The Development of near Infrared Wheat Quality Models by Locally Weighted Regressions

2000 ◽  
Vol 8 (3) ◽  
pp. 201-208 ◽  
Author(s):  
F.E. Barton ◽  
J.S. Shenk ◽  
M.O. Westerhaus ◽  
D.B. Funk
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yan-Ge Tian ◽  
Zheng-Nan Zhang ◽  
Shuang-Qi Tian

Nondestructive testing with sensor technology is one of the fastest growing and most promising wheat quality information analysis technologies. Nondestructive testing with sensor technology benefits from the latest achievement of many disciplines such as computer, optics, mathematics, chemistry, and chemometrics. It has the advantages of simplicity, speed, low cost, no pollution, and no contact. It is widely used in wheat quality analysis and testing research. This article summarizes nondestructive testing with sensor technology for wheat quality, including the mechanical model, hyperspectral technology, Raman spectroscopy, and near-infrared techniques for wheat mechanical properties, storage properties, and physical and chemical properties (such as moisture, ash, protein, and starch) in the past decade. Based on the current research progress, big data technology needs a lot of research in spectral data mining, modeling algorithm optimization, model robustness, etc. to provide more data support and method reference for the research and application of wheat quality.


2011 ◽  
Vol 233 (2) ◽  
pp. 267-274 ◽  
Author(s):  
Ayse C. Mutlu ◽  
Ismail Hakki Boyaci ◽  
Huseyin E. Genis ◽  
Rahime Ozturk ◽  
Nese Basaran-Akgul ◽  
...  

2010 ◽  
pp. 65-69
Author(s):  
Éva Kónya ◽  
Zoltán Győri

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.


2018 ◽  
Vol 4 (2) ◽  
Author(s):  
Shahid Yousaf ◽  
Salman Khurshid ◽  
Saqib Arif ◽  
Hafiza Mehwish Iqbal ◽  
Qurrat ul Ain Akbar ◽  
...  

2006 ◽  
Vol 83 (5) ◽  
pp. 529-536 ◽  
Author(s):  
F. E. Dowell ◽  
E. B. Maghirang ◽  
F. Xie ◽  
G. L. Lookhart ◽  
R. O. Pierce ◽  
...  

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