dataesr/scientific-paragraphs-categorization huggingface dataset:
The data were recorded by the HPLC software "HyStar ™". For MEL and PLA2 standards, 1 mg was dissolved in 1 mL of ultra-pure water. A volume of 20 µL was analyzed. The gradient elution, as well as the time, are the same as HPLC analysis of the A. mellifera crude venom. Moreover, the composition of the elution gradient, the flow rate, as well as the wavelengths used are the same.
The Sample Selection We conducted the experiment in Dijon, Burgundy (Bourgogne), France, in multiple 1-hour sessions in October 2019. The sample consisted of 127 persons aged between 18 and 65 years. This sample of 127 participants was randomly selected based on the quota method and was representative for age groups and socio-economic status for the population of the city. Participants were recruited through the Chemosens PanelSens database built by the Centre des Sciences du Goût et de l'Alimentation, INRAE Dijon. During the recruitment, participants were informed that the experiment will focus on food without any tasting procedure, and it would last about 1 hour with a €10 indemnity. Each experimental session included between 14-16 participants and lasted 50 min. Table  1  presents some participants characteristics.
Sustainability 2021, 13, x FOR PEER REVIEW 9 of 16 random effects Tobit estimator. We used the R package pglm that approximates the likelihood function via a Gauss-Hermite quadrature  [31]. Figure  3. Average WTP for one packet of lentils. Note: 127 participants are taken into account. Δ** denotes significant difference at 5% and Δ*** denotes significant difference at 1% as tested by the Wilcoxon test for comparing paired sample WTP. For a given round, difference between the WTP for the Conventional and the Organic lentils and the WTP for Organic lentils and the Organic&Local lentils are indicated between vertical arrows. For a given type of lentils, the significant impact of information is indicated by the Δ about the segments of different curves. Figure  3  underlines that, without information at round #1, there exists a strong and significant premium given to organic and/or local labels by participants.
Given that each participant i wrote several WTPs for several products, errors related to these WTPs are potentially correlated to each participant. The random effect imposes constraints on the structure of the variance-covariance matrix. Furthermore, a WTP cannot be negative and is left-censored at zero, which is why we use the random effects Tobit estimator. We used the R package pglm that approximates the likelihood function via a Gauss-Hermite quadrature  [31]. Each product (Conventional/Organic/Organic&Local) is identified by a dummy variable (DV) equal to 1 for a given product, and zero otherwise. The type of information shared in a given round is also identified by a DV equal to 1 when it is shared before the WTP elicitation in a given round (and 0 otherwise). Thus, the DV Generic Info is equal to 1 for WTP elicited at round#3, and 0 otherwise.
This research was funded by the  European Union 's  Horizon 2020 research and innovation program  under the grant agreement No  727482 ,  DiverIMPACTS , and by the  French Agence Nationale de la Recherche (ANR)  under the grant agreement DIETPLUS  ANR-17-CE21-0003. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors only are responsible for any omissions or deficiencies. Institutional Review Board Statement: The study was conducted according to the guidelines of the  Declaration of Helsinki , and approved by the  Institutional Review Board  of  Centre National de la Recherche Scientifique -CNRS-Certificate  2-19079\UMR6265. The Chemosens PanelSens database used for the recruitment has been declared to the  Commission Nationale Informatique et Libertés-CNIL-Certificate  n  • 1148039.
Genome Sequencing, Assembly, and Annotation Isolation and purification of bacterial genomic DNA were performed with the Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA). Next-generation sequencing (NGS) libraries were prepared using the Illumina TruSeq Nano DNA Library Preparation Kit following the standard procedures recommended by the manufacturer. De novo assembly was performed using CLC NGS Cell v. 10. 0. 1. Gene annotation was carried out by the NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP 3. 3). Genomic data of selected Asaia genomes were obtained from the NCBI genome database (https://www. ncbi. nlm. nih. gov, accessed date: 5 January 2020).
bioinfotoolkits. net/task/create, accessed date: 1 April 2021) with an e-value cutoff of 0. 001 and an inflation value of 1. 5. The taxonomic assignment of Asaia sp. W12 was conducted using GTDB-Tk  [22]  with default settings, which placed this bacterium in the Asaia genus. Genomic islands (GIs) were predicted by both IslandPick and IslandPath-DIMOB methods  [23]. Eukaryotic-like proteins (ELPs) containing the motifs tetratrico peptide repeats (TPRs: PF13429, PF13371, PF00515, PF13181, PF13432, PF14559, PF14561, and PF09976); ankyrin repeats (ANKs: PF12796 and PF13637); Sel1 repeats (PF08238); and fibronectin type III (PF14310) were predicted using InterProScan v5. 44. 79 (http://www. ebi. ac. uk/interpro/ search/sequence/, accessed date: 5 January 2020). Prediction of the regulatory elements was done using the p2rp program with default settings (http://www.
