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Open Access
Climate change impact on crop water requirement of rice in Thrissur district
(Academy of Climate Change Education and Research, Vellanikkara, 2016) Basil, Abraham; KAU; Kurien, E K
Rice crop occupies a major position in the agricultural production in Kerala State. Under the present climate change scenarios the climatic parameters are subject to variations and that in turn will affect the water requirement of the crop. A great stress on the irrigation reservoirs and projects for additional water to be released will be effected. It was attempted to generate the climate data for 2030, 2050, 2080 under IPCC emission scenarios RCP.45.The crop water requirement for rice was calculated under the predicted climate for Thrissur district using CROPWAT model. The minimum temperature in the district were found to increase during the future years. The maximum temperature also showed an increasing trend through the future years. The summer months January – March were found to remain as the hot months during the predicted years. The solar radiation was also found to increase. The average annual rain fall for Thrissur district was found to vary as 3139.1, 3089.8 and 3307.6 mm for the future years of 2030, 2050, 2080. The onset of south west monsoon may become early. The summer rains will continue to give a good amount of rain fall through the future years. There will be a reduction in the post monsoon rain fall and a poor distribution of rain fall over the district. The crop evapotranspiration in all the three rice growing seasons of virippu, mundakan and punja was found to increase under the predicted scenario. Crop evapotranspiration was found to increase from 49.99 mm during 2015 to 61.27 mm during 2080 in the first crop season (virippu). During the second and third crop season (mundakan and punja) crop evapotranspiration varied from 56.53 mm to 82.17 mm and 77.06 mm to 83.17 mm respectively. When compared to the year 2050 the irrigation water demand was found to decrease during the year 2080. During the first crop season the irrigation water demand will increase to 319.6 mm in the year 2050 and later during 2080 it was found to decrease to 265.6 mm. There will be a considerable increase in the water requirement during the second crop season during 2050’s and 2080’s when compared with the present day demand. It was also indicated that under RCP 4.5 scenario the water demand to the rice crop during second crop season will be more by 100 mm of water.The crop water use efficiency was found to decrease during future years. An additional amount of 200 billion litres of water will be required for meeting increased water requirement during the second crop season for irrigating rice. The requirement for the third crop season will be high as 750 billion litres.
Open Access
Crop weather simulation model in tomato (solanum lycopersicum L.)
(Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, 2018) Navyasree, S; KAU; Ajithkumar, B
Tomato (Solanum lycopersicum L.) is known as protective food because of its special nutritive value and wide spread production. Planting time is one of the most important factors among the various cultural practices followed for the production of tomato that greatly influence its growth and yield. Weather parameters play an important role in the growth and yield of tomato. The crop is sensitive to both low and high temperatures. Moisture stress is one of the major problems for the cultivation of tomato, which affects the production adversely. Hence much attention has to be paid on the use of soil cover. The present investigation “Crop weather simulation model in tomato ( Solanum lycopersicum L.) ” was carried out in the Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2017-18, to calibrate the genetic coefficients for tomato using DSSAT CROPGRO-Tomato model and to evaluate the micrometeorological aspects of tomato under different growing environments. The field experiment was conducted at the STCR plot, College of Horticulture, Vellanikkara during September (2017) to March (2018). Split plot design was adopted with six dates of planting viz., 15th September, 1st October , 15th October, 1st November, 15th November and 1st December as the main plot treatments and three types of mulches viz., black top white bottom, white top black bottom polythene, straw mulch and control as the sub plot treatments. The number of replications for the experiment was three. The daily weather parameters like maximum and minimum temperatures, forenoon and afternoon relative humidity, bright sunshine hours, pan evaporation, wind speed, rainfall and number of rainy days were recorded during the entire crop growing period, to determine the crop weather relationship. The daily soil temperature determined during the crop growing period showed increasing trend towards the late plantings, whereas weekly soil moisture showed decreasing trend towards late plantings. Black top white bottom polythene retained highest soil temperature and soil moisture. Soil pH, organic carbon and microbial biomass carbon were found to be lowest in control when compared to mulched plots. The analysis of available nitrogen, phosphorus and potassium showed that, the soil samples taken after the harvest of the crop recorded high soil nutrients compared to initial samples. The available soil nutrients (N, P and K) was does not vary between the dates of planting, whereas mulched recorded more soil nutrients compared to control. The increased availability of available nitrogen and phosphorus in polythene mulched plot due to the optimum soil temperature, optimum soil moisture levels, increased mineralization, reduction in nutrients leaching and lower uptake of nutrients by weeds. The increased availability of available potassium in paddy straw mulched plot might be due to addition of potassium to the soil which is present in the straw. In the present investigation, it is clear that the uptake of plant nutrients (N, P, K) was increased due to the addition of mulches, due to sufficient soil moisture, optimum soil temperature, reduction in nutrients leaching, nutrient utilization and