Euphytica 25 (1976) 21 28

R E P E A T A B I L I T Y OF R E G R E S S I O N S T A B I L I T Y I N D E X E S F O R G R A I N Y I E L D O F O A T S

(A V E N A S A T I V A L.) 1

T U N D E F A T U N L A 2 a n d K . J. F R E Y

Depar tment of Agronomy, Iowa State University, Ames, Iowa 50010, USA

Received 13 March 1975

INDEX W O R D S

A vena sativa, oats, grain yield, regression stability index, repeatability.

SUMMARY

Two lines of descent were established from an F3 bulk lot of oats (Avena sativa L.) initiated by mixing seeds from approximately 250 crosses. For one line of descent, seeds were radiated with thermal neutrons or X- rays from F3 through F~, followed by five generations of bulk propagation. The second was propagated for 10 generations. No artificial selection was practiced in either line of descent. Grain yield data from 20 random strains from each of four generations f rom the radiated (F~, Fs, Fg, and F 11) and five from the nonradiated (F3, F6, F T, Fs, and F~ 2) line of descent and 20 check cultivars tested in 14 environments were used for estimating regression stability indexes of oat strains.

The 14 environments were assigned randomly to two sets of seven, and regression stability indexes were computed for the 180 experimental oat strains for both sets. Intrageneration correlations between regression stability indexes from the two sets of environments ranged from -0.35 to 0.64 (18 d.f.), and only one of nine was significant, indicating poor repeatability for estimates of this statistic computed from different sets of environments.

Correlations between regression stability indexes from two sets of environments, one in which the environments varied by soil nitrogen levels and a second in which they varied by soil phosphorus levels, ranged from 4).01 to 0.28, none of which was significant.

The relative magni tudes and ranking of the regression stability index values for the oat genotypes were nearly identical when environmental productivity indexes were assessed with any number of check cultivars from 2 to 20.

INTRODUCTION

A challenging problem in plant breeding is the development of a technique for pre- dicting productivities of cultivars when grown over a range of environments. FINLAY & WILKINSON (1963) measured the adaptation reaction for yield of a cultivar across a series of environments by computing the regression of its yields upon the mean yields of all cultivars tested in the same environments. EBERHART • RUSSELL (1966) sug- gested that the sum of deviations for a cultivar from its regression line would measure its stability, whereas the magnitude of its linear regression indicated the type of en- vironment to which the cultivar was best adapted.

We tested random lines of oats from several generations of two bulk populations

Journal paper No. J-8080 of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, USA 50010. Project 1752. 2 Present address: University of Ife, Ife-Ile, Nigeria.

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T U N D E F A T U N L A AND K. J. FREY

in 14 environments in Iowa, USA. For purposes of testing the relationship between regression stability indexes estimated for a series of lines in two sets of environments, we divided the 14 environments randomly into two sets of seven. Further, regression stability indexes were computed for the oat lines for two sets of three environments each, in which soil nitrogen or phosphorus levels caused the differential productiv- ities among environments within the sets. Correlations among the linear regressions estimated for two sets of environments were used to judge the repeatability of re- gression stability indexes.

M A T E R I A L S A N D M E T H O D S

Materials andfield evaluations. Our materials were oat (Avena sativa L.) strains from bulk populations initiated by compositing F 2 seeds from approximately 250 crosses. After one increase, the F3 (A547) seed lot was subdivided into radiated (A548) and nonradiated (A557) lines of descent.

F 3 (A548) and F 4 (A610) seeds of the radiated line of descent were treated with thermal neutrons (TN) to total dosages of 1.39 × 1013 and sown in alternate rows with A547, which served as the pollen donor for male-sterile florets on plants from radiated seeds. Seed of F s and F 6 was treated with 20000 and 15000 r of X-rays, respectively, and sown in alternate rows with the progeny of A610, which served as a pollen donor. The radiated line of descent was propagated without selection from F7 through Fla. No treatment or selection was applied to the line of descent begun with A557. In each generation of the radiated (F3-F 11) and nonradiated (F3-F12) lines of descent, approximately 100000 seeds were sown. Seeding rate was one seed per cm of row. To obtain seed for propagation in each generation, the 65 kg of seed harvested in the previous generation of a line of descent were divided into six lots and equal size samples were taken from each to make a 3.0 kg composite for planting and 1.0 kg sample for cold storage.

