Phenotypic variation of cassava root traits and their responses to drought

Cassava Breeding and Cultivation Challenges in Thailand: Past, Present, and Future Perspectives

Cassava (Manihot esculenta Crantz) was introduced to Southeast Asia in the 16th-17th centuries and has since flourished as an industrial crop. Since the 1980s, Thailand has emerged as the leading producer and exporter of cassava products. This growth coincided with the initiation of cassava breeding programs in collaboration with the International Center for Tropical Agriculture (CIAT), focusing on root yield and starch production. The success of Thai cassava breeding programs can be attributed to the incorporation of valuable genetic diversity from international germplasm resources to cross with the local landraces, which has become the genetic foundation of many Thai commercial varieties. Effective evaluation under diverse environmental conditions has led to the release of varieties with high yield stability. A notable success is the development of Kasetsart 50. However, extreme climate change poses significant challenges, including abiotic and biotic stresses that threaten cassava root yield and starch content, leading to a potential decline in starch-based industries. Future directions for cassava breeding must include hybrid development, marker-assisted recurrent breeding, and gene editing, along with high-throughput phenotyping and flower induction. These strategies are essential to achieve breeding objectives focused on drought tolerance and disease resistance, especially for CMD and CBSD.

Temporal phenotypic variation of spinach root traits and its relation to shoot performance

The root system is important for the growth and development of spinach. To reveal the temporal variability of the spinach root system, root traits of 40 spinach accessions were measured at three imaging times (20, 30, and 43 days after transplanting) in this study using a non-destructive and non-invasive root analysis system. Results showed that five root traits were reliably measured by this system (RootViz FS), and two of which were highly correlated with manually measured traits. Root traits had higher variations than shoot traits among spinach accessions, and the trait of mean growth rate of total root length had the largest coefficients of variation across the three imaging times. During the early stage, only tap root length was weakly correlated with shoot traits (plant height, leaf width, and object area (equivalent to plant surface area)), whereas in the third imaging, root fresh weight, total root length, and root area were strongly correlated with shoot biomass-related traits. Five root traits (total root length, tap root length, total root area, root tissue density, and maximal root width) showed high variations with coefficients of variation values (CV ≥ 0.3, except maximal root width) and high heritability (H2 > 0.6) among the three stages. The 40 spinach accessions were classified into five subgroups with different growth dynamics of the primary and lateral roots by cluster analysis. Our results demonstrated the potential of in-situ phenotyping to assess dynamic root growth in spinach and provide new perspectives for biomass breeding based on root system ideotypes.

Evaluation of the effects of elevated CO2 concentrations on the growth of cassava storage roots by destructive harvests and ground penetrating radar scanning approaches

Cassava (Manihot esculenta Crantz) production will need to be improved to meet future food demands in Sub-Saharan Africa. The selection of high-yielding cassava cultivars requires a better understanding of storage root development. Additionally, since future production will happen under increasing atmospheric CO₂ concentrations ([CO₂ ]), cultivar selection should include responsiveness to elevated [CO₂ ]. Five farmer-preferred African cassava cultivars were grown for three and a half months in a Free Air CO₂ Enrichment experiment in central Illinois. Compared to ambient [CO₂ ] (~400 ppm), cassava storage roots grown under elevated [CO₂ ] (~600 ppm) had a higher biomass with some cultivars having lower storage root water content. The elevated [CO₂ ] stimulation in storage root biomass ranged from 33% to 86% across the five cultivars tested documenting the importance of this trait in developing new cultivars. In addition to the destructive harvests to obtain storage root parameters, we explored ground penetrating radar as a nondestructive method to determine storage root growth across the growing season.

CC-type glutaredoxin, MeGRXC3, associates with catalases and negatively regulates drought tolerance in cassava (Manihot esculenta Crantz)

Glutaredoxins (GRXs) are essential for reactive oxygen species (ROS) homeostasis in responses of plants to environment changes. We previously identified several drought-responsive CC-type GRXs in cassava, an important tropical crop. However, how CC-type GRX regulates ROS homeostasis of cassava under drought stress remained largely unknown. Here, we report that a drought-responsive CC-type GRX, namely MeGRXC3, was associated with activity of catalase in the leaves of 100 cultivars (or unique unnamed genotypes) of cassava under drought stress. MeGRXC3 negatively regulated drought tolerance by modulating drought- and abscisic acid-induced stomatal closure in transgenic cassava. It antagonistically regulated hydrogen peroxide (H₂ O₂ ) accumulation in epidermal cells and guard cells. Moreover, MeGRXC3 interacted with two catalases of cassava, MeCAT1 and MeCAT2, and regulated their activity in vivo. Additionally, MeGRXC3 interacts with a cassava TGA transcription factor, MeTGA2, in the nucleus, and regulates the expression of MeCAT7 through a MeTGA2-MeMYB63 pathway. Overall, we demonstrated the roles of MeGRXC3 in regulating activity of catalase at both transcriptional and post-translational levels, therefore involving in ROS homeostasis and stomatal movement in responses of cassava to drought stress. Our study provides the first insights into how MeGRXC3 may be used in molecular breeding of cassava crops.

