Correlation Between Cooked Rice Texture and Rapid Visco Analyser Measurements

Transcription

1 Correltion Between Cooked Rice Texture nd Rpid Visco Anlyser Mesurements Eline T. Chmpgne, 1,2 Kren L. Bett, 1 Bryn T. Vinyrd, 3 Ann M. McClung, 4 Frnklin E. Brton II, 5 Kren Moldenhuer, 6 Steve Linscombe, 7 nd Kent McKenzie 8 ABSTRACT Cerel Chem. 76(5): Although mylose content is considered the most importnt determinnt of cooked rice texture, this constituent flls short s predictor, becuse cultivrs with similr mylose contents my differ in texturl properties. Thus, mylogrphy is used s one of bttery of tests, in ddition to mesuring mylose content, to improve differentition of cultivrs. The purpose of our study ws to determine how well mylogrphy conducted with Rpid Visco Anlyser (RVA) serves s predictor of cooked rice texture, lone nd in combintion, with mylose content. Texturl properties of 87 smples representing short-, medium-, nd long-grin rice cultivrs were ssessed by descriptive sensory nd instrumentl texture profile (TPA) nlyses nd relted to RVA mesurements. None of the cooked rice texturl ttributes, whether mesured by descriptive nlysis or TPA, were modeled by RVA with high ccurcy (i.e., high r 2 ). Sensory texture ttributes cohesiveness of mss, stickiness, nd initil strchy coting nd TPA ttribute dhesiveness hd the strongest correltions with RVA mesurements. Setbck explined most of the vrince ttributed to models describing these ttributes; the strongest correltion ws with cohesiveness of mss (r = 0.69; equivlent to coefficient of determintion, r 2 = 0.47). Inclusion of mylose nd protein contents in regression nlyses did not strengthen models. Exclusion of smples tht cook typiclly, bsed on mylose content or geltiniztion temperture types, slightly improved the ccurcy of RVA mesurements for predicting cooked rice texture. The economic vlue of rice in domestic nd interntionl mrkets is strongly ffected by the sensory qulity of cooked rice. Conventionlly, sensory qulity of rice hs been ssessed by combintion of preference sensory evlution nd series of physicochemicl property evlutions. Evlutions re typiclly timeconsuming nd only ssess whether the rice cultivr hs qulity chrcteristics deemed desirble by trget popultion or for specific ppliction, flling short in mesuring subtle differences in sensory qulity. Rpid, ccurte, universl methodologies tht relte physicochemicl mesurements to objective mesurements of sensory ttributes re needed. Amylogrphy is one of bttery of commonly conducted physicochemicl property tests tht serve s indices for sensory qulity. Amylogrphy, which is used for determining geltiniztion nd pste viscosity chrcteristics, trditionlly ws performed on Brbender Viscomylogrph nd required 1.5 hr to perform. Tody the test is routinely conducted with Rpid Visco Anlyser (RVA; Newport Scientific, Wrriewood, Austrli). Viscosity properties mesured on n RVA re similr to those mesured with Brbender Viscomylogrph nd re obtined in 15 min (Blkeney et l 1991). Reltionships exist between mylogrphic mesurements, mylose nd protein contents (two components influencing texture of cooked rice) (Hlick nd Kelly 1959; Julino et l 1964,b; Julino nd Pscul 1980; Del Mundo et l 1989; Sndhy Rni nd Bhttchry 1995), nd instrumentl mesurements of texturl properties (Julino nd Pscul 1980, Okuno nd Ynse 1983, Lee 1988, Sndhy Rni nd Bhttchry 1995). Preference nd difference sensory tests hve been used to relte cooked rice hrdness nd stickiness to mylogrphic mesurements (Tni et l 1969, Sndhy Rni nd Bhttchry 1995); the reltionships between these mesurements nd descriptive sensory evlutions of cooked rice texture hve not been reported. 1 USDA-ARS, Southern Regionl Reserch Center, New Orlens, LA. 2 Corresponding uthor. Fx: ; E-mil: etchmp@nol.srrc.usd.gov 3 USDA-ARS, Biometricl Consulting Service, Beltsville, MD. 4 USDA-ARS, Rice Qulity Lbortory, Beumont, TX. 5 USDA-ARS, Richrd B. Russell Reserch Center, Athens, GA. 6 University of Arknss Rice Reserch nd Extension Center, Stuttgrt. 7 Louisin Stte University Rice Reserch Sttion, Crowley. 