Stage‑dependent bias and practical leaf area index estimations derived from the LAI‑2200C plant canopy analyzer in soybean canopies

Leaf area index (LAI) is fundamental for estimating canopy radiation interception and yield. Although the LAI-2200C Plant Canopy Analyzer enables non‑destructive measurements, its default assumptions are difficult to satisfy in row‑planted soybean, where canopy structure and leaf‑angle distribution change with growth stage and can introduce bias. We measured LAI at V, R2, R5, and R6 using both the LAI‑2200C and destructive sampling. Bias sources under the default setting and mitigation using Campbell’s ellipsoidal model and the clumping‑free effective LAI (Le) approach were evaluated. The ellipsoidal-model correction reduced bias during canopy formation (V–R2), whereas the Le approach offset overcorrections under strong directional heterogeneity and lowered root mean square error. Segmented regression showed that Le increased the saturation threshold, expanding the applicable LAI range. In contrast, under strong canopy aggregation (notably at R6), all corrections became unstable, indicating limits of gap‑fraction‑based estimation.