Pub Date : 2020-02-17DOI: 10.15587/1729-4061.2020.193515
Y. Biletska, R. Plotnikova, O.Ye. Skyrda, M. Bakirov, S. Iurchenko, Bella Botshtein
The paper reports results from developing a technology of chickpea flour enriched with selenium. The devised technology would allow the intake of the organic forms of the microelement whose deficiency is suffered by 17 % of the global population. The study has found that the degree of selenium accumulation is affected by the protein content in the native grain. It is rational to use solutions for germination, which are the carriers of 75 μg of selenium. 95...99 % of selenium in sprouted grains are accumulated in the cotyledon, in the protein fraction. During the germination of grains, the amino acid composition increases considerably. The content of leucine, lysine, arginine, and tryptophan increases by 87, 76, 80 %, and 55 %, respectively. The base of the substituted amino acids are aspartic and glutamic acids and their amides, whose share in the non-sprouted grains of chickpea accounts for 67 %, and in the sprouted grains – 70 %. The devised technological protocol of chickpea flour production differs from the control one by that the washing and disinfection of chickpea grains are performed in an aqueous solution of citric acid (pH 3.5...4.0). Afterward, the grains germinate in a solution of NaHSeO 3 for 48 hours. As regards the organoleptic indicators, the proposed flour has a light-yellow color, a smell that is peculiar to chickpea flour, its taste has no bitterness and sour flavors. In terms of its physical-chemical indicators, the differences from control are observed in the mass share of moisture, by 1 % less than that of the control sample, and the mass fraction of fat, which decreases by 2 %. There is a 0.5 % increase in the mass fraction of total ash and the mass fraction of fiber. Regarding the content of mercury, arsenic, lead, the proposed chickpea flour's levels are not higher than those permissible for human consumption; it does not contain cadmium, and its content of copper is less than the permissible level by 1 mg/g. As regards the number of mesophilic aerobic and facultative anaerobic microorganisms, mold fungi, and yeast, the developed chickpea flour is safe for use. It includes neither bacteria from the group of Escherichia coli nor pathogens of bacteria from the genus Salmonella. Our study has allowed us to argue that the developed chickpea flour is a carrier of 52 μg of selenium in the bioavailable organic form that provides 65 % of daily requirement in selenium for an adult healthy person
{"title":"Devising a Technology for Making Flour From Chickpea Enriched With Selenium","authors":"Y. Biletska, R. Plotnikova, O.Ye. Skyrda, M. Bakirov, S. Iurchenko, Bella Botshtein","doi":"10.15587/1729-4061.2020.193515","DOIUrl":"https://doi.org/10.15587/1729-4061.2020.193515","url":null,"abstract":"The paper reports results from developing a technology of chickpea flour enriched with selenium. The devised technology would allow the intake of the organic forms of the microelement whose deficiency is suffered by 17 % of the global population. The study has found that the degree of selenium accumulation is affected by the protein content in the native grain. It is rational to use solutions for germination, which are the carriers of 75 μg of selenium. 95...99 % of selenium in sprouted grains are accumulated in the cotyledon, in the protein fraction. During the germination of grains, the amino acid composition increases considerably. The content of leucine, lysine, arginine, and tryptophan increases by 87, 76, 80 %, and 55 %, respectively. The base of the substituted amino acids are aspartic and glutamic acids and their amides, whose share in the non-sprouted grains of chickpea accounts for 67 %, and in the sprouted grains – 70 %. The devised technological protocol of chickpea flour production differs from the control one by that the washing and disinfection of chickpea grains are performed in an aqueous solution of citric acid (pH 3.5...4.0). Afterward, the grains germinate in a solution of NaHSeO 3 for 48 hours. As regards the organoleptic indicators, the proposed flour has a light-yellow color, a smell that is peculiar to chickpea flour, its taste has no bitterness and sour flavors. In terms of its physical-chemical indicators, the differences from control are observed in the mass share of moisture, by 1 % less than that of the control sample, and the mass fraction of fat, which decreases by 2 %. There is a 0.5 % increase in the mass fraction of total ash and the mass fraction of fiber. Regarding the content of mercury, arsenic, lead, the proposed chickpea flour's levels are not higher than those permissible