ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) ANALYSIS OF GRAIN YIELD STABILITY IN EARLY DURATION RICE ABSTRACT

Transcription

1 Bose et al., The Journal of Anmal & Plant Scences, 4(6): 014, Page: J Anm. Plant Sc. 4(6):014 ISSN: ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI) ANALYSIS OF GRAIN YIELD STABILITY IN EARLY DURATION RICE L. K. Bose 1, N. N. Jambhulkar and O. N. Sngh 3 Central Rce Research Insttute, Cuttack , Inda *1 Correspondng author - Senor Scentst, Crop Improvement Dvson, Central Rce Research Insttute, Cuttack , Inda. - Scentst, Dvson of Socal Scences, Central Rce Research Insttute, Cuttack , Inda 3 - Head, Crop Improvement Dvson, Central Rce Research Insttute, Cuttack , Inda Correspondng Author Emal: lotanrce@gmal.com ABSTRACT Genotype Envronment nteracton of 17 early duraton rce genotypes tested over four seasons was analyzed to dentfy stable hgh yeldng genotypes. Genotypes were grown n a randomzed complete block desgn wth three replcatons. Genotype envronment nteracton (GEI) was analyzed followng Addtve Man effects and Multplcatve Interacton (AMMI) as well as regresson models. AMMI analyss of varance showed hghly sgnfcant genotype and envronment mean squares. Frst two nteracton prncpal component axes (IPCA) cumulatvely explaned 93.76% of total nteracton effects. Integratng bplot dsplay and genotypc stablty statstcs enabled four groupngs of genotypes based on smlartes n ther performance across envronments. The bplot generated usng genotypes and envronmental scores for frst two IPCAs revealed postonng of the four genotype groups (GG) nto three sectors of the bplot. Among them, three genotype n GG-3 (G -6, G-13 and G-15) exhbted hgh yelds across envronments, low IPCA-1 scores, low stablty ndex (D ) values, unt regresson coeffcent and mnmum devaton from regresson. Hence these genotypes were recognzed as possessng stable hgh yeldng attrbutes. Although, both AMMI model and regresson models were equally potental n parttonng GEI, AMMI analyss and bplot dsplay was more nformatve n dfferentatng the genotype response over envronments and recognzng the most dscrmnatng envronments. Key words: Early rce, AMMI model, regresson model, G E nteracton, stablty parameters. INTRODUCTION Rce s the staple food for a large proporton of the world's populaton (Zhang, 007). Asa s consdered as rce bowl of the world, where nearly 90 % of world s rce s produced (Hossan and Narcso, 004). Inda s the largest rce growng country n the world; however, ts productvty per unt area s low. In Inda, rce s cultvated on mllon hectares wth a producton of mllon tons and productvty of.0 t/ha, (Economc Survey, 007).Though more than 900 rce varetes have been released n Inda, many of them have been out of cultvaton wthn a few years due to nconsstent performance n dverse envronments and only few varetes wth stable performance contnue to be under cultvaton even after 15-0 years of release. Among the rce producton areas n the country, t s the most dverse n hydrology and other sol and clmatc factors that combne to make a dfference n rce yeld (Sngh et al., 1997). In Wet season, rce s grown wth supplemental rrgaton from whch assured producton and productvty s obtaned. Due to natural calamtes when crop s not assured n wet season, dry season rrgated rce provdes food securty and ncome generaton. Analyss of nteracton of genotypes wth locatons and other agro-ecologcal condtons would help n gettng nformaton on adaptablty and stablty performance of genotypes. The method commonly used for analyss of G E nteracton s the Lnear Regresson model of Eberhart and Russell (1966) n whch the b- values gve nformaton about adaptablty and S d and R are used as measures of stablty of performance. Other workers have suggested use of AMMI stablty value (ASV) as measure of stablty. The Addtve Man and Multplcatve Interacton (AMMI) s a better model for analyss of G E nteracton n multlocaton varetal trals (Zobel et al., 1988). It not only gves estmate of total G E nteracton effect of each genotype but also parttons t nto nteracton effects due to ndvdual envronments. Adaptaton and yeld stablty studes help n dentfyng varetes that have ether specfc or general adaptaton whch can be exploted for varetal recommendaton. The present study was undertaken to analyze G E nteracton and evaluate the adaptablty and stablty of yeld performance of seventeen early rce genotypes. Genotype by envronment nteracton has been studed by varous researchers (Sngh et al., 1987; Jan and Pandya, 1988; Zubar and Ghafoor, 001). Specfc- adapted cultvars may rase crop yelds by explotng G E (locaton) nteracton effects (Annccharco, 00) and ste specfc cultvar recommendaton can be defned f the best yeldng materal dffers dependng on ste. Therefore, 1885

2 recommendng more than one cultvar per regon or a sub-regon wll be preferred so as to lmt the rsk of dsasters arsng from unforeseen botc or abotc stress of one cultvar recommended for a wde range of envronments (Annccharco, 00). Rather than just the observed data, modelng of the data by varous technques has been used for cultvar recommendaton. The adaptablty of a varety over a dverse envronment s usually tested by the degree of ts nteracton wth dfferent envronments under whch t s planted (Ashraf et al., 001). Eberhart and Russel (1966) developed a model to test the stablty of varetes under varous envronments and defned a stable varety as havng unt regresson over the envronments (b = 1.00) and wth mnmum devaton from the regresson (S d = 0). Also the jont lnear regresson method (Fnlay and Wlknson, 1963) has been used. Other new models now beng used nclude AMMI (Gauch, 199) and Factoral