p2rp. org, accessed date: 1 January 2020). Carbohydrate-Active enZyme (CAZyme) families, including enzymes of glycan assembly (glycosyltransferases, GT) and deconstruction (glycoside hydrolases, GH, polysaccharide lyases, PL, and carbohydrate esterases, CE), were semi-manually annotated using the CAZy database curation pipelines  [24] [25] [26]. More precisely, CAZymes were annotated based on a combination of BLASTP and HMMER searches and automatically processed when a high similarity to the reference CAZymes was observed and manually curated in intermediary similarity levels. The genomic context was inspected using GFF files and NCBI genome browsers  [26]. The identification of secondary metabolites was performed using the online server antiSMASH 5. 0 with "relaxed" detection strictness  [27].
| Genome assembly and scaffolding Sequencing reads from Illumina, PacBio, and Dovetail (Chicago and Hi-C reads) were used to assemble P. monodon genome. PacBio sequence data were used for de novo assembly, and Illumina sequence data were subsequently used for polishing to obtain high-quality contigs. Chicago and Hi-C reads were used to scaffold the draft genome. In brief, high-quality Illumina reads were prepared using TrimGalore (https://github. com/Felix Krueg er/TrimG alore) based on the following criteria: (i) no "N" base, (ii) trimming of adaptor sequences and low-quality bases (Q < 20), (iii) no trimmed reads <100 bp. To avoid mis-assembly due to repetitive sequences  (Tørresen et al. , 2019) , PacBio SEQUEL subreads with repetitive sequences comprised over 85% of total sequences were filtered out.
The GC content criteria (<25% and >85%) were applied for filtering low complexity DNA sequences before assembly. Noted that GC content of crustaceans ranges around 35%-41%  (Gao et al. , 2017; Yu et al. , 2015; Zhao et al. , 2012). Moreover, the reads matched mitochondria sequence (NC_002184. 1) were excluded from nucleus sequences and processed separately (Supporting Information method). Reads ≥5,000 bp were assembled using WTDBG2  (Hu et al. , 2019). Illumina reads were then aligned to the assembled contigs by minimap2  (Li, 2018)  and polished using wtpoa-cns mode in WTDBG2  (Hu et al. , 2019). Scaffolding of the genome assemblies was performed using HiRise, a software pipeline designed specifically for using proximity ligation data to scaffold genome assemblies  (Putnam et al. , 2016).
The input de novo assembly, shotgun reads, Chicago library reads, and Dovetail Hi-C library reads were used as input data for HiRise. An iterative analysis was conducted. First, shotgun and Chicago library sequences were aligned to the draft input assembly using a modified SNAP read mapper (http://snap. cs. berke ley. edu). The separations of Chicago read pairs mapped within draft scaffolds were analyzed by HiRise to produce a likelihood model for genomic distance between read pairs, and the model was used to identify and break putative misjoins, to score prospective joins, and make joins above a threshold. After aligning and scaffolding Chicago data, Dovetail Hi-C library sequences were aligned and scaffolded following the same method. After scaffolding, shotgun sequences were used to close gaps between contigs.
| Gene prediction and gene annotation Gene prediction and protein-coding sequence identification were performed using a combination of transcriptome-based prediction, homology-based prediction, and ab initio prediction methods using EvidenceModeler  (Haas et al. , 2008)  to generate consensus gene prediction for training species-specific parameter in AUGUSTUS  (Stanke et al. , 2008). To locate intron and exon regions, transcriptome-based prediction methods combined information from PacBio Iso-seq and other available P. monodon transcriptome databases (PRJNA4214000, SRR1648423, SRR1648424, SRR2191764, SRR2643301, SRR2643302, SRR2643304, SRR2643305) (Supporting Information Table  S1 ) to align against the genome sequence. For short-read transcripts, STAR  (Dobin et al. , 2013)  was employed to align against the genome before spliced read information was generated according to a previously published protocol  (Hoff & Stanke, 2019 ) using bam2wig script in AUGUSTUS.
