Showing papers in "Transactions of the ASABE in 2015"

Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria

Abstract: Performance measures (PMs) and corresponding performance evaluation criteria (PEC) are important aspects of calibrating and validating hydrologic and water quality models and should be updated with advances in modeling science. We synthesized PMs and PEC from a previous special collection, performed a meta-analysis of performance data reported in recent peer-reviewed literature for three widely published watershed-scale models (SWAT, HSPF, WARMF), and one field-scale model (ADAPT), and provided guidelines for model performance evaluation. Based on the synthesis, meta-analysis, and personal modeling experiences, we recommend coefficient of determination (R2; in conjunction with gradient and intercept of the corresponding regression line), Nash Sutcliffe efficiency (NSE), index of agreement (d), root mean square error (RMSE; alongside the ratio of RMSE and standard deviation of measured data, RSR), percent bias (PBIAS), and several graphical PMs to evaluate model performance. We recommend that model performance can be judged satisfactory for flow simulations if monthly R2 0.70 and d 0.75 for field-scale models, and daily, monthly, or annual R2 0.60, NSE 0.50, and PBIAS ≤ ±15% for watershed-scale models. Model performance at the watershed scale can be evaluated as satisfactory if monthly R2 0.40 and NSE 0.45 and daily, monthly, or annual PBIAS ≤ ±20% for sediment; monthly R20.40 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for phosphorus (P); and monthly R2 0.30 and NSE 0.35 and daily, monthly, or annual PBIAS ≤ ±30% for nitrogen (N). For RSR, we recommend that previously published PEC be used as detailed in this article. We also recommend that these PEC be used primarily for the four models for which there were adequate data, and used only with caution for other models. These PEC can be adjusted within acceptable bounds based on additional considerations, such as quality and quantity of available measured data, spatial and temporal scales, and project scope and magnitude, and updated based on the framework presented herein. This initial meta-analysis sets the stage for more comprehensive meta-analysis to revise PEC as new PMs and more data become available.

A Recommended Calibration and Validation Strategy for Hydrologic and Water Quality Models

Abstract: . Hydrologic and water quality (H/WQ) models are widely used to support site-specific environmental assessment, design, planning, and decision making. Calibration and validation (C/V) are fundamental processes used to demonstrate that an H/WQ model can produce suitable results in a particular application. However, the lack of comprehensive guidelines has led to the use of ad hoc, inconsistent, and incomplete C/V processes, which have made it difficult to interpret the myriad of published modeling studies, reduced the utility of many modeling applications, and slowed the advancement of H/WQ modeling. The objective of this article is to provide a generalized structure and process to assist modelers in developing a C/V strategy for H/WQ modeling applications. These best practice recommendations were developed based on an expansive review of the modeling literature, including a special collection of articles on H/WQ model calibration, validation, and use, as well as extensive discussion and debate among the authors. The model C/V recommendations include careful consideration, execution, and documentation of the following elements: (1) goals of model use, (2) data and parameters used in C/V, and (3) model C/V processes. Considerations in element 3 include the warm-up period, C/V strategy complexity, C/V process staging, spatiotemporal allocation of C/V comparison data, manual vs. automatic C/V, and additional diagnostics. Notable examples from the literature are provided for each strategy element. The comprehensive C/V strategy described herein will allow for better interpretation of future modeling studies, improved utility of modeling applications, and more systematic advancement of H/WQ models.

Hydrological Processes and Model Representation: Impact of Soft Data on Calibration

Abstract: Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration and validation procedures or guidelines, a special collection of 22 research articles that present and discuss calibration strategies for 25 hydrologic and water quality models was previously assembled. The models vary in scale temporally as well as spatially from point source to the watershed level. One suggestion for future work was to synthesize relevant information from this special collection and to identify significant calibration and validation topics. The objective of this article is to discuss the importance of accurate representation of model processes and its impact on calibration and scenario analysis using the information from these 22 research articles and other relevant literature. Models are divided into three categories: (1) flow, heat, and solute transport, (2) field scale, and (3) watershed scale. Processes simulated by models in each category are reviewed and discussed. In this article, model case studies are used to illustrate situations in which a model can show excellent statistical agreement with measured stream gauge data, while misrepresented processes (water balance, nutrient balance, sediment source/sinks) within a field or watershed can cause errors when running management scenarios. These errors may be amplified at the watershed scale where additional sources and transport processes are simulated. To account for processes in calibration, a diagnostic approach is recommended using both hard and soft data. The diagnostic approach looks at signature patterns of behavior of model outputs to determine which processes, and thus parameters representing them, need further adjustment during calibration. This overcomes the weaknesses of traditional regression-based calibration by discriminating between multiple processes within a budget. Hard data are defined as long-term, measured time series, typically at a point within a watershed. Soft data are defined as information on individual processes within a budget that may not be directly measured within the study area, may be just an average annual estimate, and may entail considerable uncertainty. The advantage of developing soft data sets for calibration is that they require a basic understanding of processes (water, sediment, nutrient, and carbon budgets) within the spatial area being modeled and constrain the calibration.

