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Agronomy
Special Issues
Isotopic & Nuclear Techniques in Studying (Agro)environmental Processes
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Isotopic & Nuclear Techniques in Studying (Agro)environmental Processes

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Agricultural Biosystem and Biological Engineering".

Deadline for manuscript submissions: 30 May 2025 | Viewed by 4391

Special Issue Editors

Prof. Dr. Gabrijel Ondrasek

E-Mail Website1 Website2 Website3
Guest Editor
Department of Soil Amelioration, Faculty of Agriculture University of Zagreb, 10000 Zagreb, Croatia
Interests: agroecosystems; soil salinization; crop stress; environmental salinization; salinity management
Special Issues, Collections and Topics in MDPI journals
Dr. Emil Fulajtar

E-Mail Website
Guest Editor
Soil and Water Management & Crop Nutrition Section, Joint FAO/IAEA Centre, Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, P.O. Box 100, 1400 Vienna, Austria
Interests: soil erosion; erosion assessment using fallout radionuclide methods (Cs-137); soil conservation; soil moisture monitoring using cosmic ray neutron sensor; erosion modelling using universal soil loss E
Prof. Dr. Branko Petrinec

E-Mail Website
Guest Editor
Radiation Protection Unit, Institute for Medical Research and Occupational Health, Ksaverska cesta 2, 10000 Zagreb, Croatia
Interests: radioecology and radiation protection

Special Issue Information

Dear Colleagues，

Environmental resource degradation from erosion, contamination, and salinization are among the most critical and rapidly growing constraints for the sustainable management of agroecosystems, threatening food security. Modern, long-term sustainable strategies and approaches to mitigate such degradation processes are based on the prompt and accurate detection and application of specific remediation or conservation measures. Both stable and radioactive isotopic tracer studies have shown their potential for monitoring and better understanding of environmental (e.g., erosion, sub/surface runoff, leaching, contamination) as well as physiological processes of crops (e.g., nutrients/toxic elements cycle, water cycle, evapotranspiration, photosynthesis). The principles of isotopic techniques are based on the spatiotemporal tracing of the movement and transformation of specific isotopes across the subcellular, microscopic, ecosystem, and regional scales.

Stable isotope techniques have been recognized as very powerful empirical tools for the advanced elucidation of plant–environment interactions. Water and nutrient management are very important to increasing crop yield. Improved nutrient and water use efficiency are among the major requirements to achieve sustainable land management. Therefore, stable isotopes are very important tools for measuring the nutrient uptake from various sources for studying the processes that influence the efficiency of the applied fertilizers and irrigation, tracing the fate of fertilizers and water fractions not used by crops, and developing irrigation and fertigation practices minimizing the losses of nutrients and water.

Fallout radionuclides (FRNs) are used for evaluating short- to long‐term soil erosion and deposition processes to complement modelling and conventional measurement methods.

Recently, the detection and monitoring of some environmental processes (erosion, soil moisture regime, salinization) have become instant and accurate due to significant improvements to sensors/detectors and integration with remote sensing and IoT solutions. Such combinations of advanced techniques enable the processing of large datasets and the analysis of numerous studies conducted under variable conditions (e.g., meta-analyses), while the application of artificial intelligence and machine learning algorithms enables the testing of various scenarios under different climate conditions. Therefore, multidisciplinary approaches (e.g., isotopic and nuclear techniques combined and upgraded with hydropedological, physiological, and molecular methods) to address challenges in agroenvironmental research will provide more holistic and proactive solutions for agroecosystems management.

For this Special Issue, we welcome all manuscript types (original studies, reviews, communications, opinions, perspectives, discussions) that show novelty on topics including, but not limited to, the listed keywords.

Prof. Dr. Gabrijel Ondrasek 
Dr. Emil Fulajtar
Prof. Dr. Branko Petrinec
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. Agronomy 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 2600 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

  • isotopic labelling
  • stable isotopes
  • fallout radionuclides
  • radioisotopes
  • mass spectrometry
  • gamma spectrometry
  • alpha spectrometry
  • nuclear technique
  • nuclear magnetic resonance
  • soil erosion
  • salinization
  • soil contamination
  • crop nutrition
  • fertilizers
  • nitrogen use efficiency
  • biological nitrogen fixation
  • water use efficiency
  • nutrient use efficiency
  • environmental monitoring

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Published Papers (2 papers)

