Date: January 2023
Authors: Paige Beuhler and Ines Hanrahan
In December of 2022, the WA Tree Fruit Research Commission approved $394,302 for five (5) new technology research projects for the upcoming year. All newly approved technology projects this year are funded 100% by apple.
2022 New Technology Project Details:
Project Title: Soil and Plant Diagnostic Technology for Smart Nutrient Management
Organization (s): Washington State University
PI (s): Sallato, B.; Khot, L.
Total Funding Amount for All Years: $35,906
Length: 2 Years
This proposal aims to continue exploring new testing methods and orchard mapping technology, to develop smart nutrient management programs and consequently, maximize productivity and fruit quality. The team proposes to continue providing growers with comparative and unbiased information on mapping, soil and plant nutrient methods, as well as providing access and information for new companies to expose and validate their technology to serve our tree fruit industry. The researchers will assess soil variability mapping tools and soil testing methods that best reflect orchard conditions for effective management, evaluate plant nutrient test methods that can better predict nutrient status for effective management, and develop outreach and extension activities; field days and durable products for continue learning, in English and Spanish.
Project Title: Insights into Regulated Deficient Irrigation on Apple Growth and Color Development
Organization (s): USDA-ARS Appalachian Fruit Research Station, Washington State University
PI (s): Bierer, A.; Sallato, B.; Kalcsits, L.
Total Funding Amount for All Years: $172,523
Length: 3 Years
Data-driven agricultural management is increasing in prevalence as orchard growers strive for production optimization and input reduction to increase market competitivity and maintain profitability. The team will leverage a data-driven, autonomous approach to RDI implementation for increased practice understanding with the goals of: (i) improving color development of high value bi-color apple cultivars; (ii) enhancing the precision of RDI implementation to provide more applicable grower guidance; (iii) maximizing risk aversity of RDI implementation by advancing towards autonomous RDI execution; and (iv) determining the economic viability of data-driven autonomous RDI implementation as a color improvement strategy for WA state growers. The objectives include establishing 2 replicated RDI research trial locations in WA in collaboration with grower and commercial cooperators for Fuji and Honeycrisp cultivars, utilizing a data-driven approach to autonomous RDI implementation through plant sensory and autonomous irrigation equipment, provide guidance for RDI implementation when utilizing sensory equipment, determining imposed RDI treatment effects on fruit growth and color development as well as resulting fruit quality parameters (e.g., shape/size, firmness, cuticle thickness, soluble solids, acidity), to assess the efficacy of a data-driven approach to RDI for optimization of fruit quality, and estimate economic viability of data-driven RDI implementation for improved fruit quality and color development.
Project Title: Integrated Sensing and Real-Time Control for Intelligent Fruit Picking
Organization (s): Oregon State University, Wageningen University
PI (s): Davidson, J.; Grimm, C.; Hemming, J.
Total Funding Amount for All Years: $250,000
Length: 3 Years
While the industry is highly motivated to automate its labor-intensive operations, there are still no commercial harvesters available for the fresh tree fruit market despite nearly four decades of research. Much of the prior work has focused exclusively on vision as the primary sensing modality, disregarding what happens after initial contact and ignoring the sense of touch that humans use to manipulate fruit during a pick. This has resulted in machines that can effectively see fruit on the tree, but not robustly pick and transfer them at the rates required for commercial adoption. The team’s primary goal is to increase fruit detachment rates, reduce fruit spur separations, and minimize fruit damage via a novel, cost-effective end-effector embodied with a human-like sense of touch. To accomplish this goal, the team has defined three objectives. These objectives include developing a prototype picking end-effector with integrated vision, force, and tactile sensors, designing algorithms for fusing multiple sensor streams during the pick with novel, closed-loop tactile picking controllers that incorporate this multi-sensory feedback, and finally evaluating the end-effector in preliminary lab/field trials in both Washington and the Netherlands to study the effects of cultivar, orchard system, and management practices on technology performance.
To achieve these goals, the group has created a collaborative U.S.-Dutch team of investigators, growers(Thompson Hill Orchards (Yakima, WA)), and companies (ABB Robotics and Munckhof Fruit Tech
Innovators). This team combines the resources and experience of world-class farming regions (Pacific
Northwest and Holland) and research institutions (Wageningen and Oregon State University) tackling
the same challenge – improving the efficiency of farming through technology development and
adoption.
Project Title: Low-Cost, Reliable Soft Arm for Robotic Tree Fruit Operations (Phase 2)
Organization (s): Washington State University
PI (s): Luo, M.; Karkee, M.; Whiting, M.
Total Funding Amount for All Years: $216,039
Length: 2 Years
During the funding period 03/2022-present (1-year funding), the team has been developing and testing a single, soft-growing arm-based robot system for fruit tree orchard applications. So far, the system can extend up to 4 feet (to reach the top of the canopy in the modern apple tree structure when installed on a mobile platform), grow at 0.7 ft/s to reach the target (potential to reach 1.7 ft/s), carry a 2 lb. payload, including robotic ‘hand’ or various other end-effectors, and a perception/vision system without buckling. The team integrated their customized perception system with the robot for detecting and locating apples. A lightweight soft robotic gripper has also been integrated with the overall system for picking apples without needing any force feedback. Luo’s team is currently developing two identical systems; one each for Pullman and Prosser to accelerate progress. The objectives of this project are to integrate the vision system with an optimized planning algorithm to achieve smart field operation of the robot (year 1) and then perform system evaluation and optimization of multi-soft growing arms in a commercial orchard with a mobile platform. The system integration and evaluation will also include a two-arm version of the FFRobotics (project collaborator) machine (year 2).
Project Title: Smart Orchards Year 4+ Connectivity
Organization (s): Innov8 Ag
PI (s): Mantle, S.; Khot, L.; Sallato, B.
Total Funding Amount for All Years: $97,174
Length: 1 Year
During the fourth year of the Smart Orchard project, the team will take data collected and apply it directly to actions via devices – with an emphasis on applications of irrigation, dry fertilizer, & chemical sprays. This allows the team to build on the value of data collected over the last 3 years and shifting focus to blocks where it will offer the most value. After 3 years of data collection at site 1, researchers determined that the lack of site variability limits the impact of this project – and thus plan to decommission the site. However, it’s believed that site 2 can benefit from a 3rd year of data collection due to the biennial tendencies of Honeycrisp (and the opportunity to measure impact of variable rate spray applications on smoothing the biennialism). Mantle’s team will be adding site 3 (grower cooperators have been approached but have yet to finalize the site) to better capture a younger block with modern trellising & a larger degree of variability – which would be more representative of a ‘typical’ block more recently deployed across Eastern Washington. The focus, then, in year 4 will be on integrating & enabling partners that are equipped to easily take collected data and “act”, then looking back at effectiveness & broader adoptability of certain technologies.
Overall, continued support to the smart orchard theme will benefit the tree fruit industry in the short- and long-term with impacts realized by i) identification and use (or not use) of appropriate soil, crop sensors, data aggregation/visualization interfaces, and crop management technologies, ii) realizing the reduction in use of input resources (labor, water, fertilizer, chemicals, etc.) while improving block specific production and pack-outs. The industry will also benefit from centralized public-private partnerships to realize meaningful adoption of concepts related to smart orchards of the future.
Contact:
Paige Beuhler (Administrative Officer): paigeb@treefruitresearch.com, 509 665 8271 ext. 2
Ines Hanrahan (Executive Director): hanrahan@treefruitresearch.com; 509 669 0267
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