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Assam Agricultural University, Jorhat

Assam Agricultural University is the first institution of its kind in the whole of North-Eastern Region of India. The main goal of this institution is to produce globally competitive human resources in farm sectorand to carry out research in both conventional and frontier areas for production optimization as well as to disseminate the generated technologies as public good for benefitting the food growers/produces and traders involved in the sector while emphasizing on sustainability, equity and overall food security at household level. Genesis of AAU - The embryo of the agricultural research in the state of Assam was formed as early as 1897 with the establishment of the Upper Shillong Experimental Farm (now in Meghalaya) just after about a decade of creation of the agricultural department in 1882. However, the seeds of agricultural research in today’s Assam were sown in the dawn of the twentieth century with the establishment of two Rice Experimental Stations, one at Karimganj in Barak valley in 1913 and the other at Titabor in Brahmaputra valley in 1923. Subsequent to these research stations, a number of research stations were established to conduct research on important crops, more specifically, jute, pulses, oilseeds etc. The Assam Agricultural University was established on April 1, 1969 under The Assam Agricultural University Act, 1968’ with the mandate of imparting farm education, conduct research in agriculture and allied sciences and to effectively disseminate technologies so generated. Before establishment of the University, there were altogether 17 research schemes/projects in the state under the Department of Agriculture. By July 1973, all the research projects and 10 experimental farms were transferred by the Government of Assam to the AAU which already inherited the College of Agriculture and its farm at Barbheta, Jorhat and College of Veterinary Sciences at Khanapara, Guwahati. Subsequently, College of Community Science at Jorhat (1969), College of Fisheries at Raha (1988), Biswanath College of Agriculture at Biswanath Chariali (1988) and Lakhimpur College of Veterinary Science at Joyhing, North Lakhimpur (1988) were established. Presently, the University has three more colleges under its jurisdiction, viz., Sarat Chandra Singha College of Agriculture, Chapar, College of Horticulture, Nalbari & College of Sericulture, Titabar. Similarly, few more regional research stations at Shillongani, Diphu, Gossaigaon, Lakhimpur; and commodity research stations at Kahikuchi, Buralikson, Tinsukia, Kharua, Burnihat and Mandira were added to generate location and crop specific agricultural production packages.


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Now showing 1 - 9 of 9
  • ThesisItemOpen Access
    Rainfall Probability Analysis for Crop Planning of Unakoti and West Tripura
    (2021) Ganchaudhuri, Somnath; Sarmah, Kushal
    The rainfall data of two districts of Tripura namely Unakoti and West Tripura for 20 years (2001-2020) were collected from Weather Stations under Airport Authority of India through Regional Meteorological Centre, Guwahati and were used to analyze annual, seasonal, monthly and weekly rainfall using statistical methods. It was also used to find and analyze weekly rainfall probability by using incomplete gamma probability module of WEATHER COCK software. The analyzed data revealed that the average rainfall for the last 20 years of Unakoti and West Tripura district were 2597.5 mm and 2138.4 mm respectively. The rainfall data also revealed that the districts of Unakoti and West Tripura district received about 1510.7 mm and 1272.5 mm during monsoon contributing about 58.2% and 59.5%, respectively to the total rainfall which is highest as compared to any other season. Also rainfall amount along with contribution total rainfall received in other seasons are 206.3 mm (7.9%) and 199.8 mm (9.3%) in post monsoon, 854.3 mm (32.9%) and 566.8 mm (26.5%) during pre monsoon followed by winter. The two districts of Unakoti and West Tripura district received highest rainfall of 500.2 mm and 450.3 mm in May and June respectively. Least rainfall of 5.5 mm and 2.7 mm was received during January in Unakoti and West Tripura respectively. Rainfall probability analysis is one of the most important tools to predict the rainfall of an area. The total annual rainfall of Unakoti at 90%, 75% and 50% probability is predicted to be 1640 mm, 1686 mm and 1722 mm respectively. The total annual rainfall of the West Tripura at 90%, 75% and 50% probability is likely to be 1631 mm, 1847 mm and 2108.4 mm respectively. The SWM 23 for Unakoti and SMW 24 for West Tripura is probably to receive highest rainfall in all the three level of rainfall probabilities (90%, 75% and 50%). Agro-climatic conditions of both the districts are quite similar, hence crops and cropping patterns in both the districts are same and do not vary much. The Risk proof crop which can be best suitable for kharif season are blackgram, greengram in medium and upland, aman rice in medium land and late aman can be grown in lowland condition. The crops which can be grown in rabi season are vegetables like cole crops, tomato, chilli etc along with potato, pea, toria etc. The crops grown in summer include short duration greengram, aush rice, sesame, jute in all land situations while early aush can be grown in lowland.
