@misc{13015,
  abstract     = {{<jats:p>food are discarded annually, with a worldwide total exceeding 1.3 billion tonnes. A significant contributor to this issue are consumers throwing away still edible food due to the expiration of its best-before date. Best-before dates currently include large safety margins, but more precise and cost effective prediction techniques are required. To address this challenge, research was conducted on low-cost sensors and machine learning techniques were developed to predict the spoilage of fresh pizza. The findings indicate that combining a gas sensor, such as volatile organic compounds or carbon dioxide, with a random forest or extreme gradient boosting regressor can accurately predict the day of spoilage. This provides a more accurate and cost-efficient alternative to current best-before date determination methods, reducing food waste, saving resources, and improving food safety by reducing the risk of consumers consuming spoiled food.}},
  author       = {{Wunderlich, Paul and Pauli, Daniel and Neumaier, Michael and Wisser, Stephanie and Danneel, Hans-Jürgen and Lohweg, Volker and Dörksen, Helene}},
  booktitle    = {{Foods}},
  issn         = {{2304-8158}},
  keywords     = {{Plant Science, Health Professions (miscellaneous), Health (social science), Microbiology, Food Science}},
  number       = {{6}},
  publisher    = {{MDPI }},
  title        = {{{Enhancing Shelf Life Prediction of Fresh Pizza with Regression Models and Low Cost Sensors}}},
  doi          = {{10.3390/foods12061347}},
  volume       = {{12}},
  year         = {{2023}},
}

@misc{12946,
  abstract     = {{Ostrich meat is characterized by high nutritional value; however, it remains an exotic product in most countries worldwide. In Europe, only few data are available regarding its microbial contamination, prevalence of antimicrobial-resistant bacteria, and safety. Therefore, this study aimed to investigate the microbiological quality and safety of ostrich meat samples (n = 55), each from one animal, produced in Bavaria, Germany. The provided microbiological status of ostrich meat included mesophilic aerobic bacteria, Enterobacteria, and mesophilic yeast and molds. In terms of food safety, all meat samples were negative for Salmonella spp. and Trichinella spp. Additionally, meat samples and a further 30 stool samples from 30 individuals were investigated for Shiga toxin-producing Escherichia coli genes, with two meat samples that were qPCR-positive. Antimicrobial-resistant Enterobacteriaceae, Enterococcus faecalis, and Enterococcus faecium strains were from meat and stool samples also analyzed; 13 potentially resistant Enterobacteriaceae (meat samples) and 4 Enterococcus faecium (stool samples) were isolated, and their susceptibility against 29 and 14 antimicrobials, respectively, was characterized. The results of this study provide an overview of microbial loads and food safety aspects that may be used as baseline data for the ostrich meat industry to improve their hygienic quality. However, the implementation of monitoring programs is recommended, and microbiological standards for ostrich meat production should be established.}},
  author       = {{Beindorf, Philipp-Michael and Kovalenko, Oksana and Ulrich, Sebastian and Geißler, Hanna and Korbel, Rüdiger and Schwaiger, Karin and Dorn-In, Samart and Esteban-Cuesta, Irene}},
  booktitle    = {{Biology : open access journal}},
  issn         = {{2079-7737}},
  keywords     = {{antimicrobial resistance, meat microbiology, Salmonella, STEC, Trichinella}},
  number       = {{7}},
  publisher    = {{MDPI}},
  title        = {{{Investigation of Meat from Ostriches Raised and Slaughtered in Bavaria, Germany: Microbiological Quality and Antimicrobial Resistance}}},
  doi          = {{10.3390/biology11070985}},
  volume       = {{11}},
  year         = {{2022}},
}