Two decades long-term field trial data on fertilization, tillage, and crop rotation focusing on soil microbes.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-06-12 DOI:10.1038/s41597-025-05314-z

Marie Raab, Lars Schütz, Loreen Sommermann, Doreen Babin, Ioannis Kampouris, Davide Francioli, Rita Grosch, Günter Neumann, Annette Deubel, Joerg Geistlinger, Korinna Bade, Wilfried Rozhon

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引用次数: 0

Abstract

Agricultural long-term field trials provide fundamental data on crop performance and soil characteristics under diverse management practices. This information represents essential knowledge for upcoming challenges in food and nutrition security. Data provided here have been compiled since 2004 from a nitrogen(N)-fertilization intensity, tillage, and crop rotation field trial in Central Germany including standardized metrics regarding soil management, physical soil properties, crop management, crop characteristics, yield, and harvest quality parameters. In 2015, the field trial became a member of the German Agricultural Soil Research Program BonaRes. Numerous measurement results were added including plant physiology and soil and rhizosphere microbiology. DNA of bacterial/archaeal and fungal microbiomes was sequenced in the rhizosphere and root-associated soil following a meta-barcoding approach. Taxonomic and relative abundance data were included in the dataset. The dataset is the first to include information on root characteristics, soil and rhizosphere microbiomes, and crop gene expression. We encourage reuse of these biological field trial data in terms of meta-analysis, modeling and AI approaches.

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二十年来施肥、耕作和作物轮作的长期田间试验数据，重点是土壤微生物。

农业长期田间试验提供了关于不同管理措施下作物性能和土壤特性的基本数据。这些信息是应对即将到来的粮食和营养安全挑战的基本知识。本文提供的数据是自2004年以来在德国中部进行的氮肥施肥强度、耕作和作物轮作田间试验中收集的，包括土壤管理、土壤物理性质、作物管理、作物特性、产量和收获质量参数方面的标准化指标。2015年，田间试验成为德国农业土壤研究计划BonaRes的成员。增加了许多测量结果，包括植物生理学和土壤和根际微生物学。采用元条形码方法对根际和根相关土壤中细菌/古细菌和真菌微生物组的DNA进行了测序。数据集中包括分类和相对丰度数据。该数据集是第一个包含有关根系特征、土壤和根际微生物组以及作物基因表达的信息的数据集。我们鼓励在荟萃分析、建模和人工智能方法方面重用这些生物现场试验数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.