Assessment of Watermelon Quality Using Vibration Spectra

Abbaszadeh, Rouzbeh; Rajabipour, Ali; Ahmadi, Hojjat; Delshad, Mojtaba; Mahjoob, M. J.

doi:10.1007/978-3-642-27337-7_3

Cited by 4 publications

(1 citation statement)

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“…Non-destructive techniques for appropriate pre- and postharvest handling have received much attention by replacing time-consuming and labor-intensive conventional techniques for monitoring the quality of fruits ( Arendse et al, 2021 ). Several non-destructive methods such as acoustic impulse response ( Stone et al, 1996 ; Diezma-Iglesias et al, 2004 ; Ke et al, 2009 ; Zhang et al, 2010 ; Pintor et al, 2016 ), dielectric spectroscopy ( Nelson et al, 2007a , b ), laser Doppler vibrometry ( Abbaszadeh et al, 2011a , b , 2013a , b , 2014 , 2015a , b ), machine vision systems ( Ali et al, 2017 ; Jie and Wei, 2018 ), surface elastic waves ( Stone et al, 1996 ; Ikeda et al, 2015 ; Ali et al, 2017 ), near-infrared and visible spectroscopy ( Flores et al, 2008 ; Jie et al, 2014 , 2019 ) have been studied for internal and external evaluation of watermelon quality.…”

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confidence: 99%

Raman Spectroscopy Detects Changes in Carotenoids on the Surface of Watermelon Fruits During Maturation

Dhanani

Dou

Biradar³

et al. 2022

Front. Plant Sci.

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A non-invasive and non-destructive technique, Raman spectroscopy, was explored to distinguish different maturity stages (20, 30, 40, and 50 days after anthesis) of watermelon (Citrullus lanatus) fruits from four cultivars: Fascination, Orange Crisp, Amarillo and Crimson Sweet. Spectral acquisition from the fruit surface was carried out at the wavelength range of 400–2,000 cm−1 using a handheld Raman spectrometer equipped with 830 nm laser excitation source. The spectra were normalized at 1,438 cm−1 which was assigned to CH2 and CH3 vibration. Detecting changes in the spectral features of carotenoids on the surface of watermelon fruits can be used as a marker to monitor the maturity of the fruit. The spectral analysis confirmed the presence of two major carotenoids, lutein and β-carotene, and their intensity decreased upon maturity on the fruit surface. Identification of these pigments was further confirmed by resonance Raman spectra and high-performance liquid chromatography analysis. Results of partial least square discriminant analysis of pre-processed spectra have demonstrated that the method can successfully predict the maturity of watermelon samples with more than 85% accuracy. Analysis of Variance of individual Raman bands has revealed a significant difference among the stages as the level of carotenoids was declined during the ripening of the fruits. Thus, Raman spectral signatures can be used as a versatile tool for the non-invasive determination of carotenoid changes on the watermelon fruits’ surface during ripening, thereby enabling effective monitoring of nutritional quality and maturity indices before harvesting the watermelon.

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