Methods of rhizobial inoculation and sowing techniques for Trifolium subterraneum L. establishment in a harsh winter environment

1980 ◽  
Vol 31 (4) ◽  
pp. 703 ◽  
Author(s):  
FW Hely ◽  
RJ Hutchings ◽  
M Zorin
Keyword(s):  
Soil Moisture ◽  
Trifolium Subterraneum ◽  
Fertilizer Application ◽  
Low Fertility ◽  
Winter Climate ◽  
Symbiotic Associations ◽  
Commercial Practice ◽  
Spray Inoculation ◽  
Wide Range ◽  
Commercial Inoculant

Placement of Rhizobium trifolii by vertical band spraying of commercial inoculant in suspension with adsorbing clay and fine lime in the soil, above the fertilizer and below the seed of Trifolium subterraneum L., resulted in better seedling nodulation and establishment on low-fertility problem soils over a wide range of soil moisture conditions, when compared with conventional drill-sowing of inoculated, lime-coated seed. Spray inoculation was especially effective in areas where low winter temperature put substantial stress on development of the symbiotic associations. Seed pelleting required favourable soil moisture to permit movement of the bacteria from the pellet to the rhizosphere. The combination of banded spray inoculation with fungicidal seed dusting significantly increased both the numbers and size of nitrogen-fixing nodules on seedlings, and also young plant growth and winter survival. It is concluded that this technique of simultaneous fertilizer application, seed-bed inoculation and sowing of fungicide-dressed seeds greatly increases the options available in commercial practice, particularly in the harsh winter climate of the Southern Tablelands region of New South Wales.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

2008 ◽  
Vol 88 (5) ◽  
pp. 761-774 ◽  
Author(s):  
J. A. P. Pollacco
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Bulk Density ◽  
Soil Texture ◽  
The United States ◽  
Pedotransfer Functions ◽  
Pedotransfer Function ◽  
Data Set ◽  
Wide Range ◽  
Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

Seed germination response of a noxious agricultural weed Echium plantagineum to temperature, light, pH, drought stress, salinity, heat and smoke

2018 ◽  
Vol 69 (3) ◽  
pp. 326 ◽  
Author(s):  
Singarayer Florentine ◽  
Sandra Weller ◽  
Alannah King ◽  
Arunthathy Florentine ◽  
Kim Dowling ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Drought Stress ◽  
Invasive Weed ◽  
Germination Response ◽  
Elevated Salinity ◽  
Wide Range ◽  
Agricultural Weed ◽  
Soil Seedbank ◽  
Response To Temperature ◽  
Salinity Management

Echium plantagineum is a significant pasture weed in the Mediterranean climatic zone of several countries, including Australia. This invasive weed, introduced as an ornamental into Australia (where it is known as Paterson’s curse), quickly became established and is now a significant weed of agriculture. Although E. plantagineum is a well-established, highly competitive weed that thrives under disturbance and is tolerant of a wide variety of conditions, including varying soil moisture and drought, and some aspects of its ecology remain unknown. This study investigated germination response to temperature and light, pH, soil moisture, salinity, and pre-germination exposure of seed to heat and smoke. Temperature was found to be more influential on germination than light and the species is tolerant to a wide range of pH. However, available moisture may limit germination, as may elevated salinity. Management of this weed requires approaches that minimise soil seedbank input or prevent germination of soil seedbanks.

scholarly journals Prediction Models for the Estimation of Soil Moisture Content

2011 ◽  
Author(s):  
Swathi Gorthi ◽  
Huifang Dou
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Prediction Models ◽  
Recursive Partitioning ◽  
Machine Learning Techniques ◽  
Linear Regression Models ◽  
Remotely Sensed Data ◽  
Modeling Tools ◽  
Wide Range

This paper provides a survey on different kinds of prediction models developed for the estimation of soil moisture content of an area, using empirical information including meteorological and remotely sensed data. The different models employed extend over a wide range of machine learning techniques starting from Basic Linear Regression models through models based on Bayesian framework, Decision tree learning and Recursive partitioning, to the modern non-linear statistical data modeling tools like Artificial Neural Networks. The fundamental mathematical backgrounds, pros and cons, prediction results and efficiencies of all the models are discussed.

