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 Determination of Germination Response to Temperature and Water Potential for a Wide Range of Cover Crop Species and Related Functional Groups

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0161185 ◽  
Author(s):  
Hélène Tribouillois ◽  
Carolyne Dürr ◽  
Didier Demilly ◽  
Marie-Hélène Wagner ◽  
Eric Justes
Keyword(s):  
Water Potential ◽  
Functional Groups ◽  
Cover Crop ◽  
Crop Species ◽  
Germination Response ◽  
Wide Range ◽  
Response To Temperature

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.

Variation of seed germination response to temperature in tomato landraces: An adaptation strategy to environmental conditions

2021 ◽  
Vol 281 ◽  
pp. 109987
Author(s):  
Naeimeh Sousaraei ◽  
Benjamin Torabi ◽  
Kambiz Mashaiekhi ◽  
Elias Soltani ◽  
Seyyed Javad Mousavizadeh
Keyword(s):  
Seed Germination ◽  
Environmental Conditions ◽  
Adaptation Strategy ◽  
Germination Response ◽  
Response To Temperature

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

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 Woody species do not differ in dormancy progression: differences in time to budbreak due to forcing and cold hardiness

2021 ◽  
Author(s):  
Al Kovaleski
Keyword(s):  
Maximum Rate ◽  
Path Length ◽  
Cold Hardiness ◽  
Woody Species ◽  
Two Dimensions ◽  
Spring Phenology ◽  
Wide Range ◽  
The Difference ◽  
Response To Temperature ◽  
Phenological Phases

AbstractBudbreak is one of the most observed and studied phenological phases in perennial plants. Two dimensions of exposure to temperature are generally used to model budbreak: accumulation of time spent at low temperatures (chilling); and accumulation of heat units (forcing). These two effects have a well-established negative correlation: the more chilling, the less forcing required for budbreak. Furthermore, temperate plant species are assumed to vary in amount of chilling required to complete endodormancy and begin the transition to breaking bud. Still, prediction of budbreak remains a challenge. The present work demonstrates across a wide range of species how bud cold hardiness must be accounted for to study dormancy and accurately predict time to budbreak. Cold hardiness defines the path length to budbreak, meaning the difference between the cold hardiness buds attain during the winter, and the cold hardiness at which deacclimated buds are predicted to open. This distance varies among species and throughout winter within a species. Increases in rate of cold hardiness loss (deacclimation) measured throughout winter show that chilling controls deacclimation potential – the proportion of the maximum rate response attained at high chill accumulation – which has a sigmoid relationship to chilling accumulation. For forcing, rates of deacclimation increase non-linearly in response to temperature. Comparisons of deacclimation potential show a dormancy progresses similarly for all species. This observation suggests that comparisons of physiologic and genetic control of dormancy requires an understanding of cold hardiness dynamics and the necessity for an update of the framework for studying dormancy and its effects on spring phenology.

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.

scholarly journals Bambusa tuldoides (punting pole bamboo).

2020 ◽  
Author(s):  
Julissa Rojas-Sandoval
Keyword(s):  
Pacific Region ◽  
Native Range ◽  
Wide Range ◽  
Agricultural Weed

Abstract Bambusa tuldoides is a species of bamboo native to Asia that is is widely cultivated as ornamental and hedge plant but also for its culms. It has been introduced elsewhere in Asia outside of its native range, as well as in the Americas and Pacific region. Culms and branches root very readily and often grow to form monospecific stands along riverbanks, low hills, roadsides and disturbed sites. This species is adapted to grow in a wide range of climates and can survive temperatures as low as -7°C. Currently, B. tuldoides is considered an invasive and transformer species in Cuba. It is also included in the Global Compendium of weeds as an "agricultural weed".

scholarly journals The Response of Soybean (glycine max (l.) Meer.) Varieties from the Tropical Region to Five Watering Regimes under a Controlled Environment

2018 ◽  
Vol 1 (2) ◽  
Keyword(s):  
Glycine Max ◽  
Drought Stress ◽  
Stomatal Conductance ◽  
Water Supply ◽  
Dry Season ◽  
Plant Response ◽  
Tropical Region ◽  
Transpiration Efficiency ◽  
Wide Range ◽  
Glycine Max L

In some rice dominated tropical regions, such as in Indonesia, soybeans are an increasingly important dry season crop which are often exposed to periods of drought stress. The morphological and physiological responses, which could lead to some tolerance to water stress, may vary between varieties. By better understanding the plant response to drought stress and finding if these responses vary between varieties better dry season production could be achieved. An experiment was conducted to compare the response of four varieties of soybean (glycine max (l.) Meer.) to five watering regimes, with the objective of determining the response of common soybean varieies across a wide range of water supply. Plant response to water supply was measured using gas exchange measurement with the rate of photo synthesis decreasing progressively from well watered to dry conditions across the four varieties. A correlation of stomatal conductance and transpiration rate has a close relationship with photosynthetic rate, where stomatal conductance of Burangrang variety has higher value than other varieties. Varieties Burangrang and Argomulyo stomatal conductances are higher value than those of Anjasmoro and Grobogan varieties. In a deficit of water condition, the Argomulyo varieties have a higher value of transpiration efficiency and significantly different than the other three varieties. The transpiration efficiency significantly declined for treatments watered once every two or three weeks. The transpiration efficiency values of Agromulyo and Burangrang varieties were significantly higher than another varieties.

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