Integrating Empirical and Analytical Approaches to Investigate Genotype × Environment Interactions in Sugarcane

Abstract

The causes of genotype × environment (G × E) interactions in sugarcane (Saccharum spp.) are unclear. The objectives of this study were to (i) investigate the G × E interactions and site similarity in two selection programs in South Africa, (ii) identify factors responsible for G × E interactions, and (iii) illustrate the integrated use of crop models and climatic data to better understand G × E interactions. Data from eight series of trials were analyzed using variance components, genotype plus genotype × environment (GGE) biplots, and additive main effects and multiplicative interaction (AMMI). Crop model simulations helped summarize environmental covariates before and after canopy closure. Environmental covariates and genotypic traits were correlated to AMMI scores and superimposed on biplots. The G × E interaction accounted for more variation than the main effect of genotype and the repeatable component of G × E was dominant across all series. Two sites were identifi ed as redundant and were recommended for removal. Sites from one program were characterized by higher rainfall and lower water stress compared with sites from the other. The enriched AMMI2 biplots allowed for identifi cation of factors that infl uenced genotypic traits and permitted biological interpretations and trait relations to be studied. This study has illustrated of harvest; TT, mean daily thermal time; TT1 and TT2, average daily heat units before and after canopy closure, respectively; WSI, water stress index; WSI1 and WSI2, water stress index before and after canopy closure, respectively.

Temporal and Spatial Factors Affecting the Nature of Genotype x Environment Interaction in Sugarcane (<i>Saccharum officinarum L.</i>) under Ethiopian Agro-Climatic Conditions: An Integrated Approach

“…As C2B was characterized by higher MIRH (Figure 4(a)), the positive and significant correlation of MIRH and EP with environmental IPCA1 AMMI2 scores of cane yield (Table 7) suggested these were the major climatic factors behind the separation of C2B along the first axis. Similar results were demonstrated by Binbol et al [18] and Ramburan et al [8] [11] where pan evaporation and cane yield were positively correlated. This could be attributed to the established internal moisture relation in sugar cane which is a dominant factor in the synthesis and translocation of sugars and higher evaporative demand on sugar cane causes it to expel excess water through evaporation and thus allowing some of the sugar produced to be used for building new tissue as suggested by Ramburan et al [7] [8] [19] and Clements [20].…”

“…However, our results were in opposite to their results of where the variations of yield accounted for GEI were by far greater than the variations accounted for the environmental effect for all yield traits studied. GxL accounted for 10.58%, 21.48% and 12.17% in cane yield, recoverable sucrose% and sugar yield respectively while 26.64%, 28.99% to results reported by Ramburan et al [8] in which the interaction effect was greater than the genotype effect.…”

“…Fewer sugarcane studies have focused on the interpretation of GEIs to understand the nature and causes thereof. This may benefit sugarcane improvement initiatives and allow for the exploitation of GEI rather than its avoidance or acceptance and identified site covariates (soil depth, clay percentage, organic matter percentage, nitrogen mineralization category, and total available moisture) and seasonal covariates (time of harvest, age at harvest, average daily heat units, solar radiation, rainfall, evaporation, and water stress indices) [8] [11]. Moreover, understanding about the causes of GEI is essential for the implementation of efficient selection and evalu-ation networks, important to establish breeding objectives, formulate recommendation domains, contribute to ideotype design, and identify ideal test conditions [12] [13].…”

Analysis of multienvironment trials (MET) in the sugarcane breeding program of Réunion Island

“…These two components of the genotype 9 environment (GE) interaction determine the yield potential and yield stability of sugarcane varieties. They have been quantified for cane yield and sucrose content or for derived sucrose yield in breeding programs at various locations, including Australia (Jackson and Hogarth 1992;Mirzawan et al 1994), Florida (Milligan et al 1996;Glaz and Kang 2008), South Africa (Parfitt 2000;Ramburan et al 2012a), Venezuela (Rea and De Souza Vieira 2002), and Argentina (Mariotti and Clariana 1994). All these examples of MET studies encompassed locations spread over relatively large cultivated areas, necessarily made up of environments that are more or less heterogeneous in various regards, such as soil type (Milligan et al 1996;Glaz and Kang 2008) or cultivation practices (Mirzawan et al 1994).…”

“…In a second step, genotype plus genotype 9 environment interaction (GGE) biplot analysis (Yan andTinker 2005, 2006) is a very useful graphical tool to investigate in detail the relationships between environments and the pattern of the response of genotypes across environments. This popular visualization technique for MET data has been used in several sugarcane programs to (i) investigate the similarity of environments and their ability to discriminate genotypes (Glaz and Kang 2008;Ramburan et al 2012a;Luo et al 2015), (ii) identify redundant sites or megaenvironments and analyze the stability of the site response across series of genotypes (Ramburan et al 2012a, b), and (iii) visualize the performance rank and stability of genotypes across environments for the purposes of decision-making regarding release of new cultivars (Glaz and Kang 2008;Shandu et al 2012;Klomsa-ard et al 2013;Luo et al 2015).…”