reduction in the weeds competition. The maximum height of the plants was found to be highest during 15th September and lowest during 1st December planting. Plant height was high in the mulched plots when compared to the control. The number of trusses per plant for first three plantings were found to be high, whereas it was low in last two plantings. The number of fruits per plant was high in first four plantings and was lowest in last planting. The plants under black top white bottom polythene recorded highest and control recorded lowest number of fruits per plant. The mean yield of 15th September planting was highest and lowest was recorded in control. Yield was high in plants with black top white bottom polythene and straw mulch and were on par. Low number of weeds were recorded in mulched plots, compared to control. The analysis of correlation between weather and yield parameters showed that with increase in the minimum temperature, relative humidity, rainfall and rainy days, yield increased whereas, with increase in the maximum temperature, wind speed, bright sunshine hours and evaporation the yield decreased. Number of days taken for different phenophases viz., first flowering, fifty percent flowering, first fruiting, fifty percent fruiting, harvesting and total duration decreased towards last planting. The duration of the plants with mulches showed long duration compared to control. The correlation between weather and phenophases was significant. The fruit yield and duration of phenophases were influenced by accumulated growing degree days, heliothermal units and photothermal units. The highest recorded accumulated growing degree days, heliothermal units and photothermal units was during 1st December planting. Hence lower fruit yield and less duration for attaining maturity was observed in last dates of planting. The crop genetic coefficients that influence the occurrence of developmental stages in the CROGRO – Tomato model were calibrated, to achieve the best possible agreement between the simulated and observed values. Predicted yield, phenology and leaf area under different planting dates were reasonably close to the observed values. Thus, the study revealed that there is an influence of mulches on the growth and yield of tomato especially in dry conditions. By modifying the micrometeorological conditions, the yield of the tomato can be enhanced during off season. Crop simulation models are efficient in simulating the growth and yield of tomato.
Open Access
Crop weather relationship of yard long bean (Vigna unguiculata subsp. sesquipedalis(L.) walp)
(Department of Agricultural Meteorology Vellanikkara, 2016) Aswini Haridasan; KAU; Ajithkumar, B
Yard long bean is an important leguminous vegetable crop cultivated in Kerala. It is a highly relished vegetable crop which can be cultivated throughout the year. However, weather and climate are considered to be the most limiting factors in crop production. Since weather conditions experienced by a crop play a major role in its growth and yield, the study of the influence of weather on crop is very much important. The present investigation on “Crop weather relationship of Yard long bean (Vigna unguiculata subsp. sesquipedalis (L.) Walp) was carried out in the Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2013-2014 to determine the crop weather relationship and to study the effect of date of sowing on the growth and yield of yard long bean. The experiment was laid out in randomized block design with three replications at Instructional farm, Vellanikkara from September 2013 to August 2014. The treatment comprises of twelve dates of sowing at monthly intervals from September 2013 to August 2014. Yard long bean variety lola was used for the experiment. The different growth and yield characters like plant height, biomass, number of pods per plant, number of seeds per pod, hundred seed weight, length of pod, pod yield per plot, pod yield per plant and duration of different growth phases were recorded along with monitoring of major pests and diseases. The daily weather parameters like maximum and minimum temperature, forenoon and afternoon relative humidity, forenoon and afternoon vapour pressure, rainfall and rainy days, bright sunshine hours, evaporation, wind speed and soil temperature were also recorded. The maximum temperature was found highest in February 2014 sowing and was recorded lowest in July 2014 sowing whereas the highest minimum temperature was recorded in March and April 2014 sowing. The crops sown during December 2013 and January 2014 received no rainfall and those sown during June 2014 received the maximum rainfall. The bright sunshine hours was recorded more in December 2013 sowing and was low in June 2014 sowing. Plant height, biomass, phenological stages, yield and yield attributes were highly variable among the different sowing dates. The March 2014 sown crops took more number of days to attain 50% flowering followed by February 2014 sown crops. The crop duration was also observed more for March sown crops which was on par with December 2014 sown crops. Yield and yield attributes were influenced by various weather parameters experienced during the different crop growth stages. Pod yield was highest from September and October 2013 sown crops and lowest from May and July 2014 sown crops. Yield attributes such as number of pods per plant, number of seeds, length of pods and hundred seed weight were also recorded more in September and October 2014 sown crops. Pests such as aphids, pod borer, pod bug and diseases such as mosaic, rust and anthracnose were observed in the crop during the study. To determine the critical weather elements affecting the crop growth, correlation analysis was done and it was found that maximum temperature, diurnal temperature range, soil temperature at 10cm depth, wind speed and bright sunshine hours exhibited positive influence on the pod yield, whereas increase in minimum temperature, growing degree days, relative humidity, vapour pressure, rainfall and rainy days negatively influenced the yield. Multiple linear regression models were fitted, to predict the pod yield based on the weather variables..