  • ThesisItemOpen Access
    Impact of modified microclimate on the performance of green gram under different planting systems in Upper Brahmaputra Valley Zone of Assam
    (AAU, Jorhat, 2021) Pathak, Karabi; Neog, Prasanta
    A field experiment was conducted during the summer, 2021 in the Instructional-Cum-Research (ICR) Farm of AAU, Jorhat to study the Impact of modified microclimate on the performance of green gram under different planting systems in UBVZ Assam. The variety SGC-16 was grown in a split-plot design with 3 dates of sowing (D1-20th February, D2-6th March, and D3-20th March) in main plots and three planting systems (P1 – ridge and furrow, P2 – raised bed with two rows in bed and P3 –flat bed ) in sub-plots, with three replications following recommended agronomic practices. Microclimatic parameters such as soil temperature (10 cm depth) and soil moisture content at two depths (0 - 15 cm and 15 - 30 cm) were recorded at regular intervals. The different components of photo-synthetically active radiation (PAR), viz., incident (IPAR), and transmitted (TPAR) were recorded at 7 days intervals using line quantum sensor (Model LQM-70-10) at local noon time (11:30 AM). Crop growth parameters viz., plant height, leaf area index and dry matter accumulation, phenological observations and yield attributing characters, and seed yield were recorded. Agro-climatic indices viz., growing degree day (GDD), heliothermal unit (HTU), phenothermal index (PTI), and heat use efficiency (HUE) for biomass and seed yield were computed following standard procedures. The daily maximum temperature never exceeded 37.6°C, but the daily minimum temperature went below 20°C (up to 12.4°), which was detrimental to the crop. The average soil moisture content in the upper 30 cm soil profile was the highest in the D3 (80.39 mm), followed by D2 (75 mm) and D1 (66.4 mm). As compared to P3, the decrease in weekly evening soil temperatures under P1 and P2 was up to 2.1 and 1.4°C, respectively. Incident PAR (IPAR) during the crop growth season varied from 712 to 1721 μ mol s-1 m-2. In all dates of sowing and planting systems, the lowest transmitted PAR was recorded in the case of D3 date of sowing and in P1, when the crop was with full canopy coverage. The crop took 4 to 11 days, 28 to 35 days, 34 to 43 days, 39 to 50 days, and 62 to 75 days to attain the different phenological events, such as emergence, bud formation, flowering, pod initiation, and physiological maturity, respectively under different sowing dates and planting systems. Irrespective of sowing dates mean maximum leaf area index was recorded in P1 (2.06), followed by P2 (1.91) and P3 (1.77). The biomass production at maturity was highest in D3 (15.6 g plant-1), which decreased in earlier dates of sowing, while it was highest under P1 (14.6 g plant-1), followed by P2 (13.4 g plant-1) and P3 (11.6 g plant-1), irrespective of sowing dates. The seed yield of green gram cultivar SGC-16 sown under different sowing dates and planting systems ranged from 286.3 to 681 kg ha-1 with an overall mean of 509.8 kg ha-1. Irrespective of sowing dates, the highest GDD accumulation in the entire growth period was recorded under the P1 (1010°C day) system, followed by P2 (973°C day) and P3 (930°C day). The accumulation pattern of PTU by the crops under different treatments was similar to that of GDD. HUE for total biomass production and seed yield ranged from 2.61 to 4.01 kg ha-1°C-1 and 0.38 to 0.65 kg ha-1°C-1, respectively. Regression studies showed that there were linear significant relationships between total biomass, seed yield, and max LAI with iPAR .Correlation studies between seed yield, and thermal indices confirmed the existence of a significant and positive correlation between them.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2021) Hussain, Jemima; Deka, R. L.
