ASSESSMENT OF YIELD STABILITY IN SORGHUM ABSTRACT

Transcription

1 Afrcan Crop Scence Journal, Vol. 15, No. 2, pp ISSN /2007 $4.00 Prnted n Uganda. All rghts reserved 2007, Afrcan Crop Scence Socety ASSESSMENT OF YIELD STABILITY IN SORGHUM Melkassa Agrcultural Research Center, P.O.Box 436, Nazareth, Ethopa (Receved 29 November 2006; accepted February, 2007) ABSTRACT Sorghum (Sorghum bcolor L. (Moench)) s the thrd major cereal crop n Ethopa n terms of area and producton next to tef (Eragrosts tef) and maze (Zea mays). It s the major crop n drought stressed lowland areas that cover 66% of the total arable land n the country. Yeld stablty s one of the setbacks facng plant breeders n developng wdely adapted varetes wth superor yeld. The present study was carred out to nvestgate the effect of genotype by envronment (GxE) on the yeld stablty of sorghum (Sorghum bcolor) usng ffteen genotypes n eght envronments (Locatons x years combnaton). There were sgnfcant dfferences among the genotypes, the envronments and GxE nteractons. Thus, the three types of unvarate stablty models: Type- 1 (CV and S 2 ), Type-2 (W2, s2, and b ) and Type-3 (Sd2 ) were compared for rankng of the genotypes. The parameters of W 2 and s2 had perfect postve correlaton (r=1.0) and strong postve correlaton wth b (r=0.80), but ether weak or no correlaton wth the rest of the parameters. Smlarly, CV and S 2 had strong rank correlaton (r=0.97) but both had ether very weak or no rank correlaton wth the rest of the parameters tested. The Sd 2 had very weak negatve correlaton wth the remanng parameters. Based on the three stablty statstcs, the dfferent genotypes were classfed as stable. To complment and verfy fndngs of ths unvarate approach, the GxE whch uses a mulvarate approach was used. The multvarate approach (AMMI model) gves a broader nference. Based on the AMMI model, genotypes 2 and 5 were the most stable, although genotypes 1 and 3 had satsfactory levels of yeld performance as well as stablty. Therefore, these four genotypes wth wder adaptaton are recommended for sorghum growng dry lowlands of the country. Key Words: AMMI model, Ethopa, GxE, hybrds, Sorghum bcolor RÉSUMÉ Le Sorgho (Sorghum bcolor L. (Moench)) représente la 3 e prncpale céréale en Ethope, en termes de superfce de producton, après le Tef (Eragrosts tef) et le maïs (Zea mays). Il est par alleurs la culture majeure dans les zones de stress due à la sécheresse au sen des basses terres couvrant 66% de la superfce arable totale du pays. La stablté du rendement consttue l une des dffcultés que rencontrent les agrculteurs dans le développement de varétés largement adaptées et présentant un rendement supéreur. La présente étude état menée dans le but d établr par nvestgatons l effet du genotype et de l envronnement (GXE) sur la stablté du rendement du sorgho (Sorghum bcolor) par l utlsaton de 15 génotypes au sen de hut envronnements (stes x combnasonannées). Il y avat des dfférences sgnfcatves parm les génotypes, les envronnements ans que les nteractons GXE. Par conséquent, produsant les 3 types de modèles de stablté à varable unque: Type -1 (CV et S 2 ), Type - 2 (W 2 S2 et b ) et type -3 (sd2 ) étaent comparés pour un classement de génotypes. Les paramètres de W 2 et S2 avaent une corrélaton postve parfate (r = 1,0) et une forte corrélaton postve avec b (r = 0,80), mas présentaent une fable ou aucune corrélaton avec le reste des paramètres. De façon smlare, CV et S 2 avaent une forte corrélaton de classement (r = 0,97) mas le deux avaent sot une très fable ou aucune corrélaton de classement avec le reste de paramètres testés. Le sd 2 avat une corrélaton négatve très fable avec les autres paramètres restants. Se basant sur les 3 statstques de stablté; les dfférents génotypes étaent classfés comme stables. En vue de pouvor compléter et vérfer les résultants par cette approche à varable unque, le GXE qu utlse une approche à mult varants a été utlsé. Cette dernère approche (AMMI Model) donne une large

