enhancement of corn nixtamalization by power ultrasound

ORIGINAL PAPER

Enhancement of Corn Nixtamalization by Power Ultrasound

Bhaskar Janve & Wade Yang & Austin Kozman &

Charles Sims & Arthur Teixeira &

Michael A. Gunderson & Taha M. Rababah

Received: 29 September 2011 /Accepted: 24 February 2012 /Published online: 25 March 2012# Springer Science+Business Media, LLC 2012

Abstract Nixtamalization, a key production step for masaflour used for tacos, corn tortillas, and chips, traditionallyinvolves corn kernel cooking for 1 h and a lengthy processof steeping (16–18 h) in a lime solution. This study aimed ataccelerating the traditional nixtamalization (TN) processusing power ultrasound with acoustic energy density around1.85 W/g for 1 h during cooking followed by brief steepingfor 1 h. The cooked kernels (nixtamal) were evaluated fortexture and color, while the cooking liquor (nejayote)was evaluated for solid losses. The power ultrasound-assisted nixtamalization resulted in significantly (p≤0.05) reduced process time and softer nixtamal with lesssolid losses in nejayote than control (TN). Response

surface methodology established significant relation-ships of sonication duration and cooking temperatureto texture, color of nixtamal, and dry matter loss innejayote. This study indicates that power ultrasoundameliorated traditional nixtamalization in terms of qualityand operation time.

Keywords Power ultrasound . Nixtamalization . Corn .

Masa . Tortilla

Nomenclaturea (Color scale, +Value0red, −value0green)A Area (in square centimeters)AED Acoustic energy density (in watts per gram)b (Color scale, +Value0yellow, −value0blue)C* ChromaCCRD Central composite rotatable designCT Cooking temperature (in degrees Celsius)DML Dry matter lost (in percent w/w)dY/dt Rate of change of Young’s modulus with time (in

newtons per square centimeter hour)H Thickness (in centimeters)h° Hue angleL Lightness (00black, 1000white)n No. of observationP Peak force (in newtons)PUN Power ultrasound-assisted nixtamalizationPUT Power ultrasound application time (in minutes)R2 Coefficient of determinationRSM Response surface methodologyt Time in hoursTN Traditional nixtamalizationY Young’s modulus (in newtons per square centimeter)ΔE Color differenceΔh Deformation (in centimeters)

B. Janve :W. Yang (*) :C. SimsDepartment of Food Science and Human Nutrition,University of Florida,Gainesville, FL 32611, USAe-mail: [email protected]

A. KozmanPepsiCo Advanced Research,Plano, TX 75024, USA

A. TeixeiraDepartment of Agricultural and Biological Engineering,University of Florida,Gainesville, FL 32611, USA

M. A. GundersonDepartment of Food and Resources Economics,University of Florida,Gainesville, FL 32611, USA

T. M. RababahDepartment of Nutrition and Food Technology,Jordan University of Science and Technology,Irbid 22110, Jordan

Food Bioprocess Technol (2013) 6:1269–1280DOI 10.1007/s11947-012-0816-7

Greek Symbolsα Axial pointΔ Change (delta)ε Strainσ Stress (in newtons per square centimeters)

SubscriptsCT Cooking temperature (in degrees Celsius)DML Dry matter lost (in percent w/w)HUE Hue anglePUT Power ultrasound application time (in minutes)ref Referencesample Sample observationY. Mod Young’s modulus (in newtons per square

centimeters)

Introduction

The USA is the largest consumer and producer of Corn (Zeamays sp.) in the world (FAOSTAT 2008). Corn is one of themost important cereal grains in the Latin American diet,particularly in Mexico, Central America, Colombia, Vene-zuela, and Brazil. In these countries, corn is used mostly asmasa flour. Masa flour is the main ingredient for widelyconsumed products like corn tortillas, tortilla chips, tacoshells, corn chips, and extruded snacks. Corn masa con-sumption is higher in rural areas than in urban areas. Intakeof corn masa as tortillas contributes 39–65 % of daily intakeof calories in rural areas of Central American countries, and27 to 53 % of daily protein intake (Bressani 1997).

Traditional production of masa flour requires nixtamali-zation, washing, and stone grinding. Nixtamalization wasdeveloped by ancient Maya and Aztec (Mesoamerican) civ-ilizations (Pappa et al. 2010). However, Illescas (1943) wasamong the first to describe the process as carried out inMexico. Nixtamalization is the alkaline cooking of cornkernels for 1 h, followed by a lengthy process of steepingfor 16–18 h in the same lime solution. The relatively hightemperature (near boiling point) and pH (around 12) duringcooking facilitate diverse transformations of grain compo-nents viz. protein, lipids, and starch. These transformationsinclude degradation of pericarp, loss of soluble proteins, andpartial gelatinization of starch. The lost soluble proteinsmainly include albumin and globulin of low molecularweight contained in the germ (Méndez-Montealvo et al.2008). A review of the literature reveals that some alterna-tive methods to improve the traditional process had beentested, such as extrusion cooking (Bazua et al. 1979; Brnčićet al. 2011; Mora-Rochin et al. 2010; Reyes-Moreno et al.2003), micronization (Johnson et al. 1980), selective nix-tamalization (Martinez-Montes et al. 2001; Vaqueiro andReyes 1986), high-pressure cooking (Martinez-Bustos et

