An evaluation of cultivar stability in ARC maize trials over a six year period

Loading...
Thumbnail Image
Date
2005-05
Authors
Oosthuizen, Elzandi
Journal Title
Journal ISSN
Volume Title
Publisher
University of the Free State
Abstract
English: 1. This study was undertaken to compare various statistical methods of analysis to determine the most suitable procedure to evaluate maize genotype performance under the variable production conditions in South Africa, as well as to assess the suitability of these statistical procedures for characterizing yield stability. The main objective of this study was to recommend the most appropriate statistical procedure(s) to estimate maize genotype performance and stability more accurately and to investigate the GxE interaction and stability performance of genotypes in various environments by applying different statistical methods of analysis in order to make useful recommendations for future utilization. 2. Ninety four genotypes were planted at 80 localities in South Africa for the period 1998 to 2003. These trails, which were done by the Agricultural Research Counsel, were divided into six research regions. Three of these regions were used for the purpose of this study. Twenty four cultivars were planted at three sites under irrigation for the Irrigation research region, 24 cultivars at six sites for the Eastern region and 21 genotypes at five sites for the Western region for the period of 2001 to 2003. Both the Eastern and Western region are dryland maize production regions. Grain yield was determined and genotypes were evaluated for performance and yield stability in all three regions according to eight statistical procedures, which were (i) Combined Analysis of Variance, (ii) Cultivar Superiority Measure (Pi), (iii) Wi-Ecovalence (Wi), (iv) Shukla’s procedure of stability variance, (v) Stability Variance with Locality as Covariate, (vi) Rank differences (S1) and Variance differences (S2), (vii) Eberhart and Russell Regression Model, (viii) Additive Main Effects and Multiplicative Interaction (AMMI). The procedure proposed by Purchase (1997) to determine the absolute stability measure for the AMMI model was used as well. Comparisons between results from all statistical procedures as well as recommendations from Phurcase (1997) were used to determine the best suited procedure. 3. The combined analysis of variance ranked cultivars according to their mean grain yield measured in ton ha-1. CRN3505, CRN3549, PAN6844, Phb30H22 and CRN3760 indicated good mean yield over all three different regions. On the other hand QS7608, SC405, LS8508 and SC401 delivered the lowest mean yield values over all three regions. This procedure is no indication of the stability for yield of the genotypes. 4. Lin and Binns cultivar superiority measure indicated good yield stability, according to their definition and procedure, for especially the genotypes CRN3505, CRN3549, SNK2472, PAN6146. The worst performers were PAN6777, QS7608 and SC401. There was considerable correspondence in the performance of the genotypes over the Irrigation and Eastern regions as well as the Eastern and Western (dryland condition) regions. 5. Wricke’s ecovalence, Shukla’s stability variance and stability variance with locality as covariate procedures had approximately the same results. They showed different genotypes to be more stable in different regions. These three procedures found SNK2472, LS8508, SNK2778 and Phb30G03 to be the most stable cultivars and Phb30H22 and PAN6777 to the most unstable cultivars in the Irrigation region. For the eastern region PAN6757, CRN3549, SNK2778 and SNK2969 were the most stable genotypes while PAN6777 and SC405 were the unstable genotypes. Phb3442, SNK2472, PAN6615 and PAN6043 were the most stable cultivars in the western region with PAN6734 and SC401 the most unstable ones. 6. Rank difference and variance difference procedure correlated the best with the AMMI model. This procedure found SNK2472, LS8508, SNK2778 and NS2900 as the most stable genotypes in the irrigation region, while QS7608 and CRN3505 were the unstable genotypes. These results were very much the same as the previous three procedure’s results. But for the eastern region the results were different for the previous three procedures. PAN6777, SNK2472, PAN6757 and CRN3549 were the most stable cultivars and Phb30H22 and LS8508 were the unstable genotypes. In the western region, PAN6615, PAN6043, QS7608 and Phb30H22 were the most stable genotypes while SNK2900 and SC401 were the most unstable genotypes. 