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Simple Summary: Veneto is one of the most important Italian regions for poultry biodiversity. However, the indigenous population cannot compete, in terms of production, with the commercial lines. The nutritional value significantly varies among the breeds as a consequence of changes in egg composition and size. The variability in terms of egg composition is useful to develop Near-InfraRed spectroscopy calibration models for its prediction. The aims of the present study were to characterize egg composition and develop VIS-Near-infrared spectroscopy (VIS-NIR) models for its predictions in Italian local chicken breeds, namely Padovana Camosciata, Padovana Dorata, Polverara Bianca, Polverara Nera, Pepoi, Ermellinata di Rovigo, Robusta Maculata and Robusta Lionata. Hens were reared in a single conservation center under the same environmental and management conditions. A total of 200 samples (25 samples per breed, two eggs/sample) were analyzed for the composition of albumen and yolk. Prediction models for these traits were developed on both fresh and freeze-dried samples. Eggs of Polverara Nera and Polverara Bianca differed from eggs of the other breeds (p < 0.05) in terms of the greatest moisture content (90.06 ± 1.23% and 89.57 ± 1.31%, respectively) and the lowest protein content (8.34 ± 1.27% and 8.81 ± 1.27%) in the albumen on wet basis. As regards the yolk, Robusta Maculata and Robusta Lionata differed (p < 0.05) from the other breeds, having lower protein content (15.62 ± 1.13% and 15.21 ± 0.63%, respectively) and greater lipid content (34.11 ± 1.12% and 35.30 ± 0.98%) on wet basis. Eggs of Pepoi had greater cholesterol content (1406.39 ± 82.34 mg/100 g) on wet basis compared with Padovana Camosciata, Polverara Bianca and Robusta Maculata (p < 0.05). Spectral data were collected in reflectance mode in the VIS-NIR range (400 to 2500 nm) using DS2500 (Foss, Hillerød, Denmark) on fresh and freeze-dried samples. Models were developed through partial least-squares regression on untreated and pre-treated spectra independently for yolk and albumen, and using several combinations of scattering corrections and mathematical treatments. The predictive ability of the models developed for each compound was evaluated through the coefficient of determination (R2cv), standard error of prediction (SEcv) and the ratio of performance to deviation (RPDcv) in cross-validation. Prediction models performed better for freeze-dried than fresh albumen and yolk. In particular, for the albumen the performance of models using freeze-dried eggs was excellent (R2cv ≥ 0.91), and for yolk it was suitable for the prediction of protein content and dry matter. Good performances of prediction were observed in yolk for dry matter (R2cv = 0.85), lipids and cholesterol (R2cv = 0.74). Overall, the results support the potential of infrared technology to predict the composition of eggs from local hens. Prediction models for proteins, dry matter and lipids of freeze-dried yolk could be used for labelling purposes to promote local breeds through the valorization of nutritional aspects. [ABSTRACT FROM AUTHOR]

Determining cocoa bean quality is crucial for many players in the international supply chain. However, actual methods rely on a cut test protocol, which is limited by its subjective nature, or on time-consuming, expensive and destructive wet-chemistry laboratory procedures. In this context, the application of near infrared (NIR) spectroscopy, particularly with the recent developments of portable NIR spectrometers, may represent a valuable solution for providing a cocoa beans' quality profile, in a rapid, non-destructive, and reliable way. Monitored parameters in this work were dry matter (DM), ash, shell, fat, protein, total polyphenols, fermentation index (FI), titratable acidity (TA) and pH. Different chemometric analyses were performed on the spectral data and calibration models were developed using modified partial least squares regression. Prediction equations were validated using a fivefold cross-validation and a comparison between the different prediction performances for the portable and benchtop NIR spectrometers was provided. The NIRS benchtop instrument provided better performance of quantification considering the whole than the portable device, showing excellent prediction capability in protein and DM quantification. On the other hand, the NIRS portable device, although showing lower but valuable performance of prediction, can represent an appealing alternative to benchtop instruments for food business operators, being applicable in the field. [ABSTRACT FROM AUTHOR]

