A Look Back at Root Research Breakthroughs in 2024

• Several reviews that consolidate state-of-the-art show huge strides in root research.
• Many studies have explored underlying physiological, anatomical, and molecular causes of previously observed morphology or root responses to environmental and soil conditions.
• Research is focused on applying these underlying mechanisms to manipulate patterns in root morphology and growth to increase crop yield sustainably or understand forest dynamics.

Climate change effects are increasingly being felt across the globe, impacting crop yield and disrupting natural ecosystems. Root research has progressed vastly in recent years, aided by novel root imaging and data collection techniques, which can address many climate change effects. This article covers a few of the experiments and consolidations of knowledge that occurred in 2024.

Plant Roots Sense Soil Compaction Through Ethylene Diffusion

Figure 1: “Root responses in compacted soil conditions. The left side of the image illustrates root soil compaction responses in non-compacted soil conditions that allow for the optimal diffusion of ethylene through connected soil pores, resulting in favourable root growth responses. In contrast, the right side of the image depicts the effects of soil compaction (reduced soil pore volumes), which restricts the diffusion of ethylene, causing a reduction in root growth. Compaction has several effects on root-soil responses, including the secretion of mucilage, reduced branching, thicker roots, dense root hairs, and decreased water infiltration and gaseous exchange. Ethylene is represented by filled yellow circles,” Pandey, B.K. & Bennett, M.J. (2024). (Image credits: https://doi.org/10.1093/jxb/erad389)

Drought, soil compaction, and other soil stress can cause 20-70% crop yield loss.

Soil with good structure has 50% soil, 25% water, and 25% air-filled pores. Soil compaction results in more soil and less water and air, which can restrict water availability, gas exchange, and root tip growth. Management practices are used to deal with soil compaction. However, the widespread use of heavy machinery has made soil compaction a common problem in agriculture. Besides restricting root growth, soil compaction reduces water infiltration, gas exchange, water retention capacity, and microbial activity.

Scientific Findings

A review by Pandey and Bennett 2024 reviewed recent findings on how plants detect soil compaction and the strategies scientists use to develop varieties that can grow in compacted soils. The review summary is given below.

The common wisdom was that root growth was restricted due to the soil’s mechanical impedance and lower water availability. Earlier scientific findings agreed with the following trends:

• Soil compaction causes root growth restriction, reducing root length.
• The width of root tips increases in compacted soil in several crops as it provides more resistance to buckling in compact soils than thin root tips.
• Soil compaction increases root tip mucilage secretion to reduce friction between soil particles and root cells. So, increasing root mucilage secretion can help in growth.
• Root branching density and timing are reduced in compacted soils and are regulated by ABA hormones.
• Multiple cortical sclerenchymatous (MCS) cells are higher in number in outer cortical cells and reduce root buckling, allowing for growth in compacted soil.

The findings from recent studies, depicted in Figure 1, show that ethylene is an important molecular mechanism that influences several of the above root responses to soil compaction, as listed below:

1. Porosity: Pores are usually interconnected, allowing wide diffusion of phytohormone ethylene, a growth-stopping signal. In compact soil, pore connectivity is broken, so ethylene gets trapped close to the roots in wild types. Ethylene restricts root growth more than the mechanical force of compaction and makes root tips thicker. Roots of ethylene-insensitive mutants can’t detect ethylene, so they remain sharper in shape and will continue to grow.
2. Root tip growth: Ethylene regulates radial root and cell expansion by moderating two hormone signals, ABA and auxin. Soil compaction induces genes to produce more ABA, causing root tip swelling. Higher auxin accumulation in epidermal cells restricts root growth.
3. Root tip shape: Plants with sharper root tips are more successful in piercing compacted soil than round root tips.
4. MSC: Multiple cortical sclerenchymatous (MCS) cells, which aid in growth in compacted soils, are controlled by ethylene.

Ethylene modulation of root responses to soil compaction has been tested only on sandy and clay loam. The theory must be tested in more soils with varying textures to check if the ethylene effect is a universal plant mechanism.

