# A comprehensive dataset gathering 37 cover crop field experiments across France (2004-2022): plant and soil-related agronomic variables on 33 crop species from five botanical families

Manon Pull, Lionel Alletto, Eric Justes, Jay Ram Lamichhane, Elana Dayoub, Guillaume Hustet-Caou, Emilie Sitnikow, Noémie Gaudio, Pierre Casadebaig, Rémi Mahmoud, et al.

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Manon Pull, Lionel Alletto, Eric Justes, Jay Ram Lamichhane, Elana Dayoub, et al. A comprehensive dataset gathering 37 cover crop field experiments across France (2004-2022): plant and soil-related agronomic variables on 33 crop species from five botanical families. Data in Brief, 2025, 61, pp.111863. 10.1016/j.dib.2025.111863. hal-05164858

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https://hal.inrae.fr/hal-05164858v1

Submitted on 7 Nov 2025

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Data Article

# A comprehensive dataset gathering 37 cover crop field experiments across France (2004–2022): plant and soil-related agronomic variables on 33 crop species from five botanical families

<figure><img src="image_2.png" /></figure>

Manon Pull<sup>a</sup>, Lionel Alletto<sup>a,*</sup>, Eric Justes<sup>b</sup>, Jay Ram Lamichhane<sup>a</sup>, Elana Dayoub<sup>a</sup>, Guillaume Hustet-Caou<sup>a</sup>, Emilie Sitnikow<sup>a</sup>, Noémie Gaudio<sup>a</sup>, Pierre Casadebaig<sup>a</sup>, Rémi Mahmoud<sup>a</sup>, Neïla Ait Kaci Ahmed<sup>a</sup>, Julie Constantin<sup>a</sup>, Antoine Couëdel<sup>a,b</sup>, Noémie Deschamps<sup>a</sup>, Eric Lecloux<sup>a</sup>, Damien Marchand<sup>a</sup>, François Perdrieux<sup>a</sup>, Didier Raffaillac<sup>a</sup>, Lucie Souques<sup>a</sup>, Gilles Tison<sup>c</sup>, Hélène Tribouillois<sup>a</sup>, Alexandre Wojciechowski<sup>a</sup>, Célia Seassau<sup>a,*</sup>

ARTICLE INFO

Article history:
Received 10 April 2025
Revised 18 June 2025
Accepted 2 July 2025
Available online 7 July 2025

Dataset link: A comprehensive dataset gathering 37 cover crop field experiments across France (2004–2022): plant and soil-related agronomic variables on 33 crop species from five botanical families

ABSTRACT

Cover crops, sown between cash crops to provide ecosystem services, contribute to sustainability but present challenges related to the use of environmental resources out of the main cropping season. This dataset gathers the results of 37 field experiments related to cover crops, whether grown in sole crops or in mixtures, conducted in France over 19 years. It compiles quantitative data from field measurements and laboratory analyses on 33 species among five botanical families, along with information on technical management

<figure><img src="image_3.png" /></figure>

<footnote><sup>a</sup>Université de Toulouse, INRAE, INPT, El PURPAN, AGIR, Castanet-Tolosan, France</footnote>

<footnote><sup>b</sup>CIRAD, Persyst Department, F-34398 Montpellier, France</footnote>

<footnote><sup>c</sup>UE APC, Auzeville, INRAE, France</footnote>

<footnote>* Corresponding authors.
E-mail addresses: lionel.alletto@inrae.fr (L. Alletto), celia.seassau@purpan.fr (C. Seassau).</footnote>
Keywords:
Intercropping systems
Agriculture
Ecosystem services
Functional traits
Data mining

and climate conditions, providing a valuable resource for assessing cover crops performance.

© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

<table><caption>Specifications table</caption><tr><td>Subject</td><td>Agronomy and Crop Science, Soil Science</td></tr><tr><td>Specific subject area</td><td>Experimental dataset of cover crop experiments: management, cover crop emergence, biomass production, plant and soil nutrient content</td></tr><tr><td>Type of data</td><td>Raw<br>Filtered<br>Table</td></tr><tr><td>Data collection</td><td>Data were collected from experimental fields, mainly in southwest France, and include cover crop management details, field and lab measurements, and pedo-climatic data. Measurements were performed using standard agronomic and laboratory protocols. Experimental designs, materials, methods and data collection are detailed in the Experimental design, Materials, and Methods section.</td></tr><tr><td>Data source location</td><td><ul><li>Institution: INRAE</li><li>Location: Auzeville-Tolosane and Seysses (Haute-Garonne), Orléans (Loiret)</li><li>Country: France</li><li>Coordinates: 43.529326, 1.501011 (Auzeville-Tolosane), 43.50946, 1.251009 (Seysses), 47.776, 2.098 (Orléans)</li></ul></td></tr><tr><td>Data accessibility</td><td>Repository name: Entrepôt Recherche Data Gouv<br>Data identification number: doi/10.57745/3PRE07<br>Direct URL to data: https://doi.org/10.57745/3PRE07</td></tr><tr><td>Related research article</td><td>A. Couëdel, L. Alletto, H. Tribouillois, É. Justes, Cover crop crucifer-legume mixtures provide effective nitrate catch crop and nitrogen green manure ecosystem services, Agriculture, Ecosystems & Environment 254 (2018) 50–59. https://doi.org/10.1016/j.agee.2017.11.017</td></tr></table>

## 1. Value of the data

* The dataset provides a unique and extensive range of cover crop traits collected over 19 years from field experiments at research stations.

* The traits measured are categorized into soil nutrients, causes of non-emergence and post-emergence damages, plant size, development, biomass, plant nutrient and glucosinolate content.

* The cover crops, tested as sole crops or in mixtures, belong to five botanical families (Fabaceae, Brassicaceae, Poaceae, Hydrophyllaceae, Polygonaceae), with 33 species and over 128 cultivars.

* Data for each variable and modality are provided by block, depending on the experimental design. Detailed descriptions of each trial, including management practices and climate data, are supplied.

* This dataset can be used to quantify and compare cover crop traits across species and cultivars, assess cover crop performance, and to calibrate crop simulation models.

## 2. Background

Cover crops play an important role in the agroecological transition, especially in the context of climate change. In this study, we have compiled a unique dataset gathering the results of 37 field experiments in order to study the performance of several species of cover crops across different environments {3 sites in France: Auzeville-Tolosane, Seysses and Orléans}. This dataset
gathers both qualitative and quantitative data, enabling a deeper understanding of the behaviour
and contributions of cover crops to sustainable practices. These data can inform methodological
approaches to evaluate public policies, and support modelling and analysis of multi-performance
outcomes.

3. Data description

This dataset gathers the results of 37 field experiments with cover crops. Cover crops are non-commercial, non-harvested plant species grown alone or in mixtures during the fallow period between successive main crops. Their primary function is to deliver multiple ecosystem services, including soil improvement, erosion control, nutrient cycling, and the management of pests and weeds.

The field experiments were carried in France, in Haute-Garonne (Auzeville-Tolosane, Seysses; n = 35) and in Loiret (Orléans; n = 2), from 2004 to 2022 (Fig. 1).

<figure><img src="image_4.png" /><figcaption>Fig. 1. Number of experiments per year in the dataset (ranging from 1 to 4 per year).</figcaption></figure>

The dataset is organized as six tabular data files: three in .csv format–data_trials, data_management, and data traits– with one observation per row and values within each row separated by a delimiter, and three in .xlxs format–data_climate, metadata, and references. The content of these files is described in Table 1, following the good practices for data tidying [1]. Files, except metadata and data_climate share a common identifier ("experiment_id") which corresponds to the concatenation of "site name-project name-year of experiment". Additional information on the data curation and formatting process from a raw to a tidy dataset is presented in Mahmoud et al. [2].

The dataset includes 33 crop species (Table 2), among five botanical families.

Each species can be present in one or more experiments. Each experiment corresponds to a
unique {site * year} combination and includes one or more cultivars.

Some experiments include species mixtures, with 2 to 4 species grown simultaneously. This
results in 10 types of intercropping based on botanical family mixtures (Table 3).

