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Published online 1 March 2007
Published in Crop Sci 47:656-662 (2007)
© 2007 Crop Science Society of America
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CROP BREEDING & GENETICS

Effects of Solvent Retention Capacities, Pentosan Content, and Dough Rheological Properties on Sugar Snap Cookie Quality in Chinese Soft Wheat Genotypes

Qijun Zhanga, Yong Zhanga, Yan Zhanga, Zhonghu Hea,b,* and Roberto J. Peñac

a Institute of Crop Sciences, National Wheat Improvement Centre/The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agriculture Sciences (CAAS), No. 12 Zhongguancun South St., Beijing 100081, China
b CIMMYT-China Office, c/o CAAS, No. 12 Zhongguancun South St., Beijing 100081, China
c CIMMYT, Apdo. Postal 6-641, 066000 Mexico, D.F., Mexico

* Corresponding author (zhhe{at}public3.bta.net.cn).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Development of soft wheat (Triticum aestivum L.) cultivars with excellent cookie quality is an important breeding objective in southern China. Seventeen Chinese soft wheat genotypes grown at three locations in the 2000–2001 and 2001–2002 seasons in the southern winter wheat region, were uniformly evaluated for their solvent retention capacities (SRC), pentosan content, dough rheology, and suitability for making sugar snap cookies, to identify the main parameters that could be used in wheat breeding programs for improving cookie quality. Significantly negative correlations were found between water SRC, sucrose SRC, and sugar snap cookie diameter, and between sodium carbonate SRC, alkaline water retention capacity (AWRC), and water soluble pentosan, while significantly positive correlations were obtained between water, sodium carbonate, lactic acid, and sucrose SRC and AWRC. Alveograph parameters were more closely associated with sugar snap cookie quality compared with parameters from farinograph and extensograph except for water absorption. Water SRC was highly and significantly associated with farinograph water absorption, extensograph extensibility, alveograph P (tenacity), and P/L (the ratio of tenacity and extensibility). Regression analyses showed that sucrose SRC and flour particle size could be used to predict the sugar snap cookie diameter. Cluster analysis based on sugar snap cookie diameter indicated that ‘Jianmai 1’, ‘Wanmai 19’, and ‘Wanmai 48’ were characterized by good cookie quality, with low water soluble and total pentosans, water and particularly sucrose SRC, water absorption, and P and P/L values. It also indicated that substantial progress for soft wheat sugar snap cookie quality improvement could be achieved through appropriate use of current elite germplasm.

Abbreviations: AACC, American Association of Cereal Chemists • AWRC, alkaline water retention capacity • L, alveograph extensibility • P, alveograph tenacity • SKCS, Single Kernel Characterization System • SRC, solvent retention capacities • W, alveograph deformation work.


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
SOFT WHEAT flour is used to produce a wide range of commercial baked products. Sugar snap cookie and layer cake baking tests are usually used to evaluate soft wheat baking quality, particularly in breeding programs. Soft wheat flour that can produce large spread cookies and/or large volume cakes is usually considered to be of good quality for soft wheat products. An ideal flour for one class of products, however, may not be ideal for another (Finney 1989). Abboud et al. (1985) examined 44 flours representing a wide range of qualities and observed that, among soft wheat flours, sugar snap cookie diameter mainly depended on damaged starch and water absorption, while being negatively correlated with flour protein concentration within a cultivar and production environment. Bettge et al. (1989) found that alveograph deformation work (W), a measure of gluten strength, was negatively correlated with sugar snap cookie diameter. Good cookie flours hold water poorly, and the gross hydrophilic components of a sugar snap cookie formula are flour and sugar (Faridi et al., 1994). If the flour is less hydrophilic, more water is available to the sugar to form syrup, and the decreasing dough viscosity during baking, results in further spread of the dough, producing larger diameter cookies (Slade and Levine, 1994). Pentosans are highly hydrophilic structural carbohydrates that absorb 10 times their weight in water (Kulp, 1968; Jelaca and Hlynka, 1971). Kaldy et al. (1991) surveyed 25 soft wheat genotypes from a wide range of production environments and found that water soluble and total pentosan contents correlated with smaller cookie diameters across production environments. Moreover, flours with excessive water retention require increased baking times in cookie operations, resulting in both a less tender product and increased energy costs in bakeries. Damaged starch absorbs much more water than undamaged starch. Gaines et al. (1988) demonstrated that increasing damaged starch led to sugar snap cookie dough stiffness and decreased cookie diameter. Substituting damaged starch for flour in a sugar snap cookie formulation or for native prime starch in an all starch cookie model system increased alkaline water retention capacity (AWRC) and decreased cookie diameter (Donelson and Gaines, 1998). Slade and Levine (1994) developed the solvent retention capacities (SRC) test that was adopted by the American Association of Cereal Chemists (AACC) as method 56-11 (American Association of Cereal Chemists, 2000). The SRC test of flour is used to evaluate multiple aspects of wheat quality including pentosan content, starch damage, gluten strength, and general water retention based on the ability of flour to retain a range of solvents. The usefulness of SRC in predicting soft wheat quality products has been confirmed by several studies (Bettge et al., 2002; Guttieri et al., 2001, 2004; Ram and Singh, 2004), and environmental and management factors had little influence on SRC in comparison with genotype (Guttieri et al., 2002). Ram et al. (2005) also reported the close association between the SRC test and parameters from mixograph and farinograph. Addition of water soluble pentosans resulted in higher extensograph maximum resistance and lower extensibility (Wang et al., 2004). Souza et al. (1994) reported that individual alleles of high molecular weight glutenin subunits, which possessed significant effects on gluten strength (Gupta et al., 1994), did not significantly influence cookie diameter. However, little information of rheological properties has been available for soft wheat products. Therefore, more data from diverse genetic backgrounds and origins of wheat genotypes are needed to validate the value of SRC tests and rheological parameters since the above reports involve only U.S. and Indian wheat genotypes. Moreover, little information is available for the associations between SRC and pentosan content and alveograph parameters, that appear to be all important for soft wheat quality (Guttieri et al., 2001).

