Foam fractionation is an adsorptive-bubble separation method that, according to researchers, is a feasible technique for the separation and/or concentration of proteins. The foam fractionation of bovine serum albumin (BSA) in laboratory-scale foam fractionation columns (750 and 1250 mL) and the relationship between the two laboratory-scale columns and a pilot-scale column (5000 mL) were investigated. Recovery, enrichment, and performance factor values were experimentally determined with three different column volumes with varying pore sizes, gas superficial velocities, and, in the case of the 750 mL column, foam column height. As the pore size decreased, the amount of protein recovered from the dilute protein solution increased and the enrichment decreased. As the flow rate of the gas increased, the effect of the pore size decreased. For the three column volumes, the optimal column conditions were achieved with the largest pore size (145-174 micrometer) and an intermediate superficial gas velocity (7 mm/s). Increasing the foam column height increased the enrichment without sacrificing the recovery of the target protein. In the case of the largest pore size, the linear relationships between the recovery and the ratio of gas volume to initial liquid volume are parallel, such that the recovery in a pilot-scale column (5000 mL) can be predicted with the recovery found with a laboratory-scale column (750 or 1250 mL).

Image-processing techniques had been successfully used for determination of beef maturity scores in a prior study. Automated segmentation of the cartilage and bone areas of the thoracic vertebrae was necessary to make the technique practical. Eighty-three beef carcasses were used for imaging the thoracic vertebrae. Color and spatial features were used for image segmentation. The hue value of the HSL color system was effective in segmenting cartilage areas, while the a* value of the CIELab system gave good results for the bone areas. After applying morphological operations on both cartilage and bone areas, geometric properties of these areas were used to give the final segmented object. The results of this work contribute to an automated beef maturity grading system.

The 'selective far-infrared (FIR) heating concept was applied to inactivate spores of Aspergillus niger and Fusarium proliferatum in corn meal. The selective heating method proposed denatures protein constituents in the spectral range between 5.88 and 6.66 micrometer, demonstrating an enhanced (approximately 40% in 5 min heating) lethality, compared to normal infrared (IR) radiation. A thermal death kinetics model based on the dynamic temperature profile to predict survivors under time varying conditions was developed to validate the selective IR heating process. The proposed dynamic thermal death kinetics model concept can be extended to other inactivation process.

Studies conducted since the late 1970s have estimated the net energy value (NEV) of corn ethanol. However, variations in data and assumptions used among the studies have resulted in a wide range of estimates. This study identifies the factors causing this wide variation and develops a more consistent estimate. We conclude that the NEV of corn ethanol has been rising over time due to technological advances in ethanol conversion and increased efficiency in farm production. We show that corn ethanol is energy efficient, as indicated by an energy output:input ratio of 1.34 and 1.53 under a best-case scenario.

Zero tolerance of feces on the surfaces of meat and poultry carcasses during slaughter was established as a standard to minimize the likelihood of microbial pathogens. Microbial pathogens can be transmitted to humans by consumption of contaminated meat and poultry. Compliance with zero tolerance of feces in meat processing establishments is currently verified by visual observation. The objective of this study was to investigate the use of visible, near-infrared reflectance spectroscopy as a method to discriminate between uncontaminated poultry breast skin and feces, and to select key wavelengths for use in a hyperpspectral system. Feces (n = 102), uncontaminated poultry breast skin, and skin contaminated with fecal spots were analyzed from 400 to 950 nm. The spectra were reduced by principal component (PC) analysis. The first four PCs explained 99.8% of the spectral variation. PC 1 was primarily responsible for the separation of uncontaminated skin from feces and for the separation of uncontaminated skin from contaminated skin. A classification model was developed and evaluated to classify fecal-contaminated skin from the spectral data with a success rate of 95%. Key wavelengths were identified by intensity of loading weights at 628 nm for PC 1, 565 nm for PC 2, and 434 and 517 nm for PC 4. Discrimination was dependent on the spectral variation related to fecal color and myoglobin and/or hemoglobin content of the uncontaminated breast skin.

The quality of synthesized daily weather data directly affects the output of hydrological and agricultural response models. The objectives of this study were to evaluate the ability of the CLIGEN model to reproduce daily, monthly, and annual precipitation amounts, extremes, and internal storm patterns (i.e., storm duration, relative peak intensity, and time to peak) and to assess further the impact of generated storm patterns on WEPP runoff and erosion prediction. Four Oklahoma stations with more than 50 years of daily precipitation data and eight other sites across the U.S. with an average record of 10 years of measured storm patterns were used. Mean absolute relative errors for simulating daily, monthly, and annual precipitation across the four Oklahoma stations were 4.7%, 1.7%, and 1.5% for the means and 3.7%, 6.7%, and 15% for the standard deviations, respectively. Mean absolute relative errors for the all–time maxima of daily, monthly, and yearly precipitation were 17.7%, 8.9%, and 6.5%, respectively. Storm pattern generation, especially storm duration, was determined to need improvement for better prediction of runoff and soil erosion. The measured storm patterns showed positive linear correlations between precipitation, duration, and relative peak intensity, but little correlation was shown for generated storm patterns. The CLIGEN–generated durations were generally too long for small storms and too short for large storms. Inaccurate storm pattern generation led to WEPP prediction errors as high as 35% for average annual runoff and 47% for annual sediment yield on the test sites. To improve WEPP runoff and erosion prediction, storm duration generation should be reconsidered, and a distribution–free approach may be used to induce proper correlations between the input storm variables.

