Progress 04/01/23 to 03/31/24
Outputs
Target Audience:The proposed research and extension activities in this proposal are specifically designed to cater to the needs of small-scale grape producers in the U.S. regardless of their vineyard location, management style, or market. The target audience for this proposal includes various individuals involved in grape production operations, such as vineyard managers, farm workers, winery owners, extension specialists, processing representatives, and industry consultants. These individuals are expected to benefit from the block-level spatial data analytics that will be developed through the research and technology provided in this proposal. Furthermore, the focus of this proposal is on university researchers and extension specialists who are increasingly incorporating digital agriculture technology in their field research and stakeholder consultations. The tools and information developed through this project are intended to assist these professionals in their efforts to use digital agriculture for spatial vineyard measurement and management. Although the proposed research will use New York vineyards as a model system, the tools and information developed are expected to have broader applicability to small farm operations across the United States. The aim is to provide valuable insights and tools that can be used by grape producers in various regions, regardless of their location, management practices, or target markets. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?This list includes summaries of various training resources and articles related to vineyard management using the MyEV software platform. The resources are presented in chronological order, starting from the most recent: Training Webinar 4/1/2024: Bates, T, Gunner, N., Walter-Peterson, H. Finger Lakes Grape Program MyEV Training Conference Presentation 3/14/2024: Bates, T., Chancia, R., Trivedi, M., Gunner, N. Hi-Res Vineyard Nutrient Management. Lake Erie Grape Growers' Conference, Fredonia, NY. Conference Presentation 3/8/2024: Bates, T., Chancia, R., Trivedi, M., van Aardt, J., Vanden Heuvel, J. Precision Nutrient Management Field Research Results. Hi-Res Vineyard Nutrient Management Annual Project meeting, Fresno, CA Training Webinar 2/28/2024: Bates, T and Gunner, N. Learn MyEV: An Open-access Vineyard Visualization Tool https://media.oregonstate.edu/media/t/1_z0jh726j Training Webinar 2/16/2024: Bates, T, Gunner, N., Walter-Peterson, H. Finger Lakes Grape Program MyEV Training. Tutorial Video 2/14/24: Bates, T. Keeping Track of Farm Block Information in MyEV https://www.efficientvineyard.com/blog/keeping-track-of-farm-block-information-in-myev In-person Training 2/13/2024: Bates, T, Gunner, N., Russo, J. Lake Erie Regional Grape Program Tech Tuesday. Conference Presentation 1/24/2024: Bates, T. Spatial Vineyard Data to Make More Informed Vineyard Management Decisions. Unified Wine and Grape Symposium. From Data to Decisions Session. In-person Training 1/16/2024: Bates, T, Gunner, N., Russo, J. Lake Erie Regional Grape Program Tech Tuesday. Training Webinar 11/28/2023: Bates, T and Gunner, N. Learn MyEV: An Open-access Vineyard Visualization Tool https://media.oregonstate.edu/media/t/1_br7ofwy1 Conference Presentation 11/9/2023: Bates, T. Efficient Vineyard: Spatial-data driven variable-rate vineyard management. Sustainable Ag Expo. The Vineyard Team. San Louis Obispo Conference Presentation 11/8/2023: Bates, T. Lightsabers and Jedi: Technology and Viticulture. Sustainable Ag Expo Pre-Conference Invited Speaker. The Vineyard Team. San Louis Obispo Training Webinar 9/8/2023: Bates, T., Russo, J. Between The Vines S3E17: MyEV: Estimating Concord Yield, Pruning Wt, Crop Load w/NDVI and Field Observations. https://www.youtube.com/watch?v=rlnlFGp8ofI Tutorial Video 8/17/23: Gunner, N. Managing Lots of Data at the Block Level https://www.efficientvineyard.com/blog/managing-a-lot-of-data-at-the-block-level Tutorial Video 8/1/23: Bates, T. Estimating Concord Yield, Pruning weight, and Crop Load with NDVI and Field Observations https://www.efficientvineyard.com/blog/estimating-concord-yield-pruning-weight-and-crop-load-with-ndvi-and-field-observations In-person Training 7/21/2023: Bates, T. Vineyard Sensors and Variable-Rate Equipment. GiESCO Post-Conference tour to the Cornell Lake Erie Research and Extension Laboratory Training Webinar 6/21/2023: Bates, T. and Gunner, N. MyEV Spatial Data Software Workshop. Hi-Res Vineyard Nutrition Project Conference Presentation 6/9/2023: Bates, T., Chancia, R., Gunner, N., and Keller, M. Spatial Data Processing to Inform Variable-Rate Dry Fertilizer Applications in Vineyards. ASEV-ES Conference, Austin, TX. In-person Training 5/11/2023: Bates, T. and Gunner, N. MyEV Spatial Data Software Workshop. Lake Erie Regional Grape Program. Portland, New York. Training Webinar 4/11/2023: Bates, T. Hi-Res Vineyard Nutrient Management, Precision Management Theme. Penn State Webinar. Conference Presentation 3/30/2023: Bates, T. Vineyard Data: Lo-Tech and Mid-Tech Approaches. Business, Enology, Viticulture New York Conference. Syracuse, New York. Conference Presentation 3/16/2023: Bates, T. and Chancia, R. Precision Vineyard Nutrition. Lake Erie Regional Grape Program Winter Grower Conference. Fredonia, New York. Conference Presentation 2/27/2023: Bates, T. Precision Viticulture and the Hi-Res Vineyard Nutrition Project. New York State Horticulture Society Meeting, Rochester, New York. In-person Training 2/7/2023: Bates, T. and Gunner, N. MyEV Spatial Data Software Workshop. Lake Erie Regional Grape Program. How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?Objective 1: Develop an accessible, intuitive, and affordable spatial data management software platform for small and medium-sized farms. The objective for year three of our project is to further develop an accessible, intuitive, and affordable spatial data management software platform tailored for small and medium-sized farms. To achieve this, we have outlined four key objectives. Firstly, we aim to implement automated, real-time proximal sensor data ingestion into the platform. Progress has already begun with the development of a Raspberry Pi-based data logger connected to the internet, intended to communicate directly with MyEV. This will demonstrate the utilization of MyEV APIs for posting data in real-time from automated ground sensors. Secondly, we are working on autonomous hardware integration in collaboration with the Gold Lab and Dr. Yu Jiang's Cyber Agricultural Intelligence and Robotics lab. This involves leveraging data collected via ground and aerial robots to enhance MyEV functionality. Additionally, we plan to conduct a second specialty crop trial by engaging with apple researchers at Cornell University to trial spatial data within MyEV. Lastly, we remain committed to providing responsive user support and bug mitigation, ensuring that grower inquiries and issues are addressed within 5 business days. Through these initiatives, we aim to continue advancing the capabilities of MyEV while supporting the diverse needs of our farming community. Objective 2: Evaluate strategic and efficient deployment of spatial data validation protocols and spatial decision support for efficient variable-rate management. At the Cornell Lake Erie Research and Extension Laboratory, we will embark on three precision viticulture trials to advance the capabilities of MyEV in vineyard management. Firstly, employing the Simple Univariate Method, we will utilize the MyEV data collector alongside manual observations to spatially map various vineyard characteristics for practical applications. Examples include mapping vine leaf nutrient deficiencies to inform fertilizer management, conducting insect scouting for targeted pesticide application, and sampling for crop estimation to forecast yields. These trials aim to demonstrate the utility of MyEV in addressing specific operational challenges faced by vineyard managers, enhancing efficiency and productivity. Moving forward, we will employ the Moderate Multi-variate Method, combining spatial sensor data and MyEV observations for comprehensive multi-layer management mapping. This approach will leverage satellite imagery for disease detection, utilizing NDVI data for canopy size assessment to optimize variable-rate fungicide spray applications. Furthermore, integration of soil, canopy, and yield mapping will inform precise nutrient supply and demand calculations for variable-rate fertilizer applications, ultimately enhancing vineyard sustainability and yield quality. Additionally, mapping yield and juice soluble solids will facilitate revenue calculations, providing growers with valuable insights into their financial performance. Lastly, we will delve into the Complex Multi-year, Multi-variate Method, utilizing all available data sources to generate innovative indexes, conduct multi-variate modeling, and develop prescription maps. The ultimate goal is to achieve vineyard efficiency through optimal vine crop load balance, a critical factor for vine health and fruit quality. By integrating validated yield and NDVI maps from year 1 with bloom NDVI data from year 2, we will calculate a crop load index to inform variable-rate mechanical fruit thinning strategies. These efforts will be evaluated through harvest yield and juice soluble solids monitoring, providing tangible evidence of the efficacy of MyEV in optimizing vine balance and enhancing fruit quality. Objective 3: Engage producers to use personalized digital agriculture solutions in their own operations. Although MyEV extension efforts have reached a broad audience through webinars and video tutorials, we are working with specific growers in the Lake Erie and Finger Lakes grape production regions on special case-use scenarios. In each instance, the project team has assisted growers in getting started with the MyEV platform and in collecting soil, canopy, and yield sensor data. Then the individual growers decide how and at what level of complexity they want to use the spatial information. In year 3, the project team will continue to assist growers with spatial data and MyEV use, as needed, and will evaluate the impact on the farming operation. For example, Ted Rickenbrode, a Lake Erie grower with a small operation has taken a low-tech approach to spatial data for his vineyard management. Using just a few spatial sensor maps generated by the project team, Mr. Rickenbrode collects manual vineyard measurements, such as vine pruning weight and cluster counts, using the MyEV Data Collector function on his smartphone to validate and translate the spatial maps. Then he uses the translated maps to adjust his manual pruning practices. Several other cooperating growers have been using NDVI sensors to assess frost damage, which hit the Finger Lakes in 2023 and the Lake Erie region in 2024. The measurement of variable frost damage across vineyards is helping growers develop more accurate crop estimates, which in turn assists with harvest and business scheduling. In a more advanced application, a Finger Lakes winery is using canopy reflectance and mechanical harvester yield monitor data in a Riesling vineyard to calculate and map vineyard crop load and adjust fruit thinning practices to achieve desired wine quality targets.
Impacts
What was accomplished under these goals?
A major limitation in the adoption of new digital technologies with grape producers is in the processing and management of spatial farm data. Many of the mapping software platforms are proprietary to variable-rate equipment, specific to a particular sensor, complex to use, or expensive. To increase the entry-level adoption of precision viticulture technology on small farms, producers need a simple and easy-to-use mapping platform for spatial data and educational information based on real case-use scenarios in precision viticulture. The MyEV Small Farms project is accomplishing this through the development of the free web-based MyEV spatial data software, researched based information from controlled field plots in precision viticulture, and the delivery of educational materials and live training sessions for grape producers. To experience project deliverables, please visit www.efficientvineyard.com . Efficientvineyard.com is the project website which focuses on providing tools, technologies, and information aimed at improving efficiency and productivity in vineyard management. The site offers various resources tailored to the needs of vineyard owners, managers, and workers. Efficientvineyard.com exhibits notable strengths in several key areas: MyEV Software: (Objective 1) MyEV is web-based and free software for growers to upload, clean, interpolate, validate, translate, and visualize spatial vineyard data. Multiple spatial data layers can then be integrated through k-means cluster analysis to generate multi-layer prescription maps for variable-rate vineyard applications. MyEV allows growers to build their farm blocks, import and manage sensor data, share farms and farm data with cooperators, and interact with all of their farm data in the field with the mobile application. Its features empower users to make informed decisions by consolidating data from various sources, providing analytics, and enabling customizable prescription maps. Research-based information: (Objective 2) Several research studies at the Cornell Lake Erie Research and Extension Laboratory have been established investigating real case-uses in precision viticulture. Simple examples include the mapping of frost damage across vineyard blocks and improving crop estimation based on canopy sensor mapping. Complex examples include variable-rate mechanical fruit thinning and fertilizer applications based on multi-layer spatial data analysis. Educational Resources: (Objective 3) The website offers comprehensive educational resources not only on software use through the "MyEV Documentation" page, but also on best practices in vineyard management through the "Viticulture Blog" page. These resources cater to a diverse audience, from beginners to seasoned professionals, and most materials are supported with video tutorials. Training Sessions: (Objective 3) In cooperation with the Lake Erie Regional Grape Program, the Finger Lakes