Study On Evaluation Of Food Texture Based On Chewing Simulation

Evaluation of food texture is an important aspect of food detection, has greatsignificance to food development, preservation and keeping, trade and transport, and hassome effects on human health and taking nutrition. Presently, there are two methods aboutevaluation of food texture, which are sensory assessment and instrument measurement.Sensory assessment is subjective, instabile, time consuming and laborious, while instrumentmeasurement mostly belongs to half-experience and simulation test, has much differencewith sensory assessment, and cann't determine multiple texture characters furthermore. Withthe rapid development of food industry and increasing request of high quality food,evaluation of food texture becomes more and more important, and it needs a rapid, objective,accurate and hominine assessment method. So chewing simulation system was developed bythe technology of bionic, reverse engineering and analysis of finite element in the paper,aiming at the issue and actuality of evaluation of food texture, and multiple food texturecharacters were detected by the system under lots of evaluation patterns.1． Chewing simulation system was designed and developed including hardwareequipment and testing software. Configuration data of human chewing system was acquiredby scanning human chewing organs using Three-dimensional Laser Scanner and ComputedTomography Scanner. Chewing simulation system was developed and optimized byengineering softwares such as Imageware12, Unigraphics6.0, SolidWorks2008, Ansys10.0and so on, then was made by CAD/CAM system, including bionic teeth, bionicparodontiums, bionic jaws, bionic temporomandibular joints, driving mechanism,temperature and humidity conditions, ancillary mechanisms, signal disposing circuit etc.Testing software was designed by Visual C++6.0, including signal gathering, texture dataprocessing and figure analyzing module. After movement and chewing function of chewingsimulation system were analyzed and tested, the results show that chewing simulationsystem can realize up, down, forward, back and offset three dimensional motion alike humanchewing system, and chewing force achieve the power chewing kinds of texture foods, andmasticatory efficiency is up to90%, stable, and no significant difference with subjects'.2．Experiment conditions of the chewing simulation system were ascertained by testingnine representative texture foods. Influence that bionic parodontiums, spring imitatingchewing muscle, motor speed and temperature and humidity conditions to chewing signalwas analyzed by difference, repetition and category analysis, and the optimal experimentconditions were obtained. The suitable sensors receiving testing signal are the bionicparodontiums under and around the first bionic molar on the bionic mandible. The optimalranges of elastic coefficient to kinds of samples are different, and carrot's is no less than30N/mm, bread's no less than5N/mm, waxy corn, bean curd, ham sausage and crackers' noless than10N/mm, and apple, pickle and peanut s' no less than20N/mm. Motor speed has alittle effect on testing signal, so it should keep invariable. While carrot, peanut, apple andwaxy corn are tested, range of motor speed is60～90r/min, and while pickle, bean curd, hamsausage, bread and cracker tested, it is60～120r/min. Temperature and humidity conditions have notable influence on testing signal, so the suitable temperature is37℃, and the flow ofartificial saliva is3mL/min when the chewing simulation system chewing samples.3．Under the texture profiling analysis mode, lots of texture parameters of kinds offoods were analyzed and evaluated by chewing simulation system, sensory assessment anduniversal food texture analyzer. These foods are carrot, apple, pickle, peanut, waxy corn,bean curd, ham sausage, bread and cracker. These texture parameters are hardness,brittleness, adhesiveness, cohesiveness, springiness, chewiness and recovery property. Basedon human sensory assessment, texture profiling analysis of chewing simulation system wasset up by correlation, multivariate regression, BP network analysis, compared with universalinstrument measurement. Pearson coefficients show that the correlation is good betweenmeasurement of chewing simulation system and sensory assessment to every food samples,the chewing simulation system can replace human sense, and the correlation of chewingsimulation system testing is better than universal instrument measurement with sensoryassessment. Multivariate regression analysis shows that texture regression models on thesamples are in effect and accurate, the average error and standard residual is little and thedifference is not significant between predictive and measured value. BP network analysisshows that every BP models on the samples are effective and can satisfy with food textureevaluation.4．Food fracture mechanical model was set up based on chewing simulation. On basis ofthe "pestle and mortar" chewing model of chewing simulation system, force of materielblock was analyzed during being crushed, and fracture mechanical model was set up. Effectsof materiel block, bionic molar shape and chewing speed on the model were analyzed andcarrot, apple, pickle samples were measured to validate the model. Experiment results showthat fracture mechanical equations are correct and can express the relations between fractureforce and failure stress accurately, the fracture force of chewing simulation system canreflect the situation of materiel fracture and brittleness during being crushed. Chewingfracture force was validated and compared by sensory assessment of brittleness and threepoint bend test. Experiment results show that relations between chewing fracture force, valueof three point bend test and sensory assessment of brittleness are very marked, and thecoefficients of chewing fracture force are bigger than value of three point bend test tobrittleness sensory assessment of three samples. Regression models between chewingfracture force and sensory assessment are accurate and can predict the brittleness of crispfruits and vegetables.5．Evaluation method of food chewiness was established using the chewing work ofchewing simulation system to food, under the time after time chewing mode. Effects ofspring imitating chewing muscle and motor speed on the masticatory efficiency wereanalyzed by multiple factors variance analysis, masticatory efficiency of chewing simulationsystem was compared with conner when peanuts were chewed. Experiment results show thatmotor speed has no notable effect on masticatory efficiency, while elastic coefficient ofbionic spring has great effect, and the interaction of two factors is not effective. Masticatoryefficiency of chewing simulation system has no difference with human's, and is stable after duplicated examination, and it can reach human's by adjusting elastic coefficient of bionicspring. Crushing efficiency was ascertained while swallowing after analyzed granularity ofpeanut draff during human chewing. Results show that difference of crushing efficiencybetween every group is not remarkable while swallowing and granule size is stable, peanutbolus can consider to be swallowed when crushing efficiency reaches91.67%. Area thatchewing signal curves enclose time axis is as chewing work while crushing food, byextracting chewing signal curves while swallowing. After chewing simulation system testingand sensory assessment of chewiness to peanut samples, chewing work and sensorychewiness were analyzed by relation and regression. Results show that the correlation isgood between chewing work and sensory assessment and the regression model betweenchewing work and sensory assessment is accurate and can predict the food chewiness underthe time after time chewing mode.In conclusion, chewing simulation system is as human chewing system from structureto function, can chew food and evaluate food texture. Food texture evaluation method setunder lots of patterns can measure kinds of texture characters. Chewing simulation system isobjective, accurate and close to human, better than other Food Texture Analyzer aftercomparative test on food texture evaluation.