Proceedings - Soil Science Society of America最新文献

Intensive agricultural practices to meet food demand have led to a decline in soil quality and agricultural productivity, posing significant challenges to environmental sustainability. Consequently, the present research focused on the development of models based on artificial intelligence techniques to predict the soil quality index (SQI) for soybean (Glycine max) cultivation using a total of 89 soil samples taken at 300-m grit system at depths of 0–20 cm. A set of 28 parameters categorized into main physical, chemical (organic matter, pH, EC, etc.), fertility (macro- and micronutrient elements), and biological (soil respiration, metabolic coefficient, and microbial biomass carbon) parameters were used for the total dataset (TDS). The minimum dataset (MDS), which consisted of the most sensitive parameters, was selected using principal component analysis. In this study, SQI was calculated for both TDS and MDS using a neutrosophic fuzzy analytic hierarchy process and standard scoring function. The resulting SQI_TDS and SQI_MDS values were then predicted using machine learning approaches, including multiple linear regression (MLR) and random forest regression (RFR). The accuracy of these predictions was then examined using various metrics such as mean absolute error, mean squared error, and root mean square error. The results show that MLR outperforms RFR for both SQI_TDS and SQI_MDS with significantly lower error indices and higher R² values than RFR through 10-fold cross-validation. In addition, this study statistically compared the obtained SQI_TDS and SQI_MDS values with normalized difference vegetation index (NDVI) values derived from the Sentinel-2A satellite for May 2021. The same satisfactory R² values (0.84) were obtained by statistically comparing both SQI_TDS and SQI_MDS with NDVI values. Furthermore, this study demonstrates the effective integration of advanced techniques such as machine learning models with remote sensing and geographic information system technologies, for the analysis and processing of both original and generated information in the vast domain of SQI.

Chemicals are an integral part of modern agriculture and are applied through a variety of methods. Some agrochemicals used for crop protection are absorbed by the roots prior to translocation to the rest of the plant. To be absorbed by the root, the agrochemical must first be transported through the soil, often by water. Some agrochemicals suffer from poor water-based soil transmission due to their chemical properties, limiting their application as a traditional seed treatment. Two agrochemicals with poor water-based soil transmission are Chlorantraniliprole and Spinosad. Soil protists are an important component of the soil microbial community. Certain soil protists have been shown to facilitate the transport and target delivery of suspended particles and bacteria through soil and soil-like structures. Here, we provide practical evidence that a soil protist, Colpoda sp., when co-inoculated with an agrochemical seed treatment, can substantially and robustly reduce subsequent pest feeding damage versus application of the agrochemical alone. Using maize (Zea mays L.) and fall armyworm, Spodoptera frugiperda (J. E. Smith, 1797) (Lepidoptera: Noctuidae), in a plant damage assay, we compare pest feeding damage and pest mortality for leaf samples from plants whose seeds were treated with only protists, only agrochemical, or agrochemical + protists. We discover, for both agrochemicals tested, that co-inoculation of protists with agrochemical increases protection in leaves versus agrochemical alone. Protist amendment is a simple, natural, chemical-free, soil-based transport enhancer that may be widely useful in a variety of contexts including more sustainable agriculture methods and cost-effective integrated pest management.

Enhancing crop productivity and soil sustainability under climate-smart agriculture involves strategically using soil amendments to improve soil health and resilience. A field experiment at Prairie View A&M University, Texas, studied the effects of soil amendments (chicken and dairy manures and biochar) on some soil health indicators. The experiment used two biochar rates (2268 and 4536 kg ha⁻¹) and two types of manure (chicken and dairy) at three rates (0, 224, and 448 kg total N ha⁻¹ for sweet corn [Zea mays (L.)] and 0, 180, and 360 kg N ha⁻¹ for sorghum [Sorghum bicolor (L.) Moench]) in a factorial design with three replications. Soil macronutrients and micronutrients were measured as chemical soil health indicators, and bulk density, porosity, and saturated hydraulic conductivity were measured as physical soil health indicators. Dairy manure significantly increased soil calcium (Ca) and potassium (K) concentrations. Higher manure application rates improved soil nutrient concentration, with the highest phosphorus (P), Ca, magnesium (Mg), and manganese (Mn) concentration levels at the double recommended rate. Biochar did not affect nutrient concentration but improved soil physical properties by increasing porosity, hydraulic conductivity, and reducing bulk density, especially at higher rates in sweet corn. Correlation analysis showed bulk density was negatively correlated with key nutrients like potassium (K), Ca, and Mg, while porosity and hydraulic conductivity positively influenced nutrient availability. The principal component analysis highlighted that sweet corn and sorghum respond positively to selected soil amendments, while their specific impacts vary based on crop type. The findings emphasize balancing manure and biochar application rates to optimize soil fertility and minimize environmental risks, supporting sustainable soil management strategies.

