Tab Mapper

The tab mapper is a handy little tool that will render a guitar tab file with graphic chord diagrams displayed alongside. This comes in handy for people who just don't have every single chord shape memorized. Just plug in the web site address of a valid .tab or .crd file and hit "Go". In general, the tab mapper does a better job with printer friendly URLs. If there is more than one way to play a chord, the tab mapper will choose the most common shape. To see other fingerings, click on the chord diagram and you will be taken to the chord calculator.

A chord {x 0 2 2 2 0} chord
B chord {x 2 4 4 4 2} chord
C chord {x 3 2 0 1 0} chord
G chord {3 2 0 0 0 3} chord
Gdim chord {3 4 5 3 x x} chord

Original file located @ http://cassavabase.org.

Show me scales that sound good with the chords in this song: A, B, C, G, Go.

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Cassava Genomes

Sequencing wild and cultivated cassava reveals hybridization and genetic diversity

  • Browse the cassava genomev6.1 @ JGI
  • BLAST search @ JGI
  • Download the annotations @ JGI
  • Download the Genome Sequence v6.1 @ JGI
  • Design VIGS constructs

Breeding programs

Search, retrieve, save breeding trials

  • Search accessions and trials
  • Make crossings
  • Fieldbook App & uploading
  • Cassava Trait Ontology

SolGS

Genomic selection and molecular breeding

  • Genomic Selection
  • Population Structure
  • Maps & Marker Search

NextGenCassava Community

& Partners

  • GCP21
  • RTB program
  • GatesNotes on Cassava
  • Mueller lab @BTI

SGN SlideShare

Slides from conferences and courses

    Cassavabase @ PAG Meeting 2016 SolGS @ PAG Meeting 2016 Cassavabase Workshop @ WCRTC Meeting 2015 Wizard search and list manager video demo
Previous Next
  • Genomics
  • Breeding
  • Genomic selection
  • Community
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New to the database?

Let us help!
Click this button to begin our guided help.
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What are you interested in? For General Help

Upload an experimental field trial into the database that you have saved on your computer in Excel

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Design a completely new experimental field trial in the database

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Catalog your available seed inventory into the database

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Upload phenotypic data into the database that you have saved on your computer in Excel

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Plan tissue sampling

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Upload crosses and crossing information into the database

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Print barcode labels for my experiment (for your plots or plants or tissue samples in the field, or for your 96 well plate and tissue samples)

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Analyze phenotypic performance across trials

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Prepare a 96 or 384 well plate for a genotyping experiment

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Upload VCF genotypic data

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Tissue Sampling

  1. Intro
  2. Sampling Level
  3. Select a field trial
  4. Plant Entries
  5. Create Tissue Sample Entries
  1. This workflow will guide you through tissue sampling an experiment

    Tissue samples collected from the field are linked to a single plant, which is in turn linked to a single plot.

    Many tissue samples can be created for each plant.

    Each tissue sample has a globally unique name.


    A unique tissue sample is present in each well of a genotyping plate (96 or 384 well plates).

    The tissue sample in a 96 well plate can originate from another tissue sample name, plant name, plot name, or accession name.



    Go to Next Step
  2. At which level do you plan to keep track of your sampling?

       Accession Level: The sample is not from a field trial entity and only the accession name is known.
       Plot Level: Each plot in the field has a unique identifier, ideally with a barcode label.
       Plant Level: Each plant in the field has a unique identifier, ideally with a barcode label.
       Tissue Sample Level: Each tissue sample collected from the field has a unique identifier, ideally with a barcode label.

    Go to Next Step
  3. Select a field trial

    Field trial is not relevant for the type of tissue sampling you selected. Go to next step.

    Go to Next Step
    Select Trial name Description Breeding program Folder Year Location Trial type Design Planting Date Harvest Date Download


    Go to Next Step
  4. Plant entries in your field trial

    Plant entries not relevant for the type of tissue sampling you selected. Go to next step.

    Go to Next Step

    Plant entries exist for this trial. Go to next step.

    Go to Next Step

    Please create plant entries for this trial.

    Number of plants per plot:
    Inherits Management Factor(s) From Plots:

    Submit
  5. Create tissue sample entries for this trial

    Field trial tissue sample entries not relevant for the type of tissue sampling you selected. Go to next step.

    Go to Next Step

    Tissue sample entries exist for this trial. Go to next step.

    Go to Next Step
      Number of tissue samples per plant:
    Inherits Management Factor(s) From Plots:

    Submit

Complete! You have all the entities you need to conduct your sampling.