Regresson (Hardwck and Wood, 197). Ths artcle explots combned advantages of some of these models to evaluate the sutablty of early and md early varetes for small and margnal farmers of Odsha state. MATERIALS AND METHODS The present experment was conducted to determne the yeld stablty of 17 popular early duraton (60 to 115 days) rce genotypes specally released for ran fed to rrgated ecosystems. Some of the genotypes are of long slender to short bold gran types, possess drought tolerance and cold tolerance, resstance to dfferent dseases lke Blast, Brown spot, Sheath blght, Bacteral blght, Rce tungro dsease and nsect pests lke Stem borer and Green leaf hopper. Seeds of these rce genotypes were sown n wet seed beds. Twenty one dayold healthy seedlngs were transplanted n well puddle plots of 3m 4m sze. The plant densty was mantaned at 33 plants m wth spacng of 0 15 cm lne to plant bass. Fertlzer was 90:60:60 of N: P: K ha -1. The entre dose of P and K along wth 30kg of N was appled as basal dose, whle the rest of the 60kg of N was appled n two splt doses, one 1 days after transplantng and the other at flowerng stage. Approprate cultural practces lke weedng, ntermttent rrgaton and need based plant protecton measures were undertaken n order to rase a healthy crop. The experment was conducted n a completely randomsed block desgn wth three replcatons. The experment was repeated n four consecutve wet seasons from 008 to 011 at Central Rce Research Insttute, Cuttack, Inda wth dverse envronmental condtons. At harvest, gran yelds were recorded on a plot bass and then converted to yeld hectare -1. Analyss of varance was computed for ndvdual envronment to test the homogenety, then a combned analyss of varance was performed, consderng both envronments and genotypes as fxed by usng IRRISTAT package (IRRISTAT, 007), so that sgnfcance of all effects were tested aganst mean square of error. The stable performance of 17 rce genotype tested over four envronments was assessed followng the regresson models of Eberhart and Russell (1966), Perkns and Jnks (1968) and Freeman and Perkns (1971). The stablty analyss was carred out wth the help of the statstcal package IRRISTAT (007). The assocaton among dfferent stablty parameters was determned followng Pearson s correlaton coeffcents (Pearson, 190). The AMMI model was appled, wth addtve effects for the 17 rce genotypes (G) and four seasons of testng (Envronments=E), and multplcatve term for G E nteractons. The AMMI analyss frst fts addtve effects for host genotypes and envronments by the usual addtve analyss of varance procedure and then fts multplcatve effects for G E by prncpal component analyss (PCA). The AMMI model s Y j j th envronment, g e j n k1 k k jk e where, Yj s the yeld of the th genotype n the g grand mean, PCA axs k and k k s the mean of the th genotype mnus the s the square root of the egen value of the jk are the prncpal component scores for PCA axs k of the th genotype and the j th envronment, respectvely and e s the resdual. j The envronment and genotypc PCA scores are expressed as unt vector tmes the square root of envronment PCA score = =. 5 k k. 5 k 0 (Zobel et al., 1988). k j k.e. 0 ; genotype PCA score The AMMI stablty ndex D, whch s the dstance of nteracton prncpal component (IPC) pont wth orgn n space, was estmated accordng to the formula suggested by Zhang et al (1998) as: c D Y s s1 where, c s the number of sgnfcant IPCs, Y s s the scores/yeld of the rce genotype n IPCs. The AMMI analyss was conducted usng the computer software IRRISTAT for wndows, verson 5. In addton to the above stablty parameters, varous yeld-stablty statstcs were also calculated as follows: 1886

3 AMMI stablty value (ASV): The AMMI stablty value (ASV) as descrbed by Purchase et al. (000) was calculated as follows: ASV IPCA1 IPCA SS Where SS sumofsquare sumofsquare IPCA1 IPCA ( IPCA1 score ) IPCA score s the weght gven to the IPCA1-value by dvdng the IPCA1 sum of squares by the IPCA sum of squares. The larger the IPCA score, ether negatve or postve, the more specfcally adapted a genotype s to certan envronments. Smaller ASV scores ndcate a more stable genotype across envronments. Sustanablty ndex (SI): The sustanablty ndex was calculated by the followng formula as suggested by Babarmanzoor et al. (009): ( Y n) / YM 100 S. I. Where, Y = Average performance of a genotype, n = Standard devaton and YM = Best performance of a genotype n any year. The values of SI were classfed arbtrarly nto fve groups vz. very low (up to 0%), low (1-40%), moderate (41-60%), hgh (61-80%) and very hgh (above 80%). Stablty ndex (I): The stablty ndex (I) was computed by the nonparametrc stablty analyss (Bajpa and Prabhakaran, 000) to dentfy stable and hgh-yeldng genotypes as follows: y 1 y.. 1 / n 1 I Rao (004) Where, Y = average performance of the th genotype, Y = overall mean, et al = Shukla s (197) stablty varance of the th genotype and n = number of envronments. Yeld stablty ndex (YSI) and Rank -Sum (RS): The YSI and RS were calculated as: YSI = RASV+RY where, RASV s the rank of AMMI stablty value and RY s the rank of mean gran yeld of genotypes (RY) across envronments. RS = Rank mean (R) + S tandard devaton of rank (SDR) The RS ncorporates both yeld and yeld stablty n a sngle non parametrc ndex, whle YSI ncorporates both mean yeld and stablty n a sngle crteron. Low values of both the parameters show desrable genotypes wth hgh mean yeld and stablty. The standard devaton of rank (SDR) was measured as: Where, R. S j m j1 ( R j R l 1 X R s the rank of. j ) wthn the j th envronment, s the mean rank across all envronments for the th genotype and SDR ( S ) 0.5 