Determination of capsaicin, dihydrocapsaicin and nonivamide in pungent liquids of self-defense spray were studied. The nonivamide having almost same spicy taste with capsaicin have been containing a few amounts in natural products, it had called as synthetic capsaicin or PAVA, have used to flavorings for foodstuffs and incapacitating agents of riot controls. Nowadays, it has been occasionally found that the quality controls of a self-defense sprays were not properly due to flood of illegal self-defense sprays. Thus, the simple analytical method with gas chromatography is developed, it is identified whether the products which have contained synthetic capsaicin were marked like natural materials as well as the pungent ingredients in it obeyed with permissible concentration to human or not was investigated. Finally, the pungent components and amounts in some kinds of self-defense spray were investigated.
Purpose: Various plants, herbal medicines, and marine foodstuffs have been used in kimchi preparation to improve its overall quality. Teff, which is rich in minerals and starches, facilitates stable blood glucose levels and is well-suited for use in gluten-free products; hence, it can be used to reinforce the mineral composition of kimchi. In this study, we probed the antioxidant activities of hydrolysates prepared by treatment of brown teff with three proteases under different conditions. Methods: The mineral composition of brown teff was determined by inductively coupled plasma spectrophotometry-mass spectrometry, and we established optimal hydrolysis conditions by determining the total phenol and flavonoid contents of teff hydrolysates obtained using three different proteases (protamax, flavourzyme, and alcalase), two different protease concentrations (1 and 3 wt%), and three different incubation times (1, 2, and 4 h). The antioxidant activity of the hydrolysates was further investigated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity, total antioxidant capacity (TAC), and ferrous reducing antioxidant power (FRAP) assays. Results: Brown teff was rich in I, K, Mg, and Ca, and the highest total phenol content ($24.16{\mu}g/mL$), total flavonoid content ($69.08{\mu}g/mL$), and TAC were obtained for 1 wt% protamax treatment. However, the highest DPPH scavenging activity and FRAP values were observed for hydrolysates produced by alcalase and flavourzyme treatments, respectively. Conclusion: Treatment of brown teff with proteases affords hydrolysates with significantly increased antioxidant activities and high total phenol and flavonoid contents, and these antioxidant activities of teff hydrolysates have the potential to enhance the quality and functionality of kimchi in future applications.
Objective: Aim of present study was the set up of a fast and reliable protocol using species-specific markers for the quali-quantitative analysis of DNA and the detection of ruminant biological components in dairy products. For this purpose, the promoter of the gene coding for the ${\alpha}$-lactoalbumin (LALBA) was chosen as possible candidate for the presence of short interspersed nuclear elements (SINEs). Methods: DNA was isolated from somatic cells of 120 individual milk samples of cattle (30), Mediterranean river buffalo (30), goat (30), and sheep (30) and the gene promoter region (about 600/700 bp) of LALBA (from about 600 bp upstream of exon 1) has been sequenced. For the development of a single polymerase chain reaction (PCR) protocol that allows the simultaneous identification of DNA from the four species of ruminants, the following internal primers pair were used: 5'-CACTGATCTTAAAGCTCAGGTT-3' (forward) and 5'-TCAGA GTAGGCCACAGAAG-3' (reverse). Results: Sequencing results of LALBA gene promoter region confirmed the presence of SINEs as monomorphic "within" and variable in size "among" the selected species. Amplicon lengths were 582 bp in cattle, 592 bp in buffalo, 655 in goat and 729 bp in sheep. PCR specificity was demonstrated by the detection of trace amounts of species-specific DNA from mixed sources ($0.25ng/{\mu}L$). Conclusion: We developed a rapid PCR protocol for the quali-quantitative analysis of DNA and the traceability of dairy products using a species-specific marker with only one pair of primers. Our results validate the proposed technique as a suitable tool for a simple and inexpensive (economic) detection of animal origin components in foodstuffs.
