两个芒果品种的种子在不同温度和不同预处理条件下的干燥动力学和数学建模

IF 3.2 4区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Biofuels Bioproducts & Biorefining-Biofpr Pub Date : 2024-03-20 DOI:10.1002/bbb.2611
Getachew D. Gebre, Yadessa G. Keneni, Shemelis N. Gebremariam, Jorge M. Marchetti
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引用次数: 0

摘要

全球废物产生量不断增加,这不仅是一种威胁,也是利用绿色价值化技术解决能源不安全和污染问题的机遇。然而,这需要对废物和副产品进行预处理,并优化干燥过程,以获得高质量的生物燃料。因此,本研究旨在分析目前使用的干燥模型的性能,以及不同干燥温度、干燥时间和种子预处理对两种芒果种子干燥动力学的影响。因此,在加热炉中将整粒种子和压碎的种子置于五种干燥温度(313-353 K)下。系统记录重量损失,将其转换成水分比,然后拟合成四个半理论数学模型,即:(i) Lewis 模型、(ii) Henderson 和 Pabis 模型、(iii) Page 模型以及 (iv) Avhad 和 Marchetti 模型。使用 R2、X2、均方根误差 (RMSE)、平均偏差误差 (MBE) 和平均绝对误差 (MAE) 等统计参数对这些模型的适应性进行了比较。结果表明,种子预处理和提高干燥温度可提高水分蒸发率,缩短干燥所需时间。在所有模型中,Avhad 和 Marchetti 模型的 R2 值较高,在开氏 313 度时,本地芒果和杂交芒果的 R2 值分别为 0.9994 和 0.9991;在开氏 353 度和开氏 313 度时,本地芒果和杂交芒果种子的 R2 值分别为 0.9977 和 0.9970;因此,该模型的性能最佳。在所有数学模型中,两个品种的芒果种子和不同预处理方法的活化能(Ea)略有不同。本地芒果籽和杂交芒果籽的平均 Ea 值分别为 41.18 kJ mol-1 和 46.21 kJ mol-1。对于整粒和压碎的本地芒果和杂交芒果品种,平均 Ea 值分别为 31.37 kJ mol-1、40.80 kJ mol-1、50.99 kJ mol-1 和 51.61 kJ mol-1。造成这种差异的原因可能是种子品种、化学成分、生长条件和细胞结构的不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Drying kinetics and mathematical modeling of seeds of two mango varieties at different temperatures and with different pretreatments

Increasing global waste generation is not only a threat but also an opportunity to address energy insecurity and pollution using green valorization techniques. However, this requires pretreatment of waste and byproducts and optimization of drying to obtain high-quality biofuels. Hence, this study aims to analyze the performance of currently used drying models, the influence of different drying temperatures, drying time, and seed pretreatment on the drying kinetics of two varieties of mango seed. Accordingly, whole seeds and crushed seeds were exposed to five drying temperatures (313–353 K) in a heating furnace. Weight loss was recorded systematically, converted into moisture ratio, and then fitted to four semitheoretical mathematical models, namely: (i) Lewis, (ii) Henderson and Pabis, (iii) Page, and (iv) Avhad and Marchetti models. The fitness of these models was compared using statistical parameters, such as R2, X2, root mean square error (RMSE), mean bias error (MBE), and mean absolute error (MAE). The results showed that seed pretreatment and increasing the drying temperature led to an increase in the rate of moisture evaporation and reduced the time required for drying. Among all models, the Avhad and Marchetti model provided higher R2 values of 0.9994 and 0.9991 for local and hybrid mango at 313 K, and 0.9977, and 0.9970 for local and hybrid crushed mango seeds at 353 K and 313 K, respectively; hence, it showed the best performance. The activation energy (Ea) showed a slight differences for both varieties of mango seed and among pretreatments in all mathematical models. The mean Ea values for local and hybrid mango seeds were 41.18 kJ mol−1 and 46.21 kJ mol−1, respectively. For whole and crushed local and hybrid mango varieties, the mean Ea values were 31.37 kJ mol−1, 40.80 kJ mol−1, 50.99 kJ mol−1, and 51.61 kJ mol−1. The likely reason for this variation might be differences in variety, chemical composition, growing conditions, and cellular structure of the seed varieties.

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来源期刊
CiteScore
7.80
自引率
5.10%
发文量
122
审稿时长
4.5 months
期刊介绍: Biofuels, Bioproducts and Biorefining is a vital source of information on sustainable products, fuels and energy. Examining the spectrum of international scientific research and industrial development along the entire supply chain, The journal publishes a balanced mixture of peer-reviewed critical reviews, commentary, business news highlights, policy updates and patent intelligence. Biofuels, Bioproducts and Biorefining is dedicated to fostering growth in the biorenewables sector and serving its growing interdisciplinary community by providing a unique, systems-based insight into technologies in these fields as well as their industrial development.
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