Microbial diversity and activity represent an aspect of soil quality. Bacteria, fungi, nematodes, protozoa and earthworms are part of the biological properties of the soil and their activity are interconnected with soil physical and chemical properties such as aeration, SOM or pH, and greatly contribute to C and nutrient cycling (Yang et al., 2018). The degradation of soils due to land-use change, erosion, compaction, and pesticide contamination has led to a decline in soil health and ecosystem services. To sustain these services and improve soil quality, it’s crucial to understand the role of microbial communities in soil health. Defining microbiota and microbiome, and using them as indicators of soil quality, is an important first step in this process. The plethora and diversity of microbes residing in the soil (bacteria, fungi, archaea, protists and algae) are collectively called soil microbiota, while microbiota together with their genomic, functional potential are collectively referred to as the microbiome (Pascale et al., 2020; Berg et al., 2020). High-throughput sequencing during the last two decades has revealed many key microbial phyla as well-represented in soil including the bacterial Proteobacteria, Bacteroidetes, Acidobacteria, Actinobacteria and the fungal Ascomycetes and Basidiomycetes. The plants can exert some pressure on the assembly of the bacterial and fungal microbiota surrounding them. Studies have demonstrated a microbial diversity gradient between the soil, the rhizosphere (the region of soil immediately surrounding the roots) and the root endosphere (inner root tissues), with less diverse microbiomes thriving inside roots compared to the rhizosphere and soil (Pascale et al., 2020; Trivedi et al., 2020). The aboveground parts of plants are also home to a diverse and variable community of microbes, deriving from the air, movement of pollinators and other insects, or other plant tissues (Vorholt, 2012). These microbes are a subset of the broader soil microbiome, and they have adapted to the unique conditions found on the aboveground parts of plants. This suggests that the soil acts as a reservoir for the microorganisms that colonize both the roots and aboveground parts of plants (Pascale et al., 2020; Trivedi et al., 2020). The soil microbiome holds great functional potential since most microbes can affect soil aggregation, can mobilize nutrients and have a role in nutrient cycling but also affect the growth and health of plants (Saleem et al., 2019; Pascale et al., 2020, Custódio et al., 2022, Liu et al., 2022). Some examples of microbial services to soil quality and plant health can be found in the section “Microbes can affect soil quality and plant health”. The importance of soil microbiota as an indicator of soil quality becomes more apparent considering that they are the source of plant-associated microbiota and can become part of our diet via the food web (Blum et al., 2019).

Due to its non-renewable nature, soil must be constantly monitored to prevent its degradation and promote long-term management. Information databases, and metastudies on soil assessment (Jian et al., 2020), facilitate the evaluation of existing and projected land production, the identification of land and water restrictions, and the assessment of risks associated with land degradation. This is critical for good management of natural resources, progress towards ending hunger, achieving food security and sustainable agriculture, especially in light of the issues caused by global climate change and the need to make the environment more resilient. In the last 15 years, the number of soil databases has rapidly increased and up-to-date there is a consistent number of those dedicated to specific soil parameters, and also those containing harmonized data from all over the world (reference https://soil-modeling.org/resources-links/data-portal/data-portal, International Soil Modeling Consortium ISMC) ( Figure 1 ; Table S1 ). We present here as case-study a well-structured soil database promoted by the European Union (EU), called “Land Use/Cover Area frame statistical Survey Soil” (LUCAS) (https://esdac.jrc.ec.europa.eu/projects/lucas). LUCAS represents the largest harmonized open-access dataset of topsoil parameters available for the EU (Orgiazzi et al., 2018). The LUCAS survey, carried out by EUROSTAT on a three-yearly basis since 2006, focuses on the state and the dynamics of changes in land use and cover in the EU. Currently, all 27 EU countries have been covered and over 270,000 points have been analyzed on different land cover types (agricultural, grassland, forest, built-up areas, transport network, etc.). A standardized sampling procedure was used to collect around 0.5 kg of topsoil (0-20 cm), successfully analyzed for chemical and physical parameters like the percentage of coarse fragments, particle size distribution (% clay, silt and sand content), pH (in CaCl₂ and H₂O), organic C (g/kg), carbonate content (g/kg), P content (mg/kg), total N content (g/kg), extractable K content (mg/kg), cation exchange capacity (cmol(+)/kg) and multispectral properties. In 2018, the LUCAS survey included additional analyses like bulk density (i.e. weight of dry soil in a given soil volume), soil biodiversity, visual assessment of soil erosion and measurement of the thickness of the organic horizon in organic-rich soil. LUCAS Soil survey 2022 is currently underway. Notably, the modules Soil Biodiversity and Pesticides were recently added to LUCAS, providing tools in this direction to both policymakers and the academic community. The Soil Biodiversity module contains the largest molecular biology-based analysis of soil biodiversity in the EU. The Pesticides module provides the most comprehensive and harmonized assessment of pesticide residues in European agricultural soils (Orgiazzi et al., 2022). Acquisition of extra data will surely improve our ability to monitor soils and predict soil-mediated services. However, despite this progress, our understanding and capacity to predict the effects of soil on plants is still limited.

