Proceedings - Soil Science Society of America最新文献

Conventional farming practices have negatively impacted micronutrient fertility and overall soil health. Metal lactates are an organic micronutrient amendment that provide both a labile carbon substrate as well as mineral nutrition for plant and microbial growth. To determine the ability of metal lactates to provide readily available micronutrients, Zn, Cu, Mn, Ni, and Co in lactate and chloride salt form were amended to soils and incubated for 28 days. Operationally defined speciation was determined using sequential extraction on samples incubated for 1, 5, or 28 days. The results show a comparable distribution of metals in chloride and lactate form; however, differences were detected in water-soluble and exchangeable Ni and Zn at each timepoint. For example, in the water exchangeable fraction, there was 2.6%–2.9% less Ni and 0.2%–0.3% less Zn in the metal lactate-treated soil compared to soil treated with metal chlorides. Furthermore, carbonate-bound Ni averaged 4.1% and 4% less in metal lactate-treated soils as compared to metal chloride-treated soils on days 1 and 5, and Cu decreased 2.9%–3.3% during the treatment period for the lactate-bound form. Additionally, microbial phospholipid fatty acid (PLFA) was performed and found a stimulatory effect of metal lactates on bacterial biomass with an increase of 12%–18% relative to the metal chloride treatment. Results from this study support the use of metal lactates as a sustainable alternative to conventional fertilizers by providing bioavailable micronutrients for plant nutrition in addition to a labile carbon source to support the growth of microbial populations.

Infrared spectroscopy is increasingly being adopted as a technology for soil analysis. However, laboratories worldwide are equipped with different infrared spectrometers, leading to variations that hinder the global application of soil spectroscopy. This study evaluates the transferability of soil spectra from a global dataset collected using four mid-infrared spectrometers. To evaluate the efficacy of five spectral transfer functions (direct standardization, piecewise direct standardization, spectral space transformation [SST], principal components-canonical correlation analysis [PC-CCA], and domain-invariant partial least square [DIPLS] regression), two datasets were used: dataset A (n = 224; standardized samples) was scanned using one primary spectrometer and three secondary spectrometers; dataset B (n = 1904; legacy samples) was scanned only using the primary spectrometer. The first set of chemometrics models was developed using dataset A to compare the performance of different spectrometers. The second set of models was developed using dataset B to evaluate the effectiveness of spectral transfer functions. Both models were developed using partial least squares regression. Spectral transfer functions developed using dataset A indicate that the PC-CCA method was the best in converging spectra collected from four instruments into a similar space projected using Uniform Manifold Approximation and Projection. Spectral transfer did not result in consistent improvement in the prediction of soil properties compared to the direct use of spectra collected from different spectrometers. These findings carry significant implications for the utilization of legacy models, enabling laboratories to concentrate on acquiring new samples and spectral measurements using established protocols without the need for spectral transfer.

The present study examined how the use of soil color can help build and evaluate clay content prediction models from laboratory visible and near infrared spectroscopic data. This study was based on a regional database containing 449 soil samples collected over Karnataka state in India, which has been divided into red soils (240 samples) and black soils (209 samples) based on their Munsell soil color. Partial least squares regression models were calibrated and validated from both the regional datasets and subsets stratified as red and black soils. In addition, a random forest model was used to classify the validation soil samples into black and red classes to evaluate models’ performance. First, while the clay content predicted by the regression model built from regional data was evaluated as correct at regional scale (R²_val of 0.75), this model was evaluated as more accurate over black (R²_val of 0.8) than red (R²_val of 0.63) soil samples. Second, the regression models built from subsets stratified per soil color provided different performances than the regression model built from the regional data, both at the regional scale and soil color scale. In conclusion, this study demonstrated that (1) predictions are highly dependent on calibration data, (2) the interpretation of prediction performances relies heavily on validation data, and (3) pedological knowledge, such as soil color, can be effectively employed as an encouraging covariate in both the construction and evaluation of regression models.

Manure relocation strategies are needed to mitigate excessive phosphorus (P) application to agricultural land in areas of intensive animal agricultural production. This requires conceptual frameworks such as the manureshed, which categorizes agricultural areas according to the potential to export or receive manure for P fertilization. To further understand how the manureshed concept could be utilized, assessments of the potential implementation and necessity of the manureshed model are needed. With North Carolina at the center of the largest manureshed in the United States, North Carolina is an ideal test case to identify areas of concern for manure relocation under the manureshed framework. Swine and poultry dominate North Carolina's agricultural production, and because the vast majority of North Carolina producers are not required to limit manure applications to a P-based rate, P accumulates. Therefore, soil test data from samples submitted to the North Carolina Department of Agriculture and Consumer Services (NCDA&CS) from 2017 to 2019 were used to determine how manureshed classes defined by Spiegal et al. correspond to current soil test P levels. It was determined that 36% of counties experience very high (>100 mg P kg⁻¹; N = 36) median P concentrations in soil. Furthermore, fields cultivated with warm-season forages had the highest mean P concentration (188 mg kg⁻¹) and high median P trended toward counties with high animal production. Lastly, while mean soil P for all manureshed classifications fell into the very high category, manure source counties had the highest mean soil P concentrations (188 mg kg⁻¹), which was 39%–52% higher than the other classifications. This suggests that, in addition to manuresheds classification, soil test data are needed to design and promote manure redistribution strategies.

