Greenhouse decisions often rely on static thresholds, yet crop output switches among microclimate-driven regimes. We frame daily cucumber yield as transitions among three ordered states and fit a continuous-time, covariate-dependent multistate model. Data come from four greenhouse compartments in Volos, Greece (24 lines, 62 days). States are defined once from control tertiles and applied across compartments. Transition intensities depend on within-compartment z-scores of relative humidity (RH), photosynthetically active radiation (PAR) and CO2, plus fixed effects. Results show an inherent upward drift through the medium state, "sticky" low-yield spells unless conditions improve, and short-horizon persistence once high yield is reached. RH and PAR are dominant levers, accelerating upgrades and damping regressions; day-to-day CO2 deviations show no clear pooled signal. Residual differences between compartments are modest. By mapping intensities to 7--30 day probabilities, the model yields actionable guidance for humidity and lighting and a lightweight, interpretable component for greenhouse digital twins.

翻译：温室决策通常依赖静态阈值，但作物产出会在微气候驱动的不同状态间切换。我们将每日黄瓜产量建模为三个有序状态间的转移过程，并拟合了一个连续时间、协变量依赖的多状态模型。数据来自希腊沃洛斯市的四个温室隔间（24条生产线，62天）。状态定义基于对照组的三分位数一次性确定，并应用于所有隔间。转移强度取决于各隔间内相对湿度（RH）、光合有效辐射（PAR）和CO₂的标准化值，以及固定效应。结果显示：系统存在通过中间状态的内在上升趋势；除非条件改善，低产期具有"粘性"；一旦达到高产状态则呈现短期持续性。RH和PAR是主要调控因子，能加速状态提升并抑制状态回落；而逐日CO₂偏差未显示明确的整体信号。各隔间间的残差差异较小。通过将转移强度映射至7-30天的状态概率，该模型可为湿度与光照管理提供可操作的指导，并为温室数字孪生系统提供一个轻量级、可解释的组件。