- Email: [email protected]
Explanation of the relationships between seed yield and some morphological traits in smooth bromegrass (Bromus inermis Leyss.) by path analysis
Europ. J. Agronomy 21 (2004) 1–6
Explanation of the relationships between seed yield and some morphological traits in smooth bromegrass (Bromus inermis Leyss.) by path analysis Hayati Seker a,∗ , Yunus Serin b a
b
Eastern Anatolian Agricultural Research Institute, 25090, Dadaskent, Erzurum, Turkey Field Crops Department, Agricultural Faculty, Ataturk University, 25040, Erzurum, Turkey Received 8 February 2002; received in revised form 4 April 2003; accepted 18 May 2003
Abstract Path analysis was performed on plant characters in a sward of smooth bromegrass to determine the seed yield, the direct and indirect effects of the following seed yield components: stem yield/m2 , total stem number/m2 , fertile stem number/m2 , sterile stem number/m2 , percentage of fertile stem, seeds/m2 , seeds/panicle, seed weight/panicle, 1000-seed weight, and plant height under field conditions. Seed yield was significantly correlated with all components except 1000-seed weight, total stem number/m2 , and seed weight/panicle. Stem yield/m2 , percentage of fertile stem, sterile stem number/m2 and seeds/m2 had substantial direct effects, in that order, on enhancement of seed yield. The significant positive correlation coefficients of fertile stem number/m2 and plant height with seed yield resulted from positive indirect effects of stem yield/m2 and percentage of fertile stem. Conversely, the significant negative correlation between sterile stem number/m2 and seed yield resulted from negative indirect effects of the same two components. Stepwise multiple regression analysis showed that 54.9% of total variation in seed yield could be explained by the variation in stem yield/m2 and by fertile stem number/m2 (51.4 and 3.5%, respectively). Results suggest that stem yield/m2 and fertile stem number/m2 are primary selection criteria for improving seed yield in the sward of smooth bromegrass. © 2003 Elsevier B.V. All rights reserved. Keywords: Smooth bromegrass; Seed yield and components; Correlation coefficient; Path analysis
1. Introduction Plant breeding may alleviate the deficiency in hay production by developing higher yielding varieties under the severe ecological conditions of Eastern Anatolian Region in North-eastern Turkey. For that purpose, superior varieties must be developed by selection among populations that have very rich vari∗ Corresponding author. Tel.: +90-442-327-1440x126; fax: +90-442-327-1364. E-mail address: [email protected] (H. Seker).
ations in important agronomic traits. The success of selection depends on the choice of selection criteria for improving seed yield. Because the components do not only directly affect the yield, they also affect the yield indirectly by affecting other yield components in negative or positive manners. As a trait has helpful effect on a trait for yield, it can affect some other or all traits negatively (Walton, 1980). For that reason, it is clear that a correlation coefficient which measures the simple linear relationship between two traits does not predict the success of selection. However, path analysis, regression on standardised variables, deter-
1161-0301/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/S1161-0301(03)00055-8
2
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
mine the relative importance of direct and indirect effects on seed yield (Bhatt, 1973). Path analysis has been increasingly utilised to define the best criteria for selection in biological and agronomic studies (Mishra and Drolsom, 1973; Williams et al., 1990). The relationships among some morphological traits have been determined in some forage grasses (Dewey and Lu, 1959; Knowles et al., 1970; Mishra and Drolsom, 1973). Prior research has determined that the number of panicles and weight of seed are important yield components (Knowles et al., 1970; Trupp and Carlson, 1971). However, Açıkgöz and Tekeli (1980) showed that seed number and seed weight/panicle had significant direct effects on the seed yield and those two traits could be used for selection of high seed yielding varieties as primary selection criteria in the investigation with 13 smooth bromegrass varieties. Serin et al. (1999) determined the number of fertile stems/m2 and plant height which had significant positive effects on seed yield in smooth bromegrass. Also, those researchers reported that there was a highly significant positive correlation between the number of fertile stems/m2 and plant height. In research with wild orchardgrass, Tosun et al. (1997) found significant positive correlation coefficients between seed yield and plant height (r = 0.727*), length of panicle (r = 0.856*), the number of florets/panicle (r = 0.820*), and the number of spikelet number/panicle (r = 0.921**). The researchers reported that the direct effect of spikelet number/panicle on seed yield was greater than those of other traits. They also concluded that increasing the length of panicle was a useful selection objective. In this study, the relationships between seed yield and plant components, which included not only generative but also vegetative traits, were investigated to clarify and determine the selection criteria for increasing seed yield of smooth bromegrass clones.