8 Cliforni Coopertive Rice Reserch Foundtion, Biggs. Publiction no. C R. This rticle is in the public domin nd not copyrightble. It my be freely reprinted with customry crediting of the source. Americn Assocition of Cerel Chemists, Inc., The purpose of our study ws to determine the extent to which RVA cn be used to predict the texturl properties of cooked rice. Texturl properties were ssessed by descriptive sensory nlysis (n nlyticl, objective methodology) nd instrumentl texture profile nlysis (TPA) nd relted to RVA mesurements. MATERIALS AND METHODS Rice Smples Smples of short-, medium-, nd long-grin rice cultivrs (N = 76) grown in Louisin, Arknss, Texs, nd Cliforni were hrvested t 20% moisture nd dried to 12% moisture. After drying, rice smples were shipped to the USDA-ARS, Rice Reserch Unit, Beumont, TX, where they were stored in closed continers for two to three months t 18 C. One week prior to inititing sensory nlyses, smples were shelled with rice mchine (Stke model SB) nd immeditely milled. Milling ws ccomplished with lbortory one-pss mill (Stke Perler, model SKD). A milling protocol pproprite for yielding rice with whiteness vlues in the trgeted 40 ± 2 rnge considered typicl of regulr-milled rice ws estblished for ech grin-length type. Whiteness ws mesured with milling meter (Stke model MM-1B). Broken grins were removed with pproprite lbortory-sizing devices with stndrd indented pltes nd cylinders. Milled smples were shipped overnight to the USDA-ARS, Southern Regionl Reserch Center, New Orlens, LA. Milled rice smples lso were obtined from 1996 crops in Tiwn (N = 2), Kore (N = 3), nd Austrli (N = 6). When received, smples were immeditely preweighed into portions for sensory, chemicl, nd RVA nlyses nd stored in glss jrs under nitrogen hedspce t 4 C. Chemicl Anlyses Amylose content of smples ws determined in duplicte by the simplified ssy method developed by Julino (1971). Protein contents (N 5.95) were determined in duplicte by the combustion method on nitrogen determintor (FP-428, Leco Corp., St. Joseph, MI). Moisture contents of milled kernels were determined in duplicte on ground mteril oven-dried t 130 C for 1 hr (AMS 1959). The lkli spreding vlue of whole-grin milled rice ws determined in ccordnce with the method of Little et l (1958) with minor modifictions. Six grins from ech smple were immersed in 1.5% KOH solution overnight t room temperture. Ech grin ws exmined visully the next morning for the level of intctness nd ssigned numericl score of 2 7 (2 = reltively intct, 7 = gretly dispersed). Vlues for six grins were verged to produce one vlue per smple. 764 CEREAL CHEMISTRY

2 RVA Anlysis Pste viscosity properties of rice smples were determined using n RVA (Newport Scientific model 3D) nd Approved Method (AACC 1995). Two RVA runs were conducted on ech smple following the schedule estblished for sensory nlyses. The definitions for mesured properties re psting temperture: temperture of initil viscosity increse; pek: mximum viscosity recorded during heting nd holding cycles, usully occurs soon fter heting cycle reches 95 C; pektime: time required to rech pek; trough: minimum viscosity fter pek; finl viscosity: viscosity t test finish, corresponds to mylogrph cool pste viscosity; brekdown: difference ( ) between pek nd trough, indiction of brekdown in viscosity of pste during 95 C holding period; nd setbck: difference ( ) between finl viscosity nd trough. Smple Preprtion for Sensory Anlyses Rice smples (600 g) were rinsed by covering rice three times with cold wter followed by strining to remove excess wter. After rinsing, smples were trnsferred to preweighed rice-cooker insert bowls. Wter ws dded to produce rice-to-wter weight rtios pproprite for three cook types bsed on mylose content (0%, 1:1; 10 19%, 1:1.4; 20 25%, 1:1.7). Rice known to cook similrly to cook type tht does not correspond to its mylose content ws cooked with n mount of wter corresponding to the similr cook type. Rice ws presoked in the cooker insert bowl for 20 min t room temperture nd then cooked in the rice cooker-stemer (Pnsonic SR-W10G HP) to completion, s indicted by the utomtic shift of the cooker to the wrm setting. Rice ws held for n dditionl 10 min t the wrm setting. The top 1-cm lyer of cooked rice nd rice dhering to the sides of the cooker were not used for tsting. Cooked rice for smpling ws tken directly from the middle of the pot, trnsferred to glss bowl prewrmed to 120 C, nd mixed thoroughly while minimizing kernel