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ThesisItem Open Access Micrometeorological modification with mulches to enhance the yield of Turmeric (Curcuma longa L.)(Department of Agricultural Meteorology, College of Agriculture,Vellanikkara, 2021) Abin Divakaran, A; KAU; Lincy Davis, PTurmeric (Curcuma longa L.) is one of the most important rhizomatous spices, belonging to Zingiberacea. It is an annual herbaceous plant native to tropical SouthEast Asia. Turmeric has high medicinal properties and it is wildly used in pharmaceutical, cosmetics and food industries. Due to the high value of the crop, it is getting good demand all over the world. India is one of the largest producer and consumer of turmeric around the world. In India turmeric is mainly planted in the hot summer months and grown as a rainfed crop, but due to the drastic changes in the agroclimatic conditions its production is influenced detrimentally. Mulching is an important cultural practice in turmeric, which helps to maintain an optimum microclimatic condition, reduce weed growth, add organic matter and conserve moisture throughout the high evaporative periods. Due to these changing climatic conditions assessment of an effective date of planting and finding a most suitable mulching practice are required for the effective production of turmeric. Hence, the goal of this study is to determine how planting dates and micrometeorological modifications with mulches affect turmeric yield. Turmeric variety Kanthi was raised in Plantation Crops and Spices farm, College of Agriculture, KAU, Vellanikkara with four different dates of planting (1st May, 15th May, 1 st June and 15th June) and four different mulching treatments (white polythene mulch, black polythene mulch, paddy straw mulch and green leaf mulch). The experiment was laid out in split plot design with four dates of planting as main plot treatments and four mulching practices as subplot treatments. Crop weather analysis was done by using SPSS software and crop yield prediction model was developed with the help of Principal Component Analysis (PCA) and regression analysis. The total crop period was divided into four phenophases (P1-planting to germination, P2-germination to initiation of active tillering, P3-initiation of active tillering to bulking, P4- bulking to physiological maturity). The days to reach each phenophases were different in every date of planting. May 1st planting took more days to reach 100 per cent germination and to reach physiological maturity both 1st and 2nd dates of plantings took more time. The plant biometric characters like plant height, number of leaves, leaf area, number of tillers and dry matter accumulation were found to be more in earlier dates of planting (May 1st and May 15th) in almost all the time. In mulching practices paddy straw mulch was superior and it was followed by green leaf mulch. The yield produced by May 1st and May 15th dates of planting were on par and in case of mulching treatments paddy straw mulch produced superior yield than any other mulching practice. In mulching treatments polythene mulches recorded more soil temperature and moisture content than organic mulches in almost all the time. The first phenophase of 1st date of planting recorded high maximum, minimum and soil temperature along with less rain fall and rainy days. This might have influenced the late emergence of turmeric. The increase in maximum temperature, wind speed, sunshine hours and evaporation reduced the plant height in third phenophase. Soil moisture content and relative humidity inside the plant canopy showed a positive correlation with yield, whereas soil temperature showed a negative correlation with yield during the bulking stage of turmeric. The decrease in maximum temperature, bright sunshine hours, wind speed and evaporation and the increase in the minimum temperature, forenoon and afternoon relative humidity and rainfall during bulking stage enhanced the yield in turmeric. The development of yield prediction model with principal component analysis of mulching treatments and dates of planting of four phenophases were done and the yields of turmeric crop with these equations were predicted. This showed that, the predicted yield was in accordance with the observed yield in all mulching treatments.ThesisItem Open Access Spatial variability of climate change impacts on Rice (Oryza sativa L.) yield in Kerala(Department of Agricultural Meteorology, College of Agriculture, Vellanikkara, 2021) Riya, K R; KAU; Ajithkumar, BRice is one of the essential food crops of the world. Almost 40% of the world’s population consumes rice as their staple food. Nearly 12% of the total cultivated area in Kerala accounts for rice cultivation. It is cultivated in both plains and high altitudes, therefore long-term climatic