| Multivariate calibration H Martens, T Naes John Wiley & Sons, 1992 | 8707 | 1992 |
| A user-friendly guide to multivariate calibration and classification T Næs, T Isaksson, T Fearn, T Davies NIR, 2002 | 2287 | 2002 |
| Making sense of the “clean label” trends: A review of consumer food choice behavior and discussion of industry implications D Asioli, J Aschemann-Witzel, V Caputo, R Vecchio, A Annunziata, T Næs, ... Food Research International 99, 58-71, 2017 | 674 | 2017 |
| The effect of multiplicative scatter correction (MSC) and linearity improvement in NIR spectroscopy T Isaksson, T Næs Applied Spectroscopy 42 (7), 1273-1284, 1988 | 600 | 1988 |
| Statistics for sensory and consumer science T Næs, PB Brockhoff, O Tomic John Wiley & Sons, 2011 | 464 | 2011 |
| Locally weighted regression and scatter correction for near-infrared reflectance data T Naes, T Isaksson, B Kowalski Analytical Chemistry 62 (7), 664-673, 1990 | 354 | 1990 |
| Understanding the collinearity problem in regression and discriminant analysis T Næs, BH Mevik Journal of Chemometrics: A Journal of the Chemometrics Society 15 (4), 413-426, 2001 | 308 | 2001 |
| General image and attribute perceptions of traditional food in six European countries VL Almli, W Verbeke, F Vanhonacker, T Næs, M Hersleth Food quality and preference 22 (1), 129-138, 2011 | 298 | 2011 |
| Related versions of the multiplicative scatter correction method for preprocessing spectroscopic data IS Helland, T Næs, T Isaksson Chemometrics and Intelligent Laboratory Systems 29 (2), 233-241, 1995 | 288 | 1995 |
| Principal component regression in NIR analysis: viewpoints, background details and selection of components T Næs, H Martens Journal of chemometrics 2 (2), 155-167, 1988 | 271 | 1988 |
| Comparison of prediction methods for multicollinear data T Naes, H Martens Communications in Statistics-Simulation and Computation 14 (3), 545-576, 1985 | 204 | 1985 |
| Consumer preference mapping of dry fermented lamb sausages H Helgesen, R Solheim, T Næs Food Quality and Preference 8 (2), 97-109, 1997 | 155 | 1997 |
| Linking gene regulation and the exo-metabolome: a comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast D Rossouw, T Næs, FF Bauer BMC genomics 9 (1), 1-10, 2008 | 154 | 2008 |
| Prediction of sensory characteristics of beef by near-infrared spectroscopy KI Hildrum, BN Nilsen, M Mielnik, T Naes Meat science 38 (1), 67-80, 1994 | 151 | 1994 |
| Analysis of variance for sensory data P Lea, T Næs, M Rødbotten John Wiley, 1997 | 146 | 1997 |
| Abrupt temporal fluctuations in the chicken fecal microbiota are explained by its gastrointestinal origin M Sekelja, I Rud, SH Knutsen, V Denstadli, B Westereng, T Naes, K Rudi Applied and environmental microbiology 78 (8), 2941-2948, 2012 | 139 | 2012 |
| Artificial neural networks in multivariate calibration T Næs, K Kvaal, T Isaksson, C Miller Journal of Near Infrared Spectroscopy 1 (1), 1-11, 1993 | 139 | 1993 |
| Motivation for choice and healthiness perception of calorie-reduced dairy products. A cross-cultural study SB Johansen, T Næs, M Hersleth Appetite 56 (1), 15-24, 2011 | 132 | 2011 |
| Analysing sensory panel performance in a proficiency test using the PanelCheck software O Tomic, G Luciano, A Nilsen, G Hyldig, K Lorensen, T Næs European Food Research and Technology 230, 497-511, 2010 | 131 | 2010 |
| Multivariate analysis of data in sensory science T Næs, E Risvik Elsevier, 1996 | 126 | 1996 |
HARALD MARTENSprof. emerit. Big Data Cybernetics / bio-chemometrics, Dept. Engineering Cybernetics NTNUVerified email at idletechs.com
