been conducted at UMES during the current and prior NIFA funded projects was presented by the PI for an online Mini-Series on Precision Agriculture and Opportunities for Underserved Communities in October 2020 that was organized by Prairie View A&M on behalf of 1890 institution. The mainstream engineering fields are gradually integrating with the advancement in digital agriculture and its promise in solving food, fiber, and fuel needs of the future and creating high-tech jobs in rural and suburban areas. During this period the project leaders have also continued to maintain ties with the UMES Extension, other universities in Maryland, vendors for farming technologies, and K-12 institutions around the campus using online communications whenever possible. Changes/Problems:Although the project team made progress with the project goals some of the field efforts were restricted due to the pandemic. Also team efforts involving undegraduate and graduate students in the STEAM disciplines had to be limited due to the social distancing protocols. Looking ahead as restrictions ease and normalcy is restored if possible the project leaders hope to request an extension of the validity of the project till October of 2022 to ensure appropriate utlization of resources, completion of dissertation work of the primary graduate student involved in this work, progress in dissertation efforts of a second graduate student who is now involved with the broader scope of the project and repeating and finetuning some of the field efforts that were executed under severe restrictions in this challenging reporting period. What opportunities for training and professional development has the project provided?The project utilizes state of the art technologies that is being integrated with the growing field of precision agriculture and smart horticulture. State of the art drones and multispectral camera systems as well as software tools for mapping and geospatial analysis have been utilized by the students involved with project. The students got an opportunity to interface with vendors such as PIX4D image mapper, Ag leader Technology (SMS Advanced) as well as ESRI (ArCMAP) to get exposure to contemporary remote sensing and geospatial information technologies. The project team also worked closely with the farm personnel to utilize the cloud connectivity and the advanced features of the John Deere combine harvester and sprayer recently acquired by the Ag Experiment Station at UMES, for variable rate fertilizer application and recording spatial variation of the yield data. The project team also interfaced with local John Deere dealers to get updates on the capabilities of the advanced machinery and the John Deere Operations Center. The vendors for the subsurface drip irrigation set-up (TORO) and the wireless soil moisture sensor network (IRROMETER) also provided the project team with significant support as the team navigated the nuanced capabilities of the advanced technology systems. Graduate students and some of the involved with the projects also participated in the virtual conferences organized by Northeast Agricultural and Biological Engineers Conference (NABEC 2020) and the American Society for Engineering Education (ASEE 2020) in the summer of 2020 and presented their work. Although limited in scope due to the virtual nature the conferences provided valuable professional development opportunities for the project team. How have the results been disseminated to communities of interest?The project leaders and team members participated in online events in campus, as well as among 1890 institutions and professional societies such as American Society of Agricultural and Biological Engineers and American Society of Engineering education. The project team continued to remain in touch with USDA ARS Beltsville research collaborators, local vendors, and farming community at large primarily using online platforms during the reporting period to ensure the relevance of project goals. Project results were presented at the virtual meetings of Northeast Agricultural and Biological Engineers Conference (NABEC 2020) held virtually on July 31st and Virtual annual meeting of the American Society of Engineering Education (ASEE) during June 22-26, 2020 by participating graduate, undergraduate students, and the PI. Overview of Smart Agriculture and Unmanned systems efforts that have been conducted at UMES during the current and prior NIFA funded projects was presented by the PI for an online Mini Series on Precision Agriculture and Opportunities for Underserved Communities in October 2020 that was organized by Prairie View A&M on behalf of 1890 institution. The mainstream engineering fields are gradually integrating with the advancement in digital agriculture and its promise in solving food, fiber and fuel needs of the future and creating high tech jobs in rural and suburban areas. During this period the project leaders have also continued to maintain ties with the UMES Extension, other universities in Maryland, vendors for farming technologies, and K-12 institutions around the campus using online communications whenever possible. What do you plan to do during the next reporting period to accomplish the goals?Sustainable intensification of agricultural productivity for feeding a growing world population is an enormous challenge in the face of limited availability of arable land, environmental constraints, and a dwindling agricultural workforce in developed and developing countries. In this report, the recent efforts undertaken by the smart farming project team at UMES utilizing the state of the art technologies have been outlined. Several enhancement efforts that will build upon the work described are currently underway and will gather momentum as the COVID 19 situation subsides. Grid soil sampling data will be blended with remote sensing data and other field characteristics to develop and fine-tune prescription maps for improved NUE. Wireless soil moisture sensors will be deployed at different depths at each of the 20 zones in the subsurface drip-irrigated field and the irrigation line valves will be instrumented for autonomous activation based on soil moisture status and weather predictions. Drone-based thermal imagery will be captured at active growth stages of the crop to determine crop water stress and contribute to irrigation management plans. Drone imagery will also be captured at a lower elevation with higher resolution to identify weed location for spot spraying herbicides with sprayer drones. Rainwater harvesting set-up will be completed for the FarmBot and the charging patterns of the solar and wind energy set-up will be analyzed. Several micro-farming field experiments with the FarmBot set-up described will be undertaken for NUE and WUE studies with specialty crops and vegetables. Also, an indoor FarmBot set up with grow lights will be completed to undertake small-scale field studies integrating NUE and WUE with light level variations. Artificial intelligence algorithms will be explored to optimize productivity .
