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Genotypic and Environmental Effects on Grain Yield and Quality of Oat Grown in North Dakota.

CHARACTERISTICS most commonly used to describe oat quality include test weight, groat percentage, groat weight, and groat composition. The major groat compositional characteristics relating to quality include the protein, oil, and [Beta]-glucan concentrations. Plant breeders strive to generate cultivars that will yield well and produce consistently high quality grain over a wide range of environments. A relatively small amount of information is available in the literature describing the effects of environment and genotype on oat grain yield and quality.

Test weight is the most commonly used method to evaluate oat quality (Forsberg and Reeves, 1992). Test weight is a measure of the density of oat grains as they are packed into a given volume. It is reported to be affected by kernel and groat size, groat density, hull thickness and length, and groat percentage as well as the presence of awns, diseases, and tertiary kernels (Murphy et al., 1940; Atkins, 1943; MacKey, 1959; Forsberg and Reeves, 1992). Several studies have reported genotype x environment interaction for oat test weight (Bartley and Weiss, 1951; Gullord and Aastveit, 1987).

Groat percentage is a measure of the proportion of the whole oat that is recovered as groat after dehulling. Groat percentage has long been recognized as an important indicator of oat quality (Love et al., 1925; Stoa et al., 1936; Atkins, 1943; Bartley and Weiss, 1951). Peek and Poehlman (1949) considered test weight to be a more valuable oat quality evaluation tool than groat percentage because hand-dehulling of oat was considered too tedious. Stoa et al. (1936) suggested that early maturing oat cultivars were superior in groat percentage, and rust susceptible lines were generally higher in percent hull. These conclusions were also supported by the findings of Bunch and Forsberg (1989). The studies of Bartley and Weiss (1951) indicated strong environmental effects on groat percentage and demonstrated positive correlations between groat percentage and yield, test weight and kernel weight. Youngs and Shands (1974) demonstrated that tertiary kernels had a higher groat percentage than primary and secondary kernels, although Palagyi (1983) found that genotypes with higher levels of tertiary kernels had lower groat percentage. He suggested that tertiary kernels compete with primary and secondary kernels for assimilate, preventing them from filling properly. Very little information is available concerning the control of oat groat weight, although one study (Gullord and Aastveit, 1987) indicated significant genotype x environment interactions for the trait.

Among the compositional components of oat, protein concentration often is ranked highly in importance because of its nutritional significance. Oat groats may contain from 124 to 244 g [kg.sup.-1] protein, and this protein is of higher nutritional quality than most other grains (Peterson, 1992). Studies have shown genotypic and environmental effects on oat protein concentration (Jenkins, 1969; Forsberg et al., 1974; Saastamoinen et al., 1989). In particular, nitrogen supply strongly affects oat protein concentration (Ohm, 1976; Welch and Yong, 1980; Welch et al., 1991; Humphreys et al., 1994; Jackson et al., 1994).

Oat contains much higher oil concentrations than do other small grains (Youngs, 1986). Higher oil content is an advantage for animal feeding because of its higher caloric content. However, in food applications, higher oil concentrations are deleterious because of their potential for rancidity and production of off-flavors. Studies have indicated that both genotype and environment affect groat oil concentration (Brown et al., 1966; Saastamoinen et al., 1989; Welch, 1975; Humphreys et al., 1994). Cooler growth environments have been reported to stimulate oil accumulation in groats (Beringer 1971, Saastamoinen et al., 1989). Negative correlations between protein concentration and oil concentration among different oat genotypes have been reported (Brown et al., 1966; Forsberg et al., 1974). This relationship has been disputed (Youngs and Forsberg, 1979), and cultivars with both high protein and oil concentrations have been developed.

The [Beta]-glucan component of oat has garnered increasing interest in recent years because of studies that indicated that [Beta]-glucan associated with oat bran in diets can lower blood cholesterol in both animals and humans (Peterson, 1992). Variation in groat [Beta]-glucan concentration among different oat genotypes and differing environmental conditions have been studied (Welch and Lloyd, 1989; Peterson, 1991; Welch et al., 1991; Brunner and Freed, 1994; Humphreys et al., 1994; Jackson et al., 1994; Peterson et al., 1995).

