Non-Targeted Detection and Quantification of Food Adulteration of High-Quality Stingless Bee Honey (SBH) via a Portable LED-Based Fluorescence Spectroscopy.

Stingless bee honey (SBH) is rich in phenolic compounds and available in limited quantities. Authentication of SBH is important to protect SBH from adulteration and retain the reputation and sustainability of SBH production. In this research, we use portable LED-based fluorescence spectroscopy to generate and measure the fluorescence intensity of pure SBH and adulterated samples. The spectrometer is equipped with four UV-LED lamps (peaking at 365 nm) as an excitation source. Heterotrigona itama, a popular SBH, was used as a sample. 100 samples of pure SBH and 240 samples of adulterated SBH (levels of adulteration ranging from 10 to 60%) were prepared. Fluorescence spectral acquisition was measured for both the pure and adulterated SBH samples. Principal component analysis (PCA) demonstrated that a clear separation between the pure and adulterated SBH samples could be established from the first two principal components (PCs). A supervised classification based on soft independent modeling of class analogy (SIMCA) achieved an excellent classification result with 100% accuracy, sensitivity, specificity, and precision. Principal component regression (PCR) was superior to partial least squares regression (PLSR) and multiple linear regression (MLR) methods, with a coefficient of determination in prediction (R2p) = 0.9627, root mean squared error of prediction (RMSEP) = 4.1579%, ratio prediction to deviation (RPD) = 5.36, and range error ratio (RER) = 14.81. The LOD and LOQ obtained were higher compared to several previous studies. However, most predicted samples were very close to the regression line, which indicates that the developed PLSR, PCR, and MLR models could be used to detect HFCS adulteration of pure SBH samples. These results showed the proposed portable LED-based fluorescence spectroscopy has a high potential to detect and quantify food adulteration in SBH, with the additional advantages of being an accurate, affordable, and fast measurement with minimum sample preparation.

Mandarin orange (Citrus reticulata Blanco cv. Batu 55) ripeness level prediction using combination reflectance-fluorescence spectroscopy.

Optical characteristics of Mandarin Orange cv. Batu 55 of different maturity level has been obtained using reflectance (Vis-NIR) and fluorescence spectroscopy. Spectra features of both reflectance and fluorescence spectroscopy have been evaluated to develop a ripeness prediction model. Spectra dataset and reference measurements were subject to the partial least square regression (PLSR) analysis. The best prediction models were using reflectance spectroscopy data showing the coefficient of determination R2 up to 0.89 and root mean square error (RMSE) of 2.71. On the other hand, it was found that fluorescence spectroscopy showed interesting spectra change in correlation with the accumulation of bluish and reddish fluorescence compounds in the lenticel spots on the fruit surface. The best prediction model using fluorescence spectroscopy data showed the R2 of 0.88 and RMSE of 2.81. Besides that, it wa found that combining spectra of reflectance and fluorescence features could increase the R2 of the partial least square regression (PLSR) model with Savitzky-Golay smoothing, up to 0.91 for brix-acid ratio prediction with RMSE 2.46. These results show the potential of the combined reflectance-fluorescence spectroscopy system for Mandarin ripeness assessment.

Antioxidant assessment of agricultural produce using fluorescence techniques: a review.

The study of bioactive compounds like food antioxidants is getting huge attention and curiosity by researchers and other relevant stakeholders (e.g., food and pharmaceutical industries) due to their health benefits. However, the currently available protocols to estimate the antioxidant activity of foods are time-consuming, destructive, require complex procedures for sample preparation, need technical persons, and not possible for real-time application, which are very important for large-scale or industrial applications. On the other hand, fluorescence spectroscopy and imaging techniques are relatively new, fast, mostly nondestructive, and possible to apply real-time to detect the antioxidants of foods. However, there is no review article on fluorescence techniques for estimating antioxidants in agricultural produces. Therefore, the present review comprehensively summarizes the overview of fluorescence phenomena, techniques (i.e., spectroscopy and computer vision), and their potential to monitor antioxidants in fruits and vegetables. Finally, opportunities and challenges of fluorescence techniques are described toward developing next-generation protocols for antioxidants measurement. Fluorescence techniques (both spectroscopy and imaging) are simpler and faster than available traditional methods of antioxidants measurement. Moreover, the fluorescence imaging technique has the potential to apply in real-time antioxidant identification in agricultural produce such as fruits and vegetables. Therefore, this technique might be used as a next-generation protocol for qualitative and quantitative antioxidants measurement after improvements like new material technologies for sensor (detector) and light sources for higher sensitivity and reduce the cost of implementing real-world applications.

Assessment of chalkiness index of Sake rice using transmission imaging.

