Lime induced changes in the surface and soil solution chemistry of variable charge soils

The study was conducted to improve lime recommendations as well as to design better management practices for acidic grasslands of Appalachian region. These goals were achieved by two experiments. In the first experiment, the accuracy of lime predictions by quick tests were improved by accounting soil order and develop equation based lime correlations for acidic pasture soils of West Virginia. In order to achieve this objective, 26 surface soil samples (0--7.5 cm) from three most important soil orders for the state (Alfisols, Inceptisols, Ultisols) from each of the Major Land Resource Areas (MLRAs) in West Virginia with large proportions of pasture land were collected in cooperation with state soil scientists. Standard procedures for the determination of lime requirements by the Mehlich Buffer (MB), Adams-Evans Buffer (AEB) and Shoemaker-McLean-Pratt Single Buffer (SMPB) methods were used. Statistically significant improvements in lime recommendations for target pH 6.5 and 5.5 were achieved by accounting for soil order. Mehlich single buffer recommendations were better for Alfisols and Ultisols than for Entisols to achieve pH 6.5. Lime correlations were developed for all three chemical buffers by multiple regression where the independent variables were target pH and soil-buffer pH. The Adam-Evans buffer predicted lime rates better for target pH 5.5. Equation-based lime correlations were also developed for all three chemical buffers by multiple regressions where the independent variables are target pH and soil-buffer pH. The second experiment was conducted to quantify the critical growth factors such as water potential, pH, nitrogen, and phosphorus and their interactions to deduce a comprehensive prescription of site-specific management techniques to forage production in acidified hill land pastures of West Virginia. In order to achieve this objective, a pot experiment was set up with two water potentials, five pH levels, five N and P fertilizer rates were imposed on bluegrass (sole) and bluegrass + white clover mixture. The estimation of overall effects of these four factors showed that levels of water potential, pH, N fertilizer doses as well as their interactions significantly affected the bluegrass (sole) production (p\u3c0.05). In case of bluegrass and white clover mixture cropping system, all four factors (water potential, pH, N and P levels) and their interactions exhibited significant influence on dry matter yield as well as nutrient concentration in shoot tissue. Nutrient concentrations also showed a synergistic relationship among each other as well as with dry matter yield in both bluegrass and bluegrass + white clover mixture. Response yield function was determined using significant factors and their interactions for blue grass (sole) and blue grass and white clover mixture

Recovery of Iron Values from Iron Ore Slimes using Reagents

Mining wastes include waste generated during the extraction, beneficiation or processing of minerals like iron ore fines, slimes and tailings. Approximately 10–20% of the raw material is discarded as slimes in to slime ponds/tailing dams. Recovery of iron values from slimes result in economic benefit by utilization of waste as a resource and minimizes the threat to the environment. The iron ore slime is generally considered as waste due to its ultrafine nature and its processing limitations. The chemical analysis of the present iron ore slime is 34.75% Fe with 21.94% SiO 2 , and 14.4% Al 2 O 3 . This research work presents the route to size enlargement of slime using reagents and enrichment of iron values by various beneficiation techniques for the effective utilization of iron ore slime. Screen analysis revealed that 90% of the particles are smaller than 80.15 µm. In the present investigation, the recovery of lost iron values from iron ore slime waste was attempted using different beneficiation techniques like Enhanced gravity separation (EGS) Falcon concentrator, Gravity separation by Mineral separator and Vanner, and selective flocculation after treatment with various reagents. Mineral separator generated a concentrate assaying 46.3% Fe with 56.2% recovery using polyacrylamide flocculant at 90 sec collection time and similarly Vanner produced a concentrate assaying 54.5% Fe with a recovery of 41.6% using CMC. From selective flocculation studies, a concentrate assaying 45.3% Fe with 42.1 yield % was obtained using modified corn starch at a settling time of 5 min, as starch facilitates the selective adsorption on iron particles, which in turn leads to enhancement in selectivity and recovery

Text Mining for Effective Classification of Car Problem Severity Levels

This research proposes a machine-learning approach to enhance customer satisfaction in the automotive service industry by classifying the severity of car problems based on customer descriptions using the text-mining concept. Using a dataset of labeled car service problem statements, the study employs supervised classification models using text mining, emphasizing the decision tree model for its superior performance. The aim is to empower service centers to offer pre-diagnoses, fostering loyalty even for non-severe issues. The study contributes to the intersection of machine learning and automotive services, providing a more effective and customer-centric diagnostic approach

A review of determinants for dairy farmer decision making on manure management strategies in high-income countries