Impacts
What was accomplished under these goals?
The COVID 19 restrictions related to campus access and prevailing social distancing protocols provided some challenges that the project team had to surmount during this reporting period. As in the previous year nitrogen and water use efficiency studies at UMES were explored for sustainable farming practices at two different field scales - A 15-acre plot in UMES Bozman field that has been installed with subsurface drip irrigation (SDI) and fertigation capabilities; A 10ft by 20ft. raised bed serviced by a robotic device (FarmBot) that can seed, weed, irrigate, and monitor crop growth autonomously. In early spring when the campus was shut down due to COVID 19 restriction special permission was granted by the UMES administration to continue with completing field trial initiated in December 2019. Winter wheat study at UMES is a collaborative effort with Virginia Tech and University of Delaware with broad synergistic overlaps with this NIFA 1890 CBG project. Field studies have been conducted at UMES to correlate the normalized difference vegetation index (NDVI) values from hand-held devices and unmanned aerial system (UAS) with color infrared digital camera attachment, with tiller counts of wheat plants in the field at various timing sequence of nitrogen application. Strong correlations observed and other analyses undertaken indicated that variable rate application based on NDVI data obtained from UAS at GS 25 to GS 30 growth stage following partial ( roughly 1/3rd) application of nitrogen during the seeding and germination stage will be ideal for improved yield with enhanced NUE. The field trial conducted with the stated objective during the 2020 COVID 19 pandemic is outlined below. Recently acquired Altum 6-band multispectral camera mounted on DJI Inspire-II was utilized to capture multispectral imagery over a designated portion of the field. The images were captured with sufficient frontal and side lap as shown for efficient stitching and for generating NDVI (((NIR-RED)/(NIR + RED)) map using the red and near-infrared(NIR) bands captured from the drone with the PIX4D image mapping software. The Atlas Flight application from Micasense allowed the flight planning to be done efficiently and an aviation faculty member at UMES could independently acquire the image data following the social distancing mandates on campus. Acquired imagery was sent over the internet for processing with the PIX4D mapper software to create the NDVI map of the stitched image for the area of interest. Spatial Management Software (SMS Advanced) from AgLeader Technologies was used to develop a prescription map for nitrogen application. The Agriculture Experiment Station at UMES has recently acquired a combine harvester and fertilizer sprayer (John Deere) with cloud-connectivity. The prescription map could be downloaded to the fertilizer sprayer over the internet for variable rate application based on variations in NDVI values. As the sprayer operator drove over the field the GPS unit on the sprayer picked the application rate for the location according to the prescription. These operations were conducted during a period when the campus was shut down during spring 2020 and only essential personnel (including farm personnel) were allowed on campus. Later in the summer, the cloud connectivity of the combine harvester was utilized to download the post-harvest crop yield data for analysis. It would be remiss not to mention that the process described above was integral to the field experiment that involved splitting up a 15-acre field on campus into two portions. On one portion a field experiment was designed using 4 treatments with 3 replications involving nitrogen application timing sequence. The treatments were applied in 1 to 3 applications between GS20 and GS30 growth phases. After the final application, each treatment amounted to 120 lbs/acre. A treatment of 80lbs/acre was also used to see if the reduced level of nitrogen had a significant impact. For the other portion of the field, 40lbs/acre was applied at the early stage (December 15th) and was supplemented at the GS 30 stage based on prescription developed by UAV imagery at a variable rate as described above. The ANOVA analysis and Tukey test revealed that the yield outputs were mostly similar, statistically significant difference was only present for the lower rate of nitrogen application (80 lbs/acre) and the treatment that timed the nitrogen application at 40 lbs/acre at three stages ( early (Dec 15), GS20, and GS 30)). While the results of the field trial were not conclusive about the best timing sequence for nitrogen application, it was encouraging to note that the yield from the portion of the field where variable-rate nitrogen was applied based on a prescription map developed from drone imagery, the yield was comparable to the treatments that received 120 lbs/acre in total at different timing sequences. The digital records of the actual fertilizer application in the sprayer system indicated that the average amount that was applied over this portion of the field was approximately 70lbs/acre applied at the GS30 stage. It is to be noted this is over and above the 40lbs/acre that was applied on this portion at an early stage. The field study provided an opportunity to use the new UAS and six-band camera as well as the new combine harvester and sprayer unit with precision GPS and cloud connectivity. For the micro-scale FarmBot project COVID 19 situation created similar disruption to an ongoing field trial to study effects of variable irrigation rates on radish and arugula planted in the FarmBot bed as a randomized control block (RCB) design for subsequent statistical analysis of the harvest data. Special permission was obtained from UMES administration to continue with the effort utilizing the autonomous capabilities of the robotic device that could be manipulated remotely using a cell-phone app. For the trial run performed in the spring, summer and fall of 2020, at harvest time, a mini electronic scale was used to weigh a selected number of plants from each irrigation zone and their average value (in grams) was used as the harvest data in the One-Way ANOVA analyses. ANOVA analyses were completed on the harvest for both radish and arugula. Although ANOVA results suggest that there was not an appreciable effect on the harvest due to the irrigation treatments ( I-0 : No irrigation, I-1: 1.5 gal/day, I-2 : 3 gal/day and I-3 4.5 gal/day). Treatment