Managing the Rotation from Alfalfa to Corn

This archival publication may not reflect current scientific knowledge or recommendations. Current information available from the University of Minnesota Extension: https://www.extension.umn.edu.This bulletin describes management practices for alfalfa termination and the two subsequent corn crops that will help utilize the benefits of alfalfa.This publication was funded by the Minnesota Agricultural Fertilizer Research and Education Council. The research summarized in this publication was supported by the Minnesota Agricultural Fertilizer Research and Education Council, the Minnesota Corn Research and Promotion Council, the North Central Region-Sustainable Agriculture Research and Education Program, the Minnesota Agricultural Water Resource Center, the Hueg-Harrison fellowship, the University of Minnesota, and the USDA-Agricultural Research Service

Tillage Method and Glyphosate-Resistant Alfalfa Termination Timing Affect Soil Properties and Subsequent Corn Yield

Application of glyphosate [N-(phosphonomethyl) glycine]-containing herbicides and tillage, alone or in combination, has been the standard for removing declining alfalfa (Medicago sativa L.) stands. With glyphosate no longer an option to control glyphosate-resistant alfalfa, different termination strategies are needed. Field studies across four site-years in Utah evaluated the effect of tillage type and timing (fall conventional till, spring conventional till, fall strip-till, spring strip-till, and no-till) and herbicide timing (fall, spring, in-crop, and no herbicide) of 2,4-D (2,4- dichlorophenoxyacetic acid) and dicamba (3,6-dichloro-2-methoxybenzoic acid) on penetration resistance, alfalfa regrowth, corn (Zea mays L.) emergence rate, and silage corn yield. Across tillage treatments, fall, spring, and in-crop herbicide timings compared with no herbicide reduced alfalfa stem count and biomass by at least 74 and 92%, respectively. Emergence rate was greatest under fall and spring conventional till or spring strip-till compared with fall strip-till or no-till. Silage corn yield was greatest and similar with fall or spring herbicide applications for all tillage systems and conventional tillage with an in-crop herbicide application (19–27 Mg ha−1), followed by in-crop herbicide application for conservation tillage systems and fall and spring conventional till without herbicide application (14–20 Mg ha−1), and lastly when only conservation tillage was used to terminate alfalfa (5–15 Mg ha−1). Silage corn yield can be optimized when glyphosate-resistant alfalfa is terminated with herbicides prior to planting, regardless of tillage type or timing. Termination of glyphosate-resistant alfalfa by herbicides after corn emergence, depending on tillage, reduces silage corn yield 9–19%

Nitrogen Fertilization and Glyphosate-Resistant Alfalfa Termination Method Effects on First-Year Silage Corn

Tillage type/timing and herbicide application date may change the amount and timing of N mineralization, altering fertilizer N needs for first-year corn (Zea mays L.) following glyphosate [N-(phosphonomethyl)glycine]-resistant (GR) alfalfa (Medicago sativa L.). Studies were conducted in 2012 and 2013 in Utah. Yield, quality, and economic return of silage corn as affected by five tillage type/timings (fall conventional till, spring conventional till, fall strip-till, spring strip-till, and no-till), three herbicide application dates for alfalfa termination (fall, spring, and in-crop), and four N rates (0, 56, 112, and 224 kg ha−1) were evaluated. Silage corn yield and quality following GR alfalfa was economically optimized without N fertilization regardless of tillage type/timing and herbicide application date. Thus, N from decomposing alfalfa can provide the full N requirement of first-year silage corn following GR alfalfa. Estimated animal milk production ha−1 of silage corn was greatest and similar for all herbicide application dates with conventional tillage and spring herbicide application with strip-till and no-till (26–38 Mg milk ha−1), whereas an in-crop herbicide application with strip-till and no-till resulted in the lowest estimated milk production (21–29 Mg milk ha−1). Increased economic return for the in-crop herbicide date by including economics from harvesting the first alfalfa cutting before planting corn mostly offset the reduced economic return of the lower silage corn yield. Therefore, an application of 2,4-D (2,4-dichlorophenoxyacetic acid) and dicamba (3,6-dichloro-2-methoxybenzoic acid) in the fall, spring, or in-crop to control GR alfalfa are good economic options for conventional tillage, strip-till, and no-till systems

