Comparing Small-Scale Testing Methods for Predicting Wheat Gluten Strength Across Environments Yun Fang Li,1,† Yu Wu,1 Nayelli Hernandez-Espinosa,2 and Roberto J. Pen˜a2,† ABSTRACT
Cereal Chem. 92(3):231–235
Gluten strength is the main factor determining the rheological and processing properties of wheat. Rapid, small-scale tests that can indirectly predict gluten strength are extremely important for wheat-breeding selection, particularly when using pedigree methodology. The efficiency and reliability of three small-scale tests (SDS sedimentation volume [SDSS], swelling index of glutenin [SIG], and lactic acid retention capacity [LARC]) across three environments (E1, no stress; E2, drought stress; and E3, heat stress) were evaluated by using 15 common wheat and nine durum wheat cultivars. In the case of common wheat, SIG highlighted its advantage for predicting
gluten strength, even under stress environments, compared with LARC and SDSS, whereas SDSS showed the best relationship with bread loaf volume. For durum wheat, SIG showed the best predicting value in E1 and E3; however, under drought stress, SDSS, SIG, and LARC all lost their good ability for predicting gluten strength in durum wheat, which needs further investigation. Also, the comparison between two mixograph parameters (mixograph peak time and mixograph peak integral) for predicting gluten strength and the suitability of testing SIG and LARC with whole meal (or semolina) instead of refined flour were also investigated.
Wheat is one of the main sources of calories, protein, and other nutrients for a large part of the global population. Most (95%) of the commercially cultivated species are common wheat (Triticum aestivum L., AABBDD), and only around 5% is durum wheat (T. turgidum L. subsp. durum, AABB). One of the main reasons for the global popularity of wheat is that its whole meal, refined flour, or semolina, when mixed with water, form viscoelastic dough that can be easily processed into diverse types of food products owing to the unique viscoelastic properties of its gluten protein. Generally, common wheat flour is used mainly for bread (leavened breads, flat breads, and steamed breads), noodles, cookies, and cakes, whereas durum wheat is made into pasta products globally and into regional foods such as flat breads, couscous, and bulgur. Regarding the grain quality attributes, the requirements for good quality of different enduse products vary widely. However, regardless of end-use type, gluten strength (the combination of elasticity and extensibility) is the key factor that determines the processing quality of common wheat and durum wheat (Bushuk 1998; Pen˜a et al. 2002). Physical-chemical methods, such as SDS sedimentation volume (SDSS) or gluten index, and physical dough testing methods, such as farinograph development time, alveograph deformation energy (W), and mixograph peak time (MPT), all can be used for indirectly predicting the gluten strength. However, when it comes to their application in a wheat-breeding program, there are many factors to consider, such as breeding stage to initiate selection, sample size, repeatability, cost, labor, and time requirement. In early segregating generations (F2–F4), particularly in pedigree methodology, breeders always have to test hundreds of thousands of samples in a quite short period. Physical dough tests with the Glutomatic system (Perten Instruments, Springfield, IL, U.S.A.), farinograph, mixograph, and alveograph to determine the gluten index, farinograph development time, MPT, and dough strength W, respectively, require specialized instruments handled by experienced operators, use medium to large sample sizes, and are time consuming. Therefore, although regarded as classical and reliable testing methods for predicting gluten
strength and dough rheological properties, they can only be tested in advanced stages or just before the release of candidate cultivars. In contrast, small-scale testing methods characterized by relatively short testing time, such as SDSS, lactic acid retention capacity (LARC), or swelling index of glutenin (SIG), which estimate gluten strength, may represent a better option, particularly when the breeders wish to start selection for quality at late segregating or early advanced stages. SDSS, which mainly assesses the swelling of glutenin aggregates, has been widely used in various stages of wheat breeding (Axford et al. 1978, 1979; Pen˜a et al. 1990). Solvent retention capacity (SRC) was first created and developed for evaluating soft wheat flour quality. However, it also showed ability for predicting hard wheat quality (Gaines 2000; Gaines et al. 2006; Kweon et al. 2011). Among four different SRC tests, LARC showed close relationships with gluten strength parameters from a farinograph, mixograph, and alveograph, as well as bread loaf volume (Guttieri et al. 2001; Ram et al. 2005; Xiao et al. 2006). In addition, SIG has shown a strong correlation coefficient (r ³ 0.93, P < 0.001) with insoluble glutenin content, as well as positive correlations with SDSS, gluten index, and gel protein; consequently, it has been proposed as an efficient predictor of gluten strength (Wang and Kovacs 2002a, 2002b, 2002c; Gaines et al. 2006). Because executing any of these tests requires relatively simple equipment for evaluating several samples concurrently in short periods of time, SIG, LARC, and SDSS might be efficient methods to select for gluten strength in late segregating or early advanced stages. However, there are only a few studies comparing these different small-scale testing methods (Wang and Kovacs 2002b, 2002c; Gaines et al. 2006; Clarke et al. 2010). In addition, although the ability of SDSS, SIG, and LARC to screen for gluten strength in early breeding stages is well recognized, limited information is available concerning whether their predicting ability would vary across different environments, particularly in stress environments. Because the preparation of refined flour for testing includes the additional step of flour milling, whole meal is more desirable than flour or semolina in early generation. Bettge et al. (2002) and Zhou et al. (2007) explored the possibility scaling down flour or whole meal sample size for SRC. Wang and Kovacs (2002a) also simply compared the SIG test with three different samples (whole meal, semolina, and ground semolina) in durum wheat. However, the data about the suitability of the SIG and LARC tests, with whole meal or semolina instead of flour, are still inadequate for LARC in durum wheat and for SIG in common wheat. On the basis of the questions mentioned, we will focus on the influence of flour type and environmental conditions (E1, no stress;
† Corresponding
authors. E-mails:
[email protected] (R. J. Pen˜a);
[email protected]
(Y. F. Li). 1 Chengdu
Institute of Biology, Chinese Academy of Sciences, Chengdu, China. Chemistry and Quality Laboratory, International Maize and Wheat Improvement Center (CIMMYT), Mexico.
2 Wheat
http://dx.doi.org/10.1094/CCHEM-07-14-0157-R © 2015 AACC International, Inc.
Vol. 92, No. 3, 2015
231
E2, drought stress; and E3, heat stress) on the predicting ability of the three small-scale tests (SDSS, LARC, and SIG) for gluten strength. MATERIALS AND METHODS Materials and Field Experiment. Fifteen common wheat and nine durum wheat Mexican cultivars or advanced lines were evaluated. In common wheat, eight hard to medium-hard and seven soft cultivars were included. The common wheat (Kronstad, Avelino, Tollocan, Rayon, Triguenio, Atila, Tacupeto, Bacanora, Salamanca, Torocahui, Tonichi, Cucurpe, Santa Ana, Barcenas, and Cortazar) and durum wheat (Banamichi, Samayoa, Jupare, Aconchi, Yavaros, Cocorit, Rio Colorado, and Mohawk) cultivars used in this study represent a broad range in wheat quality. All the materials were planted with two replicates in Ciudad Obregon, Sonora, Mexico, with a randomized complete block design across two crop cycles, 2008–2009 and 2009–2010. Three treatments were applied and well controlled: E1, no stress; E2, drought stress with limited irrigation; and E3, heat stress with maximum temperatures of 34–35°C during the grain filling and ripening stages, achieved by late planting about one month after the optimum planting date. More detailed information about the field experiment design and meteorology data has been previously described (Li et al. 2013b). Physical Tests. Grain hardness, moisture, and grain/refined flour protein content were determined by near-infrared spectroscopy (Foss NIR systems and Infratec 1255 food and feed analyzer, Foss, U.S.A.), and tests were calibrated based on AACC International Approved Methods for hardness with particle size index (method 55-30.01), for moisture with an air-oven method (method 44-15.02), and for protein content with the Kjeldahl method (method 46-11.02). Lower hardness index (%) values correspond to harder cultivars. Grain protein content and flour protein content were