  • All of the entities that you want to sample are saved in the database and available to use!
  • You can print barcodes for the entities you intend to sample on. These barcodes can be attached to your collection vials/containers to assist during sampling.
Download Field Trial Layout!
  • After you have finished sampling, you can use these entities as source material for a genotyping plate (96 or 384 well plate). Click the button below to create a genotyping plate now, if you will create a 96 or 384 well plate.
  • The Android Coordinate application can help you create 96 or 384 well plates. Alternatively you can create your plate layout in Excel and upload it.
Create Genotyping Plate Now!

Complete! You have all the entities you need to conduct your sampling.

  • All of the entities that you want to sample are saved in the database and available to use!
  • You can print barcodes for the entities you intend to sample on. These barcodes can be attached to your collection vials/containers to assist during sampling.
Download Field Trial Layout!
  • After you have finished sampling, you can use these entities as source material for a genotyping plate (96 or 384 well plate). Click the button below to create a genotyping plate now, if you will create a 96 or 384 well plate.
  • The Android Coordinate application can help you create 96 or 384 well plates. Alternatively you can create your plate layout in Excel and upload it.
Create Genotyping Plate Now!
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Workflow for seedlot inventory

I have new seedlots that need to be added into the database.

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I conducted an inventory (in weight(g)) and want to update the database to reflect the current state of the inventory.

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Workflow for uploading phenotypes

Nothing Here Yet
Please refer to the Documentation
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Workflow for trial barcoding

Nothing Here Yet
Please refer to the Documentation
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Workflow for comparing one or many trials

Nothing Here Yet
Please refer to the Documentation
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Upload Existing Trial(s)

  1. Intro
  2. File Formatting
  3. Enter trial information
  4. Trial Linkage
  5. Fix missing accessions problem
  6. Fix missing seedlots problem
  7. Try submitting trial again
  1. This workflow will guide you through uploading a new trial or trials into the database

    A field trial represents plots in the field where each plot has a globally unique plot_name, a sequential plot_number that is unique in the trial (e.g. 101, 102, 103 for three separate plots), and an accession_name representing the genotype being tested in that plot. In cases where a cross/family is being evaluated (e.g. F1 hybrid, backcrossing), a cross_unique_id or a family_name can be used instead of an accession_name. Each plot can belong to different blocks (block_number) and reps (rep_number) depending on the experimental design you are using (e.g. complete block vs augmented design). Each plot can have a row_number and col_number indicating the relative position of the plot in the field.

    If a specific accession is a check or control, you can indicate the plots that that accession is planted in as controls using is_a_control.

    You can provide the specific seedlot_name planted in each plot, along with the number of seeds (num_seed_per_plot) and/or the weight (g) of seed (weight_gram_seed_per_plot) that were used.

    A trial can represent a yield trial, a phenotyping trial, a crossing block, a greenhouse, a nursery, etc.

    A plot can have many plants, which the database can track as separate entities, allowing you to record plant level observations and information.



    Go to Next Step
    • Single Trial Design
    • Multiple Trial Designs

    File format information
    Single trial spreadsheet

    Go to Next Step

    Single Trial Designs may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

    Optional columns may be left out, if not used in your data.

    File format information
    Multiple trial spreadsheet


    Ignore Warnings:
    Email Alert:
    Email:

    Upload Trial Designs Reload Page

    Multiple Trial Designs may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

    Optional columns may be left out, if not used in your data.