Grape Program, the Hi-Res Vineyard Nutrition Project, and the National Grape Research Alliance, we have conducted numerous MyEV grower training sessions, including train-the-trainer events and user podcasts. These sessions equip users with the knowledge and skills needed to maximize the benefits of the MyEV Software and optimize vineyard operations effectively. User Experience: (Objectives 1 and 3) The platform prioritizes user experience, ensuring intuitive navigation and accessibility of resources. The software includes a grower feedback function to report software bugs, identify wish list items, and provide general customer service for the end user. To ensure convenience and accessibility, MyEV has a mobile interface, allowing users to access vital vineyard information and perform tasks from anywhere, using their smartphones or tablets. Community and Networking: (Objectives 1, 2, 3) Efficientvineyard.com fosters a supportive community and facilitates networking opportunities for vineyard professionals. Through forums, discussions, and field events, users can exchange insights, share experiences, and build valuable connections within the industry. Within the platform, users can share their farm and spatial data layers with farm workers, extension specialists, consultants, and processors/wineries. Impact: The MyEV software tool is being used internationally in many major grape producing regions. Currently, there are 1118 unique farm accounts in 34 countries and MyEV users have generated and mapped 4353 spatial datasets. These metrics have doubled in the past year. A heat map of the spatial datasets in the U.S. illustrates the heaviest use in the Lake Erie and Finger Lakes regions of New York, the North Coast and Central Coast regions of California, the Willamette Valley in Oregon, and the wine regions of Virginia. We believe this is a reflection of the extension programming conducted in these viticulture regions. Commercial producers are using the MyEV platform for various farm uses, from block level data recording and mapping of virus infected vines to complex spatial data mapping and integration for variable-rate applications. In 2023, the broader Efficientvineyard.com website with the project educational materials had over 5500 visitors, a 20% increase over the previous year, and 8100 page views. Overall, Efficientvineyard.com demonstrates excellence in providing innovative solutions, educational support, interactive training, user-friendly experience, and community engagement. These strengths contribute to its effectiveness as a comprehensive resource for enhancing vineyard management practices and fostering professional development within the viticulture sector.
Publications
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Progress 04/01/22 to 03/31/23
Outputs
Target Audience:The proposed research and extension activities in this proposal are specifically designed to cater to the needs of small-scale grape producers in the U.S. regardless of their vineyard location, management style, or market. The target audience for this proposal includes various individuals involved in grape production operations, such as vineyard managers, farm workers, winery owners, extension specialists, processing representatives, and industry consultants. These individuals are expected to benefit from the block-level spatial data analytics that will be developed through the research and technology provided in this proposal. Furthermore, the focus of this proposal is on university researchers and extension specialists who are increasingly incorporating digital agriculture technology in their field research and stakeholder consultations. The tools and information developed through this project are intended to assist these professionals in their efforts to use digital agriculture for spatial vineyard measurement and management. Although the proposed research will use New York vineyards as a model system, the tools and information developed are expected to have broader applicability to small farm operations across the United States. The aim is to provide valuable insights and tools that can be used by grape producers in various regions, regardless of their location, management practices, or target markets. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?This list includes summaries of various training resources and articles related to vineyard management using the MyEV software platform. The resources are presented in chronological order, starting from the most recent: 3/30/2023: In-person MyEV Training Workshop at BEV NY Conference http://www.bevny.org/ The three-hour workshop provided growers with an introduction to the MyEV system and helped them get started with this powerful yet easy-to-use tool. The workshop was appropriate for growers who were new to MyEV as well as those who had some experience using the system already. It was a hands-on workshop, and growers were required to bring their own laptops or tablets to work on. 2/3/23 Getting Started With MyEV...Spreadsheets https://www.efficientvineyard.com/blog/getting-started-with-myevspreadsheets The video is a tutorial on using spreadsheets in the context of vineyard management with the MyEV software platform. Terry Bates explains how to create and edit spreadsheets within MyEV, including adding data to vineyard blocks, managing information, and utilizing spreadsheet functionalities for efficient data management and analysis. 1/26/23 Learn More about Efficient Vineyard with Recent Podcasts https://www.efficientvineyard.com/blog/learn-more-about-efficient-vineyard-with-recent-podcasts Terry Bates recently appeared on the Hi-Res Vineyard Nutrition Podcast, discussing precision nutrient management for vineyards in Season 1, Episode 5 titled "It's All About Integration". The Efficient Vineyard project also ranked #1 in the Listener's Top 5 for 2022 on the Sustainable Winegrowing Podcast, produced by the Vineyard Team, showcasing their valuable contributions in communicating tools and technologies for grape producers. 1/10/23 Getting Started with MyEV...(part 1) https://www.efficientvineyard.com/blog/getting-started-with-myev The video provides an overview of getting started with MyEV, a software platform for vineyard management. Terry Bates walks through the process of creating an account, setting up farm blocks, importing spatial data, and utilizing features such as the Data Collector and Interpolator plugins to collect and process vineyard data for improved decision-making. 11/4/22 Using MyEV to Assess Vineyard Profitability https://www.efficientvineyard.com/blog/using-myev-to-assess-vineyard-profitability The video showcases how the MyEV software platform can be used to perform economic analysis of vineyard management. Terry Bates demonstrates how to use the platform's features to collect and analyze data on various vineyard inputs, such as fertilizer and pesticide usage, labor costs, and crop yield, and evaluate their impact on the vineyard's profitability. 9/20/22 Scouting for Nutrient Deficiencies in the Vineyard https://www.efficientvineyard.com/blog/scouting-for-nutrient-deficiencies-in-the-vineyard In this article, Terry Bates discusses how he used the MyEV software platform to scout for potassium deficiency in a vineyard by creating a customized data collector in the field. He explains how he collected observations, rated the severity of deficiency, and submitted the data, which was then processed into a spatial map that could be used for variable rate fertilizer applications in the spring. By utilizing the MyEV platform, he was able to save over 20% in fertilizer costs and apply potassium where it was needed. 8/17/22 Better Permission Options in myEV https://www.efficientvineyard.com/blog/better-permission-options-in-myev myEV now offers better permission options for farm administrators, including a 'Read-only' permission level for viewing datasets and granting 'Editor' access to individual datasets and collectors. Farm administrators need to be owners or administrators on the farm and team members must have myEV accounts. Permissions can be managed through the 'Collaborators' button in the farm details drawer. 8/12/22 Improvements Added to Farm Block Management https://www.efficientvineyard.com/blog/improvements-added-to-farm-block-management myEV has made improvements to farm block management, allowing bulk importing of blocks from GIS files, adjusting block headers, exporting block data as CSV files for editing, and re-importing updated data. These changes provide greater flexibility and efficiency in managing farm blocks. 7/25/22 New and Improved Data Joiner Plugin https://www.efficientvineyard.com/blog/new-and-improved-data-joiner-plugin The new and improved data joiner plug-in in Efficient Vineyard allows you to merge and combine data sets based on geography. You can easily join data sets from different blocks and create merged headers for combined data. This makes it convenient to combine data from different sources and create unified data sets for analysis. 7/8/22 Using Bloom NDVI to Improve Concord Crop Estimation https://www.efficientvineyard.com/blog/using-bloom-ndvi-to-improve-concord-crop-estimation The video discusses the use of Bloom NDVI (Normalized Difference Vegetation Index) to enhance crop estimation for concord grapes. NDVI is a remote sensing technique that measures the health and vigor of vegetation. The use of Bloom NDVI is presented as a valuable tool for grape growers to optimize their crop management decisions and improve overall grape yield estimation. 