The dataset includes data on cover crops sown at various times throughout the growing season and for different durations (Table 4). Within the same experiment, sowing and termination dates may vary. For further details, Fig. 2 presents the average duration of the cover crops per species according to the month of sowing. Only species present in at least two experiments are shown.

Pooling the 37 field experiments, a total of 141 variables were measured, though not system-
atically across all experiments. Table 5 provides an overview of these variables along with the
number of experiments in which each was assessed.
<table><caption>**Table 1**
Name and content of the six files composing the dataset.</caption><thead><tr><th>Name</th><th>Content</th></tr></thead><tbody><tr><td>metadata</td><td>Describes the table header variables (sheet dataset) and experimental measured variables with the unit of measurements (sheet variables).</td></tr><tr><td>data_trials</td><td>Includes the site of experiment, the project name, the year of experiment, the geographical coordinates of the fields.</td></tr><tr><td>data_management</td><td>This section provides information on crop management. Each entry represents a single crop cultivar, whether grown as a sole crop or within a mixture, managed in a specific experiment and year.<br>Each cropping modality (sole crop or mixture) is associated with a specific management practice within the same experiment, labeled from M1 to Mn. Management is not necessarily continuous, as some modalities were discontinued in certain experiments (e.g., M3 in <i>auzeville_CIMSON_2021</i> and <i>auzeville_CIMSON_2022</i>; M29 in <i>seysses_CRUCIAL_2014</i>).<br>The table includes, when available:<ul><li>The genus, cultivar(s), genus mixtures, and cultivar mixtures (if applicable), along with their Latin name.</li><li>Sowing density, sowing date and termination date</li><li>Relative density (1 = full density, 0.5 = half density, etc.)</li><li>Amount of irrigation applied (if applicable)</li><li>Use of pesticides on the plot (yes/no)</li><li>Previous crop</li><li>Subsequent crop</li></ul></td></tr><tr><td>data_climate</td><td>This dataset contains daily records of rainfall, mean/minimal/maximal temperature, and Penman-Monteith potential evapotranspiration for Auzeville-Tolosane (2004-2023) and Orléans (2014-2016), all registered by INRAE weather stations.<br>Missing data for Auzeville-Tolosane on the following dates: 2018-04-26; 2020-06-20; 2020-12-19 to 2020-12-29; 2021-01-01; 2021-01-19.</td></tr><tr><td>data</td><td>This dataset provides measurements conducted in each experiment at the plant, crop, or mixture level, including block-level data when applicable. The file integrates key information from the data_management with the addition of:<ul><li>Measurement date</li><li>Species and species mixtures</li><li>Variable name</li><li>Block (if applicable)</li><li>Measured value</li></ul></td></tr><tr><td>references</td><td>This section provides references to publications related to the experiments, linked to the corresponding experiment_id in the dataset.</td></tr></tbody></table>

<table><caption>**Table 2**
Summary of crop species included in the dataset.</caption><thead><tr><th>Plant family</th><th>Species</th><th>Latin name</th><th>No. Cultivars</th><th>No. Experiments</th></tr></thead><tbody><tr><td rowspan="12">Brassicaceae (10)</td><td>brown mustard</td><td>Brassica juncea (L.) Czern</td><td>7</td><td>16</td></tr><tr><td>chinese radish</td><td>Raphanus sativus var. longipinnatus L.H.Bailey</td><td>2</td><td>3</td></tr><tr><td>ethiopian mustard</td><td>Brassica carinata A.Braun</td><td>7</td><td>8</td></tr><tr><td>fodder radish</td><td>Raphanus raphanistrum subsp. sativus (L.) Domin</td><td>7</td><td>15</td></tr><tr><td>fodder rape</td><td>Brassica napus L.</td><td>3</td><td>4</td></tr><tr><td>fodder turnip</td><td>Brassica rapa var. rapa L.</td><td>1</td><td>2</td></tr><tr><td>oilseed radish</td><td>Raphanus raphanistrum subsp. sativus (L.) Domin</td><td>1</td><td>1</td></tr><tr><td>rocket</td><td>Eruca vesicaria var. sativa (Mill.) Thell.</td><td>2</td><td>2</td></tr><tr><td>turnip rape</td><td>Brassica rapa subsp. oleifera (DC.) Metzg.</td><td>5</td><td>16</td></tr><tr><td>white mustard</td><td>Sinapis alba L.</td><td>17</td><td>29</td></tr><tr><td>bitter vetch</td><td>Vicia ervilia (L.) Willd.</td><td>1</td><td>1</td></tr><tr><td>black medick</td><td>Medicago lupulina L.</td><td>1</td><td>1</td></tr><tr><td>blue lupin</td><td>Lupinus angustifolius L.</td><td>1</td><td>2</td></tr><tr><td rowspan="6">Fabaceae (14)</td><td>common vetch</td><td>Vicia sativa L.</td><td>12</td><td>15</td></tr><tr><td>crimson clover</td><td>Trifolium incarnatum L.</td><td>3</td><td>11</td></tr><tr><td>egyptian clover</td><td>Trifolium alexandrinum L.</td><td>3</td><td>9</td></tr><tr><td>fodder lentil</td><td>Lens nigricans (M.Bieb.) Webb &amp; Berthel.</td><td>1</td><td>2</td></tr><tr><td>fodder pea</td><td>Pisum sativum L.</td><td>3</td><td>6</td></tr><tr><td>hairy vetch</td><td>Vicia villosa Brot.</td><td>3</td><td>7</td></tr></tbody></table>

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<table><caption>**Table 2 (continued)**</caption><thead><tr><th>Plant family</th><th>Species</th><th>Latin name</th><th>No. Cultivars</th><th>No. Experiments</th></tr></thead><tbody><tr><td rowspan="10">Hydrophyllaceae (1)</td><td>narbonne vetch</td><td>Vicia narbonensis L.</td><td>2</td><td>2</td></tr><tr><td>purple vetch</td><td>Vicia benghalensis L.</td><td>6</td><td>26</td></tr><tr><td>soybean</td><td>Glycine max (L.) Merr.</td><td>1</td><td>4</td></tr><tr><td>spring fababean</td><td>Vicia faba L.</td><td>3</td><td>6</td></tr><tr><td>winter fababean</td><td>Vicia faba L.</td><td>7</td><td>13</td></tr><tr><td>phacelia</td><td>Phacelia tanacetifolia Benth.</td><td>3</td><td>10</td></tr><tr><td>black oat</td><td>Avena strigosa Schreb.</td><td>9</td><td>11</td></tr><tr><td>fodder sorghum</td><td>Sorghum bicolor (L.) Moench</td><td>1</td><td>3</td></tr><tr><td></td><td>Sorghum bicolor (L.) Moench x Sorghum bicolor nothosubsp. drummondii (Nees ex Steud.) de Wet ex Davidse</td><td>1</td><td>1</td></tr><tr><td rowspan="7">Poaceae (7)</td><td>forest rye</td><td>Secale cereale L.</td><td>3</td><td>5</td></tr><tr><td>italian ryegrass</td><td>Lolium multiflorum Lam.</td><td>1</td><td>2</td></tr><tr><td>moha</td><td>Setaria italica subsp. moharia (Alef.) H.Scholz</td><td>2</td><td>8</td></tr><tr><td>sorghum</td><td>Sorghum bicolor nothosubsp. drummondii (Nees ex Steud) de Wet ex Davidse</td><td>1</td><td>5</td></tr><tr><td>sudangrass</td><td>Avena sativa L.</td><td>3</td><td>7</td></tr><tr><td>spring oat</td><td>Avena sativa L.</td><td>2</td><td>2</td></tr><tr><td>Polygonaceae (1)</td><td>buckwheat</td><td>Fagopyrum esculentum Moench</td><td>2</td><td>2</td></tr></tbody></table>

<caption>**Table 3**</caption>

Summary of cover crops mixtures included in the dataset.

