Nitrate and phosphate availability and distribution have different effects on root system architecture of Arabidopsis

Plant root systems can respond to nutrient availability and distribution by changing the three-dimensional deployment of their roots: their root system architecture (RSA). We have compared RSA in homogeneous and heterogeneous nitrate and phosphate supply in Arabidopsis. Changes in nitrate and phosphate availability were found to have contrasting effects on primary root length and lateral root density, but similar effects on lateral root length. Relative to shoot dry weight (DW), primary root length decreased with increasing nitrate availability, while it increased with increasing phosphate supply. Lateral root density remained constant across a range of nitrate supplies, but decreased with increasing phosphate supply. In contrast, lateral root elongation was suppressed both by high nitrate and high phosphate supplies. Local supplies of high nitrate or phosphate in a patch also had different effects. Primary root growth was not affected by a high nitrate patch, but growth through a high phosphate patch reduced primary root growth after the root left the patch. A high nitrate patch induced an increase in lateral root density in the patch, whereas lateral root density was unaffected by a high phosphate patch. However, both phosphate- and nitrate-rich patches induced lateral root elongation in the patch and suppressed it outside the patch. This co-ordinated response of lateral roots also occurs in soil-grown plants exposed to a nutrient-rich patch. The auxin-resistant mutants axrl, axr4 and aux1 all showed the wild-type lateral root elongation responses to a nitrate-rich patch, suggesting that auxin is not required for this response.  

Evaluation of high yielding soybean germplasm under water limitation

Limited information is available for soybean root traits and their plasticity under drought stress. To date, no studies have focused on examining diverse soybean germplasm for regulation of shoot and root response under water limited conditions across varying soil types. In this study, 17 genetically diverse soybean germplasm lines were selected to study root response to water limited conditions in clay (trial 1) and sandy soil (trial 2) in two target environments. Physiological data on shoot traits was measured at multiple crop stages ranging from early vegetative to pod filling. The phenotypic root traits, and biomass accumulation data are collected at pod filling stage. In trial 1, the number of lateral roots and forks were positively correlated with plot yield under water limitation and in trial 2, lateral root thickness was positively correlated with the hill plot yield. Plant Introduction (PI) 578477A and 088444 were found to have higher later root number and forks in clay soil with higher yield under water limitation. In sandy soil, PI458020 was found to have a thicker lateral root system and higher yield under water limitation. The genotypes identified in this study could be used to enhance drought tolerance of elite soybean cultivars through improved root traits specific to target environments.  

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade‐offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions.