The location of this research was carried out in the village of Sallasae, Bulukumba Regency with 184 km from the provincial capital of South Sulawesi, which is geographically located at the position of 120011'39.252"E-5022'24,108" S. This research was conducted in April-August 2021. Analysis of soil properties (physical, chemical and biological properties of soil) was carried out in the soil fertility laboratory, majoring in soil science, Faculty of Agriculture, Hasanuddin University. The study used a field observation survey approach to collect primary data (regional biophysical data and data on soil properties and characteristics). The soil quality indicators were approached through laboratory analysis.
Soil sampling and laboratory analysis
The sampling point of soil sampling using the purposive sampling method is the point that has been determined in the paddy field area at the level of application of organic fertilizer in different years (0 years-8 years). Soil sampling was repeated three times at each point with a 0-30 cm depth. Analysis of the soil description in the field uses two methods, namely the method of soil boring and soil profiling. Sampling points of soil sampling using purposive sampling method, namely the point has been determined in the paddy field area at the level of organic fertilizer application in different years (0 years - 8 years) with three repetitions at each point. Analysis of the description of the soil in the field uses two methods, namely the boring soil method, which is intended to determine the thickness of the soil solum in the paddy fields. While the soil morphology data through the description of the soil profile. Soil sampling was devoted only to the topsoil and subsoil layers with a thickness of 0-30 cm and analysis to determine soil quality. Soil quality analysis was based on physical, chemical and biological soil parameters. The selected chemical, physical and biological attributes of the soils were measured using the following standard methods: texture by hydrometer method, pH H2
O with soil: water suspension (1:2.5), soil organic carbon by Walkley and black method, total N by Kjeldahl method, available P by the Bray method (acidic soil) and Olsen method (alkaline soil), and Ca, Mg, Na, K and cation exchangeable capacity with 1 N ammonium acetate and 10% sodium chloride extraction. The number of soils microbs ware calculated by (Skinner, F.A., Jones, 1952) the total plate count (TPC) method.
Data analysis of paddy soil quality index
The soil quality index was calculated based on the criteria of (Seybold et al., 1998)
modified. The steps for calculating the index were carried out as follows: The weighted index was calculated by multiplying the weight of the soil function (weight 1) by rooting medium weight (weight 2) and root depth weight (weight 3). For example, the weight index for porosity is obtained by multiplying 0.40 (weight 1) by 0.33 (weight 2) by 0.60 (weight 3) and the result is 0.080. The score is calculated by comparing the observed data from the soil indicator and the assessment function (Sarbu and Pop, 2005). Scores ranged from 0 for poor condition and 1 for good condition. Scoring can be done through interpolation or linear equations by the set range based on values or the data obtained. According to Masto 2007, the linear scoring function (FSL) is:
Y = The linear score.
x = The value of soil properties.
x2 = The upper limit value.
x1 = The lower limit value.
Soil quality index is calculated by multiplying the weight index and the score of the indicators. Soil quality assessment uses the soil quality index equation (Vestergaard et al., 2017).
SQI = Soil quality index.
S = Scores on selected indicators.
Wi = Weight index.
n = Number of soil quality indicators.
Furthermore, the soil quality index values are categorized into five criteria classes, as shown in Table 1.
Spatial analysis analysis of rice soil quality distribution
Table 1: Paddy soil quality criteria based on its function.
Mapping of paddy soil quality index was made using spatial interpolation technique. The interpolation method chosen is Co-Kriging using the ARGIS 10.3 program.