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DOI | 10.1016/j.scitotenv.2018.10.106 |
Integrating management information with soil quality dynamics to monitor agricultural productivity | |
Obade, Vincent de Paul1,2 | |
发表日期 | 2019 |
ISSN | 0048-9697 |
EISSN | 1879-1026 |
卷号 | 651页码:2036-2043 |
英文摘要 | Sustainably utilizing global resources is critical for ensuring soil security which is pertinent for biomass production, climate change mitigation, environmental quality, biodiversity conservation and thus human wellbeing. A plethora of soil quality assessmentmetrics encapsulated in different concepts exist, with each typically biased towards identifying the interrelationship between agricultural production and specific physical, chemical or biological soil attributes. Because of diversity in soil classifications and crop requirements, considerable variation exist between these metrics making it difficult for end-users to select a suitable method. Here, Partial Least Squares Regression (PLSR) method is used to integrate the physical and chemical soil properties into a Soil Quality Index (SQI) which is then used to evaluate soil quality dynamics vis-a-vis crop yields over two growing seasons. Field data was acquired from 5 sites under No-Till (NT), Conventional Till (CT) management and Natural Vegetation (NV) land use. This SQI was computed under the hypothesis that site specific soil physico-chemical attributes depended on soil type, management, and depth. Under CT management P-w (Pewamo silty clay loam) had the highest soil quality; KbA (Kibbie fine sandy loam) soils had higher quality under NT management; whereas CtA (Crosby Celina silt loams) had relatively higher quality under NV land use. Soil bulk density (rho(b)), Soil Organic Carbon (SOC), Available Water Content (AWC) and Electrical Conductivity (EC) were the significant soil parameters influencing soil quality. The correlation between SQI and corn (Zea mays) yields was 0.6, whereas SQI and Soybean (Glycine max (L.) Merr.) yield was 0.9. Future research will evaluate SQI dynamics vis-a-vis socio-economic indicators and key climate variables. (C) 2018 Elsevier B.V. All rights reserved. |
WOS研究方向 | Environmental Sciences & Ecology |
来源期刊 | SCIENCE OF THE TOTAL ENVIRONMENT |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/93434 |
作者单位 | 1.Cal Poly San Luis Obispo, BioResource & Agr Engn Dept, 1 Grand Ave, San Luis Obispo, CA USA; 2.Ohio State Univ, Sch Environm & Nat Resources, 2021 Coffey Rd, Columbus, OH 43210 USA |
推荐引用方式 GB/T 7714 | Obade, Vincent de Paul. Integrating management information with soil quality dynamics to monitor agricultural productivity[J],2019,651:2036-2043. |
APA | Obade, Vincent de Paul.(2019).Integrating management information with soil quality dynamics to monitor agricultural productivity.SCIENCE OF THE TOTAL ENVIRONMENT,651,2036-2043. |
MLA | Obade, Vincent de Paul."Integrating management information with soil quality dynamics to monitor agricultural productivity".SCIENCE OF THE TOTAL ENVIRONMENT 651(2019):2036-2043. |
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