al. 1996), enzymatic nixtamalization (Rubio et al. 2008),and fractionated nixtamalization (Cortés-Gómez et al. 2005)that reported an efficient process with less effluent. Somereported processes involved complex systems and greaterdeviation from the traditionally established nixtamalizationprocess, resulting in limited commercial applications.

Power ultrasound at the frequencies of 20 to 100 kHz hasbeen used as an alternative food processing method forsome food products (Feng et al. 2008; Fernandes et al.2008; Guan et al. 2011), and has shown promising resultsin application to rice parboiling (Wambura et al. 2008) andseparating corn pericarp (Liu 2002). The success of theseapplication can be attributed to the disintegration effect onthe cellulose structure (Aliyu and Hepher 2000) caused bycavitation and microstreaming (Nyborg 1982) action ofpower ultrasound. In this study, power ultrasound nixtamal-ization (PUN) was used as a processing aid to reduce thetraditional nixtamalization (TN) process time and garnerimprovements on nixtamal quality. The effects of PUN andTN processes on the nixtamal (cooked, steeped, and washedcorn) were determined by measuring its texture and color,washing solid losses and moisture effects on the nejayote(cooking and steeping liquor). The objectives of this studywere to:

1. Expedite the TN process using power ultrasoundwhile maintaining the traditional integrity of thenixtamalization, and

2. Examine the effect of PUN process parameters on thequality of the nixtamal and nejayote.

Materials and Methods

Materials and Equipment

Commercially available hard yellow dent corn (Z. mays L.)was obtained from a local store in Gainesville, FL. Thechemical reagent calcium hydroxide 98 % (extra pure) wasobtained from Acros-organics, NJ. A Sonics VCX 1500 CTsystem from Sonics & Materials, Inc., CT, USAwas used togenerate power ultrasound, and a standard titanium alloyprobe (L0254 mm, d025 mm, W0680 g) was used to applythe power ultrasound. The system was designed to provide1,500 W of maximal output power at 20 kHz and wasoperated at 90 % of the amplitude level.

Experimental Design and Statistical Analysis

Yellow dent corn (200 g) was added to water in a ratio of 1:3by weight. Calcium hydroxide was added to the mixture at 1% (w/w) of corn. The mixture was subjected to TN in a glassbeaker with constant magnetic stirring while cooking. In the

1270 Food Bioprocess Technol (2013) 6:1269–1280

PUN process, the same amount of mixture was subjected tosonication by inserting the power ultrasound probe, whichin turn provided acoustic stirring to the process. Figure 1shows a complete experiment process flow diagram used forcomparing the PUN with the TN process. The experimentswere conducted in triplicate. Approximately 15 g (≈15 ker-nels) of nixtamal were randomly sampled at different steep-ing times for color and texture analyses. The TN processwas monitored from the initial 1–4 h and the final 14–20 h ateach hour for nixtamal quality. In the PUN process, powerultrasound treatment was conducted for 1 h during thealkaline cooking. Nixtamal samples were obtained foranalysis after 1 h steeping.

The effect of process parameters on the nixtamal qualitywas studied by response surface methodology (RSM) follow-ing the two-variable, five-level central composite rotatabledesign (CCRD, Montgomery 1999). The two independentvariables for the PUN process were power ultrasound appli-cation time (PUT) and alkaline cooking temperature (CT).The experiments were conducted in mixtures with the samecomposition of corn, water, and lime as for the TN process.The levels of independent variables were coded usingEq. 1:

Xi ¼ "i � "icpΔ"i

ð1Þ

where Xi is coded level of the variable i,εi is real value ofthe variable i,εicp is real value at central point of variable i,andΔεi is step change of variable i.

The relationship between coded (XPUT, XCT) and actualvalues of PUTand CTwere defined as follows (Eqs. 2 and 3):

XPUT ¼ PUT� 45ð Þ=25 ð2Þ

XCT ¼ CT� 65ð Þ=25 ð3Þ

Independent variables and their variation levels for theprocess are expressed in Table 1. The coded face pointswere (1, 1), (−1, 1), (1, −1), and (−1, −1), and axial points(α) were (1.414, 0), (−1.414, 0), (0, 1.414), and (0, −1.414).These can be easily visualized as points on the locus ofcircle with origin (0, 0) (center point) and radius (α) of

1.414 (i.e.,ffiffiffi2

p) on the coordinate axes. The total exper-

imental design along with the data for the process andresponse variables is given in Table 2. For the experi-ment at each design point, approximately 15 g nixtamal(≈15 kernels) was sampled randomly and analyzed forcolor and texture. Nejayote obtained at each designpoint was analyzed for the dry matter lost (DML) fromthe nixtamal to the nejayote. All experiments at eachdesign point were performed randomly in triplicate.

Fig. 1 Traditional nixtamalization and power ultrasound-assisted nixtamalization (PUN)

Food Bioprocess Technol (2013) 6:1269–1280 1271

Data obtained from these experiments were used togenerate relationships between the process variables likePUT and CT and response variables of texture (i.e.,Young’s modulus) and color (e.g., hue) for nixtamaland DML in nejayote. These models were evaluatedstatistically for their overall significance. The criticalvariable terms in the model expression were identifiedby the significance of their individual coefficients andhow they were related to the particular response.

The initial data for comparison between the PUN and TNprocesses were analyzed by one-way analysis of variance todetermine the effect of different processing and steepingtimes on the physical characteristics of the nixtamal andtotal solids in nejayote. Fisher’s LSD was used for multiplemean comparisons. The experimental design data wereanalyzed using RSM. The significance of the modelswas tested using the variance analysis (F test) and theR2 value. The effects of the variables were registeredusing surface graphs. Data analysis was carried out withstatistical analysis system software, version 9.00 (SASInstitute Inc., Cary, NC).

Moisture Content Measurement for Nixtamal

Moisture content of the nixtamal was determined byloss of weight after 72 h drying using an air-ventilatedoven at 105 °C, according to the AACC Method 44-15A(AACC 2000).

Solid Losses

Dry Matter Lost in Nejayote

In order to study the responses of PUT and CT on the drymatter lost in nejayote at each design point of the CCRDshown in Table 2, the procedure per Sahai et al. (2000) wasfollowed. The nejayote obtained from 200 g of corn wasseparated from the nixtamal and homogenized to obtain auniform nejayote sample for each replicate. The nejayotesamples were placed in dry and preweighted glass trays, andDML was obtained by drying the samples in a ventilatedoven at 105 °C for 72 h. The DML in nejayote wasexpressed as the percentage of dry corn by weight.

Table 1 Independent variablesand variation levels inpower ultrasound-assistednixtamalization of corn

Variables Code Level

−1.414 (−α) −1 0 1 1.414 (α)

Power ultrasound time (min) X1 9.65 20 45 70 80.35

Cooking temperature (°C) X2 29.65 40 65 90 100.35

Table 2 Experimental design used to obtain different combinations of power ultrasound-assisted nixtamalization time and cooking temperature forthe production of nixtamal from hard yellow dent corn and experiment results for the response variables

S. no.a Points Location Process variablesb Response variablesc

PUT (min) CT (°C) Y h° DML

Coded Real Coded Real

1 −− Face point −1 20 −1 40 8.29±2.54 1.47±0.02 0.67±0.30

2 −+ Face point −1 20 1 90 2.47±0.86 1.49±0.02 1.55±0.18

3 +− Face point 1 70 −1 40 3.94±1.71 1.49±0.02 1.87±0.35

4 ++ Face point 1 70 1 90 2.54±1.14 1.49±0.02 3.36±0.30

5 a0 Axial point (α) −α 9.65 0 65 4.82±1.55 1.48±0.02 0.72±0.12

6 A0 Axial point (α) α 80.35 0 65 2.64±0.75 1.50±0.01 3.37±0.31

7 0a Axial point (α) 0 45 −α 29.65 6.20±1.87 1.48±0.02 0.82±0.29

8 0A Axial point (α) 0 45 α 100.35 2.19±0.81 1.50±0.01 4.10±0.90

9 0 Center point 0 45 0 65 3.73±1.52 1.48±0.02 1.13±0.17

Experimental design: central composite design variables with three levels and two factors. Nine assays with three replications

PUT power ultrasound-assisted nixtamalization time (in minutes), CT cooking temperature (in degrees Celsius), values in parentheses are the codedlevels, Y Young’s modulus (in newtons per square centimeter), DML dry matter of nejayote (in percent w/w of corn), h° hue anglea Does not correspond to order of experiment


