Development of a phenotyping platform for high throughput screening of nodal root angle in sorghum

Unravelling sorghum functional genomics and molecular breeding: past achievements and future prospects

Sorghum, renowned for its substantial biomass production and remarkable tolerance to various stresses, possesses extensive gene resources and phenotypic variations. A comprehensive understanding of the genetic basis underlying complex agronomic traits is essential for unlocking the potential of sorghum in addressing food and feed security and utilizing marginal lands. In this context, we provide an overview of the major trends in genomic resource studies focusing on key agronomic traits over the past decade, accompanied by a summary of functional genomic platforms. We also delve into the molecular functions and regulatory networks of impactful genes for important agricultural traits. Lastly, we discuss and synthesize the current challenges and prospects for advancing molecular design breeding by gene-editing and polymerization of the excellent alleles, with the aim of accelerating the development of desired sorghum varieties.

Multi-trait association mapping for phosphorous efficiency reveals flexible root architectures in sorghum

BACKGROUND

On tropical regions, phosphorus (P) fixation onto aluminum and iron oxides in soil clays restricts P diffusion from the soil to the root surface, limiting crop yields. While increased root surface area favors P uptake under low-P availability, the relationship between the three-dimensional arrangement of the root system and P efficiency remains elusive. Here, we simultaneously assessed allelic effects of loci associated with a variety of root and P efficiency traits, in addition to grain yield under low-P availability, using multi-trait genome-wide association. We also set out to establish the relationship between root architectural traits assessed in hydroponics and in a low-P soil. Our goal was to better understand the influence of root morphology and architecture in sorghum performance under low-P availability.

RESULT

In general, the same alleles of associated SNPs increased root and P efficiency traits including grain yield in a low-P soil. We found that sorghum P efficiency relies on pleiotropic loci affecting root traits, which enhance grain yield under low-P availability. Root systems with enhanced surface area stemming from lateral root proliferation mostly up to 40 cm soil depth are important for sorghum adaptation to low-P soils, indicating that differences in root morphology leading to enhanced P uptake occur exactly in the soil layer where P is found at the highest concentration.

CONCLUSION

Integrated QTLs detected in different mapping populations now provide a comprehensive molecular genetic framework for P efficiency studies in sorghum. This indicated extensive conservation of P efficiency QTL across populations and emphasized the terminal portion of chromosome 3 as an important region for P efficiency in sorghum. Increases in root surface area via enhancement of lateral root development is a relevant trait for sorghum low-P soil adaptation, impacting the overall architecture of the sorghum root system. In turn, particularly concerning the critical trait for water and nutrient uptake, root surface area, root system development in deeper soil layers does not occur at the expense of shallow rooting, which may be a key reason leading to the distinctive sorghum adaptation to tropical soils with multiple abiotic stresses including low P availability and drought.

Genetic dissection of root architecture in Ethiopian sorghum landraces

KEY MESSAGE

This study quantified genetic variation in root system architecture (root number, angle, length and dry mass) within a diversity panel of 1771 Ethiopian sorghum landraces and identified 22 genomic regions associated with the root variations. The root system architecture (RSA) of crop plants influences adaptation to water-limited conditions and determines the capacity of a plant to access soil water and nutrients. Four key root traits (number, angle, length and dry mass) were evaluated in a diversity panel of 1771 Ethiopian sorghum landraces using purpose-built root chambers. Significant genetic variation was observed in all studied root traits, with nodal root angle ranging from 16.4° to 26.6°, with a high repeatability of 78.9%. Genome wide association studies identified a total of 22 genomic regions associated with root traits which were distributed on all chromosomes except chromosome SBI-10. Among the 22 root genomic regions, 15 co-located with RSA trait QTL previously identified in sorghum, with the remaining seven representing novel RSA QTL. The majority (85.7%) of identified root angle QTL also co-localized with QTL previously identified for stay-green in sorghum. This suggests that the stay-green phenotype might be associated with root architecture that enhances water extraction during water stress conditions. The results open avenues for manipulating root phenotypes to improve productivity in abiotic stress environments via marker-assisted selection.