Threshold Effects in HRU Definition ofthe Soil and Water Assessment Tool

Abstract: The Soil and Water Assessment Tool (SWAT) uses hydrologic response units (HRUs) as the basic unit of all model calculations. ArcSWAT, the ArcGIS interface for SWAT, allows users to specify thresholds of land cover, soil, and slope in defining HRUs to improve the computational efficiency of simulations while keeping key landscape features of a watershed in the hydrologic modeling. However, this study found that applying commonly used thresholds in defining HRUs may lead to considerable loss of information about the watershed landscape, emphasizing larger soil types on smaller land covers once the land covers meet a threshold for land cover, and potentially changing average slopes. These changes often have a minor effect on water yield and streamflow simulations by SWAT but a larger effect on sediment and nutrient load simulations, which are more sensitive to slope and soil type and are more influential on outputs at the subwatershed than at the watershed outlet. Study results can help modelers improve their understanding of the HRU strategy for simplifying watershed representation while maintaining major landscape features and make decisions in the HRU delineation process to minimize the chance of biased simulations.

The Potential of Controlled Traffic Farming to Mitigate Greenhouse Gas Emissions and Enhance Carbon Sequestration in Arable Land: A Critical Review

Abstract: The drive toward adoption of conservation agriculture to reduce costs and increase production sustainably causes concern due to the potentially negative effects of increased soil compaction Soil compaction reduces aeration, water infiltration, and saturated hydraulic conductivity and increases the risk of waterlogging Controlled traffic farming (CTF) is a system in which: (1) all machinery has the same or modular working and track width so that field traffic can be confined to the least possible area of permanent traffic lanes, (2) all machinery is capable of precise guidance along those permanent traffic lanes, and (3) the layout of the permanent traffic lanes is designed to optimize surface drainage and logistics Without CTF, varying equipment operating and track widths translate into random traffic patterns, which can cover up to 85% of the cultivated field area each time a crop is produced Nitrous oxide (N2O) is the greatest contributor to agriculture's greenhouse gas (GHG) emissions from cropping, and research suggests that its production increases significantly under conditions of high (>60%) water-filled porosity when nitrate (mainly from fertilizer N) and carbon (usually from crop residues) are available Self-amelioration of soils affected by compaction occurs slowly from the surface downward; however, the rate of amelioration decreases with increase in depth Consequently, all soils in non-CTF systems in mechanized agriculture are prone to some degree of compaction, which compromises water infiltration, increases the frequency and duration of waterlogged conditions, reduces gaseous exchange between soil and the atmosphere, inhibits root penetration and exploitation of nutrients and water in the subsoil, and enhances N2O emissions Adoption of CTF increases soil porosity in the range of 5% to 70%, water infiltration by a factor of 4, and saturated hydraulic conductivity by a factor of 2 The greater cropping opportunity and enhanced crop growth for given fertilizer and rainfall inputs offered by CTF, coupled with no-tillage, provide potential for enhanced soil carbon sequestration Reduced need and intensity of tillage, where compaction is avoided, also helps protect soil organic matter in stable aggregates, which may otherwise be exposed and oxidized There is both circumstantial and direct evidence to suggest that improved soil structural conditions and aeration offered by CTF can reduce N2O emissions by 20% to 50% compared with non-CTF It is not compaction per se that increases the risk of N2O emissions but rather the increased risk of waterlogging and increase in water-filled pore space There may be an elevated risk of GHG emissions from the relatively small area of permanent traffic lanes (typically <20% of total cultivated area) if these are not managed appropriately Quantification of the benefits of compaction avoidance in terms of GHG emissions may be possible through the use of well-developed models

Uncertainty Considerations in Calibration and Validation of Hydrologic and Water Quality Models

Abstract: . Hydrologic and water quality models (HWQMs) are increasingly used to support decisions on various environmental issues and policy directions for present and future scenarios, at scales varying from watershed to continental levels. Uncertainty associated with such models may affect the ability of the models to accurately evaluate the response of complex systems, leading to misguided assessments and risk management decisions. Current well-known HWQMs contain numerous input parameters, many of which are not known with certainty, and in other cases model users can hardly recognize the genesis of uncertainty. Uncertainty in data, model structure, and model parameters can propagate throughout model runs, causing the model output to substantially deviate from the expected response of the natural system. Various uncertainty assessment methods have been used with different HWQMs, creating concerns about an adequate approach for handling uncertainty in these models and how such an approach can be implemented across various discretization complexities and scales. In this article, our primary intention is to review uncertainty in the currently used HWQMs and to provide guidance and useful information for researchers and investigators. In this regard, we explore the genesis of uncertainty in hydrologic and water quality modeling (i.e., spatiotemporal scales, model representation, model discretization, model parameterization) and provide strategies for assessing uncertainty in hydrologic and water quality modeling on local and global scales when interpreting the model output.

Hydrologic and Water Quality Models: Key Calibration and Validation Topics

Abstract: As a continuation of efforts to provide a common background and platform for development of calibration and validation (C/V) guidelines for hydrologic and water quality (H/WQ) modeling, ASABE members worked to determine critical topics related to model C/V, perform a synthesis of a previously published special collection of articles and other relevant literature, and provide topic-specific recommendations based on the synthesis as well as personal modeling expertise. This article introduces a special collection of nine research articles covering key topics related to calibration and validation of H/WQ models. The topics include: terminology, hydrologic processes and model representation, spatial and temporal scales, model parameterization, C/V strategies, sensitivity, uncertainty, performance measures and criteria, and documentation and reporting. The main objective of this introductory article is to introduce and summarize key aspects of these topics, including recommendations. Individually, the articles provide model practitioners with detailed topic-specific recommendations related to model calibration, validation, and use. Collectively, the articles present recommendations to enhance H/WQ modeling.

