Response of sunflower hybrids to nitrogen application grown under different agro-environments

ABSTRACT

A wide gap exists between production and consumption of vegetable oils in Pakistan. Thereby, a significant proportion (2.28 million tons) of vegetable oils is being imported at the cost of 2257 million US$. Therefore, the present study was conducted to quantify the comparative performance of various sunflower hybrids as influenced by various levels of nitrogen (N) fertilizer under different agro-environments. The experimental treatments consisted of three sunflower hybrids (Hysun33, Hysun38, and Pioneer-64A93) and five levels of N fertilizer (0, 60, 120, 180, 240 kg N ha⁻¹), arranged in a randomized complete block design in a split plot with four replications. The field trials were conducted for two consecutive crop seasons under three different agro-ecologies (arid, semi-arid, and sub-humid) in the province of Punjab, Pakistan. The results of the study demonstrated that the productivity of sunflower hybrids varied greatly in response to N fertilization and different ecologies. Maximum achene yield of 3177 kg ha⁻¹ was harvested under sub-humid environment, followed by the semi-arid one. Among the hybrids, Hysun38 excelled the other two hybrids with a production of 3083 kg ha⁻¹ and 41% oil contents. Generally, the productivity of hybrids increased with the increasing doses of N fertilizer. Maximum achene yield was obtained by addition of 180 kg N ha⁻¹. The findings of the study revealed that yield potential of Hysun-38 could be exploited by addition of N fertilizer at the rate of 180 kg N ha⁻¹ under sub-humid environment.

KEYWORDS:

• Helianthus annuus L.
• hybrids
• dry matter accumulation
• leaf area index
• achene yield
• achene oil content

Acknowledgments

The author appreciatea the support provided by the staff of Department of Biological and Agricultural Engineering at the University of Georgia during the visit by the first author.

Funding

The first author is grateful to the Higher Education Commission of Pakistan for providing financial support for the “Training Programme on Crop Modeling and the Decision Support System for Agrotechnology Transfer” (DSSAT) that was conducted from August 5, 2009 to March 3, 2010 in The University of Georgia, Griffin, USA. The first author is also thankful to “Government of Australia for Endeavour Research Fellowship, 4915_2015” and staff of Endeavour Fellowship especially case manager (Chris Tope), and staff (Jeremy Whish, Perry Poulton, John Hargreaves, Peter Thorburn and Dean Holzworth) of CSIRO, Toowoomba QLD, Australia for entire support during stay in Australia during 2015-2016.