气候不稳定直接影响农业环境。缺水,空气温度高,土壤生物群的变化是环境变化引起的一些因素。需要经过验证和精确的表型性状,以评估各种胁迫因素对作物性能的影响,同时将表型成本保持在合理水平。使用密度计方法来测量蒸腾效率的实验通常是昂贵的并且需要复杂的基础设施。本研究提出了一种自动化的开发和测试过程,可靠,小,和低成本的原型系统,使用具有接近实时的高频潜力的物联网。因为它的防水性,我们的设备-LysipheN-单独评估每个植物,可以在不同的环境条件下进行实验(农场,字段,温室,等。).LysipheN集成了多个传感器,根据所需的干旱情况自动灌溉,还有一个遥控器,无线连接,通过数据平台监控每个工厂和设备的性能。在测试过程中,LysipheN被证明足够灵敏,可以检测和测量植物蒸腾作用,从早期到最终的植物发育阶段。即使结果是在普通豆类上产生的,LysipheN可以扩大/适应其他作物。这个工具用来筛选蒸腾作用,蒸腾效率,和蒸腾作用相关的生理性状。因为它的价格,耐力,和防水设计,LysipheN将在现实的生态和育种背景下用于筛选种群。它通过对最合适的亲本系进行表型分型来运作,表征基因库的加入,并允许育种者根据现实的农艺背景,使用功能性状(与LysipheN单元所在的位置相关)进行目标特定的选择。
Climate instability directly affects agro-environments. Water scarcity, high air temperature, and changes in soil biota are some factors caused by environmental changes. Verified and precise phenotypic traits are required for assessing the impact of various stress factors on crop performance while keeping phenotyping costs at a reasonable level. Experiments which use a lysimeter method to measure
transpiration efficiency are often expensive and require complex infrastructures. This
study presents the development and testing process of an automated, reliable, small, and low-cost prototype system using IoT with high-frequency potential in near-real time. Because of its waterproofness, our device-LysipheN-assesses each plant individually and can be deployed for experiments in different environmental conditions (farm, field, greenhouse, etc.). LysipheN integrates multiple sensors, automatic irrigation according to desired drought scenarios, and a remote, wireless connection to monitor each plant and device performance via a data platform. During testing, LysipheN proved to be sensitive enough to detect and measure plant
transpiration, from early to ultimate plant developmental stages. Even though the results were generated on common beans, the LysipheN can be scaled up/adapted to other crops. This tool serves to screen
transpiration,
transpiration efficiency, and
transpiration-related physiological traits. Because of its price, endurance, and waterproof design, LysipheN will be useful in screening populations in a realistic ecological and breeding context. It operates by phenotyping the most suitable parental lines, characterizing genebank accessions, and allowing breeders to make a target-specific selection using functional traits (related to the place where LysipheN units are located) in line with a realistic agronomic background.