The role of activated phosphorous sources in enhancing soil quality and rice productivity under saline sodic soil conditions

Soil salinity and sodicity are among the main problems for optimum crop production in areas where rainfall is not enough for leaching of salts out of the rooting zone. Application of organic and Ca-based amendments have the potential to increase crop yield and productivity under saline–alkaline soil environments. Based on this hypothesis, the present study was conducted to evaluate the potential of compost, Ca-based fertilizer industry waste (Ca-FW), and Ca-fortified compost (Ca-FC) to increase growth and yield of maize under saline–sodic soil conditions. Saline–sodic soil conditions with electrical conductivity (EC) levels (1.6, 5, and 10 dS m−1) and sodium adsorption ratio (SAR) = 15, were developed by spiking soil with a solution containing NaCl, Na2SO4, MgSO4, and CaCl2. Results showed that soil salinity and sodicity significantly reduced plant growth, yield, physiological, and nutrient uptake parameters. However, the application of Ca-FC caused a remarkable increase in the studied parameters of maize at EC levels of 1.6, 5, and 10 dS m−1 as compared to the control. In addition, Ca-FC caused the maximum decrease in Na+/K+ ratio in shoot up to 85.1%, 71.79%, and 70.37% at EC levels of 1.6, 5, and 10 dS m−1, respectively as compared to the control treatment. Moreover, nutrient uptake (NPK) was also significantly increased with the application of Ca-FC under normal as well as saline–sodic soil conditions. It is thus inferred that the application of Ca-FC could be an effective amendment to enhance growth, yield, physiology, and nutrient uptake in maize under saline–sodic soil conditions constituting the novelty of this work.

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Richness of Rhizosphere Organisms Affects Plant P Nutrition According to P Source and Mobility

Agriculture ◽

10.3390/agriculture11020157 ◽

2021 ◽

Vol 11 (2) ◽

pp. 157

Author(s):

Jean Trap ◽

Patricia Mahafaka Ranoarisoa ◽

Usman Irshad ◽

Claude Plassard

Keyword(s):

Careful Consideration ◽

Soil Conditions ◽

Organic P ◽

P Nutrition ◽

Soil P ◽

P Acquisition ◽

Complex Interactions ◽

Experimental Trials ◽

The Relationship

Plants evolve complex interactions with diverse soil mutualist organisms to enhance P mobilization from the soil. These strategies are particularly important when P is poorly available. It is still unclear how the soil P source (e.g., mineral P versus recalcitrant organic P) and its mobility in the soil (high or low) affect soil mutualist biological (ectomycorrhizal fungi, bacteria and bacterial-feeding nematodes) richness—plant P acquisition relationships. Using a set of six microcosm experiments conducted in growth chamber across contrasting P situations, we tested the hypothesis that the relationship between the increasing addition of soil mutualist organisms in the rhizosphere of the plant and plant P acquisition depends on P source and mobility. The highest correlation (R2 = 0.70) between plant P acquisition with soil rhizosphere biological richness was found in a high P-sorbing soil amended with an organic P source. In the five other situations, the relationships became significant either in soil conditions, with or without mineral P addition, or when the P source was supplied as organic P in the absence of soil, although with a low correlation coefficient (0.09 < R2 < 0.15). We thus encourage the systematic and careful consideration of the form and mobility of P in the experimental trials that aim to assess the role of biological complexity on plant P nutrition.

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Epidemiological problems. Soil and epidemics. Experimental evidence supporting a causal relationship between soil conditions and the onset of epidemics

Kazan medical journal ◽

10.17816/kazmj50594 ◽

1935 ◽

Vol 31 (3-4) ◽

pp. 533-533

Author(s):

Н. Lotze

Keyword(s):

Experimental Evidence ◽

Causal Relationship ◽

Soil Conditions

A. advocates the theory of Pettenkofer about the role of soil in the emergence of epidemics.

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Impact and uncertainty of climate projections on Alpine catchments using high-resolution models

10.5194/egusphere-egu21-13443 ◽

2021 ◽

Author(s):

Jorge Sebastian Moraga ◽

Nadav Peleg ◽

Simone Fatichi ◽

Peter Molnar ◽

Paolo Burlando

Keyword(s):

