A rapid evaluation method for pumpkin sensory quality based on near-infrared spectroscopy

The sensory quality (SQ) of pumpkin fruit is one of the most important quality indexes for consumers. In this study, a rapid pumpkin SQ evaluation method based on near-infrared spectroscopy (NIRS) was introduced. The starch and moisture contents of pumpkins were first determined by NIRS, and then the SQ of pumpkin could be estimated indirectly by these components. Test was carried out on 97 samples of 34 pumpkin fruits. The pumpkin starch and water NIRS models based on variable dimension particle swarm optimization combined moving window (VDPSO-CMW) and standard normal variate transformation (SNV) showed the best predictive performances, whose predictive determination coefficients (R²_p) were 0.775 and 0.932, respectively. A multiple linear regression model (correlation coefficient = 0.788) was established based on the prediction results of the two models and the SQ values obtained from cooking experiments. The proposed method has the potential to provide effective support for pumpkin breeding and production.