A total of 38 long-term care facilities within a region participated in a 3-month quality improvement initiative focused on environmental cleaning and disinfection. Significant improvements in daily and discharge cleaning were observed during the project period. Further study of the sustainability and clinical impact of this type of initiative is warranted.

WEEDSIM is a bioeconomic decision aid for management of annual weeds in corn and soybean. It was field-tested for 4 yr in Minnesota. The decision aid has two categories of management recommendations: soil-applied plus postemergence (PRE+), based on estimated weed seedbank composition and density; and postemergence (POST), based upon observed weed seedling composition and density. Weed densities, weed control, herbicide use, environmental impact of herbicide use, weed management costs, crop yields, and economic returns that resulted from PRE+ and POST recommendations were compared to those associated with herbicide management systems (HERB) that were standard for the region. After 4 yr of applying WEEDSIM recommendations to the same plots, there were no increases in annual weed densities (seedbanks, seedlings, established plants, or seed production) or decreases in weed control or crop (soybean, rotation corn, and continuous corn) yields, compared to HERB. WEEDSIM recommendations resulted in average annual herbicide applications of 1.1 kg ai ha−1 for PRE+ and 1.0 kg ai ha−1 for POST, compared to 3.5 kg ai ha−1 for HERB. Environmental impact indices associated with PRE+, POST, and HERB were 0.75, 0.71, and 0.54, with the lowest value indicating greater environmental risk than the two higher values. Similarly, average weed management costs were $24, $33, and $77 ha−1 for PRE+, POST, and HERB, respectively. Based on crop prices of $94 Mg−1 for corn and $220 Mg-1 for soybean, the average gross margins over weed control costs were higher for PRE+ ($509 ha−1) and POST ($522 ha−1) than for HERB ($455 ha−1). In general, WEEDSIM appeared to make management recommendations that adequately controlled weeds, maintained crop yields, reduced herbicide use, decreased environmental risk, lowered weed management costs, and increased gross margins over weed control costs compared to the use of herbicides standard for the region.

A standard weed management system (system I) had a higher return above variable costs than did an intensive weed management system (system II) for two eastern Colorado cropping rotations. For continuous corn (Zea mays L.), the return above variable costs averaged $18.85/ha more under system I than under system II. For a barley (Hordeum vulgare L.)-corn-sugarbeet (Beta vulgaris L.) rotation, the return above variable costs averaged $20.48/ha more under System I than under System II. Based on alternative input (herbicide) and product prices, higher herbicide costs favored the standard weed management system, whereas higher crop prices favored the weed management system with the higher yields adjusted for quality. The probability that returns above variable costs differed between the two weed management systems depended upon the level of product prices and herbicide costs.

A bioeconomic weed management model was tested as a decision aid for weed control in corn at Rosemount, MN, from 1991 to 1994. The model makes recommendations for preemergence control tactics based on the weed seed content of the soil and postemergence decisions based on weed seedling densities. Weed control, corn yield, herbicide active ingredient applied, and economic return with model-generated treatments were compared to standard herbicide and mechanical control treatments. Effects of these treatments on weed populations and soybean yield the following year were also determined. In most cases, the model-generated treatments controlled weeds as well as the standard herbicide treatment. The quantity of herbicide active ingredient applied decreased 27% with the seed bank model and 68% with the seedling model relative to the standard herbicide treatment. However, the frequency of herbicide application was not reduced. In 1 yr, seed bank model treatments did not control weeds as well as the standard herbicide or seedling model treatments. Corn yields reflected differences in weed control. Net economic return to weed control was not increased by using model-generated control recommendations. Weed control treatments the previous year affected weed density in the following soybean crop. In 2 of 3 yr, these differences did not after weed control or soybean yield. Although tactics differed, the bioeconomic model generally resulted in weed control and corn yield similar to the standard herbicide. The model was responsive to differing weed populations, but did not greatly after economic returns under the weed species and densities in this research.

Previous efforts to model crop yield loss from multiple weed species constructed competitive indices based on yield loss from individual weed species. Our model uses a multispecies modification of Cousens’ rectangular hyperbolic yield function to estimate a nonlinear competitive index for weed-crop interference. Results from 13 Minnesota and Wisconsin data sets provide measures of the relative competitiveness of mixed green and yellow foxtails, common lambsquarters, redroot pigweed, velvetleaf, and several other weed species. Competition coefficient estimates are stable over years, but not locations.

