Mohammad Reza Alizadeh

Potential Applications of Computer Vision in Quality Inspection of Rice: A Review

Among the cereals, rice is the major foodstuff for a large part of the world’s population. Due to its tremendous importance in the global market, its qualitative economic aspects during processing have always been attended by producers. As the most delicate of the cereals, rice needs the utmost care during post-harvest handling and processing, because in most cases, it is consumed as whole kernel. The growing demand for production of rice with high-quality and safety standards has increased the need for its accurate, fast and objective quality monitoring. Computer vision techniques, as novel technologies, can provide an automated, nondestructive and cost-effective way to achieve these requirements. In recent years, various studies have been conducted to evaluate rice qualitative features based on computer vision techniques. This paper presents the theoretical and technical principles of computer vision for nondestructive quality assessment of rice combined with a review of the recent achievements and applications for quality inspection and monitoring of the product.

Design, development and performance evaluation of an automatic control system for rice whitening machine based on computer vision and fuzzy logic

An automatic control system was developed for controlling rice whitening machine.The system was designed based on machine vision and fuzzy logic techniques.The developed system had a high accuracy in controlling of the whitening machine.Performance speed of the system was satisfactorily higher than human operator.Decisions made by the system resulted in a good improvement in the quality of product. The objective of this study was developing an intelligent automatic control system (ACS) based on machine vision and fuzzy logic techniques to control the performance of rice whitening machines. The developed ACS consisted of two main parts, namely hardware (including sampling unit, kernel singulation unit, image capturing unit, processor (computer), discharge pressure control unit and data acquisition unit), and software (including image processing, fuzzy inference and central control units). Two important qualitative indices, degree of milling and percentage of broken kernels, were considered as input variables and the level of pressure on the discharge section of the whitening machine was selected as the output variable in the fuzzy inference unit. Results of the evaluations indicated that the developed ACS had 89.2% accuracy in determining the desired working conditions for the whitening machine. The total time of each monitoring round was, on the average, equal to 14.73s, of which 6.4s was devoted to kernel sampling and transporting the samples into the imaging chamber, 7.33s for taking three images from the kernels, processing the captured images and executing the fuzzy inference process, and the remaining 1.5s for making the adjustments in the level of pressure in the mechanism. Based on this information and in contrast to the corresponding time spent by the human operator to perform a similar process, it was revealed that the performance speed of the ACS was, on average, 31.3% higher than that of the human operator. Evaluation of the samples obtained from the discharge section of the rice whitening machine at different stages of the control process showed that the decisions made by the developed ACS during the control process resulted in a satisfactory improvement in the quality of the output product.

Effects of Moisture Content, Loading Rate, and Grain Orientation on Fracture Resistance of Paddy (Oryza Sativa L.) Grain

In order to predict the extent of mechanical damage of rice kernels during de-husking, milling, and other subsequent storage projects, information on such engineering properties of paddy grains as force and deformation curve must be provided. In this research, fracture resistance of paddy grain was determined in terms of grain rupture force and energy. The paddy grains were quasi-statically loaded in horizontal and vertical orientations at three moisture content levels of 8, 11, and 14% (w.b) and two loading rates of 5 and 10 mm min−1. In the current study, 12 treatments were performed as randomized complete block design with 10 replications. Based on the results obtained, as the moisture content of the paddy grain increased from 8 to 14% (w.b), the force required for initiating grain rupture decreased from 167.70 to 88.33 N and 43.55 to 21.68 N, and the energy absorbed at grain rupture increased from 13.08 to 34.39 mJ and 10.38 to 26.98 mJ, for horizontal and vertical orientations, respectively. This showed that the grains are more flexible in horizontal orientation. Furthermore, both the rupture force and energy decreased as the loading rate increased from 5 to 10 mm min−1.

Flow Properties of Awned and De-Awned Paddy Grains Through a Horizontal Hopper Orifice

In a modern rice mill, de-awning is an important process before husking operation to eliminate awns of the paddy grains for easy conveying in the elevators, chutes, and hopper orifices. This experiment was conducted to study the effects of independent variables of de-awning percentage, orifice cross-sectional area and paddy grains moisture content on the flowing rate (FR) and variations of flowing rate (VFR) of paddy grains through a horizontal hopper orifice. A local paddy variety, namely, Hashemi, which is characterized by long awns was used as a raw material in the test. The results indicated that flow rate (FR) and variations on flow rate (VFR) significantly (p < 0.01) affected by the de-awning percentage, orifice cross-sectional area and paddy moisture content. FR increased from 45.00 to 87.57 g s−1 and VFR decreased from 54.93 to 21.49%, as de-awning increased from 14.67 to 84.93%. FR increased as the orifice cross-sectional area increased from 12.08 to 34.81 cm2; however, higher VFR was obtained at lower orifice cross-sectional area. For the awned (87% of the grains had originally awns) and de-awned paddy (82% of the grains were de-awned), FR decreased as the paddy moisture content increased from 8.67 to 15.06%wb; while VFR increased at higher grain moisture content.