scholarly journals An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Test Using Image Processing, Curve Fitting and Clustering Method

2021 ◽  
Author(s):  
Damrongvudhi Onwimol ◽  
Wanwisa Phimcharoen ◽  
Parichat Sermwuthisarn ◽  
Sujittra Tejakhod ◽  
Tanapon Chaisan
Keyword(s):  
Image Processing ◽  
Curve Fitting ◽  
Direct Method ◽  
Indica Rice ◽  
Area Under The Curve ◽  
Dynamic Imaging ◽  
Seed Vigor ◽  
Rice Seed ◽  
Strong Negative Correlation ◽  
Radicle Emergence

Abstract Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The saturated salt accelerated aging (SSAA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from such a method are often imprecise. This paper presents the SV-RICE package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SV-RICE consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor has been classified based on radicle emergence indices, such as maximum radicle emergence (MRET), mean radicle emergence time (MaxRE), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strong negative correlation with the SSAA test. The germination time of 90 hours, at 25°C, was sufficient for effective classification based on SV-RICE, whereas the SSAA test takes approximately 400 hours to complete. The SV-RICE software algorithm was set up to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37%RH in hermetic bag). The study showed that SV-RICE could unambiguously classify 40 Indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared to the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SV-RICE package for automatic seed vigor classification of Oryza sativa seeds; however, it is likely applicable to other species as a viable alternative to current methods that require more time and are less precise.

scholarly journals An Automatic Method for Rice Seed Vigor Classification Via Radicle Emergence Testing Using Image-Processing, Curve-Fitting and Clustering Methods

2021 ◽  
Author(s):  
Damrongvudhi Onwimol ◽  
Parichat Sermwuthisarn ◽  
Wanwisa Phimcharoen ◽  
Tanapon Chaisan
Keyword(s):  
Image Processing ◽  
Curve Fitting ◽  
Direct Method ◽  
Indica Rice ◽  
Accelerated Aging ◽  
Dynamic Imaging ◽  
Seed Vigor ◽  
Rice Seed ◽  
Clustering Methods ◽  
Radicle Emergence

Abstract Background: Rice seed vigor classification is important for seed storage management by seed producers and by farmers while planning their cultivation activities. Field emergence is a direct method of seed vigor testing but is laborious, time-consuming and subjective. The accelerated aging (AA) test is often used as an indirect method for rice seed vigor classification in the laboratory. However, the results from this method are often imprecise. This paper presents the SVRice package, a simple, cost-efficient and flexible procedure that utilizes computer image analysis for high-throughput, automatic rice seed vigor classification. SVRice consists of 4 steps: dynamic imaging, image processing, curve fitting and clustering. Seed vigor was classified based on radicle emergence indices, such as maximum radicle emergence (MaxRE), mean radicle emergence time (MRET), radicle emergence speed (t50), uniformity of radicle emergence (U7525), and area under the curve of the radicle emergence fitted curve (AUC).Results: Parameters used to classify rice seed vigor, such as MRET, U7525 and t50, were strongly negatively correlated with the saturated salt accelerated aging (SSAA) test. A germination time of 90 hours at 25°C was sufficient for effective classification based on SVRice, whereas the SSAA test took approximately 400 hours to complete. The SVRice software algorithm was created to be especially suitable for assessment after 6 months under controlled atmosphere storage (at 15°C and 37% RH in a hermetic bag). The study showed that SVRice could unambiguously classify 40 indica rice samples with different varieties, production years, production sites, storage times and storage conditions compared with the SSAA test.Conclusions: This paper confirmed the accuracy, reproducibility and flexibility of the SVRice package for automatic seed vigor classification of Oryza sativa seeds; moreover, it is also likely applicable to other species as a viable alternative to current methods that require more time and are less precise.

scholarly journals UNRAVELLING DIABETIC RETINOPATHY THROUGH IMAGE PROCESSING, NEURAL NETWORKS AND FUZZY LOGIC – A REVIEW

2017 ◽  
Vol 10 (4) ◽  
pp. 32
Author(s):  
Srinivasan A ◽  
Sudha S
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Diabetic Retinopathy ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Computation Time ◽  
Automated System ◽  
Morphological Operations ◽  
Advanced Stage ◽  
Sensitivity Specificity

