Smartphone-Enabled Colorimetry.

A smartphone is used as a colorimeter. The performance characterization for colorimetry is presented using both the built-in camera and a clip-on dispersive grating. Certified colorimetric samples provided by Labsphere® are considered as test samples. Color measurements directly performed utilizing the smartphone camera only are obtained using the RGB Detector app, downloaded from the Google Play Store. More precise measurements are achieved using the commercially available GoSpectro grating and related app. In both cases, to quantify the reliability and sensitivity of smartphone-based color measurements, the CIELab color difference ΔE between the certified and smartphone-measured colors is calculated and is reported in this paper. In addition, as an example of a practical application of interest for the textile industry, several samples of cloth fabrics with a palette of the most common colors are measured, and the comparison with the certified color values is presented.

Low-Cost Pocket Fluorometer and Chemometric Tools for Green and Rapid Screening of Deoxynivalenol in Durum Wheat Bran.

Cereal crops are frequently contaminated by deoxynivalenol (DON), a harmful type of mycotoxin produced by several Fusarium species fungi. The early detection of mycotoxin contamination is crucial for ensuring safety and quality of food and feed products, for preventing health risks and for avoiding economic losses because of product rejection or costly mycotoxin removal. A LED-based pocket-size fluorometer is presented that allows a rapid and low-cost screening of DON-contaminated durum wheat bran samples, without using chemicals or product handling. Forty-two samples with DON contamination in the 40-1650 µg/kg range were considered. A chemometric processing of spectroscopic data allowed distinguishing of samples based on their DON content using a cut-off level set at 400 µg/kg DON. Although much lower than the EU limit of 750 µg/kg for wheat bran, this cut-off limit was considered useful whether accepting the sample as safe or implying further inspection by means of more accurate but also more expensive standard analytical techniques. Chemometric data processing using Principal Component Analysis and Quadratic Discriminant Analysis demonstrated a classification rate of 79% in cross-validation. To the best of our knowledge, this is the first time that a pocket-size fluorometer was used for DON screening of wheat bran.

Fourier transform near-infrared and mid-infrared spectroscopy as efficient tools for rapid screening of deoxynivalenol contamination in wheat bran.

BACKGROUND: Deoxynivalenol (DON) is the most common Fusarium mycotoxin occurring in wheat and wheat-derived products, with several adverse and toxic effects in animals and humans. Although bran fractions produced by milling wheat have numerous health benefits, cereal bran is the part of the grain with the highest concentration of DON, thus representing a risk for consumers. Increased efforts have been made to develop analytical methods suitable for rapid DON screening. RESULTS: The applicability of Fourier transform near-infrared (FTNIR), or mid-infrared (FTMIR) spectroscopy, and their combination for rapid analysis of DON in wheat bran, was investigated for the classification of samples into compliant and non-compliant groups regarding the EU legal limit of 750 µg kg-1 . Partial least squares-discriminant analysis (PLS-DA) and principal component-linear discriminant analysis (PC-LDA) were employed as classification techniques using a cutoff value of 400 µg kg-1 DON to distinguish the two classes. Depending on the classification model, overall discrimination rates were from 87% to 91% for FTNIR and from 86% to 87% for the FTMIR spectral range. The FTNIR spectroscopy gave the highest overall classification rate of wheat bran samples, with no false compliant samples and 18% false noncompliant samples when the PC-LDA classification model was applied. The combination of the two spectral ranges did not provide a substantial improvement in classification results in comparison with FTNIR. CONCLUSIONS: Fourier transform near-infrared spectroscopy in combination with classification models was an efficient tool to screen many DON-contaminated wheat bran samples and assess their compliance with EU regulations. © 2018 Society of Chemical Industry.

Comparison of lycopene changes between open-field processing and fresh market tomatoes during ripening and post-harvest storage by using a non-destructive reflectance sensor.

BACKGROUND: Accumulation and stability of tomato lycopene markedly depends on the cultivar, plant growing and storage conditions. To estimate lycopene in open-field cultivated processing and fresh market tomatoes, we used a calibrated spectral reflectance portable sensor. RESULTS: Lycopene accumulation in fruits attached to the plant, starting from the Green ripening stage, followed a sigmoidal function. It was faster and reached higher levels in processing (cv. Calista) than fresh market (cv. Volna) tomatoes (90 and 62 mg kg-1 fresh weight, respectively). During storage at 12, 20 and 25 °C, Red tomatoes retained about 90% of harvest lycopene for three weeks. Pink tomatoes increased lycopene during the first week of storage, but never reached the lycopene values of Red tomatoes ripened on the vine. Storability at 12 °C retaining the highest quality in red tomatoes was limited to 14 and 7 days for Calista and Volna cultivars, respectively. CONCLUSION: Significant differences in lycopene accumulation and stability between processing and fresh market tomatoes were established by examining with time the very same fruits by a non-destructive optical tool. It can be useful in agronomical and post-harvest physiological studies and can be of interest for producers oriented to the niche nutraceutical market. © 2018 Society of Chemical Industry.