Open Access
Assessment of rice (oryza sativa L.) production under climate change scenarios
(Department of Agricultural Meteorology Vellanikkara, 2017) Jasti Venkata, Satish; KAU; Ajithkumar, B
Agriculture is sensitive to short term changes in weather and to seasonal, annual and long term variations in climate. Climate change will have decisive impact on crop production and the prediction of this climate change emerged as a major research priority during the past decade. Numerous estimates for the impending decade projects that continuous rise of anthropogenic forcing leads to increase in greenhouse gas (GHG) atmospheric concentrations, is expected to alter regional temperature and precipitation patterns, also contributing to higher risk of extreme weather events and climate irregularity (IPCC, 2013), with obvious implications on crops (Porter and Semenov, 2005). Rice (Oryza sativa L.) is vulnerable to unfavourable weather events and climate conditions. Despite technological advances such as improved crop varieties and irrigation systems, weather and climate play significant roles in rice production. The present investigation “Assessment of rice (Oryza sativa L.) production under climate change scenarios” was carried out in the Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2016-17, to determine the crop weather relationship, to validate the CERES (Crop Environment Resource Synthesis) -Rice model for the varieties Jyothi and Kanchana and to project the changes of rice yield and growth under climate change scenarios. The field experiment was conducted at Agricultural Research Station, Mannuthy during the kharif season of 2016. 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. Analysis of weather with crop duration and yield showed that maximum and minimum temperatures showed increasing trend towards late plantings, whereas the relative humidity, rainfall and rainy days were found to be low in late planting than during early plantings. To determine the critical weather elements affecting the crop duration, correlation analysis was performed. Number of days for panicle initiation to booting stage, decreased with increase in maximum and minimum temperature, whereas, the reverse was observed with afternoon relative humidity, afternoon vapour pressure deficit and rainfall in Jyothi. In case of Kanchana, days for transplanting to active tillering decreased with increase in maximum, minimum temperatures and bright sunshine hours, whereas relative humidity, afternoon vapour pressure deficit, rainfall and 159 number of rainy days showed a positive influence. The mean yield of Jyothi and Kanchana on June 5th planting found to be on par with June 20th planting. The correlation analysis showed that with increase in maximum and minimum temperature during transplanting to Active tillering will reduce the yield for both Jyothi and Kanchana The crop genetic coefficients that influence the occurrence of developmental stages in the CERES-Rice models were validated, to achieve the best possible agreement between the simulated and observed values. Predicted yield and phenology of both rice varieties, Jyothi and Kanchana under different planting dates were reasonably close to the observed values. Analysis of yield and growth phases of rice under different climate change scenarios ( Representative Concentration Pathways (RCP) 4.5 and 8.5) for the time periods 2050s and 2080s showed that, days taken to panicle initiation, anthesis and physiological maturity decreases for all the five different dates of planting. This may be due to increase in maximum and minimum temperatures during the future scenarios. The predicted values of rice yield for the climate change scenarios during first and second plantings for the time periods 2050s and 2080s showed a low yield whereas increase in yield was observed in third, fourth and fifth plantings compared with 2016. This increase in yield is may be due to combined effect of increase in CO2 (538 and 936ppm) and solar radiation during the panicle initiation, anthesis and physiological maturity for the delayed plantings. These findings suggests that, planting date need to be shifted to late July and early August in case of kharif crop in the central zone of Kerala in future.
