| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Univ. of Idaho Research and Extension Center, P.O. Box AA, Aberdeen, ID 83210
Corresponding author (esouza{at}uidaho.edu)
 |
ABSTRACT |
|---|
 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Abbreviations: AWRC, alkaline water retention capacity • CIE, Commission Internationale de l'Eclairage • DI, drought intensity • DSI, drought-sensitivity index • ET, evapotranspiration • HMW-Glu, high molecular weight glutenin • PNW, Pacific Northwest • Yp, yield potential
|
INTRODUCTION |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Many studies have assessed interactions of genotype and production environment on wheat end-use quality parameters (Busch et al., 1969; McGuire and McNeal, 1974; Baenziger et al., 1985; Lukow and McVetty, 1991; Peterson et al., 1992; Robert and Denis, 1996; Robert, 1997; Grausgruber et al., 2000; Mikhaylenko et al., 2000). These studies have used statistical methodologies with varying degrees of sophistication to evaluate genotypic stability. A general conclusion of these studies is that genotype, environment, and interactions of genotype with environment significantly affect a wide range of end-use quality parameters; but relative to genotype main effects, the magnitude of genotype x environment interaction effects often is small. These studies, however, have not isolated the effects of moisture stress from other environmental factors, such as temperature, fertility, disease incidence, and soil type. Controlled studies have examined genotypic variation in response of yield and yield components to moisture-stress severity (Simane et al., 1993; Ehdaie and Waines, 1996; Dencic et al., 2000), but these types of studies have not been extended to evaluations of end-use quality. Moreover, a key question that remains unanswered in the literature is whether yield stability under moisture stress is related to quality stability. Therefore, the objective of this study was to characterize both genotypic yield response and quality response to applied moisture stress under relatively controlled conditions.
In describing the relationship between yield potential (Yp) and drought resistance, Blum (1996) noted that varieties with high Yp out-yield others, both under nonlimiting and under moderate stress conditions. However, under severe moisture-stress conditions (below a crossover point), Yp and yield are negatively associated. Fischer and Maurer (1978) described yield of a cultivar under drought stress (Y) as a function of the Yp of the cultivar, the severity of the moisture stress (drought intensity), and the drought-susceptibility index (DSI) of the cultivar. Drought intensity (DI) is calculated as DI = 1 - (X/Xp), where X is the mean yield of a population of cultivars under drought stress, and Xp is potential yield of the population of cultivars under nonlimiting moisture conditions. Drought intensity is a biological index of moisture stress, in contrast to physical indices such as soil water deficit. The DSI of a cultivar is the slope, d(Y/Yp)/d (X/Xp), measuring the change in yield of a given cultivar relative to the change in the biological index of stress, grain yield of a population of cultivars. Fischer and Maurer (1978) applied the DSI to cultivar yield; other parameters of cultivar performance, such as end-use quality, can be evaluated using the same analysis.
Hard red, hard white, and soft white spring wheats are produced under both irrigated and rain-fed conditions in the U.S. Pacific Northwest (PNW). These wheats have diverse end uses and quality requirements. Key quality characteristics for hard spring wheat in breadmaking include flour extraction (milling yield), flour protein concentration and composition, and dough-handling characteristics (rheological properties) (Finney et al., 1987). Although flour protein composition depends primarily on genotype, significant interactions with production environment have been reported (Huebner et al., 1997; Graybosch et al., 1996).
Soft wheat quality is determined largely by starch characteristics, pentosan concentration, and protein concentration and composition. Increased starch damage and pentosan concentration increases the hydrophilicity and thereby the water retention of flour (Donelson and Gaines, 1998; Kaldy et al., 1991). Alkaline water retention capacity (AWRC) is an indirect measurement of starch damage and pentosan concentration. In a study of genotype by environment interaction effects on wheat quality, AWRC was strongly influenced by production year (Bergman et al., 1998). Environmental stress during grain filling can result in kernel shriveling, which decreases flour extraction and increases AWRC (Gaines et al., 1997). Although both protein composition and concentration can influence soft wheat quality, protein concentration has a larger effect than protein composition (Souza et al., 1994). Therefore production variables that increase protein concentration, such as moisture stress, can decrease soft wheat quality.