2 84 déducton. Se basant sur le modèle MMI, les génotypes 2 et 5 étaent les plus stables ben que les génotypes 1 et 3 montraent des nveaux satsfasants de performance en matère de rendement et de stablté. Ans ces 4 génotypes a plus stable adaptaton sont recommandes pour la culture de sorgho dans les régon sèches et a basse alttude dans le pays. Mots Clés: Modèle AMMI, Ethope, GxE, hybrdes, Sorghum bcolor INTRODUCTION Sorghum (Sorghum bcolor L. (Moench)) s the thrd major cereal crop n Ethopa n terms of area and producton next to tef (Eragrosts tef) and maze (Zea mays). It s the major crop n drought stressed lowland areas that cover 66% of the total arable land n the country (Gebeyehu et al., 2004). These areas are charactersed by lmted and erratc ranfall, and hot temperature. A major challenge of sorghum producton n these parts of the country s lack of hgh yeldng and stable varetes. Varety development for these parts of the country has focussed on selecton of early maturng varetes that can escape drought. For the last nearly half a century, a number of early sorghum open-pollnated varetes were developed and released for these areas. The concepts of GxE and yeld stablty have been ssues to the breeders and bometrcans for a long of tme. A sgnfcant GxE for a quanttatve trat s known to reduce the usefulness of the genotype means over all locatons or envronments for selectng and advancng superor genotypes to the next stage of selecton (Pham and Kang, 1988). If there were no GxE assocated wth the genotypeenvronment system relevant to a breedng objectve, selecton would be greatly smplfed because the best genotype n one envronment would also be the best genotype for all target envronments (Basford and Cooper, 1998). Furthermore, varety trals would be conducted at only one locaton to provde unversal results (Gauch and Zobel, 1996). Though the concept of stablty s largely unclear n the plant breedng lterature partly due to the myrad of defntons that have been used to represent ths concept (Basford and Cooper, 1998), t s a powerful tool to partton the GxE nto mean squares responsble for ts occurrence. Hgh yeld stablty usually refers to a genotype s ablty to perform consstently, whether at hgh or low yeld levels, across a wde range of envronments (Annccharco, 2002). The ultmate reason for dfferental stablty among genotypes and for dfferental results from varous test envronments s non-repeatable GxE (Yan and Hunt, 2002). So far, a vast number of unvarate and multvarate, parametrc and non-parametrc stablty models, have been suggested to asses the causes of GxE. The model that has been n frequent use by breeders s one that s based on lnear regresson. Ths was frst proposed by Fnlay and Wlknson (1963). Eberhart and Russel (1966) later modfed t and suggested a dfferent selecton measure of stablty of a genotype based on hgh mean yeld, unt lnear regresson and low devaton from regresson. Ths concept of selectng a genotype based on hgh mean yeld and stablty was later gven the term yeld relablty (Kang and Pham, 1991; Eskrdge, 1990 and Evans, 1993). A relable genotype s characterzed by consstently hgh yeld across envronments (Annccharco, 2002), though ts occurrence s rare and ts measurement s dffcult or uncertan. Accordng to Kang (1998) and Pepho (1998) the assessment of yeld relablty requres numerous test envronments (at least eght). Ln et al. (1986) revsed the prevous stablty models and grouped them nto four: namely, groups A, B, C and D, whch they further grouped nto 3 types of stablty: Type-1, Type-2 and Type- 3. Accordng to these authors a genotype has Type-1 stablty f ts envronment varance s small. A genotype s consdered to have type-2 stablty f ts response to envronments s parallel to the mean response of all genotypes n the tral. On the other hand, a genotype s consdered to have type-3 stablty f the resdual MS from the regresson model on the envronmental ndex s small. Type-1 stablty, whch s analogous to the