brekge. Rice smples ( 48 g) were trnsferred with size 18 stinless-steel ice crem scoop to prewrmed (120 C) 175-mL (6-oz) glss custrd cups (Anchor Hocking) insulted by fitted polystyrene bowls, nd covered with 125-mm wtch glsses. One smple ws used for TPA; the remining smples were presented to the sensory pnel. Cooking of smples ws stggered so tht smples were nlyzed by the pnel or texture nlyzer t 20-min intervls. Sensory Evlution Protocol Twelve pnelists who were previously trined in the principles nd concepts of descriptive nlysis (Civille nd Szczesnik 1973, Civille nd Lisk 1975, Munoz 1986, Skinner 1988) were selected to prticipte in the study. The lexicon for rice texture used by the pnel ws bsed on the lexicon developed by Lyon et l (1999) nd Goodwin et l (1996) (Fig. 1). The sensory texture profile included 13 sensory ttributes tht described rice texture t different phses of sensory evlution, beginning with the feel of the rice when it is first plced in the mouth nd ending with mouthfeel chrcteristics fter the rice is swllowed. Ech smple ws presented to the pnelists twice following rndomized design in which ech session consisted of three smples, stndrd, nd blind control (Clrose, commercil cultivr). The stndrd, the wrm-up smple presented t the beginning of ech session, ws used to clibrte the pnel. After the wrm-up smple, coded test smples were presented to pnelists individully t 20-min intervls immeditely fter cooking, holding, nd portioning into serving cups. Evlutions were conducted t individul test sttions under red msking lights. Distilled, filtered wter (Hydrotech drinking wter filtrtion system) ws used to clense the mouth between smples. Fig. 1. Descriptive sensory nlysis ttributes nd definitions used to evlute cooked rice texture. Vol. 76, No. 5,

3 Instrumentl Texture Anlyses TPA ws conducted with texture nlyzer (TA.XT2, Texture Technologies Corp., Scrsdle, NY). A 1-g liquot of wrm rice from n insulted custrd cup ws weighed nd rrnged in singlegrin lyer on the bse plte. A compression plte ws set t 5 mm bove the bse. A two-cycle compression, force-versus-distnce progrm ws used to llow the plte to trvel 4.9 mm, return, nd repet. Test speed ws 1 mm/sec. A cylinder plunger with 50-mm dimeter ws used. The test ws repeted on two duplicte smples (n = 3). Prmeters recorded from test curves (Fig. 2) included hrdness (H1), dhesiveness (A3), cohesiveness (A2/A1), springiness (D2/D1), nd resilience (A5/A4). Gumminess ws obtined by multiplying hrdness by cohesiveness; chewiness is gumminess multiplied by springiness. Vlues represent stndrd clcultions of curve ttributes of TPA s described by Bourne (1982) nd defined by Munoz et l (1992). A distnce (rther thn percent) compression test ws used for TPA becuse of concerns tht height or plcement of single grins in the 1-g liquots might unduly influence the sensed contct height tht determined the beginning of the D1 mesurement used in percent compression tests. Using settings for constnt 5-mm strt nd 4.9 mm of trvel, rice smples were compressed to within 0.1 mm of the bottom plte. Sttisticl Anlyses For sensory dt, sctterplot consisting of the scores ssigned to ech smple in pnel session ws produced for ech pnelist nd ttribute. For given session, sctterplots were exmined visully to identify which pnelists were not performing to consensus during session. No outliers were identified for six ttributes. For the other seven ttributes, one (three ttributes), two (three ttributes), nd three (one ttribute) outlier scores were removed. Blind control smples were used to djust out-session effects. All smple mens obtined in pnel sessions contining blind control smple tht fell outside the 99% confidence limit of the blind control grnd men were djusted inwrd to 99%. This occurred in either no sessions or only one or two sessions for ech descriptor. Correltions were exmined mong two groups of responses by multivrite fctor nlyses: 1) RVA versus sensory texture nd 2) RVA versus instrumentl texture. All dt were stndrdized to zero men nd unit stndrd devition prior to nlysis. The promx method of oblique fctor rottion ws used to ccommodte the presence of correltions mong extrcted fctors. For ech fctor in the fctor nlysis solution, the response vribles loding onto the fctor were used in