In 1972, 20 random lines (each the progeny from a spaced plant) from each of four generations from the radiated (FT, Fs, F9, Fa 1) and five from the nonradiated (F 3, F6, FT, Fs, F12) line of descent and 20 check cultivars were evaluated for grain yield in 14 environments. In each environment we sowed one replicate of the 180 experi- mental lines (i.e., 20 strains × nine populations) and two replicates of the check cul- tivars. Replicated check cultivars provided estimates of error mean squares within environments. A plot was a hill sown with 30 seeds, and plots were spaced 30.5 cm apart in perpendicular directions.

Several environmental variables known to affect grain yields of oats were repre- sented in our set of environments (Table 1), and, to accomplish the goal of including all of them, we used environments at several sites in Iowa. Three dates of planting, reflecting a range of temperatures for the growing season, were sown on highly productive soil at Ames in Central Iowa. Soils at Castana, in west-central Iowa, are deep loess that respond to phosphorus fertilization. Soils at Sutherland in north- western and at Kanawha in northcentral Iowa are responsive to nitrogen fertilization.

Grain yield was measured in g per plot. During all years of bulk propagation and evaluation, the oat plants were sprayed with a fungicide at weekly intervals to control foliar diseases.

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Table 1. Descriptions of the environments in which oat strains were tested and grain-yield indexes. 1

Environment Location Planting Treatment Yield number date index

1 Ames April 7 temperature 3.88 2 Ames April 26 temperature 4.12 3 Ames May 6 temperature 2.03 4 Castana April 13 198 kg P2Os/ha 3.14 5 Castana April 13 0 kg P2Os/ha 1.25 6 Castana April 13 66 kg PzOs/ha 1.89 7 Castana April 13 0 kg PzOs/ha 1.00 8 Kanawha April 18 - 2.58 9 Kanawha April 18 132 kg N/ha 3.84

10 Kanawha April 18 0 kg N/ha 2.24 11 Kanawha April 18 132 kg N/ha 3.46 12 Kanawha April 18 66 kg N/ha 2.53 13 Sutherland April 11 0 kg N/ha 3.03 14 Sutherland April 11 88 kg N/ha 3.34

1 Ratio of grain yield in environment x to that in environment 7 in 1960-69.

Statistical procedures. Productivity indexes for the environments were calculated from the means of the 20 check cultivars. Data for grain yield were subjected to a regression analysis to obtain estimates of the regression stability indexes for the oat strains (EBERHART & RUSSELL, 1966; FREEMAN & PERKINS, 1971), and the regression analyses for a set of environments were integrated into a combined analysis of variance.

The data collected in this study were used to investigate three aspects of evaluation of oat genotypes for regression stability indexes: 1. First, we investigated the degree of association between regression stability indexes of oat strains when this statistic was estimated using two sets of random environments. We divided the 14 test environments into two random sets of seven, with environ- ments into two random sets of seven, with environments 1, 4, 6, 8, 10, 12, and 13 in one set and environments 2, 3, 5, 7, 9, 11, and 14 in the second. Regression stability indexes were computed for each experimental oat strain in the two sets of environ- ment?. 2. Second, we investigated the degree of association between regression stability in- dexes of oat lines when this statistic was estimated in two sets of environments in which the factors causing differential productivities in the two sets were known to differ. For one set, where phosphorus fertilization caused variable productivities, we chose environments 4, 6, and 7, all at Castana, and for the second set, where nitrogen fertilization caused variable productivities, we chose environments 9, 10, and 12. 3. Third, we investigated the optimum number of check cultivars for estimating productivity indexes of a set of test environments. All 14 environments were used as one set, and the number of check cultivars used to estimate the environmental indexes of productivity was varied from 2 to 20 (Table 2) in increments of 2 (i.e., 2, 4, 6, etc.). Regression stability indexes computed using the entire 200 strains (180 experimental strains + 20 check cultivars) were used as the standard set of values against which