<table><thead><tr><th>Plant family mixtures</th><th>Species mixtures</th><th>No. Species</th><th>No. Experiments</th></tr></thead><tbody><tr><td rowspan="24">Brassicaceae (1)</td><td>turnip rape-white mustard</td><td>2</td><td>1</td></tr><tr><td>brown mustard-common vetch</td><td>2</td><td>4</td></tr><tr><td>brown mustard-egyptian clover</td><td>2</td><td>3</td></tr><tr><td>brown mustard-fodder radish-purple vetch</td><td>3</td><td>3</td></tr><tr><td>brown mustard-purple vetch</td><td>2</td><td>5</td></tr><tr><td>brown mustard-spring fababean</td><td>2</td><td>2</td></tr><tr><td>chinese radish-spring fababean</td><td>2</td><td>2</td></tr><tr><td>ethiopian mustard-common vetch</td><td>2</td><td>5</td></tr><tr><td>ethiopian mustard-egyptian clover</td><td>2</td><td>2</td></tr><tr><td>ethiopian mustard-hairy vetch</td><td>2</td><td>2</td></tr><tr><td>ethiopian mustard-purple vetch</td><td>2</td><td>3</td></tr><tr><td>ethiopian mustard-soybean</td><td>2</td><td>2</td></tr><tr><td>ethiopian mustard-winter fababean</td><td>2</td><td>1</td></tr><tr><td>fodder radish-blue lupin</td><td>2</td><td>1</td></tr><tr><td>fodder radish-common vetch</td><td>2</td><td>2</td></tr><tr><td>fodder radish-egyptian clover</td><td>2</td><td>5</td></tr><tr><td>fodder radish-hairy vetch</td><td>2</td><td>4</td></tr><tr><td>fodder radish-purple vetch</td><td>2</td><td>6</td></tr><tr><td rowspan="15">Brassicaceae-Fabaceae (52)</td><td>fodder radish-turnip rape-purple vetch</td><td>3</td><td>3</td></tr><tr><td>fodder radish-white mustard-hairy vetch</td><td>3</td><td>2</td></tr><tr><td>fodder rape-blue lupin</td><td>2</td><td>1</td></tr><tr><td>fodder rape-common vetch</td><td>2</td><td>4</td></tr><tr><td>fodder rape-crimson clover</td><td>2</td><td>2</td></tr><tr><td>fodder rape-egyptian clover</td><td>2</td><td>4</td></tr><tr><td>fodder rape-hairy vetch</td><td>2</td><td>2</td></tr><tr><td>fodder rape-narbonne vetch</td><td>2</td><td>1</td></tr><tr><td>fodder rape-purple vetch</td><td>2</td><td>4</td></tr><tr><td>fodder rape-soybean</td><td>2</td><td>2</td></tr><tr><td>fodder rape-winter fababean</td><td>2</td><td>2</td></tr><tr><td>oilseed radish-egyptian clover</td><td>2</td><td>1</td></tr><tr><td>oilseed radish-hairy vetch</td><td>2</td><td>1</td></tr><tr><td>rocket-common vetch</td><td>2</td><td>1</td></tr><tr><td>rocket-crimson clover</td><td>2</td><td>1</td></tr><tr><td>rocket-egyptian clover</td><td>2</td><td>1</td></tr><tr><td>rocket-purple vetch</td><td>2</td><td>1</td></tr></tbody></table>

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<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Plant family mixtures</th><th>Species mixtures</th><th>No. Species</th><th>No. Experiments</th></tr></thead><tbody><tr><td rowspan="20">Brassicaceae-Fabaceae-<br>Hydrophyllaceae<br>(3)</td><td>turnip rape-black medick</td><td>2</td><td>1</td></tr><tr><td>turnip rape-common vetch</td><td>2</td><td>2</td></tr><tr><td>turnip rape-crimson clover</td><td>2</td><td>1</td></tr><tr><td>turnip rape-egyptian clover</td><td>2</td><td>3</td></tr><tr><td>turnip rape-fodder lentil</td><td>2</td><td>1</td></tr><tr><td>turnip rape-fodder pea</td><td>2</td><td>1</td></tr><tr><td>turnip rape-purple vetch</td><td>2</td><td>8</td></tr><tr><td>turnip rape-spring fababean</td><td>2</td><td>2</td></tr><tr><td>turnip rape-winter fababean</td><td>2</td><td>2</td></tr><tr><td>white mustard-blue lupin</td><td>2</td><td>1</td></tr><tr><td>white mustard-common vetch</td><td>2</td><td>4</td></tr><tr><td>white mustard-egyptian clover</td><td>2</td><td>3</td></tr><tr><td>white mustard-fodder pea</td><td>2</td><td>1</td></tr><tr><td>white mustard-hairy vetch</td><td>2</td><td>2</td></tr><tr><td>white mustard-narbonne vetch</td><td>2</td><td>1</td></tr><tr><td>white mustard-purple vetch</td><td>2</td><td>9</td></tr><tr><td>white mustard-soybean</td><td>2</td><td>2</td></tr><tr><td>white mustard-winter fababean</td><td>2</td><td>2</td></tr><tr><td>brown mustard-winter fababean-phacelia</td><td>3</td><td>2</td></tr><tr><td>chinese radish-common purple<br>vetch-spring fababean-phacelia</td><td>4</td><td>1</td></tr><tr><td>turnip rape-purple vetch-spring<br>fababean-phacelia</td><td>4</td><td>1</td></tr><tr><td>Brassicaceae-Fabaceae-<br>Poaceae<br>(1)</td><td>white mustard-crimson clover-winter<br>fababean-moha</td><td>4</td><td>1</td></tr><tr><td rowspan="10">Brassicaceae-Poaceae (4)</td><td>turnip rape-moha-sorghum sudangrass</td><td>3</td><td>1</td></tr><tr><td>white mustard-fodder sorghum</td><td>2</td><td>2</td></tr><tr><td>white mustard-moha</td><td>2</td><td>3</td></tr><tr><td>white mustard-sorghum sudangrass</td><td>2</td><td>1</td></tr><tr><td>common vetch-fodder pea</td><td>2</td><td>1</td></tr><tr><td>crimson clover-purple vetch</td><td>2</td><td>1</td></tr><tr><td>fodder pea-purple vetch</td><td>2</td><td>2</td></tr><tr><td>fodder turnip-common vetch</td><td>2</td><td>1</td></tr><tr><td>fodder turnip-egyptian clover</td><td>2</td><td>1</td></tr><tr><td>fodder turnip-purple vetch</td><td>2</td><td>1</td></tr><tr><td>black medick-phacelia</td><td>2</td><td>1</td></tr><tr><td>common vetch-spring fababean-phacelia</td><td>3</td><td>1</td></tr><tr><td>crimson clover-phacelia</td><td>2</td><td>2</td></tr><tr><td rowspan="5">Fabaceae (6)</td><td>fodder lentil-phacelia</td><td>2</td><td>1</td></tr><tr><td>fodder pea-phacelia</td><td>2</td><td>1</td></tr><tr><td>purple vetch-phacelia</td><td>2</td><td>4</td></tr><tr><td>spring fababean-phacelia</td><td>2</td><td>2</td></tr><tr><td>winter fababean-phacelia</td><td>2</td><td>1</td></tr><tr><td rowspan="2">Fabaceae-Hydrophyllaceae-<br>Poaceae<br>(2)</td><td>spring fababean-phacelia-forest rye</td><td>3</td><td>1</td></tr><tr><td>spring fababean-phacelia-forest<br>rye-sorghum sudangrass</td><td>4</td><td>1</td></tr><tr><td rowspan="10">Fabaceae-Poaceae (28)</td><td>black medick-black oat</td><td>2</td><td>1</td></tr><tr><td>black medick-italian ryegrass</td><td>2</td><td>1</td></tr><tr><td>black medick-moha</td><td>2</td><td>1</td></tr><tr><td>common vetch-moha</td><td>2</td><td>1</td></tr><tr><td>common vetch-sorghum sudangrass</td><td>2</td><td>1</td></tr><tr><td>common vetch-spring oat</td><td>2</td><td>6</td></tr><tr><td>crimson clover-black oat</td><td>2</td><td>1</td></tr><tr><td>crimson clover-fodder sorghum</td><td>2</td><td>1</td></tr><tr><td>crimson clover-italian ryegrass</td><td>2</td><td>2</td></tr><tr><td>crimson clover-moha</td><td>2</td><td>2</td></tr><tr><td>crimson clover-winter fababean-black oat</td><td>3</td><td>3</td></tr><tr><td>egyptian clover-fodder sorghum</td><td>2</td><td>1</td></tr><tr><td>egyptian clover-purple<br>vetch-moha-sorghum sudangrass</td><td>4</td><td>1</td></tr></tbody></table>