2. Materials and methods This study was carried out for 2 years (1998–1999) at research station 6, Ataturk University Agricultural Faculty in Erzurum Province which is located in the Eastern Anatolian Region of Turkey (39◦ 55 N Lat., 41◦ 16 E Long., and 1950 m elevation). The experiment field had a soil of Pasinler silty clay loam. This
location is an arid area characterised by dry summer and cool temperate with 8.9 ◦ C, and 187 mm rainfall during April to August which presented 46.5% of annual rainfall as an average of 71 years between 1929 and 1999. The population (named as Tohum Islahi) of smooth bromegrass (Bromus inermis Leyss.) originated from USA was established in 60 plots (6 m2 ) in a randomised complete block design with four replication. Seed was sown at the rate of 10 kg seed/ha with 30 cm between rows in 15 environments of the combinations of three irrigation levels (when 25, 50 and 75% of the available soil water content were consumed) and five nitrogen rates (0, 30, 60, 90 and 120 kg N/ha in early spring). Each plot was constantly fertilised with 21.8 kg P/ha and 40.0 kg N/ha annually as triple super phosphate (44% P) and ammonium sulphate (21% N) in each fall. Net harvest area used for some observations in each plot was 0.3 m2 after subtraction of 3.3 m2 for side effects. Observations were recorded on the plot basis of 0.3 m2 at the end of June prior to the first harvest. Second harvest was only aftermath. The following measurements were made: (1) seed yield (total seed weight/m2 ), (2) the number of fertile stems/m2 , (3) the number of the sterile stems/m2 , (4) the number of total stems/m2 (the number of fertile stems/m2 +the number of sterile stems/m2 ), (5) the percentage of fertile stems (the number of fertile stems/the number of total stem number for each plot), (6) seed number/m2 , (7) seed number/panicle, (8) seed weight/panicle, (9) 1000-seed weight, (10) plant height (average of 20 randomly selected stems), and (11) stem yield (as total dry matter per plot after threshing the seeds by hand). Simple correlation and stepwise multiple regression analysis’ were carried out using sas statistical program. Also, the relative importance of direct and indirect effects on seed yield was determined by path analysis for the 2 years of data (SAS Institute, 1996). In path analysis, seed yield was the dependent variable and the ten plant or sward characteristics (observations 2–11) were considered as independent variables.
3. Results Positive relationships existed between seed yield and all its components with the exceptions of the sterile stem number/m2 and total stem number/m2
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
3
Table 1 Simple correlation coefficients of seed yield components in smooth bromegrass Traits
STY
TS
PFS
FS
SS
SDS/m2
SDS/PN
SDW/PN
TSW
PH
SEY STY TS PFS FS SS SDS/m2 SDS/PN SDW/PN TSW
0.714∗∗
−0.026 0.121
0.644∗∗ 0.947∗∗ 0.072
0.581∗∗ 0.920∗∗ 0.252∗∗ 0.955∗∗
−0.616∗∗ −0.878∗∗ 0.155 −0.951∗∗ −0.838∗∗
0.545∗∗ 0.842∗∗ 0.230∗∗ 0.857∗∗ 0.898∗∗ −0.759∗∗
0.413∗∗ 0.605∗∗ 0.098 0.600∗∗ 0.596∗∗ −0.559∗∗ 0.820∗∗
0.019 0.038 0.020 0.033 0.022 −0.037 0.065 0.125
0.062 0.035 0.037 −0.015 −0.026 0.018 −0.031 −0.118 0.082
0.653∗∗ 0.959∗∗ 0.120 0.948∗∗ 0.921∗∗ −0.878∗∗ 0.865∗∗ 0.664∗∗ 0.103 0.006
SEY, Seed yield/m2 ; STY, Stem yield/m2 ; TS, total stem number/m2 ; PFS, percentage of fertile stems; FS, fertile stem number/m2 ; SS, sterile stem number/m2 ; SDS/m2 , seed number/m2 ; SDS/PN, seed number/panicle; SDW/PN, seed weight/panicle; TSW, 1000-seed weight; PH, plant height. ∗∗ P < 0.01.
(r = −0.616** and −0.026, respectively) (Table 1). Very low correlation coefficients were found for seed weight/panicle, total stem number/m2 and 1000-seed weight while the others were very high and significant. As expected, sterile stem number/m2 was negatively and significantly related with seed yield and other components (Table 1). In general, the components had significant positive correlations with each other. Only 1000-seed weight and seed weight/panicle gave no significant correlation with any other components (Table 1). Path analysis showed that only stem yield/m2 , percentage of fertile stems, sterile stem number/m2 and seeds/m2 had strong direct effects, in that order, on the seed yield while other components had strongly negative or negligible direct effects. The main effects of all components were significantly positive and resulted from the positive indirect effects via stem yield/m2 and percentage of fertile stems. However, the correlation between sterile stem number/m2 and seed yield was significantly negative due to its strong negative indirect effect via the same two components (Table 2). The main effects of most components were significantly positive and contributed to seed yield largely through indirect effects of stem yield/m2 and percentage of fertile stem. In total, 54.9% of the variation in seed yield could be explained by the variation of the two independent variables (Table 3). The unexplained variation, 45.1% of the total, may be due to variations in the other com-
ponents under consideration, abortion seed formation, fragile stalk of spikelets caused very quick shedding after maturing.