stepwise multiple regression. Vribles from one group (RVA) were used s regressors to predict vribles from the TABLE I Physicochemicl Dt for Rice Cultivrs Cultivr Loction Grin Type % Amylose % Protein 1.5% Alkli Gel Type M202 TX M 10.3 ± ± ± 0.0 Low M202 CA M 14.8 ± ± ± 0.1 Low M201 TX M 10.7 ± ± ± 0.1 Low-intermedite Pelde TX L 12.2 ± ± ± 0.0 High V 4716 LA M 12.3 ± ± ± 0.0 Low AB 869 LA M 12.4 ± ± ± 0.0 Low CP231 TX L 12.3 ± ± ± 0.0 High CP231 AR L 14.0 ± ± ± 0.0 High M401 TX M 12.4 ± ± ± 0.1 Intermedite-low M401 CA M 17.1 ± ± ± 0.0 Low Sturn LA M 13.1 ± ± ± 0.0 Low Toro 2 TX L 13.2 ± ± ± 0.1 Low-intermedite Bldo TX M 13.1 ± ± ± 0.0 Low Bldo LA M 14.7 ± ± ± 0.4 Intermedite-low Bengl LA M 13.1 ± ± ± 0.0 Low Bengl TX M 13.0 ± ± ± 0.0 Low S201 TX S 13.6 ± ± ± 0.3 Intermedite Mrs LA M 14.0 ± ± ± 0.0 Low Mercury LA M 14.1 ± ± ± 0.3 Low-intermedite Kyeem LA L 14.3 ± ± ± 0.0 High Goolrh LA L 14.4 ± ± ± 0.0 High Clrose 76 TX M 14.5 ± ± ± 0.0 Low Brzos LA M 14.2 ± ± ± 0.3 Low-high Brzos TX M 14.8 ± ± ± 0.0 Low Rico I TX M 15.1 ± ± ± 0.0 Low Kosnbre LA M 15.1 ± ± ± 0.0 Low Arborio LA M 15.2 ± ± ± 0.0 Low Tichung 8 Tiwn M 15.2 ± ± ± 0.1 Low-intermedite Toro 2 LA L 15.3 ± ± ± 0.1 Low-intermedite Pecos LA M 15.4 ± ± ± 0.2 Low-intermedite Akitkmochi CA M 15.6 ± ± ± 0.0 Low Norti LA S 15.8 ± ± ± 0.0 Low Nto LA M 15.8 ± ± ± 0.0 Low-intermedite Koshihikri CA M 16.0 ± ± ± 0.3 Low Nipponbre LA S 16.1 ± ± ± 0.1 Low-intermedite S102 CA S 16.2 ± ± ± 0.0 Low Donguin Kore M 16.5 ± ± ± 0.0 Low Kyeem Austrli L 17.0 ± ± ± 0.1 Intermedite M204 CA M 17.5 ± ± ± 0.0 Low Millin Austrli M 17.5 ± ± ± 0.1 Low Amroo Austrli M 17.6 ± ± ± 0.0 Low Ilpoom Kore M 17.9 ± ± ± 0.0 Low (continued on next pge) TX = Texs, CA = Cliforni, LA = Louisin, AR = Arknss. 766 CEREAL CHEMISTRY

4 other group (sensory or instrumentl texture). A regression ws conducted for ech fctor tht loded t lest one response vrible from ech group. RESULTS AND DISCUSSION Physicochemicl Properties Tble I lists the physicochemicl property dt for the 87 short-, medium-, nd long-grin rice smples nlyzed in this study. Amylose nd protein contents of these nonwxy cultivrs rnged from 10.3 to 24.9% nd 5.1 to 11.3%, respectively. All smples hd been dried fter hrvest to 12% moisture content. Alkli spreding vlues rnged from 2.0 to 7.0, indictive of high to low geltiniztion temperture types. Rice smples contined typicl longgrin cultivrs, which cook dry nd fluffy nd re chrcterized by reltively high mylose contents nd intermedite to high geltiniztion tempertures, nd typicl short- nd medium-grin cultivrs, which cook moist nd clingy nd hve comprtively low mylose contents nd reltively low geltiniztion tempertures (Webb 1985). The set lso contined smples tht were exceptions to the rule. For exmple, Pelde, CP231, Zen, nd Toro 2 re low mylose content (12 13%) types (typicl of long-grin cultivrs). Pelde nd CP231 re high geltiniztion temperture types, nd Zen nd Toro 2 re low geltiniztion temperture types. LA110, IRGA409, El Psso 144, Oryzicol Llmos, Tichung Sen 19, nd Doongr re long-grin, high mylose (21 25%) rices tht re low geltiniztion temperture types. Principl Fctor Anlyses Sensory texture dt. Liner correltions mong sensory texture dt, RVA prmeters, nd mylose nd protein contents were exmined by principl fctor nlysis. Prior to fctor nlysis, dt were subjected to oblique principl component nlysis to identify which vribles cuse collinerity in the correltion mtrix. RVA mesurements pek nd trough were redundnt with brekdown nd finl viscosity, respectively. Therefore, pek nd trough dt were omitted from fctor nlysis. Four fctors were extrcted tht explined 90% of dt vrition (Tble II). The mjority of vrition (51%) ws explined by fctor 1. RVA mesurements setbck (0.93), finl viscosity (0.85), nd brekdown ( 0.78) nd mylose content (0.89) loded highest on fctor 1. Sensory texture ttributes initil strchy coting ( 0.59), stickiness ( 0.68), nd cohesiveness of mss ( 0.78) lodings on fctor 1 were lower; however, the highest lodings of these ttributes ws on fctor 1. Strong lodings on fctor 1 indicte probble liner reltionships mong these ttributes nd mesurements. A positive reltionship between brek- TABLE I (continued) Physicochemicl Dt for Rice Cultivrs Cultivr Loction Grin Type % Amylose % Protein 1.5% Alkli Gel