Proper soil sampling is critical for accurate fertilizer recommendations. Samples collected in extremely wet or dry conditions may compromise the integrity of the sample and influence analytical results. We evaluated the effects of six soil moistures, two sampling depths (0–10 and 0–15 cm), and two soil probes on soil core uniformity and soil test results. Moisture treatments encompassed a range from dry (11.2%–18.5% moisture) to saturated conditions in Captina, Dewitt, Calhoun, and Calloway silt loam soils. Core depth and dry core weight were measured in all soils, and pH and Mehlich-3 extractable P, K, S, and Zn were assessed for Calhoun and Calloway soils. Soil moisture, probe, or their interaction influenced core depth and weight, while chemical properties were significantly affected only by soil moisture. Sampling very dry or saturated soils compromised the collection of uniform cores mainly for the 0- to 15-cm depth. Soil pH tended to increase with increasing moisture, but the mean values fluctuated only ±0.3 units. Across soils and depths, extractable S consistently decreased by 16%–48% as soil moisture at sampling time increased. Phosphorus was affected by soil moisture for 0–15 cm samples in both soils but showed no clear pattern. Soil moisture at the time of sampling affected soil test K for both soils and sample depths with individual cores varying up to 47 mg kg⁻¹ (i.e., 59–106 mg kg⁻¹). Greater soil test P and K variability occurred for very dry and wet conditions, which often prohibit collecting samples to the proper depth and could impact fertilizer rate recommendations.

Limestone is the most widely used agricultural input for soil acidity correction and calcium (Ca) and magnesium (Mg) fertilization. However, other materials have the potential to fulfill these purposes, such as steel slags, also known as silicates. Silicates have higher solubility than limestone, serving as agents for increase pH in no-till, in addition to being a source of Ca, Mg, and silicon (Si). This study aimed to compare the effects of surface application of dolomitic lime and calcium magnesium silicate on soil chemical properties, soybean [Glycine max (L.) Merr.] nutritional status, and grain yield under no-till. The experiment was installed in the northwest Paraná State, Brazil, on a Rhodic Eutrustox. Lime and silicate rates were applied by broadcasting before the sowing of soybean. Silicate treatment increases soil Ca²⁺, pH, and base saturation up to a depth of 0.10 m. By contrast, liming effects on soil chemistry were restricted to the 0.05 m top layer after 24 months of application. The acidity correction and Ca²⁺ supply to greater soil depths and the increased leaf Si as a beneficial element provided by silicate treatment contributed to increasing soybean yield in the 2018/2019 and 2019/2020 seasons. Lime application, regardless of the rate, did not improve soybean yield. Waste from the steel industry can be used as acidity correctives and source of Si, Ca, and Mg, improving the agronomic performance of soybean.

RETRACTION: Ibrahim, A. & Horton, R. (2021). Biochar and compost amendment impacts on soil water and pore size distribution of a loamy sand soil. Soil Sci Soc Am J., 85, 1021–1036. https://doi.org/10.1002/saj2.20242

The above article, published online on 16 March 2021 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal's Editor, William Horwath, the Soil Science Society of America's Editor-in-Chief, Craig Rasmussen, the Soil Science Society of America, and Wiley Periodicals LLC.

The retraction has been agreed following concerns raised from the corresponding author of (Al-Omran et al., 2021), who claimed that he was omitted as an author and was unaware of the article's submission as he pursued the publication of (Al-Omran et al., 2021) in another journal. An investigation by the journal, society, and Wiley observed that (Al-Omran et al., 2021) is based on the same research as this article, with evidence of significant overlap. Therefore, these parties consider this a duplicate publication.

Additionally, further investigation by the author's institution concluded that the article does not disclose the university's funding, nor does it appropriately acknowledge the omitted author. As such, the institution formally requested that the article be retracted.

Corresponding Author A. Ibrahim disagreed with the retraction. Co-author R. Horton collaborated during the investigation and agreed to the retraction.

