Active Whey Protein Edible Films and Coatings Incorporating Lactobacillus buchneri for Penicillium nordicum Control in Cheese

Fungal contamination of food is responsible for health issues and food waste. In this work, the incorporation of a lactic acid bacteria (LAB) with antifungal properties (Lactobacillus buchneri UTAD104) into whey protein-based films and coatings was tested for the control of an ochratoxigenic fungi (Penicillium nordicum) in a cheese matrix. The incorporation of L. buchneri cells resulted in thicker films with less luminosity than control films and colour alteration. Nevertheless, cells inclusion did not alter moisture content, water vapour permeability, mechanical properties, hydrophobicity and chemical structure of the films. Whey protein films were able to maintain the viability of L. buchneri UTAD104 cells in 105 CFU/mL after 30 days of storage at 25 \textdegreeC. When applied in cheese, films and coatings containing L. buchneri cells prevented fungal contamination for at least 30 days, while control cheeses with films and coatings either without LAB or with Lactobacillus casei UM3 (a strain without antifungal ability) showed fungal contamination during that period. Ochratoxin A was not found in cheeses treated with films and coatings containing L. buchneri UTAD104. Results showed that the inclusion of a LAB with antifungal properties in edible films and coatings can help to reduce or eliminate P. nordicum contamination in cheeses.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. Ana Guimarães received support through grant SFRH/BD/103245/2014 from the Portuguese FCT.info:eu-repo/semantics/publishedVersio

Color correction of baby images for cyanosis detection

\u3cp\u3eAn accurate assessment of the bluish discoloration of cyanosis in the newborn baby’s skin is essential for the doctors when making a comprehensive evaluation or a treatment decision. To date, midwives employ the score of APGAR to note any occurrence of discoloration on skin among newborn babies. However, there is still no known general method to automatically determine a cyanosis skin color and quantifying technique in a newborn baby. Furthermore, a viable yardstick is absent for evaluation purposes in training sessions. Hence, this study proposes a cyanosis skin detection in the image of a newborn with a new algorithm for a color correction using MacBeth Color Checker. This proposed system has three steps: (i) selecting cyanosis region of interest from images, (ii) correcting color via an algorithm to calibrate images, and (iii) generating a database of cyanosis CIE L*a*b* (CIELAB) values. This proposed method calculates color error with ΔE* via comparing the actual color value of MacBeth Colorchecker especially before and after applying correction for color. This proposed method to detect cyanosis allows modification of images with minimal effect upon image quality, thus assuring the viability in detecting and ascertaining values of CIELAB for cyanosis skin. Besides, this study hopes to use the outcomes of CIELAB values of cyanosis skin in order to develop a baby manikin with cyanosis that is high in fidelity in upcoming studies. This study is not associated to clinical purposes.\u3c/p\u3