STTR Phase I: Visual Information eNvironment for Effective agricultural management and Sustainability

这个小企业技术转让（STTR）第一阶段项目的更广泛的影响/商业潜力将是开发技术，以保护稀缺的水资源和改善作物管理做法。 农业生产需要大量的水。 仅在加州，80%的水用于农业。随着社区的扩大和干旱情况的发展，对稀缺和昂贵的水资源的竞争变得激烈。 种植者必须能够通过提高灌溉效率来最大限度地降低成本和水需求。 虽然新的灌溉应用技术减少了风吹、渗漏和蒸发造成的损失，但大量的水仍然被浪费，因为它通过作物根部冲刷土壤。 该项目开发的技术将使生产者能够通过土壤剖面和跨田地跟踪土壤水分运动。这将使生产者能够根据其土壤类型和地形的独特条件制定灌溉战略，并减少水资源浪费。 这将为生产者节省资金，使他们能够继续经营，并满足政府关于灌溉的新规定。 水资源管理效率的提高和更好的作物管理实践可以提高作物产量，降低粮食成本，并有助于保护环境。STTR第一阶段项目提出开发一种基于科学的方法，以最佳方式确定传感器的数量，位置和深度。 其目标是准确测量整个根区和整个田地的土壤特性，然后对其进行建模，以便通过使用3D专有的精确土壤测绘进行精确、有效和高效的水和作物管理。综合的葡萄酒酿造、葡萄栽培和统计预测模型将把这些环境条件和历史数据与作物质量和产量以及长期的树木/葡萄树健康联系起来。此外，一个新的交互式空间和时间可视化分析环境将组织产生的大量数据流和新的预测模型，使利益相关者能够根据土壤水分条件对作物进行精确管理。通过开发这种最佳的传感策略，负担得起的，精确的土壤地图和数据驱动的土壤特性模型，基于环境和历史数据的作物组成和体积模型，以及新颖的，可理解的预测可视化分析工具，该项目将产生新的作物科学见解和环境协会，以及急需的精确水和作物管理技术。

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will be to develop technology to conserve scarce water resources and improve crop management practices. Agricultural production uses a great deal of water. In California alone, 80% percent of all water usage goes to agriculture. As communities expand and drought conditions develop, the competition for scarce and expensive water resources has become intense. Growers have to be able to minimize costs and water needs by making their irrigation practices more efficient. While new irrigation application technologies have reduced losses from wind drift, leakages and evaporation, large amounts of water are still be wasted as it washes through the soil past crop roots. The technology developed in this project will allow producers to track soil moisture movement through the soil profile and across fields. This will allow producers to develop irrigation strategies based on the unique conditions of their soil types and topography and reduce water waste. It will save producers money and enable them to stay in business and meet new governmental regulations regarding irrigation. Improvements in water management efficiencies and better crop management practices can increase crop production, reduce food costs, and help preserve the environment.This STTR Phase I project proposes to develop a science-based approach to optimally determine the number, location, and depths of sensors. The goal is to accurately measure and then model soil properties throughout the root zone and across the field for use in precise, effective and efficient water and crop management through the use of 3D proprietary precision soil mapping. Integrated enological, viticultural, and statistical predictive models will relate these environmental conditions and historical data to crop quality and volume, and long-term tree/vine health. Additionally, a novel interactive spatial and temporal visual analytics environment will organize the resulting massive data flows and novel predictive models to enable stakeholders to perform precision management of crops based on soil moisture conditions. By developing this optimal sensing strategy, affordable, precise soil maps and data-driven soil property models, crop composition and volume models based on environmental and historical data, and novel, understandable predictive visual analytic tools, this project will result in new crop science insights and environmental associations, as well as a much-needed precision water and crop management technology.