Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 4 de 4
Filter
Add more filters










Database
Language
Publication year range
1.
Sci Total Environ ; 935: 173392, 2024 Jul 20.
Article in English | MEDLINE | ID: mdl-38788952

ABSTRACT

Although silicate fertilizer has been recently recognized for its ability to suppress methane (CH4) emissions in paddy fields, the effects of its consecutive application during the rice farming period are still a subject of debate. Moreover, while it was known that silicate fertilizer can mitigate CH4 emissions through several electron acceptors, the effect of additional application of electron acceptors have not been extensively studied. This study evaluated the effect of silicate fertilizer with varying concentrations of iron slag on CH4 emissions and rice yield over the 3 years rice farming period. Seasonal CH4 fluxes exhibited a significant decrease with the application of silicate fertilizer, with the treatment containing 2.5 % iron slag showing the maximum reduction of 35 % in 2020. Additionally, in 2021 and 2022, the application of silicate fertilizer with 2.5 % iron slag resulted in a decrease of total seasonal CH4 emission by 22 % and 23 %, respectively. Rice grain yield exhibited a significant increase with the inclusion of iron slag in the silicate fertilizer, which resulted in a 37 % and 16 % higher yield compared to no-silicate fertilization and no­iron slag silicate fertilization, respectively. Therefore, iron slag-based silicate fertilizer could be a beneficial soil amendment to mitigate CH4 emissions in rice paddy fields and improve rice productivity without negative effects on the atmospheric and soil ecosystem.


Subject(s)
Agriculture , Fertilizers , Iron , Methane , Oryza , Silicates , Methane/analysis , Agriculture/methods , Air Pollutants/analysis
2.
Sci Rep ; 14(1): 5692, 2024 03 08.
Article in English | MEDLINE | ID: mdl-38453974

ABSTRACT

Current agricultural practices are increasingly favoring the biochar application to sequester carbon, enhance crop growth, and mitigate various environmental pollutants resulting from nitrogen (N) loss. However, since biochar's characteristics can vary depending on pyrolysis conditions, it is essential to determine the optimal standard, as they can have different effects on soil health. In this study, we categorized rice husk biochars basis on their pH levels and investigated the role of each rice husk biochar in reducing ammonia (NH3) emissions and promoting the growth of Chinese cabbage in urea-fertilized fields. The findings of this study revealed that the variation in pyrolysis conditions of rice husk biochars and N rates affected both the NH3 emissions and crop growth. The neutral (pH 7.10) biochar exhibited effective NH3 volatilization reduction, attributed to its high surface area (6.49 m2 g-1), outperforming the acidic (pH 6.10) and basic (pH 11.01) biochars, particularly under high N rates (640 kg N ha-1). Chinese cabbage yield was highest, reaching 4.00 kg plant-1, with the basic biochar application with high N rates. Therefore, the neutral rice husk biochar effectively mitigate the NH3 emissions from urea-treated fields, while the agronomic performance of Chinese cabbage enhanced in all biochar amendments.


Subject(s)
Oryza , Soil , Ammonia/analysis , Urea , Temperature , Pyrolysis , Charcoal
3.
Sci Total Environ ; 902: 166174, 2023 Dec 01.
Article in English | MEDLINE | ID: mdl-37562609

ABSTRACT

Climate change, driven by increased greenhouse gas emissions, is a pressing environmental issue worldwide. Flooded rice paddy soils are a predominant source of methane (CH4) emissions, accounting for approximately 11 % of global emissions. Factors such as rice (Oryza sativa L.) cultivar, transplanting date, water management, and soil characteristics significantly influence these emissions. This study aimed to evaluate the CH4 emissions from rice paddies in relation to the cultivar and transplanting date. The experiment included two rice cultivars (an early-maturing cultivar, Unkwang, and a medium-late-maturing cultivar, Samkwang) and four transplanting dates (Times 1-4). In the present study, CH4 emissions were higher with earlier transplanting dates and decreased significantly with delayed transplanting. Weather conditions, such as cumulative mean air temperature, cumulative soil temperature, and total sunshine hours, were positively correlated with total CH4 emissions. The recommended regional transplanting date (Time 3) resulted in the highest rice grain yields for both cultivars. However, the earlier transplanting dates (Time 1 and Time 2) were more effective in improving plant growth characteristics such as rice straw weight, root biomass weight, and chlorophyll content. A significant positive correlation was observed between the root biomass weight of the rice and CH4 emissions in both cultivars, implying that an increase in root biomass weight led to an increase in CH4 emissions. Consequently, adhering to the advised regional transplanting dates is the most sensible approach for transplanting rice seedlings. This ensured lower CH4 emissions without compromising rice productivity or quality for both cultivars. Further research should focus on identifying the most appropriate rice-transplanting dates and management practices to effectively reduce CH4 emissions without compromising rice production.


Subject(s)
Greenhouse Gases , Oryza , Agriculture/methods , Methane/analysis , Soil , Greenhouse Gases/analysis , Nitrous Oxide
4.
Article in English | MEDLINE | ID: mdl-35954699

ABSTRACT

A quick, accurate and cost-effective method for estimating total soil carbon is necessary for monitoring its levels due to its environmentally and agronomically irreplaceable importance. There are several impediments to both laboratory analysis and spectroscopic sensor technology because the former is both expensive and time-consuming whereas the initial cost of the latter is too high for farmers to afford. RGB photography obtained from digital cameras could be used to quickly and cheaply estimate the total carbon (TC) content of the soil. In this study, we developed models to predict soil TC contents across different cropland types including paddy, upland and orchard fields as well as the TC content of the soil combined from all the aforementioned cropland types on a regional scale. Soil colour measurements were made on samples from the Chungcheongnam-do province of South Korea. The soil TC content ranged from 0.045% to 6.297%. Modelling was performed using multiple linear regression considering the soil moisture levels and illuminance. The best soil TC prediction model came from the upland soil and gave training and validation r2 values of 0.536 and 0.591 with RMSE values of 0.712% and 0.441%, respectively. However, the most accurate equation is the one that produces the lowest RMSE value. Hence, although the model for the upland soil was the most stable of all, the paddy soil model which gave training and validation r2 values of 0.531 and 0.554 with RMSE values of 0.240% and 0.199%, respectively, was selected as the best soil TC prediction equation of all due to its comparatively high r2 value and the lowest RMSE of all equations.


Subject(s)
Carbon , Soil , Agriculture/methods , Carbon/analysis , Crops, Agricultural , Photography , Soil/chemistry
SELECTION OF CITATIONS
SEARCH DETAIL
...