A.K. Nayak

Nitrate leaching, nitrous oxide emission and N use efficiency of aerobic rice under different N application strategy

ABSTRACT A field study was conducted in the sub-humid tropical region of India to examine the effect of different nitrogen (N) management strategies on nitrate leaching, nitrous oxide (N2O) emission and N use efficiency in aerobic rice. Treatments were: control (no N), 120 kg N ha−1 applied as prilled urea (PU) in conventional method, 120 kg N ha−1 applied as neem coated urea (NCU) in conventional method, N applied as PU on the basis of leaf colour chart (LCC) reading, N applied as NCU on the basis of LCC reading, and 120 kg N ha−1 applied as PU and farm yard manure (FYM) in 1:1 ratio. Results showed that 3.4–16.1 kg NO3-N ha−1 was leached below 45 cm depth and 0.61–1.12 kg N2O-N ha−1 was emitted from aerobic rice during the growing season. NCU when applied conventionally reduced nitrate-nitrogen (NO3-N) leaching and N2O emission by 18.6% and 21.4%, respectively However when applied on the basis of LCC reading NCU reduced NO3-N leaching by 39.8% as compared to PU applied in conventional method. NCU when applied on the basis of LCC reading synchronized N supply with demand and reduced N loss, which resulted in higher yield and N use efficiency.

Effects of water deficit stress on agronomic and physiological responses of rice and greenhouse gas emission from rice soil under elevated atmospheric CO2

Rice is the foremost staple food in the world, safeguarding the global food and nutritional security. Rise in atmospheric carbon dioxide (CO2) and water deficits are threatening global rice productivity and sustainability. Under real field conditions these climatic factors often interact with each other resulting in impacts that are remarkably different compared to individual factor exposure. Rice soils exposed to drought and elevated CO2 (eCO2) alters the biomass, diversity and activity of soil microorganisms affecting greenhouse gas (GHG) emission dynamics. In this review we have discussed the impacts of eCO2 and water deficit on agronomic, biochemical and physiological responses of rice and GHGs emissions from rice soils. Drought usually results in oxidative stress due to stomatal closure, dry weight reduction, formation of reactive oxygen species, decrease in relative water content and increase in electrolyte leakage at almost all growth and developmental phases of rice. Elevated atmospheric CO2 concentration reduces the negative effects of drought by improving plant water relations, reducing stomatal opening, decreasing transpiration, increasing canopy photosynthesis, shortening crop growth period and increasing the antioxidant metabolite activities in rice. Increased scientific understanding of the effects of drought and eCO2 on rice agronomy, physiology and GHG emission dynamics of rice soil is essential for devising adaptation options. Integration of novel agronomic practices viz., crop establishment methods and alternate cropping systems with improved water and nutrient management are important steps to help rice farmers cope with drought and eCO2. The review summarizes future research needs for ensuring sustained global food security under future warmer, drier and high CO2 conditions.

Characterization of land surface energy fluxes in a tropical lowland rice paddy

A field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxes were measured by eddy covariance (EC) system (make Campbell Scientific) in dry season (DS, 1–125 Julian days), dry fallow (DF, 126–181 Julian days), wet season (WS, 182–324 Julian days), and wet fallow (WF, 325–365 Julian days). The rice was cultivated in dry season (January–May) and wet season (July–November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00xa0h until evening 18:00xa0h. Mean soil temperature (Tg) was highest in DF, while the skin temperature (Ts) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43xa0kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.

Greenhouse gas emissions and energy exchange in wet and dry season rice: eddy covariance-based approach

