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Open Access
Carbon sequestration potential of selected seaweeds of Thikkodi, Kerala
(Academy of Climate Change Education and Research, Vellanikkara, 2019) Saranya, M S; KAU; Vinod, K
The coastal blue carbon is the carbon sequestered by mangrove, tidal marshes, seagrasses and macroalgae which account for less than 0.5% of the seabed. Unlike, other blue carbon sectors (mangroves, tidal marshes and seagrasses), the macroalgae do not have sedimentary substratum. The macroalgae are commonly known as seaweeds. The ‘seaweeds’ as the name suggest is not an unwanted plant or weed. It has an important role in the marine ecosystem by acting as a sink for carbon emissions. The present study is based on the carbon sequestration potential of selected seaweeds of Thikkodi coast, Kerala. The state of Kerala has a long coastline of about 580 km, ranking only third among all the maritime states of the country. Some of these coastline stretches are pegged with areas of seaweed resources. The Thikkodi coast (11º28’30.8” N, 75º37’04.5”E) in the Kozhikode district of Kerala is well known for its rocky intertidal coast with a luxuriant growth of seaweeds of diverse species. An extensive study of seaweeds and their species diversity was carried out for a period of one year from September 2018 to August 2019 along the Thikkodi coast of Kerala. A total of 40 species of seaweeds were recorded which belonged to 23 genera, 18 families and 14 orders. A total of 19 species belonged to Chlorophyta, while 12 species belonged to Rhodophyta and 9 species belonged to Phaeophyta. The distribution and seasonal abundance of different species along the Thikkodi coast was also studied. The biodiversity indices were studied using PRIMER (Plymouth Routines in Multivariate Ecological Research). The biodiversity indices such as Shannon-Wiener diversity (H’), Pielou’s evenness (J’), Margalef species richness (d) were calculated. The seaweeds collected from Thikkodi coast were used to carry out the carbon sequestration potential studies. While comparing the three zones, the highest value of species richness (S) was obtained in zone 1 (S=14.00), followed by zone 2 (S=8.75) and zone 3 (S=7.08). The Margalef’s index (d) which incorporates the number of individuals (N) and species (S) was the highest in zone 1 (2.10), while it was minimum in zone 3 (1.08). The equitability or individuals among the different species showed much variation between the zones and the values ranged from 0.67 (zone 2) to 0.77 (zone 1). In the present study, the Shannon Wiener Index (H’) showed wide variation between the zones ranging from the lowest value of 1.33 (zone 3) to the highest value of 1.99 (zone 1). The Simpson Index (1-Lambda’) showed variations in values ranging from 0.66 (zone 3) to 0.82 (zone 1). The experiments were conducted on selected seaweeds particularly Gracilaria corticata, Caulerpa scalpelliformis and Caulerpa peltata. Carbon dioxide was dissolved in seawater at different concentrations using a soda maker by adjusting the fizz. After determining the initial CO2, the seaweeds were incubated in 125ml light bottles under a water column of 50-60cm for 2 hours. The initial CO2 concentration (mg/l) and the CO2 utilization were examined by titrating the seawater against 0.5N Sodium hydroxide solution using Phenolphthalein indicator. The Gross Primary Production (GPP) and Net Primary Production (NPP) were also estimated. For Gracilaria corticata, the utilization efficiency increased from 33.33% to 83.33% in lower CO2 concentration of 26.4mg/l and 79.2mg/l respectively. For Caulerpa scalpelliformis, the utilization efficiency increased from 25% to 42.86% in a lower CO2 concentration of 17.6mg/l and 30.8mg/l respectively. For Caulerpa peltata, the utilization efficiency increased from 66.67% to 75% in a lower CO2 concentration of 13.2mg/l and 35.2 mg/l respectively. When the concentration of CO2was increased beyond a threshold level, the CO2 utilization efficiency decreases and cease down to zero .Same is the case for productivity. Therefore the study implies that the carbon sequestration potential of different species of seaweeds varies. The macroalgae have a greater potential to act as carbon sink and based on the sequestration potential of seaweeds, selection of different species of seaweeds can be made possible for developing Seaweed Aquaculture Beds (SABs). The SABs provide important structure in coastal ecosystem and play an incredible role in climate change mitigation aspects.