Galloway, L. A., Gamble, A. V., Guertal, E. A., Feng, Y., & Ogles, C. Z. (2025). Potential of ammonium thiosulfate and potassium thiosulfate to inhibit nitrification in soils. Soil Science Society of America Journal, 89, e70053. https://doi.org/10.1002/saj2.70053

In the first sentence of the fifth paragraph of the Introduction section, the sentence “Ammonium thiosulfate (ATS) and potassium thiosulfate (KTS) are used as liquid fertilizers.” should read, “Ammonium thiosulfate (ATS) and potassium thiosulfate (KTS) are used as liquid fertilizers (KTS is a registered trademark of Tessenderlo Kerley, Inc.).” to acknowledge the legal trademark status of this fertilizer.

We apologize for this error.

Slope aspect is a significant terrain attribute influencing soil physical and chemical processes. Yet its impact on soil quality and erosion has rarely been studied on gently sloping farmlands. The objective was to evaluate the effects of slope aspect on soil quality and its response to soil erosion in the black soil region of northeast China, a temperate environment featuring gently sloping farmlands. Over a nearly north-south symmetric sloping farmland spanning ∼3500 m, fifteen soil physical and chemical properties were investigated at every 40 m, and an integrated soil quality index (SQI) was calculated combining principal component analysis and scoring functions. The mean annual erosion rate (ER) was estimated using the cesium-137 tracing technique. Compared to the south-facing slope, the north-facing slope possessed significantly lower pH and higher saturated hydraulic conductivity, sand content, and almost all the essential nutrient contents, therefore overall better soil quality (p < 0.05). No statistical difference was spotted in ER between the two slopes (p > 0.05); however, erosion was found to deteriorate soil quality via distinct pathways. On the north-facing slope, erosion affected SQI predominantly through its negative impact on soil organic carbon content and wet-aggregate stability, and conservation tillage practices were suggested. However, on the south-facing slope, the detrimental influence was primarily driven through the depletion of soil nutrient contents, particularly available phosphorus and total nitrogen, and contour tillage and hedgerows were strongly recommended. These findings hold important practical implications for agricultural management in temperate environments.

Clay nanoparticles (NPs) are recognized as natural soil amendments. However, the effects of different types of clay NPs and their application rates on the physical, chemical, and biological characteristics of soils, solute transport, and plant photosynthesis parameters have not been thoroughly investigated. This study focused on amending two soil textures—sandy loam and loam—by adding 3% nano clay. The original and amended soils were packed into soil columns to conduct cultivation experiments with quinoa (Chenopodium quinoa Willd) plants and displacement solute transport experiments. The goal of column experiments was to explore the impact of the nano clay amendment on the photosynthetic properties of quinoa plants and solute transport in soils. The results indicated that adding NPs to loam soil improved photosynthesis and stomatal conductance. Additionally, the introduction of nano clays reduced sub-stomatal CO₂ levels in the amended soils compared to the control soils. In sandy loam soil, both with and without cultivation, the addition of nano clay enhanced saturated hydraulic conductivity, dispersivity, and maximum chloride concentration when compared to the control. However, it also resulted in a decrease in immobile water content and a reduction in peak travel time. In loam soil, the application of nano clay—regardless of cultivation method—increased dispersivity and immobile water contents while reducing maximum chloride concentration. It simultaneously decreased hydraulic conductivity compared to control conditions and also increased it in some instances. This research demonstrates that the nano clay amendment significantly alters soil's physical and chemical properties, affecting solute transport and the photosynthetic parameters of the quinoa cultivar.

Extracellular enzymes play a key role in microbe-mediated organic matter decomposition in soils, and the efficiency of these enzymes in substrate decomposition depends on their mobility and specific activity in soils. In this work, we explored the influence of biochar adsorption on extracellular enzyme activity across a spectrum of environmental conditions, from simple to complex. Batch adsorption results showed that biochar adsorption of two hydrolytic enzymes—α-amylase and amyloglucosidase (AMG)—similarly decreases with pH and follows the Langmuir isotherm, suggesting electrostatic interaction between them. Activity of AMG and alkaline phosphatase (ALP), which belong to carbon and phosphorus cycling enzymes, was measured using a novel calorimetric method. The technique demonstrated advantages over conventional enzyme assays, such as in situ real-time measurement of reaction rate and the ability to identify potential interferences. The technique enabled the measurement of specific activity of biochar-adsorbed AMG, which ranged from 10% to 90% of that of free AMG. The effect of substrate adsorption on activity measurement was demonstrated through the examination of two substrates for ALP, which suggested the use of effective substrate concentration (instead of nominal concentration) in calculating enzyme activity kinetics. Soil column experiments showed that biochar amendment can affect the activity of AMG in starch hydrolysis through changing the mobility of AMG (and accessibility to substrate) and its specific activity. Results from this work improve our understanding of the effects of biochar adsorption on enzyme activity and suggest the need to appropriately interpret enzyme activity data and account for confounding processes.