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<table><caption>**Table 3 (continued)**</caption><thead><tr><th>Plant family mixtures</th><th>Species mixtures</th><th>No. Species</th><th>No. Experiments</th></tr></thead><tbody><tr><td></td><td>egyptian clover-purple vetch-sorghum sudangrass</td><td>3</td><td>1</td></tr><tr><td></td><td>fodder lentil-black oat</td><td>2</td><td>1</td></tr><tr><td></td><td>fodder lentil-italian ryegrass</td><td>2</td><td>1</td></tr><tr><td></td><td>fodder lentil-moha</td><td>2</td><td>1</td></tr><tr><td></td><td>fodder pea-black oat</td><td>2</td><td>2</td></tr><tr><td></td><td>fodder pea-italian ryegrass</td><td>2</td><td>2</td></tr><tr><td></td><td>fodder pea-moha</td><td>2</td><td>1</td></tr><tr><td></td><td>fodder pea-purple vetch-forest rye</td><td>3</td><td>2</td></tr><tr><td></td><td>purple vetch-black oat</td><td>2</td><td>10</td></tr><tr><td></td><td>purple vetch-italian ryegrass</td><td>2</td><td>1</td></tr><tr><td></td><td>purple vetch-moha</td><td>2</td><td>2</td></tr><tr><td></td><td>spring fababeen-black oat</td><td>2</td><td>1</td></tr><tr><td></td><td>spring fababeen-fodder sorghum</td><td>2</td><td>1</td></tr><tr><td></td><td>spring fababeen-italian ryegrass</td><td>2</td><td>1</td></tr><tr><td></td><td>spring fababeen-moha</td><td>2</td><td>2</td></tr><tr><td>Hydrophyllaceae-Poaceae (1)</td><td>phacelia-black oat</td><td>2</td><td>3</td></tr></tbody></table>

<caption>**Table 4**</caption>

Overview of cover crops sowing period and average duration across experiments.

<table><thead><tr><th>Sowing month</th><th>No. Experiments</th><th>Average duration (months) of cover crops from sowing to termination ± sd</th></tr></thead><tbody><tr><td>July</td><td>5</td><td>4.2 ± 2</td></tr><tr><td>August</td><td>21</td><td>3.1 ± 1.3</td></tr><tr><td>September</td><td>21</td><td>3.3 ± 1.7</td></tr><tr><td>October</td><td>7</td><td>3.9 ± 1.2</td></tr><tr><td>November</td><td>1</td><td>5.5</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Average duration of cover crops by species and sowing month. Species are grouped by botanical family: Brassicaceae, Fabaceae, Poaceae, Hydrophyllaceae and Polygonaceae.</figcaption></figure>

To illustrate key features from the dataset, we focused on i) the most represented species mixture, i.e. oat-vetch (n = 10) and ii) variables that were most frequently measured across experiments i.e. biomass production (*biomass_shoot*, *biomass_root*: t.ha⁻¹ of dry matter), nitrogen and carbon uptake by plants (*carbon_acq_shoot*, *carbon_acq_root*, *nitrogen_acq_shoot*, *nitrogen_acq_root*: kg.ha⁻¹) (Fig. 3). Shoot and root biomass data were not available for all modalities. Consequently, the shoot and root boxplots are independent and based on different sample sizes. However, whenever biomass shoot is available, biomass root is also present, but the reverse is not always true.
<caption>**Table 5**</caption>

Summary of measured variables categorized by soil nutrients, causes of non-emergence and post-emergence damages, plant size, development and content, biomass, plant nutrient content, and glucosinolate content. Each variable is presented with its unit and the number of experiments (No. Experiments) in which it was measured. Categories are organized chronologically according to the timing of the measurements, with variables listed alphabetically within each category.

<table><thead><tr><th>Category</th><th>Variable</th><th>Unit</th><th>No. Experiments</th></tr></thead><tbody><tr><td>Soil</td><td>soil_nitrogen_0-30</td><td>kg.ha<sup>-1</sup></td><td>35</td></tr><tr><td>Soil</td><td>soil_nitrogen_30-60</td><td>kg.ha<sup>-1</sup></td><td>35</td></tr><tr><td>Soil</td><td>soil_nitrogen_60-90</td><td>kg.ha<sup>-1</sup></td><td>34</td></tr><tr><td>Soil</td><td>soil_nitrogen_90-120</td><td>kg.ha<sup>-1</sup></td><td>25</td></tr><tr><td>Soil</td><td>soil_sulphur_0-30</td><td>kg.ha<sup>-1</sup></td><td>6</td></tr><tr><td>Soil</td><td>soil_sulphur_30-60</td><td>kg.ha<sup>-1</sup></td><td>6</td></tr><tr><td>Soil</td><td>soil_sulphur_60-90</td><td>kg.ha<sup>-1</sup></td><td>6</td></tr><tr><td>Soil</td><td>soil_sulphur_90-120</td><td>kg.ha<sup>-1</sup></td><td>1</td></tr><tr><td>Soil</td><td>soil_swc_0-30</td><td>mm</td><td>22</td></tr><tr><td>Soil</td><td>soil_swc_30-60</td><td>mm</td><td>22</td></tr><tr><td>Soil</td><td>soil_swc_60-90</td><td>mm</td><td>22</td></tr><tr><td>Soil</td><td>soil_swc_90-120</td><td>mm</td><td>15</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_abiotic_stress</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_clods</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_crusting</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_damping_off</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_land_pests</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_seedlessness_birds</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>CNE_sowing_depth</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_animals</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_anoxia</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_avifauna</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_damping_off</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_flea_bugles</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_freeze</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_land_pests</td><td>-</td><td>1</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_slugs</td><td>-</td><td>2</td></tr><tr><td>Causes of non-emergence and post-emergence damages</td><td>PED_thermal_stress</td><td>-</td><td>1</td></tr><tr><td>Plant size, development and content</td><td>adf_shoot</td><td>%</td><td>4</td></tr><tr><td>Plant size, development and content</td><td>adl_shoot</td><td>%</td><td>4</td></tr><tr><td>Plant size, development and content</td><td>cellulose_shoot</td><td>%</td><td>4</td></tr><tr><td>Plant size, development and content</td><td>cover</td><td>%</td><td>5</td></tr><tr><td>Plant size, development and content</td><td>emergence_density</td><td>plant.m<sup>-2</sup></td><td>15</td></tr><tr><td>Plant size, development and content</td><td>height</td><td>cm</td><td>5</td></tr></tbody></table>

