Proceedings - Soil Science Society of America最新文献

Roel-Rezk, V., Horwath, W. R., & Pittelkow, C. M. (2025). Is soil health research meeting its potential? Analysis of studies in California and implications for ecosystem services. Soil Science Society of America Journal, 89, e70139. https://doi.org/10.1002/saj2.70139

Data presented in the left panel of Figure 1, 1 is incorrect and does not match the correct data mentioned in the text. The total numbers should have been 22 articles (updated from 17) measured in the three dimensions and represent 51% of the papers (updated from 52%). Four articles measure a biological and a chemical indicator (updated from 2), and five only a chemical indicator (updated from 2).

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The corrected figure with the corrected numbers appears below:

We apologize for this error.

Soil health underpins ecosystem services and sustainable agriculture. This study compared soil health properties among three long-term land-use systems in Trans Nzoia, western Kenya: biointensive agriculture (BIA), natural shrubland reserve, and conventional maize monocropping. Soil health was assessed primarily through chemical and biological indicators, with bulk density (BD) included as the measured physical property. Soil texture was also determined across sites, providing context as an inherent and potentially management-influenced property. Soil samples (from 0- to 5-cm, 5- to 15-cm, 15- to 30-cm, 30- to 60-cm, and 60- to 100-cm depths) were analyzed for microbial biomass carbon and nitrogen (MBC), dissolved organic C, total dissolved N (TDN), potential mineralizable C and N, total N (TN), total C (TC), TN stocks, TC stocks, bulk density, and soil texture. Several soil health indicators were higher in BIA and shrubland than in maize, especially at 0–5 cm. At this depth, MBC (BIA vs. maize: +117%) and TDN (nature reserve vs. maize: +141%) were greater. TC (BIA vs. maize: +69%) and TN (shrubland vs. maize: +58%) stocks were also higher. BIA had the lowest BD (1.07 g cm⁻³ at 0–5 cm) compared to maize (1.27 g cm⁻³), consistent with better aeration and root penetration. While recognizing that observed differences reflect the combined influence of management history and inherent site properties, these case comparisons suggest that BIA management is associated with higher C and N stocks, enhanced microbial biomass, and reduced compaction. Adopting BIA could help mitigate soil degradation and support agricultural sustainability in smallholder systems.

Tillage and cover cropping are known to affect soil water dynamics and crop evapotranspiration (ET), and consequently, water footprint (WF) of crop production and economic return. In this study, two tillage practices (conventional tillage [CT] and no-tillage [NT]) and cover crop (CC) treatments (Austrian winter pea [Pisum sativum] CC and no-CC [NC]) were investigated to quantify soil water balance, ET, and WF of yield and revenue for cotton (Gossypium hirsutum) and sorghum (Sorghum bicolor) production. Soil volumetric water content was measured from 0- to 120-cm depth from May to October in 2020 and 2021. Runoff, deep percolation, and ET were modeled using the root zone water quality model (RZWQM2), and WF was determined as m³ of water consumed per kg of yield or unit revenue. The RZWQM2 performance was acceptable, validated by low residual errors. Pooled across years, CT treatments depleted soil water storage by 9% and 7% over the season in cotton and sorghum, respectively, which was 6% and 7% for NT. No-till reduced the runoff by 31% over CT when averaged across years and cash crops. The NTCC (no-tillage, cover crop) minimized ET, compared to NTNC (no-tillage, no cover crop) and CT treatments, particularly in sorghum. Tillage increased the WF of yield and revenue for cotton by 7% and 6% over NT treatments, respectively. In sorghum, neither tillage nor cover cropping altered the WF outcomes. Overall, cover cropping and conservation tillage could be used to complement each other to minimize the WF of cotton and sorghum production in the humid Lower Mississippi River Basin.