    The present study investigates the trend in area, production and productivity of winter rice along with meteorological parameters, namely, temperature and rainfall during 1990-2019 and impact assessment of temperatures and rainfall on observed rice yield in the lower Brahmaputra valley (LBV) zone of Assam. In the zone, winter rice covers an area of 5.18 lakh ha with a production of 1.128 million tonnes and productivity of 2169 kg/ha. The rate of change of productivity with respect to linear time trend was found to be 35.82 kg/ha/year in the LBV zone. The decadal compound annual growth rates (CAGR) for winter rice area during 1990-2019 were negative with statistically significant negative growth observed during the decades 1990-1999 and 2010-2019. However, the growth rates for production and productivity were positive in the zone. Maximum growth rate (2.51%) for productivity was observed during the recent decade (2010-2019). Theil Sen’s slope method was used to detect the trends of temperature and rainfall during the growing season of winter rice and Mann-Kendall rank test was applied to understand the statistical significance of the trends. Results revealed that there was a significant increasing trend in maximum temperatures for the months of August, October (Reproductive phase) and November (Maturity phase). Minimum temperature showed increasing trends in August, October and November and decreasing trends in July and September. A significant increase in average temperature during maturity phase was also observed. Rainfall in different months of the growing season of winter rice exhibited no significant trend except for the month of September where it increased significantly by 4.38 mm/year. A strongly balanced district-wise panel data (yield and climatic variables viz. Tmax, Tmin and rainfall during different pheno-phases) was used to assess the impact of climatic variables on the observed yield of winter rice during 1990-2019. Fixed effect regression model based on Hausman test was used to determine the relationship between yield and climatic variables. The coefficient of determination (R2) value revealed that variables included in the model explained variation in observed rice yield up to 71 per cent. Regression results indicated that the maximum temperature during vegetative phase was negatively associated while it was positively associated with yield during reproductive and maturity phases. The minimum temperature during vegetative and reproductive phases was positively correlated with rice yield whereas during maturity phase, it was negatively correlated. Results also revealed the maximum and minimum temperature during vegetative and maturity phases and rainfall during vegetative phase were statistically significant. The maximum and minimum temperature during vegetative and maturity phases played significant role in determining the yield of winter rice during the study period. Rainfall in all the three phases had a negative impact on yield but the extent of impact on yield was negligible compared to that of temperature. Time trend (T) on the observed yield was positive and statistically significant, implying positive effects of technological advancement on the observed yield of winter rice in the study area. The present study is only an indicative of the extent of loss which could be occurring in yield due to changes in the climatic variables. Given the severity of winter rice yields to climatic factors, specific adaptation strategies like adjustment of transplanting time, growing of heat tolerant varieties must be adopted to mute the adverse effects of climatic variables. Availability of timely weather information and the development of climate-resilient varieties are two key options that the researchers and policy makers should urgently address.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2017-07) Chutia, Sumpi
    Crop yield forecasting is an art of predicting crop yields and production before the harvest actually takes place, typically a couple of months in advance. It is very much crucial for the sound planning and policy making in the agricultural sectors of the country. Different types of models viz, crop simulation models, crop weather analysis models and empirical statistical models are generally used to develop district, state and national level yield forecast. Keeping this in view, a study was carried out to develop yield forecast models of winter rice using modified Hendricks and Scholl technique in 14 districts of the Brahmaputra valley of Assam at vegetative (F1) and mid season (F2) stage of the crop. To develop the model, long-term yield data (kg/ha) and weather data on daily basis (maximum temperature, minimum temperature, rainfall, relative humidity morning and evening) were collected for the period 1990-2015. In addition, one extra parameter - BSSH from two locations (Jorhat and Tezpur) for the same period were also collected and utilized to develop forecast models for Golaghat, Jorhat and Sonitpur districts. The daily