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THE USE OF NIR IN PREDICTING NUTRITIVE VALUE OF GRASS SAMPLES AT ANIMAL FEED LABORATORY, IVM.

The rapid analysis for predicting nutritive value of grass samples with near infrared reflectance spectroscopy was studied. Wet chemistry analysis for dry matter, total ash, crude protein, crude fat, crude fibre and minerals were time consuming, involve high cost and maintenance. NIRs technology can save considerable time by testing all the parameters simultaneously; however accurate calibration of the equipment is essential. Near infrared (NIR) partial least square (PLS) regression models for determination of several grasses quality parameters were developed from NIRFlex Model N-500 (Buchi). In general, reliable prediction results were obtained for crude protein (SEP = 0.72 r2 = 0.98) and total ash (SEP = 0.64 r2 = 0.95) PLS regression models. Fifty-seven percent from 10,338 of forage samples received by Animal Feed Laboratory, IVM since 2000 to 2014 are grass samples. Data showed grass samples are among the most frequent samples sent by costumer. Nutritive value of grass is not consistence due to geographic location, environmental conditions (temperature, humidity and precipitation), types and age of grass, and grazing management (Stockin et al. 2006). It is important to evaluate grass sample quality periodically to ensure that nutrient needs of the farm’s animal group are met. Therefore, a new and reliable method should be developed to analyze grass quality accurately and fast. NIRs technology definitely can be a solution, it also has been approved by the Association of Official Analytical Chemists (AOAC) for use in determining moisture, Kjeldahl nitrogen and acid detergent fibre for feed and forage analysis (Undersander, 2006).

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Norlindawati, A. P.1*, Shariff, S.2, Noormah Miw, A.2, Sabariah, B.1, Samijah, A.1, and Mohd. Supie, J.1 1Malaysia Veterinary Institute, KM13 Jalan Batu Pahat, Beg Berkunci 520, 86009 Kluang, Johor, Malaysia. 2Makmal Kesihatan Awam Veterinar Salak Tinggi, Jalan Nilai Banting, Bandar Baru Salak Tinggi, 43900 Sepang, Selangor, Malaysia
*Email: norlindawati.dvs@1govuc.gov.my


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