Soil structure is an important feature that facilitates water infiltration, storage, and transport into the profile, as well as affecting soil organic matter storage, habitat for soil organisms, and nutrient cycling. How land use and grassland management affect soil structural characteristics in the warm, humid region of the southeastern US remains poorly described. A cross-sectional study from 308 grassland fields and 29 woodlots was sampled at 0- to 10-cm depth in North Carolina. Soils were mostly Ultisols (90%) and included some Alfisols, Inceptisols, and Entisols. Soil texture classes included sand (6%), loamy sand (7%), sandy loam (21%), sandy clay loam (27%), loam (17%), clay loam (13%), silt loam (7%), and silty clay loam (1%). Overall, soil bulk density was greater under grassland than under woodland (1.26 vs. 1.06 Mg m⁻³, respectively) but the difference narrowed with finer soil texture. Mean-weight diameter of water-stable aggregation was greater under grassland than under woodland in fine-textured soils but not in other soils. Soil stability index was not different between grassland and woodland, possibly due to high levels (>90%) in both land uses. Several grassland management factors influenced soil structural characteristics, including prior land-use history, pasture age, stocking density, and forage utilization. Soil structural characteristics were strongly negatively associated with sand concentration and positively associated with soil-test biological activity. Older pastures with moderate grazing pressure exhibited the strongest soil structural characteristics on medium- and fine-textured soils, thereby delivering vital ecosystem services from this widely prevalent land use in the eastern United States.

Poly-γ-glutamic acid (γ-PGA) has great agricultural potential due to its water-retention ability, but its effects at different application amounts on soybean [Glycine max (L.) Merr.] productivity and soil properties remain unclear. In this study, γ-PGA was applied at five amounts (0, 10, 20, 40, and 80 kg ha⁻¹, denoted as CK, T10, T20, T40, and T80, respectively) via drip irrigation to soybean plants to evaluate its impact on soil physical and hydraulic properties, nutrient availability, crop growth, and yield. The results showed that γ-PGA application increased soil porosity, reduced bulk density, and improved soil temperature in the 0–25 cm layer. Soil hydraulic parameters, including field capacity and plant-available water, also improved with γ-PGA application. However, γ-PGA application reduced soil nitrogen, phosphorus, and potassium levels at harvest. Nutrient uptake efficiency and soybean growth initially increased and then declined with higher γ-PGA application amounts, with the highest yield observed under the T40 treatment. Overall, applying γ-PGA at 40 kg ha⁻¹ effectively enhanced soil properties and nutrient uptake, leading to improved soybean productivity.

Direct measurements of free-living nitrogen fixation (FLNF) using ¹⁵N-labeled dinitrogen (¹⁵N₂) have been complicated by a lack of standardization regarding soil sampling and storage, and because key incubation parameters have yet to be systematically optimized. With the aim of developing a standardized protocol for laboratory assay of carbon (C)-stimulated FLNF, studies with four Illinois soils were conducted with respect to sampling depth, storage condition and period, surface exposure, moisture content, C source and pH, phosphorus (P) amendment, and incubation period. Among the major findings, diazotrophic activity was greatest with surface (0−7.5 cm) sampling, and storage effects were minimized when field-moist samples were kept at room temperature (25°C) or in a refrigerator (5°C) for ≤1 day with or without sieving (<2 mm). In the presence of exogenous C (4 mg C g⁻¹ dry soil), the rate of ¹⁵N₂ fixation was maximized at ≥200% water-holding capacity, with a 3-day incubation period, and by increasing atmospheric exposure with the use of a shallow soil container. A simulated corn (Zea mays L.) root exudate was identified as the optimal C source, regardless of a divergent preference observed for soil samples collected before and after a 6-month interval. By standardizing several key parameters pertinent to the measurement of C-stimulated FLNF, the work reported can help facilitate research to define the ecological importance and agricultural potential of a process that has largely been unexplored in the soil N cycle.