Parameterization Guidelines and Considerations for Hydrologic Models

Abstract: . Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) are important and difficult tasks. An exponential increase in the literature has been devoted to the use and development of these models over the years. Few articles, however, have been devoted to developing general parameterization guidelines to assist in hydrologic model application, which is the main objective of this article along with discussing a few important parameters and extracting several case studies from the literature. The following guidelines were extracted from reviewing a special collection of 22 articles along with other relevant literature: (1) use site-specific measured or estimated parameter values where possible, (2) focus on the most uncertain and sensitive parameters, (3) minimize the number of optimized parameters, (4) constrain parameter values to within justified ranges, (5) use multiple criteria to help optimize parameter values, (6) use “soft” data to optimize parameters, and (7) use a warm-up period to reduce model dependence on initial condition state variables. A few soil and hydrology related parameters common to many models are briefly described along with a discussion of measurement and estimation methods and parameter sensitivity (curve number, Manning‘s “n”, soil bulk density and porosity, soil hydraulic conductivity, soil field capacity and wilting point, and leaf area index). Weather and management inputs are also discussed, as they are critical hydrologic system information that must be imparted to the model. Several case studies from previously reported research illustrate implementation of the parameterization guidelines. This research will help improve model parameterization, resulting in more consistency, better representation of the field or watershed, and a reduced range of parameter value sets resulting in acceptable model simulations.

Hydrologic and water quality modeling: Spatial and temporal considerations

Abstract: Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Water-related issues are investigated over a range of scales, i.e., the extent and resolution of the spatial and temporal contexts, which can vary spatially from point to watershed and temporally from seconds to centuries. In addition, models‘ formulations may place scale restrictions on their use. In 2012, ASABE published a collection of 22 articles on the calibration, validation, and use of 25 hydrologic and water quality models. Each article detailed the process to follow and the issues that could arise during calibration or application of a specific model. The objective of this article is to synthesize those articles with regard to common spatial and temporal scale principles that should guide selecting, parameterizing, and calibrating a hydrologic model. This article describes how the spatio-temporal extent and resolution of a model application should relate to the modeling objectives, the processes simulated, the parameterization and calibration process, data available for parameterization and calibration, and interpretation of results. Overall, the intended scale of the model should match the scale of the processes that need to be simulated given the modeling objectives, the scale of input and calibration data should be compatible with the scale of the model and with the objectives of the study, and the model should be calibrated at the scale at which the results will be analyzed and interpreted.

Evaluation of the CSM-CROPGRO-Cotton Model for the Texas Rolling Plains Region and Simulation of Deficit Irrigation Strategies for Increasing Water Use Efficiency

Abstract: . Cotton is one of the major crops cultivated in the Texas Rolling Plains region, and it is a major contributor to the regional economy. Cotton cultivation in this region is facing severe challenges due to an increase in the frequency of droughts and a projected decrease in rainfall in the future. Development and evaluation of deficit irrigation strategies for this region could potentially conserve water while maintaining cotton yields. In this study, the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM) CROPGRO-Cotton was extensively tested and then used for evaluating various deficit irrigation strategies for this region. The model inputs were obtained from field experiments conducted at Chillicothe, Texas, during four growing seasons: 2008-2010 and 2012. The model was first calibrated using the data from a 100% evapotranspiration (ET) replacement irrigation scheduling experiment conducted in 2012 and then validated on three other irrigation scheduling treatments (75% ET replacement, soil moisture based, and tensiometer based) conducted in the same year. The model was further evaluated using the data from cotton tillage and irrigation experiments conducted in an adjacent field during 2008-2010. The model calibration, validation, and evaluation results were satisfactory except under dry conditions (0% ET replacement and 33% ET replacement). Simulated maximum seed cotton yields under normal and dry weather conditions were achieved at 100% and 110% ET replacement, respectively. Percentage decrease in seed cotton yield was marginal (3.5% to 8.8%) when the amount of irrigation water applied was decreased from 100% to 66% ET replacement under normal rainfall conditions. However, under less than normal rainfall (drier) conditions, the percentage decrease in seed cotton yield was substantial (about 17.5%) when the irrigation strategy was switched from 100% to 70% ET replacement. The simulations demonstrate that adopting deficit irrigation practices under normal weather conditions can conserve water without adversely affecting seed cotton yields. However, under dry conditions, there is a risk of increased yield loss, and therefore producers should consider that risk when adopting deficit irrigation strategies.