3 bologcal concept of homeostass, s useful for measurng stablty n a lmted range of envronments, whch may be useful for selectng genotypes for specfc adaptaton. Ths type of stablty was later termed as statc (Becker and Léon, 1988). Type-2 stablty s based on the genotypes ncluded n the test set (t s a relatve measure). As a result, a genotype whch was found to be stable n a gven set, may not be so f t s organzed wth another set of genotypes. Becker and Léon (1988) called ths type of stablty dynamc. Type-3 stablty depends on the measurements of unpredctable rregulartes n the response to envronment as provded by the devaton from regresson (because the regresson part s predctable (Eberhart and Russel, 1966)). Statc (Type 1) stablty may be more useful than dynamc n a wde range of stuatons, whch characterse farmng systems n developng countres (Smmonds, 1991). These types of stablty are all unvarate as opposed to the GxE whch s multvarate. Therefore, the GxE provdes a more robust nference based on multvarate stablty approaches. The objectve of the study was to nvestgate the effect of GxE on sorghum yeld performance n the drought stressed parts of Ethopa. Yeld stablty n sorghum 85 MATERIALS AND METHODS The experment conssted of 14 sorghum hybrds and one released open-pollnated varety, Teshale (a standard Check OPV, adapted to the mosture stressed lowland areas of Ethopa), hereafter referred to as genotypes. The parents for the hybrds were orgnally receved from Internatonal Crops Research Insttute for the Sem Ard Tropcs (ICRISAT) and Purdue Unversty, USA (Table 1). The genotypes were evaluated at three locatons: Melkassa (E , N ), Meso (E , N ) and Kobo (E , N ) representng the dry hot lowlands of Ethopa (Table 2). The experment was conducted durng the rany seasons of 2003, 2004 and 2005 at Melkassa and Meso and 2003 and 2004 at Kobo. As a result, there were a total of eght envronments (locaton x year combnatons). For all trals the desgn used was RCBD wth four replcatons. Plot sze was 5 m x 0.75 m x 3 rows (11.25m 2 ). Sowng was by hand drllng n rows. Later the plants were thnned to a spacng of 15cm gvng a total densty of plants ha -1. Management practces were unformly appled at all locatons x years followng standard agronomc recommendaton for sorghum n the dry lowlands. TABLE 1. Descrpton of the hybrds used n the study Genotype Genotype code Source of A-lne/ R-lne ICSA 21 X ICSR 50 1 ICRISAT ICSA 22 X M ICRISAT ICSA 15 X M ICRISAT P9534A X KCTENT # 17 DTN 4 Purdue/ICRISAT ICSA 15 X ICSR14 5 ICRISAT ICSA 34 X ICSR14 6 ICRISAT ICSA X SDSL ICRISAT ICSA 34 X 98 MW ICRISAT/Local cross ICSA 34 X 98 MW ICRISAT/Local cross ICSA 34 X 98 MW ICRISAT/Local cross ICSA 34 X P ICRISAT/Purdue ICSA 21 X 98MW ICRISAT/Local cross ICSA 21 X 98MW ICRISAT/Local cross ICSA 21 X 98 MW ICRISAT/Local cross OP (Standard OPV) 15

