Maturity Prediction in Yellow Peach (Prunus persica L.) Cultivars Using a Fluorescence Spectrometer

Sensors (Basel). 2020 Nov 17;20(22):6555. doi: 10.3390/s20226555.

Abstract

Technology for rapid, non-invasive and accurate determination of fruit maturity is increasingly sought after in horticultural industries. This study investigated the ability to predict fruit maturity of yellow peach cultivars using a prototype non-destructive fluorescence spectrometer. Collected spectra were analysed to predict flesh firmness (FF), soluble solids concentration (SSC), index of absorbance difference (IAD), skin and flesh colour attributes (i.e., a* and H°) and maturity classes (immature, harvest-ready and mature) in four yellow peach cultivars-'August Flame', 'O'Henry', 'Redhaven' and 'September Sun'. The cultivars provided a diverse range of maturity indices. The fluorescence spectrometer consistently predicted IAD and skin colour in all the cultivars under study with high accuracy (Lin's concordance correlation coefficient > 0.85), whereas flesh colour's estimation was always accurate apart from 'Redhaven'. Except for 'September Sun', good prediction of FF and SSC was observed. Fruit maturity classes were reliably predicted with a high likelihood (F1-score = 0.85) when samples from the four cultivars were pooled together. Further studies are needed to assess the performance of the fluorescence spectrometer on other fruit crops. Work is underway to develop a handheld version of the fluorescence spectrometer to improve the utility and adoption by fruit growers, packhouses and supply chain managers.

Keywords: flesh colour; flesh firmness; index of absorbance difference (IAD); machine learning; non-destructive measurements; pigments; ripeness; sensor; skin colour; soluble solids.

MeSH terms

  • Color
  • Crops, Agricultural
  • Fruit*
  • Prunus persica*
  • Spectrometry, Fluorescence*