Exchangeable acidity characteristics of farmland black soil in northeast China

IF 3.1 2区 农林科学 Q2 SOIL SCIENCE Geoderma Regional Pub Date : 2024-08-13 DOI:10.1016/j.geodrs.2024.e00852
Wenrui Zhao , Wenyou Hu , Feng Zhang , Yangxiaoxiao Shi , Yadan Wang , Xueqing Zhang , Tianhua Feng , Zhineng Hong , Jun Jiang , Renkou Xu
{"title":"Exchangeable acidity characteristics of farmland black soil in northeast China","authors":"Wenrui Zhao ,&nbsp;Wenyou Hu ,&nbsp;Feng Zhang ,&nbsp;Yangxiaoxiao Shi ,&nbsp;Yadan Wang ,&nbsp;Xueqing Zhang ,&nbsp;Tianhua Feng ,&nbsp;Zhineng Hong ,&nbsp;Jun Jiang ,&nbsp;Renkou Xu","doi":"10.1016/j.geodrs.2024.e00852","DOIUrl":null,"url":null,"abstract":"<div><p>Exchangeable aluminum (Exc-Al), an often overlooked yet indispensable soil parameter, predominantly contributes to soil exchangeable acidity. In this study, we utilized data from 53 sets of surface and subsurface black soil characteristics, including Exc-Al, exchangeable acid (Exc-acid), pH, soil organic matter (SOM), and available and total nutrient levels, to develop a neural network prediction model for estimating Exc-Al and Exc-acid in the black soil area of northeast China. The deterministic neural network model (NNM) was employed to predict Exc-Al and Exc-acid contents in 690 sets of surface and subsurface farmland soil samples with unknown Exc-Al and Exc-acid values. Subsequently, a black soil exchangeable acidity map for northeast China was generated through spatial interpolation. Our results revealed that the average Exc-Al and Exc-acid contents in the 53 surface soils were 0.82 and 0.93 cmol kg<sup>−1</sup>, respectively, while those in the corresponding subsurface soils were 0.58 and 0.70 cmol kg<sup>−1</sup>, respectively. Multi-layer perceptron (MLP) neural networks effectively simulated Exc-Al and Exc-acid contents in the surface and subsurface black soils, with calibrated determination coefficients (<em>R</em><sub><em>adj</em></sub><sup><em>2</em></sup>) of 0.95–0.96, relative root mean square errors (<em>rRMSE</em>) of 17.3%–24.8%, and statistical significance <em>α</em> at 0.001. The MLP estimations and spatial interpolations revealed that 2.0% and 17.6% of the surface black soil area, and 0% and 3.7% of the subsurface soil area exhibited Exc-Al content exceeding 2.0 and 1.0 cmol kg<sup>−1</sup>, respectively. Furthermore, 6.7% and 24.9% of the surface black soil area, and 0% and 6.3% of the subsurface soil area showed Exc-acid content exceeding 2.0 and 1.0 cmol kg<sup>−1</sup>, respectively. These findings break the limitation of relying solely on soil pH as the unique indicator, enrich our knowledge of black soil exchangeable acidity, and enhance our understanding of the black soil acidity status in northeast China.</p></div>","PeriodicalId":56001,"journal":{"name":"Geoderma Regional","volume":"38 ","pages":"Article e00852"},"PeriodicalIF":3.1000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoderma Regional","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352009424000993","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Exchangeable aluminum (Exc-Al), an often overlooked yet indispensable soil parameter, predominantly contributes to soil exchangeable acidity. In this study, we utilized data from 53 sets of surface and subsurface black soil characteristics, including Exc-Al, exchangeable acid (Exc-acid), pH, soil organic matter (SOM), and available and total nutrient levels, to develop a neural