Simulating management effects on crop production, tile drainage, and water quality using RZWQM-DSSAT

The objective of this study was to explore if more crop-specific plant growth modules can improve simulations of crop yields, and N in tile flow under different management practices compared with a generic plant growth module. We calibrated and evaluated the Root Zone Water Quality Model (RZWQM) with the Decision Support for Agrotechnology Transfer (DSSAT v3.5) plant growth modules (RZWQM-DSSAT) for simulating tillage (NT — no till, RT — ridge till, CP — chisel plow, and MP — moldboard plow), crop rotation {CC — continuous corn, and CS — corn (Zea mays L.)-soybean [Glycine max (L.) Merr.]}, and nitrogen (N) (SA — single application at preplant, and LSNT — late spring soil N test based application) and manure (SM — fall injected swine manure) management effects on crop production and water quality. Data from 1978 to 2003 from a water quality experiment near Nashua (Nashua experiments), Iowa, USA, were used. The model was calibrated using data from one treatment plot and validated for the rest of the plots. Simulated management effects on annual N loading in tile flow were agreeable with measured effects in 85%, 99%, 88%, and 78% of the cases for tillage, crop rotation (CS vs. CC), N application timing (SA vs. LSNT), and swine manure applications (SM vs. SA), respectively. On average, the LSNT plots were simulated to have 359 kg ha^− 1 higher corn yield compared to SA, when the observed increase was 812 kg ha^− 1. Grain yield simulations were not sensitive to differences between RT and NT, between SM and SA treatments, and between CS and CC. We conclude that considering the uncertainties of basic input data, processes in the field, and lack of site specific weather data, the results obtained with this RZWQM-DSSAT hybrid model were not much better than the results obtained earlier with the generic crop growth module.     

Empirical analysis and prediction of nitrate loading and crop yield for corn-soybean rotations

Nitrate nitrogen losses through subsurface drainage and crop yield are determined by multiple climatic and management variables. The combined and interactive effects of these variables, however, are poorly understood. Our objective is to predict crop yield, nitrate concentration, drainage volume, and nitrate loss in subsurface drainage from a corn (Zea mays L.) and soybean (Glycine max (L.) Merr.) rotation as a function of rainfall amount, soybean yield for the year before the corn-soybean sequence being evaluated, N source, N rate, and timing of N application in northeastern Iowa, U.S.A. Ten years of data (1994-2003) from a long-term study near Nashua, Iowa were used to develop multivariate polynomial regression equations describing these variables. The regression equations described over 87, 85, 94, 76, and 95% of variation in soybean yield, corn yield, subsurface drainage, nitrate concentration, and nitrate loss in subsurface drainage, respectively. A two-year rotation under average soil, average climatic conditions, and 125 kg N/ha application was predicted to loose 29, 37, 36, and 30 kg N/ha in subsurface drainage for early-spring swine manure, fall-applied swine manure, early-spring UAN fertilizer, and late-spring split UAN fertilizer (urea ammonium nitrate), respectively. Predicted corn yields were 10.0 and 9.7 Mg/ha for the swine manure and UAN sources applied at 125 kg N/ha. Timing of application (i.e., fall or spring) did not significantly affect corn yield. These results confirm other research suggesting that manure application can result in less nitrate leaching than UAN (e.g., 29 vs. 36 kg N/ha), and that spring application reduces nitrate leaching compared to fall application (e.g., 29 vs. 37 kg N/ha). The regression equations improve our understanding of nitrate leaching; offer a simple method to quantify potential N losses from Midwestern corn-soybean rotations under the climate, soil, and management conditions of the Nashua field experiment; and are a step toward development of easy to use N management tools.     

RZWQM simulation of long-term crop production, water and nitrogen balances in Northeast Iowa

Agricultural system models are tools to represent and understand major processes and their interactions in agricultural systems. We used the Root Zone Water Quality Model (RZWQM) with 26 years of data from a study near Nashua, IA to evaluate year to year crop yield, water, and N balances. The model was calibrated using data from one 0.4 ha plot and evaluated by comparing simulated values with data from 29 of the 36 plots at the same research site (six were excluded). The dataset contains measured tile flow that varied considerably from plot to plot so we calibrated total tile flow amount by adjusting a lateral hydraulic gradient term for subsurface lateral flow below tiles for each plot. Keeping all other soil and plant parameters constant, RZWQM correctly simulated year to year variations in tile flow (r² = 0.74) and N loading in tile flow (r² = 0.71). Yearly crop yield variation was simulated with less satisfaction (r² = 0.52 for corn and r² = 0.37 for soybean) although the average yields were reasonably simulated. Root mean square errors (RMSE) for simulated soil water storage, water table, and annual tile flow were 3.0, 22.1, and 5.6 cm, respectively. These values were close to the average RMSE for the measured data between replicates (3.0, 22.4, and 5.7 cm, respectively). RMSE values for simulated annual N loading and residual soil N were 16.8 and 47.0 kg N ha⁻¹, respectively, which were much higher than the average RMSE for measurements among replicates (7.8 and 38.8 kg N ha⁻¹, respectively). The high RMSE for N simulation might be caused by high simulation errors in plant N uptake. Simulated corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yields had high RMSE (1386 and 674 kg ha⁻¹) with coefficient of variations (CV) of 0.19 and 0.25, respectively. Further improvements were needed for better simulating plant N uptake and yield, but overall, results for annual tile flow and annual N loading in tile flow were acceptable.     

