Widespread consumption of fresh-cut vegetables without cooking results in ingestion of major foodborne pathogens including Bacillus cereus. In this study, we aimed to develop a method to rapidly detect B. cereus in fresh-cut vegetables by combining commercial PCR analysis with enrichment of the pathogenic levels. A mixture of B. cereus strains (KCTC1013, KCTC1014, KCTC1092, KCTC1094, and KCTC3624) was inoculated on the surface of fresh-cut cabbage lettuce (20 g) and baby leafy vegetables (10 g) to concentration 1, 2, 3, 4, and 5 log CFU/g. Eighty milliliters of TSB with 0.15% polymyxin B was used for cabbage lettuce, and 90 mL of medium was used for baby leafy vegetables and incubated at 42oC for 0, 2, 3, 4, 5, 6, and 7 h. One milliliter of the enriched media was plated on mannitol-egg yolk-polymyxin agar for quantification, and another 1 mL was used for DNA extraction for PCR analysis. Additionally, the minimum number of sub-samples to be tested from a pack of fresh-cut vegetable samples was determined using 5 sub-samples. The results from this study showed that for detecting B. cereus in fresh-cut cabbage lettuce, 3, 4, 5, 6, and 7 h enrichment were required to at least detect 5, 4, 3, 2, and 1 log CFU/g of B. cereus, respectively. B. cereus in fresh-cut baby leafy vegetables could be detected after 2, 3, 4, 5, and 6 h of enrichment at 5, 4, 3, 2, and 1 log CFU/g, respectively, using a combination of enrichment and PCR analysis. To determine if a pack of fresh-cut vegetable is positive, the minimum number of sub-samples should be 3. These results can be used to develop a rapid detection method to semi-quantify B. cereus in fresh-cut vegetable samples combining enrichment and PCR.

본 연구에서는 신선편이 양배추 내 Bacillus cereus의 최 적 증균 온도를 선정하고 증균배양액에 소수성필터를 적용하여 multiplex PCR의 검출률을 확인하였다. B. cereus 증균온도는 B. cereus 균주 5 개를 혼합하여 1 Log CFU/ mL이 되도록 증균배지에 접종하고 30oC, 37oC, 42oC에서 증균한 뒤 3시간 간격으로 MYP agar에 도말한 후 계수하여 선정하였다. 소수성필터 미적용 그룹은 B. cereus 균 주 5 개를 혼합하여 신선편이 양배추에 접종한 뒤 최적 증균온도에서 증균하였으며, 증균배양액을 가열하여 DNA 를 추출한 뒤 multiplex PCR을 진행하였다. 소수성필터 적용 그룹은 증균배양액을 소수성 필터에 적용하고 필터에 있는 균을 멸균증류수로 현탁한 뒤 가열하여 추출된 DNA 로 multiplex PCR을 진행하였다. 증균온도 확인 결과, 6시간 증균 시 42oC에서 증균된 샘플(5.4 ± 0.3 Log CFU/mL) 과 30oC에서 증균된 샘플(4.6 ± 0.6 Log CFU/mL) 간 유의 차가 확인되었다(p < 0.05). 소수성필터 적용 유무에 따른 multiplex PCR 결과, 1 Log CFU/g 접종된 샘플의 검출률이 소수성 필터 적용 전 60%(3/5)에서 100%(5/5)로 향상 되었다. 2 Log CFU/g 접종 샘플은 소수성필터 적용 전 80%(4/5)에서 소수성 필터 적용 후 100%(5/5)로 검출률이 증가하였으나, 3 Log CFU/g 접종 샘플은 소수성 필터 적용 전후 모두 100%(5/5)로 확인되었다. 이상의 결과를 통해 신선편이 양배추 내 B. cereus 검출 시 증균배양액에 소수성필터를 적용하고 multiplex PCR을 적용했을 때 신속하고 효율적인 검출이 가능할 것으로 판단된다.

본 연구에서는 도축장에서 분리된 Listeria monocytogenes를 저해할 수 있는 식물성 항균 물질을 탐색하고, 각 항균 물질의 최소살균농도(MBC)를 확인하였다. 잠재적인 항균 물질로 자몽종자 추출물, 감귤류 추출물, 생강 추출물, 배 추출물, 매실 농축액, 도라지 추출물, 대추 추출물, 오미자 추출물을 선정하였고, 대상 균주로는 국내 도축장에서 분리한 15 개의 L. monocytogenes 균주를 혼합하여 사용하였다. MBC 확인 결과, 최대 4.0 μg/mL 농도의 생강 추출물, 배 추출물, 매실 농축액, 도라지 추출물, 대추 추 출물, 오미자 추출물은 고농도의 L. monocytogenes (7 Log CFU/mL)에 대해 균 저해 효과가 전혀 나타나지 않았다. 반면, 7 Log CFU/mL의 L. monocytogenes에 대한 자몽종자 추출물과 감귤류 추출물의 MBC는 0.002 μg/mL인 것으로 확인되었다. 3 Log CFU/mL의 L. monocytogenes에 대한 MBC를 시험해 본 결과, 자몽종자 추출물과 감귤류 추출물의 MBC는 0.001 μg/mL로 나타났다. 이상의 결과로 볼 때 자몽종자 추출물과 감귤류 추출물은 L. monocytogenes를 제어하기 위해 적용될 수 있을 것으로 판단된다.

