Assessing soil quality indices and their relationships with rice yield in paddy fields of central Guilan province

Assessing soil quality and balancing between crop production and quality of natural resources are essential issues in sustainable soil management for agricultural and natural resource protection. In agricultural fields for optimum management and maximum economic productivity, knowledge of the factors affecting the soil quality is necessary. Also, determining the appropriate method for soil quality evaluation is important for sustainable soil management and soil degradation prediction. This study was carried out with the aim of assessing soil quality of paddy fields, determining the minimum data set for soil quality evaluation and investigating the effect of soil quality index using different methods on rice yield in Pirbazar region of Guilan province. Based on the mean annual rice yield, the selected paddy fields were divided into low (4.6 t ha-1) productivity. Sixty soil samples were collected from 0 to 30 cm depth. The rice products were harvested at a 1 m2 plot at each site. In this research, using the principal component analysis (PCA) method, among 20 physical, chemical and biological soil indicators as total data set (TDS), 6 indicators were selected for the minimum data set (MDS). Then, the soil quality of high and low productivity paddy fields was evaluated by simple additive integrated quality index (IQISA) and weighted additive integrated quality index (IQIWA) in two collections of soil properties include MDS and TDS. To evaluate soil quality of paddy fields, an MDS was established with organic carbon, total nitrogen, available potassium, clay percentage and urease activity and these explained about 67% of the soil quality variability. The significant differences were found between the soil quality index of low and high productivity paddy fields when IQIWA and IQISA were developed based on MDS. So that, the mean IQISA-MDS and IQIWA-MDS of the high productivity paddy fields (0.84 and 0.89, respectively) were higher than low productivity paddy fields (respectively 0.78 and 0.80, respectively). Additionally, data indicated that IQISA-MDS and IQIWA-MDS were most strongly correlated with crop yield, the correlation coefficient ranged between 0.44–0.54. Significant differences between the soil quality indices based on MDS for low and high productivity paddy fields indicated that the MDS more efficiently shows the difference of soil quality between paddy fields with different productivity. The significant correlation between IQISA-MDS and IQIWA-MDS indices with rice yield indicated that an MDS with a limited number of indicators was carefully selected and effectively evaluated the status of soils as a rice production medium. Therefore, using an MDS can save time and money and assess the reliable soil quality indices of paddy fields in the study area.