Development of a Digital Analysis System to Evaluate Peanut Maturity

B. C. Colvin; D. L. Rowland; J. A. Ferrell; W. H. Faircloth

doi:10.3146/ps13-9.1

Development of a Digital Analysis System to Evaluate Peanut Maturity

Peanut Science ◽

10.3146/ps13-9.1 ◽

2014 ◽

Vol 41 (1) ◽

pp. 8-16 ◽

Cited By ~ 7

Author(s):

B. C. Colvin ◽

D. L. Rowland ◽

J. A. Ferrell ◽

W. H. Faircloth

Keyword(s):

Imaging System ◽

Extension Agents ◽

Current Profile ◽

Color Classification ◽

Color Class ◽

Scanned Image ◽

Overall Performance ◽

Pixel Color ◽

Analysis System

ABSTRACT The profile color class method developed by Williams and Drexler in 1981 for the prediction of peanut harvest has proven to be a relative description of peanut maturity and is currently used by growers. However, the method requires the subjective visual classification of pods based on the development of color in the mesocarp layer of the hull which naturally introduces variability and possible error in maturity prediction based solely on observer bias. A Digital Image Model (DIM) was developed to eliminate subjectivity in pod color classification. The DIM is a method in which a scanned image of pod mesocarp colors is analyzed using a color definition algorithm. The final output of the DIM is a ratio of pixel color classes. To develop the DIM, replicated plots were established in Florida in 2010 and 2011 and sequentially harvested starting at 120 days after planting (DAP) and then progressing at wk intervals through 155 DAP. At harvest, yield and grade were evaluated for each plot and pod samples were collected for color classification by a single observer using the current profile board method. These same pod samples were then imaged and analyzed with the DIM method. The percentage of black and brown pods (mature pods) classified by the profile board and the DIM method were evaluated to determine the overall performance of the DIM in comparison to the profile board. The DIM method was successful in predicting the percentage of black and brown pods similarly to the profile board in both years with R2 0.63 to 0.82 with images acquired from the saddle region of the pod. There was more variability in matching the DIM prediction to the profile board when imaging pods from random regions, with R2 0.19 to 0.82. The goal of this research was to develop an imaging system that could be accessed by growers, consultants, and extension agents for objective analysis and prediction of peanut maturity.

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Enhanced concept-level sentiment analysis system with expanded ontological relations for efficient classification of user reviews

Egyptian Informatics Journal ◽

10.1016/j.eij.2021.03.001 ◽

2021 ◽

Author(s):

Asad Khattak ◽

Muhammad Zubair Asghar ◽

Zain Ishaq ◽

Waqas Haider Bangyal ◽

Ibrahim A Hameed

Keyword(s):

Sentiment Analysis ◽

User Reviews ◽

Analysis System

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A knowledge-management based process analysis system design through the classification of analysis parameters

International Journal of Precision Engineering and Manufacturing ◽

10.1007/s12541-012-0186-0 ◽

2012 ◽

Vol 13 (8) ◽

pp. 1419-1424 ◽

Cited By ~ 5

Author(s):

Sang-Hwa Lee ◽

Soo-Hong Lee

Keyword(s):

Knowledge Management ◽

System Design ◽

Process Analysis ◽

Analysis System

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Simultaneous Feulgen densitometry and autoradiographic grain counting with the Quantimet 720D image-analysis system. III. Improvements in Feulgen densitometry.

Journal of Histochemistry & Cytochemistry ◽

10.1177/31.10.6886380 ◽

1983 ◽

Vol 31 (10) ◽

pp. 1224-1232 ◽

Cited By ~ 12

Author(s):

R J Sklarew

Keyword(s):

Image Analysis ◽

Imaging System ◽

Rat Kidney ◽

Light Sources ◽

Kidney Cells ◽

Image Analysis System ◽

Replication Error ◽

Feulgen Densitometry ◽

Optical Configuration ◽

Analysis System

A method has been developed for densitometric estimation of the Feulgen-stained DNA content of 3H-labeled nuclei in autoradiographs in conjunction with automated grain counting using a Quantimet Imaging System. Refinements in the methodology are reported which include 1) the incorporation of an Image-Editor Module into the Quantimet module configuration; 2) the optimization of incident illumination based upon evaluation of various light sources; 3) changes in the optical configuration which reduce glare and minimize the level of monitor shading correction; 4) the optimization of scanner sensitivity; and 5) the evaluation of cell-flattening and staining with respect to densitometry resolution and sensitivity. These refinements resulted in a CV of less than 6.4% in the G-1 and G-2 DNA peaks of rat kidney cells in autoradiographs compared to the previous CV of 10.5%, and a G-2 to G-1 ratio of 2.025. For a fixed field position the CV was 5.1% and the replication error less than 1.0%.