  2. Enter information about the experiment and upload your trial layout

    Trial Name:
    Breeding Program:
    5CPBTICARICHCIATCIP-genebankCNRACornellCSIR-CRIEmbrapaIDIAFIITAINERA_IITA_DRCISABUITCKALROKUNaCRRINRCRIRayongSLARITARIUACUHUNILA-IndonesiaZARI
    Location:
    RestrepoIgbariamRayongGranadaSanto Tomas. Atlantico, ColombiaFlorenciabwangaNaliendeleKokrokoChokweCalabarJaguaripe (BA) - Fazenda EsperançaCorozal. Sucre, ColombiaAgborSuakokoKibahaIshiaguBarahonaNjalaSotoubouaBuenos AiresAlbaniaItanhem (BA)IlorinAcacias. Meta, ColombiaVerdelandia (MG)-Brasnica Fazenda OrienteCIATDarien. Valle, ColombiaEl Espinal. Tolima, ColombiaTerra Alta (PA)Kano[Computation]Puerto Caicedo. Putumayo, ColombiaFlorestal (MG) - UFV Campus FlorestalLUWEEROMatazulAkwa IbomLaje (BA)-RoqueEjuraVilla Garzon. Putumayo, ColombiaLuruacoHomboloQuilcace. Cauca, ColombiaTumacoCaribiaOvejasMomilLomeMukonoSabanagrandeBlamaSao Mateus (ES)KiggumbaNjuliMakokaZariaIbadanArmeroZomboAnlong Veng District, Oddar Meanchey provinceMutata. Antioquia, ColombiaAguazulValencia. Cordoba, ColombiaQuang NgaiAgustin CodazziMakeniKabalaNametilPalmiraBolivarKwaraKazilamuyagaTamalameque. Cesar, ColombiaBaranoa. Atlantico, ColombiaEsplanada (BA) - CachoeiraUkereweNhacoongoLaje (BA)-GaviaoMangabeira (BA)-IF BaianoGairoBuginyanyaMarukuMtwapa2Varzedo (BA)UmbeluziSao Francisco de Itabapoana (RJ)-Industria Dona ChicaPolonuevoBukembaRufunsaCampos Novos Paulista (SP)-Tereos SyralOgoniInharrimeBulingaUyoEmbuBarrancabermejaDarienCereteFumesuaSiayaCarimagua. Meta, ColombiaMacapa (AP)SabanalargaEl Overo. Valle, ColombiaCaldonoPallisaSabanalarga. Atlantico, ColombiaKhao Hinsorn Research Center, Kasetsart University, Chachoengsao provinceRatanak Mondul district, Battambang provinceMasakaEl Olivo. Cordoba, ColombiaApiayVitoria da Conquista (BA) - Fecularia ConquistaMvuaziKaberamaidoSulutiSan Vicente. Santander, ColombiaMontenegro. Quindio, ColombiaTouros (RN)-PrataBusiaunspecifiedMutataSanta CruzUniversity of HawaiiAkureOhawuCarepaLirakasuluApiay. Meta, ColombiaBugaPetrolina (PE)-UNIVASFPatiaMichikichiniItasyAgo-OwuPopayanDoncello. Caqueta, ColombiaDivoPajau. Brasil, BrazilQuilcaceFlorencia. Caqueta, ColombiaChiengiTangakonaOtobiMontenegroPuerto GaitanBarranquilla. Atlantico, ColombiaCorozalPinheiros (ES)MontanitaJeddoLao NgamSikhiu is a district (amphoe) in the western part of Nakhon Ratchasima provinceCienaga. Magdalena, ColombiaBela Vista de Goias (GO)TolúMarechal Candido Rondon (PR)-ATIMOPEl EspinalHoma BayArmeniaTESTKisesaAssin FosuBundaYopal. Casanare, ColombiabadagryObuduNaphokLa Dolores. Valle, ColombiaNamulonge-SendusuSenjehSampues. Sucre, ColombiaCajibioCoração de Maria (BA)GongoniLa HormigaRakaiPalmasecaChitedzeLoricaCruz das Almas (BA)-UFRB-CandealMargibiTracuateua (PA)TolúviejoPopayan. Cauca, ColombiaAcaciasTauramenaKipopoAgbarhoCIAT. Valle, ColombiaNgandajikaMkurangaOrito. Putumayo, ColombiaPuerto Asis. Putumayo, ColombiaCumaral. Meta, ColombiaRubiriziBuikweKalomoSan Martin. Meta, ColombiaMityanaOsunKiyakaPivijaySinceMontanita. Sucre, ColombiaConde (BA)-CanguritoNyankpalaVitoria da Conquista (BA)Prado (BA)MbuniHung YenLaje (BA) - Fazenda Sombra VerdeDeltaBoyce Thompson InstitutePitalitoKasinthukaPuerto AsisMorogoroMkondeziAbujaMonteria (UNICORDOBA). Cordoba, ColombiaWenchiSan VicenteCaracoli. Atlantico, ColombiaMokwaKebbiAlupeCapanema (PA)RubonaChatoCalotoUsiacuriSanta Cruz. Atlantico, ColombiaLa Hormiga. Putumayo, ColombiaMonteriaLaje (BA)-Rio de Areia 1Rio Frio. Magdalena, ColombiaTeresina (PI)OnneOrtegaIresiYopalFonsecaKabangweCaracoliEl Salado. Cordoba, ColombiaPuerto LopezLagoa D'Anta (RN)ManLagoa D'anta (RN)-LopesKWALEPuerto Gaitan. Meta, ColombiaConceicao dos Ouros (MG)Pojuca (BA)RiversMedia Luna. Magdalena, ColombiaFadaInaAremasain. Guajira, ColombiaBambiLukwakwaMalambo. Atlantico, ColombiaCornell BiotechChilimbaLoroSerereRio FrioDoncelloPalmar de VarelaMogovolasFumesua-KumasiSan Antonio de PalmitoSon LaMtwapaWarriNachingweaBulegeniVerdelandia (MG)-Brasnica Fazenda VilyamaZanzibarTapioca Development Institute (TDI), located in Huay Bong, Dan Khun Thot District, Nakhon RatchasimaPhu YenJamundi. Valle, ColombiaMalamboPureza (RN)Puerto Lopez. Meta, ColombiaFarakobaHanoiNgomaKasuluSevillaItamaraju (BA)Ban Khao Luk