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Cold temperatures limit nitrate-N load reductions of woodchip bioreactors in higher-latitude climates. This two-year, on-farm (Willmar, Minnesota, USA) study was conducted to determine whether field-scale nitrate-N removal of woodchip bioreactors can be improved by the addition of cold-adapted, locally isolated bacterial denitrifying strains (bioaugmentation) or dosing with a carbon (C) source (biostimulation). In Spring 2017, biostimulation removed 66% of the nitrate-N load, compared to 21% and 18% for bioaugmentation and control, respectively. The biostimulation nitrate-N removal rate (NRR) was also significantly greater, 15.0 g N m−3 d−1, versus 5.8 and 4.4 g N m−3 d−1, for bioaugmentation and control, respectively. After five weeks of operation, bioclogging of the biostimulation beds limited dosing for the remainder of the experiment; NRR was greater for biostimulation in Fall 2017, but in Spring 2018 there were no differences among treatments. Carbon dosing did not increase outflow of dissolved organic C concentration. The abundance of one of the inoculated strains, Cellulomonas cellacea strain WB94, increased over time, while another, Microvirgula aerodenitrificans strain BE2.4, increased briefly, returning to background levels after 42 d. Eleven days after inoculation in Spring 2017, outflow nitrate-N concentrations of bioaugmentation were sporadically reduced compared to the control for two weeks, but the effects were insignificant over the study period. The study suggests that biostimulation and bioaugmentation are promising technologies to enhance nitrate removal during cold conditions. A means of controlling bioclogging is needed for biostimulation, and improved means of inoculation and maintaining abundance of introduced strains is needed for bioaugmentation. In conclusion, biostimulation showed greater potential than bioaugmentation for increasing nitrate removal in a woodchip bioreactor, whereas both methods need improvement before implementation at the field scale. [ABSTRACT FROM AUTHOR]

Multiple critical N dilution curves [CNDCs] have been previously developed for potato; however, attempts to directly compare differences in CNDCs across genotype [G], environment [E], and management [M] interactions have been confounded by non-uniform statistical methods, biased experimental data, and lack of proper quantification of uncertainty in the critical N concentration [%N c ]. This study implements a partially-pooled Bayesian hierarchical method to develop CNDCs for previously published and newly reported experimental data, systematically evaluates the difference in %N c [∆%N c ] across G × E × M effects, and directly compare CNDCs from the Bayesian framework to CNDCs from conventional statistical methods. The partially-pooled Bayesian hierarchical method implemented in this study has the advantage of being less susceptible to inferential bias at the level of individual G × E × M interactions compared to alternative statistical methods that result from insufficient quantity and quality of experimental datasets (e.g., unbalanced distribution of N limiting and non-N limiting observations). This method also allows for a direct statistical comparison of differences in %N c across levels of the G × E × M interactions. Where found to be significant, ∆%N c was hypothesized to be related to variation in the timing of tuber initiation (e.g., maturity class) and the relative rate of tuber bulking (e.g., planting density) across G x E × M interactions. In addition to using the median value for %N c (i.e., CNDC), the lower and upper boundary values for the credible region (i.e., CNDC lo and CNDC up) derived using the Bayesian framework should be used in calculation of N nutrition index (and other calculations) to account for uncertainty in %N c. Overall, this study provides additional evidence that%N c is dependent upon G × E × M interactions; therefore, evaluation of crop N status or N use efficiency must account for variation in %N c across G × E × M interactions. • Critical N dilution curves [CNDCs] for potato are subject to G x E x M effects. • Bayesian methods can quantify uncertainty in critical N concentration [%N c ]. • Partial pooling Bayesian method enables direct comparison of G x E x M effects. • Variation in %N c for potato due to tuber initiation timing and tuber bulking rate. • N use efficiency and N nutrition index depend on %N c variability and uncertainty. [ABSTRACT FROM AUTHOR]

