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22 pages, 625 KiB  
Review
Nitrogen Dynamics in Wetland Systems and Its Impact on Biodiversity
by Anum Yousaf, Noreen Khalid, Muhammad Aqeel, Ali Noman, Nayab Naeem, Wajiha Sarfraz, Ujala Ejaz, Zonaira Qaiser and Arifa Khalid
Nitrogen 2021, 2(2), 196-217; https://doi.org/10.3390/nitrogen2020013 - 1 May 2021
Cited by 30 | Viewed by 13071
Abstract
Wetlands are viable sinks for nitrate and have also been identified as a source of nitrous oxide, a product of two microbially regulated processes: nitrification and denitrification. Anthropogenic expansion of nitrogen is a leading cause of the eutrophication of water bodies and may [...] Read more.
Wetlands are viable sinks for nitrate and have also been identified as a source of nitrous oxide, a product of two microbially regulated processes: nitrification and denitrification. Anthropogenic expansion of nitrogen is a leading cause of the eutrophication of water bodies and may also contribute to the deterioration of the ozone layer in the stratosphere. Wetlands ameliorate the quality of water percolating through them, by retaining nutrients and sequestering carbon, and simultaneously enhancing the flora and fauna diversity of these landscapes. Among the many services these wetlands provide, they also alleviate nitrate pollution by attenuating reactive nitrogen from agricultural drainage and ensure the effective reclamation of the wastewater. The literature regarding the viability of wetlands suggests a linear relationship between the removal of nitrogen and its loading rate, thereby suggesting a potential loss of nitrogen removal capacity due to the loss of wetland area. This review discusses the nitrogen removal mechanisms in existing wetlands along with the environmental variables affecting the optimum performance and management of these wetlands, in terms of greenhouse gas retention and biodiversity. Conservation of these wetlands should be contemplated to maintain the world-wide nitrogen cycle and diminish the negative repercussions of surplus nitrogen loading. Full article
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<p>Illustration of the potential pathway for nitrogen transformation in wetlands.</p>
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23 pages, 985 KiB  
Review
Nitrogen Cycling and Mass Balance in the World’s Mangrove Forests
by Daniel M. Alongi
Nitrogen 2020, 1(2), 167-189; https://doi.org/10.3390/nitrogen1020014 - 1 Dec 2020
Cited by 36 | Viewed by 7316
Abstract
Nitrogen (N) cycling in mangroves is complex, with rapid turnover of low dissolved N concentrations, but slow turnover of particulate N. Most N is stored in soils. The largest sources of N are nearly equal amounts of mangrove and benthic microalgal primary production. [...] Read more.
Nitrogen (N) cycling in mangroves is complex, with rapid turnover of low dissolved N concentrations, but slow turnover of particulate N. Most N is stored in soils. The largest sources of N are nearly equal amounts of mangrove and benthic microalgal primary production. Dissolved N fluxes between the forests and tidal waters show net uptake, indicating N conservation. N2-fixation is underestimated as rapid rates measured on tree stems, aboveground roots and cyanobacterial mats cannot currently be accounted for at the whole-forest scale due to their extreme patchiness and the inability to extrapolate beyond a localized area. Net immobilization of NH4+ is the largest ecosystem flux, indicating N retention. Denitrification is the largest loss of N, equating to 35% of total N input. Burial equates to about 29% of total inputs and is the second largest loss of N. Total inputs slightly exceed total outputs, currently suggesting net N balance in mangroves. Mangrove PON export equates to ≈95% of PON export from the world’s tropical rivers, but only 1.5% of the entire world’s river discharge. Mangrove N2O emissions, denitrification, and burial contribute 0.4%, 0.5–2.0% and 6%, respectively, to the global coastal ocean, which are disproportionate to their small worldwide area. Full article
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<p>Vertical profiles of porewater extractable ammonium (NH<sub>4</sub><sup>+</sup>, μM) compared with live root biomass (g dry weight m<sup>2</sup>) in three <span class="html-italic">Kandelia candel</span> forests in the Jiulongjiang estuary, China [<a href="#B9-nitrogen-01-00014" class="html-bibr">9</a>].</p>
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<p>Mean TN stocks in mangrove above- and belowground biomass and soils to a depth of 1 m. Biomass and soil dry weight data extrapolated to N using N content or C/N ratios (<span class="html-italic">g</span>/<span class="html-italic">g</span>) in <a href="#nitrogen-01-00014-t001" class="html-table">Table 1</a>. Tropical terrestrial forest data are presented for comparison and includes data from moist forests, peat swamp forests, and rain forests with N, C and C/N (<span class="html-italic">g</span>/<span class="html-italic">g</span>) data [<a href="#B16-nitrogen-01-00014" class="html-bibr">16</a>,<a href="#B17-nitrogen-01-00014" class="html-bibr">17</a>,<a href="#B18-nitrogen-01-00014" class="html-bibr">18</a>,<a href="#B19-nitrogen-01-00014" class="html-bibr">19</a>,<a href="#B20-nitrogen-01-00014" class="html-bibr">20</a>,<a href="#B21-nitrogen-01-00014" class="html-bibr">21</a>,<a href="#B22-nitrogen-01-00014" class="html-bibr">22</a>,<a href="#B23-nitrogen-01-00014" class="html-bibr">23</a>,<a href="#B24-nitrogen-01-00014" class="html-bibr">24</a>,<a href="#B25-nitrogen-01-00014" class="html-bibr">25</a>,<a href="#B26-nitrogen-01-00014" class="html-bibr">26</a>,<a href="#B27-nitrogen-01-00014" class="html-bibr">27</a>,<a href="#B28-nitrogen-01-00014" class="html-bibr">28</a>,<a href="#B29-nitrogen-01-00014" class="html-bibr">29</a>,<a href="#B30-nitrogen-01-00014" class="html-bibr">30</a>,<a href="#B31-nitrogen-01-00014" class="html-bibr">31</a>,<a href="#B32-nitrogen-01-00014" class="html-bibr">32</a>,<a href="#B33-nitrogen-01-00014" class="html-bibr">33</a>,<a href="#B34-nitrogen-01-00014" class="html-bibr">34</a>,<a href="#B35-nitrogen-01-00014" class="html-bibr">35</a>,<a href="#B36-nitrogen-01-00014" class="html-bibr">36</a>,<a href="#B37-nitrogen-01-00014" class="html-bibr">37</a>,<a href="#B38-nitrogen-01-00014" class="html-bibr">38</a>,<a href="#B113-nitrogen-01-00014" class="html-bibr">113</a>,<a href="#B114-nitrogen-01-00014" class="html-bibr">114</a>,<a href="#B115-nitrogen-01-00014" class="html-bibr">115</a>,<a href="#B116-nitrogen-01-00014" class="html-bibr">116</a>,<a href="#B117-nitrogen-01-00014" class="html-bibr">117</a>,<a href="#B118-nitrogen-01-00014" class="html-bibr">118</a>,<a href="#B119-nitrogen-01-00014" class="html-bibr">119</a>,<a href="#B120-nitrogen-01-00014" class="html-bibr">120</a>] and earlier references within.</p>