adjusted to 12.5% and 14% moisture basis, respectively. The moisture of whole meal and semolina was measured with a Brabender (Germany) air oven according to AACCI Approved Method 44-15.02. Tempering and Milling. For common wheat, two types of testing materials (whole meal and refined flour) were prepared. For durum wheat, whole meal, refined flour, and semolina were generated as testing materials. Regardless of common wheat and durum wheat, all samples were milled with a Brabender Senior mill to obtain refined flour and a UDY (U.S.A.) cyclone mill with a 0.5 mm sieve for whole meal flour. Semolina was prepared with a Chopin (Tripette et Renaud, France) CD1 mill and a semolina purifier. Before flour milling, the hard, medium-hard, and soft wheat grain samples of common wheat were tempered to around 16, 15, and
14% moisture contents, respectively, whereas all the durum wheat samples were tempered to about 17%. Tests for Predicting Gluten Strength and Breadmaking Quality. SDSS was measured with 1 g of flour according to the method of Pen˜a et al. (1990). MPT and mixograph peak integral (MPI) were determined in common wheat with a mixograph (National Manufacturing, U.S.A.) according to AACCI Approved Method 54-40.02 with 35 g of flour. For durum wheat samples, because of their very hard kernel, constant water absorption (62.0%) was used to determine MPT and MPI. Chopin alveograph energy (W) was tested following AACCI Approved Method 54-30.02, with 60 g of flour, adjusting dough water absorption from 50% to 52–53% when the grain hardness value indicated medium-hard to hard grain. LARC was determined with AACCI Approved Method 56-11.01, by using a scaled-down version of 0.3 g of testing flour sample. SIG was determined with lactic acid according to the method of Wang and Kovacs (2002b). Breadmaking was performed according to AACCI Approved Method 10-09.01 with 100 g of flour, and bread loaf volume was determined by rapeseed displacement. Statistical Analysis. Summary statistics and Pearson correlation analysis were performed with SAS software (SAS Institute, U.S.A.). RESULTS AND DISCUSSION Summary Statistics of Common Wheat and Durum Wheat. Although the mixograph and alveograph both can be used for evaluating gluten strength (MPT and W, respectively), they have some differences (AACCI Approved Methods 54-30.02 and 54-40.02). The mixograph gives more information about the dough mixing characteristics (such as the tolerance of the dough to overmixing), whereas the alveograph provides details on elasticity and extensibility. Gluten strength is important for both common wheat and durum wheat. However, for common wheat, the elasticity-toextensibility (P/L) ratio is also an important factor, but a high P/L ratio exist in most durum wheat, and usually that is not a focal point that we pay attention to. Thus, both mixograph and alveograph parameters were tested for common wheat, but only the mixograph was selected for durum wheat. Because durum wheat is mainly made into pasta products, we did not conduct the breadmaking test for durum wheat. Therefore, W and loaf volume values were not measured in durum wheat. The summary statistics of the quality parameters measured in samples of the no-stress environment are shown in Table I. The results indicate that the common and durum wheat cultivars used in this study truly represent a wide range of gluten strength types. The results of all common gluten strength-related parameters show that the values of durum wheat consistently fall in a narrower and lower value range than those for common wheat. These value-range
TABLE I Summary Statistics of Common Wheat and Durum Wheat in a No-Stress Environmenta Variable Common wheat SDS sedimentation volume (mL) Swelling index of glutenin Lactic acid retention capacity (%) Mixograph peak time (min) Mixograph peak integral (% torque × min) _ W (×10 4 J) Loaf volume (cm3) Durum wheat SDS sedimentation volume (mL) Swelling index of glutenin Lactic acid retention capacity (%) Mixograph peak time (min) Mixograph peak integral (% torque × min) a
Minimum
Maximum
Mean
SD
CV (%)
9.5 3.9 109.0 1.7 60.5 151 690
22.0 5.9 172.6 6.0 207.1 614 940
15.0 4.9 133.9 3.4 122.7 337.1 797.8
2.8 0.5 14.3 1.2 38.0 120.0 57.0
19.0 10.2 10.7 33.7 31.0 35.6 7.1
8.0 3.5 99.9 1.5 50.1
14.5 5.2 134.6 3.6 148.5
9.9 4.5 120.3 2.9 106.4
1.9 0.4 8.1 0.6 24.2
19.0 8.7 6.7 19.1 22.7
SD = standard deviation; CV (%) = coefficient of variation; and W = alveograph deformation energy.
