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Achieving high yields in the large-scale agricultural systems that dominate the US landscape requires critical machine-enabled field operations to be executed in narrow windows of time. Novel cropping systems hold great promise to increase ecosystem services from these large-scale systems, but researchers and end-users need effective methods of representing the timing requirements of such systems. This gap prompted our exploration of approaches to visualize the timing of critical machine-enabled field operations. We refer to the resulting graphic as a field operations visualizer (FOV). We iterated multiple versions of the FOV through a user-centered process involving extensive stakeholder feedback. The resulting FOV version offers a straightforward method of visualizing operation sequences and identifying potential conflicts. Survey results suggest that the FOV provides significant operational insights to users about the timing challenges (or benefits) of novel cropping systems. The FOV may therefore be useful in guiding efforts to improve novel cropping systems and to thereby ultimately increase their deployment to deliver ecosystem services. [ABSTRACT FROM AUTHOR]

Despite external influences such as societal restrictions imposed during the 2020 COVID-19 pandemic, farmers continue to work, and needs for outreach and education have not waned. Extension professionals must continue to support these needs by using media and channels not typically employed when more traditional vehicles, such as on-site consultations and field days, are not practical or safe. The Iowa Learning Farms team from Iowa State University Outreach and Extension has developed a successful Virtual Field Day program using available online tools that can be easily adopted by other Extension organizations to facilitate outreach.

Meeting demand for food, fiber, feed, and fuel in a world with 9.7 billion people by 2050 without negative environmental impact is the greatest scientific challenge facing humanity. We hypothesize that this challenge can only be met with current and emerging technologies if guided by proactive use of a broad array of relevant data and geospatial scaling approaches to ensure local to global relevance for setting research priorities and implementing agricultural systems responsive to real-time status of weather, soils, crops, and markets. Despite increasing availability of field-scale agricultural data, robust spatial frameworks are lacking to convert these data into actionable knowledge. This commentary article highlights this knowledge gap and calls attention to the need for developing robust spatial frameworks that allow appropriate scaling to larger spatial domains by discussing a recently developed example of a data-driven strategy for estimating yield gaps of agricultural systems. To fully leverage research on sustainable intensification of cropping systems and inform policy development at different scales, we call for new approaches combining the strengths of top-down and bottom-up approaches which will require coordinated efforts between field scientists, crop modelers, and geospatial researchers at an unprecedented level.

Crop simulation models are used at the field scale to estimate crop yield potential, optimize current management, and benchmark input-use efficiency. At issue is the ability of crop models to predict local and regional actual yield and total production without need of site-year specific calibration of internal parameters associated with fundamental physiological processes. In this study, a well-validated maize simulation model was used to estimate yield potential for 45 locations across the U.S. Corn Belt, including both irrigated and rainfed environments, during four years (2011–2014) that encompassed diverse weather conditions. Simulations were based on measured weather data, dominant soil properties, and key management practices at each location (including sowing date, hybrid maturity, and plant density). The same set of internal model parameters were used across all site-years. Simulated yields were upscaled from locations to larger spatial domains (county, agricultural district, state, and region), following a bottom-up approach based on a climate zone scheme and distribution of maize harvested area. Simulated yields were compared against actual yields reported at each spatial level, both in absolute terms as well as deviations from long-term averages. Similar comparisons were performed for total maize production, estimated as the product of simulated yields and official statistics on maize harvested area in each year. At county-level, the relationship between simulated and actual yield was better described by a curvilinear model, with decreasing agreement at higher yields (>12Mgha−1). Comparison of actual and simulated yield anomalies, as estimated from the yearly yield deviations from the long-term actual and simulated average yield, indicated a linear relationship at county-level. In both cases (absolute yields and yield anomalies comparisons), the agreement increased with increasing spatial aggregation (from county to region). An approach based on long-term actual and simulated yields and year-specific simulated yield allowed estimation of actual yield with a high degree of accuracy at county level (RMSE≤18%), even in years with highly favorable weather or severe drought. Estimates of total production, which are of greatest interest to buyers and sellers in the market, were also in close agreement with actual production (RMSE≤22%). The approach proposed here to estimate yield and production can complement other approaches that rely on surveys, field crop cuttings, and empirical statistical methods and serve as basis for in-season yield and production forecasts.

