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Osella, C. A.;Robutti, J.;Sánchez, H. D.;Borrás, F.;Torre, M. A. de la

DOUGH PROPERTIES RELATED TO BAKING QUALITY USING PRINCIPAL

COMPONENT ANALYSIS

Ciencia y Tecnología Alimentaria, Vol. 6, Núm. 2, 2008, pp. 95-100

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DOUGH PROPERTIES RELATED TO BAKING QUALITYUSING PRINCIPAL COMPONENT ANALYSIS

AbstractThis study assesses the association between physical properties and baking performance of dough. Sixty-six argentine

wheat-breeding lines were milled using an experimental mill. Wet gluten content and physical dough properties were determined

in flours; while breads, cookies and crackers were made to evaluate baking performance. Principal component analysis

(PCA) was utilized to observe variations among flour samples studied. A close association was found between some farinograph

parameters (development time, stability), some alveograph parameters (G, W, P), and the attributes of bread quality (specific

volume and total score). Results obtained in cookies and crackers indicate that there is a close positive correlation between

weak gluten content and technological attributes of quality such as specific volume and sensory evaluation (total score).

ResumenEl presente trabajo relacionó las propiedades físicas de la masa con el comportamiento tecnológico en la elaboración

de productos horneados. Se utilizaron sesenta y seis líneas de trigo argentino, molidas en un molino experimental. Se determinó

el contenido de gluten húmedo y las propiedades físicas de la masa. El comportamiento tecnológico se evaluó a través de la

elaboración de pan, galletas y galletas crujientes. Para relacionar los parámetros evaluados se utilizó el análisis de componentes

principales (PCA). Se encontró una buena asociación entre algunos parámetros farinográficos (desarrollo, estabilidad),algunos parámetros alveográficos (G, W, P) y los atributos de calidad del pan (volumen específico, puntaje total). Los

resultados obtenidos para galletas y galletas crujientes indican que hay una amplia correlación entre el contenido de gluten

débil y los atributos tecnológicos de calidad tales como: volumen específico y puntaje total otorgado en la evaluación

sensorial.

Keywords: Principal component analysis, physical dough properties, baked products, wheat-breading lines

Palabras clave: Análisis de componentes principales, propiedades físicas de la masa, productos horneados, líneas de trigo

ANÁLISIS DE COMPONENTES PRINCIPALES ENTRE PROPIEDADES DE MASAY PRODUCTOS PANIFICADOS

Osella, C. A.1; Robutti, J.2; Sánchez, H. D.1*; Borrás, F.2; de la Torre, M. A.1

1 Instituto de Tecnología de Alimentos. Facultad de Ingeniería Química - Universidad Nacional del Litoral

1º de Mayo, 3250 Santa Fe, Argentina2 INTA, EEA Pergamino. 2700 Pergamino, Buenos Aires, Argentina

Recibido/Received 14-12-2007; aceptado/accepted 25-03-2008

*Autor para la correspondencia/Corresponding author. E-mail: [email protected]

95

INTRODUCTIONThe technological quality of wheat includes many

attributes of kernel and flour, which are all important in

the production of several kinds of baked products such as

bread, cookies and crackers (Zghal et al ., 2001). It haslong been established that both quantity and quality of

protein influence the end-use quality of wheat and bread

making performance (Wieser et al., 1998). The genetic

background mainly determines the protein content in the

wheat grain, but also to a large extent by environmental

factors such as nitrogen application, water access and

temperature during growth. The gliadin/glutenin ratio has

been shown to be the most important factor influencing

the functional properties and baking quality (Pedersen and

Jorgensen, 2007). Bread baking quality is determined by

the physical properties of dough, its oxidative potential,

flour water absorption, bread volume, and color of crumb

and crust (Menkovska et al ., 2002).