Biochar may improve the health of environmentally sensitive soils (i.e., low C, sandy, sloping) especially if combined with cover crops (CCs), but research is scant. We assessed how wood biochar (836 g C kg⁻¹) applied at 0, 6.25, 12.5, 25, and 50 Mg ha⁻¹ to sandy, sloping, and semi-arid soils with and without CCs affects soils and crop yields in the central US Great Plains for 3 years. We measured crop yields and CC biomass each year, and most soil properties in Years 1 and 3. Biochar did not interact with CCs, suggesting the combination was no better than biochar or CC alone. In the semi-arid soil, crop and CC did not establish due to persistent droughts. Biochar benefits were highly site-specific. Biochar improved some soil properties but only in the sandy and sloping soils and at the biochar application depth (0- to 15-cm soil depth). The 50 Mg biochar ha⁻¹ improved the soil's ability to sorb water (0.08 cm s^−1/2). Also, in the sandy soil, it increased soil organic matter concentration (2.5 g kg⁻¹), soil pH (0.65 units), and available water (0.07 m³ m⁻³) only in Year 1, suggesting a biochar benefit in sandy soils is short-lived. In the sloping soil, >25 Mg biochar ha⁻¹ reduced bulk density (0.16 Mg m⁻³) and increased soil mean weight diameter of water-stable aggregates (0.58 mm), organic matter concentration (11.42 g kg⁻¹), infiltration (9.35 cm), CC biomass production (0.27 Mg ha⁻¹), and some microbial biomass groups. Biochar did not affect crop yields. Overall, >25 Mg biochar ha⁻¹ improved properties in some soils without interacting with CCs.

Ammonia loss following nitrogen fertilization can degrade air quality and impact human health, whereas nitrous oxide (N₂O) can contribute to global warming and climate change. Mitigation practices that target only one N-loss pathway can lead to pollution swamping; hence, practices targeting both N-losses are required. A 3-year field study examined fertilizer N-placement (broadcast urea, single-slot injection of urea ammonium nitrate [UAN], double-slot UAN injection) and N-metabolization inhibitors (with/without urease and nitrification inhibitors) impacts on NH₃ and N₂O losses and corn yields. Ammonia volatilization was reduced (p < 0.05) by 26% with single-slot UAN injection (10.6 kg N ha⁻¹) and by 63% with double-slot UAN injection (5.32 kg N ha⁻¹) compared to broadcast urea (14.3 kg N ha⁻¹). Dual urease and nitrification inhibitors reduced NH₃ volatilization (0.84–3.86 kg N ha⁻¹) by 57%–92% compared to no inhibitors (5.32–14.3 kg N ha⁻¹). When no inhibitors were applied, N₂O emissions from slot injection (6.43–7.62 kg N ha⁻¹) were 2.6–3.1 times greater than from broadcast urea (2.43 kg N ha⁻¹). Dual inhibitors reduced N₂O emissions by 43% from 6.43 to 3.66 kg N ha⁻¹ with double-slot injection. Double-slot UAN injection increased corn grain yields (9.73 t ha⁻¹) by 12%–13% compared to single-slot UAN injection (8.71 t ha⁻¹) and broadcast urea (8.6 t ha⁻¹). Double-slot UAN injection effectively decreased NH₃ losses and increased corn grain yields, but dual N inhibitors were required to also reduce N₂O. Hence, combined productivity and environmental benefits were accrued only when fertilizer containing urease and nitrification inhibitors was combined with double-slot injection.

Phosphorus (P) dynamics in the soil subsurface are relatively unstudied, especially in forest soils, and may be important in areas with groundwater-fed surface water bodies. Here, we use X-ray absorption near-edge P spectroscopy (P-XANES) and X-ray fluorescence microprobe mapping (µ-XRF) to examine P speciation and co-localization with Fe and Al as a function of depth in soils from coniferous and deciduous forests. P-XANES revealed similar trends in P speciation with depth for both forest types, with Al-P and Fe-P being dominant, whereas Ca-P and organic P were minor constituents. Correlation plots derived from µ-XRF mapping revealed a strong correlation between P and both Fe and Al at all depths. At depths of up to 378 cm, a range that includes A, E, and B horizons, the relationships between P and Al/Fe were remarkably consistent, consisting of a population of P diffusely associated with Al/Fe, consistent with Fe- or Al-adsorbed P, as well as P linearly correlated with Al/Fe in several discreet groupings, indicative of the presence of specific P compounds. At depths below 378 cm, the relationships between P and Al/Fe changed dramatically, with correlation plotting indicating the disappearance of any diffuse P:Al/Fe relationships. This change occurred concurrently with a decrease in oxalate extractable P, suggesting that the P present in this deep soil horizon may be present in a more stable form that is less available for transport, as well as potentially indicating that P adsorbed to Fe/Al did not readily pass through the overlaying Bw soil horizon.