Development of Novel Predictive Models For Estimation of Nitrogen Fixation Under Cultural and Field Conditions Using R Software

Farmers apply chemical fertilizers in the field soil to provide nitrogen and phosphorus nutrients for improving growth and yield of crop plants to provide food for ever-increasing human population. But, injudicious use of these chemical fertilizers results in environmental pollution and causes public health hazards. Recently, various nitrogen-fixing microorganisms are used as biofertilizers to reduce the application of chemical fertilizers. However, the survival and nitrogen (N2) fixation capacity of these microorganisms is adversely affected under stress conditions in recent changing agroclimatic scenario. In the present study, predictive models were developed to study biological nitrogen fixation (BNF) behaviour of rhizobia in response to exogenous nitrogen (N) level conditions under culture as well as in the soil using R software. With increase in concentration of ammonium (NH4+) or nitrate (NO3-) (represented along X axis in the graph) in the cultural medium, there is sequential fall in nitrogenase activity of Rhizobium strain 32H1 (on Y axis). Under field conditions, the comparisons of fertilizer addition showed that N2 fixation was partially suppressed after addition of 150 kg N per hactare in faba bean (Vicia faba) and chickpea (Cicer arietinum) species under glasshouse pots trial conditions. Predictive models were developed using R software to indicate the approximate values of nitrogen fixation in chickpea and faba bean under field and glasshouse conditions with application of different doses of fertilizers. These linear and non-linear predictive models could be applied to predict behaviour of nitrogen-fixing rhizobia in response to available nitrogen level under cultural as well as field conditions.