There is a worldwide need to enhance soil health, particularly in agricultural areas. Groundcovers are widely recognized sustainable land management (SLM) practices that improve soil health and provide climate benefits by sequestering atmospheric carbon. A paired-plots study was carried out in woody crops (17 sites, olive groves and vineyards) in a semiarid area of central Spain to measure soil parameter changes induced by different management practices in the medium term. The selection across different locations aimed to determine whether the impact of groundcovers was substantial enough to produce significant changes in the studied soil parameters, even when accounting for variations in soil types. Each site consisted of neighboring plots: One was managed with conventional tillage (CT). The other was managed with an alternative soil management practice: (1) spontaneous groundcovers (GC) or (2) no soil management (NM). Vegetation and soil parameters were measured in spring 2021. Despite the low aboveground biomass in GC (77 g m⁻²), this treatment improved soil organic carbon stock (+4.4 Mg ha⁻¹), infiltration rate (+50%), and aggregate stability (+35%) compared to CT, but higher compaction along the profile was detected. NM only resulted in a better infiltration rate, with high soil compaction. Our study provides supplementary information to long-term studies, which may include soil biological parameters as soil health indicators and yield response. Outcomes of these soil assessments lend support to the implementation of agricultural policies that promote GC as a SLM practice, in order to extend this technique to woody crops.

This study aimed to establish sound relationships between soil properties of agricultural land in central Spain and their spectral attributes to contribute to deriving an indicator for sustainable farm management. Sixteen plots, managed under various conditions, eight with traditional tillage and eight with other alternative managements, were selected to gather soil samples representing three predominant soil orders (Leptosols, Cambisols, and Luvisols). Soil sampling was conducted from depths ranging from 0 to 30 cm (0–50; 5–10, 10–20, and 20–30 cm), ensuring a broad spectrum of sample variability across different times and locations. The reflectance of soil 64 soil samples was measured within the range of 400 to 900 nm, and the corresponding concentrations of soil organic carbon and majoritarian minerals, calcium carbonate, quartz, phyllosilicates, K-Feldspar, and plagioclase were determined for each sample. Partial least squares analysis was employed to construct prediction models using a calibration dataset comprising 66% of randomly selected samples. The remaining 33% of samples were utilized for model validation. The prediction models for the measured soil chemical properties yielded R² values ranging from 0.14 to 0.79. Only SOC and limestone provided accurate prediction models. These findings hold promise for developing a soil health indicator tailored for site-specific crop management. However, the complex composition of soil organic carbon and calcium carbonate in certain soils underscores the importance of careful interpretation and validation of remote sensing data, as well as the need for advanced modeling approaches that can account for the interactions between multiple soil constituents.

Cover crops in woody crops as a sustainable land management alternative to conventional tillage induce changes in soil properties that improve ecosystem functioning. Soil is highly dynamic, and disturbances in environmental conditions affect soil microorganisms, particularly in gypsiferous soils, where microbiological activity remains poorly understood. This study evaluated the effects of three cover crop systems: spontaneous permanent vegetation cover (SVE), annual legume cover (VIC), and permanent grass cover (BRA), compared with conventional tillage (TIL), on soil physicochemical and biological properties in an olive grove over two crop seasons. Overall, cover crops promoted higher microbial activity and carbon storage than tillage, with responses being more pronounced during the wetter year. Conventional tillage consistently exhibited the lowest levels of enzyme activities and carbon stocks, whereas permanent covers showed stronger positive effects on soil functioning. These findings indicate that the benefits of cover crops on soil processes are reinforced under favorable moisture conditions but also remain under drier years, highlighting their stabilizing role. The improvement of soil health induced by cover crops contributes to enhancing soil ecosystem services, including soil fertility, in olive groves, supporting their adoption as a sustainable management strategy in Mediterranean agroecosystems, even under lower rainfall conditions.

