Differentiation of Bovinae teeth from the Portel‑Ouest Mousterian cave (Loubens, Ariège, France) by near‑infrared spectroscopy and chemometrics

The Portel site, located on the Pyrenean piedmont in France (Ariège), includes two caves: the Portel‑Est cave, famous for its mainly Magdalenian cave paintings, and the Portel‑Ouest cave corresponding essentially to a Mousterian habitat (layers L to B1a: 135,000 to 36,300 years BP ; Ajaja, 1994, Tissoux, 2004). Excavations over five meters deep of stratigraphy carried out in the Portel‑Ouest by Joseph and Jean Vézian between 1949 and 1987 revealed 33 Neanderthal remains associated with over 200,000 vestiges. In these vestiges, we found 1483 Bovinae remains. In a previous paleontological study of similar vestiges, differentiating Bos primigenius from Bison priscus proved challenging. Considering morphological, biometric, or morphometric criteria, only 21% of the remains could be attributed to one of the two genera, with a clear predominance for Bison priscus. Thus 79% of the Bovinae remains could not be attributed to one or the other of the two genera, either because they had composite forms or because they were too fragmented or worn to attempt a specific attribution. The aim of the present project is thus to develop and exploit the rapid tool of near infrared spectroscopy to discriminate between these genera, focusing on the teeth. Each tooth in the database was scanned with a near‑infrared spectrometer. For 53 teeth, the database containing the infrared spectra was completed by the paleontological expertise designating the tooth as belonging to Bos or Bison. Chemometric tools were then used to build a model to assign the tooth to a genus, according to its infrared spectrum. In a final step, the model was used to predict the genus of 76 teeth that could not be assigned to the Bos or Bison genus by paleontologists. This step provided a projection of the animal population living at that time at Portel site. Finally, the results were compared with paleogenetic analyses.Le site du Portel, situé sur le piémont pyrénéen en France (Ariège), comprend deux grottes : la grotte du Portel‑Est, célèbre pour ses peintures rupestres principalement magdaléniennes, et la grotte du Portel‑Ouest correspondant essentiellement à un habitat moustérien (Couches L à B1a : 135 000 à 36 300 ans avant le ; Ajaja, 1994, Tissoux, 2004). Les fouilles stratigraphiques de plus de cinq mètres de profondeur, réalisées dans le Portel‑Ouest par Joseph et Jean Vézian entre 1949 et 1987, ont révélé 33 vestiges néandertaliens associés à plus de 200 000 autres vestiges. Dans ces vestiges, 1483 restes de Bovinae ont été trouvés. Dans une étude paléontologique précédente, la différenciation entre Bos primigenius et Bison priscus s'est avérée difficile. En tenant compte de critères morphologiques, biométriques ou morphométriques, seuls 21 % des restes ont pu être attribués à l'un des deux genres, avec une nette prédominance pour Bison priscus. Ainsi, 79 % des restes de Bovinae n'ont pu être attribués à l'un ou l'autre des deux genres, soit parce qu'ils avaient des formes composites, soit parce qu'ils étaient trop fragmentés ou trop usés pour tenter une attribution spécifique. Le but du présent projet est donc de développer et d'exploiter l'outil rapide de spectroscopie proche infrarouge pour discriminer ces genres, en se concentrant sur les dents. Chaque dent de la base de données a été scannée à l'aide d'un spectromètre proche infrarouge. Pour 53 dents, la base de données contenant les spectres infrarouges a été complétée par l'expertise paléontologique désignant la dent comme appartenant à Bos ou à Bison. Des outils chimiométriques ont ensuite été utilisés pour construire un modèle permettant d'attribuer la dent à un genre, en fonction de son spectre infrarouge. Dans une dernière étape, le modèle a été utilisé pour prédire le genre de 76 dents qui ne pouvaient pas être attribuées au genre Bos ou Bison par les paléontologues. Cette étape a permis d'obtenir une projection de la population animale vivant à cette époque sur le site de Portel. Enfin, les résultats ont été comparés aux analyses paléogénétiques réalisés sur ces vestiges

Classification of Popcorn (<i>Zea mays</i> var. <i>everta</i>) Using Near-Infrared Spectroscopy to Assess Zearalenon Risk Mitigation Strategies

