Evaluation of the production year in Italian and Chinese tomato paste for geographical determination using O2PLS models

Quality Assessment and Classification of Codonopsis Radix Based on Fingerprints and Chemometrics

In China, Codonopsis Radix (CR) is frequently consumed both as food and medicine. Here, a comprehensive strategy based on fingerprinting and chemometric approaches was created to explore the influence of origins, storage time and kneading processing on the quality of CR. Firstly, high-performance liquid chromatography with diode array detection was used to obtain the fingerprints of 35 batches of CR from six different origins and 33 batches of CR from varying storage times or kneading procedures. Secondly, chemometric methods including similarity analysis (SA), principal component analysis (PCA), hierarchical clustering analysis (HCA), and two-way orthogonal partial least square with discriminant analysis (O2PLS-DA) were used to evaluate the differences of chemical components in CR so as to identify its source and reflect its quality. Moreover, 13 and 16 major compounds were identified as marker compounds for the discrimination of CR from different origins, storage time and kneading processing, respectively. Furthermore, the relative content of the marker components and the exact content of Lobetyolin were measured, indicating that the contents of these components vary significantly between various CR samples. Meanwhile, the chemical components of CR were identified using Mass spectrometry. According to the findings of our investigation, the quality of CR from Gansu was the best, followed by Shanxi and then Sichuan. The quality of CR from Chongqing and Guizhou was poor. At the same time, the quality of CR was the best when it was kneaded and stored for 0 years, indicating that the traditional kneading process of CR is of great significance. Conclusively, HPLC fingerprint in conjunction with chemical pattern recognition and component content determination can be employed to differentiate the raw materials of different CR samples. Additionally, it is also a reliable, comprehensive and prospective method for quality control and evaluation of CR.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

NMR Metabolomics Applied on the Discrimination of Variables Influencing Tomato (Solanum lycopersicum)

Tomato composition and nutritional value are attracting increasing attention and interest from both consumers and producers. The interest in enhancing fruits' quality with respect to beneficious nutrients and flavor/aroma components is based not only in their economic added value but also in their implications involving organoleptic and healthy properties and has generated considerable research interest among nutraceutical and horticultural industries. The present article reviews up to March 2020 some of the most relevant studies based on the application of NMR coupled to multivariate statistical analysis that have addressed the investigation on tomato (Solanum lycopersicum). Specifically, the NMR untargeted technique in the agri-food sector can generate comprehensive data on metabolic networks and is paving the way towards the understanding of variables affecting tomato crops and composition such as origin, variety, salt-water irrigation, cultivation techniques, stage of development, among many others. Such knowledge is helpful to improve fruit quality through cultural practices that divert the metabolism towards the desired pathways and, probably more importantly, drives further efforts towards the differentiation of those crops developed under controlled and desired agronomical conditions.

The potentiality of NMR-based metabolomics in food science and food authentication assessment

In the last years, there was an increasing interest on nuclear magnetic resonance (NMR) spectroscopy, whose applications experienced an exponential growth in several research fields, particularly in food science. NMR was initially developed as the elective technique for structure elucidation of single molecules and nowadays is playing a dominant role in complex mixtures investigations. In the era of the "omics" techniques, NMR was rapidly enrolled as one of the most powerful methods to approach metabolomics studies. Its use in analytical routines, characterized by rapid and reproducible measurements, would provide the identification of a wide range of chemical compounds simultaneously, disclosing sophisticated frauds or addressing the geographical origin, as well as revealing potential markers for other authentication purposes. The great economic value of high-quality or guaranteed foods demands highly detailed characterization to protect both consumers and producers from frauds. The present scenario suggests metabolomics as the privileged approach of modern analytical studies for the next decades. The large potentiality of high-resolution NMR techniques is here presented through specific applications and using different approaches focused on the authentication process of some foods, like tomato paste, saffron, honey, roasted coffee, and balsamic and traditional balsamic vinegar of Modena, with a particular focus on geographical origin characterization, ageing determination, and fraud detection.