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<p>The nitrogen cycle showing all oxidizing and reducing transformation pathways that occur in oxidized and anoxic environments, particularly in marine sediments and waterlogged saline soils. Ammonification (shown in gray on left side) is the microbial breakdown of organic nitrogen (N<sub>ORG</sub>) into ammonium (NH<sub>4</sub><sup>+</sup>); the reverse process is NH<sub>4</sub><sup>+</sup> immobilization (green arrows on left). Nitrification (gray arrows in top side) is the biological oxidation of NH<sub>4</sub><sup>+</sup> to NO<sub>2</sub><sup>−</sup> followed by the oxidation of the NO<sub>2</sub><sup>−</sup> to NO<sub>3</sub><sup>−</sup>. Black dotted arrows depict transport processes between oxic and anoxic environments. Abbreviations: DNRA = dissimilatory nitrate reduction to ammonium; Anammox = anaerobic ammonium oxidation; N<sub>2</sub> fixation = nitrogen fixation; NO = nitric oxide; N<sub>2</sub>O = nitrous oxide; N<sub>2</sub> = nitrogen gas; NH<sub>2</sub>OH = hydroxylamine, an intermediate in biological nitrification; N<sub>2</sub>H<sub>4</sub> = hydrazine, the intermediate in the anaerobic oxidation of ammonium (anammox) process. Reproduced with permission from [<a href="#B121-nitrogen-01-00014" class="html-bibr">121</a>].</p>
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<p>Nitrogen cycling in the world’s mangrove ecosystems. Mean fluxes = Gg N a<sup>−1</sup>; mean standing stocks = Gg N. The model assumes a global mangrove area of 86,495 km<sup>2</sup> [<a href="#B242-nitrogen-01-00014" class="html-bibr">242</a>]. Soil N transformations are lettered as: (<b>A</b>) root + rhizome N<sub>2</sub>-fixation; (<b>B</b>) net nitrification; (<b>C</b>) denitrification; (<b>D</b>) anammox; (<b>E</b>) dissimilatory nitrate reduction to ammonium. Dashed red arrows represent mean values estimated indirectly (by difference); solid blue arrows represent mean values based on empirical measurements (see text for explanation and references). The N pool (both roots and soil) in soils to a depth of 1 m is presented as a box on left in the forest floor. N transformation in soils to depths of 5–20 cm is presented as a box on the right in the forest floor. Unquantified inputs and outputs of dissolved nitrogen from land-derived groundwater and organic matter inputs from adjacent marine waters and catchments are not represented. Abbreviations: ND = no data; AG N Pool = aboveground forest N biomass pool; PP = primary production; NPP = net primary production; NO<sub>2</sub><sup>−</sup> + NO<sub>3</sub><sup>−</sup> = nitrite plus nitrate; NH<sub>4</sub><sup>+</sup> = ammonium; N<sub>2</sub> = gaseous nitrogen; N<sub>2</sub>O = nitrous oxide; NO = nitric oxide; PON = particulate organic nitrogen.</p>
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9 pages, 950 KiB  
Review
Assessing Nitric Oxide (NO) in Higher Plants: An Outline
by Francisco J. Corpas and José M. Palma
Nitrogen 2020, 1(1), 12-20; https://doi.org/10.3390/nitrogen1010003 - 4 May 2018
Cited by 32 | Viewed by 6806
Abstract
Nitric oxide (NO) is a free radical and a component of the N-cycle. Nevertheless, NO is likewise endogenously produced inside plant cells where it participates in a myriad of physiological functions, as well as in the mechanism of response against abiotic and biotic [...] Read more.
Nitric oxide (NO) is a free radical and a component of the N-cycle. Nevertheless, NO is likewise endogenously produced inside plant cells where it participates in a myriad of physiological functions, as well as in the mechanism of response against abiotic and biotic stresses. At biochemical level, NO has a family of derived molecules designated as reactive nitrogen species (RNS) which finally can interact with different bio-macromolecules including proteins, lipids, and nucleic acids affecting their functions. The present review has the goal to provide a comprehensive and quick overview of the relevance of NO in higher plants, especially for those researchers who are not familiar in this research area in higher plants. Full article
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<p>Outline of nitric oxide (NO) metabolism in plant cells. Nitric oxide can be generated, among others, by either nitrate reductase (NR) or by <span class="html-small-caps">l</span>-arginine-dependent nitric oxide synthase (NOS). Then, NO can react with reduced glutathione (GSH) to form <span class="html-italic">S</span>-nitrosoglutathione (GSNO) through a process of <span class="html-italic">S</span>-nitrosation (<span class="html-italic">S</span>-nitrosylation). This metabolite can be converted by the enzyme <span class="html-italic">S</span>-nitrosoglutathione reductase (GSNOR) into oxidized glutathione (GSSG) and NH<sub>3</sub>. GSNO and other <span class="html-italic">S</span>-nitrosothiols can interact with specific protein sulfhydryl groups (P-SH) to produce <span class="html-italic">S</span>-nitrosated proteins (P-SNO) in a process called S-transnitrosation, which can mediate signaling processes. Nitric oxide also interacts rapidly (K ~ 10<sup>10</sup> M<sup>−1</sup> s<sup>−1</sup>) with superoxide radicals (O<sub>2</sub><sup>•−</sup>) to generate peroxynitrite (ONOO<sup>−</sup>), a powerful oxidant molecule that can mediate the tyrosine nitration of proteins (P-Tyr-NO<sub>2</sub>) and also the nitration of fatty acids (NO<sub>2</sub>-FAs). Alternatively, NO in the presence of oxygen is converted into dinitrogen trioxide (N<sub>2</sub>O<sub>3</sub>) and nitrogen dioxide (NO<sub>2</sub>) which, in aqueous solutions, are transformed into nitrite and nitrate. Nitric oxide and related molecules could be part of cell signaling or nitro-oxidative stress processes.</p>
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<p>Nitric oxide (NO) content decreases during ripening of sweet pepper (<span class="html-italic">Capsicum annum</span> L.) fruits and senescence of pea (<span class="html-italic">Pisum sativum</span> L.) leaves. (<b>a</b>) Phenotype of pepper fruits at different ripening stages: green, breaking point and red); (<b>b</b>) Pea leaves from young and senescent pea plants (reproduced with permission from Photosynth. Res. (2013) 117: 221–234 [<a href="#B60-nitrogen-01-00003" class="html-bibr">60</a>] by Springer Nature and Copyright Clearance Center).</p>
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17 pages, 3191 KiB  
Article
Short-Term Effect of Nitrogen Fertilization on Carbon Mineralization during Corn Residue Decomposition in Soil
by Tanjila Jesmin, Dakota T. Mitchell and Richard L. Mulvaney
Nitrogen 2021, 2(4), 444-460; https://doi.org/10.3390/nitrogen2040030 - 27 Oct 2021
Cited by 10 | Viewed by 5968
Abstract
The effect of N fertilization on residue decomposition has been studied extensively; however, contrasting results reflect differences in residue quality, the form of N applied, and the type of soil studied. A 60 d laboratory incubation experiment was conducted to ascertain the effect [...] Read more.