Maize ( Zea mays L.) stover and cobs are potential feedstock sources for cellulosic ethanol production. Nitrogen (N) fertilization is an important management decision that influences cellulosic biomass and grain production, but its effect on cell wall composition and subsequent cellulosic ethanol production is not known. The objectives of this study were to quantify the responses of maize stover (leaves, stalks, husks, and tassel) and cob cell wall composition and theoretical ethanol yield potential to N fertilization across a range of sites. Field experiments were conducted at rainfed and irrigated sites in Minnesota, USA, over a 2-year period. Stover cell wall polysaccharides, pentose sugar concentration, and theoretical ethanol yield decreased as N fertilization increased. Stover Klason lignin increased with N fertilization at all sites. Cob cell wall composition was less sensitive to N fertilization, as only pentose and Klason lignin decreased with N fertilization at two and one site(s), respectively, and hexose increased with N fertilization at one of eight sites. Cob theoretical ethanol yield was not affected by N fertilization at any site. These results indicate variation in stover cellulosic ethanol production is possible as a result of N management. This study also demonstrated that cell wall composition and subsequent theoretical ethanol yield of maize cobs are generally more stable than those with stover because of overall less sensitivity to N management. [ABSTRACT FROM AUTHOR]

• A comprehensive assessment of the effectiveness of nitrification inhibitor DMPP under varying N rates and application timings on potato yield and NUE under tropical conditions was performed. • Compared to the conventional practice, split applied ammonium sulfate nitrate with DMPP (ASN + DMPP), at either 75% or 100% of recommended N rate (RNR), reduced N surplus in site-years with greater rainfall events and consistently increased potato tuber yield. • At reduced N rate (75% of RNR), single ASN + DMPP application at planting decreased potato yield, but at 100% of RNR potato production was not different from that receiving conventional N fertilization. • The mutual agronomic, economic, and environmental benefits of split-applied ASN + DMPP at 75% of RNR can contribute to the increased sustainability of tropical potato cropping systems. However, further studies are needed to confirm these benefits in other agro-ecosystems. Urea is the dominant nitrogen (N) fertilizer used for potato (Solanum tuberosum L.) cultivation in most parts of the world. Fertilizers containing a nitrification inhibitor (NI) claim to improve performance of crops including potato. No studies to date have conducted comprehensive assessment of N sources and the effectiveness of NI under varying N rates or application timings to enhance potato yield, tuber quality or N-use efficiency (NUE) in tropical regions. Three field experiments were conducted on irrigated sandy soils in southeastern Brazil to determine whether single or split application of ammonium sulfate nitrate (ASN) with the NI 3,4-dimethylpyrazole phosphate (DMPP) at reduced (75%) or recommended N rates (RNR, 100% = 160 kg ha-1) could improve yield, quality and/or NUE of 'Agata' potato over conventional split-applied urea at 100% of RNR. Compared to the conventional practice, split-applied ASN + DMPP, at either 75% or 100% of RNR, increased fresh tuber yield by an average of 15% across all site-years (SYs) and reduced N surplus in SYs with greater rainfall events suggesting that reactive N losses to the environment were also reduced. With split-applied ASN + DMPP at 75% of RNR, fresh tuber yield per unit of applied N increased by 34% compared to split-applied ASN + DMPP at 100% of RNR, and by 50–75% compared to a single application of ASN + DMPP at planting. These results demonstrate a mutually beneficial opportunity, where the rate of split-applied ASN + DMPP can be reduced by 25% while at the same time increasing yields, thus resulting in agronomic, economic, and environmental benefits due to the decreased potential for off-site reactive N losses. [ABSTRACT FROM AUTHOR]

Importance: Nitrate pollution is a serious problem in agricultural areas in the U.S. Midwest and other parts of the world. Woodchip bioreactor is a promising technology that uses microbial denitrification to remove nitrate from agricultural subsurface drainage, although the reactor's nitrate removal performance is limited under cold conditions. This study showed that the inoculation of cold-adapted denitrifiers (i.e., bioaugmentation) and the addition of labile carbon (i.e., biostimulation) can influence the microbial populations and enhance the reactor's performance under cold conditions. This finding will help establish a strategy to mitigate nitrate pollution., Competing Interests: The authors declare no conflict of interest.

