Analysis of the Relationship between Various Soft Wheat Flour Characteristics and Cookie Quality

Abstract

The relationship between soft wheat flour characteristics and sugar snap cookie (SSC) quality was analyzed using SSC diameter (SSCD) as an indicator of SSC quality. Various flour streams (flours), obtained by milling four kinds of soft wheat (Western White and three Japanese domestic wheats) with different characteristics, were used. The results showed that the soft wheat flour characteristics that greatly affected SSCD were damaged starch (DSC), amylose (AC) and protein contents (PC). SSCD showed a significantly higher correlation with DSC than AC and PC; the correlation coefficients were −0.938, 0.644 and −0.552, respectively. Based on the results, stepwise multiple regression analyses were performed, and a multiple regression model with DSC, AC and PC as explanatory variables was obtained. The model can be used to accurately estimate SSCD (corrected R² = 0.915, standard error of residual = 2.22 (mm)). This model was effective as a means to estimate the SSC quality of various weak flours easily and accurately.

Introduction

Recently, there has been a considerable increase in the area seeded to wheat for bread making in Japan. However, the main production remains soft wheat (moderate wheat), which has moderate gluten strength and is mainly used for white salted noodles (WSN) and confectionery products.

WSN is a representative Japan-specific noodle and many studies have been conducted to date on the suitability of moderate strength flour (moderate flour), characterized by intermediate protein content and strength with a slightly low amylose content, for its production. (Baik and Lee, 2003; Ishida et al., 2003; Park et al., 2003). The relationship between WSN quality and various wheat flour characteristics is also well understood (Hatcher et al., 2002; Noda et al., 2001; Park et al., 2004).

However, little research has been conducted, especially in Japan, on the confectionery properties of Japanese domestic soft wheat flour, including moderate flour. Generally, the confectionery properties (weak flour properties) of soft wheat flour are also evaluated by cookie quality (usually cookie diameter) and sponge cake quality (volume and shape, etc.) in the cookie and sponge cake tests, especially the former (Colomb et al., 2008; Moiraghi et al., 2011; Nagao et al., 1977; Nishio et al., 2011; Ram and Singh, 2004). The main reason for the lack of research is that the Japanese government has not established a weak wheat brand for Japanese soft weak wheats (weak wheats) and there is no official distribution system for weak wheats in Japan. Thus, the produced wheats cannot be officially distributed as weak wheats for the production of confectionery products. Therefore, the use of specific weak wheat varieties for confectioneries has not become wide-spread in Japan to date. Nevertheless, a considerable amount of domestic moderate wheat is actually used for confectionery production. ^{i), ii), iii)}

Therefore, elucidation of the relationship between the confectionary quality of soft wheat weak flour (weak flour) and its various flour characteristics is extremely important in order to breed domestic varieties of weak wheat that can produce high quality flour in the future.

Previous studies have reported that protein content and specific surface area (particle size) are important factors with regard to the suitability of weak flour (Japanese sponge cake (JSC) quality) (Nagao et al., 1977). Damaged starch content (DSC), protein content (PC) and average particle size (APS) of flour are known to be important weak flour properties related to baking quality of sugar snap cookie (SSC) (Barrera et al., 2007; Colomb et al., 2008; Kaur et al., 2014; Moiraghi et al., 2011; Ram and Singh, 2004). Recent Japanese researches on the quality of weak flours, including domestic moderate flours, have shown that amylose content, water solvent retention capacity (WSRC) and batter pasting viscosity (BVP) of flours have a significant influence on the suitability of weak flour (SSC and /or JSC quality) (Nakamura et al., 2010; Nishio et al., 2009, 2011). These researchers also showed that amylose content, WSRC and BVP are effective and convenient for evaluating the suitability of weak flour for SSC and/or JSC. In addition, modern milling procedures produce different flour streams that vary in quality characteristics. Thus, a thorough understanding of those quality behaviors in different flour streams is important to develop wheat of desirable flour quality.

However, in the previous studies, few detailed analyses were conducted on the relationship between various flour stream characteristics and the suitability of weak flour for SSC. There is also no established method for easily estimating the SSC quality from measurable flour characteristics (component characteristics and average particle size). Therefore, we conducted experiments using various flour stream samples (flours) of different characteristics prepared with a test mill in the laboratory and undertook a detailed analysis of various weak flour characteristics that significantly affect SSC. Finally, our research objective was to clarify the weak flour properties related to cookie quality and to establish a simple and accurate method for estimating the weak flour quality.