232
CEREAL CHEMISTRY
differences may be because of the influence of gluten protein composition, particularly that associated with the lack of D genome in durum wheat. Therefore, the criteria to define gluten strength are different between these two wheat species (Kerber and Tipples 1969). These results are consistent with those of previous studies (Liu et al. 1996; Ammar et al. 2000). Relationships Among Gluten-Related Parameters Across Environments. Gaines et al. (2006) compared the ability of five assessment methods to evaluate gluten quality of 33 soft wheat cultivars, and their predicting value decreased from alveograph W, LARC, MPT, Glutomatic gluten index, and SDSS, which are equivalent to the parameters of this study, except for gluten index (not included) (Gaines et al. 2006). In our study, MPT and W were regarded as gluten strength reference parameters for common wheat, but MPT for durum wheat. The correlation coefficients of small-scale tests with those reference parameters were examined across three different environments (no-stress, drought stress, and heat stress) (see Table II). All the samples tested here were refined flour. In the common wheat class, SDSS, SIG, and LARC were all significantly positively correlated with MPT, W, or both in three environments. These results implied that, to some extent, all three small-scale tests (SDSS, SIG, and LARC) can be used for predicting gluten strength. However, their correlation coefficients and significance levels were different across environments. For all the environments, SIG showed the highest correlation coefficients with MPT, followed by SDSS and LARC. However, when all parameters were compared with the alveograph deformation energy (W), the descending order was SIG, LARC, and SDSS in the no-stress (E1) and heat stress (E3) environments but SIG, SDSS, and LARC in the drought stress (E2) environment. Therefore, the advantage of SIG for predicting gluten strength was quite clear. It is interesting that SDSS and LARC showed a different order in predicting value when compared with MPT and with W, which may indicate that these two parameters are influenced by slightly different gluten functional properties. These results show that in selecting for gluten strength under different environmental conditions, there is a choice of smallscale parameters with different predicting value and that, depending on the environment, some choices are better than others. These results confirmed the conclusion that SIG was better than other small-scale tests (SDSS and LARC) in predicting the gluten strength of common wheat (Wang and Kovacs 2002c). In the case of durum wheat, the three small-scale parameters showed differences in predicting value compared with those observed in common wheat (Table II). Under heat stress, all three small-scale tests had significant correlations with MPT, whereas only SIG and LARC showed significant relationships in the nostress environment. Surprisingly, in the drought stress environment, only LARC displayed a low significant correlation with MPT, whereas the other two showed no significant correlation with MPT. Therefore, although SIG and LARC can effectively predict gluten strength of durum wheat in no-stress and heat stress environments,
in general the three small-scale tests were not reliable to select for gluten strength (as measured with the MPT parameter) under drought stress conditions. Drought and heat stress can influence almost all the quality parameters more or less in common wheat and durum wheat, as well as the gluten strength, dough rheological properties, and end-use quality (Li et al. 2013a, 2013b). It is not surprising that the changing quality attributes may affect the correlation coefficients of physical and chemical testing parameters across environments. However, it is still difficult to explain why those small-scale tests lose their predicting ability for gluten strength for durum wheat under drought stress only, whereas SDSS, SIG, and LARC still work well for durum wheat under heat stress as well as for common wheat under drought and heat stress. After a careful check, we found that in the drought stress environment of 2009–2010, the protein content (grain protein content [GP] and