RESULTS AND DISCUSSION Yeld response of rce genotypes: The 17 cultvars ncluded n the present nvestgaton were dwarf to semdwarf, hgh yeldng and early duraton cultvars specally bred for drect seedng / transplantng under ran fed upland / favorable shallow land ecologes wth yeld attrbutes of.0 to 5.0 t/ha. The hghest mean yeld of 5.9 t/ha was obtaned for G-15, followed by 5.04 t/ha for G- (Table ). The lowest mean yeld of.658 t/ha was obtaned for G-8, followed by t/ha for G-4 and the grand mean yeld was 4.07 t/ha. AMMI analyss of varance: The AMMI analyss of varance of 17 rce genotypes tested over four envronments revealed that 74.67% of the total sum of squares (SS) was attrbutable to the genotypes (G), 13.60% to the envronments (E) and 11.73% to GE nteracton effects (Table 1). A large SS due to G ndcated that the genotypes were dverse wth large dfferences among the mean yelds. The small proporton of SS due to E ndcated that the dfferences among the envronmental means (seasonal fluctuatons) w ere not very hgh. The magntude of GE SS was 6.38 tmes smaller than that for the SS due to G, thus, ndcatng that the dfferences n the response of the genotypes across envronments were not that substantal and the genotypes need mult-locatonal testng. However, the AMMI-1 and AMMI- bplots and a few other nonparametrc stablty parameters provded good nformaton leadng to recognton of stable rce genotypes. The frst nteracton prncpal component axs (IPCA-1) accounted for 6.59% of the nteracton SS n 37.50% of the nteracton degrees of freedom. Smlarly, IPCA- explaned further 31.15% of the nteracton SS. The MS for both IPCA-1 and IPCA- were sgnfcant at P = 0.01 level and cumulatvely contrbuted to 93.74% of the total nteracton. Therefore, the post-dctve evaluaton usng F-test at P = 0.01 suggested that these two IPCAs of the nteracton were sgnfcant for the model wth 34 degrees of freedom. IPCA-3 captured nose, snce the MS was not sgnfcant and explaned 1887

4 only 6.6% of the total SS and, therefore, dd not help n predcton of valdaton observatons. Thus, the nteracton of the 17 rce genotypes across four envronments was best predctable by the frst two prncpal components of genotypes and envronments. Prevous reports reveal that the most accurate model for AMMI can be predcted by usng the frst two IPCAs (Gauch and Zobel, 1996; Yan et al., 000; Yan and Rajcan, 00; Nayak et al., 008). Conversely, Svapalan et al (000) recommended a predctve AMMI model wth frst four IPCAs. These results ndcate that the number of the terms to be ncluded n an AMMI model can not be specfed a pror wthout frst tryng AMMI predctve assessment. The factors lke the type of the crop, the dversty n the germplasm and the range of envronmental condtons wll affect the degree of complexty of the best predctve model (Crossa et al., 1990). AMMI-1 bplot dsplay: The graphcal representaton (Fgure 1) of AMMI analyss reveals the man effect means on the abscssa and IPCA-1 scores of both genotypes as well as envronments, smultaneously on the ordnate. The nteracton s descrbed n terms of dfferental senstvtes of the genotypes to the most dscrmnatng envronmental varable that can be constructed. Dsplacement along the abscssa reflects dfferences n man effects, whereas dsplacement along the ordnate llustrates dfferences n nteracton effects. Genotypes or envronments appearng almost on a perpendcular lne have smlar means and those fallng almost on a horzontal lne have smlar nteracton patterns. Genotypes wth IPCA-1 scores close to zero have small nteractons and hence show wder adaptaton to the tested envronments (Carbonell et al., 004). A large genotypc IPCA-1 score (ether postve or negatve) have hgh nteracton and reflects more specfc adaptaton to the envronments wth IPCA-1 values of the same sgn. The envronments showed varablty n both man effects and nteractons ( Fgure 1). The hgh potental envronment E-3 can be seen n quadrant-ii, wth mnmum nteracton effects, hgh negatve IPCA-1 as well as IPCA- scores. The low potental envronments E-1 and E-4 were dstrbuted n quadrant- IV, wth negatve envronmental ndex, hgh postve IPCA-1 score to low negatve IPCA- scores. The E- showed the second hghest yeld potentalty, had a negatve envronmental ndex, negatve IPCA-1 and hgh postve IPCA- scores. Thus, the bplot ndcated E-3 as the hghest yeldng envronment and E-4 as the lowest yeldng envronment. The rce genotypes also showed wde varablty n yeld. The scores and man effects can be read from the graph and used to predct the expected level of yeld for any G-E combnaton. For any G-E combnaton n the AMMI bplot (Fg ure 1), the addtve part (man effects) of the AMMI model equals the G mean plus E mean mnus the grand mean. The multplcatve part (nteracton effects) s the product of G and E IPCA-1 scores (Zobel et al., 1988). For example, the genotype- wth envronment-3 had a man effect of =5.506 (Table 1). The nteracton effects would be the products of the respectve IPCA-1 scores.e x = The AMMI model estmated the yeld of genotype- n envronment-3 as =4.945 t/ha., whch fts the observed yeld level of t/ha (Table ). Genotypes and envronments wth IPCA-1 scores of the same sgn produce postve nteractons effects, whle the combnatons of IPCA-1 scores of opposte sgns have negatve specfc nteractons. Four genotype groups (GG) are evdent from the bplot generated from the present study (Fgure 1): GG-1 ncludes fve genotypes vz. 5, 9, 10, 1 and 16 wth mean yeld of t/ha, whch s hgher than the grand mean ( 4.07 t/ha). Ths group of genotypes has small postve to negatve IPCA-1 scores rangng from to and small D values. They are well adapted to E- and E-3; have hgh nteractons and possess