Type Lngi Austrli L 18.0 ± ± ± 0.1 Intermedite Choochung Kore M 18.2 ± ± ± 0.1 Low Illbong Austrli M 18.4 ± ± ± 0.0 Low AS 3510 LA L 20.0 ± ± ± 0.3 Intermedite-high Cypress TX L 20.3 ± ± ± 0.0 High Cypress LA L 21.5 ± ± ± 0.0 Intermedite-high A301 LA L 20.6 ± ± ± 0.1 High-intermedite Lemont TX L 20.7 ± ± ± 0.0 High Lbelle LA L 20.9 ± ± ± 0.1 High-intermedite LA110 LA L 21.2 ± ± ± 0.2 Low Dell LA L 21.4 ± ± ± 0.3 Intermedite-high Bluebonnet LA L 21.5 ± ± ± 0.2 Intermedite-high IR64 TX L 21.5 ± ± ± 0.1 High-intermedite Lcssine LA L 21.6 ± ± ± 0.0 High-intermedite Lebonnet LA L 21.7 ± ± ± 0.1 High-intermedite Dellmont LA L 21.8 ± ± ± 0.0 High-intermedite Leh LA L 22.3 ± ± ± 0.1 High-intermedite Kybonnet TX L 21.8 ± ± ± 0.1 High-intermedite Kybonnet AR L 22.4 ± ± ± 0.2 High-intermedite Strbonnet LA L 21.9 ± ± ± 0.1 Intermedite-high Tebonnet LA L 22.0 ± ± ± 0.0 Intermedite-high Tebonnet AR L 22.3 ± ± ± 0.2 Intermedite-high Doongr Austrli L 22.4 ± ± ± 0.4 Intermedite-low Dwn LA L 22.6 ± ± ± 0.3 Intermedite-high Drew AR L 22.7 ± ± ± 0.2 Intermedite-high L204 CA L 22.7 ± ± ± 0.2 Intermedite Bellemont LA L 23.0 ± ± ± 0.1 High-intermedite Oryzicol Llmos LA L 23.2 ± ± ± 0.0 Low Newrex LA L 23.5 ± ± ± 0.1 Intermedite-high Rexmont AR L 23.6 ± ± ± 0.1 Intermedite-high Rexmont LA L 23.7 ± ± ± 0.0 Intermedite-high IRGA409 TX L 23.8 ± ± ± 0.0 Low L202 TX L 24.0 ± ± ± 0.0 High L202 AR L 24.1 ± ± ± 0.2 High-intermedite Guichow LA M 24.1 ± ± ± 0.0 Low A201 CA L 24.1 ± ± ± 0.0 Intermedite AB 647 LA M 24.2 ± ± ± 0.0 Low Tim LA L 24.3 ± ± ± 0.0 Intermedite Nnking Sel LA M 24.5 ± ± ± 0.0 Intermedite El Psso 144 TX L 24.5 ± ± ± 0.0 Low IR72 TX L 24.5 ± ± ± 0.1 Intermedite-high L203 CA L 24.8 ± ± ± 0.2 Intermedite-high Chui 1 LA L 24.8 ± ± ± 0.1 Intermedite-high Dixiebelle TX L 24.9 ± ± ± 0.1 High-intermedite Tichung Sen19 Tiwn L 24.9 ± ± ± 0.0 Low TX = Texs, CA = Cliforni, LA = Louisin, AR = Arknss. Vol. 76, No. 5,

5 down nd stickiness hs been reported (Tni et l 1969). A negtive reltionship of mylose with brekdown nd positive reltionships with mylogrphic finl viscosity nd setbck lso hve been reported (Julino 1964, Julino nd Pscul 1980). Fctor 2 explined 20% of dt vrition. Sensory texture ttributes springiness (0.73) nd hrdness (0.74) loded high on fctor 2. Chewiness (0.56), toothpcking (0.41), residul loose prticles (0.38), cohesiveness (0.37), moisture bsorption ( 0.38), nd uniformity of bite ( 0.51) exhibited their highest loding on fctor 2, but the vlues of these ttributes were reltively low. No RVA mesurements loded high on fctor 2. Protein content (0.65) nd RVA mesurements psting temperture (0.55) nd slickness ( 0.66) loded highest on fctor 3, which explined 10% of dt vrition. Fctor 4, which explined 9% of dt vrition, hd the highest lodings for pektime (0.69) nd roughness (0.50). TPA dt. Liner correltions mong instrumentl TPA dt, RVA mesurements, nd mylose nd protein contents lso were exmined by principl fctor nlysis. Four fctors were extrcted tht explined 89% of dt vrition (Tble III). Fctor 1 represented the mjority of vrition t 48%. The only mesurements tht exhibited their highest loding on fctor 1 were TPA ttributes gumminess (0.87), hrdness (0.82), resilience (0.78), nd cohesiveness (0.60). Lodings of RVA mesurements on fctor 1 were very low ( ). Fctor 2 explined n dditionl 21% of dt vrition. RVA mesurements setbck (0.82), finl viscosity (0.71), brekdown ( 0.60), nd psting temperture (0.58) hd their highest lodings on fctor 2. The only TPA ttribute to hve its highest loding on fctor 2 ws dhesiveness (0.74). Amylose (0.75) lso loded high on fctor 2. Protein loding on fctor 2 ws low (0.35) but ws the highest loding of this mesurement on fctor. Springiness (0.94) nd chewiness (0.77) hd their highest lodings on fctor 3, which represented n dditionl 11% of dt vrition. No RVA mesurements loded on this fctor. Fctor 4 explined 9% of dt vrition. Pektime ws the only mesurement to hve its highest loding on this fctor. Stepwise Multiple Regression Anlyses RVA mesurements versus sensory texture or TPA ttributes with the strongest liner correltions, s indicted by fctor lodings, were subjected to stepwise multiple regression nlyses to determine how well RVA mesurements predicted cooked rice texture. Sensory texture dt. Tble IV shows