Leonardo Ciaccheri

Olive tree leaf is a phenol-rich, high-potential-value biomass that can be used to formulate food additives and supplements. Leaf phenolic content varies depending on numerous factors, like cultivar, geographical origin, year, and season of harvest. The aim of this research was to evaluate the variations in phenolic profile of four major Tuscan cultivars (Frantoio, Leccio del Corno, Leccino, and Moraiolo) over four different phenological phases and across two years. All 96 olive leaf samples were harvested from trees grown in the same orchard located in Florence. After drying, their phenolic profile was characterized using HPLC-DAD-MS, and the obtained data were processed by ANOVA, GA-LDA, and RF methods. A total of 25 phenolic derivatives were analyzed, with total contents ranging 16,674.0–50,594.3 mg/kg and oleuropein (4570.0–27,547.7 mg/kg) being the predominant compound regardless of cultivar, year, and season of harvest. Oleuropein and hydroxytyrosol glucoside showed inverse proportionality and similar behavior across years in all cultivars, and therefore were highlighted as main phenolic compounds correlated with the seasonal variability in studied cultivars. Interesting behavior was also pointed out for apigenin rutinoside. Application of GA-LDA and RF methods allowed pointing out the excellent performance of leaf phenols in discriminating samples based on cultivar, harvest year, and harvesting season.

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.

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.

In the present work, Raman, Fourier Transform Infrared (FTIR) and elemental Laser-Induced Breakdown Spectroscopy (LIBS) spectroscopic techniques were used for the assessment of the influence of plant root composition towards shallow landslide occurrence. For this purpose, analyses were directly carried out on root samples collected from chestnut forests of the Garfagnana basin (northern Apennines, Italy) in different areas devoid and affected by shallow landslides due to frequent heavy rain events. Results have highlighted a correlation between the biochemical constituents of wooden roots and the sampling areas. In particular, different content of lignin/cellulose, as well as minerals nutrients, have been detected in roots collected where shallow landslides occurred, with respect to more stable areas. The results achieved are in line with the scientific literature which has demonstrated the link between the chemical composition of roots with their mechanical properties and, in particular, tensile strength and cohesion. Finally, portable spectroscopic instrumentations were employed without the need for either any sample preparation for Raman and LIBS spectroscopy or minimal preparation for FTIR spectroscopy. This novel and fast approach has allowed achieving information on the content of the major constituents of the root cell, such as cellulose and lignin, as well as their mineral nutrients. This approach could be reasonably included among the vegetation protection actions towards instability, as well as for the evaluation of shallow landslide susceptibility, combining geological, vegetational and biochemical parameters with sustainability.

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.

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.