relatvely stable yelds. GG- conssts of sx genotypes vz. 1, 4, 7, 11, 14 and 17 wth a mean yeld of t/ha, whch s less than the grand mean. They have small postve and negatve IPCA-1 scores rangng from to +0.4, smaller IPCA- scores rangng from to , small D values and are well adapted to the envronments E-, 3 and 4. These genotypes have small nteractons and hence possess relatvely stable low yeldng attrbutes. GG-3 ncludes fve genotypes vz., 3, 6, 13 and 15 wth a mean yeld response of 4.99 t/ha, whch s much above the grand mean. Ths group of genotypes have small negatve to hgh postve IPCA-1 scores rangng from to and small negatve IPCA- scores rangng from to They show small D values. Ths group of genotypes s well adapted to the envronments E-1, 3 and 4. They have hgh nteractons and hence are hghly stable across the envronments. GG-4 conssts of the sngle genotype G-8 wth lowest mean yeld level of.658 t/ha, whch s much lower than the grand mean. Ths group has smallest negatve IPCA-1 score of and postve IPCA- score of +0.54, small D value, and s well adapted to the envronment E-. Ths genotype group has hgh nteractons and hence s hghly stable across tested envronments, but for low yelds. The envronments show varablty n both man effects and nteractons. Two envronments, E-1 and E-4 show postve IPCA-1 scores, whle E- and E-3 show negatve IPCA-1 scores (Table 3 and Fgure 1), whle E- 1, E-3 and E-4 show small negatve IPCA- score and E- show hgh postve IPCA- scores. The hghest mean yeld response (4.671 t/ha) was shown n E-3 whch was hgher than grand mean yelds, whle E-1, E- and E-4 show yeld response smaller than the grand mean yeld. 1888

5 The drecton and magntude of dfferences among genotypes along the abscssa and ordnate (IPCA- 1 scores) can be read from the graph. The most stable genotypes should show hgh yeld levels and should be stable across the tested envronments. Any genotype showng hgher absolute IPCA-1 score would produce a hgher absolute G E nteracton effect than that wth lower absolute IPCA-1 score and s less varable n yeld response (.e. more stable) across the envronments. The genotype stablty rankng based on hgher absolute IPCA-1 scores was GG-3 ( to ), GG- ( to 0.4), GG-1 (0.435 to +0.66) and GG-4( ).The groups of genotypes are depcted on the horzontal axs n AMMI-1 bplot dsplay (Fg. 1). GG-3 exhbt hghest mean yeld levels of 4.99 t/ha, much above the grand mean yeld, small negatve to hgh postve IPCA-1 scores and hence was recognzed as possessng stable yeld attrbutes. GG-1 exhbt second hghest mean yeld level of t/ha and small negatve to postve IPCA-1 scores. GG- exhbt mean yeld level of t/ha and small negatve to moderate postve IPCA-1 scores, whle GG-4 exhbt lowest yeld level of.658 t/ha, much below the grand mean and the smallest negatve IPCA-1 score and hence possessed stable yeld attrbute of lowest magntude. The four envronments show varablty n the man effects and nteractons, the IPCA-1 scores showng clear hgher negatve or postve nteractons (Fg ure 1) due to the groups of envronments (EG). EG-1 consttutng of E-1 and E-4 showed hghest man effects and large postve IPCA-1 scores, whle EG- consstng of E-, and E-3 showed hgh response to the genotypes wth hgh negatve nteracton IPCA-1 scores. The estmates of yeld response, envronmental ndex and frst two IPCA scores n respect of four envronments presented n (Table 3) revealed hghest yeld response of E-3 (4.671 t/ha), followed by E-(4.176 t/ha), E-1 (4.104 t/ha) and E-4 (3.876 t/ha). Hgh postve envronmental ndex was evdenced for E-3, whle t was negatve for rest of the three envronments. The IPCA-1 scores were hgh and postve for E-1 and E-4, whle t was negatve for E- and E-3. The IPCA- scores were hgh and postve for E-, whle t was negatve for E-1, E-3 and E-4. Response of four genotype groups to envronments: Yelds of four genotype groups averaged over four envronments ranged from.658t/ha for GG-4 to 4.99t/ha for GG-3 (Table 4). The rankng of the GGs n descendng order of ther average yeld levels was GG- 3>GG-1>GG->GG4. The genotypes n GG-3 exhbted hghest mean yeld levels of 4.99 t/ha across four envronments. GG-1 and GG- exhbted vared degrees of yeld response rangng from.667 t/ha to t/ha. The only genotype n GG-4 exhbted consstently low yeld response across all the four envronments. AMMI- bplot dsplay: The AMMI s an exploratve technque by whch the G E relatonshp can be expressed n terms of nteracton patterns derved n bplot. A bplot s generated by usng genotypc and envronmental scores of the frst two AMMI components n whch both genotypes and envronments are dsplayed smultaneously (Vargas and Crossa, 000). In the plottng of AMMI- bplot, Purchase (1997) ponted out that the closer the genotypes scores to the center of the bplot, the more stable they are. The nteracton s descrbed n terms of dfferental senstvtes of the genotypes to the most dscrmnatng envronmental varables (AMMI - axes) that can be constructed. These envronmental varables and the genotype senstvtes are estmated from the table tself (Schneder and Van den Boogert, 1999). For smple nterpretaton of the bplot, the genotypes wth vector end ponts far from the orgn contrbute relatvely more to the nteracton than those wth vector end ponts close to the orgn. In the present experment, the genotypes 14 n GG- and 16 n GG-1 have relatvely greater contrbuton to the nteracton than the others ( Fgure ). Genotypes wth vector end ponts far apart, show consderable nteractons lke those of n GG-3, 4 and 7 n GG- and 10 n GG-1 wth rest of the genotypes. Genotypes, for whch the drectons of the vectors almost concde, have smlar pattern of nteractons lke those of G- n GG-3, G-4 and