Chang, Ta Phraya Sistrict, Sa Kaeo provinceCienagaS. de Quilichao. Cauca, ColombiaEl MiraEdoGuanambi (BA)-IF BaianoCruz Das Almas (BA) - UFRB CAMABSerra dos Aimores (MG)-Cachoeira da MataMahondaLlanosVilla GarzonArmenia. Quindio, ColombiaMarataizes (ES)LiupoLaje (BA)-Rio de Areia 1MigoriWakisoCruz das Almas (BA)-UFRB-PP1GbarpoluEketPuerto CaicedoBarranca De Upia. Casanare, ColombiaLa Libertad. Meta, ColombiaLaberinto. Sucre, ColombiaCrossRiverMondomoLondrina (PR-Afapo)Teixeira de Freitas (BA)El Carmen. Bolivar, ColombiaMimoso do Sul (ES)CarimaguaTay NinhBayelsaValledupar. Cesar, ColombiaPonta Pora (MS)-Assentamento ItamaratiMogincualBuenaventuraBouakeItiuba (BA)San PabloKisesa-MaguEl SaladoDewoinBanteay Meanchey province Banteay MeancheyMulunguMsambweniNgabuCandelaria. Valle, ColombiaAlagoinhas (BA)-Boa UniaoNecocliCaloto. Cauca, ColombiaCabuyaro. Meta, ColombiaIkenneSan MartinSoeng Sang is a district in the southeastern part of Nakhon Ratchasima provinceInhambupe (BA)-BotelhoThateng district, Sekong provinceBuga. Valle, ColombiaCantaclaroS. de QuilichaoCorozal. Sucre, ColombiaNational Corn and Sorghum Research Center (Suwan Farm), Kasetsart University Nakhon Ratchasima provinceLuruaco. Atlantico, ColombiaLa Libertad. Meta, ColombiaIlesaPend. , ColombiaCerete. Cordoba, ColombiaVijes. Valle, ColombiaNaCRRI, Central UgandaLa UnionRokuprUnknownunknown2MbararaAugusto Correa (PA)MuhangaAzuaRwebitabadavieNiaouliJamundiChamkar Leu districtBarranquillaAtivemeNgettaGranada. Meta, ColombiaCampecheJosIBARAPAEl Carmen de BolivarChambeziMomil. Cordoba, ColombiaFrancisco PizarroSatiro Dias (BA)-Assentamento PapagaioPalmaseca. Valle, ColombiaLaje (BA)-Novo Horizonte 2ASan PedroCienaga De Oro. Cordoba, ColombiaMalam MadoriKumasiKamaConde (BA)-HumaitaRepelon. Atlantico, ColombiaNecocli. Antioquia, ColombiaCorpoica PalmiraBetuliaLaje (BA)-Rio de Areia 2MocubaNigerDanyiTororoKizimbaniFonseca. Guajira, ColombiaOshogboKaomaPitalito. Atlantico, ColombiaLaberintoAdetaSantaguedaKakamegaTchadNsukkaCabuyaroNamulongeKubwaIRRUADong NaiLa LibertadLaje (BA)-Fazenda Sao JorgekaseseBaranoaPalmar de Varela. Atlantico, ColombiaMatazul. Meta, ColombiaBwangaKisumuPescador. Cauca, ColombiaLaje (BA)-RogerioSahagun. Cordoba, ColombiaSabanalarga. Atlantico, ColombiaNgettaCarranzo. Cordoba, ColombiaMoralesSampuesChinuPouso Alegre (MG)Cajibio. Cauca, ColombiaLaje (BA)-Novo Horizonte 1YangambiNebbiPokuaseDaklakMorales. Cauca, ColombiaNyagatareMontanha (ES) - Fecularia ConquistaKibaaleBarranca De UpiaEl OveroArmero. Tolima, ColombiaCarepa. Antioquia, ColombiaSahagunLa Union. Sucre, ColombiaAlcobaca (BA)KilibaBetulia. Sucre, ColombiaAlbania. Sucre, ColombiaKaseseCIAT. Valle, ColombiaAbidjanPendembuMsabahaBarrancabermeja. Santander, ColombiaChinu. Cordoba, ColombiaUkiriguruOritolossaVijesLaje (BA)-Novo Horizonte 2BBolikham district, Bolikhamxay provinceCruz Das Almas (BA)-CNPMF-Area 2DamongoPatia. Cauca, ColombiaUmudikeRestrepo. Meta, ColombiaNeivaCostaRepelonSanto TomasChitalaEntre Rios (BA)ChochoLaje (BA) - CapelaQuissama (RJ)-PMQ HortoKadunaweBom Jesus da Lapa (BA) - IF BaianoEkitiPitalito. Atlantico, ColombiaOgutaNong Yai is a district in the province ChonburiCandelariaMolineros. Atlantico, ColombiaPescadorWenchi-BALa CumbreLaje (BA) - RailtonSanta Isabel do Para (PA)Santo Tomas. Atlantico, ColombiaMedia LunaEl OlivoTauramena. Casanare, ColombiaCumaralCaribia. Magdalena, ColombiaValleduparFloridaMondomo. Cauca, ColombiaMotiloniaAguazul. Casanare, ColombiaLaje (BA)-Novo RumoCienaga De OroStung Treng Province, Stung TrengPokuase-AccraEuclides da Cunha (BA)AKUMADANCruz Das Almas (BA) - UFRB - EstabuloAremasainLaje (BA)-Novo Horizonte 1AKibosKamuliLa DoloresAlagoinhas (BA)COLDStore, RACK1, Shelf2, Cruz Das Almas (BA) CNPMF - CitrusRuziziPlainIkot AfangaBengouPivijay. Magdalena, ColombiaKogiAruaAgenbodeValenciaNatagaimaCampos dos Goytacazes (RJ)-UENFILONGABundibugyoEgbemaKakonkoMubendeSanto Amaro (BA)BarrancasCachoeira de Minas (MG)Dourados (MS)-UFGDDOKOLOCruz Das Almas (BA) - CNPMF - Area 1 (Ladeira maracuja)Los PalmitosibadanGinebraMansaUbiaja
    Trial Type:
    Year:
    Planting Date (MM-DD-YYYY):
    Transplanting Date(MM-DD-YYYY):
    Plot Width (m):
    Plot Length (m):
    Field Size (ha):
    Plants per Plot:

