Rajesh Chintala

Effect of biochar on chemical properties of acidic soil

The effect of biochar addition on the chemical properties of acidic soil such as soil pH, electrical conductivity (EC), cation exchange capacity (CEC), and exchangeable acidity were investigated to determine the liming potential of biochars. This study was conducted by incubating acidic soil (clayey, smectitic, acid, mesic, shallow, Aridic Ustorthent) of pH < 4.80 with biochars for 165 days. The biochars were produced from two biomass feedstocks such as corn stover (Zea mays L.) and switchgrass (Panicum virgatum L.) using microwave pyrolysis (at 650°C). Corn stover biochar, switchgrass biochar, and lime (calcium carbonate) were applied at four rates (0, 52, 104, and 156 Mg ha−1) to acidic soil. Amendment type, application rate, and their interaction had significant effects (p < 0.05) on soil pH, EC, and CEC of acidic soil. Exchangeable acidity was significantly affected by amendment type. Application of corn stover biochar had shown a relatively larger increase in soil pH than switchgrass biochar at all application rates. The ameliorating effect of biochars on chemical properties of acidic soil was consistent with their chemical composition.

Molecular characterization of biochars and their influence on microbiological properties of soil.

The tentative connection between the biochar surface chemical properties and their influence on microbially mediated mineralization of C, N, and S with the help of enzymes is not well established. This study was designed to investigate the effect of different biomass conversion processes (microwave pyrolysis, carbon optimized gasification, and fast pyrolysis using electricity) on the composition and surface chemistry of biochar materials produced from corn stover (Zea mays L.), switchgrass (Panicum virgatum L.), and Ponderosa pine wood residue (Pinus ponderosa Lawson and C. Lawson) and determine the effect of biochars on mineralization of C, N, and S and associated soil enzymatic activities including esterase (fluorescein diacetate hydrolase, FDA), dehydrogenase (DHA), β-glucosidase (GLU), protease (PROT), and aryl sulfatase (ARSUL) in two different soils collected from footslope (Brookings) and crest (Maddock) positions of a landscape. Chemical properties of biochar materials produced from different batches of gasification process were fairly consistent. Biochar materials were found to be highly hydrophobic (low H/C values) with high aromaticity, irrespective of biomass feedstock and pyrolytic process. The short term incubation study showed that biochar had negative effects on microbial activity (FDA and DHA) and some enzymes including β-glucosidase and protease.

Long-term tillage and drainage influences on soil organic carbon dynamics, aggregate stability and corn yield

Abstract Labile pools of soil organic carbon (SOC) and nitrogen (N) are affecting the carbon (C) and N fluxes in the terrestrial soils, whereas long-term C and N storage is determined by the long-lived recalcitrant fractions. Tillage and subsurface drainage influences these pools; however, the effect of these systems on poorly drained soils may be different. Therefore, the present study was conducted on a field experiment, established at the Waterman Farm of the Ohio State University in 1994. Specific objectives of the study are to assess the influence of no-tillage (NT), chisel tillage (CT) with drainage (TD) and non-drainage (ND) management under a continuous corn (Zea mays L.) system on SOC, C fractions (heavy and light), and water stable aggregates (WSA). Data from this study showed that the SOC stock for the NT was 25, 37 and 32% higher for the 0–10, 10–20 and 40–60 cm depths, respectively, as compared to that under CT system. Tillage significantly influenced the light fraction (LF) and heavy fraction (HF) of carbon. The NT system increased LF and HF by 10 and 12%, respectively, compared to CT for the 0–10 cm depth. Eighteen years of NT management decreased soil bulk density and improved macroaggregates and mean weight diameter compared to that under CT system. Drainage impacts on soil parameters were negligible, and may be partially due to the reason that the corn-corn cropping system may not have sufficiently improved the soil properties between the two tillage systems. In general, drainage improved porosity and the corn yield. It can be concluded that NT with subsurface management improves SOC dynamics and promotes aggregation and corn yield as compared to that with CT system.

EFFECT OF SOIL WATER AND NUTRIENTS ON PRODUCTIVITY OF KENTUCKY BLUEGRASS SYSTEM IN ACIDIC SOILS

The grasslands of the Appalachian region spread over undulating terrain with high annual precipitation rate which causes a large variation in soil and nutrient factors like water potential (WP), pH, nitrogen (N) and phosphorus (P) levels. There is a need to understand these factors and their interactive effects to design precise agronomic practices for acidic grasslands to maximize production. A pot experiment was conducted with an objective to quantify the effects of WP, pH, N and P rates on herbage accumulation and nutrient recovery of Kentucky bluegrass (Poa pratensis L.) cropping system. Centrally rotatable composite design was applied to study the effects of two levels of WP and five levels each of pH, N, and P fertilizer additions in order to optimize bluegrass herbage mass (yield). WP, pH, and N were significant main effects, as were the interactions WP × pH, WP × N, and pH × N. The yield response function was derived from these four factors. The order of importance for these model parameters based on their effect on herbage accumulation was WP > N > WP × pH > pH >WP × N > pH × N. The optimum levels of WP, soil pH, N, and P rates were predicted for Kentucky bluegrass by using the response surface yield model of this pot study i.e., WP of −422 kPa to −166 kPa, 5.5–6.1 soil pH, 50–68 N mg kg−1, 36–40 P mg kg−1. Concentration (%) of nutrients like N, P, potassium (K), calcium (Ca), and magnesium (Mg) were determined to study the impact of WP, pH, N, and P factors and their interactions on plant nutrient recovery. Main effects like WP, pH, and N levels had significant influence on N and P concentration in plant tissue. K, Ca, and Mg concentrations in plant tissue were significantly affected by WP, pH and their interaction. The results of this greenhouse study imply the necessity to incorporate the information about the variation of soil and nutrient factors in designing precise agronomic practices to low productive acid reclaimed grasslands with undulating topography and high annual precipitation rate.

