从温室气候到单叶：一种基于器官尺度的生菜生长模型
From greenhouse climate to individual leaves: an organ-resolved model of lettuce growth
- Auburn University（奥本大学）
- SynapGarden
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出一种基于单叶生理的器官尺度生菜生长模型，耦合光合作用、碳分配与三维结构，实现温室环境与个体叶片互馈模拟，为双向数字孪生提供正向预测支持。
AI中文摘要：
温室气候管理旨在提高作物产量的同时限制能源消耗。这要求在改变环境条件之前了解作物将如何响应。作物数字孪生体只有在能够表征植物生理与结构如何协同发育时，才能支持此类决策。本研究开发了一个统一框架，从单叶生理过程出发模拟生菜生长。每片叶子接收其在冠层中位置处的环境条件，并通过光合作用贡献碳。部分碳用于维持呼吸，其余部分支持生长，并按叶龄、叶面积和局部环境在叶片间分配。预测的叶片质量、面积和年龄在NVIDIA Isaac Sim中生成了动态演化的三维植株。光线追踪计算每片叶子拦截的辐射并将其反馈至光合作用，从而使结构与生长随时间相互影响。与温室实测数据相比，总干重的相对均方根误差为9.5%，叶片数、冠层直径和最大叶面积的相对均方根误差分别为9.2%、12.7%和13.1%。入射辐射降低30%使最终干重减少10.4%，而相同幅度的增加则使其提高6.9%，增加200 ppm二氧化碳使其提高46.1%。在模拟的40株植物区块内，内部植株比初始状态相同的边缘植株累积的干重少8.6%，且叶片特异性烧尖指数在温室植株出现烧尖现象的时期内于封闭叶片中上升。因此，解析单叶能够解释局部光照暴露如何改变温室内的植物生长。该框架提供了双向数字孪生所需的正向植物模型，其中对实体植物的观测可更新预测并支持温室气候决策。
英文摘要：
Greenhouse climate management aims to improve crop production while limiting energy use. This requires knowing how a crop will respond before conditions are changed. A crop digital twin can support this decision only if it represents how plant physiology and structure develop together. A unified framework was developed to simulate lettuce growth from the physiology of individual leaves. Each leaf received the conditions at its position in the canopy and contributed carbon through photosynthesis. Part of this carbon was used for maintenance and the remainder supported growth, distributed among leaves by their age, size and local environment. The predicted leaf mass, area and age generated an evolving three-dimensional plant in NVIDIA Isaac Sim. Ray tracing calculated the radiation intercepted by each leaf and returned it to photosynthesis, so structure and growth influenced each other over time. Against greenhouse measurements, the relative root mean square error was 9.5% for total dry weight and 9.2%, 12.7% and 13.1% for leaf number, canopy diameter and largest-leaf area, respectively. A 30% decrease in incident radiation reduced final dry weight by 10.4%, while the same increase raised it by 6.9%, and adding 200 ppm carbon dioxide raised it by 46.1%. Within a simulated 40-plant block, interior plants accumulated 8.6% less dry weight than border plants with identical initial states, and the leaf-specific tipburn index rose in the enclosed leaves over the period in which tipburn appeared on the greenhouse plants. Resolving individual leaves therefore explains how local exposure changes plant growth within the greenhouse. The framework provides the forward plant model needed for a bidirectional digital twin, where observations of the physical plant can update predictions and support greenhouse climate decisions.