Metabolomic tool to identify soybean [Glycine max (L.) Merrill] germplasms with a high level of shade tolerance at the seedling stage

The isoflavone profiles of seeds of various soybean genotypes with different levels of shade tolerance at the seedling stage were investigated. High-performance liquid chromatography (HPLC) was used to quantify 12 isoflavones, and the data were analyzed using a multivariate statistical analysis. Combined with field experimental data and an orthogonal partial least-squares discriminant analysis (OPLS-DA), several aglycones (genistein (GE), daidzein (DE), and glycitein (GLE)) were selected and identified as key compounds involved in the shade tolerance of soybean seedlings. Additional correlation analysis and laboratory shading stress experiments with soybean seedlings also confirmed the function of these selected isoflavones, especially GE, in the discrimination of soybean seedlings with different levels of shade tolerance. Furthermore, the structure-antioxidant activity relationships between a range of isoflavones and the plant shade-tolerance mechanism are discussed. Targeted metabolomic analyses of isoflavones could reveal the diversity of shade tolerance in soybean seedlings, thus contributing to the breeding of excellent soybean varieties.

Performance Assessment in Fingerprinting and Multi Component Quantitative NMR Analyses

An interlaboratory comparison (ILC) was organized with the aim to set up quality control indicators suitable for multicomponent quantitative analysis by nuclear magnetic resonance (NMR) spectroscopy. A total of 36 NMR data sets (corresponding to 1260 NMR spectra) were produced by 30 participants using 34 NMR spectrometers. The calibration line method was chosen for the quantification of a five-component model mixture. Results show that quantitative NMR is a robust quantification tool and that 26 out of 36 data sets resulted in statistically equivalent calibration lines for all considered NMR signals. The performance of each laboratory was assessed by means of a new performance index (named Qp-score) which is related to the difference between the experimental and the consensus values of the slope of the calibration lines. Laboratories endowed with a Qp-score falling within the suitable acceptability range are qualified to produce NMR spectra that can be considered statistically equivalent in terms of relative intensities of the signals. In addition, the specific response of nuclei to the experimental excitation/relaxation conditions was addressed by means of the parameter named NR. NR is related to the difference between the theoretical and the consensus slopes of the calibration lines and is specific for each signal produced by a well-defined set of acquisition parameters.

Evaluation of saffron (Crocus sativus L.) adulteration with plant adulterants by (1)H NMR metabolite fingerprinting

In the present work, a preliminary study for the detection of adulterated saffron and the identification of the adulterant used by means of (1)H NMR and chemometrics is reported. Authentic Greek saffron and four typical plant-derived materials utilised as bulking agents in saffron, i.e., Crocus sativus stamens, safflower, turmeric, and gardenia were investigated. A two-step approach, relied on the application of both OPLS-DA and O2PLS-DA models to the (1)H NMR data, was adopted to perform authentication and prediction of authentic and adulterated saffron. Taking into account the deficiency of established methodologies to detect saffron adulteration with plant adulterants, the method developed resulted reliable in assessing the type of adulteration and could be viable for dealing with extensive saffron frauds at a minimum level of 20% (w/w).

Linking gene expression and membrane lipid composition of Arabidopsis

Glycerolipid metabolism of plants responds dynamically to changes in light intensity and temperature, leading to the modification of membrane lipid composition to ensure optimal biochemical and physical properties in the new environment. Although multiple posttranscriptional regulatory mechanisms have been reported to be involved in the process, the contribution of transcriptional regulation remains largely unknown. Here, we present an integrative analysis of transcriptomic and lipidomic data, revealing large-scale coordination between gene expression and changes in glycerolipid levels during the Arabidopsis thaliana response to light and temperature stimuli. Using a multivariate regression technique called O2PLS, we show that the gene expression response is strictly coordinated at the biochemical pathway level and occurs in parallel with changes of specific glycerolipid pools. Five interesting candidate genes were chosen for further analysis from a larger set of candidates identified based on their close association with various groups of glycerolipids. Lipidomic analysis of knockout mutant lines of these five genes showed a significant relationship between the coordination of transcripts and glycerolipid levels in a changing environment and the effects of single gene perturbations.

Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics

The geographical origin of beef is of increasing interest to consumers and producers due to "mad cow" disease and the implementation of the Free Trade Agreement (FTA). In this study, (1)H NMR spectroscopy coupled with multivariate statistical analyses was used to differentiate the geographical origin of beef samples. Principal component analysis (PCA) and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) showed significant separation between extracts of beef originating from four countries: Australia, Korea, New Zealand, and the United States. The major metabolites responsible for differentiation in OPLS-DA loading plots were succinate and various amino acids including isoleucine, leucine, methionine, tyrosine, and valine. A one-way ANOVA was performed to statistically certify the difference in metabolite levels. The data suggest that NMR-based metabolomics is an efficient method to distinguish fingerprinting difference between raw beef samples, and several metabolites including various amino acids and succinate can be possible biomarkers for discriminating the geographical origin of beef.