Autumn-sown spring wheat contributes about 25% of the total wheat production in China with a harvested area of 7.5 million hectares, grown across the middle and low Yangtze River Valley winter wheat region and the southwestern winter wheat region, where development of high quality soft wheat cultivars is a major breeding objective in addition to grain yield and disease resistance (He et al., 2001, 2002; Zhang et al., 2005). Breeding for better quality wheat started in the late 1980s in China, but most efforts have been focused on pan bread and noodle qualities with good progress being achieved during the last 10 yr. Breeding for soft wheat quality is still in its infancy and very little information is available on the suitability of Chinese wheat genotypes for cookies and cakes that consume around 5 million megagrams of wheat annually (Zhuang, 2003). Moreover, it has been frequently reported by millers that the farinograph and extensograph parameters recommended by the current Chinese national standardization method GB/T17983-1999 (National Quality Supervision Bureau, 1999) have little association with the qualities of the final products (Z.H. He, unpublished data, 2004). The objectives of this study were to evaluate the effects of SRC, pentosan, and dough rheology properties on baking qualities for sugar snap cookie; and to assess the suitability of Chinese germplasm for sugar snap cookie quality. The information generated from this study can be very important for Chinese wheat breeding programs and also has potential application in other wheat producing countries since germplasm from southern China is widely used as an important source for improving resistance to Fusarium head blight [caused by Fusarium graminearum (Schwabe)] worldwide.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Wheat Samples and Field Experiments
Seventeen soft wheat genotypes, including leading cultivars and advanced lines recommended by major breeding programs in China's southern winter wheat region, were grown in irrigated field trials at Dafeng in Jiangsu province, Hefei in Anhui, and Chengdu in Sichuan in the 2000–2001 and 2001–2002 cropping seasons. These well-adapted genotypes represent the current quality attributes of soft wheat genotypes grown in the middle and low Yangtze River Valley and the southwestern winter wheat regions. All these genotypes are the first group of soft wheat developed in China, which were supposed to have good cookie qualities based on indirect parameters obtained from farinograph and extensograph tests used the Chinese national standardization GB/T17983-1999 (National Quality Supervision Bureau, 1999), but no uniform cookie quality comparisons have been performed for these genotypes grown in common environments. Detailed genotype information is presented in Table 1. The three provinces are the wheat major producers in the southern winter wheat region; detailed environmental information is shown in Table 2. Each trial was planted on the locally recommended date shown in Table 2 at a seeding rate of 130 kg ha–1. Genotypes were sown in a randomized complete block design with two replications. Each plot, consisting of five rows 4 m long and 0.20 m apart, was given standard fungicide and weed protection to ensure optimal grain yield and quality. All trials were irrigated by flooding. Field management and timing of management practices including fertilization generally matched local commercial production practices.


