References

• Alomar, D., Gallo, C., Castañeda, M., Fuchslocher, R., 2003. Chemical and discriminant analysis of bovine meat by near infrared reflectance spectroscopy (NIRS). Meat Sci 63: 441–450.
   Google Scholar
• Andrés S., Murray, I., Calleja, A., Javier Giráldez, F., 2005. Nutritive evaluation of forages by near infrared reflectance spectroscopy. J Near Infrared Spec 13: 301–311.
   Google Scholar
• Andrés, S., Murray, I., Navajas, E. A., Fisher, A. V., Lambe, N. R., Bünger, L., 2007. Prediction of sensory characteristics of lamb meat samples by near infared reflectance spectroscopy. Meat Sci 76: 509–516.
   Google Scholar
• Andrés, S., Silva, A., Soares-Pereire, A. L., Martins, C., Bruno-Soares, A. M., Murray, I., 2008. The use of visible and near infrared reflectance spectroscopy to predict beef M. longissimus thoracis et lumborum quality attributes. Meat Sci 78: 217–224.
   Google Scholar
• Baeten, V., Dardenne, P., 2002. Spectroscopy: Developments in instrumentation and analysis. Grasas y Aceites 53 (1): 45–63.
   Google Scholar
• Bamelins, F. R., Kemps, B. J., Mertens, K., Govaerts, T., De Ketelaere, B., Kamers, B., Kokou, T., Decuypere, E. M., De Baerdemaeker, J. G., 2003. Non destructive internal egg freshness assessment using VIS-NIR spectroscopy. Proc. Xth European Symposium on the quality of eggs and egg products, France, Saint-Brieuc Ploufragan, pp. 91–97.
   Google Scholar
• Bechmann, I. E., Jørgensen, B. M., 1998. Rapid assessment of quality parameters for frozen cod using near infrared spectroscopy. Lebensm-Wiss U.-Technol 31: 648–652.
   Google Scholar
• Berardinelli, A., Giunchi, A., Guarnieri, A., Pezzi, F., Ragni, L., 2005. Shell egg albumen height assessment by FT-NIR spectroscopy. Transaction of the ASAE 48 (4): 1426–1428.
   Google Scholar
• Berzaghi, P., Flinn, P. C., Dardenne P., Lagerholm, M., Shenk, J. S., Westerhaus, M. O., Cowe, I. A., 2001. Comparison of linear and non-linear NIR calibration methods using large forage databases. Proceedings of the 10th International NIRS Conference Ed. By A. M. C. Davies and R. K. Cho.
   Google Scholar
• Berzaghi, P., Dalle Zotte, A., Jansson, L. M., Andrighetto, I., 2005. Near-infrared reflectance spectroscopy as a method to predict chemical composition of breast meat and discriminate between different n-3 feeding sources. Poultry Sci 84: 128–136.
   Google Scholar
• Blanco, M., Villarroya, I., 2002. NIR spectroscopy: a rapid- response analytical tool. Trends in analytical chem 21 (4): 240–250.
   Google Scholar
• Bøknæs, N., Jensen, K. N., Andersen C. M., Martens H., 2002. Freshness assessment of thawed and chilled cod fillets packed in modified atmosphere using near-infrared spectroscopy. Lebensm-Wiss. U.-Technol 35: 628–634.
   Google Scholar
• Brimmer, P. J., Hall, J. W., 2001. Method development and implementation of near-infrared spectroscopy in industrial manufacturing support laboratories. In: Williams, P. K., Norris, K. (Eds.), Near-Infrared Technology in the Agricultural and Food Industries, second ed. American Association of Cereal Chemists Inc., St. Paul, Minnesota, USA, pp. 187–198.
   Google Scholar
• Brøndum, J., Munck, L., Henckel, P., Karlsson, A., Tornberg, E., Engelsen, S. B., 2000. Prediction of water-holding capacity and composition of porcine meat by comparative spectroscopy. Meat Sci 55: 177–185.
   Google Scholar
• Castillo, M., Payne, F. A., Hicks, C. L., Lopez, M. B., 2000. Predicting cutting and clotting time of coagulating goat’s milk using diffuse reflectance: effect of pH, temperature and enzyme concentration. Int Dairy J 10: 551–562.
