4.7 Article

Quantification of soluble solids and individual sugars in apples by Raman spectroscopy: A feasibility study

Journal

POSTHARVEST BIOLOGY AND TECHNOLOGY
Volume 180, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.postharvbio.2021.111620

Keywords

Raman spectroscopy; SSC; Apples; Chemometrics; Sugars; Non-destructive analysis

Funding

  1. Norwegian Agricultural Food Research Foundation [314111, 314599]
  2. Fundacion Ramon Areces

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This study demonstrates the feasibility of using Raman spectroscopy for quantification of soluble solids and individual sugars in apples, achieving high estimation accuracy with multivariate calibration models. Results show that identifiable Raman bands related to target sugars can be highlighted in regression coefficients for all calibration models, indicating the potential for accurate estimation of sugar content in apples using Raman spectroscopy.
This study reports the feasibility of using Raman spectroscopy for quantification of soluble solids and individual sugars in apples. Six different commercial apple varieties were measured by Raman spectroscopy at three different steps: 1) Intact apples with skin, 2) apples without skin and 3) juices obtained from apples. Results indicated that it is possible to measure Raman signals to a depth of 8 mm into the apple with a wide area Raman probe. Multivariate calibration models were established to evaluate how well Raman spectra can be used to estimate the quality parameters SSC (%), total sugars, glucose, fructose and sucrose. Estimation accuracy for SSC was comparable with what is achievable with near-infrared spectroscopy: Root mean square error of crossvalidation (RMSECV) = 0.66, 0.46 and 0.72 % and coefficients of determination (R2) = 0.70, 0.85 and 0.63 for intact apples, apples without skin and juices, respectively. Sucrose and glucose were well estimated with RMSECV of 2.8, 1.9, 2.1 mg/mL for glucose and 5.8, 3.9 and 3.7 mg/mL for sucrose, for the three sample cases, respectively. Coefficient of determination was higher than 0.82 for all models. Regression coefficients for all calibration models highlighted identifiable Raman bands that could be related to the target sugars.

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