Open Access
Study the impact of abiotic stress on photosynthetic potential of tropical tuber crops under elevated CO2
(Academy of Climate Change Education and Research, Vellanikkara, 2019) Ancy, P; KAU; Nameer, P O
Climate change and agriculture are interconnected processes, both of which take place on a universal scale. Global warming is expected to have significant impacts on agriculture. Most of the studies reported a positive impact in photosynthetic rate of C3 plants due to eCO2. However other players of climate change such as drought and rising temperature can harmfully affect crops. Cassava and sweet potato are two major tropical root crops grown in India. The main objective of the present study was to figure out the impact of adverse conditions of climate change such as water deficit stress and high temperature stress on photosynthetic potential of tropical tuber crops under elevated CO2 and there by identify crop/varieties suitable for changing climate conditions. The study was conducted during the period of October 2018 to July 2019 on four contrasting cassava and four contrasting sweet potato varieties. Observations on photosynthetic parameters viz., the net photosynthetic rate (Pn), stomatal conductance (gs) transpiration and sub-stomatal/intercellular CO2 concentration (Ci) were recorded using a LI6400 portable photosynthesis system, LI-COR Inc, Lincoln, USA. Elevated CO2 have positive effects on photosynthetic parameters under WDS free as well as WDS conditions in cassava as well as sweet potato. Even though WDS reduces photosynthetic rate, eCO2 could sustain greater Pn rate than ambient CO2 under WDS. Under eCO2 rising temperature can benefit cassava and sweet potato only under WDS free conditions. For cassava Pn was not significantly affected by temperatures. For sweet potato Pn significantly increased with rise in temperature. It indicates that increasing temperature is not a limiting factor for cassava and sweet potato, but beneficial for them under WDS free conditions. Responses of cassava and sweet potato to WDS and rising temperature are also influenced by the variety. Cassava variety Sree Athulya responses well to eCO2 as well as to rising temperature under WDS free conditions. Cassava variety Sree Vijaya can perform well under WDS compared to other varieties. Sweet potato variety Sree Arun exhibits higher Pn under WDS free conditions. Bhu Krishna and Kanhangad had high Pn under WDS as well as at higher temperature. From this study it can be concluded that tropical root and tuber crops especially cassava and sweet potato have a great potential for better adaptation at elevated CO2 environment under adverse climate conditions such as water deficit stress and increasing temperature. They can become crops providing food security for future environment under climate change.
Open Access
Crop weather relationship studies in finger millet (Eleusine coracana (L.) Gaertn) in central zone of Kerala
(Department of Agriculture Meteorology, College of Horticulture, Vellanikkara, 2019) Anunayana John, T; KAU; Ajithkumar, B
Finger millet (Eleusine coracana (L.) Gaertn) is an important food crop next to rice, wheat and maize. The crop is native to Africa. Finger-millet is capable to withstand three stresses such as warming stress, water stress and nutrition stress, so it is called as Climate Change Compliant Crop (CCCC). These attributes combine to make finger millet a suitable crop for ensuring food security in drought prone areas of the countries. The present study was done to estimate the crop weather relationship in finger millet (var : GPU-28) in central zone of Kerala and to identify the ideal date of planting and best crop establishment method during 2018. The field experiment was conducted at experimental field of Instructional Farm, College of Horticulture during the kharif season of 2018. Split plot design was adopted with five dates of planting viz., May 15th, June 1st, June 15th, July 1st and July 15th as the main plot treatments and three planting methods viz., broadcasting, dibbling and transplanting as the sub plot treatments with number of replications as three. Considering the weather observations, the daily observations of weather recorded during the crop period like maximum, minimum and mean temperature, rainfall and relative humidity showed considerable variations especially during the mid-growth period. Heat units like Growing Degree Days (GDD), Heliothermal Units HTU) and Photothermal Units (PTU) were also calculated for the crop growth period. Growth and yield attributes like plant height, dry matter accumulation, number of ear heads, finger number per ear head, finger length, thousand grain weight, grain yield, straw yield, harvest index and the duration of different phenophases were also noted. Growth indices such as crop growth rate and relative growth rate were worked out to analyze the growth and development of the crop. Micrometeorological and weeds observations were also made. Correlation analysis was carried out using the weather parameters, yield and phenological data to estimate the crop weather relationship in finger millet. The results shows that maximum temperature was showing a negative correlation, while relative humidity, vapour pressure deficit and rainfall was showing positive correlation in most of the yield and yield contributing factors. Considering the micro meteorological observations, June 1st planting showed the highest values for both forenoon and afternoon soil temperature. Highest soil moisture was observed in broadcasting method of planting at 15cm depth and it did not show any considerable variations with respect to date of planting. Weed intensity and dry weight was shown higher during the dibbling method of planting. ABSTRACT Plant height was found to be higher for dibbling method of planting at 60 days after sowing and May 15th planting showed the higher values which was on par with June 15th planting. Dates of planting had significant effect on the dry matter accumulation which showed higher values for June 15th planting which was on par with June 1st planting at harvest in broadcasting method. Crop growth rate showed an increasing trend during the vegetative phases and there after followed a decreasing trend up to harvest, while relative growth rate showed a gradual decreasing trend from mid-growth period. Duration of phenophases was similar for both broadcasting and dibbling method, while transplanting took comparatively more days to attain each stages. Duration also showed a decreasing trend with delay in date of planting. Heat indices like GDD and PTU followed a decreasing trend with delay in date of planting which indicates their positive impact on the growth and yield performance of finger millet. Considering the yield attributes like number of ear heads m-2, it showed higher values for transplanting method in May 15th planting. Finger number per ear head was higher for June 1st planting which was on par with both May 15th and June 15th planting. Highest finger number per ear head was attained for transplanting method which was on par with dibbling method of planting. Finger length showed the highest value in May 15th planting which was on par with June 1st planting. Date of planting showed significant effect on the straw yield as it was higher in May 15th planting and was lower in July 1st planting which was on par with July 15th planting. Harvest index attained higher values for July 1st planting which was on par with July 15th and June 1st planting. Interaction effect of the treatment combination of May 15th planting with transplanting method attained the highest grain yield (2833.3 kg ha-1) compared to other methods. Assessment of cost of cultivation revealed dibbling method showed highest value while it was lowest in broadcasting method. But the B:C ratio was highest in transplanting and the lowest was observed in dibbling method of planting. This revealed that transplanting method not only encourages yield production, but also economically feasible compared to broadcasting and dibbling methods. So the present investigation on the crop weather relationship in finger millet suggested that the positive contribution of various weather and micrometeorological parameters like relative humidity, vapour pressure deficit, rainfall, forenoon and afternoon soil temperature etc. and the reduced maximum temperature and temperature range which increased the production of number of ear heads, finger number per ear head, increased finger length, straw yield etc. This ultimately leads to increased grain yield in May 15th and June 1st date of planting. In case of the three planting methods, studies suggested that transplanting can be considered as best establishment method for finger millet cultivation in central zone of Kerala.