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<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Category</th><th>Variable</th><th>Unit</th><th>No. Experiments</th></tr></thead><tbody><tr><td>Plant size, development and content</td><td>hemicellulose_shoot</td><td>%</td><td>4</td></tr><tr><td>Plant size, development and content</td><td>leaf_area</td><td>cm<sup>2</sup></td><td>2</td></tr><tr><td>Plant size, development and content</td><td>leaf_number</td><td>-</td><td>1</td></tr><tr><td>Plant size, development and content</td><td>length</td><td>cm</td><td>2</td></tr><tr><td>Plant size, development and content</td><td>ndf_shoot</td><td>%</td><td>4</td></tr><tr><td>Plant size, development and content</td><td>stage</td><td>-</td><td>5</td></tr><tr><td>Biomass</td><td>biomass_root</td><td>t.ha<sup>-1</sup> of dry matter</td><td>26</td></tr><tr><td>Biomass</td><td>biomass_root_regrowthprevious_crop</td><td>t.ha<sup>-1</sup> of dry matter</td><td>1</td></tr><tr><td>Biomass</td><td>biomass_shoot</td><td>t.ha<sup>-1</sup> of dry matter</td><td>36</td></tr><tr><td>Biomass</td><td>biomass_shoot_regrowthprevious_crop</td><td>t.ha<sup>-1</sup> of dry matter</td><td>3</td></tr><tr><td>Biomass</td><td>biomass_shoot_weed</td><td>t.ha<sup>-1</sup> of dry matter</td><td>18</td></tr><tr><td>Biomass</td><td>humidity_root</td><td>%</td><td>2</td></tr><tr><td>Biomass</td><td>humidity_shoot</td><td>%</td><td>9</td></tr><tr><td>Biomass</td><td>humidity_shoot_weed</td><td>%</td><td>3</td></tr><tr><td>Biomass</td><td>root_shoot_ratio</td><td>-</td><td>2</td></tr><tr><td>Plant nutrient content</td><td>boron_root</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>boron_shoot</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>calcium_root</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>calcium_shoot</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>carbon_acq_root</td><td>kg.ha<sup>-1</sup></td><td>16</td></tr><tr><td>Plant nutrient content</td><td>carbon_acq_root_regrowthprevious_crop</td><td>kg.ha<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>carbon_acq_shoot</td><td>kg.ha<sup>-1</sup></td><td>27</td></tr><tr><td>Plant nutrient content</td><td>carbon_acq_shoot_regrowth('previous_crop</td><td>kg.ha<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>carbon_acq_shoot_weed</td><td>kg.ha<sup>-1</sup></td><td>9</td></tr><tr><td>Plant nutrient content</td><td>carbon_root</td><td>%</td><td>17</td></tr><tr><td>Plant nutrient content</td><td>carbon_root_regrowth('previous_crop</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>carbon_shoot</td><td>%</td><td>28</td></tr><tr><td>Plant nutrient content</td><td>carbon_shoot_regrowth('previous_crop</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>carbon_shoot_weed</td><td>%</td><td>10</td></tr><tr><td>Plant nutrient content</td><td>copper_root</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>copper_shoot</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>delta_15N_root</td><td>-</td><td>3</td></tr><tr><td>Plant nutrient content</td><td>delta_15N_shoot</td><td>-</td><td>18</td></tr><tr><td>Plant nutrient content</td><td>delta_15N_shoot_regrowth('previous_crop</td><td>-</td><td>3</td></tr><tr><td>Plant nutrient content</td><td>delta_15N_shoot_weed</td><td>-</td><td>6</td></tr></tbody></table>

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<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Category</th><th>Variable</th><th>Unit</th><th>No. Experiments</th></tr></thead><tbody><tr><td>Plant nutrient content</td><td>iron_root</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>iron_shoot</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>magnesium_root</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>magnesium_shoot</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>manganese_root</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>manganese_shoot</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_acq_root</td><td>kg.ha<sup>-1</sup></td><td>25</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_acq_root_regrowth_previous_crop</td><td>kg.ha<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_acq_shoot</td><td>kg.ha<sup>-1</sup></td><td>36</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_acq_shoot_regrowth Previous_crop</td><td>kg.ha<sup>-1</sup></td><td>3</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_acq_shoot_weed</td><td>kg.ha<sup>-1</sup></td><td>13</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_root</td><td>%</td><td>28</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_root_regrowth_crop</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_shoot</td><td>%</td><td>37</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_shoot_regrowth Previous_crop</td><td>%</td><td>3</td></tr><tr><td>Plant nutrient content</td><td>nitrogen_shoot_weed</td><td>%</td><td>14</td></tr><tr><td>Plant nutrient content</td><td>phosphorus_acq_shoot</td><td>kg.ha<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>phosphorus_root</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>phosphorus_shoot</td><td>%</td><td>2</td></tr><tr><td>Plant nutrient content</td><td>potassium_root</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>potassium_shoot</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>sodium_root</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>sodium_shoot</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>sulphur_acq_root</td><td>kg.ha<sup>-1</sup></td><td>9</td></tr><tr><td>Plant nutrient content</td><td>sulphur_acq_shoot</td><td>kg.ha<sup>-1</sup></td><td>12</td></tr><tr><td>Plant nutrient content</td><td>sulphur_root</td><td>%</td><td>11</td></tr><tr><td>Plant nutrient content</td><td>sulphur_shoot</td><td>%</td><td>14</td></tr><tr><td>Plant nutrient content</td><td>sulphur_shoot_weed</td><td>%</td><td>1</td></tr><tr><td>Plant nutrient content</td><td>zinc_root</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Plant nutrient content</td><td>zinc_shoot</td><td>mg.kg<sup>-1</sup></td><td>1</td></tr><tr><td>Glucosinolate content</td><td>4hydroxyglucobrassicin_root</td><td>µmol.g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>4hydroxyglucobrassicin_shoot</td><td>µmol.g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>4methoxyglucobrassicin_root</td><td>µmol.g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>4methoxyglucobrassicin_shoot</td><td>µmol.g<sup>-1</sup> of dry matter</td><td>9</td></tr></tbody></table>

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<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Category</th><th>Variable</th><th>Unit</th><th>No. Experiments</th></tr></thead><tbody><tr><td>Glucosinolate content</td><td>epiprogoitrin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>epiprogoitrin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoalyssin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>5</td></tr><tr><td>Glucosinolate content</td><td>glucoalyssin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>4</td></tr><tr><td>Glucosinolate content</td><td>glucobrassicanapin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>8</td></tr><tr><td>Glucosinolate content</td><td>glucobrassicanapin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>glucobrassicin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucobrassicin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoerucin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoerucin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoiberin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoiberin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>gluconapin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>gluconapin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>gluconapoleiferin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>gluconapoleiferin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>gluconasturtiin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>gluconasturtiin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoraphanin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoraphanin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_E/Z_mixture_II_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_E/Z_mixture_II_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_E/Z_mixture_L_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_E/Z_mixture_L_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>1</td></tr><tr><td>Glucosinolate content</td><td>glucoraphasatin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>1</td></tr><tr><td>Glucosinolate content</td><td>glucoraphenin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucoraphenin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>2</td></tr><tr><td>Glucosinolate content</td><td>glucotropaeolin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>glucotropaeolin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>neoglucobrassicin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>neoglucobrassicin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>progoitrin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>progoitrin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>sinalbin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>sinalbin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>7</td></tr><tr><td>Glucosinolate content</td><td>sinigrin_root</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr><tr><td>Glucosinolate content</td><td>sinigrin_shoot</td><td>µmol·g<sup>-1</sup> of dry matter</td><td>9</td></tr></tbody></table>
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Biomass, nitrogen and carbon uptake by shoots and roots of black oat and purple vetch grown as sole crop or mixture. SC = measurements for black oat and purple vetch in sole crops; IC = separate measurements for black oat and purple vetch in intercrop; Mix (oat + vetch) = sum of both species in the mixture.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Fig. 3. Continued</figcaption></figure>

# 4. Experimental design, materials and methods

## 4.1. Experimental site and design

The experiments included in the database were conducted between 2004 and 2022 at three sites: the INRAE research station of Auzeville-Tolosane (43.529326, 1.501011), the Lamothe experimental farm of INP-EI Purpan located at Seysses (43.50946, 1.251009), and a private research station near Orléans (47.776, 2.098).

The experiments were carried out in experimental fields though two types of trials: analytical and cropping system trials. In the analytical trials, cover crops were sown in microplots with a minimum size of 14 m², while in the cropping system trials, cover crops were sown in strips, each covering at least 3000 m². The sites, number of crop campaigns, experimental design and experiment identification are summarized in Table 6.

The management and features described refer to the main features of the experiments, or specific parameters related to certain experiments. Detailed management-specific data are detailed in the *data_management* table.

## 4.2. Cover crops management

Before sowing, shallow tillage was carried out for all cover crops except for two managements. Irrigation was applied at sowing when necessary (19 out of 37 experiments) to ensure
<caption>**Table 6**</caption>

Summary of the database experiments including site, number of campaigns, experimental design and the corresponding experiment_id linked to each experiment.

