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20213
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Subject: Agricultural Meteorology × End date: 2021 × Start date: 2021 ×
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    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.
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    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.
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    ThesisItemOpen Access
    ASSESSMENT OF CLIMATE CHANGE IMPACT ON RICE PRODUCTIVITY IN THE LOWER BRAHMAPUTRA VALLEY (LBV) ZONE OF ASSAM
    (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.