In this study, it was difficult to prepare large amounts of wheat flour samples because the wheat varieties and line were cultivated in a small test field and milled with a small test mill. Therefore, we decided to use the SSC method, which can evaluate the suitability of weak flours using a small amount of the flour samples.

Materials and Methods

Wheat grain samples    Kachikei 119 (winter wheat breeding line) and Kitahonami (winter wheat variety) were sown at the National Agricultural Research Center for the Hokkaido Region (Memuro) (NARCHR) in September of 2012. Norin 61 (spring wheat variety) was sown at the same location in April of 2013. The cultivation conditions for these varieties and line were basically the same as those reported by Nishio et al. (2009). Moreover, a Western White (WW) wheat sample was kindly provided through the General Food Policy Bureau, Ministry of Agriculture, Forestry and Fisheries, Japan. Kitahonami and Norin 61 are representative moderate wheat varieties cultivated in Hokkaido and Honshu Island in Japan, respectively. Kachikei 119 is a breeding line with superior weak flour quality, which was bred at NARCHR. WW, Kachikei 119 and Norin 61 have a high amylose content and are wild (normal) genotype at the three Wx genes (Wx-A1, Wx- B1, Wx-D1), which involve the amylose content of wheat. On the other hand, Kitahonami is the Wx-B1null genotype and has a slightly low amylose content.

Wheat milling and flour quality analysis    Wheat grain samples were conditioned to 14.5% moisture content and milled with a MLU202 test mill (Bühler Inc., Uzwil, Switzerland) to obtain 1B, 2B, 3B, 1M, 2M and 3M flours (AACCI Approved Method 26-30.02, 2010). 1B, 2B, and 3B streams are the flours obtained by milling the wheats 1, 2, and 3 times with the break roll of the above test mill, respectively. 1M, 2M, and 3M streams are the flours that are milled 1, 2, and 3 times with the milling roll from the fractions that could not be sufficiently milled with the break roll, respectively. The moisture content of all flours was determined in an air oven at 135 °C (AACC Approved Method 44-19.01, 2010). Based on the moisture content of the flour samples, all analysis data were displayed on a 13.5% moisture content basis. Cookie quality of the various flours was assessed by the SSC method, which is used to evaluate the cookie quality (weak flour quality) of flours by measuring the diameter of the cookies prepared using this method, and the mean diameter of two cookies as the evaluation value of cookie quality was used (AACCI Approved Method 10-52.01, 2010). The DSC of the flours was measured with the Megazyme assay kit (Megazyme International Ireland Ltd., Wicklow, Ireland) based on the method of Gibson et al. (1992). Amylose content (AC) of the flours was determined using an autoanalyzer (System II, Bran+Lubbe, Norderstedt, Germany) according to the method of Kiribuchi-Otobe et al. (2004). This autoanalyzer easily measures the AC of grain flours. In this instrument, the absorbance of the complex color of α-1,4 glucan (amylose) and iodine is measured at 620 nm to determine AC. PC of the flours was measured using a near-infrared reflectance instrument (Inframatic 8120, PerCon, Hamburg, Germany). APS of the flours was measured by a laser diffraction Helos and Rodos particle size analyzer (Japan Laser, Tokyo, Japan). Ash content of the flours was measured using the method of the American Association of Cereal Chemists (AACCI Approved Method 54-21, 1991). WSRC was measured according to AACC Approved Method 56-11.01 (2010). The specific detailed measurement conditions were performed according to the method of Nishio et al. (2009).

Statistical analysis    All data were measured using two or three replicates except for the diameter of cookies. Cookie diameter (SSCD) was measured eight times. Specifically, using two cookies for each flour milling level, the diameter was measured four times at different angles for one cookie. A total of 8 measurements were taken. Mean values were compared by Tukey's multiple range test using the add-in Excel statistical software 2012 (SSRI Corporation, Tokyo, Japan). Pearson's linear correlation coefficients among various quality parameters were also calculated using Microsoft Excel 2012. Multiple regression analyses with stepwise selection method were conducted using SSCD as an objective variable to select appropriate explanatory variables. The significance level of F-values used to select appropriate explanatory variables was set at 1.5. The analysis of variance (ANOVA) was performed on the Pearson's linear correlation coefficients and multiple regression model (MRMd). The multiple regression analyses and ANOVA were performed using the add-in Excel statistical software 2012 (SSRI Corporation).

