Brief Summary of Minutes of Annual Meeting

NCERA 180 Meeting Summary of Meeting Minutes Thursday, 07-24-2014, 8:05 AM, Hyatt Regency Hotel, Sacramento, CA A combined business meeting was held initially between the NCERA-180 and W-2009 groups. Charlie Lee (UGA), W-2009 Chair and Manoj Karkee (WSU), NCERA-180 Chair presided (Summary does not include W-2009 discussions). State reports are due within 30 days, they will be emailed to Joe Luck. Joe will send out a template, the final report is due 09-18-2014. Van K. (180 Admin Rep) NCERA 180 renewal is coming up in the fall of 2015. Next year, we will have to get materials together. February of 2015 will be the time to review application materials. We have 60 days to complete/submit the report from today. USDA climate hubs (climate changes, excessive drought, moisture, etc.) have been designated, but no funding has come yet. An AFRI call in 2015 related to the climate hubs may be out. Appropriations (E & R) activities at the federal level are continuing to erode, impact statements, reporting are going to be critical for continuing funds. Joe Luck mentioned potential USDA focus on extension and technology transfer activities. Ken Sudduth mentioned that past A-Z sessions were to focus on these types of activities related to precision ag. Joe Luck also mentioned that program impact measurements and surveys for extension professionals might be very beneficial if ISPA could develop some program or outreach/tech sessions along those lines. ISPA: Ken Sudduth updated that the organizing committee was pleased that W2009 and NCERA-180 were able to co-locate their meetings with ICPA. They hope that the group(s) might consider the same for the 2016 ICPA conference (location TBD). DC Update from Dan Schmoldt: Reiterated the importance of impact documentation from programs (simple 4 sentences if written correctly can be useful) and this will help his group continue to go help secure funds for ag research, extension, and educational programs. Overview of the 2014 Farm Bill. Mandatory funding for several programs has returned (SCRI, OREI, BFRDP). Centers of Excellence were approved for funding, this will give priority to researchers if they are involved, for competitive grants. This could be very important for securing federal funding in the future! Matching requirements for FY 2015 may not require matching funds (AFRI SCRI) 100% match from non-project resources will be required. However, land grants (and other institutions) will not be required…this will be exceptions, see programs for details. This will likely impact non-land grand universities, for example. Dan reviewed federal funding status, AFRI should have around $325M. Recommendation from PCAST report suggested to create innovation institutes to research issues related to agriculture projects. Three requested at $25M per year (total $75M for this year) but the proposal was not approved. Review the PCAST report if you would like to see some of the major topics identified for research needs. AFRI Foundation support will be around $120M in 2014. Ag System Technology, trying to get back to releasing RFA around August, September (original cycle). Program description is quite broad again, funding will continue as in the past, $9M will be available for the current year. Challenge Areas will have $27M for 2014 (Food Security, etc.). NRI program has continued interested among multiple agencies (NSF, NASA, DARPA, DoD). MOUs among the agencies are being signed. RFA is coming out in a couple of weeks, proposals due in November. Average NIFA NRI funds has averaged around $818K. SCRI program has $80M per year for the foreseeable future. Integrated projects are still mandatory. $25M set aside for citrus insect and disease monitoring. New matching funds requirement will apply. Brief review of other programs currently in the: NIFA Fellowships, SARE, NIWQ program. Organic Ag Research and Extension, Crop Protection and Pest Management, Alfalfa and Forage Research Program, Beginning Farmer and Rancher program. New MOU w/ NSF for Cyber-Physical systems was just signed. Internet of Things, creating a smarter agricultural system. Solicitation will likely come out in January. Group Questions for Dan Schmoldt: Q: Cyber physical relations-how will ag collaborators deal with data privacy. A: data security is one emphasis of the program, certain levels need to be considered, server, cloud, wireless networks. Q: Will CARE program continue? A: CARE program will be a part of the AFRI Foundation program, they will continue. Director was very supportive of this particular program. Q: Comment of specialty crop block grant program at the state level? A: Funds go directly to Dept. of Ag within each state, the states decide which projects. Future status of that program (Ag Market Service) is unknown by Dan. Further group discussions on federal funding: Dr. Lee: NRI funded 4 projects within the group of W2009 in the previous year. WSU is moving toward a project for mechanized apple harvesting. Recap of Technical Tours/ICPA: Tours were very good, Srini Upadhyaya did an excellent job with tours, the numbers of tourists and questions posed by the group was an indication of success. Could attendees be “parsed” by country? This would be a great metric as well in terms of interest by others. W2009 will be in September 13-16, co-located with a meeting in Prosser (Food, Vegetable Handling). Group agreed that tours were excellent, sessions w/ ICPA were great. UAV needs-imagine stitching is a priority concern, this can be very costly. Future uses besides imagine (data collecting for samples) is an example. Reza Ehsani shared their experience with applying for a COA for flying UAVs for research activities. Dharmendra Saraswat also shared some experiences with U of Arkansas. Richard Ferfuson also contributed some experiences from UNL. Some type of improvement/development component likely needs to be included in COA application. Comments about ASABE 2014: Safety standards for robotics and automated field. Three committees were involved (along with IEEE), MS-58, IET-318, MS-48 with