Although strong genotypic differences in [Beta]-glucan can be demonstrated consistently, environmental effects have been more difficult to document (Peterson, 1991; Peterson et al., 1995). For example, of three recent studies where the effects of nitrogen fertilization on [Beta]-glucan accumulation were examined, one study reported significant nitrogen x location and nitrogen x year interactions affecting [Beta]-glucan concentration in groats, whereas, the other two studies found no significant main effect or interaction effects of nitrogen on [Beta]-glucan concentration (Brunner and Freed, 1994; Humphreys et al., 1994; Jackson et al., 1994). Several studies have suggested that drought conditions may influence [Beta]-glucan accumulation in oat (Peterson, 1991; Welch et al., 1991; Brunner and Freed, 1994; Peterson et al., 1995), but no study has conclusively demonstrated this.

Starch is the major storage component in oat. However, because most of the value of oat lies in the nonstarch components, its concentration is usually not considered in quality analyses. The remaining components of oat composition include ash and fiber components other than [Beta]-glucan. Fiber components, which include pentosans (arabinoxylans), cellulose, lignin, and galactomannans (Aspinall and Carpenter, 1984; Henry, 1987) are important to quality because of their contribution toward total dietary fiber. Ash represents the mineral components of oat and is primarily composed of phosphorus, calcium, potassium, copper, manganese, iron, sodium, and magnesium (Peterson et al., 1975). Although many of these are considered essential minerals to be included in the diet, they are generally not considered in selection of oat for quality.

In this study, 12 oat genotypes adapted for production in North Dakota and divergent in protein, oil, [Beta]-glucan, and groat size were grown at four different locations over three years. Detailed environmental data were gathered at these sites. Our goals were to determine the relative effects of specific meteorological factors on oat grain yield and quality, and to determine sources of quality trait variation observed in the oat breeding program.

MATERIALS AND METHODS

Plant Material

Ten oat cultivars (AC Marie, Bay, Hazel, Hytest, Jerry, Marion, Paul, Riel, Robert, and Whitestone, and two breeding lines, ND880786, and ND880946) were grown in 1994, 1995, and 1996 at Carrington, Edgeley, Minot and Prosper, ND, USA. The soil type at Carrington is Heindahl (coarse, loamy, mixed Udic Haploborolls) and Emrick loams (coarse, loamy, Pachie Haploborolls). Soils at Edgeley are Barnes (fine-loamy, mixed Udic Haploboroll) and Cresbard (fine, Montmorillonitic Glossic Udic Natriboroll) loam complex. Soils at Minot are Williams (fine, loamy, mixed Typic Argiborolls) loam. Soils at Prosper are Perella (fine, silty, mixed, frigid, Typic Haploquolls) and Beardon (fine, silty, mixed frigid, Aerie Calciaquolls) silty clay loams.

A seeding rate of 2.47 x [10.sup.6] kernels [ha.sup.-1] was used for all experiments. Herbicide treatments consisted of pre-emergence application of 3.93 kg [ha.sup.-1] propaclor (2-chloro-N-isopropylacetanilide) and post-emergence application at the 3-leaf stage with a tank mix of 0.14 kg [ha.sup.-1] thifensulfuron {methyl 3 [[[[(4-methoxy-6-methyl-1,3,5-triazin-2yl)amino]carbonyl] amino]sulfonyl]-2-thiophenecarboxylate}, 0.07 kg [ha.sup.-1] tribenuron {methyl 2-[[[[N-(methoxy-6-methyl-1,3,5-triazin-2y1) methylamino] carbonyl] amino] sulfonyl] benzoate}, and 0.14 kg [ha.sup.-1] clopyralid (3,6-dichloro-2-pyridinecarboxylic acid, mono-ethanolamine salt). Experimental units consisted of four rows spaced 0.3 m apart and 2.4 m long. The two center rows were harvested with a two-row binder and threshed with a plot thresher. Seed was cleaned with an air screen cleaner to remove chaff. Test weight was determined by weighing a fixed volume of grain. Planting and harvest dates are shown in Table 1.
Table 1. Planting and harvest dates and mean seasonal climatic
data for the environments evaluated in this study.

