The consumption of fresh-cut agricultural produce in Korea has been growing. The browning of fresh-cut vegetables
that occurs during storage and foreign substances such as worms and slugs are some of the main causes of consumers’
concerns with respect to safety and hygiene. The purpose of this study is to develop an on-line system for evaluating
quality of agricultural products using hyperspectral imaging technology. The online evaluation system with single
visible-near infrared hyperspectral camera in the range of 400 nm to 1000 nm that can assess quality of both surfaces of
agricultural products such as fresh-cut lettuce was designed. Algorithms to detect browning surface were developed for
this system. The optimal wavebands for discriminating between browning and sound lettuce as well as between
browning lettuce and the conveyor belt were investigated using the correlation analysis and the one-way analysis of
variance method. The imaging algorithms to discriminate the browning lettuces were developed using the optimal
wavebands. The ratio image (RI) algorithm of the 533 nm and 697 nm images (RI533/697) for abaxial surface lettuce and
the ratio image algorithm (RI533/697) and subtraction image (SI) algorithm (SI538-697) for adaxial surface lettuce had the
highest classification accuracies. The classification accuracy of browning and sound lettuce was 100.0% and above
96.0%, respectively, for the both surfaces. The overall results show that the online hyperspectral imaging system could
potentially be used to assess quality of agricultural products.
Melamine (2,4,6-triamino-1,3,5-triazine) contamination of food has become an urgent and broadly recognized issue for which rapid and accurate identification methods are needed by the food industry. In this study, the feasibility and effectiveness of near-infrared (NIR) hyperspectral imaging was investigated for detecting melamine in milk powder. Hyperspectral NIR images (144 bands spanning from 990 to 1700 nm) were acquired for Petri dishes containing samples of milk powder mixed with melamine at various concentrations (0.02% to 1%). Spectral bands that showed the most significant differences between pure milk and pure melamine were selected, and two-band difference analysis was applied to the spectrum of each pixel in the sample images to identify melamine particles in milk powders. The resultant images effectively allowed visualization of melamine particle distributions in the samples. The study demonstrated that NIR hyperspectral imaging techniques can qualitatively and quantitatively identify melamine adulteration in milk powders.
A nondestructive, real-time pungency measuring system with visible and near-infrared spectroscopy has been recently
developed to measure capsaicinoids content in Korean red-pepper powder. One hundred twenty-five red-pepper powder
samples produced from 11 regions in Republic of Korea were used for this investigation. The visible and near-infrared
absorption spectra in the range from 450 to 950 nm were acquired and used for the development of prediction models of
capsaicinoids contents in red-pepper powders without any chemical pretreatment to the samples. Partial Least Squares
Regression (PLSR) models were developed to predict the regional capsaicinoids contents using the acquired absorption
spectra. The chemical analysis of the total capsaicinoids (capsaicin and dihydrocapsaicin) was performed by a high
performance liquid chromatographic (HPLC) method. The determination coefficient of validation (RV2) and the standard
error of prediction (SEP) for the capsaicinoids content prediction model, for a representative region in this study, were
0.9585 and ±10.147 mg/100g, respectively.
Many researchers have been tried to find a rapid pungency measuring method for the capsaicinoids, the main component of spicy to
overcome the disadvantages of the conventional HPLC measurement which is labor-intensive, time-consuming, and expensive. In
this research, an on-line based pungency measuring system for red-pepper powder was developed using a UV/Visible/Near-Infrared
spectrometer with the wavelength range of 400 ~ 1050 nm. The system was constructed with a charge-couple device(CCD)
spectrometer, a reference measuring unit, and a sample transfer unit. Predetermined non-spicy red-pepper powder were
mixed with spicy one (var. Chungyang) to produce samples with a wide range of spicy levels. Total 33 different samples with
11 spicy levels and three particle size(below 0.425 mm, 0.425 ~ 0.71 mm, 0.71 ~ 1.4 mm) were prepared for
measurements. The Partial Least Square Regression Model (PLSR model) was developed to predict the capsaicinoids content with
the obtained spectra using the developed pungency measuring system and compared with the results measured by HPLC. The best
result of PLSR model (R2 = 0.979, SEP = ± 6.56 mg%) was achieved for the spectra of red-pepper powders of the
particle size below 1.4 mm with a pretreatment of smoothing with a 6.5 nm wavelength gap. The results show the
potential of NIRS technique for non-destructive and on-line measurement of capsaicinoids content in red-pepper powder.
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