initial discussions. A task force committee was formed. eForums will be used with ASABE to get information, a website at WSU will be hosted to keep information. CIGR world congress will be in Beijing in September. Some key symposia will be associated with that meeting. International forum for precision agriculture (round table) to discuss future issues. ECPA 2015 will be in Israel in July. Update on past AETC meeting was provided by Joe Luck and mention of the future 2015 AETC meeting dates and location (02-09 and 02-10) in Louisville, KY. Officer Elections for upcoming year: NCERA-180: Election for a Vice-Chair. Dr. John Fulton from Auburn was nominated by Joe Luck Nominations were closed, and Dr. Fulton was accepted by acclamation. Further discussions focused on planning for the 2015 meeting to be held in Lincoln, Nebraska. Challenges continue to be getting groups interested to attend the meeting. Joe and Richard will begin planning for the meeting and continue to involve the group throughout the planning process. Future discussions need to focus on the NCERA 180 group mission and developing a unique service that it provides. Attendees felt that the group provide an opportunity for networking which would be especially beneficial for new faculty and those with R&D programs in industry. Government and other public groups may also benefit from continuity. Van Kelley made a suggestion for group leaders to contact administrators within the region to ensure that their Universities were represented and continue working to get industry involvement.

---Research Activities by State--- ---Arizona--- Currently funded projects for the reporting period include: Precision canopy and water management of specialty crops through sensor-based decision making. Pedro Andrade-Sanchez, Edward Martin, Murat Kacira, James Walworth, Trent Teegerstrom. Research funded by Specialty Crops Research Initiative - NIFA - USDA. Sensor-based Management of Mid-season N Fertilizer in Durum Wheat. Pedro Andrade-Sanchez and Michael Ottman. Research funded by Arizona Grain Research and Promotion Council. Development of economically viable variable rate P application protocols for desert vegetable production systems. 2013-2015. Pedro Andrade-Sanchez and Charles Sanchez. California Department of Food and Agriculture. Fertilizer Research and Education Program. Field-level analysis of yield variability in irrigated cotton in Arizona – 2013-2014. AZ Cotton Growers Association. ---California--- Precision canopy and water management of specialty crops through sensor-based decision making (SCRI-USDA-NIFA-2010-01213. During 2014 growing, we continued our work with precision canopy and water management. The goal of this project is to develop technologies necessary to implement precision canopy and water management in specialty crops and to evaluate socio-economic implications of such practices. Please visit http://ucanr.org/sites/PCWM/ for more information on the project. Canopy Management: A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project used proximally sensed PAR interception data measured using a lightbar mounted on a mobile platform and a crop growth model to estimate potential yields of almond and walnut trees. An analytical model was developed to estimate PAR intercepted by the tree in which tree canopy was assumed to be spherical in shape. PAR intercepted by a tree was estimated taking into account the effect of row spacing, tree spacing within the row, latitude and longitude of the orchard, day of the year and row orientation. Scans were collected at solar noon in almond and walnut orchards during the 2012 and 2013 growing seasons. Moreover, diurnal scans were also collected during 2012. The results for the 2012 and 2013 seasons showed that the total amount of PAR intercepted by a block of five trees at any time during the day can be found analytically using one lightbar scan, early in the season, as a reference to estimate the radius of the canopy and its optical density. A good correlation was found between measured values of PAR intercepted and estimated values of PAR intercepted. A good correlation was also found between yield (for both actual and potential) and absolute midday PAR intercepted, and between actual and potential yield for both almond and walnut trees. Moreover, the actual yield from those blocks with lower absolute midday PAR intercepted was closer to their respective potential yield than those with higher absolute values of PAR intercepted. This result indicates that there is a potential to use spatially variable PAR interception data to implement site-specific input management and enhance production. The simulations showed that the effect of the tree spacing over the orchard productivity is strongly influenced by the tree size. This highlights the need to evaluate the effect of the tree growth over several seasons to obtain the orchard configuration that maximized the profit in the long run. Our results also suggest that the overlap effect is an important factor to be considered by models of PAR interception. This shading is the key information necessary to optimize spacing between trees so that they can capture maximum amount of PAR. Precision Water Management: Continuous Leaf Monitor: Almond and walnut are two major crops grown in the Central Valley of California. With virtually no rainfall in this area during summer, these crops need to be irrigated throughout the season. There is a demand for using irrigation scheduling tools for effective use of very limited supply of water available in California. Leaf temperature measurement using infrared thermometers has been used to predict plant water stress or to develop different indices to quantify plant water stress, but mostly on field crops. There have been very few studies conducted on tree crops. In this study, an inexpensive, easy to use sensing system called ‘Leaf Monitor’ was developed and evaluated to continuously measure leaf temperature and relevant microclimatic variables in the vicinity of a leaf for prediction of plant water status for tree crops. The system was