Assessing the Alteration of Soil Quality under Long-Term Fertilization Management in Farmland Soil: Integrating a Minimum Data Set and Developing New Biological Indicators

Author:

Li Peng12,Zhang Yue1,Li Chengzhe1,Chen Zihan1,Ying Duo3,Tian Shanyi4ORCID,Zhao Gen5,Ye Dongmei6,Cheng Chihang1,Wu Choufei1,Zhang Liqin1,Jiao Jiaguo2,Hu Feng2

Affiliation:

1. Key Laboratory of Vector Biology and Pathogen Control of Zhejiang Province, College of Life Sciences, Huzhou University, Huzhou 313000, China

2. College of Resources and Environmental Sciences, Nanjing Agricultural University, Weigang, No. 1, Nanjing 210095, China

3. Institute of Maize and Featured Upland Crops, Zhejiang Academy of Agricultural Sciences, Dongyang 322100, China

4. College of Resources and Environment, Southwest University, Chongqing 400716, China

5. Huzhou Academy of Agricultural Sciences, Huzhou 313000, China

6. Zhejiang Zhongce Geospatial Technology, Co., Ltd., Huzhou 313200, China

Abstract

The key role of soil quality improvement in achieving sustainable agricultural development based on highly intensive use of farmland is increasingly being recognized, as is the ponderance of suitable evaluation of the soil quality. The overarching goal of this study was to determine an accurate assessment framework by the comparison of the scoring function (linear and non-linear) and integration method (area and weighted additive), which integrally evaluates the soil quality of an eleven-year field fertilization experiment (including CK, no fertilizer; CF, conventional fertilization; SF, formulated fertilization; SFO, SF with organic fertilizer). Thirty-three properties, including eighteen physiochemical-related and fifteen biological-related properties, associated with soil functions were measured as potential soil quality indicators, and the soil multifunctionality (SMF) was applied to validate the soil quality indices (SQIs). Principal component analysis and relationship analysis were used with indicators sensitive to management to determine a minimum data set (MDS). The results showed that the electrical conductivity, large macroaggregate-associated total nitrogen, small macroaggregate-associated organic carbon, carbon fixation, and enzyme activities of phenol oxidase and cellulase were chosen as the MDS. All the SQIs were significantly correlated with the SMF (p < 0.05). The fertilization strategies affected most indicators in different ways, and the index developed using the non-linear function and weighted additive integration method (SQI-NL) had the best sensibility and discriminability. The SQI value with the SQI-NL-MDS method was higher following the fertilization treatments than that of no fertilizer (p < 0.05), and the treatment of the organic fertilizer had the highest SQI value (0.66). Soil quality evaluation in long-term fertilized farmland suggested that the soil quality constraints between treatments of synthetic and organic fertilizer are related to the soil functions of nutrient cycling and sustain biological activity due to their higher contribution rates to the SQI in the organic fertilizer treatment, which provides insights into ways to reduce the gap in soil quality. The framework method can provide an accurate quantitative tool for the evaluation of soil quality from the target indicators by bridging management objectives and field-level actions.

Funder

Key R&D Program of Jiangsu province, China

Talent Fund of Huzhou University, China

Publisher

MDPI AG

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