Grass and broadleaf weed densities and seed numbers, weed control practices, and grain yields were included in a bioeconomic model that evaluates alternative weed management strategies for continuous corn (Zea mays L.). Weed seed numbers in soil and herbicide carry-over provided intertemporal links. Four weed management strategies – two fixed, one mixed, and one flexible – were evaluated with annualized net returns as the performance indicator. The flexible strategy (weed control based on observed conditions) had the largest annualized net return for high and low initial weed seed numbers. The fixed weed management strategy (weed control predetermined) of an annual application of only a preemergence herbicide ranked second in terms of annualized net returns for high weed seed numbers. The mixed weed management strategy of alternative year applications of preemergence herbicide and “as needed” applications of postemergence herbicide ranked second for low initial weed seed numbers. The fixed weed management strategy of alternate year application of preemergence herbicide only generated the lowest annualized net return, regardless of initial weed seed numbers.

A fixed (conventional) weed management strategy in corn was compared to three other strategies (two mixed and one flexible) in terms of weed control, grain yield, gross margin (gross income minus herbicide treatment costs), and herbicide use under furrow irrigation for four consecutive years. The fixed strategy prespecified preplanting, preemergence, postemergence, and layby herbicides. The flexible strategy herbicide treatments were specified by a computer bioeconomic model. Model decisions were based on weed seed in soil before planting, weed densities after corn emergence, herbicide costs, expected corn grain yield and selling price, and other parameters. The two mixed strategies were a combination of fixed and flexible strategies and designated either specified soil-applied herbicides (mixed/soil), or no soil-applied herbicide (mixed/no soil); postemergence treatments were determined by the model. Average corn grain yield was 10 280 kg ha–1 and gross income was 920 $ ha–1 and neither differed among strategies. Total weed density and gross margin were significantly higher for the mixed/no soil and flexible strategies compared to the mixed/soil and fixed strategies. Total weed density averaged 28 720, 28 100, 10 910, and 680 plants ha–1 for the mixed/no soil, flexible, mixed/soil, and fixed strategies, respectively. Annual gross margins for the four strategies averaged 885, 875, 845, and 810 $ ha–1, respectively. Herbicide use over the 4-yr period for these four strategies averaged 3.8, 5.3, 20.5, and 26.9 kg ha–1, respectively, and each value differed from the other. Thus, weeds can be managed in corn, gross margins increased, and herbicide use decreased by employing a bioeconomic weed-corn model to make weed management decisions.

A bioeconomic model was tested as a decision aid for weed control in soybean at Rosemount, MN, from 1991 to 1994. The model makes recommendations for preplant incorporated and preemergence control tactics based on the weed seed content of the soil and postemergence decisions based on weed seedling densities. Weed control, soybean yield, herbicide use, and economic return with model-generated treatments were compared to standard herbicide and mechanical control systems. Effects of these treatments on weed populations and corn yield the following year were also determined. In most cases, the model-generated treatments controlled weeds as well as a standard herbicide treatment. Averaged over the 3 yr, the quantity of herbicide active ingredient applied was decreased by 47% with the seedbank model and 93% with the seedling model compared with a standard soil-applied herbicide treatment. However, the frequency of herbicide application was not reduced. Soybean yields reflected differences in weed control and crop injury. Net economic return to weed control was increased 50% of the time using model-recommended treatments compared with a standard herbicide treatment. Weed control treatments the previous year affected weed density in the following corn crop but had little effect on weed control or corn yield. The bioeconomic model was responsive to differing weed populations, maintained weed control and soybean yield and often increased economic returns under the weed species and densities in this research.

An economic analysis of four weed management systems employed on four crop sequences in a barley-corn-pinto bean-sugarbeet rotation in eastern Colorado was computed. Weeds were controlled in each crop with only conventional tillage or conventional tillage plus minimum levels of herbicides (systems 3 and 4), moderate levels of herbicides (system 1), or intensive levels of herbicides (system 2). Adjusted gross returns were higher for systems 3 and 4 where herbicide use was less/year and decreased over 4 yr than for systems 1 and 2 where herbicide use was higher/year and constant. When the four crop sequences were aggregated using yield and sucrose indices, the least herbicide-intensive weed management system had $440/ha/4 yr higher indexed adjusted gross return than the most herbicide-intensive weed management system. An income risk analysis showed that the herbicide-intensive weed management system was not risk efficient and that producers would select one of the other three less herbicide-intensive weed management systems depending upon their risk preferences.

