用于预测包裹干酪乳杆菌的喷雾干燥条件的 RSM 和 ANN 模型比较研究

IF 2.2 4区 农林科学 Q3 CHEMISTRY, APPLIED Cereal Chemistry Pub Date : 2024-10-03 DOI:10.1002/cche.10838
Poorva Sharma, Michael T. Nickerson, Darren R. Korber
{"title":"用于预测包裹干酪乳杆菌的喷雾干燥条件的 RSM 和 ANN 模型比较研究","authors":"Poorva Sharma,&nbsp;Michael T. Nickerson,&nbsp;Darren R. Korber","doi":"10.1002/cche.10838","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background and Objectives</h3>\n \n <p>The aim of this study was to develop a wall material using pea protein isolate and pectin to optimize the encapsulation of <i>Lactobacillus casei</i> by spray drying. Response surface methodology (RSM) and artificial neural network (ANN) were used to analyze the effect of processing parameters.</p>\n </section>\n \n <section>\n \n <h3> Findings</h3>\n \n <p>The results showed that both RSM and ANN could be used to successfully characterize the experimental data, although ANN demonstrated greater predictive accuracy than RSM due to a higher <i>R</i><sup>2</sup> and lower mean square error (MSE).</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>ANN was observed to show more suitability than RSM. The encapsulation efficiency (90.7%), yield (45.5%), and wettability (169 s) of spray-dried probiotic powder obtained under optimal spray drying conditions (inlet air temperature (132°C); feed flow rate (9.5 mL/min) and pea protein isolate concentration (7.1%)) were observed to be not significantly different (<i>p</i> &lt; .05) from predicted values for all three parameters, demonstrating the validity of applied model.</p>\n </section>\n \n <section>\n \n <h3> Significance and Novelty</h3>\n \n <p>In this study, production technology of vegan base probiotic powder has been developed using mathematical modeling through the spray-drying method. Therefore, this data can be useful for food processing industries to develop a high-quality probiotic powder through spray drying.</p>\n </section>\n </div>","PeriodicalId":9807,"journal":{"name":"Cereal Chemistry","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comparative study of RSM and ANN models for predicting spray drying conditions for encapsulation of Lactobacillus casei\",\"authors\":\"Poorva Sharma,&nbsp;Michael T. Nickerson,&nbsp;Darren R. Korber\",\"doi\":\"10.1002/cche.10838\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background and Objectives</h3>\\n \\n <p>The aim of this study was to develop a wall material using pea protein isolate and pectin to optimize the encapsulation of <i>Lactobacillus casei</i> by spray drying. Response surface methodology (RSM) and artificial neural network (ANN) were used to analyze the effect of processing parameters.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Findings</h3>\\n \\n <p>The results showed that both RSM and ANN could be used to successfully characterize the experimental data, although ANN demonstrated greater predictive accuracy than RSM due to a higher <i>R</i><sup>2</sup> and lower mean square error (MSE).</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>ANN was observed to show more suitability than RSM. The encapsulation efficiency (90.7%), yield (45.5%), and wettability (169 s) of spray-dried probiotic powder obtained under optimal spray drying conditions (inlet air temperature (132°C); feed flow rate (9.5 mL/min) and pea protein isolate concentration (7.1%)) were observed to be not significantly different (<i>p</i> &lt; .05) from predicted values for all three parameters, demonstrating the validity of applied model.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Significance and Novelty</h3>\\n \\n <p>In this study, production technology of vegan base probiotic powder has been developed using mathematical modeling through the spray-drying method. Therefore, this data can be useful for food processing industries to develop a high-quality probiotic powder through spray drying.</p>\\n </section>\\n </div>\",\"PeriodicalId\":9807,\"journal\":{\"name\":\"Cereal Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cereal Chemistry\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cche.10838\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cereal Chemistry","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cche.10838","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
引用次数: 0

摘要

背景与目的 本研究旨在开发一种使用豌豆蛋白分离物和果胶的壁材,以优化喷雾干燥法对干酪乳杆菌的封装。采用响应面法(RSM)和人工神经网络(ANN)分析了加工参数的影响。 研究结果 结果表明,RSM 和 ANN 都能成功地描述实验数据的特征,但 ANN 的 R2 和均方误差(MSE)更低,因此比 RSM 显示出更高的预测准确性。 结论 ANN 比 RSM 更适用。在最佳喷雾干燥条件(进气温度(132°C)、进料流速(9.5 mL/min)和豌豆蛋白分离物浓度(7.1%))下,观察到喷雾干燥益生菌粉的封装效率(90.7%)、产量(45.5%)和润湿性(169 s)与所有三个参数的预测值均无显著差异(p <.05),证明了所应用模型的有效性。 意义和新颖性 本研究利用数学模型,通过喷雾干燥法,开发了素基益生菌粉的生产技术。因此,这些数据对食品加工业通过喷雾干燥法研制优质益生菌粉很有帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A comparative study of RSM and ANN models for predicting spray drying conditions for encapsulation of Lactobacillus casei

Background and Objectives

The aim of this study was to develop a wall material using pea protein isolate and pectin to optimize the encapsulation of Lactobacillus casei by spray drying. Response surface methodology (RSM) and artificial neural network (ANN) were used to analyze the effect of processing parameters.

Findings

The results showed that both RSM and ANN could be used to successfully characterize the experimental data, although ANN demonstrated greater predictive accuracy than RSM due to a higher R2 and lower mean square error (MSE).

Conclusion

ANN was observed to show more suitability than RSM. The encapsulation efficiency (90.7%), yield (45.5%), and wettability (169 s) of spray-dried probiotic powder obtained under optimal spray drying conditions (inlet air temperature (132°C); feed flow rate (9.5 mL/min) and pea protein isolate concentration (7.1%)) were observed to be not significantly different (p < .05) from predicted values for all three parameters, demonstrating the validity of applied model.

Significance and Novelty

In this study, production technology of vegan base probiotic powder has been developed using mathematical modeling through the spray-drying method. Therefore, this data can be useful for food processing industries to develop a high-quality probiotic powder through spray drying.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Cereal Chemistry
Cereal Chemistry 工程技术-食品科技
CiteScore
5.10
自引率
8.30%
发文量
110
审稿时长
3 months
期刊介绍: Cereal Chemistry publishes high-quality papers reporting novel research and significant conceptual advances in genetics, biotechnology, composition, processing, and utili­zation of cereal grains (barley, maize, millet, oats, rice, rye, sorghum, triticale, and wheat), pulses (beans, lentils, peas, etc.), oil­seeds, and specialty crops (amaranth, flax, quinoa, etc.). Papers advancing grain science in relation to health, nutrition, pet and animal food, and safety, along with new methodologies, instrumentation, and analysis relating to these areas are welcome, as are research notes and topical review papers. The journal generally does not accept papers that focus on nongrain ingredients, technology of a commercial or proprietary nature, or that confirm previous research without extending knowledge. Papers that describe product development should include discussion of underlying theoretical principles.
期刊最新文献
Issue Information Changes of gluten protein composition during sourdough fermentation in rye flour A comparative study of RSM and ANN models for predicting spray drying conditions for encapsulation of Lactobacillus casei Differences in physicochemical properties and structure of red sorghum starch: Effect of germination treatments QTL mapping for wheat ferulic acid concentration using 50 K SNP chip in a recombinant inbred line population of Zhongmai 578/Jimai 22
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1