AbstractLowland tropical rice-rice system has a unique micrometrological characteristic that affects both energy component and net ecosystem energy. Periodic and seasonal variations of methane (CH4), carbon dioxide (CO2), and energy exchange from irrigated lowland rice-rice ecosystem were studied using open-path eddy covariance (EC) system during the dry (DS) and wet (WS) seasons in 2015. Concurrently, the manual chamber method was employed in nitrous oxide (N2O) measurement efflux. Cumulative net ecosystem carbon exchange (NEE) was observed highest (−u2009232.55xa0g C m−2) during the WS and lowest (−u200914.81xa0g C m−2) during wet fallow (WF). Similarly, the cumulative net ecosystem methane exchange (NEME) was found highest (13,456.5xa0mg CH4 m−2) during the WS and lowest (2014.3xa0mg CH4 m−2) during the WF. Surface energy fluxes, i.e., sensible (Hs) and latent heat (LE) fluxes, showed a similar trend. With the advancement of time, the ratio of ecosystem respiration (Re) and gross primary production (GPP) increased. The cumulative global warming potential (GWP) for the two cropping seasons including two fallows was 13,224.1xa0kg CO2 equivalent ha−1. The GWP and NEME showed a similar trend as soil enzymes and labile carbon pools in both seasons (except GWP at the harvesting stage in the wet season). The mean NEE exhibited a more negative value with decrease in labile pools from panicle initiation to harvesting stage in the WS. Soil labile C and soil enzymes can be used as an indicator of NEE, NEME, and GWP in lowland rice ecology.n Graphical abstractSchematic presentation of GHG emission and energy exchange in lowland rice

Root Activity and Antioxidant Enzyme Activities of Rice Cultivars under Different Iron Toxicity Mitigation Options

Iron (Fe) toxicity is a widespread environmental problem of rice growing area in many parts of the world. Amendments and genotypes can be used to mitigate the Fe toxicity. Several strategies may be adopted by higher plants to cope up with high levels of soluble Fe in their environment. A field experiment was carried out in acidic laterite soil having 400 mg kg−1 di-ethylene tri-amine-penta-acetic acid extractable Fe (DTPA-Fe) to assess the root activity and antioxidant enzyme activities of rice cultivars under different soil management options in Fe toxic soil. The treatments comprised of four cultivars (two each tolerant and susceptible) and six amendments. The amendments resulted into the increase in soil pH as compared to the control, which helps in mitigation of Fe toxicity. Tolerant cultivars recorded significantly higher rice root oxidation and Fe plaque deposition as compared to sensitive cultivars under all the soil management treatments. Cultivars also differed significantly in the amount of Fe plaque on the roots under control. Iron concentration in the roots showed a reverse trend as compared to Fe oxidation and Fe plaque for all the cultivars and soil management treatments. Under high toxic Fe level (control), due to high activity of peroxidase (POD), catalase (CAT) and superoxide dismutase (SOD) mechanisms of antioxidative defense were more active for tolerant cultivars as compared to susceptible cultivars. The effect of defense mechanism of the tolerant cultivars is manifested in yield and under control condition, higher yield were reported for tolerant cultivars as compared to susceptible. Lime application is the most effective way to overcome the Fe toxicity, which increased the yield of both the tolerant and susceptible rice cultivars. Rice roots plays important role in alleviating the Fe toxicity by oxidizing the Fe2+ and excluding its uptake. Iron resistance of the tolerant cultivars is also attributed to the comparatively high levels of POD, CAT, and SOD activities in the leaf tissues. The differential response of the cultivars to the Fe-toxicity is due to differential ability of Fe compartmentation, root oxidation power and ability of cultivars to produce antioxidative stress enzymes. The mechanisms of Fe toxicity tolerance both in plant and soil are result of combined effect of genetics of the crop plant and management interventions.

Forecasting Rice Productivity and Production of Odisha, India, Using Autoregressive Integrated Moving Average Models

Forecasting of rice area, production, and productivity of Odisha was made from the historical data of 1950-51 to 2008-09 by using univariate autoregressive integrated moving average (ARIMA) models and was compared with the forecasted all Indian data. The autoregressive () and moving average () parameters were identified based on the significant spikes in the plots of partial autocorrelation function (PACF) and autocorrelation function (ACF) of the different time series. ARIMA (2, 1, 0) model was found suitable for all Indian rice productivity and production, whereas ARIMA (1, 1, 1) was best fitted for forecasting of rice productivity and production in Odisha. Prediction was made for the immediate next three years, that is, 2007-08, 2008-09, and 2009-10, using the best fitted ARIMA models based on minimum value of the selection criterion, that is, Akaike information criteria (AIC) and Schwarz-Bayesian information criteria (SBC). The performances of models were validated by comparing with percentage deviation from the actual values and mean absolute percent error (MAPE), which was found to be 0.61 and 2.99% for the area under rice in Odisha and India, respectively. Similarly for prediction of rice production and productivity in Odisha and India, the MAPE was found to be less than 6%.