G-7 n GG- and G-10 n GG-1. On the other hand, when the drectons are opposte, the nteracton patterns of the correspondng genotypes show negatve correlaton lke those wthn GG-1, GG- and GG-3. Thus, the genotypes and envronments showng consderable nteractons could be easly dentfed from the bplot. AMMI analyss extracted values of the scores for IPCA-1 to IPCA- n respect of 17 genotypes (Table ) as well as 4 envronments (Table 3). A bplot s generated usng the IPCA-1 and IPCA- scores for the 17 rce genotypes and 4 envronments wth the frst prncpal component axs on the abscssa and the second on the ordnate (Fg ure ). The bplot dsplayed both the genotypes and envronments smultaneously n four sectors of a sngle scattered plot dependng upon the postve or negatve sgns of the scores on the frst two prncpal components. Sector-1 represents host genotypes or envronments wth postve IPCA-1 as well as IPCA- scores, whle sector- represent postve IPCA-1 and negatve IPCA- scores. Sector-3 represents negatve IPCA-1 as well as IPCA- scores and sector-4 represents negatve IPCA-1 and postve IPCA- scores. In the present study, the envronments were dstrbuted nto three sectors n the followng manner: E-1 and E-4 n sector-; E-3 n sector-3; and E- n sector-4 (Fgure ). The rankng of the envronments n order of ther level of response to yelds was E-3>E->E-1>E-4. Among the genotypes, G-1, 16 and 17 fell nto sector-1, G-, 3, 6, 14 and 15 fell nto sector-; G-4, 9, 10, 11 and 13 nto sector-3 and G-1, 5, 7 and 8 nto sector-4. The rankng of 1889

6 genotypes accordng to ther yeld levels was G- 15>>6>3>13>1>5>16>10>9>14>7>11>1>17>4>8 and the rankng of the genotype groups accordng to ther mean yeld levels was GG-3>GG-1>GG->GG-4. Thus, the bplot not only dsplayed the GEI but also facltated n vsual descrpton of whch wn where pattern descrbed by L et al. (006). A polygon drawn n the bplot (Fg ure ) by jonng the genotypes located farthest from the bplot orgn, encompassng all other genotypes, facltates dentfcaton of the genotypes that are hgh yelders n specfc envronments (Yan et al., 000). The vertex genotype n a sector s hghest or lowest yelders n the envronment fallng n that sector. In the present study, the vertex genotypes, 4, 7 and 10 exhbt such attrbutes n all the envronments. The fve genotypes n GG-3 exhbted hghly stable yeld response n all the four envronments. However, the only genotypes G-8 n GG-4 showed stable low yeldng response n all the four envronments. There was a sgnfcant correlaton between the mean yelds and the IPCA-1 scores (r = * ). Hence, the G man effects can be represented by the IPCA-1 scores for the genotypes. The genotypes wth lower IPCA-1 scores would produce a lower absolute G E nteracton effect than those wth hgher absolute IPCA-1 scores and have less varable degree of yelds (more stable) across genotypes. The stablty rankng of the genotypes n ascendng order of absolute IPCA-1 scores was GG-4> GG-3> GG-1> GG-. Thus, the genotypes n GG-4 and GG-3 possessed hgh stablty across the tested envronments. Among them, the genotype G-8 n GG-4 exhbted least mean yelds and hence possessed stable yelds of lower magntude. The fve genotypes n GG-3 exhbted hghest mean yeld levels for whch these were consdered as stable hgh yelders. The dscrmnatng ablty of the envronments can be judged by calculatng the dstance of each envronment from the bplot orgn. In ths regard, the envronments E-1, E- and E-3 are most dscrmnatng as ndcated by long dstance from the bplot orgn. Genotypes wth IPCA-1 scores >0 responded postvely (adaptable) to the envronments that had IPCA-1 scores > 0 (.e. ther nteracton s postve), but responded negatvely to the envronments that had IPCA-1 scores <0. The reverse apples for the genotypes that had IPCA- 1 scores < 0 (Samonte et al., 005). The bplot revealed that the genotypes G-, 3, 6, 1, 14, 15, 16 and 17 wth IPCA-1 scores >0 responded postvely to the envronments E-1 and E-4 and hence ther nteracton s hgh, postve and these genotypes are adaptable to the correspondng envronments. On the other hand, the rest of the genotypes, G-1, 4, 5, 7, 8, 9, 10, 11 and 13, wth IPCA-1 scores <0 are adapted to the envronments E- and E-3. AMMI stablty ndex D : The dstance of nteracton prncpal component pont wth the orgn n space s the AMMI stablty coeffcent D. The estmate of the stablty ndex D ncorporates the IPCA scores of the sgnfcant IPCs dependng upon ther contrbutons towards the nteracton SS (Zhang et al., 1998). The stablty ndex s useful n evaluaton and dentfcaton of genotypes possessng stable yelds. The lower D values ndcate hgh stablty across the tested envronments and vce versa. The rankng of genotype groups n ascendng order of D values was those n GG-4 (0.54) < GG-3 (0.16 to 0.753) < GG-1 (0.73 to 0.544) < GG- (0.106 to 0.630). The sngle genotype G-8 n GG-4 exhbted low D values wth lowest mean yeld level of.658 t/ha and smallest negatve IPCA-1 score (-0.006). Hence ths genotype was recognzed as possessng stable yeld of lowest magntude. The top yeldng fve genotypes n GG-3 possessed hghest level of mean yelds (4.99 t/ha), second lowest level of stablty ndex across the envronments, low negatve to hgh postve IPCA-1 scores but low negatve IPCA- scores and hence were dentfed as possessng hgh yeld stablty. The fve genotypes n GG-1 showed second hghest yeld (4.368 t/ha) wth low stablty ndex rangng from 0.73 to and hence possessed average stablty for yeld. The sx genotypes n GG- showed thrd hghest mean yelds of t/ha wth stablty ndex rangng from to and negatve to postve IPCA-1 as well as IPCA- scores and hence were recognzed as possessng average stablty for yeld. Interacton pattern from