Results and Discussion

Characteristics of various flours and their cookie suitability    The characteristics of various WW flours generated by a test mill are shown in Table 1. Basically, each of the flours of the other wheat samples showed similar characteristics. Therefore, only the results of the WW flours are shown. SSCD decreased significantly in the order of 1B to 3M flours, and cookie quality decreased drastically. On the other hand, DSC showed significantly larger values in the above order.

Table 1. Chacteristics of various WW flour streams milled by a Bühler test mill¹⁾

Flour stream samples	SSCD	DSC	AC	PC	APS	Ash content
	(mm)	(%)	(%)	(%)	(µm)	(%)
IB	85.76 ± 0.69a	3.58 ± 0.19e	26.3 ± 1.3ab	7.79 ± 0.07d	57.02 ± 0.01a	0.371 ± 0.004c
2B	83.88 ± 0.62b	4.31 ± 0.02d	27.6 ± 1.1a	9.85 ± 0.00b	42.24 ± 0.28c	0.391 ± 0.009c
3B	82.15 ± 0.68c	4.71 ± 0.06d	23.6 ± 1.9ab	10.92 ± 0.14a	35.21 ± 0.40d	0.529 ± 0.001b
IM	78.04 ± 0.76d	7.15 ± 0.10c	25.7 ± 2.0ab	8.65 ± 0.14c	50.63 ± 0.38b	0.374 ± 0.006c
2M	71.12 ± 0.41e	9.55 ± 0.22b	23.5 ± 0.3ab	9.79 ± 0.07b	56.27 ± 0.52a	0.474 ± 0.013b
3M	68.43 ± 0.38f	10.85 ± 0.29a	21.9 ± 0.6b	10.43 ± 0.21a	50.43 ± 0.01b	0.687 ± 0.039a

¹⁾  WW: Western White, SSCD: Sugar snap cookie diameter, DSC: Damaged starch content, AC: Amylose content, PC: Protein content, APS: Average particle size. Each value is the mean ± SD (SSCD: n=8, DSC, AC, PC, PS and Ash content: n=2∼3). 1B, 2B, 3B, 1M, 2M and 3M are shown 1B, 2B, 3B, 1M, 2M and 3M flour stream milled from WW with Bühler test mill, respectively. The values followed by different letters within column are significantly different (p < 0.05).

AC showed a significant difference between 2B and 3M only; however, it showed a tendency to decrease in the order of 1M to 3M flours, and the values of 3B and 3M flours were lower than the others. AC values showed a decreasing tendency as the flour contained more fractions close to the wheat grain bran. Ando et al. (2002a) and Tang et al. (2005) found that the starches of various flours, which were prepared by grinding wheat grains from the surface, show nearly the same AC. Therefore, the AC in Table 1 seems to be influenced by the fact that the flour components, except for the starch, protein and ash contents, increase in the order of 1B to 3B flours and 1M to 3M flours and the apparent starch content in the flours showed a relative decrease.

PC showed an almost opposite tendency to AC and its value was significantly higher in the order of 1B to 3B flours and 1M to 3M flours. The ash content also showed almost the same tendency as PC. The reason the PC and ash content increased in the order of 1B to 3B flours and 1M to 3M flours is related to the high protein and ash contents in the fractions close to the bran, as reported by Ando et al. (2002b) and Maeda and Morita (2003).

The APS values decreased significantly in the order of 1B to 3B flours, but there was no consistent tendency for the other flours. In terms of APS, the average value (µm) of the six flours from the four wheats was WW: 48.68, Kachikei 119: 37.31, Kitahonami: 33.82 and Norin 61: 27.03. The largest values were found in WW. Although all four of these wheats are soft wheats, it seemed that some differences in the hardness properties of each wheat grain affected the APS. Regarding DSC, which is known to increase as the hardness of wheat grains increases (Obuchowski et al., 2010; Williams, 1967), the average value (%) of the six types of flours from each wheat were WW: 6.69, Kachikei 119: 4.84, Kitahonami: 4.64 and Norin 61: 5.40. WW showed the greatest DSC. This result indicates that the hardness of wheat grains is related to the large APS of WW flours as compared with those of the other flours. However, it is possible that other factors are related to the low APS of Norin 61.

