A Weekly E-Commerce Seed Price Index and Short-Term Forecasting System: Evidence from Tomato, Pepper, and Lettuce

Measuring prices in agricultural e-commerce markets is complicated by promotional spikes, rapid product turnover, and specification heterogeneity. The aim of this study is to develop and validate a reproducible framework that couples promotion-robust weekly price measurement with calibrated short-term forecasting for agricultural e-commerce input markets. Drawing on 452,489 de-identified raw transaction records (448,308 retained after quality control) of tomato, pepper, and lettuce seeds from major Chinese e-commerce platforms (July 2020–October 2025), we construct a weekly Paasche-robust price index with a Top-10 SKU basket and winsorized prices, benchmarked against Laspeyres, Fisher, Törnqvist, and GEKS-TPD formulations. A time-dummy hedonic regression is applied for quality adjustment. Short-term forecasts are generated by a two-level ensemble combining SARIMAX, Temporal Fusion Transformer, and LightGBM via inverse-MAPE weighting, with adaptive conformal intervals for uncertainty quantification. The Paasche-robust index attenuates promotional noise while co-moving closely with superlative formulas (MA-12 correlations > 0.80). Machine-learning models reduce the one-week-ahead MAPE by 42–58% relative to SARIMAX, and the weighted ensemble achieves the best four-week-ahead accuracy for two of three crops. Conformal intervals deliver near-nominal coverage at short horizons. The framework offers a reproducible, deployable tool for real-time monitoring of agricultural e-commerce input markets and supports evidence-based decisions by farmers and policymakers.