Genotype × Environment Interaction for Germination in Spine gourd (Momordica dioica Roxb.)
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Authors
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JK TIWARI
RMD Collage of Agriculture and Research Station, IGKV, Ambikapur, C.G.-497001, India
Author
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NK RASTOGI
RMD Collage of Agriculture and Research Station, IGKV, Ambikapur, C.G.-497001, India
Author
Keywords:
AMMI, G × E interaction, Seed germination, Spine gourd, StabilityAbstract
Seed dormancy is a major limiting factor constraining commercial cultivation of spine gourd and hence the present study was undertaken to identify better environment for the germination. The germination of fifteen spine gourd genotypes, grown at three different locations was analyzed. All the combinations were tested under optimal conditions for germination. We have evaluated the seed germination response to different environment along with different physical factors which influence seed germination and found that the genotype, G10 did perform well under all the three environments which was followed by G2, G4, G8 and G12. Among the environments, E2 was a best suited environment for germination and E1 is at par with E2. Germination deciding factors like soil
pH, temperature, N, P, K and organic matter content did affect germination in some extent and these factors can be additive, synergistic or inhibitory, depending on the combination, providing an almost infinite spectrum of dormancy levels. The location caused the greatest variation across all the experiments and the impact was greater for germination than for vitality. The results should encourage breeding for seed vitality and some reconsideration of provenance effects on seed vitality.
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References
BASUMATARY P, BORA GC, KALITA UC, SAIKIA L and DEKA
N C (2014). Variability and correlation studies in spine guard
(Momordica dioica Roxb.). Journal of Agriculture and Food
Science,2: 77-81.
BHARATHI LK, SINGH HS, SHIVASHANKAR S,
GANESHAMURTHY AN (2014). Characterization of a fertile
backcross progeny derived from inter-specific hybrid of
Momordica dioica and M. subangulata subsp. renigera and
its implications on improvement of dioecious Momordica spp”,
Scientia Horticulturae, 172pp, 142-148.
EBDON JS and GAUCH HG (2002). Additive Main Effect and
Multiplicative Interaction Analysis of national turf grass
performance Trials: II. Cultivar recommendations, Crop Sci.,
: 497-506.
FENNER M (2000). Seeds: the ecology of regeneration in plant
communities. Wallingford, UK: CABI Publishing.
FENNER M and THOMPSON K (2005). The Ecology of Seeds.
Cambridge: Cambridge University Press (2005) pp. 260.
GAUCH HG (1988). Model selection and validation for yield
trials with interaction. Biometrics, 44(3): 705–715.
GAUCH HG and ZOBEL RW (1988). Predictive and postdictive
success of statistical analysis of yield trials. Theor. Appl.
Genet., 76: 1-10.
SAMONTE S O P, WILSON L T, McCLUNG A M and MEDLEY
J C (2005). Targeting cultivars onto rice growing environments
using AMMI and SREG GGE biplot analyses. Crop Science,
: 2414-2424.
ZOBEL RW, WRIGHT MW and Gauch HG (1988). Statistical
analysis of a yield trial. Agronomy Journal,80: 388-393.
YAN W. (2002) Singular value partitioning in biplot analysis of
multi-environment trial data. Agronomy Journal, 94: 990-
YAN W. and RAJCAN I. (2002) Biplot analysis of test sites
and trait relations of soybean in Ontario. Crop Science, 42:
-20.
BEWLEY JD, BRADFORD KJ, HILHORST HWM and
NONOGAKI H (2013) Seeds: Physiology of Development,
germination and dormancy. 3rd edn. Springer, New Yark.
NONOGAKI H (2019) Seed germination and dormancy: The
classic story, new puzzels, and evolution. Journal of Integrative
Plant Biology, 5: 541-563.
