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Naslov:Application of self-organizing maps to explore the interactions of microorganisms with soil properties in fruit crops under different management and pedo-climatic conditions
Avtorji:ID Antonucci, Francesca (Avtor)
ID Violino, Simona (Avtor)
ID Canfora, Loredana (Avtor)
ID Tartanus, Malgorzata (Avtor)
ID Furmanczyk, Ewa M. (Avtor)
ID Turci, Sara (Avtor)
ID Tommasini, Maria Grazia (Avtor)
ID Cvelbar Weber, Nika (Avtor)
ID Razinger, Jaka (Avtor)
ID Ourry, Morgane (Avtor)
ID Bickel, Samuel (Avtor)
ID Passey, Thomas A. J. (Avtor)
ID Bohr, Anne (Avtor)
ID Maisel, Heinrich (Avtor)
ID Pugliese, Massimo (Avtor)
ID Vitali, Francesco (Avtor)
ID Mocali, Stefano (Avtor)
ID Pallottino, Federico (Avtor)
ID Figorilli, Simone (Avtor)
ID Costa, Corrado (Avtor)
ID Malusà, Eligio (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://www.mdpi.com/2571-8789/9/1/10
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo KIS - Kmetijski inštitut Slovenije
Povzetek:Self-organizing maps (SOMs) are a class of neural network algorithms able to visually describe a high-dimensional dataset onto a two-dimensional grid. SOMs were explored to classify soils based on an array of physical, chemical, and biological parameters. Methods: The SOM analysis was performed considering soil physical, chemical, and microbial data gathered from an array of apple orchards and strawberry plantations managed by organic or conventional methods and located in different European climatic zones. Results: The SOM analysis considering the “climatic zone” categorical variables was able to discriminate the samples from the three zones for both crops. The zones were associated with different soil textures and chemical characteristics, and for both crops, the Continental zone was associated with microbial parameters—including biodiversity indices derived from the NGS data analysis. However, the SOM analysis based on the “management method” categorical variables was not able to discriminate the soils between organic and integrated management. Conclusions: This study allowed for the Soil Syst. 2025, 9, 10 https://doi.org/10.3390/soilsystems9010010 Soil Syst. 2025, 9, 10 2 of 14 discrimination of soils of medium- and long-term fruit crops based on their pedo-climatic characteristics and associating these characteristics to some indicators of the soil biome, pointing to the possibility of better understanding the interactions among diverse variables, which could support unraveling the intricate web of relationships that define soil quality.
Ključne besede:apple, neural networks, soil microbiome diversity, strawberry
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:26.01.2025
Leto izida:2025
Št. strani:14 str.
Številčenje:Vol. 9, iss. 1, art. 10
PID:20.500.12556/DiRROS-21443 Novo okno
UDK:634.1/.7
ISSN pri članku:2571-8789
DOI:10.3390/soilsystems9010010 Novo okno
COBISS.SI-ID:224921091 Novo okno
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 3. 2. 2025;
Datum objave v DiRROS:03.02.2025
Število ogledov:31
Število prenosov:10
Metapodatki:XML DC-XML DC-RDF
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Gradivo je del revije

Naslov:Soil systems
Skrajšan naslov:Soil syst.
Založnik:MDPI AG, 2017-
ISSN:2571-8789
COBISS.SI-ID:529825561 Novo okno

Gradivo je financirano iz projekta

Financer:EC - European Commission
Številka projekta:817946
Naslov:Exploiting the multifunctional potential of belowground biodiversity in horticultural farming
Akronim:EXCALIBUR

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

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