Evaluation of the Fruit Quality and Phytochemical Compounds in Peach and Nectarine Cultivars.

Qualitative traits and chemical properties of 32 peach cultivars (yellow flesh and white flesh fruits) and 52 nectarine cultivars (yellow flesh and white flesh fruits) of different pomological characteristics is performed, and the correlation between cultivars and chemical characteristics is analyzed. Yellow nectarines have a higher variability in soluble solids concentration (SSC) and titratable acidity (TA) values. Evaluation of color parameters (a*, b*, L*) shows a significant interaction between pulp color (white vs. yellow) and types (peaches vs. nectarines) of fruit. The difference between yellow and white fruits is stronger in nectarines than in peaches. Sucrose is the main sugar detected in peach fruits, with a percentage content of 78.37% and 76.70% of the total sugar content in yellow and white peaches, respectively, and 78.29% and 78.12% in yellow and white nectarines, respectively. Variability is found among cultivars for the chemical compounds analyzed. The yellow flesh has higher amounts of total carotenoids and TPC, while white-flesh fruits present an average antioxidant value higher than yellow-flesh fruits. No significant correlation is found for polyphenol content and DPPH, while an interaction (p < 0.005) between neochlorogenic acid content and peaches and nectarines is evidenced, with a neochlorogenic acid content higher in nectarines than in peaches.

Bluetooth-Connected Pocket Spectrometer and Chemometrics for Olive Oil Applications.

Unsaturated fatty acids are renowned for their beneficial effects on the cardiovascular system. The high content of unsaturated fatty acids is a benefit of vegetable fats and an important nutraceutical indicator. The ability to quickly check fat composition of an edible oil could be advantageous for both consumers and retailers. A Bluetooth-connected pocket spectrometer operating in NIR band was used for analyzing olive oils of different qualities. Reference data for fatty acid composition were obtained from a certified analytical laboratory. Chemometrics was used for processing data, and predictive models were created for determining saturated and unsaturated fatty acid content. The NIR spectrum also demonstrated good capability in classifying extra virgin and non-extra virgin olive oils. The pocket spectrometer used in this study has a relatively low cost, which makes it affordable for a wide class of users. Therefore, it may open the opportunity for quick and non-destructive testing of edible oil, which can be of interest for consumer, retailers, and for small/medium-size producers, which lack easy access to conventional analytics.

Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods.

Size and concentration are two important parameters for the analysis of microplastics (MPs) in water. The analytical tools reported so far extract this information in a single-particle analysis mode, dramatically increasing the analysis time. Here, we present a combination of multi-angle static light scattering technique, called "Goniophotometry", with chemometric multivariate data processing for the batch analysis of size and concentration of MPs in water. Nine different sizes of polystyrene (PS) MPs with diameters between 500 nm and 20 µm are investigated in two different scenarios with uniform (monodisperse) and non-uniform (polydisperse) size distribution of MPs, respectively. It is shown that Principal Component Analysis (PCA) can reveal the existing relationship between the scattering data of mono- and polydisperse samples according to the size distribution of MPs in mixtures. Therefore, a Linear Discriminant Analysis (LDA) model is constructed based on the PCA of scattering data of PS monodisperse samples and is subsequently employed to classify the size of MPs not only in unknown mono- and polydisperse PS samples, but also for other types of MPs such as Polyethylene (PE) and Polymethylmethacrylate (PMMA). When the size of MPs is classified, their concentration is measured using a simple linear fit. Finally, a Linear Least Square (LLS) model is used to evaluate the reproducibility of the measurements.

Visible and near-infrared absorption spectroscopy by an integrating sphere and optical fibers for quantifying and discriminating the adulteration of extra virgin olive oil from Tuscany.