                    Planting   Harvest     Mean daily
Location     Year     date      date     solar radiation

                                             Langley

Carrington   1994     4 May     8 Aug          511
Carrington   1995     5 May    14 Aug          488
Carrington   1996     3 May     8 Aug          488
Edgeley      1994    12 May     8 Aug          517
Edgeley      1995    23 May    22 Aug          485
Edgeley      1996    23 May    21 Aug          511
Minot        1994    20 Apr    11 Aug          513
Minot        1995     3 May    14 Aug          474
Minot        1996     2 May    20 Aug          479
Prosper      1994     9 May     4 Aug          493
Prosper      1995    24 May    15 Aug          465
Prosper      1996    28 May    20 Aug          492

             Mean daily high   Mean daily low   Total seasonal
Location       temperature      temperature     precipitation

                        [degrees] C                   cm

Carrington        21.1              7.9              22.3
Carrington        20.3              8.3              33.6
Carrington        19.7              6.8              28.1
Edgeley           21.9              8.7              28.5
Edgeley           20.8              9.1              29.4
Edgeley           20.7              8.0              21.7
Minot             21.4              8.2              30.5
Minot             20.8              8.3              26.3
Minot             20.6              7.8              18.6
Prosper           22.3              9.0              33.1
Prosper           21.7              9.3              29.3
Prosper           21.1              8.4              17.3


Climatic data included daily high and low temperatures, precipitation, and solar radiation. Climatic data were gathered by automated stations maintained by the Soil Science Department, North Dakota State University, Fargo, ND. Seasonal means of climatic conditions for each environment analyzed here are presented in Table 1.

Sample Preparation

Sound grain was stored in paper bags and envelopes. Whole oat samples were steam-treated in a vegetable steamer for 20 min to inactivate enzymes. Samples were dehulled with a Codema Laboratory Oat Huller (Codema Inc., Eden Prairie, MN)(1). The groat proportion was obtained by weighing the sample before and after dehulling. Dehulled groats were cleaned by hand to ensure that all hulls and broken groats were removed. Oil concentration and groat weight were determined on whole groats. Groats for starch, protein, [Beta]-glucan, and ash analyses were milled in a Retsch model ZM-1 centrifugal mill with a 0.5-mm collar screen (Brinkmann Instruments, Westbury, NY). Flour was stored in small sealable plastic bags and placed in a desiccator at room temperature until analyzed.

Chemical Analyses

Moisture of flour samples was determined by heating a 2-g flour sample for 2 h in a convection oven at 130 [degrees] C. Samples were allowed to cool in a desiccator and reweighed. Moisture was proportional to the weight loss during the heat treatment. All chemical analyses are expressed on a dry weight basis.

Oil analysis was performed on whole groats with an Oxford 4000 NMR (Abingdon, England). Groats were dried in a convection oven at 130 [degrees] C for 2 h to eliminate the interference of water to the oil signal. Samples were allowed to cool in a desiccator before analysis. Calibration of the instrument had been established by comparison of signals with groats with known oil concentration, established by Soxhlet extraction with petroleum ether. Starch was analyzed according to the American Association of Cereal Chemists (1995) method 76-11.

Protein was analyzed by combustion analysis with a Leco FP-428 Nitrogen Analyzer (Leco Corporation, St. Joseph, MI). Total nitrogen was converted to protein by multiplying by 6.25.

