Proceedings - Soil Science Society of America最新文献

Soil structure is a standard component of pedon descriptions collected to characterize the nature and function of soils as a natural body. Soil structure is an important indicator of soil development and a predictor of water, air, and root movement throughout the profile. However, inconsistencies exist within the current standardized methodologies used to describe soil structure in the field, making soil structure data difficult to use and often confusing to students encountering these concepts for the first time. Therefore, we propose an updated method of soil structure description to add an interpretive component that clearly distinguishes geogenic, pedogenic, and human-induced structures. This method employs terminology that communicates both observable morphology and the mechanism of formation. The updated method herein differentiates three classes of structure: (a) geogenic structural formation (GS), (b) natural pedological structural formation (current nomenclature), and (c) significant human-induced structure changes from natural pedological structure. This updated approach improves the documentation of scientifically relevant soil morphology and communicates the processes involved in the formation of all forms of soil structure. As a result, this change eases description challenges around soil structure and interpretations common in soil science classes, including soil judging.

We used mid-infrared (MIR) spectra (4000–600 cm⁻¹) to identify and classify soil orders and soil horizons from 102 pedons across five soil orders (Alfisols, Entisols, Mollisols, Spodosols, and Histosols). The soils were analyzed for texture, total carbon, pH, and elemental properties. Random forest models were used to group the spectra of master horizons (O, A, E, B, and C), B horizons (Bs, Bt, and Bw), and the five soil orders. The prediction accuracies for the master horizons and B horizons were 0.81 and 0.89, respectively. The Kappa coefficient was 0.71 for the prediction of master horizons and 0.73 for the prediction of B horizons. The soil orders had an overall accuracy of 0.73 and a Kappa coefficient of 0.64. Histosols exhibited unique absorption characteristics at 2930 and 2860 cm⁻¹ that differed distinctly from mineral soils. The MIR spectra accurately distinguished the O horizons. The spectral curve of topsoil of Spodosols was comparable to the O horizons. Spodosols under forest had A horizons with high organic matter and were classified accurately. Entisols (Psamments) displayed absorption peaks associated with sand, facilitating their differentiation from the other soil orders. The model struggled to discern subtle differences among some soil orders, and identification is hampered if soils undergo irreversible changes upon drying. However, our results showed that MIR spectra can be used for effectively identifying and classifying soil orders as well as soil horizons.

Plant growth-promoting rhizobacteria (e.g., Bacillus) confer health benefits to the host. Bacillus siamensis has been used to control plant disease in fruits and vegetables, but its potential effects on crop performance remain unclear. This study investigated changes in the growth, root transcriptomic profile, and rhizosp here microbiome of maize plants (Zea may L.) following inoculation with B. siamensis 33. All inoculated plants grew better than non-inoculated controls in pots, as exemplified by 24.0% and 6.8% increase in plant height and stem diameter, respectively (p < 0.01). Shoot dry weight also increased by 20.6% upon inoculation, accompanied by 46.9% increase in root dry weight (p < 0.01). Transcriptomic analysis revealed that inoculation induced (2.16- to 5.53-fold) upregulated expression of genes related to auxin signal transduction in maize. The expression of genes involved in phenylpropanoid biosynthesis, glutathione metabolism, and plant defense-related signal (e.g., jasmonic acid and salicylic acid) transduction was (2.06- to 11.30-fold) upregulated in inoculated plants. Upon inoculation, bacterial α-diversity trended higher and potentially beneficial taxa (e.g., Sphingobium, Flavihumibacter, and Parasegetibacter) were enriched in the rhizosphere, likely a result of enhanced root exudation of specific metabolites (e.g., flavonoids) and subsequent recruitment of beneficial microbial taxa. Potential microbial functions associated with nitrogen cycling and pollutant degradation were stimulated by inoculation. These findings indicate that B. siamensis 33 mediates the reprogramming of plant gene expression and reshaping of rhizosphere microbiome structure to bolster maize crop performance.

