Non Technical Summary
Our goal is to develop, validate, and commercialize an innovative, integrated system that enables growers to germinate seeds on the farm and to then precisely plant them in the field. As envisioned, this innovation will replace costly and labor-intensive transplant-based methods while maintaining high crop establishment. Since transplants require heated/ventilated structures, eliminating the need for transplants boosts energy efficiency and cuts costs. Our lighter-weight equipment reduces soil compaction, promoting soil health.Our main Phase II objective is to capitalize on our Phase I SBIR success by validating a proprietary, autonomous integrated planting system that prepares and plants one--and only one--germinated tomato seed at a time and that meets/exceeds all performance requirements in actual field conditions.Growers face increasing difficulty finding and affording the labor required to produce vegetable crops. The Eden solution reduces labor up to 96% and produces more food with lower input costs.Food production must expand worldwide to support a growing population. Improving farm productivity directly benefits society by expanding the availability of nutritious, affordable food. Vegetables are significant crops in the U.S. in terms of food sources and farm profitability. Fresh market tomatoes, for example, are one of the highest-value crops grown in the U.S., with a value of about $648 million in 2022. Florida is the top producer with over half of the nation's total production.One challenge for growers that limits productivity and profit is the need to grow starter plants for vegetables in greenhouses (or to purchase them), and to then transplant them into tilled soil. The process is highly labor-intensive and expensive, relies on fossil fuels for transplant production and transplanting, and uses heavy farm equipment that compacts the soil. Successful commercialization of the new autonomous system we are developing would eliminate the critical drawbacks of current planting approaches. Our technology's autonomous features enable growers to eliminate most of the labor used to acquire/grow/plant transplants--increasingly hard-to-acquire labor. Our technology will provide major social/economic benefits by reducing the labor and time required to get seeds in place and to wait for germination. As an all-electric technology, fossil fuel use in planting will be eliminated. Thus, the system makes a major contribution to reducing greenhouse gases. Finally, as a much lighter-weight system, soil compaction is reduced, and growers can also plant when fields may be too wet for incumbent equipment to enter the fields.Farmers will have more flexibility when they don't rely on available transplant varieties from third parties, and they will save money by reducing the high energy costs related to greenhouses and transplanting. Further, the implementation simplicity of the Eden system will enable those farms not currently growing vegetables to begin growing them without investing in greenhouses to grow transplants and to find, train, and retain labor to transplant the crops and use fossil fuels to plant the crops.The anticipated low barrier to entry will enable these crops to be grown in new areas--e.g., lettuce may be field-grown in fertile Midwest soils near major cities such as Chicago. The Eden system will enable planting lettuce when the soil is too warm for in-ground germination but when enough growing season remains to produce the crop before frost. This would reduce transportation costs and related greenhouse gases by eliminating the need to ship this produce from California. As climate changes, this flexibility to adapt to new growing regions/conditions will be increasingly important. Growing fresh vegetables close to the consumer provides higher quality and more nutritious food. The ability of a country to grow more of its own food improves its security by reducing its dependence upon other countries for the food or the labor to produce it.The labor-saving quality of this innovative solution applies to all farm sizes. Some 98% of U.S. farms are family farms, producing 87% of all farm output. Small farms, classified as having annual gross cash farm income of less than $350,000, make up 89% of U.S. farms. These farms accounted for nearly 75% of high-value crops such as vegetables, fruit/tree nuts, and nursery/greenhouse products. Although they comprise a high percentage of U.S. farms, these farms have higher financial risk, and about 40% report having off-farm income. Surveys show that more time spent on farm work reduces the time available for off-farm employment. Improving productivity and reducing the costs for these farms can significantly increase our food supply by enabling these farms to produce more food and be more profitable. The solution clearly provides major potential benefits to all farm sizes concurrently.

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
402	5310	2020	100%

Knowledge Area
402 - Engineering Systems and Equipment;

Subject Of Investigation
5310 - Machinery and equipment;

Field Of Science
2020 - Engineering;

