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Microplastics and nanoplastics represent one of the major environmental issues nowadays due to their ubiquitous presence on Earth, and their high potential danger for living systems, ecosystems, and human life. The formation of both microplastics and nanoplastics strongly depends on both the type of pristine materials and the degradation processes related to biological and/or abiotic conditions. The aim of this study is to investigate the effect of two of the most relevant abiotic parameters, namely temperature and light, taken under direct control by using a Solar box, on five types of reference polymers: high density polyethylene (HDPE), low density polyethylene (LDPE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET). A multi-analytical approach was adopted to investigate in detail the first steps of plastics degradation. Samples of plastic materials at different degradation times were analyzed by means of 1H NMR spectroscopy and thermal desorption gas chromatography mass spectrometry (TD-GC-MS) technique. Several minor molecular species released during degradation were consistently identified by both techniques thus providing a comprehensive view of the various degradation products of these five types of microplastics. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR)‐based screening of materials is a powerful tool for quality control, authenticity testing, and purity testing of compounds. However, reliance on 3‐(trimethylsilyl)‐propane‐1‐sulfonate (DSS) and 3‐(trimethylsilyl)propanoic acid (TMSP) for referencing the spectra of aqueous samples is not without hazard, particularly with automated analyses. The assumption that these reference signals always represent 0 ppm is ubiquitous in NMR spectroscopy and is routinely used for spectral alignment. However, it has been found that cyclodextrins readily generate inclusion complexes with DSS and TMSP with the effect of rendering this assumption incorrect. These inclusion complexes alter the electronic shielding of the trimethylsilane functional groups on DSS and TMSP yielding a small, but significant, shift to a higher frequency in the signal relied upon for spectral referencing. As a result, samples containing traces of these compounds may be incorrectly declared fraudulent, inconsistent with standards, or adulterated. In order to maintain the viability of this screening method, vigilance and/or improved referencing of spectra is needed. [ABSTRACT FROM AUTHOR]

Microplastics and nanoplastics represent one of the major environmental issues nowadays due to their ubiquitous presence on Earth, and their high potential danger for living systems, ecosystems, and human life. The formation of both microplastics and nanoplastics strongly depends on both the type of pristine materials and the degradation processes related to biological and/or abiotic conditions. The aim of this study is to investigate the effect of two of the most relevant abiotic parameters, namely temperature and light, taken under direct control by using a Solar box, on five types of reference polymers: high density polyethylene (HDPE), low density polyethylene (LDPE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET). A multi-analytical approach was adopted to investigate in detail the first steps of plastics degradation. Samples of plastic materials at different degradation times were analyzed by means of 1H NMR spectroscopy and thermal desorption gas chromatography mass spectrometry (TD-GC-MS) technique. Several minor molecular species released during degradation were consistently identified by both techniques thus providing a comprehensive view of the various degradation products of these five types of microplastics.

Sweet oranges with distinguished origin label have been becoming a fraud target by confusing or hiding origins. In this study, high-resolution nuclear magnetic resonance (NMR) spectroscopy in combination with chemometrics was used to discriminate the geographical origins of China's sweet oranges from four main producing regions (Hunan, Hubei, Sichuan and Guangxi). Sixty-two components, including various saccharides, amino acids, organic acids, alcohols, ketone, flavanones and other compounds, were identified and quantified via their 1H NMR spectra, and the producing region-specific geographical indication components of China's sweet orange were further screened out. The sweet oranges in Hubei show favorable antioxidant properties due to their rich phenolic compounds, and those in Sichuan show rich and fresh flavors due to their wealthy amino acids. Our results are readily available for nutritional recommendation in human consumption, and helpful to distinguish the geographical origin of sweet oranges based on their nutritional characteristics especially geographical indication markers. • A rapid and inexpensive NMR method was used to analyze sweet orange. • 62 nutritional components in China's sweet oranges were identified and quantified. • The geographical indication markers of each geographical origin were screened out. • The results are available for nutritional recommendation in human consumption. [ABSTRACT FROM AUTHOR]

• Chemical compositions of Chinese honeys were identified via NMR technique. • Different pattern recognition methods were used to honey authentication. • The predictive models of adulterated honey were established with an accurate rate of above 95%. • Eight components were screened out as the potential markers of honey authentication. Honey authentication has been becoming more and more important and necessary to the honey producers, the consumers and the market regulatory authority due to its favorite organoleptic and healthy properties, high value and increasing export but prevalent falsification practice for economic motivation in China and the potential health risk of adulterated honey. In this study, we obtained the spectral profiles of 90 authentic and 75 adulterated Chinese honey samples by means of high resolution nuclear magnetic resonance (NMR) spectroscopy, and 65 kinds of major and minor components in honey were identified and quantified from their NMR spectra. Combining with the multivariate statistical analyses including principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squared-discriminant analysis (OPLS-DA), the discrimination models were successfully established to identify the adulterated honeys from the authentic ones with an accurate rate of 97.6%. Furthermore, the corresponding volcano plot was used to screen out 8 components including proline, xylobiose, uridine, β-glucose, melezitose, turanose, lysine and an unknown component, which are responsible for the differentiation between the authentic and adulterated honeys and will help to control Chinese domestic honey market. [ABSTRACT FROM AUTHOR]