4 86 TABLE 2. Descrpton of the test envronments Locaton Year Envronment Alttude Sol type Seasonal ranfall (mm) code (m.a.s.l) a (July-November) Melkassa E3-E4-E Andosol Meso E1-E5-E Vertsol Kobo E2-E Vertsol a m.a.s.l., meters above sea level Data were recorded for gran yeld plot -1, whch was latter, converted to ha -1. Analyss of varance was done separately for each envronment followed by combned analyss of varance usng IRRISTAT for Wndows Verson 4.0. (IRRI, 1999). Because the genotype-by-envronment nteracton was sgnfcant, fve out of the nne stablty models, whch were grouped nto four groups and latter, dvded n to three types of stablty by Ln et al. (1986), were analysed and compared for ther effectveness n parttonng the GxE nto parameters that permt a study of phenotypc stablty of the sorghum genotypes. These were: envronmental varance, S 2 (Ln et al., 1986); Coeffcent of varaton, CV (Francs and Kannenbert, 1978); Regresson coeffcent, b (Fnlay and Wlknson, 1963), devaton from regresson, Sd 2 (Eberhart and Russel, 1966); Ecovalence, W 2 (Wrcke, 1962); and Stablty 2 varance, s (Shukla, 1972). The addtve man effects and multplcatve nteracton (AMMI) analyss was also performed separately as an ndvdual multvarate model usng IRRISTAT for Wndows Verson 4.0. (IRRI, 1999). Moreover, rank correlaton coeffcents were calculated between all possble pars of computed stablty parameters and stablty parameters and mean yeld of the genotypes. RESULTS AND DISCUSSION Dfferences among the envronments were sgnfcant ndcatng that they were dverse (Table 3). The GxE was sgnfcant showng varable performance of the genotypes n the varous envronments. The grand mean yeld was 4611 kg ha -1. Eght genotypes were above mean yeld. The hghest genotype yeld was produced by genotype 1 followed by genotype 3. Stablty analyss and rank correlaton. Because the GxE mean square was sgnfcant further analyss was done to dsaggregate the kg ha -1 causes responsble for the varaton. The three types of stablty statstcs: Type-1 (S 2 and CV ), Type-2 (W 2, s2 and b ) and Type-3 (Sd2 ) were compared for rankng of the genotypes. The results of stablty models are presented n Table 4. Genotypes wth smlar ranks receved the average value (Table 5). The W 2 and s2 had perfect postve rank correlaton (r=1.0) and ranked the genotypes n exactly the same way (Table 6). Ths was n conformaton to the fndngs of Ln et al. (1986), Kang et al. (1987) and Pham and Kang (1988). These two stablty parameters had strong correlaton wth b (r=0.80) but very weak correlaton wth CV (r=0.16), S 2 (r=0.12) and Sd 2 (-0.12). CV and S2 had strong rank correlaton (r=0.97) but both had ether very weak or no rank correlaton wth the rest of the parameters tested. Ths was n agreement wth the results of Jalaluddn and Harrson (1993). The Sd 2 had very weak negatve correlaton wth the remanng parameters. Type-1 stablty parameters (CV and S 2 ) rankng ndcated that the genotypes are smlar. Type-2 parameters (W 2, s2 and b ) rankng also ndcated smlartes among genotypes. However, Type-3 stablty parameter (Sd 2 ) ranked the genotypes dfferently. Accordngly, genotypes 11, 12 and 14 had Type-1 stablty. Genotypes 2, 3, and 5 had the hghest Type-2 stablty; whle genotypes 6 and 15 had the

5 Yeld stablty n sorghum 87 TABLE 3. Gran yeld (kg ha -1 ) of the 15 test hybrds evaluated at the 8 envronments n Ethopa Genotype Envronment code code E1 E2 E3 E4 E5 E6 E7 E8 Genotype means Envronment Means TABLE 4. Varous models of stablty used to partton the GxE for gran yeld n the test sorghum genotypes n Ethopa Genotypes Mean gran W 2 CV (%) 2 s S 2 b Sd 2 yeld (kg ha -1 ) * * * Mean 4611 LSD (5%) 556 CV (%) 17.5 * ndcates slopes sgnfcantly dfferent from the slope for the overall regresson whch s1.00

6 88 TABLE 5. Ranks of the sorghum genotypes based on the varous stablty parameters n Ethopa Genotype Stablty statstc code Gran yeld W 2 CV (%) σ 2 S 2 b Sd TABLE 6. Rank correlaton among the sorghum stablty parameters and stablty parameters-yeld n Ethopa CV (%) σ 2 S 2 b Sd 2 Yeld W ** CV (%) ** σ ** S b Sd **, sgnfcant (p<0.01) hghest Type-3 stablty. No sngle stablty parameter had sgnfcant rank correlaton wth mean gran yeld of the genotypes. The absence of postve correlaton wth b and yeld s n agreement wth the fndng of Sudarc et al. (2006) but conflcts wth earler fndngs of Weber and Wrcke (1990), Helms (1993), Sneller et al. (1997), and Mekbb (2003). Ths was probably due to the fact that fve of the eght envronments were consdered unfavourable and thus causng poor response of the genotypes. Type-1 stablty s often assocated wth a relatvely poor response and low yeld n envronments that are hgh yeldng for other cultvars though t has broad nferental base, because ts stablty defnton does not depend on the other genotypes ncluded n the test and s thus unambguous (Ln et al., 1986). However, t does not provde nformaton on the response pattern over the range of test envronments that s so vtal for cultvar recommendatons (Ln et al., 1986). Accordng to Kang (2002), ths type of stablty would not be benefcal for the farmer