In an agricultural set up, crop performance is dramatically influenced by the physico-chemical soil parameters, and agronomical practices are often intended to modify them to maximize field production. A fertile agricultural soil should have structure and porosity that allow the exchange of air and water, ensuring good root penetration. Improper agricultural practices can threaten soil structure via the breakage of aggregates, increasing soil compaction and decreasing soil porosity. This leads to a reduced soil water content and aeration, limiting root development, and crop performance in general (Rogers and Benfey, 2015).

Soil density influences root growth and shoot traits. Hard soils strongly inhibit root growth and elongation and further affect the development of leaves and shoots (Passioura, 2002). Interestingly, this inhibitory effect in hard soils has been recorded on aboveground plant traits, independently from root nutrient and water uptake, suggesting that a “soil density signal” might be sensed and systemically transmitted from roots independently from a nutritional effect (Passioura, 2002; Correa et al., 2019). In more detail, plants can adaptively respond to soil density (and in particular to soil compaction) by modifying the architecture of their root systems. This can have both positive and negative effects on plant performance, leading to either tolerance to soil compaction or a reduction in the plant yield (Correa et al., 2019). Such plastic response has a genetic component, so that “soil compaction tolerance” is to date considered a trait to be targeted in breeding programmes. On the other hand, excessively loose soils can also lead to poor crop performance, potentially due to an inadequate contact surface between roots and soil particles (Passioura, 2002). Many physical parameters influence crop productivity by affecting how the soil retains water and makes it available for crop production (Rogers and Benfey, 2015). Soil texture plays a crucial role in determining a soil’s water holding capacity and the amount of plant-available water it can provide. Different soils, such as loamy, sandy, or clay, have different abilities to attract and hold water due to the size of their pore space and the way water is held within the pores. This means that even when two soils have similar field capacity, they may not perform equally in terms of providing water for plants. In general, silt loam soils tend to provide a larger amount of plant-available water compared to other types of soil (Rogers and Benfey, 2015).

The relationship between soil nutrients and crop yield is well-established for some commercially important leafy and fruit crops (Incrocci et al., 2017). Plant nutrient availability strongly depends on their interplay with the soil physico-chemical parameters such as cation exchange capacity (CEC), water content, pH and presence of colloids. For each crop there is a range from a minimum to a maximum concentration of a nutrient that ensures the best crop performance. However, finding this range for each nutrient and for each crop is challenging. Interestingly, a meta-analysis that included different plant communities growing in different sites worldwide showed that leaf traits such as area, N and P contents were more tightly linked to nutrient availability than parameters related to plant growth (Thomas et al., 2016). This suggests that leaf traits could be used as a proxy to monitor nutrient availability in the soil.

