Significant advances in plant-available and replenishable macro- and micronutrients with soil health-oriented conservation farming: Novel insights from a multi-site on-farm evaluation

作者：Christoph Rosinger, Katharina Keiblinger, Luca Giuliano Bernardini, Dietmar Horn, Gereon Heller, Herbert Eigner, Hans‐Peter Kaul, Sabine Huber, Orracha Sae-Tun, Gernot Bodner · 发表于：Geoderma · 年份：2025 · DOI：10.1016/j.geoderma.2025.117275 · 被引用次数：4 · 研究领域：Soil Carbon and Nitrogen Dynamics、Agricultural Science and Fertilization、Agronomic Practices and Intercropping Systems

• Evaluation of plant-available and replenishable macro- and micronutrients. • On-farm comparison of conventional and conservation farming systems at 21 sites. • Significant conservation farming advances particularly for N org , P, S, K and B. • Increased nutrient availability was also observed at lower soil depths (20–35 cm) • Microbial necromass was confirmed as an important nutrient source in arable soils. While conservation farming practices are known to increase soil health and ecosystem functioning, little is known about their effect on nutrient availability. In this study, we conducted an on-farm evaluation of conservation farming advances in plant-available and replenishable macro- and micronutrients. Therefore, three different management systems (conventional farming, conservation farming, and an adjacent field margin as reference system) at 21 sites were sampled at three soil depths (0–5, 5–20 and 20–35 cm), and plant-available and replenishable nutrients were extracted by electro-ultrafiltration and subsequently measured by absorption and emission spectrophotometry. Conservation farming systems significantly increased both plant-available and replenishable nutrient fractions as compared to conventional farming systems. In particular, both fractions of N org , P, S and K were strongly elevated through conservation farming; plant-available S contents in the conservation farming system were even higher than in adjacent field margins. Using multiple linear regression a...