Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines

Abstract

The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. ‘Big Top’ (yellow flesh) and ‘Magique’ (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630–900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the ‘Big Top’ cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the ‘Big Top’ and ‘Magique’ cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines.

Plant phenotyping relevance

ネクタリン果実の内部品質、硬さ、裂果障害を hyperspectral transmittance imaging と解析モデルで評価しており、表現型取得法の開発・検証が研究の中心である。

Code and data availability

The article describes hyperspectral transmittance imaging of nectarines with PLS-R/PLS-DA analysis, but contains no public phenotype dataset, image deposit, author code, or model availability statement. HYPER-Tools and PLS_Toolbox are generic third-party libraries, not paper-specific assets. The redivia.gva.es URL is a

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