Evaluating and predicting agricultural management effects under tile drainage using modified APSIM

An accurate and management sensitive simulation model for tile-drained Midwestern soils is needed to optimize the use of agricultural management practices (e.g., winter cover crops) to reduce nitrate leaching without adversely affecting corn yield. Our objectives were to enhance the Agricultural Production Systems Simulator (APSIM) for tile drainage, test the modified model for several management scenarios, and then predict nitrate leaching with and without winter wheat cover crop. Twelve years of data (1990-2001) from northeast Iowa were used for model testing. Management scenarios included continuous corn and corn-soybean rotations with single or split N applications. For 38 of 44 observations, yearly drain flow was simulated within 50 mm of observed for low drainage (< 100 mm) or within 30% of observed for high drain flow. Corn yield was simulated within 1500 kg/ha for 12 of 24 observations. For 30 of 45 observations yearly nitrate-N loss in tile drains was simulated within 10 kg N/ha for low nitrate-N loss (< 20 kg N/ha) or within 30% of observed for high nitrate-N loss. Several of the poor yield and nitrate-N loss predictions appear related to poor N-uptake simulations. The model accurately predicted greater corn yield under split application (140-190 kg N/ha) compared to single 110 kg N/ha application and higher drainage and nitrate-N loss under continuous corn compared to corn/soybean rotations. A winter wheat cover crop was predicted to reduce nitrate-N loss 38% (341 vs. 537 kg N/ha with and without cover) under 41-years of corn-soybean rotations and 150 kg N/ha applied to corn. These results suggest that the modified APSIM model is a promising tool to help estimate the relative effect of alternative management practices under fluctuating high water tables.     

Evidence for a collective intelligence factor in the performance of human groups

Psychologists have repeatedly shown that a single statistical factor--often called "general intelligence"--emerges from the correlations among people's performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of "collective intelligence" exists for groups of people. In two studies with 699 people, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group's performance on a wide variety of tasks. This "c factor" is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group.     

Probing the Local Effects of Magnetic Impurities on Superconductivity

The local effects of isolated magnetic adatoms on the electronic properties of the surface of a superconductor were studied with a low-temperature scanning tunneling microscope. Tunneling spectra obtained near magnetic adsorbates reveal the presence of excitations within the superconductor's energy gap that can be detected over a few atomic diameters around the impurity at the surface. These excitations are locally asymmetric with respect to tunneling of electrons and holes. A model calculation based on the Bogoliubov-de Gennes equations can be used to understand the details of the local tunneling spectra.     

Galactose toxicity in the chick: hyperosmolality

Galactose-fed chicks have been found to develop severe hyperosmolar dehydration. Although biochemical abnormalities have been observed in the brain of the galactose-toxic chick, the observed physiologic alteration of serum osmolality could be the major factor responsible for the galactose toxicity syndrome in the chick.     

"Coulomb Staircase" at Room Temperature in a Self-Assembled Molecular Nanostructure

Double-ended aryl dithiols [alpha,alpha'-xylyldithiol (XYL) and 4,4'-biphenyldithiol] formed self-assembled monolayers (SAMs) on gold(111) substrates and were used to tether nanometer-sized gold clusters deposited from a cluster beam. An ultrahigh-vacuum scanning tunneling microscope was used to image these nanostructures and to measure their current-voltage characteristics as a function of the separation between the probe tip and the metal cluster. At room temperature, when the tip was positioned over a cluster bonded to the XYL SAM, the current-voltage data showed "Coulomb staircase" behavior. These data are in good agreement with semiclassical predictions for correlated single-electron tunneling and permit estimation of the electrical resistance of a single XYL molecule (approximately18 ± 12 megohms).     

Bench-Scale Evaluation of a Micro-Computer Automated Algal Turbidostat

A bench-scale, micro-computer automated algal turbidostat was constructed and its production and culture maintenance capabilities were evaluated. The computer program "Supervisor," written in Turbo Pascal, consisted of a series of functions and procedures integrated through a core program consisting of a: 1) stack; 2) bubble sort routine; and 3) supervisor procedure. The program controlled the daily routine procedures including harvesting, feeding, monitoring and a semimonthly disinfection process. Data received from the monitoring devices were used by the computer for decision making processes concerning changes in operation. In addition to reducing labor, continuous computer monitoring insured more reliable system operation.
The system operated successfully for five months, reliably producing Chlorella minutissima . For each harvesting event, the percent volume removed from each chamber depended on the solar cell reading recorded immediately before the harvest cycle began. Significant correlations between millivolts and algal biomass concentrations allowed the use of solar cells as a reliable and inexpensive method of culture density management. Kinetic studies using Chlorella minutissima resulted in a maximum biomass concentration of approximately 190 g/m³ and an average specific growth rate of 0.66/d. Experimental data combined with a first order computer analysis projected a daily harvest of 82 g/m³/d (dry weight) based on a 38% turnover rate, the average observed harvest rate for the three chambers.