As soil nutrients are taken up by roots as ions (i.e. NO 3 − , NH 4 + and H 2 PO 4 − ), the soil pH plays a pivotal role in nutrient availability. Plants can tolerate a wide range of soil pH, the optimum range for most agricultural crops is between 5.5 and 7.5, as the maximum availability of the macronutrients is displayed in slightly acidic to neutral soils. Poor crop growth and yield on acidic soils are usually due to the toxicity of H⁺, aluminum (Al), and manganese (Mn), nutrient deficiencies (particularly Ca and Mg) and reduced uptake of water (Long et al., 2017). In particular, Al toxicity is a common problem in acidic soils, where Al is present as soluble Al³⁺ ion. This form can passively enter plant roots, impairing many physiological processes and eventually impacting crop yield (Oshunsanya, 2018). Unfortunately, soil acidification is a problem that affects many cultivated areas worldwide, due to the excessive use of N fertilizers, acid rain and intensive monoculture (Long et al., 2017). Alkaline conditions affect more than 25% of the world’s soils, including calcareous, saline, and sodic soils (López-Bucio et al., 2000). High pH decreases the availability of many mineral nutrients in the soil solution causing nutrient deficiencies and reduces the soil hydraulic conductivity and soil water retention (Suarez, 2012; Xu et al., 2020). Beside the negative effect on nutrient uptake, salinity and sodicity mainly impact plant growth through ion toxicity and osmotic stress (Huang et al., 2017), while high pH affects root cell elongation and root water transport (Xu et al., 2020). All these mechanisms eventually lead to reduced crop growth and productivity as demonstrated for rice, where grain yield was shown to significantly decrease with increasing pH in a range from 7 to 9 (Huang et al., 2017).

While the relationship between individual soil parameters, such as nutrient content, soil structure, or pH, and crop performance is clear in principle, it becomes more complicated and unpredictable in field conditions. This is because multiple physico-chemical soil parameters can affect soil quality simultaneously, creating a unique environment for each field. This indicates that methods that consider multiple parameters can be more accurate to predict their effect on plant performance than single-use parameters. As an example, Peralta et al. (2014) studied the relationship between different soil parameters and wheat nitrogen demand and grain yield in different sites. Despite a positive correlation between N availability and grain yield, the study also showed that the parameters more relevant to explain the wheat N demand were mostly site-specific. This highlights the importance of considering the “site” variable when analyzing soil factors and their impact on crop performance. In a study focusing on wheat yield in hilly regions they found that spatial variability significantly affected crop performance, underscoring the importance of considering the “site” variable when analyzing soil factors and their impact on crop performance. The study also showed that topographic attributes, such as slope, can have a dramatic impact on water availability and should be integrated into crop performance predictions (Ajami et al., 2020). Furthermore, the annual weather conditions could influence the physico-chemical soil features that are critical for crop yield. That was suggested by Juhos et al. (2015) that performed a multivariate analysis on the same fields using data coming from 10 years and considering different crops (maize, wheat, sunflower). They found that in droughty years, the salinization, soil texture, and nutrient contents were the most influencing parameters, while in rainy years the SOM and the nutrient contents were the main limiting factors determining the crop yields.

