A new method using evolving splines can accurately model changing seasonal patterns in agricultural data. By adjusting seasonal effects based on fixed reference points, this model captures fluctuations that vary in period or magnitude over time. The approach allows for testing if seasonal patterns remain consistent across multiple years. Applying this method to weekly tomato export data revealed significant insights into the evolving seasonal trends within the agricultural industry.