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Onion Yield with Web-Based Irrigation Scheduling and Subsurface Drip Irrigation as Opposed to Trench Irrigation | OMICS International| Abstract
ISSN: 2329-8863

Advances in Crop Science and Technology
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  • Review   
  • Adv Crop Sci Tech 2023, Vol 11(4): 4
  • DOI: 10.4172/2329-8863.1000570

Onion Yield with Web-Based Irrigation Scheduling and Subsurface Drip Irrigation as Opposed to Trench Irrigation

Kenjal*
Department of Science and technology, Albania
*Corresponding Author : Kenjal, Department of Science and technology, Albania, Email: ken@gmail.com

Received Date: Apr 03, 2023 / Published Date: Apr 28, 2023

Abstract

Selecting the right irrigation method will be beneficial to manage limited water supplies and increase crop profitability. The overall objective of this study was to evaluate the effect of subsurface drip irrigation and trench irrigation on onion yield and irrigation water use efficiency. This study was performed as split plots for two sites with two SDI and trench irrigation treatments and three replicates for each treatment. The total onion yield obtained with the SDI system was 93% higher than that obtained with the trench irrigation system. Onion size was 181% larger in the SDI system than in the bed system at both sites. The productivity at the giant size is also higher. At one site, the yield of giant onion was 206% higher than that of rowed onions, while at another site the onion beds did not produce giant onions and SDI had some yield. It was concluded that drip irrigation systems more than doubled yield and increased onion size while using almost half the amount of water. This is because SDI allows for more frequent watering and smaller depth with higher irrigation efficiency than trench irrigation.

Citation: Kenjal (2023) Onion Yield with Web-Based Irrigation Scheduling and Subsurface Drip Irrigation as Opposed to Trench Irrigation. Adv Crop Sci Tech 11: 570. Doi: 10.4172/2329-8863.1000570

Copyright: © 2023 Kenjal. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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