changes within a region and their impact on productivity is very important. Crop weather models have a vital role in climate change studies. Rice studies are mainly carried out in the CERES- Rice (Crop Environment Resource Synthesis- Rice) model. The CERES - Rice has been calibrated and validated and found suitable for simulation of rice growth and development in the tropical humid climate. The present experiment was aimed to study the impact of climate change on phenophase and yield aspects of rice varieties under climate change scenarios of RCP 4.5 and 8.5 in 14 districts of Kerala. Short-duration rice variety, Jyothi and medium-duration variety, Jaya have been selected for the experiment. The experiment was carried out with the split-plot design. The main plot treatments were five dates of plantings (June 5 th , June 20th , July 5 th , July 20th and August 5 th) and subplot treatments were two varieties (Jyothi and Jaya) with four replications. Various observations like weather, phenological, biometric, physiological, yield and yield attributes had been recorded to studythe crop weather relationship. The crop weather analysis has been carried out with SPSS software. The results indicated that duration of phenophases had a negative correlation with the maximum temperature. A significant variation in the biometric observations was also obtained. Plant height and dry matter accumulation were found to be higher in Jyothi when compared to Jaya. Both varieties recorded the maximum leaf area index (LAI) and leaf area duration (LAD) at 75 days after planting. The crop growth rate was obtained maximum at an interval of 45 to 60 days after planting irrespective of the variety. The highest grain yield in Jyothi was obtained during June 5th and August 5th plantings which were found to be on par. In Jaya, July 20th planting and August 5 th planting were found to be on par. Using the observations from the field, validation of genetic coefficient of DSSAT- CERES model. To study the impact of climate change on rice production, climate change in Kerala had been estimated. The current climate (1980 – 2020) has been compared with three different future 2010-2030 (near-century), 2021-2050 (mid-century) and 2051-2080 (latecentury) simulations for the 14 districts of Kerala under Representative Concentration Pathway (RCP) 4.5 and 8.5. The annual and seasonal (southwest monsoon, northeast monsoon, winter and summer season) comparison of weather data has been carried out. Under RCP 4.5 the amount of solar radiation is expected increase by greater than 1 MJ/m2 districts like Wayanad, Malappuram, Thrissur, Ernakulam, Kottaym and Pathanamthitta by the end of century. Under RCP 8.5 a normal departure (-1 to 1 MJ/m2 ) is expected by the end of century in most parts except in Wayanad and Thrissur, where an above normal increase is predicted. At the same time in Palakkad a below normal decrease is expected in solar radiation. During the southwest monsoon an increase in solar radiation is expected in mid-century and by the end of century a normal departure is expected except in Malappuram, Palakkad and problematic zone where the solar radiation is expected to increase. Under RCP 8.5 a normal departure is expected by the end of century except in Kasargod, Kozhikode, Wayanad and Thiruvananthapuram where a below normal departure is expected. In northeast monsoon season solar radiation is expected to increase in central and problematic zone and a normal departure is expected in other parts under RCP 4.5. In RCP 8.5 by the end of century solar radiation is expected to decrease in Kozhikode, Idukki and Thiruvananthapuram during northeast monsoon. An increase in solar radiation is expected in central, problematic and southern zone during RCP 4.5 in winter season while in northern zone solar radiation is expected to be normal in RCP 4.5 and a below normal departure is expected in RCP 8.5. In Thiruvananthapuram a solar radiation is expected to decrease in both scenarios. A normal departure of solar radiation is expected to increase in most parts of Kerala during the summer season. In Kannur, Kozhikode, Thiruvananthapuram and Wayanad solar radiation are expected to decrease by -1.5 MJ m2 or less than that by the end of century under RCP 8.5 except in Malappuram where an above-normal increase is expected. An increasing trend in maximum and minimum temperature is expected in future simulations. The annual temperature is expected to increase in all parts of Kerala except in Idukki where a below normal departure (-1.5 to 1.5°C) is expected in near and mid-century. By the end of century a normal departure of annual maximum temperature is expected in high range zone and Thiruvananthapuram under RCP 4.5 and while under RCP 8.5 only Idukki and Thiruvananthapuram is showing a normal departure. In