I-3(maximum irrigation) yielded better results compared to other treatments for radish as well as for arugula. These results confirm that the sustainability goals and costs associated with water use will be favorably impacted utilizing the rainwater harvesting capabilities. Tukey test results confirm that the harvest with the I-3 treatment was better than the other treatments (P<0.05) and the blocks had some effect on the harvest as well. For brevity the RCB design is not included in this report, but will be documented on a publication that a project team is working on. The project team had stalled the installation of the wireless soil moisture sensor network that was acquired in the previous reporting period due to the COVID situation, however, a small team of undergraduate students in engineering and graduate students in food science and technology worked with the project leaders in fall 2020 to do a preliminary installation and trial run with the sensor network in the 15 acre SDI field. The deployed field sensors at every relay node communicated the data wirelessly to a cellular gateway via a base node that allowed users to login through a web application to observe the sensor data in real-time. The set-up was demonstrated to the students in the online Instrumentation Course (ENGE 380) using the web access and integrated with aspects of the project efforts in the course.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2020
Citation:
3. Nagchaudhuri, A., & Pandya, J. R., & Mitra, M., & Ford, T. (2020, June), Education and Research at the Nexus of Food, Energy, and Water with a 3-Axis Farming Robot Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual Online. 10.18260/1-234492 https://peer.asee.org/34492
- Type:
Other
Status:
Other
Year Published:
2020
Citation:
2. Ford, T., Hartman, C., Nagchaudhuri, A., and Mitra, M., Integrating Smart Farming Technologies for Research and Production Agricultural Practices at the University of Maryland Eastern Shore Northeast Agricultural and Biological Engineering Virtual Conference, Poster No: 20-049 July- 2020, http://nabec.asabe.org/uploads/1/1/2/5/112547767/nabecnewsletters20.pdf
- Type:
Other
Status:
Other
Year Published:
2020
Citation:
1.Pandya, J., Ford, T., Davis, K., Nagchaudhuri, A., Nindo, C, and Mitra, M., Smart Agriculture Using Autonomous Robots , NorthEast Agricultural and Biological Engineering Virtual Conference, Poster No: 20-052 July- 2020, http://nabec.asabe.org/uploads/1/1/2/5/112547767/nabecnewsletters20.pdf
|
Progress 04/01/19 to 03/31/20
Outputs
Target Audience:As in the past, the project team worked closely with the farm personnel on campus and brought together faculty and students from science, technology, engineering, agriculture, and mathematics (STEAM) backgrounds in a vertically integrated multidisciplinary team to advance the project goals. The project leaders and team members participated in campus events to raise awareness among a broader base of the campus community the social, educational, and research priorities of the 1890 land grant mission of the campus. Besides students and the campus community, the project team continued to remain in touch with USDA ARS Beltsville research collaborators, local vendors, and farming community at large to ensure the relevance of project goals. Research results were presented at the international meeting of the American Society of Agricultural and Biological Engineers (ASABE) held in Boston in July 2019. The project leader chaired a session on "Mechatronics and Embedded Systems in Agriculture" at the 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications which was held in concurrently with the ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference during 18th -21st August 2019. Overview of remote sensing efforts with unmanned systems that have been conducted at UMES during the current and prior NIFA funded projects was presented at the conference. The mainstream engineering fields are getting integrating with the advancement in digital agriculture and its promise in solving food, fiber and fuel needs of the future and creating high tech jobs in rural and suburban areas. The project leaders and USDA collaborator participated in an exploratory conference involving Industrial Hemp held in the UMES campus in 2019 fall and discussed the possibility of adapting project efforts to grow industrial hemp using precision technologies integral to the current project. During this period the project leaders have also continued to maintain ties with the UMES Extension, vendors for farming technologies, and K-12 institutions around the campus. Changes/Problems:The PI in discussion with the Agricultural Experiment Station director and Authorised Organizational Representative has applied for a no-cost extension until 3/31/2021 to accomplish all the stated goals of the project. At the time of submitting this report, the UMES campus like other campuses in the nation are adhering to the social distancing mandates and access to campus is strictly regulated. Some of the ongoing field experiments for the winter-spring growing season have been impacted. We hope to complete these efforts at a later date with the no-cost extension of the project. What opportunities for training and professional development has the project provided?The project team have familiarized themselves with the newly acquired PIX4D and SMS Advanced Software environments that are being extensively utilized for remote sensing and agricultural data analysis through online webinars and self-guidance. The team has upgraded the computing facilities for the project and are now able to process UAV imagery within an hour of the aerial imaging mission. The novel UAV systems acquired by the project team have allowed the aviation faculty and project participants to get exposed new advancements in UAV technology. The project leaders and graduate students have attended the 2019 American Society of Agricultural and Biological Engineers (ASABE) annual conference as well the 2019 symposium of 1890 Association of Research Directors. The PI has promoted the field of digital agriculture in the broader engineering community and have organized, chaired and presented at a session titled Mechatronics and Embedded Systems in Agriculture at the 15th IEEE/ASME Mechatronics and Embedded Systems Applications (MESA). ASABE, MESA, and the 1890 conferences have also provided additional opportunities of professional development in relevant fields addressed