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13 pages, 4732 KiB  
Article
Fly Bioash Ameliorates Acid Luvisol and Increases Sunflower (Helianthus annuus L.) Yield in Field Conditions without Compromising the Risk of Radioactive Contamination
by Gabrijel Ondrasek, Filip Kranjčec, Jelena Horvatinec, Marina Bubalo Kovačić, Stjepan Husnjak, Lepomir Čoga, Dinko Babić, Davor Rašeta, Nikola Volarić, Emil Fulajtar, Muhammad Imtiaz Rashid, Aleksandar Včev and Branko Petrinec
Agronomy 2023, 13(7), 1899; https://doi.org/10.3390/agronomy13071899 - 18 Jul 2023
Cited by 3 | Viewed by 1500
Abstract
Fly bioash (FBA) as a by-product of biomass-fuelled facilities exhibits alkaline properties and is enriched with phytonutrients, thereby offering the potential to effectively ameliorate acidic and nutrient-deficient soils. However, concerns about health risks due to a potential FBA radioactive contamination are still not [...] Read more.
Fly bioash (FBA) as a by-product of biomass-fuelled facilities exhibits alkaline properties and is enriched with phytonutrients, thereby offering the potential to effectively ameliorate acidic and nutrient-deficient soils. However, concerns about health risks due to a potential FBA radioactive contamination are still not well studied, notably under field conditions. This study examined pH changes and concentrations of natural (238U, 232Th, 226Ra, 40K) and anthropogenic (137Cs) radionuclides after application of very alkaline (pH > 12) FBA in: (i) highly acid (pHKCl = 4.1) Luvisol and (ii) sunflower (Helianthus annuus L.) seeds, grown in organic farming and rain-fed conditions. FBA (originated from a modern cogeneration, fuelled on certified deciduous forest wood chips) was applied at increasing doses; 0, 4.5, 8.6, 13, and 17.2 t/ha. After 54 months of application, FBA significantly increased soil pHKCl by up to 1.8 unit and the seed yield by 15%, compared with no amended Control, without compromising soil electrical conductivity (salinity). The activity concentrations (Ac) of all observed radionuclides, measured using high-resolution gamma-ray spectrometry, were not altered under FBA application, neither in the surface (0–30 cm) Luvisol horizon nor in the sunflower seed. Moreover, the Ac of 238U, 232Th, and 137Cs in the seed were below detection limit, whereas the Ac of 40K and 226Ra were lower by up to 2.6 and 61 times, respectively, than their corresponding Ac in the soil treatments. The radiological footprint of FBA exhibited lower Ac for most of the observed radionuclides compared with both (i) Croatian non-arable topsoils (with reductions of 238U 3.6 times, 232Th 1.8 times, 226Ra 1.7 times, and 137Cs 1.5 times) and (ii) widely used mineral N/P/K fertilisers in conventional agroecosystems (with reductions of 238U 12.5 times; 226Ra 1.3 times, and 40K 2.4 times). Our findings provide evidence that the application of FBA as a soil conditioner does not pose radiological health or environmental risks, contributing to more sustainable agri-food production and circular bioeconomy. However, it is essential to conduct further studies to comprehensively investigate the effects of FBA application on soil and crop quality across diverse environmental conditions and extended spatiotemporal scales. Full article
(This article belongs to the Special Issue Isotopic & Nuclear Techniques in Studying (Agro)environmental Processes)
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14 pages, 3516 KiB  
Article
Three Bayesian Tracer Models: Which Is Better for Determining Sources of Root Water Uptake Based on Stable Isotopes under Various Soil Water Conditions?
by Junming Liu, Zhuanyun Si, Shuang Li, Sunusi Amin Abubakar, Yingying Zhang, Lifeng Wu, Yang Gao and Aiwang Duan
Agronomy 2023, 13(3), 843; https://doi.org/10.3390/agronomy13030843 - 14 Mar 2023
Cited by 6 | Viewed by 1944
Abstract
Stable hydrogen and oxygen isotopes provide a powerful technique for quantifying the proportion of root water uptake (RWU) from different potential water sources. Although many models coupled with stable isotopes have been developed to estimate plant water source apportionment, inter-comparisons of different methods [...] Read more.
Stable hydrogen and oxygen isotopes provide a powerful technique for quantifying the proportion of root water uptake (RWU) from different potential water sources. Although many models coupled with stable isotopes have been developed to estimate plant water source apportionment, inter-comparisons of different methods are still limited, especially their performance under different soil water content (SWC) conditions. In this study, three Bayesian tracer mixing models, which included MixSIAR, MixSIR and SIAR, were tested to evaluate their performances in determining the RWU of winter wheat under various SWC conditions (normal, dry and wet) in the North China Plain (NCP). The proportions of RWU in different soil layers showed significant differences (p < 0.05) among the three Bayesian models, for example, the proportion of 0–20 cm soil layer calculated by MixSIR, MixSIAR and SIAR was 69.7%, 50.1% and 48.3% for the third sampling under the dry condition (p < 0.05), respectively. Furthermore, the average proportion of the 0–20 cm layer under the dry condition was lower than that under normal and wet conditions, being 45.7%, 58.3% and 59.5%, respectively. No significant difference (p > 0.05) was found in the main RWU depth (i.e., 0–20 cm) among the three models, except for individual sampling periods. The performance of three models in determining plant water source allocation varied with SWC conditions: the performance indicators such as coefficient of determination (R2) and Nash-Sutcliffe efficiency coefficient (NS) in MixSIAR were higher than that in MixSIR and SIAR, showing that MixSIAR performed well under normal and wet conditions. The rank of performance under the dry condition was MixSIR, MixSIAR, and then SIAR. Overall, MixSIAR performed relatively better than other models in predicting RWU under the three different soil moisture conditions. Full article
(This article belongs to the Special Issue Isotopic & Nuclear Techniques in Studying (Agro)environmental Processes)
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