southwest monsoon season temperature is expected to rise by 1.5°C by end of century under RCP 8.5 while under RCP 4.5 a normal departure is expected in Wayanad, Idukki and Kollam. During the northeast monsoon season and summer season the maximum temperature is expected to increase in all parts expect in Idukki in near and mid-century under both RCPs. In RCP 4.5, a normal departure of annual maximum temperature is projected in the high range zone and Thiruvananthapuram by the end of the century, but only Idukki and Thiruvananthapuram will show a normal departure under RCP 8.5. During the winter season a decrease in temperature is expected in Idukki while in other districts the temperature is expected to increase. The minimum temperature is expected to increase in Kerala except in Idukki in all the future simulations under both RCPs in all seasons. In Idukki the minimum temperature is expected to decrease in near century and then increase in mid and end of century with a normal depature. A spatial variation in rainfall is expected in Kerala in future simulations, with an excess or normal rainfall in some parts at the same time deficiency in other parts of Kerala. The annual rainfall is expected to increase in most parts of Kerala. In districts like Kasargod, Idukki and Alappuzha a normal departure (+19 to -19%) in annual rainfall is expected in all the future simulations under RCP 4.5 ad 8.5. During the southwest monsoon season, rainfall is expected to show a large excess and excess in most parts of Kerala except in Kasargod where a normal departure is expected. Under RCP 4.5 the rainfall is expected to decrease in Wayanad and Alappuzha by the end of century. While under RCP 8.5 the rainfall is expected to increase in Wayanad and Thiruvanathapuram by the end of century. Northeast monsoon is expected to be show a normal departure in most places. Under RCP 4.5 it is expected to decrease in Idukki, Pathanamthitta, Kollam and Kasargod. While under RCP 8.5 it is expected to increase in Ernakulam, Alappuzha, Pathanamthitta and Kollam at the same time a deficit rainfall is expected in Kannur and Thrissur. Winter rainfall was predicted to decrease from normal in almost all parts of Kerala in near and mid-century. By the end of century under RCP 4.5 and by mid and end of the century under RCP 8.5 and excess rainfall is predicted in parts of the northern zone and problematic zone. Summer rainfall is expected to be large excess and excess in most parts during near and mid century under RCP 4.5 and in the near century of RCP 8.5. In the end of century under RCP 4.5 and in mid and end of the century under RCP 8.5 a normal rainfall is expected in most places. In Idukki and Thiruvananthapuram the rainfall is expected to be deficient. The potential yield had been predicted with the DSSAT- CERES model using the genetic coefficient validated using field experiment. the predicted weather for 13 districts of Kerala. The duration of crop is expected to decrease as a result of increase in temperature in both varieties. Yield reduction is expected in future simulations under both the RCPs in most places of Kerala. Under RCP 4.5 in Jyothi, June 5th planting showed maximum deviation from base period (2020). The maximum deviation was observed in Kozhikode i.e. in near (-58%), mid (-63%) and end of century (-60%) under RCP 4.5 and in near (- 62%), mid (-60%) and end of century (-64%) under RCP 8.5. The least deviation was found in July 20th planting in all the future simulations. In Idukki, an increase in yield had been observed in July 5 th , July 20th and August 5 th plantings. An increase by 34%, 28% and 23% in near, mid and end of century respectively is expected. Under RCP 8.5 in July 20th planting higher yield has been observed and shows a positive deviation of 38%, 28% in near and mid century respectively in Idukki. By the end of century yield is expected to decrease except in August 5th planting which showed a positive deviation of 12%. In southern zone the highest potential yield had been observed in August 5 th planting. In Jaya also the maximum deviation had been observed during June 5th palnting in Kozhikode i.e. in near (-58%), mid (- 63%) and end of century (-60%) under RCP 4.5 and in near (-62%), mid (-60%) and end of century (-64%) under RCP 8.5. In Idukki under RCP 4.5 an increase in yield was observed during July 20th planting with an increase by 27% in near and mid century and by the end of century a deviation of 20% was observed. Under RCP 8.5 in July 20th planting higher yield has been observed and shows a positive deviation of 27%, 24% and 10% in near, mid and end of century. In southern zone of Kerala, highest potential yield of Jaya has been observed in July 20th planting in all the future simulations under both RCPs. The duration of crop showed a