SBIR Phase I: A Precision Autonomous Fluid Planting System for Pre-Germinated Vegetable, Flower and Specialty Crops

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是为农民和消费者提供经济利益，以及美国和全球许多不同农场经营的更广泛的社会利益（例如，蔬菜、花卉和草药种植者以及温室操作）和农场客户。 提高农业生产力可以扩大营养丰富、价格合理的食品供应，从而直接造福社会。就食物来源和农场盈利能力而言，蔬菜是美国至关重要的作物。 限制生产力和总产量的菜农面临的主要挑战之一是需要在温室中种植蔬菜的起始植物（或购买它们），然后将它们移植到耕作的土壤中，这是高度劳动密集型和昂贵的。 该系统取代了这一过程，该系统将预先发芽的种子直接精确地种植到田间，预计成本为现有方法的26%。 该技术是一种全电动系统，减少了100%的种植中使用的化石燃料的使用，并且比使用柴油拖拉机的现有移栽解决方案重量轻75%。该技术还通过自动引导和机器学习的自主种植系统解决了农业劳动力日益短缺的问题。该小型企业创新研究（SBIR）第一期项目将致力于解决在一批触变凝胶中分离预发芽种子的问题，以便在实际田间种植条件下实时将一颗且仅一颗预发芽种子种植在每个所需位置。 植物科学家已经在许多科学研究中证明，种植发芽前的种子可以提高产量并降低成本。 然而，可靠的田间播种机并不成功。主要研究目标是证明一个自主的种子分离系统，结合了流量控制、种子检测、主动机器学习、分离和实时挤出，可以满足该领域的要求，从而证明商业可行性。 项目研究将开始，采用离散事件模拟来模拟用于获得系统最佳参数的分离过程。该模型的输出将用于开发控制算法和程序。 将开发一个原型自主系统，在实际的现场条件下测试算法。这项研究的预期结果是，该系统可以可靠地种植一个和只有一个种子在每个所需的位置至少90%的时间。这一奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to provide economic benefits to farmers and consumers as well as broader societal benefits in the U.S. and globally for many different farm operations (e.g., vegetable, flower, and herb growers as well as greenhouse operations) and farm customers. Higher farm productivity directly benefits society by expanding the availability of nutritious, affordable food. Vegetables are vital U.S. crops in terms of food sources and farm profitability. One of the main challenges for vegetable farmers that limits productivity and total yield is the need to grow starter plants for the vegetables in greenhouses (or to purchase them) and then transplant them into tilled soil, which is highly labor-intensive and expensive. This system replaces that process with a system that plants pre-germinated seeds directly into the field with precision at a projected cost of 26% of the incumbent methods. The technology is an all-electric system that reduces the use of fossil fuels used in planting 100% and is 75% lighter weight than incumbent transplanting solutions using diesel tractors. The technology also addresses the increasing scarcity of farm labor with an autonomous planting system using automatic guidance and machine learning.This Small Business Innovation Research (SBIR) Phase I project will work to solve the problem of separating pre-germinated seeds in a batch of thixotropic gel such that one and only one pre-germinated seed is planted at each desired location in real-time under actual field planting conditions. Plant scientists have proven in numerous scientific studies that planting pre-germinated seeds increases production and lowers costs. Reliable field planters have not been successful, however. The primary research objective is to prove that an autonomous seed-singulation system combining flow controls, seed detection, active machine learning, singulation, and extrusion in real-time can meet the requirements of the field to prove commercial viability. The project research will begin by using discrete event simulation to model the singulation process used to obtain optimal parameters for the system. The model’s output will be used to develop control algorithms and programs. A prototype autonomous system will be developed to test the algorithms in actual field conditions. The anticipated result of this research is that the system can reliably plant one and only one seed at each desired location at least 90% of the time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.