"Millet Models" for harnessing nuclear factor-Y transcription factors to engineer stress tolerance in plants: current knowledge and emerging paradigms

MAIN CONCLUSION

The main purpose of this review is to shed light on the role of millet models in imparting climate resilience and nutritional security and to give a concrete perspective on how NF-Y transcription factors can be harnessed for making cereals more stress tolerant. Agriculture faces significant challenges from climate change, bargaining, population, elevated food prices, and compromises with nutritional value. These factors have globally compelled scientists, breeders, and nutritionists to think of some options that can combat the food security crisis and malnutrition. To address these challenges, mainstreaming the climate-resilient and nutritionally unparalleled alternative crops like millet is a key strategy. The C4 photosynthetic pathway and adaptation to low-input marginal agricultural systems make millets a powerhouse of important gene and transcription factor families imparting tolerance to various kinds of biotic and abiotic stresses. Among these, the nuclear factor-Y (NF-Y) is one of the prominent transcription factor families that regulate diverse genes imparting stress tolerance. The primary purpose of this article is to shed light on the role of millet models in imparting climate resilience and nutritional security and to give a concrete perspective on how NF-Y transcription factors can be harnessed for making cereals more stress tolerant. Future cropping systems could be more resilient to climate change and nutritional quality if these practices were implemented.

Modelling plants across scales of biological organisation for guiding crop improvement

Grain yield improvement in globally important staple crops is critical in the coming decades if production is to keep pace with growing demand; so there is increasing interest in understanding and manipulating plant growth and developmental traits for better crop productivity. However, this is confounded by complex cross-scale feedback regulations and a limited ability to evaluate the consequences of manipulation on crop production. Plant/crop modelling could hold the key to deepening our understanding of dynamic trait-crop-environment interactions and predictive capabilities for supporting genetic manipulation. Using photosynthesis and crop growth as an example, this review summarises past and present experimental and modelling work, bringing about a model-guided crop improvement thrust, encompassing research into: (1) advancing cross-scale plant/crop modelling that connects across biological scales of organisation using a trait dissection-integration modelling principle; (2) improving the reliability of predicted molecular-trait-crop-environment system dynamics with experimental validation; and (3) innovative model application in synergy with cross-scale experimentation to evaluate G×M×E and predict yield outcomes of genetic intervention (or lack of it) for strategising further molecular and breeding efforts. The possible future roles of cross-scale plant/crop modelling in maximising crop improvement are discussed.

OMICS in Fodder Crops: Applications, Challenges, and Prospects

Biomass yield and quality are the primary targets in forage crop improvement programs worldwide. Low-quality fodder reduces the quality of dairy products and affects cattle's health. In multipurpose crops, such as maize, sorghum, cowpea, alfalfa, and oat, a plethora of morphological and biochemical/nutritional quality studies have been conducted. However, the overall growth in fodder quality improvement is not on par with cereals or major food crops. The use of advanced technologies, such as multi-omics, has increased crop improvement programs manyfold. Traits such as stay-green, the number of tillers per plant, total biomass, and tolerance to biotic and/or abiotic stresses can be targeted in fodder crop improvement programs. Omic technologies, namely genomics, transcriptomics, proteomics, metabolomics, and phenomics, provide an efficient way to develop better cultivars. There is an abundance of scope for fodder quality improvement by improving the forage nutrition quality, edible quality, and digestibility. The present review includes a brief description of the established omics technologies for five major fodder crops, i.e., sorghum, cowpea, maize, oats, and alfalfa. Additionally, current improvements and future perspectives have been highlighted.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

RhizoPot platform: A high-throughput in situ root phenotyping platform with integrated hardware and software

Quantitative analysis of root development is becoming a preferred option in assessing the function of hidden underground roots, especially in studying resistance to abiotic stresses. It can be enhanced by acquiring non-destructive phenotypic information on roots, such as rhizotrons. However, it is challenging to develop high-throughput phenotyping equipment for acquiring and analyzing in situ root images of root development. In this study, the RhizoPot platform, a high-throughput in situ root phenotyping platform integrating plant culture, automatic in situ root image acquisition, and image segmentation, was proposed for quantitative analysis of root development. Plants (1-5) were grown in each RhizoPot, and the growth time depended on the type of plant and the experimental requirements. For example, the growth time of cotton was about 110 days. The imaging control software (RhizoAuto) could automatically and non-destructively image the roots of RhizoPot-cultured plants based on the set time and resolution (50-4800 dpi) and obtain high-resolution (>1200 dpi) images in batches. The improved DeepLabv3+ tool was used for batch processing of root images. The roots were automatically segmented and extracted from the background for analysis of information on radical features using conventional root software (WinRhizo and RhizoVision Explorer). Root morphology, root growth rate, and lifespan analysis were conducted using in situ root images and segmented images. The platform illustrated the dynamic response characteristics of root phenotypes in cotton. In conclusion, the RhizoPot platform has the characteristics of low cost, high-efficiency, and high-throughput, and thus it can effectively monitor the development of plant roots and realize the quantitative analysis of root phenotypes in situ.

Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane

Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder’s equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement.

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.

Improving the efficiency of plant root system phenotyping through digitization and automation

Root system architecture (RSA) determines unevenly distributed water and nutrient availability in soil. Genetic improvement of RSA, therefore, is related to crop production. However, RSA phenotyping has been carried out less frequently than above-ground phenotyping because measuring roots in the soil is difficult and labor intensive. Recent advancements have led to the digitalization of plant measurements; this digital phenotyping has been widely used for measurements of both above-ground and RSA traits. Digital phenotyping for RSA is slower and more difficult than for above-ground traits because the roots are hidden underground. In this review, we summarized recent trends in digital phenotyping for RSA traits. We classified the sample types into three categories: soil block containing roots, section of soil block, and root sample. Examples of the use of digital phenotyping are presented for each category. We also discussed room for improvement in digital phenotyping in each category.

New approaches to improve crop tolerance to biotic and abiotic stresses

During the last years, a great effort has been dedicated at the development and employment of diverse approaches for achieving more stress-tolerant and climate-flexible crops and sustainable yield increases to meet the food and energy demands of the future. The ongoing climate change is in fact leading to more frequent extreme events with a negative impact on food production, such as increased temperatures, drought, and soil salinization as well as invasive arthropod pests and diseases. In this review, diverse "green strategies" (e.g., chemical priming, root-associated microorganisms), and advanced technologies (e.g., genome editing, high-throughput phenotyping) are described on the basis of the most recent research evidence. Particularly, attention has been focused on the potential use in a context of sustainable and climate-smart agriculture (the so called "next agriculture generation") to improve plant tolerance and resilience to abiotic and biotic stresses. In addition, the gap between the results obtained in controlled experiments and those from application of these technologies in real field conditions (lab to field step) is also discussed.

Phenotyping seedlings for selection of root system architecture in alfalfa (Medicago sativa L.)

BACKGROUND

The root system architecture (RSA) of alfalfa (Medicago sativa L.) affects biomass production by influencing water and nutrient uptake, including nitrogen fixation. Further, roots are important for storing carbohydrates that are needed for regrowth in spring and after each harvest. Previous selection for a greater number of branched and fibrous roots significantly increased alfalfa biomass yield. However, phenotyping root systems of mature alfalfa plant is labor-intensive, time-consuming, and subject to environmental variability and human error. High-throughput and detailed phenotyping methods are needed to accelerate the development of alfalfa germplasm with distinct RSAs adapted to specific environmental conditions and for enhancing productivity in elite germplasm. In this study methods were developed for phenotyping 14-day-old alfalfa seedlings to identify measurable root traits that are highly heritable and can differentiate plants with either a branched or a tap rooted phenotype. Plants were grown in a soil-free mixture under controlled conditions, then the root systems were imaged with a flatbed scanner and measured using WinRhizo software.

RESULTS

The branched root plants had a significantly greater number of tertiary roots and significantly longer tertiary roots relative to the tap rooted plants. Additionally, the branch rooted population had significantly more secondary roots > 2.5 cm relative to the tap rooted population. These two parameters distinguishing phenotypes were confirmed using two machine learning algorithms, Random Forest and Gradient Boosting Machines. Plants selected as seedlings for the branch rooted or tap rooted phenotypes were used in crossing blocks that resulted in a genetic gain of 10%, consistent with the previous selection strategy that utilized manual root scoring to phenotype 22-week-old-plants. Heritability analysis of various root architecture parameters from selected seedlings showed tertiary root length and number are highly heritable with values of 0.74 and 0.79, respectively.

