scholarly journals Optimizing rice plant photosynthate allocation reduces N2O emissions from paddy fields

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Yu Jiang ◽  
Xiaomin Huang ◽  
Xin Zhang ◽  
Xingyue Zhang ◽  
Yi Zhang ◽  
...  
Keyword(s):  
Rice Plant ◽  
Paddy Fields ◽  
N2o Emissions ◽  
Photosynthate Allocation

Cultivation of rice for animal feed with circulated irrigation of treated municipal wastewater for enhanced nitrogen removal: comparison of cultivation systems feeding irrigation water upward and downward

2015 ◽  
Vol 72 (4) ◽  
pp. 579-584 ◽  
Author(s):  
A. Muramatsu ◽  
H. Ito ◽  
A. Sasaki ◽  
A. Kajihara ◽  
T. Watanabe
Keyword(s):  
Nitrogen Removal ◽  
Irrigation Water ◽  
Rice Plant ◽  
Municipal Wastewater ◽  
Animal Feed ◽  
Paddy Fields ◽  
Treated Wastewater ◽  
Human Consumption ◽  
Cultivation System ◽  
Treated Municipal Wastewater

To achieve enhanced nitrogen removal, we modified a cultivation system with circulated irrigation of treated municipal wastewater by using rice for animal feed instead of human consumption. The performance of this modified system was evaluated through a bench-scale experiment by comparing the direction of circulated irrigation (i.e. passing through paddy soil upward and downward). The modified system achieved more than three times higher nitrogen removal (3.2 g) than the system in which rice for human consumption was cultivated. The removal efficiency was higher than 99.5%, regardless of the direction of circulated irrigation. Nitrogen in the treated municipal wastewater was adsorbed by the rice plant in this cultivation system as effectively as chemical fertilizer used in normal paddy fields. Circulated irrigation increased the nitrogen released to the atmosphere, probably due to enhanced denitrification. Neither the circulation of irrigation water nor its direction affected the growth of the rice plant and the yield and quality of harvested rice. The yield of rice harvested in this system did not reach the target value in normal paddy fields. To increase this yield, a larger amount of treated wastewater should be applied to the system, considering the significant amount of nitrogen released to the atmosphere.

scholarly journals Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2169 ◽  
Author(s):  
Tabassum Abbasi ◽  
Tasneem Abbasi ◽  
Chirchom Luithui ◽  
Shahid Abbas Abbasi
Keyword(s):  
Nitrous Oxide ◽  
Paddy Fields ◽  
Anthropogenic Sources ◽  
Nitrous Oxide Emissions ◽  
Soil Conditions ◽  
N2o Emissions ◽  
Ch4 Emissions ◽  
Artificial Neural ◽  
Ch4 And N2o

Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available.

scholarly journals Effects of Green Manure Application and Prolonging Mid-Season Drainage on Greenhouse Gas Emission from Paddy Fields in Ehime, Southwestern Japan

Agriculture ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 29 ◽  
Author(s):  
Yo Toma ◽  
Nukhak Nufita Sari ◽  
Koh Akamatsu ◽  
Shingo Oomori ◽  
Osamu Nagata ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Green Manure ◽  
Greenhouse Gas Emission ◽  
Rice Paddy ◽  
Paddy Fields ◽  
N2o Emissions ◽  
Gas Emission ◽  
Manure Application ◽  
Ch4 And N2o ◽  
Rice Paddy Fields

