Investigation of some morphological traits in studied lentil (Lens culinaris Medik.) genotypes grown with foliar application of nanosized ferric oxide

Naser Sabaghnia

Abstract


Interest in growing lentil (Lens culinaris Medik.) is increasing due to its potential returns relative to other legume crops in semi-arid areas. An experiment was conducted to examine the important traits on lentil under application of nano-fertilizer by using eight genotypes with application of the biplot technique in visualizing research data. Nano-iron oxide (2 g L-1) was utilized as foliar spray during vegetative and reproductive stages. The study revealed that genotype by trait (GT) biplot can graphically display the interrelationships among traits and facilitate visual comparison of genotypes. The first two principal components (PC1 and PC2) accounted for 76% of the total variation. The polygon view of GT biplot suggested four sections for the lentil genotypes as well as traits. The vertex genotypes G1 had plant height, number of branches per plant, number of pods per plant, 100-grains weight and grain yield traits. The most prominent relation were: a strong positive association among biological yield, number of branches per plant, number of pods per plant, grains yield and plant height as indicated by the small obtuse angles between their vectors. The traits’ relationship in the semi-arid was highly variable, and grain yield improvement can be achieved by selecting for number of pods per plant, 100-grains weight. We suggest that the GT biplot be used jointly to better understand and more fully explore interaction pattern data.

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References


Bryan J.A. 2000. Nitrogen-fixing trees and shrubs: a basic resource of agroforestry, [in:] The Silvicultural Basis for Agroforestry Systems. Eds M.S. Ashton, F. Montagnini (CRC Press, Baton Rouge, LA), pp. 41–60.

Dehghani D., Omidi H., Sabaghnia N. 2008. Graphic analysis of trait relations of canola (Brassica napus L.) using biplot method. Agronomy Journal 100: 760–764.

Rubio J., Cubero J.I., Martín L.M., Suso M.J., Flores F. 2004. Biplot analysis of trait relations of white lupin in Spain. Euphytica 135 (2): 217–224.

Sabaghnia N., Dehghani H., Alizadeh B., Mohghaddam M. 2010. Genetic analysis of oil yield, seed yield, and yield components in rapeseed using additive main effects and multiplicative interaction biplots. Agronomy Journal 102: 1361–1368.

Sabaghnia N., Karimizadeh R., Mohammadi M. 2014. Graphic analysis of yield stability in new improved lentil (Lens culinaris Medik.) genotypes using nonparametric statistics. Acta Agriculturae Slovenica 103: 113 – 127.

Sabaghnia N., Janmohammadi M. 2014. Interrelationships among some morphological traits of wheat (Triticum aestivum L.) cultivars using biplot. Botanica Lithuanica 20 (1): 19–26.

Sabaghnia N., Karimizadeh R., Mohammadi M., 2013. GGL biplot analysis of durum wheat (Triticum turgidum spp. durum) yield in multi-environment trials. Bulgarian Journal of Agricultural Science 19 (4): 756–765.

Sabaghnia N., Dehghani H., Alizadeh B., Moghaddam M. 2011. Yield analysis of rapeseed (Brassica napus L.) under water-stress conditions using GGE biplot methodology. Journal of Crop Improvement 25: 26–45.

Sekhon B.S. 2014. Nanotechnology in agri-food production: an overview. Nanotechnology, Science and Applications 7: 31–53.

Yan W., Cornelius P.L., Crossa J., Hunt L.A. 2001. Comparison of two types of GGE biplots for studying genotype by environment interaction. Crop Science 41: 656–663.

Yan W., Kang M.S. 2000. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press, Boca Raton, FL.

Yan W., Rajcan I. 2002. Biplot evaluation of test sites and trait relations of soybean in Ontario. Crop Science 42: 11–20.

Yan W. 2001. GGEbiplot – A Windows application for graphical analysis of multienvironment trial data and other types of twoway data. Agronomy Journal 93: 1111–1118.

Yan W., Kang M.S., Ma B., Woods S., Cornelius P.L. 2007. GGE biplot vs. AMI analysis of genotype-by-environment data. Crop Science 47: 643–655.

Yan W., Hunt L.A., Sheng Q., Szlavnics Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40: 597–605.




DOI: http://dx.doi.org/10.17951/c.2014.69.2.29
Date of publication: 2015-05-23 17:52:02
Date of submission: 2015-05-09 17:32:30


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