6/10/22 Getting More Out of Your Soil Map https://www.efficientvineyard.com/blog/getting-more-out-of-your-soil-map The article discusses the use of MyEV, a software platform, to process DualEM soil sensor data and interpret soil patterns in vineyards. It highlights how this information can aid in nutrient management decisions and potential variable-rate applications. 6/2/22 Vineyard Scanning in the Finger Lakes https://www.efficientvineyard.com/blog/vineyard-scanning-in-the-finger-lakes The article describes a vineyard scanning activity conducted in the Finger Lakes region, where soil and NDVI (Normalized Difference Vegetation Index) data were collected using sensors and processed in the MyEV platform. The objective was to establish baseline data, train a team member on equipment usage, and provide data for growers to use in mapping. 5/20/22 Track Where Jobs are Left Off https://www.efficientvineyard.com/blog/track-where-jobs-are-left-off The video showcases the use of the MyEV platform for managing and tracking jobs in the field of precision agriculture. It discusses how the platform allows users to create and assign tasks, monitor progress, and analyze data related to soil and crop management. The video focuses on the "Jobs" feature of MyEV, highlighting its functionalities and benefits for streamlining job management in precision agriculture operations. 5/19/22 Shoot Mapping Follow-up https://www.efficientvineyard.com/blog/shoot-mapping-follow-up The video provides a follow-up on a shoot mapping project using the MyEV platform in a vineyard. It discusses the results and insights gained from analyzing the shoot mapping data, including identifying areas of high and low shoot density, and making management decisions based on the findings. 5/13/22 Early Season Grapevine Shoot Mapping https://www.efficientvineyard.com/blog/early-season-grapevine-shoot-mapping The article introduces the "MyEV Small Farms" project, which aims to develop and implement software tools for generating spatial vineyard maps for small to medium-sized vineyard operations. It outlines the workflow for translating vineyard sensor data into viticulture information. 11/19/21 MyEV Training Session https://www.efficientvineyard.com/blog/myev-training-session-part-1 The video is a recording of a training session for using the MyEV platform, which is a software tool for managing and analyzing data in the field of precision agriculture. How have the results been disseminated to communities of interest?In addition to the Efficient Vineyard website software and educational materials (www.efficientvineyard.com), the content of this project has been presented at various grower conferences, viticulture lectures, and podcasts: Bates, T. Specialty Crop Production Technology. Carnegie Mellon University Tech in Ag guest lecture. (1/31/2023) Bates, T. Introduction to the MyEfficientVineyard Spatial Data Mangement Software. (12/14/2022) Bates, T. On-Farm Experimentation in Precision Viticulture. Montpellier Vine and Wine Sciences International Seminar. (10/13/2022) Bates, T. Digital Technologies for Grape Production. Washington State University Grad Seminar. (9/15/2022) Bates, T. Precision Viticulture and Western New York Grape Production. Cornell Advanced Viticulture Class guest lecture. (9/12/2022) Bates, T. Precision Agriculture Discussion with U.S. Government Accountability Office. (8/25/2022) Bates, T. CLEREL Research Field Day Tour. Portland, NY. (8/2/2022) Bates, T. Vineyard Water Management in Unirrigated NY Vineyards. Lake Erie Regional Grape Program. (7/14/2023) Bates, T. Spatial data informed vineyard mechanization in New York grape production. AWITC VitiTech Workshop. Adelaide Convention Center. (6/26/2022) Bates, T. Efficient Vineyard: Assessing Program Impacts. Cornell Regional Extension Teams Retreat. Geneva, NY. (6/23/2022) Bates. T. and Vanden Heuvel, J. Precision Viticulture - Digital Agriculture Solutions. eCornell. https://ecornell.cornell.edu/keynotes/overview/K060822/. (6/8/2022). Bates, T. Vineyard Nutrition Update. The Lake Erie Regional Grape Program. (5/11/2022) Bates, T. The Efficient Vineyard Project and the MyEV Software Tool for Grape Producers. Penn State Wine and Grape Series. (4/12/2022) Bates, T. The Efficient Vineyard Project. Washington State University Horticulture Seminar. Prosser, WA. (3/29/2022) Bates, T. Precision Viticulture Technology in New York. BEV NY. (3/31/2022) Bates, T. Vineyard Nutrient Management and New Technology. Lake Erie Grape Growers' Conference. Fredonia, NY. (3/16/2022) Bates, T. Precision Nutrient Management Technology. Hi-Res Nutrient Management Project Meeting. Prosser, WA. (3/10/2022) Bates, T. Variable Rate Mechanical Vine Management. Mason Earles' UC Davis