Euphytica 25 (1976) 23

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Table 2. Check cultivars used to estimate environmental productivity indexes, t

Number of Cultivars used 2 cultivars

2 4 6 8

10 12 14 16 18 20

3,8 2, 7, 12, 14 1 ,9 ,11 ,12 ,14 ,20 1, 2, 3, 6, 10, 14, 17, 19 2 ,4 ,7 , 1,2,3, 2 ,4 ,6 , 2 ,3 ,4 , 2 ,3 ,4 , All 20

8 ,10 ,11 ,12 ,16 ,19 ,20 5, 8, 9, 10, 11, 12, 13, 17, 19 7, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20 5, 6, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20

1 The specific cultivars used were chosen at random. z Cultivars by number and name were: 1. Richland, 2. Cherokee, 3. Tippecanoe, 4. Jaycee, 5. Neal, 6. Multiline E72, 7. Garland, 8. Holden, 9. Multiline M72, 10. Taylor, 11. Otter, 12. C.I. 9170, 12. Portal, 14. Lodi, 15. Nodaway, 16. O'Brien, 17. C.I. 9172, 18. C.I. 9174, 19. C.I. 9178, 20. C.I. 9171.

to compare those computed when the environmental indexes were based on yields of 2 to 20 cultivars.

Degrees of association between two sets o f regression stability indexes for the same oat strains were evaluated through correlation coefficients. All correlations were computed for sets o f oat strains within generations within lines of descent (i.e., each correlation had 18 degrees of freedom). For investigations 1 and 2, correlation coef- ficients were tested for significance of departure from zero. For investigation 3, it was necessary to test the similarity of two correlation coefficients, neither of which had a value of zero.

RESULTS AND DISCUSSION

In the analysis of variance for the two sets of random environments, all sources of mean squares were significant except pooled deviations (Table 3). Especially impor- tant was that the mean squares for genotypes within populations were significant for both sets because it showed that, if correlation values between arrays of regression stability indexes from the two sets of environments were not significant, it would not be due to lack of significant variation among indexes within arrays.

When the regression stability indexes for the strains in populations from one set of random environments were correlated with the comparable values from the other set, two coefficients were negative and only one (i.e., in the F 9 of the radiated popula- tion) was significant (Table 4). These results show that a poor relationship existed between the regression stability indexes estimated in the two sets of environments. This result was unexpected in light of previous reports. FINLAY (1971), PERKINS & JINKS (1968) and BucIo ALANIS et al. (1969) have demonstrated that production stability is a heritable trait in plants, and FREV (1972) found that oat lines isogenic for crown-rust resistance genes differed significantly for magnitudes of this index.

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Table 3. Mean squares from combined analyses of variance of data for grain yield from two sets of random environments.

Source of variation Degrees of Mean squares ~ freedom

set 1 set 2

Environments (linear) 1 9465.8** 11322.7** Populations 8 754.8** 352.7** Environments(linear) x populations 8 53.1"* 31.3"* Genotypes/population s 171 121.1 * * 67.7* * Environments (linear) x genotypes/populations 171 51.9"* 61.2"* Pooled deviations 900 24.6 15.3 Error 1 133 21.5 14.3

1 Error estimated from replicated check cultivars. ** Significant at 1 ~ level.

Table 4. Correlation coefficients between regression stability indexes estimated in two sets of random environments.

Generation Line of descent

nonradiated radiated

F 3 ~3.31 Fo 0.25 Fr ~),35 0.31 F, 0.07 0.12 F 9 0.64** Fl l 0.35 F12 0.32 -

** Significant at ~ level.

These previous reports suggested the existence of genetic determination for stability of production, which supposedly could be exploited in breeding programs.