Efforts to mitigate the nitrogen (N) footprint of maize production include using N-fixing microbes (NFM) and/or microbial inhibitors. We quantified the effects of NFM, the nitrification inhibitor (NI) 2-(N-3,4-dimethyl-1H-pyrazol-1-yl) succinic acid isomeric mixture, and the urease inhibitor (UI) N-(n-butyl) thiophosphoric triamide, each applied by itself or paired with another additive, on nitrous oxide (N 2 O) emissions, nitrate (NO 3 - ) leaching, and crop performance in contrasting irrigated and rainfed maize systems over two growing seasons. We also used published emission factors to estimate indirect N 2 O emissions from leached NO 3 - that can be converted to N 2 O. Agronomic effects were relatively small; the NI + NFM treatment increased N use efficiency and grain yield and protein content in some cases by 11%-14% relative to a treatment receiving only urea. Most of the additive treatments reduced direct (in-field) N 2 O emissions, most consistently for treatments that contained NI which reduced emissions by 24%-77%. However, these beneficial effects were counteracted by increased NO 3 - leaching, which occurred most consistently with UI or NFM applied as single additives or with NI. In these treatments, NO 3 - leaching increased during at least one growing season, and at both sites, by factors of 2-7. In three site-years, increased NO 3 - leaching with NFM and NI + NFM offset large reductions in direct N 2 O, such that total direct + indirect N 2 O emissions were not different from that in the urea only treatment. These unintended effects may have resulted from unfavorable rainfall timing, varying crop N demand, and declining additive effectiveness. Use of these soil additives requires caution and further study., (© 2023 The Authors. Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Field studies conducted over time to collect any type of plant response to a set of treatments are often not treated as repeated measures data. The most used approaches for statistical analyses of this type of longitudinal data are based on separate analyses such as ANOVA, regression, or time contrasts. In many instances, during the review of manuscripts, reviewers have asked researchers to treat year, for example, as a random effect and ignore the interactions between year and other main effects. One drawback of this approach is that the correlation between measurements taken on the same subject over time is ignored. Here, we show that avoiding the covariance between measurements can induce erroneous (e.g., no differences reported when they exist, or differences reported when they actually do not exist) inference of treatment effects. Another issue that has received little attention for statistical inference of multi-year field experiments is the combination of fixed, random, and repeated measurement effects in the same statistical model. This type of analysis requires a more in-depth understanding of modeling error terms and how the statistical software used translates the statistical language of the given command into mathematical computations. Ignoring possible significant interactions among repeated, fixed, and random effects might lead to an erroneous interpretation of the data set. In this manuscript, we use data from two field experiments that were repeated during two and three consecutive years on the same plots to illustrate different modeling strategies and graphical tools with an emphasis on the use of mixed modeling techniques with repeated measures.