Herbicide evaluation trials are typically conducted with the objective of rating herbicide efficacy and assessing crop yield loss. There is little if any attempt to quantify the economic risk associated with each treatment. The objective of this research was to use second-degree stochastic dominance to evaluate the economic stability of corn and soybean weed management systems between two contrasting environments. Weed management systems were evaluated in small-plot replicated trials over a 3-yr time period at two locations in southern Minnesota. One location (Waseca) had a slightly cooler and wetter environment than the second location (Lamberton). The Waseca location also had higher weed density and greater weed species diversity. Adjusted returns from weed management were calculated for each system by measuring economic returns, as determined by deducting weed management costs from the product of crop price and grain yield. Stochastic dominance is a technique that considers the entire distribution of net returns from weed management and compares these cumulative distributions as a basis for analyzing risk. Climate, soils, and weed diversity dictated differences in risk efficiency and effectiveness of the various weed management systems evaluated between the Waseca and Lamberton sites. Stochastic dominance testing is a useful tool for understanding long-term risk across environments. Results can be used to develop effective long-term weed management systems that minimize risk while maximizing profit potential.

Evaluation of economic outcome associated with a given weed management system is an important component in the decision-making process within crop production systems. The objective of this research was to investigate how risk-efficiency criteria could be used to improve herbicide-based weed management decision making, assuming different risk preferences among growers. Data were obtained from existing weed management trials in corn conducted at the University of Minnesota Southern Research and Outreach Center at Waseca. Weed control treatments represented a range of practices including one-pass soil-applied, one-pass postemergence, and sequential combinations of soil and postemergence herbicide application systems. Analysis of risk efficiency across 23 herbicide-based weed control treatments was determined with the mean variance and stochastic dominance techniques. We show how these techniques can result in different outcomes for the decision maker, depending on risk attitudes. For example, mean variance and stochastic dominance techniques are used to evaluate risk associated with one- vs. two-pass herbicide treatments with and without cultivation. Based on these analyses, it appears that a one-pass system is preferred by a risk-averse grower. However, we argue that this may not be the best option considering potential changes in weed emergence patterns, application timing concerns, etc. The techniques for economic analysis of weed control data outlined in this article will help growers match herbicide-based weed management systems to their own production philosophies based on economic risk.

The Agricultural Risk Management Simulator (ARMS) is a microcomputer program designed to help users evaluate strategies for managing yield and price risk in crop farming operations. Risk management strategies are defined by choices regarding crop mix, the purchase of multiple peril crop insurance, and the use of forward contracting. Probabilistic budgeting is used to determine the net cash flow probability distribution for each strategy considered. Flexibility with regard to both sources of probabilistic information and the form of yield and price probability distributions is a noteworthy feature of the program.

Nanomedicine is yielding new and improved treatments and diagnostics for a range of diseases and disorders. Nanomedicine applications incorporate materials and components with nanoscale dimensions (often defined as 1-100 nm, but sometimes defined to include dimensions up to 1000 nm, as discussed further below) where novel physiochemical properties emerge as a result of size-dependent phenomena and high surface-to-mass ratio. Nanotherapeutics and in vivo nanodiagnostics are a subset of nanomedicine products that enter the human body. These include drugs, biological products (biologics), implantable medical devices, and combination products that are designed to function in the body in ways unachievable at larger scales. Nanotherapeutics and in vivo nanodiagnostics incorporate materials that are engineered at the nanoscale to express novel properties that are medicinally useful. These nanomedicine applications can also contain nanomaterials that are biologically active, producing interactions that depend on biological triggers. Examples include nanoscale formulations of insoluble drugs to improve bioavailability and pharmacokinetics, drugs encapsulated in hollow nanoparticles with the ability to target and cross cellular and tissue membranes (including the bloodbrain barrier) and to release their payload at a specific time or location, imaging agents that demonstrate novel optical properties to aid in locating micrometastases, and antimicrobial and drug-eluting components or coatings of implantable medical devices such as stents.