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  		Table 1. Name, pedigree, and Single Kernel Characterization System (SKCS) grain hardness of 17 soft wheat genotypes grown across six environments.

 

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  		Table 2. Characteristics of the testing environments during the two wheat seasons.

 
Quality Trait Testing and Baking Analyses
Harvested grain samples from two replications were mixed and cleaned before conditioning and milling to maintain a manageable number of samples for quality testing. Thousand kernel weight was obtained as an average of three samples, each containing 200 seeds. Grain volume was determined using a Schopper chondrometer with a 1-L container according to AACC approved method 55-10 (American Association of Cereal Chemists, 2000). Grain hardness was determined on 300-kernel samples with a Perten 4100 Single Kernel Characterization System (SKCS, Perten Instruments North America Inc., Reno, NV). Samples were tempered to around 14.5% moisture content by AACC method 26-10 and milled with a Brabender Quadramat Senior Mill (AACC method 26-21A). Grain and flour protein concentrations were obtained with a near-infrared analyzer (Instalab 600, Newport Scientific Sales and Services Ltd., Warriewood, NSW) following AACC method 39-10, calibrated by the Kjeldahl method (AACC method 46-12). Grain and flour moisture contents, flour ash content, Zeleny sedimentation value, and Falling Number were measured according to AACC methods 44-15A, 08-01, 56-61A, and 56-81B, respectively. Flour particle size was measured by a laser-diffraction Heros and Rodos particle size analyzer (Japan Laser Co. Ltd., Tokyo).

Farinograph parameters (water absorption, development time, and stability) were determined from a 15-min farinograph mixing curve using 50 g of flour (14% moisture basis) according to AACC method 54-21. Extensograph parameters (maximum resistance, extensibility, and energy) were determined according to AACC method 54-10. Alveograph values (tenacity P, extensibility L, P/L, and W) were obtained using a Chopin alveograph (Chopin, Villeneuve-la-Garenne, France) with the RCV4 calculator according to AACC method 54-30A.

Solvent retention capacities and AWRC were determined for each flour sample according to AACC methods 56-11 and 56-10, respectively. Total and soluble pentosans were analyzed by the method of Hashimoto et al. (1987). All determinations were done at least twice and were expressed on a 14% moisture basis.

Sugar snap cookies were prepared and evaluated according to AACC method 10-52. The average diameter, thickness, and ratio of diameter and thickness for six cookies were recorded.

Statistical Analyses
Analysis of variance was conducted by PROC MIXED in the Statistical Analysis System (SAS Institute, 1997) with genotypes as fixed effects, while environments, the combination of location and year, as random. PROC VARCOMP was used to estimate variance components associated with different sources of variation. Genotypic least square means across all six environments for all quality traits were calculated and used for subsequent analyses. Pearson's linear correlation coefficients among quality parameters were obtained by SAS PROC CORR (N = 17). Multiple regression analyses was conducted with cookie diameter as the dependent variable, independent variables were selected on the basis of their ability to optimize the R2 value of the model. Regression models were selected using the Mallows Cp statistics, identifying the models for which Cp approximated (p + 1), where p is the number of independent variables in the model. The optimum regression was identified as the model having P with the greatest difference in Cp between the optimum and second optimum subset of independent variables (SELECTION = RSQUARE in PROC REG).

Genotypic classification based on the average sugar snap cookie diameter across locations was conducted using PROC Cluster function of SAS. Cookie diameter was standardized to avoid potential scaling effects, and Ward's method (Ward, 1963; Williams, 1976) using squared Euclidean distance as the dissimilarity measure was adopted. The tree diagram assisted in the determination of clusters in the data, along with experience and knowledge of the genotypes. Classification efficacy was determined by examining the partitioning of the sum of squares among sources, the proportion of variance accounted for by the clusters. Analysis of variance was conducted again with cluster as a categorical variable to derive mean cookie quality parameters for each cluster and to test levels of significance.


