Morphological Characterization of Twenty One Sweet Pepper (Capsicum annuum L.) Genotypes Collected from Native and Alien Sources

Autor: MA Hoque, Md. Iqbal Hossain, Nasrin Akter Ivy, Jannatul Ferdousi, Satya Ranjan Saha, Mohammad Zakaria
Rok vydání: 2021
Předmět:
Zdroj: European Journal of Biology and Biotechnology. 2:1-8
ISSN: 2684-5199
DOI: 10.24018/ejbio.2021.2.5.254
Popis: Sweet pepper is one of the most important nutritious vegetable and its demand is increasing day by day in Bangladesh indicating need to characterize and assess morphological variability for varietal improvement programme. Twenty-one sweet pepper genotypes from native and alien sources were characterized for twenty-six morphological traits using vegetative and reproductive appearances at Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh from October 2018 to March 2019. Marked variation was exhibited among twenty-six qualitative traits (26) studied. Twenty-two (22) characters showed undeniable variation among the genotypes. The presence of higher percentage (61.90%) of light purple color at node were observed indicated high amount of anthocyanin content. Leaf shape is used as genotypes identifier at vegetative stage and herein three types of leaves were found with dark green color (76.19%) that is highly correlates with yield. In case of flower, same level of stigma exertion (61.90%) with 100% white color corolla indicates higher number of fruit sett were exhibited. Entire genotypes exerted one or more exclusive characters especially fruit shape and color in Bangladesh perspective which could be used as an important breeding tools. Fruit color was observed in various categories at intermediate and mature stage as for instance yellow, green, purple, orange, red etc. in addition higher percentage of blocky fruit shape (38.09%) were observed and these are the consumer fascinating attributes of sweet pepper. However, selection of genotypes with desirable morphological trait can be used for their exploitation of future breeding programme.
Databáze: OpenAIRE