4. Discussion In a canopy of Bromus inermis (Leyss.) which is composed of plants having aggressive growth habit with strong rhizomes, the competition among plants was very effective under field condition. Therefore, the associations among components of plants are expected to be different from those obtained from single or spaced plants of smooth bromegrass. When selection is performed on the sward of smooth bromegrass, it is more reasonable that the criterion should depend on the results obtained from the sward. In most former studies, researchers usually concentrated on panicle measurements and components of individual plants grown in pots or spaced in plots. But in this study, we studied on the 3-year sward of smooth bromegrass and simultaneously investigated the vegetative components with generative components on plot basis. Very strong correlations between seed yield and almost its all components were found (Table 1). In particular, high positive correlation coefficients were found for stem yield/m2 , plant height, percentage of fertile stem, fertile stem number/m2 , seeds/m2 and seeds/panicle, in that order. In former studies with
4
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
Table 2 Path coefficients for seed yield components of smooth bromegrass Stem yield vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2
r = 0.714 1.227 0.801 −0.818 0.084 −0.003 −0.293 −0.284
FS/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.581 −0.889 0.806 0.090 −0.002 −0.281 −0.272 1.129
Plant height vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via SS/m2 Indirect effect via stem yield
r = 0.653 −0.306 0.801 −0.818 0.087 −0.003 −0.285 1.177
Seeds/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.545 0.100 0.724 −0.798 −0.004 −0.264 −0.246 1.033
PFS vs seed yield Direct effect Indirect effect via Indirect effect via Indirect effect via Indirect effect via Indirect effect via Indirect effect via
r = 0.644 0.845 −0.849 0.086 −0.003 −0.290 −0.308 1.163
Seeds/panicle vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.413 −0.004 0.507 −0.530 0.082 −0.203 −0.181 0.742
FS/m2 seeds/m2 seeds/panicle plant height SS/m2 stem yield
SS/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via stem yield/m2
r = −0.616 0.324 −0.803 0.745 −0.076 0.002 0.269 −1.077
smooth bromegrass, stem yield/m2 and plant height (Serin et al., 1999), seeds/panicle and 1000-seed weight (Açıkgöz and Tekeli, 1980) exhibited strong positive correlations with seed yield. Our results confirm the findings of Açıkgöz and Tekeli (1980) and
Table 3 Summary of stepwise multiple regression analysis of seed yield and seed yield components in smooth bromegrass Regression equations
Coefficient of determination
SEY = 11.818 + 0.021 STY SEY = 13.342 + 0.034 STY−0.021 FS/m2
0.514 0.549
Serin et al. (1999) for seeds/panicle, stem yield/m2 and plant height, but not for 1000-seed weight. Also, Sethi and Singh (1972), Singh and Sethi (1974) and Kamboj and Mani (1983) found a non-significant correlation between seed yield and 1000-seed weight in triticale, and their results are consistent with our results (Table 1). Fertile stem number/m2 and seeds/panicle (Table 1) were positively correlated with seed yield (r = 0.581 and 0.413, P < 0.01, respectively). This is contrary to the findings of Açıkgöz and Tekeli (1980) and Serin et al. (1999) for fertile stem number/m2 and seeds/m2 , respectively. The relationship between seed yield and seed weight/panicle was not significant (r = 0.019)
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
which is consistent with Serin et al. (1999). Additionally, the relationships among other components were significant (except 1000-seed weight, seed weight/panicle and total stem number/m2 , Table 1). This is contrary to the findings of Gökku¸s et al. (1997) in smooth bromegrass. Path coefficients divided the correlation coefficient into a series of direct and indirect effects of yield components on the seed yield of smooth bromegrass (Table 2). Most traits were significantly correlated with seed yield. However, path analysis showed that only stem yield/m2 , percentage of fertile stem, sterile stem number/m2 and seeds/m2 had strong direct effects on the enhancement of seed yield of smooth bromegrass, in that order, while it was strongly negative for fertile stem number/m2 and plant height. The indirect effects via stem yield/m2 and percentage of fertile stems substantially increased the total correlations between the components and seed yield (except for sterile stem number/m2 ). But, those via fertile stem number/m2 considerably reduced the total correlations. As the results of those conflict relationships, the significant positive correlation coefficients of fertile stem number/m2 and plant height with seed yield resulted from positive indirect effects of stem yield/m2 and percentage of fertile stem in spite of their strong negative direct effects on seed yield. Conversely, the significant negative total correlation between seed yield and sterile stem number/m2 resulted from the negative indirect effects of the same two components although sterile stem number/m2 had strong positive direct effect on seed yield (Table 2). On the other hand, in the present study, the indirect effects of other components via fertile stem number/m2 were strongly negative, suggesting seed yield component compensation (Adams, 1967). It is clear that when the percentage of fertile stem number in total stems which were composed of vegetative and generative stems increases, seed yield could be increased (r = 0.644, P < 0.01). Plant size (as stem yield), seed and total biomass yields would increase when fertile stem number/m2 increased (r = 0.714, 0.581, P < 0.01). However, if sterile stem number/m2 increased, those quantities would expected to significantly decrease (r = −0.616, P < 0.01) (Table 1). However, when fertile stem number/m2 excessively increased after certain point, additional increase in seed yield could not be obtained. Because it was ob-
5
served that when fertile stem number/m2 excessively increased in quantity, individual fertile stem reduced in size which results in infrequent and small leaves, puny, short and small panicles, reductions in spikelet number/panicle, and reduced seeds in size and quantity. Plants that produced many stems generally produced shorter panicles on the fertile stems which have fewer florets per stem, small seeds, and were less fertile than plants producing few stems. It was reported that mature plant weight was positively correlated with seed yield in crested wheatgrass (Agropyron cristatum L.) because these species have the advantage by having more spikes per plant (Dewey and Lu, 1959). In smooth bromegrass, the stem yield was especially composed by size and number of fertile stems per se. Also, 51.4 and 3.5% of the total variation in seed yield could be expected by variation in the stem yield/m2 and fertile stem number/m2 , respectively. This is particularly important since fertile stem number/m2 is positively correlated with forage yield as measured stem yield (r = 0.920**, P < 0.01) and plant height (r = 0.921, P < 0.01) (Table 1). It could be possible to develop high forage yielding populations that also produce substantial amounts of high quality seed of smooth bromegrass depending on stem yield/m2 and percentage of fertile stems in total stem number. Consequently, the indirect effects via stem yield/m2 , percentage of fertile stems and fertile stem number/m2 were major determinants of the main effects of all components for the seed yield of the smooth bromegrass grown under field condition. Highly significant and positive correlation coefficients as well as high direct effects of stem yield/m2 and percentage of fertile stems on seed yield indicated that both two components in co-operation are simultaneously the most reliable components for selecting high-yielding smooth bromegrass types. But other components having highly significant positive correlations with seed yield were initially not the most reliable components for selection.