by the project for the graduate students and the faculty investigators. How have the results been disseminated to communities of interest?As in the past years, the project team disseminated project results among academic communities and researchers that were reached by attending relevant conferences. The project team continued to interact with UMES extension, NASA collaborator and research collaborator at USDA - ARS Beltsville to advance project goals and disseminate project results. Vendors who have installed SDI andfertigation systems and other field devices on campus are also integrated with the farming community in and around the eastern shore area and are helping to disseminate project efforts by word of mouth. The project team has also interacted with the campus community at large to disseminate project goals within and outside the university. The remote sensing using UAVs and FarmBot efforts were demonstrated during the UMES Agriculture/STEM field day. There is a lot of interest in K-12 community and local industries around UMES to work collaboratively with the FarmBot and UAV related efforts that are being conducted at the UMES campus under the auspices of the project. What do you plan to do during the next reporting period to accomplish the goals?At the ASABE conference in Boston in 2019, the project team discussed with several vendors about developing wireless soil moisture monitoring capability in the SDI field used for the experiments conducted under the umbrella of this project. The project team has now identified and is in the process of installing the wireless soil moisture sensing capability in the SDI field. The project team will utilize this capability to monitor soil moisture levels in the SDI field as well as develop the capability to activate the irrigation zones in the field as needed. The project team has also acquired new unmanned systems for 5-band imaging and spraying capability. Initial field trials will be conducted with these advanced technology implements for field studies conducted in the SDI field. The project teamplans to utilize the new capabilities for field experiments to demonstrate the use of UAV imagery-based variable rate applications to improve water and nutrient use efficiency forproduction farming in small and moderately size fields. Plans are also underway to demonstrate the nexus of food, energy, and water in micro-farms that will be serviced by outdoor and indoor setups of FarmBots on the campus. Development of other ground robots and robotic boats to support precision agriculture-relatedapplications andwater quality monitoring will also be addressed in the next reporting period.
Impacts
What was accomplished under these goals?
All four project objectives were advanced in the reporting period. The results from the 2018 growing season of corn were elaborated in our last report. For the 2019 growing season, the project team made suitable improvements/modifications with the assistance of a local vendor to develop fertigation capability on the Subsurface Drip Irrigation (SDI) field. Nitrogen was applied using this capability at a flat rate of 190-200 lbs/acre throughout the SDI field. The application was staggered over three stages over the growing period. A split-plot field experiment with 2 seed rates and three irrigation levels was conducted. Other than the fertigation component the basic field experiment planned for 2019 growing season was similar to that of 2018 growing consisting of split-plot experiment with 2 seed rates (28000 seeds/acre and 32000 seeds/acre) and three irrigation levels (0,1/8th in. and 1/4th in). Although, no significant difference in yield was observed with higher density seeding the overall productivity of the field was significantly better than other non-irrigated fields on campus. The average yield was around 235 bushels/acre with portions of the field with 1/4th inch irrigation reached close to the average yield of 300 bushels/acre. The results of the field experiment will be presented at the North-East Agricultural and Biological Engineering Conference (NABEC 2020) in late July 2020 at Pennsylvania State University. Significant refinement has been achieved with UAV imaging and analysis capability to support remote sensing efforts integral to the project. A new UAV system and 5 band camera have been acquired by the project team. Also, the PIX4D image mapping software has now been installed on 64 GB RAM desktop computer to speed up the processing of UAV imagery. Aviation faculty at UMES campus continues to work with the project team to refine the UAV missions and camera triggering set up so that the entire experimental field can be imaged with the thermal as well as the color infrared digital camera onboard the UAV. The CIR imagery is being utilized for observing nutrient stress and analyzing nutrient use efficiency while the thermal imagery is being utilized to observe crop water stress and analyze water use efficiency. UAV flights have been also conducted over field experiments that are being conducted with winter wheat on campus. The project team is looking into expanding UAV applications to include spot spraying (herbicide/pesticide) with the precision agriculture efforts on campus. The Magic Tech automated soil probe is being utilized for efficient grid soil sampling. The system has been utilized for sampling the SDI field after harvesting or prior to seeding the SDI field. The soil samples have been sent to the soil testing labs and the results have been documented. Lime and macronutrient applications have been conducted based on these results. The results will also help monitor phosphorus levels in the field with the progress of time. Additional support from Maryland Space Grant/NASA has allowed several undergraduate students from engineering and other STEAM majors at UMES to work with graduate students in the FDST program at UMES to advance the project goals. A synergistic effort has been undertaken by the project team for a small plot (10 ft by 20 ft) automated precision farming effort using a Cartesian robotic platform that is being marketed as FarmBot. FarmBot can seed, weed, water, and take lapse photography of crops/vegetables planted and grown in the 10 by 20 ft raised bed serviced by the robot. FarmBot has been installed and a basic field trial has been initiated to understand the capabilities of the system. Small plot trials with FarmBot can provide insight into agronomic variables that are likely to impact field applications on a larger scale. Additional FDST doctoral student who joined the project team last year is leading the FarmBot and other field-robotic platform development efforts to advance the project goals. A hoop house has been built around the FarmBot to extend the growing season. Solar and wind power generation set up has been integrated with the FarmBot and rainwater harvesting capability is being developed. The FarmBot efforts will not only complement precision farming efforts on a small scale but help to sensitize project participants ( multidisciplinary team of undergraduate and graduate students) to develop and spread awareness of sustainability considerations that will drive the nexus of food, energy, and water in the future.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
