Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

Grapegenomics.com: a web portal with genomic data and analysis tools for wild and cultivated grapevines

<a href="https://grapegenomics.com">Grapegenomics.com</a> is a web portal that provides public access to genome references for grapevine cultivars (Vitis vinifera ssp. vinifera), wild grapevines (Vitis vinifera ssp. sylvestris), various wild grape species (Vitis spp. and Muscadinia spp.), and major fungal pathogens affecting grapes. All genomes are accessible through dedicated genome browsers, and published genomes are available for complete <a href="https://www.grapegenomics.com/download.php">download</a>. The site hosts all genomes produced by the laboratory of Dario Cantù in the Department of Viticulture and Enology at the University of California, Davis, along with published genome references generated by others, such as PN40024 and Pinot noir ENTAV115. Instructions for genome submission are provided <a href="https://www.grapegenomics.com/submit.php">here</a>. The portal is maintained by Noé Cochetel (ndcochetel[at]ucdavis.edu). In this version 2.0, all genome browsers utilize <a href="https://jbrowse.org/jb2/">jbrowse 2</a>.  Link to the website: <a href="https://www.grapegenomics.com">https://www.grapegenomics.com</a>

FASTA file containing to the MYB encoding gene Ant1 genomic sequences corresponding to wild and cultivated tomato accessions

Fasta sequence correspond to the MYB encoding gene An2-like. The genomic sequences correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome, and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>).

FASTA file containing the MYB encoding gene An2-like genomic sequences corresponding to wild and cultivated tomato accessions

FASTA sequence corresponds to the MYB encoding gene An2-like. The genomic sequences correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome (Hosmani et al., 2019), S. lycopersicum variety Indigo Rose (Yan et al., 2020), S. lycopersicum accession LA1996 [MN242011.1 (Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018),  Indigo Rose [MN433087 (Yan et al., 2020)], S. lycopersicum accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI)(available at NCBI: <a href="https://www.ncbi.nlm.nih.gov">https://www.ncbi.nlm.nih.gov</a>).

FASTA file containing the MYB encoding genes at the Aft locus with genomic sequences corresponding to wild and cultivated tomato accessions

FASTA sequences correspond to the MYB encoding genes An2-like and Ant1. The genomic sequences were combined correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome (Hosmani et al., 2019), LA1996 [MN242011.1, EF433417.1(Sapir et al., 2008; Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), S. lycopersicum accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI) (available at NCBI: <a href="https://www.ncbi.nlm.nih.gov/">https://www.ncbi.nlm.nih.gov</a>).

opencc-by-4.0Dec 2017View details →

Database of weeds in cultivation fields of France and UK, with ecological and biogeographical information

The database includes a list of 1577 weed plant taxa found in cultivated fields of France and UK, along with basic ecological and biogeographical information. The database is a CSV file in which the columns are separated with comma, and the decimal sign is ".". It can be imported in R with the command "tax.discoweed <- read.csv("tax.discoweed_18Dec2017_zenodo.csv", header=T, sep=",",  dec=".", stringsAsFactors = F)" Taxonomic information is based on TaxRef v10 (Gargominy et al. 2016), - 'taxref10.CD_REF' = code of the accepted name of the taxon in TaxRef, - 'binome.discoweed' = corresponding latine name, - 'family' = family name (following APG III), - 'taxo' = taxonomic rank of the taxon, either 'binome' (species level) or 'infra' (infraspecific level), - 'binome.discoweed.noinfra' = latine name of the superior taxon at species level (different from 'binome.discoweed' for infrataxa), - 'taxref10.CD_REF.noinfra' = code of the accepted name of the superior taxon at species level. The presence of each taxon in one or several of the following data sources is reported: - Species list from a reference flora (observations in cultivated fields over the long term, without sampling protocol), * 'jauzein' =  national and comprehensive flora in France (Jauzein 1995), - Species lists from plot-based inventories in cultivated fields, * 'za' = regional survey in 'Zone Atelier Plaine & Val de Sèvre' in SW France (Gaba et al. 2010), * 'biovigilance' = national survey of cultivated fields in France (Biovigilance, Fried et al. 2008), * 'fse' = Farm Scale Evaluations in England and Scotland, UK (Perry, Rothery, Clark et al., 2003), * 'farmbio' = Farm4Bio survey, farms in south east and south west of England, UK (Holland et al., 2013) - Reference list of segetal species (species specialist of arable fields), * 'cambacedes' = reference list in France (Cambacedes et al. 2002) Life form information is extracted from Julve (2014) and provided in the column 'lifeform'. The classification follows a simplified Raunkiaer classification (therophyte, hemicryptophyte, geophyte, phanerophyte-chamaephyte and liana). Regularly biannual plants are included in hemicryptophytes, while plants that can be both annual and biannual are assigned to therophytes. Biogeographic zones are also extracted from Julve (2014) and provided in the column 'biogeo'. The main categories are 'atlantic', 'circumboreal', 'cosmopolitan, 'Eurasian', 'European', 'holarctic', 'introduced', 'Mediterranean', 'orophyte' and 'subtropical'. In some cases, a precision is included within brackets after the category name. For instance, 'introduced(North America)' indicates that the taxon is introduced from North America. In addition, some taxa are local endemics ('Aquitanian', 'Catalan', 'Corsican', 'corso-sard', 'ligure', 'Provencal'). A single taxon is classified 'arctic-alpine'. Red list status of weed taxa is derived for France and UK: - 'red.FR' is the status following the assessment of the French National Museum of Natural History (2012), - 'red.UK' is based on the Red List of vascular plants of Cheffings and Farrell (2005), last updated in 2006. The categories are coded following the IUCN nomenclature. A habitat index is provided in column 'module', derived from a network-based analysis of plant communities in open herbaceous vegetation in France (Divgrass database, Violle et al. 2015, Carboni et al. 2016). The main habitat categories of weeds are coded following the Divgrass classification, - 1 = Dry calcareous grasslands - 3 = Mesic grasslands - 5 = Ruderal and trampled grasslands - 9 = Mesophilous and nitrophilous fringes (hedgerows, forest edges...) Taxa belonging to other habitats in Divgrass are coded 99, while the taxa absent from Divgrass have a 'NA' value. Two indexes of ecological specialization are provided based on the frequency of weed taxa in different habitats of the Divgrass database. The indexes are network-based metrics proposed by Guimera and Amaral (2005), - c = coefficient of participation, i.e., the propensity of taxa to be present in diverse habitats, from 0 (specialist, present in a single habitat) to 1 (generalist equally represented in all habitats), - z = within-module degree, i.e., a standardized measure of the frequency of a taxon in its habitat; it is negatve when the taxon is less frequent than average in this habitat, and positive otherwise; the index scales as a number of standard deviations from the mean.

opencc-by-4.0Nov 2024View details →

Dataset: Co-composting to close the cycle of resources during rose cultivation in Kenya: An agronomic and pesticide residue assessment

This dataset and these scripts supports the article 'Co-composting to close the cycle of resources during rose cultivation in Kenya: An agronomic and pesticide residue assessment' as published in Cleaner Waste Systems. https://doi.org/10.1016/j.clwas.2024.100154 Roses are an important crop for the floricultural sector of Kenya and roses are a perennial crop and under continuous production for six to ten years. The cultivation produces large quantities of green waste, up to 50 kg per hectare per day. In this experiment we focused on exploring the potential of large-scale composting of rose waste in Kenyan rose cultivation. The objective of this study was to examine the potential of composting rose waste in this large-scale commercial setting with low operational costs, exploring its benefits and challenges. In piles of 4000 kg green waste the evolution of three mixtures was closely monitored in terms of their physico-chemical parameters. Furthermore, the pesticide residue levels of mature rose waste were assessed.

opencc-by-4.0Nov 2024View details →

Dataset: The impact of rose-waste compost on commercial cut rose cultivation in Kenya

This dataset and these scripts supports the manuscript 'From waste to fertilizer: The impact of rose-waste compost on commercial cut rose cultivation in Kenya' as submitted to Cleaner Waste Systems.  Roses are an important crop for the floricultural sector of Kenya and roses are a perennial crop and under continuous production for six to ten years. The cultivation produces large quantities of green waste, up to 50 kg per hectare per day. In this experiment we evaluated the impact of compost amendment on the yield and quality of cut roses cultivation in a large-scale commercial setting with over 7,500 rose plants. It was conducted between August 2022 and February 2024 near Lake Naivasha in Kenya. Additionally we evaluated the potential of compost to partially substitute mineral fertilizer. Yields were recorded daily and cut rose quality and physicochemical soil parameters were assessed every three to six months to  comprehensively evaluate the impact of compost incorporation on cut rose production.

