Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms.

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional-structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional-structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

Theoretical evidence that root penetration ability interacts with soil compaction regimes to affect nitrate capture.

BACKGROUND AND AIMS: Although root penetration of strong soils has been intensively studied at the scale of individual root axes, interactions between soil physical properties and soil foraging by whole plants are less clear. Here we investigate how variation in the penetration ability of distinct root classes and bulk density profiles common to real-world soils interact to affect soil foraging strategies. METHODS: We utilize the functional-structural plant model 'OpenSimRoot' to simulate the growth of maize (Zea mays) root systems with variable penetration ability of axial and lateral roots in soils with (1) uniform bulk density, (2) plow pans and (3) increasing bulk density with depth. We also modify the availability and leaching of nitrate to uncover reciprocal interactions between these factors and the capture of mobile resources. KEY RESULTS: Soils with plow pans and bulk density gradients affected overall size, distribution and carbon costs of the root system. Soils with high bulk density at depth impeded rooting depth and reduced leaching of nitrate, thereby improving the coincidence of nitrogen and root length. While increasing penetration ability of either axial or lateral root classes produced root systems of comparable net length, improved penetration of axial roots increased allocation of root length in deeper soil, thereby amplifying N acquisition and shoot biomass. Although enhanced penetration ability of both root classes was associated with greater root system carbon costs, the benefit to plant fitness from improved soil exploration and resource capture offset these. CONCLUSIONS: While lateral roots comprise the bulk of root length, axial roots function as a scaffold determining the distribution of these laterals. In soils with high soil strength and leaching, root systems with enhanced penetration ability of axial roots have greater distribution of root length at depth, thereby improving capture of mobile resources.

Root hair phenotypes influence nitrogen acquisition in maize.

BACKGROUND AND AIMS: The utility of root hairs for nitrogen (N) acquisition is poorly understood. METHODS: We explored the utility of root hairs for N acquisition in the functional-structural model SimRoot and with maize genotypes with variable root hair length (RHL) in greenhouse and field environments. KEY RESULTS: Simulation results indicate that long, dense root hairs can improve N acquisition under varying N availability. In the greenhouse, ammonium availability had no effect on RHL and low nitrate availability increased RHL, while in the field low N reduced RHL. Longer RHL was associated with 216 % increase in biomass and 237 % increase in plant N content under low-N conditions in the greenhouse and a 250 % increase in biomass and 200 % increase in plant N content in the field compared with short-RHL phenotypes. In a low-N field environment, genotypes with long RHL had 267 % greater yield than those with short RHL. We speculate that long root hairs improve N capture by increased root surface area and expanded soil exploration beyond the N depletion zone surrounding the root surface. CONCLUSIONS: We conclude that root hairs play an important role in N acquisition. We suggest that root hairs merit consideration as a breeding target for improved N acquisition in maize and other crops.

A Comparative Analysis of Quantitative Metrics of Root Architecture.

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, and lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length, total volume, convex hull volume, and bushiness index estimate different subsets of the constituent phenes; they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

Traditional fruits of South India: Bioactive components and their potential health implications in chronic diseases.

Fruits are colorful, flavorful, and nutritious components and play an important role for the vital health and maintenance of our body. Experimental evidences suggested that fruits contain various bioactive constituents including flavonoids, polyphenols, carotenoids, and micronutrients such as vitamins and minerals. Because of these, fruits are receiving greater attention to treat and/or control various health complications such as diabetes, obesity, cancer, cardiovascular disease, immune system decline, and certain neurological disorders. Experimental evidences from various in vitro and in vivo imply that fruit extracts and/or isolated bioactive compounds are associated with antioxidant, anti-inflammatory, antimicrobial, cardioprotective, and neuroprotective properties. Therefore, fruits have the potential to be converted into functional foods as well as pharmaceuticals to prevent or/and treat several chronic complications. In the present article, we review current knowledge about the bioactivities and health benefits of selected Indian fruits for the treatment/management of the chronic health complications in humans. PRACTICAL APPLICATIONS: This review provides practical information about how best to take advantage of the bioactive compounds and health implications of the South Indian fruits like Bael, Jujube, Cotton Candy Berry, and Manilla Tamarind as a potential source of functional and nutritive compounds. It aims at emphasizing the most recent findings on biological effects of major groups of fruits like Bael, Jujube, Cotton Candy Berry, and Manilla Tamarind and their major components, their medical interest, potential drug interaction, notably for human nutrition, health benefits, and therapeutic impacts.

Co-optimization of axial root phenotypes for nitrogen and phosphorus acquisition in common bean.

Background and Aims: Root architecture is a primary determinant of soil resource acquisition. We hypothesized that root architectural phenes will display both positive and negative interactions with each other for soil resource capture because of competition for internal resources and functional trade-offs in soil exploration. Methods: We employed the functional-structural plant model SimRoot to explore how interactions among architectural phenes in common bean determine the acquisition of phosphate and nitrate, two key soil resources contrasting in mobility. We evaluated the utility of basal root whorl number (BRWN) when basal root growth angle, hypocotyl-borne roots and lateral root branching density (LRBD) were varied, under varying availability of phosphate and nitrate. Key Results: Three basal root whorls were optimal in most phenotypes. This optimum shifted towards greater values when LRBD decreased and to smaller numbers when LRBD increased. The maximum biomass accumulated for a given BRWN phenotype in a given limiting nutrient scenario depended upon root growth angle. Under phosphorus stress shallow phenotypes grew best, whereas under nitrate stress fanned phenotypes grew best. The effect of increased hypocotyl-borne roots depended upon BRWN as well as the limiting nutrient. Greater production of axial roots due to BRWN or hypocotyl-borne roots reduced rooting depth, leading to reduced biomass under nitrate-limiting conditions. Increased BRWN as well as greater LRBD increased root carbon consumption, resulting in reduced shoot biomass. Conclusions: We conclude that the utility of a root architectural phenotype is determined by whether the constituent phenes are synergistic or antagonistic. Competition for internal resources and trade-offs for external resources result in multiple phenotypes being optimal under a given nutrient regime. We also find that no single phenotype is optimal across contrasting environments. These results have implications for understanding plant evolution and also for the breeding of more stress-tolerant crop phenotypes.