Ash of a 2-g sample was determined in an ashing oven by initially incubating samples in crucibles for 1-h at 350 [degrees] C, then increasing the oven temperature to 450 [degrees] C, and 590 [degrees] C after 1-h intervals, then maintaining 590 [degrees] C for 18 h. After ashing, crucibles were removed from the ashing oven and allowed to cool in a desiccator before measuring ash weight. Total (1 [right arrow] 3), (1 [right arrow] 4)-[Beta]-D-glucan ([Beta]-glucan) was determined by the method of McCleary and Glennie-Holmes (1985).

Groat weight was derived from the number of kernels in a 10-g sample.

Experimental Design and Statistical Analyses

Experimental plots were arranged in a randomized complete block design with three replicates within each environment Analysis of variance was performed with the SAS General Linear Model procedure (SAS Institute, Cary, NC), where all environments were considered random and genotypes were considered fixed. Pearson correlation matrixes were calculated across all environments for each genotype with the Statistix computer package (Analytical Software, Tallahassee, FL) and were pooled and their homogeneity determined by procedures described by Steel et al. (1997, p. 295-297). Significance of individual correlation coefficients were evaluated using 108 degrees of freedom, according to Steel et al (1997, p. 295).

RESULTS AND DISCUSSION

Means and ANOVA

Genotypic means of grain yield and quality characteristics (Table 2) indicated that the hull-less cultivar Paul ranked highest in groat proportion and test weight and was second lowest in grain yield, as would be expected for a hull-less cultivar. Calculation of groat yields (not shown) indicated that Paul had the highest groat yield of all the cultivars grown.
Table 2. Genotypic means of oat grain yield and grain quality
characteristics across 12 environments.

                                 Test                  Groat    Groat
Genotype            Yield       weight       % Groat   weight   starch

                                                                g [kg.
                   Mg [ha.   kg [m.sup.-3]      %        mg     sup.-1]
                   sup.-1]                                       dry
                                                                 basis

AC Marie            3.41          433         68.8      20.2      596
Bay                 4.11          457         66.1      19.5      590
Hazel               3.49          493         70.8      21.8      571
Hytest              3.31          546         71.2      23.3      571
Jerry               3.63          512         68.9      21.1      598
Marion              3.62          477         67.8      22.4      581
ND880786            3.14          457         64.0      16.8      591
ND880946            3.94          466         68.9      18.7      598
Paul([dagger])      3.22          601         91.7      21.3      572
Riel                3.85          504         70.7      20.9      592
Robert              3.51          468         67.7      22.5      604
Whitestone          3.85          470         63.7      17.0      602
LSD([double
  dagger])(0.05)    0.46           20          2.7       1.2       12

                   Groat     Groat       Groat       Groat
Genotype           protein   lipid   [Beta]-glucan    ash

                          g [kg.sup.-1] dry basis

AC Marie            146       78.1        48.8        18.7
Bay                 196       46.4        51.9        20.4
Hazel               191       69.9        53.3        21.3
Hytest              195       54.2        51.6        20.7
Jerry               173       50.0        43.4        19.6
Marion              165       65.6        57.6        20.3
ND880786            161       68.7        57.0        19.8
ND880946            158       67.2        53.3        18.6
Paul([dagger])      183       71.7        49.9        19.1
Riel                175       59.5        46.3        18.4
Robert              157       59.9        43.3        19.1
Whitestone          160       63.1        47.7        18.7
LSD([double
  dagger])(0.05)      5        1.4         2.0         0.6

([dagger]) Hull-less genotype.

([double dagger]) Calculated using the environment x genotype mean
square as an error term.


Environmental means for grain yield and quality characteristics (Table 3) indicated that the Carrington, Edgeley, and Prosper locations in the 1995 growing year had reduced grain yields, test weights, groat percentages, and groat weights compared to other environments. These differences are attributed to particularly severe crown rust infections at those locations in that year. Unfortunately, no quantitative measures of crown rust infestation of plots were collected during this experiment. Groat composition appeared to be relatively unaffected at the locations heavily infested by crown rust (Table 3).
Table 3. Environmental means of oat gr. in yield and grain quality
characteristics across 12 environments.