To solve the problem of raw milk surplus, the Korean government encouraged the farmstead milk processing industry. However, the hygiene of farmstead dairy products has not been evaluated. Therefore, the microbiological analysis of farmstead cheeses was performed in this study. Farmstead cheeses (Berg, Colby, Cottage, Gouda, Mozzarella, String, Tilsiter, and Quark) were purchased from 16 dairy farms. In qualitative analysis, the presence of foodborne pathogens (Bacillus cereus, Escherichia coli, Clostridium perfringens, Salmonella, Staphylococcus aureus, Listeria monocytogenes, and Campylobacter spp.) were examined. Also, total aerobic bacteria, Pseudomonas spp., coliform, and E. coli, and yeast/mold were enumerated. Seventeen samples (37.8%) of 45 farmstead cheeses were contaminated with B. cereus and the highest detection rate was observed in String cheese. Two samples (4.4%) were E. coli positive and seven samples (15.6%) were S. aureus positive. Four other foodborne pathogens were not detected in all farmstead cheeses. Also, the mean levels of total aerobic bacteria, coliform, E. coli, and yeast/mold were 4.3 Log CFU/g, 1.4 Log CFU/g, 1.1 Log CFU/g, and 3.8 Log CFU/g, respectively. These results indicate that the food safety of farmstead cheese is extremely poor and, thus, the hygiene management of farmstead cheese should be improved to provide safe farmstead cheese to consumers.

The objective of this study was to develop software to predict the kinetic behavior and the probability of foodborne bacterial growth on processed meat products. It is designed for rapid application by non-specialists in predictive microbiology. The software, named Foodborne bacteria Animal product Modeling Equipment (FAME), was developed using Javascript and HTML. FAME consists of a kinetic model and a probabilistic model, and it can be used to predict bacterial growth pattern and probability. In addition, validation and editing of model equation are available in FAME. The data used by the software were constructed with 5,400 frankfurter samples for the kinetic model and 345,600 samples for the probabilistic model using a variety of combinations including atmospheric conditions, temperature, NaCl concentrations and NaNO2 concentrations. Using FAME, users can select the concentrations of NaCl and NaNO2 meat products as well as storage conditions (atmosphere and temperature). The software displays bacterial growth patterns and growth probabilities, which facilitate the determination of optimal safety conditions for meat products. FAME is useful in predicting bacterial kinetic behavior and growth probability, especially for quick application, and is designed for use by non-specialists in predictive microbiology.

This study investigated the physical properties of polymers and antimicrobial activities of organic acids on Listeria monocytogenes to develop hydrogels. κ-carrageenan (1, 2, and 3%), carboxymethylcellulose (CMC; 1, 3, and 5%), and agar (1.5 and 3%) were mixed with cross-linkers (Na+, K+, Ca2+, and Al3+) or each other by stirring or heating to form cross-linkage, and their physical properties (hardness, elasticity, and swelling) were measured. The hydrogels formulated with organic acid (1, 3, and 5%) were analyzed by spot assay against L. monocytogenes. κ-carrageenan formed hydrogels with high hardness without other cross-linkers, but they had low elasticity. The elasticity was improved by mixing with other cross-linkers such as K+ or other polymer, especially in 3% κ-carrageenan. CMC hydrogel was formed by adding cross-linkers Al3+, Na+, or Ca2+, especially in 5% CMC. Thus, stickiness and swelling for selected hydrogel formulations (two of κ-carrageenan hydrogels and three of CMC hydrogels) were measured. Among the selected hydrogels, most of them showed appropriate hardness, but only 3% κ-carrageenan-contained hydrogels maintained their shapes from swelling. Hence, 3% κ-carrageenan+0.2% KCl and 3% κ-carrageenan+1% alginate+0.2% KCl+0.2% CaCl2 were selected to be formulated with lactic acid, and showed antilisterial activity. These results indicate that 3% κ-carrageenan hydrogels formulated with lactic acid can be used to control L. monocytogenes on food surface.

본 연구에서는 선택배지와 건조필름을 이용하여 신선편이 엽채류 3종(양상추, 양배추, 어린잎채소)에서 병원성 E. coli를 분리하였고, 의심집락 동정을 위해 생화학적 분석법을 사용하여 동정한 후 결과를 비교 분석하였다. 양상추 20 g, 양배추 20 g, 어린잎채소 10 g에 병원성 E. coli 혼합 균액(Enterohemorrhagic E. coli NCCP11142, Enterotoxigenic E. coli NCCP14037, Enteropathogenic E. coli NCCP14038, Enteroaggregative E. coli NCCP14039, Enteropathogenic E. coli NCCP15661)을 최종농도가 1, 2, 3 log CFU/g이 되도록 접종하였고, BPW (80~90 ml)을 넣은 후60초 동안 균질화하여 분석하였다. 연구결과, 모든 시료에서 건조필름 시험 양성, 양상추 시료 일부(최종농도 3 log CFU/g 접종시료)를 제외한 모든 시료에서 증균배양법을 이용한 정성시험결과가 음성으로 나타났다. 증균배양과 건조필름 시험을 통해 분리한 병원성 E. coli를 이용하여 생화학적 분석을 실시한 결과, 양상추에서 분리한 병원성 E. coli의 경우, API 20E 100% (44/44), Microgen GNA 100% (44/44), Food System 66.7% (10/15)의 동정률이 나타났다. 양배추의 경우, API 20E 64.7% (22/34), Microgen GNA 50% (16/32), Food System 60% (9/15), 어린잎채소의 경우, API 20E 65.1% (28/43), Microgen GNA 62.3% (27/43), Food System 53.3% (8/15)가 병원성 E. coli로 동정되었다. 본 연구의 결과는 신선편이 엽채류에 대한 병원성 E. coli 검출법 선택에 유용하게 이용될 것으로 판단된다.

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship between features, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.