将与西瓜成熟度相关的10项指标， 经聚类分析分为完全成熟和不完全成熟两大类， 利用PCADA和PLSDA两种建模方法， 通过近红外光谱分析， 针对小型西瓜京秀果实成熟度进行了定性判定。 其中PCADA模型的效果最好。 赤道部位建模的效果优于瓜顶部位。 两个模型中均有误判， 且存在着共同被误判的样品， 果实样品理化成分和结构的不同都会对光谱信息产生影响， 从而导致误判。 漫透射近红外技术在小型西瓜成熟度检测方面可以获得较好的效果。 但是建立预测模型时应选择合适的光谱采集部位和建模方法。

Dividing watermelons into two categories as not complete mature and fully mature by cluster analyzing the 10 indicators associated with maturity, the two modeling methods PCADA and PLSDA were used, and through the near-infrared spectroscopy, the maturity of small watermelon fruit JINGXIU was qualitatively determined. The PCADA model is the best. Modeling at the top position is better than that of the equatorial parts of the melon. The two models both have a miscarriage of justice, and exists the same sample with a miscarriage of justice. Fruit samples of different physical and chemical composition and structure will have an impact on the spectral information, resulting in miscarriage of justice. Near-infrared diffuse transmittance technique can get better results in detection of small watermelon maturity. But the prediction model should be established to select the appropriate parts of the spectrum acquisition and modeling methods.