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Plants react to their environment and to management interventions by adjusting physiological functions and structure. Functional–structural plant models (FSPM), combine the representation of three-dimensional (3D) plant structure with selected physiological functions. An FSPM consists of an architectural part (plant structure) and a process part (plant functioning). The first deals with (i) the types of organs that are initiated and the way these are connected (topology), (ii) co-ordination in organ expansion dynamics, and (iii) geometrical variables (e.g. leaf angles, leaf curvature). The process part may include any physiological or physical process that affects plant growth and development (e.g. photosynthesis, carbon allocation). This paper addresses the following questions: (i) how are FSPM constructed, and (ii) for what purposes are they useful? Static, architectural models are distinguished from dynamic models. Static models are useful in order to study the significance of plant structure, such as light distribution in the canopy, gas exchange, remote sensing, pesticide spraying studies, and interactions between plants and biotic agents. Dynamic models serve quantitatively to integrate knowledge on plant functions and morphology as modulated by environment. Applications are in the domain of plant sciences, for example the study of plant plasticity as related to changes in the red:far red ratio of light in the canopy. With increasing availability of genetic information, FSPM will play a role in the assessment of the significance towards plant performance of variation in genetic traits across environments. In many crops, growers actively manipulate plant structure. FSPM is a promising tool to explore divergent management strategies.

A low-energy electronic recoil calibration of XENON1T, a dual-phase xenon time projection chamber, with an internal$^{37}$$37 Ar source was performed. This calibration source features a 35-day half-life and provides two mono-energetic lines at 2.82 keV and 0.27 keV. The photon yield and electron yield at 2.82 keV are measured to be ($$32.3\\,\\pm \\,0.3$$32.3 ± 0.3 ) photons/keV and ($$40.6\\,\\pm \\,0.5$$40.6 ± 0.5 ) electrons/keV, respectively, in agreement with other measurements and with NEST predictions. The electron yield at 0.27 keV is also measured and it is ($$68.0^{+6.3}_{-3.7}$$68 . 0 - 3.7 + 6.3 ) electrons/keV. The$^{37}$$37 Ar calibration confirms that the detector is well-understood in the energy region close to the detection threshold, with the 2.82 keV line reconstructed at ($$2.83\\,\\pm \\,0.02$$2.83 ± 0.02 ) keV, which further validates the model used to interpret the low-energy electronic recoil excess previously reported by XENON1T. The ability to efficiently remove argon with cryogenic distillation after the calibration proves that$^{37}$$37 Ar can be considered as a regular calibration source for multi-tonne xenon detectors.

Plant architectural traits have been reported to impact pest and disease, i.e., attackers, incidence on several crops and to potentially provide alternative, although partial, solutions to limit chemical applications. In this paper, we introduce the major concepts of plant architecture analysis that can be used for investigating plant interactions with attacker development. We briefly review how primary growth, branching and reiteration allow the plant to develop its 3D structure which properties may allow it (or not) to escape or survive to attacks. Different scales are considered: (i) the organs, in which nature, shape and position may influence pest and pathogen attack and development; (ii) the individual plant form, especially the spatial distribution of leaves in space which determines the within-plant micro-climate and the shoot distribution, topological connections which influence the within-plant propagation of attackers; and (iii) the plant population, in which density and spatial arrangement affect the micro-climate gradients within the canopy and may lead to different risks of propagation from plant to plant. At the individual scale, we show how growth, branching and flowering traits combine to confer to every plant species an intrinsic architectural model. However, these traits vary quantitatively between genotypes within the species. In addition, we analyze how they can be modulated throughout plant ontogeny and by environmental conditions, here considered lato sensu , i.e. including climatic conditions and manipulations by humans. Examples from different plant species with various architectural types, in particular for wheat and apple, are provided to draw a comprehensive view of possible plant protection strategies which could benefit from plant architectural traits, their genetic variability as well as their plasticity to environmental conditions and agronomic manipulations. Associations between species and/or genotypes having different susceptibility and form could also open new solutions to improve the tolerance to pest and disease at whole population scale.

The XENONnT experiment has achieved an exceptionally low Rn 222 activity concentration within its inner 5.9 tonne liquid xenon detector of ( 0.90 ± 0.02 stat ± 0.07 syst ) μ Bq kg − 1 , equivalent to about 430 Rn 222 atoms per tonne of xenon. This was achieved by active online radon removal via cryogenic distillation after stringent material selection. The achieved Rn 222 activity concentration is 5 times lower than that in other currently operational multitonne liquid xenon detectors engaged in dark matter searches. This breakthrough enables the pursuit of various rare event searches that lie beyond the confines of the standard model of particle physics, with world-leading sensitivity. The ultralow Rn 222 levels have diminished the radon-induced background rate in the detector to a point where it is for the first time comparable to the solar neutrino-induced background, which is poised to become the primary irreducible background in liquid xenon-based detectors.