5. Conclusion The data obtained from this study could be useful for smooth bromegrass breeders and seed produc-
6
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
ers concerned with increasing seed yield. The main positive traits determining the seed yield in smooth bromegrass growing in a dense sward are stem yield, percentage of fertile stems, fertile stem number/m2 , seeds/m2 and seeds/panicle having a direct effect and plant height and sterile stem numbers/m2 having indirect effect.
References Açıkgöz, E., Tekeli, A.S., 1980. Seed yield and its components in smooth bromegrass (Bromus inermis Leyss.) cultivars. Euphytica 29 (1), 199–203. Adams, W.M., 1967. Basis of yield component compensation in crop plants with special reference to the field bean, Phaseolus vulgaris. Crop Sci. 7, 505–510. Bhatt, G.M., 1973. Significance of path coefficient analysis determining the nature of character association. Euphytica 22, 89–97. Dewey, D.R., Lu, K.H., 1959. A correlation and path coefficient analysis of components of crested wheatgrass seed production. Agron. J. 51, 515–518. Gökku¸s, A., Serin, Y., Koç, K., Tan, M., 1997. Farkli sıra aralı˘gına ekilen kılçıksız brom (Bromus inermis Leyss.)’a uygulanan de˘gi¸sik biçim yüksekli˘gi ve aniz yakmanin tohum verimi ve bazi özellikler üzerine etkisi. Türkiye II. Tarla Bitkileri Kongresi, 22–25 Eylül 1997, Samsun, Ondokuz Mayis Üni., Zir. Fak. Tarla Bitk. Bl., Tarla Bitk. Bilimi Derne˘gi, s. pp. 455–460.
Kamboj, R.K., Mani, S.C., 1983. Correlation and path analysis in hexaploid triticale. Indian J. Agric. Sci. 53 (6), 394–397. Knowles, R.P., Cooke, D.A., Buglas, E., 1970. Breeding for seed yield and seed quality in smooth bromegrass, Bromus inermis LEYSS. Crop Sci. 10, 539–542. Mishra, S.N., Drolsom, P.N., 1973. Association among certain morphological traits of diallel cross progenies in Bromus inermis LEYSS. J. Agric. Sci. Camb. 81, 69–76. SAS Institute, 1996. sas/stat Software: Changes and enhancements through release 6.11. SAS Inst. Inc., Carry, NC, USA. Serin, Y., Tan, M., Koç, A., Gökku¸s, A., 1999. Farkli mevsim ve dozlarda verilen azotun kilçiksiz brom (Bromus inermis Leyss.)‘un tohum verimi ile buna iliskin karakterlere etkisi ve karakterler arasindaki iliskiler. Tr. J. Agric. Forestry 23 (2), 257–264. Sethi, G.S., Singh, H.B., 1972. Interrelationship of quantitative traits with grain yield in triticale. Indian J. Agric. Sci. 42, 281–285. Singh, H.B., Sethi, G.S., 1974. Path and regression analysis in triticale. Plant Sci. 6, 10–16. Tosun, M., Akgün, I., Sagsöz, S., 1997. Yabani domuz ayrigi (Dactylis glomerata L.) bitkilerinde ot ve tohum verimi ile bazi morfolojik özellikler arasindaki iliskiler. Atatürk Üni. Zir. Fak. Derg. 28 (4), 605–619. Trupp, C.R., Carlson, I.T., 1971. Improvement of seedling vigor of smooth bromegrass (Bromus inermis LEYSS) by recurrent selection for high seed weight. Crop Sci. 11, 225–228. Walton, P.D., 1980. The production characteristics of Bromus inermis Leyss. and their inheritance. Adv. Agron., 341–369. Williams, W.A., Jones, M.B., Demment, M.W., 1990. A concise table for path analysis statistics. Agron. J. 82, 1022–1024.
