Determination of storage period of harvested plums by near‐infrared spectroscopy and quality attributes

Abstract

Harvested plums can be stored at low temperatures for a long time. During storage, several quality attributes of plums undergo changes, which are also associated with their best‐before date. This research proposed a fast method for the quick determination of plum storage time. With the integration of near‐infrared spectra measurements, plum quality parameters (firmness, soluble solids content, pH, and color), several classification models have been developed to determine the storage time. A variety of methods such as linear discriminant analysis (LDA), partial least squares (PLS), support vector machine (SVM), and generalized linear models (GLM) were used. It is concluded that the models based on near‐infrared spectra only with 14 selected features using LDA and PLS provide the best estimations, with accuracy values of 0.9917 and 0.9854, respectively. The models built with the attributes provide favorable results when using LDA and SVM (Radial basis), with accuracy values of 0.9261 and 0.8734, respectively. NOVELTY IMPACT STATEMENT: For the first time, we proposed the use of non‐destructive NIRS to establish classification models in plums based on post‐harvest storage time for maturity prediction. At the same time, several fruit quality attributes were also used for comparison.

Plant phenotyping relevance

収穫果実の貯蔵期間・成熟状態をNIRSと分類モデルで非破壊推定する手法が研究の中心であり、果実品質形質の取得・推定を技術的に評価している。

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