Problem:
Root systems are essential for faba bean productivity because they determine how effectively plants acquire water and nutrients and interact with soil organisms. However, studying and measuring roots in the field is far more labour-intensive and complex than assessing above-ground plant traits.

Solution:
To support efficient and standardised field assessment of faba bean root architecture, the shovelomics method was developed and validated. It provides a practical way to characterise root traits directly from excavated plants using simple tools.

Principle:
Shovelomics involves excavating plants to a depth of about 20 cm, washing the root crown, and evaluating the 3D structure of the root system using a shovelomics board. The method allows measurement of key traits, including root angle, taproot diameter, maximum root depth, root number and length, epicotyl root number, and biomass, with optional assessment of nodulation.

Benefits:
The method is well-suited for high-throughput phenotyping in breeding and research programmes and does not require specialised equipment. It enables consistent measurement of relevant faba bean root traits within the topsoil layer (0–20 cm). Additional parameters, such as root dry weight or nodulation activity, can be included when needed to extend the analysis.

For more information, please see:
https://zenodo.org/records/17296615

• Full practice abstract
• Video - Shovelomics in Faba Beans: A Practical Guide

Problem:
Root systems are essential for crop performance because they determine how plants access water and nutrients. However, studying and measuring root traits in the field is difficult and labour-intensive compared to above-ground observations.

Solution:
To make field root studies more accessible, the shovelomics method was developed and adapted for cereals. It enables rapid, standardised measurements of key root crown traits directly from plants excavated with a spade.

Principle:
Shovelomics consists of sampling plants to a depth of about 20 cm, washing the root crowns, and assessing their 3D architecture. Using a shovelomics board, traits such as root width, depth, angle, number, length, and branching density can be measured by hand in a simple and repeatable way.

Benefits:
The method is well suited for high-throughput field phenotyping and does not require specialist equipment. It provides reliable measurements of root traits in the upper soil layer (0–20 cm), supporting breeding programmes and research on plant resilience. Some traits, such as root length or diameter, may be complemented with software-based measurements if needed.

For more information, please see:
https://zenodo.org/records/13584451

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• Video - Shovelomics in straw cereals: A practical guide

Problem

Conventional methods to quantify arbuscular mycorrhizal fungal (AMF) colonization include microscopy, which involves staining of the roots and meticulous observation. This method is time consuming and subjective because it depends on the observer’s level of expertise.

Solution

The use of broad range qPCR primers was validated to quantify AMF root colonization in different crops. This high-throughput and reliable technique is versatile and suitable for a wide range of research projects.

Benefits and weaknesses

Compared to the conventional microscopy method, qPCR allows the simultaneous analysis of a larger number of samples. Moreover, the results of qPCR are not influenced by observer subjectivity. AMF quantification can be complemented by sequencing the PCR product to assess AMF diversity. One weakness of the qPCR method is that it cannot distinguish between the different AMF  structures. In addition, it is worth noting that the qPCR method
yielded inconclusive results when applied to leek, possibility due to negligible changes in colonization rate (Corona Ramírez et al. 2023). We conclude that the qPCR method should be validated for each crop.

For more information, please see https://zenodo.org/records/10812217

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Problem
Crop genotypes interact with their environment, which is influenced by soil type and weather, and are affected by the management systems used for their cultivation. To understand why a crop has performed in a particular way and to allow comparison of this performance across multiple locations, it is necessary to characterize the growing environment.

Solution
Envirotyping can show how environmental factors affect plant growth and development. Recording weather conditions, soil parameters and management practices is crucial to accurately characterise the crop growing environment. This information can further be used in crop models to estimate aspects of crop performance that are more difficult to measure, such as crop water use (IRRIGUIDE, ADAS) and nitrogen uptake (CHN, ARVALIS). See figure 1 and 2 for examples.

Principle data inputs

Weather: Rainfall, temperature, solar radiation, humidity, wind speed
Soil: Topsoil depth, subsoil depth to rock, texture in the different horizons, pH, soil organic matter, nutrient concentrations (e.g., P, K and Mg), water holding capacity, bulk density, stone content, total nitrogen, calcium carbonate content, maximum rooting depth
Field: Location (longitude and latitude), altitude, previous crop, sowing and harvest dates, crop type, nutritional inputs, dates of main developmental stages, irrigation, crop protection management information
Quality of the data determines model quality: The quality of the data will determine how well the interaction between genotype, environment and management can be assessed. For instance, localized rainfall data, recent soil nutrient reports, soil organic matter and pH information alongside representative soil sampling methods are essential for an accurate evaluation.

For full practice abstract, see: https://zenodo.org/records/13683214 

• Full practice abstract

Problem: Agricultural production and it’s crop breeding programs are mainly oriented towards above-ground biomass. Nevertheless, phenotypic plasticity of the root system can improve resilience to environmental stress and ensure crop production under detrimental  conditions.

Solution: The ability to alter phenotypic root traits in response to the environment can be integrated in breeding programs when the plasticity of individual root traits can be quantified. The relative distance plasticity index (RDPI), as describes by Valladares et al. (2006), is a useful and easy to use index for the quantification of the plasticity of root traits. It can be applied in laboratory as well as in field conditions.

Benefits: By integrating root plasticity in breeding programs, the resilience of crops to drought, heat stress or limited nutrient availability  can be improved.