    Creates plant entries for each plot. Ignore if not adding plant entries.

    Inherits Management Factor(s) From Plots:
    Description:
    Stock Type Being Evaluated in Trial:
    Select a stock type accession cross family_name
    Design Type:
    Completely Randomized Complete Block Resolvable Row-Column Doubly-Resolvable Row-Column Augmented Row-Column Alpha Lattice Lattice Augmented Modified Augmented Design Nursery/Greenhouse Split Plot Strip Plot Partially Replicated Westcott
    Upload File:


    Go To Next Step
  3. Is your trial linked with other field trials, genotyping plates, or crossing experiments in the database? If you are unsure, you can skip this. This information can be added from the trial detail page after the trial is saved.

    Is this trial following-up a previous field trial?:
    No Yes
    Select the trial(s) which preceded this trial:

    If you go on to collect tissue samples for creating a 96 well plate for genotyping, when adding the genotyping plate (96 well plate layout) to the database you can use plot names or plant names or tissue sample names from this field trial. By doing so, we can create linkage between this field trial and the genotyping plate.

    Will this trial be genotyped?:
    No Yes

    If you go on to perform crosses on this field trial, each cross can be linked to specific female and male plots. When you upload these crosses we can then automatically link this field trial to the crossing experiment in the database.

    Will crosses be done on this trial?:
    No Yes

    Check this box to ignore any possible warning messages and save the trial to the database.

