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Aims: Laser micromanipulation such as dissection or optical trapping enables remote physical modification of the activity of tissues, cells and organelles. To date, applications of laser manipulation to plant roots grown in soil have been limited. Here, we show laser manipulation can be applied in situ when plant roots are grown in transparent soil. Methods: We have developed a Q-switched laser manipulation and imaging instrument to perform controlled dissection of roots and to study light-induced root growth responses. We performed a detailed characterisation of the properties of the cutting beams through the soil, studying dissection and optical ablation. Furthermore, we also studied the use of low light doses to control the root elongation rate of lettuce seedlings (Lactuca sativa) in air, agar, gel and transparent soil. Results: We show that whilst soil inhomogeneities affect the thickness and circularity of the beam, those distortions are not inherently limiting. The ability to induce changes in root elongation or complete dissection of microscopic regions of the root is robust to substrate heterogeneity and microscopy set up and is maintained following the limited distortions induced by the transparent soil environment. Conclusions: Our findings show that controlled in situ laser dissection of root tissues is possible with a simple and low-cost optical set-up. We also show that, in the absence of dissection, a reduced laser light power density can provide reversible control of root growth, achieving a precise "point and shoot" method for root manipulation. [ABSTRACT FROM AUTHOR]

Summary: Limitation to root growth results from forces required to overcome soil resistance to deformation. The variations in individual particle forces affects root development and often deflects the growth trajectory.We have developed transparent soil and optical projection tomography microscopy systems where measurements of growth trajectory and particle forces can be acquired in a granular medium at a range of confining pressures. We developed image‐processing pipelines to analyse patterns in root trajectories and a stochastic‐mechanical theory to establish how root deflections relate to particle forces and thickening of the root.Root thickening compensates for the increase in mean particle forces but does not prevent deflections from 5% of most extreme individual particle forces causing root deflection. The magnitude of deflections increases with pressure but they assemble into helices of conserved wavelength in response linked to gravitropism.The study reveals mechanisms for the understanding of root growth in mechanically impeding soil conditions and provides insights relevant to breeding of drought‐resistant crops. [ABSTRACT FROM AUTHOR]

Background: There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration. Results: Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database. Conclusions: Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions. [ABSTRACT FROM AUTHOR]

Major research efforts are targeting the improved performance of root systems for more efficient use of water and nutrients by crops. However, characterizing root system architecture (RSA) is challenging, because roots are difficult objects to observe and analyse. A model-based analysis of RSA traits from phenotyping image data is presented. The model can successfully back-calculate growth parameters without the need to measure individual roots. The mathematical model uses partial differential equations to describe root system development. Methods based on kernel estimators were used to quantify root density distributions from experimental image data, and different optimization approaches to parameterize the model were tested. The model was tested on root images of a set of 89 Brassica rapa L. individuals of the same genotype grown for 14 d after sowing on blue filter paper. Optimized root growth parameters enabled the final (modelled) length of the main root axes to be matched within 1% of their mean values observed in experiments. Parameterized values for elongation rates were within ±4% of the values measured directly on images. Future work should investigate the time dependency of growth parameters using time-lapse image data. The approach is a potentially powerful quantitative technique for identifying crop genotypes with more efficient root systems, using (even incomplete) data from high-throughput phenotyping systems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Models of root systems are essential tools to understand how crops access and use soil resources during their development. However, scaling up such models to field scale remains a great challenge. In this paper, we detail a new approach to compute the growth of root systems based on density distribution functions. Growth was modelled as the dynamics of root apical meristems, using Partial Differential Equations. Trajectories of root apical meristems were used to deform root domains, the bounded support of root density functions, and update density distributions at each time increment of the simulation. Our results demonstrate that it is possible to predict the growth of root domains, by including developmentally meaningful parameters such as root elongation rate, gravitropic rate and branching rate. Models of this type are computationally more efficient than state-of-the-art finite volume methods. At a given prediction accuracy, computational time is over 10 times quicker; it allowed deformable models to be used to simulate ensembles of interacting plants. Application to root competition in crop–weed systems is demonstrated. The models presented in this study indicate that similar approaches could be developed to model shoot or whole plant processes with potential applications in crop and ecological modelling. [Copyright &y& Elsevier]

Microbial activity in the soil surrounding plant roots contributes to nutrient bioavailability, crop growth, and soil biodiversity and fertility. Colonization of the rhizosphere and the rhizoplane in particular requires early establishment on root surfaces where sources of nutrients are abundant. In this study, we investigated the physical interactions taking place between bacteria and the root surface when a root tip enters unexplored regions of soil. We developed a theoretical framework that generalizes the prevailing approaches for describing root growth kinematics and bacterial growth and adhesion on root surfaces. We found that the root elongation rate, bacterial attachment rate, and root cap carrying capacity are key traits for successful establishment. Models also indicate that chemotaxis is more important for radial transport and adhesion than for longitudinal movement of bacteria. Controls on bacterial attachment are required for both efficient root colonization and subsequent dispersal of bacteria in soil. The findings of this study help to understand the establishment of the structure and composition of microbial communities in soil. [ABSTRACT FROM AUTHOR]