Hydroxyapatite is an important phosphorus (P) sink in calcareous soils. The activity of carbonate in soil pore water, however, is often underestimated because soil respiration and solution-calcite equilibria could elevate CO₂(g) concentration much greater than 415 ppmv (i.e., pCO₂: ∼0.3 mm Hg). Thus far, the role of CO₂(g) or pCO₂ in the hydroxyapatite formation in calcareous soils has not been extensively investigated. Accordingly, the effects of CO₂ concentration (415, 8000, and 20,000 ppmv) on hydroxyapatite formation were investigated at pH 8 using experimental geochemistry and X-ray diffraction (XRD) analysis. XRD analyses showed the formation of hydroxyapatite under all CO₂ concentrations, but the extent of calcite formation increased with increasing CO₂ concentration. The formation of calcium (Ca) carbonate phosphate was also observed after 30 days under [CO₂(g)] up to 8000 ppmv. This is attributed to an increase in calcium carbonate formation. Scanning electron microscopy showed rounded hydroxyapatite particles. The variability of [CO₂(g)] in subsoils should be considered in the P cycle in calcareous soils.

Soybeans (Glycine max (L.) Merr.) are mainly grown in Brazil during the rainy season. However, there are typically periods of rainfall deficiency, which causes water-deficit stress to the crop. Plant growth-promoting rhizobacteria (PGPR) can help alleviate these stresses by inducing water deficit tolerance. The objective of this study was to evaluate the role of PGPR in enhancing soybean tolerance to water-deficit stress. Six PGPR isolates, two for induction of water-deficit tolerance (ESA 441, BRM 034008), two AIA-producing (Ab-V5, BRM 063574), and two phosphate solubilizing (BRM 063573, BRM 67205), and their combination were evaluated, for a total of 16 treatments. The experiment was conducted in a greenhouse using a randomized block design with three replicates. Effects were measured on gas exchange parameters (stomatal conductance, transpiration, internal CO₂ concentration, and photosynthetic rate), growth parameters (shoot dry weight, root dry weight, root length, root surface area, root diameter, and root volume), and yield components (pod weight, number of pods, number of grains, and grain weight). Co-inoculation significantly reduces the effects of water stress on gas exchange, plant growth, and productivity compared to single inoculation. Notable combinations, such as BRM 063574 + BRM 67205 + BRM 034008 and BRM 063574 + BRM 063573 + ESA 441, improved root and shoot growth under stress conditions. Yield components also improved with co-inoculations, with combinations such as BRM 063574 + BRM 67205 + ESA 441 showing the highest efficacy. These results suggest that specific PGPR co-inoculations can improve soybean resilience to water deficit stress and promote better growth and yield.

Mathematical models are used extensively to estimate soil pesticide leaching in regulatory risk assessments and are often solved numerically, which can obscure simple insights. We developed an analytical solution that highlights the role of the ratio of sorption to degradation in compound leaching, denoted as the sorption-extinction (S_e) coefficient. We extend the classic analytical work of Jury to derive a steady-state solution for pesticide concentrations as a function of soil depth considering nonlinear sorption. We consider degradation in the soil water and solid phases and transport driven by advection, diffusion, and dispersion. Nonlinear sorption was handled using the mathematical technique of asymptotic expansions. We compared the steady-state analytic solution with extended duration simulations of the European regulatory numerical model PEARL for all FOCUS scenarios (i.e., nine European regions). The analytic solution was consistent with the long-term PEARL results across most FOCUS scenarios, and the results show that for a fixed S_e coefficient, similar mean pesticide concentrations at the regulatory leaching depth (1 m) are obtained despite varying the sorption and degradation by an order of magnitude. This indicates that the S_e coefficient is a dominant component of mean leaching behavior rather than degradation or sorption alone. However, as the absolute value of degradation and sorption decreases, variability of the pesticide concentration increases. While we demonstrate the approach using the FOCUS scenarios weather and soil data, this method can be applied as a rapid and time-efficient predictive tool for any region with either highly or more scarcely parameterized soil/weather data.