Soluble and Insoluble Solid Losses During Washingand Processing

The nixtamalization mixture that resulted after steeping(shown in Fig. 1) was passed through a wire mesh of6–8 mm pore size to separate the nixtamal from thenejayote. The nejayote thus obtained (processing liquid)was analyzed to determine solid losses during thecooking and steeping processes. The nixtamal obtainedwas rinsed with 300 ml of water. The liquid collectedafter rinsing was termed washing liquid. As stated byPflugfelder et al. (1988), both processing and washingliquids were adjusted to pH 5–6 with 2 N HCl todissolve all residual lime. Both liquids were centrifugedat 4,000×g for 15 min to obtain water-soluble andinsoluble fractions as supernatant and precipitate, re-spectively. The collected fractions were dried in an air-ventilated oven at 105 °C for 72 h to determine thesoluble and insoluble solid components, respectively.The sum of soluble and insoluble fractions was indicat-ed as total solid losses for each processing and washingliquid sample. Each of these components wereexpressed as percentage of the dry corn taken by weightin order to compare PUN and TN effects on solid losses

Texture Analysis

The nixtamals were analyzed for texture in terms of stiffnessand apparent Young’s modulus. The texture parameterswere determined by a TA.XT Plus Texture Analyzer (StableMicro Systems, UK) with a 7.8-mm diameter probe (T-215).The data were obtained and analyzed by the ExponentStable Micro System TEE 32 v 4.0.8.0 software. The instru-ment was equipped with a 50-kg load cell. Corn kernelswere placed in the orientation of germ side facing down.The probe was allowed to travel a distance of 1 mm into thekernel with the test speed of 2 mm/s. The initial experimen-tal trial data revealed that a 1.0-mm penetration was found tobe widely linear and fairly reversible over the entire steepingrange of nixtamal. The stiffness, which is the force per unitdeformation determined from the slope of the curve, wasobtained from the force deformation curve within the 1-mmcrosshead movement. Apparent Young’s modulus, i.e., theratio of compressive stress (σ) and strain (ε), as in Eq. 4, wasused as criterion to judge the kernel softness.

Young’s modulusðY Þ ¼ σ"¼ ðP=AÞ

ðΔh=HÞ ðN=cm2Þ ð4Þ

where P0force (in newtons)A0contact surface area ofthe probe (in square centimeters),Δh0deformation (incentimeters), and H0 initial thickness of the corn kernel(in centimeters).

Color Analysis

The color of corn was measured using a machine visionsystem consisting of a Nikon D200 digital camera housed ina light box [42.5 cm (W)×61.0 cm (L)×78.1 cm (H)] (Wallatet al. 2002), with D65 (daylight) lamp and 10° observerangle. Each image was calibrated against a yellow colorreference tile (L087.09, a07.71, and b070.75) obtainedfrom the Lab Sphere X-Rite Company (North Sutton,NH). The images obtained were analyzed by the softwareLensEyeSk® v10.0.0 (Engineering and Cyber Solutions,Inc., FL). In order to obtain precise calibration, the initialimage was obtained using a round reference tile (Fig. 2a)that was converted to a rectangular (≈150×130 pixels) im-age in order to obtain the processed image (Fig. 2b), whichfacilitated the prevention of interference from the tile’s blackborder. The processed images were subsequently subjectedto background corrections resulting in corrected images(Fig. 2c). The final corrected images were calibrated withrespect to reference Lref, aref, and bref values for standardyellow color as shown in Fig. 2. The standard L*, a*, and b*values from the Hunter color system obtained for eachsample, i.e., L (00black, 1000white), a (+value0red,−value0green), and b (+value0yellow, −value0blue) wererecorded for each image of corn kernel individually forobtaining different color parameters. The most commonL*, a*, and b* coordinates did not express hue (h°) andchroma (C*) directly, and were difficult to interpret inde-pendently (McGuire 1992). Thus, the three measured colorparameters were converted into C* (chroma), h° (hue angle),and total color difference ΔE values using Eqs. 5, 6, and 7.

C� ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiða2 þ b2Þ

pð5Þ

h� ¼ tan�1 b

a

� �ð6Þ

ΔE ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiðLref � LsampleÞ2 þ ðaref � asampleÞ2 þ ðbref � bsampleÞ2

q

ð7Þ

Results and Discussion

Moisture Content of Nixtamal

Appropriate final moisture content of nixtamal is animportant factor to facilitate subsequent processing. Afinal moisture level around 48–50 % is deemed desir-able (Serna-Saldivar et al. 1993). However, the finalmoisture contents of the nixtamal in this study were


51.5±0.6 % and 52.5±0.5 % wet basis for the TN andthe PUN processes, respectively. The nixtamal moisturecontent of the TN process appeared to be slightly higherin value than the foregoing desirable level reported bySerna-Saldivar et al. (1993), probably because the cornkernels in the TN process were steeped a bit longer thanthe established period of 16–18 h. However, statistically, therewere no significant (p≤0.05) differences observed in thefinal nixtamal moisture contents between the TN andPUN processes.

Solid Losses

The solids lost from corn during the TN and PUN processesincluded two parts. The first part accounted for the losses inthe cooking and steeping process. The second part includedthe solids that went into the nejayote during the washing ofnixtamal as shown in Fig. 3. The solid losses were furthercategorized into water-soluble and insoluble fractions(Fig. 3). The total solid losses for TN (i.e., processing totaland washing total) were found to be approximately 7.5 %w/w of dry corn, which were similar to the findings reportedby Pflugfelder et al. (1988), Bressani et al. (1958), and Khanet al. (1982).