   RESULTS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Both genotype and environment contributed to the diversity of all test quality parameters (Table 3). Analysis of variance indicated that genotypic effects were highly significant for all traits. The environmental variance components were much larger than genotype for most of the traits investigated such as thousand kernel weight, grain volume, grain and flour protein content, flour yield, flour particle size, ash content, Zeleny sedimentation value, water SRC, sucrose SRC, farinograph development time and stability, alveograph P/L value, and cookie thickness and diameter/thickness, while genotypic variance components contributed more to grain hardness, water soluble and total pentosans, lactic acid SRC, extensograph maximum resistance, extensibility, and energy, and alveograph P and W values. However, the variance components of genotype, environment, and genotype by environment interaction which included error variance, contributed almost the same for AWRC, sodium carbonate SRC, farinograph water absorption, alveograph L value, and cookie diameter. There was a narrow range of grain and flour protein contents and ash contents, and a relatively narrow range of AWRC, water SRC, and sodium carbonate SRC values were also presented in comparison with lactic acid and sucrose SRC among genotypes (Table 3). However, there was a wide range of variation for milling quality, rheological, and cookie quality parameters among genotypes. The range in grain and flour protein content, particle size, flour yield, and sucrose SRC among environments was somewhat larger than that measured across genotypes.


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  		Table 3. Mean and range for milling quality, solvent retention capacities, pentosan, dough rheological parameters, and starch pasting properties of 17 wheat cultivars across six environments.

 
The ranges in grain volume, grain hardness, Zeleny sedimentation value, all extensograph parameters, alveograph P and W values, total and water soluble pentosans, AWRC, and lactic acid SRC across genotypes were much larger than that of environments, whereas ranges in thousand kernel weight, ash content, all farinograph parameters, alveograph L, sodium carbonate SRC, and cookie baking quality were similar for genotypes and environments.

Association of Quality Parameters
Falling numbers of {alpha} amylase activity for each sample were at low levels, together with the overall range of thousand kernel weight (31.9–54.1 g), all indicting that samples were sound, and eliminating uncertainties associated with the nonamylase factors, such as flour particle size, which are associated with other factors affecting the quality of soft wheat products.

The relationship between cookie diameter, thickness, and quality traits, determined by genotype means over six environments with N = 17, are presented in Table 4. Thousand kernel weight, grain volume, flour yield, and flour particle size were significantly correlated with sugar snap cookie diameter. However, no significant associations between protein content, Zeleny sedimentation value, and cookie diameter were observed. High and significant negative correlations between water SRC, sucrose SRC, and sugar snap cookie diameter were found, followed by sodium carbonate SRC, AWRC, and water soluble and total pentosans. For rheological parameters from farinograph and extensograph, the only significant associations were between water absorption and extensibility, with cookie diameter. However, alveograph P, P/L, and W values were all significantly negatively associated with cookie diameter. This clearly indicated that alveograph measures are more suitable for evaluation of soft wheat genotypes for cookie than farinograph and extensograph methods. Very similar associations between the above traits and cookie diameter/thickness were observed, however, their contributions to cookie thickness are in a different direction due to the negative association between cookie diameter and thickness.


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  		Table 4. Correlations of milling quality, solvent retention capacities, pentosan, dough rheological parameters, and starch pasting properties with cookie quality of 17 wheat cultivars across six environments.

 
Associations among milling quality, SRC tests, pentosan, and dough rheological properties are presented in Table 5. Flour yield was strongly and negatively correlated with water soluble and total pentosans, sodium carbonate SRC, sucrose SRC, and to a lesser extent with AWRC and water SRC. Flour particle size was significantly and positively correlated with SKCS grain hardness (r = 0.696, P < 0.01), water SRC (r = 0.575, P < 0.05), and alveograph P (r = 0.619, P < 0.01) and W (r = 0.575, P < 0.05). Highly and significantly positive correlation among water, sodium carbonate, lactic acid, and sucrose SRC, and AWRC were also observed, with r ranging from 0.723 (P < 0.001) to 0.883 (P < 0.001). Farinograph water absorption was significantly positively correlated with water soluble and total pentosans, water SRC, sodium carbonate SRC, and sucrose SRC, AWRC, and alveograph P and P/L, but significantly and negatively correlated with extensograph extensibility and alveograph L. Extensograph extensibility was significantly and positively correlated with alveograph L, but significantly negatively correlated with water soluble SRC, sodium carbonate SRC, sucrose SRC, AWRC, farinograph water absorption, and alveograph P and W.


