MSc

Rice (Oryza saiva L.) is vulnerable to unfavourable weather events and climate conditions. Despite technological advances such as improved crop varieties and irrigation systems, weather and climate are important factors which play a significant role in rice production.
The present investigation “Validation of CERES model to calibrate the genetic coefficients of rice (Oryza sativa L.)” was carried out in the Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2013-15, to determine the crop weather relationship, to validate the CERES (Crop Environment Resource Synthesis) -Rice model and to calibrate the genetic coefficients for rice. The field experiment was conducted at Agricultural Research Station, Mannuthy during the kharif season of 2014. Split plot design was adopted with five dates of planting viz., 5th June, 20th June, 5th July, 20th July and 5th August as the main plot treatments and two varieties viz., Jyothi and Kanchana as the sub plot treatments. The number of replications for the experiment was four.
Different growth and yield characters viz., plant height, dry matter accumulation, number of panicles, spikelets, filled grains, 1000 grain weight, grain yield, straw yield and duration of different crop growth phases were recorded. The daily weather parameters like maximum and minimum temperatures, forenoon and afternoon relative humidity, forenoon and afternoon vapour pressure deficits, bright sunshine hours, pan evaporation, wind speed, rainfall and rainy days were recorded during the entire crop growing period, to determine the crop weather relationship.
The maximum temperature showed an increasing trend towards the late plantings. The minimum temperature, afternoon and forenoon relative humidity, rainfall and rainy days were found to be higher in early planting dates compared to late plantings. Plant height, dry matter accumulation, yield and yield attributes were highly variable among the different planting dates. Yield and yield attributes were influenced by various weather parameters experienced by the crop during different dates of planting. Days taken to complete maturity got reduced with delay in planting dates in both the varieties. Jyothi variety took more days to complete different phenophases, compared to Kanchana. The highest yield in Jyothi was
recorded for June 5th planting, whereas June 20th planted crop recorded highest yield in Kanchana.
The various growth indices such as leaf area index, leaf area ratio, leaf area duration, absolute growth rate, crop growth rate, net assimilation rate and relative growth rate were worked out to study the crop growth and development. During the early growth stages, these growth indices showed an increasing trend and decreasing trend was noticed in the later stages. To determine the critical weather elements affecting the crop growth, correlation analysis was performed. It was observed that crop duration decreased with increase in temperature and bright sunshine hours, whereas, the forenoon and afternoon relative humidity, rainfall and rainy days showed positive influence on crop duration. Multiple linear regression equations were fitted, to predict the grain yield based on weather variables.
A crop model can simulate the actual system of field in the lab. CERES-Rice model has been widely used to understand the relationship between rice and its environment. Crop performance in terms of genetic coefficients used in the model can be used as a tool for strategic decision making. The crop genetic coefficients that influence the occurrence of developmental stages in the CERES-Rice models were derived and validated, to achieve the best possible agreement between the simulated and observed values. Calibration was done with independent data sets of two rice varieties viz., Jyothi and Kanchana for different genetic coefficients, which characterize the performance of the crop. The results of simulation studies in respect of phenophases and yield of rice were compared with the observed values. Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and D-stat (index of agreement) were used as model accuracy measures. Predicted yield and phenology of both rice varieties, Jyothi and Kanchana under different planting dates were reasonably close to the observed values, as indicated by the RMSE, MAPE and D-stat values.