Near-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4-allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm⁻¹) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r² = 96.34; RPD = 5.23), 4-methyl-guaiacol (r² = 96.1; RPD = 5.07), eugenol (r² = 96.06; RPD = 5.04), syringol (r² = 97.32; RPD = 6.11), 4-methyl-syringol (r² = 95.79; RPD = 4.88) and 4-allyl-syringol (r² = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beverages.

Fourier transform infrared spectroscopy (FTIR) with Attenuated Total Reflection (ATR) combined with functional data analysis (FDA) was applied to differentiate aged wine spirits according to the ageing technology (traditional using 250 L wooden barrels versus alternative using micro-oxygenation and wood staves applied in 1000 L stainless steel tanks), the wood species used (chestnut and oak), and the ageing time (6, 12, and 18 months). For this purpose, several features of the wine spirits were examined: chromatic characteristics resulting from the CIELab method, total phenolic index, concentrations of furfural, ellagic acid, vanillin, and coniferaldehyde, and total content of low molecular weight phenolic compounds determined by HPLC. FDA applied to spectral data highlighted the differentiation between all groups of samples, confirming the differentiation observed with the analytical parameters measured. All samples in the test set were differentiated and correctly assigned to the aged wine spirits by FDA. The FTIR-ATR spectroscopy combined with FDA is a powerful methodology to discriminate wine spirits resulting from different ageing technologies.

The traditional ageing of wine spirits is done in wooden barrels, however, high costs have led to the search for alternative technologies, such as the use of stainless steel tanks with wooden staves and the application of micro-oxygenation. This work evaluates the changes in the major volatile compounds of wine spirits aged for 6, 12 and 18 months in wooden barrels and stainless steel tanks with micro-oxygenation. For both ageing technologies, two types of wood (Limousin oak and Portuguese chestnut wood) were used. The samples were analysed concerning their alcohol strength (electronic densimetry) and volatile composition, namely of methanol, acetaldehyde, ethyl acetate and other major volatile compounds ((GC-FID) and near-infrared spectroscopy (NIR)). The results show that the ageing technology was more influential than the wood species for the volatile composition of wine spirits, namely acetaldedehyde, methanol, 2-methylpropan-1-ol and 2+3-methylbutan-1-ol. However, the opposite behaviour was found for the spectral data. The ageing process was accelerated by using the alternative ageing technology, especially with chestnut wood staves. The most informative spectral regions to discriminate samples were around 6859 cm⁻¹ and from 5200 cm⁻¹ to 4200 cm⁻¹. NIR is a promising technique to identify different technologies and different wood species used in the ageing process of wine spirits.

Many species of the so-called exotic plants coexist with native species in a balanced way, but others thrive very quickly and escape human control, becoming harmful—these are called invasive alien species. In addition to overcoming geographic barriers, these species can defeat biotic and abiotic barriers, maintaining stable populations. Ailanthus altissima is no exception; it is disseminated worldwide and is considered high risk due to its easy propagation and resistance to external environmental factors. Currently, it has no particular use other than ornamental, even though it is used to treat epilepsy, diarrhea, asthma, ophthalmic diseases, and seborrhoea in Chinese medicine. Considering its rich composition in alkaloids, terpenoids, sterols, and flavonoids, doubtlessly, its use in medicine or other fields can be maximised. This review will focus on the knowledge of the chemical composition and the discovery of the biological properties of A. altissima to understand this plant better and maximise its possible use for purposes such as medicine, pharmacy, or the food industry. Methods for the extraction and detection to know the chemical composition will also be discussed in detail.

Acacia spp. is an invasive species that is widespread throughout the Portuguese territory. Thus, it is pertinent to better understand this species in order to find different applications that will value its use. To evaluate the phenolic profile in Acacia flowers, ethanolic extracts obtained through an energized guided dispersive extraction were analysed, focusing on two species, Acacia retinodes and Acacia mearnsii, at two flowering stages. The phytochemical profile of each extract was determined by ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry and high-performance liquid chromatography coupled with diode array detector. The FTIR-ATR technique was used to distinguish the different samples’ compositions. The results showed the presence of high concentrations of phenolic compounds (>300 mg GAE/g extract), among which are flavonoids (>136 mg QE/g extract), for all combinations of species/flowering stages. The phytochemical profile showed a complex composition with 21 compounds identified and quantified (the predominant ones being epicatechin, rutin, vanillin, and catechol). Both species and flowering stages presented significant variations regarding the presence and quantity of phenols and flavonoids, so much so that a principal component analysis performed with FTIR-ATR spectra data of the extracts was able to discriminate between species and flowering stages.

This study intended to evaluate the potential industrial applications of various Acacia species (Acacia melanoxylon, Acacia longifolia, Acacia cyclops, Acacia retinodes, Acacia pycnantha, Acacia mearnsii, and Acacia dealbata) by examining their chemical composition, antioxidant, and antimicrobial properties. Using high-resolution mass spectrometry, a comprehensive analysis successfully identified targeted compounds, including flavonoids (flavonols/flavones) and phenolic acids, such as 4-hydroxybenzoic acid, p-coumaric acid, and ellagic acid. Additionally, p-coumaric acid was specifically identified and quantified within the hydroxycinnamic aldehydes. This comprehensive characterization provides valuable insights into the chemical profiles of the studied species. Among the studied species, A. pycnantha exhibited a higher concentration of total phenolic compounds, including catechin, myricetin, quercetin, and coniferaldehyde. Furthermore, A. pycnantha displayed notable antibacterial activity against K. pneumoniae, E. coli, S. Typhimurium, and B. cereus. The identified compounds in Acacia pods and their shown antibacterial activities exhibit promising potential for future applications. Moreover, vibrational spectroscopy was a reliable method for distinguishing between species. These significant findings enhance our understanding of Acacia species and their potential for various industrial applications.