Goals / Objectives
The successful completion of this research will result in an integrated system for germinating and planting germinated seeds on the farm. It will demonstrate the capability of the system to germinate the required quality and quantity of seeds, plant a 10-acre field/day, and provide data on the system precision (1- seed proportion, seed depth, soil cover, alignment, and plant spacing), the labor savings, energy savings and soil compaction reduction vs transplanting, and crop stand produced by the system. The information gained from this research will provide key information to the system's potential early adopters as proof of the system's performance. Growers, consultants and volunteer participants have clearly indicated that we must demonstrate a system in the field to gain early adopters of this novel approach.Objective 1: Determine the optimal control parameters that produce the most-uniform batch of germinated tomato seeds.Objective 1 milestone/metric: This Objective will be met when we have compiled tables showing the distribution of radicle length and percent germination at discrete time intervals so the system can be configured to produce optimal batches of germinated tomato seeds.Objective 2: Determine the maximum radicle length of a tomato seed that the planting system can process without clogging the system or damaging the seeds.Objective 2 milestone/metric: The percentage of seeds that pass through the system successfully will be calculated for each set of seeds of a specific radicle length. The radicle length with the highest percentage of seed successfully passing through the system undamaged will be designated as optimal. We will be successful when this radicle length is determined.Objective 3. Demonstrate and evaluate a field-scale germination system to prepare large, uniform batches of germinated tomato seeds to meet planter requirements.Objective 3 milestone/metric: A percentage of the tomato seeds put into the system for germination will show signs of growth by visual inspection for an emerging radicle. The germination rate of the seeds used will be considered when calculating the success level. The Objective will be successful when the field scale germination system produces a batch of germinated seeds that meet the requirements of the planter as determined in Objectives 1 and 2.Objective 4: Evaluate field-scale planter performance in open field trials.Objective 4 milestone/metric: Key performance factors to evaluate:Single-seed extrusion/crop stand - Is there a performance variation over periods equivalent to field-level requirements (continuous planting for hours)? The targeted 1-seed extrusion and resulting crop stand is 90%.Time to plant--Does the system meet time performance goals, and if not, is the singulation module performance a factor in not meeting this goal? Does the singulation system frequently stop the planter to locate seeds to be planted? The target is planting 1 acre per hour on average over a 10-hour period.Seed spacing - Does the planter speed control by the singulation system affect spacing? Spacing is consistently within +/- 10% of the target for fresh market tomatoes, commonly 24" apart.Seed placement depth - Does the planter place the seeds at the programmed depth? Typically, seed-placement data is related to the placement of dry seeds to ensure good germination. Little published information is available on optimal depth for germinated seeds. For this factor, 100% of the seeds must be covered with soil and no deeper than twice the target depth for planting dry tomato seeds in seed-starting trays - ¼".Crop stand - how well does the system produce a uniform crop stand?Gel performance - does a large gel volume produce any new issues?The results of these objectives must demonstrate to potential investors/partners/customers that the system is capable of the following:will plant a tomato crop in actual field conditions that grows as well as a crop grown using transplants at equivalent or lower overall costs;the spacing between plants in a row is consistent with the requirements for field-grown tomatoes (at least as accurate as incumbent methods);the labor required to plant a crop with the system is 90% less than the labor required to transplant a similar crop of tomatoes;the system can operate in the field for the time required to plant 10 acres of tomatoes at approximately 4,500 plants per acre andthe system weight in the field is at least 50% lighter than the incumbent transplanting systems used by commercial growers.