response plot: Response plots ndcated the nature of GEI wth the man effects of genotypes and envronments removed. The values plotted for each genotype group by envronments are the devatons from addtve man effects predctons of each varable. The larger the devaton, the greater s the nteracton of the GG wth the envronment. The response may be postve or negatve dependng upon whether or not the GG resulted n more or less effects than the man effects expectaton. In the present study, 5 genotypes n GG-1 showed postve nteractons wth E-1, E-, E-3 and negatve nteractons wth E-4 (Fgure 3); second hghest mean yelds (Table 4); located near the centre of the bplot (Fgure ) wth low negatve to postve IPCA-1 as well as IPCA- scores and hence were recognzed as possessng stable yelds. The sx genotypes n GG- showed negatve nteractons wth E-1, E-, E-3 and postve nteractons wth E-4 located near the centre of the bplot (Fgure ) wth low negatve to postve IPCA- 1 as well as IPCA- scores; and hence were consdered as possessng stable yelds. The fve genotypes n GG-3 showed hgh to low postve nteractons wth E-1, E-, E-3 and hgh negatve nteractons wth E-4, hghest mean yelds wth hgh to low postve and negatve IPCA-1 scores and low negatve IPCA- scores; located nearer to away from the centre of bplot even at the apex 1890

7 of the polygon and mean yelds (4.99 t/ha) much above the grand mean (4.07 t/ha). Hence ths group of genotypes was consdered to be possessng hgh stable yelds. The sngle genotype (G-8) n GG-4 showed negatve nteractons wth E-1, E-, E-3 and hgh postve nteractons wth E-4, low negatve IPCA-1 and low postve IPCA- scores; located away from the centre of the bplot, showed lowest mean yelds and hence was recognzed as hghly stable low yeldng genotype. Stablty analyss by regresson models: Comparson among the three regresson models (E and R, P and J, F and J) based on GEI from ANOVA tables and genotype rankngs based on the regresson coeffcent ( B ) and devaton from regresson ( S d) revealed smlar trends. Hence, the ANOVA and GEI for E and R model only are presented here (Table 5). The hghly sgnfcant G and E mean squares revealed that the yeld responses for 17 genotypes are sgnfcantly dfferent from each other and the envronments also represented an array of dverse condtons for dsease development. The pooled ANOVA showed that the GEI was a lnear functon of the addtve envronmental component. Further parttonng of GEI nto lnear and nonlnear components revealed hghly sgnfcant mean squares (MS) for these component s ndcatng the presence of both predctable and unpredctable components of GEI. Hghly sgnfcant G E (lnear) nteracton ndcated the presence of genetc dfferences among the genotypes for ther regresson on the envronmental ndex. Sgnfcantly larger pooled devaton over pooled error ndcated the exstence of a sgnfcant departure from lnearty and, therefore, some of the GEI cannot be predcted from the lnear regressons. The mean gran yeld of 17 rce genotypes ranged from.658 t/ha for G-8 to 5.9 t/ha for G-15 (Table ). Eberhart and Russell (1966) emphaszed that both lnear ( B ) and nonlnear ( S d) components of GEI are necessary for judgng the stablty of a genotype. A regresson coeffcent B approxmatng 1.0 coupled wth an S d of zero, ndcates average stablty. Regresson values above 1.0 descrbe genotypes wth hgher senstvty to envronmental changes (below average stablty) and greater specfcty of adaptablty to hgh yeldng envronments. A regresson coeffcent below 1.0 provdes a greater resstance to envronmental changes (above average stablty) and, thus, ncreases the specfcty of adaptablty to low yeldng envronments. Lnear regresson for average gran yeld of a sngle genotype on the average yeld of all genotypes n each envronment resulted n B values rangng from to.101 for gran yeld. Ths large varaton n regresson coeffcents ndcated the dfferental responses of genotypes to envronmental changes (Table and Fgure 4). jhjhjhj The results of stablty analyss based on Eberhart and Russell (1966) revealed that the regresson coeffcents of nne genotypes vz.1, 3, 5, 6, 7, 8, 13, 15 and 17 were close to 1.0.e. wthn the confdence lmts for regresson. Among them, the genotypes 3, 5, 6, 13 and 15 were hgh yelders (above the grand mean yeld) and ther devaton from regresson were also mnmum (S d = 0). Hence, these genotypes were best adaptable to all envronments. The G-8 was also adaptable to all envronments but possessed lowest yeldng ablty and, thus, was recognzed as stable low yeldng genotype. The genotypes, 1 and 16 although were hgh yelders (> than grand mean yelds), ther B values were sgnfcantly lower than unt ( B <1.0) and the devaton from regresson for G- was hghest whle that for 1 and 16 was low negatve. Hence these three genotypes were recognzed as possessng above average yeld stablty. The genotype 14 showed regresson coeffcent sgnfcantly less than unt (B <1.0), low gran yelds and was nsenstve to envronmental changes and have adapted to poor envronments. Rest of the genotypes vz. 4, 9, 10 and 11 exhbted mean yeld levels less than the grand mean, regresson coeffcents sgnfcantly greater than unt and mnmum devaton from regresson, less adaptable to envronmental changes and hence possessed below average stablty. Comparson between AMMI and regresson models: Assocaton among dfferent stablty parameters estmated followng E and R model, P and J model, F and P models and AMMI model was verfed by calculatng Pearson s correlatons (Table 6). There was a hghly sgnfcant correlaton among the stablty parameters, except the stablty ndex D whch was not correlated wth any of the other regresson parameters. The strong relatonshp among the