In order to obtain white rice from paddy, from harvesting to final production, several operations such as threshing, handling, de-husking, milling and whitening are carried out on rice grains. If the adjustment of implements, used in the various mentioned operations, be not properly carried out, excessive losses in the rice final crop may occur (Zareiforoush et al. 2010a). Generally in rice mills, due to unavailability of continuous on-line measurement methods, quality rice grader of product is monitored visually by experienced operators at 1–2 h intervals (Yadav and Jindal 2007). This means that the operator, based on his experience and proficiency with the processing machinery, assesses the quality grade of the product by mere visual inspection of the machine output and making the required adjustments. Most of the time, this operation is neither carried out with enough accuracy nor performed in a short time. In this regard, development of automated systems which can work based on the operators’ expertise may be an efficacious method for fast and reliable quality grading of the product.
Soft computing is an innovative method for development of intelligent systems which has attracted increasing interest by the scientific communities during the past few decades. It has been stated that utilization of the machine vision and artificial intelligence can result in increased quality of the product, abolish inconsistent manual evaluation, and reduce dependence on available manpower (Li et al. 2009). In recent years, many scientists and researchers attempted to design and develop automatic system based on computer vision and artificial intelligence for quality evaluation and grading of rice.
Rice processing machines produced in developed countries are mostly unaffordable by rural farmers, hence there was need to develop cost effective/efficient machines produced from available local materials desirable in food industry that meets the need of the rural farmers. This study was to evaluate the performance of a developed rice destoner at Federal University of Agriculture, Abeokuta, Nigeria.
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