菠菜流化床干燥工艺优化:用RSM和ANN模型评价漂烫效果

IF 3.5 2区 农林科学 Q2 FOOD SCIENCE & TECHNOLOGY
Mir Tuhin Billah, Noor E Zannat, Md Akram Hossain, Ishmam Haque Sachcha, Sabina Yasmin, Md. Sazzat Hossain Sarker
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引用次数: 0

摘要

干燥的叶菜的质量,如水菠菜(Ipomoea aquatica),已被发现在水分含量和重要营养物质,即维生素C和β-胡萝卜素的保留方面受到干燥过程的显著影响。由于目前还没有对叶类蔬菜的流化床干燥进行研究,因此在优化工艺参数以最大限度地保留养分方面具有很大的应用潜力。研究了温度、干燥时间和床层厚度对焯水菠菜和未焯水菠菜营养品质的影响。本研究采用中心复合设计(CCD)和响应面法(RSM)对流化床干燥过程进行了设计和优化。为了进一步比较,本研究建立了RSM和人工神经网络(ANN)预测模型。利用多目标期望函数,从实验模型中得到了水分含量、维生素C和β-胡萝卜素保留率的最优响应。应用了适当的统计度量,例如AARD(绝对平均相对偏差)、MRD(平均相对偏差)、MSE(均方误差)和R2(决定系数),有助于在研究过程中进行模型比较。实验结果表明,干燥温度、干燥时间和床层厚度对各响应变量均有显著影响。与未漂白的样品相比,漂白后样品的床层厚度变化对水分含量的影响为16%,而与之相反,由于漂白后样品的床层厚度变化,维生素C含量的变化超过25%。RSM在预测精度和预测能力上都优于人工神经网络。结果表明,最佳干燥条件为干燥温度60℃,干燥时间7.19 min,床层厚度5.12 cm,可获得水分含量2.95%,维生素C 5.99 mg/100 g, β-胡萝卜素139.16 μg/g。预测值与实验值吻合较好,证实了优化条件对叶菜工业化干燥的适宜性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Process Optimization of Fluidized Bed Drying for Water Spinach: Evaluating the Effect of Blanching Through RSM and ANN Models

Process Optimization of Fluidized Bed Drying for Water Spinach: Evaluating the Effect of Blanching Through RSM and ANN Models

The quality of the dried leafy vegetables, such as water spinach (Ipomoea aquatica), has been found to be significantly affected by the drying process in terms of moisture content and retention of important nutrients, namely vitamin C and β-carotene. There is great potential for fluidized bed drying to be applied for leafy vegetables in optimizing process parameters for maximum nutrient retention since it has not been researched. This work investigated the effect of temperature, drying time, and bed thickness on the nutritional quality of blanched and unblanched water spinach samples. In the present study, the fluidized bed drying process has been designed and optimized using a Central Composite Design (CCD) and Response Surface Methodology (RSM). For this study, both RSM and artificial neural network (ANN) predictive models are developed for further comparison. Using a multiobjective desirability function, the best-optimized response was given from the experimental model for the responses of moisture content, vitamin C, and β-carotene retention. Appropriate statistical metrics are applied, for example, AARD (Absolute Average Relative Deviation), MRD (Mean Relative Deviation), MSE (Mean Squared Error), and R2 (Coefficient of Determination), which helped in model comparison during the study. It was observed from the experiment that all the response variables are significantly affected by drying temperature, time, and bed thickness. Variation of bed thickness in the blanched samples affected > 16% in moisture content attainment compared to unblanched samples, and vitamin C content exhibited a variation of more than 25% due to changes in bed thickness for blanched samples on the contrary. RSM has shown a better performance than ANN in its precision and prediction power. The optimized drying conditions came out to be 60°C as the drying temperature, 7.19 min as the drying time, and 5.12 cm as the bed thickness, which resulted in 2.95% of moisture content, 5.99 mg/100 g vitamin C, and 139.16 μg/g of β-carotene. The close alignment between predicted and experimental values confirms the suitability of the optimized conditions for industrial-scale drying of leafy vegetables.

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来源期刊
Food Science & Nutrition
Food Science & Nutrition Agricultural and Biological Sciences-Food Science
CiteScore
7.40
自引率
5.10%
发文量
434
审稿时长
24 weeks
期刊介绍: Food Science & Nutrition is the peer-reviewed journal for rapid dissemination of research in all areas of food science and nutrition. The Journal will consider submissions of quality papers describing the results of fundamental and applied research related to all aspects of human food and nutrition, as well as interdisciplinary research that spans these two fields.
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