One of the main causes of blindness is diabetic retinopathy (DR) and it may affect people of any ages. In these days, both young and old ages are affected by diabetes, and the di abetes is the main cause of DR. Hence, it is necessary to have an automated system with good accuracy and less computation time to diagnose and treat DR, and the automated system can simplify the work of ophthalmologists. The objective is to present an overview of various works recently in detecting and segmenting the various lesions of DR. Papers were categorized based on the diagnosing tools and the methods used for detecting early and advanced stage lesions. The early lesions of DR are microaneurysms, hemorrhages, exudates, and cotton wool spots and in the advanced stage, new and fragile blood vessels can be grown. Results have been evaluated in terms of sensitivity, specificity, accuracy and receiver operating characteristic curve. This paper analyzed the various steps and different algorithms used recently for the detection and classification of DR lesions. A comparison of performances has been made in terms of sensitivity, specificity, area under the curve, and accuracy. Suggestions, future workand the area to be improved were also discussed.Keywords: Diabetic retinopathy, Image processing, Morphological operations, Neural network, Fuzzy logic. 

scholarly journals Survey of rice seed quality analysis for varietal purity estimation by using image processing techniques

2018 ◽  
Vol 7 (1.7) ◽  
pp. 34
Author(s):  
S. Durai ◽  
C. Mahesh ◽  
T. Sujithra ◽  
A. Suresh
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
South India ◽  
Seed Quality ◽  
Quality Analysis ◽  
Rice Seed ◽  
Two Factors ◽  
Computer Vision Technology ◽  
Processing Techniques ◽  
Varietal Purity

 In south India rice is the major food source and in agriculture, rice production covers more than 70 percentages of entire forming. But in recent the production only from south India not enough to satisfy the need of all, such a huge demand is there. The better production comes from the selection of good seeds. Up to now formers depend on two factors for selecting better seeds, One is the brand which is approved by some quality standards and second one is analyzed manually by experienced people. Both are risky one, we are not pretty much sure the accuracy of analyze. The second one is seeing and feeling. The inspection is not consistent also very time consuming. In the other way we can use computer vision technology to analyze the quality of the seeds. In recent years many of the big industries they are using computer vision technology with Digital Image Processing for many of the applications. In this Paper we are going to discuss the different seed quality analyzing methods and accuracy of result also. Moreover there are different factors and features are there for it, here we are going to study about varietal purity estimation by different methods.

scholarly journals Development of Liquid Enhancer for Germination of Drought-stressed Oryza sativa subsp. indica Seed cv. MR284

2019 ◽  
pp. 1-9 ◽  
Author(s):  
S. N. Mahadi ◽  
F. Zawawi ◽  
R. Nulit ◽  
M. H. Ibrahim ◽  
N. I. Ab. Ghani
Keyword(s):  
Oryza Sativa ◽  
Seed Germination ◽  
Germination Percentage ◽  
Leaf Length ◽  
Seed Vigor ◽  
Rice Seed ◽  
Combination Treatments ◽  
Randomized Design ◽  
Completely Randomized Design ◽  
Selection Of

Aim: This study was conducted to develop liquid enhancer containing KCl, TU, GA, and SA for germination of drought-stressed Oryza sativa subsp. indica cv. MR284 seed. Study Design: All experiments were conducted in a completely randomized design. Two steps were involved in the development process which are to select an ideal concentration for each KCl, TU, GA, and SA, and to find an ideal combination of chemicals from the selection of ideal concentrations acquired in step 1 to form liquid enhancer. There were 20 treatments for step 1 and 9 treatments for step 2. All of these treatments with 6 replicates. Place and Duration of Study: Department of Biology, Faculty of Science, University Putra Malaysia, between June 2018 and December 2018. Methodology: The sterilized rice seed cv. MR284 was stressed in the -1.2 Mpa PEG 6000 solution for three days and germinated in the KCl, TU, GA, and SA solution in a series of concentration for 10 days, in a controlled room. Seed germination was observed daily. Results: In the first step, drought-stressed rice seed showed the best germination performance in the 30 mM of KCl, 2.0 mM of TU, 0.24 mM GA, and 0.5 mM SA. Meanwhile, in the second step, the drought-stressed rice seed showed the best germination performance in the combination of 30 mM KCl + 2.0 mM TU + 0.24 mM GA + 0.5 mM SA. The best germination performance was evaluated by the highest germination percentage (%), germination index, seed vigor, leaf length, root length and biomass. Conclusion: Therefore, the combination treatments of 30 mM KCl + 2.0 mM TU + 0.5 mM SA was found to be the most effective and simplest liquid enhancer formula that has an ability to enhance seed germination of drought-stressed rice cv. MR284 seed.

