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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #350269
Research Project: Nondestructive Quality Assessment and Grading of Fruits and Vegetables

Location: Sugarbeet and Bean Research

Title: Assessment of tomato soluble solids content and pH by spatially-resolved and conventional Vis/NIR spectroscopy

Author
item HUANG, YUPING - Nanjing Agricultural University
item Lu, Renfu
item CHEN, KUNJIE - Nanjing Agricultural University

Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/9/2018
Publication Date: 5/25/2018
Citation: Huang, Y., Lu, R., Chen, K. 2018. Assessment of tomato soluble solids content and pH by spatially-resolved and conventional Vis/NIR spectroscopy. Journal of Food Engineering. 236:19-28.

Interpretive Summary: Soluble solids content (SSC) and pH are two important quality parameters in determining optimal harvest time and implementing appropriate postharvest storage, processing, and marketing strategies for harvested tomato fruit. Currently, destructive methods are routinely used to measure the SSC and pH of tomatoes, which destroy the fruit and also are time consuming. Studies have demonstrated that visible and near-infrared spectroscopy is useful for nondestructive assessment of tomato quality attributes. However, conventional spectroscopy, also referred to as single-point (SP) spectroscopy, only provides point/area measurements, and it has limitations in assessing food products such as tomato, which are heterogeneous in structure and spatially variable in composition and property. To address the shortcomings of conventional SP spectroscopy, a new spectroscopic system was recently developed for simultaneous acquisition of up to 30 spatially-resolved (SR) spectra of 550-16,50 nm for the light source-detector distances of 1.5-36 mm. In this research, the SR system, along with two SP spectroscopic instruments covering the visible and shortwave near-infrared (Vis/SWNIR) region of 400-1,100 nm and the near-infrared (NIR) region of 900-1,650 nm, was used to assess the SSC and pH of 600 ‘Sun Bright’ tomatoes harvested at six maturity stages. Mathematical models for the acquired SR spectra and for SP Vis/SWNIR and NIR spectra were then developed to predict tomato SSC and pH. Results showed that combination of individual SR spectra overall resulted in better, more consistent predictions of SSC and pH, compared with single SR spectra. Better predictions of pH were obtained by using SR spectra (correlation coefficient r=0.819) than by SP Vis/SWNIR and NIR spectra (r=0.743 and 0.741 respectively). SR and SP NIR techniques had similar results for SSC prediction (r=0.801 versus 0.810). The SR spectroscopic technique enables acquiring more spatial-spectral information for food samples, and it thus can enhance quality assessment of tomato and other horticultural products.

Technical Abstract: A spatially-resolved (SR) spectroscopic system with a point light source and 30 detection optic fibers covering the wavelength range of 550-1,650 nm and the light source-detector distances of 1.5-36 mm was recently developed for optical property measurement and quality evaluation of food products. This paper reports on assessing quality of tomato fruit by using this SR system, in comparison with conventional single-point (SP) spectroscopy in interactance mode. SR spectra of 550-1,300 nm and SP spectra for the visible and shortwave near-infrared (Vis/SWNIR) (400-1,100 nm) and near-infrared (NIR) (900-1,300 nm) regions were acquired for 600 ‘Sun Bright’ tomato fruit of six maturity stages. Soluble solids content (SSC) and pH of tomato fruit were measured using standard destructive techniques. Partial least squares (PLS) models for individual SR spectra and their combinations and for SP Vis/SWNIR and NIR spectra were developed for prediction of SSC and pH. Results showed that SR spectra acquired at the light source-detector distances of 1.5-36 mm resulted in different prediction results for SSC and pH, with the correlation coefficient of prediction (r) ranging 0.608-0.791 and 0.688-0.800, respectively. Combinations of two or more SR spectra resulted in better, more consistent SSC and pH predictions, compared with individual SR spectra. PLS models for the optimum single and combined SR spectra had better predictions of pH (r=0.800 and 0.819, respectively) than those for SP Vis/SWNIR (r=0.743) and NIR (r=0.741) spectra, while SR predictions of SSC were comparable to SP NIR predictions (r=0.801 versus 0.810) but better than SP Vis/SWNIR (r=0.729). Since SR spectroscopy provides more spatial-spectral information, the technique has potential for enhancing quality assessment of tomato and other horticultural products.