installed on orchard trees to continuously monitor a selected leaf on each tree by logging leaf temperature, air temperature, relative humidity, wind speed and Photosynthetically Active Radiation (PAR). This study also proposed a method to develop a modified crop water stress index (MCWSI) in which reference well watered baseline was developed after every irrigation event for each tree for incorporating any temporal variability throughout the season. Design of leaf monitor also assists in controlling levels of disturbance variables like wind speed and light conditions. Leaf monitors were installed in almond and walnut orchards as a part of a wireless mesh network. Data were obtained remotely over the web, and daily MCWSI values were calculated by assigning first day after irrigation as the reference day. MCWSI values were found to be highly correlated with measured plant water stress. Sensing system has potential to be used as irrigation scheduling tool as it was able to provide daily stress index value which follows similar pattern as the actual plant water stress. Thermal IR Based Canopy Temperature Sensing Using a Drone Copter (Unmanned Aerial Vehicle): Monitoring water stress in specialty crops to increase water use efficiency (WUE) is becoming more necessary when faced with the reality of depleting water resources. Leaf temperature (TL) of almond [prunus dulcis] and walnut [juglans regia] trees has been shown to be closely linked to stem water potential, a sensitive indicator of stress in woody plants. This study was conducted to explore the feasibility of remotely measuring canopy temperature (Tcan) of walnut and almond trees with a small, inexpensive unmanned aerial vehicle (UAV). An infrared (IR) point sensor was installed with a lightweight camera on the underside of a multi-rotor UAV. The UAV was flown over a targeted tree canopy recording temperature and images. Image classification was used to identify the ground contents of each temperature measurement, and a linear system of equations utilizing the image/temperature records pertaining to a targeted tree canopy was established to approximate the temperature of the sunlit and shaded portions of that canopy. Analyses of three flights over almond tree canopies approximated the temperatures of the sunlit and shaded portions of the canopies within an average of 2.2oC of their respective ground truths for both portions, and analyses of four flights over walnut canopies approximated the sunlit and shaded portions within 1.0 and 1.3oC of their respective ground truths, the average difference for all temperature approximations between the seven trees being 1.5oC. With canopy temperatures ranging from 16 to 40oC, the approximations fit a linear trend with a coefficient of determination (r2 value) of 0.96. The use of an IR sensor coupled with a camera to establish a linear system of equations for individual trees showed promising ability to approximate a tree’s canopy temperature. This method also has the advantage of distinguishing between the sunlit and shaded portions of the canopy. ---Florida--- A novel technique was developed to detect immature green citrus in tree canopy under natural outdoor conditions. Shape analysis, texture classification, SVM, graph based connected component algorithm, and Hough line detection were used to identify fruit and to remove false positives. Keypoints by scale invariant feature transform algorithm were used to further remove false positives. The algorithm was able to detect and count 80% of citrus fruit for validation. This method was published in the Biosystems Engineering. An algorithm for detecting immature peach fruit on the tree was also developed and was published in the Precision Agriculture journal. Hyperspectral images of blueberry fruit were taken in a commercial blueberry field. Mature fruit, intermediate fruit, young fruit and background were the four classes to be studied. A supervised band selection method was proposed using Kullback-Leibler divergence (KLD). Based on the analysis, six combined bands were selected. The test result showed that the proposed band selection method worked well for the task of blueberry growth stages detection. Using polarized filter and narrow band imaging technique, a portable machine vision system was developed to detect the citrus greening symptomatic leaves. This study yielded detection rates of over 90%, and this method was accepted for publication in the Transactions of the ASABE in 2014. Different dimension reduction methods were investigated to detect the citrus greening disease using airborne hyperspectral imaging. These methods yielded detection accuracies of 63-93%. A novel detection method, ‘extended spectral angle mapping (ESAM)’ was developed to detect citrus greening disease using Savitzky-Golay smoothing filter, SVM and vertex component analysis. A high detection accuracy of 86% was achieved for validation. Also satellite images were used to detect citrus greening disease over large areas from a Landsat 5 Thematic Mapper (TM) and a WorldView-2 images. It was demonstrated that there is a great potential for citrus greening disease detection using a satellite image. Another machine vision system was developed to detect dropped citrus fruit on the ground along with a GPS receiver. It can count the number of fruit and estimate mass of the fruit with an accuracy of 89%. A prototype laser weeding system was developed to kill in-row weeds using machine vision and a set of lasers to demonstrate the concept. This work was presented at the 5th Asian Conference on Precision Agriculture. An automated in-row weed control system was being tested, consisting of an ultrasonic sensor and a pair of pinch rollers. A preliminary field test results showed that the mechanical weeding machine were able to uproot weeds. Weeds height was ranged from 10 cm to 18 cm. Further field experiments will be conducted to evaluate the efficacy of the intra-row weeding prototype and crop injury. Equilibrium moisture content (EMC) for triticale seed was investigated. A prediction algorithm was developed to represent