Because of its high price, extra virgin olive oil is frequently targeted for adulteration with lower quality oils. This paper presents an innovative optical technique capable of quantifying and discriminating the adulteration of extra virgin olive oil caused by lower-grade olive oils. An original set-up for diffuse-light absorption spectroscopy in the wide 400-1,700 nm spectral range was experimented. It made use of an integrating sphere containing the oil sample and of optical fibers for illumination and detection; it provided intrinsically scattering-free absorption spectroscopy measurements. This set-up was used to collect spectroscopic fingerprints of authentic extra virgin olive oils from the Italian Tuscany region, adulterated by different concentrations of olive-pomace oil, refined olive oil, deodorized olive oil, and refined olive-pomace oil. Then, a straightforward multivariate processing of spectroscopic data based on principal component analysis and linear discriminant analysis was applied which was successfully capable of predicting the fraction of adulterant in the mixture, and of discriminating its type. The results achieved by means of optical spectroscopy were compared with the analysis of fatty acids, which was carried out by standard gas chromatography.

A Study of Overripe Seed Byproducts from Sun-Dried Grapes by Dispersive Raman Spectroscopy.

Overripe seeds from sun-dried grapes submitted to postharvest dehydration constitute a scarcely investigated class of vinification byproduct with limited reports on their phenolic composition and industrial applications. In this study, Raman spectroscopy was applied to characterize a selection of overripe seed byproducts from different white grapes (cv. Moscatel, cv. Pedro Ximénez and cv. Zalema) submitted to postharvest sun drying. The Raman measurements were taken using a 1064 nm excitation laser in order to mitigate the fluorescent effect and the dispersive detection scheme allowed a compactness of the optical system. Spectroscopic data were processed by a principal component analysis to reduce the dimensionality and partner recognition. The evolution of the Raman spectrum during the overripening process was compared with the phenolic composition of grape seeds, which was determined by rapid resolution liquid chromatography/mass spectrometry (RRLC/MS). A multivariate processing of the spectroscopic data allowed the classification of overripe seeds according to the grape variety and the monitoring of stages of the postharvest sun drying process.

Prediction Models for Assessing Lycopene in Open-Field Cultivated Tomatoes by Means of a Portable Reflectance Sensor: Cultivar and Growing-Season Effects.

Reflectance spectroscopy represents a useful tool for the nondestructive assessment of tomato lycopene, even in the field. For this reason, a compact, low-cost, light emitting diode-based sensor has been developed to measure reflectance in the 400-750 nm spectral range. It was calibrated against wet chemistry and evaluated by partial least squares (PLS) regression analyses. The lycopene prediction models were defined for two open-field cultivated red-tomato varieties: the processing oblong tomatoes of the cv. Calista (average weight: 76 g) and the fresh-consumption round tomatoes of the cv. Volna (average weight: 130 g), over a period of two consecutive years. The lycopene prediction models were dependent on both cultivar and season. The lycopene root mean square error of prediction produced by the 2014 single-cultivar calibrations validated on the 2015 samples was large (33 mg kg-1) in the Calista tomatoes and acceptable (9.5 mg kg-1) in the Volna tomatoes. A more general bicultivar and biyear model could still explain almost 80% of the predicted lycopene variance, with a relative error in red tomatoes of less than 20%. In 2016, the in-field applications of the multiseasonal prediction models, built with the 2014 and 2015 data, showed significant ( P < 0.001) differences in the average lycopene estimated in the crop on two sampling dates that were 20 days apart: on August 19 and September 7, 2016, the lycopene was 98.9 ± 9.3 and 92.2 ± 10.8 mg kg-1 FW for cv. Calista and 54.6 ± 13.2 and 60.8 ± 6.8 mg kg-1 FW for cv. Volna. The sensor was also able to monitor the temporal evolution of lycopene accumulation on the very same fruits attached to the plants. These results indicated that a simple, compact reflectance device and PLS analysis could provide adequately precise and robust (through-seasons) models for the nondestructive assessment of lycopene in whole tomatoes. This technique could guarantee tomatoes with the highest nutraceutical value from the production, during storage and distribution, and finally to consumers.

Observation of eight ancient olive trees (Olea europaea L.) growing in the Garden of Gethsemane.

For thousands of years, olive trees (Olea europaea L.) have been a significant presence and a symbol in the Garden of Gethsemane, a place located at the foot of the Mount of Olives, Jerusalem, remembered for the agony of Jesus Christ before his arrest. This investigation comprises the first morphological and genetic characterization of eight olive trees in the Garden of Gethsemane. Pomological traits, morphometric, and ultrastructural observations as well as SSR (Simple Sequence Repeat) analysis were performed to identify the olive trees. Statistical analyses were conducted to evaluate their morphological variability. The study revealed a low morphological variability and minimal dissimilarity among the olive trees. According to molecular analysis, these trees showed the same allelic profile at all microsatellite loci analyzed. Combining the results of the different analyses carried out in the frame of the present work, we could conclude that the eight olive trees of the Gethsemane Garden have been propagated from a single genotype.