Proceedings - Soil Science Society of America最新文献

Tobacco–rice rotation cropping (TRRC) can optimize the physical and chemical properties of the soil, improve soil fertility, and increase yields of tobacco (Nicotiana tabacum) and rice (Oryza sativa). However, there is a lack of attention to the quality of rice affected by TRRC. This study aims to investigate the effects of TRRC on rice quality and soil nutrient availability. Comparative analysis was conducted between TRRC and single-season rice (R mode) areas over 2 years, assessing rice quality metrics and soil nutrient profiles. The results indicated that rice quality significantly improved in TRRC areas, evidenced by an increase of 0.3%–1650% in metrics such as protein content and amylose content, with a notable reduction in cadmium (Cd) levels. Comparing with R mode, the content of organic matter and the available nitrogen (N) was respectively reduced 1.3%–73.3% and 3.8%–84.6% in soils of TRRC mode, while the content of available potassium (K) and available phosphorus (P) was respectively increased 4.0%–84% and 6.8%–95%. Pesticide residue detection of rice in TRRC area and R mode area meets the national pesticide residue standards for rice in China. These findings suggest that TRRC can optimize rice production and safety in Cd-contaminated regions.

Insufficient dietary intake of zinc (Zn) is a significant public health concern globally, as it is closely linked to impaired immune function and pregnancy complications. Addressing this issue may include strategies such as agronomic biofortification of globally important vegetables. For example, lettuce (Lactuca sativa L.) contributes to the dietary intake of millions of people and may be well used for agronomic biofortification. Arbuscular mycorrhizal fungi (AMF), symbiotic with 80% of terrestrial plants, also facilitate nutrient uptake, contributing to improving the nutritional value of crops. Our research aimed to assess the effects of AMF inoculation and Zn fertilization on plant growth and biofortification of lettuce leaves. A greenhouse pot experiment was conducted in a completely randomized block design, in a double factorial arrangement (5 × 2), composed of five rates of Zn (0, 8, 32, 64, and 96 mg dm⁻³) and two levels of mycorrhizal inoculation (presence and absence) with 10 replicates. Plant growth, AMF colonization, and plant Zn uptake were measured. AMF inoculation substantially increased AMF root colonization across all Zn levels, while non-inoculated plants presented an 89% decrease in root colonization at the highest Zn rate (96 mg Zn dm⁻³). Without inoculation, high Zn fertilization reduced lettuce yield by 16% at the highest Zn rate (96 mg Zn dm⁻³), with no negative effects in inoculated plants. Inoculated plants produced 37% more fresh biomass without Zn fertilization (0 mg Zn dm⁻³) and 68% more at the highest Zn rate (96 mg Zn dm⁻³) compared to non-inoculated plants. Fertilized plants were successfully biofortified, reaching Zn concentrations eightfold (inoculated plants) to 10-fold (non-inoculated plants) higher than controls. AMF inoculation promoted superior Zn absorption under toxic Zn levels while inhibiting detrimental effects of Zn toxicity on plant growth. Therefore, our data provide new evidence that AMF inoculation enables the application of high Zn rates in lettuce biofortification programs while enhancing plant growth.

Soil weathering is the term that describes soil genesis, and its good visual indicators are natural vegetation cover and soil morphology. However, do the same soil types under different vegetation covers affect the degree of soil weathering? Our objective was to study two contrasting soil types under natural vegetation to discuss the degree of weathering, considering their morphology, silicon (Si) content, and fine mineralogy assemblage. Soil samples were collected in nearby Brazilian regions with Ferralsol and Regosol soils, as well as native forest and grassland areas. Soil profile, mineralogy, and chemical composition (total and available ions) were described. Both soils presented the following minerals: mica/illite, kaolinite, quartz, and cristobalite. Available Si content ranged from 6.31 to 8.76 mg kg⁻¹, and it was higher in Ferralsol than in Regosol soils but did not show dependency on the vegetation type. The total SiO₂ content ranged from 283.5 to 341.4 g kg⁻¹. The Ki index was higher in the A horizons (2.77) of Ferralsols than in Regosols. The silt/clay ratio content discriminated soil types more accurately. Although vegetation types, mineralogy effects, and Si availability were weak as factors of soil evolution under native conditions, these findings do not end the discussion about the impact of vegetation cover on soil weathering. Further studies on different soil classes are recommended, including assessments of Si content in plant tissues, to elucidate the link of vegetation and mineralogy to chemical availability.

