Article abstract

Journal of Agricultural and Crop Research

Research Article | Published December 2017 | Volume 5, Issue 6, pp. 108-116

 

Graphical assessment of yield stability and adaptation of cucumber (Cucumis sativus L) genotypes in Cross River State, Nigeria

 


 

 

Odor E. O.*

Iwo G. A.*

Obok E. E.

 

 Email Author

 

     Department of Crop Science, University of Calabar, PMB 1115 Calabar, Cross River State, Nigeria.


……....…...………..........................…………....………............…............……...........……........................................................………...……..…....……....…

Citation: Odor EO, Iwo GA, Obok EE (2017). Graphical assessment of yield stability and adaptation of cucumber (Cucumis sativus L) genotypes in Cross River State, Nigeria. J. Agric. Crop Res. 5(6): 108-116.

……....…...………..........................…………....………............…............……...........……........................................................………...……..…....……....…

 Abstract 


Cucumbers are essentially beneficial for total health. During the dry season, due to its high water content and important nutrients that are essential for human body, its production and demand is usually high. Five commercial cucumber genotypes: Ashley (ASL), Market more (MM), Marketer (MK), Poinsett (P.ST) and Supper marketer (SM) obtained from the National Institute of Horticulture (NIHORT) Mbato Okigwe station, Imo State, Nigeria, were grown in four environments which include Calabar, Ikom, Obudu and Obubra in Cross River State during 2015 cropping season. The aim was to determine the genotype by environment interaction and the stability of performance of the genotypes across environments. Additive main effect and multiplicative interaction (AMMI) model and Genotype plus Genotype by environment interaction (GGE) biplot were used to identify agronomic stability among the genotypes. The two techniques adopted proved the genotype Ashley to be relatively more stable when compared with other genotypes. The Ikom environment specifically supported high fruit yield performance for all the genotypes evaluated.

Keywords  Cucumber   environment   genotypes   stability   yield  

 

 

Copyright © 2018 Author(s) retain the copyright of this article.

This article is published under the terms of the Creative Commons Attribution License 4.0

 

 

  References 

 

Asrat A, Fistum A, Fekadu G, Mulueta A (2009). AMMI and SREG, GGE bi-plot analysis for marching varieties onto soybean production environment in Ethiopia. Sci. Res. Essay 4(11):1322-1330.

Baclay AA, Classens S, Wehner FC, De Beer JM (2001). Influence of Residual manure on selected nutrient elements and microbial composition of soil under long term crop rotation. South Afr. J. Plant Soil 18:1-6.

Derera J, Tongonna P, Pixley KV, Vivek B, Laing MD, Rij NC (2009). Gene action controlling grey leaf spot resistance in South African maize germplasm. Crop Sci. 48:93-98.

Ezatollah F, Mahsa S (2014). GGE Bi-plot Analysis of genotype x environment interaction in wheat Agropyron Disomic Addition lines. Agric. commun. 2(3):1-7.

Felix C, Serquen JB, Jack ES (1997). Genetic analysis of yield component in cucumber at low plant density. J. Am. Soc. Hortic. Sci. 122(4):522-528.

Guach GH, Zobel RW (1997). Identifying mega-environments and targeting genotypes. Crop Sci. 37:311-326.

Guach HG Jr (1992). AMMI & related model. In Guach H. G. (ed.) statistical analysis of regional trials. Elsevier Science publishers. The Netherlands.

Kandus M, Almorza D, Boggio R, Salerno JC (2010). Statistical model for evaluating the genotype – environment interaction in maize (Zea mays) PYTON 79:39-46.

Makumbi D (2005). Phenotypic and genotypic characterization of white maizeinbreds, hybrids and synthetics under stress environments. Ph.D. dissertation submitted to the office of graduate studies of the Texas A and M University.

Nzuve F, Githiri S, Mukunya DM, Gethi J (2013). Analysis of genotype x environment interaction for grain yield in maize hybrids. J. Agric. Sci. 5(11):75-85.

Singh A, Ram HH (2012). Estimate of stability parameters of yield and its component in cucumber (Cucumis sativus L.) Vegetable Sci. 39(1):31-34.

Tesfaye MB, Baye KM, Biagini MJM, Martin LJ, Lindsey M, Patterson TL, He H, Ericksen MB, Gupta J, Tsoras AM, Lindsley A,Rothenberg ME, Wills-Karp M, Eissa NT, Borish L, Hershey GKK (2011). Differences in candidate gene association between European Ancestry and African American Asthmatic Children. PLoS One 6(2): e16522. doi: 10.1371/journal.pone.0016522

Thanki HP, Sawargaonka SL, Hudge BV (2010). Genotype x environment interaction for biometrical trait in pigeon pea (Cajanus cajan L.) undev. Varying spacings, Electron. J. Plant Breed. 1(4):925-938.

Vasanthkumar AM, Shirol RM, Thammaih N, Prasakumar (2012). Genotype x environment interaction in water melon (Citrilus lanatus Thumb.) genotypes for yield and quality traits. Kanataka J. Agric. Sci. 25(2):248-252.

Vijendra LDD (2005). Genetic & Plant Breeding. New Age International Limited, Publisher: New Delhi. pp. 76-79.

Yan W, Kang MS (2003). GGE Bi-plot Analysis and graphical tool for Breeders, Geneticists and Agronomists. CRC Press LLC Boca Raton, Florida p. 267.

Yan W, Rajcan I (2002). Bi-plot analysis of test sites and traits relation in Ontario. J. Crop Sci. 44:11-20.

Yan W, Hunt LA, Sheng Q, Szlannics Z (2000). Cultivar evaluation and mega-environment investigation bed on the GGE bi-plot. Crop Sci. 40:597-605.

Zobel RW, Wright MJ, Guach GH (1988). Statistical analysis of yield trial. Agron. J. 80:388-393.