the relationship between relative humidity and EMC with coefficient of determination (R2) equal to 0.99. It was also found that the Modified Henderson equation represents this relationship accurately. A method was developed to determine the degrees of infestation (DI) in the triticale seed at two growth stages by measuring their spectral reflectance. The reflectance was measured from 400 nm to 2500 nm. The result showed that the DI for larvae 2nd instar stage could be detected using an average reflectance in 400 - 410 nm, with an R2 of 0.87. The adult outside stage also resulted in a good prediction, where it yielded four wavelengths that provided an acceptable result with an R2 of 0.87 for the adult outside stage. ---Kansas--- Use of sUAVS in agricultural applications: Research projects are being conducted in Manhattan (KS) at the Kansas State University –Department of Agronomy- on winter canola and corn crop. The goals of this group are to identify the potential uses of the sUAVS for agronomic crops with emphasis on serving large farming systems and also research programs. The team is also working with the Agricultural Economics department to understand the benefits and costs in using this technology for providing services to farmers, public and private sectors. In addition to the latter, collaborations with the Aviation program at K-State Salina for developing new platforms and improving data collection are continuously pursued. On the research side, measurements in corn are involving but not limited to: canopy temperature, photosynthesis, leaf area index, plant height, number of green leaves, and biomass. The collection of new information using the sUAVS is related to the calculation of NDVI (estimation of biomass) and canopy temperature (thermal camera). Extensive testing of this last technique is currently under evaluation in collaboration with scientist of the Department of Biological and Agricultural Engineering. Canola biomass, nutrient uptake, and stand counts. Measurements of biomass and nutrient concentration are correlated with NDVI determinations at diverse growth stages. Determination of early stand count is also pursued comparing “ground truthing” information with the imagery collected from the sUAVS. In overall, these examples of the use of sUAVS together with the preparation of support decision tools will determine the potential contribution and impact of this technology in the precision agriculture discipline with the primary and ultimate objective of assisting producers, crop advisors, and other agri-business professionals for facilitating the decision-making process. ---Nebraska--- At the University of Nebraska-Lincoln, several projects involving site-specific crop management and precision agriculture technology research include Richard Ferguson in the Department of Agronomy and Horticulture and Joe D. Luck in the Department of Biological Systems Engineering. Projects include: Interactions of Water and Nitrogen Supply for Irrigated Corn across Field Landscapes: This existing project was completed in 2013. The primary goal of the project was to evaluate response of irrigated corn to site specific water and N management across variable landscapes. The project provided a good deal of infotrmation regarding the performance of various soil moisture sensing technologies and the potential for variable-rate water and N management. Evaluation of Scrubber Ash as Soil Amendment: This research project was initiated in 2013, with the goal being to establish potential uses for this coal-production by product. This project utilized site-specific management application techniques to apply, track, and evaluate the addition of Scrubber Ash and the effects on corn yield. Preliminary results are expected in the fall of 2014. Improving Irrigation Water and Energy use Efficiency through Accurate Spatial and Temporal Management: The primary goal of this project is to determine guidelines for the adoption and management of variable-rate irrigation (VRI) systems based on spatial datasets that can be acquired by producers throughout the growing season. Objectives include the demonstration of potential water and energy savings by adopting VRI management. Deployment and Evaluation of a Tracking System for Improved Animal Management: Precision livestock management is evolving as a potential method for improving management of animals in confined spaces. The goal of this project is to build on preliminary research using commercially available systems to track animal movement. Specific objectives include the development of advanced identification techniques based on animal behavior signatures. Promoting Adoption of In-Season Canopy Sensor-Based Nitrogen Fertilization of Corn through the Nebraska On-Farm Research Network: While primarily an Extension activity, data will be collected during this project to improve N recommendation algorithms for use with in-field N application using crop canopy sensors. Demonstration sites will be setup across the state in five difference Natural Resource Districts to cover a broad range of climatic regions. ---North Dakota--- Use of precision farming methods has increased in North Dakota within the past several years. Many farmers use auto-steer on their farm machinery, have yield monitors in their combines and DGPS aids in variable-rate fertilizer application. Variable-rate fertilizer application is common across North Dakota. AgVise Laboratories, Northwood, ND, is the state’s largest soil and plant analysis laboratory for agriculture. They reported in December, 2013 that they received more samples from zone-sampled fields than they received for whole-field composite tests for the first time in 2013. Use of precision farming methods has been adopted by growers of all crops, not just sugar beets. Research and Extension education in precision farming methods is supported by the following efforts (Franzen). Publication April, 2014 of new corn N recommendations with emphasis on side-dress N application using active-optical sensor algorithms for the GreenSeeker and Holland Crop Circle sensors. Publication by September 1, 2014 of algorithms for corn using the GreenSeeker and Crop Circle sensors. Ongoing research into additional or complimentary in-season N management tools for corn. Research began spring 2014 to build a database to support the use of active-optical sensors for in-season N application in sunflower. With work from Anne Denton and her colleagues and students in the NDSU Computer Science Department, a ‘machine-learning’ program for use by farmers adopting active-optical sensor in-season corn N application is being developed. With this tool, farmers can incorporate on-farm active-optical sensor data with published sensor algorithms, and morph published NDSU algorithms into their personal farm algorithm. Preliminary relationships between active-optical sensors and sugar beet yield and quality have been established and more work on improving the data base is planned. Relationships between NDVI satellite imagery (Rapid-Eye) and corn, sunflower, spring wheat and sugar beet yield have been produced, but more data is required to use these relationships as a logistics tool for farmers to screen fields for in-season N application and determine total in-season fertilizer N needs. With Joel Ransom, NDSU Plant Sciences Department, data is being accumulated to support the use of active-optical sensors with red edge NDVI capabilities to predict the need for post-anthesis N application for spring wheat protein enhancement to avoid protein discounts and take advantage of possible higher protein premiums from grain buyers. Additional Research efforts supported (Nowatzki) include: Use of UAV’s to enable improved field scouting, usefulness of compaction sensing for improved crop yield in North Dakota, and Use of active-optical sensors for use in aiding soybean fertilization (with Hans Kandel, Plant Sciences Department). Research from the Computer Science Department (Denton) include the use of data-mining techniques has shown that rainfall data can be used most effectively by relating monthly rainfall data to sugar beet yield and quality prediction. Ignoring rainfall amounts greater than 1 inch within a 24 hour day improved model prediction. Including small amounts of rainfall within a 24 hour period was surprisingly important to include in the model. ---Washington State University--- At Washington State University, Manoj Karkee, Qin Zhang and their teams conducted several research projects and achieved substantial accomplishments in developing systems and technologies for precision and automated agriculture. Major projects and corresponding accomplishments are listed below. 3D Machine Vision for Improved Apple Crop Load Estimation Accurate estimation of apple crop-load is essential for efficient orchard management. We designed an over the row platform capture images from two side of apple canopies to minimize the occlusions and improve the accuracy of crop-load estimation. A tunnel structure was used to minimize the variation in lighting condition and artificial lights were installed for night time operation. A color camera, a 3D camera and an orientation sensor were mounted in the sensor platform and were moved along rows of apple trees in three different commercial orchards of Allan Bros. Inc., Prosser, WA. Images were capture in both day and night times. A apple identification algorithm and a 3D mapping algorithm was used to count apples while avoiding duplicate counting of apples that were visible from both sides of tree canopies. Crop load estimation improved by approximately 20% when imaged from two sides compared to that with single-side imaging. Human machine collaboration for automated harvesting of tree fruit The long-term goal of this work is to reduce dependency on human labor through mechanization and human-machine collaboration while increasing yields of premium quality fruit. The overall objective is to develop a framework for knowledge transfer and collaboration between human and machine. This objective will be achieved through the understanding of the dynamics of the hand picking of fruit, development of an effective end-effector based on the knowledge of hand picking, and a framework of hardware and software for optimal collaboration between human and machine for fruit identification. A trans-disciplinary team of experts is involved in this project, which is crucial for the successful completion of these activities. Development and Optimization of Solid-Set Canopy Delivery Systems for Resource-Efficient, Ecologically Sustainable Apple and Cherry Production This project is a subcontract to a SCRI project with Michigan State University. This is a multidisciplinary research and extension project to develop, evaluate, and deliver resource-efficient, innovative management technologies and tactics for apple and cherry production systems. It aims to establish innovative delivery technologies for canopy and orchard floor inputs (including high efficiency irrigation systems, precision-activated micro-emitters, and reduced risk pesticides) to address critical fruit production needs as identified by commodity PMSPs and the Technology Roadmap for Tree Fruit Production. Direct outcomes of system implementation that will be analyzed include: economic and agro ecosystem impacts. Sociological research will focus on how these integrated technologies impact urban-farm relations, barriers to grower adoption, and how these factors can inform better extension and educational programmatic efforts. Design and Development of Apple Harvesting Techniques This research aimed to investigate a few conceptual end effector designs capable of harvesting a cluster of apples in fruiting wall canopy architecture. A rotational robber-wheel based technique and a dual motor-based shaking system were developed and evaluated. Initially, the technology has been applied to apples but the extension to other similar-size fruits such as pears may be possible. The results from 2 years of field evaluation showed a successful fruit removal technique applicable to apples grown on a trellised orchard system. Signs of branch punctures were visible on some of