<table><thead><tr><th>Project</th><th>Site</th><th>No. of campaign</th><th>Experimental design</th><th>Experiment_id linked</th></tr></thead><tbody><tr><td>CIAG</td><td></td><td>1</td><td>1 block</td><td>auzeville_CIAG_2017</td></tr><tr><td>CIFRE NAK [3]</td><td></td><td>3</td><td>Completely randomized design 3 blocks</td><td>auzeville_CIFRE_NAK_2018<br>auzeville_CIFRE_NAK_2019<br>auzeville_CIFRE_NAK_2020</td></tr><tr><td rowspan="2">CIMSON [4]</td><td rowspan="2">Auzeville</td><td>2</td><td>Randomized incomplete block design with a split-plot layout 2021-2022 : 4 blocks 2022-2023 : 3 blocks</td><td>auzeville_CIMSON_2021<br>auzeville_CIMSON_2022</td></tr><tr><td>2</td><td>1 block<br>Non-randomized design 3 blocks</td><td>auzeville_CRUCIAL_2015<br>auzeville_CRUCIAL_2016</td></tr><tr><td rowspan="2">CRUCIAL [5, 6, 7, 8]</td><td>Seysses</td><td>3</td><td>Completely randomized design 3 blocks</td><td>seysses_CRUCIAL_2014<br>seysses_CRUCIAL_2015<br>seysses_CRUCIAL_2016</td></tr><tr><td>Orléans</td><td>2</td><td></td><td>orleans_CRUCIAL_2014<br>orleans_CRUCIAL_2015</td></tr><tr><td>LGBI [9, 10]</td><td></td><td>6</td><td>Cover crop on semi-subplot, 1 block (cropping system experiment)</td><td>auzeville_LGBI_2004<br>auzeville_LGBI_2005<br>auzeville_LGBI_2006<br>auzeville_LGBI_2007<br>auzeville_LGBI_2008<br>auzeville_LGBI_2009</td></tr><tr><td>MICMAC [11]</td><td>Auzeville</td><td>8</td><td>Cover crop on semi-subplot, 1 block (cropping system experiment)</td><td>auzeville_MICMAC_2010<br>auzeville_MICMAC_2011<br>auzeville_MICMAC_2012<br>auzeville_MICMAC_2013<br>auzeville_MICMAC_2014<br>auzeville_MICMAC_2015<br>auzeville_MICMAC_2016<br>auzeville_MICMAC_2017</td></tr><tr><td>NPC</td><td></td><td>2</td><td>Completely randomized design 6 blocks</td><td>auzeville_NPC_2020<br>auzeville_NPC_2021</td></tr><tr><td rowspan="2">PFAE</td><td rowspan="2">Auzeville</td><td>2</td><td>3 blocks<br>6 blocks</td><td>auzeville_PFAE_2020<br>auzeville_PFAE_2021</td></tr><tr><td>4</td><td>Cover crop on semi-subplot, 1 block (cropping system experiment)</td><td>auzeville_REDUCE_2018<br>auzeville_REDUCE_2019<br>auzeville_REDUCE_2020<br>auzeville_REDUCE_2021</td></tr><tr><td>REDUCE</td><td></td><td>2</td><td>Completely randomized design 3 blocks</td><td>auzeville REGION HT_2012<br>auzeville REGION HT_2013</td></tr><tr><td>REGION HT [12, 13, 14]</td><td></td><td>2</td><td></td><td></td></tr></tbody></table>

uniform emergence and robust plant establishment. Cover crops were not directly fertilized; however, in some cropping system trials, plots received phosphorus (P) fertilization during or just before the sowing of the cover crop to meet the nutrient requirements for subsequent cash crops.

Only a few experiments (8 out of 37) received plant protection treatments during the cover crop growth phase. These treatments were mainly limited to pesticides against slugs, insecticides targeting specific pests such as sawfly, or herbicides for weed control. Some experiments included bare soil as a control treatment, most of them being kept weed-free using mechanical methods.

## 4.3. Measurement and sampling

Table 7 provides a description of the methods.
<caption>**Table 7**</caption>

Summary of the method descriptions by variable category. Categories are organized chronologically according to the timing of the measurements, with variables listed alphabetically within each category and comparable method grouping.

<table><thead><tr><th>Category</th><th>Variable</th><th>Method description</th></tr></thead><tbody><tr><td rowspan="10">Soil</td><td>soil_nitrogen_0-30</td><td rowspan="10">Depending on the experiments, soil samples were collected both before sowing and at the end of the growing season (n = 9), or only at the cover crop termination (n = 26). Soil cores were randomly extracted using a hydraulic core drill at different horizons with depths varying according to the experiment (0-30, 30-60, 60-90, 90-120 cm). Soil mineral nitrogen (nitrate and ammonium) and soil sulfur concentrations were analyzed using a continuous flow auto-analyzer (Skylar 51,000, Skalar Analytic, Breda, Netherlands) following the standard NF ISO 14,256-2. Soil water content was calculated by multiplying the measured gravimetric water content by the estimated bulk density.</td></tr><tr><td>soil_nitrogen_30-60</td></tr><tr><td>soil_nitrogen_60-90</td></tr><tr><td>soil_nitrogen_90-120</td></tr><tr><td>soil_sulphur_0-30</td></tr><tr><td>soil_sulphur_30-60</td></tr><tr><td>soil_sulphur_60-90</td></tr><tr><td>soil_sulphur_90-120</td></tr><tr><td>soil_swc_0-30</td><td></td></tr><tr><td>soil_swc_30-60</td><td></td></tr><tr><td>soil_swc_60-90</td><td></td></tr><tr><td>soil_swc_90-120</td><td></td></tr><tr><td rowspan="12">Causes of non-emergence and post-emergence damages</td><td>CNE_abiotic_stress</td><td rowspan="12">During the emergence phase, the causes of non-emergence were identified at a set number of empty points within subplots, using a visual diagnostic key [15]. At each empty point, once seeds or seedling remnants were found the likely causes of non-emergence were recorded. For each subplot, the percentage of occurrences attributed to each identified cause was calculated.</td></tr><tr><td>CNE_clods</td></tr><tr><td>CNE_crusting</td></tr><tr><td>CNE_damping_off</td></tr><tr><td>CNE_land_pests</td></tr><tr><td>CNE_seedlessness_birds</td></tr><tr><td>CNE_sowing_depth</td></tr><tr><td>PED_animals</td></tr><tr><td>PED_anoxia</td></tr><tr><td>PED_avifauna</td></tr><tr><td>PED_damping_off</td></tr><tr><td>PED_flea_beetles</td></tr><tr><td>PED_freeze</td></tr><tr><td>PED_land_pests</td></tr><tr><td>PED_slugs</td></tr><tr><td>PED_thermal_stress</td></tr><tr><td>PED_shoot</td><td rowspan="4">The same approach was applied during the post-emergence phase to assess damage occurring after seedling emergence. Plants with damage were counted and the percentage of each type of damage relative to the total number of plants that had emerged was calculated.</td></tr><tr><td>adl_shoot</td></tr><tr><td>adf_shoot</td></tr><tr><td>cellulose_shoot</td></tr><tr><td rowspan="4">Plant size, development and content</td><td>hemicellulose_shoot</td><td rowspan="4">Some plant samples were analyzed in a specialized laboratory to determine cell wall components using the Van Soest method [16], with results expressed as cellulose, hemicellulose, and acid detergent lignin (ADL), acid detergent fiber (ADF), and neutral detergent fiber (NDF) content.</td></tr><tr><td>ndf_shoot</td></tr><tr><td>cover</td></tr><tr><td>height</td></tr><tr><td>leaf_area</td><td rowspan="4">The soil cover provided by the cover crops was assessed through visual observation and scored on a scale from 1 to 5, where 1 corresponded to 0-12.5 % cover, 2 to 12.5-25 %, 3 to 25-50 %, 4 to 50-75 % and 5 corresponded to 75-100 % cover. In the database, these results are expressed as a percentage.</td></tr><tr><td>leaf_number</td></tr><tr><td>length</td></tr><tr><td>emergence_density</td></tr><tr><td>stage</td><td>Plant traits were measured or counted on selected plants within plots or subplots, including height, length, and leaf number. Sampled plants were collected for leaf area measurements using a planimeter (LI-COR 3100C) or a manual scanner, these methods are comparable. The reported plant height and length corresponded to the aerial part only (shoot).</td></tr><tr><td></td><td>A few days after sowing, the number of emerged plants for each cover crop species was counted within areas measuring 0.5 to 1 m². The results were then expressed as plants per square meter (plants.m⁻²).</td></tr><tr><td></td><td>Visual observation (BBCH scale).</td></tr></tbody></table>