Hyperspectral Microscope Imaging Methods to Classify Gram-Positive and Gram-Negative Foodborne Pathogenic Bacteria

Abstract: . An acousto-optic tunable filter (AOTF)-based hyperspectral microscope imaging (HMI) method has potential for rapid identification of foodborne pathogenic bacteria from micro-colonies with a cell level. In this study, we successfully developed a method to acquire quality hyperspectral microscopic images from various gram-negative and gram-positive bacteria live cells. Among the contiguous spectral images from the visible/NIR region between 450 and 800 nm, the scattering intensity of spectral images was distinct at mostly visible wavelengths. Specifically, the scattering peak intensity was distinct at 458, 498, 522, 546, 574, 590, 646, 670, and 690 nm for Staphylococcus. Similarly, distinct peak spectra were observed at 462, 498, 522, 546, 574, 598, 642, 670, and 690 nm for Salmonella. For both cases, the scattering intensity of outer cell membranes was brighter than that of inner membranes except at 546 nm, which was possibly caused by excitation of the metal-halide lighting source. The scattering intensity from a single cell varied with the wavelength as well as the type of bacteria. The overall variability of intensity was 31.2% for gram-negative (Salmonella) and 42.7% for gram-positive (Staphylococcus) bacteria. With scattering intensity data from five serotypes of Salmonella (Kentucky, Enteritidis, Typhimurium, Infantis, and Heidelberg) and five species of Staphylococcus (aureus, haemolyticus, hyicus, simulans, and sciuri) bacterial cells, a classification accuracy of 99.9% with a kappa coefficient of 0.9998 was obtained from the support vector machine (SVM) classification algorithm.

Hydrologic and Water Quality Models: Sensitivity

Abstract: . This article is part of a collection of articles that provides a comprehensive description of hydrologic and water quality (H/WQ) model calibration and validation concepts and processes. Sensitivity analysis (SA), which is often used to quantify the strength of relationships between model inputs and outputs, is an essential evaluation of any kind of modeling. SA is crucial in H/WQ models due to various aspects involved in H/WQ modeling processes, such as empiricism, spatiotemporal scales, and complexity, that require an assessment of parameters‘ influence on the model‘s prediction. This study synthesized SA applications for 25 H/WQ models in the special collection on model use, calibration, and validation published in 2012 and provides guidance on their future applications. Commonly used SA methods are summarized along with tools to implement them. While SA was not employed for all 25 models in the special collection, a wide range of SA methods (from partial derivatives to variance-based global methods) and sensitivity measures (from scatter plots to variance decomposition measures) were used in the literature. Some model parameters were found to be important in most sensitivity applications performed for the models; however, their relative importance varied from study to study, underscoring the necessity of SA for every new model application. Nevertheless, summarizing important model parameters can still serve as a starting point for model users. Since most studies concentrated on model parameters alone; future SA applications in H/WQ modeling should also consider other inputs (climate data, boundary conditions, etc.) and non-parametric aspects, such as features and processes considered in the model.

Water Repellency of Two Forest Soils after Biochar Addition

Abstract: . Practical application of black carbon (biochar) to improve forest soil may be limited because biochar is hydrophobic. In a laboratory, we tested the water repellency of biochar application (mixed or surface applied) to two forest soils of varying texture (a granitic coarse-textured Inceptisol and an ash cap fine-textured Andisol) at four different application rates (0, 1, 5, and 10 Mg ha -1 ) and five soil moisture contents (0%, 25%, 50%, 75%, and 100% of saturation). To address the impact of biochar on water infiltration into the soil, we measured soil water repellency using three methods (tension infiltrometer, water drop penetration, and molarity of ethanol). Generally, all three infiltration methods gave similar results. Compared to the unamended coarse-textured Inceptisol at 0% saturation (oven dry), biochar mixed into the soil at the rate of 5 Mg ha -1 did not result in a significant change (p ≤ 0.05) in infiltration rate. The fine-textured Andisol soil at 0% saturation did not show a significant change in infiltration at the application rate of 1 Mg ha -1 when biochar was mixed into the soil. Surface applications of biochar on both soil textures resulted in less water infiltration than the mixing treatments. Our results suggest that biochar decreases infiltration rates less on coarse-textured forest soils as compared to finer-textured soils, and 1 to 5 Mg ha -1 will likely not detrimentally alter water infiltration rates.

Measurement Methods for Optical Absorption and Scattering Properties of Fruits and Vegetables

Abstract: Quality evaluation of fruits and vegetables based on visible and near-infrared (Vis-NIR) spectroscopy has been investigated by many research groups worldwide during the last two decades. However, conventional Vis-NIR spectroscopy approximately measures the aggregate effect of absorption and scattering in fruits and vegetables without being able to separate them from each other. Optical property measurement, as an important means for analyzing or quantifying light scattering and propagation, would decouple and obtain absorption and scattering properties simultaneously. This article first gives a brief introduction to tissue optical properties, followed by a description of light transfer models. It also reviews recent developments of methods for measuring optical absorption and scattering properties of fruits and vegetables. Due to the complexity, diversity, and inhomogeneity of fruits and vegetables, major obstacles still exist for accurate measurement of the optical properties of fruits and vegetables composed of homogeneous or uniform layers. Furthermore, standard model samples with known optical properties, improved instrumentation, and better models for photon migration are needed for optical property measurement of fruits and vegetables. Research in the measurement and application of optical properties of fruits and vegetables is expected to grow in the future.

Feasibility of using PFC3D to simulate soil flow resulting from a simple soil-engaging tool.

