BioNMR
NMR aggregator & online community since 2003
BioNMR    
Learn or help to learn NMR - get free NMR books!
 

Go Back   BioNMR > Educational resources > Journal club
Advanced Search
Home Forums Wiki NMR feeds Downloads Register Today's Posts



Jobs Groups Conferences Literature Pulse sequences Software forums Programs Sample preps Web resources BioNMR issues


Webservers
NMR processing:
MDD
NMR assignment:
Backbone:
Autoassign
MARS
UNIO Match
PINE
Side-chains:
UNIO ATNOS-Ascan
NOEs:
UNIO ATNOS-Candid
UNIO Candid
ASDP
Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
XPLOR-NIH
ASDP
UNIO ATNOS-Candid
UNIO Candid
Fragment-based:
BMRB CS-Rosetta
Rosetta-NMR (Robetta)
Template-based:
GeNMR
I-TASSER
Refinement:
Amber
Structure from chemical shifts:
Fragment-based:
WeNMR CS-Rosetta
BMRB CS-Rosetta
Homology-based:
CS23D
Simshift
Torsion angles from chemical shifts:
Preditor
TALOS
Promega- Proline
Secondary structure from chemical shifts:
CSI (via RCI server)
TALOS
MICS caps, β-turns
d2D
PECAN
Flexibility from chemical shifts:
RCI
Interactions from chemical shifts:
HADDOCK
Chemical shifts re-referencing:
Shiftcor
UNIO Shiftinspector
LACS
CheckShift
RefDB
NMR model quality:
NOEs, other restraints:
PROSESS
PSVS
RPF scores
iCing
Chemical shifts:
PROSESS
CheShift2
Vasco
iCing
RDCs:
DC
Anisofit
Pseudocontact shifts:
Anisofit
Protein geomtery:
Resolution-by-Proxy
PROSESS
What-If
iCing
PSVS
MolProbity
SAVES2 or SAVES4
Vadar
Prosa
ProQ
MetaMQAPII
PSQS
Eval123D
STAN
Ramachandran Plot
Rampage
ERRAT
Verify_3D
Harmony
Quality Control Check
NMR spectrum prediction:
FANDAS
MestReS
V-NMR
Flexibility from structure:
Backbone S2
Methyl S2
B-factor
Molecular dynamics:
Gromacs
Amber
Antechamber
Chemical shifts prediction:
From structure:
Shiftx2
Sparta+
Camshift
CH3shift- Methyl
ArShift- Aromatic
ShiftS
Proshift
PPM
CheShift-2- Cα
From sequence:
Shifty
Camcoil
Poulsen_rc_CS
Disordered proteins:
MAXOCC
Format conversion & validation:
CCPN
From NMR-STAR 3.1
Validate NMR-STAR 3.1
NMR sample preparation:
Protein disorder:
DisMeta
Protein solubility:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


Reply
 
Thread Tools Search this Thread Rate Thread Display Modes
  #1  
Old 11-24-2010, 11:14 PM
nmrlearner's Avatar
Senior Member
 
Join Date: Jan 2005
Posts: 23,732
Points: 193,617, Level: 100
Points: 193,617, Level: 100 Points: 193,617, Level: 100 Points: 193,617, Level: 100
Level up: 0%, 0 Points needed
Level up: 0% Level up: 0% Level up: 0%
Activity: 50.7%
Activity: 50.7% Activity: 50.7% Activity: 50.7%
Last Achievements
Award-Showcase
NMR Credits: 0
NMR Points: 193,617
Downloads: 0
Uploads: 0
Default Correlation of porous and functional properties of food materials by NMR relaxometry

Correlation of porous and functional properties of food materials by NMR relaxometry and multivariate analysis.

Related Articles Correlation of porous and functional properties of food materials by NMR relaxometry and multivariate analysis.

Magn Reson Imaging. 2005 Feb;23(2):343-5

Authors: Haiduc AM, van Duynhoven J

The porous properties of food materials are known to determine important macroscopic parameters such as water-holding capacity and texture. In conventional approaches, understanding is built from a long process of establishing macrostructure-property relations in a rational manner. Only recently, multivariate approaches were introduced for the same purpose. The model systems used here are oil-in-water emulsions, stabilised by protein, and form complex structures, consisting of fat droplets dispersed in a porous protein phase. NMR time-domain decay curves were recorded for emulsions with varied levels of fat, protein and water. Hardness, dry matter content and water drainage were determined by classical means and analysed for correlation with the NMR data with multivariate techniques. Partial least squares can calibrate and predict these properties directly from the continuous NMR exponential decays and yields regression coefficients higher than 82%. However, the calibration coefficients themselves belong to the continuous exponential domain and do little to explain the connection between NMR data and emulsion properties. Transformation of the NMR decays into a discreet domain with non-negative least squares permits the use of multilinear regression (MLR) on the resulting amplitudes as predictors and hardness or water drainage as responses. The MLR coefficients show that hardness is highly correlated with the components that have T2 distributions of about 20 and 200 ms whereas water drainage is correlated with components that have T2 distributions around 400 and 1800 ms. These T2 distributions very likely correlate with water populations present in pores with different sizes and/or wall mobility. The results for the emulsions studied demonstrate that NMR time-domain decays can be employed to predict properties and to provide insight in the underlying microstructural features.

