Islam Monzurul, Wahid Khan A, Dinh Anh V, Bhowmik Pankaj
1Department of Electrical and Computer Engineering, Office Room 3B14 Engineering Building, University of Saskatchewan, 57 Campus Drive, Saskatoon, S7N 5A9 Canada.
2National Research Council Canada, Saskatoon, Canada.
J Food Sci Technol. 2019 Jun;56(6):2814-2824. doi: 10.1007/s13197-019-03590-3. Epub 2019 Feb 7.
Onion is perishable and thereby subject to drying during unrefrigerated storage. Its moisture content is important to ensure optimum quality in storage. To track and analyze the dynamics of natural dehydration in onion and also to assess its moisture content, noninvasive and nondestructive methods are preferred. One of them is known as electrical impedance spectroscopy (or EIS in short). In the first phase of our experiment, we have used EIS, where we apply alternating current with multiple frequency to the object (onion in this case) and generate impedance spectrum which is used to characterize the object. We then develop an equivalent electrical circuit representing onion characteristics using a computer assisted optimization technique that allows us to monitor the response of onion undergoing natural drying for a duration of 3 weeks. The developed electrical model shows better congruence with the impedance data measured experimentally when compared to other conventional models for plant tissue with a mean absolute error of 0.42% and root mean squared error of 0.55%. In the second phase of our experiment, we attempted to find a correlation between the previous impedance data and the actual moisture content of the onions under test (measured by weighing) and developed a mathematical model. This model will provide an alternative tool for assessing the moisture content of onion nondestructively. Our model shows excellent correlation with the ground truth data with a deterministic coefficient of 0.9767, root mean square error of 0.02976 and sum of squared error of 0.01329. Therefore, our two models will offer plant scientists the ability to study the physiological status of onion both qualitatively and quantitatively.
洋葱易腐坏，因此在未冷藏储存期间容易干燥。其水分含量对于确保储存中的最佳品质很重要。为了追踪和分析洋葱自然脱水的动态过程，并评估其水分含量，首选非侵入性和非破坏性方法。其中一种方法称为电阻抗光谱法（简称EIS）。在我们实验的第一阶段，我们使用了EIS，即向物体（在这种情况下是洋葱）施加多频率交流电，并生成用于表征该物体的阻抗谱。然后，我们使用计算机辅助优化技术开发了一个代表洋葱特性的等效电路模型，这使我们能够监测洋葱在3周自然干燥过程中的响应。与其他传统的植物组织模型相比，所开发的电模型与实验测量的阻抗数据具有更好的一致性，平均绝对误差为0.42%，均方根误差为0.55%。在我们实验的第二阶段，我们试图找出先前的阻抗数据与被测洋葱实际水分含量（通过称重测量）之间的相关性，并建立了一个数学模型。该模型将为无损评估洋葱水分含量提供一种替代工具。我们的模型与实测数据具有极好的相关性，决定系数为0.9767，均方根误差为0.02976，平方和误差为0.01329。因此，我们的这两个模型将为植物科学家提供定性和定量研究洋葱生理状态的能力。