negative correlation with the temperature. As a result decrease in duration of phenophase had been observed in future simulations. An increased temperature and precipitation patterns during panicle initiation to anthesis may be the reason for the yield variability. During the base period higher yield was obtained during June 5th and June 20th planting i.e. early plantings while in future simulations the higher yield is expected in July 5th, July 20th and August 5th plantings i.e. late plantings. Hence there is a chance of shift in date of planting in Kerala in future.ThesisItem Open Access Inter- and intra-specific variations of casuarina under elevated CO2(Academy of Climate Change Education and Research, Vellanikkara, 2021) Abhin Sukumar, P; KAU; Buvaneswaran, CThesisItem Open Access Weather extremes preparedness of nutmeg (Myristica fragrans) farmers in Kerala(Academy of Climate Change Education and Research, Vellanikkara, 2021) Adharsh, C J; KAU; Ajith Kumar, BThesisItem Open Access Estimation of glacier stored water in bhaga basin, Himalayas(Academy of Climate Change Education and Research, Vellanikkara, 2020) Gopika, J S; KAU; Nameer, P OThesisItem Open Access Climate-forest fire linkages in selected protected areas in Kerala(Academy of Climate Change Education and Research, Vellanikkara, 2020) Sreedevi, K; KAU; Gopakumar, SThesisItem Open Access Long - term changes in the Indo-Sri Lankan Upwelling System, a perspective to study the impact of climate change in a tropical ocean(Academy of Climate Change Education and Research, Vellanikkara, 2020) Parvathy, V S; KAU; Muraleedharan, K RThesisItem Open Access Vulnerability and adaptation study of women exposed to extreme weather events in Thrissur district(Academy of Climate Change Education and Research, Vellanikkara, 2020) Aiswarya, T Pavanan; KAU; Chitra, ParayilThesisItem Open Access Analysis of soil and water conservation investments in Kerala and farm level financial gains(Department of Agricultural Economics, College of Agriculture, Vellanikkara, 2020) Lokesh, S; KAU; Indira Devi, PClimate change is expected to increase stress on water resources which impacts the agricultural production and farmers’ livelihoods. Tropical high range regions like Wayanad are more vulnerable to climate change because of the faster rate of temperature increase and irregular rainfall pattern. Soil and Water Conservation (SWC) measures assumes significance in such situations in which the gradient, land use and rainfall factors trigger top soil loss. The SWC measures in Wayanad is promoted through four major schemes which are heavily subsidised by the State and Central Governments. This study was taken up with the specific objectives viz., to analyse the institutional credit flow towards soil and water conservation investments in Kerala, to assess the household level investment on soil and water conservation, understand the local preferences for soil/water conservation methods, assess the farm level economic viability and finally efficiency of such investments and understand the farmers’ perceptions on effectiveness of conservation measures. The study was based on both primary data and secondary data. Secondary data on institutional credit support, refinance and rainfall pattern was compiled from various issues of Economic Review, Government of Kerala; Annual Reports and potential linked credit plan documents of NABARD. The samples for the primary data were identified based on the multistage random sampling method. The major interventions in SWC are implemented through four schemes viz. Arable Land Treatment (ALT), Drainage Line Treatment (DLT), Drought Mitigation Scheme (DMS) and Western Ghats Development Scheme (WGDP). Total sample of 360 farmers (30 beneficiaries x 4 schemes x 3 taluks) were identified from the list of beneficiaries collected from the Department of Soil and Water Conservation. One neighboring farmer each to the sample farm was also interviewed. The data was collected through personal interview method employing a structured and pretested interview schedule. The analysis was done using appropriate statistical tools. The major findings of the study are as follows: Institutional credit support to agriculture in Kerala was ₹ 67,089 crore during 2017-18, wherein crop loans constituted major share (72%). The Commercial banks were leading with 65 per cent share. NABARD refinance support to agriculture amounted to ₹ 10024.29 crores. There has been an increasing preference for Non-Farm Sector, which enjoyed two third of total refinance support. Among the major institutions, RRB’s enjoyed the highest share of 33 per cent. In the farm sector, plantation and horticulture sector (31.26%) remained the prime sector in refinance support during the period 1990-91 to 2017-18. The institutional credit support to