Shakespeare's plays deploy an interesting array of food signs in a way to illuminate the historical process of what Stephen Mennell has described as "the civilizing of appetite"-a process in which the changes of food choices and eating habits took place in response to the changes in people's way of life and personality structure over the long-term modern period since the middle ages. Shakespeare's plays suggest that the civilizing of appetite in early modern England was heavily affected by the forces of social mobility as well as the nascent market economy. The Capulets' costly preparation of Juliet's wedding banquet is a showcase of conspicuous consumption which was a structural necessity for the ruling class in Shakespeare's time. Some fifteen years later, the same kinds of foodstuffs are included in a shepherd's shopping list for the sheepshearing festival in Winter's Tale. This is a significant coincidence to prove that food was an important source of emulation and contest among different social classes; and that the rich diet of the upper class gave impetus to social mobility. The Elizabethan subjects, especially among the elite noblemen, were interpellated by the ideology of food that equated the quality of food and the eater's social identity. Faced with bankruptcy as a consequence of his extravagant consumption habit, Bassanio in The Merchant of Venice testifies to the gripping ideology of food onto early modern people, while Poor Tom in King Lear presents a comic parody of the rich people's conspicuous waste. Also in Coriolanus and The Merry Wives of Winsor, Shakespeare uses food as a metaphor for class-motivated social struggles.
Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.
Muhammad Umer Farooq;Mustafa Latif;Waseemullah;Mirza Adnan Baig;Muhammad Ali Akhtar;Nuzhat Sana
International Journal of Computer Science & Network Security
/
v.23
no.9
/
pp.1-7
/
2023
Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.
Muhammad Umer Farooq;Mustafa Latif;Waseem;Mirza Adnan Baig;Muhammad Ali Akhtar;Nuzhat Sana
International Journal of Computer Science & Network Security
/
v.23
no.8
/
pp.210-216
/
2023
Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.
The objective of this study was to compare the healthy dining out attitude of restaurant diners by self-rated health status. Using healthy dining attitude and behavior questionnaire and a single question describing self-rated health status, the needs and importance of healthy dining out was detected. Mean age of the 182 respondents was 38.9${\pm}$11.37 years old and 37.4% of the respondents answered their mean monthly income was over 6,000,000won showing the subjects belonged in high income diners. The needs of healthy dining measured by five scales and offering healthy menus(3.80), labeling foods about original country(3.79), using environmentally friendly foodstuffs(3.71) and labeling nutrients on menu board(3.62) show higher score than others. A total of 76.4% of the respondents assessed their health status as 'good-rated Health' and 23.6% was 'poor-rated health'. There was no difference in frequency of eating out by self-perception of health status but, the 'poor-rated health' group need more nutrition information in restaurant specially for calorie(p<0.05), cholesterol(p<0.05), fiber(p<0.05), functional nutrients(p<0.001) showing significant differences comparing to 'good-rated health' group. In good-rated health group, selection of Korean cuisine for eating out was more frequent than the poor. The results shows the needs of healthy dining can be varied by diner's health status and therefore restaurateur should focus on understanding of the needs of diners with various health status.