   Google Scholar
• Cattaneo, T. M. P., Giardina, C, Sinelli, N., Riva, M., Giangiacomo, R., 2005. Application of FT-NIR and FT-IR spectroscopy to study the shelf-life of Crescenza cheese. Int Dairy J 15: 693–700.
   Google Scholar
• Cattaneo, T. M. P., Tornelli, C., Erini, S., Panarelli, E. V., 2008. Relationship between sensory scores and near infrared absorptions in characterising Bitto, an Italian protected denomination origin cheese. J Near Infrared Spec 16: 173–178.
   Google Scholar
• Cen, H., He, Y., 2007. Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends Food Sci Tech 18: 72–83.
   Google Scholar
• Cozzolino, D., Murray, I., Scaife, J. R., 2002. Near infrared reflectance spectroscopy in the prediction of chemical characteristics of minced raw fish. Aquacultur Nutr 8: 1–6.
   Google Scholar
• Cozzolino D., Murray I., 2004. Identification of animal meat muscles by visible and near infrared reflectance spectroscopy. Lebensm.-Wiss. U.-Technol 37: 447–452.
   Google Scholar
• Cozzolino, D., Fassio, A., Fernández, E., Restaino, E., La Manna, A., 2006. Measurement of chemical composition in wet whole maize silage by visible and near infrared reflectance spectroscopy. Anim Feed Sci Tech 129: 329–336.Čurda, L., Kukačková, O., 2004. NIR spectroscopy: a useful tool for rapid monitoring of processed cheeses manufacture. J Food Eng 61: 557–560.
   Google Scholar
• Dalle Zotte, A., Berzaghi, P., Jansson, L. M., Andrighetto, I., 2006. The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition of freeze dried egg yolk and discriminant between different n-3 PUFA feeling source. Anim Feed Sci Tech 128: 108–121.58
   Google Scholar
• De la Haba, M. J., Garrido-Varo, A., Pérez-Marín, D. C., Guerrero, J. E., 2007. Near infrared analysis as a first-line screening technique for identifying animal species in rendered animal by-product meals. J Near Infrared Spec 15: 237–245.
   Google Scholar
• De la Haba, M. J., Fernández Pierna, J. A., Fumière, O., Garrido-Varo, A., Guerrero, J. E., Pérez-Marín, D. C., Dardenne, P., Baeten, V., 2007a. Discrimination of fish bones from other animal bones in the sedimented fraction of compound feeds by near infrared microscopy. J Near Infared Spec 15: 81–88.
   Google Scholar
• De la Haba, M. J., Garrido-Varo, A., Núñez, N., Pérez-Marín, D. C., Guerrero, J. E., 2008. Using calibrations developed for fine milled meat and bone meal on spectra measured on non-milled samples. J Near Infrared Spec 6:275–279.
   Google Scholar
• De la Roza-Delgado , B., Soldado, A., Martínez-Fernández, A., Vicente, F., Garrido-Varo, A., Pérez-Marín, D., De la Haba, M. J., Guerrero-Ginel, J. E., 2007. Application of near-infrared microscopy (NIRM) for the detection of meat and bone meals in animal feeds: A tool for food and feed safety. Food Chem 105: 1164–1170.
   Google Scholar
• De Roos, A. P. W., Van Den Bijgaart, H. J. C. M., Horlyk, J., De Jong, G., 2007. Screening for subclinical ketosis in dairy cattle by Fourier transform infrared spectrometry. J Dairy Sci 90: 1761–1766.
   Google Scholar
• Dračková, M., Hadra, L., Janštová, B., Navrátilová, P., Přidalová, H., Vorlová, L., 2008. Analysis of goat milk by Near-Infrared spectroscopy. Acta vet Brno 77: 415–422.
   Google Scholar
• Fasolato, L., Ferlito, J. C., Mirisola, M., Tepedino, G., Tanzi, E., Barbuti, S., 2008b. Pros and cons of smoked salmon. Eurofishmarket 10: 18–53.
   Google Scholar
• Fasolato, L., Manfrin, A., Corrain, C., Perezzani, A., Arcangeli, G., Rosteghin, M., Novelli, E., Lopparelli, R. M., Balzan, S., Mirisola, M., Serva, L., Segato, S., Bianchi, E., 2008a. Assessment of quality-parameters and authentication in sole (Solea vulgaris) by NIRS (Near infrared reflectance spectroscopy). Industrie alimentari-XLVIII 355–362.