The economically optimal nitrogen rate (EONR), while an accepted standard as the “right rate” for corn (Zea mays L.) fertilization, does not directly account for environmental impacts. This study evaluated the effects of nitrogen (N) fertilizer application rate and timing on crop N use and N loss potential, using residual soil nitrate-N (RSN; 0- to 0.9-m depth) relative to EONR. The evaluation was conducted using 49 N response trials from eight US Midwest states from 2014 to 2016. Nitrogen rates were applied as ammonium nitrate, either all at planting or split between at planting (45 kg N ha⁻¹) and the remainder at the ∼V9 growth stage. At EONR, RSN was 42 kg N ha⁻¹ for at-plant applications and 62 kg N ha⁻¹ for split applications. However, unaccounted for N at the end of the growing season was greater for at-plant (46 kg N ha⁻¹) than for split applications (21 kg N ha⁻¹). This suggests a higher susceptibility of N loss during the early season for at-planting applications and after the season for split applications. Differences in RSN at the EONR between N timings were not explained by differences in total aboveground N uptake at R6. Residual soil nitrate did not substantially increase until N application rates exceeded the EONR by 30 kg N ha⁻¹. These findings support using EONR, at an N:corn price ratio of 5.6, as an N application sustainability standard that balances profitability and environmental concerns.

Many poorly drained soils require subsurface drainage to facilitate crop production, but excessive drainage can lead to loss of soil organic carbon (SOC). The effects of subsurface drains installed at 5-, 10-, and 20-m spacings compared to an undrained control (40-m spacing) on soil physical properties, biomass production, and C balance were evaluated for a low organic matter silt loam soil in Indiana, following 19 years of installation. The more intense drain spacings significantly reduced bulk density and moisture retention and increased aeration porosity compared to the undrained control in the surface 30-cm soil depth. Among the 5-, 10-, and 20-m spacings, total biomass production and biomass C input to soil were greatest for 5-m spacing and least for the 20-m spacing (average: total plant biomass = 10.1; biomass C = 4.3 Mg ha⁻¹ year⁻¹), but biomass production and biomass C input were greater for all three spacing treatments than the undrained control (total biomass = 9.4; biomass C = 4.0 Mg ha⁻¹ year⁻¹). All three spacing treatments had greater SOC mass to a 1-m depth (average = 51.8 Mg C ha⁻¹) than the undrained control (48.3 Mg C ha⁻¹). The results showed that for soils low in SOC, long-term subsurface drainage at the appropriate drain spacing could be beneficial to C accumulation. In this soil, the 20-m spacing appeared to have the best combination of increased biomass production and decreased SOC loss over the initial 19 years of drainage.

The soil test correlation determines the critical soil test value (CSTV) of phosphorus (P) required to achieve 95%–100% of the maximum crop yield. However, CSTV predictions vary with the mathematical model used, which has implications for fertilizer recommendations. This study compared the P CSTVs for corn (Zea mays) estimated using four models, (1) modified arcsine-log calibration curve (ALCC), (2) linear plateau (LP) at the join point (JP), (3) quadratic plateau (QP) at the JP (QP-JP), and (4) QP at 95% of maximum yield (QP-95), and then calculated the frequency of crop response at different Mehlich-3 soil test phosphorus (STP) concentrations. Corn was grown in long-term trials in 2010, 2012, and 2014 in the Piedmont, Coastal Plain, and Tidewater regions of North Carolina. The P CSTVs obtained with ALCC, LP-JP, QP-JP, and QP-95 models were 42, 24, 31, and 26 mg kg⁻¹, respectively, at the Coastal Plain site and 55, 43, 55, and 49 mg kg⁻¹ at the Tidewater site, but these models could not calculate CSTVs at the Piedmont site. Nevertheless, the 95% confidence interval of CSTV did not differ for these models and sites analyzed. The frequency of corn response to STP declined with increasing STP, reaching 10% at 37.0 and 44.9 mg kg⁻¹ at Coastal Plain and Tidewater sites, respectively, defining critical soil test range (CSTR) of 26–37 and 45–49 mg kg⁻¹. Additional approaches combined with CSTV using broader datasets may help to refine the CSTR definition and improve fertilizer recommendations.

Potassium (K) is a critical macronutrient for maximizing yields in agricultural crops. However, inconsistent responses to K fertilizer or soil test K levels have led researchers to question which soil properties influence K availability and cycling in soils. This study aimed to evaluate how K is retained in sandy soils. The specific objectives of this research were to (1) determine the influence of pH level on cation exchange capacity (CEC) and K sorption in coarse-textured soils and (2) assess the impact of freeze–thaw cycling on K release across a range of agricultural soils. Soil was collected from 10 agricultural sites in Minnesota. Of these, four were used to evaluate K sorption and eight were used to assess K leaching following freeze–thaw weathering. Potassium sorption experiments revealed that sand-textured soils exhibited limited K sorption as solution K increased, but a higher clay percent or CEC allowed for greater K sorption. The addition of calcium (Ca) in the sorption experiments resulted in K release for all sandy-textured soils. In weathering studies, freeze–thaw cycling led to mixed effects on K leaching. Simulated irrigation water containing Ca and magnesium (Mg) significantly increased K leaching in comparison to deionized water. These studies indicate the need for tailored K recommendations in coarse-textured, low-CEC soils considering the limited K sorption capacity and influence of divalent cations.

