Research Methodology

Fuzzy Analytic Hierarchy Process

A multi-criteria decision making (MCDM) framework for evaluating soil health using eight key indicators with expert-derived fuzzy weights.

Overview

The Soil Health Diagnostic System (SHDS) employs the Fuzzy Analytic Hierarchy Process (FAHP) as its core decision-making model. FAHP extends the classical AHP method developed by Thomas L. Saaty by incorporating fuzzy set theory to handle the inherent uncertainty and imprecision in expert judgments. The system evaluates soil health through eight critical indicators, each assigned a weight derived from expert pairwise comparisons expressed as triangular fuzzy numbers. The final Soil Health Index (SHI) provides a single composite score that classifies soil into one of seven health categories.

Soil Health Indicators

IndicatorMinMaxOptimal RangeUnitFAHP Weight
Soil pH08.56 - 7.5-0.215391
Nitrogen (N)1050050 - 250mg/kg0.185427
Phosphorus (P)1020020 - 100mg/kg0.159677
Potassium (K)1040050 - 200mg/kg0.129830
EC040 - 2dS/m0.088770
Temperature05010 - 30°C0.091019
Moisture010020 - 80%0.062241
Humidity010030 - 70%0.067645

Weight Distribution

Soil pH
21.54%
Nitrogen (N)
18.54%
Phosphorus (P)
15.97%
Potassium (K)
12.98%
EC
8.88%
Temperature
9.10%
Moisture
6.22%
Humidity
6.76%

FAHP Algorithm Pipeline

1

Define Soil Health Indicators

Eight soil health indicators are identified as evaluation criteria: pH, Nitrogen (N), Phosphorus (P), Potassium (K), Electrical Conductivity (EC), Temperature, Moisture and Humidity. Each indicator has defined acceptable ranges and optimal values based on agronomic research.

2

Construct Fuzzy Pairwise Comparison Matrix

Expert judgments are collected to compare each pair of indicators using triangular fuzzy numbers (l, m, u). The 8x8 fuzzy comparison matrix captures the relative importance of each indicator pair with inherent uncertainty modeled through fuzzy sets.

3

Compute Fuzzy Geometric Means

For each row of the fuzzy comparison matrix, the geometric mean of all fuzzy numbers is calculated. This produces a single fuzzy number per indicator that represents its aggregate comparison against all other indicators.

4

Calculate Fuzzy Weights

Fuzzy weights are derived by normalizing the fuzzy geometric means. Each indicator receives a triangular fuzzy weight (l, m, u) representing its relative importance in the overall soil health assessment.

5

Defuzzification (Center of Area)

The triangular fuzzy weights are converted to crisp (single-value) weights using the Center of Area method: W = (l + m + u) / 3. A consistency ratio check ensures the comparison matrix is logically consistent (CR < 0.10).

6

Soil Health Index Computation

Each indicator value is normalized to a 0-1 scale. The Soil Health Index (SHI) is computed as the weighted sum of all normalized indicator scores. The SHI is then classified into one of seven health categories.

Health Classification

The Soil Health Index (SHI) is a weighted composite score ranging from 0 to 1. It is mapped to seven health categories based on the following thresholds:

Very Poor

SHI >= 0.0 and < 0.2

Poor

SHI >= 0.2 and < 0.4

Below Average

SHI >= 0.4 and < 0.6

Average

SHI >= 0.6 and < 0.7

Above Average

SHI >= 0.7 and < 0.8

Good

SHI >= 0.8 and < 0.9

Excellent

SHI >= 0.9

0.00.51.0

Crop Recommendations

Excellent
Rice, Maize, Vegetables, Fruit orchards, Cash crops

Soil is in optimal condition for all major crops. Maintain current practices.

Good
Rice, Maize, Legumes, Root vegetables, Oilseeds

Suitable for most crops. Minor nutrient supplementation may benefit yields.

Above Average
Rice, Maize, Pulses, Leafy vegetables

Balanced soil. Regular monitoring recommended for sustained productivity.

Average
Rice, Millet, Hardy legumes, Root crops

Consider organic amendments to improve soil structure and nutrient content.

Below Average
Millet, Sorghum, Hardy pulses

Soil improvement needed. Apply compost and consider cover cropping.

Poor
Drought-resistant grains, Native grasses

Significant soil rehabilitation required. Prioritize organic matter addition.

Very Poor
Limited to soil-building cover crops

Intensive soil restoration needed before productive cultivation. Use green manure crops.

References

  1. Saaty, T.L. (1980). The Analytic Hierarchy Process. McGraw-Hill, New York.
  2. Chang, D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655.
  3. Buckley, J.J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233-247.
  4. Doran, J.W. and Parkin, T.B. (1994). Defining and assessing soil quality. In Defining Soil Quality for a Sustainable Environment, SSSA Special Publication No. 35, pp. 1-21.
  5. Karlen, D.L. et al. (1997). Soil quality: A concept, definition and framework for evaluation. Soil Science Society of America Journal, 61(1), 4-10.
  6. Andrews, S.S., Karlen, D.L. and Cambardella, C.A. (2004). The Soil Management Assessment Framework: A quantitative soil quality evaluation method. Soil Science Society of America Journal, 68(6), 1945-1962.