Longitudinally and Vertically Balanced Sparse Indoor Temperature–Humidity Sensing Preserves Threshold-Defined Risk Inference in a Chinese Solar Greenhouse

Sensor failures reduce the spatial information available for greenhouse microclimate monitoring, but their practical consequences depend on whether agronomic risk decisions remain reliable. We evaluated the progressive loss of paired indoor temperature–relative humidity (T/RH) sensors in a Chinese solar greenhouse using whole-sensor holdout. Longitudinally and vertically balanced subsets and transparent estimators were frozen before a sealed final test of 28 dates, four calendar blocks and six stage-aware risks. Relative to a 20-input reference, a longitudinally and vertically balanced six-input network increased the temperature mean absolute error by 0.014 °C and the relative-humidity error by 0.027 percentage points; macro-recall changed by −0.001 and support-aware macro-F1 by −0.004, while median false-negative exposure remained unchanged. The results remained within the predefined limits across 26 agricultural-threshold variants. In an exploratory validation-only comparison, spatially concentrated six-input layouts had greater temperature error (+0.080 °C, 95% block-bootstrap interval +0.058 to +0.104 °C), relative-humidity error (+0.099 percentage points), and macro-F1 loss (−0.004) than longitudinally and vertically balanced layouts. Macro-F1 did not differ consistently between the longitudinally and vertically balanced layouts and the unconstrained random layouts. Longitudinal and vertical coverage therefore functions as a robustness constraint against concentrated input loss in this system, rather than evidence of universal six-sensor sufficiency or cross-greenhouse generalisation.