Mathematical Modelling of the Mechanical Properties of Four Varieties of Brine Pickles Using Neural Networks

K. Pentoś, D. Migut, N. Matłok, J. Gorzelany
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Abstract

Abstract The study assesses the impact of selected fruit properties and the souring process parameters on the mechanical properties of four varieties of field cucumbers (Śremianin, Śremski, Polan and Izyd) harvested from 2014 to 2016. The analyses focused on the changes in the values of the puncture strength parameters of the peel and the mesocarp, the deformation from the moment of puncture and the energy needed to puncture the peel and the mesocarp of the selected cucumber varieties relative to the year of harvest, fruit size, type of brine, puncture location and souring time. Neural networks were used to model the relationships studied. Sensitivity analysis of the obtained models showed that the length fraction had the greatest impact on the puncture strength and the energy needed to puncture the peel and the mesocarp. On the other hand, deformation was most affected by the souring time and the brine composition.
基于神经网络的四种卤菜力学特性数学建模
摘要以2014 - 2016年收获的4个大田黄瓜品种(Śremianin、Śremski、Polan和Izyd)为研究对象,研究了不同果实特性和酸洗工艺参数对黄瓜力学性能的影响。分析了不同黄瓜品种果皮和中果皮穿刺强度参数、穿刺瞬间变形及穿刺果皮和中果皮所需能量随采收年份、果实大小、卤水类型、穿刺位置和酸化时间的变化。神经网络被用来模拟所研究的关系。对模型的敏感性分析表明,长度分数对穿刺强度和穿刺果皮和中果皮所需能量的影响最大。另一方面,发酵时间和卤水成分对变形的影响最大。
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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