Abstract: . PFC 3D is a discrete element modeling tool that has been used for simulations of soil-tool interaction in agriculture. However, existing studies have mainly focused on simulations of soil cutting forces, not soil flow. In this study, a soil-tool model was developed using the parallel bond model (PBM) of PFC 3D to determine if the model could be used to simulate the soil flow characteristics resulting from a simple soil-engaging tool while satisfying the draft force prediction accuracy. In the simulations, soil was modeled as spherical particles with bonds between particles. The model outputs examined were the two most important soil dynamic properties: thrown-soil and draft force. By examining the effects of model microproperties on the simulated thrown-soil and draft force, we found that the feasible ranges of the model microproperties were: 1e4 to 5e6 Pa for the modulus of elasticity of particle, 1e5 to 1e8 Pa for the modulus of elasticity of bond, 1e4 to 1e5 Pa for bond strength, 0.3 to 0.7 for local damping coefficient, and 0 to 1.0 for viscous damping coefficient. For simulation of soil-tool interactions, the model microproperties should be selected within these feasible ranges. Otherwise, the behavior of the model particles would not reflect the behavior of real soil. Within these feasible ranges, the model outputs were influenced the most by the modulus of particle elasticity; the other model microproperties had little impact on the model outputs. Soil cutting tests were conducted in a sandy loam soil to evaluate the soil-tool model. The results showed that a modulus of particle elasticity of 2.5e5 Pa resulted in a good match between the simulated and measured draft forces. However, with this modulus, the simulated thrown-soil was significantly lower than the measured value. Further investigations showed that it may not be possible to match the simulated and measured thrown-soil using the PBM of PFC 3D . Therefore, redefining the constitutive laws of particle contacts would be required to improve the accuracy of the model for simulations of soil flow behavior.

A Fluorescent Aptasensor Coupled with Nanobead-Based Immunomagnetic Separation for Simultaneous Detection of Four Foodborne Pathogenic Bacteria

Abstract: . There is a growing need for rapid detection of multiple foodborne pathogens. The objective of this study was to develop an aptasensor for rapid, sensitive, specific, quantitative, and simultaneous detection of Escherichia coli O157:H7, Staphylococcus aureus, Listeria monocytogenes, and Salmonella Typhimurium in food using magnetic nanobeads (MNBs) for separation and quantum dots (QDs) as fluorescence reporters. Streptavidin-coated 25 nm MNBs, conjugated with four corresponding biotin-labeled antibodies, respectively, were used to simultaneously capture and magnetically separate four bacterial pathogens from the food matrix in 45 min. Streptavidin-coated QDs with emission wavelengths of 528, 572, 621, and 668 nm, conjugated with four corresponding biotin-labeled aptamers, were used to label the separated MNB-cell complexes. The fluorescence intensities of all reporting QDs in the MNB-cell-QD complexes were measured simultaneously with a portable spectrometer for quantitation of four different types of bacterial cells. SEM and confocal microscopy were used for characterization of the binding between nanobeads, QDs, and bacterial cells, and a simulation model was used to analyze the magnetic separation. Results showed that the capture efficiencies of antibodies with 25 nm MNBs were 90.4%, 87.5%, 92.0%, and 92.0% for E. coli O157:H7, S. aureus, L. monocytogenes, and S. Typhimurium, respectively. The limits of detection for E. coli O157:H7, S. aureus, L. monocytogenes, and S. Typhimurium were 80, 100, 47, and 160 CFU mL -1 , respectively, in pure culture and 320, 350, 110, and 750 CFU mL -1 , respectively, in ground beef. The developed aptasensor was capable of simultaneously detecting four bacteria within 2.5 h in a broad range of 10 1 to 10 4 CFU mL -1 , showing great potential for multiplex detection of other foodborne pathogens.

Performance Analysis of Capacitance and Electrical Resistance-Type Soil Moisture Sensors in a Silt Loam Soil

Abstract: The performance of the Irrometer 200SS Watermark granular matrix sensor (WM), John Deere Field Connect (JD-v2) probe, and Delta-T PR1-capacitance (PR1-C) probe were evaluated against a Troxler 4302 neutron gauge (NG) for in-season field volumetric water content (θv) measurements at two soil depths in a Hastings silt loam soil at the University of Nebraska-Lincoln/Institute of Agriculture and Natural Resources South Central Agricultural Laboratory (SCAL) near Clay Center, Nebraska. The performances of the sensors were investigated over three years (2011-2013) under various water, nutrient, and crop management practices. The WM sensors performed best when using a field-calibrated soil water retention curve (SWRC) [root mean square difference (RMSD) = 0.024 m3 m-3] as compared to a SWRC developed from a pedotransfer function (RMSD = 0.070 m3 m-3). The WM sensors using a previously developed SWRC for the experimental field resulted in RMSD values less than 0.05 m3 m-3 when compared to the NG-measured θv at all depths and years. The JD-v2 probes underestimated θv in the dry range and overestimated θv in the wet range, which resulted in regression slopes and intercepts for the 0.30 and 1.0 m soil depths that were significantly different from unity (i.e., 1.0) and zero (p0.05