the multiple regression nlysis results for predicting cohesiveness of mss, stickiness, initil strchy coting, slickness, cohesiveness, nd hrdness from RVA mesurements. Setbck explined most of the vrince ttributed to the models describing cohesiveness of mss (47%), stickiness (33%), TABLE II Principl Fctor Anlysis of Sensory Texture Dt, Rpid Visco Anlyser (RVA) Mesurements, nd Amylose nd Protein Contents Vrible Fctor 1 Fctor 2 Fctor 3 Fctor 4 Chemicl composition Amylose Protein Sensory texture Initil strchy coting Slickness Roughness Stickiness Springiness Cohesiveness Hrdness Cohesiveness of mss Chewiness Uniformity of bite Moisture bsorption Residul loose prticle Toothpcking RVA mesurement Psting temp Pektime Finl viscosity Brekdown Setbck % Vrition explined (totl = 90%) Bold vlues indicte highest lod for ech vrible. Fig. 2. Typicl texture profile nlysis (TPA) curve of 1-g rice smples. TPA text prmeters: force-distnce test, compression plte set t 5 mm to trvel 4.9 mm t 1 mm/sec. Attributes on curves: H1, hrdness (kg), mesurement of force t pek of first curve; A1, re under first curve; A2, re under second curve; A4, mesured from first dt point to first probe reversl point; A5, mesured from first probe reversl point to point where force returns to zero; A2/A1, cohesiveness, rtio of re under curves A2/A1; A3, dhesiveness, re of negtive force curve, representing work to seprte plunger from smple on upstroke fter first curve; D2/D1, springiness, rtio of D2 to D1, where D1 is totl distnce (4.9 mm) trveled by plunger on downstroke nd D2 is distnce trveled on downstroke by plunger from point of smple contct to end of downstroke. TABLE III Principl Fctor Anlysis of Instrumentl Texture Dt, Rpid Visco Anlyser (RVA) Mesurements, nd Amylose nd Protein Contents Vrible Fctor 1 Fctor 2 Fctor 3 Fctor 4 Chemicl composition Amylose Protein Instrumentl texture Adhesiveness Resilience Hrdness Cohesiveness Gumminess Springiness Chewiness RVA mesurement Psting temp Pektime Finl viscosity Brekdown Setbck % Vrition explined (totl = 89%) Bold vlues indicte highest lod for ech vrible. 768 CEREAL CHEMISTRY

6 nd initil strchy coting (31%). The full, multiple regression models explined 56, 45, nd 40% of the vrition in cohesiveness of mss, stickiness, nd initil strchy coting, respectively. Most of the vrince ttributed to the models describing slickness (14%) nd cohesiveness (8%) ws explined by psting temperture. Only 22 nd 12% of the vrition in slickness nd cohesiveness, respectively, were explined by the full models. Brekdown (22%) explined most of the vrince in the model for hrdness; the full model explined 26% of the vrition. Tble V shows the effect of including mylose nd protein contents s vribles in the multiple regression nlyses. Inclusion of these vribles hd little effect on the mount of vrince ttributed to the models describing sensory ttributes. Setbck still explined 33 nd 31% of the vrition in stickiness nd initil strchy coting, respectively. However, most of the vrince (48%) in the model for cohesiveness of mss ws explined by mylose; setbck ws not included s vrible. Most of the vrince (21%) in the model for slickness ws explined by protein; psting temperture explined only 5% of the vrince. Psting temperture still explined 8% of the vrince in cohesiveness; protein ws not included s vrible. Brekdown (22%) still explined most of the vrince in hrdness when mylose nd protein were included s vribles in the nlysis. Amylose explined 8% of the vrince; the contribution of protein to the model ws smll. TPA dt. Tble VI shows the multiple regression nlysis results for predicting dhesiveness using RVA mesurements. Setbck explined most of the vrince (38%) ttributed to the model describing dhesiveness. The full model explined 48% of the vrition in dhesiveness. Tble VI lso shows the effect of including mylose nd protein s vribles. Amylose nd protein explined 50 nd 2%, respectively, of the totl vrince (58%) ttributed to the model. Only 1% of the vrince ttributed to the model ws explined by setbck. Exception-to-the-rule smples. The exception-to-the-rule smples tht cook typiclly of their mylose content or geltiniztion temperture types were excluded from the dt set to determine whether their exclusion would improve the ccurcy of RVA mesurements