Showing papers in "Journal of Agrometeorology in 2017"

Effect of sowing time on productivity and thermal utilization of mustard (Brassica juncea) under sub-tropical irrigated conditions of Jammu.

Abstract: Field experiments were conducted to study the effect of weather variability on mustard crop at Research Farm of Agromet Research Centre, SKUAST-J, Chatha, Jammu during rabi seasons of 201011 to 2012-13. Treatments were comprised of three sowing dates (9 th October, 24 th October and 8 th November) and two cultivars of mustard (RL-1359 and RSPR-01). The results revealed that days taken to physiological maturity and yield reduced significantly with delayed sowing. Mustard crop sown on 9 th October utilised more thermal, and heat units as compared to 24 th October and 8 th November sown crops. The shortening of the duration of the crop sown late was due to forced maturity because of higher temperature during reproductive phase of the crop. Heat use efficiency (HUE) was found to be higher for earlier sown crop and it decreased with delay in sowing. Correlation studies indicated that lower night temperature during vegetative phase is favourable and higher day temperature during reproductive phase is not favourable for mustard yield.

Climate change impacts vis-a-vis productivity of soybean in Vertisol of Madhya Pradesh

Abstract: The impact of climate change on agricultural crops is a major concern and threats to the global food security. It also limits the potential of crops and cropping system in a given area. Therefore, the present study was aimed to assess the combined effect of positive (CO2 fertilization, lesser temperature and higher rainfall) and negative (higher temperature, lower rainfall) impacts of the futuristic climatic scenarios on productivity of soybean using APSIM (Agricultural Production Systems sIMulator) model. We have followed the Climate-Crop Modeling Project (C3MP) methodology and generated ninety-nine sensitive test to achieve each test’s temperature, rainfall and CO2 concentration range. Using 30 years of climate data (1980-2010) of Central India as base, the simulation results showed that increasing CO 2 concentrations alone resulted in increased soybean yield. Similarly, reduction in rainfall amount indicated negative impact on it. This effect further compounded with increase in temperature and thus, reduced soybean yield. Increasing the temperature with 10% decrease in rainfall declined the soybean yield by 10%. Whereas, increase in temperature along with increase in rainfall also not resulted favorably soybean growth. Decreasing the temperature from the base by 1oC and increasing the rainfall by more than 10% benefitted the soybean productivity, whereas increasing the temperature by 1oC with no change in rainfall resulted decline in soybean productivity by 10-15%.

Comparison and evaluation of selected evapotranspiration models for Ludhiana district of Punjab.

Abstract: Evapotranspiration is the key component of hydrologic cycle.Its precise estimation is of vital importance for studying hydrologic water balance, crop yield simulation and design of irrigation systems (Kumar et al., 2011; Parasuraman et al., 2007).Various methods are employed to measure the evapotranspiration, but owing to difficulty in getting precise evapotranspiration measurement directly, it is generally estimated from meteorological data with the help of different models.Several studies have been conducted to compare and evaluate the performance of different ET models (Kingra and Mahey 2009; Kingra et al., 2002, Jadhav et al., 2015;Sibale et al., 2015; Prasad and Kumar, 2013). In the present study the performance of different evapotranspiration models were evaluated and compared with pan evaporation for their use in Ludhiana district of Punjab using 21 years (1995-2015) of data obtained from School of Agrometeorology and Climate Change, PAU, Ludhiana.

Projecting future changes in water requirement of grain sorghum in India

Abstract: The spatial distribution and trend in rainfall and crop water requirement for sorghum during different time periods viz. baseline (1981-2010) and two future climate epochs (2021-2050 and 2051- 2080) over all major sorghum (kharif and rabi) growing regions of India was studied using climate change projections data from NorESM-1M model of the CMIP-5 in RCP4.5 scenario. A significant decreasing trend in kharif season rainfall is noticed during 2021-2050 over Madhya Pradesh. Majority of the kharif and rabi sorghum growing regions may receive more rainfall during 2051-2080. Increasing trend is projected for crop water requirement over majority of sorghum regions in both seasons with significant increase over the core growing area of rabi sorghum. Regions were identified where moisture stress is likely to be severe during kharif and rabi seasons.

A comparative assessment of crop phenology, agrometeorological indices and yield of Bt and non-Bt cotton in Akola, Maharashtra.

Abstract: Cotton production has influenced the economic development of many nations throughout the world. The area under Bt cotton increased from a mere 0.05 million hectare during 2002-03 to 11.6 million hectare in 2013-14 which account 94.6 per cent of cotton area (Choudhary and Gaur, 2015).The agronomic performance of Bt cultivars may vary substantially from their non-Bt counterparts (Jenkins et al., 1997).Taking into consideration the above aspects, it was felt necessary to conduct the experiment to evaluate the Bt cotton hybrid for its morpho-phenological event, agrometeorological indices and yield in relation to agronomical intervention over its non-Bt version.

Heat utilization and productivity of summer transplanted rice (Oryza sativa L.) in relation to irrigation schedules and date of transplanting.

Abstract: A study was undertaken at Regional Research and Technology Transfer Station, Chiplima, Sambalpur, Odisha on rice var. khandagiri during summer season of 2011, 2012 and 2013 in split plot design with three irrigation schedule (main plots) and three date of transplanting (sub plots). Experimental results indicated that the irrigation schedules at one day after disappearance of ponded water (DPW) recorded the highest grain yield of 3.07 t ha-1 which was at par with irrigation schedule at 2-days after DPW. Both the irrigation schedules were significantly superior over 3-days after DPW. The date of transplanting on 15th January produced highest grain yield (3.11t ha-1) which was significantly superior to other transplanting date on 30 th January and 15 th February. Highest water use efficiency was observed with irrigation schedule at 3-days after DPW (43.7 kg ha-cm -1) and transplanting on 15 th January(43.2 kg ha-cm-1). The treatment that received irrigation schedule at 1-day after DPW registered the highest dry matter heat use efficiency (3.62 kg ha -10C day-1) and grain yield heat use efficiency(1.84 kg ha -10C day-1).The transplanting on 15 th January produced highest dry matter heat use efficiency(3.83 kg ha-10C day-1) and grain yield heat use efficiency(2.05 kg ha-10C day-1) which was significantly superior to other transplanting dates of 30 th January and 15th February.

Evaluation of CERES-rice model for Upper Brahmaputra Valley Zone of Assam.

Abstract: Rice (Oryza sativa) is the single most important food crop of Assam.In spite of technological advancement, rice is a risky enterprise under unfavorable climatic environment, which seems to be increased in future due to increase in climate change related weather variability. As rice is sensitive to weather and various rice cultivars response to different environment in dissimilar way, it is desirable to identify the potential of the crop and to better understanding of cultivars, soil and weather interactions. For this purpose, crop growth models such as those in Decision Support System for Agro technology Transfer (DSSAT) have been used successfully in many places around the world for a wide range of conditions and applications (Hoogenboom et al., 2010).Usually in many cases the models are found site as well as crop specific and are not always relevant for other regions. Thus their applicability needs to be evaluated; generally when such models are introduced into a new region. The CERESRice model has been successfully adopted in Indian condition and successfully calibrated by many workers (Kumar et al., 2007, Singh et al., 2015, Vysakh et al., 2016) to predict phenology and grain yield of rice accurately. Thus, the present study was undertaken to calibrate and validate CERES-Rice model for two rice cultivars (Luit and TTB404) for Upper Brahmaputra Valley Zone (UBVZ) of Assam.