Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
2.6
1.6
Journals
Nitrogen
Special Issues
Nitrogen Management and Water-Nitrogen Interactions in Agriculture
share announcement

Nitrogen Management and Water-Nitrogen Interactions in Agriculture

A special issue of Nitrogen (ISSN 2504-3129).

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 2819

Special Issue Editor

Dr. José Salvador Rubio-Asensio

E-Mail Website
Guest Editor
Department of Stress and Plant Pathology, Spanish National Research Council, Murcia, Spain
Interests: environment; soil fertility; plant nutrition; soil; agronomy; carbon dioxide; fruit quality; hydroponics; nitrate; weed ecophysiology; salinity stress; atmospheric CO2 concentration

Special Issue Information

Dear Colleagues,

Water and nitrogen are probably the main external resources that most contribute to crop development and yield and whose best use defines the profitability and sustainability of many irrigated agricultural systems. In irrigated agriculture, nitrogen fertilizer management practices, i.e., the forms used, the time and place of application, as well as the amounts applied, are greatly influenced by the irrigation management practices, i.e., type of irrigation, irrigation design, irrigation frequency and irrigation rates. These two farming practices, irrigation and nitrogen fertilization and their joint management, contribute substantially to the higher or lower efficiency in the use of both resources, water and nutrients, and therefore to the sustainability of the agricultural system. In this Special Issue of the journal Nitrogen, we want to highlight the relevance of the joint management of water and nitrogen, how both factors can affect each other, and how necessary it is to integrate or consider both factors to discuss the sustainability of the agricultural system. Therefore, all those works that integrate both practices (irrigation and fertilization) for greater efficiency in the use of water and/or nitrogen will be welcome.

Dr. José Salvador Rubio-Asensio
Guest Editor

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. Nitrogen is an international peer-reviewed open access quarterly 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 1000 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

  • nitrogen
  • water-nitrogen interactions
  • nitrogen fertilizer management
  • nitrogen use efficiency (NUE)
  • water use efficiency (WUE)

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2912 KiB  
Article
Spectral Index-Based Estimation of Total Nitrogen in Forage Maize: A Comparative Analysis of Machine Learning Algorithms
by Aldo Rafael Martínez-Sifuentes, Ramón Trucíos-Caciano, Nuria Aide López-Hernández, Enrique Miguel-Valle and Juan Estrada-Ávalos
Nitrogen 2024, 5(2), 468-482; https://doi.org/10.3390/nitrogen5020030 - 29 May 2024
Cited by 1 | Viewed by 931
Abstract
Nitrogen plays a fundamental role as a nutrient for the growth of leaves and the process of photosynthesis, as it directly influences the quality and yield of corn. The importance of knowing the foliar nitrogen content through Machine Learning algorithms will help determine [...] Read more.
Nitrogen plays a fundamental role as a nutrient for the growth of leaves and the process of photosynthesis, as it directly influences the quality and yield of corn. The importance of knowing the foliar nitrogen content through Machine Learning algorithms will help determine the efficient use of nitrogen fertilization in a context of sustainable agronomic management by avoiding Nitrogen loss and preventing it from becoming a pollutant for the soil and the atmosphere. The combination of machine learning algorithms with vegetation spectral indices is a new practice that helps estimate parameters of agricultural importance such as nitrogen. The objective of the present study was to compare random forest and neural network algorithms for estimating total plant nitrogen with spectral indices. Five spectral indices were obtained from remotely piloted aircraft systems and analyzed by mean, maximum and minimum from each sample plot to finally obtain 15 indices, and total nitrogen was estimated from the georeferenced points. The most important variables were selected with backward, forward and stepwise methods and total nitrogen estimates by laboratory were compared with random forest models and artificial neural networks. The most important indices were NDREmax and TCARImax. Using 15 spectral indices, total nitrogen with a variance of 79% and 81% with random forest and artificial neural network, respectively, was estimated. And only using NDREmax and TCARmax indices, 73% and 79% were explained by random forest and artificial neural network, respectively. It is concluded that it is possible to estimate nitrogen in forage maize with two indices and it is recommended to analyze by phenological stage and with a greater number of field data. Full article
(This article belongs to the Special Issue Nitrogen Management and Water-Nitrogen Interactions in Agriculture)
►▼ Show Figures

Figure 1

20 pages, 1297 KiB  
Article
Crop Rotation and Nitrogen Fertilizer on Nitrate Leaching: Insights from a Low Rainfall Study
by Isabeli P. Bruno, Augusto G. Araújo, Gustavo H. Merten, Audilei S. Ladeira and Victor M. Pinto
Nitrogen 2024, 5(2), 329-348; https://doi.org/10.3390/nitrogen5020022 - 19 Apr 2024
Cited by 1 | Viewed by 1217
Abstract
The intensive use of agricultural fertilizers containing nitrogen (N) can increase the risk of nitrate (NO3−) leaching. However, little information exists regarding its interaction with other factors that influence NO3− leaching, such as no-tillage, which is associated with [...] Read more.
The intensive use of agricultural fertilizers containing nitrogen (N) can increase the risk of nitrate (NO3−) leaching. However, little information exists regarding its interaction with other factors that influence NO3− leaching, such as no-tillage, which is associated with different crop rotation schemes. The objective of this study was to quantify the leachate NO3− concentration and load below the root zone in two different crop rotations under no-tillage, with and without mineral N fertilizer. The experiment was conducted in a no-tillage area in Brazil between 2018 and 2020. The factors were two crop rotations (diversified and simplified) and two N fertilization managements (with and without N fertilizer). The soil solution was collected with suction lysimeters (1 m depth), the NO3− concentration (mg L−1) was spectrophotometrically determined, and the NO3− load (kg ha−1) was calculated from the volume of water drained and the NO3− concentration. The results were categorized into 24 evaluation periods. NO3− leaching was extremely low due to low rainfall throughout the experiment, with no significant differences between the factors and treatments. In the presence of N fertilization, leaching was substantially greater when rainfall increased, and vice versa. No significant difference was observed between the crop rotation schemes, except for one period in which the simplified soybean rotation exhibited high leaching. The evaluated treatments showed less NO3− leaching during the four periods when grass species were cultivated, indicating the importance of grasses in rotation systems. Full article
(This article belongs to the Special Issue Nitrogen Management and Water-Nitrogen Interactions in Agriculture)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop