Recipient Organization
OKLAHOMA STATE UNIVERSITY
(N/A)
STILLWATER,OK 74078
Performing Department
Plant & Soil Sciences
Non Technical Summary
Nitrogen (N) fertilizer is one of the greatest inventions in human history. Smil (2001) estimates that 40% of the current human population would not be alive if the process for turning atmospheric N gas into fertilizer had not been invented. Around half of current global food production can be attributed to the use of N fertilizer (Smil, 2011). Along with its tremendous impact on food production, N fertilizer has potent effects when it escapes to water and air from the agricultural systems where it was applied. For example, plants in coastal waters are, like plants on land, usually N-limited in their growth rate (Vitousek and Howarth, 1991). Coastal waters receiving drainage from intensive agricultural regions (e.g., the Gulf of Mexico, Yellow Sea, Baltic Sea) have excessive plant growth that can sometimes be severe enough to lead to dissolved oxygen-depleted as low as to harm marine life (Burkart and James, 1999; Rabalais et al., 2002; Guo et al., 2020; Conley et al., 2011). Nitrogen fertilizer is the main agricultural contributor to global warming potential in the U.S., both through CO2produced during its manufacture and N2O released after its application to farm fields (USEPA, 2016; Davidson, 2009). Although CO2from transport and other industries have a much larger global warming impact, the most important reduction advances in agriculture are likely to be from N fertilizer management. In addition, the N2O from agriculture is now the largest human-driven source of compounds that deplete stratospheric ozone (Ravishankara et al., 2009). Thus, N fertilizer is essential to the U.S. and world food supply but has substantial negative impacts on the environment. There is currently great potential to maintain or increase N benefits in food production while reducing the negative environmental consequences. That potential is the main interest of this committee.The U.S. was one of the earliest widespread users of N fertilizer following the conversion of munitions (high in N) factories to fertilizer factories after World War II. In the U.S., more N fertilizer is applied to corn than to all other crops combined; however, it is also used on nearly all non-legume crops. A large proportion of the N fertilizer used in the U.S. is for crops fed to animals (especially corn), and most of that N is excreted by those animals as manure. Efficient management of manure N is also important, both to support crop production and in terms of negative consequences in the environment. Increasing N use efficiency (NUE) from fertilizer and manure has been a key driver increasing crop production efficiency in the U.S. (Houlton et al., 2012). However, the manure N source is often not accounted for, and applying fertilizer N to crops in amounts that are needed reduces profitability and increases environmental impact and costs (Hong et al., 2007; Shcherbak et al., 2014).Considering the availability of the various N sources; "How much N fertilizer is needed?". This turns out to be a difficult question and one that is of great interest to this research group. Corn production in the U.S. today relies on large inputs of N fertilizer to meet N demand by the crop (Simons et al., 2014), but also soil N supply. Nitrogen mineralization from soil organic matter (SOM), of which manure can greatly increase, provides a substantial portion of corn's total N need in many areas (Lynch, 2013), and is supplemented as needed with inorganic N fertilizer, manures, and co-products (Yan et al., 2019). Although more total N is needed by corn as yield increases (Ciampitti and Vyn, 2011), more fertilizer N may not be needed (Shapiro and Wortmann, 2006; Scharf et al., 2006b). The amount of N supplied by the tremendous reserves in soil organic matter can vary widely--this is a purely biological process that is very sensitive to both inorganic and organic inputs, soil temperature, moisture, and oxygen (Sierra, 1997; Fernández et al., 2017). The release of N from organic compounds in manure is similarly complex. Complicating the matter further is the impact of temperature, moisture, and oxygen on N loss via leaching, denitrification, and ammonia volatilization (Scharf and Alley, 1988). The result is that even the optimal N fertilization rate can vary widely from place to place even in a single field (Mamo et al., 2003; Scharf et al., 2005). There is still much to learn and predict both spatially and temporally and spatially about these fundamental processes that control plant N availability and, thus, optimal N fertilizer management.A key component to improved fertilizer N efficiency and reduced environmental impact is a better understanding and quantification of N mineralization from all sources coupled to crop uptake. Fertilizer N efficiency is normally based on N uptake/yield of unfertilized (check) plots. An important, possibly incorrect, assumption in this approach is that release of organic soil N is unaffected by N fertilization (Jenkinson et al., 1985; Mahal et al., 2019). Not accounting for N fertilizer's impact on soil organic N release can lead to over-fertilization and increased N loss. While it is commonly accepted that N fertilizer influences soil N mineralization by "priming" processes (Jenkinson et al., 1985; Mahal et al., 2019) little has been done to quantify these effects and incorporate this knowledge into our fertilizer N recommendations or calculations of NUE. Thus, quantifying uptake of fertilizer N by the crop and associated changes in soil N mineralization is paramount to developing sound management approaches that maintain high crop yields while minimizing N losses. Thus, methods to predict the best N fertilizer rate that can account for spatially and temporally variable N loss and release of organic N from soil and manure are a key step toward improved N management. This research group has collected data and published three papers addressing this issue (Scharf et al., 2006a; Laboski et al., 2008; McDaniel et al., 2020). Each of these papers benefited from the regional nature of the group, producing conclusions that were much more robust than can be achieved by a few investigators in limited geographies. The relatively recent addition of microbiological and modeling expertise to the committee adds new approaches that can be used in pursuit of this goal.The long-term goals of this regional project are to better understand how the interactions of soil, weather, climate, and cropping system influence N availability and optimal N management from all N containing inputs. Additionally, we plan to develop tools that help farmers translate this understanding into practice. Over the next five years, we aim to develop one key new piece of knowledge and/or one new management tool that moves N management toward reduced environmental impact while maintaining production benefits. The ultimate success of the project - reduced N loss, efficient N fertilizer use, and continued increase in crop yield - lies in grower adoption of N recommendations and management practices developed. This will require a thorough understanding of how practices within a cropping system impact N availability and yield, understanding the producer and adviser decision-making process, and development/enhancement of decision tools that will inform N fertilization decisions. Thus, a strong, transformative extension education/outreach program targeted to producers and crop advisors (in conjunction with extension educators, local/state/federal regulatory personnel, and policymakers), is central to this project.
Animal Health Component
85%
Research Effort Categories
Basic
15%
Applied
85%
Developmental
0%
Goals / Objectives
Determine the roles of innovative management practices, the environment, and their interactions on optimum use of nitrogen in agroecosystems.
Translate field and laboratory research into nitrogen management decision-making tools and educational resources promoting improved profitability and sustainability of corn-based cropping systems.
Project Methods
We will use field studies that evaluate how corn responds to N inputs in different edaphoclimatic settings and innovative management systems, such as cover crop-based systems and alternative drainage designs. Our methods will also include soil characterization, including soil health testing. To understand the environment by management interactions, we will likely use traditional statistical approaches as well as spatial statistics and perhaps multivariate statistics as well.We will use a wide array of methods to assess soil microbial biomass, activity, community structure, and diversity from soil samples collected during field, greenhouse, and laboratory experiments. Methods to include soil microbial biomass by chloroform extraction and fatty acid-based lipid approaches, e.g. fatty acid methyl esters (FAMEs), gas fluxes for CO2, N2O, and CH4, soil extracellular enzyme activities, and molecular-based approaches for microbial community composition, estimates of diversity, and functional genes (e.g. N-cycling). Field and laboratory studies undertaken by group members will include plant-available N assessment using15N labeled fertilizer combined with cover crops and or15N pool dilution experiments under contrasting N management systems. The effects of N management on microbial communities and their activities will be addressed through functional metagenomics and community structural equation modeling.We will develop new N recommendation algorithms to incorporate soil properties, weather information, and other field data collected into the existing N recommendation tools with the goal of improving farm profitability and sustainability. One strategy is to combine the existing trial data the committee members already have, and match with location, soil, weather, and management factors of the trial fields to build a large meta-dataset. Multivariate regression approach will be employed to fit the meta-data and identify the models that statistically best explain the field-level N responses. Theex antefield-specific N recommendations will then be predicted using available field information. Another newer strategy is to build a comprehensive multi-year, multi-location response trial dataset that consistently collects the yield-impacting factors for each trial plot. That new dataset can be developed as part of trial designs of Objectives 1 and 2, where the impacting factors are suggested by the strategy one modeling results. This large plot-level primary dataset will enable the fitting of more advanced varying coefficient regression models, both parametrically and non-parametrically, to better explain the spatial and temporal variability in N responses. More accurate N rates can be recommended based on the estimated varying N responses.Educational materials such as extension bulletins and videos will be developed to educate farmers and their crop advisors about corn N decision tools.