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<table><caption>**Table 7 (continued)**</caption><thead><tr><th>Category</th><th>Variable</th><th>Method description</th></tr></thead><tbody><tr><td rowspan="10">Biomass</td><td>biomass_root</td><td>To estimate biomass produced by cover crops, because of the sampling method the estimated biomass include weeds, or regrowth from previous crops, shoot biomass samples were collected for each species at cover crop termination using areas of 0.25 m² to 1 m². In some experiments, root biomass was collected, typically at a depth from 25-30 cm, either for all species or selected ones, and from either all subplots, specific zones, or a subset of plants. This was done to calculate the root:shoot ratio.</td></tr><tr><td>biomass_root_regrowth_previous_crop</td><td>Fresh shoot and root samples were weighed, sub-sampled, dried at 80 °C for 48 hours, and then reweighed to estimate dry matter biomass per species.</td></tr><tr><td>biomass_shoot</td><td></td></tr><tr><td>biomass_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>biomass_shoot_weed</td><td></td></tr><tr><td>humidity_root</td><td></td></tr><tr><td>humidity_shoot</td><td></td></tr><tr><td>humidity_shoot_weed</td><td></td></tr><tr><td>root_shoot_ratio</td><td></td></tr><tr><td rowspan="20">Plant nutrient content</td><td>boron_root</td><td>Dried biomass samples were ground and analyzed for nitrogen (N), carbon (C), sulphur (S) or other mineral element concentrations using the Dumas method (MicroVario Cube, Elementar, Langenselbold, Germany).</td></tr><tr><td>boron_shoot</td><td></td></tr><tr><td>calcium_root</td><td></td></tr><tr><td>calcium_shoot</td><td></td></tr><tr><td>carbon_acq_root</td><td></td></tr><tr><td>carbon_acq_root_regrowth Previous_crop</td><td></td></tr><tr><td>carbon_acq_shoot</td><td></td></tr><tr><td>carbon_acq_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>carbon_acq_shoot_weed</td><td></td></tr><tr><td>carbon_root</td><td></td></tr><tr><td>carbon_root_regrowth Previous_crop</td><td></td></tr><tr><td>carbon_shoot</td><td></td></tr><tr><td>carbon_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>carbon_shoot_weed</td><td></td></tr><tr><td>copper_root</td><td></td></tr><tr><td>copper_shoot</td><td></td></tr><tr><td>iron_root</td><td></td></tr><tr><td>iron_shoot</td><td></td></tr><tr><td>magnesium_root</td><td></td></tr><tr><td>magnesium_shoot</td><td></td></tr><tr><td>manganese_root</td><td></td></tr><tr><td>manganese_shoot</td><td></td></tr><tr><td>nitrogen_acq_root</td><td></td></tr><tr><td>nitrogen_acq_root_regrowth Previous_crop</td><td></td></tr><tr><td>nitrogen_acq_shoot</td><td></td></tr><tr><td>nitrogen_acq_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>nitrogen_acq_shoot_weed</td><td></td></tr><tr><td>nitrogen_root</td><td></td></tr><tr><td>nitrogen_root_regrowth Previous_crop</td><td></td></tr><tr><td>nitrogen_shoot</td><td></td></tr><tr><td>nitrogen_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>nitrogen_shoot_weed</td><td></td></tr><tr><td>phosphorus_acq_shoot</td><td></td></tr><tr><td>phosphorus_root</td><td></td></tr><tr><td>phosphorus_shoot</td><td></td></tr><tr><td>potassium_root</td><td></td></tr><tr><td>potassium_shoot</td><td></td></tr><tr><td>sodium_root</td><td></td></tr><tr><td>sodium_shoot</td><td></td></tr><tr><td>sulphur_acq_root</td><td></td></tr><tr><td>sulphur_acq_shoot</td><td></td></tr><tr><td>sulphur_root</td><td></td></tr><tr><td>sulphur_shoot</td><td></td></tr><tr><td>sulphur_shoot_weed</td><td></td></tr><tr><td>zinc_root</td><td></td></tr><tr><td>zinc_shoot</td><td></td></tr><tr><td>delta_15N_root</td><td>In some experiments, 15 N concentration was measured using a stable isotope ratio mass spectrometer in continuous flow (Isoprime 100, UK)</td></tr><tr><td>delta_15N_shoot</td><td>to determine the percentage of plant nitrogen (N) derived from the atmosphere.</td></tr><tr><td>delta_15N_shoot_regrowth Previous_crop</td><td></td></tr><tr><td>delta_15N_shoot_weed</td><td></td></tr></tbody></table>

(continued on next page)
<table><caption>**Table 7 (continued)**</caption><thead><tr><th>Category</th><th>Variable</th><th>Method description</th></tr></thead><tbody><tr><td rowspan="20">Glucosinolate content</td><td>4hydroxyglucobrassicin_root</td><td rowspan="20">For glucosinolate analysis, a sub-sample of Brassicaceae plants were collected per plot, cut, and frozen at -80 °C before lyophilization. Glucosinolate profiles and concentrations were then analyzed according to their characteristics as described by de Graaf et al. [17].</td></tr><tr><td>4hydroxyglucobrassicin_shoot</td></tr><tr><td>4methoxyglucobrassicin_root</td></tr><tr><td>4methoxyglucobrassicin_shoot</td></tr><tr><td>epiprogoitrin_root</td></tr><tr><td>epiprogoitrin_shoot</td></tr><tr><td>glucoalyssin_root</td></tr><tr><td>glucoalyssin_shoot</td></tr><tr><td>glucobrassicanapin_root</td></tr><tr><td>glucobrassicanapin_shoot</td></tr><tr><td>glucobrassicin_root</td></tr><tr><td>glucobrassicin_shoot</td></tr><tr><td>glucoerucin_root</td></tr><tr><td>glucoerucin_shoot</td></tr><tr><td>glucoiberin_root</td></tr><tr><td>glucoiberin_shoot</td></tr><tr><td>gluconapin_root</td></tr><tr><td>gluconapin_shoot</td></tr><tr><td>gluconapoleiferin_root</td></tr><tr><td>gluconapoleiferin_shoot</td></tr><tr><td>gluconasturtiin_root</td></tr><tr><td>gluconasturtiin_shoot</td></tr><tr><td>glucoraphanin_root</td></tr><tr><td>glucoraphanin_shoot</td></tr><tr><td>glucoraphasatin_E/Z_mixture_II_root</td><td></td></tr><tr><td>glucoraphasatin_E/Z_mixture_II_shoot</td><td></td></tr><tr><td>glucoraphasatin_E/Z_mixture_I_root</td><td></td></tr><tr><td>glucoraphasatin_E/Z_mixture_I_shoot</td><td></td></tr><tr><td>glucoraphasatin_root</td><td></td></tr><tr><td>glucoraphasatin_shoot</td><td></td></tr><tr><td>glucoraphenin_root</td><td></td></tr><tr><td>glucoraphenin_shoot</td><td></td></tr><tr><td>glucotropaeolin_root</td><td></td></tr><tr><td>glucotropaeolin_shoot</td><td></td></tr><tr><td>neoglucobrassicin_root</td><td></td></tr><tr><td>neoglucobrassicin_shoot</td><td></td></tr><tr><td>progoitrin_root</td><td></td></tr><tr><td>progoitrin_shoot</td><td></td></tr><tr><td>sinalbin_root</td><td></td></tr><tr><td>sinalbin_shoot</td><td></td></tr><tr><td>sinigrin_root</td><td></td></tr><tr><td>sinigrin_shoot</td><td></td></tr></tbody></table>

## 5. Limitations

The data originate from a variety of experiments conducted on different plots, which introduces a certain degree of pedological variability, despite the relative geographical proximity of the sites. Some level of heterogeneity is also expected due to variations in experimental designs, the types of phenotypic traits recorded, the organizational scale of measurements (organ, plant, crop), and the completeness of available data. In some cases, not all variables were measured across all experiments, which may slightly limit the potential for direct comparisons. Additionally, a few management data are missing. When exact measurement dates were unavailable, a reasonable approximation was made by assigning a date close to the known cover crop termination period.