CONCLUSIONS

The results show that seedling root phenotyping is a reliable tool that can be used for alfalfa germplasm selection and breeding. Phenotypic selection of RSA in seedlings reduced time for selection by 20 weeks, significantly accelerating the breeding cycle.

In situ Root Phenotypes of Cotton Seedlings Under Phosphorus Stress Revealed Through RhizoPot

Phosphorus (P) deficiency is a common challenge in crop production because of its poor mobility through the soil. The root system plays a significant role in P absorption from the soil and is the initial indicator of low P levels. However, the phenotypic dynamics and longevity of cotton roots under P stress remain unknown. In this study, RhizoPot, an improvised in situ root observation device, was used to monitor the dynamics of root phenotypes of cotton seedlings under P-deficient (PD) and P-replete (PR) conditions. Low P stress reduced P absorption and accumulation in the roots, leading to low dry weight accumulation. Cotton seedlings responded to low P stress by increasing the number of lateral roots, specific root length, branch density, root length density, and length of root hairs. Additionally, the life span of root hairs was prolonged. Low P stress also reduced the average diameter of roots, promoted root extension, expanded the root coverage area, and increased the range of P acquisition. Principal component analysis revealed that the net root growth rate, root length density, root dry weight, P absorption efficiency, average root hair length, and taproot daily growth significantly influenced the cotton root architecture. Collectively, these results show that low P stress reduces the net growth rate of cotton seedling roots and restricts plant growth. Plants respond to P deficiency by extending the life span of root hairs and increasing specific root length and lateral root branch density. This change in root system architecture improves the adaptability of plants to low P conditions. The findings of this study may guide the selection of cotton varieties with efficient P utilization.

Use of Transcriptomic Analyses to Elucidate the Mechanism Governing Nodal Root Development in Eremochloa ophiuroides (Munro) Hack

Centipedegrass [Eremochloa ophiuroides (Munro) Hack.] is a perennial warm-season grass that originated in China, and its speed of nodal rooting is important for lawn establishment. In our study, centipedegrass nodal rooting ability was limited by node aging. Transcriptome sequencing of nodal roots after 0, 2, 4, and 8 days of water culture was performed to investigate the molecular mechanisms of root development. GO enrichment and KEGG pathway analyses of DEGs indicated that plant hormone signal transduction and transcription factors might play important roles in centipedegrass nodal root growth. Among them, E3 ubiquitin-protein ligases participated in multiple hormone signal transduction pathways and interacted with transcription factors. Furthermore, an E3 ubiquitin protein ligase EoSINAT5 overexpressed in rice resulted in longer roots and more numerous root tips, while knockout of LOC_Os07g46560 (the homologous gene of EoSINAT5 in rice) resulted in shorter roots and fewer root tips. These results indicated that EoSINAT5 and its homologous gene are able to promote nodal root development. This research presents the transcriptomic analyses of centipedegrass nodal roots, and may contribute to elucidating the mechanism governing the development of nodal roots and facilitates the use of molecular breeding in improving rooting ability.

High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement

Development of high-throughput phenotyping technologies has progressed considerably in the last 10 years. These technologies provide precise measurements of desired traits among thousands of field-grown plants under diversified environments; this is a critical step towards selection of better performing lines as to yield, disease resistance, and stress tolerance to accelerate crop improvement programs. High-throughput phenotyping techniques and platforms help unraveling the genetic basis of complex traits associated with plant growth and development and targeted traits. This review focuses on the advancements in technologies involved in high-throughput, field-based, aerial, and unmanned platforms. Development of user-friendly data management tools and softwares to better understand phenotyping will increase the use of field-based high-throughput techniques, which have potential to revolutionize breeding strategies and meet the future needs of stakeholders.

Loss of COMT activity reduces lateral root formation and alters the response to water limitation in sorghum brown midrib (bmr) 12 mutant

Lignin is a key target for modifying lignocellulosic biomass for efficient biofuel production. Brown midrib 12 (bmr12) encodes the sorghum caffeic acid O-methyltransferase (COMT) and is one of the key enzymes in monolignol biosynthesis. Loss of function mutations in COMT reduces syringyl (S) lignin subunits and improves biofuel conversion rate. Although lignin plays an important role in maintaining cell wall integrity of xylem vessels, physiological and molecular consequences due to loss of COMT on root growth and adaptation to water deficit remain unexplored. We addressed this gap by evaluating the root morphology, anatomy and transcriptome of bmr12 mutant. The mutant had reduced lateral root density (LRD) and altered root anatomy and response to water limitation. The wild-type exhibits similar phenotypes under water stress, suggesting that bmr12 may be in a water deficit responsive state even in well-watered conditions. bmr12 had increased transcript abundance of genes involved in (a)biotic stress response, gibberellic acid (GA) biosynthesis and signaling. We show that bmr12 is more sensitive to exogenous GA application and present evidence for the role of GA in regulating reduced LRD in bmr12. These findings elucidate the phenotypic and molecular consequences of COMT deficiency under optimal and water stress environments in grasses.

Phenotyping Tomato Root Developmental Plasticity in Response to Salinity in Soil Rhizotrons

Plants have developed multiple strategies to respond to salt stress. In order to identify new traits related to salt tolerance, with potential breeding application, the research focus has recently been shifted to include root system architecture (RSA) and root plasticity. Using a simple but effective root phenotyping system containing soil (rhizotrons), RSA of several tomato cultivars and their response to salinity was investigated. We observed a high level of root plasticity of tomato seedlings under salt stress. The general root architecture was substantially modified in response to salt, especially with respect to position of the lateral roots in the soil. At the soil surface, where salt accumulates, lateral root emergence was most strongly inhibited. Within the set of tomato cultivars, H1015 was the most tolerant to salinity in both developmental stages studied. A significant correlation between several root traits and aboveground growth parameters was observed, highlighting a possible role for regulation of both ion content and root architecture in salt stress resilience.

Harnessing High-throughput Phenotyping and Genotyping for Enhanced Drought Tolerance in Crop Plants

Development of drought-tolerant cultivars is one of the challenging tasks for the plant breeders due to its complex inheritance and polygenic regulation. Evaluating genetic material for drought tolerance is a complex process due to its spatiotemporal interactions with environmental factors. The conventional breeding approaches are costly, lengthy, and inefficient to achieve the expected gain in drought tolerance. In this regard, genomics-assisted breeding (GAB) offers promise to develop cultivars with improved drought tolerance in a more efficient, quicker, and cost-effective manner. The success of GAB depends upon the precision in marker-trait association and estimation of genomic estimated breeding values (GEBVs), which mostly depends on coverage and precision of genotyping and phenotyping. A wide gap between the discovery and practical use of quantitative trait loci (QTL) for crop improvement has been observed for many important agronomical traits. Such a limitation could be due to the low accuracy in QTL detection, mainly resulting from low marker density and manually collected phenotypes of complex agronomic traits. Increasing marker density using the high-throughput genotyping (HTG), and accurate and precise phenotyping using high-throughput digital phenotyping (HTP) platforms can improve the precision and power of QTL detection. Therefore, both HTG and HTP can enhance the practical utility of GAB along with a faster characterization of germplasm and breeding material. In the present review, we discussed how the recent innovations in HTG and HTP would assist in the breeding of improved drought-tolerant varieties. We have also discussed strategies, tools, and analytical advances made on the HTG and HTP along with their pros and cons.

Root Response to Drought Stress in Rice (Oryza sativa L.)

The current unpredictable climate changes are causing frequent and severe droughts. Such circumstances emphasize the need to understand the response of plants to drought stress, especially in rice, one of the most important grain crops. Knowledge of the drought stress response components is especially important in plant roots, the major organ for the absorption of water and nutrients from the soil. Thus, this article reviews the root response to drought stress in rice. It is presented to provide readers with information of use for their own research and breeding program for tolerance to drought stress in rice.

Non-destructive phenotyping for early seedling vigor in direct-seeded rice

BACKGROUND

Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops.

RESULTS

To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPA_i) approaches was strongly related (R² > 83%) and suggested that WPA_i can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation.

CONCLUSIONS

The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.

