A functional-structural model of upland rice root systems reveals the importance of laterals and growing root tips for phosphate uptake from wet and dry soils

Root traits for low input agroecosystems in Africa: Lessons from three case studies

In many regions across Africa, agriculture is largely based on low-input and small-holder farming systems that use little inorganic fertilisers and have limited access to irrigation and mechanisation. Improving agricultural practices and developing new cultivars adapted to these environments, where production already suffers from climate change, is a major priority for food security. Here, we illustrate how breeding for specific root traits could improve crop resilience in Africa using three case studies covering very contrasting low-input agroecosystems. We first review how greater basal root whorl number and longer and denser root hairs increased P acquisition efficiency and yield in common bean in South East Africa. We then discuss how water-saving strategies, root hair density and deep root growth could be targeted to improve sorghum and pearl millet yield in West Africa. Finally, we evaluate how breeding for denser root systems in the topsoil and interactions with arbuscular mycorrhizal fungi could be mobilised to optimise water-saving alternate wetting and drying practices in West African rice agroecosystems. We conclude with a discussion on how to evaluate the utility of root traits and how to make root trait selection feasible for breeders so that improved varieties can be made available to farmers through participatory approaches.

Integrated root phenotypes for improved rice performance under low nitrogen availability

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional-structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L-type and S-type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct-seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct-seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding.

Rice increases phosphorus uptake in strongly sorbing soils by intra-root facilitation

Upland rice (Oryza sativa) is adapted to strongly phosphorus (P) sorbing soils. The mechanisms underlying P acquisition, however, are not well understood, and models typically underestimate uptake. This complicates root ideotype development and trait-based selection for further improvement. We present a novel model, which correctly simulates the P uptake by a P-efficient rice genotype measured over 48 days of growth. The model represents root morphology at the local rhizosphere scale, including root hairs and fine S-type laterals. It simulates fast- and slowly reacting soil P and the P-solubilizing effect of root-induced pH changes in the soil. Simulations predict that the zone of pH changes and P solubilization around a root spreads further into the soil than the zone of P depletion. A root needs to place laterals outside its depletion- but inside its solubilization zone to maximize P uptake. S-type laterals, which are short but hairy, appear to be the key root structures to achieve that. Thus, thicker roots facilitate the P uptake by fine lateral roots. Uptake can be enhanced through longer root hairs and greater root length density but was less sensitive to total root length and root class proportions.

Breeding rice for a changing climate by improving adaptations to water saving technologies

Climate change is expected to increasingly affect rice production through rising temperatures and decreasing water availability. Unlike other crops, rice is a main contributor to greenhouse gas emissions due to methane emissions from flooded paddy fields. Climate change can therefore be addressed in two ways in rice: through making the crop more climate resilient and through changes in management practices that reduce methane emissions and thereby slow global warming. In this review, we focus on two water saving technologies that reduce the periods lowland rice will be grown under fully flooded conditions, thereby improving water use efficiency and reducing methane emissions. Rice breeding over the past decades has mostly focused on developing high-yielding varieties adapted to continuously flooded conditions where seedlings were raised in a nursery and transplanted into a puddled flooded soil. Shifting cultivation to direct-seeded rice or to introducing non-flooded periods as in alternate wetting and drying gives rise to new challenges which need to be addressed in rice breeding. New adaptive traits such as rapid uniform germination even under anaerobic conditions, seedling vigor, weed competitiveness, root plasticity, and moderate drought tolerance need to be bred into the current elite germplasm and to what extent this is being addressed through trait discovery, marker-assisted selection and population improvement are reviewed.

Response of root development and nutrient uptake of two chinese cultivars of hybrid rice to nitrogen and phosphorus fertilization in Sichuan Province, China

Background

Chemical fertilization helped modern agriculture in grain yield improvement to ensure food security. The response of chemical fertilization for higher hybrid rice production is highly dependent on optimal fertilization management in paddy fields. To assess such responses, in the current work we examine the yield, root growth, and expression of related genes responsible for stress metabolism of nitrogen (N) and phosphorus (P) in two hybrid-rice cultivars Deyou4727 (D47) and Yixiangyou2115 (Y21).

Methods and results

The experiment followed four nitrogen (N) (N₀, N₆₀, N_120, and N₁₈₀ kg/ha) and phosphorus (P) (P₀, P₆₀, P₉₀, and P₁₂₀ kg/ha) fertilizer levels. The grain yield in D47 was more sensitive to nitrogen application, while Y21 was more sensitive to phosphorus application, which resulted in comparatively higher biomass and yield. Our findings were corroborated by gene expression studies of glutamine synthetase OsGS1;1 and OsGS1;2 and phosphate starvation-related genes PHR1 and SPX, confirming sensitivity to N and P application. The number of roots was less sensitive to nitrogen application in D47 between N₀ and N₆₀, but the overall nutrient response difference was significantly higher due to the deep rooting system as compared to Y21.

Conclusions

The higher yield, high N and P use efficiency, and versatile root growth of D47 make it suitable to reduce unproductive usage of N and P from paddy fields, improving hybrid rice productivity, and environmental safety in the Sichuan basin area of China.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11033-021-06835-7.