Figure 3 shows a significant difference (p≤0.05) insoluble and insoluble solids during processing (cookingand steeping) between TN and PUN. This could be attrib-uted to cavitation effects of the power ultrasound, whichhave caused more leaching of soluble compounds due to thesono-induced endosperm and pericarp separation (Zhang etal. 2005). The significant difference (p≤0.05) in total solidlosses between TN and PUN was probably due to lessersteeping time involved in the PUN process (1 h) as com-pared to TN (20 h). Katz et al. (1974) indicated that higher

total corn solid losses might result in higher nutritional loss,as it is comprised mainly 75.6 % nonstarch polysaccharides,11.6 % starch, 1.4 % protein, and high levels of calcium.Thus, reduction in cooking or steeping time would be de-sirable to minimize the losses during the nixtamalizationprocess.

The DML in nejayote has been modeled successfully bythe response surface model as indicated by the coefficient ofdetermination R200.92 in Eq. 8. The coded and real variablemodels with statistical significance (p≤0.063) are shown inEq. 8 and Table 4, respectively. The real variable model hasan optimal fit to the experimental data in Table 2, expressedgraphically in Fig. 4. Both PUT and CT linear terms werefound to be significant (p≤0.02), contributing to the DMLprediction model. It was apparent from Fig. 5 that values ofPUT and CT below 45 min and 60 °C, respectively, corre-sponded to less than 2 % w/w of dry matter lost in nejayote.

YDML¼ 1:127þ 0:845XPUTþ0:876XCTþ0:363X 2PUT

þ0:568X 2CT þ 0:154XPUTXCT

ð8Þ

Texture Analysis

Texture parameters reflecting the degree of softening ofnixtamal have prime importance in determining the end ofnixtamalization process. In a study by Martinez-Herrera andLachance (1979), the peak compression force correspondingto the bio-yield point of the nixtamal was used to indicatethe endpoint of the nixtamalization. However, subsequentstudies showed that not only the nixtamal texture wasrelated to corn solid losses in processing and washing(Pflugfelder et al. 1988) but also to the final moisturecontent of the nixtamal, which could serve as alternative

Fig. 2 Left to right: a initialimage, b processed image forcalibration, and c correctedimage, used by color machinevision system for determiningHunter L*, a*, and b* valuesfor the nixtamal samples


process termination index and an evaluating factor for theprocess quality (Billeb and Bressani 2001). Process termi-nation index is the desired endpoint for the nixtamalizationprocess, which rather solely depending on one particularprocess evaluation parameter considers combinations ofvital factors like total solid loss, the final texture of nixtamal,moisture, etc. Recently, the calcium content in the pericarpin addition to moisture was used as a physicochemical crite-rion to establish the end of the cooking step (Gutiérrez-Cortezet al. 2010). At a small-scale rural level, the manual method ofpressing the nixtamal between fingers was used to ascertainthe completion of the TN process. The texture parameterindicating the penetration of moisture as well as stiffness ofnixtamal should be integrated for evaluating the nixtamaliza-tion process. Shelef and Mohsenin (1969) established a strong

relationship between the moisture content of corn and theapparent Young’s modulus. Hence, apparent Young’s modu-lus (in newtons per square centimeters) could serve as anobjective, repeatable, and reproducible method for evaluatingthe quality and determining the endpoint of the nixtamaliza-tion process. According to Table 3, corn kernels from the TNfor 18 and 17 h steeping had Young’s modulus (Y) andstiffness (S) as 1.56 N/cm2 and 1.39 N/cm, respectively. Thesewere significantly different (p≤0.05) from those taken fromthe PUN 1 h steeping, for which Yand S were 1.29 N/cm2 and1.11 N/cm, respectively. The data indicated that PUN cookinglowered the apparent Young’s modulus and stiffness valuessignificantly (p≤0.05), which may be explained by successfulprogress of strong shear forces, particle fragmentation, andincreased mass and heat transfer occurring due to the

Fig. 3 Total dissolved solidsprofile for the traditionalnixtamalization and powerultrasound-assisted nixtamali-zation processes. Each bar hasstandard deviation bars withunique letter/s; bars having dif-ferent letters indicate significantdifferent letters indicate signifi-cant difference (p≤0.05) ofmean

Fig. 4 Nejayote dry matter lost (in percent w/w of corn), duringmodeling of power ultrasound application time (PUT, in minutes)and cooking temperature (CT, in degrees Celsius) by response surfacemethod

Fig. 5 Young’s modulus (in newtons per square centimeter) duringmodeling of power ultrasound application time (PUT, in minutes),cooking temperature (CT, in degrees Celsius) by response surfacemethod


cavitation process of ultrasound (Riera et al. 2004). Theacoustic cavitation resulted in decreasing processing timeand increasing final moisture content of the nixtamal.

The apparent Young’s modulus resulted in a statisticallysignificant (p≤0.01) regression model with coefficient ofdetermination R200.98 as shown in Table 4. The intercept

along with linear and interaction (cross-product) terms ofprocess variables PUT and CT were found to critically (p≤0.05) affect the Young’s modulus. The coded and real mod-els are shown in Eq. 9 and Table 4, respectively. As themodel shown in Fig. 5 would predict, the soft texture whichnormally results after cooking for 60 min under boiling(≈100 °C) conditions as shown in Table 3 from theTN process in 0 h steeping, i.e., 2.14 N/cm2, could beachieved by power ultrasound cooking within 50 min ofPUT at a CT of approximately 75 °C.

YY:Mod ¼ 3:73� 0:92XPUT � 1:61XCT þ 0:087X 2PUT

þ 0:32X 2CT þ 1:1XPUTXCT ð9Þ

Rate of Softening

The trend for the decrease in the apparent Young’s moduluswith time during the TN steeping process was found to befairly linear (R200.933) as shown in Fig. 6. Softening of thenixtamal was indicated by the decrease in apparent Young’smodulus, which marked the completion of the nixtamaliza-tion process. The initial level of apparent Young’s modulus(i.e., t00) after cooking was assumed to be the same for boththe TN and PUN processes under similar conditions ofsteeping at ambient temperature (25 °C). The rate of soften-ing, dY/dt, was determined by the negative slope of the Y–tlines in Fig. 6. The slopes were calculated as 0.026 and 0.85for the TN and PUN processes, respectively. The results

Table 3 Effect of processing and steeping time on nixtamal color and texture

Process Steeping time (h) Texture of nixtamala Color analysis of nixtamalb

Y (N/cm2) S (N/cm) ΔE L* value h° Chrome

TN 0 2.14±0.92a 2.03±0.79a 23.38±2.67e 68.23±1.83a 1.274±0.036abc 67.32±1.93a

TN 1 1.92±0.58bc 1.65±0.64b 23.25±2.77e 68.17±1.91a 1.287±0.039a 66.17±2.98b

TN 2 1.97±0.63b 1.67±0.62b 23.13±2.75e 68.31±2.15a 1.288±0.032a 65.88±3.12b

TN 3 1.87±0.77bcd 1.51±0.65bc 23.83±2.49e 67.81±1.85a 1.279±0.040ab 66.12±2.76b

TN 4 1.97±0.62b 1.70±0.68b 23.95±2.47e 67.61±1.65a 1.278±0.037ab 65.91±2.19b

TN 14 1.72±0.51cde 1.38±0.49c 25.94±2.92d 66.37±2.20b 1.254±0.037de 65.45±2.61bc

TN 15 1.65±0.61de 1.47±0.68bc 26.11±3.02cd 65.92±2.08bc 1.262±0.044bc 64.78±2.11c

TN 16 1.59±0.65e 1.30±0.65cd 27.27±2.28b 65.05±2.28de 1.251±0.036de 64.51±2.70cd

TN 17 1.62±0.45e 1.39±0.56c 28.58±3.01a 64.45±2.16e 1.234±0.046f 63.85±2.93de

TN 18 1.56±0.43e 1.30±0.62cd 27.27±2.57bc 65.07±1.91de 1.252±0.029de 64.01±2.45de

TN 19 1.50±0.44ef 1.35±0.57cd 27.69±2.53ab 64.81±1.78de 1.243±0.035ef 64.74±2.21cd

TN 20 1.48±0.19ef 1.28±0.51cd 25.86±3.26d 66.06±2.23bc 1.267±0.043bcd 64.37±1.68cd

PUN 1 1.29±0.19f 1.11±0.39d 26.71±2.78bcd 65.30±2.02cd 1.274±0.028abc 62.94±3.59e

Observations mean±standard deviation (n045) having different lowercase letters are significantly (p≤0.05) different from other in the same column

TN traditional nixtamalization process, PUN power ultrasound-assisted nixtamalizationa Texture of nixtamal in terms of stiffness (S, in newtons per centimeter) and Young’s modulus (Y, in newtons per square centimeter)b Color of nixtamal in terms of chroma , hue angle h°, lightness L*, and total color difference ΔE

Table 4 Regression coefficients and analyses of the second orderpolynomial equation (predictive models) the relationships among re-sponse (Y) and process variables (X1, X2)

