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Kazaal MA, Hamad WA, Atiya WH, Saeed BJ, Abd-Alsatar AN. Impact of antibiotic resistance on sustainable development goals. 1ST INTERNATIONAL CONFERENCE ON ACHIEVING THE SUSTAINABLE DEVELOPMENT GOALS 2023. [DOI: 10.1063/5.0137246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
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Gao R, Chen C, Wang H, Chen C, Yan Z, Han H, Chen F, Wu Y, Wang Z, Zhou Y, Si R, Lv X. Classification of multicategory edible fungi based on the infrared spectra of caps and stalks. PLoS One 2020; 15:e0238149. [PMID: 32833991 PMCID: PMC7444812 DOI: 10.1371/journal.pone.0238149] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 08/10/2020] [Indexed: 11/18/2022] Open
Abstract
As a characteristic edible fungus with a high nutritional value and medicinal effect, the Bachu mushroom has a broad market. To distinguish among Bachu mushrooms with high value and other fungi effectively and accurately, as well as to explore a universal identification method, this study proposed a method to identify Bachu mushrooms by Fourier Transform Infrared Spectroscopy (FT-IR) combined with machine learning. In this experiment, two kinds of common edible mushrooms, Lentinus edodes and club fungi, were selected and classified with Bachu mushrooms. Due to the different distribution of nutrients in the caps and stalks, the caps and stalks were studied in this experiment. By comparing the average normalized infrared spectra of the caps and stalks of the three types of fungi, we found differences in their infrared spectra, indicating that the latter can be used to classify and identify the three types of fungi. We also used machine learning to process the spectral data. The overall steps of data processing are as follows: use partial least squares (PLS) to extract spectral features, select the appropriate characteristic number, use different classification algorithms for classification, and finally determine the best algorithm according to the classification results. Among them, the basis of selecting the characteristic number was the cumulative variance interpretation rate. To improve the reliability of the experimental results, this study also used the classification results to verify the feasibility. The classification algorithms used in this study were the support vector machine (SVM), backpropagation neural network (BPNN) and k-nearest neighbors (KNN) algorithm. The results showed that the three algorithms achieved good results in the multivariate classification of the caps and stalks data. Moreover, the cumulative variance explanation rate could be used to select the characteristic number. Finally, by comparing the classification results of the three algorithms, the classification effect of KNN was found to be the best. Additionally, the classification results were as follows: according to the caps data classification, the accuracy was 99.06%; according to the stalks data classification, the accuracy was 99.82%. This study showed that infrared spectroscopy combined with a machine learning algorithm has the potential to be applied to identify Bachu mushrooms and the cumulative variance explanation rate can be used to select the characteristic number. This method can also be used to identify other types of edible fungi and has a broad application prospect.
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Affiliation(s)
- Rui Gao
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Cheng Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
- * E-mail: (CC); (XL)
| | - Hang Wang
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Chen Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Ziwei Yan
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Huijie Han
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China
| | - Fangfang Chen
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Yan Wu
- Quality of Products Supervision and Inspection Institute, Urumqi, Xinjiang, China
| | - Zhiao Wang
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Yuxiu Zhou
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Rumeng Si
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
| | - Xiaoyi Lv
- College of Information Science and Engineering, Xinjiang University, Urumqi, China
- * E-mail: (CC); (XL)
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Makinde OM, Ayeni KI, Sulyok M, Krska R, Adeleke RA, Ezekiel CN. Microbiological safety of ready‐to‐eat foods in low‐ and middle‐income countries: A comprehensive 10‐year (2009 to 2018) review. Compr Rev Food Sci Food Saf 2020; 19:703-732. [DOI: 10.1111/1541-4337.12533] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 12/01/2019] [Accepted: 01/07/2020] [Indexed: 12/11/2022]
Affiliation(s)
| | | | - Michael Sulyok
- Department of Agrobiotechnology (IFA–Tulln)Institute of Bioanalytics and Agro‐Metabolomics, University of Natural Resources and Life Sciences Vienna (BOKU) Tulln Austria
| | - Rudolf Krska
- Department of Agrobiotechnology (IFA–Tulln)Institute of Bioanalytics and Agro‐Metabolomics, University of Natural Resources and Life Sciences Vienna (BOKU) Tulln Austria
- Institute for Global Food Security, School of Biological SciencesQueen's University Belfast Belfast United Kingdom
| | - Rasheed A. Adeleke
- Department of MicrobiologyNorth‐West University Potchefstroom South Africa
| | - Chibundu N. Ezekiel
- Department of MicrobiologyBabcock University Ilishan Remo Nigeria
- Department of Agrobiotechnology (IFA–Tulln)Institute of Bioanalytics and Agro‐Metabolomics, University of Natural Resources and Life Sciences Vienna (BOKU) Tulln Austria