in predicting cooked rice texture. The bility of the full models to predict sensory nd instrumentl texture ttributes improved slightly, s indicted by incresed r 2 vlues ( ). Correltions of mylose nd protein contents to combined texture ttributes nd RVA mesurements. Becuse mylose is considered the single most importnt determinnt of cooked rice texture, mylose ws modeled s combintion of texture ttributes nd RVA mesurements. As shown in Tble VII, sensory ttributes cohesiveness of mss nd stickiness explined 53% of the model vrince for mylose; most of the vrince ws explined by cohesiveness of mss (47%). The model describing mylose in terms of TPA ttributes ws stronger thn tht described by sensory ttributes. TPA ttributes dhesiveness (50%), hrdness (9%), nd cohesiveness (6%) explined model vrince. The direct correltion between mylose nd hrdness ws r = 0.45 (dt not shown). In comprison, Ohtsubo et l (1990) reported correltion of mylose to texturometer dhesiveness nd hrdness of r = nd , respectively, for set of 29 smples with mylose contents in the rnge of %. Reported correltions of mesurements of Instron hrdness to mylose hve rnge of r = (Perez nd Julino 1979, Ohtsubo et l 1990). The model for protein content in terms of sensory ttributes ws wek (r 2 = 0.29); slickness (21%), roughness (4%), nd stickiness (4%) explined the vrince (Tble VII). Combined TPA ttributes correlted more poorly with protein with the model explining only 9% of the vrince. Tble VIII shows the bility of combined RVA mesurements to predict mylose nd protein contents. RVA mesurements explined TABLE IV Multiple Regression Anlysis for Predicting Sensory Texture Attributes from Rpid Visco Anlyser (RVA) Mesurements Dependent Vrible Vrible Model r 2 F P > F Cohesiveness of mss Setbck Psting temp. pektime Setbck setbck Psting temp Psting temp. psting temp Stickiness Setbck Brekdown psting temp Setbck setbck Setbck psting temp Finl viscosity Initil strchy coting Setbck Setbck finl viscosity Brekdown psting temp Psting temp. psting temp Setbck psting temp Slickness Psting temp Setbck Finl viscosity psting temp Cohesiveness Psting temp Setbck Psting temp. psting temp Hrdness Brekdown Setbck brekdown Vribles entered into model consecutively s listed; model r 2 is cumultive with ddition of ech vrible. TABLE V Multiple Regression Anlysis for Predicting Sensory Texture Attributes from Rpid Visco Anlyser (RVA) Mesurements nd Amylose nd Protein Contents Dependent Vrible Vrible Model r 2 F P > F Cohesiveness of mss Amylose Finl viscosity Brekdown protein Stickiness Setbck Brekdown psting temp Setbck setbck Finl viscosity protein Finl viscosity mylose Initil strchy coting Setbck Setbck finl viscosity Brekdown psting temp Finl viscosity protein Finl viscosity brekdown Psting temp. mylose Slickness Protein Psting temp Psting temp. protein Cohesiveness Psting temp Hrdness Brekdown Amylose mylose Brekdown protein Amylose protein Vribles entered into model consecutively s listed; model r 2 is cumultive with ddition of ech vrible. Vol. 76, No. 5,

7 90% of model vrince for mylose, with setbck (71%) explining most of the vrince. The correltion of mylose with setbck (r = 0.84) ws higher thn ws reported in n erlier RVA study (r = 0.64) (Delwiche et l 1996). The model for protein using RVA mesurements ws not s strong. The totl model for protein explined 41% of the vrince; most of the vrince ws ttributed to psting temperture (15%). CONCLUSIONS Although mylose content is considered the most importnt determinnt of cooked rice texture, this constituent flls short s predictor, becuse cultivrs with similr mylose contents my differ in texturl properties. Thus, mylogrphy is used s one of bttery of tests, in ddition to mesuring mylose content, to improve differentition of cultivrs. The intent of our study ws to determine how well mylogrphy conducted using n RVA serves s predictor of cooked rice texture, s stnd-lone tool nd in combintion with mylose contents. We concluded tht none of the cooked rice texturl ttributes, whether mesured by descriptive nlysis or instrumentl TPA, were linerly modeled with high ccurcy by RVA. Sensory texture ttributes cohesiveness of mss, stickiness, nd initil strchy coting nd TPA ttribute dhesiveness hd TABLE VI Multiple Regression Anlysis for Predicting