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 relationship of rice varieties under different growing environments
(Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, 2019) Haritharaj, S; KAU; Ajithkumar, B
In India, rice production is an important part of the national economy. India is the second largest producer in the world with approximately 43 million hectares planted area, accounting for 22% of the total rice production in this world. World’s leading rice exporter is India, marketing about 12.5 million metric tonnes in 2018-19. Rice is grown in rainfed areas with heavy annual rainfall. Therefore it is fundamentally considered as a kharif crop. But its production mainly depends up on weather prevailing in that area. Weather has a profound influence on growth, development and yields of crop; on the incidence of pests and diseases; on water needs; and on fertilizer requirements. The present experiment was aimed to study the crop weather relationship of rice varieties under different growing environments and to validate different crop weather models for rice varieties including statistical models and crop simulation model (DSSAT CERES-Rice model). Two varieties of rice, Jyothi and Jaya were raised at Agricultural Research Station, Mannuthy by adopting split plot design. Five planting dates such as June 5th, June 20th, July 5th, July 20th and August 5th were used as main plot treatments and the two varieties were used as sub plot treatments. The replication number used for this experiment was four. During the field experiment, daily weather data were collected like maximum temperature, minimum temperature, relative humidity, rainfall, bright sunshine hours, wind speed and evaporation. Biometric observations like plant height, leaf area, dry matter accumulation, number of tillers per unit area, number of panicles per unit area, number of spikelets per panicle, number of filled grains per panicle, thousand grain weight, straw yield and grain yield were observed. Duration of different phenophases and physiological observations such as leaf area index, net assimilation rate, leaf area duration and crop growth rate were also calculated. Pests and diseases were noticed during different growing conditions. Considerable variation among weather variables were noticed during the field experiment. Plant height was higher for Jyothi compared to Jaya and it showed variation among different planting dates. Maximum dry matter accumulation was recorded during 75 days after planting and it exhibited a decreasing trend with delayed planting in both the varieties. Number of spikelets per panicle, number of filled grains per panicle, thousand grain weight and straw yield were found to be decreasing as the planting date was delayed. Highest grain yield (4698 kg ha-1) was observed in Jyothi during June 20th planting whereas, June 5th planting showed maximum grain yield (5527 kg ha-1) in Jaya. Because, continuous morning rainfall during flowering stage of Jyothi reduced its yield in June 5th planting (3021.25 kg ha-1). Maximum duration was observed during June 20th planting in Jyothi (129 days) and Jaya (139 days). Total duration was less for August 5th plantings in both the varieties (121 and 129 days for Jyothi and Jaya respectively). Leaf area index and leaf area duration were more during 75 days after planting for both the varieties and leaf area duration showed a maximum value during 60-75 days after planting for both the varieties. In general, crop growth rate of both Jyothi and Jaya was found to be more during 45- 60 days after planting while net assimilation rate was more in the early growth stages. Validation of statistical models for Jyothi such as models based on weekly weather variables, fortnightly weather variables, crop stage-wise weather variables and that based on composite weather variables, were carried out in which model which uses composite weather variables was selected as the best one in yield prediction of Jyothi after comparing the estimated yield and observed yield. Crop weather model using statistical methods was also developed for Jyothi and Jaya with the aid of principal component analysis. Two principal components were identified for Jaya and three for Jyothi. The regression analysis was carried out using SPSS software. This formed a better tool in predicting the yield of Jyothi and Jaya. DSSAT CERES- Rice model was also run for Jyothi as well as for Jaya after creating weather file, soil file, crop management file and experimental file for the year 2018.
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.

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