Dynamic modelling of lettuce transpiration for water status monitoring

Real-time information on the plant water status is an important prerequisite for the precision irrigation management of crops. The plant transpiration has been shown to provide a good indication of its water status. In this paper, a novel plant water status monitoring framework based on the transpiration dynamics of greenhouse grown lettuce plants is presented. Experimental results indicated that lettuce plants experiencing adequate water supply transpired at a higher rate compared to plants experiencing a shortage in water supply. A data-driven model for predicting the transpiration dynamics of the plants was developed using a system identification approach. Results indicated that a second order discrete-time transfer function model with incoming radiation, vapour pressure deficit, and leaf area index as inputs sufficiently explained the dynamics with an average coefficient of determination of . The parameters of the model were updated online and then applied in predicting the transpiration dynamics of the plants in real-time. The model predicted dynamics closely matched the measured values when the plants were in a predefined water status state. The reverse was the case when there was a significant change in the water status state. The information contained in the model residuals (measured transpiration – model predicted transpiration) was then exploited as a means of inferring the plant water status. This framework provides a simple and intuitive means of monitoring the plant water status in real-time while achieving a sensitivity similar to that of stomatal conductance measurements. It can be applied in regulating the water deficit of greenhouse grown crops, with specific advantages over other available techniques

Dispersive Waves in Microstructured Solids

The wave motion in micromorphic microstructured solids is studied. The mathematical model is based on ideas of Mindlin and governing equations are derived by making use of the Euler–Lagrange formalism. The same result is obtained by means of the internal variables approach. Actually such a model describes internal fields in microstructured solids under external loading and the interaction of these fields results in various physical effects. The emphasis of the paper is on dispersion analysis and wave profiles generated by initial or boundary conditions in a one-dimensional case

Competing exchange interactions on the verge of a metal-insulator transition in the two-dimensional spiral magnet Sr3_3Fe2_2O7_7

We report a neutron scattering study of the magnetic order and dynamics of the bilayer perovskite Sr$_3$Fe$_2$O$_7$, which exhibits a temperature-driven metal-insulator transition at 340 K. We show that the Fe$^{4+}$ moments adopt incommensurate spiral order below $T_\text{N}=115$ K and provide a comprehensive description of the corresponding spin wave excitations. The observed magnetic order and excitation spectra can be well understood in terms of an effective spin Hamiltonian with interactions ranging up to third nearest-neighbor pairs. The results indicate that the helical magnetism in Sr$_3$Fe$_2$O$_7$ results from competition between ferromagnetic double-exchange and antiferromagnetic superexchange interactions whose strengths become comparable near the metal-insulator transition. They thus confirm a decades-old theoretical prediction and provide a firm experimental basis for models of magnetic correlations in strongly correlated metals.Comment: PRL, in pres

Mechatronics teaching in preparing agricultural engineers for precision farming technology development

Smart Farming объединяет использование машин, компьютеров, спутниковых и сенсорных технологий для повышения эффективности сельскохозяйственных операций. В статье рассмотрены проблемы подготовки инженеров-механиков для агропромышленного комплекса и обоснована необходимость преподавания мехатроники, рассмотрен опыт Университета Харпер Адамс в преподавании мехатроники в соответствии с существующим учебным планом. В заключении определены возможности для будущего сотрудничества между Белорусской государственной сельскохозяйственной академией и Университетом Харпер Адамс через европейские программы

Advanced monitoring and management systems for improving sustainability in precision irrigation

Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil–plant–atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation

Predicting base editing outcomes using position-specific sequence determinants.

CRISPR/Cas base editors promise nucleotide-level control over DNA sequences, but the determinants of their activity remain incompletely understood. We measured base editing frequencies in two human cell lines for two cytosine and two adenine base editors at ∼14 000 target sequences and find that base editing activity is sequence-biased, with largest effects from nucleotides flanking the target base. Whether a base is edited depends strongly on the combination of its position in the target and the preceding base, acting to widen or narrow the effective editing window. The impact of features on editing rate depends on the position, with sequence bias efficacy mainly influencing bases away from the center of the window. We use these observations to train a machine learning model to predict editing activity per position, with accuracy ranging from 0.49 to 0.72 between editors, and with better generalization across datasets than existing tools. We demonstrate the usefulness of our model by predicting the efficacy of disease mutation correcting guides, and find that most of them suffer from more unwanted editing than pure outcomes. This work unravels the position-specificity of base editing biases and allows more efficient planning of editing campaigns in experimental and therapeutic contexts

Two Gaps Make a High Temperature Superconductor?

One of the keys to the high-temperature superconductivity puzzle is the identification of the energy scales associated with the emergence of a coherent condensate of superconducting electron pairs. These might provide a measure of the pairing strength and of the coherence of the superfluid, and ultimately reveal the nature of the elusive pairing mechanism in the superconducting cuprates. To this end, a great deal of effort has been devoted to investigating the connection between the superconducting transition temperature Tc and the normal-state pseudogap crossover temperature T*. Here we present a review of a large body of experimental data that suggests a coexisting two-gap scenario, i.e. superconducting gap and pseudogap, over the whole superconducting dome.Comment: Related material can be found at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

Long-range incommensurate charge fluctuations in (Y,Nd)Ba2Cu3O(6+x)

There are increasing indications that superconductivity competes with other orders in cuprate superconductors, but obtaining direct evidence with bulk-sensitive probes is challenging. We have used resonant soft x-ray scattering to identify two-dimensional charge fluctuations with an incommensurate periodicity of $\bf \sim 3.2$ lattice units in the copper-oxide planes of the superconductors (Y,Nd)Ba$_2$Cu$_3$O$_{6+x}$ with hole concentrations $0.09 \leq p \leq 0.13$ per planar Cu ion. The intensity and correlation length of the fluctuation signal increase strongly upon cooling down to the superconducting transition temperature, $T_c$; further cooling below $T_c$ abruptly reverses the divergence of the charge correlations. In combination with prior observations of a large gap in the spin excitation spectrum, these data indicate an incipient charge-density-wave instability that competes with superconductivity.Comment: to appear in Scienc

Dispersive spin excitations in highly overdoped cuprates revealed by resonant inelastic x-ray scattering

Using resonant inelastic x-ray scattering (RIXS) at the Cu $L$-absorption edge, we have observed intense, dispersive spin excitations in highly overdoped Tl$_2$Ba$_2$CuO$_{6+\delta}$ (superconducting $T_c =6$ K), a compound whose normal-state charge transport and thermodynamic properties have been studied extensively and shown to exhibit canonical Fermi-liquid behavior. Complementary RIXS experiments on slightly overdoped Tl$_2$Ba$_2$CuO$_{6+\delta}$ ($T_c =89$ K) and on Y$_{1-x}$Ca$_{x}$Ba$_2$Cu$_3$O$_{6+\delta}$ compounds spanning a wide range of doping levels indicate that these excitations exhibit energies and energy-integrated spectral weights closely similar to those of antiferromagnetic magnons in undoped cuprates. The surprising coexistence of Fermi-liquid-like charge excitations and high-energy spin excitations reminiscent of antiferromagnetic insulators in highly overdoped compounds poses a challenge to current theoretical models of the cuprates