edi48/100

Data for 'The value of shifting cultivation for biodiversity in Northeast India'

Shifting cultivation is a widespread land-use in many tropical countries that also harbours significant levels of biodiversity. Increasing frequency of cultivation cycles and expansion into old-growth forests have intensified the impacts of shifting cultivation on biodiversity and carbon sequestration. We assessed how bird diversity responds to shifting cultivation and the potential for co-benefits for both biodiversity and carbon in such landscapes to inform carbon-based payments for ecosystem service (PES) schemes. We conducted this study in Nagaland, Northeast India. We surveyed above-ground carbon stocks and bird communities across various stages of a shifting cultivation system and old-growth forest using composite carbon sampling plots and repeated point counts directly overlaying the carbon plots in both summer and winter. We assessed species diversity using species accumulation and rarefaction curves based on Hill numbers. We fitted a linear mixed-effect model to assess the relationship between species richness and fallow age. We also examined possible co-benefits between carbon and biodiversity from fallow regeneration in terms of relative community similarity to old-growth forest across carbons stocks. Farmland and secondary forests regenerating on fallowed land had similar bird species richness to old-growth forests in summer and relatively higher species richness in winter. Within regenerating fallows, we did not find any strong evidence that fallow age influenced bird species richness. Bird community resemblance to old-growth forest increased with secondary forest maturity, correlating also with carbon stocks in summer. However, bird community assemblage did not show a strong association with habitat types and carbon stocks during winter. This study underscores the important role of traditional non-intensive shifting cultivation in providing refuges for biodiversity within heterogeneous habitat mosaics. Effectively managing these landscapes is crucial f

openCC (other)Jun 2022View details →

opencc-by-4.0Dec 2021View details →

The impact of Syrian Civil War on cultivated cropland dynamics

The data needed to replicate paper --'The impact of Syrian Civil War on cultivated cropland dynamics'

FASTA file containing the MYB encoding gene An2-like and Ant1 coding sequences corresponding to wild and cultivated tomato accessions

The coding sequence (CDS) of the MYB encoding genes Ant1 and An2-like. Sequences were retrieved from regions corresponding to the Aft locus from Solanum galapagense accession LA1141, S. lycopersicum variety OH8245, and  84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences were compared to available CDS available from the Sol genomics network (SGN) and the National Center for Biotechnology Information. The CDS was retrieved from S. lycopersicum variety Indigo Rose [MN433087 (Yan et al., 2020)], S. lycopersicum accession LA1996 [MN242011.1, EF433417.1( Sapir et al., 2008; Colanero et al., 2020)], and S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)], The orthologous CDS corresponding to the Aft MYB encoding genes from Solanum tuberosum L. Group Phureja clone DM1-3 genome (PGSC DM v4.03 Pseudomolecules) was retrieved from the Potato Genome Sequence Consortium (PGSC: Potato Genome Sequencing Consortium et al., 2011), and the Capsicum annum cv. CM334 genome was retrieved from Capsicum annuum cv CM334 genome chromosome release 1.55 (Hulse-Kemp et al. 2018). These CDS were obtained using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at https://solgenomics.net/tools/blast/). Comparison of syntenic chromosomal regions using known positions of tomato, potato, and pepper markers with comparative map viewer from  SGN: (available at https://solgenomics.net/cview) on chromosome 10, was used as a quality check for S. tuberosom and C. annuum. Orthologous CDS corresponding to Salvia miltiorrhiza, Arabidopsis thaliana, [NM_105308.2, NM_105310.4 (Teng et al., 2005, Cominelli et al., 2008; Beradini et al., 2015)] were chosen based on tomato Aft sequence homology and gene annotations of positive R2R3 MYB regulation of anthocyanin. The CDS corresponding to the Aft genes were retrieved from the CDS reference genomes available from the Sol Genomics Network SGN: Tomato Genome CDS (ITAG release 4.0), Potato PGSC DM v3.4 CDS sequences, Capsicum annuum cv CM334 Genome CDS (release 1.55), or from the National Center for Biotechnology Information (NCBI: https://www.ncbi.nlm.nih.gov) reference sequences (RefSeq) section of the Genbank records. When accessed from Genank records, the CDS sequence was extracted from the “features” section and exported as a FASTA file.