Project Methods
Conduct multiple germination tests of tomato seeds with different control values.The team will determine the initial value bounds of the germination control factors of temperature, water refresh cycling, and aeration rate for multiple tests. For each test, only one factor will be varied. A full factorial test design will be replicated at least 3X for a minimum of 81 tests. Three bench-scale germination systems will allow multiple simultaneous tests, with each replication executed in a different system. During each test, a random sample of 150 seeds will be removed from the batch at 12-hr intervals and examined for radicle growth, and each seed will be assigned to a radical length class corresponding to the measured radicle length. These seeds will not be returned to the batch but will be used in subsequent teststo evaluate them for clogging of the singulation module. The system will adjust the water volume to maintain a one-seed per 4 ml water ratio with the remaining seeds. The bench system has a minimum required volume of 1.8 L, so to maintain the 4 ml of water to 1 seed ratio, each test will require 2,400 seeds to enable a full 7-day test. The data will bestatistically analyzedto identify the factor value set that produces the optimal radicle length in the shortest time.Execute germination tests of tomato seeds with the optimal control values for the factors. Thegermination tests will be repeated using each benchtop system with the selected optimal control factors. Each test will be replicated 3X per bench system. The data will be analyzed to confirm the parameters produce results that are similar statistically. Further, ANOVA will compare results from the three germination systems and respective replications.Execute multiple germination tests of tomato seeds with optimum control values to evaluate for clogging. The combined germinated seed samples taken at intervals from each germination station used in prior tests will contain 450 seeds. A visual inspection will segregate the seeds into sets with the same radicle lengths. A minimum of 150 seeds of a specific radicle length will be collected to form a sample. The sample will be mixed with water retained from the germination test and Laponite RD powder at 2% w/w to form a thixotropic gel. The mixture will be stirred for 20 min and then allowed to rest one hour. The rest time will be the same for all samples. The seeds in the mixture will be visually examined for seed or radicle damage. Any damaged seeds will be removed and replaced with seeds that are not damaged. The seed-gel sample will be loaded into the test stand and extruded. The number of seeds extruded will be counted, and the proportion extruded will be calculated. Any seeds not extruded will be assumed to be caught in the system. The system will be taken apart and examined for any clogging. This procedure will be repeated for radicle lengths of 1, 2, 3, 4, and 5 mm, assuming germination produces the necessary volume of each to conduct the test. Then, the prior experiment will be repeated twice for a total of three replications, and the radicle length and clogging tests will be repeated as described here. The seeds that flow through the system for each test will also be visually inspected for damage.The proportion of seeds that did not flow through the system will be calculated for each radicle length and sample. ANOVA will be used to evaluate the tests, and the maximum radicle length that results in the least seed loss will be selected. This data and prior test results will determine optimal germination system settings.Complete preliminary design of field-scale germination system #1. PI Cromer will lead a preliminary design of the field-scale germination system early in the project. At this point, basic parameters for the system design such as volume, temperature ranges, and aeration can be estimated for design work to begin. The team will complete the design and build the field-scale germination system capable of preparing seeds to plant 10 ac of tomatoes at a plant density of 4,500 plants/ac. The team will determine the vessel geometry to meet specifications,develop the heating and cooling models and select devices to meet requirements. The control software will be adapted to the larger system, which will include sensor changes, due to size and likely geometry changes. Execute germination tests using the field-scale germination system with optimal control values. The field scale germination station will be used to repeat the germination testing but at the higher capacity of the field-scale system. For a 10-acre field planting tomatoes at 4,500 plants per acre, 45,000 seeds will be used per test. The data will bestatistically analyzed and compared to the results to the bench scale analysis to confirm that the parameters produce results that are similar statistically.Design of field-scale planter. PI Cromer will lead a preliminary design of the field-scale autonomous planter for planting 10 acres daily. At this point, basic parameters for the system design, such as payload weight, battery life, chassis, and drive system geometry, are known or can be confidently estimated. Starting this task before prior objectives are completed reduces risks of supply chain issues with critical components and optimizes team use.Build and prepare the planter unit for field-testing. The team will build the one-row autonomous planter for field-testing. Elements that the results of Objective 3 might influence will not be built before reviewing Objective 3 results to reduce the risk of rework and associated costs.Make remaining modifications based on Objective 3 results. The team will review the results of Objective 3 and adjust designs accordingly. Once changes, if required, are made, the field-scale planter will be finished.Conduct field-testing by Eden of the first field-scale planter.The team will conduct basic field-scale testing to confirm operation and identify any required changes before building units for independent field-testing. This testing will occur at Eden's R&D office on prepared test plots and at the Combs Farm in Grainger County, Tennessee. Each test will capture and compare the following performance data/metrics to target values.Determine the proportion of 1-seed outputs.Spacing of a randomized seed sample along a row will be measured and min, max, and mean determined.A randomized sample of planted seeds will be uncovered, and the seed depth below the soil surface will be measured. The sample will be analyzed statistically to determine if the planting depth is within the target range.Any required modifications will be implemented, and the tests will be repeated until they meet requirements.Build field-scale germination systems for UGA testing. On completion of Eden's field-scale systems testing, the team will assemble/integrate a field-scale germination system to deliver to the University of Georgia (UGA)-Tifton for independent field testing.Build field-scale autonomous planters for UGA testing. On completion of Eden's field-scale systems testing, the team will assemble/integrate a field-scale germination system to deliver to the UGA-Tifton for independent field testing.UGA conducts independent field-testing. UGA-Tifton will complete independent field-testing of the integrated system to test operation at a field scale. An experimental design will establish the plot sizes necessary to provide statistically valid results without planting 10 acres. The tests will evaluate the following performance metrics:Percentage of 1-seed proportion plantedAccuracy of plant spacingAccuracy of planting depthAverage planting speedGerminated seed plant stands vs. transplanted plant stands at seven, fourteen, and 21 days.In addition, anecdotal observations of operations that will improve the system will be noted.