Near-infrared Spectroscopy Based Arthroscopic Evaluation of Human Knee Joint Cartilage, Through Automated Selection of an Anatomically Specific Regression Model

2018 ◽  
Author(s):  
Mithilesh Prakash ◽  
Antti Joukainen ◽  
Jaakko K. Sarin ◽  
Lassi Rieppo ◽  
Isaac O. Afara ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Knee Joint ◽  
Regression Model ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Joint Cartilage ◽  
Human Knee ◽  
Arthroscopic Evaluation ◽  
Human Knee Joint ◽  
Selection Of

scholarly journals Selection of optimal conversion path for willow biomass assisted by near infrared spectroscopy

2017 ◽  
Vol 10 (2) ◽  
pp. 506-514 ◽  
Author(s):  
A Sandak ◽  
J Sandak ◽  
B Waliszewska ◽  
M Zborowska ◽  
M Mleczek
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Selection Of

scholarly journals Detection of ventilatory thresholds using near-infrared spectroscopy with a polynomial regression model

2020 ◽  
Vol 27 (6) ◽  
pp. 1637-1642
Author(s):  
Chih-Wei Lin ◽  
Chun-Feng Huang ◽  
Jong-Shyan Wang ◽  
Li-Lan Fu ◽  
Tso-Yen Mao
Keyword(s):  
Infrared Spectroscopy ◽  
Regression Model ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Polynomial Regression ◽  
Polynomial Regression Model

Global regression model for moisture content determination using near-infrared spectroscopy

2017 ◽  
Vol 119 ◽  
pp. 343-352 ◽  
Author(s):  
Matthieu Clavaud ◽  
Yves Roggo ◽  
Klara Dégardin ◽  
Pierre-Yves Sacré ◽  
Philippe Hubert ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Moisture Content ◽  
Regression Model ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Content Determination ◽  
Global Regression ◽  
Moisture Content Determination

A novel DPSO-SVM system for variable interval selection of endometrial tissue sections by near infrared spectroscopy

Talanta ◽  
2013 ◽  
Vol 112 ◽  
pp. 136-142 ◽  
Author(s):  
Guiyun Wang ◽  
Mingyu Ma ◽  
Zhuoyong Zhang ◽  
Yuhong Xiang ◽  
Peter de B. Harrington
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Variable Interval ◽  
Endometrial Tissue ◽  
Tissue Sections ◽  
Interval Selection ◽  
Selection Of

scholarly journals Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum).

2020 ◽  
Author(s):  
Gokhan Hacisalihoglu ◽  
Jelani Freeman ◽  
Paul R. Armstrong ◽  
Brad W. Seabourn ◽  
Lyndon D. Porter ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Pisum Sativum ◽  
Protein Content ◽  
Near Infrared Spectroscopy ◽  
Seed Weight ◽  
Oil Content ◽  
Near Infrared ◽  
Seed Quality ◽  
Single Seed ◽  
Selection Of

Abstract Background: Pea (Pisum sativum) is a prevalent cool season crop that produces seeds valued for high protein content. Modern cultivars have incorporated several traits that improved harvested yield. However, progress toward improving seed quality has received less emphasis, in part due to the lack of tools for easily and rapidly measuring seed traits. In this study we evaluated the accuracy of single-seed near-infrared spectroscopy (NIRS) for measuring pea seed weight, protein, and oil content. A total of 96 diverse pea accessions were analyzed using both single-seed NIRS and wet chemistry methods. To demonstrate field relevance, the single-seed NIRS protein prediction model was used to determine the impact of seed treatments and foliar fungicides on protein content of harvested dry peas in a field trial. Results: External validation of Partial Least Squares (PLS) regression models showed high prediction accuracy for protein and weight (R2 = 0.94 for both) and less accuracy for oil (R2 = 0.75). Single seed weight was not significantly correlated with protein or oil content in contrast to previous reports. In the field study, the single-seed NIRS predicted protein values were within 1% of an independent analytical reference measurement and were sufficiently precise to detect small treatment effects. Conclusion: The high accuracy of protein and weight estimation show that single-seed NIRS could be used in the dual selection of high protein, high weight peas early in the breeding cycle allowing for faster genetic advancement toward improved pea nutritional quality.

scholarly journals Expression profiles of two types of human knee-joint cartilage

2003 ◽  
Vol 48 (4) ◽  
pp. 177-182 ◽  
Author(s):  
Kensuke Ochi ◽  
Yataro Daigo ◽  
Toyomasa Katagiri ◽  
Akihiko Saito-Hisaminato ◽  
Tatsuhiko Tsunoda ◽  
...  
Keyword(s):  
Knee Joint ◽  
Expression Profiles ◽  
Joint Cartilage ◽  
Human Knee ◽  
Human Knee Joint
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