scholarly journals Characterizing Soil Physical Properties for Soil Moisture Monitoring with the North Carolina Environment and Climate Observing Network

2012 ◽  
Vol 29 (7) ◽  
pp. 933-943 ◽  
Author(s):  
Weinan Pan ◽  
R. P. Boyles ◽  
J. G. White ◽  
J. L. Heitman
Keyword(s):  
North Carolina ◽  
Soil Moisture ◽  
Physical Properties ◽  
Soil Properties ◽  
Water Content ◽  
Bulk Density ◽  
Soil Physical Properties ◽  
The North ◽  
Wide Range ◽  
Soil Moisture Monitoring

Abstract Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.

scholarly journals Family and childcare support public expenditures and short-term fertility dynamics

2013 ◽  
Vol 60 (3) ◽  
pp. 347-364 ◽  
Author(s):  
Cosmin Enache
Keyword(s):  
Birth Rate ◽  
Crude Birth Rate ◽  
Low Fertility ◽  
Alternative Methods ◽  
Public Expenditures ◽  
Short Term ◽  
Wide Range ◽  
Policy Measures ◽  
Support Policy ◽  
Cash Benefits

In a period of very low fertility, effective family and childcare support policy measures are needed. From a wide range of instruments available to government intervention, we focus on public expenditures effects on short-term fertility. Using a sample of 28 European countries in a panel framework, we found that there is a small positive elasticity of crude birth rate to cash benefits related to childbirth and childrearing provided through social security system. Different public services provided to ease the burden of parents and all other benefits in kind, means or non-means tested, are found to be insignificant. These results are robust to alternative methods of estimation. Controlling for country heterogeneity by religion and by culture, some particularly interesting differences in birth rate determinants were highlighted as well.

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

Adjoint retrieval of prognostic land surface model variables for an NWP model: Assimilation of ground surface temperature

2010 ◽  
Vol 2 (2) ◽  
Author(s):  
Diandong Ren
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Land Surface ◽  
Surface Soil ◽  
Land Surface Model ◽  
Initial Guess ◽  
Surface Model ◽  
Soil Moisture Condition ◽  
Wide Range ◽  
Surface Soil Temperature

AbstractBased on a 2-layer land surface model, a rather general variational data assimilation framework for estimating model state variables is developed. The method minimizes the error of surface soil temperature predictions subject to constraints imposed by the prediction model. Retrieval experiments for soil prognostic variables are performed and the results verified against model simulated data as well as real observations for the Oklahoma Atmospheric Surface layer Instrumentation System (OASIS). The optimization scheme is robust with respect to a wide range of initial guess errors in surface soil temperature (as large as 30 K) and deep soil moisture (within the range between wilting point and saturation). When assimilating OASIS data, the scheme can reduce the initial guess error by more than 90%, while for Observing Simulation System Experiments (OSSEs), the initial guess error is usually reduced by over four orders of magnitude.Using synthetic data, the robustness of the retrieval scheme as related to information content of the data and the physical meaning of the adjoint variables and their use in sensitivity studies are investigated. Through sensitivity analysis, it is confirmed that the vegetation coverage and growth condition determine whether or not the optimally estimated initial soil moisture condition leads to an optimal estimation of the surface fluxes. This reconciles two recent studies.With the real data experiments, it is shown that observations during the daytime period are the most effective for the retrieval. Longer assimilation windows result in more accurate initial condition retrieval, underlining the importance of information quantity, especially for schemes assimilating noisy observations.

scholarly journals Temperature, Moisture, and Seed Treatment Effects on Rhizoctonia solani Root Rot of Soybean

