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Evaluation of near infrared spectra for the prediction of post harvest quality in canning peaches

机译:评价近红外光谱以预测桃罐头收获后的品质

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Huge production losses occur because of deterioration of quality of clingstone peaches during cold storage, rendering the fruit unsuitable for canning. Near infrared (NIR) spectra recorded from intact clingstone peaches were evaluated to predict post harvest quality of these peaches. The NIR spectra were recorded, before storage, on the fresh peaches while the subjective post-storage quality, fruit firmness and diameter (reference data) were determined after either three- (2002 season) or two-week (2003 season) cold storage periods at -0.5 degrees C. Poor post-storage quality was indicated by softening of the flesh, loosening of the skin and adhesion of the flesh to the stone after destoning. Soft independent modeling by class analogy (SIMCA) gave correct total classifications of between 53 and 60% in comparison to the 57 to 65% obtained by multivariate adaptive regression splines (MARS). However, when predicting only poor post-storage quality, correct classfication rates of between 60 and 80% were obtained using MARS. Using classification trees, the fruit were classified into good and poor post-storage quality classes according to fruit firmness and diameter. Only reasonable results were obtained due to the poor relationship between the NIR spectra and firmness measurements.
机译:由于冷藏期间粘石桃的质量下降而导致巨大的生产损失,从而使该水果不适合罐装。评价了从完整的粘石桃中记录的近红外(NIR)光谱,以预测这些桃的收获后质量。在储藏之前,在鲜桃上记录近红外光谱,而在冷藏(2002年季节)或两周(2003年季节)之后,确定主观的储藏后品质,果实硬度和直径(参考数据)在-0.5摄氏度下。贮藏后质量差表明,肉体软化,皮肤松弛以及在爆轰后肉体与石材的粘附。通过类比法(SIMCA)进行的软独立建模给出了正确的总分类,介于53%和60%之间,而多元自适应回归样条(MARS)获得的正确分类为57%至65%。但是,当仅预测较差的存储后质量时,使用MARS可获得60%至80%的正确分类率。使用分类树,根据水果的硬度和直径将其分为良好和较差的存储后质量等级。由于近红外光谱和硬度测量之间的关系不佳,只能获得合理的结果。

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