2. Nagchaudhuri, A., Ford, T.W., and Hartman, C., "Overview of Remote Sensing Efforts at University of Maryland Eastern Shore." Proceedings of the ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications. Anaheim, USA. August 1821, 2019. V009T12A027. ASME. https://doi.org/10.1115/DETC2019-98457
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
" Ford, T., Hartman, C., Mitra, M., and Nagchaudhuri, A., Mission Planning and Ortho-Mosaicking of UAS Imagery for Remote Sensing in Precision Agriculture on Winter Wheat and a Subsurface Drip Irrigated Corn Field, Paper No 190075, 2019 Proceedings of ASABE International Meeting, July 7-10, 2019 Boston, MA
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2019
Citation:
J. Pandya, T. Ford, K. Davis, A. Nagchaudhuri, C. Nindo and M.Mitra , FarmBot?A Platform for Backyard Precision Farming:Installation and Initial Experimental Layout , Paper # 1900194
2019 Proceedings of ASABE International Meeting, July 7-10, 2019,Boston, MA
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Progress 04/01/18 to 03/31/19
Outputs
Target Audience:As in the past the project team worked closely with the farm personnel on campus and brought together faculty and students from science, technology, engineering, agriculture, and mathematics (STEAM) backgrounds in a vertically integrated multidisciplinary team to advance the project goals and raise awareness among a broader base of campus community to embrace salient social, educational, ,and research priorities of 1890 land grant mission of the campus. Besides students and campus community, the project team continued to remain in touchwith USDA ARS Beltville research collaborators, local vendors, and farming community at large to ensure relevance of project goals. Research results were presented at the international meeting of American Society of Agricultural and Biological Engineers ( ASABE) held in Detroit in July 2018 as well as at the Biennial Symposium of 1890 Research Directors in Spring 2019 held at Jacksonville Florida in March/April 2019. The project leader co-chaireda session on "Mechatronics and Embedded Systems in Agriculture" at The 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications lastsummer and will be chairing a similar session later this summer at 15thIEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications. The broader engineering community is gradually getting more integrated with the advances in digital agriculture and its promise in solving food, fiber and fuel needs of the future and creating high tech jobs rural and suburban areas.The project leaders have also reinforced ties with the UMES Extension, vendors for farming technologies, and K-12 institutions around the campus. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project team have familiarized themselves with the newly acquired PIX4D and SMS Advanced Software environments that are being extensively utilized for remote sensing and agricultural data analysis through online webinars and selfguidance. The project leaders and graduate students have attended the American Society of Agricultural and Biological Engineers(ASABE) annual conference as well the 2019 symposium of 1890 Association of Research Directors. The PI has promoted the field of digital agriculture in the broader engineering community and have organized, chaired and presented at a session titled Mechatronics and Embedded Systems in Agriculture at the 14th IEEE/ASME Mechatronics and Embedded Systems Applications (MESA). ASABE,MESA, and the 1890 conferences have alsoprovided additional opportunities of professional development in relevant fields addressed by the project for the graduate students and the faculty investigators. How have the results been disseminated to communities of interest?Besides academic communities and researchers that were reached by attending relevant conferences.The project team interacts closely with UMES extension, NASA collaborator and research collaborator at USDA - ARS Beltsville to advance project goals and disseminate project results. Vendors who have installed SDI system and other field devices on campus are also integrated with the farming community in and around the eastern shore area and disseminate project efforts by word of mouth. The project team has also interacted with the campus community at large to disseminate project goals within and outside the university. The remote sensing using UAVs and FarmBot efforts were demonstrated during the UMES Agriculture/STEM field day. There is a lot of interest in K-12 community around UMES to work collaboratively with the FarmBot efforts. What do you plan to do during the next reporting period to accomplish the goals?Major goals of the future are to refine the fertigation capability and integrate tissue sampling and analysis for site-specific application of nutrients through SDI tubes. The project team will continue to work with UMES extension to disseminate results to local farmers and K-12 system. Remote sensing capabilities are also being refined with the progress of the project. The annual grid soil sampling results will be documented and analyzed to enunciate the impact related to agricultural run-offs and water quality, especially with regard to phosphorus levels in the soil which is a concern for the eastern shore area. Results of the field experiments conducted under the auspices of the project will be published in relevant conferences and journals. The FDST graduate students working on the project will integrate project results to develop and advance theirdissertation efforts. Additional proposals will be developed to seek support from USDA, NIFA, NASA and Maryland Space Grant to continue the project efforts.