                                  Test                Groat    Groat
Environment         Yield        weight     % Groat   weight   starch

                      Mg           kg                          g [kg.
                 [ha.sup.-1]   [m.sup.-3]      %        mg     sup.-1]

Carrington '94      4.31          508        80.3      19.7     594
Carrington '95      1.79          408        57.5      15.9     614
Carrington '96      1.90          468        63.6      21.6     549
Edgeley '94         4.52          541        77.2      23.2     640
Edgeley '95         3.09          415        64.6      15.5     622
Edgeley '96         5.23          520        66.1      25.3     547
Minor '94           4.77          570        82.4      22.7     597
Minot '95           2.78          547        74.4      22.7     600
Minot '96           3.40          538        67.3      23.3     546
Prosper '94         4.19          493        81.7      19.9     588
Prosper '95         2.60          411        63.6      16.9     620
Prosper '96         4.49          467        61.5      18.9     548
LSD([dagger])
  0.05              0.21           12         1.3       0.9      24

                  Groat    Groat       Groat       Groat
Environment      protein   lipid   [Beta]-glucan    ash

                             g [kg.sup.-1]

Carrington '94     163      61.7        53.9        20.9
Carrington '95     162      63.6        52.1        22.1
Carrington '96     166      63.4        47.2        19.1
Edgeley '94        180      58.7        55.5        19.4
Edgeley '95        153      68.6        53.5        21.1
Edgeley '96        186      61.7        45.6        17.5
Minor '94          189      61.5        51.2        17.1
Minot '95          190      65.0        49.3        18.3
Minot '96          184      63.6        44.7        16.0
Prosper '94        168      57.3        52.1        22.5
Prosper '95        161      63.4        52.8        22.6
Prosper '96        158      65.9        46.3        18.2
LSD([dagger])
  0.05               4       1.7         3.2         0.8

([dagger]) Calculated with the environment x replicate mean
square as the error term.


Analyses of variance indicated significant genotype x environment interactions (P [is less than] 0.05) for all characteristics measured (Table 4), although the magnitude of the interactions MS were relatively small in comparison to the main effects. Interactions for yield, test weight, groat percentage, and groat weight were all due to differences in ranking as well as differences in magnitude of changes of genotypes among the environments. The most likely factor contributing to the significant environment x genotype interactions for yield, test weight, groat percentage, and groat weight was the differential level of crown rust infection among the cultivars. The genotypes Paul and Bay appeared to be more resistant to crown rust races prevalent that year because these genotypes were less severely affected than were the other genotypes. The significant (P [is less than] 0.05) genotype x environment interactions for groat composition were almost entirely due to differences in changes in magnitude of values among the genotypes in the different environments. The genotypic ranking for compositional characters was very uniform among the environments.

The magnitude of the main effect MS (Table 4) suggested that yield, groat starch and groat ash were more strongly influenced by environment than genotype. Test weight, groat percentage, groat weight, protein, and [Beta]-glucan appeared to be about equally affected by environment and genotype, whereas groat lipid appeared to be more strongly influenced by genotype than by environment.
Table 4. Mean squares (MS) for grain yield and quality
characteristics of 12 genotypes across 12 environments.

                        Grain yield,   Test weight,   % Groat,
Source            df         MS             MS            MS

Environment        11    48.07(**)     115 104(**)    2 713.8(**)
Replicate          24     0.19             616            7.2
  (Environment)
Genotype           11     3.24(**)      76 366(**)    1 900.9(**)
Genotype x        121     0.95(**)       1 895(**)       32.5(**)
  Environment
Residual          264     0.15             229            8.9

Source            Groat weight, MS   Starch, MS   Protein, MS

Environment            366.6(**)     40 777(**)     6 296(**)
Replicate                3.6          2 486            72
  (Environment)
Genotype               157.2(**)      5 498(**)     9 946(**)
Genotype x               6.9(**)        695(**)       103(**)
  Environment
Residual                 1.1            398            24

Source            Lipid, MS   [Beta]-glucan, MS   Ash, MS

Environment         334(**)        469.2(**)      180.5(**)
Replicate            13             42.6            2.7
  (Environment)
Genotype          3 120(**)        791.5(**)       31.9(**)
Genotype x            9(**)         18.0(**)        1.6(**)
  Environment
Residual              2             13.1            0.4

(**) P < 0.01.