Early studies show that manipulating the ethylene response in roots can help produce cultivars that can overcome soil compaction effects in tested soils.

Takeaway: The review of recent studies shows that plants use ethylene diffusion to detect soil compaction indirectly and that the molecular and physiological responses connected to it could be manipulated to improve crop yields.

2. Root Phenotypes to Improved Nitrogen Capture

Figure 2: “Genotypes vary in their plastic response to environment, nitrogen stress, and drought. Architectural and anatomical images are presented from a single genotype in response to different environments and edaphic stress conditions. Phenotypic plasticity is shown for root architecture, root anatomy, and lateral branching length and density. Scale bar represents 2 cm (root crown and lateral branch) and 1 mm (anatomy) ” Lynch et al 2024. (Image credits: https://doi.org/10.1007/s11104-023-06301-2)

Lack of nitrogen, a crucial macronutrient, is the primary factor limiting crop yields in low-input regions and is a cause of environmental and economic problems in high-input areas. Crops use only 25-50% of the applied nitrogen, so current nitrogen fertilization levels are inefficient, with leaks into soil, water, and air. Developing cultivars that capture more nitrogen can reduce fertilization levels and improve yields.

Review

Plants use growth and root exploration to get more nitrogen. Attributes like vigor, adaptation, and stress resistance can influence the resources that are finally allotted for root and shoot growth, affecting nitrogen exploration. Crop plants develop different phenology in various stress conditions, as shown in Figure 2. Phenology is vital as soil nitrogen availability varies over time, and it can influence soil exploration duration, nutrient absorption, and crop use.

Lynch et al. 2024, reviewed the root phenotypes that could be targeted for improving nitrogen absorption by plants. The scientists chose root traits for future crop breeding that have a chance in realistic controlled or natural conditions. The key variations, according to the scientists, can be classified into four categories described below:

• Architectural phenotypes: Intraspecific root variation in cereal crops is associated with better nitrogen capture, such as architectural phenotypes, which influence the correlation of root foraging with soil nitrogen availability.
• Anatomical phenotypes: Root anatomic features can improve penetration in challenging soils, exploit the rhizosphere, and reduce metabolic costs of soil exploration for nitrogen.
• Subcellular phenotypes: Developing plants with tissue that require less nitrogen.
• Molecular phenotypes: At the molecular level, the plant roots should improve associations with rhizosphere microbiome and nitrate uptake kinetics.

The scientists found that considerable phenotypic variations have already been identified in each category. The effect of these phenotypes in improving root nitrogen capture is influenced by soil hydrology and compaction, as well as breeding strategies. Internal factors like integrated phenotypes and plasticity will also be essential to consider.

The scientists concluded that we have an adequate understanding of root phenotypes to apply in developing new cultivars to enhance nitrogen capture.

Takeaway: Root phenotypes are currently underutilized but are a viable option for improving nitrogen capture with the available knowledge of morphological to molecular phenotypes in global agriculture.

Ethylene Controls Root Angle

Root angle is the angle at which the root grows away from the vertical primary root. It is a crucial trait in cereal crops, determining resource capture from various soil layers and yield. Root angle also influences the spatial distribution of roots in soils and stress tolerance. Shallow roots absorb more phosphorus and can avoid salinity due to salt accumulation in deeper soils. Meanwhile, deeper roots are necessary for water and nitrogen absorption. The ability to modify root angle could improve crop stress resilience and yield.

Several genes controlling root angle are involved in auxin signaling. Auxin mechanisms controlling root angle are well-known in model plant Arabidopsis. Consensus also exists that ethylene played no role in root branching. These results were also assumed to apply to cereals.