flour protein content [FP]) of durum wheat was abnormal, even lower than that in the no-stress environment: GP, 11.88% (drought stress) versus 12.11% (no stress); FP, 10.17% (drought stress) versus 10.66% (no stress) (Li et al. 2013a). Because the correlations among parameters can be affected by the effects of environment on the deposition of the different gluten protein entities (Flagella et al. 2010), we believe significant correlations in drought stress of durum wheat still exist among the three small-scale tests for predicting gluten strength, but they may have been indirectly affected by some other parameters, such as the unexpected lower protein content. Another mixograph parameter, MPI (% torque × min), was also evaluated. Both MPT and MPI are parameters taken at peak time. MPI, a direct indicator of dough mixing energy, is the equivalent of moment of impulse, a concept in classical mechanics, which means the time cumulative effect of torque. It correlates better with alveograph deformation energy (W) and therefore is a better predictor of gluten strength (Tables II and III). The correlation coefficients between MPI and other parameters in common wheat and durum wheat are shown in Table III. Irrespective of wheat type TABLE III Correlation Coefficients Between Gluten-Related Parameters and Mixograph Peak Integrala Environment Common wheat E1, no stress E2, drought E3, heat Durum wheat E1, no stress E2, drought E3, heat a
SDSS
SIG
LARC
MPT
W
0.63*** 0.58*** 0.37**
0.66*** 0.77*** 0.65***
0.59*** 0.56*** 0.32*
0.89*** 0.93*** 0.94***
0.75*** 0.83*** 0.87***
0.51** 0.20 0.50**
0.59** 0.32 0.78***
0.70*** 0.29 0.70***
0.94*** 0.96*** 0.97***
… … …
SDSS = SDS sedimentation volume; SIG = swelling index of glutenin; LARC = lactic acid retention capacity; MPT = mixograph peak time; and W = alveograph deformation energy. *, **, and *** indicate significance levels of P < 0.05, 0.01, and 0.0001, respectively.
TABLE II Correlation Coefficients Between Small-Scale Gluten-Related Parameters Across Environmentsa Versus W
Versus MPT Environment Common wheat E1, no stress E2, drought E3, heat Durum wheat E1, no stress E2, drought E3, heat a
SDSS
SIG
LARC
SDSS
SIG
LARC
MPT
0.53*** 0.47*** 0.34**
0.54*** 0.68*** 0.66***
0.47*** 0.45** 0.31*
0.65*** 0.68*** 0.37**
0.90*** 0.83*** 0.84***
0.76*** 0.61*** 0.52***
0.58*** 0.73*** 0.84***
0.24 0.23 0.45**
0.68*** 0.16 0.77***
0.60*** 0.42* 0.74***
… … …
… … …
… … …
… … …
MPT = mixograph peak time; W = alveograph deformation energy; SDSS = SDS sedimentation volume; SIG = swelling index of glutenin; and LARC = lactic acid retention capacity. *, **, and *** indicate significance levels of P < 0.05, 0.01, and 0.0001, respectively. Vol. 92, No. 3, 2015
233
(common or durum wheat), MPT showed the highest correlation coefficients across different environments, which means that when using the mixograph, MPT and MPI can be used alternatively with practically the same predictive value. However, all small-scale parameters (SDSS, SIG, and LARC) and the alveograph deformation energy value (W) showed better relationships with MPI than with MPT in common wheat and slightly better in durum wheat, although the poor relationship of small-scale parameters with MPI was again observed with durum wheat samples originating from drought stress (Table III). Therefore, MPI may be slightly better than MPT for predicting gluten strength in both common wheat and durum wheat. Comparing the Ability of Testing Methods for Predicting Bread Loaf Volume. Bread loaf volume is one of the most common parameters used to determine breadmaking quality. However, the breadmaking test can only be carried out during the last stages of the breeding program owing to the large sample size and labor requirements. Thus, using bread loaf volume as reference parameter to evaluate the predicting value of rapid small-scale tests to select for breadmaking quality in early stages of breeding is extremely useful. Therefore, correlation analysis between smallscale tests (SDSS, SIG, and LARC), dough viscoelastic properties (MPT, MPI, and W), and bread loaf volume were performed in common wheat samples across no-stress (E1), drought (E2), and heat stress (E3) environments. Table IV shows that the