Soil quality assessment of yellow clayey paddy soils with different productivity

文献类型： 外文期刊

第一作者： Liu, Zhanjun

作者： Liu, Zhanjun;Zhou, Wei;Li, Shutian;Ai, Chao;Liu, Zhanjun;Shen, Jianbo

作者机构：

关键词： Minimum data set;PLFA;Soil quality evaluation;Soil quality index;Yellow clayey paddy soil

期刊名称：BIOLOGY AND FERTILITY OF SOILS （ 影响因子：6.432； 五年影响因子：6.332 ）

ISSN： 0178-2762

年卷期： 2014 年 50 卷 3 期

页码：

收录情况： SCI

摘要： Yellow clayey paddy soil is a typical soil with low productivity in southern China. However, a systematic evaluation of soil quality, which is important for improving sustainable land use management and increasing crop yields, has not been carried out for yellow clayey paddy soils. This study adopted two indicator selection methods, Total Data Set (TDS) and Minimum Data Set (MDS), to evaluate soil quality of high (HPPS), medium (MPPS) and low (LPPS) productive yellow clayey paddy soils and aimed to identify the factors limiting the rice productivity. Twenty-six soil parameters including physical, chemical and microbiological properties including phospholipid fatty acid analysis, were determined. Most measured soil parameters showed significant differences (P a parts per thousand currency signaEuro parts per thousand 0.05) between the different productivity paddy soils. Best values were always observed for many soil properties in HPPS, indicating a better nutrient supply and microbiological activity. Those 15 variables having significant differences were selected for principal component analysis, and arbuscular mycorrhizal fungi (AMF), microbial biomass carbon (MBC), available silicon (ASi), available potassium (AK) and total nitrogen (TN) were retained in the refined MDS. After scoring and weighting the selected indicators, a soil quality index (SQI) was calculated using the Integrated Quality Index equation. Based on the TDS method, the mean SQI scores of HPPS, MPPS and LPPS were 0.79, 0.71 and 0.57, respectively. Similarly, HPPS, MPPS and LPPS showed average SQI scores of 0.82, 0.67 and 0.50, respectively, using the MDS method. A significant correlation was observed between SQI and rice yield considering both TDS and MDS methods. Although the TDS method is more accurate, the MDS method can adequately represent the TDS method (r (2) = 0.85). Low levels of AK and TN were considered as the major constraints limiting the rice productivity for LPPS. All soil samples collected were rich in available P, Zn and Si, but deficient in available K, which may be the major constraint for the studied regions.

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