7. The Eberhart and Russel procedure, based on deviation from the regression in regression analysis, showed exactly the same results as Stability variance with locality as covariate and therefore had exactly the same rankings for all three regions as Wricke’s ecovalence, Shukla’s stability variance and stability variance with locality as covariate. 8. For the AMMI method, a procedure combining the IPCA1 and IPCA2 scores was used to determine an absolute AMMI value. According to this analysis, Phb30H22, PAN6740, QS7608 and CRN3604 were the most stable genotypes in the irrigation region. This differs totally from the results found by the other procedures. PAN6568 and CRN3505 were the most unstable genotypes. For the eastern region SC405, LS8508, QS7608 and SNK2472 were the most stable cultivars and Phb30H22 and PAN6777 were the most unstable cultivars. In the western region PAN6734, PAN6146, Phb30H22 and Phb3442 were the most stable genotypes and PAN6043 and PAN6479 were the most unstable genotypes. 9. Wricke’s ecovalence, Shukla’s stability analysis and Eberhart and Russel’s procedures correlated highly significantly. However, no correlation was found in the pair wise comparison of Lin and Binns’ (Cultivar Superiority Measure) procedure with the other procedures and very little correlation was found in the pair wise comparison of the AMMI model and the other procedures. The more holistic approach of AMMI is particularly effective in clarifying GxE interactions. Using the IPCA1 and IPCA2 scores to determine an AMMI stability value, superiority ranking of genotypes can easily be done. The AMMI model can summarize patterns and relationships of genotypes and environments successfully and offers a valuable prediction assessment. For this reason, it is recommended that this model is used for analyzing GxE interaction of maize genotypes in South Africa. The Lin and Binns procedure appears to be more of a cultivar performance measure than a stability measure which explains its correlation with the mean yield of the genotypes. The Eberhart and Russel, Wricke’s ecovalence and Shukla’s stability analysis showed highly significant correlation and are recommended to be used to describe genotype stability of maize genotypes rather than to be used to describe GxE interactions, due to the limitations of these techniques. 10. There were six genotypes and three localities that were common over the six year period for the irrigation region and six genotypes with six localities for the eastern region and seven genotypes with five localities for the western region. Wricke’s stability parameter was used to determine the most stable cultivars over all six years over all localities for all three regions. SNK2778 was the most stable genotype for the irrigation maize production region in South Africa for a six year period. In the eastern region, Phb3442 was the most stable cultivar with the lowest Wi value, while NS9100 was the most stable cultivar in the western region. The genotypes planted in the western region are different from those planted in the eastern and irrigation regions. This is due to the difference in climatic conditions. The western region is much dryer and warmer and therefore needs genotypes that are more stable under these extreme conditions. PAN6479 had one of the lowest mean yields throughout all three regions and was found to be relatively unstable in all the analyses. CRN3760 had a good mean yield and intermediate stability throughout all three regions over the period 1998-2003. 11. In the yield progress study, no significant progress was visible. Eighty cultivars planted for a six year period at Cradock were used for this analysis. Year 1998 had the lowest mean yield and 2000 the highest mean yield. The cultivars that were tested in the later part of the period 1998-2003, had overall higher mean yield, which proves that progress has been made by breeding companies in genotype yield increase.