Coefficients Young’s modulus(N/cm2), YY.Mod

Dry mater lostin nejayote(%, w/w), YDML

Hue index(h°), YHUE

Intercept (β0) 17.20* 3.06, NS 1.46*

Linear p≤0.004 p≤0.022 p≤0.02

β1 −0.165** −0.034** −0.0003, NS

β2 −0.210** −0.094** −0.00005, NS

Quadratic p≤0.545 p≤0.375 p≤0.4680

β11 0.0001, NS 0.0006, NS 0.000006, NS

β22 0.0005, NS 0.0009, NS 0.000005, NS

Interaction p≤0.02 p≤0.634 p≤0.096

β12 0.002** 0.0002, NS −0.000009, NS

R2 0.978 0.927 0.93

p ≤0.01 ≤0.063 ≤0.05

Y0β0+β1X1+β2X2+β11X12 +β22X2

2 +β12X1X2; Y [Y (in newtons persquare centimeter), h°, DML (in percent w/w)], X1 (PUT), X2 (CT)

NS not significant

*p≤0.01 level, significant; **p≤0.05 level, significant


apparently showed that the PUN process was approximately32 times faster in softening the corn kernels than the TNprocess.

Color Analysis

Machine vision has emerged as an efficient method inevaluating nonhomogeneous color in agricultural and bio-logical materials (Balaban 2008; Balaban et al. 2008) com-pared to conventional colorimetric and the Minolta system(Oliveira and Balaban 2006; Yagiz et al. 2009). The chrome(C*), lightness (L), and total color difference (ΔE) weremeasures of saturation, brightness, and difference from thereference yellow color, respectively. The parameters ofchrome (C*), lightness (L), and total color difference ΔEdepended on the surface optical properties of the nixtamal,which had significant difference (p≤0.05) between the rowsof PUN 1 h and TN 1–4 h steeping for these parameters asshown in Table 3. However, no significant difference be-tween the rows of PUN 1 h and TN 18 h was shown for C*,L, andΔE parameters. These results indicated that there wasa sufficient cavitation effect of power ultrasound resulting inthe surface erosion of the nixtamals. In contrast, hue angle(h°) was not affected much by minor surface deterioration ofnixtamal. The hue angle (h°) expressed the true color of thenixtamal. The data for hue angle revealed significant differ-ences (p≤0.05) between the rows of PUN 1 h and TN forsteeping 14–20 h except two outliers at 15 and 20 h with h°1.262 and 1.267, respectively (Table 3). There was nosignificant difference (p≤0.05) observed between the hue(h°) for the PUN 1 h and TN for steeping 1–4 h, due to the

appreciably low processing time limiting any furtherchanges in the hue of the nixtamal during the PUN process.

No statistically significant polynomial models were pro-duced for lightness (L*), chrome (C*), and total color dif-ference (ΔE) values. Acoustic microstreaming, developedduring ultrasonication, caused surface erosion (Maisonhauteet al. 2002), which affected the surface optical propertiesand explained the random surface effects of corn kernelsduring the PUN process. The hue angle (h°) for nixtamalexhibited statistically significant regression model (p≤0.05)with coefficient of determination R200.93. The model isshown graphically in Fig. 7, and the real model parametersfor hue angle are shown in Table 4. None of the processvariables, i.e., PUT and CT, affected the hue angle signifi-cantly. The intercept term in the model was found to besignificant (p≤0.02). The coded polynomial model for hueangle (h°) is shown in Eq. 10.

YHUE ¼ 1:48þ 0:005XPUTþ0:004XCT þ 0:002X 2PUT

þ 0:005X 2CT � 0:005XPUTXCT ð10Þ

Power Ultrasound-Assisted Nixtamalization

According to Table 3, the steeping time could be reduced from20 h in the TN process to 1 h in the PUN process with acomparable Young’s modulus (Y), stiffness (S), and total colordifference (ΔE). This can be seen from the row of TN 20 hsteeping and the row PUN 1 h steeping, namely, for Y, S, andΔE; the former were respectively 1.48 N/cm2, 1.28 N/cm, and25.86, and the latter were 1.29 N/cm2, 1.11 N/cm, and 26.71,respectively. The corresponding Y, S, andΔE between the TNand PUN processes were not statistically different (p≤0.05).

In literature, many researchers have tried to improve theprocessing time and nixtamal quality by modifying traditionalcooking and steeping conditions for nixtamalization. However,

Fig. 6 The measured data of Young’s modulus and the linear regres-sion lines for the power ultrasound-assisted nixtamalization (PUN) andtraditional nixtamalization (TN) process. The slope of the linear regres-sion line was the rate of kernel softening

Fig. 7 Hue index (h°) during modeling of power ultrasound applica-tion time (PUT, in minutes), cooking temperature (CT, in degreesCelsius) by response surface method


the PUN process in this study basically maintained traditionalcooking and steeping conditions, but with a 20-fold reductionin steeping time.