Regarding flours other than WW, the characteristics of the other six flours except for APS, which showed different values, tended to be similar to those of WW.

Figure 1 shows cookies produced by the SSC method using six types of WW flours. Clearly, the size of cookies became smaller in the order of 1B to 3M flours. This corresponds with the results of Table 1, in which the SSCD significantly declined in the order of 1B to 3M flours. From these results, it is evident that even in the flours prepared from the same wheat, the cookie quality change drastically due to differences in flour characteristics.

Fig. 1.

Photograph of cookies made from various WW flour streams¹⁾

¹⁾ WW: Westem White. lB, 2B, 3B, 1M, 2M and 3M are shown lB, 2B, 3B, lM, 2M and 3M flour stream milled from WW with a Bühler test mill, respective1y.

Figure 2 shows the relationships between all wheat flours and SSCD. These results indicate that as SSCD decreases in any of the flours made from the four wheats in the order of 1B to 3M flours, there is a concomitant decrease in cookie quality. It was found that flour from the core part of the wheat grains had a higher SSC quality.

Fig. 2.

Relationship between flour stream and SSCD¹⁾

¹⁾ 1B, 2B, 3B, 1M, 2M and 3M are flour streams milled flom various wheats with Bühler test mill, respectively. : WW, : Kachikei 119, : Kitahonami, : Norin 61. SSCD : Sugar snap cookie diameter, WW: Western White. The vertical bar is standard deviation of each value (n=8). The symbols folowed by different letters are significantly different (p < 0.05).

Comparing the differences between raw wheats and cookie quality of identical flours, the cookie quality of Kachikei 119 and Kitahonami flours was superior or equivalent to those of the others. In particular, the cookie quality of 1B, 2B and 1M flours of these wheats was significantly superior to those of WW and Norin 61. These results suggest that the aptitude of Kachikei 119 and Kitahonami might be better than that of WW, which is commonly used as a typical weak flour material in Japan, for cookie making. Kitahonami is a particularly good cultivar for WSN because of its somewhat low amylose content. It has been reported that a decrease in amylose content in flour reduces cookie quality (Kaidy et al., 1991; Nishio et al., 2009, 2011); however, with wheats such as Kitahonami, which has a slightly lower amylose content, this may not significantly affect cookie quality.

Simple correlations among characteristics of various flours    The relationships among the characteristics of the various flours are presented in Table 2 as simple correlation coefficients. The results show a significantly high correlation between SSCD and flour characteristics except for APS. In particular, very high correlations (P <0.001) were observed between SSCD, DSC and ash content. However, as there was also a very high correlation between DSC and ash content, it seems that DSC and ash content are likely evaluating almost the same flour characteristics in the wheat flour samples of this study.

Table 2. Correlation coefficients between characteristics of various flour streams milled from four wheats¹⁾

	SSCD	DSC	AC	PC	APS	Ash content
DSC	−0.938***	–
AC	0.644***	−0.500*	–
PC	−0.552**	0.433*	−0.577**	–
APS	−0.390	0.472*	0.052	0.137	–
Ash content	−0.814***	0.776***	−0.705***	0.646***	0.073	–

¹⁾  SSCD: Sugar snap cookie diameter, DSC: Damaged starch content, AC: Amylose content, PC: Protein content, APS: Average particle size.

*, ** and ***  indicate p < 0.05, 0.01 and 0.001, respectively.

These results can be attributed to the number of mill roll grindings, which basically increase in the order of 1B to 3M flours due to the milling mechanism of the test mill. In particular, a large amount of DSC is generated for 1M to 3M flours, in where the grinding is performed with a smooth roll. Therefore, the starch in the flours was damaged more in the order of 1B to 3M flours and DSC increased sharply (Table 1). On the other hand, the reason why the ash content showed the same tendency as DSC is that the flour produced by several roll grindings contains a high ash content, which is obtained from the fractions close to the bran of wheat grains. The positive correlation between DSC and ash content is apparent from the WW flour data in Table 1, and similar trends were seen in the flours of the other wheat samples (data not shown).