opencc-by-4.0May 2022View details →

Mapping the Atlantic Ocean i.e. the Gulf of Maine to identify suitable cultivation sites for kelp species

Input source: <ul> <li>Temperature data</li> <li>Depth data</li> <li>Wave data</li> <li>Nutrients data</li> <li>Current data</li> <li>Marine use data</li> </ul> All from other available sources outside the project   DATA SET GENERATED: <ul> <li>Environmental data</li> <li>Training/validation data</li> <li>The socioeconomic datasets</li> </ul> <ul> <li>Map of suitable sites</li> <li>Model using GIS</li> </ul>

Cultivation practices in soybean production at a glance

This video contains information about cultivation practices in soybean production. It was made within the scope of the Legumes Translated Horizon 2020 project. It is available in Serbian with subtitles in English, German, Hungarian, Italian, Romanian, Russian and Serbian.

opencc-by-4.0May 2024View details →

Morphological and physical chemical characterization of main agricultural plastics articles used for protected cultivation systems during ageing in fields, and collection practices

This dataset includes data generated upon the implementation of the ST 1.2.1 "Analysis of degradation and fragmentation of AP and transfer of MNP to soil". The activities dealt with the study of degradation and fragmentation from weathering and agricultural practices of conventional and biodegradable AP relevant for transfer of MNP to soil (during both use and end of life). In particular, the experimental data refer to characterization of biodegradable mulch films, pristine (coded M-BIO0) or subjected to photo-oxidative weathering (M-BIO192), as well as the same samples buried in soil for varying time periods, up to 353 days. The folders included contain gel permeation chromatography (GPC) and Matrix-assisted Laser Desorption Ionization (MALDI-TOF) data, which account for the change in film molecular weight upon soil burial. Furthermore, Differential Scanning Calorimetry (DSC) data and  Scanning Electron Microscopy (SEM) and Water Contact Angle (WCA) images of some selected samples are also provided. The folder named MS RAW FILES.zip includes all the mass spectrometry raw data.

opencc-by-4.0Apr 2022View details →

Small-scale farming in drylands: New models for resilient practices of millet and sorghum cultivation - Dataset and code

This repository contains the primary research data and R code used for data analysis for the article "Small-scale farming in drylands: New models for resilient practices of millet and sorghum cultivation" Published in the journal PLOS ONE (<a href="https://doi.org/10.1371/journal.pone.0268120">https://doi.org/10.1371/journal.pone.0268120</a>) N.B. To run the code unzip the folder 9-RData.zip and save it in the same working directory as the datasets V 2.0 changes: A. Datasets 1-2-3 - small formatting corrections B. Dataset 7 - fixing some errors in the calculations C. Code - minor fixes and seimplicifaction

opencc-by-4.0Sep 2023View details →

Global Wheat Cultivation Distribution under Future Climatic and Socio-economic Conditions (RCP-SSP combinations)

