Proceedings - Soil Science Society of America最新文献

Soluble sulfide is toxic to many plants and animals and is especially problematic in brackish environments of the coastal zone (e.g., marshes and benthic environments). In addition to traditional techniques for measuring porewater sulfide in marsh and subaqueous systems (peepers, sippers, and centrifugal extraction), over the last decade or so, Indicator of Reduction in Soils (IRIS) has been added to the arsenal of available methods. Soluble sulfide reacts with the Fe oxide coatings on IRIS devices to form gray to black iron monosulfide (FeS) stains and coatings, the color of which is a function of both the concentration of the sulfide and the time of exposure. Challenges in using IRIS for sulfide analysis stem from the fact that the dark FeS colors fade quickly over a period of minutes to hours. During the last few years, significant advances in IRIS technology, as well as recent advances in digital image acquisition and image analysis, have allowed us to develop an IRIS approach for quickly and effectively collecting and quantifying porewater sulfide levels in coastal environments (e.g., subaqueous areas and marshes). This article will introduce new tools for deploying IRIS in subaqueous settings and will also demonstrate the utility of the new digital technology for image acquisition and analysis, as sulfide data from two marsh sites and four subaqueous soil sites are presented and discussed.

Sunflower (Helianthus annuus L.), a dominant crop in Hetao Irrigation District, Western Inner Mongolia, is cultivated in arid and saline-alkaline fields due to their salt and alkali tolerance, ensuring that farmers’ income from these fields is not lower than those from fertile lands. However, little is known about the integrated analysis of nitrogen (N) dynamics, including soil total N (TN), nitrate (NO₃⁻), leachate TN and NO₃⁻, nitrous oxide (N₂O) fluxes, and N cycling microbial gene abundance in sunflower fields. The specific objective was to explore N dynamics for 2021 through 2023 in sunflower seeded to saline-alkali croplands under arid condition based on treatments of irrigation rate (I rate: I1, 5110; I2, 4050; I3, 2985 m³ ha⁻¹) for washing salinity by irrigation and nitrogen fertilization rate (N rate: N1, 750; N2, 600; N3, 450; N0, 0 kg ha⁻¹). Our findings indicated that I rate did not affect soil N dynamics; N rate significantly increased soil TN, NO₃⁻ and N₂O fluxes, especially showing an extremely significant increase for leachate TN and NO₃⁻ leachate. The interaction of I and N rates impacted soil TN, NO₃⁻, their leachate, and N cycling microbial gene abundances, especially denitrification genes. Soil leachate TN and NO₃⁻ increased exponentially over time. Soil N₂O fluxes increased annually with the growth of sunflowers. In the saline-alkali sunflower fields, low N rate (450 kg ha ⁻¹) can be an optimal strategy, and the precise calibration of I and N rates can guarantee adequate N dynamics and yields, highlighting the intricate balance required for sustainable agricultural practices.

This study compares acid digestion and temperature ramping methods for obtaining soil organic carbon (SOC) reference data to train Fourier transform near infrared (FT-NIR) models in carbonate-rich Saskatchewan agricultural soils. FT-NIR spectra were measured on soil samples (n = 431) from carbonate-rich Dark Brown Chernozem soil, with quantification of inorganic and organic carbon. Spectra were transformed using continuous wavelet transform and analyzed using cubist regression tree models. Models were built using a 70:30 train test split validation approach. Spectral feature selection, wavelet scale, and model and hyperparameter optimization were conducted using fivefold cross-validation analysis on the training dataset. All validation metrics were calculated using the testing dataset. The temperature ramping method identified outliers with soil inorganic carbon (SIC) greater than 1.5%, which were not detected using the acid digestion method. SOC and SIC prediction accuracy was higher using temperature ramping data (coefficient of determination: R² = 0.66 and 0.63, Lin's concordance: ccc = 0.78 and 0.77) compared to acid digestion data (R² = 0.44 and 0.42, ccc = 0.64 and 0.62). Total carbon (TC) prediction accuracy was similar for both methods (R² = 0.58, ccc = 0.71). Removing samples with high carbonate (SIC > 1.5%) improved SOC and TC prediction accuracy using temperature ramping data (R² = 0.70, ccc = 0.81 for SOC; R² = 0.64, ccc = 0.75 for TC) but not when using acid digestion method. This study suggests that high carbonate content may negatively affects SOC model accuracy, especially when relying upon acid digestion methods for reference SOC data.