Impacts
What was accomplished under these goals?
All four project objectives were advanced in the reporting period. The results from the 2017 growing season of corn was elaborated in our last report. In the 2018 growing season we used 3 irrigation ( 0, 1/8, 1/4 inch) levels and 2 seeding rates of 28,000 and 32,000 seeds/acre to study the yield response. Due to inclement weather the planting of the seeds for the corn was delayed and it impacted yield, however, the yield in the SDI field was superior to most of the other fields on campusas well as otherfields in the local area. Analysis of the yield data revealed although the seeding rate did not affect the yield significantly the higher irrigation level did produce a statistically significant yield advantage. For the 2019 growing season the project team has worked with a local vendor to develop fertigation capability on the SDI field. We plan to apply nitrogen using this capability at a flat rate of 180 lbs/acre throughout the SDI field. However, the application will be staggered over three stages over the growing period. The first fertigation trial has been kept simple however this capability will allow researchers to do field studies on quantity, timing, and frequency of nitrogen and other nutrient application based on tissue analyses. Besides fertigation the basic field experiment planned for 2019 growing season will be similar to that of 2018 consisting of split plot experiment with 2 seed rates and three irrigation levels. Significant refinement has been achieved with UAV imaging and analyses capability to support remote sensing efforts integral to the project. Aviation faculty at UMES campus continues to work with the project team to refine the UAV missions and camera triggering set up so that the enitre experimental field can be imaged with the thermal as well as the color infra red digital camera on board the UAV. The new software image mapping software acquired by the project team requires 75-85% side and forward overlap of image frames for proper stitching of the images for subsequent analyses. The CIR imagery is being utilized for observing nutrient stress and analyzing nutrient use efficiency while the thermal imagery is being utilized to observe crop water stress and analyze water use efficiency. The CIR imagery will also be used as in the past to develop prescription maps for nitrogen application in other fields growing corn and other cereal crops. The project team is looking into adding other user friendly capability to the software system for UAV image mosaicking and analyses. The Magic Tech automated soil probe has allowed efficient grid soil sampling capability. The system has been utilized for sampling the SDI field after harvesting or prior to seeding the SDI field. The soil samples have been sent to the soil testing labs and the results have been documented. Lime and macronutrient applications have been conducted based on these results. The results willalso help monitorphosphorus levels in the field with progress of time. Additional support from Maryland Space Grant/NASA have allowed several undergraduate students from engineering and other STEAM majors at UMESto work with graduate students in the FDST program at UMES to advance the project goals. A synergistic effort has been undertaken by the project team for a small plot (10 ft by 20 ft) automated precision farming effort using a Cartesian robotic platform that is being marketed as FarmBot. FarmBot can seed, weed, water, and take lapse photography of crops/vegetables planted and grownin the 10 by 20 ft raised bed serviced by the robot. FarmBot has been installed and a basic field trial has been initiated to understand the capabilities of the system. Small plot trials with FarmBot can provide insight into agronomic variables that are likely to impact field applications on a larger scale. An additional FDST doctoral student has joined the project team to lead the FarmBot and other field robotic efforts to advance the project goals. Immediate plans for the FarmBot project also involves building a hoop house to extend the growing season and utilize solar power and rain water harvesting capability to sensitize young minds about sustainablity considerations.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
2. Ford, T., Hartman, C., Nagchaudhuri, A., and Mitra, M., Analyses of Yield Response with Subsurface Drip Irrigation Strategies and Remote Sensing with UAVs , 2018 ASABE Annual International Meeting, DOI: https://doi.org/10.13031/aim.201801152, Paper Number: 1801152, July 29-August 1, 2018, Detroit, Michigan USA
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
3. Nagchaudhuri, A., Mitra M, Hartman, C., Ford, T., and Pandya, J., Mobile Robotic Platforms to Support Smart Farming Efforts at UMES , Proceedings of 14th IEEE/ASME Mechatronics and Embedded Systems Applications (MESA 2018), July 2-4, 2018, Oulu
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2018
Citation:
T. Ford, C. Hartman, A. Nagchaudhuri, Department of Engineering M. Mitra, J. Pandya, Analyses of Yield Response of Corn with Subsurface Drip Irrigation Strategies and Remote Sensing with UAVs Abstract #36, 19th Biennial Research Symposium of the 1890 Association of Research Directors , March 30- April 3, Jacksonville, Florida 2019 (Oral Presentation)
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2019
Citation:
2. T. Ford, C. Hartman, A. Nagchaudhuri, M. Mitra, and J. Pandya, Mission Planning and Ortho-mosaicking of UAS Imagery for Remote Sensing in Precision Agriculture on a Subsurface Drip Irrigated (SDI) Corn Field. Abstract #529, 19th Biennial Research Symposium of the 1890 Association of Research Directors , March 30- April 3, Jacksonville, Florida 2019 (Poster)
- Type:
Conference Papers and Presentations
Status:
Other
Year Published:
2019
Citation:
J. Pandya*, T. Ford, K. Davis, and A. Nagchaudhuri, FarmBot- A Platform for Backyard Precision Farming: Installation and Initial Experimental Layout Abstract #534 19th Biennial Research Symposium of the 1890 Association of Research Directors , March 30- April 3, Jacksonville, Florida 2019 (Poster)
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Progress 04/01/17 to 03/31/18
Outputs
Target Audience:The first year efforts for the grant, builton the past successes of the ongoing efforts in precision farming and remote sensing from unmanned systems in the broader context of smart farming and agricultural automation to improve nutrient and water use efficiency in production agriculture. As in the past the project team worked closely with the farmpersonnel on campus and brought together faculty and students from science, technology, engineering, agriculture, and mathematics (STEAM) backgrounds in a vertically integrated multidisciplinary team to advance the project goals and raise awareness among a broader base of campus community to embrace salient social, educational, ,and research priorities of 1890 land grant mission of the campus. Besides students and campus community, the project team was also involved in the Beltsville Agriculture Research Center Poster Day on April 25, 2018 that was integrated with the the 2nd1890 ARD & USDA-ARS Food Safety Consortium Symposium (April 23-25, 2018) that was attended by NIFA personnel, faculty and students from 1890 institutions, researchers from Beltsville and other USDA-ARS and 1890 Agriculture Research Directors(ARD). The venue also provided an opportunity to showcase a synergistic project led by the project director related to design and development of an autonomous boat for water quality monitoringinvolving UMES engineering students. The project leader is alsoco-chairing a session on "Mechatronics and Embedded Systems in Agriculture" at The 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications later this summer The project leaders have also reinforced ties with the UMES Extension, Vendors for farming technologies, and K-12 institutions around the campus. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Some of the undergraduate students and FDST doctoral student got an opportunity to attend and present their work at the USDA ARS Beltsville, during the Beltsville Agriculture Research Center Poster Day at the Association of 1890 Research Directors and USDA-ARS Joint Food Safety Symposium during April 23-25, 2018. The opportunity provided the students and the project team to meet with various USDA-NIFA personnel, interact with members of other 1890 universities and USDA research scientists. The project team havefamiliarized themselves with the newly acquired PIX4D and SMS Advanced Software environments that are being extensively utilized for remote sensing and agricultural data analysis through online webinars and self-guidance. The team will consider attending some of the training workshops conducted by the vendors when they are held in the vicinity of the UMES area. How have the results been disseminated to communities of interest?The project team interacts closely with UMES extension and research collaborator at USDA - ARS Beltsville to advance project goals and disseminate project results. Vendors who have installed SDI system and other field devices on campus are also integrated with the farming community in and around the eastern shore area and disseminate project efforts by word of mouth. The project team has also interacted with the campus community at large to disseminate project goals within and outside the university. The project leader and team members plan to attend and present their work at the annual conference of American Society for Agriculturaland Biological Engineers (ASABE) and Agricultural Mechatronics and Embedded Systems Session at the 14th IEEE/ASME Mechatronics and Embedded Systems Application (MESA 2018) later in 2018 summer. Beside disseminating project results, both conferences will provide additional opportunities of professional development in relevant fields addressed by the project. What do you plan to do during the next reporting period to accomplish the goals?The project team has planned a follow up field experiment with the newly laid out Subsurface Drip Irrigation(SDI) system for the 2018 growing season of corn. It is planned to divide the SDI field area in two portions. One portion will receive a flat application of nitrogen while the other will receive nitrogen application based on a prescription map developed from sUAS imagery at an appropriate growth stage of corn. Other than nitrogen application the irrigation levels will also be varied and two seeding densities will be studied during the field experiment to investigate effects of yield outputs for variations in irrigation, nutrient application and seeding rates. The project team will devote signifcant effort to fully utilize the capabilities of the PIX4D software to stitch and analyze CIR and thermal imagery acquired from sUAS imagery. ArCMAP, PIX4D and SMS Advanced softwares will be utilized in conjunction with Sprayer unit and other intelligent hardware implements to effectively conduct the field experiment planned. As in prior years yield data will be recorded using combine harvester retrofitted with a GPS and yield monitor. Image and yield data analyses will also be conducted using appropriate statistical software environments. The project team will continue to publish results in journals and conference proceedings and disseminate project efforts in and outside UMES campus among students, faculty, staff, farmers, K-12 institutions and the broader community at large. The project team will also continue to collaborate with partners such as NASA, USDA ARS, other 1862 and 1890 land grant campuses, Pioneer-Hi Bred and the Vendor that is working with the UMES project team for the SDI set up.