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Amare A, Worku T, Ashagirie B, Adugna M, Getaneh A, Dagnew M. Bacteriological profile, antimicrobial susceptibility patterns of the isolates among street vended foods and hygienic practice of vendors in Gondar town, Northwest Ethiopia: a cross sectional study. BMC Microbiol 2019; 19:120. [PMID: 31174476 PMCID: PMC6556002 DOI: 10.1186/s12866-019-1509-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 06/02/2019] [Indexed: 11/25/2022] Open
Abstract
Background There are numerous advantages offered by street vended foods, but evidence exists that foods exposed for sale on the road side may be contaminated by pathogenic microorganisms. However, information on the bacteriological profile, bacterial load and antimicrobial susceptibility patterns of bacterial isolates from street food in Gondar town are lacking. The aim of this study was to assess bacterial profile, bacterial load, and antimicrobial susceptibility patterns of bacterial isolates among street vended foods and also the hygienic practice of vendors in Gondar town, Northwest Ethiopia. Methods Socio-demographic characteristics and the hygienic practices of 24 vendors were collected using structured questionnaire. A total of 72 food samples from four different food items were analyzed and counted by standard aerobic plate count method. Ten grams of each food sample was transferred in to 90 ml of buffered peptone water and homogenized. The homogenates were serially dilute and a volume of 0.1 ml dilution was spread on solid media and incubated at 35-37 °C for 24 h. Antibiotic susceptibility testing was done for isolated species using Muller Hinton agar and data was entered and analyzed by using SPSS version 20.0. Results Seventy two food samples of street vended food were analysed for bacterial pathogens. 44/72 tested positive, a total of 63 isolates were identified as 19 samples contained two pathogens. The total mean aerobic bacterial count was 6.64 × 104 CFU/g which is varied from 1 × 104–1.86 × 105 CFU/g. S. aureus is the most frequent isolate 34 (53.96%) followed by E.coli 15(23.8%), Enterobacter species 10(15.87%) and Citrobacter species 4(6.3%). Gentamycin, chloramphenicol, tetracycline, ciprofloxacin, and trimethoprim-sulfamethoxazole were found to be the most effective antimicrobials against all isolates but the enterobactereaceae were resistant to ampicillin and Ceftaziidime and S.aureus were resistant to penicillin. Conclusion The results of this study showed that, the majority of street-vended food items in Gondar were contaminated with one or more different pathogenic bacteria. The presence of these bacteria in foods could lead to potential health problems for consumers. Therefore, health education as well as training in food safety and hygienic handling is required for food handlers to minimize contamination and the likelihood of people falling ill.
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Affiliation(s)
- Azanaw Amare
- Department of Medical Microbiology, University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Gondar, Ethiopia
| | - Tifito Worku
- University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Comprehensive Specialized Hospital Laboratory, Gondar, Ethiopia
| | - Birukitait Ashagirie
- University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Comprehensive Specialized Hospital Laboratory, Gondar, Ethiopia
| | - Marie Adugna
- University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Comprehensive Specialized Hospital Laboratory, Gondar, Ethiopia
| | - Alem Getaneh
- Department of Medical Microbiology, University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Gondar, Ethiopia.
| | - Mulat Dagnew
- Department of Medical Microbiology, University of Gondar, College of Medicine and Health Sciences School of Biomedical and Laboratory Sciences, Gondar, Ethiopia
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Udomkun P, Ilukor J, Mockshell J, Mujawamariya G, Okafor C, Bullock R, Nabahungu NL, Vanlauwe B. What are the key factors influencing consumers' preference and willingness to pay for meat products in Eastern DRC? Food Sci Nutr 2018; 6:2321-2336. [PMID: 30510732 PMCID: PMC6261168 DOI: 10.1002/fsn3.813] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 08/28/2018] [Accepted: 08/30/2018] [Indexed: 01/06/2023] Open
Abstract
Dietary patterns for consumers among the elite and middle-income classes in developing countries are shifting rapidly toward the consumption of more animal-based products. Although this shift presents opportunities, there are significant market failures affecting their preferences and willingness to pay (WTP). This study used a multistage sample survey of 309 consumers from three different communities of Bukavu, Eastern DRC, to examine the effect of socioeconomic/socio-demographic characteristics and quality attributes on consumers' purchasing decisions and WTP for meat products. The results suggested that about 53% of the respondents were dissatisfied with meat products in the market due to their high price, low quantity, unhealthiness, and harmful effects. Older female respondents living in urban areas were more likely to purchase meat products. Their WTP was significantly determined by attributes such as color, in-mouth texture, and availability. Nutrition, harmful effects, and availability of meat products are the important factors that influence purchasing decisions among higher income groups. Addressing these market failures could have an impact on the meat market, improving the nutrition of low-income consumers and ensuring food safety standards in DRC and other developing countries with similar challenges.