The global dairy sector is a major source of human nutrition and farmer livelihoods, while also generating manure, an important nutrient for crop production, but one that must be managed to minimize environmental risk. Manure management - manure handling, processing, storage and application - is an important part of managing a dairy system. Rising awareness of environmental stewardship is increasing for dairy production that meets multiple sustainability goals. Importantly, a large body of research has identified a suite of potential manure management strategies (MMS) that can contribute to reduced environmental impact, and in some cases, provide additional benefits for farmers and society. Despite this growing body of technical and agronomically-focused research, there has been far less research on farmer decision making and adoption of MMS. To explore this gap, we conduct a systematic literature review of peer-reviewed articles exploring the drivers of farmer adoption and decision making related to MMS. We focus on high-income countries, where MMS strategies are more diverse and often involve advanced technologies. We find 36 articles across Europe, the United States, and Canada and focus on four key areas associated with MMS practices: (1) farm size and structural characteristics associated with MMS adoption including the relationship of certain MMS to each other; (2) existing adoption of MMS practices; (3) socio-economic and regulatory factors associated with MMS adoption; and (4) individual information, attitudes, and demographics associated with MMS adoption. We identify and discuss three gaps in the existing literature: (1) a dearth of studies exploring farmer adoption of MMS, especially from certain highly productive milk regions; (2) a lack of comparative studies across multiple regions and/or across time to identify more direct casual pathways of decision making; and (3) technical and other feasibility needs for future MMS adoption. These suggest a clear pathway for future research to better understand the myriad factors that influence dairy farmer decision making as it relates to MMS

Nitrogen Rate and Landscape Impacts on Life Cycle Energy Use and Emissions from Switchgrass-derived Ethanol

Switchgrass-derived ethanol has been proposed as an alternative to fossil fuels to improve sustainability of the US energy sector. In this study, life cycle analysis (LCA) was used to estimate the environmental benefits of this fuel. To better define the LCA environmental impacts associated with fertilization rates and farm-landscape topography, results from a controlled experiment were analyzed. Data from switchgrass plots planted in 2008, consistently managed with three nitrogen rates (0, 56, and 112 kg N ha−1), two landscape positions (shoulder and footslope), and harvested annually (starting in 2009, the year after planting) through 2014 were used as input into the Greenhouse gases, Regulated Emissions and Energy use in transportation (GREET) model. Simulations determined nitrogen (N) rate and landscape impacts on the life cycle energy and emissions from switchgrass ethanol used in a passenger car as ethanol–gasoline blends (10% ethanol:E10, 85% ethanol:E85s). Results indicated that E85s may lead to lower fossil fuels use (58 to 77%), greenhouse gas (GHG) emissions (33 to 82%), and particulate matter (PM2.5) emissions (15 to 54%) in comparison with gasoline. However, volatile organic compounds (VOCs) and other criteria pollutants such as nitrogen oxides (NOx), particulate matter (PM10), and sulfur dioxides (SOx) were higher for E85s than those from gasoline. Nitrogen rate above 56 kg N ha−1 yielded no increased biomass production benefits; but did increase (up to twofold) GHG, VOCs, and criteria pollutants. Lower blend (E10) results were closely similar to those from gasoline. The landscape topography also influenced life cycle impacts. Biomass grown at the footslope of fertilized plots led to higher switchgrass biomass yield, lower GHG, VOCs, and criteria pollutants in comparison with those at the shoulder position. Results also showed that replacing switchgrass before maximum stand life (10–20 years.) can further reduce the energy and emissions reduction benefits

Differential Effects of Biochar on Soils Within an Eroded Field

Future uses of biochar will in part be dependent not only on the effects of biochar on soil processes but also on the availability and economics of biochar production. If pyrolysis for production of bio-oil and syngas becomes wide-spread, biochar as a by-product of bio-oil production will be widely available and relatively inexpensive compared to the production of biochar as primary product. Biochar produced as a by-product of optimized bio-oil production using regionally available feedstocks was examined for properties and for use as an amendment targeted to contrasting soils within an eroded field in an on-farm study initiated in 2013 at Brookings, South Dakota, USA. Three plant based biochar materials produced from carbon optimized gasification of corn stover (Zea mays L.), Ponderosa pine (Pinus ponderosa Lawson and C. Lawson) wood residue, and switchgrass (Panicum virgatum L.) were applied at a 1% (w/w) rate to a Maddock soil (Sandy, Mixed, Frigid Entic Hapludolls) located in an eroded upper landscape position and a Brookings soil (Fine-Silty, Mixed, Superactive, Frigid Pachic Hapludolls) located in a depositional landscape position. The cropping system within this agricultural landscape was a corn (Zea mays L.) and soybean (Glycine max L.) rotation. Biochar physical and chemical properties for each of the feedstocks were determined including pH, surface area, surface charge potential, C-distribution, ash content, macro and micro nutrient composition. Yields, nutrient content, and carbon isotope ratio measurements were made on the harvested seed. Soil physical properties measured included water retention, bulk density, and water infiltration from a ponded double ring infiltrometer. Laboratory studies were conducted to determine the effects of biochar on partitioning of nitrate and phosphorus at soil surface exchange complex and the extracellular enzymes activity of C and N cycles. Crop yields were increased only in the Maddock soil. Biochar interacted with each soil type to alter physical and chemical properties. However the pattern of interaction depended on soil and biochar typ

