Mechanistic framework to link root growth models with weather and soil physical properties, including example applications to soybean growth in Brazil

Background and aimsRoot elongation is generally limited by a combination of mechanical impedance and water stress in most arable soils. However, dynamic changes of soil penetration resistance with soil water content are rarely included in models for predicting root growth. Better modelling frameworks are needed to understand root growth interactions between plant genotype, soil management, and climate. Aim of paper is to describe a new model of root elongation in relation to soil physical characteristics like penetration resistance, matric potential, and hypoxia.MethodsA new diagrammatic framework is proposed to illustrate the interaction between root elongation, soil management, and climatic conditions. The new model was written in Matlab®, using the root architecture model RootBox and a model that solves the 1D Richards equations for water flux in soil. Inputs: root architectural parameters for Soybean; soil hydraulic properties; root water uptake function in relation to matric flux potential; root elongation rate as a function of soil physical characteristics. Simulation scenarios: (a) compact soil layer at 16 to 20 cm; (b) test against a field experiment in Brazil during contrasting drought and normal rainfall seasons.Results(a) Soil compaction substantially slowed root growth into and below the compact layer. (b) Simulated root length density was very similar to field measurements, which was influenced greatly by drought. The main factor slowing root elongation in the simulations was evaluated using a stress reduction function.ConclusionThe proposed framework offers a way to explore the interaction between soil physical properties, weather and root growth. It may be applied to most root elongation models, and offers the potential to evaluate likely factors limiting root growth in different soils and tillage regimes

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Soybean growth affected by seeding rate and mineral nitrogen

ABSTRACT This study aimed to evaluate the effect of seeding rates and nitrogen (N) fertilization on plant growth in soybean cultivar with indeterminate growth habit. Two experiments were conducted in the 2013/14 and 2014/15 growing seasons, in a complete block design with split-plot scheme and six replicates. Four seeding rates (150, 300, 440 and 560 000 viable seeds ha-1) and two N doses (0 and 45 kg ha-1) were allocated in the plots and subplots, respectively. The cultivar NK7059 RR was used. The following traits were assessed: leaf, stem and total shoot dry matter, leaf/stem dry matter ratio, stem and leaf N content, SPAD index, plant height, first pod height, number of branches per plant and grain yield. Soybean growth is not affected by the interaction of plant density and mineral N fertilization. Higher seeding rates increase plant dry matter in the initial development stages and reduce leaf/stem ratio and the number of branches per plant. The effects of N fertilization on soybean growth vary between growing seasons, but do not affect grain yield, even considering a wide range of seeding rates