Green manure application helps maintain soil fertility, reduce chemical fertilizer use, and carbon sequestration in the soil. Nevertheless, the application of organic matter in paddy fields induces CH4 and N2O emissions. Prolonging mid-season drainage reduces CH4 emissions in paddy fields. Therefore, the combined effects of green manure application and mid-season drainage prolongation on net greenhouse gas emission (NGHGE) were investigated. Four experimental treatments were set up over a 2-year period: conventional mid-season drainage with (CMG) and without (CM) green manure and prolonged (4 or 7 days) mid-season drainage with (PMG) and without (PM) green manure. Astragalus sinicus L. seeds were sown in autumn and incorporated before rice cultivation. No significant difference in annual CH4 and N2O emissions, heterotrophic respiration, and NGHGE between treatments were observed, indicating that green manure application and mid-season drainage prolongation did not influence NGHGE. CH4 flux decreased drastically in PM and PMG during mid-season drainage under the hot and dry weather conditions. However, increasing applied carbon increases NGHGE because of increased CH4 and Rh. Consequently, combination practice of mid-season drainage prolongation and green manure utilization can be acceptable without changing NGHGE while maintaining grain yield in rice paddy fields under organically managed rice paddy fields.

scholarly journals Direct N2O emissions from rice paddy fields: Summary of available data

2005 ◽  
Vol 19 (1) ◽  
Author(s):  
Hiroko Akiyama ◽  
Kazuyuki Yagi ◽  
Xiaoyuan Yan
Keyword(s):  
Rice Paddy ◽  
Paddy Fields ◽  
N2o Emissions ◽  
Rice Paddy Fields

Changes in fertilizer-induced direct N2O emissions from paddy fields during rice-growing season in China between 1950s and 1990s

2009 ◽  
Vol 15 (1) ◽  
pp. 229-242 ◽  
Author(s):  
JIANWEN ZOU ◽  
YAO HUANG ◽  
YANMEI QIN ◽  
SHUWEI LIU ◽  
QIRONG SHEN ◽  
...  
Keyword(s):  
Growing Season ◽  
Paddy Fields ◽  
N2o Emissions ◽  
Rice Growing Season

The effect of floating vegetation on CH4 and N2O emissions from subtropical paddy fields in China

2014 ◽  
Vol 13 (4) ◽  
pp. 425-431 ◽  
Author(s):  
Chun Wang ◽  
Shouchun Li ◽  
Derrick Y. F. Lai ◽  
Weiqi Wang ◽  
Yongyue Ma
Keyword(s):  
Paddy Fields ◽  
N2o Emissions ◽  
Floating Vegetation ◽  
Ch4 And N2o

Assessment of a three-stage sampling strategy to investigate the spatial distribution and population density of Aphelenchoides besseyi among Oryza sativa seeds

Nematology ◽  
2010 ◽  
Vol 12 (3) ◽  
pp. 373-380
Author(s):  
Katsumi Togashi ◽  
Shigeru Hoshino
Keyword(s):  
Spatial Distribution ◽  
Oryza Sativa ◽  
Paddy Field ◽  
Rice Plant ◽  
Spatial Scales ◽  
Sampling Strategy ◽  
Paddy Fields ◽  
Nematode Density ◽  
Aphelenchoides Besseyi ◽  
The Mean

AbstractThis study aimed to determine the spatial distribution patterns of Aphelenchoides besseyi among Oryza sativa seeds on panicle, plant hill, and paddy field spatial scales and to present a three-stage sampling method for estimating the mean density per seed in paddy fields. Living and dead nematodes were extracted individually from 20 seeds sampled from each of five panicles, which were sampled from each of six rice plant hills in each of eight paddy fields, where all plants had leaves exhibiting the 'white tip' symptom. Nested ANOVA indicated that A. besseyi density per seed was significantly different among the eight paddy fields, among rice plant hills in paddy fields, and among panicles in rice plant hills. The proportion of nematode-infested seeds (prevalence) increased and reached an upper limit as the mean density per seed on the panicle scale increased, whereas linear relationships were observed between nematode prevalence and the mean density on plant hill and paddy field scales. Relationships between mean density and mean crowding of nematodes per seed indicated that the nematodes exhibited clumped distribution on each of panicle, plant hill and field scales. Using these relationships, a three-stage sampling plan for estimating nematode density per seed at a specified precision level is presented.

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