the apples. A method to seclude the apple from any branch was tried. Apples that were grown on small spurs tended to be removed easier than apples growing on long flexible branches. Long branches allowed apples to move more than apples growing on small spurs. This flexibility reduced the effectiveness of both rotational and shaking mechanisms. Horticulture can play an important role in aiding the fruit removal technique described in the above research. Multi- and Hyper-spectral imaging for potato stress sensing Hyperspectral imaging system was used as a non-contact sensing instrument in this study for detecting nitrogen stress in potato plants non-destructively. An experiment was setup with potato plants planted at five different nitrogen levels in a research field. Reflectance plots of plant leaves at different nitrogen levels showed differences in spectral signature. Spectral indices were calculated from reflectance data and were correlated with nitrogen levels measured in the lab with leaf samples. A multivariate linear model is being developed in this study to predict nitrogen levels using reflectance at different frequencies. Red Raspberry trellising demonstration plot for development of automation Technologies: Cane management in red raspberry production is highly labor intensive. Labor availability is uncertain at best and labor cost is increasing. Currently, Washington growers estimate the pruning and tying cost in red-raspberry production to be from $500 to $800 per acre. In addition, labor is at risk for chronic and acute injury. Mechanization has the potential to substantially reduce labor use from cane management. Through this project, we established a red raspberry plot in Prosser, WA and collected preliminary data with different horticultural systems established in Mt. Vernon, WA. Further evaluations of different types cane management techniques will be carried out to identify mechanization friendly system for pruning and tying while maintaining or improving fruit quality and yield. Field phenomics platform development This project is to develop a field research platform and conduct preliminarily tests based on an automatically navigated and steered agricultural tractor. Field-based sensor and imaging devices will be mounted on the platform to efficiently collect data related to crop productivity, input-efficiency, and health while simultaneously applying methods to determine and account for spatial variation due to soil heterogeneity. This automated field research platform, with state-of-the-art imaging, sensing, and positioning/guidance systems, will be capable of rapid, in situ, assessment of crop nutrient and water status, crop health, vigor and productivity, and other important characteristics. ---Extension/Outreach/Teaching Activities by State--- ---Arizona--- Invited Seminars: Tree monitoring for advanced irrigation control. Presentation at the Arizona Pecan Growers Association Annual Meeting on the use of soil and plant sensors for irrigation timing in pressurized systems. Tucson, AZ, 9/13/2013. Development of cotton management app for irrigated cotton in AZ. CottonInc precision management meeting. New Orleans, LA, 1/8/2014. Variable rate management of P fertilizer for vegetable production in the low desert. Presentation at the Yuma Ag Summit on first year results of experimental work. Yuma, AZ 2/27/2014. Presentations during statewide extension and outreach events: Cotton pre-season meetings. Topic: Using mobile devices for improved management. Live demonstration on access and use of the University of Arizona cotton calculator with web-enabled mobile devices. Avondale AZ, 2/20/2013; Gilbert, AZ, 2/22/2013; Coolidge AZ, 2/26/2013; Marana AZ, 2/27/2013; and Safford AZ, 2/28/2013 Delivered field demonstrations for delegations visiting Arizona including: Mexico's INIFAP (2/15/2013), Chapingo University irigation students (10/30/2013) and Chinese irrigation district managers (11/20/2013) Workshop in spraying technology using new displays for GPS-based rate and section control (October 10, 2013). Maricopa County Extension. Workshops and other events: Field phenomics part I: Developing and using a sensor array. On-line webinar, October 30, 2013. Materials available at the following URL: http://www.extension.org/pages/68269/part-one-of-field-phenomics:-developing-and-using-a-sensor-array Workshop in field-based high throughput phenotyping. NSF-funded workshop that targeted graduate students and early-career plant breeders in the use of electronic equipment such as plant sensors, GPS, data-loggers, and data post-processing and analysis. Maricopa AZ 4/7-10/2014 Specialized-media articles: Gabrielle Fimbres. UA-developed apps aid Arizona cotton farmers. UANews, Office of University Communications. University of Arizona. Tucson, AZ. August 27, 2013. Karl Haro von Mogel. Taking the phenomics revolution into the field. CSA News 58(3): 4-10. ASA-CSSA-SSSA. March 2013. Cary Blake. Variable-rate management of P fertilizer. Western Farm Press. Agricultural Technology and Irrigation. Oct 2013/Vol 18 No.2 ---Kansas--- Extension Education for Ag Professionals: A total of 10 meetings were provided on the uses of sUAVS in agriculture since the last August 2013 (more than a year). This constitutes a continuous demand for our clientele and key-stake holders in understanding the uses of the new technologies and the impact of those in the future of agricultural production systems. Participation resulted in training to farmers, extension Ag agents, crop consultants in the use and agronomic applications of sUAVS technology. The extension effort impacted 100 agribusiness stakeholders in the last year and continuous to promote information on the use of this technology for agricultural purposes. ---North Dakota--- Extension (Nowatzki) continues to have great success with the Precision Ag Workshop in Jamestown, ND. Winter 2014 the event was attended by over 200 producers and ag-industry people over a two day period. ---Nebraska--- Recently developed Precision Ag Data Management Workshops have been developed to lead producers through