Evaluation of Carrot Quality Using Visible-Near Infrared Spectroscopy and Multivariate Analysis

Abstract

Carrot has a relatively high content of Vitamin C and it is a major source of natural carotenoids. However, carrot has a short shelf-life and is better consumed fresh. A quick assessment of its quality attributes is important to preserving its freshness. The objective of this study was to apply Vis-NIR spectroscopy to noninvasively assess and predict the various quality attributes of carrot (cv. Nectar), namely color (L*a*b*), moisture content (MC), total soluble solids (TSS), firmness, Vitamin C, and β-carotene. Two spectroscopic sensors (400-1,000 nm and 900-1,700 nm) were utilized and samples included whole root and 25.4 mm thick sliced disc. The best prediction models using partial least squares regression yielded correlation coefficient, r, and ratio of performance to deviation or r(RPD) of 0.50(0.73), 0.84(0.88), 0.86(2.07), 0.69(0.66), 0.97(1.44), 0.90(1.49), 0.47(1.47), and 0.92(1.76) for color indices, L* a* b*, firmness, MC, TSS, Vitamin C, and β-carotene, respectively. However, using only the wavelengths selected by interval partial least squares, the r(RPD) values for the aforementioned attributes improved and are presented as follows: 0.92(1.97), 0.96(2.83), 0.98(5.85), 0.99(6.65), 0.98(3.91), 0.99(5.93), 0.98(4.16), and 0.98(4.43), respectively. Generally, Vis-NIR region had higher prediction performance than NIR region, and whole roots had similar prediction performance as sliced samples. This study shows that rapid determination of quality parameters of carrot is possible through non-destructive Vis-NIR sensing, which could be useful for quality tracking during carrot supply chain. Moreover, results of this study could be improved using a larger sample size.

The Use of Infrared Spectroscopy for the Quantification of Bioactive Compounds in Food: A Review

“…Toledo-Martín et al [ 100 ] also found acceptable results for the total carotenoid content in blackberry (R 2 CV = 0.76, RMSECV = 0.01 mg/100 g), with the carotenoid model outperforming that developed for total phenolic content in the same crop. Higher model accuracies (R 2 CV > 0.9; RMSECV < 0.01 mg/100 g) were reported for β-carotene content in carrot [ 115 ] and marsh grapefruit [ 13 ], as well as for total carotenoids in honey [ 139 ].…”

“…Studies using infrared spectroscopy (NIRS or MIRS) for the estimation of ascorbic acid content were performed in Kakadu plum powder [ 109 ], carrot [ 115 ], frozen guava pulp [ 107 ], cashew apple and guava nectar [ 135 ], and soft drinks [ 138 ]. Most models showed reasonable accuracy (R 2 CV = 0.7–0.98; RMSECV = 4–7 mg/100 g).…”

Development of Detection System with Low Predictive Errors for Determining Vitamin C Content of Indian Jujube

“…For example, r 2 p values of 0.81 and 0.87 were obtained by an FT-NIR-based detection system for the vitamin C content of oranges and kiwifruit, respectively, with RMSEP values of 5.9 mg/100 g and 6.4 mg/100 g, respectively [18,29]. The r 2 p values of a system based on visible NIR spectroscopy in measuring the vitamin C content of carrots and tangerines were 0.72 and 0.82, respectively and the corresponding RMSEP values were 4.3 mg/100 g and 2.3 mg/100 g, respectively [30,31]. Another system that is based on NIR spectroscopy obtained r 2 p values of 0.80 and 0.70 and RMSEP values of 4.0 mg/100 g and 16.0 mg/100 g when measuring the vitamin C contents of apples and infant cereals, respectively [32,33].…”

Review on Yield Sensing Technologies for Horticultural crops

“…Therefore, these indices can be successfully used to determine water stress. Ahmed et al [43] utilized visible NIR spectroscopy to assess various internal characteristics like colour, firmness, vitamin C, β carotene and moisture content for carrot. 400-1000 nm and 900-1700 nm spectral range were used for the crop to find out characteristics of carrot (Dacus carota).…”