Traditional soil management in vineyards and olive groves of semi-arid regions relies on repeated tillage, which accelerates soil organic matter (SOM) oxidation and limits long-term carbon storage. In the context of carbon-neutral agricultural strategies, understanding how alternative practices influence SOM stocks, redistribution, and stabilization is essential. We sampled six paired sites in central Spain (three vineyards and three olive groves), each comprising adjacent plots under conventional tillage or continuous cover cropping, at 0–10 and 10–30 cm depths. We analyzed water-extractable organic carbon (WEOC), optical properties of water-extractable organic matter (WEOM; specific UV absorbance at 254 nm (SUVA₂₅₄) and the absorbance ratio E4/E6), β-glucosidase activity, and the SOC/clay ratio as a proxy for mineral-associated SOC stabilization. Depth was the main factor structuring SOC and biological activity, with higher values in the topsoil. Management effects on bulk SOC were limited although cover cropping increased aboveground biomass and influenced WEOC dynamics. Vertical contrasts (30–10 cm) showed a positive association between WEOC and SOC/clay, suggesting that increased WEOC at depth co-varies with stabilization potential. Partial least squares analysis for 10–30 cm showed that SOC/clay was associated with WEOC, E4/E6, and β-glucosidase activity. These results suggest that subsoil carbon stabilization in semi-arid conditions may be linked to DOC availability and microbial processing rather than directly to surface biomass inputs.

Visible–near infrared–shortwave infrared (VIS–NIR–SWIR, 350–2500 nm) soil reflectance spectroscopy provides a rapid and non-destructive approach for characterizing soil properties, yet the relative contribution of spectral integration metrics, preprocessing strategies, and diagnostic wavelength regions remains an active area of research. In this study, a dataset of 220 soil samples from 30 agricultural sites representing contrasting pedological conditions was analyzed using laboratory reflectance spectra acquired over the full 350–2500 nm range. In addition to point reflectance values, two cumulative reflectance variables were computed: a visible cumulative reflectance (VCR, 350–780 nm) and a full-spectrum cumulative reflectance (CR, 350–2500 nm), designed to capture integrated spectral behavior related to soil color and overall albedo. Partial least squares regression (PLSR) models were developed to predict soil organic matter determined by wet oxidation (SOM), and the influence of spectral range and preprocessing was systematically evaluated.In particular, VCR emerged as a particularly meaningful descriptor of soil optical behavior, functioning analogously to an integrated soil color or saturation metric and revealing distinct linear trends associated with different soil groups.The PLSR models based on the full VIS–NIR–SWIR range consistently outperformed those restricted to the visible domain. The most robust and parsimonious configuration used original reflectance data subjected to mean centering, standard normal variate correction, and detrending. Under this configuration, SOM was predicted with coefficients of determination of approximately R² ≈ 0.58–0.61 and RMSE values near 0.8, using 6–7 latent variables. More aggressive preprocessing strategies, including second derivatives and extensive Savitzky–Golay smoothing, produced only marginal improvements while increasing the spurious effects of noise or reducing interpretability, and were therefore deemed unnecessary.The Variable Importance in the Projection (VIP) trace revealed that SOM prediction was primarily controlled by a limited number of SWIR absorption regions centered near 552, 1414, 1918–2008, 2140, and 2201–2216 nm, consistent with absorptions associated with organic matter and clay minerals—mainly montmorillonites and kaolinite—with comparatively lower influence from calcite and oxides.Overall, the results demonstrate that VIS–NIR–SWIR spectroscopy up to 2500 nm enables a physically interpretable estimation of soil organic matter with predictive performance across very different soil types.However, the results also show that SOM prediction remains highly significant when PLSR models are built exclusively from visible-range data (380–780 nm). The findings highlight the utility of cumulative reflectance metrics and the importance of prioritizing model robustness and spectral interpretability over excessive spectral manipulation, supporting the application of full-range soil spectroscopy for soil characterization and mapping at larger scales. Acknowledgements, this research was funded by EJP-SOIL grant agreement 862695. Javier González Canales received funding through grant PRE2021-097966 from MCIU/AEI/10.13039/501100011033 and the European Social Fund (ESF, Investing in Your Future)