Explanation of the relationships between seed yield and some morphological traits in smooth bromegrass (Bromus inermis Leyss.) by path analysis Hayati Seker a,∗ , Yunus Serin b a
b
Eastern Anatolian Agricultural Research Institute, 25090, Dadaskent, Erzurum, Turkey Field Crops Department, Agricultural Faculty, Ataturk University, 25040, Erzurum, Turkey Received 8 February 2002; received in revised form 4 April 2003; accepted 18 May 2003
Abstract Path analysis was performed on plant characters in a sward of smooth bromegrass to determine the seed yield, the direct and indirect effects of the following seed yield components: stem yield/m2 , total stem number/m2 , fertile stem number/m2 , sterile stem number/m2 , percentage of fertile stem, seeds/m2 , seeds/panicle, seed weight/panicle, 1000-seed weight, and plant height under field conditions. Seed yield was significantly correlated with all components except 1000-seed weight, total stem number/m2 , and seed weight/panicle. Stem yield/m2 , percentage of fertile stem, sterile stem number/m2 and seeds/m2 had substantial direct effects, in that order, on enhancement of seed yield. The significant positive correlation coefficients of fertile stem number/m2 and plant height with seed yield resulted from positive indirect effects of stem yield/m2 and percentage of fertile stem. Conversely, the significant negative correlation between sterile stem number/m2 and seed yield resulted from negative indirect effects of the same two components. Stepwise multiple regression analysis showed that 54.9% of total variation in seed yield could be explained by the variation in stem yield/m2 and by fertile stem number/m2 (51.4 and 3.5%, respectively). Results suggest that stem yield/m2 and fertile stem number/m2 are primary selection criteria for improving seed yield in the sward of smooth bromegrass. © 2003 Elsevier B.V. All rights reserved. Keywords: Smooth bromegrass; Seed yield and components; Correlation coefficient; Path analysis
1. Introduction Plant breeding may alleviate the deficiency in hay production by developing higher yielding varieties under the severe ecological conditions of Eastern Anatolian Region in North-eastern Turkey. For that purpose, superior varieties must be developed by selection among populations that have very rich vari∗ Corresponding author. Tel.: +90-442-327-1440x126; fax: +90-442-327-1364. E-mail address: [email protected] (H. Seker).
ations in important agronomic traits. The success of selection depends on the choice of selection criteria for improving seed yield. Because the components do not only directly affect the yield, they also affect the yield indirectly by affecting other yield components in negative or positive manners. As a trait has helpful effect on a trait for yield, it can affect some other or all traits negatively (Walton, 1980). For that reason, it is clear that a correlation coefficient which measures the simple linear relationship between two traits does not predict the success of selection. However, path analysis, regression on standardised variables, deter-
1161-0301/$ – see front matter © 2003 Elsevier B.V. All rights reserved. doi:10.1016/S1161-0301(03)00055-8
2
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
mine the relative importance of direct and indirect effects on seed yield (Bhatt, 1973). Path analysis has been increasingly utilised to define the best criteria for selection in biological and agronomic studies (Mishra and Drolsom, 1973; Williams et al., 1990). The relationships among some morphological traits have been determined in some forage grasses (Dewey and Lu, 1959; Knowles et al., 1970; Mishra and Drolsom, 1973). Prior research has determined that the number of panicles and weight of seed are important yield components (Knowles et al., 1970; Trupp and Carlson, 1971). However, Açıkgöz and Tekeli (1980) showed that seed number and seed weight/panicle had significant direct effects on the seed yield and those two traits could be used for selection of high seed yielding varieties as primary selection criteria in the investigation with 13 smooth bromegrass varieties. Serin et al. (1999) determined the number of fertile stems/m2 and plant height which had significant positive effects on seed yield in smooth bromegrass. Also, those researchers reported that there was a highly significant positive correlation between the number of fertile stems/m2 and plant height. In research with wild orchardgrass, Tosun et al. (1997) found significant positive correlation coefficients between seed yield and plant height (r = 0.727*), length of panicle (r = 0.856*), the number of florets/panicle (r = 0.820*), and the number of spikelet number/panicle (r = 0.921**). The researchers reported that the direct effect of spikelet number/panicle on seed yield was greater than those of other traits. They also concluded that increasing the length of panicle was a useful selection objective. In this study, the relationships between seed yield and plant components, which included not only generative but also vegetative traits, were investigated to clarify and determine the selection criteria for increasing seed yield of smooth bromegrass clones.