For more information, please see: https://zenodo.org/records/8392071 

• Full practice abstract

Problem: To study the plasticity of root traits related to exploration and exploitation of soil environments, a range of methods need to be applied simultaneously. Tradeoffs between sample size and resolution for  visualisation as well as sample size for metabolome and transcriptome analysis and potential compromise of the quantification of root system size and diameters, need to be considered.

Solution: An ‘in-depth traits assessment and understanding of plasticity’ combines (1) X-ray computed tomography (CT) for the visualisation and characterisation of root system architecture (RSA) in 3D during growth
(figure 1); (2) WinRHIZO-analysis for quantification of root system size and diameters; (3) root gene expression analysis (Transcriptomics) for adaption of the plants to actual growth conditions, and (4) root metabolome analysis (Metabolomics) for information on the history of growth conditions.

Benefits: By combining the above mentioned methods it is possible to study the plasticity of root systems in response to environmental conditions like differences in soil texture and chemical properties, water availability and nutrient supply.

For more information, please see: https://zenodo.org/records/8392410 

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Problem: Root systems, along with their interactions with soil conditions and micro-organisms, are crucial for crop performance, mainly through the efficient capture of water and nutrients. These root traits significantly enhance crop resilience against climate change. However, measuring root systems is more labor-intensive compared to the above-ground  parts of plants.

Solution: Four methods – minirhizotron, soil pit, soil coring and shovelomics (figure 1) – were evaluated to assess their capacity to measure root traits in different crops and their accessibility (table 1).

Benefits: All four methods have advantages. The minirhizotron, soil pit, and soil coring methods can measure roots to depths of 1 m or more. Shovelomics, while limited to measuring surface roots in the top 20 cm, is a much faster method.

For more information, please see: https://zenodo.org/records/13683049 

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Problem: Conventional root measurement methods rely on destructive sampling, which is time-consuming and prevents monitoring living roots over time. This limits the ability to study root dynamics and their contribution to crop resilience.

Solution: The minirhizotron method uses transparent soil tubes and a rotary scanner to capture images of roots at different depths. ARVALIS has developed dedicated software with deep learning algorithms to extract traits such as root length, density, and diameter.

Benefits: This non-destructive technique enables continuous and objective monitoring of root growth, including deep roots (30–100 cm). While not a high-throughput method, it provides reliable data across arable crops and supports research into crop performance under stress.

For more information, please see: https://zenodo.org/records/13883914

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Problem: Breeding for resilience to abiotic stress is difficult because it is challenging to quantify how specific root and rhizosphere traits influence crop performance. Traditional approaches cannot easily capture the complex interactions between root systems, soil, water, and microorganisms.

Solution: Mathematical models, developed using genotypic and environmental data, can simulate root system growth and their interactions with soil. These models account for processes such as rhizodeposition, water transport, and microbial activity, enabling predictions of plant performance under different conditions.

Benefits: Rhizosphere models allow researchers to test how root traits influence resilience, such as the capacity of roots to maximise water uptake during drought. They provide a powerful tool to design crop ideotypes and to inform breeding and management strategies under climate change.

For more information, please see: https://zenodo.org/records/14674393

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Problem: The root system architecture and its interactions with soil microorganisms play a key role in crop performance, particularly in the capture of water and mineral elements. Studying roots is more complicated than studying the above-ground parts.

Solution: To facilitate the complex study of root systems, the shovelomics method was validated.

Principle: The Shovelomics method measures root traits on plants sampled with a spade. With this simple method, we can access the 3D architecture of the main roots growing into the ridge.

Benefits: Using shovelomics, root traits can be measured in 0 to 20 cm depth in the ridge. The parameters are measured by hand and software is required to measure the root length and root diameter automatically.

For more information, please see: https://zenodo.org/records/13584451

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• Full practice abstract in French
• Video - Shovelomics in Potato: how to study potato root systems with a shovel

Problem: Root systems play a central role in crop performance by capturing water and nutrients, but their development can be restricted by soil structure, compaction, or agronomic practices. Measuring root growth at depth is essential for assessing crop resilience and resource-use efficiency, yet it remains challenging under field conditions.

Solution: The soil coring method involves collecting soil cores down to 1 m (or deeper with suitable equipment), washing out roots, and analysing traits such as root length density, diameter, and biomass. Standardised procedures allow comparison of varieties, treatments, and management practices in real field conditions.

Benefits: Soil coring provides detailed information on root distribution throughout the soil profile, making it a robust method applicable to many crops. However, it is time- and labour-intensive, which limits its use in large-scale breeding trials.

For more information, please see: https://zenodo.org/records/15591147

• Full Practice Abstract

Problem: Root systems are essential for water and nutrient capture, but their growth is often constrained by soil structure, compaction, and management. Measuring root depth and distribution in situ is necessary to understand how crops establish under real field conditions, yet it is difficult to assess these traits without destructive methods.

Solution: The soil pit method (or profile wall method) involves digging a pit to 1–2 m depth, scraping the soil face, and recording root presence and distribution of roots on a grid. This direct field-based approach provides insight into root depth, spread, and interactions with soil conditions.

Benefits: The soil pit method gives a clear picture of root system distribution and soil–root interactions, making it valuable for detailed agronomic studies. However, it is time-consuming and destructive, so it is better suited for research requiring fewer but more detailed observations rather than large-scale breeding trials.

For more information, please see: https://zenodo.org/records/15591203

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