Identifying challenges and opportunities for improved nutrient management through U.S.D.A's Dairy Agroecosystem Working Group

Nutrient management is a priority of U.S. dairy farms, although specific concerns vary across regions and management systems. To elucidate challenges and opportunities to improving nutrient use efficiencies, the USDA’s Dairy Agroecosystems Working Group investigated 10 case studies of confinement (including open lots and free stall housing) and grazing operations in the seven major U.S. dairy producing states. Simulation modeling was carried out using the Integrated Farm Systems Model over 25 years of historic weather data. Dairies with a preference for importing feed and exporting manure, common for simulated dry lot dairies of the arid west, had lower nutrient use efficiencies at the farm gate than freestall and tie-stall dairies in humid climates. Phosphorus (P) use efficiencies ranged from 33 to 82% of imported P, while N use efficiencies were 25 to 50% of imported N. When viewed from a P budgeting perspective, environmental losses of P were generally negligible, especially from dry lot dairies. Opportunities for greater P use efficiency reside primarily in increasing on-farm feed production and reducing excess P in diets. In contrast with P, environmental losses of nitrogen (N) were 50 to 75% of annual farm N inputs. For dry lot dairies, the greatest potential for N conservation is associated with ammonia (NH3) control from housing, whereas for freestall and tie-stall operations, N conservation opportunities vary with soil and manure management system. Given that fertilizer expenses are equivalent to 2 to 6% of annual farm profits, cost incentives do exist to improve nutrient use efficiencies. However, augmenting on-farm feed production represents an even greater opportunity, especially on large operations with high animal unit densities

Nitrate retention and release by biochars produced from fast pyrolysis

Rajesh Chintala - Research Associate, Department of Plant Science at South Dakota State University, Brookings, SD. Agricultural activities have been implicated as a major source of nutrient ions such as nitrate to surface and ground water resources. There is a need to control the nitrate movement in soil to sustain soil and water quality. Batch experiments were conducted to evaluate the nitrate sorption potential and release by non-activiated and activated biochars produced from microwave pyrolysis using selected biomass feedstocks of corn stover (Zea mays L.), Ponderosa pine wood residue (Pinus ponderosa Lawson and C. Lawson), and switchgrass (Panicum virgatum L.). Surface characteristics including surface area and net surface charge have shown significant effects on nitrate sorption in biochars. Freundlich isotherms performed well to fit the nitrate sorption data of biochars. The first order model fit the nitrate desorption kinetics of biochars with a high coefficient of determination.Ope

Effect of Sample Size on the Performance of Ordinary Least Squares and Geographically Weighted Regression

A recently developed spatial analytical tool, Geographically Weighted Regression (GWR) was used to deal with spatial nonstationarity in modeling the crop residue yield potential for North Central region of the USA. Average of daily mean temperature and total precipitation of crop growing season were the explanatory variables. In this study, the model performance of Ordinary Least Squares (OLS) and GWR were compared in terms of coefficient of determination ( R2 ) and corrected Akaike Information Criterion (AICc). Moran’s I and Geary’s C were used to test the spatial autocorrelation of OLS and GWR residuals. The explanatory power of the models was assessed by approximate likelihood ratio test. Furthermore, the test of spatial heterogeneity of the GWR parameters was conducted by using data sets with small and large samples. The comparative study of R2 and AICc between the models showed that all the GWR models performed better than the analogous OLS models. Test of spatial autocorrelation of residuals revealed that the OLS residuals had higher degrees of spatial autocorrelation than the GWR residuals indicating that GWR mitigated the spatial autocorrelation of residuals. Results of the approximate likelihood ratio test showed that GWR models performed better than the OLS models suggesting that the OLS relationship was not constant across the space of interest. More importantly, it was demonstrated that the data set would have to be large enough for the individual parameters of GWR models to be spatially heterogeneous

Effective Utilization of Fly Ash, Iron Ore Slime and LD-Slag in Geopolymer Mortar

An attempt was made for the effective utilization of iron ore slime in making of geopolymer mortar along with other industrial wastes fly ash and LD-slag and achieved the appreciable compressive strength results with 8 M NaOH after 28 days at a curing period of 24 h at 55°C