Cassava root crown phenotyping using three-dimension (3D) multi-view stereo reconstruction

Phenotypic analysis of cassava root crowns (CRCs) so far has been limited to visual inspection and very few measurements due to its laborious process in the field. Here, we developed a platform for acquiring 3D CRC models using close-range photogrammetry for phenotypic analysis. The state of the art is a low cost and easy to set up 3D acquisition requiring only a background sheet, a reference object and a camera, compatible with field experiments in remote areas. We tested different software with CRC samples, and Agisoft and Blender were the most suitable software for generating high-quality 3D models and data analysis, respectively. We optimized the workflow by testing different numbers of images for 3D reconstruction and found that a minimum of 25 images per CRC can provide high quality 3D models. Up to ten traits, including 3D crown volumes, 3D crown surface, root density, surface-to-volume ratio, root numbers, root angle, crown diameter, cylinder soil volume, CRC compactness and root length can be extracted providing novel parameters for studying cassava storage roots. We applied this platform to partial-inbred cassava populations and demonstrated that our platform provides reliable 3D CRC modelling for phenotypic analysis, analysis of genetic variances and supporting breeding selection.

Nutrient deficiency effects on root architecture and root-to-shoot ratio in arable crops

Plant root traits play a crucial role in resource acquisition and crop performance when soil nutrient availability is low. However, the respective trait responses are complex, particularly at the field scale, and poorly understood due to difficulties in root phenotyping monitoring, inaccurate sampling, and environmental conditions. Here, we conducted a systematic review and meta-analysis of 50 field studies to identify the effects of nitrogen (N), phosphorous (P), or potassium (K) deficiencies on the root systems of common crops. Root length and biomass were generally reduced, while root length per shoot biomass was enhanced under N and P deficiency. Root length decreased by 9% under N deficiency and by 14% under P deficiency, while root biomass was reduced by 7% in N-deficient and by 25% in P-deficient soils. Root length per shoot biomass increased by 33% in N deficient and 51% in P deficient soils. The root-to-shoot ratio was often enhanced (44%) under N-poor conditions, but no consistent response of the root-to-shoot ratio to P-deficiency was found. Only a few K-deficiency studies suited our approach and, in those cases, no differences in morphological traits were reported. We encountered the following drawbacks when performing this analysis: limited number of root traits investigated at field scale, differences in the timing and severity of nutrient deficiencies, missing data (e.g., soil nutrient status and time of stress), and the impact of other conditions in the field. Nevertheless, our analysis indicates that, in general, nutrient deficiencies increased the root-length-to-shoot-biomass ratios of crops, with impacts decreasing in the order deficient P > deficient N > deficient K. Our review resolved inconsistencies that were often found in the individual field experiments, and led to a better understanding of the physiological mechanisms underlying root plasticity in fields with low nutrient availability.

DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r2>0.84 and a high broad-sense heritability of Hmean2> 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

Rated-M for mesocosm: allowing the multimodal analysis of mature root systems in 3D

A plants' water and nutrients are primarily absorbed through roots, which in a natural setting is highly dependent on the 3-dimensional configuration of the root system, collectively known as root system architecture (RSA). RSA is difficult to study due to a variety of factors, accordingly, an arsenal of methods have been developed to address the challenges of both growing root systems for imaging, and the imaging methods themselves, although there is no 'best' method as each has its own spectrum of trade-offs. Here, we describe several methods for plant growth or imaging. Then, we introduce the adaptation and integration of three complementary methods, root mesocosms, photogrammetry, and electrical resistance tomography (ERT). Mesocosms can allow for unconstrained root growth, excavation and preservation of 3-dimensional RSA, and modularity that facilitates the use of a variety of sensors. The recovered root system can be digitally reconstructed through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. Lastly, we demonstrate how 3-dimensional water availability can be measured using ERT inside of root mesocosms.

Technological Innovations for Improving Cassava Production in Sub-Saharan Africa

Cassava is crucial for food security of millions of people in sub-Saharan Africa. The crop has great potential to contribute to African development and is increasing its income-earning potential for small-scale farmers and related value chains on the continent. Therefore, it is critical to increase cassava production, as well as its quality attributes. Technological innovations offer great potential to drive this envisioned change. This paper highlights genomic tools and resources available in cassava. The paper also provides a glimpse of how these resources have been used to screen and understand the pattern of cassava genetic diversity on the continent. Here, we reviewed the approaches currently used for phenotyping cassava traits, highlighting the methodologies used to link genotypic and phenotypic information, dissect the genetics architecture of key cassava traits, and identify quantitative trait loci/markers significantly associated with those traits. Additionally, we examined how knowledge acquired is utilized to contribute to crop improvement. We explored major approaches applied in the field of molecular breeding for cassava, their promises, and limitations. We also examined the role of national agricultural research systems as key partners for sustainable cassava production.