The results show that DSC, AC and PC, especially DSC, greatly influence the SSC quality (SSCD) of flour. Previous studies have reported that DSC and the value of sodium carbonate SRC (SC-SRC), which is related to DSC, have a significantly negative correlation with SSCD (Barrera et al., 2007; Colombo et al., 2008; Donelson and Gaines, 1998; Kaur et al., 2014). It has also been reported that there is a significant negative correlation between amylose content of wheat flour and SSCD (Kaldy et al., 1991; Nishio et al., 2009, 2011). Kang et al. (2014), Ram and Singh (2004) and Souza et al. (1994) reported that PC was correlated with SSCD.

It has been reported that APS is negatively correlated with SSCD (Barak et al., 2012; Kang et al., 2014), which is a representative indicator of weak flour quality. However, in this study, there was no significant correlation between APS and SSCD (Table 2). Since all the samples milled in this study were soft wheat, all the flours showed a small APS, and APS size does not have a significant effect on SSCD. The high correlation between APS of wheat flour and SSCD in previous studies may indicate the relationship between DSC, which rises in conjunction with APS to increase with grain hardness (Obuchowski et al., 2010; Williams, 1967), and SSCD. Therefore, it is suggested that since APS and DSC do not obviously change in conjunction with each other in the flours prepared from the soft wheats in this study, the correlation between APS and SSCD decreased.

DSC showed significant correlations with AC, PC, APS and ash content. The significant high correlation between DSC and ash content seems to be attributable to the flour characteristics changing in conjunction with each other. The following reason is thought to be related to the negative correlation between DSC and AC. The value of DSC significantly increased in the order of 1B to 3M flours, while the value of AC basically decreased in the order of 1B to 3B flours and 1M to 3M flours with some exceptions, and the average value of 1B to 3B flours showed a slightly higher value than that of 1M to 3M flours. The considerable correlation between DSC, PC and APS also seems to be related to the fact that these characteristic values tended to increase in the order of 1B to 3M flours.

As the correlations between other flour characteristics, significantly high correlations were found between AC and PC, AC and ash content, and PC and ash content. These results are thought to be related to fact that AC tends to decrease, and PC and ash content tend to increase in the grain fractions closer to the bran.

Multiple regression analyses between SSCD (SSC quality) of flours and various flour characteristics    Weak flour characteristics that greatly affect SSCD (SSC quality) are clarified in Table 2. Then, multiple regression analyses were performed using the stepwise method with SSCD as an objective variable. The results are shown in Table 3. DSC, AC and PC were selected as factors (explanatory variables) that can sufficiently explain the value of SSCD, and the contributions to changes in SSCD of DSC, AC and constant terms were statistically significant. The values of partial regression coefficient (PRC) for these three explanatory variables indicate that SSCD decreases with the increase of DSC and PC, and the decrease of AC. The values of standard partial regression coefficient (SPRC) also show that the most significant factor affecting SSCD, of the three explanatory variables, is DSC, and the contribution of DSC, AC and PC as explanatory variables to SSCD (total variance of this model) was 74.0, 17.1 and 8.9%, respectively.

Table 3. Multiple regression analysis with SSCD as objective variable¹⁾

Explanatory variable	PRC	SPRC	F	p	SL
DSC	−2.4078	−0.802	125.66	0.0000	***
AC	0.5648	0.187	5.59	0.0283	*
PC	−0.5728	−0.097	1.63	0.2157
Constant term	85.0692	–	95.19	0.0000	***

¹⁾  SSCD: Sugar snap cookie diameter, PRC: Partial regression coefficient, SPRC: Standard partial regression coefficient, F: F-value, p: Probability, DSC: Damaged starch content, AC: Amylose content, PC: Protein content, SL: Significant level (*; p < 0.05 and ***; p < 0.001)

The results are supported by previous reports of a high correlation between SC-SRC related to DSC or DSC and SSCD and between AC and SSCD (Barrera et al., 2007; Colombo et al., 2008; Donelson and Gaines, 1998; Kaldy et al., 1991; Kaur et al., 2014; Nishio et al., 2009, 2011), and Kang et al. (2014), Ram and Singh (2004) and Souza et al. (1944) also reported that PC affects SSCD.