Iso-Seq raw reads containing both 5' and 3' adapters (derived from full-length transcripts) were identified, and the adapters and poly (A) sequences were trimmed. Cleaned consensus reads were then mapped using Genomic Mapping and Alignment Program (GMAP)  (Wu & Watanabe, 2005). Expressed sequence tags  (Tassanakajon et al. , 2006)  were aligned to the genome using BLAT  (Kent, 2002)  and converted to potential gene structures using blat2hints script of AUGUSTUS. Protein sequences of P. monodon were mapped against proteins from closely related organisms including Hyalella azteca, and L. vannamei, using Exonerate version 2. 2. 0  (Slater & Birney, 2005). All gene models derived from these three methods were integrated by EvidenceModeler into a high confident nonredundant gene set, which was used to set species-specific parameters.
| Data preprocessing To obtain short-read RNA sequences, 30 libraries (n = 15 for each group) were constructed using the HiSeq Library Preparation kit (Illumina) and sequenced using Illumina NovaSeq 6000. Illumina sequencing (150 pair-end reads) was performed at Omics Drive, Singapore. The raw reads were quality-filtered (Q < 20, >50 bp) and adapter-trimmed using TrimGalore (https://github. com/Felix Krueg er/TrimG alore).
| Genome sequencing, assembly, and annotation A whole-genome shotgun strategy was used to sequence and assemble a black tiger shrimp genome from PacBio long-read data. A total of 13,157,113 raw reads (178. 94 Gb) representing 69. 08× sequence coverage based on the estimated genome size of 2. 59 Gb obtained from a previous report using the flow cytometry method  (Swathi et al. , 2018). De novo assembly of PacBio sequences yielded a preliminary assembly of 2. 39 Gb (70,380 contigs) with a contig N50 of 79 kb and an L50 of 6786 contigs (Table  1 ). The draft genome was further assembled using the long-range Chicago (in vitro proximity ligation; 444 million read pairs) and Hi-C (in vivo fixation of chromosomes; 430 million read pairs) library data scaffolded with the HiRise software (Dovetail Genomics; Tables  S2  and S3 ).
monodon genome was 9 genes per 500 Kb (Figure  1a , track c) and GC content was 36. 6% per 500 Kb (Figure  1a , track d). To evaluate the quality of our de novo assembly, we aligned Illumina DNA short reads obtained from this work and the previous report  (Yuan et al. , 2018)  to the assembled genome and found that approximately 93% of the DNA short reads could be mapped on our de novo assembly. We also aligned the publicly available RNA-seq reads  (Huerlimann et al. , 2018)  and Iso-Seq reads  (Pootakham et al. , 2020)  to the assembly and 90. 22% and 98. 77% of the RNA-seq and Iso-Seq reads were mapped to the assembly, respectively. To further assess the completeness of the genome assembly, we checked the gene content with the BUSCO software using the Eukaryota (odb9) database  (Simão et al.
, growth-associated genes, Hi-C, PacBio, Penaeus monodon, reference genome, transcriptomics for accurate genome annotation, thorough comparative analyses and marker-assisted breeding programs. Here, we combined a long-read sequencing technology and two long-range scaffolding techniques to obtain a high-quality, chromosome-scale genome assembly. First, the Pacific Biosciences (PacBio) sequencing platform was employed to generate the preliminary assembly. The PacBio sequencing technology enables contiguous assembly of repetitive regions containing transposable elements and tandem repeats, which are often omitted or highly fragmented in genomic sequences currently available in public databases. Subsequently, we applied the long-range Chicago (in vitro proximity ligation) and Hi-C (in vivo fixation of chromosomes) scaffolding techniques to further scaffold the preliminary assembly to achieve the first chromosome-scale genome assembly in P.
86 Mb. It is also one of the highest-quality crustacean genomes currently available. Of the 45 crustacean genome sequences listed in the NCBI genome database, only three species (Tigriopus japonicus (PRJNA592403), T. californicus (PRJNA237968), and Daphnia magna (PRJNA612523)) have their genomes assembled at a chromosome level. The present genome provides an invaluable resource for shrimp research. The availability of the chromosome-scale assembly allowed us to examine the syntenic relationship between the genomes of two economically important penaeid shrimp species: the black tiger shrimp and the Pacific white shrimp. The synteny analysis revealed a one-to-one relationship between most of the P. monodon and L. vannamei pseudochromosomes; however, a few pairs exhibited one-totwo synteny, suggesting that certain chromosomes derived from the common ancestor of P.