Nitrogen (N) loss from cropping systems has important environmental implications, including contamination of drinking water with nitrate. A 2-yr study evaluated the effects of six N rate, source, and timing treatments, including a variable rate (VR) N treatment based on the N sufficiency index approach using remote sensing, and two irrigation rate treatments, including conventional and reduced rate, on nitrate leaching, residual soil nitrate, and plant N uptake for potato (Solanum tuberosum L. cv. Russet Burbank) production in 2016 and 2017 on a Hubbard loamy sand. Nitrate leaching losses measured with suction-cup lysimeters varied between 2016 and 2017 with flow-weighted mean nitrate N concentrations of 5.6 and 12.8 mg N L -1 , respectively, and increased from 7.1 to 10.4 mg N L -1 as N rate increased from 45 to 270 kg N ha -1 . Despite reductions in N rate of 22 and 44 kg N ha -1 in 2016 and 2017, respectively, for the VR N treatment, there was no significant difference in nitrate leaching compared with the existing N best management practices (BMPs). Reducing irrigation rate by 15% decreased nitrate leaching load by 17% through a reduction in percolation. Residual soil nitrate N in the top 60 cm across all treatments (7.9 mg N kg -1 ) suggests a risk for nitrate leaching during the nongrowing season, and plant N uptake did not explain yearly variation in nitrate leaching and residual soil nitrate. Although existing N BMPs are effective at controlling N losses, development of alternative practices is needed to further reduce the risk of groundwater contamination., (© 2020 The Authors. Journal of Environmental Quality © 2020 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Three different woodchip forms were tested for bromide sorption including ground woodchip, unwashed woodchips, and washed woodchips. We used six varying initial bromide concentrations to conduct the bromide sorption experiments with each woodchip form. Data on the initial and equilibrium bromide concentrations, wood mass, and initial and equilibrium solution pH from each of the six experiments are presented. Seven bromide tracer tests were conducted on field-scale denitrification beds. In this paper, data from each of the tracer tests including variation of bromide concentration over time and hydraulic indices of the tracer tests are presented. Interpretation of the data can be found in the research article entitled "Efficacy of bromide tracers for evaluating the hydraulic performance of denitrification beds treating agricultural drainage water" [1].

Woodchip bioreactor technology removes nitrate from agricultural subsurface drainage by using denitrifying microorganisms. Although woodchip bioreactors have demonstrated success in many field locations, low water temperature can significantly limit bioreactor efficiency and performance. To improve bioreactor performance, it is important to identify the microbes responsible for nitrate removal at low temperature conditions. Therefore, in this study, we identified and characterized denitrifiers active at low-temperature conditions by using culture-independent and -dependent approaches. By comparative 16S rRNA (gene) analysis and culture isolation technique, Pseudomonas spp., Polaromonas spp., and Cellulomonas spp. were identified as being important bacteria responsible for denitrification in woodchip bioreactor microcosms at relatively low temperature conditions (15°C). Genome analysis of Cellulomonas sp. strain WB94 confirmed the presence of nitrite reductase gene nirK . Transcription levels of this nirK were significantly higher in the denitrifying microcosms than in the non-denitrifying microcosms. Strain WB94 was also capable of degrading cellulose and other complex polysaccharides. Taken together, our results suggest that Cellulomonas sp. denitrifiers could degrade woodchips to provide carbon source and electron donors to themselves and other denitrifiers in woodchip bioreactors at low-temperature conditions. By inoculating these denitrifiers (i.e., bioaugmentation), it might be possible to increase the nitrate removal rate of woodchip bioreactors at low-temperature conditions.

Phosphorus enrichment of surface water is a concern in many urban watersheds. A 3-yr study on a silt loam soil with 5% slope and high soil test P (27 mg kg(-1) Bray P1) was conducted to evaluate P fertilization and clipping management effects on P runoff from turfgrass (Poa pratensis L.) under frozen and nonfrozen conditions. Four fertilizer treatments were compared: (i) no fertilizer, (ii) nitrogen (N)+potassium (K)+0xP, (iii) N+K+1xP, and (iv) N+K+3xP. Phosphorus rates were 21.3 and 63.9 kg ha(-1) yr(-1) the first year and 7.1 and 21.3 kg ha(-1) yr(-1) the following 2 yr. Each fertilizer treatment was evaluated with clippings removed or clippings recycled back to the turf. In the first year, P runoff increased with increasing P rate and P losses were greater in runoff from frozen than nonfrozen soil. In year 2, total P runoff from the no fertilizer treatment was greater than from treatments receiving fertilizer. This was because reduced turf quality resulted in greater runoff depth from the no fertilizer treatment. In year 3, total P runoff from frozen soil and cumulative total P runoff increased with increasing P rate. Clipping management was not an important factor in any year, indicating that returning clippings does not significantly increase P runoff from turf. In the presence of N and K, P fertilization did not improve turf growth or quality in any year. Phosphorus runoff can be reduced by not applying P to high testing soils and avoiding fall applications when P is needed.