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Research on Vigor, Viability Testing Methods of Rice (Oryza Sativa L.) Seed and Computer Vision Application

Author: ZhangHuaXian
Tutor: ChengFang;YanJianFang
School: Zhejiang University
Course: Biological Systems Engineering
Keywords: Image disposal rice seed vigor viability germination TTC dyeing
CLC: S511
Type: Master's thesis
Year: 2007
Downloads: 231
Quote: 1
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Executive Summary


Seed vigor is the important index of measuring the seed quality. A seed vigor testing can reflect thepotential of seed in the field or under storage. In this paper, the author had concentrated on some vigorand viability testing methods of rice seed. They are standard germination test, Ultraweak PhotonEmission (UPE) test, TTC (2,3,5-Triphenyl Tetrazolium Chloride) dyeing test and computer visiontechnology to analyze the dyed image method. The author adopt the computer image analysis system toacquire the dyed embryo image of rice seed, combine the computer vision analysis technology with theTTC dyeing test methods to deal with the image to determine the seed vigor and viability.The main content and results of the research were as follows:1. Apply the Ultraweak Photon Emission detection Technology on the rice seed viability test,and detect the Photons of the rice seeds after inspired with the ultraviolet radiation. The author foundthat the Photons after inspired with the ultraviolet radiation of each breeds were declined with the timeof storage, and the seed of same breed harvested in the same year were increased with the inspired time.So, the detection of Ultraweak Photon Emission can be used as a qualitative analysis method to knowthe extent of the seed aging.2. Apply the TTC dyeing testing method to detect the vigor and viability of rice seed, andclassify them into four types the entirely dyed ones, the main embryo structures dyed ones, no part dyedones, and other instances. The author defined the vigor index and viability index, and compared thevigor index to the germination potential, the viability index to the germination percentage. Theregression equations between vigor index and germination potential were: Y1=0.9897 X1-1.075, R12=0.9991; Y2=0.9635 X2-1.584, R22=0.9998; Y3=1.0703 X3-1.722, R32=0.9988. The Y1, X1; Y2, X2;Y3, X3 corresponded to the vigor index and potential germination of Jinzao47, Eryou084, Xiushui09.The regression equations between viability index and germination percentage were: Y4=1.027 X4+1.0901, R42=0.9986; Y5=1.0804 X5-7.1884, R52=0.8995; Y6=1.1774 X6-12.715, R62=0.9326.The Y4, X4; Y5, X5; Y6, X6 corresponded to the viability index and germination percentage of Jinzao47,Eryou084, Xiushui09. These values of R2 indicated that the vigor and viability index by TTC test had agood reflection of the germination potential and germination percentage level.3. Adopt the computer image analysis system to acquire the dyed embryo image of rice seed,and use the software of Matlab6.5 to deal with the images. After pretreatment of the images, thresholdselection, image segmentation, feature extraction, area designation, image identification, the author gotthe goal region of the dyed embryo and computed the area of the dyed region. Through the ratio of thedyed area and the embryo area, the seeds were classified into three types, first was the entirely dyedseeds had the ratio larger than 0.95, and second type was the main embryo structures dyed ones had theratio lager than 2/3 but smaller than 0.95, the last type was the seeds without viability. The first type wasthe seeds with vigor, and the first and second types were the seeds with viability.4. Through comparison with the results of the standard germination and TTC test, the author gotthe regression equations between results by image and standard germination were: Y01=0.9791X01- ??1.9643, R012=0.9996; Y02=0.9351X02-1.7449, R022=0.999; Y03=1.0933 X03-5.6643, R032=1; Y11=0.9426 X11+9.9336, R112=0.9993; Y12=1.0302 X12-1.6332, R122=0.947; Y13=1.0927 X13-4.4382, R132=0.9396. The Y01, X01; Y02, X02; Y03, X03 corresponded to the vigor index by image andgermination potential, and Y11, X11; Y12, X12; Y13, X13 corresponded to the viability index andgermination percentage of Jinzao47, Eryou084, Xiushui09. The regression equations between results byimage and TTC test were: Y04=0.9889 X04-0.8747, R042=0.9999; Y05=0.9698 X05-0.1616, R052=0.9979; Y06=1.0205 X06-3.8449, R062=0.9991; Y14=0.9174 X14+8.9664, R142=0.9999; Y15=1.167 X15-13.556, R152=0.8909; Y16=0.9245 X16+7.6625, R162=0.9998. The Y04, X04; Y05, X05; Y06,X06 corresponded to the vigor index by image and germination potential, and Y11, X11; Y12, X12; Y13, X13corresponded to the viability index and germination percentage of Jinzao47, Eryou084, Xiushui09.These values of R2 indicated that the results by image had a good reflection of the germination test andTTC test.