Optimization of Oxygen Parameters for Determination of Carbon and Nitrogen in Biochar Materials

Recently, there has been increased focus on biochar materials due to their ability to sequester carbon for long-term in soil. In the production of biochar or charcoal, plant biomass is heated in a low or no oxygen environment. This process results in a product with unique characteristics. But there is limited research on the standardization of methods for determining total carbon (C) and nitrogen (N) in the biochar materials whose properties vary by feedstock type and pyrolytic conditions. The objective of this study was to determine the oxygen dosing time (OT) and dose (OD) for total organic carbon (TC) and nitrogen (TN) analysis in biochar materials by dry combustion method (using Vario Max CNS analyzer). Central composite rotatable design was used to determine the effect of five levels of oxygen dosing time (OT) and dosing level (OD) on measurement of total carbon and total nitrogen in four types of plant originated biochars. OT and OD level interaction had significant impact on the measurement of TC and TN in all types of biochar materials. Optimum levels of OT and OD were determined as 103 to 110 sec and 180 to 232 ml/min, respectively.

Modeling the Effect of Temperature and Precipitation on Crop Residue Potential for the North Central Region of the United States

In an effort to advance fuel security in this era of increasing fuel demand and climate change, crop residue can play an important role by serving as an alternative source of biofuel feedstock. Crop grain yield and residue production are tied to the changing climate over regional and global scale. Precipitation and temperature are among the prime climate variables that drive agricultural production across the globe. This study was carried out to understand the effect of temperature and precipitation on spatial distribution of crop residue yield potential at regional scale. Spatial autoregressive models were fitted for county level crop residue yield potential (as a major potential biomass feedstock) in the north central region of the United States using daily mean temperature and total precipitation during the crop growing season. The results of this observational study found the linear increasing trend in crop residue yield potential in most of the states across north central region of USA. Crop residue potential was also identified to have significant spatial variability. The influences of temperature and precipitation on crop residue yield potential exhibited significant interactions. Positive interaction effects were observed in states including Iowa, North Dakota, and Wisconsin. Negative interaction effects of daily mean temperature and total precipitation were observed in states including Illinois and Indiana. These results emphasize that the availability of crop residues for biofuels feedstocks will be sensitive to climatic variability and that these sensitivities will vary geographically.

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.

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 ( 2 R ) 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 2 R 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.

Grouping Soils by Taxonomic Order to Improve Lime Recommendations

The success of a liming program is dependent upon the accuracy of the lime recommendation, which in turn depends on the quality of the underlying correlations and calibrations. Because of the expense, large-scale field calibration experiments are rarely conducted. The relatively low economic returns from pastures make it even more unlikely that a calibration experiment would be conducted, especially in West Virginia. Therefore, any improvements in lime recommendations have to be made from lime correlations. Moreover, it is unlikely that a single lime correlation can accurately identify appropriate lime rates for all soils. Hence, the objectives of this study were to improve the accuracy of lime recommendations by using quick tests that account for soil order and to develop lime correlations for acidic pasture soils of West Virginia. Twenty-five surface soil samples (0–7.5 cm) from the three major soil orders in the state (Alfisols, Inceptisols, Ultisols) were collected, most in cooperation with state soil scientists. Standard procedures for the determination of lime requirements by the Adams–Evans buffer (AEB), Mehlich single buffer (MB), and Shoemaker–McLean–Pratt single buffer methods (SMPB) were used. Statistically significant improvements in lime recommendations for target pH values of 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 AEB predicted lime rates better for target pH 5.5.

Soil and Crop Management for Sustainable Agriculture

Sustainable management systems have continuously been promoted as an alternative to conventional farming practices for improving soil health and crop yield. However, benefits of these systems largely depend on the type of soil and climatic conditions prevalent locally. Loss of fertile topsoil due to water, wind, or tillage erosion, or due to management practices such as over-tillage of fragile soils, and removal of too much residue, can lead to reduced soil organic carbon (SOC) content, degraded soil health, loss of soil resiliency, and lower crop productivity. Conservation practices have been promoted to improve SOC content. Some of these practices include: conservation tillage, cover crops, organic farming, grazing management, and manure management. These conservation practices are designed to maintain C in sufficient areas and improve C in deficient areas. Conservation tillage is one of several management practices for increasing SOC and improving soil health of agriculture lands. The no-till (NT) system, in general, improves SOC content which is a strong indicator of soil health and crop productivity and strongly influences various ecosystem services. In contrast, intensive tillage generally stimulates soil C losses through enhanced decomposition and erosion. However, contrasting results have been obtained by different researchers under a variety of environmental conditions. Many of these findings are incomplete because they are based on information collected from a single site and soil type and measured over a relatively short duration. Process-based models can be used to integrate and extend the findings from multiple empirically-based research studies to aid in the prediction of the effects of conservation practices on SOC and greenhouse gas emissions over long periods of time, under a variety of environmental conditions, and for exploring novel management strategies to improve SOC and mitigate greenhouse gas emissions. Literature collected from research conducted globally by different researchers have shown that conservation practices often are helpful in improving SOC content, reducing greenhouse gas emissions, and improving crop productivity. However, monitoring of these parameters should be considered over a longer duration under a variety of environmental conditions and integrated with process based models.