data were grouped into weekly basis as per requirement of the model. Weekly data were used to prepare simple and weighted weather indices for individual weather variables as well as for interaction of variables. Among the 25 years of yield and weather indices, 22 years data (1990-2012) were used to develop the forecast models and remaining three years data (2013, 2014 and 2015) were used for validation of the models developed. Stepwise regression analysis was executed by trial and error method to obtain the finest combination of predictors at 5% significant level. Result revealed that the model developed for Kamrup district showed good performance compared to other models with highest value of R2 (0.88 & 0.92 in F1 & F2) and with acceptable limit of per cent error, RMSE, nRMSE, MAE and MBE during the process of validation. On the other hand, yield forecast model developed for Bongaigaon district showed poor performance during validation and recorded the highest value of per cent error, RMSE, nRMSE, MAE and MBE compared to other districts during both the forecast (F1 & F2). Interaction of weather variables like Tmax & RH-II, Tmin & RF and Tmin & RH-1 were mainly found to influence the rice yield during F1 and F2 forecast in most of the districts. Forecast model developed after inclusion of BSSH has shown improvement in R2 except Sonitpur district during F1 forecast compared to the model developed without BSSH. Better result was observed in Golaghat district with highest R2 and lowest per cent error, RMSE, nRMSE MAE and MBE compared to Jorhat and Sonitpur. Yield forecast models developed in these three districts showed their dependency on the interaction of BSSH with rainfall as an important weather variable in influencing the winter rice yield. Thus, BSSH data may be included in developing the crop yield forecast models wherever available for better accuracy of forecast.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2019-07) Saikia, Raktim Jyoti; Neog, Prasanta
    A field experiment was conducted during rabi, 2018-19 in the Instructional-Cum-Research (ICR) Farm of Assam Agricultural University, Jorhat to study the impact of thermal and radiation regimes on growth and yield of Potato under varying microenvironments. The cultivar Kufri Jyoti was grown in split plot design with four dates of planting (P1 - 10th Nov, P2 - 20th Nov, P3 - 30th Nov and P4 - 10th Dec) in main plots and mulches (M0 - non mulch, M1 - water hyacinth and M2 - black polythene) in sub-plots, following recommended agronomic practices. Microclimatic parameters like soil temperature (daily), soil moisture and photosynthetically active radiation (PAR) were recorded periodically. Occurrences of different phenological events along with periodic LAI, plant biomass, yield attributing characters and tuber yield were recorded. Phenophase-wise agroclimatic indices viz., growing degree days (GDD), heliothermal unit (HTU), day temperature, phenothermal index (PTI) and heat use efficiency (HUE) were computed following established procedure. The weekly maximum and minimum temperature throughout the crop growth period ranged from 21.3 to 27.2℃ and 8.1 to 16.1℃, respectively. A total of 110.7 mm rainfall from 16 rainy days was received during the growing period and weekly average BSSH ranged from 1.5 to 7.7 hr. The maximum soil moisture depth (mm) was recorded under water hyacinth (85.7 mm) followed by non-mulched (81.2 mm) and lowest under black polythene mulch (79.7 mm). Among different dates of plantings P1 recorded highest (83.3mm) soil moisture depth, followed by P4 (82.0 mm), P2 (81.8 mm) and P3 (81.5 mm). The weekly mean morning and evening soil temperature ranged from 13.6 to 19.3°C and 19.6 to 28.6°C, respectively under different planting dates and mulching treatments. Irrespective of planting dates, soil temperatures under black polythene was higher in morning and evening by 0.8 to 1.9°C and 1.5 to 2.8°C, respectively, while soil temperatures under water hyacinth were 0.3°C to 0.9°C higher in the morning and 0.5 to 2.2°C lower in the evening as compared to non mulched treatment. No considerable difference in incident PAR was observed among mulching treatments. However, it varied considerably when measured at different days in all planting dates. Irrespective of planting dates the reflected PAR increased in later growth period of the crop with the onset of senescence. The lowest (65 μ mol s-1 m-2) RPAR values under black polythene treatment were attributed to greater absorption by black surface. The transmitted PAR was lowest, when measured on 55 DAP with full coverage of canopy, after that it increased again with maturity of the crop. PAR interception was highest on 55 DAP (74.8 %) in all the planting dates and mulching treatments. Among the mulching treatments, crops under water hyacinth recorded highest (80.6%) interception of PAR. The duration of the crop was highest under first date of planting (100.33 days) followed by second (96.7 days), third (90 days) and fourth (87.6 days) date