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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Soil salinization and alkalization is a global problem restricting agricultural production. This study compared different fertilizer regimes (addition rate and application depth) on maize growth and soil quality in saline-alkali soil. Cow manure compost was applied with addition rates of 6, 12, 18 and 24 t·ha−1, and application depths of 5 and 20 cm, along with 0.6 t·ha−1 mineral fertilizer, and compared to a control treatment with only mineral fertilizer application. Results indicated that cow manure compost application could promote maize growth and ameliorate soil quality in saline-alkali soil. Increasing cow manure compost addition rate alleviated soil salinity better than alkalinity, while increasing compost application depth could reduce soil alkalinity more effectively than soil salt content. Moreover, increasing cow manure compost addition rate improved soil organic matter and soil nutrient content, thus promoting shoot growth and maize yield. However, increasing cow manure compost application depth could boost root growth, and further absorbed more nutrients to promote maize yield. Cow manure compost application increased maize yield by 6.0% to 28.4% with a maximum yield of 8.14 t·ha−1 in a treatment with compost addition rate of 24 t·ha−1 and application depth of 20 cm. Comprehensive evolution of soil quality, maize growth and maize yield, cow manure compost addition rate of 24 t·ha−1 and application depth of 20 cm along with 0.6 t·ha−1 mineral fertilizer application is suggested for use in saline-alkali soil.

Details

Title
Cow Manure Compost Promotes Maize Growth and Ameliorates Soil Quality in Saline-Alkali Soil: Role of Fertilizer Addition Rate and Application Depth
Author
Li, Shuyan; Liu, Zhijun; Jiao, Li; Liu, Zhanwei; Gu, Xuhan; Shi, Lianhui
First page
10088
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2706444971
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.