This study delves into the detection of the mycotoxin zearalenone (ZEA) in popcorn, aligning with the broader goal of ensuring food safety and security. Employing fast, non-destructive near-infrared spectroscopy, the research analyzes 88 samples collected in France. In order to emphasize the dedication to robust methodologies, an essential element of sustainable practices, the assessment of various validation methods becomes significant. Six CART classification tree models, with a threshold of 68 µg/kg, are meticulously assessed. The study not only scrutinizes various validation strategies but also explores the concrete impact of the detection process, emphasizing sustainable practices. Model F (Kennard and Stone) is chosen for its commendable ability to generalize and its balanced performance, boasting 91% precision and 57% recall. Notably, this model excels in specificity, minimizing false positives and contributing to food safety. The identification of key wavelengths, such as 1007 nm, 1025 nm, and 1031 nm, highlights the potential for targeted interventions in crop management. In conclusion, this research showcases near-infrared spectroscopy as a sustainable approach to fortifying the food safety of popcorn, paving the way for advancements in ZEA risk detection and prevention, while minimizing environmental impact

Assessing macro- (P, K, Ca, Mg) and micronutrient (Mn, Fe, Cu, Zn, B) concentration in vine leaves and grape berries of vitis vinifera by using near-infrared spectroscopy and chemometrics

International audienceMacronutrients (phosphorus, potassium, calcium, and magnesium) and micronutrients (manganese, iron, copper, zinc, and boron) play an essential role not only in the general physiology of vines but also in the quality of wine produced. The quantity of each nutrient in the vine is generally determined by analyzing the leaf blades or petioles, but this approach imposes a typical delay of two weeks between sampling and receiving the results, which precludes real-time detection of nutritional deficiencies (e.g., boron deficiency at flowering). Therefore, a method to rapidly analyze vine organs is highly desirable. One candidate for such a method is near-infrared (NIR) reflectance spectroscopy coupled with chemometric methods, based on which winegrowers have already developed prediction models. This approach is widely used today in agriculture. The aim of the present study is to determine whether NIR spectroscopy can be used to obtain accurate information about the nutritional status of vines. In this study, we focus on the mass of phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), manganese (Mn), iron (Fe), copper (Cu), zinc (Zn), and boron (B) contained in different vine organs (leaf blades, petioles and berries) over the course of a year. The concentration of these elements was determined based on NIR absorbance spectra from 677 samples of various dried vine organs. Partial least square models for classification and prediction were then developed based on raw and pretreated spectra for each organ, following which the models were tested on an external prediction set. The results show that, for Ca and Mg, all organ models can be used routinely for classification or prediction. For prediction, the Ca (Mg), model produces r2 = 0.88, 0.70, and 0.72 (0.60, 0.72, and 0.80) for leaf blades, petioles, and berries, respectively. Only for leaf blades (berries) is the Ca (Mg) model sufficiently accurate to be used for prediction. For berries, the P, K, and Zn models produce r2 in prediction of 0.77, 0.79, and 0.82, respectively. For petioles, the K model proves reliable for prediction, with r2 = 0.76. The Fe, Cu, and B models produce r2 = 0.72, 0.71, and 0.52, which are suitable for classification but not for prediction. Finally, for leaf blades, the Fe and Cu models produce r2 0.58 and 0.61, respectively, in prediction and thus can be used routinely for classification

Assessing Risk of Fumonisin Contamination in Maize Using Near-Infrared Spectroscopy

Fumonisins are major mycotoxins found worldwide in maize and maize products. Because of their toxicity for both human and animals, European Union regulations were created to fix the maximal fumonisin B1 and B2 content allowed in foods and feeds. Unfortunately, directly measuring these mycotoxins by current analytical techniques is tedious and expensive and most measurement methods do not lend themselves to online control. Alternative approaches to chemical analysis have been developed and involve models that allow the mycotoxin contamination to be predicted based on environmental conditions and analysis by near-infrared (NIR) spectroscopy. In the present work, we use NIR spectroscopy to determine the fumonisin and fungal contents of 117 samples of maize. The determination coefficient between fumonisin and fungal-biomass content was 0.44. We establish herein a threshold for the number of CFUs for fungal biomass beyond which the fumonisin content is likely to exceed the European regulatory level of 4000 μg/kg. In addition, we determine the fungal content by using a NIR-spectroscopy model that allows us to sort samples of maize. Upon calibration, the percentage of well-classified samples was 96%, which compares favorably to the 82% obtained by independent verification