2. Materials and methods This study was carried out for 2 years (1998–1999) at research station 6, Ataturk University Agricultural Faculty in Erzurum Province which is located in the Eastern Anatolian Region of Turkey (39◦ 55 N Lat., 41◦ 16 E Long., and 1950 m elevation). The experiment field had a soil of Pasinler silty clay loam. This
location is an arid area characterised by dry summer and cool temperate with 8.9 ◦ C, and 187 mm rainfall during April to August which presented 46.5% of annual rainfall as an average of 71 years between 1929 and 1999. The population (named as Tohum Islahi) of smooth bromegrass (Bromus inermis Leyss.) originated from USA was established in 60 plots (6 m2 ) in a randomised complete block design with four replication. Seed was sown at the rate of 10 kg seed/ha with 30 cm between rows in 15 environments of the combinations of three irrigation levels (when 25, 50 and 75% of the available soil water content were consumed) and five nitrogen rates (0, 30, 60, 90 and 120 kg N/ha in early spring). Each plot was constantly fertilised with 21.8 kg P/ha and 40.0 kg N/ha annually as triple super phosphate (44% P) and ammonium sulphate (21% N) in each fall. Net harvest area used for some observations in each plot was 0.3 m2 after subtraction of 3.3 m2 for side effects. Observations were recorded on the plot basis of 0.3 m2 at the end of June prior to the first harvest. Second harvest was only aftermath. The following measurements were made: (1) seed yield (total seed weight/m2 ), (2) the number of fertile stems/m2 , (3) the number of the sterile stems/m2 , (4) the number of total stems/m2 (the number of fertile stems/m2 +the number of sterile stems/m2 ), (5) the percentage of fertile stems (the number of fertile stems/the number of total stem number for each plot), (6) seed number/m2 , (7) seed number/panicle, (8) seed weight/panicle, (9) 1000-seed weight, (10) plant height (average of 20 randomly selected stems), and (11) stem yield (as total dry matter per plot after threshing the seeds by hand). Simple correlation and stepwise multiple regression analysis’ were carried out using sas statistical program. Also, the relative importance of direct and indirect effects on seed yield was determined by path analysis for the 2 years of data (SAS Institute, 1996). In path analysis, seed yield was the dependent variable and the ten plant or sward characteristics (observations 2–11) were considered as independent variables.
3. Results Positive relationships existed between seed yield and all its components with the exceptions of the sterile stem number/m2 and total stem number/m2
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
3
Table 1 Simple correlation coefficients of seed yield components in smooth bromegrass Traits
STY
TS
PFS
FS
SS
SDS/m2
SDS/PN
SDW/PN
TSW
PH
SEY STY TS PFS FS SS SDS/m2 SDS/PN SDW/PN TSW
0.714∗∗
−0.026 0.121
0.644∗∗ 0.947∗∗ 0.072
0.581∗∗ 0.920∗∗ 0.252∗∗ 0.955∗∗
−0.616∗∗ −0.878∗∗ 0.155 −0.951∗∗ −0.838∗∗
0.545∗∗ 0.842∗∗ 0.230∗∗ 0.857∗∗ 0.898∗∗ −0.759∗∗
0.413∗∗ 0.605∗∗ 0.098 0.600∗∗ 0.596∗∗ −0.559∗∗ 0.820∗∗
0.019 0.038 0.020 0.033 0.022 −0.037 0.065 0.125
0.062 0.035 0.037 −0.015 −0.026 0.018 −0.031 −0.118 0.082
0.653∗∗ 0.959∗∗ 0.120 0.948∗∗ 0.921∗∗ −0.878∗∗ 0.865∗∗ 0.664∗∗ 0.103 0.006
SEY, Seed yield/m2 ; STY, Stem yield/m2 ; TS, total stem number/m2 ; PFS, percentage of fertile stems; FS, fertile stem number/m2 ; SS, sterile stem number/m2 ; SDS/m2 , seed number/m2 ; SDS/PN, seed number/panicle; SDW/PN, seed weight/panicle; TSW, 1000-seed weight; PH, plant height. ∗∗ P < 0.01.
(r = −0.616** and −0.026, respectively) (Table 1). Very low correlation coefficients were found for seed weight/panicle, total stem number/m2 and 1000-seed weight while the others were very high and significant. As expected, sterile stem number/m2 was negatively and significantly related with seed yield and other components (Table 1). In general, the components had significant positive correlations with each other. Only 1000-seed weight and seed weight/panicle gave no significant correlation with any other components (Table 1). Path analysis showed that only stem yield/m2 , percentage of fertile stems, sterile stem number/m2 and seeds/m2 had strong direct effects, in that order, on the seed yield while other components had strongly negative or negligible direct effects. The main effects of all components were significantly positive and resulted from the positive indirect effects via stem yield/m2 and percentage of fertile stems. However, the correlation between sterile stem number/m2 and seed yield was significantly negative due to its strong negative indirect effect via the same two components (Table 2). The main effects of most components were significantly positive and contributed to seed yield largely through indirect effects of stem yield/m2 and percentage of fertile stem. In total, 54.9% of the variation in seed yield could be explained by the variation of the two independent variables (Table 3). The unexplained variation, 45.1% of the total, may be due to variations in the other com-
ponents under consideration, abortion seed formation, fragile stalk of spikelets caused very quick shedding after maturing.