   Google Scholar
• Fasolato, L., Mirisola, M., Tepedino, G., Balzan, S., Arcangeli, G., Rosteghin, M., Corrain, C., Manfrin, A., Berzaghi, P., 2008. No more defrost for fresh. Eurofishmarket 1: 22–45.
   Google Scholar
• Fernández-Ahumada, E., Garrido-Varo, A., Guerrero-Ginel, J. E., Pérez-Marín, D., Fearn, T., 2008a. Taking NIR calibrations of feed compounds from the laboratory to the process: calibration transfer between predispersive and postdispersive instruments. J Agric Food Chem. 56: 10135–10141.
   Google Scholar
• Fernández-Ahumada, E., Guerrero-Ginel, J. E., Pérez-Marín, D., Garrido-Varo, A., 2008. Near infrared spectroscopy for control of the compound-feed manufacturing process: mixing stage. J Near Infrared Spec 16: 285–290.
   Google Scholar
• Fernández Pierna, J. A., Baeten, V., Michotte Renier, A., Cogdill, R. P., Dardenne, P., 2004. Combination of support vector machines (SVM) and near-infrared (NIR) imaging spectroscopy for the detection of meat and bone meal (MBM) in compound feeds. J Chemometr 18: 341–349.
   Google Scholar
• Gaitán-Jurado, A. J., Ortiz-Somovilla, V., España-España, F., Pérez-Aparicio, J., De Pedro-Sanz E. J., 2008. Quantitative analysis of pork dry-cured sausages to quality control by NIR spectroscopy. Meat Sci 78: 391–399.
   Google Scholar
• Geesink, G. H., Schreutelkamp, F. H., Frankhuizen, R., Vedder, H. W., Faber, N. M., Kranen, R. W., Gerritzen, M.A., 2003. Prediction of pork quality attributes from near infrared reflectance spectra. Meat Sci, 65: 661–668.
   Google Scholar
• Garcia, J., Cozzolino, D., 2006. Use of Near infrared reflectance (NIR) spectroscopy to predict chemical composition of forages in broad-based calibration model. Agricultura técnica 66 (1): 41–47.
   Google Scholar
• García-Olmo, J., De Pedro, E., Garrido-Varo, A. Jimenez, A., Salas, J., Santolalla, M., 2000. Fatty acids analysis of Iberian pig fat by near infrared spectroscopy (NIRS). CIHEAM- Options Mediterraneennes: 191–195.
   Google Scholar
• Garrido-Varo, A., Pérez-Marín, D., Bautista-Cruz, J., Guerrero-Ginel, J. E., 2008. Near infrared spectroscopy for quantification of animal-origin fats in fat blends. J Near Infrared Spec 16: 281–283.
   Google Scholar
• Gelaldi, P., 2002. Some recent trends in the calibration literature. Chemometr Intell Lab, 60: 211–214.
   Google Scholar
• Giangiacomo, R., Lizzano, R., Barzaghi, S., Cattaneo, T.M.P., 1998. NIR and other luminometric methods to monitor the primary clotting phase of milk. J Near Infrared Spec 6 (1): 205–212.
   Google Scholar
• Giunchi A., Bardinelli, A., Ragni, L., Fabbri, A., Silanghi, F. A., 2008. Non-destructive assessment of shell eggs using FT-NIR spectroscopy. J Food Eng 89: 142–148.
   Google Scholar
• Givens, D. I., Deaville, E. R, 1999. The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review. Aust J Agric Res 50: 1131–1145.
   Google Scholar
• González-Martín, I., Hernández-Hierro, J. M., Vivar-Quintana, A., Revilla, I., González-Pérez, 2009. The application of near infrared spectroscopy technology and a remote reflectance fibre-optic probe for the determination of peptides in cheeses (cow’s, ewe’s and goat’s) with different ripening times. Food Chem 114: 1564–1569.
   Google Scholar
• Hildrum, K. I., Nilsen, B. N., Mielnik, M., Naes, T., 1994. Prediction of sensory characteristics of beef by near infrared spectroscopy. Meat Sci 38 (1): 67–80.
   Google Scholar
• Huang, Y., Cavinato, A. G., Mayes, D. M., Kangas, L. J., Bledsoe, G. E., Rasco, B. A., 2003. Nonde-structive determination of moisture ad sodium chloride in cured Atlantic salmon (Salmo salar) (Teijin) using short-wavelength near-infrared Spectroscopy (SW-NIR). J Food Sci 68(2): 482–486.