The effect of N fertilization on residue decomposition has been studied extensively; however, contrasting results reflect differences in residue quality, the form of N applied, and the type of soil studied. A 60 d laboratory incubation experiment was conducted to ascertain the effect of synthetic N addition on the decomposition of two corn (Zea mays L.) stover mixtures differing in C:N ratio by continuous monitoring of CO2 emissions and periodic measurement of microbial biomass and enzyme activities involved in C and N cycling. Cumulative CO2 production was greater for the high than low N residue treatment, and was significantly increased by the addition of exogenous N. The latter effect was prominent during the first month of incubation, whereas N-treated soils produced less CO2 in the second month, as would be expected due to more rapid substrate depletion from microbial C utilization previously enhanced by greater N availability. The stimulatory effect of exogenous N was verified with respect to active biomass, microbial biomass C and N, and cellulase and protease activities, all of which were significantly correlated with cumulative CO2 production. Intensive N fertilization in modern corn production increases the input of residues but is not conducive to soil C sequestration. Full article
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<p>Unit used for incubation with atmospheric sampling by the system of Horgan et al. [<a href="#B38-nitrogen-02-00030" class="html-bibr">38</a>], consisting of a specimen container with soil (1) in a 1.9 L Mason jar equipped with a lid having inlet (2) and outlet (3) ball valves (item # 38EF92, Grainger, Lake Forest, IL, USA) connected to 6.4 mm O.D. brass tubing (4).</p>
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<p>Total quantity of CO<sub>2</sub>-C produced by soil in 10 d intervals during a 60 d aerobic incubation involving the following nine treatments: (<b>A</b>) unamended control, potassium nitrate (PN), ammonium sulfate (AS); (<b>B</b>) high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS); and (<b>C</b>) low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data shown as a mean from triplicate incubations with standard error bars and a table for mean comparisons. Within a given incubation interval, treatments followed by the same letter do not differ significantly at <span class="html-italic">p</span> &lt; 0.05. When compared at a smaller scale (<b>A</b>), CO<sub>2</sub>-C was significantly greater (<span class="html-italic">p</span> &lt; 0.01) for the control than for the PN or AS treatment.</p>
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<p>Cumulative CO<sub>2</sub>-C produced by soil during half or all of a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data shown as a mean from triplicate incubations with standard error bars obtained for the total amount of CO<sub>2</sub> collected. Treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) for the entire 60 d incubation period when bars are accompanied by the same letter.</p>
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<p>Soil pH during a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data shown as a mean from duplicate incubations for 7 and 60 d with standard error bars. Treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) when bars are accompanied by the same letter.</p>
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<p>Active biomass measured at five intervals (7, 14, 30, 45, and 60 d) during a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data for each incubation interval shown as a mean from duplicate subsamples with standard error bars. Statistical analyses were performed after averaging data for all five intervals, and treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) when bars are accompanied by the same letter.</p>
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<p>Microbial biomass C (<b>A</b>) and microbial biomass N (<b>B</b>) measured at five intervals (7, 14, 30, 45, and 60 d) during a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data for each incubation interval shown as a mean from duplicate subsamples with standard error bars. Statistical analyses were performed after averaging data for all five intervals, and treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) when bars are accompanied by the same letter.</p>
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<p>Mean cellulase (<b>A</b>) and protease (<b>B</b>) activities measured at five intervals (7, 14, 30, 45, and 60 d) during a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (LNR + AS). Data shown as a mean from triplicate incubations with standard error bars. Treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) when bars are accompanied by the same letter.</p>
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<p>Gross mineralization/immobilization (<b>A</b>) and net immobilization (<b>B</b>) measured at five intervals (7, 14, 30, 45, and 60 d) during a 60 d aerobic incubation involving an unamended control and the following eight treatments: potassium nitrate (PN), ammonium sulfate (AS), high N residue (HNR) with or without PN (HNR + PN) or AS (HNR + AS), and low N residue (LNR) with or without PN (LNR + PN) or AS (HNR + AS). Values reported as a mean with standard error bars representing duplicate data collected before and after a 3 d incubation with (<sup>15</sup>NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>. Treatments do not differ significantly (<span class="html-italic">p</span> &lt; 0.05) when bars are accompanied by the same lowercase (mineralization) or uppercase (immobilization) letter.</p>
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34 pages, 4799 KiB  
Review
Communicating Nitrogen Loss Mechanisms for Improving Nitrogen Use Efficiency Management, Focused on Global Wheat
by Rebecca L. Whetton, Mary A. Harty and Nicholas M. Holden
Nitrogen 2022, 3(2), 213-246; https://doi.org/10.3390/nitrogen3020016 - 28 Apr 2022
Cited by 14 | Viewed by 5658
Abstract
Nitrogen (N) losses are a major environmental issue. Globally, crop N fertilizer applications are excessive, and N use efficiency (NUE) is low. N loss represents a significant economic loss to the farmer. NUE is difficult to quantify in real time because of the [...] Read more.
Nitrogen (N) losses are a major environmental issue. Globally, crop N fertilizer applications are excessive, and N use efficiency (NUE) is low. N loss represents a significant economic loss to the farmer. NUE is difficult to quantify in real time because of the multiple chemical–biological–physical factors interacting. While there is much scientific understanding of N interactions in the plant–soil system, there is little formal expression of scientific knowledge in farm practice. The objective of this study was to clearly define the factors controlling NUE in wheat production, focusing on N inputs, flows, transformations, and outputs from the plant–soil system. A series of focus groups were conducted with professional agronomists and industry experts, and their technical information was considered alongside a structured literature review. To express this understanding, clear graphical representations are provided in the text. The analysis of the NUE processes revealed 16 management interventions which could be prioritized to increase farm nitrogen use efficiency. These management interventions were grouped into three categories—inputs, flow between pools, and outputs—and include management options through the range of application errors, fertilizer input choice, root development, pests and disease, soil structure, harvesting and storage errors, and soil resources of water, micronutrients, carbon, nitrogen, and pH. It was noted that technical solutions such as fertilizer formulation and managing organic matter require significant supply chain upgrades. It was also noted that farm-scale decision support would be best managed using a risk/probability-based recommender system rather than generic guidelines. Full article
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<p>The N loss mechanism web showing interactions between N pools and the processes that regulate inputs, flows, and outputs.</p>
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<p>Causes of reduced NUE at the inputs stage due to application management. Icons show rain, frozen ground, dry soil, high temperatures, low wind, relevant to temperate climate (spring, summer, autumn, and winter), and balance (calibration) of application.</p>
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<p>N flow through the soil plant system. Note: Soil pools are oval, and mechanisms are rectangular. Red rectangles indicate losses; green rectangles indicate transformation.</p>
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<p>The mineralization and immobilization processes that regulate the balance of N between soil solution and plant available N pools. Icons show: crop, crop residue, rainfall, wet ground, balance of CNR ratio, and pH, oxygen, moisture, and temperature.</p>
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<p>Soil–root interaction as a regulation of N uptake by the plant. Icons show: weight/pressure applied to dry and wet ground, and oxygen and water availability.</p>
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<p>Uptake and translocation of N by the plant pool. Icons show: rainfall, light intensity, pH, oxygen, plant available water, and temperature.</p>
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<p>Control of volatilization losses from the soil–plant system. Icons show: temperature, wind, rainfall, and crop residue.</p>
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<p>The nitrification-denitrification process that regulates change in the soil solution and plant-available N pools. Icons show: crop uptake, mineral and legume plants (nitrogen fixing), oxygen availability, pH, water availability and temperature.</p>
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<p>Factors controlling leaching, runoff, and erosion loss pathway from the soil-plant system. Icons show: wind, slope and wet ground, and water bonding to cation charge.</p>
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<p>Factors controlling harvest and grain store losses.</p>
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14 pages, 490 KiB  
Article
Effect of Organic and Inorganic Sources of Nitrogen on Growth, Yield, and Quality of Beetroot Varieties in Nepal
by Arati Sapkota, Moha Dutta Sharma, Hom Nath Giri, Bishal Shrestha and Dinesh Panday
Nitrogen 2021, 2(3), 378-391; https://doi.org/10.3390/nitrogen2030026 - 2 Sep 2021
Cited by 3 | Viewed by 5639
Abstract
Economic use of organic and inorganic fertilizers following their availability is necessary for livestock-based Nepalese farming systems. However, how best to integrate these fertilizers in an appropriate manner is not yet clear. Thus, this study was conducted in the horticulture farm of the [...] Read more.