To understand phosphorus (P) mobility in agricultural soils and its potential environmental risk, it is essential to directly measure solid phase P speciation. Often, bulk P K-edge X-ray absorption near edge structure (XANES) spectroscopy followed by linear combination fitting (LCF) is utilized to determine the solid P phases in soil. However, this method may limit results to only a few major phases. Additionally, XANES spectra for different P species may have very similar features, leading to an over- or underestimate of their contribution to LCF. Here, an improved P speciation by pairing multimodal microbeam-X-ray fluorescence (µ-XRF) mapping coupled with µ-XANES (microbeam-X-ray absorption near edge structure) analysis to directly speciate major and minor P phases on the micron scale is provided. We combined maps of both tender (P, sulfur, aluminum, and silicon) and hard energy (calcium, iron [Fe], and manganese) elements to evaluate the elemental co-locations with P. To better account for uncertainty assigning XANES peaks to individual compounds, a more quantitative fingerprinting by “spectral feature analysis” was completed. With this analysis, an R-factor is reported for the fit. These results were compared to traditional LCF. Pre-edge fitting results revealed the presence of a two-component pre-edge feature for phosphate adsorbed to ferrihydrite. Additionally, phytate co-precipitated with ferrihydrite (Phytate-Fe-Cop) had a pre-edge feature, indicating direct association with Fe. Lastly, a unique P species associated with manganese oxide was identified in the soil via multimodal mapping and µ-XANES. These results allow for better prediction of P dissolution and mobility.

Manure treatment technologies are of interest to dairy operations to improve nutrient management, although there are little data related to nutrient availability and environmental impacts of these manure-based fertilizer products. This field trial experiment investigated the impact of two manure-based fertilizer sources (phosphorus enriched solids [PE] and mechanical vapor recompression solids [VR]) on soil nutrients, crop yields, and N₂O emissions in a forage rotation. The study was a factorial random complete block design, with two main factors: manure history (with [M]; without [NM]) and manure-based fertilizer product (control [Con], PE, VR), under a continuous corn and triticale rotation. M had greater soil organic carbon, total carbon, total nitrogen, and M3-P (30%–128%) and reduced NH₄-N (15%) than NM, with no other treatment differences. Corn silage yields were greater in NM versus M (7%) treatments only in 2021, while in 2022 VRNM was 17% greater than ConNM only. Triticale yields were 14% greater in M plots versus NM treatments only in 2021. In 2022, triticale yields were 1.7 times lower in ConNM versus all other treatments, and PENM was 71% greater than ConM. The greatest N₂O fluxes occurred in May, June, and July with M having 69% greater average cumulative fluxes than NM, while average VR cumulative fluxes were 102% greater than PE and Con. Over both years, net loss of N_applied as N₂O-N was 1.9%–2.2% for VR and 0.4%–0.8% for PE solids. While manure-based fertilizers performed well as a nutrient source, their susceptibility to N₂O loss needs to be considered in management strategies.

Mangroves provide fundamental ecosystem services; however, the growing impact of human activities has resulted in increased pollution pressure, such as chemical contaminants. The redox processes are major biogeochemical players in the fate of contaminants. We investigate the effects of the redox environment on As(V) and Cr(VI) adsorbed on goethite (i.e., Fe(III)-oxide) over 40 days of incubation in columns containing mangrove soil subjected to seawater saturation cycles. Our spectroscopic data highlighted a less Fe(III)-ordered arrangement on goethite over time; As(V) is strongly bound to goethite, which delayed until 20 days its remobilization and reduction to As(III). After 40 days, the goethite held ∼50% of the initial As, but it was 15% as As(III). On the other hand, Cr(VI) was desorbed almost completely in less than 10 days, and the residual Cr ions bound to goethite were almost totally converted to Cr(III). Our study stresses the importance of individual time-dependence in evaluating chemical speciation changes among potential toxic elements in wetland systems, such as mangroves and artificial wetlands designed to water treatment or soil remediation.

One of the most popular soil conservation campaigns is based on the USDA Natural Resource Conservation Service's Soil Health Principles (NRCS-SHPs). The NRCS-SHP program identifies four principles—maximize presence of living roots, minimize disturbance, maximize soil cover, and maximize biodiversity—with the underlying assumption that the more principles one follows, the greater improvements in soil health. Despite the popularity of the NRCS-SHPs, this underlying assumption has not been rigorously tested. To do so, we used nine long-term experiments all located in central Iowa, but with varying degree of NRCS-SHP adoption, to determine if greater adoption increases three slow-changing (maximum water holding capacity, bulk density [BD], and soil organic carbon) and three dynamic (microbial biomass carbon [MBC], potentially mineralizable carbon [PMC], and permanganate oxidizable carbon [POXC]) soil health indicators. We regressed these indicators with a soil health principle score that can scale soil management based on adoption of the NRCS-SHPs. Of the slow-changing soil properties, increased adoption of NRCS-SHPs only decreased soil BD (R² = 0.22, p = 0.024). On the other hand, increased adoption of NRCS-SHPs strongly predicted increases in both MBC and PMC and across two sampling dates (R² > 0.23, p < 0.015); POXC, however, did not increase with greater adoption. The consistent increases in MBC and PMC with greater adoption of NRCS-SHPs supports their usefulness as sensitive indicators of positive soil health change. Our study provides scientific evidence to support the NRCS-SHPs concept, improving its usefulness as an extension campaign, and stands as a step toward evidence-based soil conservation.