The fermentation of Baijiu grains in the cellar is significantly influenced by the quality of the cellar soil, which contains a diverse range of microorganisms and physicochemical components. Among these, the total nitrogen content (TNC) is a critical indicator of soil quality and thus requires real-time monitoring to ensure quality control of the Baijiu. In this study, we developed two optimized machine learning algorithms—successive projection algorithm-genetic algorithm (SPA-GA) and crown porcupine optimization (CPO) achieve the rapid and accurate detection of the TNC in cellar soil using hyperspectral imaging (HSI). The feature wavelengths were selected by combining the SPA with the GA. Subsequently, the support vector machine regression (SVR) algorithm was further optimized using the CPO algorithm to establish a prediction model for determining the TNC. Comparative analysis of the various models demonstrated that the CPO-SVR model based on the feature wavelength spectral data extracted by the SPA-GA exhibited the best performance ($��{R_p}^2��$= 0.9958, root-mean square error of prediction [RMSEP] = 0.0073 g/100 g). This model reduced the number of wavelengths by 86.16%, increased the $���{R_p}^2�$ by 0.3014, and decreased the RMSEP by 0.0566 compared to the same model built using the full-wavelength spectral data. These results indicated that the GA significantly enhanced the feature extraction capability of the SPA, thereby improving the model accuracy while reducing the number of wavelengths to reduce computational load. Furthermore, CPO was introduced to optimize the SVR, yielding the optimal parameter combination, which further improved the prediction model performance and accuracy while mitigating artificial parameter-seeking instability. HSI, in conjunction with the optimization algorithms, offers a novel method for the rapid, non-destructive detection of total nitrogen and other components in cellar mud.

Water retention is crucial in many applications, including canal irrigation, agriculture storage ponds, and mine tailings impoundments. A capillary barrier system (CBS) offers a promising solution by utilizing contrast in pore sizes between soil layers to minimize infiltration. However, the application of compacted bentonite as the finer CBS layer remains underexplored due to challenges in characterizing its unsaturated hydraulic behavior. Recent advancements in laboratory and theoretical studies provide an opportunity to evaluate its breakthrough response and mechanism under ponding conditions. This study presents a comprehensive hydraulic analysis of CBS incorporating compacted bentonite as the fine layer. Laboratory experiments were conducted to determine the soil-water characteristic curve and hydraulic conductivity function of the studied compacted soils, while one-dimensional column tests for breakthrough head, breakthrough time, water storage, and infiltration rates for various CBS configurations. The influence of bentonite plasticity and coarser layer density on CBS performance was systematically examined. Further laboratory investigations explored the impact of coarser layer soil type variations. A novel breakthrough mechanism was identified for CBS employing different soil as coarser layer. The laboratory and field scale tests demonstrate the suitability of compacted bentonite as an effective component in CBS designed for water retention applications.

Sound estimations of blue carbon (C) stocks have important implications for global carbon accounting. This is especially true in tidal marshes because of their capacity to accumulate and store large quantities of C. Reliable field data, however, have historically been limited. More recent research has focused on general estimates of C stocks in the conterminous United States but without regard to the differences in soil characteristics, which vary based on the particular geomorphic setting where a marsh has formed. This may lead to inaccuracies in C stock estimates at a regional scale. In this study, we set out to measure tidal marsh C stocks in the Mid-Atlantic region and to understand the impact of geomorphology on the variability of C storage. We collected and analyzed 455 samples from 72 pedons distributed across five pedogeomorphic units (PGUs) representative of the Mid-Atlantic region: (1) submerged upland, (2) estuarine fresh, (3) estuarine non-fresh, (4) coastal barrier, and (5) coastal mainland. Carbon stocks were measured for each pedon, and significant differences in mean C stocks were found among the five PGUs. Differences became more pronounced with increased sampling depth (up to 200 cm). Additionally, we found that C stocks change spatially and systematically within certain types of marshes. These results suggest that geomorphic setting, which influences the pedogenesis of tidal marsh soils, has a meaningful impact on C storage and must be considered for accurate C accounting.