Economic use of organic and inorganic fertilizers following their availability is necessary for livestock-based Nepalese farming systems. However, how best to integrate these fertilizers in an appropriate manner is not yet clear. Thus, this study was conducted in the horticulture farm of the Agriculture and Forestry University (AFU), Rampur, Chitwan, Nepal from November 2018 to February 2019 to evaluate the effect of organic and inorganic sources of nitrogen (N) on growth, yield, and quality of beetroot (Beta vulgaris L.) varieties. The experiment was laid out in a two factorial randomized complete block design with four replications consisting of two beetroot varieties, i.e., Madhur and Ruby Red, and five N source combinations, i.e., N1: 100% poultry manure (PM), N2: 50% PM + 50% urea, N3: 100% farmyard manure (FYM), N4: 50% FYM + 50% urea, and N5: 100% urea (120:80:40 kg NPK ha−1). Results of this study indicated a significant impact of N sources and varieties on the assessed parameters. During harvest, a significantly higher plant height (41.84 cm), number of leaves per plant (14.68), leaf length (34.56 cm), leaf width (11.38 cm), and beetroot diameter (72.15 mm) were observed in the N2 treatment. Likewise, higher economic (49.78 t ha−1) and biological yields (78.69 t ha−1) were also recorded in the N2 compared to other N sources. Out of the two varieties, the Madhur variety was significantly better in most growth and yield parameters. Similarly, the Madhur variety showed a significantly higher economic (44.49 t ha−1) and biological yields (69.79 t ha−1) compared to the Ruby Red variety. However, the physiological weight loss was higher in the Ruby Red variety. Therefore, the current study suggests that an integration of poultry manure along with the combination of N fertilizer and the Madhur variety is the best combination for quality beetroot production in the Terai region of Nepal. Full article
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<p>The weekly average meteorological data of the experimental site (Horticulture farm, AFU, Rampur, Chitwan from November 2018 to January 2019.</p>
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16 pages, 1026 KiB  
Review
Efficiency and Management of Nitrogen Fertilization in Sugar Beet as Spring Crop: A Review
by Ivana Varga, Jurica Jović, Mirta Rastija, Antonela Markulj Kulundžić, Vladimir Zebec, Zdenko Lončarić, Dario Iljkić and Manda Antunović
Nitrogen 2022, 3(2), 170-185; https://doi.org/10.3390/nitrogen3020013 - 12 Apr 2022
Cited by 17 | Viewed by 5609
Abstract
Sugar beet fertilization is a very complex agrotechnical measure for farmers. The main reason is that technological quality is equally important as sugar beet yield, but the increment of the root yield does not follow the root quality. Technological quality implies the concentration [...] Read more.
Sugar beet fertilization is a very complex agrotechnical measure for farmers. The main reason is that technological quality is equally important as sugar beet yield, but the increment of the root yield does not follow the root quality. Technological quality implies the concentration of sucrose in the root and the possibility of its extraction in the production of white table sugar. The great variability of agroecological factors that directly affect root yield and quality are possible good agrotechnics, primarily by minimizing fertilization. It should be considered that for sugar beet, the status of a single plant available nutrient in the soil is more important than the total amounts of nutrients in the soil. Soil analysis will show us the amount of free nutrients, the degree of soil acidity and the status of individual elements in the soil so that farmers can make a compensation plan. An estimate of the mineralizing ability of the soil, the N min, is very important in determining the amount of mineral nitrogen that the plant can absorb for high root yield and good technological quality. The amount of N needed by the sugar beet crop to be grown is an important factor, and it will always will be in the focus for the producers, especially from the aspect of trying to reduce the N input in agricultural production to preserve soils and their biodiversity but also to establish high yields and quality. Full article
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<p>Linear regression models of sugar beet root yield and sucrose content (data obtained from: Malnou et al. [<a href="#B16-nitrogen-03-00013" class="html-bibr">16</a>], Marinković et al. [<a href="#B90-nitrogen-03-00013" class="html-bibr">90</a>,<a href="#B93-nitrogen-03-00013" class="html-bibr">93</a>], Milić et al. [<a href="#B124-nitrogen-03-00013" class="html-bibr">124</a>], Pogłodziński et al. [<a href="#B130-nitrogen-03-00013" class="html-bibr">130</a>], Varga et al. [<a href="#B134-nitrogen-03-00013" class="html-bibr">134</a>], Barłóg et al. [<a href="#B85-nitrogen-03-00013" class="html-bibr">85</a>], Lentz and Lehrsch [<a href="#B137-nitrogen-03-00013" class="html-bibr">137</a>] Carter and Traveller [<a href="#B23-nitrogen-03-00013" class="html-bibr">23</a>], Tarkalson et al. [<a href="#B22-nitrogen-03-00013" class="html-bibr">22</a>], Lauer [<a href="#B138-nitrogen-03-00013" class="html-bibr">138</a>]).</p>
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17 pages, 3153 KiB  
Review
Review on Detection Methods of Nitrogen Species in Air, Soil and Water
by Md Faishal Yousuf and Md Shaad Mahmud
Nitrogen 2022, 3(1), 101-117; https://doi.org/10.3390/nitrogen3010008 - 4 Mar 2022
Cited by 2 | Viewed by 5276
Abstract
Nitrogen species present in the atmosphere, soil, and water play a vital role in ecosystem stability. Reactive nitrogen gases are key air quality indicators and are responsible for atmospheric ozone layer depletion. Soil nitrogen species are one of the primary macronutrients for plant [...] Read more.
Nitrogen species present in the atmosphere, soil, and water play a vital role in ecosystem stability. Reactive nitrogen gases are key air quality indicators and are responsible for atmospheric ozone layer depletion. Soil nitrogen species are one of the primary macronutrients for plant growth. Species of nitrogen in water are essential indicators of water quality, and they play an important role in aquatic environment monitoring. Anthropogenic activities have highly impacted the natural balance of the nitrogen species. Therefore, it is critical to monitor nitrogen concentrations in different environments continuously. Various methods have been explored to measure the concentration of nitrogen species in the air, soil, and water. Here, we review the recent advancements in optical and electrochemical sensing methods for measuring nitrogen concentration in the air, soil, and water. We have discussed the advantages and disadvantages of the existing methods and the future prospects. This will serve as a reference for researchers working with environment pollution and precision agriculture. Full article
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<p>Deteciton methods of nitrogen species.</p>
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<p>Human activities that form reactive nitrogen, and resulting consequences in the environment. [Image credit: Galloway et al., Climate Change Impacts in the United States: The Third National Climate Assessment; Technical Report (U.S. Global Change Research Program; 2014) [<a href="#B24-nitrogen-03-00008" class="html-bibr">24</a>]].</p>
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<p>The n-type and p-type MOS-based gas-sensing method and conduction model. [Reprinted with permission from ref. [<a href="#B32-nitrogen-03-00008" class="html-bibr">32</a>]].</p>
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<p>(<b>A</b>) Schematic of typical NDIR sensor for gas detection. (<b>B</b>) Infrared absorption features for several gases. [Reprinted with permission from ref. [<a href="#B34-nitrogen-03-00008" class="html-bibr">34</a>]].</p>
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<p>(<b>A</b>) Schematic of typical NDIR sensor for gas detection. (<b>B</b>) Infrared absorption features for several gases. [Reprinted with permission from ref. [<a href="#B34-nitrogen-03-00008" class="html-bibr">34</a>]].</p>
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<p>NO<sub>2</sub> measurement across mainland France using ESA satellite data. (<b>a</b>) Correlation coefficient between the overhead columns and the tract-averaged NO<sub>2</sub> (<b>b</b>) distance between the closest surface NO<sub>2</sub> monitoring site and the census tract center point. [Reprinted with permission from ref. [<a href="#B41-nitrogen-03-00008" class="html-bibr">41</a>]].</p>
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<p>Electrochemical cell for a potentiometric measurement with ISE. [Reprinted from ref. [<a href="#B45-nitrogen-03-00008" class="html-bibr">45</a>], by Pavan M. V. Raja &amp; Andrew R. Barron; via OpenStax CNX (CC BY 4.0)].</p>
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<p>(<b>a</b>) Photograph of five LIG SC ISEs on a single polyimide swatch. (<b>b</b>) Illustration of SC-ISE ion sensing. (<b>c</b>) Representative electrode used in soil column studies. Passivated regions are shown as well as bonding pads, working electrode, and reference electrode. [Reprinted with permission from ref. [<a href="#B46-nitrogen-03-00008" class="html-bibr">46</a>]].</p>
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<p>ATR spectroscopy illustration. When an infrared beam enters the ATR device, it is reflected by a series of reflectors and directed toward the ATR crystal that is in contact with target sample. The light is reflected by the crystal producing an evanescence. After leaving the ATR crystal, the reflected energy is directed toward a spectrometer, which generates a sample reflectance spectrum. [Reprinted from ref. [<a href="#B13-nitrogen-03-00008" class="html-bibr">13</a>], by Lamar Burton1, K. Jayachandran2 and S. Bhansali; via IOP (CC BY 4.0)].</p>
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<p>Type and structure of multi-parameter composite probes. [Reprinted with permission from ref. [<a href="#B65-nitrogen-03-00008" class="html-bibr">65</a>]].</p>
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<p>Ammonia concentration detection using (<b>a</b>,<b>c</b>) Nessler’s reagent and (<b>b</b>,<b>d</b>) indophenol blue at different pH. [Reprinted with permission from ref. [<a href="#B75-nitrogen-03-00008" class="html-bibr">75</a>]].</p>
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2053 KiB  
Communication
Biosensor-Mediated In Situ Imaging Defines the Availability Period of Assimilatory Glutamine in Maize Seedling Leaves Following Nitrogen Fertilization
by Travis L. Goron and Manish N. Raizada
Nitrogen 2020, 1(1), 3-11; https://doi.org/10.3390/nitrogen1010002 - 19 Jul 2017
Cited by 2 | Viewed by 4996
Abstract
The amino acid glutamine (Gln) is an important assimilatory intermediate between root-derived inorganic nitrogen (N) (i.e., ammonium) and downstream macromolecules, and is a central regulator in plant N physiology. The timing of Gln accumulation after N uptake by roots has been well characterized. [...] Read more.
