Prediction of nitrogen mineralization from novel bio-based fertilizers using chemical extractions

IF 6.7 2区 环境科学与生态学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
L. Agostini , E.K. Bünemann , C. Jakobsen , T. Salo , L. Wester-Larsen , S. Symanczik
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Abstract

Bio-based fertilizers (BBFs) are an increasingly important source of nutrients in agriculture, promoted by the new EU fertilizer regulation aiming to enable a circular bioeconomy. Predicting the mineralization-dependent nutrient release of BBFs is critical for their appropriate use and to minimize environmental losses. We assessed mineralizable nitrogen (N) and carbon (C) of a representative selection of 32 BBFs and evaluated a set of chemical extraction methods to predict their N mineralization dynamics. In 84-day aerobic incubations, cumulative mineral N release varied between −13 and 100 % of amended N. Mineralized C ranged from 10 % to 117 % of amended C. Based on the dynamics of N and C mineralization, BBFs were classified into five significantly different groups. Among the tested chemical indicators of N mineralization from BBFs, cold and hot water presented the lowest extraction intensities, followed by hot potassium chloride and hot sulfuric acid extractions, while C:N ratio is based on total contents. Mineral N released almost immediately was best predicted by cold water extractable N, while hot sulfuric acid extractable N and C:N ratio predicted N released after the first two weeks and after 84 days, respectively. The combination of these three indicators was able to discriminate BBFs into four out of five mineralization classes. Such a cost-effective yet accurate estimation of N mineralization dynamics from BBFs can therefore be used as a basis to inform farmers on suitable timing and amount of BBF application, improving the synchrony between N release from BBFs and crop N demand.

利用化学萃取法预测新型生物基肥料的氮矿化度
生物基肥料(BBFs)是农业中日益重要的养分来源,欧盟新肥料法规旨在促进循环生物经济的发展。预测生物基肥料随矿化度变化的养分释放量,对于合理使用生物基肥料和最大限度地减少环境损失至关重要。我们评估了具有代表性的 32 种 BBF 的可矿化氮(N)和碳(C),并评估了一套化学萃取方法,以预测它们的氮矿化动态。根据氮和碳的矿化动态,BBF 被分为五个明显不同的组别。在测试的 BBF N 矿化化学指标中,冷水和热水的萃取强度最低,其次是热氯化钾和热硫酸萃取,而 C:N 比率则基于总含量。冷水可萃取氮最能预测几乎立即释放的矿物氮,而热硫酸可萃取氮和 C:N 比率则分别预测头两周和 84 天后释放的氮。这三个指标的组合能够将 BBF 区分为五个矿化类别中的四个。因此,这种既经济又准确的 BBF 氮矿化动态估算方法可作为农民了解施用 BBF 的适当时机和用量的依据,从而提高 BBF 氮释放与作物氮需求之间的同步性。
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来源期刊
Environmental Technology & Innovation
Environmental Technology & Innovation Environmental Science-General Environmental Science
CiteScore
14.00
自引率
4.20%
发文量
435
审稿时长
74 days
期刊介绍: Environmental Technology & Innovation adopts a challenge-oriented approach to solutions by integrating natural sciences to promote a sustainable future. The journal aims to foster the creation and development of innovative products, technologies, and ideas that enhance the environment, with impacts across soil, air, water, and food in rural and urban areas. As a platform for disseminating scientific evidence for environmental protection and sustainable development, the journal emphasizes fundamental science, methodologies, tools, techniques, and policy considerations. It emphasizes the importance of science and technology in environmental benefits, including smarter, cleaner technologies for environmental protection, more efficient resource processing methods, and the evidence supporting their effectiveness.
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