Comparison of Soil Quality Evaluation Methods and Their Relationships with Tea Yield in West Guilan Province

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Iran

2 MSc., Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Iran

3 Associated Professor, Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Iran

4 Agronomy& Technology Department, Tea Research Center, Horticultural Sciences Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Lahijan, Iran

Abstract

Developing an appropriate methodology to evaluate soil quality is urgent and has great implications in sustainable agricultural production. This study was carried out with the aim of determining the minimum data set (MDS) for soil quality evaluation and the comparison of soil quality evaluation methodsin tea cultivation with different productivities in west Guilan province. Sixty-six soil samples were collected from 0 to 30 cm depth. The green tea leaves were harvested at a 2 m2 plot at each site. In this research, using the principal component analysis (PCA) method, among 15 physical, chemical and biological soil indicators as total data set (TDS), available potassium, organic carbon, pH, available phosphorus, available zinc and nematode were determined as the MDS. Then, the soil quality of tea cultivation with different productivities was evaluated by Integrated Quality Index(IQI) and Nemoro Quality Index (NQI) using two linear and non-linear scoring methods (LS and NLS) and two soil indicator selection approaches, a Total Data Set (TDS) and a Minimum Data Set (MDS). The results showed that all mean soil quality indices of the high productivity tea cultivationexcept IQI-NLSMDSand NQI-NLSMDS were significantly higher than low productivity tea cultivation. It was found that linear scoring methods are superior to non-linear. So that, the correlations between soil quality indices and crop yields for the IQI-LS and NQI-LS methods were Stronger than in the other methods in both TDS (R2=0.55 and 0.54, respectively) and MDS (R2=0.45 and 0.46, respectively). The correlation between TDS and MDS evaluated by the IQI–LS (R2=0.80) were higher than that by NQI–LS (R2=0.59)

Keywords


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