4. Discussion In a canopy of Bromus inermis (Leyss.) which is composed of plants having aggressive growth habit with strong rhizomes, the competition among plants was very effective under field condition. Therefore, the associations among components of plants are expected to be different from those obtained from single or spaced plants of smooth bromegrass. When selection is performed on the sward of smooth bromegrass, it is more reasonable that the criterion should depend on the results obtained from the sward. In most former studies, researchers usually concentrated on panicle measurements and components of individual plants grown in pots or spaced in plots. But in this study, we studied on the 3-year sward of smooth bromegrass and simultaneously investigated the vegetative components with generative components on plot basis. Very strong correlations between seed yield and almost its all components were found (Table 1). In particular, high positive correlation coefficients were found for stem yield/m2 , plant height, percentage of fertile stem, fertile stem number/m2 , seeds/m2 and seeds/panicle, in that order. In former studies with
4
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
Table 2 Path coefficients for seed yield components of smooth bromegrass Stem yield vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2
r = 0.714 1.227 0.801 −0.818 0.084 −0.003 −0.293 −0.284
FS/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.581 −0.889 0.806 0.090 −0.002 −0.281 −0.272 1.129
Plant height vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via SS/m2 Indirect effect via stem yield
r = 0.653 −0.306 0.801 −0.818 0.087 −0.003 −0.285 1.177
Seeds/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.545 0.100 0.724 −0.798 −0.004 −0.264 −0.246 1.033
PFS vs seed yield Direct effect Indirect effect via Indirect effect via Indirect effect via Indirect effect via Indirect effect via Indirect effect via
r = 0.644 0.845 −0.849 0.086 −0.003 −0.290 −0.308 1.163
Seeds/panicle vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via plant height Indirect effect via SS/m2 Indirect effect via stem yield/m2
r = 0.413 −0.004 0.507 −0.530 0.082 −0.203 −0.181 0.742
FS/m2 seeds/m2 seeds/panicle plant height SS/m2 stem yield
SS/m2 vs seed yield Direct effect Indirect effect via PFS Indirect effect via FS/m2 Indirect effect via seeds/m2 Indirect effect via seeds/panicle Indirect effect via plant height Indirect effect via stem yield/m2
r = −0.616 0.324 −0.803 0.745 −0.076 0.002 0.269 −1.077
smooth bromegrass, stem yield/m2 and plant height (Serin et al., 1999), seeds/panicle and 1000-seed weight (Açıkgöz and Tekeli, 1980) exhibited strong positive correlations with seed yield. Our results confirm the findings of Açıkgöz and Tekeli (1980) and
Table 3 Summary of stepwise multiple regression analysis of seed yield and seed yield components in smooth bromegrass Regression equations
Coefficient of determination
SEY = 11.818 + 0.021 STY SEY = 13.342 + 0.034 STY−0.021 FS/m2
0.514 0.549
Serin et al. (1999) for seeds/panicle, stem yield/m2 and plant height, but not for 1000-seed weight. Also, Sethi and Singh (1972), Singh and Sethi (1974) and Kamboj and Mani (1983) found a non-significant correlation between seed yield and 1000-seed weight in triticale, and their results are consistent with our results (Table 1). Fertile stem number/m2 and seeds/panicle (Table 1) were positively correlated with seed yield (r = 0.581 and 0.413, P < 0.01, respectively). This is contrary to the findings of Açıkgöz and Tekeli (1980) and Serin et al. (1999) for fertile stem number/m2 and seeds/m2 , respectively. The relationship between seed yield and seed weight/panicle was not significant (r = 0.019)
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
which is consistent with Serin et al. (1999). Additionally, the relationships among other components were significant (except 1000-seed weight, seed weight/panicle and total stem number/m2 , Table 1). This is contrary to the findings of Gökku¸s et al. (1997) in smooth bromegrass. Path coefficients divided the correlation coefficient into a series of direct and indirect effects of yield components on the seed yield of smooth bromegrass (Table 2). Most traits were significantly correlated with seed yield. However, path analysis showed that only stem yield/m2 , percentage of fertile stem, sterile stem number/m2 and seeds/m2 had strong direct effects on the enhancement of seed yield of smooth bromegrass, in that order, while it was strongly negative for fertile stem number/m2 and plant height. The indirect effects via stem yield/m2 and percentage of fertile stems substantially increased the total correlations between the components and seed yield (except for sterile stem number/m2 ). But, those via fertile stem number/m2 considerably reduced the total correlations. As the results of those conflict relationships, the significant positive correlation coefficients of fertile stem number/m2 and plant height with seed yield resulted from positive indirect effects of stem yield/m2 and percentage of fertile stem in spite of their strong negative direct effects on seed yield. Conversely, the significant negative total correlation between seed yield and sterile stem number/m2 resulted from the negative indirect effects of the same two components although sterile stem number/m2 had strong positive direct effect on seed yield (Table 2). On the other hand, in the present study, the indirect effects of other components via fertile stem number/m2 were strongly negative, suggesting seed yield component compensation (Adams, 1967). It is clear that when the percentage of fertile stem number in total stems which were composed of vegetative and generative stems increases, seed yield could be increased (r = 0.644, P < 0.01). Plant size (as stem yield), seed and total biomass yields would increase when fertile stem number/m2 increased (r = 0.714, 0.581, P < 0.01). However, if sterile stem number/m2 increased, those quantities would expected to significantly decrease (r = −0.616, P < 0.01) (Table 1). However, when fertile stem number/m2 excessively increased after certain point, additional increase in seed yield could not be obtained. Because it was ob-
5
served that when fertile stem number/m2 excessively increased in quantity, individual fertile stem reduced in size which results in infrequent and small leaves, puny, short and small panicles, reductions in spikelet number/panicle, and reduced seeds in size and quantity. Plants that produced many stems generally produced shorter panicles on the fertile stems which have fewer florets per stem, small seeds, and were less fertile than plants producing few stems. It was reported that mature plant weight was positively correlated with seed yield in crested wheatgrass (Agropyron cristatum L.) because these species have the advantage by having more spikes per plant (Dewey and Lu, 1959). In smooth bromegrass, the stem yield was especially composed by size and number of fertile stems per se. Also, 51.4 and 3.5% of the total variation in seed yield could be expected by variation in the stem yield/m2 and fertile stem number/m2 , respectively. This is particularly important since fertile stem number/m2 is positively correlated with forage yield as measured stem yield (r = 0.920**, P < 0.01) and plant height (r = 0.921, P < 0.01) (Table 1). It could be possible to develop high forage yielding populations that also produce substantial amounts of high quality seed of smooth bromegrass depending on stem yield/m2 and percentage of fertile stems in total stem number. Consequently, the indirect effects via stem yield/m2 , percentage of fertile stems and fertile stem number/m2 were major determinants of the main effects of all components for the seed yield of the smooth bromegrass grown under field condition. Highly significant and positive correlation coefficients as well as high direct effects of stem yield/m2 and percentage of fertile stems on seed yield indicated that both two components in co-operation are simultaneously the most reliable components for selecting high-yielding smooth bromegrass types. But other components having highly significant positive correlations with seed yield were initially not the most reliable components for selection.