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Affiliation(s)
| | - John Ilukor
- World BankDevelopment Data Group‐Survey UnitKampalaUganda
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Abrahale K, Sousa S, Albuquerque G, Padrão P, Lunet N. Street food research worldwide: a scoping review. J Hum Nutr Diet 2018; 32:152-174. [DOI: 10.1111/jhn.12604] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- K. Abrahale
- EPIUnit - Unidade de Investigação em Epidemiologia; Instituto de Saúde Pública; Universidade do Porto; Porto Portugal
| | - S. Sousa
- EPIUnit - Unidade de Investigação em Epidemiologia; Instituto de Saúde Pública; Universidade do Porto; Porto Portugal
- Faculdade de Ciências da Nutrição; Alimentação da Universidade do Porto; Porto Portugal
| | - G. Albuquerque
- EPIUnit - Unidade de Investigação em Epidemiologia; Instituto de Saúde Pública; Universidade do Porto; Porto Portugal
| | - P. Padrão
- EPIUnit - Unidade de Investigação em Epidemiologia; Instituto de Saúde Pública; Universidade do Porto; Porto Portugal
- Faculdade de Ciências da Nutrição; Alimentação da Universidade do Porto; Porto Portugal
| | - N. Lunet
- EPIUnit - Unidade de Investigação em Epidemiologia; Instituto de Saúde Pública; Universidade do Porto; Porto Portugal
- Departamento de Ciências da Saúde Pública e Forenses e Educação Médica; Faculdade de Medicina da Universidade do Porto; Porto Portugal
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Manyi-Loh C, Mamphweli S, Meyer E, Okoh A. Antibiotic Use in Agriculture and Its Consequential Resistance in Environmental Sources: Potential Public Health Implications. Molecules 2018; 23:E795. [PMID: 29601469 PMCID: PMC6017557 DOI: 10.3390/molecules23040795] [Citation(s) in RCA: 616] [Impact Index Per Article: 102.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 02/14/2018] [Accepted: 03/02/2018] [Indexed: 01/08/2023] Open
Abstract
Due to the increased demand of animal protein in developing countries, intensive farming is instigated, which results in antibiotic residues in animal-derived products, and eventually, antibiotic resistance. Antibiotic resistance is of great public health concern because the antibiotic-resistant bacteria associated with the animals may be pathogenic to humans, easily transmitted to humans via food chains, and widely disseminated in the environment via animal wastes. These may cause complicated, untreatable, and prolonged infections in humans, leading to higher healthcare cost and sometimes death. In the said countries, antibiotic resistance is so complex and difficult, due to irrational use of antibiotics both in the clinical and agriculture settings, low socioeconomic status, poor sanitation and hygienic status, as well as that zoonotic bacterial pathogens are not regularly cultured, and their resistance to commonly used antibiotics are scarcely investigated (poor surveillance systems). The challenges that follow are of local, national, regional, and international dimensions, as there are no geographic boundaries to impede the spread of antibiotic resistance. In addition, the information assembled in this study through a thorough review of published findings, emphasized the presence of antibiotics in animal-derived products and the phenomenon of multidrug resistance in environmental samples. This therefore calls for strengthening of regulations that direct antibiotic manufacture, distribution, dispensing, and prescription, hence fostering antibiotic stewardship. Joint collaboration across the world with international bodies is needed to assist the developing countries to implement good surveillance of antibiotic use and antibiotic resistance.
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Affiliation(s)
- Christy Manyi-Loh
- Fort Hare Institute of Technology, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
- Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
| | - Sampson Mamphweli
- Fort Hare Institute of Technology, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
| | - Edson Meyer
- Fort Hare Institute of Technology, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
| | - Anthony Okoh
- Applied and Environmental Microbiology Research Group (AEMREG), Department of Biochemistry and Microbiology, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
- SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice Campus, Alice 5700, Eastern Cape, South Africa.
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