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Evaluation Of Split Application Of Potassium And Nitrogen On The Performance Of Winter Maize Hybrid At Rampur, Chitwan

Author

Listed:
  • Kamal Ghimire

    (Agriculture and Forestry University, Rampur, Chitwan, Nepal)

  • Nisha Bhandari

    (Agriculture and Forestry University, Rampur, Chitwan, Nepal)

  • Bamdev Regmi

    (Agriculture and Forestry University, Rampur, Chitwan, Nepal)

  • Manshi Jaiswal

    (Agriculture and Forestry University, Rampur, Chitwan, Nepal)

Abstract

Nutrient management practices significantly impact crop productivity and economics. A field experiment was conducted in the winter season of 2019-2020 in the sub-tropical climate of inner Terai, Nepal, using a split-plot design with three replications. The main plots included three potassium application methods: 0 kg K2O ha-1, 60 kg K2O ha-1 as basal, and 60 kg K2O ha-1 in two splits. The subplots involved five nitrogen application methods: 0 kg N ha-1, and 180 kg N ha-1 applied in different splits. Data on growth, yield attributes, yield, economics, nutrient use, uptake, and efficiency were collected. The results showed that grain and stover yield did not vary with different potassium application methods. The highest grain yield (6896.40 kg ha-1) was achieved with 90 kg N ha-1 at 15 DAS followed by 45 kg N ha-1 each at knee-high and tasseling stages. This yield was statistically similar to the method with 90 kg N ha-1 at basal and 45 kg N ha-1 each at knee-high and tasseling stages. Overall, yield attributes were similar across nitrogen treatments. The highest nutrient uptake was observed with the same nitrogen application method that produced the highest yield. Thus, applying 90 kg N ha-1 at 15 DAS followed by 45 kg N ha-1 at knee-high and tasseling stages is recommended for similar soils and climates as in Chitwan.

Suggested Citation

  • Kamal Ghimire & Nisha Bhandari & Bamdev Regmi & Manshi Jaiswal, 2024. "Evaluation Of Split Application Of Potassium And Nitrogen On The Performance Of Winter Maize Hybrid At Rampur, Chitwan," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 6(2), pages 129-146, October.
    • Handle: RePEc:zib:zbnbda:v:6:y:2024:i:2:p:129-146
    DOI: 10.26480/bda.02.2024.129.146
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