Background and AimsExperimental evidence challenges the approximation, central in crop models, that developmental events follow a fixed thermal time schedule, and indicates that leaf emergence events play a role in the timing of development. The objective of this study was to build a structural development model of maize (Zea mays) based on a set of coordination rules at organ level that regulate duration of elongation, and to show how the distribution of leaf sizes emerges from this.MethodsA model of maize development was constructed based on three coordination rules between leaf emergence events and the dynamics of organ extension. The model was parameterized with data from maize grown at a low plant population density and tested using data from maize grown at high population density.Key ResultsThe model gave a good account of the timing and duration of organ extension. By using initial conditions associated with high population density, the model reproduced well the increase in blade elongation duration and the delay in sheath extension in high-density populations compared with low-density populations. Predictions of the sizes of sheaths at high density were accurate, whereas predictions of the dynamics of blade length were accurate up to rank 9; moderate overestimation of blade length occurred at higher ranks.ConclusionsA set of simple rules for coordinated growth of organs is sufficient to simulate the development of maize plant structure without taking into account any regulation by assimilates. In this model, whole-plant architecture is shaped through initial conditions that feed a cascade of coordination events.

A 3D architectural and process-based model of maize development was implemented on the basis of the L-system software Graphtal, interfaced with physical models computing microclimate distributed on the 3D canopy structure. In a first step, we incorporated in the software Graphtal additional functions that enable bi-directional communication with external modules. A simple model for distributed photosynthetically active radiation and the model for apex temperature by Cellieret al. (Agricultural and Forest Meteorology63: 35–54, 1993) were interfaced with Graphtal. In a second step we developed a L-system model for maize, where production rules for growth and development of organs are based on the current state of knowledge of maize development as a function of temperature. Visual representation of the plant is based on the geometrical model of leaf shape by Prévot, Aries and Monestiez (Agronomie11: 491–503, 1991). Finally, various data sets were used to evaluate the physiological aspects and the geometrical representation. It is concluded that environmental L-systems are a convenient tool to integrate biophysical processes from organ to canopy level, and provide a framework to model growth of individual plants in relation to local conditions and ability to forage for resources. However, progress is needed to improve both the knowledge of physiological processes at the organ level and the calculation of physical environmental parameters; some directions for future research are proposed.

• The emergence of a regular phyllochron from the dynamic processes of leaf initiation, leaf elongation and whorl construction suggests causal relationships between leaf elongation and leaf emergence. This paper presents a hypothesis as to how the ontogeny of the growth zone of leaves is triggered by emergence events, and implements it in a dynamic model of leaf elongation. • Two different experiments, presenting two contrasted cases of relationships between leaf emergence and kinetics of leaf elongation, were analysed and interpreted with the model in terms of the functioning of the growth zone. • Analysis of elongation kinetics revealed that the hypothesis allows for several contrasted elongation patterns that were observed, and for a regular phyllochron emerging from the variable dynamic of elongation. The model was able to simulate these patterns, and helped to identify the mechanisms underlying the key points of the analysis. • The hypothesis is not demonstrated, but its coherence and robustness are established, which should inform a renewal of the modelling of leaf elongation in architectural models.

The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run.

The kinetics of elongation of individual internodes of maize stems were studied under field conditions. Thermal time courses of internode length were recorded using non-destructive methods, based on direct measurement of X-ray photographs or on indirect estimates using heights of leaf collars. These data were complemented by serial dissections of maize stems, and by precise observation of the process of sheath emergence, to specify its role in the kinetics of internode elongation. The kinetics of elongation were found to be composed of four phases. The rate of elongation rises exponentially during phase I, and then increases sharply during a short period (phase II), which is followed by a major period of constant growth rate (phase III) and a shorter period in which the rate declines (phase IV). During phase I, elongation appears to be integrated at the level of the whole apical cone. From phase II onwards, elongation becomes determined at the level of the phytomer. The emergence of the sheath attached to the internode appears to be a possible trigger for the transition between phase I and phase II, and it may also be involved in variation in final length among phytomers.

In maize ( Zea mays L.), the gradient in floret development and silk length along the ear at silking determines a time lag between early‐ and late‐appearing silks, which results in pollination asynchrony between them. This asynchrony is partially responsible of reduced kernel set at the ear tip, and hybrids differ in this trait. The objective of this work was to analyze the pattern of floret and silk differentiation and elongation at different spikelet positions (S n ) along the apical ear of two hybrids of contrasting ear size (DEA ≅ 500 spikelets ear −1 ; DK696 ≅ 800 spikelets ear −1 ). At silking, both hybrids had reached approximately the same proportion of final ear length (about 44%), but DK696 had differentiated a greater number of spikelets row −1 (46 spikelets) than DEA (33 spikelets). Silk initiation rate was always faster than spikelet initiation rate, and silk extension dynamics was similar for all spikelet positions. Silks from the base of the ear were always longer than those from the tip (S 25 in DEA or S 35 in DK696). Before pollination, silks experienced an early phase of exponential elongation followed by a phase of linear growth. A drastic reduction in elongation rate followed silk emergence, which did not occur when ears were bagged and pollination was prevented. Convergence in silking among spikelets along the ear could be attained by (i) synchronous silk initiation among spikelet positions, followed by a similar pattern of silk elongation in all florets (hybrid DEA), or (ii) increased silk elongation rate in apical florets (hybrid DK696).