The higher chalkiness level of the white core kernel is prone to breakage during the high degree polishing. So, grading white core kernel based on chalkiness level is crucial to making premium quality Sake (rice wine) in the brewing industry. The chalkiness level in the white core kernel is currently performed destructively. Thus, a chalkiness index is required to assess the level in the white core kernel. This research assesses the white core rice kernel based on the chalkiness index non-destructively. Here, the optical transmission property in the visible to near-infrared (VIS-NIR) region of rice was measured using a V-670 spectrophotometer equipped with an integrating sphere to investigate the variation of chalkiness level rice samples. The images were then acquired by transmission mode of four types of intact Sake rice kernel using blue light-emitting diodes (LEDs), green, red, and NIR LEDs in which the peak wavelength of the LEDs was 465 nm, 525 nm, 630 nm, and 830 nm, respectively. The result indicates that the rice samples were more penetrated and better visualized chalkiness by light in the NIR region. Therefore, the wavelength region in NIR showed better discrimination between transparent and opaque parts in white core's Sake rice. Furthermore, the proposed chalkiness index was inversely correlated with the gray-level intensity of the transmittance image. This gray value was significantly correlated (R2 = 0.89) with the chalkiness index in the NIR region. So, gray values of NIR transmittance images were identified as sensitive for chalkiness index, which would be applied for sorting the white core kernel with different levels of chalkiness in the Sake brewing industry.

Association of fruit, pericarp, and epidermis traits with surface autofluorescence in green peppers.

We investigated the association of blue fluorescence (excitation at 365 nm) with the traits of the fruit, pericarp, and epidermis in green peppers. The fruits were manually classified into two groups based on fluorescence brightness. The dark fluorescence group showed the accumulation of blue-absorbing pigments and a thicker cuticular structure, suggesting epidermal development.

Thermal oxidation assessment of Italian extra virgin olive oil using an UltraViolet (UV) induced fluorescence imaging system.

Extra virgin olive oil is a high-quality product with profound health benefits but is susceptible to degradation due to oxidation. Environmental conditions such as temperature, oxygen, and light, promote the oxidation process. From this perspective thermal oxidation stability is of primary concern in terms of food quality and safety. The ability to resist oxidation ensures continued nutritional and economic value. In this study, the thermal oxidation stability of four mono-cultivars of extra virgin olive oil from four different regions of Italy was studied. The samples underwent thermal treatment at 120 °C with measurements taken at regular time intervals over 180 min. To develop a simplified imaging system, the fluorescence characteristics of the samples during thermal exposure were measured using front-face fluorescence and transmittance spectroscopy in order to assess the changes that occur due to thermal exposure. Standard quality indices including; Peroxide value, acidity, K232, and K270, were also measured following IOC (International Olive Council) procedures. Image processing of both color and fluorescence images was done to ascertain cultivar responses to the thermal treatment. Fluorescence peaks associated with polyphenols, oxidation products, and chlorophyll were identified and monitored, and a comparison made between the different cultivars. Fluorescence peaks were observed at emission wavelengths 435, 465, and 570 nm, which are suspected to be products of oxidation and hydrolysis, respectively. The cultivars with a higher concentration of polyphenols showed greater resistance to the formation of oxidation products; an indication that they have a higher thermal stability. The B channel of the RGB color space was identified as being sensitive to changes in UltraViolet (UV) induced fluorescence images due to thermal exposure, and to enable the monitoring of the thermal stability of the different cultivars of extra virgin olive oil.

Combined fluorescence-transmittance imaging system for geographical authentication of patchouli oil.

Recently, demand for authentication technology is growing rapidly in an attempt to overcome counterfeiting of high-value agricultural products, such as patchouli oil. Fingerprinting methods based on spectroscopy are one such technology being used for authentication. However, the spectral datasets obtained are multivariate in nature; containing thousands of data points for a single sample, making data acquisition and processing time-consuming. Therefore, reduction and simplification in the number of variables used required is needed to provide a more rapid and applicable method. Color cameras, which can capture image in the visible region light, could be such an alternative spectral data acquisition approach. In this research, a simplified spectroscopy method was developed for origin authentication of patchouli oil. The system consists of front ultraviolet light induced (365 nm) fluorescence and a white LED-based backlighting imaging system that consecutively captures the fluorescence and transmittance characteristics of the oil in the visible region. From the captured images, features were extracted and analyzed using Principle Component Analysis (PCA) to identify important image features for discrimination of origin. From the samples measured, the samples clustered around three islands of origin in the PCA space. A classification model based on fluorescence and transmittance image features (color values) could discriminate origin classes with a total accuracy of 88.46%. A lower accuracy was found for the Java class due to low sample numbers. This result demonstrates that the proposed system has the potential to be a rapid authentication tool for determining the geographical origin of patchouli oils.