network prediction model for estimating Exc-Al and Exc-acid in the black soil area of northeast China. The deterministic neural network model (NNM) was employed to predict Exc-Al and Exc-acid contents in 690 sets of surface and subsurface farmland soil samples with unknown Exc-Al and Exc-acid values. Subsequently, a black soil exchangeable acidity map for northeast China was generated through spatial interpolation. Our results revealed that the average Exc-Al and Exc-acid contents in the 53 surface soils were 0.82 and 0.93 cmol kg−1, respectively, while those in the corresponding subsurface soils were 0.58 and 0.70 cmol kg−1, respectively. Multi-layer perceptron (MLP) neural networks effectively simulated Exc-Al and Exc-acid contents in the surface and subsurface black soils, with calibrated determination coefficients (Radj2) of 0.95–0.96, relative root mean square errors (rRMSE) of 17.3%–24.8%, and statistical significance α at 0.001. The MLP estimations and spatial interpolations revealed that 2.0% and 17.6% of the surface black soil area, and 0% and 3.7% of the subsurface soil area exhibited Exc-Al content exceeding 2.0 and 1.0 cmol kg−1, respectively. Furthermore, 6.7% and 24.9% of the surface black soil area, and 0% and 6.3% of the subsurface soil area showed Exc-acid content exceeding 2.0 and 1.0 cmol kg−1, respectively. These findings break the limitation of relying solely on soil pH as the unique indicator, enrich our knowledge of black soil exchangeable acidity, and enhance our understanding of the black soil acidity status in northeast China.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
中国东北地区农田黑土的可交换酸度特征
可交换铝(Exc-Al)是一个经常被忽视但又不可或缺的土壤参数,主要影响土壤的可交换酸度。在本研究中,我们利用 53 组地表和地下黑土特征数据,包括 Exc-Al、可交换酸(Exc-acid)、pH 值、土壤有机质(SOM)、可利用养分和总养分水平,建立了一个神经网络预测模型,用于估算中国东北黑土区的 Exc-Al 和 Exc-acid。采用确定性神经网络模型(NNM)预测了690组Exc-Al和Exc-acid含量未知的地表和地下农田土壤样品。随后,通过空间插值生成了东北黑土可交换酸度图。结果表明,53 个表层土壤的平均Exc-Al 和Exc-acid 含量分别为 0.82 和 0.93 cmol kg-1,而相应的地下土壤的平均Exc-Al 和Exc-acid 含量分别为 0.58 和 0.70 cmol kg-1。多层感知器(MLP)神经网络有效地模拟了地表和地下黑土中的Exc-Al和Exc-酸含量,其校正确定系数(Radj2)为0.95-0.96,相对均方根误差(rRMSE)为17.3%-24.8%,统计显著性α为0.001。通过 MLP 估算和空间插值发现,分别有 2.0% 和 17.6% 的表层黑土面积以及 0% 和 3.7% 的地下土壤面积的 Exc-Al 含量超过 2.0 和 1.0 cmol kg-1。此外,分别有 6.7% 和 24.9% 的表层黑土和 0% 和 6.3% 的表层下层土壤的 Exc-acid 含量超过 2.0 和 1.0 cmol kg-1。这些发现打破了单纯以土壤pH值作为唯一指标的局限性,丰富了我们对黑土可交换酸度的认识,增进了我们对东北黑土酸度状况的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Geoderma Regional
Geoderma Regional Agricultural and Biological Sciences-Soil Science
CiteScore
6.10
自引率
7.30%
发文量
122
审稿时长
76 days
期刊介绍: Global issues require studies and solutions on national and regional levels. Geoderma Regional focuses on studies that increase understanding and advance our scientific knowledge of soils in all regions of the world. The journal embraces every aspect of soil science and welcomes reviews of regional progress.
期刊最新文献
Wind erosion escalation in western Slovakia driven by climate and land use and land cover shifts Content and quality of soil organic matter in topsoils under different tundra vegetation in central Spitsbergen (High Arctic) Microbial communities of urban and industrial polluted soils in the Russian Arctic Higher temperature accelerates carbon cycling in a temperate montane forest without decreasing soil carbon stocks Co-amendment of silicate dust and manure improves soil health metrics and crop yield in coarser-textured more than medium-textured soils
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1