E. Fernández-Ahumada et al., J. Near Infrared Spectrosc. 14, 27–35 (2006) 27 © NIR Publications 2006, ISSN 0967-0335 Abbreviations CP crude protein CV coefficient of variation DM dry matter EC European Commission FT Fourier transformation NIR near infrared N number PCR principal component regression PLS partial least squares R 2 coefficient of determination RP recoverable protein RPD ratio of the standard deviation of the calibration set to the SECV or SEP SD standard deviation SECV standard error of cross-validation SEL standard error of the laboratory reference method SEP standard error of prediction ST starch Introduction Most factories belonging to the Dutch company Avebe are working on products based on potato starch. More recently, there has been strong development in the extrac- tion and use of constituents other than starch from potatoes. At present, farmers are paid on the outcome of the “under water weight” measurement, a procedure prescribed by the EC to predict the starch content. The introduction of near infrared (NIR) spectroscopy as a fast quality control technology may be of great help in achieving this objective. NIR, placed either at-the-gate or at-line or in-line at plant level, will contribute to the setting up of a more objec- tive payment method which, in turn, will contribute to an improvement in the financial situation of the farmers and, by measuring absolute values at the entrance of the factory, will also lead to better quality control throughout the com- plete manufacturing process. 1 NIR spectroscopy has commonly been used to quantify the main constituents in various agro-food products and even Understanding factors affecting near infrared analysis of potato constituents Elvira Fernández-Ahumada, a Ana Garrido-Varo, a J. Emilio Guerrero-Ginel, a Arjan Wubbels, b Catrinus Van der Sluis b and Jos M. Van der Meer b a Department of Animal Production, ETSIAM, University of Córdoba (UCO), Avda. Menéndez Pidal s/n, 14080, Córdoba, Spain b Avebe Group Technology/R&D, Prins Hendrikplein 20, PO Box 15, 9640 AA Veendam, The Netherlands Most factories belonging to the Dutch company Avebe are working on products based on potato starch. More recently, there has been a strong development in the extraction and use of other potato constituents (i.e. protein, fibres). At present, farmers are paid on the outcome of the “under water weight” measurements, a procedure prescribed by the EC to predict the starch content. However, since there is an outlet in the market, the company is also willing to pay out according to the protein content. The introduction of near infrared (NIR) spectroscopy as a fast quality control technology may be of great help in reaching this objective. NIR, placed either at-the-gate or at-line or in-line at plant level, will contribute to the setting up of a more objective payment method which will, in turn, contribute to an improvement in the financial situation of the farmers and also to better control of the complete manufacturing process. A total of 275 mashed potatoes were analysed by using a FT-NIR (ABB Bomem MB160D) spectrometer and calibration equations were developed to predict dry matter (DM), starch (ST), crude protein (CP) and recoverable protein (RP) content. The equations developed for the prediction of DM and ST presented an accuracy and precision acceptable for routine analysis according to their RPD values (4.2 and 3.1, respectively). However, the equations obtained for CP and RP presented a low predictive ability (RPD ≈ 1.5). A discriminant analysis performed by using PLS2 regression correctly classified 87.5% of mashed potato samples in groups of low (< 14 mg g –1 ) and high (≥ 14 mg g –1 ) protein content. A feasibility study with entire potatoes and a diode array spectrometer (Corona 45 VIS+NIR) was carried out and the preliminary results show great expectations concerning further implementation of NIR technology at the factory gate. However, further research and demonstration activities are needed before application will become possible. Keywords: NIR, potato, dry matter, starch, protein, discriminant analysis, at-line, in-line