We anticipated that the make-up of our two sets of environments would provide optimum opportunity for positive association between arrays of regression stability indexes. All the environments represented 1 year, 1972, and each set included en- vironments in which differential yields were caused by temperature during the growth cycle and by nitrogen and phosphorus fertilization. True, the range of environmental indexes in set 1 was only from 1.89 (number 6) to 3.88 (number 1), whereas the range in set 2 was from 1.00 (number 7) to 4.12 (number 2). To maximize the opportunity for a high association between regression stability indexes from two sets of environ- ments, perhaps we should have enforced a nearly equal range by dividing the 14 en- vironments into seven strata of two each and then have randomly assigned the two environments of a stratum to the two sets. This, although it would have ensured equal ranges of environmental indexes in both sets, would have created an experi- mental condition that would not likely be duplicated in a routine plant breeding pro-

Euphytica 25 (1976) 25

TUNDE FATUNLA AND K. J. FREY

Table 5. Correlation coefficients between regression stability indexes estimated in sets of 'nitrogen' and 'phosphorus ' environments.

Generat ion Line of descent

nonradiated radiated

F3 0.03 F6 0.20 - F7 0.02 0.01 F8 0.12 0.08 F9 0.05 F l l - 0.04 F12 0.28 -

gram. In a breeding program, regression stability indexes, to have selection value, would need to be repeatable over years, at least, and experience has shown that ranges of environmental indexes can contract and expand from year to year due to uncon- trollable causes. Therefore, we propose that creation of two sets of environments by random assignment was more closely akin to what actually occurs in breeding pro- grams than would be created by stratified random assignment.

Obviously, our results show the regression stability index is not a very heritable trait for oats.

The correlation coefficients between regression stability indexes computed from 'phosphorus' and 'nitrogen' environments ranged from -0.01 to 0.28, and none was significantly different from zero (Table 5). Actually, we anticipated this result because nitrogen and phosphorus uptake, translocation, and metabolism by an oat genotype probably utilize two groups of genes that are quite independent in inheritance and function. With this assumption, the responses of an array of oat strains to differing nitrogen and phosphorus availability should be unrelated. Perhaps FINLAY (1971) obtained a high repeatability for regression stability indexes for his array of barley strains because the primary factor causing different environmental productivity in- dexes in his experiments was available moisture. His experiments were grown in South Australia where the primary cause of variable crop yields was fluctuating an- nual rainfall. Therefore, repeatability of regression stability indexes, in his study, would involve primarily the expression of genes that functioned in water uptake and utilization by the barley genotypes.

We also correlated the regression stability indexes obtained from the 'nitrogen' and 'phosphorus' sets of environments with those computed from all 14 environ- ments (Table 6). Three of the 18 correlations were significant. This indicates that neither nitrogen or phosphorus was of overwhelming effect in determining the mag- nitudes of the regression stability indexes computed for the 14 environments. Our results in this section of the study support the suggestion of KNIGHT (1970); namely, that the response of genotypes to a single environmental factor might be quite dif- ferent from the response obtained when all environmental factors (edaphic and climatic) are taken into consideration.

In our study, the number of oat strains and/or cultivars used to estimate environ-

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Table 6. Correlation coefficients between regression stability indexes estimated from 'nitrogen' and 'phosphorus ' environments with those estimated from all 14 environments.

Generation Line of descent and set of environments

nonradiated radiated

phosphorus nitrogen phosphorus nitrogen

F 3 0.00 0.01 F 6 0.01 0.09 F7 0.65** 0.14 0.20 0.09 Fs 0.05 0.07 0.28 0.50* F 9 - 0.26 0.31 Vii 0.15 0.40 F12 0.36 0.62** -

* and ** denote correlation coefficients are significantly different from zero at 5 ~o and 1 ~ levels, respec- tively.

mental productivity indexes had little or no effect on relative ranking of the experi- mental strains for regression stability indexes. When regression stability indexes computed from environmental indexes involving 2, 4, 6 . . . . 20 cultivars were cor- related with those from environmental indexes involving all 200 entries, the r values all were greater than 0.92 (Table 7). When correlations were compared by use of two and 20 check cultivars, three of nine pairs were significantly different (F 6 and F12

in the nonradiated and F S in the radiated line of descent), but in one pair (Flz in nonradiated line of descent), the r value for the two-cultivar index was higher. Thus, our results indicate no advantage for a small or large number of cultivars for assessing environmental indexes. Probably of more importance is the suitability of the specific cultivars used. For example, the use of two cultivars, Tippecanoe and Holden, gave

Table 7. Correlations between regression stability indexes computed with environment productivity indexes assayed using different numbers of check cultivars and those computed when all entries were used.

