Transpiration Rate Estimation | 室内绿植蒸腾速率估算

Turn a plant photo into a 0–100% wilting index and identify whether underwatering or overwatering is the likely cause.

Get a 0–100 root health score and vitality grade from a transparent-pot or seedling-box image, plus care-direction advice.

In a plant factory, a fixed thermal imaging camera continuously captures thermal images of the plant canopy leaves at night (no-light period), analyzes leaf temperature trends (respiration releases heat, causing leaf temperature to be slightly higher than air temperature), and combined with optional ambient CO₂ sensor data (respiration releases CO₂ raising concentration), an AI model estimates the relative respiration. | 通过植物工厂内的固定热成像摄像头，在夜间（无光照时段）连续采集植物冠层叶片的热图像，分析叶片温度变化趋势（呼吸作用释放热量导致叶片温度略高于气温），结合可选的环境CO₂传感器数据（呼吸作用释放CO₂浓度升高），利用AI模型估算整株或群体的呼吸强度相对值（0-100%）。

AI-powered non-invasive rooting-stage detection for plant cuttings in transparent containers. From smart propagation boxes or transparent cutting containers, periodically captures images of the cutting base (water roots or substrate roots visible through the transparent wall), uses AI vision to detect white root primordia (tiny white callus dots) and count/locate them, and outputs the rooting stage (No Roots / Few Primordia / Many Primordia / Well-Developed Roots). Helps propagators monitor cutting-rooting progress without disturbing the cutting and choose the optimal transplant time. Scenarios: smart propagation boxes, home cutting propagation, tissue-culture rooms, agricultural research. | 通过智能育苗箱或透明扦插容器的固定摄像头，定期拍摄枝条基部的水生根或土培根系（通过透明壁观察），利用AI视觉分析技术识别枝条基部是否出现白色凸起根点（根原基发育形成的白色小点）以及根点的数量和分布，输出生根阶段（无生根/少量根点/大量根点/根系发达）。该技能帮助育苗者在不干扰枝条的情况下，无创监测扦插生根进度，判断移栽时机。应用场景：智能育苗箱、家庭扦插繁殖、植物组培室、农业科研。

AI-powered plant growth stage auto-detection from periodic full-plant images via smart pot / greenhouse fixed cameras. Recognizes key phenological features—cotyledon emergence, true-leaf count, flower bud differentiation, blooming, fruit setting, fruit ripening—and identifies the current developmental stage (germination, seedling, vegetative, flowering, fruiting, ripening), enabling precision irrigation/fertilization/lighting control and personalized growing guidance. Scenarios: smart pots, home grow boxes, greenhouses, plant factories. | 通过智能花盆或温室内固定摄像头，定期拍摄植物整体图像，利用AI视觉分析技术识别子叶展开、真叶数量、花芽分化、开花、结果、果实成熟等关键物候特征，自动判定植物当前所处的生长发育阶段（如发芽期、幼苗期、生长期、开花期、结果期、成熟期）。有助于精准农业管理，实现自动化灌溉、施肥、光照调节，并为用户提供种植指导。应用场景：智能花盆、家庭种植机、温室大棚、植物工厂。

Using fixed cameras in a smart greenhouse to analyze plant morphology in real time (e.g., leaf wilting angle, stem uprightness, leaf color changes) combined with environmental sensors (light intensity, temperature, humidity, soil moisture), an AI decision model outputs climate control commands including irrigation (pump/solenoid valve), shade-net opening, fan/wet-curtain on-off, heater on-off, etc. | 通过智能温室中的固定摄像头实时分析植物的形态（如叶片萎蔫角度、茎秆挺直度、叶色变化）以及结合环境传感器（光照强度、温度、湿度、土壤水分），利用AI决策模型输出环境调控指令，包括灌溉（水泵/电磁阀）、遮阳网开度、风机/湿帘启停、加热器开关等。