Traditional analysis of composting process dynamics has focused on changes in physical variables such as temperature, pH, and effluent gas composition. However, to better understand the effect and value of microbial inoculation for reducing process variability, it is necessary to employ techniques that allow for the measurement of changes in community composition. In this study, automated ribosomal intergenic spacer amplification (ARISA) analysis was performed to characterize the ability of inoculated microorganisms from primary effluent wastewater to persist during the initial stages of composting in micro-scale reactors. We found that while the initial microbial communities differed based on inoculation level, after 24 h the microbial community no longer resembled the initial community. In addition, the effect of inoculation was no longer apparent at this point. There was a clear relationship between the variability observed between physical process variables and the composition of the microbial communities. The largest source of variation was due to seasonal changes, suggesting that despite the addition of an inoculum, a source of inoculation that varies between reactor groups is not being controlled. It is hypothesized that this source of inoculation is either from the air being forced through the reactors or from sparsely populated microbial populations in the initial substrate that become active at different rates in different reactor groups. Furthermore, this analysis demonstrates that it is possible to employ a simple molecular technique to understand the effects of inoculation and process reproducibility in a traditional agricultural waste treatment bioprocess.

Three macroscopic root water uptake models (Molz-Remson, Feddes, and Selim-Iskandar) have been widely used in modeling water flow in soil-plant systems. In this article, we use evapotranspiration data and soil water content data obtained from lysimeter measurements and root distribution data obtained in a nearby wheat field to evaluate the accuracy of these root water uptake models in predicting the soil water content profiles in the winter wheat field. To account for the role of root distribution, we modified the Molz-Remson model and the Selim-Iskandar model with the Feddes reduction function, and the Feddes model with the root length density. These models, with and without modifications, were then individually incorporated into the soil water flow equations as a sink term. The flow equations were solved numerically with the measured evapotranspiration data as input, and the predicted soil water content profiles were compared with the measured profiles to evaluate the validity of the root water uptake models. The comparison showed that: (1) the average deviation of the Molz-Remson (linear version) model, the Feddes model, and the Selim-Iskandar model could reach as high as 25%, and the non-linear version of the Molz-Remson model performed slightly better, with an average deviation of 13%; (2) modifications made to the Molz-Remson models and the Selim-Iskandar model did not achieve any improvement in the model predictions, but the modified Feddes model significantly improved the prediction accuracy, reducing the average deviation to 5.6%.

The DRAINMOD computer model has been widely used for simulating the performance of subsurface drainage systems. The ADAPT model was created by merging components of DRAINMOD and GLEAMS and has evolved for over ten years, including the recent addition of soil freeze/thaw processes. DRAINMOD was also recently modified for soil freeze/thaw processes for application in cold climates. Computational time step, method of ET estimation, and soil freeze/thaw processes are examples of ways in which current versions of these models differ from one another. Previous comparisons of these models were made for warmer climates, before the addition of cold-climate hydrology to both models. The performances of DRAINMOD and ADAPT were compared for cold-climate conditions, calibrated using two years of observed data from a 23-ha farm field in southern Minnesota. Model performance was evaluated and compared for seasonal, monthly, daily, and event-based time scales and during snowmelt runoff periods. Observed data showed that 60% and 20% of annual subsurface drainage runoff occurred during the transition period between winter and spring (snowmelt period) in 1998 and 1999, respectively. DRAINMOD overpredicted drainage by 11% and 25% for these periods, and ADAPT's results were within 10% of observed values for the snowmelt periods. Both models performed well at simulating the number and timing of drainage events in both snowmelt and later-season periods. The models performed best on a cumulative basis over the 2-year simulation period, where DRAINMOD overpredicted cumulative subsurface drainage by 1.7%, and ADAPT underestimated cumulative drainage by 0.2%. The models diverged in their abilities to predict the largest daily drainage events: DRAINMOD overpredicted and ADAPT underpredicted these events. Substantially more effort was required to calibrate ADAPT because of the increased complexity of the model.

Several processes take place within vegetated buffer strips that affect their performance. To better understand these processes, a runoff study was conducted to evaluate vegetated buffer strips performance in reducing atrazine, metolachlor, and chlorpyrifos transport as affected by the drainage area to buffer strip area ratio. The simulated runoff water mixed with pesticide-treated soil was distributed onto six vegetated buffer strips, each 1.52 m wide × 20.12 m long, located downslope of the inflow distribution tank in a well established vegetated grassed waterway. These strips provided for three replications of two inflow rates designated as "drainage area/buffer strip area ratio treatments" of 15:1 and 30:1. Infiltration for the 15:1 treatment averaged 38.8% of the inflow volume, whereas it averaged 30.4% for the 30:1 treatment. Sediment retention efficiencies averaged 90.1% and 86.8% for the 15:1 and 30:1 treatments, respectively. Concentrations of atrazine and metolachlor associated with sediment outflows from the strips were larger than their respective inflow concentrations, while the results were opposite for chlorpyrifos. Concentrations in runoff water for both atrazine and metolachlor in outflow from the strips were smaller than the inflow concentrations; again, the results were opposite for chlorpyrifos. The 15:1 treatment retained an average of 52.5% of the total input of atrazine, 54.4% of metolachlor, and 83.1% of chlorpyrifos. Corresponding numbers for the 30:1 treatment were 46.8% for atrazine, 48.1% for metolachlor, and 76.9% for chlorpyrifos. Analysis of variance using the randomized block design showed that differences of percent retention of pesticide between treatments were not significant for any of the three pesticides at the 10% significance level. A lack of significant difference indicates either a need for more than three replications and/or larger area ratio treatments to be studied. The results of this study indicate that a 30:1 area ratio buffer strip could perform equally as well as a 15:1 area ratio buffer strip. Thus, less land would be required under buffer strips to get the desired results.