Growth and yield estimation of rice based on satelite data and land based observation using growing degree days(GDD)

Abstract

Rice, the primary staple food for approximately 3.5 billion people worldwide, is supporting food security in numerous countries through irrigated as well as rainfed rice ecosystems. Elevated temperatures may lead to a decline in productivity, impacting the ability to feed future generations. To address this challenge, the utilization of temperature-based agrometeorological indices, such as Growing Degree Days (GDD) supported by satellite data, emerges as a valuable tool for predicting crop growth and yield across large areas. Growth and yield estimation of rice based on satellite data and land-based observation using growing degree days (GDD) conducted in the Department of Agricultural Meteorology, College of Agriculture, Vellanikkara during the year 2022-23 with the objective of establishing a relationship between GDD and performance of rice crop and to examine the possibilities of remote sensing tools to evaluate plant and GDD interactions to a wider area. The field experiment was conducted in two medium-duration rice varieties, Uma and Pournami, at the Regional Agricultural Research Station, Kumarakom during mundakan season of 2022-23, and was laid out in Randomized Block Design. The treatments consist of five dates of planting, viz. D1-5th September, D2-20th September, D3-5th October, D4-20th October, D5-5th November, with four replications. Various biometric observations, heat unit accumulations, yield and yield attributes were recorded at definite intervals. The study on phenology revealed that crop duration decreased from early planting to late planting in both varieties. Grain yield was significantly affected by the planting dates in both varieties. D1 planting produced the highest grain yield in both Uma (4388.8 kg ha-1) and Pournami (3715 kg ha-1) varieties, while D5 planting produced the lowest yield in Uma (2118.8 kg ha-1) and Pournami (2313.8 kg ha-1). The yield attributes were also significantly affected by planting dates and showed similar trend. Heat units like GDD and Photothermal units (PTU) were found to reduce in delayed planting. D2 recorded the highest GDD in both Uma (2055°C days) and Pournami (2090°C days). The lowest GDD was recorded by D5 planting in Uma (1820°C days) and Pournami (1872°C days). A linear regression equation was developed to predict yield for both varieties using GDD as independent variables. The results indicated that the Uma variety performed better than Pournami variety in the field experiment with respect to plant characters and yield. Palakkad district and Kuttanad. MODIS LST product (MOD11A2) 8-day composite was used to retrieve day and night land surface temperature for the mundakan rice growing season of 2022-23. A linear relationship was developed with MODIS LST and air temperature data obtained from the ground station. The developed relationship was then validated to ensure its accuracy and reliability. Daily maximum and minimum air temperature was estimated from MODIS LST using the linear equation during the crop season for the study locations. GDD was calculated, and it was employed to estimate the number of days required to attain various phenological stages of the mundakan rice. Validation of the predicted number of days in comparison with the observed showed a good relationship with R2 values of 0.82, 0.82, 0.80, 0.87, 0.86, and 0.81, and RMSE 0.42, 0.65, 0.72, 0.74, 0.84, 1.33 respectively, for the six phenophases of the rice crop. Further studies were done to assess the potential of GDD as an agroclimatic indicator for climate change in selected 9 locations in Palakkad and Kuttanad. The study attempted to understand the spatial and temporal distribution of GDD of mundakan rice over the past 30 years (1993-2022). The 30-year period were divided into six pentads. Additionally, GDD during three warming scenarios (+1°, +2° and +3°C rise of daily temperature from last pentad) were also studied. The research finding indicates that accumulated GDD was found to be higher at Kuttanad compared to Palakkad ie., GDD decreases from lower latitude to higher latitude. Chittur of Palakkad district had the lowest accumulation of GDD, while the highest was reported at Moncompu in Kuttanad in the last pentad and as well as during the three warming scenarios. Analysis of the 30 year GDD data of Palakkad revealed that an alternate warming and cooling trend is observed during the first four pentads (i.e. the period from 1993 to 2012) and during the last two pentads (ie. period from 2013 to 2022) the cooling trend is not visible. In Kuttanad region the warming trend is more predominant and the GDD values showed a steady increase form the first pentad to the last pentad. The GDD values seems to decrease from west to east in both Palakkad and Kuttanad.