   Google Scholar
• Huang, H., Yu, H., Xu, H., Ying, Y., 2008. Near infrared spectroscopy for on/in line monitoring of quality in foods and beverages: A review. J Food Eng 87: 303–313.
   Google Scholar
• Hoving-Bolink, A. H., Vedder, H. W., Merks, J. W. M., De Klein, W. J. H., Reimert, H. G. M., Frankhuizen, R., van den Broek, W. H. A. M., Lambooij, E., 2005. Perspective of NIRS measurements early post mortem for prediction of pork quality. Meat Sci 69: 417–423.
   Google Scholar
• Isaksson, T., Nilsen, B. N., Tøgersen, G., Hammond, R. P., Hildrum, K. I., 1996. On-line, proximate analysis of ground meat batches directly at a meat grinder outlet. Meat Sci 43: 245–253.
   Google Scholar
• Karoui, R., Dufour, É., Pillonel, L., Schaller, E., Picque, D., Cattenoz, T., Mouazen, A. M., Schaller, E., De Baerdemaeker, J., Bosset J. O., 2005. The potential of combined infrared and fluorescence spectroscopies as a method of determination of the geographic origin of Emmental cheeses. Int Dairy J 15: 287–298.
   Google Scholar
• Karoui, R., Mouazen, A. M., Dufour, É., Pillonel, L., Schaller, E., De Baerdemaeker, J., Bosset J. O., 2006. Chemical characterisation of European Emmental cheeses by near infrared spectroscopy using chemometric tools. Int Dairy J 16: 1211–1217.
   Google Scholar
• Karoui, R., Pillonel, L., Schaller, E., Bosset J. O., De Baerdemaeker, J., 2006a. Prediction of sensory attributes of European Emmental cheese using near-infrared spectroscopy: a feasibility study. Food Chem 101: 1121–1129.
   Google Scholar
• Katsumoto, Y., Jang, J. H., Berry, R. J. and Ozaki, Y., 2001. Modern pre-treatment methods in NIR spectroscopy. Near Infrared Analysis 2: 29–36.
   Google Scholar
• Kawasaki, M., Kawamura, S., Tsukahara, M., Morita, S., Komiya, M., Natsuga, M., 2008. Near infrared spectroscopic system for on-line milk quality assessment in a milking robot. Computers and electronics in agriculture 63: 22–27.
   Google Scholar
• Kemps, B. J., Bamelins, F. R., De Ketelaere, B., Mertens, K., Tona, K., Decuypere, E. M., De Baerdemaeker, J. G., 2006. Visible transmission spectroscopy for the assessment of egg freshness. J Sci food agr 86: 1399–1406.
   Google Scholar
• Klandar, A. H., Lagaude, A., Chevalier-Lucia, D., 2007. Assessment of the rennet coagulation of skim milk: A comparison of methods. Int Dairy J 17: 1151–1160.
   Google Scholar
• Laporte, M. F., Martel, R., Pasquin, P., 1998. The near-infrared optic probe for monitoring rennet coagulation in cow’s milk. Int Dairy J 8: 659–666.
   Google Scholar
• Laporte, M. F., Pasquin, P., 1999. Near-Infrared analysis of fat, protein, and casein in cow’s milk. J Agri Food Chem 47: 2600–2605.
   Google Scholar
• Leardi, R., 2008. Chemometric methods in food authentication. In: modern techniques for food authentication Da-Wen Sun 1st ed., Amsterdam; Boston: Elsevier/Academic Press. Pp 585–616.
   Google Scholar
• Li, H., Lv, X., Wang, J., Li, J., Yang, H., Qin, Y., 2007. Quantitative determination of soybean meal content in compound feeds: comparison of near-infrared spectroscopy and real-time PCR. Anal Bioanal Chem 389: 2313–2322.
   Google Scholar
• Lin, M., Mousavi, M., Al-Holi, M., Cavinato, A. G., Rasco, B.A., 2006. Rapid near infared spectroscopic method for the detection of spoilage in rainbow trout (Oncorhynchus mykiss) fillet. J Food Sci 71(1): S18-S23
   Google Scholar
• Lovett, D. K, Deaville, E. R, Mould, F., Givens, D. I., Owen, E., 2004. Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage. Anim Feed Sci Tech 115: 179–187.