relationships between all the parameters with bread loaf volume changed with the environment. SDSS seemed to be the best and most stable parameter for predicting loaf volume across all environments, followed by W and SIG. The relationships between LARC, mixograph parameters (MPT and MPI), and loaf volume were low. However, these results were not consistent with those of Xiao et al. (2006), who found that when comparing SDSS and 5% LARC to predict bread loaf volume, the latter showed a higher correlation coefficient (Xiao et al. 2006). The results of the present study indicate that bread loaf volume is influenced importantly by other factors in addition to gluten strength, and these factors also influence importantly SDSS, SIG, and the deformation energy (W), which can be detected well under drought stress conditions. Effect of Testing Material on the Prediction Ability of Small-Scale Tests. Generally, in common wheat, refined flour is the main raw material to prepare diverse foods such as bread and noodles, whereas in durum wheat, semolina is the raw material to prepare different pasta. However, in wheat-breeding selection, especially in the early stages, whole meal is the best choice because of the small amount of sample available and time constraints between crop cycles; milling into semolina and refined flour is not feasible. It is well accepted that in determining SDSS, whole meal or refined flour can be used (Axford et al. 1979; Pen˜a et al. 1990). Therefore, we only focused on comparing the suitability of whole meal, flour, or semolina in determining SIG and LARC. Mean and coefficient correlation among different sample types (refined flour, semolina, and whole meal) of common wheat and durum wheat are shown in Table V. The results showed that irrespective of wheat species, the values of SIG and LARC decreased with the increase in particle size and/or with the level of refinement TABLE IV Correlation Coefficients Between Gluten-Related Parameters and Bread Loaf Volume in Common Wheata Environment
SDSS
SIG
LARC
MPT
MPI
W
E1, no stress E2, drought E3, heat
0.61*** 0.62*** 0.44**
0.36** 0.66*** 0.38**
0.24 0.49*** 0.17
0.24 0.24 0.30*
0.35** 0.36** 0.38**
0.47*** 0.66*** 0.35**
a
SDSS = SDS sedimentation volume; SIG = swelling index of glutenin; LARC = lactic acid retention capacity; MPT = mixograph peak time; MPI = mixograph peak integral; and W = alveograph deformation energy. *, **, and *** indicate significance levels of P < 0.05, 0.01, and 0.0001, respectively.
234
CEREAL CHEMISTRY
(amount of bran in the testing material). As for the possibility of using alternatively refined flour, semolina, or whole meal in common wheat, the correlation coefficient of values of refined flour and whole meal were quite high (0.92 and 0.83 for SIG and LARC, respectively); similarly, in durum wheat the relationships among whole meal, semolina, and refined flour all were significant. Bettge et al. (2002) reported that there was no problem for testing SRC with 1 g of flour or 0.2 g of whole meal. Zhou et al. (2007) also found that when using 0.5 g of flour instead of 5.0 g of flour, all four SRC parameters significantly correlated; however, only LARC still kept its positive correlation with 0.5 g of whole meal used. We imagine that ratios of soft and hard wheat may account for the difference (one used seven soft wheat and one hard wheat; another was made up of eight hard wheat and seven soft wheat). As for SIG, Wang and Kovacs (2002a) demonstrated that whole meal and ground semolina can be alternatives to semolina, but only durum wheat was evaluated. The results of this study, together with previous studies, showed that microscale whole meal, refined flour, and/or durum semolina can be applied in the testing of SIG and LARC for common wheat and durum wheat. CONCLUSIONS In common wheat, SDSS, SIG, and LARC all were significantly positively correlated with MPT, W, or both in three environments (E1, no stress; E2, drought stress; and E3, heat stress). However, the correlation coefficients and significance level may vary a lot, depending on growing (environmental) conditions of the cultivar. Compared with LARC and SDSS, SIG highlighted its ability for predicting gluten strength across