This paper investigates the physical properties of soil samples repacked from aggregate beds and the potential for retrieving representative soil pore properties at the field scale based on shrinkage analysis of a repacked composite sample. This approach was tested on 60 arable fields in Switzerland presenting a large range of soil organic carbon (SOC) and texture. Soil cores constituted from composite samples were repacked at the observed field bulk density. Their pore properties were compared to undisturbed soil samples from the same fields. The soil pore properties were characterized using shrinkage analysis and correlated to soil texture and SOC. The repacking protocol successfully recreated structured samples. The <40-µm equivalent diameter pore and structural pore size distributions were comparable to those of the undisturbed soils. For pores >40 µm, a larger porosity was measured for repacked samples compared to undisturbed ones, limiting the approach to assess the structure and dynamics of larger soil pores. Furthermore, soil clay content as well as SOC were strong predictors for the samples’ physical properties including pore space. The increase in structural porosity in the repacked sample was inversely proportional to the structural porosity already present in the undisturbed samples. Steeper regression slopes of the pore volume to SOC or clay relationship were observed for the repacked samples. These slope changes were comparable to those observed in soil structure restoration experiments and opposite to those observed in soil compaction trials. We conclude that repacking soil from a composite sample allows us to characterize the potential soil structure condition with respect to its SOC and clay content. The method can be used to assess soil structure quality in response to changes in soil management.

Winter cover crops (WCC) have received much attention due to their environmental benefits, particularly improvements to soil health. However, most studies are made less than 5 years after implementation, and there is no consensus about when to soil sample to best quantify a WCC effect. We used a paired, chronosequence approach with 1–15 years since implementation of cereal rye (Secale cereale) as a WCC, and analyzed soils collected in spring and autumn. We measured soil bulk density, maximum water-holding capacity, penetration resistance, pH, total carbon (C) and nitrogen (N), permanganate oxidizable carbon, microbial biomass carbon (MBC), and microbial biomass N, potentially mineralizable carbon (PMC), and potentially mineralizable nitrogen (PMN). We also analyzed maize (Zea mays) and soybean (Glycine max) grain yield. We found that WCC increased MBC and PMC by 8% each and increased PMN by 11%, regardless of time-since-implementation. Furthermore, sampling biological soil health indicators in the spring resulted in more positive, significant treatment effects (12%–19%) compared to sampling in the autumn, where we found no effect. WCC increased soybean yields by 7% after 8–9 years but decreased maize yield by 23% after 15 years. WCC reduced soil penetration resistance by 10% after 8–9 years but increased it by 20% after 15 years. These later contrasting results may be due to management nuances or biophysical changes in cropping systems with time. Overall, WCC have many environmental benefits, and in our study, WCC increase biological soil health indicators quickly, but yield drag and increased soil penetration resistance may occur later in WCC adoption.

Here, we review the prediction accuracy for soil properties using portable X-ray fluorescence (pXRF), mid-infrared (MIR), and visible near-infrared (Vis-NIR) and the factors impacting predictions and its accuracy. In total, 305 published papers were reviewed, and most of them were from Australia, Brazil, China, and the United States. About 44% of papers focused on the prediction of soil organic carbon (SOC) using Vis-NIR spectra. Partial least squares regression was most frequently used. Most studies sampled Alfisols, Inceptisols, and Entisols, and up to 40-cm depth. Researcher-based factors (type or brand of spectrometers, which differ in hardware, spectral range, resolution, and calibration protocols; preprocessing methods; prediction models; and soil analysis methods for calibration) and soil-based factors (horizon and depth) were explored. MIR spectra had better prediction accuracy with a mean R² over 0.8 for sand, clay, total N, total C (TC), SOC and soil inorganic carbon (SIC), and cation exchange capacity compared to Vis-NIR and pXRF. In the past 20 years, prediction accuracy tended to increase for sand, silt, clay, SIC, soil organic matter, and EC when using MIR and Vis-NIR spectra, and for TC and CaCO₃ when using pXRF spectra. Preprocessing methods, spectral range, calibration, type of the prediction models (i.e., machine and deep learning), and source of soil spectra (Vis-NIR, MIR, and pXRF), which are used to reduce noise and multicollinearity, calibrate data, and smooth spectra, all affected the prediction. In general, MIR spectra obtained the highest prediction accuracy for most soil properties. Future studies should focus on the effects of soil-based factors (parent material, soil mineralogy, pedogenesis, soil type, and horizon/depth) on the prediction accuracy of soil physical and chemical properties.

Farmers are increasingly recognizing the importance of building healthy soils to enhance farm resilience and profitability. Advances in metagenomic DNA sequencing of soil microbial communities offer opportunities to explore relationships between genes linked to key soil functions and established soil health metrics. Since soil nitrogen (N) is critical for crop growth, our study aimed to assess soil health and N transformation gene abundances and correlate soil health with genes involved in inorganic and organic N transformations on commercial dairy farms in Pennsylvania. Soils from three conventional no-till farms and three organic farms using plow-tillage were evaluated with an array of soil health tests as well as metagenomic sequencing. Undisturbed soils from fencerows or farm edges served as reference soils with native properties. Soil health variables of reference soils were more similar to those of no-till soils than to the tilled organic soils. Reference soils had greater relative abundances of microbial genes related to organic N use, while no-till and tilled organic soils exhibited greater abundances of genes related to inorganic N transformations. Carbon and N mineralization and autoclave citrate-extractable (ACE) protein were positively correlated with abundances of genes involved in organic N use, with ACE protein negatively associated with genes involved in inorganic N transformations. Differences in soil health metrics and N use microbial profiles between reference and cropped soils offer insights into the status of microbial communities before and after agricultural disturbance, likely reflecting the history of external N inputs and internal N cycling.