Generation Number of check cultivars

2 4 6 8 10 12 14 16 18 20

Nonradiated Fs -- 0.94 0.98 0.99 0.97 0.94 0.98 0.97 0.97 0.97 0.97 F6 0.95 0.92 0.98 0.98 0.96 0.98 0.98 0.99 0.98 0.99 F7 0.97 0.92 0.98 0.96 0.93 0.97 0.98 0.97 0.97 0.97 Fs 0.97 0.93 0.99 0.99 0.97 0.99 0.99 0.98 0.99 0.99 F,2 0.99 0.95 0.98 0.97 0.96 0.98 0.99 0.98 0.98 0.98

Radiated F~ 0.98 0.95 0.99 0.99 0.97 0.99 0.99 0.99 0 .98 0.99 Fs 0.97 0.94 0.99 0.99 0.97 0.99 0.99 0.99 0.99 0.99 F 9 0.98 0.95 0.99 0.99 0.97 0.99 0.99 0.99 0.99 0.99 F11 0.98 0.95 0.99 0.99 0.97 0.99 0.99 0.99 0.99 0.99

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TUNDE FATUNLA AND K.J. FREY

higher correlations than the use of four, Cherokee, Garland, C.I. 9170, and Lodi. FINLAY (1963, 1971) and EBERHART & RUSSELL (1969) have used the entire set of

strains and cultivars in an experiment to establish environmental productivity in- dexes, whereas FREEMAN & PERKINS (1971) proposed environmental indexes should be assessed by a set of check cultivars that are independent from the experimental strains being assayed. In our experiment, it made no difference in the relative ranking of experimental strains whether check cultivars, in any number from two to 20, or all 200 entries were used to establish the environmental productivity indexes. Perhaps the best reason for using a standard set of cultivars for this purpose is that it would permit direct comparisons between regression stability index values from experi- ments conducted at different sites in different years.

REFERENCES

BucIo ALANIS, L., JEN M. PERKINS & J. L. JINKS, 1969. Environmental and genotype - environmental components of variability. V. Segregating generations. Heredity 24: 115-127.

EBERHART, S. A. t~ W. A. RUSSELL, 1966. Stability parameters for comparing varieties. Crop Sci. 6: 3t%40. EBERHART, S. A. & W. A. RUSSELL, 1969. Yield and stability for a 10-line diallel of single-cross and double-

cross maize hybrids. Crop Sci. 9 : 357-361. FINLAY, K. W., 1963. Adaptat ion - its measurement and significance in barley breeding. Int. Barley

Genet. Symp. Proc. 1 : 351-359. F1NLAY, K. W., 1971. Breeding for yield in barley. Int. Barley Genet. Symp. Proc. 2: 338-345. FINLAY, K. W. & G. N. WILKINSON, 1963. The analysis of adaptat ion in a plant breeding programme.

Aust. J. agric. Res. 14: 742-754. FREEMAN, G. H. & J. M. PERKINS, 1971. Environmental and genotype - environmental components of

variability. VIII. Relations between genotypes grown in different environments and measures of these environments. Heredity 27 : 15-23.

FREY, K. J., 1972. Stability indexes for isolines of oats (Avena sativa L.). Crop Sci. 12 : 809 812. KNIGHT, R., 1970. The measurement and interpretation of genotype environment interactions. Euphytica

19 : 225-235. PERKINS, J. M. & J. L. LINKS, 1968. Environmental and genotype environmental components of variabi-

lity. III. Nonlinear interactions for multiple inbred lines. Heredity 23 : 525 535.

28 Euphy~ica 25 (1976)