of planting. The maximum leaf area index (LAI) was observed under water hyacinth (2.77) followed by black polythene (2.44) and non-mulched (2.14) treatment. Maximum partitioning of photosynthates towards tuber was found in case of water hyacinth (386.77 g m-2) and lowest in non-mulched (241.63 g m-2). Highest average total dry matter accumulation was obtained in P1 (465.2 g m-2) followed by P2 (431.6 g m-2), P3 (309.6 g m-2) and P4 (284.8 g m-2). The tuber yield was found to be highest on P1 (135.6 q ha-1) followed by P2 (118.3 q ha-1), P3 (86.3 q ha-1) and P4 (60.0 q ha-1). The RUE for tuber yield was highest under water hyacinth (2.35 g MJ-1) followed by black polythene (2.03 g MJ-1) and non-mulched (1.67 g MJ-1) condition. From correlation study it was observed that tuber yield, biomass accumulation and LAI were found significant and positively correlated with PAR interception and RUE as well as with AGDD, AHTU, HUE and PTI. The predictive model have been developed by using stepwise regression to predict tuber yield from radiation and thermal indices with higher R2 value of 0.96 and 0.99, respectively.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2019-07) Hazarika, Sangeeta
    The present research work was carried out for five districts under Upper Brahmaputra Valley Zone of Assam (UBVZ) to find out the probabilities of occurrence of dry and wet spells and onset and withdrawal of rainy season to suggest suitable crop planning in the region. Long term rainfall data were collected from Department of Agrometeorology, AAU, Jorhat and IMD, Pune for all the districts. The probability analysis was carried out by using Markov chain model which calculates the initial, conditional and consecutive probability of occurrence of dry and wet spell and onset and withdrawal of rainy season were determined by using forward and backward accumulation method, result pertaining to which was used for crop planning in different growing season over the region. The highest annual rainfall was recorded in Dibrugarh district (2590.2mm) followed by Tinsukia (2475.7mm), Sivasagar (2022.0 mm), Jorhat (1923.5mm) and lowest in Golaghat (1648.2mm). Seasonal rainfall analysis indicated that, monsoon season receives the highest amount of rainfall with least CV and the winter records the lowest rainfall with a higher CV in all the districts. From the result of initial probability, it was found that there was higher chances of occurrence of wet spell of minimum 10mm of threshold limit from 12th SMW (19th – 25th March) to 41st (8th – 14th Oct) and 42nd SMW( 15th – 21st Oct) in all the districts. The consecutive probability of occurrence of wet spell of two weeks is more than 50% from 13th (26th march – 1st April) and 15th SMW (9th – 15th April) onwards in Sivasagar and Golaghat, respectively whereas the such condition occurs from 12th SMW in rest of the three districts. There was higher chances of getting wet spell of three consecutive weeks of more than 40mm rainfall at different periods in Jorhat (26th – 28th SMW), Sivasagar (25th – 28th ), Dibrugarh (23rd – 31st ) and Tinsukia(22nd – 29th , 31st , 32nd SMW), which may lead to flood like condition in the districts. So, water harvesting of the excess moisture as well as provision of drainage in the crop field is suggested during the aforesaid period. The probabilities of occurrence of dry spell were higher before 12th SMW and after 42nd SMW, but during monsoon season it was found to be very less which indicates that Kharif crops can be grown without any supplemental irrigation. Considering forward accumulation from 9th SMW there was accumulation of 75 mm and 200 mm of rainfall within 13th – 15th SMW and 16th – 19th SMW, respectively in all the districts which indicates that sowing of summer crops can be started within these weeks. Considering forward accumulation from 22nd SMW it was found that within 23rd – 24th SMW and 25th – 26th SMW, there was accumulation of 75mm and 200 mm rainfall, respectively in the districts. The mean week for end of rainy season was found to be within 34th – 37th SMW (20th Aug – 16th Sept) for 300mm rainfall and 31st to 35th SMW (30th Aug – 2nd Sept) for 500 mm rainfall for all the districts. It indicates that delayed sowing of rice crop may be done latest by the week on which rainy season ends after backward accumulation of 500 mm of rainfall. On the other hand sowing of short duration crops with low water requirements may be done latest by the week on which there will be backward accumulation of 300mm of rainfall. Sowing of summer crops such as greengrm, blackgram, ahu rice were suggested to complete within 12th SMW onwards for all the districts. Nursery bed preparation for Sali rice can be started as early as 18th SMW in the district of Jorhat, Dibrugarh and Tinsukia. Sowing of Kharif greengram blackgram could be started after 34th SMW and Rabi crops and sowing of vegetables could be started after 40th SMW.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2019-07) Annie, Mangshatabam; Goswami, B.