Bambara groundnut: an exemplar underutilised legume for resilience under climate change

Bambara groundnut has the potential to be used to contribute more the climate change ready agriculture. The requirement for nitrogen fixing, stress tolerant legumes is clear, particularly in low input agriculture. However, ensuring that existing negative traits are tackled and demand is stimulated through the development of markets and products still represents a challenge to making greater use of this legume. World agriculture is currently based on very limited numbers of crops, representing a significant risk to food supplies, particularly in the face of climate change which is expected to increase the frequency of extreme events. Minor and underutilised crops can help to develop a more resilient and nutritionally dense future agriculture. Bambara groundnut [Vigna subterranea (L.) Verdc.[, as a drought resistant, nitrogen-fixing, legume has a role to play. However, as with most underutilised crops, there are significant gaps in knowledge and also negative traits such as 'hard-to-cook' and 'photoperiod sensitivity to pod filling' associated with the crop which future breeding programmes and processing methods need to tackle, to allow it to make a significant contribution to the well-being of future generations. The current review assesses these factors and also considers what are the next steps towards realising the potential of this crop.

Root phenotypes for improved nutrient capture: an underexploited opportunity for global agriculture

Nutrient-efficient crops are a solution to the two grand challenges of modern agriculture: improving food security while reducing environmental impacts. The primary challenges are (1) nitrogen (N) and phosphorus (P) efficiency; (2) potassium (K), calcium (Ca), and magnesium (Mg) efficiency for acid soils; and (3) iron (Fe) and zinc (Zn) efficiency for alkaline soils. Root phenotypes are promising breeding targets for each of these. The Topsoil Foraging ideotype is beneficial for P capture and should also be useful for capture of K, Ca, and Mg in acid soils. The Steep, Cheap, and Deep ideotype for subsoil foraging is beneficial for N and water capture. Fe and Zn capture can be improved by targeting mechanisms of metal mobilization in the rhizosphere. Root hairs and phenes that reduce the metabolic cost of soil exploration should be prioritized in breeding programs. Nutrient-efficient crops should provide benefits at all input levels. Although our current understanding is sufficient to deploy root phenotypes for improved nutrient capture in crop breeding, this complex topic does not receive the resources it merits in either applied or basic plant biology. Renewed emphasis on these topics is needed in order to develop the nutrient-efficient crops urgently needed in global agriculture.

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high-throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype-phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.

Mapping QTLs and Identification of Genes Associated with Drought Resistance in Sorghum

Water limits global agricultural production. Increases in global aridity, a growing human population, and the depletion of aquifers will only increase the scarcity of water for agriculture. Water is essential for plant growth and in areas that are prone to drought, the use of drought-resistant crops is a long-term solution for growing more food for more people with less water. Sorghum is well adapted to hot and dry environments and has been used as a dietary staple for millions of people. Increasing the drought resistance in sorghum hybrids with no impact on yield is a continual objective for sorghum breeders. In this review, we describe the loci, quantitative trait loci (QTLs), or genes that have been identified for traits involved in drought avoidance (water-use efficiency, cuticular wax synthesis, trichome development and morphology, root system architecture) and drought tolerance (compatible solutes, pre- and post-flowering drought tolerance). Many of these identified genes and QTL regions have not been tested in hybrids and the effect of these genes, or their interactions, on yield must be understood in normal and drought-stressed conditions to understand the strength and weaknesses of their utility.

Designer Roots for Future Crops

Despite the importance of roots, they have largely been ignored by modern crop research and breeding. We discuss important progress in crop root research and highlight how the context-dependent optimisation of below- and above-ground plant components provides opportunities to improve future crops in the face of increasing environmental fluctuations.

Volatilomics: a non-invasive technique for screening plant phenotypic traits

BACKGROUND

Climate change represents a grand challenge for agricultural productivity. Understanding complex plant traits such as stress tolerance, disease resistance or crop yield is thus essential for breeding and the development of sustainable agriculture strategies. When screening for the most robust plant phenotypes, fast, high-throughput phenotyping represents the means of choice.

RESULTS

We have developed a plant phenotyping platform to measure the emission of volatile organic compounds (VOCs), photosynthetic gas exchange and transpiration under ambient, or abiotic and biotic stress conditions. These parameters are highly suitable markers to non-invasively and dynamically study plant growth and plant stress status, making them perfect test variables for long-term, online plant monitoring. Here we introduce the new phenotyping platform, termed VOC-SCREEN, and present results of a first case study with three barley cultivars, demonstrating that the plant's volatilome can be successfully applied to discriminate different barley varieties.

CONCLUSION

Volatilomics is a promising technique to non-invasively screen for plant phenotypic traits.