Artificial intelligence is an emerging technology which harbors a suite of mechanisms that have the potential to be leveraged for reaping value across multiple domains. Lately, there is an increased interest in embracing applications associated with Artificial Intelligence to positively contribute to food safety. These applications such as machine learning, computer vision, predictive analytics algorithms, sensor networks, robotic inspection systems, and supply chain optimization tools have been established to contribute to several domains of food safety such as early warning of outbreaks, risk prediction, detection and identification of food associated pathogens. Simultaneously, the ambition toward establishing a sustainable food system has motivated the adoption of cutting-edge technologies such as Artificial Intelligence to strengthen food security. Given the myriad challenges confronting stakeholders in their endeavors to safeguard food security, Artificial Intelligence emerges as a promising tool capable of crafting holistic management strategies for food security. This entails maximizing crop yields, mitigating losses, and trimming operational expenses. AI models present notable benefits in efficiency, precision, uniformity, automation, pattern identification, accessibility, and scalability for food security endeavors. The escalation in the global trend for adopting alternative protein sources such as edible insects and microalgae as a sustainable food source reflects a growing recognition of the need for sustainable and resilient food systems to address the challenges of population growth, environmental degradation, and food insecurity. Artificial Intelligence offers a range of capabilities to enhance food safety in the production and consumption of alternative proteins like microalgae and edible insects, contributing to a sustainable and secure food system.

Objectives: Worldwide, but especially in emerging nations, concerns about food safety pose a serious obstacle to societal and economic progress. This research aimed to examine the prevalence of Listeria spp. in raw milk and dairy products in Burdur, as well as the presence of genes associated with biofilm formation and antibiotic resistance in the isolates. Methods: A total of 185 samples, including raw milk, curd, cream, butter, yogurt and cheese, were randomly collected in Burdur. The enrichment and isolation methods specified by the United States Department of Agriculture was used to identify Listeria species in milk and dairy product samples. Culture‐positive strains were identified as Listeria genus and as species by PCR. Antibiotic susceptibility of the isolates was evaluated against 14 antibiotics using the disc diffusion technique (EUCAST). Results: Of them, 2.2% (4/185) were positive for Listeria spp. Listeria species were isolated from cheese and yogurt samples. Two of them were Listeria innocua 1.1% (2/185), one was Listeria ivanovii 0.5% (1/185) and the other was Listeria welshimeri 0.5% (1/185). As a result of multiplex PCR of the biofilm genotypic marker luxS and flaA genes, the flaA gene was detected in three of four isolates, the luxS gene was detected in one isolate, and these two genes were not found in one isolate. Although all isolates were resistant to gentamicin and rifampicin, they also showed multidrug resistance. Conclusion: This study revealed that the diversity of prevalence of Listeria spp. in Burdur requires microbial risk assessment in the milk and dairy products value chain and the need to focus on the problem of multiple antibiotic resistance.

Listeria monocytogenes is a ubiquitous microorganism that is isolated from a variety of sources such as soil, water, decaying vegetation, sewage, animal feeds, silage, farm environments and food -processing environments. This study aimed to determine the prevalence, serogroups, biofilm formation, virulence factor genes, and genetic relationships of L. monocytogenes strains isolated from beef meat and meat contact surfaces obtained from a slaughterhouse in Burdur, Turkey. In this study, a total of 179 beef meat and meat contact surface samples were analyzed for the presence of L. monocytogenes by polymerase chain reaction (PCR). Out of a total of 179 beef meat and meat contact surface samples, 83 (46.37%) were found to be contaminated with L. monocytogenes, with the highest incidence (53.01%) occurring in beef meat. In the present study, most of the isolated strains belonged to serogroups IIB and IVB (lineage I). The L. monocytogenes strain also contained monoA-B, prfA, plcA, plcB, mpl, hlyA, actA, gtcA, dltA, Fri, flaA, InlA, InlC, InlJ, and iap genes. Biofilm formation was not determined in the tested samples at pH 5.5 and different temperatures (4 degrees C, 10 degrees C, 25 degrees C, and 37 degrees C). However, strong biofilm formation was observed in 6.45% (2/31) of the strains at pH 7.0 after 48 h incubation at 37 degrees C, and in 3.22% (1/31) of the strains at pH 7.0 after 48 h incubation at 4 degrees C and 10 degrees C. Pulsed -field gel electrophoresis (PFGE) results showed that L. monocytogenes isolates were clonally related, and cross -contamination was present. In addition, PFGE results also revealed that AscI had more distinguishing power than the ApaI restriction enzyme. These results indicate that L. monocytogenes detected from meat and meat contact surfaces in the slaughterhouse pose a potential risk to public health.

Bu çalışma, gıdalarda aflatoksin bulunmasından kaynaklanan ekonomik kayıplar ve halk sağlığı endişeleri nedeniyle aflatoksin M1 (AFM1) düzeyini belirlemek amacıyla yapılmıştır. Burdur ilindeki çiftliklerden toplam 82 çiğ inek sütü örneği rastgele alındı ve Enzyme-Linked Immunosorbent Assay (ELISA) yöntemi kullanılarak AFM1 açısından analiz edildi. İncelenen 82 çiğ inek sütü örneğinin 48'inde (%58,5) AFM1 seviyesinin 5,06 ila 50,63 ng kg-1 arasında ve ortalama kontaminasyon oranının 15,53 ±1,49 ng kg-1 olduğu tespit edildi. Süt örneklerinin 1'inde (%1,2) AFM1 düzeyi Türk Gıda Kodeksi ve AB Yönetmeliği'nde belirtilen yasal sınırların üzerinde olduğu belirlendi. Sonuç olarak çiğ süt örneklerinde belirlenen AFM1 seviyesi maksimum kalıntı limitlerinin altında ve insan tüketimine uygun bulunmuştur. Ayrıca Türkiye'deki yetişkin tüketici için AFM1'in tahmini günlük alım miktarı (EDI) belirlenmiştir. Yetişkin tüketicinin ortalama EDI'si (0,19 ng kg-1 vücut ağırlığı gün-1), önerilen günlük 0,2 ng kg-1 vücut ağırlığı gün-1 AFM1 alımına yakın bulunmuştur. Ancak bu konudaki çalışmaların düzenli bir program dahilinde tekrarlanması ve hem üreticilerin hem de tüketicilerin konu hakkında bilgilendirilmesi önerilmektedir.