Climate Change ◽

High Resolution ◽

Climate Variability ◽

Soil Conditions ◽

Internal Climate Variability ◽

Mountainous Catchments ◽

Precipitation Decrease ◽

Alpine Catchments ◽

Impacts Of Climate Change

<p>Hydrological processes in mountainous catchments will be subject to climate change on all scales, and their response is expected to vary considerably in space. Typical hydrological studies, which use coarse climate data inputs obtained from General Circulation Models (GCM) and Regional Climate Models (RCM), focus mostly on statistics at the outlet of the catchments, overlooking the effects within the catchments. Furthermore, the role of uncertainty, especially originated from natural climate variability, is rarely analyzed. In this work, we quantified the impacts of climate change on hydrological components and determined the sources of uncertainties in the projections for two mostly natural Swiss alpine catchments: Kleine Emme and Thur. Using a two-dimensional weather generator, AWE-GEN-2d, and based on nine different GCM-RCM model chains, we generated high-resolution (2 km, 1 hour) ensembles of gridded climate inputs until the end of the 21<sup>st</sup> century. The simulated variables were subsequently used as inputs into the fully distributed hydrological model Topkapi-ETH to estimate the changes in hydrological statistics at 100-m and hourly resolutions. Increased temperatures (by 4&#176;C, on average) and changes in precipitation (decrease over high elevations by up to 10%, and increase at the lower elevation by up to 15%) results in increased evapotranspiration rates in the order of 10%, up to a 50% snowmelt, and drier soil conditions. These changes translate into important shifts in streamflow seasonality at the outlet of the catchments, with a significant increase during the winter months (up to 40%) and a reduction during the summer (up to 30%). Analysis at the sub-catchment scale reveals elevation-dependent hydrological responses: mean annual streamflow, as well as high and low flow extremes, are projected to decrease in the uppermost sub-catchments and increase in the lower ones. Furthermore, we computed the uncertainty of the estimations and compared them to the magnitude of the change signal. Although the signal-to-noise-ratio of extreme streamflow for most sub-catchments is low (below 0.5) there is a clear elevation dependency. In every case, internal climate variability (as opposed to climate model uncertainty) explains most of the uncertainty, averaging 85% for maximum and minimum flows, and 60% for mean flows. The results highlight the importance of modelling the distributed impacts of climate change on mountainous catchments, and of taking into account the role of internal climate variability in hydrological projections.</p>

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Justification of elements of rice cultivation technology

E3S Web of Conferences ◽

10.1051/e3sconf/202017501006 ◽

2020 ◽

Vol 175 ◽

pp. 01006 ◽

Cited By ~ 1

Author(s):

Nadezhda Malysheva ◽

Anna Khadzhidi ◽

Evgeny Kuznetsov ◽

Noureldin Sharaby ◽

Alexander Koltsov

Keyword(s):

Soil Fertility ◽

Crop Rotation ◽

Rice Variety ◽

Sprinkler Irrigation ◽

Rice Fields ◽

Water Soluble ◽

Rice Crop ◽

Soil Conditions ◽

Rice Productivity ◽

The Impact

The purpose of the research is to identify the impact of sprinkler irrigation in rice crop rotation on rice productivity and soil fertility of irrigated lands of the Krasnodar region. To achieve this goal, the tasks of studying the density of weed seedlings after sprinkler irrigation, the content of water-soluble salts and humus in the soil of rice fields, and the reaction of an intensive variety of rice cultivated after irrigation and drainage techniques in rice fields were completed. Material and methods. Field studies were carried out on the Kuban irrigation system of the Krasnodar territory, which is the most typical in terms of soil conditions for the western climatic zone of the region, with various variants for sprinkler irrigation after major planning of basins. An intensive of Rapan rice variety was used. The methods of the Federal Research Center for Rice, the Kuban State Agrarian University, and Russian standards were applied. Conclusions, the obtained results of the conducted studies prove the effectiveness of sprinkler irrigation in rice crop rotation, increase soil fertility, rice productivity, and contribute to the production of environmentally friendly products without herbicides treatment.

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

Water ◽

10.3390/w11102169 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2169 ◽

Cited By ~ 4

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.

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