A Semi-Automated Harvesting Prototype for Shaking Fruit Tree Limbs

Abstract: Mechanizing the fruit removal operation during fresh-market apple harvesting is essential for labor and cost savings for fruit growers. This study introduces a semi-automated mechanical fruit harvesting system that uses a fruit removal technique based a unique limb shaking mechanism called a dual motor actuator (DMA). The harvesting system was tested on ‘Gala‘ apples grown in a formally trained fruiting wall orchard. A manipulator arm, positioned by a human, held a fruit catchframe and an end-effector. The system was mounted on a mobile orchard platform. The DMA was developed as an infinitely variable pattern end-effector that applies rhythmic motions to a fruiting limb to remove fruit. The novelty of the DMA design is the use of two eccentrics mounted to electric motors that are pinned together to form a triangle with an adjustable base. Pattern, rhythm, and actuation time were varied to characterize the removal efficiency and fruit damage percentages. Removal efficiency averaged only 35% across the fruiting limb but increased to 88% within the actuation zone of the fruiting section, showing the potential of a semi-selective harvesting technique for localized fruit removal on branches trained to trellis wires. A circular pattern using a 200 cycles min-1 rhythm achieved the lowest overall damage (10%) of all combinations of the patterns and rhythms tested. Bruise percentage was also lowest (4%) using the same pattern and rhythm. Rhythm and actuation time were significant factors that influenced the fruit removal condition. No fruit was removed outside of the targeted actuation zone when using a single limb grasper. This localized limb actuation method shows great potential for removing apples from a limb while maintaining fresh-market quality fruit.

A Method for Three-Dimensional Reconstruction of Apple Trees for Automated Pruning

Abstract: Labor cost and availability have been a major concern for tree fruit growers, as many field operations, including tree pruning, are highly labor intensive. Currently, pruning in apple production is primarily a manual operation. However, newer orchards are being planted in simple, narrow, accessible, and productive (SNAP) architectures such as the tall spindle fruiting wall system, which provides opportunities for automated pruning. This technical note presents a method to obtain the 3D structures of apple trees and identify branches as a first step toward developing an automated pruning system. A time-of-flight-of-light-based three-dimensional (ToF 3D) camera is used to obtain 3D images of apple trees in a commercial orchard. The images are preprocessed to remove noise and fill unwanted voids. The preprocessed images are then used to generate tree skeletons using a medial axis thinning algorithm. Tree skeletons are analyzed to detect trunks and identify branches. This method successfully reconstructed 3D structures of apple trees with 100% accuracy in detecting trunks. The method achieved a branch identification accuracy of 77%, with a false negative identification of 23%. This work provides a promising method for 3D reconstruction of apple trees that can be used to generate a database of tree branches including branch length and interbranch spacing, which is critical information for developing a system for automated pruning.

Automated Lettuce Nutrient Solution Management Using an Array of Ion-Selective Electrodes

Abstract: Automated sensing and control of macronutrients in hydroponic solutions would allow more efficient management of nutrients for crop growth in closed systems. This article describes the development and evaluation of a computer-controlled nutrient management system with an array of ion-selective electrodes (ISEs) and fertilizer pumps that could effectively manage concentrations of NO3, K, and Ca ions in closed hydroponic systems. A fertilizer dosing algorithm was developed to calculate the volumes of individual nutrient stock solutions to be supplied based on the measurement of present concentrations in a mixing tank. In a five-step spiking test, the system was able to formulate five different concentrations of NO3 and Ca ions comparable to the target concentrations, showing almost 1:1 relationships between the actual and target values. However, actual K concentrations were prepared almost 40% higher than target concentrations due to low K estimates. The use of a two-point normalization method in conjunction with ISEs was effective in minimizing signal drifts resulting from in-line measurement of ion concentrations in the closed system. The automated nutrient management system was used to grow lettuce in a greenhouse with the ebb and flow method. After water was automatically added to the mixing tank to maintain the level of water within 10% of the total volume of the tank, the amounts of three different salts, i.e., KNO3, KH2PO4, and Ca(NO3)2, were variably supplied to the mixing tank based on real-time measurement of concentrations. The three ions were automatically controlled to reach target concentrations of 280, 140, and 70 mg L-1 within errors of -7.7 ±28.1, 20.8 ±28.5, and -5.6 ±8.2 mg L-1 for NO3, K, and Ca ions, respectively.

Identification of Vibration Frequency, Acceleration, and Duration for Efficient Olive Harvesting Using a Trunk Shaker

Abstract: . In this study, an orbital trunk shaker was employed to determine the optimal frequency and shaking time that maximizes the fruit removal percentage of olives. The vibration imparted from the shaker to the trunk and the weight of the fruit removed were determined. The resulting acceleration was linearly correlated with the frequency and acceleration transmitted to the trunk by the clamp and decreased by more than 53%, probably due to the additional rubber covering on the clamp that was used to reduce the risk of damage to the bark. The frequencies that maximized the fruit removal percentage were 25 Hz for the Frantoio and Picholine cultivars, 23 Hz for the Leccino cultivar, and 27 Hz for the Cima di Melfi cultivar, and the tri-dimensional acceleration value measured on the trunk ranged from 70.41 to 99.25 m s -2 . The fruit removal percentage versus the shaking time exhibited a sigmoidal trend, and the optimal shaking time was 8 s for the Frantoio and Cima di Melfi cultivars and 6 s for the Leccino and Picholine cultivars. Improving the mechanical and hydraulic characteristics of the shaker is necessary to achieve the optimal vibration conditions.