hands-on farm management software activities using agriculture spatial data layers. The focus of the workshops is to communicate how to perform data collection and analysis to enable site-specific crop management in their operations. Emphasis is placed on details to connecting the farm office to the field equipment. Over 120 have attended the workshops in 2013 and 2014; workshops were held in Nebraska and Kentucky and represented a collaborative effort of multiple Universities in the NC region. The annual Nebraska Agricultural Technology Association (NeATA). Association Conference was held in February, 2014. Attendees included crop producers, researchers and advisors related to site-specific crop management and other emerging agricultural technologies. The conference includes a day long symposium followed by a second day of breakout sessions. Over 150 attended the 2014 conference in Grand Island, Nebraska. For more details visit: http://neata.org/ Site-Specific Crop Management. AGRO/MSYM/AGEN 431. Senior level course on agronomic and engineering aspects of site-specific crop management. 3 credit hours. Offered fall semesters. The enrollment in fall 2013 was 55; currently 51 students are enrolled in the fall 2014 semester.

Andrade-Sanchez P., M.A. Gore, J.T. Heun, K.R. Thorp, A.E. Carmo-Silva, A.N. French, M.E. Salvucci, and J.W. White. 2013. Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology 41(1) 68-79. Andrade-Sanchez P. and Heun J.T. 2013. Operation of yield monitors in Central Arizona: Grains and cotton. Bulletin AZ1598. The University of Arizona - Cooperative Extension. Tucson, Arizona 85721 Andrade-Sanchez P. and J.T. Heun. 2013. Sensor-based estimation of cotton plant height: Potential for site-specific plant growth management. Paper No. 131668472. ASABE Annual Int. Meetng. Balasundram, S.K, H. Memarian, and R. Khosla. 2013. Estimating Oil Palm Yields Using Vegetation indicesDerived from Quickbird. Life Sciences Journal 10(4) 851-860. Balasundram, S.K, H. Memarian, M.Y. Hakimah, L. Osmund, S. Nini and R. Khosla. 2013. Comparison between Pixel-based and Object-based Image Classification of a Tropical Landscape using SPOT-5 Imagery. J. Appl. Remote Sens. 7(1), 073512 (Aug 28, 2013). doi:10.1117/1.JRS.7.073512 Bansal, R., W. S. Lee, and S. Satish. 2013. Green citrus detection using Fast Fourier Transform (FFT) leakage. Precision Agriculture 14(1): 59-70. http://dx.doi.org/10.1007/s11119-012-9292-3. Cao, Q., Y. Miao, H. Wang, S. Huang, S. Cheng, R. Khosla and R. Jiang. 2013. Non-destructive estimation of rice plant nitrogen status with Crop Circle multispectral active canopy sensor. Field Crops Research. 154:133-144 Choi, D., W. S. Lee, R. Ehsani, and A. Banerjee. 2013. Detecting and counting citrus fruit on the ground using machine vision. ASABE Paper No. 131591603. St. Joseph, Mich.: ASABE. Crawford, K., J. Roach, R. Dhillon, F. Rojo., and S. K. Upadhyaya. 2014. An inexpensive aerial platform for precise remote sensing of almond and walnut canopy temperature. A paper presented at the 12th International Conference on Precision Agriculture in Sacramento, CA, USA. July 20-23. Dhillon, R., V. Udompetaikul, F. Rojo, S. Upadhyaya, J. Roach, and D. Slaughter, B. Lampinen, K. Shackel. 2014. Detection of plant water stress using leaf temperature and microclimatic measurements in almond, walnut, and grape crops. Transaction of the ASABE (In press). Dhillon, R. S., F. Rojo, J. Roach, and S. Upadhyaya. 2014. Handheld sensor suite for plant water status measurements and a comparison of different techniques to measure canopy temperature in orchard crops. ASABE paper 141893976. ASABE St. Joseph, MI 49085. Dhillon, R., F. Rojo., J. Roach., R. Coates, S. K. Upadhyaya, M. Delwiche, and C. Han. 2014. Development and evaluation of a leaf monitoring systemfor continuous measurement of plant water status in almond and walnut crops. A paper presented at the 12th International Conference on Precision Agriculture in Sacramento, CA, USA. July 20-23. Eduardo, Claudio, R. Khosla, and R. Reich. 2013. Interpolation type and data computation of crop yield maps is important for precision crop production. J. of Plant Nut. Soil Analysis. (Accepted in Press). Garcia-Ruiz, F., S. Sankaran, J. M. Maja, W. S. Lee, J. Rasmussen, and R. Ehsani. 2013. Comparison of two aerial imaging platforms for identification of Huanglongbing infected citrus trees. Computers and Electronics in Agriculture 91: 106-115. http://dx.doi.org/10.1016/j.compag.2012.12.002 He, L., J. Zhou, X. Du, D. Chen, Q. Zhang, and M. Karkee. 2013. Energy Efficacy Analysis of a Mechanical Shaker in Sweet Cherry Harvest. Biosystems Engineering, 116(4): 309-315. Katti, A. R., W. S. Lee, and C. Yang. 2013. Laser weeding system for elimination of in-row weeds. In Proceedings of the 5th Asian Conference on Precision Agriculture (ACPA), June 25-28, 2013, Jeju, Korea. Khedher Agha, M. K., W. S. Lee, R. A. Bucklin, A. A. Teixeira, and A. Blount. 2013. Equilibrium moisture content equation for triticale seed. ASABE Paper No. 131620333. St. Joseph, Mich.: ASABE. Khedher Agha, M. K., W. S. Lee, C. Wang, R. W. Mankin, N. Bliznyuk, and R. A. Bucklin. 2013. Determination degrees of insect infestation in triticale seed using NIR spectroscopy. ASABE Paper No. 131592957. St. Joseph, Mich.: ASABE. Lee, W. S. 2013. Book review: N. Kondo, M. Monta, and N. Noguchi, Agricultural robots - mechanisms and practice, Corona Publishing Co., Ltd. Tokyo, Japan, 2011, xii + 348 pp., ISBN: 978-4-87698-553-1. Journal of Biosystems Engineering 38(2): i. Li, H., W. S. Lee, and K. Wang. 2013. Airborne hyperspectral imaging based citrus greening disease detection using different dimension reduction methods. ASABE Paper No. 131592802. St. Joseph, Mich.: ASABE. Li, H., W. S. Lee, K. Wang, R. Ehsani, and C. Yang. 2013. ‘Extended spectral angle mapping (ESAM)’ for citrus greening disease detection using airborne hyperspectral imaging. Precision Agriculture. http://dx.doi.org/10.1007/s11119-013-9325-6. Li, H., W. S. Lee, and K. Wang. 2013. Spectral mixture analysis based citrus greening disease detection using satellite image of Florida. In Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). 