Boron (B) is the micronutrient very much essential for stability of cell wall, viability of pollen grains, pollen germination, pollen tube growth, and development of fruits and seeds. However, it was found to be the limiting nutrient in oil palm plantations in India. B interacts with other nutrients synergistically or antagonistically. There is a need to study the B fractions and their association with other nutrients for efficient B management. The soil samples (0- to 60-cm depth) of nutrient management trial with graded levels of N (0, 1200, 2400 g N palm⁻¹ year⁻¹), P (0, 600, 1200 g P₂O₅ palm⁻¹ year⁻¹), and K (0, 600, 1200 g K₂O palm⁻¹ year⁻¹) were collected and analyzed for pH, electrical conductivity, organic carbon (OC), nutrient content, and B fractions. The majority of B fractions were residual boron (RSL-B), which constituted 73.3%–93.8% of total B. In contrast, the plant-available B fractions (readily soluble B [RDS-B] and specifically adsorbed boron [SAD-B]) accounted for <2.0% of the total B content. The oxide bound boron (OXD-B) accounted for 2.35%–8.18%, whereas the organically bound boron (ORG-B) constituted 1.25%–20.1% of total B. Fractions of B were significantly influenced by the dose of primary nutrients. The plant accessible B fractions were positively influenced by soil parameters like soil reaction, OC, and available nitrogen (N), whereas OXD-B was negatively associated with available phosphorus (P). Considering the relationship within B fractions, SAD-B and ORG-B showed a positive correlation with RDS-B, indicating their involvement in replenishment of plant-available B pool. The study suggests that application of 1200 g N, 600 g P₂O₅, and 600 g K₂O significantly increased the plant-available B fractions in soils of oil palm plantations. The information generated from the study aids in efficient management of B.

Barley (Hordeum vulgare L.) is used mainly for malting, brewing, and animal feed. In antiquity, barley was a major calorie source for humans and has recently become of increased interest as consumers seek healthier options. Hull-less barley plays a key role in this resurgence as the need to process barley through pearling is removed and modern cultivars have high fiber content. To our knowledge, no work has established fertilizer-nitrogen (N) recommendations for hull-less food barley under high-yielding irrigated conditions common in the semi-arid western United States. Research was conducted in the major irrigated production area of southern Idaho over 11 site-years of replicated N response trial data (∼5 fertilizer-N rates) from 2019 to 2023 for the cultivars Goldenhart and Julie. N-supply is reported and is the sum of applied fertilizer-N and soil inorganic-N to 60 cm. Analysis of variance (ANOVA) critical N-supply (CNS) was calculated site-by-site as the lowest yield that did not differ from the maximum. The average ANOVA CNS was 194 kg N ha⁻¹ across all site-years. A yield-based approach and corresponding nitrogen requirements (Nr) from the ANOVA CNS resulted in an N-supply range from 200 to 224 kg N ha⁻¹. A 95% relative grain yield (RGY) was used for linear- and quadratic-plateau models which determined CNS of 194 and 234 kg N ha⁻¹, respectively. Protein increased slightly but was poorly explained by N-supply. A static-N range from 194 to 234 kg N ha⁻¹ is suitable for irrigated hull-less barley production.

Soil CO₂ emissions surpass anthropogenic fluxes by an order of magnitude, with tropical soils exhibiting significant flux variability. We measured soil CO₂ flux, stable carbon isotope ratio (δ¹³C), and radiocarbon (¹⁴C) in soil-respired CO₂ as well as in soil pore space CO₂ (soil CO₂) and soil organic carbon (SOC). The objectives were to estimate CO₂ flux, identify influencing factors, and trace the sources of CO₂ in soil pore space and surface emissions. Soil CO₂ concentrations ([CO₂]) ranged from 13,780 to 26,300 ppmv. The surface CO₂ flux varied between 4.6 and 8.6 µmolCO₂/m²/s. It was strongly influenced by soil moisture content. Under relatively dry summer day with soil moisture content in the range of 7.7%–9.5% by weight, the flux varied between 8.0 and 8.6 µmolCO₂/m²/s. Under increased soil moisture conditions (14.3%–17.9%), CO₂ flux decreased to 4.6–6.6 µmolCO₂/m²/s, with larger fluctuations attributed to moisture variability. The ¹⁴C in soil and respired CO₂ is predominantly modern, while SOC exhibited much older radiocarbon ages, ranging from 2700 before present (BP) at 10 cm to 12,900 BP at 150-cm depth. Therefore, the SOC contributes minimally (at most 5%) to both soil and respired CO₂. Instead, root respiration and the decomposition of fresh organic matter are the dominant sources, even at deeper soil layers. As a result, the SOC pool and soil CO₂ appear to function as largely decoupled systems, suggesting that estimating the mean residence time of SOC based solely on surface CO₂ flux may be misleading.