Integrating cover crops into conventional cropping systems can improve soil health, but field management, soil type, and climate can limit the rate of improvements. This study evaluated the effects of cereal rye (Secale cereale) cover crops on soil organic carbon (SOC) content and physical properties in a no-till, corn–soybean rotation on a poorly structured silt loam in southeastern Indiana. An earlier assessment of this trial found cover crops had increased aggregate stability after just 4 years but had no significant effect on bulk density (BD), water dynamics, or SOC. Revisiting this trial after an additional 6 years, we observed significant improvements across multiple soil health indicators. Cover crops increased SOC by 7.5% and total nitrogen by 12.9%, alongside improvements in BD (−2.9%) and water holding capacity (+8.6%). Aeration porosity was significantly enhanced (+7.7% at 0–10 cm, +9.0% at 10–20 cm, and +30.1% at 20–40 cm), indicating potential improvements in water infiltration. Aggregate stability remained a strong indicator of cover crop benefits, higher by 33% in the top 10 cm and by 35% at 10–20 cm as compared to no cover plots. These results align with findings from similar long-term trials and underscore how aggregate stability may be a valuable early predictor of broader improvements. Our findings support cereal rye as an effective strategy to enhance soil health and resilience in Midwestern no-till corn-soybean systems.

The Northeast Region Phosphorus Index (NR P-index) is a risk assessment tool that evaluates phosphorus (P) loss potential using soil test P (STP) concentrations, transport factors, and management practices. It informs whole-farm P strategies by guiding site-specific manure application decisions. This study aimed to (1) evaluate the implications of grid-based versus whole-field STP concentrations on P management implications according to the NR P-index, and (2) examine if different grid sizes impact NR P-index-based management implications. Soil samples were collected from 20 corn (Zea mays L.) fields across six farms in New York, each with varying STP concentrations, and analyzed at three grid resolutions (0.2, 0.5, and 1.0 ha). Grid sampling allowed for more precise P management in fields with moderate STP concentrations (20–80 mg kg⁻¹), through identification of areas with higher or lower P-index score compared to whole-field assessment. For fields with STP concentrations in the agronomic range (<20 mg kg⁻¹ Morgan P) or excessive levels (>80 mg kg⁻¹ Morgan P), whole-field assessments can be used to inform P recommendations. Grid sizes finer than 1.0 ha did not impact the management implications, indicating limited benefit from higher spatial resolution when STP concentrations are largely uniform or fall within a single P-index category. These findings suggest that grid sampling for P-index assessment was most effective for these fields with moderate STP concentrations and P-index scores, allowing for more targeted P management.

Soil detachment capacity (D_c) is a key parameter for characterizing the soil erosion process. Polyacrylamide (PAM) mitigates soil erosion, but the mechanism by which it acts on soil–rock mixtures is unclear. This study investigated the impact of applying PAM on detachment of soil–rock mixtures and predicted D_c using machine learning models. Small-sample scouring tests were conducted in a flume with a 30° slope, under flow discharges of 4, 8, 12, 16, and 24 L·min⁻¹; gravel content of 0%, 10%, 30%, 50%, and 70%; and PAM (anionic type, molecular weight 12 million, degree of hydrolysis 20%) application rates of 0, 1, 2, 3, 4, and 5 g·m⁻². When flow discharge was lower than 16 L·min⁻¹, the best D_c inhibition effect was achieved by applying 4 g·m⁻² PAM rate. From 16–24 L·min⁻¹, the optimal application rate of PAM for D_c inhibition varied according to gravel content: 3 g·m⁻² for gravel content of <50% and 4 g·m⁻² for gravel content of 50%–70%. PAM primarily influenced D_c indirectly by enhancing shear strength, but as gravel content increased, PAM effect on shear strength reduced. At 30% gravel content, the soil–rock mixture was more stable, and D_c remained consistently low. The extreme gradient boosting model trained using four parameters (PAM application rate, gravel content, shear strength, and stream power) outperformed multiple regression equations when used to predict D_c.