Predicting Wheat Quality Characteristics and Functionality Using Near-Infrared Spectroscopy

2006 ◽  
Vol 83 (5) ◽  
pp. 529-536 ◽  
Author(s):  
F. E. Dowell ◽  
E. B. Maghirang ◽  
F. Xie ◽  
G. L. Lookhart ◽  
R. O. Pierce ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Characteristics ◽  
Wheat Quality

scholarly journals Development of near-infrared spectroscopy calibrations to measure quality characteristics in intact Brassicaceae germplasm

2016 ◽  
Vol 89 ◽  
pp. 52-58 ◽  
Author(s):  
Emily A. Oblath ◽  
Terry A. Isbell ◽  
Mark A. Berhow ◽  
Brett Allen ◽  
David Archer ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Characteristics

Prediction of wheat quality parameters using near-infrared spectroscopy and artificial neural networks

2011 ◽  
Vol 233 (2) ◽  
pp. 267-274 ◽  
Author(s):  
Ayse C. Mutlu ◽  
Ismail Hakki Boyaci ◽  
Huseyin E. Genis ◽  
Rahime Ozturk ◽  
Nese Basaran-Akgul ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Parameters ◽  
Wheat Quality ◽  
Artificial Neural

scholarly journals New possibilities to determine wheat quality parameters by near-infrared spectroscopy

2010 ◽  
pp. 65-69
Author(s):  
Éva Kónya ◽  
Zoltán Győri
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Parameters ◽  
Wheat Quality ◽  
Falling Number ◽  
Flour Quality ◽  
Time Work ◽  
Sample Time

Analyses and methods in wheat quality determination require more sample, time, work and cost, thatswhy flour quality control needs rapid, reliable tools. Near-infrared spectroscopy has many advantages, which make it suitable in quality control. NIR instruments need calibrations to their work. In our study we examined gluten content, falling number, valorigrpahic waterabsorption, alveographic P/L and W value of wheat samples. Modified partial least squares analyses on NIR spectra were developed for each property. The results show that we got such calibration modells, which are able to predict the properties (expect falling number) with enough accuracy.

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