Comprehensive dataset on the physicochemical characteristics of agrowastes digestates from anaerobic digestion

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-04-08 DOI:10.1016/j.dib.2025.111550

Lucille Caradec , Aurélia Michaud , Mariana Moreira , Ivan Desneulin , Sylvaine Berger , Dominique Patureau , Sabine Houot , Florent Levavasseur , Antoine Savoie , Julie Jimenez

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引用次数: 0

Abstract

The established database represents one of the largest and most diverse collections of digestates compositions, with a total of 806 digestates derived from two main collections: (i) 608 digestates from French agricultural anaerobic digestion (AD) plants, which include detailed physicochemical characterization, trace metal elements and organic contaminants concentrations, and potential C and N mineralization during soil incubation in controlled conditions as agronomic indicators, and (ii) 198 digestates collected from an international literature review, with physicochemical characterization and some trace metal elements concentrations. An additional dataset of process metadata was also set-up, including feedstock compositions, operational conditions and post-treatments descriptions. A preliminary description of both collections is provided using descriptive statistics. This dataset can help to better understand the variability in digestates quality based on feedstock compositions, operational conditions and post-treatments, thereby improving their agronomic benefits.

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厌氧消化沼液理化特性的综合数据集

已建立的数据库是最大和最多样化的消化菌组成集合之一，共有806个消化菌来自两个主要集合：(i)来自法国农业厌氧消化（AD）工厂的608个消化物，包括详细的理化表征、微量金属元素和有机污染物浓度，以及在受控条件下土壤培养过程中潜在的C和N矿化，作为农艺指标；（ii）来自国际文献综述的198个消化物，包括理化表征和一些微量金属元素浓度。另外还建立了一个过程元数据集，包括原料成分、操作条件和后处理描述。使用描述性统计提供了两个集合的初步描述。该数据集可以帮助更好地了解基于原料组成、操作条件和后处理的消化质量变化，从而提高其农艺效益。

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

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.