Oriental noodle quality characteristics are particularly important for hard white cultivars. However, noodle quality characteristics also are important in hard red and soft white cultivars because flours from these classes may be blended with hard white flours to achieve texture targets. Color and color stability are critical criteria for oriental noodle flours. Miskelly (1984) characterized components affecting yellowness and brightness of Chinese- and Japanese-style noodles. Differences in brightness and yellowness were attributed to cultivar, flour extraction, protein concentration, starch damage, and brown and yellow pigment. While variation in these attributes largely was explained by cultivar differences, production environment also affected noodle color. However, specific environmental factors affecting noodle quality were not identified. Noodle eating quality also is determined by the firmness and elasticity of the cooked product. Protein concentration, dough strength, and starch paste viscosity affect the eating quality of Chinese noodles (Miskelly and Moss, 1985). A previous study of hard red spring genotypes produced under varying irrigation levels identified cultivar x irrigation level interactions for both protein concentration and dough strength (Guttieri et al., 2000).
Our primary objective was to compare the response of yield and quality parameters of diverse spring wheat genotypes to moisture-deficit treatments toward developing a comprehensive testing strategy for quality stability. A secondary objective was to evaluate the response of relatively new noodle quality parameters to moisture-deficit treatments and place those responses within the context of better-understood economic traits: yield, test weight, flour extraction, protein concentration, and dough rheology.
|
MATERIALS AND METHODS |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
|
|
General Experimental Conditions
The soil type was a Declo sandy loam (coarse-loamy, mixed, superactive, mesic Xeric Haplocalcids). Wheat was seeded at 110 kg ha-1 in rows spaced 18 cm apart. Experimental areas received broadcast applications of 146 kg ha-1 of N in 1995 and 45 kg ha-1 of N in 1996 as ammonium nitrate before planting, based on University of Idaho soil test recommendations. Bromoxynil (420 g ai ha-1) plus 4-chloro-2-methylphenoxyacetic acid (420 g ai ha-1) were applied for broadleaf weed control on 31 May 1995 and 4 June 1996.
The experimental area was irrigated by a fixed sprinkler system. Differential irrigation was achieved by blocking sprinkler nozzles. On 28 May 1995 and 4 June 1996, the entire experimental area was irrigated to 100% of field capacity based on estimated soil water holding capacity of a Declo sandy loam. Differential irrigation was applied from 12 June to 31 July 1995, and from 23 June to 29 July 1996 (Fig. 2) . Initiation of differential irrigation was timed to Feekes stage 4 to 6 (late tillering), depending on cultivar, and continued through crop maturity. Well-watered control subplots were irrigated weekly to replace estimated crop evapotranspiration (ET). Moderate moisture-deficit subplots received irrigation equivalent to the well-watered control only on alternate weeks. Severe moisture-deficit subplots were not irrigated after 19 June 1995 and 14 June 1996. Crop ET estimates were obtained from the United States Bureau of Reclamation Pacific Northwest Region Agrimet System, which maintains a weather station at the Aberdeen Research and Extension Center. Irrigation amounts were measured using rain gauges placed in the crop. In 1995, over the period of differential irrigation, control subplots, moderate moisture-deficit subplots, and severe moisture-deficit subplots received rainfall plus irrigation amounts equivalent to 109, 53, and 31%, respectively, of estimated ET. In 1996, over the period of differential irrigation, control subplots, moderate moisture-deficit subplots, and severe moisture-deficit subplots received rainfall plus irrigation amounts equivalent to 107, 59, and 25%, respectively, of estimated ET.
|
End-Use Quality Analyses
End-use quality analyses were conducted at the University of Idaho, Aberdeen quality laboratory. Methods for tempering, milling, measuring flour extraction, and mixograph analyses were as Souza et al. (1993) described and were in accordance with those described by the AACC (1995).