Viticulture Class. (02/17/2022). Bates, T. The MyEfficientVineyard software tool for spatial data processing in commercial vineyards. Maryland Grape Grower Conference. (01/19/2022). Bates, T. Precision Viticulture in Commercial Concord Vineyards. Lake Erie Regional Grape Program - Grower Conference. (01/19/2022). What do you plan to do during the next reporting period to accomplish the goals?Objective 1: Develop an accessible, intuitive, and affordable spatial data management software platform for small and medium-sized farms. The project team is ahead of schedule in the planned development of the MyEfficientVineyard software platform by having the core functions, from spatial data importing to prescription map exporting, complete and accessible to all users. The plan for year 2 is to support and improve the software core functions through the use and feedback of end users. The more the software is used, growers are providing feedback on new case uses, wish list items, and bug fixes. Our plan is to support this feedback to improve the function of the platform and to address the needs of the end users. Generating prescription management maps, although ahead of schedule, is still a relatively new function to the MyEV platform. We plan to spend effort in year 2 testing the flexibility and efficiency of prescription mapping from multiple input data layers. Prescription maps generated in MyEV also need to translate to actionable management in the field by interacting with farm workers or variable-rate farm machines. We plan to address both through smartphone applications and exporting MyEV files to precision agriculture equipment. Growers have also provided feedback on improving the "front end" of the MyEV platform with farm creation, block organization, and data management. MyEV was built as a tool to process sub-block spatial data. Growers are requesting more utility in creating farm attributes, collecting block data, and sharing with farm workers and processor groups. Objective 2: Evaluate strategic and efficient deployment of spatial data validation protocols and spatial decision support for efficient variable-rate management. The appropriate collection, processing, and validation of spatial sensor information is an important theme in the success of precision agriculture. The vision of flying a drone over a farm field and having it tell you everything about the soil and plants is not currently realistic. Agricultural sensors give a relative electronic response to a field attribute, such as canopy reflectance or crop weight. The relative response can be translated into an absolute horticulture measurement through manual field validation measurements. Determining where to make the best field measurements can be directed through the appropriate processing of the spatial sensor data. The Cornell Lake Erie Research and Extension Laboratory has become a testing ground for new agricultural sensors for use in viticulture management. We currently test proximal soil, canopy, nutrient, disease, yield, and juice quality sensors in our research vineyards. Spatial data from each sensor are cleaned and processed in MyEV. The relative spatial map is used to generate stratified field validation sample locations, which are then used to translate the relative sensor map into an absolute horticulture map. Multiple horticulture layers, such as soil pH, vine size, or crop yield, can then be used alone or in combination to create spatial management maps. Our year 2 plan is to continue evaluating multi-modal ways of collecting spatial vineyard data, from simple smartphone data collectors to high-tech sensors; testing validation protocols for translating sensor data; and generating uni- bi- and multi-variate spatial management maps for improved vineyard efficiency. Objective 3: Engage producers to use personalized digital agriculture solutions in their own operations. In year 1, we identified and worked with six cooperating growers, three in the Lake Erie region and three in the Finger Lakes region, to collect and process soil and canopy sensor spatial data in commercial vineyard plots. Our plan for year two is to repeat the sensor data collection, identify stable spatial patterns in their fields, and work with the cooperating growers on identifying and implementing a variable rate management plan for the vineyard plots. This year, we would like the growers to process the data in MyEV and provide feedback on the use. Also, we would like the growers to identify what they would use the spatial data for in their own management operation. We plan to continue to develop the educational material on the Efficient Vineyard website and provide case use tutorials throughout the growing season.
Impacts
What was accomplished under these goals?