    Ignore Warnings?:

    First validate the form Upload Trial
  4. Fixing the missing accession(s) problem

    • Accessions tested in your trial must exist in the database prior to adding your trial. The reason for this is that an accession can be tested in many trials and therefore exists as a separate entity in the database. We also want to be careful about adding new accessions into the database because we do not want incorrectly duplicated data.
    • When adding accessions into the database, you can use either a list of accessions or an Excel file.
    Add your accessions to the database

    Once all your accessions are in the database Click Here

    Trial Upload Error Messages

  5. Fixing the missing seedlot(s) problem

    • Seedlots tested in your experimental trial must exist in the database prior to adding your trial. The reason for this is that a seedlot can be tested in many trials and therefore exists as a separate entity in the database. We also want to be careful about adding new seedlots into the database because we do not want data to be incorrectly linked to duplicates.
    • When adding seedlots into the database, you can upload an Excel file or you can add seedlots one at a time.

      • Upload Excel file

      • Add One Seedlot

    Once all your seedlots are in the database Click Here

    Trial Upload Error Messages

  6. Submit your trial again. You should have corrected all errors by now, but if not please take a look at the errors in the red box below. You can continue to modify your file and then click Upload until it works.

    Upload Trial

    There exist these problems in your file:

Finished! Your trial is now in the database

The trial file was uploaded successfully

  • You may want to proceed to the trial detail page for the trial you just created.
  • You can print barcodes for the plots or plants or tissue samples in this trial.
  • You an add phenotypes for the plots or plants in this trial now.

Finished! Your trial is now in the database

The trial file was uploaded successfully

  • You may want to proceed to the trial detail page for the trial you just created.
  • You can print barcodes for the plots or plants or tissue samples in this trial.
  • You an add phenotypes for the plots or plants in this trial now.

Close
×

Upload Template Information

Trials may be uploaded in an Excel file (.xls or .xlsx)
Stock type being evaluated in this trial: accession Stock type being evaluated in this trial: accession  
Header:
The first row (header) must contain the following:
plot_name accession_name plot_number block_number is_a_control rep_number range_number row_number col_number seedlot_name num_seed_per_plot weight_gram_seed_per_plot entry_number
Header as a string:

plot_name,accession_name,plot_number,block_number,is_a_control,rep_number,range_number,row_number,col_number,seedlot_name,num_seed_per_plot,weight_gram_seed_per_plot,entry_number

Stock type being evaluated in this trial: cross unique id Stock type being evaluated in this trial: cross unique id  
Header:
The first row (header) must contain the following:
plot_name cross_unique_id plot_number block_number is_a_control rep_number range_number row_number col_number seedlot_name num_seed_per_plot weight_gram_seed_per_plot entry_number
Header as a string:

plot_name,cross_unique_id,plot_number,block_number,is_a_control,rep_number,range_number,row_number,col_number,seedlot_name,num_seed_per_plot,weight_gram_seed_per_plot,entry_number

Stock type being evaluated in this trial: family name Stock type being evaluated in this trial: family name  
Header:
The first row (header) must contain the following:
plot_name family_name plot_number block_number is_a_control rep_number range_number row_number col_number seedlot_name num_seed_per_plot weight_gram_seed_per_plot entry_number
Header as a string:

plot_name,family_name,plot_number,block_number,is_a_control,rep_number,range_number,row_number,col_number,seedlot_name,num_seed_per_plot,weight_gram_seed_per_plot,entry_number

Required fields:
  • accession_name or cross_unique_id or family_name (must exist in the database. This is the accession or cross unique id or family name being tested in the plot.)
  • plot_number (a sequential number for the plot in the field (e.g. 1001, 1002, 2001, 2002). These numbers should be unique for the trial.)
  • block_number (a design parameter indicating which block the plot is in)
Optional fields:
  • plot_name (must be unique across entire database. If not provided in the file, it will be automatically generated as {trial_name}-PLOT_{plot_number}.)
  • is_a_control (type 1 in this field if the plot is a control, otherwise leave blank. generally you will have accessions/cross unique ids/family names that are controls, so you should indicate the plots of those accessions/cross unique ids/family names as a control.)
  • rep_number (replicate number, numeric)
  • range_number (range number. often synonymous with col_number, numeric)
  • row_number (row number. If the field is a grid, this represents the y coordinate, numeric, required for field map generation.)
  • col_number (column number. If the field is a grid, this represents the x coordinate. Sometimes called range_number, numeric, required for field map generation.)
  • seedlot_name (the seedlot from where the planted seed originated. Must exist in the database)
  • num_seed_per_plot (number seeds per plot. Seed is transferred from seedlot mentioned in seedlot_name. Numeric)
  • weight_gram_seed_per_plot (weight in gram of seeds in plot. seed is transferred from seedlot mentioned in seedlot name. Numeric)
  • entry_number (a trial-level entry number assigned to the stock. Numeric)
Treatments:
  • treatment columns (additional column(s) that specify the name of a treatment (e.g. inoculated, drought, etc). The value for each plot should be 1 if the treatment was applied or empty.)

