Full-cycle management of greenhouse tomato requires continuous information on crop state together with estimates of daily water and nutrient use, yet destructive biomass measurements are sparse, and a single fixed model shared across resources is prone to stage-dependent negative transfer. This study proposes Dual-Path Multi-timescale Fusion (DPMF), a development-aware framework for reconstructing crop state from sparse observations and estimating daily resource fluxes. The state path combines a process-based dry-matter prior with a gated recurrent unit trained on three kinds of supervision: point states, biomass increments between adjacent samples, and cumulative harvested-fruit dry matter.... More >