Wayanad agriculture was ₹ 2469.89 crores (2017-18) which registered a Compound Annual Growth Rate (CAGR) of 18.97 per cent (2007-08 to 2017-18). Though crop loans constituted for 86 per cent of the total credit, the CAGR of term loans was faster (22.77%). Commercial banks were the main provider of credit and plantation and horticulture sector and dairy development sectors were given priority in lending. Considered as the hot spot of climate change in Kerala, the district was regularly facing drought situation and water scarcity was reported as one of the major problems. The irrigated agriculture in the district (44.72% of the respondents) was mainly depending on open wells and facing challenges as the water was enough to irrigate only during 2-3 months. Most of the respondents were middle aged, literate and marginal farmers. The SWC, on an average attracted an investment of ₹ 2,49,217 per household. Overall, nearly 50 per cent (177) of the respondents have adopted SWC structures on individual basis and have paid a share of 10 per cent at the rate of ₹ 24,922/household. About 40 per cent of the respondents adopted on group basis paying a share of five per cent. However, none of the respondents bothered to undertake the annual maintenance of the SWC structures. Impact of SWC measures on cropping pattern, productivity, production and farm income were assessed by comparing it with the situation before the investment. The SWC measures have facilitated the area expansion of ginger (56.94%), banana (38.53%), rubber (32.71%) and turmeric (31.65%). The significance of SWC measures was evident through the positive effect on productivity in all the crops. The significant area expansion and productivity gains in ginger, banana, rubber and turmeric has translated into substantial production gains (95.24% in ginger, 81.80% in banana, 64.77% in rubber, 49.60% in turmeric). The farm income increased to the tune of 45.61 per cent, the major increase being from ginger (95.24%), banana (81.80%), rubber (64.77%) and turmeric (49.60%) cultivation. All the major crops (coffee, pepper, arecanut and banana) performed well with positive indicators of financial viability and efficiency. The relative economic performance with respect to net returns was in the order of arecanut (₹ 4,24,074/ha), banana (₹ 3,42,202), coffee (₹ 2,73,365/ha) and black pepper (₹ 1,86,929/ha). The efficiency of investment as indicated by the BC ratio was in favour of arecanut (5.55) followed by coffee (3.96), banana (3.53) and black pepper (3.26). SWC is expected to improve the water availability and irrigation. Resource use efficiency analysis was done to assess whether it has contributed significantly to the returns. The results confirmed that irrigation has significantly contributed to the returns in arecanut, coffee and pepper. The economic viability of SWC investments was estimated to assess the economic worthiness of the investment as it involves substantial part of public money. The NPW of the investment was positive in all the schemes and averaged at ₹ 3,02,792/farm. DLT scheme was proven to be the best in terms of NPW. The efficiency in investment as measured by the BC ratio was highest in ALT (9.37) which averaged at 2.33, thus confirming the economic efficiency of the investment. IRR averaged at 28 per cent, which is significantly higher than the opportunity cost of capital (interest on fixed investments). The analysis justifies the social investment of SWC, as it leads to higher production and returns which supports the agricultural profession and welfare of the farmers. The impact of SWC measures on farm enterprise diversification, tree diversity, employment generation and ground water level were also found to be positive and helped in improving farm income. The positive externalities of SWC measures were acknowledged by the neighbouring farmers and they were reported to be motivated to adopt the same. However, the adoption of water saving technologies were found to be rather low. The decision to adopt SWC in any farm is decided by demographic, social, economic and institutional factors. Age, education levels, family size and number of literate persons in the family and knowledge on soil erosion influenced the decision to adopt the SWC, in all the cases irrespective of the scheme. Organizational membership also influenced the decisions making except in the case of WGDP scheme. The institutional credit delivery and refinance support in Kerala need to give more focus towards capital formation investments through LT credit support. The analysis justifies the public allocation and investment in SWC measures in farm holdings. The quantified positive impacts and externalities of SWC schemes can be used in educational and awareness creation programmes for wider implementation of the schemes