Afrikaans: 1. Hierdie studie is onderneem om die wye verskeidenheid statistiese metodes van analisering van genotipes se prestasies, te vergelyk en sodoende die mees geskikte prosedure te bepaal waarmee mielie genotipes se prestasies onder veranderlike produksie omstandighede in Suid Afrika geevalueer kan word, sowel as die assesering van die statistiese prosedures tov geskiktheid vir die karakterisering van opbrengs stabiliteit. Die primêre doel van hierdie studie was die aanbeveling van die mees gepaste statistiese prosedure(s) om die mielie genotipes se prestasies te kan bepaal so wel as die akkurate bepaling van stabiliteit en die bestudering van GxE interaksies en stabiliteits prestasies van genotipes in verskillende omgewings. Dit is gedoen deur die toepassing van ‘n verskeidenheid van verskillende statistiese metodes vir analises om sodoende waardevolle aanbevelings vir toekomstige toepassings te maak. 2. Vier en negentig genotipes was in 80 verskillende lokaliteite in Suid Afrika geplant van 1998 tot 2003. Hierdie proewe is deur die Landbou Navorsings Raad gedoen. Data is versamel vir ses verskillende navorsings streke. Drie van hierdie streke se inligting is vir hierdie betrokke studie gebruik. Vier en twintig kultivars was by drie lokaliteite onder besproeiing geplant, 24 kultivars in die oostelike mielie produksie streek van Suid Afrika by 6 verskillende lokaliteite en 21 kultivars in die westelike streek by 5 verskillende lokaliteite. Beide die oostelike en westelike streke is droëland mielie produksie streke. Graan opbrengs was bepaal en die genotipes was geevalueer tov prestasie en opbrengs stabiliteit in al drie streke. Die analises was gedoen mbv agt verskillende statistiese prosedures, nl. (i) Gekombineerde Analise van Variansie, (ii) Kultivar Superioriteits Bepaling (Pi), (iii) Wricke se ekovalensie (Wi), (iv) Shukla se prosedure van stabiliteitsvariansie, (v) Stabiliteitsvariansie met Lokaliteit as Ko-variant, (vi) Rangorde verskille (S1) en Variansie verskille (S2), (vii) Eberhart and Russell Regressie Model, (viii) AMMI stabiliteitsmodel. Die prosedure wat deur Purchase (1997) voorgestel is vir die bepaling van die absolute stabiliteits meting vir die AMMI model is ook toegepas. Vergelykings tussen al die toegepaste statistiese prosedures se resultate en aanbevelings van Purchase (1997) is gebruik om die mees geskikte prosedure(s) te bepaal. 3. Die gekombineerde analise van variansie het die kultivars se rangorde bepaal tov die kultivars se gemiddelde graan opbrengs gemeet in ton ha-1. CRN3505, CRN3549, PAN6844, Phb30H22 en CRN3760 het hoë gemiddelde opbrengste gehad in al drie van die verskillende navorsings streke. QS7608, SC405, LS8508 en SC401 het die laagste gemiddelde opbrengs waardes gehad oor al drie streke. Hierdie prosedure is egter geen aanduiding van die stabiliteit vir opbrengs van die kultivar nie. 4. Lin en Binns se kultivar superioriteits meting het goeie opbrengs stabiliteit bepaal, volgens hulle definisie, vir die genotypes CRN3505, CRN3549, SNK2472, en PAN6146. Die swakste presteerders was PAN6777, QS7608 en SC401. Daar was ‘n betekenisvolle ooreenkoms tussen die prestasie van die genotipes in die besproeiing en oostelike droëland produksie streke sowel as die oostelike en westelike droëland produksie streke. 5. Wricke se ekovalensie, Shukla se stabiliteitsvariansie and stabiliteitsvariansie met lokaliteit as ko-variant se prosedures het ongeveer dieselfde resultate opgelewer. Verskillende genotipes was meer stabiel in die verskillende navorsings streke. Hierdie drie prosedures het SNK2472, LS8508, SNK2778 en Phb30G03 as die mees stabiele kultivars bepaal en Phb30H22 en PAN6777 as die mins stabiele kultivars, vir die besproeiings streek. Vir die oostelike streek was PAN6757, CRN3549, SNK2778 en SNK2969 die mees stabiele genotipes terwyl PAN6777 en SC405 die mees onstabiele genotipes was. Phb3442, SNK2472, PAN6615 en PAN6043 was die mees stabiele kultivars in die westelike streek met PAN6734 en SC401 as die mins stabiele kultivars. 6. Rangorde verskille en variansie verskille se prosedure het die beste gekorreleer met die AMMI model se resultate. Hiedie prosedure het SNK2472, LS8508, SNK2778 en NS2900 as die mees stabiele genotipes bepaal in die besproeiings area, terwyl QS7608 en CRN3505 die mees onstabiele genotipes was. Die resultate vir die besproeiings area het baie ooreengestem met die vorige drie prosedures se resultate. Maar die oostelike streek se resultate het verskil van die vorige drie prosedures se resultate. PAN6777, SNK2472, PAN6757 en CRN3549 was die mees stabiele kultivars en Phb30H22 en LS8508 was die mees onstabiele genotipes. In die westelike area was PAN6615, PAN6043, QS7608 en Phb30H22 die meer stabiele genotipes terwyl SNK2900 en SC401 die mins stabiele genotipes was. 7. Die Eberhart en Russel prosedure is gebaseer op die deviasie van die regressie in regressie analise en het presies dieselfde resultate gehad as die stabiliteitsvariansie met lokaliteit as ko-variant en het dus dieselfde rangorde opgelewer as Wricke se ekovalensie, Shukla se stabiliteitsvariansie en stabilitietsvariansie met lokaliteit as ko-variant. 