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  		Table 5. Correlations among milling quality, solvent retention capacities, pentosans, dough rheological parameters, and starch pasting properties of 17 wheat cultivars across six environments.{dagger}

 
Regression of sugar snap cookie diameter from all six experiments on sucrose SRC was highly significant, with the following model explaining 56.5% of the total variation in cookie diameter: y = 9.626 – 0.019x1, where y represents cookie diameter (cm), x1 represents sucrose SRC (F = 58.5). The cookies with 8-cm or larger diameter in the total dataset were produced by flour ranging in sucrose SRC between 63.8 and 91.4 g kg–1. After fitting the sucrose SRC model, the partial R2 of flour particle size was 8.8%, indicating that this value predicts additional variation in cookie diameter. All regressions of cookie diameter for each genotype (N = 17) in the six environments on flour sucrose SRC and particle size were statistically significant (P < 0.05) in each of the six environments. The optimum multiple regression model for cookie diameter of each genotype across the six environments (N = 17) included flour sucrose SRC and particle size and followed y = 9.758 – 0.021x1 – 0.011x2, where x2 represents particle size (F = 33.5, R2 = 0.827), suggesting that genotypes with large cookie diameter could be selected in soft wheat breeding programs using sucrose SRC and flour particle size, that is, these two traits could be used to predict 82.7% of the variation in cookie diameter.

Clustering Genotypes by Cookie Diameter
Cluster analysis was also applied to assess differences in quality traits among genotypes based on sugar snap cookie diameter. To classify genotypes meaningfully, the cluster number was arbitrarily set to 3 (Fig. 1 ). This gave 90.6% of the sum of squares of the genotypes retained, resulting in 82% reduction in the data array size. The dendrogram for the classification analysis appears in Fig. 1.


Figure 1
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  		Figure 1. Dendrograms from the classification of cultivar using Ward's method on environment standardized mean data from the six environments for sugar snap cookie diameter.

 
Analysis of variance indicated that there were significant differences among clusters for grain volume, water soluble pentosans, AWRC, water, sodium carbonate, and sucrose SRC, farinograph water absorption, alveograph P and P/L, and cookie baking quality parameters. Among these measured parameters, there was little overlap among clusters for water soluble and total pentosans, water and sucrose SRC, farinograph water absorption, alveograph P and P/L values, and cookie diameter and spread factor (Table 6). No significant differences among clusters, however, were observed for most of the measured parameters, including thousand kernel weight, SKCS grain hardness, kernel and flour protein content, flour yield, ash content, lactic acid SRC, farinograph development time and stability, extensograph maximum resistance, extensibility, and energy, and alveograph deformation work.


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  		Table 6. Means and ranges for milling quality, solvent retention capacity, dough rheological properties, and cookie quality of the three groups of genotypes across six environments.

 
Cluster 1, comprising Jianmai 1, Wanmai 19, and Wanmai 48, was characterized by low water soluble and total pentosans, low water and, particularly, low sucrose SRC, low farinograph water absorption, low alveograph P and P/L values, and good cookie baking quality (Table 6). Cluster 2, consisting of Y 10–8, Fengyou 4, Chuanmai 107, Fengmai 24, and Fengmai 27, was characterized by medium water soluble and total pentosans, medium to high water and sucrose SRC, medium farinograph water absorption, and medium to high alveograph P value, medium to low P/L value, with medium cookie diameter and medium to low spread factor. Cluster 3, including cultivars Demai 4, Yangmai 5, Yangmai 9, Yangmai 13, Wanmai 18, Yumai 18, Yumai 50, Ningmai 9, and Chuannong 1, had the highest water soluble and total pentosans, water and sucrose SRC, farinograph water absorption, and alveograph P and P/L values, with low cookie diameter and spread factor.


   DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
As shown in Table 6, both genotype and environment contributed to the wide range of variation in solvent retention capacities, pentosan, dough rheological properties, and cookie quality parameters of China's autumn-sown soft spring wheat genotypes. This was similar to the findings for China's spring-sown spring wheat genotypes and autumn-sown winter wheat genotypes (Zhang et al., 2004, 2005). Genotypic effect was highly significant for all measured traits, and genotypes grouped into three clusters based on sugar snap cookie diameter. Cluster 1 including Jianmai 1, Wanmai 19, and Wanmai 48, among which Wanmai 19 is one of the parents of Wanmai 48, was characterized by acceptable cookie quality. This indicated that although a broad range of variation is available in Chinese soft wheat genotypes, selection among the currently available genotypes could greatly improve overall wheat quality before new genotypes with better quality are developed. Moreover, substantial progress in soft wheat sugar snap cookie quality improvement could be achieved through appropriate use of current elite germplasm. The effect of environment on variation for most of the quality traits, however, suggested that production of cultivars conferring improved quality will require a growing environment that favors expression of their genetic potential, for the eventual stable production of high quality soft wheat grain.

