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Regional Yield Trial of Grasspea (2019--2020)

M. M. HOSSAIN,
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

M. J. ALAM,
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

AKMM ALAM,
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

M MMUKTADIR
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

S. R. MALLICK
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

R. U. CHOUDHURY
Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

Abstract/ Executive Summary:

The experiment was carried out to evaluate the performance of three grasspea genotypes along with check BARI Khesari-5 for yield and yield-related traits in three locations viz. Pulses Research Centre, Ishwardi, Pabna; PRSS, Gazipur and ARS, Satkhira during Rabi 2019-20. Different genotypes of grass pea showed significant or non-significant variations among all the parameters across all the environments. Considering mean data for both days to flower and maturity BGP 13009 was found earlier. The genotype BGP 13010 gave the highest mean seed yield (1549 kg/ha) followed by BGP 13009 (1545 kg/ha) and the lowest (1401 kg/ha) yielded by BARI Khesari-5 across the locations. Compared to the three locations, almost all the genotypes produced a higher yield at Ishwardi. Considering yield, the desired yield contributing characters, and stability parameters, two genotypes BGP 13010 and BGP 13009 were selected for the PVS trial in the next rabi season.

Keywords: Grasspea, Genotypes, Regional yield trial, Evaluation

Location: Pulses Research Centre, Ishwardi, Pabna; PRSS, Gazipur and ARS, Satkhira

Start Date: 00-00-2019

End Date: 00-00-2020

Program Area: Variety and Species

Commodity: Grasspea

Objectives:

The objective of this experiment was to evaluate the performance of grasspea genotypes across the region.

Methodology:

Selected three best-performed genotypes from previous year preliminary yield trial were grown along with BARI Khesari-5 as check variety during Rabi 2019-2020 at Pulses Research Centre, Ishwardi, Pabna; PRSS, Gazipur and ARS, Satkhira under this trial. The experiment was laid out in an RCB design with three replications and spacing of 50 cm between rows. Entries were sown in 8 rows of 4m length plot on 7 November at Satkhira; 13 November at Ishwardi and 20 November 2019 at Gazipur. Seeds were sown in the rows carefully by hands at 3 cm depth and then covered by soils. Post sowing irrigation was given to ensure seed germination. Fertilizers were used as per recommendation as basal during final land preparation. Mulching was done and soil crusts were broken. Each of the entries was investigated from seedling to harvest and compared with checks. At the maturity stage, individual lines were selected on the basis of earliness, 100 seed weight and higher yield. Yield data was recorded from the whole plot and converted into kg/ha. Yield contributing data were analyzed following R software and yield stability was analyzed by Rstat software. GGE biplot analysis was done to find out stable genotypes among locations (Fig. 4.1). GGE biplot is exploited for graphical display of G×E pattern of yield trial data with several advantages. The yield of each cultivar in a tested environment is a result of genotypic main effect (G), environmental main effect (E) and genotype × environment (GE) interaction in biplot analysis (Yan and Kang, 2003). GGE biplot technique separates two principal components, PC1 and PC2 which are derived from subjecting environment-Centered yield data (the yield variation due to GGE) to singular value decomposition where the horizontal axis (PC1) indicates the main effect of genotype while the vertical axis (PC2) shows the interaction of genotype and environment which is the basic criterion for judging genotypic stability (Yan et al., 2000). In this experiment, the first two PCs of the GGE model explained 98.73% of variation in G+GE. The polygon view of the GGE-biplot analysis helps to detect genotype-by-environment interaction and possible mega environments in multi-location yield trials. Here, four genotypes represented a polygon and among them three were the vertex genotypes, in corner of the polygon. They are best in the environment lying within their respective sector in the polygon view of the GGE-biplot; thus these genotypes are considered specifically adapted i.e. most responsive genotypes. The environments fall into two quadrants while the genotypes into four quadrants. Among the tested locations, Ishwardi had larger environmental vectors reflecting a high capacity to discriminate the genotypes therefore these should be regarded as the most suitable to select widely adapted genotypes. In the GGE biplot, genotypes with high PC1 scores have high mean yield, and those with low PC2 scores have stable yield across environments (Yan and Tinker, 2005). Vertex genotype BGP 13010 performed well in all the tested environments. Considering all, the genotypes BGP 13010 and BGP 13009 yielded higher but BGP 13009 showed the best stable performances suggesting its adaptation to Gazipur and Satkhira with higher yield. According to mean ranks and cultivar superiority over locations, the entry BGP 13010 ranked first among the genotypes

