Assessing Paddy Rice Yield Sensitivity to Temperature and Rainfall Variability in Peninsular Malaysia Using DSSAT Model (original) (raw)
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Agricultural crop production is vulnerable to the effects of changing temperature and rainfall. This study assess the spatio-temporal vulnerability of rice MR219 to the effect of temperature and rainfall changes in MADA, IADA, BLS and KADA granary areas of Peninsular Malaysia. The study predicted changes in yield between 2016 up to 2035 using DSSAT CERES-rice model v4.6.1.0. Genetic coefficients of the rice cultivar used in the model was determined iteratively. To validate the model, daily observatory weather data including both minimum and maximum temperature, solar radiation, rainfall and relative humidity spanning for the period 2001 to 2014 for Subang Jaya meteorological station were obtained from Malaysia Meteorological Department and used in the model to simulate yield for the Main season at IADA, Barat Laut Selangor. The study shows marked seasonal and spatial variation in the predicted rice yield. An analysis of variance shows a significant difference between granary areas during both main and off seasons with F (2, 57) = 71.976, p = .000 and F (2, 57) = 43.995, p = .000 respectively. However, multiple comparison using Turkey HSD reveals a significant difference between granary areas for both seasons, with exception of IADA and MADA which shows no significant difference in predicted yield during off season.
Journal of Cereal Research, 2021
Declaration of climate emergency reminds that the main source of variations in worldwide food production sourced from developing countries and is of utmost concern. Process-based models use simplified functions to express the interactions between upland rice growth and the major environmental factors (i.e., climate, soils, and management) that affect crops yield. This research was conducted to investigate the DSSAT-CERES-Rice model for simulating the impact of different temperature (28˚C, 30˚C and 32˚C) on upland grain yield (Dawk Payawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm). The results showed that the temperature significantly affected the grain yield, flowering, and maturity date. The highest grain yield bearing genotype was Bow leb Nahng (6235.80 kgha-1) with the highest variation between the genotypes. At maximum temperature 32˚C simulated grain yield varied from (3194-6669) kgha-1 , at high temperature 30˚C it varied from 3252-6667 kgha-1 while at moderate temperature 28˚C 3189-6711 kgha-1 was the observed range. However, results indicated that moderate temperature i.e., 28°C gave the highest simulated grain yield. Thus, it was demonstrated that the CERES-Rice model was more useful as a tool for simulating grain yield under the changing different temperature conditions.
Journal of Cereal Research, 2021
Declaration of climate emergency reminds that the main source of variations in worldwide food production sourced from developing countries and is of utmost concern. Process-based models use simplified functions to express the interactions between upland rice growth and the major environmental factors (i.e., climate, soils, and management) that affect crops yield. This research was conducted to investigate the DSSAT-CERES-Rice model for simulating the impact of different temperature (28˚C, 30˚C and 32˚C) on upland grain yield (Dawk Payawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm). The results showed that the temperature significantly affected the grain yield, flowering, and maturity date. The highest grain yield bearing genotype was Bow leb Nahng (6235.80 kgha-1) with the highest variation between the genotypes. At maximum temperature 32˚C simulated grain yield varied from (3194-6669) kgha-1 , at high temperature 30˚C it varied from 3252-6667 kgha-1 while at moderate temperature 28˚C 3189-6711 kgha-1 was the observed range. However, results indicated that moderate temperature i.e., 28°C gave the highest simulated grain yield. Thus, it was demonstrated that the CERES-Rice model was more useful as a tool for simulating grain yield under the changing different temperature conditions.
International Journal of Environment and Climate Change
The Field experiments were conducted during 2012-19 to determine the effect of changing weather such as (Tmax, Tmin, Tavg, Solar radiation and CO2 concentration) on grain yield, LAI, Anthesis days and maturity days of four rice cultivars i.e (Swarna sub 1, Sarjoo 52, Pant Dhan 4 and NDR 359) at the college of forestry farm , SHUATS Prayagraj. The DSSAT-CERES rice model was calibrated and validated, for the cultivars under Prayagraj conditions and it was observed that the values i.e Percent error, RMSE, nRMSE and Pearson correlation coefficient (r) were good in agreement and within permissible limit. Among all the four varieties NDR 359 yields more followed by pant dhan 4, Swarna sub 1 and sarjoo-52. The result revealed that by increasing temperature (Tmax, Tmin, Tavg) for all the variety and phenophases the yield got reduced but under increased condition of Solar radiation and CO2 concentration the yield got increased. In case of LAI same result was observed but during the phenophas...
