Determining the number of sugar beet seedling using image processing method
2020
Mohammad Shaker (Assistant Professor of Agricultural Engineering Research Department, Fars Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREOO), Shiraz, Iran.) | M. Bazrafshan (Assistant Professor of Sugar beet Reseach Department, Fars Agricultural and Natural Resources Research Center, Agricultural Research, Education and Extension Organization (AREOO), Shiraz, Iran.) | Abdolabbas Jafari (3-Assistant Professor of Biosystem Engineering Department, Faculty of Agriculture, Shiraz University, Shiraz, Iran.)
The germination percentage of different sugar beet cultivars and hybrids in the field is of special importance for the breeder as a superior feature of the improved cultivar. The aim of this study was to provide an image processing-based method for rapid and accurate counting of seedling number of various sugar beet cultivars in the field. The images were taken using a digital camera from a fixed height and transferred to the Matlab software environment in May 2017 at Zarghan Agricultural Research Station. Using image processing techniques and functions in the software, the algorithm for counting and determining the number of sugar beet seedling in a fixed length was coded and presented. The proposed algorithm was related to situations in which the leaves of sugar beet seedling were far from each other or only in contact with each other. The accuracy of the algorithm was 90.32% and its execution time was about 1.67 seconds. The actual number of seedlings and the number observed by the algorithm were statistically analyzed by paired t-student test and it was found no significant difference between them (P<0.05). Also, different sugar beet cultivars had no effect on the implementation of the algorithm and its accuracy. The results showed that instead of visually counting the number of seedlings, this procedure can be done with more than 90% accuracy for the above two conditions by imaging and using the algorithm.
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