Rapeseed oil, a vital oilseed crop facing growing global demand, encounters a significant challenge in achieving uniform seed maturity, owing to asynchronous flowering. Traditional maturity assessment methods are limited by their destructive nature. Hyperspectral imaging (HSI) offers a non-destructive, efficient solution by using spatial and spectral data to accurately classify crop maturity. This advancement in HSI technology presents an opportunity to enhance rapeseed quality and breeding research, addressing the need for more effective maturity classification methods.