25-28 June 2013, Gainesville, Florida, USA. Lo, T.H., L. Mateos, D.M. Heeren, and J.D. Luck. 2014. The applicability of VRI for managing variability in infiltration capacity and plant-available water: a preliminary discussion and GIS study. Paper No. 1897710 in Proc. of the 2014 ASABE International Meeting, July 13-16, Montreal, Quebec, Canada. Longchamps, L., and R. Khosla. 2014. Early detection of nitrogen variability in maize (Zea mays L.) using fluorescence. Agron. J Vol. 106 No. 2, p. 511-518. Longchamps, L., R. Khosla and D.G Westfall. 2013. Can fluorescence based sensing detect nitrogen deficiency at early growth stages of maize? In Precision Agriculture. J. Stafford (ed) Wageningen Academic Publishers. The Netherlands. Marx, S.A. and J.D. Luck. 2014. Assessing Accuracy of Machine CAN Bus Data using SAE J1939 and Nebraska Tractor Test Laboratory Data. Paper No. 1897599 in Proc. of the 2014 ASABE International Meeting, July 13-16, Montreal, Quebec, Canada. Miller, K.A., T.H. Lo, J.D. Luck, and D.M. Heeren. 2014. Combining Site Specific Data with Geospatial Analysis to Identify Variable Rate Irrigation Opportunities in Irrigated Agricultural Fields. Paper No. 1896808 in Proc. of the 2014 ASABE International Meeting, July 13-16, Montreal, Quebec, Canada. Moshia, M.E., R. Khosla, D.G. Westfall, J.G. Davis, R. Reich and L. Longchamps. 2014. Precision Manure Management across Site-Specific Management Zones: Grain Yield and Economic Analysis. Agron J. (Accepted: In Press). Moshia, M.E., R. Khosla, D.G. Westfall, J.G. Davis, R. Reich and L. Longchamps. 2014. Precision Manure Management across Site-Specific Management Zones: Nitrogen Mineralization Rates. J. of Plant Nut. Soil Analysis. (Accepted: In Press). Moshia, M.E., R. Khosla, D.G. Westfall, J.G. Davis, R. Reich and L. Longchamps. 2014. Precision Manure Management across Site-Specific Management Zones: Soil Quality. Commun. In Plant Sci and Anal. (Accepted: In Press). Pan, L., Adamchuk, V.I., Ferguson, R.B., Dutilleul, P.R.L. and Prasher, S.O. (2014) Analysis of Water Stress Prediction Quality as Influenced by the Number and Placement of Temporal Soil-Water Monitoring Sites. Journal of Water Resource and Protection, 6:961-971. Patil, V.C., Khalid A. Al-Gaadi, Rangaswamy Madugundu, ElKamil H.M. Tola, Samy A. Marey, A.M. Al-Omran, R. Khosla, S. K. Upadhyaya, David J. Mulla and Ali Al-Dosari. 2014. Delineation of Management Zones and Response of Spring Wheat (Triticum aestivum L.) to Irrigation and Nutrient Levels in Saudi Arabia. International J. of Agri. Biol. 1560–8530; ISSN Online: 1814–959613–035/2014/16–1–104–110. Peter J.A. Kleinman, Anthony R. Buda, Andrew N. Sharpley and Raj Khosla. 2014. Elements of Precision Manure Management. In Precision Conservation. J. Delgado (ed) In press. [Book Chapter] Pitla, S.K., J.D. Luck, and S.A. Shearer. 2014. Multi robot system control architecture (MRSCA) for agricultural mobile robots. In Proc. of the 2014 RHEA Conference, May 21-23, Madrid, Spain. Pitla, S.K., S.A. Shearer, J.D. Luck, N. Lin, B.A Schroeder, and A.A. Klopfenstein. 2013 Work and Load Performance Profiles for Agricultural Field Machinery. Proc. of the 71st International Conference on Agricultural Engineering 2013, Hannover, Germany. Pourreza, A., W. S. Lee, E. Raveh, Y. K. Hong, and H. J. Kim. 2013. Identification of citrus greening disease using a visible band image analysis. ASABE Paper No. 131591910. St. Joseph, Mich.: ASABE. Qiang Cao, Yuxin Miao, Guohui Feng, Xiaowei Gao, Fei Li, Bin Liu, Shanchao Yue, Shanshan Cheng, R. Khosla, and Susan L. Ustin. 2014. Active canopy sensing of winter wheat nitrogen status: an evaluation of two sensor systems. J. of Comp. Ag. (Accepted: In Press) Reich, R., A. Mohammed, R. Khosla, C. Aguirre-Bravo and M. Mendoza. 2014. Influence of Climatic Conditions, Topography and Soil Attributes on the Spatial Distribution of Site Productivity Index of the Species Rich Forests of Jalisco, Mexico. J. of Forestry Research 25 (1) 87-95. Rojo, F., R. Dhillon, S. Upadhyaya, B. Jenkins., B. Lampinen, J. Roach, K. Crawford, and S. Metcalf. 2014. Modeling canopy light interception for estimating yield in almond and walnut trees. A paper presented at the 12th International Conference on Precision Agriculture in Sacramento, CA, USA. July 20-23. Saber, M., W. S. Lee, T. F. Burks, G. E. MacDonald, and G. Salvador. 2013.An automated mechanical weed control system for organic row crop production. ASABE Paper No. 131593595. St. Joseph, Mich.: ASABE. Sharda, A., J.D. Luck, J.P. Fulton, T.P. McDonald, and S.A. Shearer. 2013. Field application uniformity and accuracy of two rate control systems with automatic section capabilities on agricultural sprayers. Precision Agric. 14(3): 307-322. Shaver, T.M., R. Khosla, and D.G. Westfall. 2014. Evaluation of two crop canopy sensors for nitrogen recommendations in irrigated maize. Journal of Plant Nutrition. Vol 37:406-419. Wang, H., Y. Miao, G. Zhao, Y. Yao, and R. Khosla. 2013. Evaluating different integrated precision rice management strategies in Northeast China. In Precision Agriculture. J. Stafford (ed) Wageningen Academic Publishers. The Netherlands. Yang, C., W. S. Lee, P. Gader, and H. Li. 2013. Hyperspectral band selection using Kullback-Leibler divergence for blueberry fruit detection. In Proceedings of the 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). 25-28 June 2013, Gainesville, Florida, USA. Yang, C., W. S. Lee, and P. Gader. 2013. Band selection of hyperspectral imagery for the classification of blueberry fruit maturity stages and leaf. ASABE Paper No. 131593276. St. Joseph, Mich.: ASABE. Zandonadi, R.S., J.D., Luck, T.S. Stombaugh, and S.A. Shearer. 2013. Evaluating field shape descriptors for estimating off-target application area in agricultural fields. Computers Electronics Agric. 96: 217-226. Zhou, J., L. He, Q. Zhang, X. Du, D. Chen, and M. Karkee. 2013. Evaluation of the Influence of Shaking Frequency and Duration in Mechanical Harvesting of Sweet Cherry. Applied Engineering in Agriculture, 29(5): 607-612.