Some wheat classes are particularly suited for specific purposes. For example, soft wheat is best adapted

for making cookies, cakes and other derived products

(Robutti et al ., 1998; Hou et al ., 1996; Yamamoto et al.,

1996). Soft wheat flours are complex mixtures of

constituents such as starch, proteins (e.g. gluten proteins),

lipids and several non-starch polysaccharides (e.g.

pentosans). Cookie quality is generally associated with soft

wheat flour of low protein content, smaller particle size

and low alkaline water retention capacity. The negative

Cienc. Tecnol. Aliment. 6(2) 95-100 (2008)

www.somenta.org/journal ISSN 1135-8122SOMENTA Sociedad Mexicana de Nutrición

y Tecnología de los Alimentos

CIENCIA CIENCIA CIENCIA CIENCIA CIENCIA Y Y Y Y Y

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96

impact of protein content on cookie spread has been long

recognized (Fustier et al ., 2008). Lack of these

characteristics, plus possibly unique soft wheat

characteristics, assures that flours milled from soft wheat

cultivars make large, tender, and less-dense products

(Gaines et al ., 1996).

Rheological properties of wheat flour dough are

essential for the successful manufacturing of bakery

products because they determine its behavior during

mechanical handling, thereby affecting the quality of the

finished products (Hoseney et al ., 1988; Weipert, 1992).

Using the alveograph technique, Agyare et al . (2005),

evaluated the bread and cookie-making qualities of hard

and soft wheat flour. The rheology of cracker dough is

important to the processor; therefore, a battery of

rheological tests has been used. These include farinograph,

alveograph, and mixograph tests and Mac Michael

viscosity test (Hoseney et al ., 1988).

In contrast to traditional statistical approaches in

which correlation among variables causes problems, the

multivariate data compression PCA utilizes the correlationand enables visualization of relationships among variables.

This method projects the information in the original

intercorrelated variables onto a small number of new

variables, called principal components (PCs) (Aamodt et

al ., 2003).

To further assess the degree of association between

physical dough properties and baking performance for

bread, cookies and crackers, this study examines these

factors for sixty-six Argentine wheat-breeding lines using

principal component analysis.

MATERIALS AND METHODS

Wheat samplesBreeders from the Estación Experimental

Agropecuaria Pergamino - INTA - Argentina supplied

sixty-six wheat samples (breeding line set) from various

breeding programs carried out at spring seasons between

1998 and 2005 with warm and wet climate. Samples were

analyzed one month after harvest. Samples were cleaned,

conditioned to 15.5 % moisture, and stored for 24 h before

milled with an experimental mill (Buhler Miag mill type

MLGV Variostuhl and Buhler Rotostar Plansifter type

MPAR-H) as described by Robutti et al . (1998). Three

breaks and three reduction passes were made. Wet glutencontent was determined by approved methods of the AACC

(1994).

Mixing and physical dough propertiesFlours were evaluated for farinograph water

absorption (%), dough development time (min), degree of

dough stability (BU), and degree of dough softening or

drop off (BU) with the Brabender farinograph on 300 g

samples (AACC 54-21). Deformation energy W (J x 10-4),

overpressure P (mm), swelling index G (ml), abscissa at

rupture L (mm) and P/L ratio were measured with the

Chopin alveograph on 250 g samples (AACC 54-30).

Baking performanceBreads were made as in the baking test for French

type bread proposed by Sánchez et al . (1983). The formula

contained 300 g flour (14 % moisture basis), 6 g yeast, 6 g

NaCl, 100 ppm ascorbic acid, and 50 ppm fungal amylase

5000 SKB. Water was added according to farinograph

water absorption to obtain equal dough consistency in all

cases. Kneading was done in the farinograph (60 rpm) for

15 min. After mixing, dough was rounded and bulk

fermented at 27 ºC and 80 % relative humidity, controlling

the rising with a push-meter, used to measure proofing. In

this instrument, 25 g of dough rise from 12 to 25 mm during

50-70 min. The apparatus consists of a glass cylinder (75

mm height, 45 mm i.d.) with a tight-fitting plastic piston

that rises during proofing. After proofing, dough was

divided into 100 and 200 g dough pieces, then shaped and

proofed (final fermentation) at 27 ºC and 80 % relativehumidity, controlling rising from 25 to 45 mm height with

the push-meter. Pieces were baked at 210 ºC for 30 min

using an electric oven with steam (Ojalvo S.A., Santa Fe,

Argentina). After one hour of cooling breads were

evaluated. Loaf volume was determined by rapeseed

displacement and three trained people scored for external

and internal characteristics (total score). As recommended

by Pyler (1973), attributes evaluated and maximum scores

were: specific volume, 15 (5 cc/g or higher correspond to

the maximum); crust, 15 (color and thickness); texture, 15

(elasticity, stickiness); crumb color, 10 (cream white being

the highest score); crumb structure, 10 (grain); aroma, 15

(fresh-bread like); and taste, 20 (flavor and mouth feeling)(Sánchez et al., 1996).

