210,579 research outputs found
Root developmental responses to heterogeneous water and nitrogen supply
No full textBetter understanding of the interaction between the soil physical properties determining water and nitrate availability and the root proliferation and gene expression components of nutrient acquisition could contribute to food security, but may have been limited by experimental systems.
A sand rhizotron system was developed to investigate Arabidopsis (Arabidopsis thaliana) root responses to altered water and nitrate supply as manipulated by soil physical properties. When this system was compared to agar, root disparities were explained by differences in hydraulic properties, highlighting the importance of the soil physical component. The sand rhizotron system was adopted to quantify root proliferation and gene expression responses to altered water and nitrate availability in wild-type and selected mutant seedlings.
In the sand rhizotron system, primary root length and lateral root density were oppositely regulated by water availability, but similarly independent of nitrate supply. The expression of the nitrate transporter AtNRT2.1 and the aquaporin AtPIP2.2 was coordinated across all treatments. Their concentration-dependent hydraulic regulation was confirmed for AtNRT2.1 by in situ imaging of a Green Fluorescent Protein reporter line. AtNAR2.1 and AtNRT2.1 expression demonstrated independent responses to water and nitrate availability despite the requirement of AtNAR2.1 for AtNRT2.1 uptake function. Root proliferation responses to water availability under high (10.0 mM) nitrate were lost in the atnar2.1 mutant and coincided with altered hormone-associated gene (AtEIN2, AtABI4 and AtIPT5) expression. Root proliferation and AtNAR2.1 responses to water availability under high (10.0 mM) nitrate required AtPIP2.2. The coordination of root proliferation and gene expression responses to altered water and nitrate availability is proposed, that includes novel roles for AtNRT2.1, AtNAR2.1 and AtPIP2.2
Range Unit Root (RUR) Tests: Robust against Nonlinearities, Error Distributions, Structural Breaks and Outliers
No full textSince the seminal paper by Dickey and Fuller in 1979, unit-root tests have conditioned the standard approaches to analysing time series with strong serial dependence in mean behaviour, the focus being placed on the detection of eventual unit roots in an autoregressive model fitted to the series. In this paper, we propose a completely different method to test for the type of long-wave patterns observed not only in unit-root time series but also in series following more complex data-generating mechanisms. To this end, our testing device analyses the unit-root persistence exhibited by the data while imposing very few constraints on the generating mechanism. We call our device the range unit-root (RUR) test since it is constructed from the running ranges of the series from which we derive its limit distribution. These nonparametric statistics endow the test with a number of desirable properties, the invariance to monotonic transformations of the series and the robustness to the presence of important parameter shifts. Moreover, the RUR test outperforms the power of standard unit-root tests on near-unit-root stationary time series; it is invariant with respect to the innovations distribution and asymptotically immune to noise. An extension of the RUR test, called the forward?backward range unit-root (FB-RUR) improves the check in the presence of additive outliers. Finally, we illustrate the performances of both range tests and their discrepancies with the Dickey?Fuller unit-root test on exchange rate series.Publicad
Estimation in threshold autoregressive models with a stationary and a unit root regime
No full textThis paper treats estimation in a class of new nonlinear threshold autoregressive models with both a stationary and a unit root regime. Existing literature on nonstationary threshold models have basically focused on models where the nonstationarity can be removed by differencing and/or where the threshold variable is stationary. This is not the case for the process we consider, and nonstandard estimation problems are the result. This paper proposes a parameter estimation method for such nonlinear threshold autoregressive models using the theory of null recurrent Markov chains. Under certain assumptions, we show that the ordinary least squares (OLS) estimators of the parameters involved are asymptotically consistent. Furthermore, it can be shown that the OLS estimator of the coefficient parameter involved in the stationary regime can still be asymptotically normal while the OLS estimator of the coefficient parameter involved in the nonstationary regime has a nonstandard asymptotic distribution. In the limit, the rate of convergence in the stationary regime is asymptotically proportional to n-1/4, whereas it is n-1 in the nonstationary regime. The proposed theory and estimation method are illustrated by both simulated data and a real data example.Autoregressive process; null-recurrent process; semiparametric model; threshold time series; unit root structure.