Correlation Analyses

Phenotypic correlations of oat grain yields and quality characteristics with environmental conditions were calculated to determine environmental conditions associated with oat characteristics (Table 5). Grain yield was correlated positively with both high and low temperatures in April and May, indicating that warm spring weather was favorable for higher yields. These conditions provided for earlier planting and accelerated seedling development. Both July and August low temperatures were correlated negatively with yield. This suggested that the high night temperatures during the final stages of grain development may reduce grain yields through excessive respiration. Several previous studies have found negative relationships between high night temperatures and grain yield in maize and other crops (Peters et al., 1971; Christy and Williamson, 1985). They suggested that excessive respiration at night depleted photosynthate that would have otherwise contributed to grain yield. A negative correlation between seasonal precipitation and grain yield (Table 5) suggested that most of the environments had adequate moisture to sustain growth. Excessive rain in July probably contributed to more severe crown rust infections, which were associated with negative effects on yields. Seasonal solar radiation was highly and correlated positively with yield (Table 5). The importance of solar radiation to yield suggests that gross photosynthesis may have been a major limiting factor to plant growth. Many previous investigators have attempted to link photosynthesis and yield, and most have failed (Gifford et al., 1984), usually because so many factors influence yield. However, shading experiments have resulted in decreased yields in maize, Zea mays L., (Early et al., 1967; Reed et al., 1988) and in soybeans, Glycine max (L.) Merr., (Christy and Porter, 1982). In soybeans, 50% shade resulted in a 25 to 35% yield decrease (Christy and Porter, 1982).
Table 5. Phenotypic correlations of grain yield and grain quality
characteristics with environmental condition across twelve
environments pooled from 12 genotypes.

                         Test                     Groat        Groat
           Yield        weight      % Groat       weight      starch

                          Mean Daily High Temperature

Season    0.494(**)    0.180        0.580(**)   -0.073        0.425(**)
April     0.591(**)    0.476(**)    0.843(**)    0.201(*)     0.414(**)
May       0.422(**)    0.364(**)    0.830(**)    0.070        0.467(**)
June     -0.186       -0.564(**)   -0.495(**)   -0.368(**)    0.082
July     -0.040       -0.266(**)   -0.052       -0.452(**)    0.383(**)
August   -0.323(**)   -0.364(**)   -0.702(**)   -0.181       -0.291(*)

                          Mean Daily Low Temperature

Season    0.160       -0.027        0.413(**)   -0.138        0.092
April     0.493(**)   -0.055        0.405(**)   -0.267(*)     0.613(**)
May       0.536(**)    0.153        0.618**)    -0.141        0.563(**)
June     -0.168       -0.390(**)   -0.044       -0.449(**)    0.586(**)
July     -0.427(**)   -0.353(**)   -0.206(*)    -0.501(**)    0.451(**)
August   -0.533(**)   -0.517(**)   -0.593(**)   -0.365(**)    0.126

                              Precipitation

Season   -0.362(**)   -0.283(**)    0.175       -0.377(**)    0.623(**)
April    -0.198(*)    -0.143       -0.105       -0.183        0.705(**)
May       0.134       -0.081       -0.294(**)    0.014       -0.122
June      0.220(*)     0.570(**)    0.568(**)    0.272(*)    -0.225(*)
July     -0.498(**)   -0.527(**)   -0.122       -0.439(**)    0.362(**)
August   -0.063        0.109        0.529(**)   -0.109        0.656(**)