This is the outcome data from our study titled "<a href="http://dx.doi.org/10.1016/j.scitotenv.2024.170481" target="_blank" rel="noopener">Prediction of global wheat cultivation distribution under climate change and socioeconomic development</a>" which was published in The Science of The Total Environment.  The present study represents a significant extension of our previous research on "<a href="http://dx.doi.org/10.1016/j.scitotenv.2019.06.153" target="_blank" rel="noopener">The Potential Distribution and Dynamics of Global Wheat under Multiple Climate Change Scenarios"</a>. Socioeconomic and climate change are both critical factors influencing the global distribution of crop cultivation. However, there has been limited exploration of the role of socioeconomic factors in predicting future crop cultivation distribution under climate change. We have proposed the MaxEnt-SPAM approach under the assumption that environmental conditions are the primary determinants of land suitability for cultivating wheat, while socioeconomic factors play a crucial role in influencing farmers' crop choices. In essence, the distribution of wheat cultivation is contingent upon maximizing potential revenue and ensuring suitability for wheat planting. The proposed MaxEnt-SPAM approach was utilized to estimate the distribution of wheat cultivation in three combined Representative Concentration Pathway (RCP) - Shared Socioeconomic Pathway (SSP) scenarios, namely RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP3. The methodology involved estimating wheat planting suitability under future RCP scenarios using the MaxEnt model, predicting farmers' crop choices under future SSP scenarios through Time series-Backpropagation (TS-BP) models, and ultimately estimating global wheat cultivation distribution based on the SPAM model. Validation of this approach against major known datasets on the distribution of wheat cultivation demonstrated satisfactory accuracy, with a predictive accuracy exceeding 85% and a significant positive correlation (p < 0.01) between the predicted global wheat cultivation and multiple known datasets. Based on the aforementioned concept and methodology, a global wheat cultivation distribution grid (0.5 degree × 0.5 degree) was projected under the RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP3 scenarios. The findings suggest that RCP8.5-SSP3 may offer the most favorable conditions for wheat cultivation. Additionally, socioeconomic development significantly constrains the potential distribution of wheat cultivation, with estimated areas accounting for an average of 77% of the potential distribution determined by climatic factors under the selected RCP-SSP scenarios. Socioeconomic development appears to have a positive impact on wheat cultivation in Africa. Our results illustrate the influence of socioeconomic factors on crop distribution within a market economy framework, underscoring the importance of integrating socioeconomic factors and climate change for accurate predictions of crop cultivation distribution. We contend that the global wheat cultivation distribution datasets under future climatic and socio-economic conditions (RCP-SSP combinations) are a valuable addition to existing products. This prediction data is among the few products to consider both climate change and socio-economic development, providing a more comprehensive understanding of crop cultivation distribution dynamics. The Global Wheat Cultivation Distribution under Future Climatic and Socio-economic Conditions (RCP-SSP combinations) is expected to enhance our comprehension of the dynamics and distribution of global wheat cultivation under different climate change and socio-economic development paths in the future, potentially supporting research in earth system simulation and agricultural sciences. The dataset for the Global Wheat Cultivation Distribution under Future Climatic and Socio-economic Conditions (RCP-SSP combinations) and the Maxent-SPAM approach code is stored in a zip package named SPAM_MaxEnt.zip, which contains two folders (code and data). code: This sub-folder provides the main program and example data for the MaxEnt-SPAM approach. Codes are written in Matlab language by Puying Zhang. There are also 'read me.txt' files under the code folder to provide the necessary information. The exampleData contains 1. h_pri.tif: prior data 2. h_res.tif: global C3 crop cultivation proportion Run the main programme: cross_entroy.m data: This sub-folder contains global wheat cultivation distribution stored in GeoTIFF file format. 1 Global distribution of the long-term wheat-cultivation area fraction: This sub-folder contains the data for the global distribution of the long-term wheat-cultivation area fraction in RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP3 scenarios. The value of each data ranges from 0 to 1, indicating the long-term wheat-cultivation area fraction in each grid, and the higher the value, the more wheat cultivated. r2s1f_sub.tif: the data for global distribution of the long-term wheat-cultivation area fraction in RCP2.6-SSP1 scenario r4s2f_sub.tif: the data for global distribution of the long-term wheat-cultivation area fraction in RCP4.5-SSP2 scenario r8s3f_sub.tif: the data for global distribution of the long-term wheat-cultivation area fraction in RCP8.5-SSP3 scenario 2 Spatial overlap between the long-term period of land suitability for wheat planting and wheat cultivation distribution: This sub-folder contains the data for Spatial overlap between the long-term period of land suitability for wheat planting and wheat cultivation distribution in multi-scenarios. The value of each data contains three values:{1, 2, 3}, 1 wheat cultivation existed but was predicted to be unsuitable to plant wheat; 2 presented a reduction in the wheat cultivation area compared to the land's suitability; 3 presented the region that wheat cultivation existed and was predicted to be suitable to plant wheat. com_suit_fra126.tif: the spatial overlap between the long-term period land suitability for wheat planting and wheat cultivation distribution in (a) RCP2.6-SSP1 scenario and RCP2.6 com_suit_fra245.tif: the spatial overlap between the long-term period land suitability for wheat cultivation and wheat cultivation distribution in (b) RCP4.5-SSP2 scenario and RCP4.5 com_suit_fra385.tif: the spatial overlap between the long-term period land suitability for wheat cultivation and wheat cultivation distribution in (c) RCP8.5-SSP3 scenario and RCP8.5 3 Differences in the proportion of long-term wheat cultivation: This sub-folder contains the data for the difference in the proportion of long-term wheat cultivation under the RCP-SSP scenarios and the distribution of long-term wheat planting suitability under the same RCP scenarios. The value of each data ranges from -1 to 1, This data is obtained by using the wheat-cultivation area fraction minus planting suitability grid to grid. the negative value indicates that the proportion of wheat cultivation is lower than the wheat planting suitability, while this positive value indicates that the proportion of wheat cultivation is higher than the wheat planting suitability. r2s1_f.tif: Difference in the proportion of long-term wheat cultivation under the RCP2.6-SSP1 scenario and the distribution of long-term wheat planting suitability under the RCP2.6 scenario r4s2_f.tif: Differences between the proportion of long-term wheat cultivation in RCP4.5-SSP2 and the suitability of long-term wheat planting under the RCP4.5 scenario r8s3_f.tif: Differences between the proportion of long-term wheat cultivation in RCP8.5-SSP3 and the suitability of long-term wheat planting under the RCP8.5 scenario  References: Yaojie Yue, Puying Zhang, Yanrui Shang. The Potential Distribution and Dynamic of Global Wheat under Multiple Climate Change Scenarios. Science of the Total Environment, 2019, 688: 1308-1318. Xi Guo, Puying Zhang, Yaojie Yue. Prediction of global wheat cultivation distribution under climate change and socio-economic development. Science of the Total Environment, 2024, 919: 170481. For more details on the MaxEnt (Maximum entropy) model, please refer to (Phillips et al., 2006; Elith et al., 2011). SPAM (spatial production allocation model) refers to (You et al., 2009; You et al., 2014). Elith, J., Phillips, S.J., Hastie, T., Dudík, M., Chee, Y.E., Yates, C.J., 2011. A statistical explanation of maxent for ecologists. Divers Distrib 17 (1), 43-57. https://coi.org/10.1111/j.1472-4642.2010.00725.x. Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecol Model 190 (3-4), 231-259. https://coi.org/10.1016/j.ecolmodel.2005.03.026. You, L.Z., Wood, S., Wood-Sichra, U., 2009. Generating plausible crop distribution maps for sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach. Agr Syst 99 (2-3), 126-140. https://coi.org/10.1016/j.agsy.2008.11.003. You, L.Z., Wood, S., Wood-Sichra, U., Wu, W.B., 2014. Generating global crop distribution maps: from census to grid. Agr Syst 127, 53-60. https://coi.org/10.1016/j.agsy.2014.01.002

