Measuring Method for Solar Irradiance at Multi-points with Different Color Based on Image Analysis

Author(s):  
Kento Kawakami ◽  
Akiko Takahashi ◽  
Jun Imai ◽  
Shigeyuki Funabiki
2020 ◽  
pp. 49-52
Author(s):  
Trine Aabo Andersen

A new fast measuring method for process optimization of sucrose crystallization using image analysis based on high quality images and algorithms is introduced. With the mobile, non-invasive at-line system all steps of the sucrose crystallization can be measured to determine the crystal size distribution. The image analysis system is easy to operate and is as well an efficient laboratory solution with user-friendly and customized software. In comparison to sieve analysis, image analyses performed with the ParticleTech Solution have been proven to be reliable.


Author(s):  
Nazle E. Herrera-Carrillo ◽  
Michel Rivero ◽  
Emmanuel Gomez-Ramirez ◽  
Rodrigo Loera-Palomo

2020 ◽  
Vol 24 (2) ◽  
pp. 1-8
Author(s):  
Jan Thore Benthien ◽  
Sabrina Heldner ◽  
Benjamin Seppke ◽  
Jan Hörbelt

AbstractThe chaff quality or, more specifically, the distribution of stalk length after straw shredding during wheat harvest with a combined harvester is of significant interest for ploughless tillage practices. The currently applied characterization methods (manual length measurement or the cascade sieve analysis) are time-consuming and labour-intensive. Image analysis-based size characterization has the potential to solve these problems. In this study, two techniques of digital image processing, the well-known method of image moments (rectangular model) and a sub-pixel skeletonization approach (flow lines-tracing), were applied comparatively for stalk length measurement. Upon applying the rectangular model, the analyzed stalks were found to be longer than when the flow lines-tracing algorithm was applied. This was attributed to the unbiased decision criteria of the measuring method. A greater length of the stalk is to be expected in the main stalk than when the length of a twisted or branched stalk is measured from the edge length of a rectangular box that encloses it.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
A. N. Underhill ◽  
C. D. Hirsch ◽  
M. D. Clark

Grape berry color is an economically important trait that is controlled by two major genes influencing anthocyanin synthesis in the skin. Color is often described qualitatively using six major categories; however, this is a subjective rating that often fails to describe variation within these six classes. To investigate minor genes influencing berry color, image analysis was used to quantify berry color using different color spaces. An image analysis pipeline was developed and utilized to quantify color in a segregating hybrid wine grape population across two years. Images were collected from grape clusters immediately after harvest and segmented by color to determine the red, green, and blue (RGB); hue, saturation, and intensity (HSI); and lightness, red-green, and blue-yellow values (L∗a∗b∗) of berries. QTL analysis identified known major QTL for color on chromosome 2 along with several previously unreported smaller-effect QTL on chromosomes 1, 5, 6, 7, 10, 15, 18, and 19. This study demonstrated the ability of an image analysis phenotyping system to characterize berry color and to more effectively capture variability within a population and identify genetic regions of interest.


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