for human consumption; it does not contain cadmium, and its content of copper is less than the permissible level by 1 mg/g. As regards the number of mesophilic aerobic and facultative anaerobic microorganisms, mold fungi, and yeast, the developed chickpea flour is safe for use. It includes neither bacteria from the group of Escherichia coli nor pathogens of bacteria from the genus Salmonella. Our study has allowed us to argue that the developed chickpea flour is a carrier of 52 μg of selenium in the bioavailable organic form that provides 65 % of daily requirement in selenium for an adult healthy person","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125915217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-31DOI: 10.21303/2504-5571.2020.001136
Y. Biletska, A. Perepelytsia, Olha Bilovska
Marketing research of consumer preferences of consumers when purchasing various groups of food products are conducted, the factors affecting respondents when purchasing food products are studied. It is established that the consumer in its daily diet takes 10.5 % of bakery products; 7.1 % cereals and soups based on cereals and legumes. 9.5 % of respondents consume confectionery for breakfast and during snacks, and 6.2 % consume sweets. Meat is consumed daily by 5.8 % of respondents. Products based on meat –10.7 %. 8.1 % of respondents consume fish daily and fish-based products 3.1 %. 5.9 % consume milk every day, and milk-based products – 10.2 % of respondents. 12.8 and 10.1 % of the daily diet of respondents are vegetables and fruits (respectively). It is established that the recommended consumption norms are exceeded for such food groups as sweets, meat-based products, and confectionery. Diet within the norm for the consumption of bakery products, milk, fish and fish-based products. Inadequate consumption of cereals, legumes, meat, fruits. Based on the results, it is determined that the consumer prefers food products that have a pleasant (familiar) taste, without harmful, unnatural substances, high nutritional value at a low price. The studies are useful for specialists in food industry who work and develop new foods and diets.
{"title":"Determination of Consumer Preferences of Different Groups of Food","authors":"Y. Biletska, A. Perepelytsia, Olha Bilovska","doi":"10.21303/2504-5571.2020.001136","DOIUrl":"https://doi.org/10.21303/2504-5571.2020.001136","url":null,"abstract":"Marketing research of consumer preferences of consumers when purchasing various groups of food products are conducted, the factors affecting respondents when purchasing food products are studied. It is established that the consumer in its daily diet takes 10.5 % of bakery products; 7.1 % cereals and soups based on cereals and legumes. 9.5 % of respondents consume confectionery for breakfast and during snacks, and 6.2 % consume sweets. Meat is consumed daily by 5.8 % of respondents. Products based on meat –10.7 %. 8.1 % of respondents consume fish daily and fish-based products 3.1 %. 5.9 % consume milk every day, and milk-based products – 10.2 % of respondents. 12.8 and 10.1 % of the daily diet of respondents are vegetables and fruits (respectively). It is established that the recommended consumption norms are exceeded for such food groups as sweets, meat-based products, and confectionery. Diet within the norm for the consumption of bakery products, milk, fish and fish-based products. Inadequate consumption of cereals, legumes, meat, fruits. Based on the results, it is determined that the consumer prefers food products that have a pleasant (familiar) taste, without harmful, unnatural substances, high nutritional value at a low price. The studies are useful for specialists in food industry who work and develop new foods and diets.","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sentiment analysis is a huge volume increasing at a humongous rate everyday which has made it almost impossible to evaluate the data manually. In Social media, twitter, restaurant site people share their opinion as in a huge number of their prevalence. In order to make the process of analyzing the text automatic there are various machine learning techniques that could be applied. The data set is for those enthusiasts who are willing to play with text data and perform sentiment analysis or text classification. The huge quantity of data in textual is generated every day has no value unless processed. The text data problem can be resolute by a choose to take up data mining technique. By using classifier it helps to predict the text data using naïve bayes classifier. This data set consists of actual reviews from real people. So this data set will give a real time experience as to how to deal with textual data.
