24 DECEMBER 2012 • WORLD AQUACULTURE • WWW.WAS.ORG formulation. Near Infrared Spectroscopy allows for immediate acceptance or rejection of incoming raw materials, eliminating the costly step of holding material in quarantine. Near Infrared Spectroscopy can be used to verify that inprocess and finished product matches required specifications. Analysis at the mixer can optimize the addition of liquid fat and other materials, including costly items such as amino acids, vitamins, enzymes, and organic acids. Near Infrared Spectroscopy can be used at the extruder and dryer to control moisture as well as at the oil sprayer to catch blockages and ensure proper fat levels. Finished product can be analyzed to verify and document label claims quickly. With NIRS, analysis of all finished product is possible, providing traceability for every shipment that leaves the feed mill. Near Infrared Spectroscopy calibration models have been developed for prediction of moisture, ash, oil, TVN and sodium chloride content in fishmeal. The NIRS estimation of fishmeal quality is a relatively inexpensive method to predict heat damage, available lysine, biogenic amines and other nutritional parameters of fishmeal (Cozzolina et al. 2002). Near Infrared Spectroscopy can be routinely used for nutritional analysis of feed ingredients and compounded feeds in the same way it is being used in agriculture for nutritional analysis of feedstuffs and forages (Roberts et al. 2004). NIRS can reduce inter- and intra- laboratory errors for moisture, protein, fat, ash, starch, sand and silica, fiber and digestibility (Argamenteria et al. 1993). NIRS can also be used to predict total digestible nutrients, digestible energy, metabolizable energy, net energy of maintenance or net energy of gain. Calcium and phosphorous levels can also be estimated. The technology can also be used to screen ingredients for anti-nutritional factors and other toxic or harmful substances that might cause poor growth or mortality in fish. As with other analytes, the essential amino acid profile of each ingredient can be analyzed by NIR spectroscopy through the development of robust calibrations. Software is available to predict the total and digestible amino acid profiles of different conventional feed ingredients, which is named AminoNIR spectroscopy. This is offered by one of the popular feed additive firms to their customers as a complementary service to promote their products. Advantages and Disadvantages of NIRS Positive attributes of NIRS include: a non-destructive method, simple to use, minimal sample preparation, no reagents, no waste, low cost per sample, instant analysis, high reliability, safety and timeliness of analysis, low maintenance cost, mobile analysis, analysis and data transfer through satellite networking of remote instruments is possible, low inter- and intra-laboratory variation and it is eco-friendly (Givens and Deaville 1999). As with any scientific innovation, there are also certain disadvantages of NIRS. It is typically a secondary analytical method. It must be calibrated with samples of known concentrations, which is time-consuming and laborious. Separate spectra for each ingredient and feed group must be developed. There is weak sensitivity to minor constituents. Fineness of samples and storage temperature also plays a vital role in determining the precision of the analysis. There is a high initial investment for the NIRS analyzer and grinding mill. Near Infrared Spectroscopy can bridge the gap between advanced scientific knowledge generated by scientists in laboratories and application in the field. NIRS has most of the attributes of an efficient tool for quality control at different levels in the feed production process, including raw material procurement, intermediate product, and finished feed. Notes 1 Research Assistant, Department of Fisheries, Tamil Nadu, India 2 Nutritionist, Growel Feeds Pvt Ltd, Andhra Pradesh, India 3 Ph.D. student, INRA, France * Corresponding author E-mail: ferosecife@gmail.com References Argamentería, A., F. Muñoz and D. Andueza. 1993. Control de resultados interlaboratorios. ln: Nuevas Fuenfes de Alimentos para la Producción Animal IV, Gómez, A. and E. de Pedro, editors. Junta de Andalucía, Congresos y Jornadas 30:227-234. Cozzolina, D., A. Chree, I. Murray and J. R. Scaife. 2002. The assessment of the chemical composition of fishmeal by near infrared reflectance spectroscopy. Aquaculture Nutrition 8:149155. Dreassia, E., G. Ceramellia, P. L. Perrucciob and P. Corti. 1998. Transfer of calibration in near-infrared reflectance Spectrometry. Analyst 123:1259-1264. Givens, D. I. and E. R. Deaville. 1999. The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review. Australian Journal of Agricultural Research 50:1131-1145. Hymowitz, T., J. W. Dudley, F. I. Collins and C. M. Brown. 1974. Estimation of protein and oil concentration in corn, soybean, and oat seed by near-infrared light reflectance. Crop Science 14:713-715. Jordon, J. R. 1996a. Near infrared: breaking analytical traditions. The Referee. AOAC International, February. Jordon, J. R. 1996b. Chemometrics: calibration for the 90s. The Referee. AOAC International, February. Rinne, R. W., S. Gibbons, J. Bradley, R. Sief and C. A. Brim. 1975. Soybean protein and oil percentages determined by infrared analysis. U.S.Department of Agriculture, Agriculture Research Publication ARC-NC-26. Roberts, C. A., J. W. Stuth and P. Flinn. 2004. Analysis of forages and feedstuffs. Pages 231-267 In: C. A. Roberts, J. Workman Jr. and J. B. Reeves III, eds. Near-Infrared Spectroscopy in Agriculture. Agronomy No. 44. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Madison, WI, USA. Ruiz, N. 2001. Near infrared spectroscopy: present and future applications. ASA Technical Bulletin, FT52-2001:1-13. Williams, P. C. and K. Norris. 1987. Near-Infrared Technology in the Agricultural and Food Industries. American Association of Cereal Chemists, Inc., St. Paul, Minnesota, USA.
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