Alkaline noodles were prepared from 50 g of flour mixed to a crumbly consistency with 9 mL of an alkaline salt solution (0.25% w/v Na2CO3, 1% NaCl) on a 35-g National pin mixer (National Mfg., Lincoln, NE) for 45 s. Dough then was scraped down and mixed for an additional 45 s. The dough ball was rolled through an Atlas/Marcato (Wilton Industries, Woodridge, IL) hand-crank pasta maker at the zero (widest) setting for the first pass. The dough was folded twice and rolled again through the zero setting. The dough sheet then was passed successively through the narrower 4, 5, and 6 settings, for a final noodle sheet thickness of approximately 1.5 mm. The dough sheet was cut into three strips, which were stacked on a white ceramic tile for initial color measurement. Noodle sheet color was measured in Commission Internationale de l'Eclairage (CIE) tristimulus color space (L,* a,* b*) using a Minolta CM-2002 spectrophotometer (Minolta Camera, Chuo-Ku, Osaka, Japan) with a 50-mm measurement aperture. Noodle dough color was measured after sheeting (initially) and after 24-h incubation in a resealable plastic bag at room temperature. An average of three readings on one stack of three strips was recorded. CIE-L* measures noodle lightness, CIE-a* measures redness-greenness, and CIE-b* measures yellowness-blueness.
Statistical Analysis
Calculation of cultivar DSI is appropriate only for parameters having significant cultivar x treatment interactions. To test the significance of cultivar x irrigation treatment interactions, data initially were analyzed as a split-plot design: main plots were irrigation treatments (two well-watered blocks, one moderate, and one severe deficit block in each replication) and subplots were cultivars. Analysis of variance used PROC MIXED in SAS (SAS Institute, Release 6.12, 1997) with years and replications treated as random effects. Specific comparisons noted in the text and tables were tested using the ESTIMATE option in PROC MIXED.
Drought intensities in each of the two years of the study were calculated for each parameter significantly affected by moisture-deficit treatment. Fischer and Mauer's definition of DI (1978) presumed parameters would be reduced by moisture stress; parameters that increase under moisture stress have negative DI values. Therefore we modified Fischer and Mauer's original formula to use an absolute value: DI = |1 - (X/Xp)|, where X is the mean of the population of cultivars under a given moisture-deficit level and Xp is the mean of all cultivars under well-watered conditions. Drought intensities were calculated for each moisture-deficit level (moderate, severe) within each replication and were analyzed by analysis of variance.
The DSI was calculated for each cultivar and each parameter for which cultivar x irrigation treatment interactions were significant using PROC REG in SAS with the NOINT option (no fitted intercept). Cultivar response (e.g., 1 - Y/Yp) within each main plot (moisture-deficit level) within each replication was regressed on the DI calculated for the main plot within the replication. Data were combined over years in the calculation of DSI because the two drought treatments established similar DIs in the two years of the study. Tests of significance for the hypotheses DSI < 1 or DSI > 1 were based on 1-tailed t-tests at the 95% confidence interval using the parameter estimates and standard errors generated by PROC REG.
|
RESULTS AND DISCUSSION |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
|
|
|
|
|
In principle, calculation of DSI should mitigate the effect of cultivar Yp on assessment of cultivar drought tolerance (Fischer and Maurer, 1978). Yet Fischer and Maurer (1978) observed that, despite using the slope, or DSI, to remove effects of cultivar variation in Yp, cultivar DSI and Yp still appeared to be positively associated. The relationship of cultivar yield DSI with cultivar Yp (estimated as the mean of the two well-watered check blocks) in this trial was evaluated by regression analysis. Consistent with the observation of Fischer and Maurer (1978), regression of cultivar-yield DSI on cultivar Yp was highly significant (P < 0.001). Cultivar DSI increased 1.57 x 10-4 per unit increase in cultivar yield potential (Yp). Fischer and Maurer (1978) explained this relationship as a consequence of traits advantageous for maximum Yp that are inherently disadvantageous for drought tolerance. Fischer and Maurer (1978) also suggested that the positive association between Yp and DSI indicated the existence of traits desirable under drought that were undesirable under adequate moisture. Blum (1996) also raised the possibility of a penalty in Yp for genotypes with superior adaptation to drought stress. Blum noted that under some drought stress conditions, high Yp can be advantageous, but that "as stress intensifies, high yield potential and drought resistance become mutually exclusive." Blum noted that the understanding of the biological basis of these relationships is very limited. Higher stomatal conductance could be causally related to greater DSI values of high Yp genotypes. Stomatal conductance was highly correlated with grain yield in a set of CIMMYT wheat cultivars (Fischer et al., 1998). Canopy temperature depression (canopy minus air temperature) increased as stomatal conductance increased (Fischer et al., 1998). Reynolds et al. (1994) reported close association between canopy temperature depression and improved yields of spring wheat under irrigation. Genotypes with high stomatal conductance could be less able to conserve moisture throughout the growing season relative to genotypes with lower stomatal conductance.