parameters ndcated that all the regresson parameters as well as the AMMI parameter IPCA-1 are equally effcent n dentfcaton of genotypes possessng stable hgh yeldng potentals. A crtcal comparson of 17 rce genotypes for ther stablty across four envronments revealed perfect agreement between the regresson and AMMI models n expresson of stable hgh yeld attrbutes of G- n GG-3, G-5 n GG- 1 and G-3, 13 and 15 n GG-3 wth B =1.0, S d = 0 and hgh yelds. The only genotype G-8 n GG-4 possessed stable low yeldng attrbutes n both regresson as well as AMMI models. Rest of the genotypes vz. G-1, 7, 8 and 17 n GG-, although showed stable attrbutes of B =1.0, S d = 0, were low yelders (below the grand mean yeld) and hence were recognzed as stable low yelders. Out of the fve genotypes n GG-3 those exhbted stable hgh yeldng attrbutes and hgh stablty, wth low negatve to hgh postve IPCA-1 scores and low D values n AMMI model, the genotype G-, although showed hgh yeldng potental, was not stable snce ts IPCA-1 score was hgh postve, D value was also hgh n AMMI model and also the regresson coeffcent was sgnfcantly lower than unt ndcatng above average stablty. Rest of the four genotypes G-3, 1891

8 6, 13 and 15 exhbted low negatve IPCA-1 scores, low D values n AMMI model and B values well wthn the confdence lmts as well as S d values equals to zero n regresson model. Hence ths group of genotypes was recognzed as possessng stable hgh yeldng attrbutes. The genotypes G-8 n GG-4, G-1, 7 and 17 n GG-; although exhbted stable attrbutes of unt regresson coeffcents and mnmum S d values n regresson models and low IPCA-1 scores n AMMI model; were low yelders (below the average yelds) and hence were recognzed as stable low yeldng genotypes. Stablty of genotypes by dfferent yeld stablty statstcs: Among the 17 rce genotypes G-, G-3, G-6, G-13 and G-15 were the best fve n order of ther mean yelds (Table 3). The AMMI model recognzed these genotypes are stable hgh yelders (Table 4). Regresson analyss recognzed G-3, G-5, G-6, G-13 and G-15 as stable hgh yelders (Fgure 4). These genotypes were among the top rankng 10 genotypes accordng to the stablty parameters B ER, IPCA1, ASV, I, YSI, SI and RS. On the contrary, SI and I were not consder as sutable stablty ndces for dscrmnatng stable genotypes wth hgh gran yeld (Farshadfar et al., 011). In the present study, IPCA-1, ASV, SI, I, YSI and RS were recognzed as most desrable ndces for dscrmnatng most stable genotypes wth hgh gran yelds. Based on above sutable stablty ndces the genotypes G-, G-3, G-6, G-13 and G-15 were recognzed as the most stable hgh yeldng genotypes. The rankng of genotypes based on all stablty statstcs recognzed G-13 (Tara) and G -15 (Annada) as hghly stable hgh yelders across four envronments. Annada s well known for ts stable hgh yeld performance snce ts release n 1987 and very popular among the farmers of eastern Inda. Table 1. AMMI analyss of varance for gran yelds of 17 rce genotypes tested across four envronments Sources of varaton d.f. SS MS % varance explaned Trals *** Genotypes (G) *** Envronments(E) *** G x E nteracton AMMI IPCA *** 6.59 AMMI IPCA ** AMMI IPCA Pooled resdual ** and *** Sgnfcant at P < 0.01 and levels, respectvely. Table. Mean yeld response (t/ha) of 17 rce genotypes across four envronments, estmates of IPCA scores, AMMI stablty ndex and stablty parameters n three regresson models. Varety Mean IPCA-1 IPCA- D B ER S d B PJ S d BFP S d 1 Vanaprava Kalyan-II ** Kalnga-II Vandana ** Daya Pathara Ghantes Heera Neela ** Anjal ** Dhalaheera ** Parjat ** Tara Sankar ** Annada Kalnga-I ** Kalnga-III ** B s sgnfcantly dfferent from

9 Table 3. Mean yeld response (t/ha), envronmental ndex and estmates of frst two IPCA scores n respect of four envronments. Envronments Mean yeld Envronmental ndex IPCA-1 scores IPCA- scores Table 4. Mean response of four genotype groups (GG) to four envronments (E), range of IPCA -1 and IPCA- scores. GG Genotypes * Mean(t/ha) D range IPCA-1 range IPCA- range GG-1 5,9,10,1, to to to +0.8 GG- 1,4,7,11,14, to to to GG-3,3,6,13, to to to GG * The numerals for genotypes are provded n Table- Table- 5. ANOVA for stablty E and R model Source of varatons Df Sum of squares Mean squares F Rato Probablty Rep wthn Env Genotypes (G) *** E+ (GxE) ** Envronment (E) *** G E E (Ln.) *** GxE (Ln.) Pooled Devaton ** Pooled Error Total Table 6. Correlaton among the stablty parameters for 17 rce genotypes tested across four envronments D B ER B PJ B FP IPCA ** ** ** D B ER ** ** B PJ ** ** Sgnfcant at P < 0.01 level Table 7. The mean yelds, frst and second IPCAs and varous yeld-stablty statstcs for 17 early rce genotypes. Varety IPCA-1 IPCA- Mean ASV YSI SI (%) I RS D Vanaprava Kalyan-II Kalnga-II Vandana Daya Pathara Ghantes Heera Neela Anjal Dhalaheera Parjat

10 Tara Sankar Annada Kalnga-I Kalnga-III Fgure 1. AMMI-1 bplot dsplay of mean yelds and IPCA-1 scores of 17 rce genotypes ( ) across four envronments ( ). The numerals for rce genotypes and envronments are provded n Table- and Table-3, respectvely. Fgure. AMMI- bplot dsplay of 17 rce genotypes and four envronments for ther yeld response. Envronment ponts are at the end of the spke. The numerals for genotypes and envronments are provded n Table- and Table-3, respectvely. 1894

11 Fgure 3. Response plot for the four genotype groups and four envronments Fgure 4. Relaton of yeld and stablty of 17 rce genotypes. Concluson: The AMMI analyss provded () a better understandng of the GEI through analyss of varance, () facltated dentfcaton of genotypes possessng stable yelds as well as dscrmnatng envronments through the bplot dsplay and () specfcty n adaptablty of the genotypes to specfc envronments n a whch won where pattern. The genotypes Kalyan-II, Kalnga-II, Pathara, Tara and Annada were dentfed as most stable across four envronments. The scentfc nformaton obtaned, could be of consderable mportance n developng locaton specfc breedng 1895