Mycorrhizal associations change root functionality: a 3D modelling study on competitive interactions between plants for light and nutrients

Recent studies show that the variation in root functional traits can be explained by a two-dimensional trait framework, containing a 'collaboration' axis in addition to the classical fast-slow 'conservation' axis. This collaboration axis spans from thin and highly branched roots that employ a 'do-it-yourself' strategy to thick and sparsely branched roots that 'outsource' nutrient uptake to symbiotic arbuscular mycorrhizal fungi (AMF). Here, we explore the functionality of this collaboration axis by quantifying how interactions with AMF change the impact of root traits on plant performance. To this end, we developed a novel functional-structural plant (FSP) modelling approach that simulates plants competing for light and nutrients in the presence or absence of AMF. Our simulation results support the notion that in the absence of AMF, plants rely on thin, highly branched roots for their nutrient uptake. The presence of AMF, however, promotes thick, unbranched roots as an alternative strategy for uptake of immobile phosphorus, but not for mobile nitrogen. This provides further support for a root trait framework that accommodates for the interactive effect of roots and AMF. Our modelling study offers unique opportunities to incorporate soil microbial interactions into root functionality as it integrates consequences of belowground trait expression.

Root developmental responses to phosphorus nutrition

Phosphorus is an essential macronutrient for plant growth and development. Root system architecture (RSA) affects a plant's ability to obtain phosphate, the major form of phosphorus that plants uptake. In this review, I first consider the relationship between RSA and plant phosphorus-acquisition efficiency, describe how external phosphorus conditions both induce and impose changes in the RSA of major crops and of the model plant Arabidopsis, and discuss whether shoot phosphorus status affects RSA and whether there is a universal root developmental response across all plant species. I then summarize the current understanding of the molecular mechanisms governing root developmental responses to phosphorus deficiency. I also explore the possible reasons for the inconsistent results reported by different research groups and comment on the relevance of some studies performed under laboratory conditions to what occurs in natural environments.

Cost-Benefit Analysis of the Upland-Rice Root Architecture in Relation to Phosphate: 3D Simulations Highlight the Importance of S-Type Lateral Roots for Reducing the Pay-Off Time

The rice root system develops a large number of nodal roots from which two types of lateral roots branch out, large L-types and fine S-types, the latter being unique to the species. All roots including S-types are covered by root hairs. To what extent these fine structures contribute to phosphate (P) uptake under P deficiency was investigated using a novel 3-D root growth model that treats root hairs as individual structures with their own Michaelis-Menten uptake kinetics. Model simulations indicated that nodal roots contribute most to P uptake followed by L-type lateral roots and S-type laterals and root hairs. This is due to the much larger root surface area of thicker nodal roots. This thickness, however, also meant that the investment in terms of P needed for producing nodal roots was very large. Simulations relating P costs and time needed to recover that cost through P uptake suggest that producing nodal roots represents a considerable burden to a P-starved plant, with more than 20 times longer pay-off time compared to S-type laterals and root hairs. We estimated that the P cost of these fine root structures is low enough to be recovered within a day of their formation. These results expose a dilemma in terms of optimizing root system architecture to overcome P deficiency: P uptake could be maximized by developing more nodal root tissue, but when P is growth-limiting, adding more nodal root tissue represents an inefficient use of the limiting factor P. In order to improve adaption to P deficiency in rice breeding two complementary strategies seem to exist: (1) decreasing the cost or pay-off time of nodal roots and (2) increase the biomass allocation to S-type roots and root hairs. To what extent genotypic variation exists within the rice gene pool for either strategy should be investigated.

Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology

BACKGROUND

Functional-structural plant models (FSPMs) explore and integrate relationships between a plant's structure and processes that underlie its growth and development. In the last 20 years, scientists interested in functional-structural plant modelling have expanded greatly the range of topics covered and now handle dynamical models of growth and development occurring from the microscopic scale, and involving cell division in plant meristems, to the macroscopic scales of whole plants and plant communities.

SCOPE

The FSPM approach occupies a central position in plant science; it is at the crossroads of fundamental questions in systems biology and predictive ecology. This special issue of Annals of Botany features selected papers on critical areas covered by FSPMs and examples of comprehensive models that are used to solve theoretical and applied questions, ranging from developmental biology to plant phenotyping and management of plants for agronomic purposes. Altogether, they offer an opportunity to assess the progress, gaps and bottlenecks along the research path originally foreseen for FSPMs two decades ago. This review also allows discussion of current challenges of FSPMs regarding (1) integration of multidisciplinary knowledge, (2) methods for handling complex models, (3) standards to achieve interoperability and greater genericity and (4) understanding of plant functioning across scales.

CONCLUSIONS

This approach has demonstrated considerable progress, but has yet to reach its full potential in terms of integration and heuristic knowledge production. The research agenda of functional-structural plant modellers in the coming years should place a greater emphasis on explaining robust emergent patterns, and on the causes of possible deviation from it. Modelling such patterns could indeed fuel both generic integration across scales and transdisciplinary transfer. In particular, it could be beneficial to emergent fields of research such as model-assisted phenotyping and predictive ecology in managed ecosystems.