The amino acid glutamine (Gln) is an important assimilatory intermediate between root-derived inorganic nitrogen (N) (i.e., ammonium) and downstream macromolecules, and is a central regulator in plant N physiology. The timing of Gln accumulation after N uptake by roots has been well characterized. However, the duration of availability of accumulated Gln at a sink tissue has not been well defined. Measuring Gln availability would require temporal measurements of both Gln accumulation and its reciprocal depletion. Furthermore, as Gln varies spatially within a tissue, whole-organ in situ visualization would be valuable. Here, the accumulation and subsequent disappearance of Gln in maize seedling leaves (Zea mays L.) was imaged in situ throughout the 48 h after N application to roots of N-deprived plants. Free Gln was imaged by placing leaves onto agar embedded with bacterial biosensor cells (GlnLux) that emit luminescence in the presence of leaf-derived Gln. Seedling leaves 1, 2, and 3 were imaged simultaneously to measure Gln availability across tissues that potentially vary in N sink strength. The results show that following root N fertilization, free Gln accumulates and then disappears with an availability period of up to 24 h following peak accumulation. The availability period of Gln was similar in all seedling leaves, but the amount of accumulation was leaf specific. As Gln is not only a metabolic intermediate, but also a signaling molecule, the potential importance of regulating its temporal availability within plant tissues is discussed. Full article
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<p>Schematic image of the <span class="html-italic">GlnLux</span> in situ imaging assay, courtesy of Lisa Smith (University of Guelph). The dots shown in the Petri dish represent <span class="html-italic">GlnLux</span> biosensor cells embedded in the agar. The figure may be re-used under the Creative Commons BY license. CCD, charge-coupled device.</p>
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<p>Luminescence imaging of free Gln from maize seedling leaves: Trial 1 (July 2016). Maize plants were grown in N-free media from germination for 8 d. Plants were then transferred for 2 h to a nutrient solution containing either 0 mM (−N) or 20 mM (+N) total nitrogen provided as ammonium nitrate (<b>A</b>). Three different seedling leaves were harvested and imaged using <span class="html-italic">GlnLux</span> agar (<b>B</b>). Harvesting was performed just prior to application of the −/+N treatments, and twice during the treatments after 1 h and 2 h of N uptake. Following the 2 h N-uptake period, all plants were transferred to N-free nutrient solution. Leaves were again harvested after 4 h, 6 h, 12 h, 24 h, 36 h, and 48 h. Displayed are <span class="html-italic">GlnLux</span> false-colour images of four replicates of each leaf from both the –N (above dashed lines) and +N (below dashed lines) treatments at equivalent harvest timepoints, roughly corresponding to panel <b>A</b>. For display purposes, the three leaves from each plant are arranged along a single column, and the four biological replicates are shown in the same order within each box. The intensity of <span class="html-italic">GlnLux</span> output, from greatest to least, is white, red, yellow, green, and blue, with black indicating absence of <span class="html-italic">GlnLux</span> output. The reader is encouraged to magnify the images.</p>
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<p>Luminescence imaging of free Gln from maize seedling leaves: Trial 2 (December 2016). Maize plants were grown in N-free media from germination for 8 d. Plants were then transferred for 2 h to a nutrient solution containing either 0 mM (−N) or 20 mM (+N) total nitrogen provided as ammonium nitrate (<b>A</b>). Three different seedling leaves were harvested and imaged using <span class="html-italic">GlnLux</span> agar (<b>B</b>). Harvesting was performed just prior to application of the −/+N treatments, and twice during the treatments after 1 h and 2 h of N uptake. Following the 2 h N-uptake period, all plants were transferred to N-free nutrient solution. Leaves were again harvested after 4 h, 6 h, 12 h, 18 h, 24 h, 30 h, 36 h, and 48 h. Displayed are <span class="html-italic">GlnLux</span> false-colour images of four replicates of each leaf from both the –N (above dashed lines) and +N (below dashed lines) treatments at equivalent harvest timepoints, roughly corresponding to panel <b>A</b>. For display purposes, the three leaves from each plant are arranged along a single column, and the four biological replicates are shown in the same order within each box. The intensity of <span class="html-italic">GlnLux</span> output, from greatest to least, is white, red, yellow, green, and blue, with black indicating absence of <span class="html-italic">GlnLux</span> output. The reader is encouraged to magnify the images.</p>
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15 pages, 3454 KiB  
Review
Identifying Sustainable Nitrogen Management Practices for Tea Plantations
by Rhys Rebello, Paul J. Burgess and Nicholas T. Girkin
Nitrogen 2022, 3(1), 43-57; https://doi.org/10.3390/nitrogen3010003 - 14 Jan 2022
Cited by 9 | Viewed by 4988
Abstract
Tea (Camellia sinensis L.) is the most widely consumed beverage in the world. It is mostly grown in the tropics with a heavy dependence on mineral nitrogen (N) fertilisers to maintain high yields while minimising the areas under cultivation. However, N is [...] Read more.
Tea (Camellia sinensis L.) is the most widely consumed beverage in the world. It is mostly grown in the tropics with a heavy dependence on mineral nitrogen (N) fertilisers to maintain high yields while minimising the areas under cultivation. However, N is often applied in excess of crop requirements, resulting in substantial adverse environmental impacts. We conducted a systematic literature review, synthesising the findings from 48 studies to assess the impacts of excessive N application on soil health, and identify sustainable, alternative forms of N management. High N applications lead to soil acidification, N leaching to surface and groundwater, and the emission of greenhouse gases including nitrous oxide (N2O). We identified a range of alternative N management practices, the use of organic fertilisers, a mixture of organic and inorganic fertilisers, controlled release fertilisers, nitrification inhibitors and soil amendments including biochar. While many practices result in reduced N loading or mitigate some adverse impacts, major trade-offs include lower yields, and in some instances increased N2O emissions. Practices are also frequently trialled in isolation, meaning there may be a missed opportunity from assessing synergistic effects. Moreover, adoption rates of alternatives are low due to a lack of knowledge amongst farmers, and/or financial barriers. The use of site-specific management practices which incorporate local factors (for example climate, tea variety, irrigation requirements, site slope, and fertiliser type) are therefore recommended to improve sustainable N management practices in the long term. Full article
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<p>Selection process for the systematic literature review.</p>
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<p>Nitrogen flows in tea plantations, focusing on organic management. Inorganic fertiliser additions could also be used to increase the size of the NO<sub>3</sub><sup>−</sup> and NH<sub>4</sub><sup>+</sup> pools.</p>
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<p>Integrating alternative nitrogen management practices for tea plantations.</p>
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14 pages, 1318 KiB  
Article
Perennial Trees Associating with Nitrogen-Fixing Symbionts Differ in Leaf After-Life Nitrogen and Carbon Release
by Thomas E. Marler
Nitrogen 2020, 1(2), 111-124; https://doi.org/10.3390/nitrogen1020010 - 17 Sep 2020
Cited by 9 | Viewed by 4633
Abstract
Plants that enter symbiotic relationships with nitrogen (N)-fixing microbes contribute some of their N to the community through leaf litter decomposition and mineralization processes. The speed of these processes varies greatly among tree species. Mesocosm methods were used to determine the speed of [...] Read more.
