Research on Rice Grain Shape Detection Method Based on Machine Vision

2019 ◽  
Author(s):  
Yadan Hu ◽  
Yunming Du ◽  
Linna San ◽  
Jing Tian
Keyword(s):  
Machine Vision ◽  
Grain Shape ◽  
Detection Method ◽  
Rice Grain ◽  
Shape Detection

scholarly journals Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 590
Author(s):  
Zhenqian Zhang ◽  
Ruyue Cao ◽  
Cheng Peng ◽  
Renjie Liu ◽  
Yifan Sun ◽  
...  
Keyword(s):  
Machine Vision ◽  
Edge Detection ◽  
Detection Method ◽  
Region Of Interest ◽  
Average Error ◽  
Vertical Projection ◽  
Cut Edge ◽  
Fitting Method ◽  
Combine Harvester ◽  
Edge Detection Method

A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

scholarly journals Substitution Mapping of Two Closely Linked QTLs Controlling Grain Chalkiness and Grain Shape on Rice Chromosome 8

2021 ◽  
Author(s):  
Weifeng Yang ◽  
Liang Xiong ◽  
Jiayan Liang ◽  
Qingwen Hao ◽  
Xin Luan ◽  
...  
Keyword(s):  
Grain Quality ◽  
Grain Shape ◽  
Rice Chromosome ◽  
Chromosome 8 ◽  
High Yield ◽  
Rice Grain ◽  
Rice Varieties ◽  
Substitution Mapping ◽  
Grain Width ◽  
Grain Chalkiness

Abstract Background: Rice varieties are required to have high yield and good grain quality. Grain chalkiness and grain shape are two important traits of rice grain quality. Low chalkiness slender grains are preferred by most rice consumers. Here, we dissected two closely linked quantitative trait loci (QTLs) controlling grain chalkiness and grain shape on rice chromosome 8 by substitution mapping. Results: Two closely linked QTLs controlling grain chalkiness and grain shape were identified using single-segment substitution lines (SSSLs). The two QTLs were then dissected on rice chromosome 8 by secondary substitution mapping. qPGC8.1 was located in an interval of 1382.6 kb and qPGC8.2 was mapped in a 2057.1 kb region. The maximum distance of the two QTLs was 4.37 Mb and the space distance of two QTL intervals was 0.72 Mb. qPGC8.1 controlled grain chalkiness and grain width. qPGC8.2 was responsible for grain chalkiness and for grain length and grain width. The additive effects of qPGC8.1 and qPGC8.2 on grain chalkiness were not affected by heat stress. Conclusions: Two closely linked QTLs qPGC8.1 and qPGC8.2 were dissected on rice chromosome 8. They controlled the phenotypes of grain chalkiness and grain shape. The two QTLs were insensitive to high temperature.

scholarly journals Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a japonica × indica cross

2015 ◽  
Vol 65 (4) ◽  
pp. 308-318 ◽  
Author(s):  
Kazufumi Nagata ◽  
Tsuyu Ando ◽  
Yasunori Nonoue ◽  
Tatsumi Mizubayashi ◽  
Noriyuki Kitazawa ◽  
...  
Keyword(s):  
Genetic Control ◽  
Qtl Analysis ◽  
Grain Shape ◽  
Rice Grain ◽  
Advanced Backcross

scholarly journals Whole-Genome Sequencing Identifies a Rice Grain Shape Mutant, gs9–1

Rice ◽  
2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Liangrong Jiang ◽  
Guotian Li ◽  
Mawsheng Chern ◽  
Rashmi Jain ◽  
Nhan T. Pham ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Grain Shape ◽  
Rice Grain ◽  
Whole Genome

Monocular Dynamic Machine Vision-Based Pearl Shape Detection

2019 ◽  
Vol 24 (5) ◽  
pp. 654-662
Author(s):  
Yuzong Wang ◽  
Fei Deng ◽  
Daxu Zhao ◽  
Jiaying Ye ◽  
Peixin Wang ◽  
...  
Keyword(s):  
Machine Vision ◽  
Shape Detection

Novel OsGRAS19 mutant, D26, positively regulates grain shape in rice (Oryza sativa)

2019 ◽  
Vol 46 (9) ◽  
pp. 857 ◽  
Author(s):  
Zhimin Lin ◽  
Jingwan Yan ◽  
Jun Su ◽  
Huaqing Liu ◽  
Changquan Hu ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Grain Size ◽  
Transcription Factor ◽  
Grain Shape ◽  
Rice Yield ◽  
Reproductive Development ◽  
Cell Number ◽  
Rice Grain ◽  
Regulatory Effect ◽  
Site Mutation

Grain size is an important factor in rice yield. Several genes related to grain size have been reported, but most of them are determined by quantitative trail loci (QTL) traits. Gene D26 is a novel site mutation of OsGRAS19 and involved in the brassinosteroid (BR) signalling pathway. However, whether D26 is involved in the process of rice reproductive development remains unclear. Here, gene cloning and functional analysis revealed that D26 has an obvious regulatory effect on grain size. Overexpression or CRISP/Cas9 mutant of D26 also showed that grain size was positively influenced. Cellular analyses show that D26 modulates grain size by promoting cell division and regulating the cell number in the upper epidermis of the glume. The overexpression results further suggest that the level of D26 expression positively impacts grain length and leaf angles and that the expression of several known grain size genes is involved in the regulation. Based on our results, D26, as a transcription factor, effectively improves rice grain shape.

The Appraisal of Velcro’s Surface Quality Based on Machine Vision Systems

2011 ◽  
Vol 201-203 ◽  
pp. 2045-2048
Author(s):  
Da Xing Zhao ◽  
Qing Lin
Keyword(s):  
Machine Vision ◽  
Product Quality ◽  
Surface Quality ◽  
Detection Method ◽  
Experimental Results ◽  
Vision Systems ◽  
Examination Method ◽  
The Common ◽  
Develop Environment ◽  
Common Defect

The most important problem of the Velcro Manufacturer face is to control the surface quality, and how to improve the product quality has become the key of the enterprise. Therefore, this paper take the research on the examination method of the Velcro’s surface flaw, and propose a simply and effectively detection method on the marginal check and the flaw extraction of the buckle in the considering of the system’s real-team and the effectiveness. The experiments have been carried on the results been analyzed under the Visual c + + develop environment. Experimental results show that the system can detect the common defect of the fastening surface accurately and classify them.

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