Soil Depth Stratification of Mineral Nitrogen and Functional Genes in Organic Sugar Beet Fields

(1) Background: Soil fertility in organic systems depends on interactions between physicochemical properties and biological processes that regulate nutrient availability along the soil profile. However, information on their vertical distribution remains limited, particularly for root crops such as sugar beet. This study evaluated depth-related patterns in soils from three organic farms growing sugar beet. (2) Methods: Soil profiles (0–120 cm) were sampled and analyzed for physicochemical properties, mineral nitrogen (N) forms, and biological indicators, including the QBS-ar index, microbial abundance, and functional genes involved in N and carbon cycling. (3) Results: Nitrate-N and total mineral N were mainly concentrated in the 0–40 cm layer and declined markedly with depth. Microbial abundance and most N-cycling functional genes were similarly enriched in the topsoil, showing clear vertical stratification. Statistical analyses suggested that functional gene composition was associated with mineral N gradients after accounting for soil depth. (4) Conclusions: These findings provide an exploratory indication of relationships between mineral N forms and microbial indicators in an organically managed sugar beet system. Given the limited number of sampling units, results should be interpreted cautiously. However, these results highlight the value of soil profile approaches for understanding N redistribution and improving nutrient management strategies.

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Publication Details

Journal
Agriculture
Published
2026-04-26
DOI
https://doi.org/10.3390/agriculture16090952
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Soil Depth Stratification of Mineral Nitrogen and Functional Genes in Organic Sugar Beet Fields

Federico Gavinelli, Claudia Chiodi, Andrea Squartini, Carmelo Maucieri et al.
Agriculture
Soil Carbon and Nitrogen Dynamics
article

Soil Depth Stratification of Mineral Nitrogen and Functional Genes in Organic Sugar Beet Fields

Federico Gavinelli, Claudia Chiodi, Andrea Squartini, Carmelo Maucieri, Giuseppe Concheri, Giulia Zardinoni, Lucia Giagnoni, Samathmika Ravi, Francesca Ragazzi, Maria Giordano, Gui Geng, Piergiorgio Stevanato, Shunlei Li, Yuguang Wang, Marco Gnudi
article en

Abstract

(1) Background: Soil fertility in organic systems depends on interactions between physicochemical properties and biological processes that regulate nutrient availability along the soil profile. However, information on their vertical distribution remains limited, particularly for root crops such as sugar beet. This study evaluated depth-related patterns in soils from three organic farms growing sugar beet. (2) Methods: Soil profiles (0–120 cm) were sampled and analyzed for physicochemical properties, mineral nitrogen (N) forms, and biological indicators, including the QBS-ar index, microbial abundance, and functional genes involved in N and carbon cycling. (3) Results: Nitrate-N and total mineral N were mainly concentrated in the 0–40 cm layer and declined markedly with depth. Microbial abundance and most N-cycling functional genes were similarly enriched in the topsoil, showing clear vertical stratification. Statistical analyses suggested that functional gene composition was associated with mineral N gradients after accounting for soil depth. (4) Conclusions: These findings provide an exploratory indication of relationships between mineral N forms and microbial indicators in an organically managed sugar beet system. Given the limited number of sampling units, results should be interpreted cautiously. However, these results highlight the value of soil profile approaches for understanding N redistribution and improving nutrient management strategies.

AgricultureVol. 16(9)
Agenzia Regionale per la Protezione Ambientale del Piemonte (IT), University of Padua (IT), Heilongjiang University (CN)
China Scholarship Council
Life in Land
Openalex Percentile: Top 9%
Soil Carbon and Nitrogen Dynamics
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