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The present study titled “Optimization techniques in long term fertilizer trails: rice-rice system” was carried out using the experimental data from AICRP on Long Term Fertilizer Experiments(LTFE) in rice at RARS, Pattambi for a period from 1997-2017 with the objectives to study the effect of weather factors and plant nutrients on crop production, to study the dynamics of soil characters in relation to fertilizer treatment and to suggest appropriate statistical optimization tools with respect to yield and its forecast.
A significant upward linear trend was observed in annual average yield of Aiswarya variety of rice in kharif season (Virippu) while in rabi season (Mundakan)it was not so pronounced. Highest grain yield was obtained under T8 (100 percent NPK + FYM @ 5t/ha to the kharif rice) followed by T10(100 percent NPK + in situ growing of Sesbania aculeata, as green manure crop for kharif rice only) and T9 (50 percent NPK + FYM @ 5t/ha to the kharif rice only) in both the seasons. The most consistent treatment in kharif season was T7 (100 per cent N) whereas in rabi season it was T8. Exploratory data analysis through box plot revealed that grain yield in rabi season was higher and more consistent when compared to that of kharif season. Comparative performance of different treatments in both seasons exposed that grain yield response under T7 was significantly different at 1 per cent level in the two seasons owing to the fact that it was the most imbalanced treatment susceptible to even minute changes of weather variables and other factors.
The post hoc test effected for analysis of variance performed for each of the
experiments during both the seasons using DMRT revealed that superior treatment in all the experiments was T8. Analysis of groups of experiments also showed superiority of treatment T8 followed by T10 in both the seasons. The minute changes due to time variable were studied by splitting the whole period of study into three subperiods. It was found that in kharif season the treatments, years and their interaction effects were significant in all the three periods. During rabi season, the treatments and year interaction was absent for the first period. Repeated measures ANOVA revealed that86 per cent and 59 per cent of the variability in grain yield during kharif and rabi season respectively was explained by the time variable, when all the other variables were fixed.
Correlation analysis showed that in kharif season, significant positive effect was there for maximum temperature in the early stages of crop growth while sunshine hours and minimum temperature in early as well as later stages had significant positive influence on crop yield. Wind velocity and rainfall in early and later stages had negative impact on treatment responses. During rabi season, maximum temperature in the later stages had significant positive impact on treatment responses. Minimum temperature in early stages affected the crop yield negatively. Relative humidity in early and later stages had significant negative correlation with crop yield. Wind velocity had significant positive correlation with crop yield but towards flowering stage it had negative effect. Rainfall and number of rainy days during early vegetative stage had negatively affected treatment responses.
The influence of plant nutrients viz., N,P and K uptake on crop yield was quantified using a quadratic model. Studies on dynamics of soil organic carbon during kharif season showed a sharp decline during the initial years. Similarly, in rabi season there was decline but was less steep when compared to kharif season. The soil pH showed a decline towards the end of experimental period during kharif season whereas in rabi season it was stabilized towards the end. Time variable explained 66 per cent and 82 per cent of the variability in available P in kharif and rabi seasons respectively. In both the seasons, 94 per cent of the variability in available K in soil could be explained by the time variable.
Linear regression models using weather variables were found to give a reasonable fit for treatment responses during kharif season. The predictability of linear regression models could be improved using principal components as regressors in rabi season. Response curves were fitted using linear, quadratic and cubic models to forecast crop yield taking time as the predictor. For kharif season, cubic function was found to be a best fit to the treatment responses as they could capture fluctuating growth patterns over time.Compiling the results from aforesaid analyses, the optimal fertilizer treatment for rice was T8 (100 percent NPK + FYM @5t/ha to the kharif rice) followed by T10(100 percent NPK + in situ growing of Sesbania aculeata, as green manure crop for kharif rice only). Significant treatment x year interaction could be exposed through split plot analysis and the percentage variability in crop yield over the entire period of study was better quantified using repeated measures analysis. For kharif season, the linear regression models taking significant weather variables at different crop growth stages and response curves using time as the predictor provided reasonable fit to the yield data. For rabi season, linear regression models with principal components of weather variables as regressors gave better predictability.