Optical Methods and Techniques for Meat Quality Inspection

Abstract: Meat and meat products are closely associated with the daily eating habits of people around the world. Quality monitoring of meat and meat products is essential to ensure public health. In recent years, the meat industry has employed state-of-the art, high-speed processing technology, and meat processors need rapid, non-destructive, easy-to-use technology to monitor the safety and quality of meats and meat products for economic benefit. Optical technology has been gaining importance in research and industrial applications for real-time, non-destructive, accurate measurement of the quality attributes of meat and meat products. Hyperspectral imaging, multispectral imaging, visible-near-infrared (Vis/NIR) spectroscopy, and machine vision are used in research and industry for detection of the physical, chemical, sensory, and microbiological attributes of meat and meat products. These optical technologies have shown potential for accurate detection of individual attributes as well as multiple attributes simultaneously. This article reviews these optical technologies for detecting the quality attributes of meat (especially beef, pork, lamb, and poultry). This article also discusses the prevailing challenges for practical application of optical technologies and future research prospects.

Tile Drainage Simulation in SWAT2012: Parameterization and Evaluation in an Indiana Watershed

Abstract: . Subsurface drainage is an important flow pathway in the poorly drained soils of the Midwestern U.S. and therefore needs to be included in modeling studies. The SWAT2012 tile drainage simulation method, based on the Hooghoudt and Kirkham equations with a drainage coefficient, shows promise for predicting drainage impacts in drained watersheds but has had limited application. In this study, SWAT2012 was implemented in a small agricultural watershed in Indiana using parameters based on knowledge of typical drainage systems and drainage design theory. Monthly Nash-Sutcliffe efficiency (NSE) values for streamflow exceeded 0.70 in all calibration and validation years but were lower for nutrients during some years, with values ranging between 0.14 and 0.88. Simulated tile flow compared well with measured values from field-scale studies in similar locations, ranging from 8.5% to 16.2% of annual precipitation when tile drains were implemented on 50.9% of the watershed. The depth to impermeable layer (DEP_IMP) parameter was found to be the most important calibration parameter, as it also controls seepage through the restrictive layer. Curve number values need to be substantially decreased for tile flow prediction, while two new tile drain parameters that control the ratio of lateral to vertical hydraulic conductivity (LATKSATF) and the static maximum surface roughness (SSTMAXD) likely need to be calibrated, as they could not be assigned values based on real-world properties. This study provides appropriate parameter values for the SWAT2012 tile drainage routine and demonstrates its ability to improve watershed-scale predictions in tile-drained watersheds.

Hydrologic and Water Quality Terminology as Applied to Modeling

Abstract: A survey of the literature and in particular an examination of the terminology use in a previous special collection of modeling calibration and validation articles were conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and validation The terminology list includes rudimentary terms necessary for proper understanding of modeling literature for the novice modeler This article also provides discussions regarding confusing or conflicting terminology found in the literature, alternative terms to those recommended herein, and alternative definitions for those terms that may be used by some authors

Rapid Measurement of Drought Resistance in Plants Based on Electrophysiological Properties

Abstract: . Water loss in plant leaves causes mesophyll cells and their cell walls to shrink; thus, the cell volume becomes smaller. When leaf cells absorb water and expand, the cell volume becomes larger. The characteristic of water retention for cells is related to this expansion and contraction and is expressed as leaf tensity. In this study, leaves of Broussonetia papyrifera and Morus alba were used to examine the physiological capacitance, water potential, minimal fluorescence, and maximal photochemical efficiency of photosystem II (PS II) before and after water loss. The measured physiological capacitance value and water potential were used to calculate the relative tensity of leaves. The values of relative tensity in B. papyrifera and M. alba were 3.965 and 2.624, respectively. By measuring the minimum chlorophyll fluorescence and maximal photochemical efficiency of PS II in the leaves, the relative minimal fluorescence and maximal photochemical efficiency were calculated; the measured minimal fluorescence and maximal photochemical efficiency were 5.496 and 7.640 for B. papyrifera and 6.577 and 5.359 for M. alba, respectively. Results of the two methods showed that the drought-resistance ability of B. papyrifera was greater than that of M. alba. The electrophysiological characteristics of the plants reflected their ability to resist drought.

Hydrologic and Water Quality Models: Documentation and Reporting Procedures for Calibration, Validation, and Use

Abstract: The increasing use of hydrologic and water quality (H/WQ) models for technical, policy, and legal decision making calls for greater transparency in communicating the methods used and decisions made when using H/WQ models The objectives of this article are to: (1) provide guidelines to properly document H/WQ model calibration, validation, and use, and (2) raise issues about how to improve model documentation and reproducibility, and encourage open discussion of these topics in the H/WQ modeling community First, eight recommended elements of model documentation and reporting are identified and described, and good examples are provided for each Next, steps to move the H/WQ modeling community toward a culture of full model reproducibility are discussed The use by model practitioners of the consistent and comprehensive elements described herein for documentation and reporting of H/WQ model calibration, validation, and use will allow better interpretation of published modeling studies, improve the utility of modeling studies, and allow more systematic advancement of H/WQ models

Finite Element Modeling and Analysis of Radio Frequency Heating Rate in Mung Beans

Abstract: . Radio frequency (RF) heating has been extensively studied as a novel disinfestation method for dry agricultural products. A major difficulty in using this method is that different heating rates at the corners and edges of materials may cause negative effects on product quality. A systematic analysis of factors that influence the RF heating rate is desirable to help in designing effective treatment protocols. A finite element model using COMSOL Multiphysics software was developed and experimentally validated with 3 kg of mung beans in a 6 kW, 27.12 MHz free-running oscillator RF system to study the influence of sample moisture content, density, specific heat capacity, thermal conductivity, dielectric properties, top electrode voltage, and electrode gap on RF heating rate. Simulation results demonstrated that the variation in sample density and specific heat capacity, especially thermal conductivity, had a relatively slight effect on RF heating rate. The RF heating rate was significantly influenced by electrode gap, top electrode voltage, and the dielectric properties and moisture content of the sample. These heating rate distributions might be valuable in guiding and optimizing RF treatment conditions, which are helpful to improve RF heating uniformity for disinfecting dry products.