In comparison, Morad et al. (1986) used presoaked grainfor alkali cooking and achieved around 40 % reduction incooking time. However, considerable increase in the dry mat-ter losses, water uptake, calcium content, and enzyme-susceptible starch was observed in the process. Johnson etal. (1980) used micronization to produce sorghum and cornflours. Micronizing is a dry-heat process using gas-fired in-frared generators in which rapid internal heating takes place tocook the product from inside out. This process was used toproduce tortilla flour and claimed to be quicker and moreeconomical than the traditional method. Herbster (1993) usedthis method for corn nixtamalization and reported that a briefhigh-alkali treatment (6 %) at 38–66 °C (100–150 °F) for12 min, with optional steeping for 24–72 h, was required forthe process. An additional step involving removal of pericarpfollowed by washing was used for this process, resultingpronounced reduction in time.

As a novel process, enzymatic nixtamalization (Sahai andJackson 2000) involves cooking the corn in hot water with-out alkali. The steeping involves digestion in enzyme solu-tion with 0.05 % alkali at 50–60 °C for 3–4 h, resulting inthe acidic conditions after steeping that was contrary to thetraditional nixtamalization. Enzymatic nixtamalization hasreported minimal solid losses and is regarded as anenvironment-friendly process.

Extrusion nixtamalized corn flour reported by Irvin et al.(1991) and Mensah-Agyapong and Horner (1992) involvescooker extruders as continuous reactors to convert corn tomasa or instant corn flour. Although the extrusion cookinghas shown considerable improvement in reducing the pro-cessing time, it resulted in tortillas with lower sensorialquality as compared to the TN process and required furtherimprovements (Arambula et al. 1998). Similarly, pressurecooking was used in a comparative study by Khan et al.(1982) which involved three lime-cooking methods: tradi-tional, commercial, and a laboratory pressure cooking pro-cedure. Nixtamals obtained separately for each process inundercooked, optimally cooked and overcooked conditionsto measure the physical and chemical changes. In spite ofthe greatest loss of dry matter from the grain, the traditionalmethod gave the best tortillas in terms of texture, color, andacceptability. The study concluded that the pressure cookingprocedure resulted in sticky dough and undesirable tortillas.

Based on the solid loss profile in Fig. 3 and texture valuesin Fig. 6, PUN resulted in lower total solid losses andsuperior softening of nixtamal in a short duration of pro-cessing as compared to TN. These results established asuperior PUN process with about 90 % reduction in process-ing time and reduction in total solid loss, i.e., approximately6 % for PUN as compared to 7.5 % for TN, as shown in

Fig. 3. The PUN resulted in better nixtamal than TN processin terms of initial color degradation after cooking (hueangle), softer texture (Young’s modulus, Table 3), andhigher values of moisture. The PUN process has not affectedthe integrity of the traditional nixtamalization process ascompared to the other reported process improvements suchas enzymatic, selective, micronized, fractionated nixtamali-zation, and extrusion nixtamalization process. The PUNprocess appeared to be faster than high pressure, fractionat-ed, selective, and enzymatic nixtamalization processes,while comparable to extrusion nixtamalization processaccording to the published literature. The PUN process didnot involve any additional pretreatments and extensive pro-cess modifications as compared to some other advancedprocesses. The PUN AED in the application medium werefound to be approximately 1.85 W/g obtained by dividing1,500 W of ultrasound power by the mass of the mixture ofnixtamal and nejayote. This indicates that PUN could be apromising alternative method to the traditional nixtamaliza-tion process. However, further research is required to exam-ine the final masa and tortilla quality and consistencyproduced from the nixtamals by the PUN process.

Conclusions

Findings from this study show that power ultrasound haspotential to accelerate the nixtamalization process by reducingsteeping time from 20 h in the TN process to 1 h in the PUNprocess. Besides ultrasonication during nixtamal cooking, therewas no major deviation from the traditional nixtamalizationprocess. The traditional integrity of the process with ease ofexecution has been demonstrated by PUN process. The overallcolor and moisture for nixtamal during PUN were comparableor better than in the TN process, while texture (Young’smodulus) and total solid losses were lower for PUN than TN.

The power ultrasound application time and cooking tem-perature were found to be critical in affecting the PUN pro-cess, and were successfully modeled by response surfacemethodology for predicting physical and texture properties.The Young’s modulus of nixtamal was significantly (p≤0.05)affected by individual as well as interaction of process varia-bles. The DML in nejayote was significantly (p≤0.05) influ-enced by the individual process variables PUT and CT for thePUN, while the hue angle of nixtamal was independent of it.

Further research on application of power ultrasound onthe nixtamalization process is encouraged to determine itseffect on masa flour quality and the commercial viability ofthis technology. Efforts to introduce power ultrasound as ameans to improve the quality of nixtamal and elimination ofsteeping at commercial level have to be undertaken to un-derstand and eliminate practical problems in implementingthe technology to masses.


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enhancement of corn nixtamalization by power ultrasound

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