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Vol. 11, Issue 4 (2022)

Effect of zinc and sulphur on growth and yield of groundnut (Arachis hypogaea) and yield validation using SPSS model

Author(s):
Nagaushodaya Reddy T, Biswarup Mehera and Nagavarapu Swarna Priya
Abstract:
A field experimental trail on groundnut was conducted during Zaid, 2021 at Krishi Vigyan Kendra (KVK), Department of Agronomy, SHUATS, Prayagraj (U.P.) to evaluate the effect of zinc and sulphur on growth and yield of groundnut and to validate the yield using SPSS model. The soil of the experiment plot was sandy loam in texture, nearly neutral in soil reaction (pH 7.1), low in organic carbon (0.28%), available N (225 kg/ha), available P (19.50 kg/ha), available K (92 kg/ha). The experiment was laid out in Randomized Block Design (RBD) with ten treatments replicated thrice. In the view of this experiment, zinc and sulphur were applied thrice at different levels (ZnSO4 at 20, 25, 30 kg/ha and S at 30, 45, 60 kg/ha respectively) along with RDF and control plot with RDF alone. Results revealed that significantly higher growth parameters at 60 DAS and yield parameters at harvest viz: plant height (22.13 cm), number of nodules/plant (192.40), plant dry weight (16.40 g), number of pods per plant (50.20), number of kernels per pod (2), seed index (40.20 g), shelling percentage (70.20%), pod yield (4.20 t/ha), seed yield (2.95 t/ha), haulm yield (4.45 t/ha) and harvest index (34.37%) were recorded with the application of ZnSO4 30 kg/ha + Sulphur 60 kg/ha. Also, there was highest percentage increase in the actual yield (26.81%) over the predicted yield through SPSS with the application of ZnSO4 30 kg/ha + Sulphur 60 kg/ha. Thus, application of 30 kg ZnSO4 and 60 kg sulphur per hectare along with RDF could be a promising option for yield enhancement in groundnut.
Pages: 132-136  |  894 Views  286 Downloads


The Pharma Innovation Journal
How to cite this article:
Nagaushodaya Reddy T, Biswarup Mehera, Nagavarapu Swarna Priya. Effect of zinc and sulphur on growth and yield of groundnut (Arachis hypogaea) and yield validation using SPSS model. Pharma Innovation 2022;11(4):132-136.

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