Only the required fields are necessary to include in the upload template. You may add any additional optional fields. The fields can be in any order.

Close
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Upload Template Information


Multiple Trial Designs:
Header:
The first row (header) must contain the following, which is an expansion of the single trial design header:
trial_name breeding_program location year transplanting_date design_type description trial_type plot_width plot_length field_size planting_date harvest_date plot_name accession_name plot_number block_number is_a_control rep_number range_number row_number col_number seedlot_name num_seed_per_plot weight_gram_seed_per_plot entry_number
Header as a string:

trial_name,breeding_program,location,year,transplanting_date,design_type,description,trial_type,plot_width,plot_length,field_size,planting_date,harvest_date,plot_name,accession_name,plot_number,block_number,is_a_control,rep_number,range_number,row_number,col_number,seedlot_name,num_seed_per_plot,weight_gram_seed_per_plot,entry_number

Required fields:
  • trial_name (Must be unique across entire database. It is often a concatenation of the year, transplanting_date, purpose, unique number, and location.)
  • breeding_program (The name of breeding program that managed the trial, must exist in the database.)
  • location (The name or abbreviation of the location where the trial was held, must exist in the database.)
  • year (The year the trial was held.)
  • design_type (The shorthand for the design type, must exist in the database. Possible values include CRD (Completely Randomized Design), RCBD (Randomized Complete Block Design), RRC (Resolvable Row-Column), DRRC (Doubly-Resolvable Row-Column), ARC (Augmented Row-Column), Alpha (Alpha Lattice Design), Lattice (Lattice Design), Augmented (Augmented Design), MAD (Modified Augmented Design), greenhouse (undesigned Nursery/Greenhouse), splitplot (Split Plot), stripplot (Strip Plot / Split Block), p-rep (Partially Replicated), Westcott (Westcott Design))
  • description (Additional text with any other relevant information about the trial.)
  • accession_name (The accession being tested in the plot, must exist in the database.)
  • plot_number (A sequential number for the plot in the field (e.g. 1001, 1002, 2001, 2002). These numbers should be unique for the trial.)
  • block_number (A design parameter indicating which block the plot is in.)
Additional optional fields:
  • plot_name (Must be unique across entire database. If not provided in the file, it will be automatically generated as {trial_name}-PLOT_{plot_number})
  • trial_type (The name of the trial type, must exist in the database. Possible values include Seedling Nursery, phenotyping_trial, Advanced Yield Trial, Preliminary Yield Trial, Uniform Yield Trial, Variety Release Trial, Clonal Evaluation, genetic_gain_trial, storage_trial, heterosis_trial, health_status_trial, grafting_trial, Screen House, Seed Multiplication, crossing_block_trial, Specialty Trial)
  • plot_width (plot width in meters)
  • plot_length (plot length in meters)
  • field_size (field size in hectares)
  • planting_date (Date of Planting in YYYY-MM-DD format)
  • transplanting_date(The transplanting_date of the trial was conducted. Date in YYYY-MM-DD format)
  • harvest_date (Date of Harvest in YYYY-MM-DD format)
  • is_a_control (type 1 in this field if the plot is a control, otherwise 0 or leave blank. generally you will have accessions that are controls, so you should indicate the plots that that accession is in as a control.)
  • rep_number (replicate number, must be numeric)
  • range_number (range number. often synonymous with col_number, must be numeric)
  • row_number (row number. if the field is a grid, this represents the y coordinate, numeric, required for field map generation.)
  • col_number (column number. if the field is a grid, this represents the x coordinate. sometimes called range_number, numeric, required for field map generation.)
  • seedlot_name (the seedlot from where the planted seed originated. must exist in the database)
  • num_seed_per_plot (number seeds per plot. seed is transferred from seedlot mentioned in seedlot_name. numeric)
  • weight_gram_seed_per_plot (weight in gram of seeds in plot. seed is transferred from seedlot mentioned in seedlot name. numeric)
  • entry_number (a trial-level entry number assigned to the stock. Numeric)
Treatments:
  • treatment columns (additional column(s) that specify the name of a treatment (e.g. inoculated, drought, etc). the value for each plot should be 1 if the treatment was applied or empty if not applied.)

Trials may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

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Upload Trial Metadata

This upload can be used to update the metadata of trials that have already been added to the database

Any metadata provided in the upload file will replace any existing metadata. Blank values in the upload file will leave the existing metadata unchanged.