Causal shoot and root system traits to variability and plasticity in juvenile cassava (Manihot esculenta Crantz) plants in response to reduced soil moisture

Cassava is an important source of food security and livelihoods for millions of consumers daily. Water deficit conditions are one of the major factors that affect the development of root system architecture (RSA) and consequently, crop productivity, and yet, due to its long maturity periods and bulky storage root systems, RSA studies in cassava are uncommon. The objective of this study was to identify traits that are responsible for the variability and plastic responses of cassava in response to drought at the juvenile stage of growth. Eight cassava genotypes were grown in soil-filled pots under well-watered and droughted conditions for up to 45 days and multivariate analyses employed to determine the major contributory traits to variability and the relative distance plasticity index (RDPI) was computed to evaluate plasticity. There were significant genotypic variations for most of the traits measured. Drought generally inhibited root production and development and the degree of inhibition was between 2 and 22%. Regardless of the soil moisture condition, traits which differentiated the RSA included root biomass, root numbers, root branching density, and total root length, and these were also the important contributory traits to variability under well-watered soil conditions. Important contributory traits to variability traits under drought were shoot-related traits such as leaf area and shoot biomass, and also root system traits such as nodal root number, root biomass, diameter and branching density. Phenotypic plasticity was found in most traits where the number, branching density and diameter of upper nodal roots presented the highest RDPI. These traits corresponded with the traits contributing greatly to variation. Plastic responses of cassava to drought were dependent on trait and genotype. It is concluded that upper nodal roots-related traits could have importance in breeding cassava to better tolerate water deficit conditions. The secondary growth and ability to maintain or increase the upper nodal root count or density under limited soil moisture may be related to good growth and yield performance of cassava under drought conditions. Upper nodal roots could be used to screen and select cassava genotypes adapted to drought at the juvenile stage but as a potential indirect selection strategy, the persistence and pertinence of these traits and their relationship with yield and yield components under drought conditions in the field must be confirmed.

The search for yield predictors for mature field-grown plants from juvenile pot-grown cassava (Manihot esculenta Crantz)

Cassava is the 6th most important source of dietary energy in the world but its root system architecture (RSA) had seldom been quantified. Ability to select superior genotypes at juvenile stages can significantly reduce the cost and time for breeding to bridge the large yield gap. This study adopted a simple approach to phenotyping RSA traits of juvenile and mature cassava plants to identify genotypic differences and the relationships between juvenile traits and harvest index of mature plants. Root classes were categorised and root and shoot traits of eight (8) juvenile pot-grown cassava genotypes, were measured at 30 and 45 days after planting (DAP). The same or related traits were measured at 7 months after planting of the same genotypes grown in the field while yield and yield components were measured in 12-months old field-grown plants. The field experiment was done in 2017 and repeated in 2018. Differences between genotypes for the measured traits were explored using analysis of variance (ANOVA) while traits in juvenile plants were correlated or regressed onto traits measured in 7- and 12-months old plants. The results show significant genotypic variations for most of the traits measured in both juvenile and 7-months old plants. In the 12-months old plants, differences between genotypes were consistent for both 2017 and 2018. Broad-sense heritability was highest for the number of commercial roots (0.87) and shoot fresh weight (0.78) and intermediate for the total number of roots (0.60), harvest index (0.58), fresh weight of roots (0.45). For all the sampling time points or growth stages, there were greater correlations between traits measured at a particular growth stage than between the same traits at different growth stages. However, some juvenile-mature plant trait relationships were significant, positive and consistent for both 2017 and 2018. For example, total root length and the total number of roots in 30 DAP, and branching density of upper nodal roots in 45 DAP, positively correlated with harvest index of 12-months old plants in both 2017 and 2018. Similarly, the diameter of nodal roots, for example, had a negative, significant correlation with fresh shoot biomass of mature plants in both 2017 and 2018. Regression of traits measured in 30 DAP explained up to 22% and 36% of the variation in HI of mature plants in 2017 and 2018, respectively. It is concluded that the simple, rapid, inexpensive phenotyping approach adopted in this study is robust for identifying genotypic variations in juvenile cassava using root system traits. Also, the results provide seminal evidence for the existence of useful relationships between traits of juvenile and mature cassava plants that can be explored to predict yield and yield components.