Cookies were made using the following laboratory

method: 300 g flour, 37 g sucrose, 0.4 g NaHCO3, 1.5 g

(NH4)HCO

3, 0.75 g NaCl, 25 g oleomargarine (MP = 36

ºC), and 3 g whey protein concentrate. Water was added

so as to have a ratio of 2.3 g dry flour/ml total water.

Kneading was done in a farinograph at 30 rpm for 40 min.

After mixing, dough rested during 30 min before sheeted

to a final thickness of 1.4 - 1.6 mm, and baked at 210 ºC

for 5- 6 min using an electric oven without steam (Ojalvo

S.A., Santa Fe, Argentina). Cookies were evaluated one

hour after baking. Volume was determined by rapeseed

displacement and three trained people scored for externaland internal characteristics (total score). Parameters

evaluated and maximum scores, according to Sanchez et

al. (1990), were: color, 10; upper surface, 10; bottom

surface, 10; rising, 10; texture, 10; tenderness, 10; mouth

feeling, 15; and taste, 25.

Crackers were made using the following laboratory

method: 300 g flour, 6 g yeast, 6 g NaCl, 1.2 g NaHCO3,

36 g oleomargarine (MP = 36 ºC), and 100 ppm fungal

amylase 5000 SKB. Water was added so as to have a ratio

Cienc. Tecnol. Aliment. 6(2) 95-100 (2008) ISSN 1135-8122 ©2008 SOMENTA

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97

Table 1. Means and ranges (n = 66) of wet gluten content, physical dough properties and baking performance of flour samples.

Tabla 1. Valores medios y rangos (n = 66) de gluten húmedo, propiedades físicas de la masa y resultados de panificación en muestras de harina.

of 1.65 g dry flour/ml total water. Kneading was done in a

farinograph at 20 rpm for 10 min. After mixing, dough

was fermented (27 ºC and 80 % humidity) for 8 h before

sheeted to a final thickness of 1.4 - 1.6 mm, and baked at

250 ºC for 5-6 min using an electric oven without steam

(Ojalvo S.A., Santa Fe, Argentina). Crackers were

evaluated one hour after baking. Volume was determined by rapeseed displacement and three trained people scored

for external and internal characteristics (total score).

Attributes evaluated and maximum scores, according to

Sanchez et al. (1990), were: color, 10; upper surface, 10;

bottom surface, 10; rising, 10; texture, 10; tenderness, 10;

mouth feeling, 15; and taste, 25.

Statistical analysisPrincipal component analysis (PCA), which is a

multivariate approach designed for multicorrelated data,

was done using Statgraphics Plus 3.0 on the whole data

set. This method projects the information in the original

variables onto a small number of new variables, called

principal components (PCs), which are linear combinations

of the original variables. The PCs are orthogonal to each

other and give, in decreasing order, the best description of

the variability in the data. The PCs are used as new axes in

a plot of samples (score plot) and a corresponding plot of

variables (loading plot). This makes it possible to get an

overview of the data and to find which properties are

related, and which properties are most important in

distinguishing between samples (Aamodt et al ., 2003). All

variables were scaled to unit variance before analysis, and

cross-validation was used for evaluation of the model. Two

variables that are close to each other in the plot represent

properties that vary in the same way, whereas variables

appearing on opposite sides are negatively correlated.

Variables located in perpendicular directions along the PC

axis are independent of each other.