    A field experiment was carried out during kharif, 2018 at the Instructional-Cum-Research (ICR) Farm of Assam Agricultural University, Jorhat to study crop-weather relationships of Kharif green gram grown under different micro-climatic environments: MR-I: 25thAug, MR-II: 10th Sep and MR-III: 25th Sep with three varieties: SG-16 , SG-20 and IPBM-02-3, following a split plot (in number) design with four replications.Weekly mean maximum and minimum temperatures,morning and evening relative humidities, duration of bright sunshine hours and pan evaporation ranged from 25.6 to 34.5°C , 11.1 to 25.8°C, 89 to 99%, 59 to 83%, 1.3 to 8.2 Hours and 1.3 to 3.4 mm respectively. Rainfall during the crop growth season was found to be nearly evenly distributed, barring few weeks when there was no rainfall. Biometric observations, viz. leaf area index, plant height, total biomass production, no of pod per plant , no of seeds per pod, Test weight and seed yield were recorded periodically. Meteorological variables showed a near normal distribution during the crop growth period. Total accumulated agro-climatic indices showed a gradual decrease in the three successive micro-climatic regimes irrespective of varieties. Early-sown (MR-I) crop took less number of days from sowing to maturity as compared to late sown crop (MR-II & MR-III). Total biomass differed significantly both in varieties and microclimatic regimes in all the crop growth stages. Highest biomass was found in MR-I and the lowest in MR-III. Similarly, leaf area index (LAI) also differed significantly under microclimatic regimes and varieties at 45 DAS and 60 DAS. Most of the agro-climatic indices and meteorological parameters yielded higher correlation coefficients with final yield irrespective of varieties and microclimatic regimes for all growth stages. Highest correlation coefficient of seed yield (0.965) was obtained against accumulated growing degree days (AGDD) corresponding to physiological maturity stage. Among the mean meteorological parameters, the highest correlation coefficients was found in rainfall, DTRF (0.957), corresponding to the Vegetative stages. A few predictive models involving both accumulated indices and mean parameters were also developed combined over both varieties and microclimatic regimes corresponding to some selected crop growth stages. From the stepwise regression analysis, the most efficient model was found for the accumulated bright sunshine hours (ABSH) and accumulated rainfall (ADRF) corresponding to Pod Initiation stage. Among the mean meteorological parameters, the best model was found for the maximum temperature (MAXT) corresponding to the physiological maturity stages. Lower per cent variations (PCV) were indicative of the fact that the predicted models are very effective under agro-climatic conditions of Jorhat.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2019-07) Das, Parishmita; Deka, R. L.
    A pot experiment was conducted during kharif, 2018 to assess the effect of elevated CO2 and temperature under different transplanting dates on growth and yield of rice variety Ranjit. The treatment composed of three CO2-temperature levels [T0: ambient temperature & ambient CO2, T1: elevated temperature (ambient +1°C) & elevated CO2 (ambient+25% of ambient) and T2: elevated temperature (ambient +2°C) & elevated CO2 (ambient + 50% of ambient)] and three dates of transplanting (D1: 25th June, D2: 10th July and D3: 25th July). The experiment was conducted in three CO2 Temperature Gradient Tunnels (CTGTs) following factorial CRD with 4 replications. Occurrence of different phenological stages like tiller initiation, panicle initiation and flowering was earlier under elevated CO2-Temperature condition which significantly differed with the ambient condition. On the other hand, days to tillering increased whereas days to panicle initiation, flowering and physiological maturity reduced with delay in transplanting. The crop duration was reduced by about 15 days and 8 days under T2 and T1 respectively compared to T0 and by about 10 days and 5 days in D3 and D2 respectively compared to D1. Reduction in the duration of vegetative phase was found to be more distinct than the reproductive and ripening phases. Accumulated agro-climatic indices viz., AMaxT, AMinT, AMeanT and AGDD showed a gradual decline with delay in date of transplanting from 25th June onwards during vegetative, reproductive and maturity stages irrespective of CO2-Temperature treatments. Similarly, accumulated agro-climatic indices decreased under elevated CO2-Temperature during vegetative stage but increased during reproductive and ripening phases of the crop. Plant height