8. Vir die AMMI model is die prosedure wat die kombinasie van die IPCA1 en IPCA2 waardes bepaal, gebruik om die absolute stabiliteits waardes vir AMMI te bepaal. Volgens hierdie analise was, Phb30H22, PAN6740, QS7608 en CRN3604 die mees stabiele genotipes in die besproeiings area. Hierdie resultate verskil totaal van die ander prosedures se resultate. PAN6568 en CRN3505 was die mees onstabiele genotipes. Vir die oostelike streek was SC405, LS8508, QS7608 en SNK2472 die mees stabiele kultivars en Phb30H22 en PAN6777 die mins stabiele kultivars. In die westelike streek was PAN6734, PAN6146, Phb30H22 en Phb3442 die mees stabiele genotipes en PAN6043 en PAN6479 die mees onstabiele genotipes. 9. Wricke se ekovalensie, Shukla se stabiliteits analise en Eberhart en Russel se prosedures het hoogs betekenisvol gekorreleer met mekaar. Geen korrelasie kon gevind word tussen die vergelykings van Lin en Binn se kultivar superioriteits meting prosedure en die ander prosedures nie, terwyl daar baie min korrelasie was tussen die AMMI model se resultate en die ander prosedures se resultate. Die meer oorsiggewende benadering van die AMMI model is in besonder effektief in die ontleding van GxE interaksies. Deur gebruik te maak van die IPCA1 en IPCA2 waardes om die AMMI stabiliteits waarde te bepaal kan die superioriteits rangordes van kultivars ook bepaal word. Die AMMI model kan patrone en interaksies van genotipes en omgewings suksesvol opsom. Daarom word dit aanbeveel dat hierdie model gebruik word vir die analisering van GxE interaksies van mielie genotipes in Suid Afrika. Die Lin en Binns prosedure blyk meer van ‘n kultivar prestasie metings te wees as ‘n stabiliteits bepaling, wat ook die korrelassie met die gemiddelde opbrengs van die genotipes verduidelik. Die Eberhart en Russel, Wricke se ekovalensie and Shukla se stabiliteits analise het hoogs betekenisvolle korrelasies getoon en word ook aanbeveel vir die beskrywing of bepaling van mielie genotipes se stabiliteit eerder as vir die analisering van GxE interaksie, agv die beperkings wat hierdie tegnieke het. 10. Daar was ses genotipes en drie lokaliteite wat gemeenskaplik oor ‘n ses jaar periode in die besproeiings area voorkom. Ses genotipes en ses lokaliteite in die oostelike streek en sewe genotipes met vyf lokaliteite vir die westelike streek. Wricke se stabiliteits analise was gebruik om die mees stabiele kultivars oor die ses jaar periode te bepaal vir al drie streke. SNK2778 was die mees stabiele genotipe vir die besproeiings area. In die oostelike streek was, Phb3442 die mees stabiele kultivar met die laagste Wi waarde, terwyl NS9100 die mees stabiele kultivar in die westelike streek was. Die genotipes wat in die westelike streek geplant word verskil van die wat beter in die oostelike en besproeiings gebiede presteer. Dit is ‘n oorsaak van die verskil in klimaats toestande. Die westelike streek is baie droër en warmer as die ander twee streke, dus word kultivars wat aangepas is vir hierdie uiterste omstandighede vir hierdie area benodig. CRN3760 het ‘n goeie gemiddelde opbrengs en middelmatige stabiliteit in al drie streke gehad, vir die tydperk van 1998-2003. 11. In die opbrengs progressie studie was geen betekenisvolle vorderings sigbaar. Agt kultivars wat vir ‘n ses jaar periode by Cradock geplant was, was vir hierdie analise gebruik. 1998 het die laagste gemiddelde opbrengs gehad en 2000 die hoogste gemiddelde opbrengs. Die kultivars wat tydens die laaste drie jaar van die betrokke tydperk nuut by die proewe ingesluit was het oor die algemeen hoër gemiddelde opbrengste gehad, wat ‘n bewys is van die vordering wat gemaak is deur telings organisasie tov mielie kultivars se opbrengs eienskappe.
Description
Keywords
Corn -- South Africa, Genotype-environment interaction -- Statistical methods, Developmental genetics, Dissertation (M.Sc.Agric. (Plant Sciences (Plant Breeding))--University of the Free State, 2005
Citation