5. Conclusion The data obtained from this study could be useful for smooth bromegrass breeders and seed produc-
6
H. Seker, Y. Serin / Europ. J. Agronomy 21 (2004) 1–6
ers concerned with increasing seed yield. The main positive traits determining the seed yield in smooth bromegrass growing in a dense sward are stem yield, percentage of fertile stems, fertile stem number/m2 , seeds/m2 and seeds/panicle having a direct effect and plant height and sterile stem numbers/m2 having indirect effect.
References Açıkgöz, E., Tekeli, A.S., 1980. Seed yield and its components in smooth bromegrass (Bromus inermis Leyss.) cultivars. Euphytica 29 (1), 199–203. Adams, W.M., 1967. Basis of yield component compensation in crop plants with special reference to the field bean, Phaseolus vulgaris. Crop Sci. 7, 505–510. Bhatt, G.M., 1973. Significance of path coefficient analysis determining the nature of character association. Euphytica 22, 89–97. Dewey, D.R., Lu, K.H., 1959. A correlation and path coefficient analysis of components of crested wheatgrass seed production. Agron. J. 51, 515–518. Gökku¸s, A., Serin, Y., Koç, K., Tan, M., 1997. Farkli sıra aralı˘gına ekilen kılçıksız brom (Bromus inermis Leyss.)’a uygulanan de˘gi¸sik biçim yüksekli˘gi ve aniz yakmanin tohum verimi ve bazi özellikler üzerine etkisi. Türkiye II. Tarla Bitkileri Kongresi, 22–25 Eylül 1997, Samsun, Ondokuz Mayis Üni., Zir. Fak. Tarla Bitk. Bl., Tarla Bitk. Bilimi Derne˘gi, s. pp. 455–460.
Kamboj, R.K., Mani, S.C., 1983. Correlation and path analysis in hexaploid triticale. Indian J. Agric. Sci. 53 (6), 394–397. Knowles, R.P., Cooke, D.A., Buglas, E., 1970. Breeding for seed yield and seed quality in smooth bromegrass, Bromus inermis LEYSS. Crop Sci. 10, 539–542. Mishra, S.N., Drolsom, P.N., 1973. Association among certain morphological traits of diallel cross progenies in Bromus inermis LEYSS. J. Agric. Sci. Camb. 81, 69–76. SAS Institute, 1996. sas/stat Software: Changes and enhancements through release 6.11. SAS Inst. Inc., Carry, NC, USA. Serin, Y., Tan, M., Koç, A., Gökku¸s, A., 1999. Farkli mevsim ve dozlarda verilen azotun kilçiksiz brom (Bromus inermis Leyss.)‘un tohum verimi ile buna iliskin karakterlere etkisi ve karakterler arasindaki iliskiler. Tr. J. Agric. Forestry 23 (2), 257–264. Sethi, G.S., Singh, H.B., 1972. Interrelationship of quantitative traits with grain yield in triticale. Indian J. Agric. Sci. 42, 281–285. Singh, H.B., Sethi, G.S., 1974. Path and regression analysis in triticale. Plant Sci. 6, 10–16. Tosun, M., Akgün, I., Sagsöz, S., 1997. Yabani domuz ayrigi (Dactylis glomerata L.) bitkilerinde ot ve tohum verimi ile bazi morfolojik özellikler arasindaki iliskiler. Atatürk Üni. Zir. Fak. Derg. 28 (4), 605–619. Trupp, C.R., Carlson, I.T., 1971. Improvement of seedling vigor of smooth bromegrass (Bromus inermis LEYSS) by recurrent selection for high seed weight. Crop Sci. 11, 225–228. Walton, P.D., 1980. The production characteristics of Bromus inermis Leyss. and their inheritance. Adv. Agron., 341–369. Williams, W.A., Jones, M.B., Demment, M.W., 1990. A concise table for path analysis statistics. Agron. J. 82, 1022–1024.