Refinar búsqueda
Resultados 1-2 de 2
Feasibility of near-infrared reflectance spectroscopy for predicting amino acids composition in edible bird’s nest
2016
Suhaimi D. | Wan Syahidah H. | Sharif S. | Normah Miw A.
A preliminary study of nearinfraredreflectance spectroscopy (NIRS)for the feasibility of analytical monitoring ofamino acids and total protein compositionsin edible bird’s nest (EBN) was conducted.The training (n=134) and validation sets todevelop the equations were built with localunprocessed EBN samples sourced fromdifferent states of Malaysia. The regressionmethod employed was modified partialleast-squares (MPLS). The values ofstandard error for cross validation (SECV)and the coefficient of determination (r2)of the calibrations of these constituentsfor use to predict of amino acids in EBNwere determined, but with a low predictiveability. To find an acceptable accuracyfor each constituent is to increase thenumber of training samples. The findings,however, showed a potential alternativefor the implementation of near-infraredreflectance spectroscopy technology inthis field of analysis.
Mostrar más [+] Menos [-]Analysis of palm kernel cake by near infrared reflectance technology
2013
Noormah Miwa A. | Shariff S. | Omar R. | Samijah A. | Norlindawati A. P. | Supie J. | Sabariah B. | Jamnah O.
The rapid method for predicting palm kernel cake quality with near infrared reflectance spectroscopy was investigated. Chemical tests for moisture, ash, crude protein, crude fat, crude fibre, total digestible nutrients (TDN), nitrogen free extract (NFE), metabolisable energy (ME), calcium and phosphorous were time
consuming and involve high cost. This 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 palm kernel cake quality parameters were
developed from NIRFlex Model N-500 (Buchi). In general, reliable prediction results were obtained for the TDN (SEP = 0.85 r2 = 0.99), NFE (SEP = 0.42 r2 = 0.97) and crude protein (SEP = 0.57 r2 = 0.98)
PLS regression models.
Mostrar más [+] Menos [-]