Determining head rice yield by image analysis | |
| Author | Vykundeshwari, Ganesan |
| Call Number | AIT Thesis no.PH-03-5 |
| Subject(s) | Rice--Milling Image analysis |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering |
| Publisher | Asian Institute of Technology |
| Abstract | In milling, rough rice is initially subjected to dehusking and then to whitening in order to produce polished edible grain. A high percentage of broken kernels in milled rice symbolize a direct economic loss to the millers. Image analysis was used to determine the head rice yield (HRY). An image analysis setup consisting of personal computer, frame grabber and a color CCD camera was used for dimensional measurements with Image Tool 2.0 and Particle Image Analysis softwares that are available in the internet. Two rice varieties namely SPR 1 and HKLG were selected for the study. A total of 10 samples, 5 for each variety, of paddy weighing 250 g each were subjected to 5 different degrees of milling by altering the test mill duration from 0.5 to 2.5 min. at an interval of 0.5 min. A representative sample of about 10 - 12 g milled rice was used for imaging by placing the kernels under CCD camera manually. Dimensional features like length, perimeter and projected area were extracted from the images of individual kernels and used to compute CDR. CDR was then related to HRY by means of power functions based on the above three dimensional features with R2 more than 0.99 in all cases. The CDR computed based on projected area estimated the HRY with the highest accuracy (R2 = 0.999). Bulk samples of milled rice were imaged for determining the size distributions of kernel when subjected to different degrees of milling and also used for estimating HRY from CDR for various kernel cut-off lengths. Hence, it becomes possible to predict the HRY and CDR directly from the size distribution plots. A vacuum sampler was designed for automatic sampling and its performance was evaluated. The results showed that it picks up more broken kernels instead of picking up representative sample. |
| Year | 2003 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Food, Agriculture and Natural Resources (Former title: Department of Food Agriculture, and BioResources (DFAB)) |
| Academic Program/FoS | Postharvest and Food Process Engineering (PH) |
| Chairperson(s) | Jindal, Vinod K.; |
| Examination Committee(s) | Athapol Noornhorm;Rakshit, Sudip K.; |
| Scholarship Donor(s) | Government of Norway (NORAD);Asian Institute of Technology |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2003 |