The result of this study indicated that the selected Chinese soft wheat genotypes generally conferred medium to poor cookie quality. Some of the cultivars in clusters 1 and 2, like Yumai 50 and Chuanmai 107, even had P values below 40 and P/L ratio below 0.75, which would be on target for a good cookie quality in Latin America (Souza, personal communication, 2006), but both had a medium gluten strength with farinograph stability time longer than 2.0 min, this may make these cultivars more appropriate for crackers or batter coatings (Souza, personal communication, 2006). This is in agreement with what we have found for Chinese autumn-sown winter wheat genotypes (Zhang et al., 2005), in which the commonly observed phenomenon that hard wheat was characterized by high protein content and strong gluten strength, and soft wheat was characterized by low protein content and weak gluten strength was not always found in Chinese wheat genotypes. Some genotypes with low grain hardness had strong gluten and low protein content, whereas others with high grain hardness had weak gluten properties and high protein content, due to the lack of divergent selection made in different hardness classes. In fact, there has been no direct selection on quality traits, especially grain hardness and gluten strength in China in the past. Therefore, more efforts are needed to improve cookie quality in the southern winter wheat region.

Regression and multiple regression analyses of sugar snap cookie diameter on sucrose SRC and flour particle size indicated that these two parameters together are strong predictors of cookie diameter. There was a highly significantly positive correlation between sucrose SRC, and water soluble and total pentosans, which is consistent with the observation of Gaines (2000), who reported that sucrose SRC could generally be used to predict pentosan content, and thus cookie diameter was a function of pentosan content and flour particle size. Bettge and Morris (2000) also indicated that variation for cookie diameter came primarily from total pentosans, and pentosans had played a role on grain texture among soft wheat genotypes, thereby acting as major contributors to cookie baking quality. Flour requirements for all four SRC tests are relatively small, with only 20 g required for two determinations in each solvent. The parameters are easy to measure and a large number of samples could be analyzed in a single day (Ram et al., 2005). Highly significant positive correlations among water, sodium carbonate, lactic acid, and sucrose SRC were also observed (Table 5). Due to the highly significant genotypic effect for all four solvents, the relatively narrow range of water SRC and sodium carbonate SRC values, and the lack of significant correlation between lactic acid SRC and cookie diameter, it seems to be of less value for selection for water and sodium carbonate SRC. Moreover, Guttieri and Souza (2003) also found that around 89% of the total variance was attributed to the genotypic variance for sucrose SRC, indicating that selection for a lower sucrose value should be highly effective in identifying genotypes with larger cookie diameter. Therefore, sucrose SRC could be used in early generation selection for soft wheat cookie quality. Such predictions are consistent with the reports of Guttieri et al. (2001), Guttieri and Souza (2003), and Bettge et al. (2002).

Bettge and Morris (2000) and Guttieri et al. (2001) also reported that flour protein content was the most important factor in influencing soft wheat cookie quality besides sucrose SRC. No significant correlation between flour protein content and cookie diameter occurred in the current study, this might have been partially due to the relatively narrow range of protein contents. Flour particle size was independent of most of the measured traits, and significant positive correlations were found only between particle size and water soluble SRC, and alveograph P and W values, largely in agreement with Yamamoto et al. (1996). The results also indicted that after sucrose SRC, flour particle size was an important predictor of cookie diameter, and therefore, it also was an important selection criteria for improving cookie quality of Chinese wheat genotypes.

This study clearly indicated that alveograph parameters were more suitable for evaluation of cookie quality as compared with farinograph and extensograph properties, and alveograph P, P/L, and W values all were significantly negatively correlated with cookie diameter, as reported by other researchers of strong negative association between alveograph parameters and cookie diameter (Bettge et al., 1989; Guttieri et al., 2001, Agyare et al., 2005). Therefore, alveograph parameters instead of farinograph and extensograph should be used in the Chinese national standardizations for soft wheat. In breeding programs, alveograph testing can be used only for testing advanced generation lines because it requires more sampling and is more expensive than sucrose SRC and flour particle size tests.


   ACKNOWLEDGMENTS
 
The authors are grateful to Professors Edward Souza and Bob McIntosh, and Dr. Gerard Branlard for kindly reviewing this manuscript. Financial support was kindly provided by the National Natural Science Foundation of China (30471085), the National Basic Research Program (2002CB111300), and the international collaboration project on wheat improvement from Ministry of Agriculture of the People's Republic of China.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Q. Zhang and Yo. Zhang contributed equally to this work.

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication May 31, 2006.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 





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