Environmental Stratification in Trials of Unbalanced Multiyear Soybean (Glycine max (l.) Merril) via the Integration of GGE Biplot Graphs and Networks of Environmental Similarity

Genotype x enviroment (GE) interaction can difficult soybean breeding programs to atieve the aim of obtain more productive cultivars. Enviroment stratification is a way to circunvent this problem. This work aimed to gather GGE Biplot graphs of a network of trials unbalance multiyear soybean via matrices of coincidence and networks of enviroment to optimize environmental stratification. Data from an experimental network of 43 trials was used, these experiments were implanted during the crop seasons of 2011/12, 2012/13, 2013/14 and 2015/16 in Brazil. The GE interaction were statistically significant for all 43 trials. The step by step of our analses was: GGE Biplots graphs were obtained; the enviroment coincidence matrices were calculated; the values of matrices were used for to obtain the networks of environmental similarity. The study demonstrated that by the method was possible to identify, using unbalanced multiyear data, the formation of four mega-environments. Therefore, integrating GGE Biplot graphs and networks of environmental similarity is an efficient method to optimize a soybean program by environment stratification.

Assessment of G x E Interactions in Maize (Zea mays L.) Hybrids for Yield using AMMI and GGE Models

Background: In the wake of unpredictable climate change, it is imperative for the breeders to identify hybrids with better adaptation to meet the growing food demand. The present study was carried out to identify stable maize hybrids across various environments. Methods: Twenty one maize hybrids along with two commercial checks viz., CP-818 and Bioseed-TX369 were tested over three locations viz., Viluppuram, Trivandrum and Nagercoil. The experiments were laid out in randomized block design with three replications. Result: AMMI and GGE analysis of variance revealed that the first two principal axes explained the majority of G ´ E interaction. According to AMMI analysis, the hybrid AUK 6240 was relatively stable with high mean whereas, GGE biplots-genotype view identified AUMH 1277 as stable with better yield per plant. GGE biplot-environment view identified Nagercoil as the ideal test location. What-won-where biplots identified three hybrids viz., AU-101, AU-110 and CP-818 suited to Viluppuram and Nagercoil. Though, hybrids with specific adaptability and ideal test location were efficiently identified, study must be extended to more number of environments and hybrids.

Stability and Adaptability of Yield among Earliness Sweet Corn Hybrids in West Java, Indonesia

Multienvironment testing is an important phase to study the interaction of G × E and to select stable hybrids for a broad environment or for a specific environment. To study the interaction of G × E and the stability of earliness and yield of Indonesian new sweet corn hybrids under different locations and seasons in West Java, Indonesia, eighteen hybrids were evaluated in six environments in West Java, Indonesia, and were analysed using parametric and nonparametric stability models, additive main effects and multiplicative interaction (AMMI), and GGE biplots. Results showed that the most promising sweet corn hybrids including hybrids G5 (SR 24 x SR 17) and G11 (SR 31 x SR 17) were identified. The parametric and nonparametric stability parameters and ASV were complement to the AMMI and GGE biplots in selecting stable and adaptable hybrids in terms of earliness and yield. G5 was selected as a high-response hybrid for grain yield to Jatinangor (E1, E2), Lembang (E3, E4), and Wanayasa (E5, E6), as well as earliness to Jatinangor (E2), Lembang (E3, E4), and Wanayasa (E5, E6). G5 sweet corn hybrid, therefore, is suggested to be extensively evaluated on farm and produced for smallholder farmers in West Java, Indonesia.

Stability and adaptability in assai palm tree progenies by gge biplot

TThe increasing demand for the fruit of the assai palm has generated the need for research to enable higher productivity. A GGE biplot was used to analyze the behavior of 30 assai palm tree genotypes from Anajás city and grown in Tomé-Açu, Pará, in a randomized complete block design, with 30 treatments (progenies G1 until G30), three replicates and five plants per plot in four years (A1 until A4). The following characteristics were evaluated: total weight of bunches (PTC), in grams; total weight of fruit (PTF), in grams; and average weight of 100 fruit (PCF). Obtaining as conclusions that the progenies G10 for PTC and PTF; G19 for large fruits or G25 for “chumbinho” fruits for PCF are closest to the ideotype, with better average performance and also in terms of stability and adaptability; most progenies with higher averages have poor stability in PTC and PTF, differently for PCF whose progenies were very close averages and concentrated in terms of stability; the GGE biplots allow us to visualize of the progenies behavior, of the years, of the interrelationship between progenies and years and identify the superior progenies. By graphical analysis of GGE Biplot the environments contribute more intensely to the interaction G x E in relation to the progenies, highlighting A3 for PTC; A2 for PTF and; A4 to PCF. The years A1 and A2 for PTC; A1 for PTF and; A2 for PCF represent the average from all years.