7 because a genotype n ths sense would not respond to hgh levels of nputs. Type-2 stablty s useful for comparng a specfc set of genotypes, but by beng a relatve measure, t does not have a suffcently broad nferental base for general assessment (Ln et al., 1986). Ths parametrc approach gves only the ndvdual aspects (Types 1, 2, 3) of stablty but cannot provde an overall pcture of the response (Ln et al., 1986). In ths study, the three types of stablty parameters declared dfferent genotypes to be the most stable. As a result of ths nconsstency, t was dffcult to reach a concluson on producng genotype recommendaton. Smlar nconsstency n rankng usng a unvarate approach was prevously suggested to be dffcult to reconcle nto a unfed concluson by Ln et al. (1986). Accordng to them, the basc reason for the dffculty s that a genotype s response to envronments s multvarate, yet the parametrc approach tres to transform t to a unvarate problem va a stablty ndex. Furthermore, Ln et al. (1986) suggested that clusterng of genotypes accordng to ther response structure emerged as a dfferent lne of thought to escape the dffculty mposed by the unvarate approach. A dsadvantage of clusterng analyss, however, s that t gves no nsght nto the yeld response of genotypes across envronments (Flores et al., 1998). Ths problem has been overcome by usng the AMMI model (Romagosa and Fox, 1993). Yeld stablty n sorghum 89 In ths study, the AMMI analyss of varance for gran yeld of the 15 genotypes n the eght envronments revealed that 73.8% of the total sum of squares was attrbutable to envronmental effects (Table 7). Only 5.9% of the total sum of squares was attrbutable to genotype effects and the remanng 20.3% was due to GxE effects. The large sum of squares for envronments ndcated that the envronments were dverse, wth large dfferences among envronmental means causng most of the varaton n gran yeld. The magntude of the GxE sum of squares was 3.41 tmes larger than that of the genotypes, ndcatng, that there were substantal dfferences n genotype response across envronments. Accordng to Crossa et al. (1990), AMMI wth two, three or four IPCA axes s the best predctve model. Smlarly, n the present study, the AMMI analyss further revealed that the frst two nteracton prncpal component axes (IPCA 1 & IPCA 2) explaned 68.7% of the GxE sum of squares. Ths was n agreement wth Sneller et al. (1997), who suggested that GxE pattern s collected n the frst prncpal components of analyss. The frst nteracton prncpal component axs (IPCA 1) alone captured 50.7% of the GxE sum of squares wth 20.41% of the GxE degrees of freedom. The thrd nteracton prncpal component axs (IPCA 3) was also sgnfcant. However, accordng to Zobel et al. (1988) the frst two IPCA axes best explan the GxE sum of squares and the remanng can be consdered as nose. Therefore, n the present study 31.3% of TABLE 7. Analyss of varance for the AMMI model of the 15 genotypes n the 8 envronments for gran yeld Source df Sum of squares Explaned (%) Mean squares Total Genotypes (G) ** Envronments(E) ** G x E ** IPCA ** IPCA ** IPCA ** IPCA G x E resdual ** sgnfcant at P<0.01

8 90 Fgure 1. A bplot of gran yeld means (Kg ha -1 ) versus IPCA1 for 15 sorghum genotypes n the 8 envronments. the GxE sum of squares was consdered as nose (Table 7). The AMMI1 bplot, showng man effects means on the abscssa and IPCA 1 values as the ordnates, genotypes (or envronments) that appear almost on a perpendcular lne have smlar means and those that fall almost on a horzontal lne have smlar nteracton patterns (Crossa et al., 1990). Accordng to these authors, genotypes (or envronments) wth large IPCA 1 scores (ether postve or negatve) have hgh nteractons, whereas genotypes (or envronments) wth IPCA 1 scores near zero have small nteractons. Smlarly, n the bplot (Fg. 1) that reveals 90% of the total sum of squres, fve of the eght envronments had below average man effects and were unfavourable. Envronments E2 (Kobo n 2003) and E4 (Melkassa n 2004) had the hghest man effects and were favorable to the performance of most of the genotypes. On the contrary, envronments E5 (Meso n 2004), E3 (Melkassa n 2003) and E8 (Meso n 2005) were the most unfavourable envronments. In general Kobo showed hgher man effect values n both years (E2 and E6), whereas Meso showed consstently below average (poor) man effect values. However, Melkassa showed below average man effects n 2003 and 2005 (E3 and E7) but above average man effects n 2004 (E4). The nteracton was also varable from year to year. Ths nconsstency n nteracton at Melkassa poses dffculty n producng varety recommendaton for that partcular locaton. Genotypes 5, 9, and 15, and envronments E1 and E7 were least nteractve. Genotypes 2 and 5 placed closer to the bplot orgn and were, therefore, the most stable but had average man effects of close to the grand mean. Genotypes 1 and 3 had hgher average man and smlar lower nteracton whch makes them most stable genotypes. On the contrary, genotypes 4, 6 and 11 had smlar man effects but genotype 4 had larger IPCA 1 score and s more unstable. CONCLUSION In ths study, attempts have been made to compare the varous stablty models and wth whch to select the stable sorghum genotypes n the lowlands of Ethopa. There are remarkable