Full-text Catalog


Abstract     5-6
ABSTRACT     6-8
directory     8-11
first chapter     11-18
1.1 research purpose and significance of     11-12
120 domestic and international research trends     12-16
1.3 research     16-17
1.4 Summary     17-18
germination test in the second chapter     18-25
2.1 crop seed germination rate and germination potential     18-19
2.1.1 rice seed structure and germination process     18
2.1.2 germination rate and germination energy     18-19
2.2 germination test method     19-22
2.2.1 test materials     19
2.2.2 test steps     19-21
2.2.3 Calculation of results and presentation     21-22
2.3 germination test results and discussion     22-24
2.3.1 germination test results     22-23
2.3.2 discuss     23-24
2.4 Summary     24-25
weak luminescence characteristics of     25-37
3.1 weak luminescence system     25-28
3.1.1 weak luminescence About     25-27
3.1.2 weak luminescence test principle     27-28
3.1.3 weak luminescence of the composition of the test system     28
3.2 The test method     28-30
3.2.1 Test Notes     28
3.2.2 test steps     28-30
3.3 Test results and discussion     30-36
3.3.1 test results     30
3.3.2 results     30-36
3.4 Summary     36-37
tetrazole staining test     37-51
4.1 tetrazol-staining method     37-39
4.1.1 Principles of     37
4.1.2 characteristics     37
4.1.3 The purpose and application     37-39
420 tetrazole staining test preparation     39-40
4.2.1 sample     39
4.2.2 preparation test     39
4.2.3 staining reagents tetrazole solution configuration     39-40
4.3 Test Method     40-43
4.3.1 Materials and equipment     40
4.3.2 Test procedure     40-43
4.4 Results and Discussion     43-50
4.4.1 test results     43-46
4.4.2 Results and discussion     46-50
4.5 Summary     50-51
the fifth chapter of the computer vision systems and digital image processing technology     51-62
5.1 computer vision technology and its application     51-54
5.1.1 computer vision technology     51-52
5.1.2 computer vision system components     52-53
5.1.3 Computer Vision applications     53-54
5.2 The topics in the computer vision system hardware components     54-56
5.3 digital image processing technology     56-61
5.3.1 image acquisition     57
5.3.2 image transformation     57-58
5.3.3 image enhancement     58-60
5.3.4 image segmentation     60
5.3.5 image recognition     60-61
5.4 Summary     61-62
using computer vision techniques to deal with the the tetrazole staining test results in the sixth chapter     62-83
6.1 image acquisition     62-64
6.1.1 image acquisition system parameter adjustment     62-63
6.1.2 tetrazol-stained image acquisition     63-64
6.2 Matlab language Introduction     64-67
6.2.1 Matlab language characteristics     64-65
6.2.2 Matlab6.5 GUI design     65-67
6.3 image processing     67-74
6.3.1 image to open and save     68
6.3.2 image preprocessing     68-71
6.3.3 Segmentation     71-73
6.3.4 the results of processing     73-74
6.4 results and compare     74-82
6.4.1 results     74-77
6.4.2 Comparison and analysis     77-82
6.5 Summary     82-83
Chapter VII Conclusion and Outlook     83-85
7.1 Conclusion     83-84
7.2 Looking     84-85
References     85-88
Acknowledgements     88

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