Assessment of yield stability in sugarcane genotypes using non-parametric methods

Abstract

The evaluation of performance stability and high yields is essential for yield trials in different environments. This study was carried out to identifysugarcane genotypesthat have both a high mean cane yield, mesured in tons of cane per hectare (TCH), and stability across seven different environments, using 11 non-parametric statistical methods: Si(1), Si(2), Si(3), Si(6), NPI(1), NPI(2), NPI(3), NPI(4), RS, TOP and DE. The data came from acane yield of 20 genotypes, as measured at seven locations over three crop-years in the sugarcane regional trials of the Instituto Nacional de Investigaciones Agrícolas (INIA) of Venezuela. The genotypes V99-213, V99-236 and V00-50 showed promising yields and stability according to all of the non-parametric statistics. The TCH presented a positive association with the TOP, NPI(2), NPI(3) and Si(6) statistics. The analysis distinguished two groups of statistics using a principal component analysis (PCA). The first group (G1) was composed of the TOP, NPI(4), NPI(2), NPI(3), Si(3) and Si(6) statistics, which were located under the concept of dynamic or agronomic stability because they are associated with yield. The other group (G2) was composed of the NPI(1), Si(1), Si(2), DE and RS statistics, which fell within the static or biological stability concept.

Performance and stability analysis of some sugarcane genotypes across different environments

“…The other genotypes were unstable (S2di gave highly significant from zero). Similar results obtained by Bissessur et al (2001), , Jun et al (2009, Rea et al (2011), Tiawari et al (2011), Dutra et al (2014), Jun et al (2014, Rea et al (2015), Anand et al (2016) and Prema et al (2017). Klomsa et al (2013) noticed that the genotype K88-92 was the most superior genotype in cane yield.…”

“…Eberhart and Russell (1966) model has been widely used in studies of adaptability and stability of genotypes, the most desired and stable genotypes can be considered when their regression coefficient equal one (bi=1) with mean square deviations from regression (S2di) closed zero. The differences in relative performance of sugarcane genotypes due to the differences in GE interaction in different environments were found and significant genotypeenvironment interactions were reported by (Queme et al, 2005,Rea et al, 2014Guddadamathet al, 2014;Rea et al, 2015;Sphamandla et al, 2017;Premaet al, 2017).The objective of this study was estimation the performance and stability of tested elite genotypes for cane, sugar yields and related components across the entire range of environments in three production areas in Egypt.…”

Propiedades Mecánicas Y Viscoelásticas De Queso Fresco Elaborado Con Leche De Bufala Y Vaca

“…Estos resultados señalan que al menos entre dos ambientes o entre dos genotipos se registraron diferencias en las características evaluadas. La presencia de interacción significativa refleja las diferentes sensibilidades de los genotipos en los ambientes evaluados, lo que limita la identificación de cultivares superiores para todo el Caribe húmedo con diferentes condiciones ambien-tales, circunstancia que concuerda con [9,11,12,13 en Montería 2013B (Cuadro 3), lo que puede obedecer a la cantidad y distribución de la precipitación y la fertilidad de los suelos [3].…”

Assessment of sugarcane varieties for their stability and yield potential in Fiji

“…The relative performance of genotype differs due to the difference in GE interactions in different environments. Many authors, such as Kennedy (1978), Galvez (1980), Tai et al (1982), Kang and Miller (1984), Jackson and Hogarth (1992), Ceccarelli (1996), Rattey and Kimbeng (2001), Khan et al (2002), Kimbeng et al (2002Kimbeng et al ( , 2009, Chapman (2004), Ferreira et al (2006), Queme et al (2010), Tiwari et al (2011), Chen et al (2012), Luo et al (2015), Rea et al (2015), Pereira et al (2017) etc., reported significant genotype-environment interactions.…”