Open Access
Comparison of different weather based models for forecasting rice yield in central zone of Kerala
(Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, 2018) Athira Ravindran; KAU; Ajithkumar, B
Rice is the staple food and the major field crop cultivated in Kerala. Its production is highly influenced by unfavourable weather events and climatic conditions. Thus it poses a challenge to farmers, crop planners and government owing to varying production of grains. Reliable crop yield forecasts are highly essential to estimate crop production, to assist farmers, exporters and government in decision making for efficient resource allocation, price adjustment and export planning. It also helps to reduce various secondary risks associated with local and national food systems. The present investigation “Comparison of different weather based models for forecasting rice yield in central zone of Kerala” was carried out at the Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2017-18, to compare the accuracy of different weather based models developed using five years’ rice crop data collected from previous studies at the department for forecasting rice yields in central zone of Kerala and to validate them using the present experimental data. The field experiment was conducted at Agricultural Research Station, Mannuthy during the kharif season of 2017. 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. Daily observations of weather during the crop period were made which showed an increase in the maximum and minimum temperature and decrease in rainfall and relative humidity towards the end of the crop period. Different growth and yield attributes like plant height, dry matter accumulation, number of tillers, panicles, spikelets, filled grains, grain yield, straw yield and the duration of different phenophases were also noted. Correlation analysis was carried out using the weather, yield and phenological data of 5 years in both the varieties. The various growth indices such as leaf area index, net assimilation rate, leaf area duration and crop growth rate were worked out to analyze the growth and development of the crop. Plant height was found to be higher for Jyothi compared to Kanchana. Dry matter accumulation, yield attributes except straw yield were found varying between five dates of planting. Yield and yield attributes were influenced by different weather parameters during different dates of planting. With delay in dates of planting the duration of different phenological stages were reduced in both the varieties. Jyothi took more number of days to attain different growth stages compared to Kanchana. The highest yield in Jyothi and Kanchana were obtained for June 5th planting. Crop weather models using statistical techniques were developed using five years’ weather and crop yield data by adopting four different methods for Jyothi and Kanchana separately. The methods were (i) based on weekly weather variables (ii)based on fortnightly weather variables (iii) based on crop stage wise weather variables and (iv) based on composite weather parameters. Each crop weather model was fitted by stepwise regression analysis using SPSS software. CERES-Rice model also was run for Jyothi and Kanchana by creating weather file, soil file, crop management file and experimental files separately for each year. For comparing the accuracy of the developed crop weather models and simulation model for Jyothi and Kanchana, and for their validation, mean absolute percentage error (MAPE) was calculated for each model using the observed and estimated yield data. The model with least mean absolute percentage error (MAPE) is considered as a better model for yield prediction. In the case of Jyothi, lowest MAPE (4.00%) was obtained for model based on 5 fortnightly weather variables. In Kanchana also, the model developed using 5 fortnightly weather variables was selected with an MAPE value 7.62%. All the crop weather models are showing very good results out of which crop weather model using 5 fortnightly weather variables which coincide with flowering stage has given a good forecast compared to the other models for both Jyothi and Kanchana.
Open Access
Influence of weather parameters on growth and yield of black pepper (Piper nigrum L.)
(Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, 2016) Sushna, K; KAU; Ajithkumar, B
Black pepper (Piper nigrum L.) (Family: Piperaceae) is a perennial vine grown for its berries extensively used as spice and in medicine. India is one of the major producer, consumer and exporter of black pepper in the world. It is cultivated to a large extent in Kerala, Karnataka and Tamil Nadu and to a limited extent in Maharashtra, North eastern states and Andaman & Nicobar Islands. Black pepper is a plant of humid tropics requiring high rainfall and humidity.
Open Access
Effect of growing environment and microclimate on parthenocarpic cucumber
(Department of Agricultural Meteorology,College of Horticulture, Vellanikkara, 2016) Smitha, K; KAU; Sunil, K M
An investigation was carried out in Department of Agricultural Meteorology, College of Horticulture, Vellanikkara during 2015-16 to determine the the effect of growing environments and microclimate on growth and yield of cucumber and crop weather relationships in cucumber under different growing environment.
Open Access
Climate change adaptation on rice production
(Academy of Climate Change Education and Research, Vellanikkara, 2016) Navya, M; KAU; Sunil, K M
Open Access
Impact of climate change variables on young coconut seedlings (Cocos nucifera L.)
(Academy of Climate Change Education and Research, Vellanikkara, 2016) Kannan, S; KAU; Mary, Regina F (

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