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An Application and Research of Gray-Relation for Color Classification in Dyeing Textile

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.694-697.2881 ◽

2013 ◽

Vol 694-697 ◽

pp. 2881-2885

Author(s):

Hai Yan Wang ◽

Jian Xin Zhang

Keyword(s):

System Analysis ◽

High Efficiency ◽

Information Management System ◽

Space Distribution ◽

Color Classification ◽

Uniform Sampling ◽

Forecast Precision ◽

Internal Instability ◽

The Stability

Dyeing textile’s information management system is the basis of accurate classification of color， machine studying methods have became a popular area of research for application in color classification. Traditional classification methods have high efficiency and are very simple ， but they are dependent on the distribution of sample spaces. If the sample data properties are not independent， forecast precision will been affected badly and internal instability will appear. An application of Gray-Relation for dyeing textile color classification has been designed， which offsets the discount in mathematical statistics method for system analysis. It is applicable regardless of variant in sample size， while quantizing structure is in agreement with qualitative analysis. On the basis of theoretical analysis， Dyeing textile color classification was conducted in the conditions of random sampling、 uniform sampling and stratified sampling. The experimental results proofs that by using Gray-Relation， dyeing textile color classification does not need to be dependent on sample space distribution， and increases the stability of classification.

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Analysis of the coefficient of variation in shear and tensile bond strength tests

Journal of Applied Oral Science ◽

10.1590/s1678-77572005000300008 ◽

2005 ◽

Vol 13 (3) ◽

pp. 243-246 ◽

Cited By ~ 14

Author(s):

Fábio Lourenço Romano ◽

Gláucia Maria Bovi Ambrosano ◽

Maria Beatriz Borges de Araújo Magnani ◽

Darcy Flávio Nouer

Keyword(s):

Coefficient Of Variation ◽

Mean Value ◽

Scientific Article ◽

A Value ◽

Statistical Analysis System ◽

Strength Tests ◽

Analysis System ◽

Very High

The coefficient of variation is a dispersion measurement that does not depend on the unit scales, thus allowing the comparison of experimental results involving different variables. Its calculation is crucial for the adhesive experiments performed in laboratories because both precision and reliability can be verified. The aim of this study was to evaluate and to suggest a classification of the coefficient variation (CV) for in vitro experiments on shear and tensile strengths. The experiments were performed in laboratory by fifty international and national studies on adhesion materials. Statistical data allowing the estimation of the coefficient of variation was gathered from each scientific article since none of them had such a measurement previously calculated. Excel worksheet was used for organizing the data while the sample normality was tested by using Shapiro Wilk tests (alpha = 0.05) and the Statistical Analysis System software (SAS). A mean value of 6.11 (SD = 1.83) for the coefficient of variation was found by the data analysis and the data had a normal distribution (p>0.05). A range classification was proposed for the coefficient of variation from such data, that is, it should be considered low for a value lesser than 2.44; intermediate for a value between 2.44 and 7.94, high for a value between 7.94 and 9.78, and finally, very high for a value greater than 9.78. Such classification can be used as a guide for experiments on adhesion materials, thus making the planning easier as well as revealing precision and validity concerning the data.

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Classification of Personnel Procedures in the National Police of Ukraine

Revista Amazonia Investiga ◽

10.34069/ai/2020.28.04.12 ◽

2020 ◽

Vol 9 (28) ◽

pp. 100-107

Author(s):

Khrystyna Volodymyrivna Solntseva ◽

Oleksandr Mykolaiovych Kurakin ◽

Alina Rashydivna Chanysheva ◽

Andrii Oleksiovych Sobakar

Keyword(s):

Negative Impact ◽

Highly Qualified ◽

Effective Work ◽

Law Enforcement Agency ◽

Police Personnel ◽

The Subject ◽

Analysis System ◽

National Police ◽

Selection Of

The purpose of the article is to explore the types of personnel procedures in the National Police of Ukraine on the basis of scientific developments of scholars and to carry out their classification. To achieve this goal, such methods as formal-logical, comparative analysis, system-structural and comparative-legal was used. The successful functioning the National Police of Ukraine is not possible without the proper selection of highly qualified employees, which can be ensured through the introduction of truly effective and efficient personnel procedures. The theoretical and legal approaches to the division of personnel procedures into appropriate types by different classification criteria are analyzed and summarized, in particular, depending on: a) the subject of the initiative; b) the nature of the consequences; c) the type (direction) of the activity of the authority. The personnel procedures, which are divided into ordinary and simplified, are also illustrated. The tasks of the National Police Personnel Department are given. It is stated that the achievement of effective work of the National Police bodies is not possible without further improvement of the mechanism of personnel procedures, since insufficient work with staff has a negative impact on the reform of this law enforcement agency. As a result of the study the author's classification of personnel procedures in the National Police of Ukraine was proposed, namely, according to the following criteria: 1) by the subject of the initiative of the personnel procedure; 2) by the nature of the consequences for the subject of the personnel relations; 3) by the stage of staffing; 4) by the direction of activity of the subject of personnel relations in the police force; 5) by the degree of regulation; 6) by functional purpose; 7) by tasks of staffing.