Plants that enter symbiotic relationships with nitrogen (N)-fixing microbes contribute some of their N to the community through leaf litter decomposition and mineralization processes. The speed of these processes varies greatly among tree species. Mesocosm methods were used to determine the speed of N and carbon (C) release from Cycas micronesica, Intsia bijuga, and Serianthes nelsonii leaf litter. Microcosm methods were used to determine soil respiration traits in soils containing the leaf litter. The speed of leaf litter N and C release during decomposition occurred in the order C. micronesica < I. bijuga < S. nelsonii. Soil carbon dioxide efflux was increased by adding leaf litter to incubation soils, and the increase was greatest for S. nelsonii and least for C. micronesica litter. Ammonium, nitrate, total N, organic C, and total C were increased by adding litter to incubation soils, and the differences among the species converged with incubation duration. The rate of increases in available N and decreases in organic C were greatest for S. nelsonii and least for C. micronesica litter. These findings indicate that S. nelsonii litter released N and C rapidly, C. micronesica litter released N and C slowly, and the leaf economic spectrum accurately predicted the differences. Full article
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<p>The influence of decomposition time on leaf litter traits for three Guam tree species. (<b>a</b>) Total pool of carbon in litter that was 3 g initially; (<b>b</b>) Total pool of nitrogen in litter that was 3 g initially; (<b>c</b>) The carbon/nitrogen quotient within litter that was 3 g initially. Markers are mean of 4 replications, and markers with the same letters are not different according to Tukey’s honest significant difference.</p>
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<p>The influence of incubation time on carbon dioxide (CO<sub>2</sub>) efflux from soil following addition of 1% leaf litter from three Guam tree species. Markers are mean of 4 replications. Control: <span class="html-italic">y</span> = 584.172/(<span class="html-italic">x</span> + 3.44) + 13.194; <span class="html-italic">Cycas micronesica</span>: <span class="html-italic">y</span> = 54,333.726/(<span class="html-italic">x</span> + 59.809) − 458.228; <span class="html-italic">Intsia bijuga</span>: <span class="html-italic">y</span> = 17,333.339/(<span class="html-italic">x</span> + 19.363) − 217.959; <span class="html-italic">Serianthes nelsonii</span>: <span class="html-italic">y</span> = 35,929.52/(<span class="html-italic">x</span> + 32.299) − 382.979.</p>
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<p>The influence of incubation time on nitrogen traits as influenced by the addition of leaf litter of three Guam tree species to incubation soil. (<b>a</b>) Ammonium; (<b>b</b>) Nitrate. Markers are mean of 4 replications, and markers with the same letters are not different according to Tukey’s honest significant difference.</p>
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<p>The influence of incubation time on nitrogen (N) traits as influenced by the addition of leaf litter of three Guam tree species to incubation soil. (<b>a</b>) Available N; (<b>b</b>) Total N. Markers are mean of 4 replications, and markers with the same letters are not different according to Tukey’s honest significant difference.</p>
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<p>The influence of incubation time on carbon (C) traits as influenced by the addition of leaf litter of three Guam tree species to incubation soil. (<b>a</b>) Organic C; (<b>b</b>) Total C. Markers are mean of 4 replications, and markers with the same letters are not different according to Tukey’s honest significant difference.</p>
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19 pages, 8593 KiB  
Article
Optimizing N Fertilization for Increasing Yield and Profits of Rainfed Maize Grown under Sandy Loam Soil
by Krishna Dhakal, Bandhu Raj Baral, Keshab Raj Pokhrel, Naba Raj Pandit, Yam Kanta Gaihre and Shree Prasad Vista
Nitrogen 2021, 2(3), 359-377; https://doi.org/10.3390/nitrogen2030025 - 1 Sep 2021
Cited by 13 | Viewed by 4622
Abstract
The optimum dose of fertilizers for crops varies with soil, agro-ecology, and crop management practices. Optimizing application dose is critical to reduce nutrient loss to the environment and increase nitrogen use efficiency (NUE), crop yields, and economic return to farmers. An experiment was [...] Read more.
The optimum dose of fertilizers for crops varies with soil, agro-ecology, and crop management practices. Optimizing application dose is critical to reduce nutrient loss to the environment and increase nitrogen use efficiency (NUE), crop yields, and economic return to farmers. An experiment was conducted to determine the optimum N dose for increasing maize (Zea mays L. cv, Manakamana-3) yield, NUE, and farm profits under rainfed conditions. Five levels of N (0, 60, 120, 180, and 240 kg ha−1), and a non-fertilized treatment were tested in a randomized complete block design with three replications. Effects of each treatment on yield and yield attributing traits, plant lodging and Sterility (plants with no cob or grain formation), NUE, and stay green trait of maize were recorded. Application of N above 120 kg ha−1 (N120) did not have any significant effects on yield and yield components. Nitrogen, at N120 and above, produced highly fertile plants (though sterility slightly increased at N180 and N240), higher N uptake, and lower dead leaf area (18–27%). N120 produced the highest agronomic; yield increase per unit of N application (AEN—26.89 kg grain kg−1 N) and physiological efficiency of N (PEN—42.67 kg grain kg−1 N uptake), and net benefit (USD 500.43). Considering agronomic, economic, and NUE factors, an N dose of 120 kg ha−1 was found optimum for the cultivation of rainfed maize (Manakamana-3) under sandy loam soil. Full article
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<p>Daily fluctuations of maximum and minimum temperature, humidity, and rainfall recorded during the study period. Data of rainfall and temperatures are represented in the primary vertical axis and humidity in the secondary vertical axis. Dates are presented in day-month-year format, year is 2020 (Data source; Office of Hydrology and Meteorology, Kohalpur—we used data of nearest sub-station Mehelkuna).</p>
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<p>Lodging and Sterility observed in different treatments influenced by varying doses of Nitrogen. CK; control treatment, N0; 0 kg ha<sup>−1</sup> N, N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N. Similar letters across the treatments indicate a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Leaf senescence score in different treatments as influenced by N doses. DAS; days after sowing, CK; control treatment, N0; 0 kg ha<sup>−1</sup> N, N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N, senescence scores can be converted to % by using a multiplication factor of 10 (Score of 2 indicates 20% dead leaf area). Same letters across the treatments indicate a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Grain yield produced by different treatments as influenced by Nitrogen doses. CK; control treatment, N0; 0 kg ha<sup>−1</sup> N, N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N, means with similar letters across the treatments denote a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Yield advantage of N fertilized treatments over N omission (N0) plots. CK; control treatment, N0; 0 kg ha<sup>−1</sup> N, N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N. Inverted bar (as in CK) represents negative yield advantage over N0. Similar letters across the treatments indicate a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Total nitrogen uptake, agronomic use efficiency and partial factor productivity of N as influenced by different levels of N. TN; total nitrogen, AEN; agronomic N use efficiency (kg grain kg<sup>−1</sup> N), PFPN; partial factor productivity of N (kg grain kg<sup>−1</sup> N), CK; control treatment, N0; 0 kg ha<sup>−1</sup> N, N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N, the mean values with similar letters across the treatments denote a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Different components of NUEs as influenced by different N doses. REN; Recovery efficiency of N (kg N uptake kg<sup>−1</sup> N), PEN; Physiological efficiency of N (kg grain kg<sup>−1</sup> N uptake), IEN; Internal efficiency of N (kg grain kg<sup>−1</sup> N uptake), UEN; Utilization efficiency of N (kg grain kg<sup>−1</sup> N), N60; 60 kg ha<sup>−1</sup> N, N120; 120 kg ha<sup>−1</sup> N, N180; 180 kg ha<sup>−1</sup> N, N240; 240 kg ha<sup>−1</sup> N. Similar letters across the treatments indicate a non-significant effect (<span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Cob yield in the different treatments as influenced by varying levels of Nitrogen; (<b>T<sub>1</sub></b>) CK—control treatment, (<b>T<sub>2</sub></b>) N0—0 kg ha<sup>−1</sup> N, (<b>T<sub>3</sub></b>) N60—60 kg ha<sup>−1</sup> N, (<b>T<sub>4</sub></b>) N120—120 kg ha<sup>−1</sup> N, (<b>T<sub>5</sub></b>) N180—180 kg ha<sup>−1</sup> N, (<b>T<sub>6</sub></b>) N240—240 kg ha<sup>−1</sup> N.</p>
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44 pages, 3089 KiB  
Review
Microbiogeochemical Traits to Identify Nitrogen Hotspots in Permafrost Regions
by Claudia Fiencke, Maija E. Marushchak, Tina Sanders, Rica Wegner and Christian Beer
Nitrogen 2022, 3(3), 458-501; https://doi.org/10.3390/nitrogen3030031 - 12 Aug 2022
Cited by 8 | Viewed by 4603
Abstract
Permafrost-affected tundra soils are large carbon (C) and nitrogen (N) reservoirs. However, N is largely bound in soil organic matter (SOM), and ecosystems generally have low N availability. Therefore, microbial induced N-cycling processes and N losses were considered negligible. Recent studies show that [...] Read more.
Permafrost-affected tundra soils are large carbon (C) and nitrogen (N) reservoirs. However, N is largely bound in soil organic matter (SOM), and ecosystems generally have low N availability. Therefore, microbial induced N-cycling processes and N losses were considered negligible. Recent studies show that microbial N processing rates, inorganic N availability, and lateral N losses from thawing permafrost increase when vegetation cover is disturbed, resulting in reduced N uptake or increased N input from thawing permafrost. In this review, we describe currently known N hotspots, particularly bare patches in permafrost peatland or permafrost soils affected by thermokarst, and their microbiogeochemical characteristics, and present evidence for previously unrecorded N hotspots in the tundra. We summarize the current understanding of microbial N cycling processes that promote the release of the potent greenhouse gas (GHG) nitrous oxide (N2O) and the translocation of inorganic N from terrestrial into aquatic ecosystems. We suggest that certain soil characteristics and microbial traits can be used as indicators of N availability and N losses. Identifying N hotspots in permafrost soils is key to assessing the potential for N release from permafrost-affected soils under global warming, as well as the impact of increased N availability on emissions of carbon-containing GHGs. Full article
(This article belongs to the Special Issue Nitrogen Cycling in Permafrost Soils)
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<p>Map of study sites of N hotspots in the Arctic and the Antarctic in the continuous and discontinuous permafrost zone summarized in this review. Study sites of permafrost peatlands are marked in red, the sites of hillslope thermokarst in yellow, sites of alluvial soils in green and animal-influenced sites in purple. Maps modified after Brown et al. [<xref ref-type="bibr" rid="B31-nitrogen-03-00031">31</xref>].</p>
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<p>Levels of N availability in permafrost-affected soils. (<bold>I</bold>) N limitation level with tight, mainly organic N cycle dominated by depolymerization and zero or negative net N ammonification rates. Plants and soil organisms compete strongly for dissolved organic N (DON) and ammonium in soils with high soil organic matter (SOM) content and high C/N ratio in bulk soil, which is mainly controlled by high water content. (<bold>II</bold>) Intermediate N level with more open N cycle, indicated by positive net N ammonification, therefore higher ammonium content and lower N competition. (<bold>III</bold>) N hotspot level with lower N immobilization (uptake) and therefore more available N for net inorganic N turnover and therefore more open N cycling with aerobic nitrification and anaerobic denitrification, both processes producing the gases nitric oxide (NO) and nitrous oxide (N<sub>2</sub>O) (in addition to N<sub>2</sub> of denitrification) with the highly mobile nitrate for leaching as an intermediate product. This N level is characterized by a low C/N ratio &lt;25 in bulk soil and intermediate moisture. Due to high inorganic N forms ammonium and nitrate, this level is called N hotspot of N availability.</p>
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<p>Photographs of hotspots with high N availability. (<bold>A</bold>) permafrost peatland in Seida, Komi Republic, Russia (N 67°03′, E 62°57′) with bare peat and vegetation on the frozen peat plateau (July 2010, Maija Marushchak), (<bold>B</bold>) palsa mire in Utsjoki, Finland (N 67°45′, E 27°00′) with bare and vegetated palsa underlied by permafrost and wet fen surface without permafrost (August 2009, Maija Marushchak), (<bold>C</bold>) retrogressive thaw slump on Kurungnakh Island, Lena River Delta, Russia (N 72°20, E 126°17′), with bare and revegetated slump floor and thaw mounds (July 2016, Alexander Schütt), (<bold>D</bold>) alluvial soils on Samoylov Island, Lena River Delta, Russia, (N 72°22, E 126°28′) with bare bright organic-poor and dark organic-rich soil surfaces (July 2008, Claudia Fiencke).</p>
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<p>Hotspots of high N availability in a schematic permafrost landscape of a tundra ecosystem with (<bold>A</bold>) permafrost peat plateaus and palsas with bare peat surfaces in the discontinuous permafrost zone; hillslope thermokarst landscapes such as (<bold>B</bold>) retrogressive thaw slump in the continuous and (<bold>C</bold>) thermo-erosion gully in the discontinuous permafrost zone, (<bold>D</bold>) alluvial soils in the transition between terrestrial and aquatic ecosystems, and the occurrence of (<bold>E</bold>) animal-influenced soils and (<bold>F</bold>) wildfire throughout ecosystem. Blue arrows indicate known gaseous (N<sub>2</sub>O, NO, HONOH) and red arrows indicate lateral N (DIN, DON and TN) fluxes, black arrows indicate probability of N<sub>2</sub>O loss. N form without arrow describes enrichment in soil. DIN = dissolved inorganic, DON = dissolved organic nitrogen, TN = total nitrogen, ? = the N<sub>2</sub>O emission is largely unresolved.</p>