RESULTS AND DISCUSSION

Basic statistical studiesTable 1 shows wet gluten content and the data of

physical dough properties and baking performance for flour

samples. Development time, stability and drop off exhibit

high coefficients of variation (CV), calculated as the

percentage rate between the standard deviation and the

mean value, this indicates a large variation of quality among

lines. On the other hand, water absorption (14 % moisture

basis) shows a low CV (4.30 %). Variation in farinograph

water absorption is generally recognized as affected by

two major factors, protein content and damaged starch

(Yamamoto et al., 1996). The mean value for wet gluten

content was 32 % with sixty-four samples above 25 % and

only two samples below 25 %. Most of flours with these

high wet gluten contents showed low W values, ranged

between 40 and 265 (Table 1). It means a low gluten quality

for bread.

SOMENTA ©2008 Osella et al .: Dough properties related to baking quality…

Variable Mean CV % Min Max

Wet gluten (%) 32.0 11.3 22.2 38.1

Farinograph dataWater absorption (%) (14 % moisture basis) 57.4 4.30 50.0 61.9Development time (min) 4.53 51.5 1.50 10.5Stability (min) 6.02 67.3 0.50 16.5

Drop off (B.U.) 111 57.0 30 290

Alveograph data

W (J x 10-4) 145 37.1 40 265

P (mm) 59.0 26.3 20.0 92.5

G (ml) 18.5 15.3 11.5 26.5

P/L ratio 0.89 39.9 0.33 2.30

Baking performance

French bread

Specific volume (cc/g) 4.02 11.6 2.61 4.70

Total score (max. 100) 67.4 23.6 34.2 87.8

Cookies


Total score (max. 100) 71 21.2 50 100

Crackers


Total score (max. 100) 75.1 18.3 40 91

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distinguishes between specific volume and total score. G

shows a positive effect on specific volume and negative

on total score, while P a positive effect on total score and

negative on specific volume. The influence of W values

was small, since their loadings for PC2 is close to null. It

could be explained because of low W values, in most of

our set of flours, produce a low influence in bread making.

Addo et al. (1990) gave a detailed account of the

considerable differences in correlations between alveogram

indices and baking quality of flours. The strongest

correlation reported by the authors was between loaf

volume and swelling index (G) whereas P and W values

appeared to be somewhat less reliable predictors of baking

quality. Along the PC3 (Figure 1b) loading axis, specific

volume has no association with wet gluten content. This

indicates that weak gluten quality could be the cause of

this low correlation between wet gluten content and bread

making quality.

In Figure 2, for cookies, the first three PCs

explained 71.3 % of the variation, with PC1 explaining

40.6 %. The plot of PC1 vs. PC2 loadings (Figure 2a)shows, along the PC1 axis, a close association among the

rheological parameters: development time, stability, P, G,

W, and total score; drop off, however, is inversely

correlated with these parameters. Also, total score shows

some correlation with wet gluten. PC2 distinguishes P and

P/L from G. The influence of W, development time,

stability, drop off, specific volume, and total score was

small since their loadings for PC2 were close to null. Along

the PC3 loading axis (Figure 2b), specific volume and total

98

French type bread making ability of wheat tested

varied greatly. Specific loaf volumes ranged from 2.61 to

4.70 cc/g. The smallest loaf volume was attained with the

higher drop off and the lower W. Total scores were ranged

from 34.2 to 87.8; it shows large differences among

samples because of the varied gluten qualities in the wheat

breeding lines studied. In general, the use of this type of

weak flours causes problems in the manufacture of French

type bread; normally they are preferred for flat breads

(Hoseney et al ., 1988).

Cookies and crackers showed specific volumes

from 2.32 to 5.97 and from 2.81 to 4.11 ml/g respectively.

Total scores ranged from 50 to 100 and 40 to 91,

respectively with mean values above 70 points. These

flours are then suitable for the manufacture of crackers,

cookies, and also others type of products including wafers,

pretzels, cakes, etc. (Hoseney et al ., 1988).