                          Mean Daily Solar Radiation

Season    0.668(**)    0.480(**)    0.487(**)    0.407(**)    0.019
April     0.579(**)    0.522(**)    0.649(**)    0.442(**)   -0.040
May       0.344(**)    0.400(**)    0.804(**)    0.085        0.470(**)
June     -0.049       -0.189       -0.531(**)    0.214(*)    -0.358(**)
July     -0.085        0.261(*)     0.077        0.102        0.386(**)
August   -0.297(**)   -0.054       -0.643(**)    0.311(**)   -0.542(**)

           Groat        Groat                        Groat
          protein       lipid      [Beta]-Glucan      ash

                       Mean Daily High Temperature

Season    0.042       -0.542(**)    0.449(**)       0.308(**)
April     0.230(*)    -0.696(**)    0.517(**)       0.168
May       0.093       -0.703(**)    0.586(**)       0.310(**)
June     -0.385(**)    0.167       -0.016           0.391(**)
July     -0.149        0.352(**)    0.228(*)        0.244(*)
August   -0.092        0.707(**)   -0.466(**)      -0.466(**)

                       Mean Daily Low Temperature

Season   -0.119       -0.519(**)    0.205(*)        0.463(**)
April    -0.206(*)    -0.321(**)    0.627(**)       0.477(**)
May      -0.042       -0.441(**)    0.586(**)       0.382(**)
June     -0.209(*)     0.062        0.430(**)       0.593(**)
July     -0.114        0.380(**)    0.219(*)        0.278(*)
August   -0.136        0.539(**)   -0.111           0.137

                           Precipitation

Season   -0.133       -0.259(*)     0.565(**)       0.624(**)
April    -0.033        0.087        0.478(**)       0.188
May       0.080        0.498(**)   -0.205          -0.290(*)
June      0.381(**)   -0.242(*)    -0.106          -0.356(**)
July     -0.427(**)   -0.315(**)    0.400(**)       0.744(**)
August    0.148       -0.406(**)    0.568(**)       0.467(**)

                       Mean Daily Solar Radiation

Season    0.232(*)    -0.472(*)     0.170          -0.226(*)
April     0.195       -0.660(**)    0.192          -0.129
May       0.071       -0.590(**)    0.591(**)       0.204(*)
June     -0.033        0.272       -0.389(**)      -0.212(*)
July      0.405(**)    0.261(*)     0.141          -0.338(**)
August    0.217(*)     0.408(**)   -0.662(**)      -0.503(**)

(*) Indicates significance at P = 0.05.

(**) Indicates significance at P = 0.01.


Test weight and groat percentage, like yield, were correlated positively with warm spring temperatures and correlated negatively with hot late summer temperatures (Table 5). It is likely that test weight and groat percentage were affected by many of the same physiological processes discussed that affected yield. Like yield, test weight was also correlated negatively with July precipitation. This probably also was due to the association of crown rust infections with heavy July precipitation. Test weight and groat percentages were correlated positively with June precipitation, suggesting the importance of good vegetative growth towards full groat development. Test weight and groat percentages were also correlated positively with seasonal solar radiation, again suggesting the importance of gross photosynthesis to the grain filling process. The similarity of factors affecting both test weight and groat percentage is consistent with previous studies indicating correlations between test weight and groat percentage (Doehlert et al., 1999).

Groat weight differed from yield, test weight and groat percentage, in that it was less strongly correlated with warmer spring temperatures, but was more strongly negatively correlated with warmer summer temperatures. This suggested that groat weight was more strongly influenced by temperatures occurring during the grain filling period.

Groat starch was correlated positively with warmer temperatures in most months (Table 5). It was also correlated positively with precipitation for the season, and for April and August. Physiological reasons for mechanisms by which these environmental factors would affect groat starch are not clear at this time.

Groat protein was significantly correlated with relatively few environmental factors (Table 5). Of particular interest was a positive correlation with June precipitation and a negative correlation with July precipitation. June precipitation may have stimulated vegetative growth that allowed oat plants to accumulate nitrogen prior to grain filling, and July precipitation may have washed any remaining soil nitrogen out of the root zone, preventing its accumulation in grain. Alternatively, July precipitation may have stimulated starch accumulation, which would have diluted the protein concentration.

