| 1 |
Comparative analysis of pork tenderness prediction using different optical scattering parameters
Sun HW, Peng YK, Zheng XC, Wang WX, Zhang J
Journal of Food Engineering, 248, 1, 2019 |
| 2 |
An intelligent machine vision-based smartphone app for beef quality evaluation
Hosseinpour S, Ilkhchi AH, Aghbashlo M
Journal of Food Engineering, 248, 9, 2019 |
| 3 |
Potential of hyperspectral imaging combined with chemometric analysis for assessing and visualising tenderness distribution in raw farmed salmon fillets
He HJ, Wu D, Sun DW
Journal of Food Engineering, 126, 156, 2014 |
| 4 |
Application of biospeckle laser technique for determining biological phenomena related to beef aging
Amaral IC, Braga RA, Ramos EM, Ramos ALS, Roxael EAR
Journal of Food Engineering, 119(1), 135, 2013 |
| 5 |
Prediction of beef quality attributes using VIS/NIR hyperspectral scattering imaging technique
Wu JH, Peng YK, Li YY, Wang W, Chen JJ, Dhakal S
Journal of Food Engineering, 109(2), 267, 2012 |
| 6 |
Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef
ElMasry G, Sun DW, Allen P
Journal of Food Engineering, 110(1), 127, 2012 |
| 7 |
Image analysis study of the perimysial connective network, and its relationship with tenderness and composition of bovine meat
El Jabri M, Abouelkaram S, Damez JL, Berge P
Journal of Food Engineering, 96(2), 316, 2010 |
| 8 |
Application of an ultrasonic assisted curing technique for improving the diffusion of sodium chloride in porcine meat
Siro I, Ven C, Balla C, Jonas G, Zeke I, Friedrich L
Journal of Food Engineering, 91(2), 353, 2009 |
| 9 |
Beef meat electrical impedance spectroscopy and anisotropy sensing for non-invasive early assessment of meat ageing
Damez JL, Clerjon S, Abouelkaram S, Lepetit J
Journal of Food Engineering, 85(1), 116, 2008 |
| 10 |
Prediction of lamb tenderness using image surface texture features
Chandraratne MR, Samarasinghe S, Kulasiri D, Bickerstaffe R
Journal of Food Engineering, 77(3), 492, 2006 |
