Predicting rice bran nutrients based on physical characteristics

Abstract

Rice bran is a feedstuffs widely used for both ruminants and non ruminants. The main problem of using rice bran as feedstuff is adulteration that quite often exists during dry season. Therefore, application of rapid test technique is essential to assess the quality of rice bran quickly. The aim of this study was to predict nutrient content of rice bran through measuring its physical characteristics. Twenty one standard samples made from mixture combination of 0-100% husk and rice bran were analyzed their chemical composition (proximate analysis) and physical characteristics (density test, density compaction test, total solubility test and fluoroglucinol test). The data were analysed with the least square method of regression, and the equations obtained were then validated on 61 rice bran samples to know standard of prediction (SEP) and coefficient variable (CV) values. There were correlations (P< 0.05) between physical characteristics and nutrient content of rice bran. The content of ash, crude protein, crude fibre, and crude fat could be predict with total solubility equation y (ash) = 28.81-0.624x (total solubility), y (crude protein) = - 5.012+ 0.657x, y (crude fibre) = 72.31- 2.058x, and y (crude fat) = -10.42 + 0.982x. The SEP and CV values from those equations are respectively 2.52%, and 23,62%; 2.53% and 23.50%; 8.20% and 56.91%; and also 3.80% and 35.49%. Fluoroglucinol test could also be used to predict crude protein with the equation y (crude protein )= 12.86 - 0.1046x (prediction of rice husk), with CV and level of acceptance (0.05%) were 19.13% and 28.57%. Multiple regression model showed that crude protein could be predict with the equation y (crude protein)= -3.03 + 9.4x1 – 9.9x2 + 0.629x3, r = 0.994 with x1 was density test, x2 was density compaction test, and x3 was total solubility test with SEP and CV value 2.26% and 20.99%. It is concluded that chemical composition of rice bran could be predict by measuring total solubility especially for ash and crude protein, while fluoroglucinol test and multiple regression of physical test was capable of predicting crude protein of rice bran.