and tiller number was recorded highest under T2 followed by T1 compared to T0, which decreased with delay in transplanting. Both plant height and number of tillers differed significantly in CO2-temperature treatment as well as dates of transplanting. Number of panicles hill-1, panicle length, number of filled grains panicle-1 and 1000-grain weight were significantly influenced by elevated CO2-temperature levels and date of transplanting. Number of panicles was greater but filled grains panicle-1 slightly reduced under T2. With respect to dates of transplanting, D2 recorded higher number of panicles hill-1 (17.9) and higher filled grains panicle-1 (156.6). Higher grain yield (55.9g hill-1) attributed to higher number of panicles hill-1 and filled grains panicle-1 was observed under T2 which was at par with T1 and it was statistically significant over ambient. Grain yield significantly reduced (40.6g hill-1) when transplanting was delayed after 10th July. Similarly, straw yield and above ground biomass at harvest were significantly increased with CO2-temperature elevation but reduced with delay in transplanting. Though the interaction effect of CO2-temperature and dates of transplanting on rice yield was not statistically significant, the results revealed that the growth and yield of rice variety Ranjit was found to be better under elevated CO2-temperature levels when transplanted on 10th July.
  • ThesisItemOpen Access
    (AAU, Jorhat, 2019-07) Sharma, Saurabh; Khanikar, P. G.
    Pan coefficient is an important parameter for computation of reference crop evapotranspiration (ETo) from pan evaporation (Epan). In this study the five empiricalapproaches proposed by Snyder (1992), Cuenca (1989), Orang (1998), Allen and Pruit (1991), Pereira et al. (1995) were used to estimate pan coefficient (Kpe) by using weather parameter of Jorhat over 20 years (1996 to 2016). Kpe values obtained from the empirical methods, on regression did not reveal a good fit line with that of the pan coefficient (PMKp) values calculated from FAO Penman-Monteith method which is considered as one of the most accepted methods worldwide. However Snyder method gave best pan coefficient value among all empirical approaches with coefficient of determination (R2 ) value of 0.16, root mean square error (RMSE) value of 0.35, mean absolute deviation (MAD) value of 0.33, correlation coefficient (r) value of 0.42 and percent error (PE) value of 34.29 on monthly basis. Reference Evapotranspiration (EToe) estimated by multiplying Epan values by Kpe values obtained by empirical methods were compared with the reference evapotranspiration values estimated by Penman-Monteith method (PM ETo). On comparison of EToe values from all empirical methods with PM ETo values, evaluation statistics revealed that EToe estimated from Snyder method was closer to PMETo, with R2 value of 0.36, RMSE value of 0.71 mm, MAD value of 0.69 mm, r value of 0.57 and PE value of 24.68% on mean monthly data. Hence Snyder method is assumed to be the best method for calculating ETo using pan coefficient and pan evaporation data. The line graphs drawn among daily EToe of all empirical methods and daily PM ETo revealed that EToe from Snyder method was closer to PM ETo than EToe of other empirical methods. Based on visual comparison as well as from statistical criteria EToe computed from Snyder method gave closer agreement with PM ETo for daily and monthly estimates as compared to other approaches. Moreover the model developed (Equation I) between Epan and PM ETo revealed a strong correlation between the two variables with R2value of 0.938. Another model obtained from regression line fitted with mean daily PM ETo on mean daily EToe from Snyder method showeda good correlation between the two variables (Equation II) with coefficient of determination (R2) value of 0.893. ETo estimated by all the three above mentioned approaches viz. Snyder equation, Equation I and Equation II were ultimately validated with PMETo for the mean daily ETo of individual year 2017 and 2018 and pooled data of two years (2017-18) respectively. On comparison of different EToe values with PM ETo values, evaluation statistics revealed that equation II was the best approach among all the three approaches with lowest RMSE, MAD and PE values for all above mentioned time period. With available Kpe data estimated by Snyder method, EToe (Snyder) can easily be estimated by multiplying pan evaporation data and thenmodel II can be used to get better value of reference evapotranspiration. On the other hand reference evapotranspiration can also be estimated with only the available pan evaporation data by equation I for this region.