Optimisation of agricultural input application to enhance the crop quality and yield quantity in paddy under precision farming

Recently, technological advances have converged to ensure the quality and quantity of crop yield on a site-specific basis. The aim of the present work was to adapt precision farming techniques in paddy under Indian farming system using modern tools such as apparent electrical conductivity (ECa) mappers, differential global positioning systems, software procedures (univariate and multivariate geostatistical modelling), principal component analysis and cluster analysis. A field experiment was conducted on paddy (Oryza sativa) in the research farm fields of Punjab Agriculture University, Ludhiana (Punjab), India. The results revealed that management units can easily be drawn by assessing spatio-temporal factors using geospatial technologies. Three zones were identified and validated using Fuzzy-c means and indices, respectively, to enhance efficiency and optimise input applications that can produce best quality and quantity of the yield. High-resolution and geo-referenced digital spatial variability maps of different yield-limiting factors (soil moisture, pH, ECa, phosphorous and potassium) were generated to assist decision-making in various agronomic practices. The complexity in analysing the spatio-temporal factors affecting yield were correlated; yield showed a positive correlation with ECa, pH, soil temperature, and available phosphorous and potassium. The yield was negatively correlated with soil moisture and soil real dielectric.