   Google Scholar
• Lovett, D. K., Deaville, E. R., Givens, D. I., Finlay, M., Owen, E., 2005. Near infrared reflectance spectroscopy (NIRS) to predict biological parameter of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture. Anim Feed Sci Tech 129: 323–332.
   Google Scholar
• Manley, M., Downey, G., Baeten, V., 2008. Spectroscopic technique: Near-Infrared (NIR) spectroscopy. In: Modern techniques for food authentication. Da-Wen Sun 1st ed., Amsterdam; Boston: Elsevier/Academic Press. Pp 65–115.
   Google Scholar
• Massart, D. L., Vandeginste, B. G. M., Buydens, L. M. C., et al, 1988. Chemometrics: A textbook, Vol.2. Amsterdam: Elsevier.
   Google Scholar
• McElhinney, J., Downey, G., 1999. Chemometric processing of visible and near infrared reflectance spectra for species identification in selected raw homogenised meat. J Near Infrared Spec 7: 145–154.
   Google Scholar
• Molette, C. , Berzaghi, P., Dalle Zotte, A., Remignon, H., Babile, R., 2001. The Use of Near-Infrared Reflectance Spectroscopy in the Prediction of the Chemical Composition of Goose Fatty Liver. Poultry Sci 80: 1625–1629.
   Google Scholar
• Monin, G., 1998. Recent methods for predicting quality of whole meat. Meat Sci 49: S231-S243.
   Google Scholar
• Murray, I., 1999. NIR spectroscopy of food: single things, dabble things and spectra. NIR news 10: 10–12.
   Google Scholar
• Nilsen, H., Esaiassen, M., Heia, K., Sigernes, F., 2002. Visible/near infrared spectroscopy. A new tool for the evaluation of fish frshness? J Food Sci 67(5): 1821–1826.
   Google Scholar
• Norris K. H., Barnes R F., Moore J. E., Shenk J. S., 1976. Predicting forage quality by near infrared reflectance spectroscopy. J Anim Sci 43 (4): 889–897.
   Google Scholar
• Norris, K. H., 1996. History of NIR. J Near Infrared Spec 4: 31–37
   Google Scholar
• Pasquini C., 2003. Near infrared spectroscopy: fundamental, practical aspects and analytical application. J Braz Chem Soc, 14 (2): 198–219.
   Google Scholar
• Pérez-Marín, D., Garrido-Varo, A., Guerrero-Ginel, J. E., Gómez-Cabrera, A., 2004. Near-infrared reflectance spectroscopy (NIRS) for the mandatory labelling of compound feedingstuffs: chemical composition and open-declaration. Anim Feed Sci Tech 116: 333–349.
   Google Scholar
• Prevolnik, M., Candek-Potokar, M., Skorjanc, D., 2004. Ability of NIR spectroscopy to predict meat chemical composition and quality – a review. Czech J Anim Sci 49, 500–510.
   Google Scholar
• Prieto, N., Andrés, S., Giráldez, F. J., Mantecón, A. R., Lavín, P., 2006. Potential use of near infrared reflectance spectroscopy (NIRS) for the estimation of chemical composition of oxen meat samples. Meat Sci 74: 487–496.
   Google Scholar
• Prieto, N., Andrés, S., Giráldez, F. J., Mantecón, A. R., Lavín, P., 2008. Ability of near infrared reflectance spectroscopy (NIRS) to estimate physical parameters of adult steers (oxen) and young cattle meat samples. Meat Sci 79: 692–699.
   Google Scholar
• Ripoll, G., Albertí, P, Panea, B., Olleta, J. L., Sañudo, C, 2008. Near-infrared reflectance spectroscopy for predicting chemical, instrumental and sensory quality of beef. Meat Sci 80: 697–702.
   Google Scholar
• Sarawong, S., Kawano, S., 2008. System design for non-destructive near infrared analysis of chemical components and total aerobic bacteria count of raw milk. J Near Infrared Spec 16: 389–398.
   Google Scholar
• Savenije, B. , Geesink G. H., Van Der Palen, J. G. P., Hemke G., 2006. Prediction of pork quality using visible/near-infrared reflectance spectroscopy. Meat Sci 73: 181–184.
   Google Scholar
• Shao, Y., He., Y., Feng, S., 2007. Measurement of yogurt internal quality through using Vis/NIR spectroscopy. Food Res Int 40: 835–841.
