scholarly journals Distribution of root system of hop plants in hop gardens with regular rows cultivation

2020 ◽  
Vol 66 (No. 7) ◽  
pp. 317-326
Author(s):  
Vaclav Brant ◽  
Karel Krofta ◽  
Milan Kroulík ◽  
Petr Zábransky ◽  
Pavel Prochazka ◽  
...  
Keyword(s):  
Image Analysis ◽  
Root System ◽  
Soil Profile ◽  
Infrared Image ◽  
Root Systems ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Soil Layers ◽  
Humulus Lupulus L ◽  
Lateral Width

Spatial distribution of the root system of hop (Humulus lupulus L.) in the soil profile is a less explored issue. However, it is known that it can play an important role in the development of new tillage technologies, fertilisation and irrigation, including the use of precision farming principles. In the period from 2015 to 2018, the distribution of the hop root system was evaluated on twelve hop plants of five Czech hop cultivars. The age of the plants ranged from 3 to 15 years. The evaluation took place in the Saaz region at regularly cultivated hop gardens. As part of the evaluation, the root systems of hop plants were removed from the soil profile and subsequently spatially reconstructed. With the help of infrared image analysis, the root intensity in the soil profile and the morphology of the root systems were determined. The root depth of the plants ranged from 1 m to 2.25 m. The lateral width of the hop root system ranged from 0.6 m to 1.5 m. As a result of the rows cultivation, the lateral development of the roots in the upper soil layers was limited. The results were confirmed using the infrared image analysis method to specify the distribution of the root system and the root density of hop plants in the soil profile.  

scholarly journals Automated image analysis method for oil-release test of lipid-based materials

MethodsX ◽  
2021 ◽  
pp. 101447
Author(s):  
Fabio Valoppi ◽  
Petri Lassila ◽  
Ari Salmi ◽  
Edward Haeggström
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Release Test

A Computerized Image Analysis Method for Measuring Elastic Tissue.

1989 ◽  
Vol 93 (3) ◽  
pp. 358-362 ◽  
Author(s):  
Thomas J. Flotte ◽  
Johanna M. Seddon ◽  
Yuqing Zhang ◽  
Robert J. Glynn ◽  
Kathleen M. Egan ◽  
...  
Keyword(s):  
Image Analysis ◽  
Elastic Tissue ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Computerized Image Analysis

ASSESSMENT OF OSTEOARTHRITIS INITIATIVE–KELLGREN AND LAWRENCE SCORING PROJECTS QUALITY USING COMPUTER ANALYSIS

2010 ◽  
Vol 13 (04) ◽  
pp. 197-201 ◽  
Author(s):  
Lior Shamir ◽  
David T. Felson ◽  
Luigi Ferrucci ◽  
Ilya G. Goldberg
Keyword(s):  
Image Analysis ◽  
Gold Standard ◽  
Population Studies ◽  
Detection Accuracy ◽  
X Rays ◽  
Analysis Method ◽  
Image Analysis Method ◽  
X Ray ◽  
Osteoarthritis Initiative ◽  
Kellgren And Lawrence

The detection of knee osteoarthritis (OA) is a subjective task, and even two highly experienced and well-trained readers might not always agree on a specific case. This problem is noticeable in OA population studies, in which different scoring projects provide significantly different scores for the same knee X-rays. Here we propose a method for quantitative assessment and comparison of knee X-ray scoring projects in OA population studies. The method works by applying an image analysis method that automatically detects OA in knee X-ray images, and comparing the consistency of the scores when using each of the scoring projects as "gold standard." The method was applied to compare the osteoarthritis initiative (OAI) clinic reading derived Kellgren and Lawrence (K&L) scores to central reading, and showed that when using the derived K&L scores the automatic image analysis method was able to accurately differentiate between healthy joints and moderate OA joints in ~70% of the cases. When the OAI central reading scores were used as gold standard, the detection accuracy was elevated to ~77%. These results show that the OAI central readings scores are more consistent with the X-rays, indicating that the central reading better reflects the radiographic features associated with OA, compared to the OAI K&L scores derived from clinic readings.

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