Genotype by environment analysis of rice (Oryza sativa L.) populations under drought stressed and well-watered environments

In Kenya, the key abiotic stress affecting rice production is drought stress which is experienced mainly during reproductive phase of the crop. This study evaluated the performance of Kenyan rice populations including 19 generation of crosses, 6 parental and 5 checks under well-watered and drought stressed environment with the aim of identifying the phenotypic traits that confer drought tolerance in rice. The 19 generation of crosses were in F3 when they were evaluated in the short rains season and later advanced to F4 in the long rains season. Nineteen generation of crosses rice (Oryza sativa L.) lines, six parental and five check lines were evaluated for response to drought under drought stressed and well-watered environment. The study was conducted over two seasons in the year 2016/2017 at Kenya Agricultural Livestock Research Organization (KALRO) -Mwea Centre. The experiment was set up in an alpha lattice design with three replications. Drought stress was imposed at panicle initiation by withholding irrigation till physiological maturity meanwhile the well-watered environment continued to enjoy the recommended irrigation regime from planting to physiological maturity. Yield data were scored for drought tolerance. AMMI analysis of variance for grain yield showed that genotypes from crosses of crosses of SARO5XNERICA11, NERICA2XSARO5 and NERICA15XSARO5 expressed high grain yield. AMMI stability Variance (ASV) showed genotypes NERICA15, Duorado Precoce and progenies from crosses of NERICA11XNERICA2, SARO5XKomboka and NERICA2XNERICA11 expressed high stability in both well-watered and drought-stressed environment. GGE analysis showed that Principal Components (PC1) and PC2 accounted for 96.46% and 3.54%, respectively. GGE biplots showed that genotypes from crosses SARO5XNERICA11 and NERICA15XSARO5 were the most stable and high yielding. GGE biplots ranked the rice lines as follows: those above average in performance, the stable ones, unstable and those below average in performance. SARO5XNERICA11 is worth of selection due to its high mean yield value and is stable across the mega-environments.

Análise GGE biplot na avaliação de características de cachos em Açaizeiros da região Amazônica

El interés por los frutos de la palma Açaí en otras regiones del país hace necesario para el mejoramiento genético de la Euterpe oleracea. Las investigaciones destinadas a comprobar, por GGE (principales efectos del genotipo y la interacción genotipo x ambiente) biplot, esas prometedoras para la selección entre 30 familias de diferentes plantas madre de una población del municipio de Anajás y cultivadas en Tomé-Açu, Pará, y también identificar el médio ambiente que mejor permite la discriminación de éstas. El diseño experimental fue en bloques al azar, con 30 tratamientos (progenies) y tres repeticiones. Se evaluaron las siguientes características: peso promedio de los racimos (PMC), peso total en gramos de racimos (PTC), en gramos y; el número total de clusters (NTC). Se llegó a la conclusión de que, para los fines de la selección basada en el ideotype, los mejores genotipos en PMC fueron G22 y G19; en el PTC son G10 y G14, y el NTC fue el genotipo G10; los genotipos con valores de promedio más altos para las características mostraron una menor estabilidad, excepto G10 para PTC; excepto G10 para PTC; el GGE Biplots permiten ver el diseño, la inter-relación con los efectos ambientales y seleccionar genotipos superiores; en la análisis gráfica por método GGE biplot los efectos de entornos (años) permitir la diferenciación de genotipos, con énfasis en el medio ambiente A3 para PMC y PTC y A1 Para NTC; a la representatividad de todos los ambientes es el A1 sobre las características PMC y PTC; mientras que el A2 para el NTC.