Relationship between wet gluten, physical doughproperties and baking performance

PCA was performed on wet gluten content, physicaldough properties, and baking performance for bread, to

test variation among flour samples. The first three PCs

(PC1, PC2, and PC3) (Figure 1) explain 74.1 % of the

variation, with PC1 explaining 42.9 %. The plot of PC1

vs. PC2 loadings (Figure 1a) shows along the PC1 axis, a

close relationship between , physical dough properties

(stability, development time, P, and W) and bread

characteristics (total score). Drop off, however, is inversely

correlated with total score and specific volume. PC2


(a)

(b)

PC1 (42.9 % explained variance)

P C 3 ( 1 1 . 2

% e

x p l a i n e d v a r i a n c e )

Development time

Drop off G

PP/L

Specific volume

Stability

Total score W

Wet gluten

-0.38 -0.18 0.02 0.22 0.42-0.3

-0.1

0.1

0.3

0.5

0.7

0.9

P C 2 ( 2 0 % e


Development timeDrop off

G

P

P/L

Specific volume

StabilityTotal score

W

Wet gluten

-0.5

-0.3

-0.1

0.1

0.3

0.5

0.7

P C

2 ( 1 7 . 9

% e


Development time

Drop off

G

P

P/L

Specific volume

StabilityTotal score

W

Wet gluten

-0.4

-0.2

0

0.2

0.4

0.6

0.8


P C 3 ( 1 2 . 8

% e


Development timeDrop off

GP

P/L

Specific volume

Stability

Total score

W

Wet gluten

-0.37 -0.17 0.03 0.23 0.43 0.63

-0.16

0.04

0.24

0.44

0.64

0.84

(a)

(b)

Figure 1. PCA loadings of wet gluten, physical dough properties and

bread quality. (a) PC1 and PC2 loadings; (b) PC1 and PC3 loadings.

Figura 1. PCA para gluten húmedo, propiedades físicas de la masa y

calidad de pan. (a) PC1 y PC2; (b) PC1 y PC3.


cookies quality. (a) PC1 and PC2 loadings; (b) PC1 and PC3 loadings.


calidad de galletas. (a) PC1 y PC2; (b) PC1 y PC3.

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99

score is closely associated with wet gluten, and inversely

correlated with W. According to Hoseney et al. (1988),

cookie flours are generally low in protein (7-8 %), and

protein quality does not appear to be strongly correlated

with cookie-baking quality, the gluten does not develop to

any appreciable extent. In our set of wheats, although most

of flours had wet gluten content above 25 %, they did not

exhibit high W values (weak gluten); indicating that a high

content of weak gluten causes improved cookies

characteristics measured as specific volume and total score.

On the other hand, for crackers (Figure 3), the first

three PCs explained 74.6 % of the variation, with PC1

explaining 41.9 %. The plot of PC1 vs. PC2 loadings

(Figure 3a) shows, along the PC1 axis, a high relationship

among wet gluten, drop off, and specific volume, while

are inversely correlated with development time, stability,

W, P, and total score. Specific volume is inversely

correlated with P/L and closely correlated with wet gluten

content. Flours for crackers are normally higher in protein

content (9-10 %) than cookie flours. The quantity and

quality of these proteins is very important, because cracker dough contains relatively low levels of soluble ingredients

such as sugar, and thus the protein becomes hydrated and

form gluten during sheeting. If too much protein is present

or if too strong, excessive product shrinkage and crackers

toughness result. In our work, wet gluten content was above

25 % in most of flours, but they did not exhibit large W

values. The second PC distinguishes between G and P/L.

Along the PC3 axis (Figure 3b), wet gluten, development

time, and stability are inversely correlated with P, G, W,

and drop off.

CONCLUSIONS

Principal component analysis of data set shows a

high association between some physical dough properties

(development time, stability, G, W, P) and bread quality

(specific volume and total score). Flours with low W values

(weak gluten) and cookies characteristics (specific volume

and total score) have a high relationship between them,

indicating that this gluten characteristic is predictive of

cookie manufacturing quality.

For crackers, a close positive relationship between

development time, stability, W, P and total score was found.

Drop off, wet gluten, and specific volume, however, were

inversely associated with those rheological parameters. The

specific volume of crackers was closely correlated with

wet gluten content, but inversely associated with the

alveographic parameter P/L, indicating that a high content

of weak gluten causes an improved specific volume.

ACKNOWLEDGMENTS

We would like to acknowledge the great

contributions of Jerold A. Bietz for critically reviewing

the manuscript and we also are grateful to the research

group "Mejoramiento de Trigo" (INTA - EEA -Pergamino

- Argentina) for the provision of raw materials to this study.

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