Evaluation of high-yielding groundnut genotypes in preliminary trials at NARC, Islamabad, Pakistan

Muhammad Haseeb Ur Rehman, Nazakat Nawaz, Muhammad Jahanzaib and Ghulam Rasool

Advances in Agriculture and Biology, 2019, vol. 02, issue 01

Abstract: Groundnut (Arachis hypogaea) is a very vital legume crop which is usually grown in rain fed areas of Pakistan. Productivity potential of groundnut genotypes in our cropping systems is very important for the development of an agricultural system that is sustainable, environmentally passionate and has a capacity to produce enough production to fulfill the demand of the people for groundnut. To increase production it is the need of the hour to evaluate and identify the best suiting genotypes of groundnut. Fifteen genotypes of groundnut were planted for the purpose of evaluation. All the agronomic or cultural practice was kept same for the genotypes under evaluation. The study was conducted at Oil Seed Program, National Agricultural Research Centre (NARC), Park Road, Chak Shahzad, Islamabad, Pakistan. The experiment used a randomized complete block design (RCBD) with 3 replications. The study was aimed to assess and identify the genotypes/cultivars, which produce high yield for general adoption in the country. The results of the study revealed that genotype GP-1265 was the highest yielding genotype which produced 2293 kg ha-1 dry pod yield, while the second one genotype was PG-1267 which produced 2201.9 kg ha-1 dry pod yield. The lowest yield was obtained from the cultivar BARD-479 i.e., 1456.6 kg ha-1. Among the fifteen entries evaluated in these preliminary yield trials, PG-1265 showed the maximum mean dry pods yield of 2293.3 kg ha-1 as compared to check variety BARD-479 with mean dry pods yield of 1132 kg ha-1. This showed that per hectare yield of PG-1265 was 36 percent more as compared to check variety BARD-479, which is the most common and popular variety of Pothohar region of Pakistan. However, dry pod yield is highly correlated with pod yield per plant, 100 seed weight and seed yield. © 2019 The Author(s)

Keywords: Crop Production/Industries; Research Research Methods/Statistical Methods (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ags:advagr:358914

DOI: 10.22004/ag.econ.358914

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