9 nconsstences wth the unvarate stablty estmates (Types 1, 2 and 3), whch create dffculty n producng genotype recommendaton. However, the multvarate approach, the AMMI model s better for parttonng the GxE nto the causes of varaton. As a result a more robust nference s that genotypes 2 and 5 are the most stable but genotypes 1 and 3 have very good level of yeld performance as well as stablty. Therefore, these four genotypes are recommended for the drought stressed sorghum growng areas. ACKNOWLEDGEMENT Ths research was funded by the Ethopan Insttute of Agrcultural Research (EIAR). All Research Staff at Melkassa, Meso and Kobo Research Centers are duly acknowledged for handlng the experment. REFERENCES Annccharco, P Genotype x envronment nteractons: challenges and opportuntes for plant breedng and cultvar recommendatons. FAO Plant Producton and Protecton Paper 174, FAO, Rome. Basford, K. E. and Cooper, M Genotype x envronment nteractons and some consderatons of ther mplcatons for wheat breedng n Australa. Australan Journal of Agrcultural Research 49: Becker, H. C. and Léon, L Stablty analyss n plant breedng. Plant Breedng 101:1-23. Crossa, J., Gauch, H.G. and Zobel, R.W Addtve Man Effects and Multplcatve Interacton Analyss of Two Internatonal Maze Cultvar Trals. Crop Scence 30: Eberhart, S. A. and Russel, W.A Stablty parameters for comparng varetes. Crop Scence 6: Eskrdge, K. M Selecton of stable cultvars usng a safety-frst rule. Crop Scence 30: Evans, L. T Crop Evoluton, Adaptaton and Yeld. New York, Cambrdge Unversty Press. Yeld stablty n sorghum 91 Fnley, W. K. and Wlknson, G.N The analyss of adaptaton n a plant breedng programme. Australan Journal of Agrcultural Research 14: Flores, F., Moreno, M.T. and Cubero, J.I A comparson of unvarate and multvarate methods to analyze G x E nteracton. Feld Crops Research 56: Francs, T. R, and Kannenberg, L. W Yeld stablty studes n short-season maze. 1. A descrptve method for groupng genotypes. Canadan Journal of Plant Scences 58: Gebeyehu, G., Adugna, A., Tadesse, A., Tesso, T., Belete, K. and Mchael, H Development of sorghum varetes and hybrds for dryland areas of Ethopa. Uganda Journal of Agrcultural Scences 9: Helms, T. C selecton for yeld and stablty among oat lnes. Crop Scence 33: IRRI IRRISTAT verson 4.0. Statstcal Software. Mlan, Phlppnes. Jalaluddn, Md. and Harrson, S.A Repeatablty of stablty estmators to gran yeld n wheat. Crop Scence 33: Kang, M. S. and Pham, H.N Smultaneous selecton for hgh yeld and stable crop genotypes. Agronomy Journal 83: Kang, M. S Usng genotype-byenvronment nteracton for crop cultvar development. Advances n Agronomy 62: Kang, M. S Genotype-Envronment Interacton: Progress and Prospects. In: Kang, M. S., (Ed.) Quanttatve Genetcs, Genomcs and Plant Breedng. CABI Publshng. Kang, M. S., Mller, J.D. and Darrah, L.L A note on relatonshp between stablty varance and ecovalence. Journal of Heredty 78: 107. Ln, C. S., Bans, M.R., and Lefkovtch, L.P Stablty Analyss: Where Do We Stand? Crop Scence 26: Mekbb F Yeld stablty n common bean (Phaseolus vulgars L.) genotypes. Euphytca 130: Pham, H. N. and Kang, M.S Interrelatonshps among and repeatablty of several stablty statstcs estmated from

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