   Google Scholar
• Shenk, J. S., Westerhaus, M. O., 1991. Population definition, sample selection, and calibration procedures for near infrared Reflectance spectroscopy. Crop Sci 31: 469–474.
   Google Scholar
• Sierra, V., Aldai, N., Castro, P., Osoro, K., Coto-Montes, A., Oliván, M., 2008. Prediction of the fatty acid composition of beef by near infrared transmittance spectroscopy. Meat Sci 78: 248–255.
   Google Scholar
• Sørensen, L. K., 2004. Prediction of fermentation parameters in grass and corn silage by near infrared spectroscopy. J Dairy Sci 87: 3826–3835.
   Google Scholar
• Stuth, J., Jama, A., Tolleson, D., 2003. Direct and indirect means of predicting forage quality through near infrared reflectance spectroscopy. Field Crop Res 84: 45–56.
   Google Scholar
• Schwarze, H., 1996. Report n. 96–10-1. Third European Symposium on Near Infrared (NIR) Spectroscopy: Continuous fat analysis in the meat industry, pp. 43–49.
   Google Scholar
• Tøgersen, G., Isaksson, T., Nilsen, B. N., Bakker, E. A., Hildrum, K. I., 1999. On-line NIR analysis of fat, water and protein in industrial scale ground meat batches. Meat Sci 51: 97–102.
   Google Scholar
• Tsenkova, R., Atanassova, S., Toyoda, K., Ozaki, Y., Itoh, K., Fearn, T., 1999. Near-infrared spectroscopy for dairy management: measurement of unhomogenized milk composition. J Dairy Sci 82: 2344–2351.
   Google Scholar
• Tsenkova, R., Atanassova, S, Itoh, K., Ozaki, Y., Toyoda, K, 2000. Near infrared spectroscopy for biomonitoring. Cow milk composition measurements in a spectral region from 1,100 to 2,400 nanometers. J Anim Sci 78: 515–522.
   Google Scholar
• Tsenkova, R., Atanassova, S, Ozaki, Y., Toyoda, K, Itoh, K., 2001. Near-infrared spectroscopy for biomonitoring: influence of somatic cell count on cow’s milk composition analysis. Int Dairy J 11: 779–783.
   Google Scholar
• Tsenkova, R., Atanassova, S, Kawano, S., Toyoda, K, 2001a. Somatic cell count determination in cow’s milk by near-infrared spectroscopy: a new diagnostic tool. J Anim Sci 79: 2550–2557.
   Google Scholar
• Tsenkova, R., Atanassova, S, Morita, H., Ikuta, K, Toyoda, K., Iordanova, I. K., Hakogi, E., 2006. Near infrared spectra of cows’milk for milk quality evaluation: disease diagnosis and pathogen identification. J Near Infrared Spec 14: 363–370.
   Google Scholar
• Uddin, M., Okazaki, E., Turza, S., yumico, Y., tanaka, M., Fukuda, Y., 2005. Non-destructive Visible/ NIR spectroscopy for differentiation of fresh and frozen-thawed fish. J Food Sci 70 (8): C506-C510.
   Google Scholar
• Uddin, M., Okazaki, E., Fukushima, H., Turza, S., Yumiko, Y., Fukuda, Y., 2006. Nondestructive determination of water and protein in surimi by near-infared spectroscopy. Food Chem 96: 491–495.
   Google Scholar
• Xiccato, G., Trocino, A., De Boever, J. L., Maertens, L., Carabaño, R., Pascual, J. J., Perez, J. M., Gidenne, T., Falcao-E-Cunha, L., 2003. Prediction of chemical composition, nutritive value and ingredient composition of European compound feeds for rabbits by near infrared reflectance spectroscopy (NIRS). Anim Feed Sci Tech 104: 153–168.
   Google Scholar
• Xiccato, G., Trocino, A., Tulli, F., Ribaldi, E., 2004. Prediction of chemical composition and origin identification of European sea bass (Dicentrarcus labrax L.) by near infrared reflectance spectroscopy (NIRS). Food Chem 86: 275–281.
   Google Scholar
• Woodcock, T., Downey, G., O’Donnel, C. P., 2008. Better quality food and beverages: the role of near infrared spectroscopy. J. Near Infrared Spec. 16: 1–29.
   Google Scholar
• Websites: www.foragetesting.org
   Google Scholar