From the ANOVA results of the MRMd, this MRMd shows a high R² = 0.926 and a corrected R² = 0.915, and the level of significance of this model was less than 0.001%. The value of R² could explain 92.6% of the total variation of SSCD by this MRMd.

Figure 3 shows the correlation between the actual measured SSCD value and the estimated SSCD value obtained using this MRMd. There was a high correlation (R² = 0.926) between the two values at a significance level of less than 0.001% and the standard error of residuals was very small at 2.22 mm. Moreover, it turned out that the actual value and the estimated value corresponded with each of the wheat flours from the four types of wheat.

Fig. 3.

Relationship between actual SSCD and estimated SSCD¹⁾

¹⁾ SSCD: Sugar snap cookie diameter, ○: WW, △: Kachikei 119, □: Kitahonami, ◇: Norin 61. Estimated SSCD was calculated using multiple regression model. WW: Western White. The line is straight line of linear correlation. The corrected R² is 0.915 at a level significance of less than 0.001% and its standard error of residual is 2.22 mm.

The results revealed that DSC, AC and PC of wheat flour characteristics affect the SSC quality (SSCD) of weak flour; and the influence of DSC is especially large. It was also shown that MRMd can be used to estimate SSCD with high accuracy.

Previous studies reported that higher water-absorbing flour causes lower SSC quality because the properties of the SSC dough limit the water content. The SSC dough of high water-absorbing wheat flour becomes hard because it takes water from the sugar that forms the syrup (Slade and Levine, 1994). The factors (DSC, AC and PC) identified in this study that affect SSCD all have properties that affect the water absorption of flour. From this, it is believed that the higher water absorption of flour is accompanied by a rise in DSC and PC and a decline in AC and is the main cause for the decrease in SSC quality. To support this idea, data for the relationship between the WSRC value, which is an index of the water absorption of flour, and the SSCD value were analyzed. They showed a significantly high correlation at R² = 0.916 and a level of significance of less than 0.001% (data not shown in detail).

In this study, MRMd, which can estimate SSCD with high accuracy, was obtained; however, this model was derived as a way to properly estimate SSC quality (SSCD) of the flour samples. Therefore, in order to evaluate the effectiveness of MRMd, it will be important to verify the accuracy of this model using various flours other than those used in this study in further studies. These results also indicate the importance of each flour stream quality to obtain desirable flour blending based on these quality characteristics. The combination of each flour stream yield and individual quality parameters should bring effective screening of wheat products and breeding selections.

Conclusion

The relationships between various soft wheat flour (prepared using a test mill from four soft wheats) characteristics and their SSC quality (SSCD) using 24 flour streams were analyzed. The results showed that the flour characteristics affecting SSCD are DSC, AC and PC; and the contribution of DSC is extremely large. The MRMd for estimating SSCD was derived using these factors as explanatory variables. Based on the ANOVA, this model was significant at a level of less than 0.001% and the estimation accuracy of SSCD was high (corrected R² = 0.915, standard error of residual = 2.22 (mm)). This model was effective as a simple and accurate method for estimating the SSC quality of various weak flours.

When these results are applied to commercial milling, where a large number of streams are produced, the weak flour characteristics of various streams can be evaluated much more easily and rationally than previously, dramatically improving the development of weak flour. In addition, the weak flour products of milling companies are usually developed by optimally blending of various streams. By using the results of the present paper, it is possible to easily estimate the weak flour properties of these blended flours.

Furthermore, DSC, AC and PC are all components related to the water absorption of flour, and water absorption characteristics are closely related to the SSC quality of flour. This is also supported by the extremely high correlation between WSRC and SSCD (R² = 0.916, P <0.001), which is considered to be an index of water absorption of flour. The results of this study suggest that the SSC suitability of Kachikei 119, a promising breeding line, and Kitahonami, a representative moderate wheat variety in Hokkaido, is equal to or greater than WW.

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• ii) https://www.hro.or.jp/info_headquarters/event/lunch/25.html (Apr.20.2019)
• iii) http://www.danno-shop.co.jp/shopbrand/ct186/ (Apr.20.2019)