## 6. Ethics statement

All participants provided informed consent prior to their inclusion in the study. The study was approved by the appropriate institutional research ethics committees and this dataset does not involve human subjects, animal experiments, or sensitive data.
## Data availability

A comprehensive dataset gathering 37 cover crop field experiments across France (2004–2022): plant and soil-related agronomic variables on 33 crop species from five botanical families (https://entrepot.recherche.data.gouv.fr)

## CRediT Author Statement

**Manon Pull:** Data curation, Writing – original draft, Writing – review & editing; **Lionel Alletto:** Conceptualization, Funding acquisition, Investigation, Writing – review & editing; **Eric Justes:** Conceptualization, Investigation, Funding acquisition, Writing – review & editing; **Jay Ram Lamichhane:** Conceptualization, Investigation, Writing – review & editing; **Elana Dayoub:** Data curation; **Guillaume Hustet-Caou:** Data curation; **Emilie Sitnikow:** Data curation; **Noémie Gaudio:** Conceptualization, Data curation, Methodology, Software, Writing – review & editing; **Pierre Casadebaig:** Conceptualization, Methodology, Software, Writing – review & editing; **Rémi Mahmoud:** Conceptualization, Methodology, Software; **Neïla Ait Kaci Ahmed:** Investigation; **Julie Constantin:** Conceptualization, Investigation; **Antoine Couëdel:** Investigation; **Noémie Deschamps:** Investigation; **Eric Lecloux:** Investigation; **Damien Marchand:** Investigation; **François Perdrieux:** Investigation; **Didier Raffaillac:** Investigation; **Lucie Souques:** Investigation; **Gilles Tison:** Investigation; **Hélène Tribouillois:** Investigation; **Alexandre Wojciechowski:** Investigation; **Célia Seassau:** Conceptualization, Funding acquisition, Investigation, Writing – review & editing.

## Acknowledgements

We thank the technical team of UMR AGIR, the technicians from UE APC 0802 (https://doi.org/10.15454/1.5483266728434124E12), the members of GIP LIA, and the interns for the technical support during the experiments. The studied were funded by CRUCIAL project supported by French Ministry of Agriculture (CASDAR project no. C-2013-05) and the Occitanie Region (CLE project no. 13053068), Plant2Pro® Carnot Institute by the French National Research Agency (agreement #20-CARN-024-01-2021) for CIMSON, MAS Seeds and the National Association for Research in Technology (ANRT), FP6 Grain Legumes Integrated Project (Food-CT-2004-506223) and French Ministry of Agriculture (CASDAR Leg-N-GES), ARVALIS – Institut du Végétal, the Midi-Pyrénées Region, ANR Systerra MicMac-Design project (Grant No. ANR-STRA-06) and the ONEMA through the SYSTEM-Eco-4 and the Ecopest projects, NaturellementPopcorn project, funded by Bpifrance, within the frame of the Programme d'Investissements d'Avenir, and DEPHY EXPE within French national Ecophyto program by French Ministries of Agriculture, ecology, health and research with the technical and financial support of the French Biodiversty Agency.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## References

[1] H. Wickham, Tidy Data, J Stat Softw 59 (2014) 1–23, doi:10.18637/jss.v059.i10.

[2] R. Mahmoud, P. Casadebaig, N. Hilgert, N. Gaudio, A workflow for processing global datasets: application to intercropping, Peer Community J. 4 (2024), doi:10.24072/pcjournal.389.

[3] N. Ait Kaci Ahmed, B. Galaup, J. Desplanques, G. Dechamp-Guillaume, C. Seassau, Ecosystem services provided by cover crops and biofumigation in sunflower cultivation, Agronomy 12 (2022) 120, doi:10.3390/agronomy12010120.
[4] L. Souques, N.B. Langlade, P. Debaeke, M. Labadie, N. Deschamps, R. Lackdari, D. Marchand, E. Lecloux, C. Tapy, L. Alletto, Phenotypic traits of sunflower varieties depend on the composition of cover crops, Field Crops Res. 321 (2025) 109692, doi:10.1016/j.fcr.2024.109692.

[5] A. Couëdel, L. Alletto, É. Justes, Crucifer-legume cover crop mixtures provide effective sulphate catch crop and sulphur green manure services, Plant Soil 426 (2018) 61–76, doi:10.1007/s11104-018-3615-8.

[6] A. Couëdel, L. Alletto, É. Justes, The acquisition of macro- and micronutrients is synergistic in species mixtures: example of mixed crucifer-legume cover crops, Front. Agron. 5 (2023), doi:10.3389/fagro.2023.1223639.

[7] A. Couëdel, L. Alletto, J. Kirkegaard, É. Justes, Crucifer glucosinolate production in legume-crucifer cover crop mixtures, Europe. J. Agronomy 96 (2018) 22–33, doi:10.1016/j.eja.2018.02.007.

[8] A. Couëdel, L. Alletto, H. Tribouillois, É. Justes, Cover crop crucifer-legume mixtures provide effective nitrate catch crop and nitrogen green manure ecosystem services, Agric Ecosyst Environ 254 (2018) 50–59, doi:10.1016/j.agee.2017.11.017.

[9] D. Plaza-Bonilla, J.-M. Nolot, S. Passot, D. Raffaillac, E. Justes, Grain legume-based rotations managed under conventional tillage need cover crops to mitigate soil organic matter losses, Soil Tillage Res. 156 (2016) 33–43, doi:10.1016/j.still.2015.09.021.

[10] D. Plaza-Bonilla, J.-M. Nolot, D. Raffaillac, E. Justes, Cover crops mitigate nitrate leaching in cropping systems including grain legumes: field evidence and model simulations, Agric Ecosyst Environ. 212 (2015) 1–12, doi:10.1016/j.agee.2015.06.014.

[11] C. Bonnet, N. Gaudio, L. Alletto, D. Raffaillac, J.-E. Bergez, P. Debaeke, A. Gavaland, M. Willaume, L. Bedoussac, E. Justes, Design and multicriteria assessment of low-input cropping systems based on plant diversification in southwestern France, Agron. Sustain. Dev. 41 (2021) 65, doi:10.1007/s13593-021-00719-7.

[12] H. Tribouillois, J.-P. Cohan, E. Justes, Cover crop mixtures including legume produce ecosystem services of nitrate capture and green manuring: assessment combining experimentation and modelling, Plant Soil. 401 (2016) 347–364, doi:10.1007/s11104-015-2734-8.

[13] H. Tribouillois, P. Cruz, J.-P. Cohan, É. Justes, Modelling agroecosystem nitrogen functions provided by cover crop species in bispecific mixtures using functional traits and environmental factors, Agric. Ecosyst. Environ. 207 (2015) 218–228, doi:10.1016/j.agee.2015.04.016.

[14] H. Tribouillois, F. Fort, P. Cruz, R. Charles, O. Flores, E. Garnier, E. Justes, A functional characterisation of a wide range of cover crop species: growth and nitrogen acquisition rates, Leaf Traits Ecologic. Strateg. 10 (2015) e0122156 PLOS ONE, doi:10.1371/journal.pone.0122156.

[15] J.R. Lamichhane, Editorial - impact assessment, ecology and management of animal pests affecting field crop establishment: an introduction to the special issue, Crop Protect. 150 (2021) 105779, doi:10.1016/j.cropro.2021.105779.

[16] D.O., Holst, Holst filtration apparatus for Van Soest detergent Fiber analyses, J. Associat. Offic. Analytic. Chem. 56 (1973) 1352–1356, doi:10.1093/jaoac/56.6.1352.

[17] R.M. de Graaf, S. Krosse, A.E.M. Swolfs, E. te Brinke, N. Prill, R. Leimu, P.M. van Galen, Y. Wang, M.G.M. Aarts, N.M. van Dam, Isolation and identification of 4-α-rhamnosyloxy benzyl glucosinolate in Noccaea caerulescens showing intraspecific variation, Phytochemistry 110 (2015) 166–171, doi:10.1016/j.phytochem.2014.11.016.