PMID: 15833642 [PubMed - indexed for MEDLINE]



Source: PubMed
Reply With Quote


Did you find this post helpful? Yes | No

Reply
Similar Threads
Thread Thread Starter Forum Replies Last Post
A Slowly Relaxing RigidBiradical for Efficient DynamicNuclear Polarization Surface-Enhanced NMR Spectroscopy: ExpeditiousCharacterization of Functional Group Manipulation in Hybrid Materials
A Slowly Relaxing RigidBiradical for Efficient DynamicNuclear Polarization Surface-Enhanced NMR Spectroscopy: ExpeditiousCharacterization of Functional Group Manipulation in Hybrid Materials Alexandre Zagdoun, Gilles Casano, Olivier Ouari, Giuseppe Lapadula, Aaron J. Rossini, Moreno Lelli, Mathieu Baffert, David Gajan, Laurent Veyre, Werner E. Maas, Melanie Rosay, Ralph T. Weber, Chloe? Thieuleux, Christophe Coperet, Anne Lesage, Paul Tordo and Lyndon Emsley ...
nmrlearner Journal club 0 01-18-2012 03:07 AM
Visualizing the principal component of 1H,15N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C
Visualizing the principal component of 1H,15N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C Abstract Laboratories often repeatedly determine the structure of a given protein under a variety of conditions, mutations, modifications, or in a number of states. This approach can be cumbersome and tedious. Given then a database of structures, identifiers, and corresponding 1H,15N-HSQC NMR spectra for homologous proteins, we investigated whether structural information could be ascertained for a new homolog solely from its...
nmrlearner Journal club 0 09-30-2011 08:01 PM
Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C.
Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C. Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C. J Biomol NMR. 2011 Sep;51(1-2):115-22 Authors: Robertson IM, Boyko RF, Sykes BD Abstract Laboratories often repeatedly determine the structure of a given protein under a variety of conditions,...
nmrlearner Journal club 0 09-30-2011 06:00 AM
Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C.
Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C. Visualizing the principal component of (1)H, (15)N-HSQC NMR spectral changes that reflect protein structural or functional properties: application to troponin C. J Biomol NMR. 2011 Sep;51(1-2):115-22 Authors: Robertson IM, Boyko RF, Sykes BD Abstract Laboratories often repeatedly determine the structure of a given protein under a variety of conditions,...
nmrlearner Journal club 0 09-30-2011 05:59 AM
[NMR tweet] Multinuclear Solid-State Nuclear Magnetic Resonance of Inorganic Materials, Volume 6 (Pergamon Materials Series): http://amzn.to/kSPkSn
Multinuclear Solid-State Nuclear Magnetic Resonance of Inorganic Materials, Volume 6 (Pergamon Materials Series): http://amzn.to/kSPkSn Published by Carolazkl (Carola Dundlow) on 2011-05-22T01:28:17Z Source: Twitter
nmrlearner Twitter NMR 0 05-22-2011 01:54 AM
[NMR tweet] Multinuclear Solid-State Nuclear Magnetic Resonance of Inorganic Materials, Volume 6 (Pergamon Materials Series): http://amzn.to/ewA2OW
Multinuclear Solid-State Nuclear Magnetic Resonance of Inorganic Materials, Volume 6 (Pergamon Materials Series): http://amzn.to/ewA2OW Published by Simonago63 (Simona Likes) on 2011-04-25T19:18:52Z Source: Twitter
nmrlearner Twitter NMR 0 04-25-2011 07:21 PM



Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is On
Trackbacks are Off
Pingbacks are Off
Refbacks are Off



BioNMR advertisements to pay for website hosting and domain registration. Nobody does it for us.



Powered by vBulletin® Version 3.7.3
Copyright ©2000 - 2024, Jelsoft Enterprises Ltd.
Copyright, BioNMR.com, 2003-2013
Search Engine Friendly URLs by vBSEO 3.6.0

All times are GMT. The time now is 09:21 PM.


Map