scholarly journals Automated processing of thermal imaging to detect COVID-19

2020 ◽  
Author(s):  
Rafael Y. Brzezinski ◽  
Neta Rabin ◽  
Nir Lewis ◽  
Racheli Peled ◽  
Ariel Kerpel ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Income ◽  
Thermal Imaging ◽  
Point Of Care ◽  
Area Under The Curve ◽  
Screening Tools ◽  
Imaging Device ◽  
Thermal Images ◽  
Image Processing Algorithms ◽  
Processing Algorithms

ABSTRACTRapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on image-processing algorithms and machine learning analysis. We captured thermal images of the back of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in detecting COVID-19 with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. We show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.

scholarly journals Effects of Matric and Osmotic Priming Treatments on Broccoli Seed Germination

1996 ◽  
Vol 121 (3) ◽  
pp. 423-429 ◽  
Author(s):  
Lewis W. Jett ◽  
Gregory E. Welbaum ◽  
Ronald D. Morse
Keyword(s):  
Polyethylene Glycol ◽  
Seed Germination ◽  
Root Growth ◽  
Growth Rates ◽  
Germination Rate ◽  
Membrane Integrity ◽  
Seed Vigor ◽  
Radicle Emergence ◽  
The Mean ◽  
Peg 8000

Priming, a controlled-hydration treatment followed by redrying, improves the germination and emergence of seeds from many species. We compared osmotic and matric priming to determine which was the most effective treatment for improving broccoli seed germination and to gain a greater understanding of how seed vigor is enhanced by priming. Broccoli (Brassica oleracea L. var. italica) seeds were osmotically primed in polyethylene glycol (PEG 8000) at -1.1 MPa or matrically primed in a ratio of 1.0 g seed:0.8 g synthetic calcium silicate (Micro-Cel E):1.8 ml water at -1.2 MPa. In the laboratory, germination rates and root lengths were recorded from 5 to 42C and 10 to 35C, respectively. Broccoli seeds germinated poorly at >35C. Root growth after germination was more sensitive to temperatures >30C and <15C than radicle emergence. Matric and osmotic priming increased germination rate in the laboratory, greenhouse, and field. However, matric priming had a greater effect on germination and root growth rates from 15 to 30C. Neither priming treatment affected minimum or maximum germination or root growth temperatures. Both priming treatments decreased the mean thermal time for germination by >35%. The greater germination performance of matrically primed seeds was most likely the result of increased oxygen availability during priming, increased seed Ca content, or improved membrane integrity.

Effect of High Temperature Intermittent Drying on Rice Seed Viability and Vigor

2017 ◽  
Vol 13 (10) ◽  
Author(s):  
Pan Wang ◽  
Dong Li ◽  
Li-jun Wang ◽  
Benu Adhikari
Keyword(s):  
High Temperature ◽  
Ambient Temperature ◽  
Seed Viability ◽  
Seed Vigor ◽  
Drying Rate ◽  
Rice Seed ◽  
Rice Cultivars ◽  
Moisture Contents ◽  
Rice Seeds ◽  
Tempering Process

AbstractThis work aimed at determining whether high temperature intermittent drying followed by tempering at ambient temperature could preserve the seed viability and vigor.JaponicaandIndicarice seeds with 21.2 % and 22.6 % wet moisture contents (w.b.) were dried at 50 ºC and 60ºC for either 5, 10, 15 or 20 minutes, followed by tempering at 25ºC for 45 minutes. Each drying cycle was repeated until the rice seeds were dried to 12.0 % (w.b.). The drying rate was improved and the total in-dryer time was reduced in the intermittent drying when compared to continuous drying, due to the tempering process. The seed vigor was significantly reduced by intermittent drying at 60 °C with all exposure times, although the seed still kept the ability to germinate for both rice cultivars. The intermittent drying at 50 ºC for 5 minutes per drying cycle preserved the seed vigor ofJaponicarice well, while inIndicarice, the intermittent drying at 50 ºC up to 20 minutes could still be able to maintain the seed vigor.

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