Interviewees Out of the database from the French Ministry of Agriculture that contains all inspection reports, we selected 22 dairy farmers located in an area of 150 km around Lyon (France) and that had been inspected at least once between 2009 and 2013. The farmers were randomly selected from this population because we had no pre-conceived hypotheses of the factors that would influence their perceptions. Once we selected the farmers, we checked that we obtained a range of elements that are usually taken into account in farm surveys such as farmer gender (17 men and 5 women), age (from 25 to 59 years old) and size of herds (from 12 to 350 dairy cows) (Table  2 ). All farms were run by the family or in partnership. Only one farm was certified organic. Some farmers had another professional experience before becoming farmers, and one farmer had another part-time job.
Acknowledgements We thank the farmers and the inspectors who gave their time for the interviews, and we are grateful to the students who carried out the interviews, namely  Anne-Cécile Meyer Warnod ,  Cecile Adam ,  Philippe Ambroise ,  Heidi Beaudoin ,  Bénédicte Beneult ,  Amal Boutaleb ,  Coraline Chamoret ,  Sandy Lecoq-Espellargas  and  Laure Paget , and offer our thanks to  Frédéric Mougeot  and  Anne-Claire Lomellini-Dereclenne  who supervised their work. We thank  Diane Bowden  for editing the English writing. I. Veissier 's work is supported by the  French government IDEX-ISITE  initiative  16-IDEX-0001  ( CAP 20-25 ).
Value of the Data • These data were obtained from one of the first long-term field trial (2009-2020) carried out in France, at the AgroParisTech experimental farm at Grignon (France, N 48. 84 °, E 1. 95 °). The experiment was focused on the assessment of innovative cropping systems with multiple environmental and production objectives designed to deliver an entire package of ecosystem services. Here, the data were collected for the first eight years of the field assessment. • These data have already been used to assess the environmental and production performances of the innovative cropping systems  [ 1 , 2 ]. • These data can be used as a benchmark for future studies aiming to design new cropping systems to decrease nitrogen (N) losses and improve N management in northern Europe cropping systems.
N 2 O fluxes were calculated for the 2010-2016 period in two cropping systems: the PHEP (productive and high environmental performance) system and the L-GHG (less greenhouse gas emissions) system. All the other data were measured over the 2009-2016 period in all four cropping systems: the PHEP system, the L-GHG system, the No-Pest (no pesticide use) system and the L-EN (less energy consumption) system. The data sets involved here have already been used: (i) to assess system performances, in terms of greenhouse gas emissions, energy consumption, pesticide use and yield, over the first crop sequence (2009-2014;  [2]  ); (ii) to evaluate and improve a tool for assessing N losses  [ 3 , 4 ].
File: 21_06_30_N2O_2010_2016 This file includes data for N 2 O fluxes and soil N (NO 3 -and NH 4 + ) contents, measured at a depth of 0-25 cm or 0-30 cm, collected at the same time in the PHEP and L-GHG systems over the 2010-2016 period. There are thirteen columns, corresponding to: (1) year of harvest (YYYY), (2) name of cropping system (PHEP and L-GHG); (3) number of replicate (1 to 3); (4) number of plot (1 to 12);  (5)   + content (mgN. l -  ); (13) soil N-NO 3 -content (mgN. l -  ).
File: 21_06_30_Soil_N_2009_2016 This file includes data for soil N (NO 3 -and NH 4 + ) contents measured at a depth of 0-150 cm, collected at three different time periods (at the start and end of winter, post-harvest), in all four cropping systems over the 2009-2016 period. There are fifteen columns corresponding to: (1) year of harvest (YYYY), (2) name of cropping system (PHEP, L-GHG, L-EN and No-Pest), (3) number of replicate (1 to 3), (4) number of plot (1 to 12), (5) number of sample (1 to 2), (  6 ) species (W and S indicate winter and spring crops, respectively. CC and CI indicate catch crops and cover crops, respectively), (7) period of measurement (BW indicates the beginning of winter, AW stands for after winter and PH for post-harvest), (8) date of measurement (DD/MM/YYYY),  (9)  soil layer (0-30 cm, 30-60 cm, 60-90 cm, 90-120 cm, 120-150 cm),  (10)  soil bulk density, (11) soil N-NH 4 + content (kgN.