Microbiota and soil quality have a reciprocal relationship, as evidenced by various examples in the literature. Microbes can directly affect soil quality through their ability to release extracellular polymeric substances (EPS), which are mostly composed of polysaccharides, proteins, and DNA. These substances improve soil particle aggregation and help retain moisture (Costa et al., 2018). In addition, arbuscular mycorrhizal fungi (AMF) can form dense networks of hyphae that facilitate nutrient transfer between different soil areas and also contribute to maintaining soil structure and aggregation (Rillig et al., 2015). In the next examples, we will use plant health as a readout of soil quality. Although the term “plant health” can be interpreted in multiple ways, we aim to define a plant as healthy “as long as its physiological performance, determined by its genetic potential and environmental conditions, is maintained” (Döring et al., 2011 and references therein). An ideal soil for agricultural production should accommodate a diverse microbiome containing many microbes with enhanced nutrient mobilization capacity and the ability to suppress plant pathogens (Weller et al., 2002; Saleem et al., 2019). Many studies have shown that when plants are stressed, they “cry for help” by emitting chemical signals that attract helpful soil microbes that can assist in relieving the stress (Pascale et al., 2020). For instance, when soil P or N is unavailable for plants, they secrete molecules to attract AMF and nitrogen-fixing rhizobia from the soil that can facilitate P and N uptake respectively (Oldroyd, 2013; Lanfranco et al., 2018). When plants experience drought, they can also recruit microbes that can specifically attenuate drought-related stresses in plants (Williams and de Vries, 2020). Similarly, in soils with unavailable iron (Fe) plants release metabolites to attract iron-mobilizing microbiota (Stringlis et al., 2018; Harbort et al., 2020). In the case of increased pathogen load in soil and a disease outbreak, there is an enrichment of selected microbiota e.g. fluorescent Pseudomonas sp. that can lead to the suppression of disease (Weller et al., 2002). This phenomenon is known as specific soil suppressiveness to plant diseases. However, disease suppression can be also achieved by increasing the activity of soil microbiota via soil manipulation and the addition of organic matter, certain agronomic practices, or improvement of soil fertility, leading to general suppressiveness (Raaijmakers and Mazzola, 2016). Additionally, the presence or absence of rare bacterial taxa in the soil can determine whether the soil can favor future disease outcomes, opening new avenues toward the use of microbes as indicators of “disease-prone” soils (Wei et al., 2019). Finally, drought can disrupt soil structure and water content and in turn affect the structure and activity of microbiomes. Severe drought can affect the presence of microbiota that can contribute to plant resilience (Santos-Medellín et al., 2021), while conditions of mild drought can increase bacterial activity related to Fe transport and metabolism (Xu et al., 2021). Therefore, achieving plant tolerance to drought requires decoding how soil and plant microbiomes respond and adapt to drought conditions. Caution is needed under conditions of (a)biotic stress, since plants may have less control over their microbiota, leading to the formation of dysbiotic plant microbiomes. Dysbiosis can affect the host, the microbiota, or both, and occurs when the proportions of microorganisms in the microbiome are not balanced or when harmful microorganisms are present in high numbers. This can lead to negative effects on the plant, such as reduced growth and increased susceptibility to disease. It is important to take steps to prevent or mitigate dysbiosis in plant microbiomes to maintain the health and productivity of the plants (Arnault et al., 2022).

The expansion of ecosystem services provided by soils and their connection with human, animal and ecosystem health underpins the key role of soil in the emerging “One Health” vision (Banerjee and van der Heijden, 2022; Lehmann et al., 2020). The numerous health indicators for soil (physical, chemical and biological) and the complex interactions between them in many different processes makes it challenging for soil scientists to select the most representative indicators or to determine how many indicators should be considered during soil health evaluation (Creamer et al., 2022). Moreover, in different climatic conditions the same indicator could be considered high or low depending on other parameters (for example organic C levels can be considered high or low depending on the soil clay content).

Recently, the EU soil mission launched a new set of eight objectives proposing clear targets and new measurable physical, chemical, biological and socio-economic indicators for monitoring the state of the soil (European Mission - A soil deal for Europe). However, not all of the proposed parameters can be used to assess different ecosystems, and the range of indicators is somewhat limited and may not be fully representative of specific contexts. In general, biological properties are under-represented in soil health evaluations, despite their direct link to physico-chemical parameters and their recognized impacts on soil fertility, plant productivity, and human health (Bongiorno, 2020). For instance, while the EU has recognized the importance of improving soil biota quality as part of its trajectory toward sustainable soil management and restoration, the monitoring of microbiota dynamics and biodiversity is not included as a critical soil indicator. Novel criteria and indicators based on the tracking of microbiota diversity should be introduced to evaluate soil quality. This is feasible considering the advances in next-generation sequencing technologies that have been extensively used in the last two decades toward microbiota mapping in different ecosystems, including soils. However, some challenges still exist before adopting soil microbiota-based indicators: a) while taxonomy and composition can be easily tracked, the functionality of microbiomes relies on more expensive and bioinformatically demanding approaches such as shotgun metagenomics and metatranscriptomics, and b) the existing microbial databases, usually used for microbiome characterization and functionality, might not be representative of most soils and ecosystems. In this framework, the use of microbiota diversity as a soil quality indicator is not yet widely adopted. Given that microbial colonization alters plant physiology, development and gene expression, it may be possible to monitor host plant traits and use plant health as a reliable soil quality indicator.