Plant Disease ◽  
2003 ◽  
Vol 87 (5) ◽  
pp. 533-538 ◽  
Author(s):  
A. E. Dorrance ◽  
M. D. Kleinhenz ◽  
S. A. McClure ◽  
N. T. Tuttle
Keyword(s):  
Soil Moisture ◽  
Rhizoctonia Solani ◽  
Root Rot ◽  
Seed Treatment ◽  
Anastomosis Group ◽  
Control Measures ◽  
Root Weight ◽  
Wide Range ◽  
Plant Stand ◽  
Growth Chamber Studies

The effects of temperature and soil moisture on infection and disease development by Rhizoctonia solani on soybean were studied individually. In addition, the anastomosis group of R. solani isolates recovered from soybean from 35 fields in 15 counties was determined. All of the 44 isolates recovered in this study were AG-2-2 IIIB. Five isolates of R. solani were able to infect and colonize soybean roots and hypocotyls at 20, 24, 28, and 32°C in growth chamber studies. The temperatures evaluated in this study were not limiting to the isolates tested. In greenhouse studies, nine R. solani isolates and a noninoculated control were evaluated at 25, 50, 75, and 100% soil moisture holding capacity (MHC). Root weights were greater and percent stand averages higher at 50 and 75% than at 25 or 100% MHC; however, as percentage of control, the main effect on percent moisture for percent stand, plant height, or root weight was not significant. There were significant differences among the isolates for the percent stand, root rot rating, and root fresh weight of soybean in each study. In both temperature and moisture studies, the R. solani isolates could be separated as predominantly causing (i) seed rot, as detected by greatly reduced plant stand; (ii) root rot generally having no effect on plant stand but a high root rot rating and low root weight; or (iii) hypocotyl lesions, having no effect on plant stand, a low root rot score, and a high number of red lesions on the hypocotyl. In the greenhouse seed treatment evaluations of five fungicides, there was no fungicide by isolate interaction using these pathogenic types of R. solani. None of the seed treatments evaluated in this study provided 100% control of the four isolates tested. Due to the wide range of environmental factors that permit R. solani infection and disease on soybeans, other control measures that last all season, such as host resistance, should be emphasized.

Effect of soil moisture and fertilizer application on clonal growth and reproduction in a tristylous weed, Lythrum salicaria

1997 ◽  
Vol 75 (1) ◽  
pp. 46-60 ◽  
Author(s):  
Tarun K. Mal ◽  
Jon Lovett-Doust ◽  
Lesley Lovett-Doust
Keyword(s):  
Soil Moisture ◽  
Clonal Growth ◽  
Spatial Separation ◽  
Field Studies ◽  
Fertilizer Application ◽  
Lythrum Salicaria ◽  
Relative Mass ◽  
Total Length ◽  
Proportional Allocation ◽  
Growth And Reproduction

Clonal growth and reproduction in tristylous Lythrum salicaria L. were examined experimentally, using cloned genotypes of each of the three flower morphs, in field studies involving four moisture and three nutrient treatments. Clonal growth was measured in terms of diameter of clones, number of ramets per clone, and total length of ramets, and an index of reproduction was recorded as the total length of infructescence per clone. Neither clonal growth nor reproduction differed significantly among flower morphs, but both differed significantly as a consequence of both moisture and nutrient treatments. The pattern of seasonal growth indicates that ramet production was restricted mainly to the beginning of the season following vigorous vegetative growth. Although flowering began in June, it was restricted to plants in drier treatments in the water-gradient experiment. Characters intrinsic to tristyly (such as lengths of styles and stamens, and allocation of biomass to stamens and pistil) differed significantly among morphs. Soil moisture levels but not fertilizer treatments significantly affected the size of floral structures and biomass. Although absolute levels of biomass allocation to whole flowers and to attractive structures did not differ significantly among morphs, relative allocation to stamens increased progressively from long morph to mid-morph to short morph, with a corresponding decrease in relative mass of pistil. Although proportional allocation differed significantly among morphs, it was unaffected by moisture treatment, suggesting tight genetic control of herkogamy (spatial separation between anther and stigma). This should maintain the floral polymorphism in different ecological conditions. Key words: Lythrum salicaria, nutrient and water gradients, heterostyly, floral morphometry, floral allocation, clonal growth, sexual reproduction.

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