Indirect determination of moisture using biospeckle technique

Abstract The classification and selection of agricultural products are very important to assure post-harvest quality processes. However, most of physical and chemical analyses are destructive. It means those products turn useless after these analyses. Moisture is one of the most important parameters to assure the storage quality and as well to facilitate product processing. This research offers an alternative method to determine that parameter through an indirect and non-destructive way, using the image analysis based on the Biospeckle phenomenon. This method consists in get a 10 seconds video of a laser focused on the object. This video is divided in frames, using a computational routine in Matlab and, then, the sequence of images is processed using the computational program named ImageJ. The results are expressed in terms of modified correlation matrix and Moment of Inertia (MI). At the same time, a moisture analysis is carried out using the traditional methodology employing conventional heater equipment set at 130 ºC. By correlating MI and moisture values, it was possible to determine the moisture content by means of an indirect method. To this research, it was employed grains of Moringa oleifera.

摘要 农产品的分类与甄选对保障采后品质管控流程意义重大。然而，绝大多数理化检测方法均具有破坏性，即经此类分析后，被测农产品将丧失使用价值。水分是保障农产品贮藏品质、助力产品加工的关键参数之一。本研究提出一种间接无损的替代检测方法，通过基于生物散斑（Biospeckle）现象的图像分析来测定水分含量。该方法的具体流程为：对聚焦于被测对象的激光录制一段10秒的视频，借助Matlab计算程序将视频拆解为连续帧图像，随后使用ImageJ图像处理软件对图像序列进行处理。最终结果以修正相关矩阵与惯性矩（Moment of Inertia，MI）的形式输出。与此同时，采用传统烘箱法（设置加热温度为130℃）开展水分含量对照实验。通过建立惯性矩与水分含量值的关联关系，即可通过该间接方法实现水分含量的测定。本研究以辣木（Moringa oleifera）籽粒作为实验材料。