Indeed, plant health can be considered as the final output of the integration of many soil quality parameters since it reflects the complexity of the interaction between plants and their environment into a single outcome. Plants can therefore be seen as a powerful lens through which we can interpret the soil, as already suggested by ecologists (van der Putten et al., 2013). This approach can offer a real-time and up-to-date methodology to interpret the status of a plant by focusing on multiple reliable measurements, rather than just plant yield ( Figure 2 ). Each of the suggested plant health parameters represents an important proxy for different soil quality parameters, including soil microbial diversity. By using plant health as an indicator of soil quality, we could monitor and address important societal goals, such as reducing soil pollution, improving soil restoration and enhancing soil structure to support habitat quality and soil biota and crops.

As an example, we are here listing a set of plant health parameters that are easy to measure and essential to evaluate soil status ( Table 2 ). The plant photosynthetic capacity likely mirrors important information about soil chemical parameters, such as nutrient availability (Ai et al., 2017), but it is also affected by soil physicochemical and biological parameters, such as root-associated microbes (Moustakas et al., 2020; Balestrini et al., 2020) or conditions affecting these parameters like desertification (Qiu et al., 2018), pH (Long et al., 2017). It is a sensitive indicator, with rapid and large changes influenced by external factors. Chlorophylls, including Chl a, Chl b and Chl a+b, can be easily measured with a simple ethanol-based extraction and colorimetric assays or with on-field portable approaches. A correct range of photosynthetic pigment concentration correlates with a healthy content of macro- and micro- nutrients. Another plant parameter useful to infer crucial soil physico-chemical indicators and microbiota dynamics is represented by the plant elemental composition (Callaham and Stanturf, 2021; Schjoerring et al., 2019; Shaaban et al., 2016; Mohiuddin et al., 2022; Singh et al., 2022) ( Table 2 ). The macro- and micro-elements accumulating in plant tissues provide a clear readout of soil nutrient availability that can impact plant food security and human nutrition, therefore mirroring a meaningful soil service. In addition, detailed nutritional profiling of plant tissues can facilitate precision in fertilizer management and can be performed at different stages of plant growth. Monitoring it over time can provide a better resolution and improve our ability to interpret soil nutrient availability and its fluctuations. Furthermore, tracking the presence of pollutants in plant tissues can also provide insights into soil health, including its levels of heavy metals, herbicides, pesticides and microplastics, which are all absorbed by plant roots and accumulate in plant tissues (Biswas et al., 2018; Stoykova and Inui, 2021; Walder et al., 2022; Edlinger et al., 2022). Altogether, monitoring the levels of different target molecules accumulating inside plant tissues could help us fingerprint the quality of soils.

Soil and plant resilience are considered two sides of the same coin. Seaton et al. (2020) and Deng et al. (2020) showed that several physico-chemical soil parameters such as water repellency, texture, pH, SOC and nutrient soil content can affect the ability of plants to withstand (a)biotic stresses. Additionally, alterations in the composition and activities of the plant-associated microbiota can affect plant resilience to biotic and abiotic stresses (Chialva et al., 2018; Pascale et al., 2020; Jansson and Hofmockel, 2020; Chialva et al., 2022; Vannini et al., 2021; Trivedi et al., 2022). It is also suggested that plant adaptation to climate change will be driven by eco-evolutionary interactions with its associated microbiome (Trivedi et al., 2022). Metatranscriptomic and metagenomics technologies could be used to identify plant-associated microorganisms and their relationship to soil characteristics and plant adaptation. Moreover, meta-omics studies provide information about gene expression levels via genomics and transcriptomics, as well as about post-translational changes via proteomics. Additionally, metabolomics or volatilomics can provide information about metabolites as a result of cellular processes, or volatile organic compounds (VOCs), respectively. Therefore, a combination of -omics methods can connect all aspects of the plant-microbe-soil relationship at the cellular level (Sharma et al., 2020; Brown et al., 2021; Gupta et al., 2021; Mishra et al., 2022; Yu et al., 2022).