Effect of Moisture Stress on Flour Quality Characteristics
Moisture deficit significantly affected flour extraction and time to peak mixograph resistance (mixograph peak time), but did not significantly affect flour protein concentration or mixograph peak height or tolerance (Table 2). Peak time was significantly longer in flours from grain produced under severe moisture deficit (3.7 min) relative to that produced under well-watered conditions (2.9 min). Cultivars differed significantly for flour protein, flour extraction, mixograph peak time, mixograph peak height, and mixograph tolerance (Table 2). The severe moisture-deficit treatment produced a significantly higher DI for flour extraction and mixograph peak time than the moderate moisture-deficit treatment.
Cultivar x moisture treatment interactions were highly significant for flour extraction and mixograph peak time (Table 2). For example, flour extraction of Amidon was not significantly reduced by moderate or severe moisture deficit, yet flour extraction of Westbred 926 was significantly reduced by moderate and severe moisture deficit (Table 7). Test weight was predictive of flour extraction; the Pearson correlation coefficient for test weight and flour extraction was 0.41 (P < 0.001). Mixograph peak time of flour from Penawawa produced under moisture stress was significantly longer than flour from Penawawa produced under well-watered conditions, yet mixograph peak times of flours of the other soft white cultivars, ‘Centennial’, ‘Fieldwin’, Pomerelle, and Treasure, were not significantly affected by moisture deficit (Table 7).
|
Differential response of cultivar flour mixograph peak time to drought stress may be associated with cultivar high molecular weight glutenin (HMW-Glu) genes. For example, Penawawa is a strong gluten soft white cultivar with the bread allele 5 + 10 for the HMW-Glu 1D locus (Souza et al., 1994). In contrast, Pomerelle has the weaker 2 + 12 allele (unpublished data). As a group, the cultivars carrying the 2 + 12 allele (Treasure, Pomerelle, Centennial, and Fieldwin) had an average DSI for mixograph peak time of 0.20. The DSI for mixograph peak time of Penawawa (1.22) is more similar to the DSIs of the hard red spring bread wheats carrying the 5 + 10 allele, such as Westbred 926 and Yecora Rojo. Precedent for this type of interaction is found in the interaction of HMW-Glu alleles with irrigation water salinity stress for mixing time of recombinant inbred lines (Kelman and Qualset, 1993).
Cultivar x moisture treatment interactions were not significant for flour protein concentration, mixograph peak height, or mixograph tolerance (Table 2). This is in contrast to the literature on quality genotype x environment interaction (Busch et al., 1969; McGuire and McNeal, 1974; Baenziger et al., 1985; Lukow and McVetty, 1991; Peterson et al., 1992; Guttieri et al., 2000; Mikhaylenko et al., 2000). Because we included genotypes of multiple market classes rather than a single market class as is common, cultivar effects may have outweighed interaction effects. Alternatively, the genotype x environment interactions previously observed for flour protein concentration, mixograph peak height, and mixograph tolerance reflect responses to environmental factors other than declining moisture availability from tillering through crop maturity. For example, when moisture availability was reduced from tillering through anthesis, but restored following anthesis, Guttieri et al. (2000) observed significant cultivar x irrigation treatment interactions for flour protein, mixograph peak height, and mixograph tolerance. Heat stress during grain filling also significantly affects flour protein accumulation and dough rheology (Corbellini et al., 1997), and genotype x nitrogen fertilization interaction effects on protein composition have been documented (Wieser and Seilmeier, 1998).