Effect of Popcorn (Zea mays var. everta) Popping Mode (Microwave, Hot Oil, and Hot Air) on Fumonisins and Deoxynivalenol Contamination Levels

International audienceMycotoxins are secondary metabolites that are produced by molds during their development. According to fungal physiological particularities, mycotoxins can contaminate crops before harvest or during storage. Among toxins that represent a real public health issue, those produced by Fusarium genus in cereals before harvest are of great importance since they are the most frequent in European productions. Among them, deoxynivalenol (DON) and fumonisins (FUM) frequently contaminate maize. In recent years, numerous studies have investigated whether food processing techniques can be exploited to reduce the levels of these two mycotoxins, which would allow the identification and quantification of parameters affecting mycotoxin stability. The particularity of the popcorn process is that it associates heat treatment with a particular physical phenomenon (i.e., expansion). Three methods exist to implement the popcorn transformation process: hot air, hot oil, and microwaves, all of which are tested in this study. The results show that all popping modes significantly reduce FUM contents in both Mushroom and Butterfly types of popcorn. The mean initial contamination of 1351 _g/kg was reduced by 91% on average after popping. For DON, the reduction was less important despite a lower initial contamination than for FUM (560 _g/kg). Only the hot oil popping for the Mushroom type significantly reduced the contamination up to 78% compared to unpopped controls. Hot oil popping appears to provide the most important reduction for the two considered mycotoxins for both types of popcorn (-98% and- 58% average reduction for FUM and DON, respectively

Prediction and detection of human epileptic seizures based on SIFT-MS chemometric data

International audienceAlthough epilepsy is considered a public health issue, the burden imposed by the unpredictability of seizures is mainly borne by the patients. Predicting seizures based on electroencephalography has had mixed success, and the idiosyncratic character of epilepsy makes a single method of detection or prediction for all patients almost impossible. To address this problem, we demonstrate herein that epileptic seizures can not only be detected by global chemometric analysis of data from selected ion flow tube mass spectrometry but also that a simple mathematical model makes it possible to predict these seizures (by up to 4 h 37 min in advance with 92% and 75% of samples correctly classified in training and leave-one-out-cross-validation, respectively). These findings should stimulate the development of non-invasive applications (e.g., electronic nose) for different types of epilepsy and thereby decrease of the unpredictability of epileptic seizures

Fate, uptake and gut toxicity of two colloidal silver products in mice: how micro X-ray fluorescence, micro X-ray absorption spectroscopy and near-infrared spectroscopy provide new insights in food nanotoxicology

International audienceSSilver biodistribution and gut toxicity of two commercially available colloidal silver products, Mesosilver™ and AgC, were evaluated in male mice. AgC is composed solely of ionic silver (Ag+) while Mesosilver™ contains a mix of silver nanoparticles (AgNPs) and Ag+ ions. After high-dose (approximately 3 mg per kg body weight (bw) per day) sub-chronic exposure, silver accumulation was close for Mesosilver™ and AgC. The combination of micro X-ray fluorescence and micro X-ray absorption spectroscopy showed that metallic AgNPs and Ag+ ions initially contained in Mesosilver™ were subjected to physicochemical modifications during their fate in the gut. In the colon, most Ag atoms were oxidized and dissolved to form Ag complexes with thiol groups (-SH) of proteins and/or peptides. Sub-chronic exposure at lower dose (150 μg per kg bw per day) led to a moderate impact on the gut barrier for both colloidal silver products. An increase in colonic LCN-2 was observed only after AgC exposure. For gut microbiota at the genus level, exposure to Mesosilver™ led to a decrease in Ruminococcus and Anaerosporobacter, while Intestinimonas increased. Exposure to AgC resulted in an increase in Clostridium sp. ASF356 and Tyzzerella, while the relative abundance of Anaerosporobacter decreased. In addition, the Saccharomycetes fungal population increased. Near-infrared spectroscopy was able to satisfactorily discriminate the Mesosilver™-vs. AgC-exposed mice for both exposure doses. This study highlights the applicability of biophysics-based methodologies for providing novel insights into colloidal silver uptake, fate and toxicological effects after oral exposur