environments. As for durum wheat, SIG and LARC can effectively predict gluten strength in no-stress and heat environments. However, all three (SDSS, SIG, and LARC) exhibit poor predictability of gluten strength in durum wheat when cultivated under drought stress, and the reason for this puzzling result is still to be determined. MPI (% torque × min) can be an alternative to MPT, but it was slightly better than MPT for predicting gluten strength in both common wheat and durum wheat. In addition, it was found that SDSS was the best and most stable parameter for predicting loaf volume across environments; whole meal, refined flour, and semolina of common wheat and durum wheat can be used for the testing of SIG and LARC, although the values of SIG and LARC decrease as particle size and/or level of refinement of the testing sample increases. Except for durum wheat under drought stress, SIG is strongly recommended in early generations of common wheat and durum wheat breeding selection for gluten strength, together with the use TABLE V Mean Values and Correlation Coefficients Among Different Testing Sample Types of Common Wheat and Durum Wheata Sample Type Mean Common wheat Whole meal (WM) Refined flour (RF) Durum wheat WM Semolina (SE) RF Correlation coefficient Common wheat WM versus RF Durum wheat WM versus RF SE versus RF WM versus SE a
SIG
LARC (%)
3.87 4.76
86.07 131.07
3.78 4.15 4.42
103.50 110.40 122.36
0.92***
0.83***
0.77** 0.90*** 0.78***
0.80*** 0.84*** 0.91***
SIG = swelling index of glutenin; and LARC = lactic acid retention capacity. ** and *** indicate significance levels of P < 0.01 and 0.0001, respectively.
of SDSS for predicting bread loaf volume in common wheat breeding, especially in early stages of generation. However, the suitability of their utilization in other stress environments needs further investigation. ACKNOWLEDGMENTS This project was partially funded by State-Sponsored Postgraduates Study Abroad Program of the China Scholarship Council, Main Direction Program of Knowledge Innovation of Chinese Academy of Sciences (No. KSCX3-EW-N-02-2), and the “Twelfth Five-Year” National Key Technology Research and Development Program (No. 2011BAD35B03). LITERATURE CITED AACC International. Approved Methods of Analysis, 11th Ed. Method 10-09.01. Basic straight-dough bread-baking method—Long fermentation. Approved November 8, 1995. Method 44-15.02. Moisture—Airoven methods. Approved October 30, 1975. Method 46-11.02. Crude protein—Improved Kjeldahl method, copper catalyst modification. Approved October 8, 1976. Method 54-30.02. Alveograph method for soft and hard wheat flour. Approved October 3, 1984. Method 5440.02. Mixograph method. Approved November 8, 1995. Method 5530.01. Particle size index for wheat hardness. Approved September 25, 1985. Method 56-11.01. Solvent retention capacity profile. Proposed November 3, 1999. [Archived method.] Available online only. AACCI: St. Paul, MN. Ammar, K., Kronstad, W. E., and Morris, C. F. 2000. Breadmaking quality of selected durum wheat genotypes and its relationship with high molecular weight glutenin subunits allelic variation and gluten protein polymeric composition. Cereal Chem. 77:230-236. Axford, D. W. E., McDermott, E. E., and Redman, D. G. 1978. Smallscale tests of bread-making quality. Mill. Feed Fertiliser 161:18-20. Axford, D. W. E., McDermott, E. E., and Redman, D. G. 1979. Note on the sodium dodecyl sulfate test of breadmaking quality: Comparison with Pelshenke and Zeleny tests. Cereal Chem. 56:582-584. Bettge, A. D., Morris, C. F., DeMacon, V. L., and Kidwell, K. K. 2002. Adaptation of AACC Method 56-11, solvent retention capacity, for use as an early generation selection tool for cultivar development. Cereal Chem. 79:670-674. Bushuk, W. 1998. Wheat breeding for end-product use. Euphytica 100: 137-145. Clarke, F. R., Clarke, J. M., Ames, N. A., Knox, R. E., and Ross, R. J. 2010. Gluten index compared with SDS-sedimentation volume for early generation selection for gluten strength in durum wheat. Can. J. Plant Sci. 90:1-11. Flagella, Z., Giuliani, M. M., Giuzio, L., Volpi, C., and Masci, S. 2010. Influence of water deficit on durum wheat storage protein composition and technological quality. Eur. J. Agron. 33:197-207.