A long‑term precision agriculture system sustains grain profitability

After two decades of availability of grain yield-mapping technology, long-term trends in field-scale profitability for precision agriculture (PA) systems and conservation practices can now be assessed. Field-scale profitability of a conventional or ‘business-as-usual’ system with an annual corn (Zea mays L.)-soybean (Glycine max [L.]) rotation and annual tillage was assessed for 11 years on a 36 ha field in central Missouri during 1993 to 2003. Following this, a ‘precision agriculture system’ (PAS) with conservation practices was implemented for the next 11 years to address production, profit and environmental concerns. The PAS was multifaceted and temporally dynamic. It included no-till, cover crops, crop rotation changes, site-specific N and variable-rate or zonal P, K and lime. Following a recent evaluation of differences in yield and yield variability, this research compared profitability of the two systems. Results indicated that PAS sustained profits in the majority (97%) of the field without subsidies for cover crops or payments for enhanced environmental protection. Profit was only lower with PAS in a drainage channel where no-till sometimes hindered soybean stands and wet soils caused wheat (Triticum aestivum L.) disease. Although profit gains were not realized after 11 years of PA and conservation practices, this system sustained profits. These results should help growers gain confidence that PA and conservation practices will be successful

Assessing Within-Field Variation in Alfalfa Leaf Area Index Using UAV Visible Vegetation Indices

This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between LAI and visible vegetation indices (VVIs) using unmanned aerial vehicle (UAV) imagery. This research has three objectives: (1) to measure and describe the within-field variation in LAI and canopy height for an irrigated alfalfa field, (2) to evaluate the relationships between the alfalfa LAI and various VVIs with and without field average canopy height, and (3) to use UAV images and field average canopy height to describe the within-field variation in LAI and the potential application to VRI. The study was conducted in 2021–2022 in Rexburg, Idaho. Over the course of the study, the measured LAI varied from 0.23 m2 m−2 to 11.28 m2 m−2 and canopy height varied from 6 cm to 65 cm. There was strong spatial clustering in the measured LAI but the spatial patterns were dynamic between dates. Among eleven VVIs evaluated, the four that combined green and red wavelengths but excluded blue wavelengths showed the most promise. For all VVIs, adding average canopy height to multiple linear regression improved LAI prediction. The regression model using the modified green–red vegetation index (MGRVI) and canopy height (R2 = 0.93) was applied to describe the spatial variation in the LAI among VRI zones. There were significant (p \u3c 0.05) but not practical differences

Meta-research evaluating redundancy and use of systematic reviews when planning new studies in health research:a scoping review

BACKGROUND: Several studies have documented the production of wasteful research, defined as research of no scientific importance and/or not meeting societal needs. We argue that this redundancy in research may to a large degree be due to the lack of a systematic evaluation of the best available evidence and/or of studies assessing societal needs. OBJECTIVES: The aim of this scoping review is to (A) identify meta-research studies evaluating if redundancy is present within biomedical research, and if so, assessing the prevalence of such redundancy, and (B) to identify meta-research studies evaluating if researchers had been trying to minimise or avoid redundancy. ELIGIBILITY CRITERIA: Meta-research studies (empirical studies) were eligible if they evaluated whether redundancy was present and to what degree; whether health researchers referred to all earlier similar studies when justifying and designing a new study and/or when placing new results in the context of earlier similar trials; and whether health researchers systematically and transparently considered end users’ perspectives when justifying and designing a new study. SOURCES OF EVIDENCE: The initial overall search was conducted in MEDLINE, Embase via Ovid, CINAHL, Web of Science, Social Sciences Citation Index, Arts & Humanities Citation Index, and the Cochrane Methodology Register from inception to June 2015. A 2nd search included MEDLINE and Embase via Ovid and covered January 2015 to 26 May 2021. No publication date or language restrictions were applied. CHARTING METHODS: Charting methods included description of the included studies, bibliometric mapping, and presentation of possible research gaps in the identified meta-research. RESULTS: We identified 69 meta-research studies. Thirty-four (49%) of these evaluated the prevalence of redundancy and 42 (61%) studies evaluated the prevalence of a systematic and transparent use of earlier similar studies when justifying and designing new studies, and/or when placing new results in context, with seven (10%) studies addressing both aspects. Only one (1%) study assessed if the perspectives of end users had been used to inform the justification and design of a new study. Among the included meta-research studies evaluating whether redundancy was present, only two of nine health domains (medical areas) and only two of 10 research topics (different methodological types) were represented. Similarly, among the included meta-research studies evaluating whether researchers had been trying to minimise or avoid redundancy, only one of nine health domains and only one of 10 research topics were represented. CONCLUSIONS THAT RELATE TO THE REVIEW QUESTIONS AND OBJECTIVES: Even with 69 included meta-research studies, there was a lack of information for most health domains and research topics. However, as most included studies were evaluating across different domains, there is a clear indication of a high prevalence of redundancy and a low prevalence of trying to minimise or avoid redundancy. In addition, only one meta-research study evaluated whether the perspectives of end users were used to inform the justification and design of a new study. SYSTEMATIC REVIEW REGISTRATION: Protocol registered at Open Science Framework: https://osf.io/3rdua/ (15 June 2021). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02096-y