Groat lipid concentration was correlated negatively with warm spring temperatures but correlated positively with warmer summer temperatures. This might appear to be inconsistent with earlier studies that suggested that cooler temperatures during grain fill increased oil accumulation (Beringer, 1971; Saastamoinen et al., 1989). It should be noted that very little overall variation in groat oil concentration could be attributed to the environment, and that genotypic effects accounted for most of the variation (Table 4).

Groat [Beta]-glucan concentration was correlated with many of the same environmental factors as groat starch (Table 5). This suggests that these two complex polymers of glucose responded in about the same way to environmental conditions. Several earlier studies had suggested that drought conditions might stimulate [Beta]-glucan concentrations in oat groats (Peterson, 1991; Welch et al., 1991; Brunner and Freed, 1994; Peterson et al., 1995). In the current study, precipitation in July and August was correlated positively with [Beta]-glucan concentration, suggesting the opposite to these previous studies.

Groat ash concentration was correlated positively with warmer temperatures in most months and with precipitation in July and August. Physiological reasons for these correlations are not clear.

Attempts to correlate quality characteristics with each other across environments were partially unsuccessful because of excessive heterogeneity of correlation coefficients among genotypes (Table 6). However, it was apparent that groat percentage was correlated positively with yield and test weight. This suggests that conditions leading to higher yields generally also lead to improved quality. This analysis also indicated that across environments, starch concentration was correlated positively with ash and [Beta]-glucan concentration, protein concentration was correlated positively with groat weight, and lipid concentration was correlated negatively with yield, test weight and groat percentage and weight.
Table 6. Phenotypic correlations of oat grain yield, quality
characteristics and composition with each other calculated across
12 environments. Correlation coefficients are pooled from 12 genotypes.

                                    Test        Groat        Groat
                    Yield          weight     percentage     weight

Test Weight       NH([dagger])
Groat
  Percentage     0.525(**)        0.680
Groat Weight      NH                NH           NH
Groat Lipid     -0.344(**)       -0.451(**)   -0.587(**)   -0.414(**)
Groat Ash       -0.377(**)       -0.632(**)   -0.064(**)   -0.708(**)
Groat Protein     NH                NH         0.407(**)    0.803(**)
Groat Starch    -0.099           -0.182        0.225(*)    -0.381(**)
Groat [Beta]    -0.067           -0.202(*)     0.343(**)      NH
  -glucan

                  Groat       Groat       Groat     Groat
                  lipid        ash       protein   starch

Test Weight
Groat
  Percentage
Groat Weight
Groat Lipid
Groat Ash       -0.158
Groat Protein   -0.338(*)   -0.608(**)
Groat Starch    -0.101       0.513(**)   -0.153
Groat [Beta]       NH        0.615(**)      NH     0.729(**)
  -glucan

(*) Indicates significance at P = 0.05.

(**) Indicates significance at P = 0.01.

([dagger]) NH = correlations coefficients not homogenous across
genotypes.


In summary, it appears that warm spring weather with abundant sunlight were most conducive to improved oat grain yield and quality. Also, conditions in midsummer that discouraged disease development, such as cooler temperature and less than excessive rains, were associated with improved yields and grain quality. Relatively low environmental effects on the economically important compositional traits of protein, lipid and [Beta]-glucan indicate excellent potential for trait stability across environments.

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(1) The mention of firm names or trade products does not imply that they are endorsed or recommended by the U.S. Department of Agriculture over other firms or similar products not mentioned.

Douglas C. Doehlert,(*) Michael S. McMullen, and James J. Hammond

D.C. Doehlert, USDA-ARS Hard Red Spring and Durum Wheat Quality Lab., Harris Hall, North Dakota State Univ., Fargo, ND 58105; M.S. McMullen and James J. Hammond, Dep. of Plant Sciences, Loftsgard Hall, North Dakota State Univ., Fargo, ND 58105. Received 1 June 2000. (*) Corresponding author (Douglas_Doehlert@ndsu.nodak. edu).
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