Gaines, C. S. 2000. Collaborative study of methods for solvent retention capacity profiles (AACC Method 56-11). Cereal Foods World 45: 303-306. Gaines, C. S., Fr´egeau Reid, J., Vander Kant, C., and Morris, C. F. 2006. Comparison of methods for gluten strength assessment. Cereal Chem. 83:284-286. Guttieri, M. J., Bowen, D., Gannon, D., O’Brien, K., and Souza, E. 2001. Solvent retention capacities of irrigated soft white spring wheat flours. Crop Sci. 41:1054-1061. Kerber, E. R., and Tipples, K. H. 1969. Effects of the D genome on milling and baking properties of wheat. Can. J. Plant Sci. 49:255-263. Kweon, M., Slade, L., and Levine, H. 2011. Solvent retention capacity (SRC) testing of wheat flour: Principles and value in predicting flour functionality in different wheat-based food processes and in wheat breeding—A review. Cereal Chem. 88:537-552. Li, Y. F., Wu, Y., Hernandez-Espinosa, N., and Pen˜a, R. J. 2013a. Heat and drought stress on durum wheat: Responses of genotypes, yield, and quality parameters. J. Cereal Sci. 57:398-404. Li, Y. F., Wu, Y., Hernandez-Espinosa, N., and Pen˜a, R. J. 2013b. The influence of drought and heat stress on the expression of end use quality parameters of common wheat. J. Cereal Sci. 57:73-78. Liu, C.-Y., Shepherd, K. W., and Rathjen, A. J. 1996. Improvement of durum wheat pastamaking and breadmaking qualities. Cereal Chem. 73:155-166. Pen˜a, R. J., Amaya, A., Rajaram, S., and Mujeeb-Kazi, A. 1990. Variation in quality characteristics associated with some spring 1B/1R translocation wheats. J. Cereal Sci. 12:105-112. Pen˜a, R. J., Trethowan, R., Pfeiffer, W. H., and Van Ginkel, M. 2002. Quality (end-use) improvement in wheat: Compositional, genetic, and environmental factors. J. Crop Prod. 5:1-37. Ram, S., Dawar, V., Singh, R. P., and Shoran, J. 2005. Application of solvent retention capacity tests for the prediction of mixing properties of wheat flour. J. Cereal Sci. 42:261-266. Wang, C., and Kovacs, M. I. P. 2002a. Swelling index of glutenin test for prediction of durum wheat quality. Cereal Chem. 79:197-202. Wang, C., and Kovacs, M. I. P. 2002b. Swelling index of glutenin test. I. Method and comparison with sedimentation, gel-protein, and insoluble glutenin tests. Cereal Chem. 79:183-189. Wang, C., and Kovacs, M. I. P. 2002c. Swelling index of glutenin test. II. Application in prediction of dough properties and end-use quality. Cereal Chem. 79:190-196. Xiao, Z. S., Park, S. H., Chung, O. K., Caley, M. S., and Seib, P. A. 2006. Solvent retention capacity values in relation to hard winter wheat and flour properties and straight-dough breadmaking quality. Cereal Chem. 83:465-471. Zhou, M. P., Wu, H. Y., Yu, G. H., Zhang, X., and Ma, H. X. 2007. Microdetermination of solvent retention capacity in wheat. Jiangsu J. Agric. Sci. 23:270-275 (In Chinese).
[Received July 23, 2014. Accepted December 9, 2014.]
Vol. 92, No. 3, 2015
235