N 2 O fluxes N 2 O fluxes were calculated for each of the three replicates of the PHEP and L-GHG systems. Data were collected monthly, except during the winter (from November to March) and August. Additional measurements were carried out during specific periods: four measurements were performed over a two-week period after each N fertilizer application; two measurements were made after the faba bean harvest if a significant rainfall event occurred ( > 10 mm). For each plot, N 2 O emissions were measured manually, with three static chambers inserted into the soil at a depth of 10 cm after sowing and left in place until harvest. Each chamber covered a surface area of 0. 25 m 2 and the top of the chamber was 0. 2 m above the soil surface. N 2 O emissions were measured between 10 a. m. and 3 p.
Soil N contents (NO 3 -and NH 4 + ) Two sets of soil N content data were managed and are provided in two different files: Set 1: measurements performed at the same time as those for N 2 O fluxes. Three randomized soil samples were collected close to the static chambers, at the depth either 0-25 cm or 0-30 cm, and pooled (data provided in file 21_06_30_N2O_2010_2016, columns 9, 10, 12 and 13). Set 2: measurements performed at three different periods over the year (i. e. at the beginning of winter (BW) around November 15, after winter (AW) around February 15, and about eight days post harvesting (PH) of the main crop). Six samples were collected from five layers (0-30 cm, 30-60 cm, 60-90 cm, 90-120 cm, and 120-150 cm) in each plot. Three samples from each layer were pooled to generate two soil samples per layer for each plot (data are in file 21_06_30_Soil_N_2009_2016, columns 11, 12, 14 and 15).
Acknowledgments We thank  Dominique Le Floch  and  Véronique Tanneau  for their contributions to the sampling and measuring processes, and the technical team of the " Versailles-Grignon " experimental unit for managing agricultural practices. Climatic data were collected from the Thiverval-Grignon meteorological station, which belongs to the  INRAE national agroclimatic network  ( http: //w3. avignon. inrae. fr/carto/), and is managed by the  US1116 AgroClim unit in Avignon (France). This work was supported by the  European Commission  through the  Seventh Framework Program  [ PURE  project:  FP72011-2014 ]; the  ADEME French agency  [ SYSCLIM  project; 2014]; and the  French Ecophyto plans  [Res0Pest projects 1 and 2; 2016 and 2023].
Alignment and phylogenetic reconstruction Sequences were aligned using the software Se-Al v. 2. 0  (Rambaut 1996). Insertion/deletion events were inferred by eye. Gaps were treated as missing data in the alignment and were added as binominal characters (absent or present) at the end of the matrix. Bayesian analyses were performed using MrBayes v. 3. 1. 2 (Huelsenbeck & Ronquist 2001; Ronquist & Huelsenbeck 2003). For each single gene data set, the best performing evolutionary model was identified under three different model selection criteria: Akaike information criterion (AIC)  (Akaike 1973) , AICc (a second order AIC, necessary for small samples), and the Bayesian information criterion (BIC)  (Schwartz 1978). We performed these calculations using MrModeltest v. 2. 4  (Nylander 2004 ). Ambiguous alignments and insertions-deletions were excluded from the data sets for analyses.
The tribe Gardenieae in New Caledonia According to the database FLORICAL  (Morat et al. 2012; Munzinger et al. 2020) , the family Rubiaceae is represented by 220 species in New Caledonia, to which we can add the 12 undescribed Atractocarpus species. The tribe Gardenieae, with 31 Atractocarpus species (30 endemic + one native), two endemic Aidia species, and three endemic Gardenia species, covers 15. 5% of the native Rubiaceae diversity of the New Caledonian islands, with 97% of endemism. Gardenia species are largely distributed on the main island; G. urvillei occurs in lowland sclerophyll forests or rarely bushes, G. oudiepe in forested vegetation from sea level to mountain, and G. aubryi is common in bushes on ultramafic substrates. The Aidia species, A. congesta and A. vieillardii, are dioecious, presenting sexual dimorphism.
ACKNOWLEDGEMENTS The authors wish to thank the staff and administrations of the NOU, P, S, and  UPS  herbaria for granting access to their collections, and several other herbaria, A, BM, BR, G, HBG, K, and Z, for providing digitized material on the web. The authors also thank  Birgitta Bremer  from the  Bergius Foundation (Sweden) , the  University of Bourgogne Franche-Comté , and  Jérôme Munzinger & Sandrine Isnard  of the  IRD of Montpellier & Nouméa  for silica-preserved material and sequencing facilities. The authors thank the New Caledonian province authorities for plant collection permits.