These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Prediction chemical composition and alveograph parameters on wheat by near-infrared transmittance spectroscopy.
    Author: Miralbés C.
    Journal: J Agric Food Chem; 2003 Oct 08; 51(21):6335-9. PubMed ID: 14518964.
    Abstract:
    Moisture, protein, wet gluten, dry gluten, and alveograph parameters (W, P, and P/L) of whole wheat grown in different countries around the world were analyzed using near infrared (NIR) transmittance spectroscopy. Modified partial least squares on NIR spectra (850-1048.2 nm) were developed for each constituent or physical property. The best models were obtained for protein, moisture, wet gluten, and dry gluten with r(2) = 0.99, 0.99, 0.95, and 0.96, respectively. Initial alveograph NIR models proposed for all wheat samples did not perform well. However, when wheat samples were divided in two groups depending on W (deformation energy) values, NIR models were highly improved, showing enough prediction accuracy for screening wheat at the receiving stage at mills or elevators.
    [Abstract] [Full Text] [Related] [New Search]