{"title":"Sentiment Analysis of Customer Feedback on Restaurant Reviews","authors":"Spoorthi C, Dr. Pushpa Ravikumar, Mr. Adarsh M.J","doi":"10.2139/ssrn.3506637","DOIUrl":"https://doi.org/10.2139/ssrn.3506637","url":null,"abstract":"Sentiment analysis is a huge volume increasing at a humongous rate everyday which has made it almost impossible to evaluate the data manually. In Social media, twitter, restaurant site people share their opinion as in a huge number of their prevalence. In order to make the process of analyzing the text automatic there are various machine learning techniques that could be applied. The data set is for those enthusiasts who are willing to play with text data and perform sentiment analysis or text classification. The huge quantity of data in textual is generated every day has no value unless processed. The text data problem can be resolute by a choose to take up data mining technique. By using classifier it helps to predict the text data using naïve bayes classifier. This data set consists of actual reviews from real people. So this data set will give a real time experience as to how to deal with textual data.","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132516487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Food products claim to be healthy in many ways, but prior research has either investigated these claims at the macro level (using broad descriptions such as “healthy�? or “tasty�?) or at the micro level (using single claims like “low fat�?). Our meso-level framework examines 1) whether these claims invoke natural or scientific arguments and 2) whether they communicate about positive attributes present in the food or negative attributes absent from the food. We find that common front-of-packaging (FOP) claims can be appropriately classified into (1) science and absence-focused claims about “removing negatives�?; (2) science and presence-focused claims about “adding positives�?; (3) nature and absence-focused claims about “not adding negatives�?; and (4) nature and presence-focused claims about “not removing positives.�? We conduct validation studies using breakfast cereals, a category for which nutrition quality varies but food claims are constant. We find that claim type is completely uncorrelated to actual nutrition quality and yet influences inferences consumers make about taste, healthiness, and dieting. Claim type also helps predict the effects of hedonic eating, healthy eating, or weight loss goals on food choice.
{"title":"Healthy Through Presence or Absence, Nature or Science? A Framework for Understanding Front-of-Package Food Claims","authors":"Quentin André, Pierre Chandon, Kelly L. Haws","doi":"10.2139/ssrn.3230779","DOIUrl":"https://doi.org/10.2139/ssrn.3230779","url":null,"abstract":"Food products claim to be healthy in many ways, but prior research has either investigated these claims at the macro level (using broad descriptions such as “healthy�? or “tasty�?) or at the micro level (using single claims like “low fat�?). Our meso-level framework examines 1) whether these claims invoke natural or scientific arguments and 2) whether they communicate about positive attributes present in the food or negative attributes absent from the food. We find that common front-of-packaging (FOP) claims can be appropriately classified into (1) science and absence-focused claims about “removing negatives�?; (2) science and presence-focused claims about “adding positives�?; (3) nature and absence-focused claims about “not adding negatives�?; and (4) nature and presence-focused claims about “not removing positives.�? We conduct validation studies using breakfast cereals, a category for which nutrition quality varies but food claims are constant. We find that claim type is completely uncorrelated to actual nutrition quality and yet influences inferences consumers make about taste, healthiness, and dieting. Claim type also helps predict the effects of hedonic eating, healthy eating, or weight loss goals on food choice.","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133123408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to determine the effects of packaging attributes on consumers’ buying behavior. Specifically, to investigate the effect of packaged food’sgraphics, color, size, shape, product information and/or packaging material on consumers’ buying behavior in Pakistan. Data was collected through the used of questionnaire from 300 individuals and was analyzed through Confirmatory Factor Analysis and Structural Equation Modeling. The study found a significant relationship between graphics colors, packaging size, shape, product information of packaging material with consumers’ buying behavior. The study concluded that the packaging attributes are examined, are contributed in communicating product quality that affects purchase behavior. The study recommends that food manufacturers must understand the consumer response towards their packaging and integrate their input into designing a better packaging by innovations. This can be achieved by involving consumer directly in designing the final packaging of product through their response.
{"title":"Packaging Features and Consumer Buying Behavior Towards Packaged Food Items","authors":"Muhammad Usama Ahsan Ansari, D. Siddiqui","doi":"10.2139/ssrn.3381882","DOIUrl":"https://doi.org/10.2139/ssrn.3381882","url":null,"abstract":"This study aimed to determine the effects of packaging attributes on consumers’ buying behavior. Specifically, to investigate the effect of packaged food’sgraphics, color, size, shape, product information and/or packaging material on consumers’ buying behavior in Pakistan. Data was collected through the used of questionnaire from 300 individuals and was analyzed through Confirmatory Factor Analysis and Structural Equation Modeling. The study found a significant relationship between graphics colors, packaging size, shape, product information of packaging material with consumers’ buying behavior. The study concluded that the packaging attributes are examined, are contributed in communicating product quality that affects purchase behavior. The study recommends that food manufacturers must understand the consumer response towards their packaging and integrate their input into designing a better packaging by innovations. This can be achieved by involving consumer directly in designing the final packaging of product through their response.","PeriodicalId":210491,"journal":{"name":"Food Product Development eJournal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124305396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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