Nonthermal Plasma System for Extending Shelf Life of Raw Broiler Breast Fillets

Abstract: . A nonthermal dielectric barrier discharge (DBD) plasma system was modified and enhanced to treat broiler breast fillets (BBF) in order to improve the microbial quality of the meat. The system consisted of a high-voltage source and two parallel, round aluminum electrodes separated by three semi-rigid polypropylene barriers extending well beyond the electrodes. The broiler samples were packaged in sealed polyolefin plastic bags to allow for adequate gas volume in the package. A modified atmosphere (MA) blend of gas (65% O 2 , 30% CO 2 , 5% N 2 ) was used to enhance the generation of reactive oxygen species during treatment. This research investigates the ability of this plasma system to extend the shelf life of BBF by reducing the number of spoilage bacteria. The system was tested on BBF and compared to triplicate untreated controls. Samples were treated outside the plasma generation field at ambient air temperature and pressure for 3 min at 75 kV and then stored at 4°C. Surviving microbes were recovered on days 1, 3, 7, 10, and 14 via standard rinsing and plating on nutrient agar. There was a mean log reduction of 1.53 log 10 cfu mL -1 after 24 h. After 14 days of storage, the treated samples had a mean population of 5.53 log 10 cfu mL -1 , which was 2.39 cfu mL -1 lower than the control packaged in air and 1.52 log 10 cfu mL -1 lower than the control packaged in MA. A level of 5.56 log 10 cfu mL -1 falls below the generally accepted spoilage limit of 10 7 cfu mL -1 . Results demonstrate the ability of the nonthermal plasma system to reduce natural microflora on the surface of BBF and its applications in food safety and shelf life extension.

Optimization of a Citrus Canopy Shaker Harvesting System: Properties and Modeling of Tree Limbs

Abstract: . This article presents a part of the research work for the design and optimization of a fruit tree harvesting system using numerical methods. The analytical framework for the optimization is formulated based on a continuous canopy shaker that harvests citrus crops, primarily Valencia oranges (). Tree limbs are modeled analytically in the numerical based design optimization of a shaker that requires information regarding the limb configuration and properties. The objective of this study is to formulate a mathematical model to predict the configuration of primary limbs and to determine the properties of citrus wood. The tree limbs, thus proposed, are statistical prototypes or representations that account for the 5th, 25th, 50th, 75th, and 95th percentiles of actual tree limbs from random individual citrus trees. Polynomial response surface models were developed to predict sectional properties of the statistical model of the tree limbs. The distributions of the secondary branches and fruits were also predicted to model their effect on the dynamic response of the tree limbs. A three-point bending test, specific gravity test, moisture content test, and damping test were conducted on freshly cut samples of citrus wood. An elastic modulus of 8.5 GPa and modulus of rupture of 67.3 MPa were calculated from a load-deflection curve, and a density of 1450.8 kg m -3 , moisture content of 42%, and damping ratio of 10.78 were measured. Although the proposed methodology was developed for a canopy shaker, it could be easily implemented for other vibratory harvesters, such as limb shakers, foliage shakers, and over-the-row harvesters.

Life cycle analysis and production potential of camelina biodiesel in the Pacific Northwest.

Abstract: Camelina sativa could be a potential feedstock to help meet the U.S. biodiesel production goal of 36 billion gallons by 2022, as set forth by Energy Independence and Security Act of 2007. This research is focused on assessing the energy balance and greenhouse gas (GHG) emissions of camelina biodiesel production in the Pacific Northwest (PNW) region of the U.S. Field data were collected from a camelina farm in the region, and crushing and transesterification data were measured using facilities at the University of Idaho. It was estimated that use of camelina biodiesel reduces GHG emissions by 69% compared to 2005 baseline diesel. However, camelina biodiesel does not meet the ASTM D6751 specification for oxidative stability without an additive. Camelina has a smaller seed size compared to canola and required 23% more energy for crushing. The net energy ratio for camelina biodiesel was found to be 3.6, and the fossil energy ratio was found to be 4.2. From an agronomic standpoint, camelina can be incorporated into low rainfall areas of the PNW as a rotational crop. Wheat areas of the PNW with annual rainfall of 19 to 38 cm that currently incorporate fallow into their rotations were considered as potential areas for camelina production. There were 846,500 ha (2.1 million acres) of land meeting the criteria in the region that could potentially produce 443.0 million L of biodiesel (117.1 million gal) and 1.2 billion kg of meal per year. This is 12.1% of the approved amount of camelina meal that could be used in livestock feed within the PNW. It was concluded that camelina biodiesel qualifies as an advanced biofuel, and camelina meal has potential to be consumed locally as a feed mix for livestock.