Simple Summary: Mineral content in dog food is essential to ensure animals' adequate development and health status, but its analysis is time-consuming and companies are not always equipped with the technology to perform it. Near-infrared spectroscopy (NIRS) is a rapid, objective, easy to manage, chemical-free, and non-destructive method that is already available in the food industry for the prediction of gross composition (e.g., moisture, protein, fat, etc.). However, this technological approach is not yet used for the prediction of minerals because there is scarce information regarding the feasibility of NIRS to predict minerals in pet food. Results of this study revealed that, among all minerals analyzed, adequate NIRS prediction models were obtained for S and K for extruded dry dog food. The development of prediction models for mineral content in dry dog food opens the possibility of on-line and at-line analyses of minerals in the products during the manufacturing process, which could help the manufacturing decision support system in the pet food industry. The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850–2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules. [ABSTRACT FROM AUTHOR]

Bacillus cytotoxicus is considered a potential emerging foodborne pathogen that has been under investigation in recent years. Most studies have focused on strains from vegetables, particularly potato products, but there is limited information on strains from other food sources. This study addresses the current research gap by investigating the genomic and phenotypic features of B. cytotoxicus isolated from edible insects. The whole genomes and key phenotypic traits of 20 strains isolated from edible insects were investigated. The comparative genome analysis also included 44 available genomes from other sources to identify possible genetic links and the mosaicism of virulence profiles (VP) and antimicrobial resistance genes (AMR). B. cytotoxicus isolated from edible insects showed marked thermotolerance, when vegetative forms could grow at 50-60 °C and survive at 65 °C and exhibited marked proteolytic activities, even at higher temperatures. The heterogeneous phenotypes observed suggest potential issues with defining suitable protocols for isolation and identification in this food matrix. Despite the limited genomic diversity observed, it was possible to identify links between isolates, demonstrating the co-isolation of different genomes/phenotypes from various insect samples and suggesting trade links between insect companies and the persistence of certain strains. A genomic comparison suggested segregating strains from edible insects with similar VP and AMR profiles. These findings indicate a degree of adaptation to different food niches, with strains from insects or insect-based products differing partially from those isolated from vegetable sources, showing possible associations with their respective food environments. The survival advantage conferred by thermotolerance underscores the need to assess the presence of these spore-forming bacteria carefully and to calibrate treatments and processes, to address the emerging risk posed by this pathogen and its implications for food safety., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study aimed to identify critical issues in artisanal bakery and pastry production in Italy that could improve food safety and quality. Fifteen voluntary Italian companies underwent on-site inspections and interviews from 2018 to 2021. The inspection concerned the production site characteristics, processing flows, materials, and personnel to pinpoint potential product contamination and record objective data collection through a 126-question demerit scoring system. The examined areas encompassed various aspects, such as the point of sale, management of raw materials and packaging, hygiene practices, finished product quality, sanitization procedures, external spaces, personnel, and other factors impacting food safety and hygiene. Additionally, assessments of the microbiological air quality were carried out. Two cohorts (six and nine companies in 2018-2019 and in 2020-2021, respectively) revealed critical issues in warehouse/packaging (70% non-compliance), finished product/cooling (50% non-compliance), and people/products flow (38% non-compliance). Site visits identified pest management and raw material handling challenges. Significant airborne mold and yeast contamination (30-50 colony-forming units/plate/h) were observed in areas near processing sites or with air turbulence. This study facilitated constructive discussions and proposed solutions with the participating companies., Competing Interests: Conflict of interest: the authors declare no potential conflict of interest., (Copyright © 2024, the Author(s).)

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples ( n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination ; R 2 = 0.89), K ( R 2 = 0.85), and Li ( R 2 = 0.74), followed by P, B, and Sr ( R 2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules., Competing Interests: The authors declare no conflicts of interest.