Impacts
What was accomplished under these goals?
In consultation with the UMES farm manager the project team identified a ~15 acre field on UMES campus to install a subsurface drip irrigation(SDI) system to conduct field experiments related to water and nutrient use efficiency as proposed. A vendor was identified and contracted to layout SDI system that allowed20 independently controlled zones in the field. The vendor worked with the project team in expediting the process so that the field could be utilized to conduct a field experiment for the first growing season of corn after the award of the grant by NIFA. A simple field trial was laid out with four irrigation levels ( 1/4,1/8, 1/16, 0 inches of irrigation per day) with five replicates to study water use efficiency. If the soil capacity was saturated or rainfall occurred the irrigation was not applied. For this field experiment a flat nitrogen application was done. A 12 row planter was utilized to seed corn at the rate of 28000 seeds/acre. Pioneer Hi Bred P1197 AM was the seed type used. A 6 row combine harvester retrofitted with Ag Leader yield monitor was used to harvest and collect yield data. Since there was adequate rainfall during the 2017 growing season the effect of irrigation in the yield output wasnot pronounced but inspite of the rainfall ANOVA analysis and Tukey test with the yield data shows signifcant differenceon the yield data for the 0 and 1/4 inch irrigation levels. The doctoral student in the Food Science and Technology(FDST) who serves as the student lead and the involved faculty are working on a paper to document the results in a conference publication for the 2018 proceedings of theAmerican Society forAgriculture and Biological Engineers (ASABE)that will be held in July/August 2018. A new image processing and analysis software has been acquired by the project team. The PIX4D software has advanced features for processing Color InfraRed (CIR) and thermal imagery acquired from small unmanned aerial systems (sUAS). Preliminary trials have been conducted with using the software for thermal imagery acquired from the SDI field experiment for corn in 2018 growing season, however the need for additional hardware modification to geotag thermal imagery has been identified to fully utilize the software for stitching and analyzing UAV based thermal imagery. CIR imagery acquired from sUAS for a field experiment using winter wheat for a synergistic collaborative project that the project team at UMES is involved with alongside University of Delaware and Virginia Tech was successfully stitched, processed, and analyzed using the software. Trial sUAS flights will be conducted in 2018 summer with the CIR and thermal camera to fully explore the capabilities of the PIX4D software. The FDST graduate student and the PI are considering attending PIX4D trainingworkshop in the near future for additional knowledge and familiarity with the software. As proposed the project team has also acquired an automated soil sampler from MagicTech LLC and integrated the system with an All Terrain Vehicle (ATV) that was available in the UMES farm shop and an SMS mobile mapper. Soil sampling was performed on the SDI field prior to seeding using the ATV system on a 0.5 acre grid. The samples were sent to a soil testing and analysis lab and mapped on ArCMAP software. The project team plans to conduct soil sampling before seeding corn for the 2018 growing season and compare the soil nutient status. Particular attention will be paid to soil phosphorus levels. In keeping with the project objectives and goals the project leaders are collaborating with USDA scientists and engineers at USDA ARS Beltsville and NASA Wallops Flight Facility of Goddard Space Flight Center. A vertically integrated team of multidisciplinary STEAM undergraduate students worked alongside the FDST graduate student, UMES farm personnel, and project leaders to execute the broad project goals in the first year of the project executionand will continue to do so in the foreseeable future.
Publications
- Type:
Other
Status:
Other
Year Published:
2018
Citation:
Ford, T., Hartman, C., Nagchaudhuri, A., Mitra, M., Marsh, L., and Daughtry, C., "Analysis of Yield Response with Subsurface Drip Irrigation Strategies, Remote Sensing with UAVs, and Thermal Image Processing" Poster Presentation at the Beltsville Agricultural Research Center(BARC) Poster Day, Beltsville, MD, April 25, 2018
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