2.4. Statistical analysis
The SPSS16.0 (2001) software was used for descriptive statistical and correlation analysis. Pearson product moment correlation test was applied to assess the relationship among the soil variables. The sampling adequacy of individual and set variables were computed by using Kaiser-Meyer-Olkin test (>0.5) and Bartlett’s test of sphericity (P <0.05). The PCA was computed to derive the most identical soil indicators. To assess the long-term sugarcane monocropping impact, two approaches were employed. First, the percentage alter in the individual soil fertility parameters under different cane producing zones of Uttar Pradesh to assess whether soil fertility parameters were declines or improve. Second, Nutrient Index (NI) was calculated using parameters following the Ramamurthy & Bajaj (1969) approach. A Nutrient Index is an estimate of the % distribution of soil samples across categories: low, medium and high classes of nutrient status as per the soil test value interpretation (Amara et al., 2017) by using: Nutrient Index (NI) = [(NL × 1) + (NM × 2) + (NH × 3)/NT]
where, ‘NL, ‘NM’ and ‘NH’ typify the number of samples falling in the low, medium and high class of nutrient status, respectively, and ‘NT’ is the total number of samples analyzed across the cane producing zones of Uttar Pradesh. The NI levels were computed according to low (<1.67), medium (1.67-2.33) and high (>2.33) category. Maps showing geographical locations of the soil sampling site were created through Google map.