Instrumentl Adhesiveness from Rpid Visco Anlyser (RVA) Mesurements With nd Without Amylose nd Protein Contents Included Dependent Vrible Vrible Model r 2 F P > F Adhesiveness: model without mylose nd protein Setbck Brekdown Psting temp Adhesiveness: model with mylose nd protein Amylose Brekdown mylose Protein Setbck Setbck psting temp Vribles entered into model consecutively s listed; model r 2 is cumultive with ddition of ech vrible. TABLE VII Multiple Regression Anlysis for Determining Correltion Between Amylose nd Protein Contents nd Combined Sensory or Instrumentl Texture Profile (TPA) Anlyses Attributes Dependent Vrible Vrible Model r 2 F P > F Amylose: model with combined sensory ttributes Cohesiveness of mss Stickiness Amylose: model with combined TPA ttributes Adhesiveness Hrdness Cohesiveness Protein: model with combined sensory ttributes Slickness Roughness Stickiness Protein: model with combined TPA ttributes Adhesiveness Cohesiveness Vribles entered into model consecutively s listed; model r 2 is cumultive with ddition of ech vrible. the strongest correltions with RVA mesurements. Setbck explined most of the vrince ttributed to models describing these ttributes; the strongest correltion (r = 0.69) ws with cohesiveness of mss. Inclusion of mylose content in regression nlyses did not strengthen models. Exclusion of smples tht cook typiclly of their mylose content or geltiniztion temperture types did not improve the ccurcy of RVA mesurements in predicting cooked rice texture. Ascertining how well mylose predicts cooked rice texture is difficult bsed on prior studies (e.g., Julino et l 1965, Perez nd Julino 1979, Sowbhgy et l 1987, Del Mundo et l 1989, Ohtsubo et l 1990, Perez et l 1993, Kwmur et l 1996). Interprettion nd comprison of results mong these studies is difficult becuse n rry of different sensory evlution methods (e.g., preference, difference tests) using the mouth or fingers were used, nd the sensory texturl ttributes mesured were not defined or uniformly defined. Additionlly, texture evlutions in these studies were limited to properties such s firmness or tenderness, stickiness, nd dhesiveness tht fll short in cpturing the complexity of rice texture. In our study, we were ble to better ssess rice texture in its entirety using descriptive sensory nlysis, which is n nlyticl, objective methodology. Using this methodology, trined pnelists identified 13 sensory ttributes tht described rice texture t different phses of sensory evlution, beginning with the feel of the rice when it ws first plced in the mouth nd ending with mouthfeel chrcteristics fter the rice ws swllowed. Correltion of the intensities of the 13 texturl ttributes with mylose produced model with r 2 = 0.53; cohesiveness of mss (47%) nd stickiness (6%) explined vrince. The model describing mylose s combintion of TPA mesurements ws stronger (r 2 = 0.65) thn the model with combined sensory ttributes. Adhesiveness (50%), hrdness (9%), nd cohesiveness (6%) explined model vrince. There re few reports relting protein content nd cooked rice texture (Primo et l 1962, Onte et l 1964, Julino et l 1965). In our study, the impct of protein content on cooked rice texture ppered to be minor. Protein content ws wekly, negtively correlted to slickness nd stickiness nd wekly, positively correlted to roughness. When protein content ws included in the model explining sensory texture using RVA mesurements, it replced psting temperture in describing slickness. The model, however, ws wek. TABLE VIII Multiple Regression Anlysis for Determining Correltion Between Amylose nd Protein Contents nd Rpid Visco Anlyser (RVA) Mesurements Dependent Vrible Vrible Model r 2 F P > F Amylose: model with combined RVA mesurements Setbck Setbck setbck Brekdown Finl viscosity Psting temp. psting temp Finl viscosity finl viscosity Brekdown psting temp Protein: Model with combined RVA mesurements Psting temp Finl viscosity pektime Finl viscosity finl viscosity Finl viscosity Setbck Finl viscosity brekdown Finl viscosity psting temp Psting temp. pektime Psting temp. psting temp Setbck pektime Vribles entered into model consecutively s listed; model r 2 is cumultive with ddition of ech vrible. 770 CEREAL CHEMISTRY

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