Figure 3: “A proposed model for how endogenous ethylene regulates RSA. During the developmental process of root system, endogenous ethylene was perceived by ethylene receptors, which fail to activate CTR2, reducing its repression on OsEIN2. OsEIL1 is directly responsible for activating the expression of MHZ10, an auxin biosynthesis gene, which is necessary for the formation of deep RSA via enhancing gravitropism. Ethylene-insensitive mutants exhibit shallow root systems ascribed to reduced gravitropism” Kong et al. 2024. (Image credits: https://doi.org/10.1093/plphys/kiae134)

Experiment

To discover the mechanisms influencing root angle in cereals, Kong et al. studied rice and maize ethylene and auxin signaling mutants. They germinated the seeds and grew them in a growth chamber to study hormone signaling through exogenous auxin (NAA) and 1-aminocyclopropane-1-carboxylic acid (ACC) treatments. The cultivars were grown in fields, and soil monoliths were used to observe the root system.

The study showed that ethylene influences root gravitropism by regulating auxin biosynthesis and is crucial for developing deep roots in maize and rice. Ethylene-insensitive mutants produced little auxin and had shallow root system architecture (RSA), while ethylene-sensitive mutants had deeper RSA.

Ethylene increases root gravitropism (or growth into the soil) by influencing root angle. It works upstream to auxin, which accumulates at the root tips to promote deeper growth of roots. The scientists propose a model for the ethylene-auxin mechanisms, shown in Figure 3.

The mechanisms observed in rice and maize differ from root angle control in Arabidopsis. Ethylene biosynthesis is highly regulated and influenced by abiotic and biotic stress. Hence, it can produce cultivars that grow in stressed soils, like climate change-induced drought.

Takeaway: The interaction between ethylene and auxin determined root angle in rice, maize, and possibly in other cereals.

Fine Root Lifespan Linked to Environment and Morphological Traits

 

Figure 4: “MRL distribution based on (A) leaf habits, (B) mycorrhizal types, (C) evolutionary group, and (D) plant growth rate, as well as the environmental drivers (E) MAT and (F) mean annual precipitation (MAP). AM: arbuscular mycorrhizal, EM: ectomycorrhizal,” Hou et al. 2024. (Image credits: https://doi.org/10.1073/pnas.2320623121)

Fine roots contribute to over 20% of global terrestrial net primary productivity. Still, factors controlling their persistence and turnover on large scales are poorly understood and are not well-represented in plant trait variations. Median fine root lifespan (MRL) is a vital trait that must be understood in relationship to resource acquisition and protection.

Experiment

Therefore, Hou et al. compiled a massive global dataset on MRL from 98 observations of 79 woody species across 40 sites and checked their link to other plant traits. The dataset was minirhizotron images from an extensive literature search from the Web of Science and China National Knowledge Infrastructure. The scientists analyzed the MRL of the woody species and the external and internal factors controlling them.

They studied the influence of leaf habit (deciduous and evergreen), mycorrhizal type (endo or ecto mycorrhiza), plant growth rate (fast, moderate, and slow), and evolutionary groups (gymnosperm and angiosperms) on MRL.

Their findings, summarized in Figure 4, show that MRL is affected by other root attributes like root diameter, nitrogen, and C: N ratio, which explains a large portion of variations in MRL. Larger root construction is associated with more mycorrhizal activity and increases MRL. However, more root nitrogen seen in more active root tissues reduces MRL. However, root defense categorized by root tissue density and specific root length did not affect MRL.

Gymnosperms had significantly higher MRL than angiosperms.

There is no link between shoot growth and MRL, as leaf lifespan is not correlated with MRL. Nor is plant growth rate connected with fine root lifespan.

Environmental factors like higher temperature and lower rainfall shorten MRL. The fine root lifespan was longer in sites with low temperatures and more precipitation.

Takeaway: The work shows the influence of various ecophysiological and environmental factors on woody species’ fine root lifespan. Since the dataset was massive and worldwide, it contributed to the global understanding of fine root dynamics.

5. Analyzing Minirhizotron Images With AI

Root analysis is done by detecting and counting pixels of root tissue by people using root tracing software. This process is used to find the length and diameter of roots. Manual analysis of minirhizotron root images needs a lot of resources and time; an average of 1 to 1.5 hours is required for analyzing 100 sq cm of roots. Long-term studies generate thousands of images and result in analysis bottlenecks.