The rapid needs assessment and response technique (RNR) is a useful tool for Extension professionals seeking ways to improve workshop structure. Facilitators using RNR organize workshop participants in small groups and then rotate the groups through a series of stations where participants dialogue on questions central to the workshop topic. The technique helps adult learners actively engage with one another, thus improving their ability to learn the subject matter. Use of RNR also allows facilitators to understand participants' existing knowledge of a workshop topic and tailor their education to participants' specific questions and needs.

Plain Language Summary: As profit margins become increasingly smaller for Midwest farmers, it is crucial to understand how a crop reacts to weather‐related stress. Cornfield edge effect is a new phenomenon Iowa farmers are experiencing where grain yield is lower at the field edge and progressively improves towards the field interior. Our objective was to verify if cornfield edge effect is occurring in Iowa along southern or western field edges when soybean is the adjacent field. And, if an edge effect is observed, determining the timing of the effect through the analysis of grain yield components. Field data collection was conducted in two regions of Iowa in 2019 and 2020 with observations at four distances from the field edge to interior. A field edge effect was detected in three of seven locations. We believe cornfield edge effect is occurring and that often it is a result of lower kernel numbers per ear and/or kernel weight. [ABSTRACT FROM AUTHOR]

The current investigation tested the effectiveness of an online student research project designed to supplement traditional methods (e.g., lectures, discussions, and assigned readings) of teaching research methods in a large-enrollment Introduction to Psychology course. Over the course of the semester, students completed seven assignments, each representing a stage of the research process. Students formed hypotheses, tested their hypotheses using data from the class, interpreted their results, generated future directions, created PowerPoint slides summarizing their projects, and presented their results in a poster session. We found support for the hypothesis that the research methods intervention would lead to better performance on a research methods quiz compared to students in a nonintervention section taught by the same instructor. This intervention demonstrated that it is feasible to use project-oriented active-learning techniques to foster understanding of research methods in large classes.

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Cover crops decrease nutrient leaching from high‐input cropping systems and improve soil quality. In Iowa, cereal rye (CR, Secale cereale L.) is the most adopted species due to its winter hardiness, high biomass productivity, and low cost. Field management of CR is still not completely understood, and as its adoption brings more complexity to farmers, especially with the uncertain effects on corn (Zea mays L.) yields, adoption is slow. Additionally, cover crops immobilize N and increase the inoculum of pathogens such as Pythium spp. A 2‐year field experiment was conducted at three locations in Iowa investigating the effect of two seeding methods, three seeding rates, and two termination timings (one location only) of CR on CR biomass and corn growth, root disease, and yield. Cereal rye biomass and consequently corn growth and development were not affected by seeding rate but by seeding method and termination timing. Broadcast CR produced an average of 3.5 times more biomass but 7.2% less corn yield than the drilled CR. Cereal rye when terminated late (3 days before planting [DBP]) produced 2.1 times greater biomass but 4.1% less corn yield compared to early termination (14 DBP). In general, greater root rot incidence and more Pythium clade B were detected in corn seedlings sampled from broadcast CR than drilled CR. Radicle rot incidence of corn was also greater in the late‐terminated plots in 1 year. Farmers should be careful using broadcast seeding and later termination of CR cover crop when planted before corn. Core Ideas: Spring cereal rye biomass accumulation was greatly affected by fall establishment.Corn growth and yield were negatively related to spring cereal rye biomass accumulation.Greater seedling disease occurred in corn planted into broadcast cereal rye.Farmers can benefit from using lower seeding rates to adopt cover crops while balancing costs.Drill seeding with early termination is a good strategy to balance cereal rye biomass and corn yield penalty. [ABSTRACT FROM AUTHOR]

The ability of the "Millon Adolescent Clinical Inventory"("MACI"; Millon, 1993) to identify serious adolescent, male sexual-offenders and to predict their recidivism following treatment was examined. "MACI" scores were evaluated for 381 adolescent, male sexual-offenders adjudicated delinquent for felony crimes and given maximum sentences, and, on the basis of detailed court and clinical records, diagnosed as conduct-disordered (79.5%) or antisocial-behaviored (20.5%). No mean "MACI" Base Rate Scores exceeded the clinically significant threshold, indicating low sensitivity from the "MACI" for identifying individuals as belonging in this extreme population of offenders and no ability from the "MACI" for predicting recidivism in this group on community release following treatment. The "MACI", and possibly self-report instruments in general, is simply not sufficient for these purposes. (Contains 3 tables.)