Background and Aims Root diameter, especially apical diameter, plays an important role in root development and function. The variation in diameter between roots, and along roots, affects root structure and thus the root system’s overall foraging performance. However, the effect of diameter variation on root elongation, branching and topological connections has not been examined systematically in a population of high-order roots, nor along the roots, especially for mature plants grown in the field. Methods A method combining both excavation and analysis was applied to extract and quantify root architectural traits of adult, field-grown maize plants. The relationships between root diameter and other root architectural characteristics are analysed for two maize cultivars. Key Results The basal diameter of the lateral roots (orders 1–3) was highly variable. Basal diameter was partly determined by the diameter of the bearing segment. Basal diameter defined a potential root length, but the lengths of most roots fell far short of this. This was explained partly by differences in the pattern of diameter change along roots. Diameter tended to decrease along most roots, with the steepness of the gradient of decrease depending on basal diameter. The longest roots were those that maintained (or sometimes increased) their diameters during elongation. The branching density (cm^–1) of laterals was also determined by the diameter of the bearing segment. However, the location of this bearing segment along the mother root was also involved – intermediate positions were associated with higher densities of laterals. Conclusions The method used here allows us to obtain very detailed records of the geometry and topology of a complex root system. Basal diameter and the pattern of diameter change along a root were associated with its final length. These relationships are especially useful in simulations of root elongation and branching in source–sink models.

Thidiazuron (TDZ) is widely used as a defoliant to induce leaf abscission in cotton. However, the underlying molecular mechanism is still unclear. In this study, RNA-seq and enzyme-linked immunosorbent assays (ELISA) were performed to reveal the dynamic transcriptome profiling and the change of endogenous phytohormones upon TDZ treatment in leaf, petiole, and abscission zone (AZ). We found that TDZ induced the gene expression of ethylene biosynthesis and signal, and promoted ethylene accumulation earlier in leaf than that in AZ. While TDZ down-regulated indole-3-acetic acid (IAA) biosynthesis genes mainly in leaf and IAA signal and transport genes. Furthermore, the IAA content reduced more sharply in the leaf than that in AZ to change the auxin gradient for abscission. TDZ suppressed CTK biosynthesis genes and induced CTK metabolic genes to reduce the IPA accumulation for the reduction of ethylene sensitivity. Furthermore, TDZ regulated the gene expression of abscisic acid (ABA) biosynthesis and signal and induced ABA accumulation between 12–48 h, which could up-regulate ABA response factor genes and inhibit IAA transporter genes. Our data suggest that TDZ orchestrates metabolism and signal of ethylene, auxin, and cytokinin, and also the transport of auxin in leaf, petiole, and AZ, to control leaf abscission.

In order to efficiently determine genotypic differences in rooting patterns of crops, novel hardware and software are needed simultaneously to characterize dynamics of root development. We describe a prototype robotic monitoring platform—the RhizoChamber-Monitor for analyzing growth patterns of plant roots automatically. The RhizoChamber-Monitor comprises an automatic imaging system for acquiring sequential images of roots which grow on a cloth substrate in custom rhizoboxes, an automatic irrigation system and a flexible shading arrangement. A customized image processing software was developed to analyze the spatio-temporal dynamics of root growth from time-course images of multiple plants. This software can quantify overall growth of roots and extract detailed growth traits (e.g. dynamics of length and diameter) of primary roots and of individual lateral roots automatically. It can also identify local growth traits of lateral roots (pseudo-mean-length and pseudo-maximum-length) semi-automatically. Two cotton genotypes were used to test both the physical platform and the analysis software. The combination of hardware and software is expected to facilitate quantification of root geometry and its spatio-temporal growth patterns, and therefore to provide opportunities for high-throughput root phenotyping in support of crop breeding to optimize root architecture.

Background: Mepiquat chloride (MC), a plant growth regulator, enhances root growth by promoting lateral root formation in cotton. However, the underlying molecular mechanisms of this phenomenon is still unknown. Methods: In this study, we used 10 cotton (Gossypium hirsutum Linn.) cultivars to perform a seed treatment with MC to investigate lateral root formation, and selected a MC sensitive cotton cultivar for dynamic monitor of root growth and transcriptome analysis during lateral root development upon MC seed treatment. Results: The results showed that MC treated seeds promotes the lateral root formation in a dosage-depended manner and the effective promotion region is within 5 cm from the base of primary root. MC treated seeds induce endogenous auxin level by altering gene expression of both gibberellin (GA) biosynthesis and signaling and abscisic acid (ABA) signaling. Meanwhile, MC treated seeds differentially express genes involved in indole acetic acid (IAA) synthesis and transport. Furthermore, MC-induced IAA regulates the expression of genes related to cell cycle and division for lateral root development. Conclusions: Our data suggest that MC orchestrates GA and ABA metabolism and signaling, which further regulates auxin biosynthesis, transport, and signaling to promote the cell division responsible for lateral root formation.

Root distribution has a major influence on soil exploration and nutrient and water acquisition by plants. Soil coring is a well-known way to estimate root distribution. However, identifying an optimal core-sampling strategy is important if one is to strike the right balance between the high cost of making field estimates of root length density (RLD) vs. the need for accurate estimates. Virtual assessment of competing soil-coring strategies, based on three-dimensional (3-D) models of root system architecture (RSA), is a highly effective way to find that balance. The trajectories of the axile roots of two maize cultivars having contrasting axile root angles were measured in the field using in situ 3-D digitization. Lateral roots were also measured by recording topological and geometrical parameters. Based on the measurement dataset obtained, contrasting 3-D RSA models of individual maize plants were constructed in which the different lateral rooting angles were represented. Using these RSA models the accuracies of various core-sampling strategies for estimating RLD were assessed in a series of virtual experiments. Substantial biases occur if a one-core sampling strategy is used to estimate RLD. The biases largely remain for two-core sampling, although a weighting method can reduce these. However, given that identification of an optimal weighting method is difficult in practice, a new sampling strategy is proposed based on an area-weighting algorithm. In this way low deviations in RLD estimation can be achieved by sampling between rows and also by using larger-diameter (7.5 or 10 cm) cores. A 3-D root architecture model based on a detailed measurement dataset provides an ideal platform for assessing a range of soil-coring strategies. The improved two-core sampling strategy, based on an area-weighting algorithm, shows considerable promise as a cost-efficient way of obtaining good quality RLD estimates for maize.