Special Issue "Nitrogen and Carbon Cycle in Agriculture"

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Soils".

Deadline for manuscript submissions: 20 October 2022 | Viewed by 806

Special Issue Editors

Dr. Paolo Ruisi
E-Mail Website
Guest Editor
Department of Agricultural, Food and Forest Sciences, University of Palermo, 90128 Palermo, Italy
Interests: conservation agriculture; N use efficiency; N2 fixation; AM symbiosis; crop productivity; cereals; pulses
Special Issues, Collections and Topics in MDPI journals
Dr. Vito Armando Laudicina
E-Mail Website
Guest Editor
Dipartimento di Scienze Agrarie, Alimentari e Forestali, University Palermo, Viale Sci, I-90128 Palermo, Italy
Interests: soil fertility; indicators of soil quality; soil carbon dynamics; soil microorganisms; greenhouse gas emissions from soil and wastewater treatment
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Badagliacca
E-Mail Website
Guest Editor
Dipartimento di Agraria, University of Reggio Calabria, Reggio Calabria, Italy
Interests: agricultural systems; nitrogen; field crops

Special Issue Information

Dear Colleagues,

Agriculture strongly impacts the global carbon (C) and nitrogen (N) cycles through land-use change and the agronomic management. Unlike natural ecosystems, where the C and N cycles are generally closely coupled, in the agricultural systems farmers profoundly alter the stoichiometric relations between C and N fluxes through practices, such as soil cultivation, N fertilization, use of cover crops or N-fixing crops, and so on. This alteration determines a potential for depletion or accumulation of these two elements in agricultural soils. Thus, for example, soil processes, such as nitrate leaching or emissions of N2O via denitrification would tend to restore stoichiometry by releasing the N in excess. Evidently, such processes can have deleterious, far-reaching consequences for the environment and human health. In this regard, agricultural soils are one of the major contributors to greenhouse gas (GHG) emissions, accounting for about 10–12% of total anthropogenic GHG.

Consequently, there is currently a great interest in developing agronomic practices to minimize C and N losses in order to mitigate their associated negative environmental impacts (e.g., acidification, eutrophication, and GHG emissions). An increased retention of C and N in soil could be achieved through the adoption of integrated management strategies that allow for a recoupling of C and N cycles.

This justifies the pressing urgency to expand understanding of the mechanisms and processes that regulate C and N fluxes in the agricultural systems. This knowledge is, in fact, crucial to develop agronomic practices and design management strategies that increase the efficiency of C and N cycling, which ultimately enhances the sustainability and resilience of the farming systems.

We, therefore, invite scholars to submit manuscripts (e.g., research articles, reviews, meta-analyses) that address the various aspects of C and N cycling in agriculture—from molecular to agro-ecosystem/regional/global scales. Contributions may include, but are not limited to, the following topics:

  • C and N turnover in agricultural soils;
  • Assessing and mitigating GHG emissions from agriculture;
  • Improving C sequestration in agricultural soils;
  • Improving N-use efficiency in crops;
  • Managing C and N cycling to enhance ecosystem services from agriculture;
  • Modeling C and N dynamics in the soil-plant-atmosphere system.

Dr. Paolo Ruisi
Dr. Vito Armando Laudicina
Dr. Giuseppe Badagliacca
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • C and N pools in agricultural soils
  • microbial processes in agricultural soils
  • soil organic matter turnover
  • N mineralization/immobilization
  • C:N ratio
  • C sequestration
  • GHG emissions
  • global warming
  • N-use efficiency
  • soil management
  • conservation agriculture
  • soil degradation
  • denitrification
  • ammonia volatilization
  • N leaching
  • biological N2 fixation

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Calibration Spiking of MIR-DRIFTS Soil Spectra for Carbon Predictions Using PLSR Extensions and Log-Ratio Transformations
Agriculture 2022, 12(5), 682; https://doi.org/10.3390/agriculture12050682 - 11 May 2022
Viewed by 590
Abstract
There is a need to minimize the usage of traditional laboratory reference methods in favor of spectroscopy for routine soil carbon monitoring, with potential cost savings existing especially for labile pools. Mid-infrared spectroscopy has been associated with accurate soil carbon predictions, but the [...] Read more.
There is a need to minimize the usage of traditional laboratory reference methods in favor of spectroscopy for routine soil carbon monitoring, with potential cost savings existing especially for labile pools. Mid-infrared spectroscopy has been associated with accurate soil carbon predictions, but the method has not been researched extensively in connection to C lability. More studies are also needed on reducing the numbers of samples and on how to account for the compositional nature of C pools. This study compares performance of two classes of partial least squares regression models to predict soil carbon in a global (models trained to data from a spectral library), local (models trained to data from a target area), and calibration-spiking (spectral library augmented with target-area spectra) scheme. Topsoil samples were+ scanned with a Fourier-transform infrared spectrometer, total and hot-water extractable carbon determined, and isometric log-ratio coordinates derived from the latter measurements. The best RMSEP was estimated as 0.38 and 0.23 percentage points TC for the district and field scale, respectively—values sufficiently low to make only qualitative predictions according to the RPD and RPIQ criteria. Models estimating soil carbon lability performed unsatisfactorily, presumably due to low labile pool concentration. Traditional weighing of spiking samples by including multiple copies thereof in training data yielded better results than canonical partial least squares regression modeling with embedded weighing. Although local modeling was associated with the most accurate predictions, calibration spiking addressed better the trade-off between data acquisition costs and model quality. Calibration spiking with compositional data analysis is, therefore, recommended for routine monitoring. Full article
(This article belongs to the Special Issue Nitrogen and Carbon Cycle in Agriculture)
Show Figures

Figure 1

Back to TopTop