Objective 1: Develop an accessible, intuitive, and affordable spatial data management software platform for small and medium-sized farms. The project team successfully developed the My Efficient Vineyard (MyEV) software tool, a free web-based platform that allows small and medium-sized farms to easily work with spatial data. It is important to note that the software platform is live and currently available to any farm operation nationally and internationally. There are over 650 farms and 2500 data layers created by users going to the efficient vineyard website https://www.efficientvineyard.com/. The team achieved the following objectives: Added data import functions to the existing MyEV platform to record block data and capture raster imagery, improving the recording and storage of block level information for farm management. Created semi-automated data validation software for growers, which processes high-density spatial data into management classifications and then automatically stratifies low-density validation sample locations for in-field vine measurements. Developed spatial decision support software to generate spatial prescription management maps, allowing growers to select spatial data layers of interest for multi-layer cluster analysis. The team also conducted an accessibility and security audit/refinement of the MyEV core, expanded mobile data collector functionality, refined data interpolation, data joining, raster management/analysis, and grid/validation-point generation features, and provided user support and bug mitigation. The project's deliverables included a stable, secure, and accessible version of MyEV Core, MyEV mobile data collection features, stable MyEV plugins for data interpolation, data joining, raster management/analysis, and grid/validation-point generation, and timely responses to grower support and bug inquiries within 5 business days. Overall, the project successfully developed an accessible, intuitive, and affordable spatial data management software platform for small and medium-sized farms, providing a valuable tool for managing and analyzing farm data. Objective 2: Evaluate strategic and efficient deployment of spatial data validation protocols and spatial decision support for efficient variable-rate management. The Efficient Vineyard project has made significant progress in evaluating the strategic and efficient deployment of spatial data validation protocols and spatial decision support for efficient variable-rate (VR) management in vineyards. In the past, we identified a usable spatial data pipeline for importing, translating, integrating, and using spatial data to generate prescription management maps. However, questions remain about the most effective and cost-efficient methods for growers to use in data validation and spatial decision support processing. In year one, we tested various low-density sampling protocols against high-density sensor and manual measurements in a six-acre Concord vineyard at the Cornell Lake Erie Research and Extension Laboratory. We collected four years of repeated soil, canopy, yield, and juice quality spatial data layers and validated them with both low-density and high-density manual sampling. The results of this testing will be used to inform the validation software protocols in Theme 1 of the project. We also conducted activities to evaluate potential research vineyard plots for VR management at different levels of complexity, collected spatial data using proximal and remote sensing technologies, measured the degree of spatial structure in each vineyard, and selected three research vineyards based on VR management suitability. In a simple case, the MyEV data collector was used to rate and map vineyard potassium deficiency using only a smartphone. In this case, the grower's visual observation acts as the sensor and the smartphone GPS gives observation locations in collecting and mapping spatial data. In the medium case, proximal NDVI sensors and commercial GPS antennas were used to map vineyard canopy growth and used to direct crop estimation samples for more accurate yield predictions. In the advanced example, multiple soil, canopy, and yield sensors were used in multi-layer data processing for vineyard crop load balance and variable-rate fruit thinning applications. The deliverables of Year One include an approach to evaluate vineyard VR management at different levels of complexity, integrated and comparative vineyard sensing from proximal and remote sensors, a commercially useful evaluation of vineyard spatial data to recommend (or not recommend) VR management, a comparison of in-field validation sampling protocols, and identification of three research vineyards for VR evaluation. Objective 3: Engage producers to use personalized digital agriculture solutions in their own operations. Our project aims to help small producers in the grape production regions of Lake Erie and Finger Lakes adopt precision viticulture (PV) practices through research-based digital agriculture education and new spatial processing tools. In the first year of our project, we achieved the following: Established on-farm trials: We identified and partnered with six grape producers (three in each region) to establish commercial PV demonstration trials on their farms. These growers are leading the trials and choosing the PV treatments based on their specific business needs. Our project team helped with data collection, field validation, and evaluating the impact of the treatments on their operations. These on-farm trials also served as sites for grower education meetings. Supported MyEV users: We continued to engage and support current and new users of our digital agriculture tool, MyEV, through our Efficient Vineyard website. We added a feedback button on the MyEV platform where users can provide input on software issues, suggestions, and ask PV-related questions. This feedback has been valuable in improving the software based on growers' needs. Developed training materials: We created technical user articles (https://orbitist.atlassian.net/wiki/spaces/EV/overview?NO_SSR=1) and video tutorials (https://www.efficientvineyard.com/blog) on the new functions of MyEV, such as farm data management, raster imagery analysis, and validation sampling. These tutorials follow a curriculum that reflects the spatial data pipeline in our project. We also created sample data sets for interactive hands-on training for growers. Our accomplishments in the first year include establishing commercial PV trials in cooperation with grape growers, providing support to MyEV users through our website, and developing training materials to educate growers on how to effectively use MyEV for PV. These achievements will contribute to our goal of increasing precision viticulture adoption by helping growers make informed decisions based on spatial data and improving their farm management practices.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Taylor, J. A., Bates, T. R., Jakubowski, R., & Jones, H. (2023). Machine-Learning Methods for the Identification of Key Predictors of Site-Specific Vineyard Yield and Vine Size. American Journal of Enology and Viticulture. ajev.2022.22050. https://doi.org/10.5344/ajev.2022.22050
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