12 strateges and selectng stable genotypes n breedng programme. REFERENCES Annccharco, P. (00). Defnng adaptaton strateges and yeld stablty targets n breedng programmes. In Kang, M.S. (Ed.) Quanttatve genetcs, genomcs and plant breedng, Wallngford, UK, CABI, pp Ashraf, M., A.S. Quresh, I.A. Ghafoor and N.A. Khan (001). Genotype-Envronment nteracton n wheat. Pakstan J. Bol. Sc., 1(5): Babarmanzoor, A., M.S. Tarq, A. Ghulam and A. Muhammad (009). Genotype envronment nteracton for seed yeld n Kabul Chckpea (Ccer aretnum L.) genotypes developed through mutaton breedng. Pakstan J. Bot., 41(4): Bajpa, P.K. and V.T. Prabhakaran (000). A new procedure of smultaneous selecton for hgh yeldng and stable crop genotypes. Ind. J. Genet., 60: Carbonell, S.A., J.A. Flho, L.A. Das, A.A. Garca and L.K. Moras (004). Common bean genotypes and lnes nteractons wth envronments. Scentfc Agrc., 61: Crossa, J., H.G. Gauch and R.W. Zobel (1990). Addtve man effects and multplcatve nteractons analyss of two nternatonal maze cultvar trals. Crop Sc., 30: Eberhart, S.A. and W.A. Russell (1966). Stablty parameters for comparng varetes. Crop Sc., 6: Economc Survey (007). Mnstry of fnance economc dvson, Government of Inda, New Delh. Farshadfar, E., N. Mahmod and A. Yaghotpoor (011). AMMI stablty value and smultaneous estmaton of yeld and yeld stablty n bread wheat (Trtcum aestvum L.). Aus. J. Crop Sc., 13: Fnlay, K.W. and G.N. Wlknson (1963). The analyss of adaptaton n a plant-breedng programme. Aus. J. Agrc. Res., 14: Freeman, G.H. and J.M. Perkns, (1971). Envronmental and genotype envronmental components of varablty. VIII. Relatons between genotypes grown n dfferent envronments and measure of these envronments. Heredty, 7: Gauch, H.G. (199). Statstcal analyss of regonal yeld trals: AMMI analyss of factoral desgns. Elsever, New York, 78 p. Gauch, H.G. and R.W. Zobel (1996). AMMI analyses of yeld trals. In Kang MS and Gauch (eds.). Genotype by Envronment Interacton. CRC. Boca Raton, Florda, pp Hardwck, R.C. and J.T. Wood (197). Regresson methods for studyng genotype envronment nteractons. Heredty, 8: 09-. Hossan, M. and J. Narsco (004). Global Rce Economy: Long-term Perspectves. Paper presented at the FAO Conference on Rce n Global Markets and Sustanable Producton Systems, Rome, Italy, February IRRISTAT (007). Internatonal Rce Research Insttute. Metro Manla, Phlppnes. Jan, K.C. and B.P. Pandya (1988). Relatonshp between mean performance and stablty parameters n Chckpea. Legume Res., 11(3): L, W., Z.H. Yan, Y.M. We, X.J. Lan and Y.L. Zheng (006). Evaluaton of genotype envronment nteracton n Chnese sprng wheat by the AMMI model, correlaton and path analyss. J. Agron. Crop Sc., 19: 1-7. Nayak, D., L.K. Bose, S. Sngh and P. Nayak, (008). Addtve man effects and multplcatve nteracton analyss of host-pathogen relatonshp n rce-bacteral blght pathosystems. Plant Path. J., 4: Pearson K. (190). Notes on the hstory of correlaton. Bometrka, 13: Perkns, J.M. and J.L. Jnks (1968). Envronmental and genotype envronmental components of varablty. III. Multple lnes and crosses. Heredty, 3: Purchase, J.L. (1997). Parametrc analyss to descrbe G E nteracton and yeld stablty n wnter wheat. Ph.D. Thess, Dept. of Agronomy, Faculty of Agrculture, Unversty of the Orange Free State, Bloemfonten, South Afrca. Purchase, J.L., H. Hattng and C.S. Vandeventer (000). Genotype envronment nteracton of wnter wheat (Trtcum aestvum L.) n South Afrca: Π. Stablty analyss of yeld performance. South Afr. J. Plant Sol, 17: Rao, M., R.G. Lakshmkantha, R.S. Kulkarn, S.S. Laltha Reddy, and S. Ramesh (004). Stablty analyss of sunflower hybrds through nonparametrc model. Hela, 7: Samonte, S.O.P.B., L.T. Wlson, A.M. Mcclung and J.C. Medley (005). Targetng cultvar onto rce growng envronments usng AMMI and SREG GGE bplot analyses. Crop Sc., 45: Schneder, J.H.M., P.H.J.F. Van Den Boogert and J.C. Zadoks (1999). Explorng dfferental nteractons between Rhzoctona solan AG -t solates and tulp cultvars. Plant Ds., 83: Shukla, G.K. (197 ). Some statstcal aspects of parttonng genotype envronmental components of varablty. Heredty, 9:

13 Sngh, I.P., S. Sngh and I.S. Pawar (1987). Phenotypc stablty n chckpea. ICN 16 pp. Sngh, B.N., S. Fagade, M.N. Ukwungwu, C. Wllams, S.S. Jagtap, O. Oladmej, A. Efsue and O. Okhavebe (1997). Rce growng envronment and bophyscal constrant n rce agroecologcal Zones of Ngera. Met. J., (1): Svapalan, S., L.O. Bren, G.O. Ferrara, G.L. Hollamby, I. Barclay and P.J. Martn (000). An adaptaton analyss of Australan and CIMMIT/CARDA wheat germplasm n Australan producton envronments. Australan J. Agrc. Res., 51: Vargas, M. and J. Crossa (000). The AMM analyss and groupng the bplot. Bometrcs and Statstcs Unt, CIMMYT. Yan, W., L.A. Hunt, O. Sheng and Z. Szlavncs (000). Cultvar evaluaton and mega- envronment nvestgaton based on the GGE bplot. Crop Sc., 40: Yan, W. and I. Rajcan (00). Bplots analyss of the test stes and trat relatons of soybean n Ontaro. Crop Sc., 4: Zhang, Z., C. Lu and Z.H. Xang (1998). Analyss of varety stablty based on AMMI model. Acta Agron. Sn., 4: Zobel, R.W., M.J. Wrght and H.G. Gauch (1988). Statstcal analyss of yeld tral. Agron. J., 80: Zhang, Q. (007). Strateges for developng green super rce. Proc. Nat. Acad. Sc. USA 104: Zubar, M. and A. Ghafoor (001). Genotype Envronment nteracton n mung bean. Pakstan J. Bot., 33():