114 related articles for article (PubMed ID: 26072581)
1. Novel, non-destructive cereal quality analysis: potential for triticale.
Manley M
Commun Agric Appl Biol Sci; 2014; 79(4):129-38. PubMed ID: 26072581
[TBL] [Abstract][Full Text] [Related]
2. Near infrared hyperspectral imaging in quality and safety evaluation of cereals.
Sendin K; Williams PJ; Manley M
Crit Rev Food Sci Nutr; 2018 Mar; 58(4):575-590. PubMed ID: 27622307
[TBL] [Abstract][Full Text] [Related]
3. Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials.
Manley M
Chem Soc Rev; 2014 Dec; 43(24):8200-14. PubMed ID: 25156745
[TBL] [Abstract][Full Text] [Related]
4. Applications of single kernel conventional and hyperspectral imaging near infrared spectroscopy in cereals.
Fox G; Manley M
J Sci Food Agric; 2014 Jan; 94(2):174-9. PubMed ID: 24038031
[TBL] [Abstract][Full Text] [Related]
5. Triticale adaption and competence assessment result in the high lands of Ethiopia.
Legesse W
Commun Agric Appl Biol Sci; 2014; 79(4):54-61. PubMed ID: 26072574
[TBL] [Abstract][Full Text] [Related]
6. Influence of grain topography on near infrared hyperspectral images.
Manley M; McGoverin CM; Engelbrecht P; Geladi P
Talanta; 2012 Jan; 89():223-30. PubMed ID: 22284484
[TBL] [Abstract][Full Text] [Related]
7. Validation and transferability study of a method based on near-infrared hyperspectral imaging for the detection and quantification of ergot bodies in cereals.
Vermeulen P; Fernández Pierna JA; van Egmond HP; Zegers J; Dardenne P; Baeten V
Anal Bioanal Chem; 2013 Sep; 405(24):7765-72. PubMed ID: 23404130
[TBL] [Abstract][Full Text] [Related]
8. [Research advances in imaging technology for food safety and quality control].
Deng Y; Wang X; Yang M; He M; Zhang F
Se Pu; 2020 Jul; 38(7):741-749. PubMed ID: 34213280
[TBL] [Abstract][Full Text] [Related]
9. A review on the applications of portable near-infrared spectrometers in the agro-food industry.
dos Santos CA; Lopo M; Páscoa RN; Lopes JA
Appl Spectrosc; 2013 Nov; 67(11):1215-33. PubMed ID: 24160873
[TBL] [Abstract][Full Text] [Related]
10. [Application of near-infrared spectroscopy to quality detection of milk and its products].
Wang J; Wang JQ; Bu DP; Guo WJ; Shen JS; Wei HY; Zhou LY; Liu KL
Guang Pu Xue Yu Guang Pu Fen Xi; 2009 May; 29(5):1281-5. PubMed ID: 19650471
[TBL] [Abstract][Full Text] [Related]
11. Near-infrared analysis of whole kernel barley: comparison of three spectrometers.
Sohn M; Himmelsbach DS; Barton FE; Griffey CA; Brooks W; Hicks KB
Appl Spectrosc; 2008 Apr; 62(4):427-32. PubMed ID: 18416902
[TBL] [Abstract][Full Text] [Related]
12. Prediction of some quality attributes of lamb meat using near-infrared hyperspectral imaging and multivariate analysis.
Kamruzzaman M; ElMasry G; Sun DW; Allen P
Anal Chim Acta; 2012 Feb; 714():57-67. PubMed ID: 22244137
[TBL] [Abstract][Full Text] [Related]
13. Evaluation of freshness decay of minced beef stored in high-oxygen modified atmosphere packaged at different temperatures using NIR and MIR spectroscopy.
Sinelli N; Limbo S; Torri L; Di Egidio V; Casiraghi E
Meat Sci; 2010 Nov; 86(3):748-52. PubMed ID: 20655668
[TBL] [Abstract][Full Text] [Related]
14. Near-infrared hyperspectral imaging for grading and classification of pork.
Barbin D; Elmasry G; Sun DW; Allen P
Meat Sci; 2012 Jan; 90(1):259-68. PubMed ID: 21821367
[TBL] [Abstract][Full Text] [Related]
15. Skullcap and germander: preventing potential toxicity through the application of hyperspectral imaging and multivariate image analysis as a novel quality control method.
Sandasi M; Vermaak I; Chen W; Viljoen AM
Planta Med; 2014 Oct; 80(15):1329-39. PubMed ID: 25184892
[TBL] [Abstract][Full Text] [Related]
16. [Application and recent development of research on near-infrared spectroscopy for meat quality evaluation].
Xu X; Cheng F; Ying YB
Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Jul; 29(7):1876-80. PubMed ID: 19798962
[TBL] [Abstract][Full Text] [Related]
17. Development of a simple algorithm for the detection of chilling injury in cucumbers from visible/near-infrared hyperspectral imaging.
Liu Y; Chen YR; Wang CY; Chan DE; Kim MS
Appl Spectrosc; 2005 Jan; 59(1):78-85. PubMed ID: 15720741
[TBL] [Abstract][Full Text] [Related]
18. A rapid and sensitive method for the evaluation of cereal grains in bioethanol production using near infrared reflectance spectroscopy.
Pohl F; Senn T
Bioresour Technol; 2011 Feb; 102(3):2834-41. PubMed ID: 21071215
[TBL] [Abstract][Full Text] [Related]
19. Raman and near-infrared spectroscopy for quantification of fat composition in a complex food model system.
Afseth NK; Segtnan VH; Marquardt BJ; Wold JP
Appl Spectrosc; 2005 Nov; 59(11):1324-32. PubMed ID: 16316509
[TBL] [Abstract][Full Text] [Related]
20. Near-infrared hyperspectral imaging in tandem with partial least squares regression and genetic algorithm for non-destructive determination and visualization of Pseudomonas loads in chicken fillets.
Feng YZ; Sun DW
Talanta; 2013 May; 109():74-83. PubMed ID: 23618142
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
