Specific Dimensions of Soybean Grains Through Digital Images

Abstract

Abstract The determination of the physical properties of grains is laborious work and subject to subjectivities. Therefore, the objective of this work was to develop an automated method to measure the characteristic dimensions of soybean grains through digital images. Images of whole grains were captured and through them, the width, length, projected area, and perimeter of 50 grains were analyzed Using a computer application using Python programming language. The measurements for the grains obtained by the application were compared with those determined using a digital caliper. A Bland-Altman test was applied for the variables of width, length, and circularity, in which satisfactory results were obtained for the variable length, in which the method of obtaining measurements by digital images was not statistically different from the caliper method, making them equivalents. The width and circularity variables did not show equivalence, however, most of the data are within the 95% confidence interval. The variables of projected area and perimeter and the agreement between the data were analyzed employing an ANOVA followed by the Tukey test at 5% probability. The projected area variable did not differ significantly according to the methods used in the experiment, while the perimeter differed only for the method in which OpenCV library functions were used.

Keywords

• automation
• OpenCV
• python
• physical properties