• Follow us

01 January 2010


Development of analytical solutions based on near-infrared hyperspectral imaging for the agricultural and food sectors


Nowadays, imaging is largely used as a decision support tool in the agricultural and agrofood sectors. It enables a better management of resources in the field of precision agriculture and quality control of products both at laboratory and at field levels as well as online in processing plants. In image analysis, images are usually obtained in the visible field, however due to large analytical improvements, images can be also obtained from techniques based on near-infrared sensors. Near infrared hyperspectral imaging allows to simultaneously acquire spatial (i.e. distribution) and spectral (thus composition) information from a sample. The hyperspectral imaging technology provides the ability to collect thousands of spectra from a sample or process in a non-destructive manner and without interfering with the sample composition or process. Powerful computers and image processing techniques, including statistical and chemometric tools are essential for the analysis of this type of data. In recent years, CRA-W has acquired a large expertise in this field through various projects and collaborations with public institutes or private companies, at regional, national or international level. It maintains this competence by (i) conducting feasibility studies on various applications, (ii) developing standardized methods and algorithms for the acquisition, processing and interpretation of NIR images and spectra as well as (iii) producing appropriate and optimized responses for a given agricultural and agro food problem.



Baeten, V. , Dardenne, P. , Dubois, J. , Lewis, E. , Burger, J. & Fernández Pierna, J.A. (2009). Spectroscopic Imaging In: Comprehensive chemometrics Chemical and Biochemical Data Analysis, Oxford, Elsevier, 4, 173-196. Baeten, V. , Vermeulen, P. , Dardenne, P. & Fernández Pierna, J.A. (2010). NIR hyperspectral imaging methods for quality and safety control of food and feed products: contributions to four European projects NIR News 21, (6), 10-13. Dardenne, P. , Baeten, V. & Fernández Pierna, J.A. (2010). In-house validation of a near infrared hyperspectral imaging method for detecting processed animal proteins (PAP) in compound feed. Journal of NIRS, 18: 121-133. Vermeulen, P. , Fernández Pierna, J.A. , van Egmond, H.P. , Dardenne, P. & Baeten, V. (2012). On-line detection and quantification of ergot bodies in cereals using near infrared hyperspectral imaging. Food Additives and Contaminants: Part A, 29: (2), 232-240. Dale, L.M. , Fernández Pierna, J.A. , Vermeulen, P. , Lecler, B. , Bogdan, A.D. , Pacurar, F.S. , Rotar, I. , Thewis, A. & Baeten, V. (2012). Research on crude protein and digestibility of Arnica montana L. using conventional NIR spectrometry and hyperspectral imaging NIR. Journal of Food, Agriculture and Environment, 10: (1), 391-396. Fernández Pierna, J.A. , Vermeulen, P. , Amand, O. , Tossens, A. , Dardenne, P. & Baeten, V. (2012). NIR hyperspectral imaging spectroscopy and chemometrics for the detection of undesirable substances in food and feed. Chemometrics and Intelligent Laboratory Systems, 117: 233-239. Dale, L.M. , Thewis, A. , Boudry, C. , Rotar, I. , Dardenne, P. , Baeten, V. & Fernández Pierna, J.A. (2013). Hyperspectral Imaging Applications in Agriculture and Agro-Food Product Quality and Safety Control : A Review. Applied Spectroscopy Reviews, 48: 142-159. Vermeulen, P. , Fernández Pierna, J.A. , van Egmond, H.P. , Zegers, J. , Dardenne, P. & Baeten, V. (2013). Validation and transferability study of a method based on near-infrared hyperspectral imaging for the detection and quantification of ergot bodies in cereals. Analytical and Bioanalytical Chemistry, 405: (24), 7765-7772. Baeten, V. , Dardenne, P. & Fernández Pierna, J.A. (2007). Hyperspectral imaging techniques: an attractive solution for the analysis of biological and agricultural materials. In: Techniques and Applications of Hyperspectral Image Analysis, Hans F. Grahn & Paul Geladi Editors. 289-311. Guns, C. , Pissard, A. & Abbas, O. (2013). Valorisation du contenu polyphénolique des pommes par l’utilisation de la spectroscopie moyen infrarouge. 65. Fernández Pierna, J.A. , Vincke, D. , Dardenne, P. , Zengling, Yang , Lujia, Han & Baeten, V. (2014). Line scan hyperspectral imaging spectroscopy for the early detection of melamine and cyanuric acid in feed. Journal of Near Infrared Spectroscopy, 22: (2), 103-112. Vincke, D. , Baeten, V. , Sinnaeve, G. , Dardenne, P. & Fernández Pierna, J.A. (2014). Determination of outer skin in dry onions by hyperspectral imaging spectroscopy and chemometrics. NIR News, 25: (2), 9-12. Vincke, D. , Miller, R. , Stassart, E. , Otte, M. , Dardenne, P. , Collins, M. , Wilkinson, K. , Stewart, J. , Baeten, V. & Fernández Pierna, J.A. (2014). Analysis of collagen preservation in bones recovered in archaeological contexts using NIR hyperspectral imaging. Talanta, 125: 181-188. Yang, Z. , Han, L. , Wang, C. , Li, J. , Fernández Pierna, J.A. , Dardenne, P. & Baeten, V. (2016). Detection of melamine in soybean meal using near-infrared microscopy imaging with pure component spectra as the evaluation criteria. Journal of Spectroscopy, ID 5868170: 11p. Vermeulen, P. , Flemal, P. , Pigeon, O. , Dardenne, P. , Fernández Pierna, J.A. & Baeten, V. (2017). Assessment of pesticide coating on cereal seeds by near infrared hyperspectral imaging. J. Spectral Imaging, 6: (a1), 1-7. Vermeulen, P. , Ebene, M.B. , Orlando, B. , Fernández Pierna, J.A. & Baeten, V. (2017). Online detection and quantification of particles of ergot bodies in cereal flour using near infrared hyperspectral imaging. Food Additives & Contaminants: Part A, 34: (8), 1312-1319. Fernández Pierna, J.A. , Baeten, V. , Dardenne, P. & Fernández Pierna, J.A. (2006). Screening of compound feeds using NIR hyperspectral data. Chemom. Intell. Lab. Syst. 84: (1-2), 114-118. Baeten, V. , Michotte Renier, A. , Cogdill, R. , Dardenne, P. & Fernández Pierna, J.A. (2004). Combination of Support Vector Machines (SVM) and Near Infrared (NIR) imaging spectroscopy for the detection of meat and bone meat (MBM) in compound feeds. Journal of chemometrics, 18: (7-8), 341-349. Baeten, V. & Dardenne, P. (2005). Application of near-infrared imaging for monitoring agricultural food and feed products In: Spectrochemical analysis using infrared multichannel detectors, Blackwell Publishing, 283-301.


Share this article
On the same subject