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Advances in the Application of the Dual Fluoroscopic Imaging System in Sports Medicine: A Literature Review

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2021.3579 ◽

2021 ◽

Vol 11 (8) ◽

pp. 2067-2076

Author(s):

Cui Zhang ◽

Xiaole Sun ◽

Yunqi Tang ◽

Shaobai Wang ◽

Dongqiang Ye ◽

...

Keyword(s):

Sports Medicine ◽

Soft Tissues ◽

Imaging System ◽

Relevant Literature ◽

Test Results ◽

Non Invasive ◽

Ligament Strain ◽

Fluoroscopic Imaging ◽

Analysis System ◽

Six Degree Of Freedom

The dual fluoroscopic imaging system (DFIS) is a new non-invasive motion analysis system that does not interfere with movement, has high precision and repeatability and is not affected by the errors caused by the relative movement of skin and soft tissues. DFIS has been recently used in the field of sports medicine. This narrative review focuses on relevant literature on the origin, development and mechanism of action of DFIS and summarises the application of DFIS in injury and rehabilitation treatment, such as the reliability of test results; the position relationships of bony structures in the shoulder, lumbar spine, knee joint and ankle joint during exercise and its six degree-of-freedom (6DOF) movement to calculate cartilage deformation, contact area/trajectory and ligament strain. This article puts forward the problems encountered in practice that need to be solved and looks forward to the future applications of DFIS in the field of sports, especially in injury prevention and treatment.

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Hyperspectral Imaging Using Laser Excitation for Fast Raman and Fluorescence Hyperspectral Imaging for Sorting and Quality Control Applications

Journal of Imaging ◽

10.3390/jimaging4100110 ◽

2018 ◽

Vol 4 (10) ◽

pp. 110 ◽

Cited By ~ 4

Author(s):

Florian Gruber ◽

Philipp Wollmann ◽

Wulf Grählert ◽

Stefan Kaskel

Keyword(s):

Quality Control ◽

Hyperspectral Imaging ◽

Lead Zirconate Titanate ◽

Imaging System ◽

Measurement Data ◽

Machine Learning Algorithms ◽

Area Measurement ◽

Large Area ◽

Sorting Tasks

A hyperspectral measurement system for the fast and large area measurement of Raman and fluorescence signals was developed, characterized and tested. This laser hyperspectral imaging system (Laser-HSI) can be used for sorting tasks and for continuous quality monitoring. The system uses a 532 nm Nd:YAG laser and a standard pushbroom HSI camera. Depending on the lens selected, it is possible to cover large areas (e.g., field of view (FOV) = 386 mm) or to achieve high spatial resolutions (e.g., 0.02 mm). The developed Laser-HSI was used for four exemplary experiments: (a) the measurement and classification of a mixture of sulphur and naphthalene; (b) the measurement of carotenoid distribution in a carrot slice; (c) the classification of black polymer particles; and, (d) the localization of impurities on a lead zirconate titanate (PZT) piezoelectric actuator. It could be shown that the measurement data obtained were in good agreement with reference measurements taken with a high-resolution Raman microscope. Furthermore, the suitability of the measurements for classification using machine learning algorithms was also demonstrated. The developed Laser-HSI could be used in the future for complex quality control or sorting tasks where conventional HSI systems fail.

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Comparison of color indexes for tomato ripening

Horticultura Brasileira ◽

10.1590/s0102-05362004000300006 ◽

2004 ◽

Vol 22 (3) ◽

pp. 534-537 ◽

Cited By ~ 144

Author(s):

Andrés F. López Camelo ◽

Perla A. Gómez

Keyword(s):

Color Index ◽

Human Perception ◽

Color Difference ◽

Color Classification ◽

Color Changes ◽

Color Categories ◽

Visual Color ◽

Postharvest Life ◽

Range Of Values

Color in tomato is the most important external characteristic to assess ripeness and postharvest life, and is a major factor in the consumer's purchase decision. Degree of ripening is usually estimated by color charts. Colorimeters, on the other hand, express colors in numerical terms along the L*, a* and b* axes (from white to black, green to red and blue to yellow, respectively) within the CIELAB color sphere which are usually mathematically combined to calculate the color indexes. Color indexes and their relationship to the visual color classification of tomato fruits vine ripened were compared. L*, a* and b* data (175 observations from eleven cultivars) from visually classified fruits at harvest in six ripening stages according to the USDA were used to calculate hue, chroma, color index, color difference with pure red, a*/b* and (a*/b*)². ANOVA analysis were performed and means compared by Duncan's MRT. Color changes throughout tomato ripening were the result of significant changes in the values of L*, a* and b*. Under the conditions of this study, hue, color index, color difference and a*/b* expressed essentially the same, and the color categories were significantly different in terms of human perception, with hue showing higher range of values. Chroma was not a good parameter to express tomato ripeness, but could be used as a good indicator of consumer acceptance when tomatoes are fully ripened. The (a*/b*)² relationship had the same limitations as chroma. For vine ripened fruits, hue, color index, color difference and a*/b* could be used as objective ripening indexes. It would be interesting to find out what the best index would be if ripening took place under inadequate conditions of temperature and ilumination.

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