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<p>Biochemical traits of (<bold>A</bold>,<bold>C</bold>,<bold>E</bold>,<bold>G</bold>) N hotspots with high N availability and (<bold>B</bold>,<bold>D</bold>,<bold>F</bold>,<bold>H</bold>) adjacent control sites with N limitation using one described site as an example. (<bold>A</bold>,<bold>B</bold>) water-filled pore space (WFPS), C/N ratio (<bold>C</bold>,<bold>D</bold>) dissolved inorganic nitrogen (DIN, ammonium + nitrate), ratio of DIN to total N (DIN/TN) and nitrate. (<bold>E</bold>,<bold>F</bold>) microbial net N turnover: N mineralization, nitrification, denitrification, and (<bold>G</bold>,<bold>H</bold>) abundance of genes of key functional enzymes of nitrification (<italic>amo</italic>, ammonia monooxygenase in % of 16S rRNA and **log10 gdw<sup>−1</sup>), denitrification (<italic>nirS</italic> + <italic>nir K</italic>, nitrite reductases in % of 16S rRNA, *% of N genes and **log10 gdw<sup>−1</sup>) and (<italic>nirS</italic> + <italic>nirK</italic>)/<italic>nosz</italic> ratio (nitrite reductase/N<sub>2</sub>O reductase *** × 10<sup>3</sup>) in subarctic bare (BP) and vegetated peatland (VP, references see <xref ref-type="table" rid="nitrogen-03-00031-t001">Table 1</xref>), Arctic retrogressive thaw slump (RTS) and undisturbed site (URTS, references see <xref ref-type="app" rid="app1-nitrogen-03-00031">Table S1</xref>), thermoerosion-gully (TEG) and undisturbed site (UTEG) on the Tibet Plateau [<xref ref-type="bibr" rid="B218-nitrogen-03-00031">218</xref>], Arctic bare alluvial soils (AS) and vegetated floodplain (VP) [<xref ref-type="bibr" rid="B119-nitrogen-03-00031">119</xref>,<xref ref-type="bibr" rid="B302-nitrogen-03-00031">302</xref>,<xref ref-type="bibr" rid="B304-nitrogen-03-00031">304</xref>] and animal-influenced permafrost affected soils of the Arctic (AIA) [<xref ref-type="bibr" rid="B234-nitrogen-03-00031">234</xref>] and Antarctic (AIAA) [<xref ref-type="bibr" rid="B188-nitrogen-03-00031">188</xref>,<xref ref-type="bibr" rid="B189-nitrogen-03-00031">189</xref>,<xref ref-type="bibr" rid="B236-nitrogen-03-00031">236</xref>] and non-influenced soils of Arctic (NIA) and Antarctic (NIAA). For more detail, see <xref ref-type="app" rid="app1-nitrogen-03-00031">Table S2</xref>.</p>
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151 KiB  
Editorial
Nitrogen: A New Cross-Disciplinary International Open Access Journal
by Stephen A. Macko
Nitrogen 2020, 1(1), 1-2; https://doi.org/10.3390/nitrogen1010001 - 12 Jun 2017
Viewed by 4567
Abstract
Nitrogen, the element that is intimately associated with essentially all processes on Earth, is the broad focus of a new online, open access journal.[...] Full article
14 pages, 4958 KiB  
Article
Low-Cost Multispectral Sensor Array for Determining Leaf Nitrogen Status
by Mohammad Habibullah, Mohammad Reza Mohebian, Raju Soolanayakanahally, Ali Newaz Bahar, Sally Vail, Khan A. Wahid and Anh Dinh
Nitrogen 2020, 1(1), 67-80; https://doi.org/10.3390/nitrogen1010007 - 25 Aug 2020
Cited by 5 | Viewed by 4566
Abstract
A crop’s health can be determined by its leaf nutrient status; more precisely, leaf nitrogen (N) level, is a critical indicator that carries a lot of worthwhile nutrient information for classifying the plant’s health. However, the existing non-invasive techniques are expensive and bulky. [...] Read more.
A crop’s health can be determined by its leaf nutrient status; more precisely, leaf nitrogen (N) level, is a critical indicator that carries a lot of worthwhile nutrient information for classifying the plant’s health. However, the existing non-invasive techniques are expensive and bulky. The aim of this study is to develop a low-cost, quick-read multi-spectral sensor array to predict N level in leaves non-invasively. The proposed sensor module has been developed using two reflectance-based multi-spectral sensors (visible and near-infrared (NIR)). In addition, the proposed device can capture the reflectance data at 12 different wavelengths (six for each sensor). We conducted the experiment on canola leaves in a controlled greenhouse environment as well as in the field. In the greenhouse experiment, spectral data were collected from 87 leaves of 24 canola plants, subjected to varying levels of N fertilization. Later, 42 canola cultivars were subjected to low and high nitrogen levels in the field experiment. The k-nearest neighbors (KNN) algorithm was employed to model the reflectance data. The trained model shows an average accuracy of 88.4% on the test set for the greenhouse experiment and 79.2% for the field experiment. Overall, the result concludes that the proposed cost-effective sensing system can be viable in determining leaf nitrogen status. Full article
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Figure 1

Figure 1
<p>Destructive and non-destructive methods used for estimating leaf nitrogen status.</p>
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<p>(<b>a</b>) Front view and (<b>b</b>) back view of Sensor1 [<a href="#B27-nitrogen-01-00007" class="html-bibr">27</a>]. (<b>c</b>) Normalized spectral responsivity versus wavelength of Sensor1, which detected at six visible channels―450 nm (channel V), 500 nm (channel B), 550 nm (channel G), 570 nm (channel Y), 600 nm (channel O), and 650 nm (channel R), each with 40 nm FWHM [<a href="#B28-nitrogen-01-00007" class="html-bibr">28</a>].</p>
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<p>(<b>a</b>) Front view and (<b>b</b>) back view of AS7263 spectral breakout board [<a href="#B29-nitrogen-01-00007" class="html-bibr">29</a>]. (<b>c</b>) Normalized spectral responsivity versus wavelength of Sensor2, which detected at six channels―610 nm (channel R), 680 nm (channel S), 730 nm (channel T), 760 nm (channel U), 810 nm (channel V), and 860 nm (channel W), each with 20 nm FWHM [<a href="#B28-nitrogen-01-00007" class="html-bibr">28</a>].</p>
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<p>Side view (<b>a</b>) and bottom view (<b>b</b>) of the physical design, and the connection diagram of the devices (<b>c</b>). Here, Sensor1 and Sensor2 are connected to the multiplexer’s channel 1 and channel 2, and the mux is connected to the control circuit (Raspberry Pi 3 Model B). All read and write communications are through I2C protocol.</p>
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<p>One random canola plant from each of the four nitrogen fertilization concentrations. The photograph was taken during week seven.</p>
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<p>Field view of different canola plots grown under two nitrogen levels at Lewellyn Farm, Saskatoon, Saskatchewan, Canada during the summer of 2019. Here, a total of 42 canola varieties were subjected to low-N and high-N levels, totaling 336 plots. (<b>a</b>). The proposed sensor, (<b>b</b>), is used for taking measurements in the field, (<b>c</b>).</p>
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<p>Field view of different canola plots grown under two nitrogen levels at Lewellyn Farm, Saskatoon, Saskatchewan, Canada during the summer of 2019. Here, a total of 42 canola varieties were subjected to low-N and high-N levels, totaling 336 plots. (<b>a</b>). The proposed sensor, (<b>b</b>), is used for taking measurements in the field, (<b>c</b>).</p>
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<p>Process flow diagram of the methodology starting from calibrating the data with respect to the white surface to hold-out testing.</p>
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<p>Average reflectance versus wavelength (Sensor1) of leaves subjected to four nitrogen fertilization regimes under visible range. The red line indicates the reflectance from 0 g/L plant, the black line represents 6 g/L, blue represents 12 g/L, and the green represents 20 g/L nitrogen rates. All the reflectance is scaled to the 20 g/L reflectance at 550 nm.</p>
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<p>Average reflectance versus wavelength (Sensor2) of canola leaves subjected to four nitrogen fertilization regimes under the NIR range. The red line indicates the reflectance from 0 g/L plant, the black line represents 6 g/L, blue represents 12 g/L, and the green represents 20 g/L nitrogen rates. All the reflectance is scaled to the 20 g/L reflectance at 610 nm.</p>
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<p>Box plots of the weights achieved by the features in five runs. Here, the 12 features are 450, 500, 550, 570, and 600 nm, and 650, 610, 680, 730, 760, 810, and 860 nm.</p>
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