Source of Information: Annual Research Report 2019-2020, Pulses Research Centre, RARS, BARI, Ishurdi, Pabna

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Different genotypes of grasspea showed significant or non-significant variations among all the parameters across all the environments. The genotype BGP 13009 flowered earlier considering the mean values of three locations. Among the locations, most of the genotypes flowered earlier (Range: 57-59 days) in Satkhira and in Gazipur it was late (73-77 days). Narail Local matured earlier considering the mean values. In case of locations, all the genotypes comparatively matured earlier in Gazipur and Satkhira. Mean plant height was maximum in BGP 13010 (73 cm) and minimum (68 cm) in Narail Local. Comparatively taller plants were observed in Ishwardi and shorter in Satkhira. The mean highest pods per plant recorded from genotype BGP 13009 (25) followed by BGP 13010 and BARI Khesari-5; and lowest (24) from genotype Narail Local. The number of pods varied from location to location. At Ishwardi, it was maximum ranging 26-35 whereas in Gazipur it was minimum with a range of 15-19. The mean highest 100 seed weight (4.79 g) was recorded from BGP 13010 and the lowest (3.98 g) from Narail Local. The genotype BGP 13010 gave the highest mean seed yield (1549 kg/ha) followed by BGP 13009 and lowest (1401 kg/ha) yielded by BARI Khesari-5 across the locations. Compared to the three locations, almost all the genotypes produced higher yield (Range: 1483-1813 kg/ha) at Ishwardi and Gazipur; and Satkhira location showed comparatively low yield. GGE biplot analysis was done to find out stable genotypes among locations (Fig. 4.1). GGE biplot is exploited for the graphical display of G×E pattern of yield trial data with several advantages. The yield of each cultivar in a tested environment is a result of the genotypic main effect (G), environmental main effect (E) and genotype × environment (GE) interaction in biplot analysis (Yan and Kang, 2003). GGE biplot technique separates two principal components, PC1 and PC2 which are derived from subjecting environment-Centered yield data (the yield variation due to GGE) to singular value decomposition where the horizontal axis (PC1) indicates the main effect of genotype while the vertical axis (PC2) shows the interaction of genotype and environment which is the basic criterion for judging genotypic stability (Yan et al., 2000). In this experiment, the first two PCs of the GGE model explained 98.73% of variation in G+GE. The polygon view of the GGE-biplot analysis helps to detect genotype-by-environment interaction and possible mega environments in multi-location yield trials. Here, four genotypes represented a polygon and among them, three were the vertex genotypes, in corner of the polygon. They are best in the environment lying within their respective sector in the polygon view of the GGE-biplot; thus these genotypes are considered specifically adapted i.e. most responsive genotypes. The environments fall into two quadrants while the genotypes are into four quadrants. Among the tested locations, Ishwardi had larger environmental vectors reflecting a high capacity to discriminate the genotypes therefore these should be regarded as the most suitable to select widely adapted genotypes. In the GGE biplot, genotypes with high PC1 scores have a high mean yield, and those with low PC2 scores have stable yield across environments (Yan and Tinker, 2005). Vertex genotype BGP 13010 performed well in all the tested environments. Considering all, the genotypes BGP 13010 and BGP 13009 yielded higher but BGP 13009 showed the best stable performances suggesting its adaptation to Gazipur and Satkhira with a higher yield. According to mean ranks and cultivar superiority over locations, the entry BGP 13010 ranked first among the genotypes

Knowledge Management: Report/Proceedings