Journal of the Korean Society of Food Science and Nutrition
/
v.34
no.1
/
pp.66-74
/
2005
This survey was conducted to assess the consumer perceptions of food-related hazard in 500 housewives from all over Korea. The subjects were selected by stratified random sampling method. The survey was performed using structured questionnaire through telephone interview by skilled interviewers. The results showed that 34.6% of the respondents felt secure and were not concerned about food safety, and 65.4% were concerned about food safety. Logistic regression analysis showed that the increasing concern on food brands, food additives (such as food preservatives and artificial color), and imported foodstuffs indicated the current increasing concern on food safety. Other related factors indicating the increasing concern on food safety were education level and care for children's health. The respondents who cared about food safety expressed a high degree of concern on processed foodstuffs such as commercial boxed lunch (93.3%), imported foods (92.7%), fastfoods (89.9%), processed meat products (88.7%), dining out (85.6%), cannery and frozen foods (83.5%), and instant foods (82.0%). The lowest degree of concern was on rice. All the respondents perceived that residues of chemical substances such as pesticides and food additives, and endocrine disrupters were the most potential food risk factors, followed by food-borne pathogens, and GMOs (Genetically Modified Organisms). However, these results were not consistent with scientific judgment. Therefore, more education and information were needed for consumers' awareness of facts and myths about food safety. In addition, the results showed that consumers put lower trust in food products information such as food labels, cultivation methods (organic or not), quality labels, and the place of origin. Nevertheless, the respondents expressed their desire to overcome alienation, and recognized the importance of knowing of the origin or the producers of food. They identified that people who need to take extreme precautions on food contamination were the producers, government officials, food companies, consumers, the consumer's association, and marketers, arranged in the order of highest to lowest. They also believed that the production stage of agriculture was the most important step for improving the level of food safety Therefore, the results indicated that there is a need to introduce safety systems in the production of agricultural products, as follows: Good Agricultural Practice (GAP), Hazard Analysis and Critical Control Point (HACCP), and Traceability System (75).
The yellow fungal isolates inhabiting at the cereals (Hwang-Kuk, HK-fungi) were widely collected from the mejus and nuluks in Korea; the meju is a raw material for Korean traditional foods for soysauce and soypaste, and the nuluk is a raw material for Korean traditional rice wine. These isolates, well known as an Aspergillus oryzae producing amylase for Korean rice wine or producing protease for soybeans, were compared with Aspergillus species known. All isolates were microscopically observed to be a species of A. oryzae or its related, but to be difficult to be identified. Thus, RAPD-DNA techniques were applied for these isolates and analyzed with nummerical values using NT-system, or Ecological programs or Factorial analyses. Several common bands of RAPD-DNA in the 28 isolates were synthesized with the different OPD primers and speculated to be used for identification of HK fungi. The HK-fungi isolated were revealed to belong to the group of A. flavus previously defined. Particularly, the isolates collected from mejus were analyzed to be more closed to A. flavus, The species of A. flavus, A. oryzae and A. sojae were grouped at the values lower than those indicating the diversity of species. In other words, these three fungal species were not distinguishable and all isolates known as a HK-fungus were very closed to A. flavus, All isolates were not diversified at groupings of RAPD-DNA, and considered to be not the natural flora at the mejus or nuluks. The meju or nuluk having the above fungi as the fungal flora were speculated to be not termed "Korean traditional foodstuffs".The yellow fungal isolates inhabiting at the cereals (Hwang-Kuk, HK-fungi) were widely collected from the mejus and nuluks in Korea; the meju is a raw material for Korean traditional foods for soysauce and soypaste, and the nuluk is a raw material for Korean traditional rice wine. These isolates, well known as an Aspergillus oryzae producing amylase for Korean rice wine or producing protease for soybeans, were compared with Aspergillus species known. All isolates were microscopically observed to be a species of A. oryzae or its related, but to be difficult to be identified. Thus, RAPD-DNA techniques were applied for these isolates and analyzed with nummerical values using NT-system, or Ecological programs or Factorial analyses. Several common bands of RAPD-DNA in the 28 isolates were synthesized with the different OPD primers and speculated to be used for identification of HK fungi. The HK-fungi isolated were revealed to belong to the group of A. flavus previously defined. Particularly, the isolates collected from mejus were analyzed to be more closed to A. flavus, The species of A. flavus, A. oryzae and A. sojae were grouped at the values lower than those indicating the diversity of species. In other words, these three fungal species were not distinguishable and all isolates known as a HK-fungus were very closed to A. flavus. All isolates were not diversified at groupings of RAPD-DNA, and considered to be not the natural flora at the mejus or nuluks. The meju or nuluk having the above fungi as the fungal flora were speculated to be not termed 'Korean traditional foodstuffs'.
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