Study On Predictive Model For Edible Quality Of Rice Blends And The Mechanism

Edible quality of rice has become the decisive factor in rice market, and the application of rice blends is a good way of improving edible quality of rice, therefore the relevant study is of important significance. However, the related comprehensive study is scarce. This study is to obtain the predictive model relating edible quality with all other parameters by making analysis on the correlation of edible quality with all other parameters of different rice cultivars, and to make the model validated in rice blends, finally the predictive model that can applied in rice blends have been established and to make analysis on mechanism of edible quality. The main research results are as follow1. The amylose content (AC) and blue value (BV) of rice have significant correlation with hardness (HRD)(0.7412,0.5457), adhesiveness (ADH) (0.5553,0.4997), gumminess (GUM) (0.7071,0.5543), chewiness (CHW) (0.5136,0.5446) and resilience (RES) (0.6798,0.5512)of the cooked rice, the protein (PRO) of rice has no significant correlation with all texture properties of cooked rice. AC has significant correlation with Peak viscosity (0.4673), viscosity hold (0.6354), viscosity end (0.7814), breakdown (0.7473) and peak time (0.7976)of the rice flour, however, PRO and BV have no significant correlation with all pasting properties of rice flour. The flavor (-0.6094)and palatability(-0.7083)of the cooked rice have significant negative correlation with AC, only PRO has significant negative correlation with color (-0.3989)of the cooked rice and physicochemical properties of rice have no significant correlation with form and aroma that are sensory properties. The breakage that is one of the pasting properties has significant negative correlation with all texture properties(-0.3685,-0.3824,-0.4408,-0.6495,-0.4937,-0.6077,-0.5519)。Pasting temperature have no significant correlation with all the textural properties, the flavor and palatability have significant negative correlation with HRD(-0.5092,-0.6714), ADH(-0.4901,-0.6438), GUM(-0.5208,-0.6922), CHW(-0.4833,-0.6353), RES(-0.5208,-0.6773). Springiness (SPR) have no significant correlation with sensory properties.The principal component analysis for physicochemical property show that the first eigenvalue (51.96%) explained by AC(-0.86749), WC(0.72386), WAR(0.77708); the sencond eigenvalue (20.38%) explained by SC (0.78159), BV (0.64701), T(-0.71039). the third eigenvalue (13.82%) explained by Pro (-0.67425). the fourth eigenvalue (13.82%) explained by (12.91%) explained by PH. The principal component analysis for pasting property show that the first eigenvalue (51.96%) explained by visc hold (0.93366), visc end (0.98086), setback (0.94837); the sencond eigenvalue (26.45%) explained by peak visco(0.89245) and setback (0.90993); the third eigenvalue (11.43%) explained by paste temperature(0.84884).Based on the regression analysis and parameter estimate, the predictive models that relating physicochemical and pasting properties of rice to texture, pasting and sensory properties have been established, which are of high accuracy. These models are basis for the development of the instrument for fast and accurate evaluation of the edible quality.2 As for the predictive models relating physicochemical property, all the measued value of rice blends are within the 95% confidence limit, and as for the predictive models relating pasting property to textural property, more than 90% of the measured value are within the 95% confidence limit, which indicated the success validation and application of models in rice blends. The coefficients of all the optimized predictive models are higher than the original one, and only small difference parameter estimate compared with the original one. These models are basis for the development of the:automatic rice-selling machine for blending rice to meet the needs of the edible quality controlled by computer.3 SEM (scanning electron microscope) analysis show that the pore and cavity for the starch granule of rice of low amylose content are more than those of rice of high amylose content. These pore and cavity maybe have osmosis effect when the starch gelatinized, because this is good for water to come into and for the amylose to come out, which directly leads to the swelling of rice starch granule.FT-IR (Fourier transform-infrared) analysis of changing temperature show that the change in proportion of area of crystalline(1047 cm-1)to non-crystalline(1022 cm-1)is related to amylose content of rice, because higher amylose can prevent the damage of structure of starch crystal in the process of heating. The peak of different rice cultivars are almost the same in crystalline and in non-crystalline area, but a certain difference in the peak of different rice cultivars in crystalline and in non-crystalline area really exist after heating, and the change in peak position in crystalline area is bigger than that of non-crystalline area.FT-IR (Fourier transform-infrared) analysis of changing temperature show that the change in proportion of area of crystalline(1047 cm-1)to non-crystalline(1022 cm-1)is related to amylose content of rice, because higher amylose can prevent the damage of structure of starch crystal in the process of heating. The peak of different rice cultivars are almost the same in crystalline and in non-crystalline area, but a certain difference in the peak of different rice cultivars in crystalline and in non-crystalline area really exist after heating, and the change in peak position in crystalline area is bigger than that of non-crystalline area.DSC (Differential Scanning Calorimetry) analysis show that peak for the Guangliangyou558(Amylose24.00) of the medium AC appear the first, the pasting temperature and pasting enthalpy are the lowest, which indicate that the heat energy required for the melting of crystalloid is the lowest. AC have no correlation with pasting temperature and pasting enthalpy. DSC property of rice blends is the simple combination of the original cultivars, not any strengthening or weakening.