opencc-by-4.0Mar 2014View details →

Figure 7 in New eriophyoid mites (Acari: Prostigmata: Eriophyoidea) from cultivated plants from northeastern Brazil, including the second taxon in the Prothricinae

Figure 7. Tegolophus indica. CGM, coxigenital region, male; D, dorsal habitus, female; DS, detail of prodorsal shield; em, empodium, leg I, female; IG,. internal genital structures, female; L1, leg I, female; L2, leg II, female; V, ventral habitus, female.

opencc-by-4.0Mar 2014View details →

Figure 6 in New eriophyoid mites (Acari: Prostigmata: Eriophyoidea) from cultivated plants from northeastern Brazil, including the second taxon in the Prothricinae

Figure 6. Thamnacus paubrasil sp. nov. (A) Dorsal habitus, female; (B) ventral habitus, female; (C) lateral habitus, female; (D) leg I and II, female; (E) epigynum; (F) genitalia, male; (G) empodium, female.

opencc-by-4.0Dec 2020View details →

Display a simulation of a batch or fed-batch cultivation of S. cerevisiae

The model is implemented as it is described in the paper "Pham, Larsson, Enfors - 1998 - Growth and energy metabolism in aerobic fed-batch cultures of Saccharomyces cerevisiae Simulation and mod". The batch and fed-batch are both implemented, the oscillation function was not used. All parameters were taken from the paper and are saved under parameters.py.

opencc-zeroJul 2001View details →

FIGURE 1 in Crenidorsum aroidephagus Martin & Aguiar sp. nov. (Sternorrhyncha: Aleyrodidae), a New World whitefly species now colonising cultivated Araceae in Europe, Macaronesia and The Pacific Region

FIGURE 1. Computer-montage image of slidemounted puparium of Crenidorsum aroidephagus Martin & Aguiar sp. nov. ex- Philodendron gloriosum, Berlin Botanic Garden, with lingula unfolded and excluded from vasiform orifice.