Root analysis also depends on the annotator’s experience, training, and knowledge of the species examined. Moreover, inconsistencies arise within or between experiments when different individuals analyze the root images. Artificial intelligence (AI) has been used to overcome annotator bias in analyzing root images in homogeneous soils. However, their efficacy has not been tested in image analysis in heterogenous soils in forests, where root systems data is collected for carbon cycle studies.

Figure 5: “Examples of images annotated by a Novice Annotator, Experienced Annotator, and CNN model. For the manual annotation, the red lines represent the traced length, and the circles represent the traced diameter. For the CNN model annotation, the red represents all areas where the model predicted root to be present. Row one; O Horizon, 2.6 cm vertical depth. Row two; A Horizon, 19 cm vertical depth. Row three; O Horizon, 2.7 cm vertical depth,” Handy et al. 2024. (Image credits: https://doi.org/10.1186/s13007-024-01279-z)

Experiment

Handy et al. wanted to find if AI applications for analyzing diverse root data from several species could potentially improve forest root dynamic studies and help in restoration projects.

• They compared the performance of an AI with annotators having different experience levels in analyzing heterogeneous minirhizotron root images from a mature, multispecies, deciduous temperate forest. The images were of root length in a single time point and of a time series experiment.
• They also compared performance between annotators of different experiences and before and after training in root annotation.

The AI was a convolutional neural network (CNN) model trained on data that used software (RootPainter) without machine learning.

Root data was collected from the “Birmingham Institute of Forest Research Free Air Carbon Enrichment (BIFoR FACE) experimental site” in central England.

The results showed that novice annotators identified more root lengths than experienced annotators. The performance also differed between experienced annotators. See Figure 5.

The CNN model was quick and needed only 10% of the time taken by manual root annotation. The root image analysis by the CNN model was inaccurate, and it significantly overestimated root length compared to work done by experienced annotators. See Figure 5.

Due to the difference between experience and individuals, the scientists concluded that the same experienced annotator familiar with the root system should be used to analyze highly heterogeneous images with a “noisy background.”

Takeaways: The only available AI (CNN model) for heterogeneous forest root image analysis is inaccurate. More work needs to be done to develop a suitable AI model for forest root systems. Manual annotation is still necessary in ecological studies.

Data Collection

One promising root data collection method is imaging through minirhizotron systems, where a transparent root tube is installed in the soil near a plant being studied. It allows for single or time series studies as roots grow around the tube. A camera can take scans of roots at different soil depths. As the 2024 research shows, scientists are trying to make data collection and analysis more efficient to help in quicker root analysis.

Contact us at CID Bio-Science Inc. to learn how the CI-600 In-Situ Root Imager and CI-602 Narrow Gauge Root Imager can assist in your research.

Sources

Handy, G., Carter, I., Mackenzie, A. R., Esquivel-Muelbert, A., Smith, A. G., Yaffar, D., … & Arnaud, M. (2024). Variation in forest root image annotation by experts, novices, and AI. Plant Methods, 20(1), 154.

Hou, J., McCormack, M. L., Reich, P. B., Sun, T., Phillips, R. P., Lambers, H., … & Freschet, G. T. (2024). Linking fine root lifespan to root chemical and morphological traits—A global analysis. Proceedings of the National Academy of Sciences, 121(16), e2320623121.

Kong, X., Xiong, Y., Song, X., Wadey, S., Yu, S., Rao, J., … & Huang, G. (2024). Ethylene regulates auxin-mediated root gravitropic machinery and controls root angle in cereal crops. Plant Physiology, kiae134.

Lynch, J.P., Galindo-Castañeda, T., Schneider, H.M. et al. (2024).  Root phenotypes for improved nitrogen capture. Plant Soil 502, 31–85 (2024). https://doi.org/10.1007/s11104-023-06301-2

Pandey, B.K. & Bennett, M.J. (2024). Uncovering root compaction response mechanisms: new insights and opportunities, Journal of Experimental Botany, 75 (2) 578–583, https://doi.org/10.1093/jxb/erad389