Moisture-deficit treatment significantly affected initial noodle lightness, initial yellowness, and yellowness after 24 h (Table 2). Severe moisture-deficit treatments reduced initial lightness (L*) and increased initial and 24-h yellowness (b*) (Table 5). The moderate and severe moisture-deficit treatments did not produce significantly different drought intensities for noodle lightness or yellowness at 24 h after sheeting, but produced significantly different drought intensities for initial noodle yellowness (Table 4). Cultivars differed for all initial and 24-h color parameters. Noodle color parameters of cultivar flours responded similarly to moisture deficit (Table 2).
Correlation among Drought-Susceptibility Indices
Correlations among DSIs were evaluated for the 16 cultivars included in the study. Grain yield DSI was positively correlated with test weight DSI (r = 0.63, P < 0.01) and flour extraction DSI (r = 0.62, P < 0.01). Test weight and flour extraction DSIs also were positively correlated (r = 0.58, P < 0.05), as would be expected by the overall correlation between test weight and flour extraction. However, mixograph peak time DSI was uncorrelated with grain yield, test weight, or flour extraction DSI. This is consistent with the results of a previous genotype x environment interaction study (Peterson et al., 1992) in which mixing parameter stability was uncorrelated with yield stability.
|
CONCLUSIONS |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
|
NOTES |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Received for publication November 29, 1999.
|
REFERENCES |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  B. N. Otteson, M. Mergoum, and J. K. Ransom Seeding Rate and Nitrogen Management on Milling and Baking Quality of Hard Red Spring Wheat Genotypes Crop Sci., March 19, 2008; 48(2): 749 - 755. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. R. Clayshulte, S. D. Haley, P. F. Byrne, and X. Shan Trait Associations at the Xgwm 261 and Rht-B1 Loci in Two Winter Wheat Recombinant Inbred Line Populations Crop Sci., November 7, 2007; 47(6): 2346 - 2355. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. J. Guttieri, K. M. Peterson, and E. J. Souza Milling and Baking Quality of Low Phytic Acid Wheat Crop Sci., October 2, 2006; 46(6): 2403 - 2408. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. J. Guttieri, R. McLean, J. C. Stark, and E. Souza Managing Irrigation and Nitrogen Fertility of Hard Spring Wheats for Optimum Bread and Noodle Quality Crop Sci., August 26, 2005; 45(5): 2049 - 2059. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. D. Butler, P. F. Byrne, V. Mohammadi, P. L. Chapman, and S. D. Haley Agronomic Performance of Rht Alleles in a Spring Wheat Population across a Range of Moisture Levels Crop Sci., March 28, 2005; 45(3): 939 - 947. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. J. Souza, J. M. Martin, M. J. Guttieri, K. M. O'Brien, D. K. Habernicht, S. P. Lanning, R. McLean, G. R. Carlson, and L. E. Talbert Influence of Genotype, Environment, and Nitrogen Management on Spring Wheat Quality Crop Sci., March 1, 2004; 44(2): 425 - 432. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. J. Guttieri and E. Souza Sources of Variation in the Solvent Retention Capacity Test of Wheat Flour Crop Sci., September 1, 2003; 43(5): 1628 - 1633. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Triboi, P. Martre, and A.-M. Triboi-Blondel Environmentally-induced changes in protein composition in developing grains of wheat are related to changes in total protein content J. Exp. Bot., July 1, 2003; 54(388): 1731 - 1742. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
I. H. Khalil, B. F. Carver, E. G. Krenzer, C. T. MacKown, G. W. Horn, and P. Rayas-Duarte Genetic Trends in Winter Wheat Grain Quality with Dual-Purpose and Grain-Only Management Systems Crop Sci., July 1, 2002; 42(4): 1112 - 1116. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| The SCI Journals | Agronomy Journal | Vadose Zone Journal | |||
| Journal of Natural Resources and Life Sciences Education |
Soil Science Society of America Journal | ||||
| Journal of Plant Registrations | Journal of Environmental Quality |
The Plant Genome | |||