A decision theoretic analysis of the unit root hypothesis using mixtures of elliptical models
No full textTime Series;Unit Root
Root traits for infertile soils
No full textThis work was supported by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government through Workpackage 3.3 (2011–2016)Crop production is often restricted by the availability of essential mineral elements. For example, the availability of N, P, K, and S limits low-input agriculture, the phytoavailability of Fe, Zn, and Cu limits crop production on alkaline and calcareous soils, and P, Mo, Mg, Ca,and K deficiencies, together with proton, Al and Mn toxicities, limit crop production on acid soils. Since essential mineral elements are acquired by the root system, the development of crop genotypes with root traits increasing their acquisition should increase yields on infertile soils. This paper examines root traits likely to improve the acquisition of these elements and observes that, although the efficient acquisition of a particular element requires a specific set of root traits, suites of traits can be identified that benefit the acquisition of a group of mineral elements. Elements can be divided into three Groups based on common trait requirements. Group 1 comprises N, S, K, B, and P. Group 2 comprises Fe, Zn, Cu, Mn, and Ni. Group 3 contains mineral elements that rarely affect crop production. It is argued that breeding for a limited number of distinct root ideotypes,addressing particular combinations of mineral imbalances, should be pursued.Peer reviewe
COMMODITY PRICES AND UNIT ROOT TESTS
No full textEndogenous variables in structural models of agricultural commodity markets are typically treated as stationary. Yet, tests for unit roots have rather frequently implied that commodity prices are not stationary. This seeming inconsistency is investigated by focusing on alternative specifications of unit root tests. We apply various specifications to Illinois farm prices of corn, soybeans, barrows and gilts, and milk for the 1960 through 2002 time span. The preponderance of the evidence suggests that nominal prices do not have unit roots, but under certain specifications, the null hypothesis of a unit root cannot be rejected, particularly when the logarithms of prices are used. If the test specification does not account for a structural change that shifts the mean of the variable, the results are biased toward concluding that a unit root exists. In general, the evidence does not favor the existence of unit roots.Marketing,
Modelling diverse root density dynamics and deep nitrogen uptake — a simple approach
No full textWe present a 2-D model for simulation of root density and plant nitrogen (N) uptake for crops grown in agricultural systems, based on a modification of the root density equation originally proposed by Gerwitz and Page in J Appl Ecol 11:773–781, (1974). A root system form parameter was introduced to describe the distribution of root length vertically and horizontally in the soil profile. The form parameter can vary from 0 where root density is evenly distributed through the soil profile, to 8 where practically all roots are found near the surface. The root model has other components describing root features, such as specific root length and plant N uptake kinetics. The same approach is used to distribute root length horizontally, allowing simulation of root growth and plant N uptake in row crops. The rooting depth penetration rate and depth distribution of root density were found to be the most important parameters controlling crop N uptake from deeper soil layers. The validity of the root distribution model was tested with field data for white cabbage, red beet, and leek. The model was able to simulate very different root distributions, but it was not able to simulate increasing root density with depth as seen in the experimental results for white cabbage. The model was able to simulate N depletion in different soil layers in two field studies. One included vegetable crops with very different rooting depths and the other compared effects of spring wheat and winter wheat. In both experiments variation in spring soil N availability and depth distribution was varied by the use of cover crops. This shows the model sensitivity to the form parameter value and the ability of the model to reproduce N depletion in soil layers. This work shows that the relatively simple root model developed, driven by degree days and simulated crop growth, can be used to simulate crop soil N uptake and depletion appropriately in low N input crop production systems, with a requirement of few measured parameters
Nonlinear unit root tests of PPP using long-horizon data
No full textThe Kapetanios, Shin, and Snell (KSS, 2003) test for a nonlinear unit root is used to study purchasing power parity using Taylor's extensive data set, d to include recent exchange rate and price level data. The results i) indicate that PPP holds with respect to the US dollar for most countries and ii) are more supportive of PPP than those from standard linear unit root tests.
Root-depth profiles of important agricultural crops
No full textBased on a literature review we describe root density profiles in terms of a logistic dose-response function for important global agricultural crops (wheat, maize, rice, barley, soybean, pulses, cotton, potato, sunflower, rye, rapeseed, and sugarbeet). These root density profiles can be used in 1-D macroscopic root water uptake models. For use in 1-D microscopic root water uptake models, we analyze root density data in terms of the half mean distance between roots. Based on the database there is little support for a predictive relationship between parameters of the root density distribution of agricultural crops and climate or management factors. Constancy of the shape of the root density distribution with time is shown not to hold in some experiments, but evidence is anecdotical. At present the basis to describe rooting profiles with depth only seems to allow profiles which are constant in time and with depth. The correlation between half mean distance and drought sensitivity is investigated and conclusions will be presented
Range unit root tests
No full textSince the seminal paper by Dickey and Fuller in 1979, unit-root tests have conditioned the standard approaches to analyse time series with strong serial dependence, the focus being placed in the detection of eventual unit roots in an autorregresive model fitted to the series. In this paper we propose a completely different method to test for the type of "long-wave" patterns observed not only in unit root time series but also in series following more complex data generating mechanism. To this end, our testing device analyses the trend exhibit by the data, without imposing any constraint on the generating mechanism. We call our device the Range Unit Root (RUR) Test since it is constructed from running ranges of the series. These statistics allow a more general characterization of a strong serial dependence in the mean behavior, thus endowing our test with a number of desirable properties. Among these properties are the invariance to nonlinear monotonic transformations of the series and the robustness to the presence of level shifts and additive outliers. In addition, the RUR test outperforms the power of standard unit root tests on near-unit-root stationary time series
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