{"title":"预测花生基三维可打印食品油墨的粘弹性能。","authors":"Amaresh Kadival, Jayeeta Mitra, Manish Kaushal, Rajendra Machavaram","doi":"10.1111/jtxs.12817","DOIUrl":null,"url":null,"abstract":"<p>Viscoelastic properties of 3D printable peanut-based food ink were investigated using frequency sweep and relaxation test. The incorporation of xanthan gum (XG) improved the shear thinning behavior (<i>n</i> value ranging from 0.139 to 0.261) and lowered the η*, G′, and G′′ values, thus making food ink 3D printable. The addition of XG also caused a downward shift in the relaxation curve. This study evaluates the possibility of an artificial neural network (ANN) approach as a substitute for the Maxwell three-element and Peleg model for predicting the viscoelastic behavior of food ink. The results revealed that all three models accurately predicted the decay forces. The inclusion of XG decreased the hardness and enhanced the cohesiveness, so enabling the 3D printing of food ink. The hardness was highly positively correlated with Maxwell model parameters F<sub>e</sub>, F<sub>1</sub>, F<sub>2</sub>, F<sub>3,</sub> and Peleg constant k<sub>2</sub> (0.57) and negatively correlated with k<sub>1</sub> (−0.76).</p>","PeriodicalId":17175,"journal":{"name":"Journal of texture studies","volume":"55 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of viscoelastic properties of peanut-based 3D printable food ink\",\"authors\":\"Amaresh Kadival, Jayeeta Mitra, Manish Kaushal, Rajendra Machavaram\",\"doi\":\"10.1111/jtxs.12817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Viscoelastic properties of 3D printable peanut-based food ink were investigated using frequency sweep and relaxation test. The incorporation of xanthan gum (XG) improved the shear thinning behavior (<i>n</i> value ranging from 0.139 to 0.261) and lowered the η*, G′, and G′′ values, thus making food ink 3D printable. The addition of XG also caused a downward shift in the relaxation curve. This study evaluates the possibility of an artificial neural network (ANN) approach as a substitute for the Maxwell three-element and Peleg model for predicting the viscoelastic behavior of food ink. The results revealed that all three models accurately predicted the decay forces. The inclusion of XG decreased the hardness and enhanced the cohesiveness, so enabling the 3D printing of food ink. The hardness was highly positively correlated with Maxwell model parameters F<sub>e</sub>, F<sub>1</sub>, F<sub>2</sub>, F<sub>3,</sub> and Peleg constant k<sub>2</sub> (0.57) and negatively correlated with k<sub>1</sub> (−0.76).</p>\",\"PeriodicalId\":17175,\"journal\":{\"name\":\"Journal of texture studies\",\"volume\":\"55 1\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2023-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of texture studies\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jtxs.12817\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of texture studies","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jtxs.12817","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Prediction of viscoelastic properties of peanut-based 3D printable food ink
Viscoelastic properties of 3D printable peanut-based food ink were investigated using frequency sweep and relaxation test. The incorporation of xanthan gum (XG) improved the shear thinning behavior (n value ranging from 0.139 to 0.261) and lowered the η*, G′, and G′′ values, thus making food ink 3D printable. The addition of XG also caused a downward shift in the relaxation curve. This study evaluates the possibility of an artificial neural network (ANN) approach as a substitute for the Maxwell three-element and Peleg model for predicting the viscoelastic behavior of food ink. The results revealed that all three models accurately predicted the decay forces. The inclusion of XG decreased the hardness and enhanced the cohesiveness, so enabling the 3D printing of food ink. The hardness was highly positively correlated with Maxwell model parameters Fe, F1, F2, F3, and Peleg constant k2 (0.57) and negatively correlated with k1 (−0.76).
期刊介绍：
The Journal of Texture Studies is a fully peer-reviewed international journal specialized in the physics, physiology, and psychology of food oral processing, with an emphasis on the food texture and structure, sensory perception and mouth-feel, food oral behaviour, food liking and preference. The journal was first published in 1969 and has been the primary source for disseminating advances in knowledge on all of the sciences that relate to food texture. In recent years, Journal of Texture Studies has expanded its coverage to a much broader range of texture research and continues to publish high quality original and innovative experimental-based (including numerical analysis and simulation) research concerned with all aspects of eating and food preference.
Journal of Texture Studies welcomes research articles, research notes, reviews, discussion papers, and communications from contributors of all relevant disciplines. Some key coverage areas/topics include (but not limited to):
• Physical, mechanical, and micro-structural principles of food texture
• Oral physiology
• Psychology and brain responses of eating and food sensory
• Food texture design and modification for specific consumers
• In vitro and in vivo studies of eating and swallowing
• Novel technologies and methodologies for the assessment of sensory properties
• Simulation and numerical analysis of eating and swallowing
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