Vegetos

References

Ajay BC, Aravind J, Abdul Fiyaz R, Kumar N, Lal C, Gangadhar K, Kona P, Dagla MC, Bera SK (2019) Rectification of modified AMMI stability value (MASV). Indian J Genet Plant Breed 79(4):726–731


Akinwale RO, Fakorede MAB, Badu-Apraku B, Oluwaranti A (2014) Assessing the usefulness of GGE biplot as a statistical tool for plant breeders and agronomists. Cereal Res Commun 42(3):534–546


Canter PH, Thomas H, Ernst E (2005) Bringing medicinal plants into cultivation: opportunities and challenges for biotechnology. Trends Biotechnol 23(4):180–185


Cavaliere C (2009) The effects of climate change on medicinal and aromatic plants. Herbal Gram 81:44–57


Cornelius PL, Crossa J, Seyedsadr MS (1996) Statistical tests and estimators of multiplicative models for genotype-by-environment interaction. In: Kang MS, Gauch HG (eds) Genotype-by-environment interaction. CRC Press, Boca Raton, FL, USA, pp 199–234


Crossa J, Gauch HG, Zobel RW (1990) Additive main effects and multiplicative interaction analysis of two international maize cultivar trials. Crop Sci 30:493–500


Farshadfar E, Mahmodi N, Yaghotipoor A (2011) AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L). Aust J Crop Sci 5:1837–1844


Gauch H (1992) Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Elsevier Health Sciences, Amsterdam, Netherlands


Jambhulkar NN, Bose LK, Singh ON (2014) AMMI stability index for stability analysis. In: Mohapatra T (ed) CRRI Newsletter January–March 2014, Central Rice Research Institute, Cuttack, Orissa, p 15


Kendal E, Tekdal S, Karaman M (2019) Proficiency of biplot methods (AMMI and GGE) in the appraisal of triticale genotypes in multiple environments. Appl Ecol Env Res 17(3):5995–6007


Kumar M, Patel M, Chauhan R, Tank C, Solanki S, Patel P, Bhadauria H, Gami R, Pachchigar K, Soni N, Patel P, Singh A, Patel N, Patel R (2020a) Elucidation of genotype-environment interactions and genetic stability parameters for yield, quality and agromorphological traits in ashwagandha (Withania somnifera (L.) Dunal). J Genet 99:59. https://doi.org/10.1007/s12041-020-01207-9


Kumar M, Patel MP, Chauhan RM, Tank CJ, Solanki SD, Gami RA, Soni NV, Patel PC, Patel PT, Bhadauria HS, Patel NB, Patel RM, Rani K (2020b) Delineating G × E interactions by AMMI method for root attributes in ashwagandha [Withania somnifera (L.) Dunal]. Indian J Genet Plant Breed 80(4):441–449


Kumar M, Patel M, Chauhan R, Tank C, Solanki S, Gami R (2021) Genetic analysis in indian ginseng [Withania somnifera (L.) Dunal]. Electron J Plant Breed 12(3):804–811


Lin CS, Binns MRA (1988) Superiority measure of cultivar performance for cultivar × location data. Can J Plant Sci 68:193–198


Mathur S, Sharma S, Gupta MM, Kumar S (2003) Evaluation of an Indian germplasm collection of the medicinal plant Bacopa monnieri by use of multivariate approaches. Euphytica 133:255–265


Miranda GV, Souza LV, Guimarães M, Lauro JM, Namorato H, Oliveira LR, Marcelo OS (2009) Multivariate analyses of genotype × environment interaction of popcorn. Pesq Agropec Bras 44(1):45–50


Mohammadi R, Amri A (2008) Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica 159(3):419–432


Neisse AC, Kirch JL, Hongyu K (2018) AMMI and GGE Biplot for genotype × environment interaction: a medoid-based hierarchical cluster analysis approach for high-dimensional data. Biom Lett 55(2):97–121


Ninemets UE (2015) Uncovering the hidden facets of drought stress: secondary metabolites make the difference. Tree Physiol 36(2):129–132


Oliveira EJ, Godoy IJ (2006) Pod yield stability analysis of runner peanut lines using AMMI. Crop Breed Appl Biotechnol 6:311–317


Oliveira EJ, de Freitas JPX, de Jesus ON (2009) AMMI analysis of the adaptability and yield stability of yellow passion fruit varieties. Sci Agric 71(2):139–145


Purchase JL, Hatting H, Van Deventer CS (2000) Genotype × environment interaction of winter wheat in South Africa: II. Stability analysis of yield performance. South Afr J Plant Soil 17:101–107


Roostaei M, Mohammadi R, Amri A (2014) Rank correlation among different statistical models in ranking of winter wheat genotypes. Crop J 2:154–163


Selmar D, KleinwaÈchter M (2013) Stress enhances the synthesis of secondary plant products: the impact of stress-related over-reduction on the accumulation of natural products. Plant Cell Physiol 54(6):817–826


Shahriari Z, Heidari B, Dadkhodaie A (2018) Dissection of genotype × environment interactions for mucilage and seed yield in Plantago species: application of AMMI and GGE biplot analyses. PLoS ONE 13(5):e0196095


Srivastava A, Siddiqui S, Ahmad R, Mehrotra S, Ahmad B, Srivastava AN (2020) Exploring nature’s bounty: identification of Withania somnifera as a promising source of therapeutic agents against COVID-19 by virtual screening and in silico evaluation. J Biomol Struct Dyn 40(4):1858–1908


Van De Velde H, Bonte D, AbdElgawad H, Asard H, Nijs I (2015) Combined elevated CO2 and climate warming induces lagged effects of drought in Lolium perenne and Plantago lanceolata. Plant Ecol 216(8):1047–1059


Xu Y (2016) Envirotyping for deciphering environmental impacts on crop plants. Theor Appl Genet 129:653–673


Yan W (2002) Singular value partitioning for biplot analysis of multi-environment trial data. Agron J 4:990–996


Yan W, Tinker NA (2006) Biplot analysis of multi-environment trial data: principles and applications. Can J Plant Sci 86(3):623–645


Yan W, Kang MS, Ma B, Woods S, Cornelius PL (2007) GGE Biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci 47:643–655


Zobel RW, Wright MJ, Gauch HG (1988) Statistical analysis of a yield trials. Agron J 80:388–393


R Development Core Team (2021) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org