Relating four‐day soil respiration to corn nitrogen fertilizer needs across 49 U.S. Midwest fields

Soil microbes drive biological functions that mediate chemical and physical processes necessary for plants to sustain growth. Laboratory soil respiration has been proposed as one universal soil health indicator representing these functions, potentially informing crop and soil management decisions. Research is needed to test the premise that soil respiration is helpful for profitable in‐season nitrogen (N) rate management decisions in corn (Zea mays L.). The objective of this research was two‐fold: (i) determine if the amount of N applied at the time of planting effected soil respiration, and (ii) evaluate the relationship of soil respiration to corn yield response to fertilizer N application. A total of 49 N response trials were conducted across eight states over three growing seasons (2014–2016). The 4‐day Comprehensive Assessment of Soil Health (CASH) soil respiration method was used to quantify soil respiration. Averaged over all sites, N fertilization did not impact soil respiration, but at four sites soil respiration decreased as N fertilizer rate applied at‐planting increased. Across all site‐years, soil respiration was moderately related to the economical optimum N rate (EONR) (r2 = 0.21). However, when analyzed by year, soil respiration was more strongly related to EONR in 2016 (r2 = 0.50) and poorly related for the first two years (r2 \u3c 0.20). These results illustrate the factors influencing the ability of laboratory soil respiration to estimate corn N response, including growing‐season weather, and the potential of fusing soil respiration with other soil and weather measurements for improved N fertilizer recommendations

Leveraging Important Covariate Groups for Corn Yield Prediction

Accurate yield information empowers farmers to adapt, their governments to adopt timely agricultural and food policy interventions, and the markets they supply to prepare for production shifts. Unfortunately, the most representative yield data in the US, provided by the US Department of Agriculture, National Agricultural Statistics Service (USDA-NASS) Surveys, are spatiotemporally patchy and inconsistent. This paper builds a more complete data product by examining the spatiotemporal efficacy of random forests (RF) in predicting county-level yields of corn – the most widely cultivated crop in the US. To meet our objective, we compare RF cross-validated prediction accuracy using several combinations of explanatory variables. We also utilize variable importance measures and partial dependence plots to compare and contextualize how key variables interact with corn yield. Results suggest that RF predicts US corn yields well using a relatively small subset of climate variables along with year and geographical location (RMSE = 17.1 bushels/acre (1.2 tons/hectare)). Of note is the insensitivity of RF prediction accuracy when removing variables traditionally thought to be predictive of yield or variables flagged as important by RF variable importance measures. Understanding what variables are needed to accurately predict corn yields provides a template for applying machine learning approaches to estimate county-level yields for other US crops

Irrigation Zone Delineation and Management with a Field-Scale Variable Rate Irrigation System in Winter Wheat

Understanding spatial and temporal dynamics of soil water within fields is critical for effective variable rate irrigation (VRI) management. The objectives of this study were to develop VRI zones, manage irrigation rates within VRI zones, and examine temporal differences in soil volumetric water content (VWC) from irrigation events via soil sensors across zones. Five irrigation zones were delineated after two years (2016 and 2017) of yield and evapotranspiration (ET) data collection. Soil sensors were placed within each zone to give real time data of VWC values and assist in irrigation decisions within a 23 ha field of winter wheat (Triticum aestivum ‘UI Magic’) near Grace, Idaho, USA (2019). Cumulative irrigation rates among zones ranged from 236 to 298 mm. Although a statistical comparison could not be made, the irrigation rates were 0.6 to 21% less than an estimated uniform grower standard practice (GSP) irrigation approach. Based on soil sensor data, crop water stress was avoided with VRI management in all but Zone 3. Thus, this simple approach to VRI zone delineation and VWC monitoring has the potential to reduce irrigation, such as this study, on average by 12% and should be evaluated in other site-years to assess its viability