The existing models for estimating cation exchange capacity (CEC) from easy-to-measure hygroscopic water content (θ_h) were based on a single water activity (a_w) value rather than on the processes that govern soil water vapor adsorption for a distinct a_w range. Here, we present a new CEC estimation model based on θ_h data of 119 soils with different clay mineralogy (i.e., illitic [IL], montmorillonitic [ML], and kaolinitic [KA] samples) and organic carbon (OC) contents for the a_w range from 0.23 to 0.57 (Δθ_0.23–0.57) and validate its performance. Based on the hypothesis that multilayer adsorption exhibits a higher correlation with CEC than monolayer adsorption and capillary condensation, the a_w range from 0.23 to 0.57 was chosen with CEC calculated as CEC = k × Δθ_0.23–0.57. The performance of the new model is compared to the Arthur (2017) model and the Torrent (2015) model, which considers a single θ_h value. The average proportionality coefficient (k) varied with the dominant clay mineralogy of the investigated soils. For soils dominated by 2:1 clay minerals (i.e., IL and ML), the new model showed a good estimation accuracy (Nash-Sutcliffe model efficiency [E] ≥ 0.85; root mean squared error [RMSE] ≤ 4.18 cmol₍₊₎ kg⁻¹). The new model performed better for IL and ML samples than for KA samples, and yielded more accurate CEC estimations than the Arthur model and Torrent model for soils with 2:1 clay minerals. For soil with high OC content (>23.2 g kg⁻¹), the new model slightly underestimated CEC (E = 0.66; RMSE = 5.87).

To explore the specific effects of pig manure and rice straw on cadmium-contaminated soils and the effect of different mass fractions of calcium carbonate on cadmium efficacy, a pot experiment was conducted with different rates of pig manure, rice straw, and calcium carbonate. The results showed that pig manure addition increased the soil humic acid/fulvic acid ratio, thereby reducing the available Cd. The addition of calcium carbonate increased the soil pH and reduced the available Cd. The addition of pig manure and calcium carbonate significantly reduced the Cd content of wheat grains by 51.96% and 45.95%, respectively, at 3% and 5% application rates. Rice straw application reduced the soil pH, improved the soil Cd availability, and increased the accumulation of Cd in wheat grains. Compared with that in the control, the grain biomass increased significantly with 3% pig manure and 3% rice straw application, and the grain biomass increased significantly, by 58.86% and 39.11%, and 93.3% and 75.08%, respectively, in 2020 and 2021. With the application of calcium carbonate, the grain biomass of wheat first decreased and then increased. Additionally, the grain biomass significantly increased by 26.36% and 71.22%, respectively, at the 5% calcium carbonate application rate. Therefore, high application rates of pig manure (3% and 5%) have potential application in the safe production of wheat in Cd-contaminated soils.

This inquiry is aimed at discerning the impact of various agricultural practices, such as crop rotation, the incorporation of plant residues, and the application of mineral fertilizers, on soil health and crop productivity, notably focusing on maize production. Cultivation included maize (Zea mays), velvet beans (Mucuna pruriens), soybeans (Glycine max), and vetch (Vicia sativa). After harvest, maize seeds were sown across all 48 plots to evaluate the influence of preceding crop rotation on soil properties and maize yield. Hypotheses posited in the study suggested that crop rotation, nitrogen fertilizer application, and the incorporation of crop residues positively impact soil fertility. The study further argues that the utilization of cover crops in crop rotation aids in nitrogen retention within the soil and enhances yield. The results were processed utilizing a two-way analysis of variance (ANOVA) with interaction and post hoc comparisons. The findings confirm that crop rotation, nitrogen fertilizer application, and incorporation of crop residues influence soil fertility. The study found that crop rotation and nitrogen fertilizers have a significant impact on soil properties. Crop rotations such as “velvet beans-maize” and “soybeans-maize” increased soil fertility by 10%–15% compared to crop rotations of “vetch-maize” and maize monocultures. Nitrogen fertilizers increased the total nitrogen content in the soil by 5%–10% in both years. Crop residues also positively affected soil properties, increasing pH and total nitrogen by 1%–5%. The study demonstrates that crop rotation, nitrogen fertilizers, and crop residues can be effective management methods for improving soil fertility and reducing the risk of nitrate leaching.