Abstract
Herein, we developed a nondestructive detection system with low prediction errors for determining the vitamin C content in Indian jujube. This system comprises a Ge photodetector, a halogen lamp and five near-infrared (NIR) bandpass filters. The detection of vitamin C is enabled by the absorption of its OH and CH2 bonds in the NIR region. The light beams of our system were parallel-polarized and designed to be incident on the fruit at the Brewster angle (θB), which reduces reflectance noise from the fruit’s skin and enhances the OH and CH2 absorption signals of the fruit’s flesh. After the reflectance signal was analyzed by the partial least squares (PLS) algorithm to obtain the predicted vitamin C content of each fruit, the coefficient of prediction ( r p 2 ) and root-mean-square error of prediction (RMSEP) were calculated. When wavelengths of 1200, 1400, 1450, 1500 and 1550 nm were used for probing, r p 2 and RMSEP of the system detecting vitamin C were 0.84 and 1.65 mg/100 g, respectively. In summary, the vitamin C content of Indian jujube was predicted using a low-cost NIR detection system having a high r p 2 and low RMSEP; further, it comprises five parallel-polarized NIR beams and the PLS algorithm.
Highlights
Indian jujube is a typical high value crop in Asia; it is rich in vitamin C, an essential trace element that serves as an antioxidant and neutralizes free radicals in the human body [1]
A total of 180 fruits were purchased for this study and the number of Indian jujube samples used in this study was based on the number of samples used by Qing et al [14]
All of the light will penetrate into the flesh of the Indian jujube fruits, maximizing the absorption of incident light by chemical bonds within the fruit, which will manifest in the reflectance signal measured by the
Summary
Indian jujube is a typical high value crop in Asia; it is rich in vitamin C, an essential trace element that serves as an antioxidant and neutralizes free radicals in the human body [1]. The determination of a fruit’s vitamin C content typically requires destructive methods, for example, high-performance liquid chromatography (HPLC) analysis, where the fruit is sliced, squeezed and filtered to produce an extract for HPLC analysis [2]. This method is highly time consuming and the damaged fruits cannot be sold. The resulting spectrum is analyzed to predict the fruit quality These testing systems are costly owing to their built-in spectrometers [4], which has hindered the spread of their use in fruit collection centers and consumer applications
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