International Journal of Agricultural Sciences and Technology, 2021
This research paper aims to evaluate the performance of DSSAT CERES-Rice model in simulating the impact of different (28 °C, 30 °C and 32 °C) increased temperatures change with the relations of five upland rice genotypes (Dawk Pa-yawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm) on grain yield for future crop management. Results showed that temperature significantly affected grain yields, harvest index, flowering and maturity date which indicate that medium temperature (30 °C) gave highest grain yield bearing genotype Dawk Kahm (6,700 kg/ ha) whereas at maximum temperature (32 °C), simulated grain yields varied from 3094 to 6460 kg/ ha. Root Mean Square Error (RMSE) values of simulated and observed data less than 10% indicated that grain weight, leaf area index, tillers number and harvest index had more consistency agreement with the yield. Thus, it was proved that the CERES-Rice crop simulation model was more useful as a tool for different phenological traits under changing temperature conditions. And the model approximated grain yields at different temperatures with reasonable accuracy.
Changes of climate will be one of the deciding factors that affect for future food production in the world because crop growth is highly sensitive to any changes of climatic conditions. As the rice is staple food of Sri Lankans, it is essential to identify the impacts of climate changes on country's rice production. This study was conducted to identify the yield and growth changes of most popular two rice varieties (At362 and Bg357) cultivated in Nilwala river basin at Yala season under the global climate change scenario Representative Concentrate Pathway (RCP) 8.5. The Decision Support System for Agro technology Transfer (DSSAT) software is used to forecast the rice yield for Yala season in mid-centuries. To simulate the rice yield DSSAT requires data sets of crop growth and management, daily weather data and soil data. Crop management data were obtained from an experiment which was conducted in Palatuwa area at Nilwala downstream in Matara district. Daily weather data were collected from Mapalana weather station and soil data were collected from wet zone soil classification. Model was calibrated using experimental data for Yala season 2014 and model was validated using collected data in Yala season 2013. Future yield was predicted using forecasted weather data under climate change scenario RCP 8.5 for Mapalana area. The results show that increasing temperature and solar radiation and decreasing rainfall in mid-centuries affects both yield and growth of rice. Grain yield in mid-centuries shows decreasing trend in both varieties by 25% to 35% than the yield at 2014 and growth period will be shorter than the present conditions.
Temperature and precipitation effect on rice productivity
Pattern of temperature and precipitation are changing due to global warming, resulting in having impact on crop productivity. The objective of this study was to estimate the impact of climatic variables on rice productivity in the ricewheat cropping system of the Punjab. Aggregated time series data were used for rice crop. Cobb Douglas type production function was employed with rice yield as dependent variable and climatic factors as independent variables. Results showed that an increase in temperature by 1.5 o C and 3 o C would enhance rice yield by 2.09% and 4.33%, respectively compared to the base year regression estimates. However, an increase in precipitation by 5% and 15% during September-October could adversely affect rice productivity by 5.71% and 15.26%, respectively. However, its decrease is positively related with rice yield. Evolving and disseminating rice varieties having adaptation to climate change should be the focus of future research and development. Improved farm management practices, creating awareness among farmers about climate change and strengthening extension department are some measures to be taken for adaptation to climate change in the rice region.
Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model
International Journal of Agronomy, 2014
Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI) in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from each irrigation scheme and their farms were used as research fields. Daily maximum and minimum temperatures and precipitation were collected from the weather station in each of the irrigation schemes while daily solar radiation was generated using weatherman in the DSSAT shell. The study revealed that increase in both maximum and minimum temperatures affects Basmati 370 and IR 2793-80-1 grain yield under SRI. Increase in atmospheric CO2concentration led to an increase in grain yield for both Ba...