File format information
Spreadsheet format

Trial Metadata File:
Reload Page

Trial Metadata may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

Close Upload
×

Upload Trial Metadata Template Information

Header:
The first row (header) should contain the following:
trial_name breeding_program location year transplanting_date planting_date harvest_date design_type description trial_type plot_width plot_length field_size
Required Fields:
  • trial_name: the name of the trial (must already exist in the database)

Optional values:
  • new_trial_name (A new name for the trial, must not already exist in the database)
  • breeding_program (The name of breeding program that managed the trial, must exist in the database.)
  • location (The name or abbreviation of the location where the trial was held, must exist in the database.)
  • year (The year the trial was held.)
  • transplanting_date (The transplanting_date of the trial was conducted. Date in YYYY-MM-DD format or 'remove' to remove the date)
  • planting_date (Date of Planting in YYYY-MM-DD format or 'remove' to remove the date)
  • harvest_date (Date of Harvest in YYYY-MM-DD format or 'remove' to remove the date)
  • design_type (The shorthand for the design type, must exist in the database. Possible values include CRD (Completely Randomized Design), RCBD (Randomized Complete Block Design), RRC (Resolvable Row-Column), DRRC (Doubly-Resolvable Row-Column), ARC (Augmented Row-Column), Alpha (Alpha Lattice Design), Lattice (Lattice Design), Augmented (Augmented Design), MAD (Modified Augmented Design), greenhouse (undesigned Nursery/Greenhouse), splitplot (Split Plot), p-rep (Partially Replicated), Westcott (Westcott Design))
  • description (Additional text with any other relevant information about the trial.)
  • trial_type (The name of the trial type, must exist in the database. Possible values include Seedling Nursery, phenotyping_trial, Advanced Yield Trial, Preliminary Yield Trial, Uniform Yield Trial, Variety Release Trial, Clonal Evaluation, genetic_gain_trial, storage_trial, heterosis_trial, health_status_trial, grafting_trial, Screen House, Seed Multiplication, crossing_block_trial, Specialty Trial)
  • plot_width (plot width in meters)
  • plot_length (plot length in meters)
  • field_size (field size in hectares)

Trial Metadata may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

Close
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Design New Trial

  1. Intro
  2. Trial Information
  3. Design Information
  4. Trial Linkage
  5. Field Map Information
  6. Custom Plot Naming
  7. Review Designed Trial
  1. This workflow will guide you through designing a new trial in the database

    A field trial represents a field where each plot has a globally unique plot name, a sequential plot number that is unique in the trial (e.g. 101, 102, 103 for three separate plots), and an accession representing the genotype being tested in that plot. In cases where crosses/families are being evaluated (e.g. F1 hybrid, backcrossing), cross unique ids or family names can be used instead of accessions. Each plot can belong to different blocks and reps depending on the experimental design you are using (e.g. complete block vs augmented design). Each plot can have a row number and col number indicating the relative position of the plot in the field.

    To design a trial you need to provide a globally unique trial name. The plot names will be generated based on the trial name you provide (e.g. if the trial name is 2018MyTrial, plot_names will be generated like 2018MyTrial_101, 2018MyTrial_102, etc).

    You also need to provide a list of accessions, cross unique ids or family names to use. Based on the design you have picked, the accessions, cross unique ids or family names will be randomized over the blocks or replicates in the trial.

    You can provide a list of accessions to use as controls or checks in your experiment.

    Depending on the design you have picked, you will need to provide different design parameters (e.g. for complete block you will need to provide number of blocks, while for alpha lattice you will need to provide block size and number of replicates.).

    A trial can represent a yield trial, a phenotyping trial, a crossing block, a greenhouse, a nursery, etc.

    A plot can have many plants, which the database can track as separate entities, allowing you to record plant level observations and information.



    Go to Next Step
  2. Enter basic information about the trial

    Breeding Program:
    5CPBTICARICHCIATCIP-genebankCNRACornellCSIR-CRIEmbrapaIDIAFIITAINERA_IITA_DRCISABUITCKALROKUNaCRRINRCRIRayongSLARITARIUACUHUNILA-IndonesiaZARI
    Locations: (One or More)
    RestrepoIgbariamRayongGranadaSanto Tomas. Atlantico, ColombiaFlorenciabwangaNaliendeleKokrokoChokweCalabarJaguaripe (BA) - Fazenda EsperançaCorozal. Sucre, ColombiaAgborSuakokoKibahaIshiaguBarahonaNjalaSotoubouaBuenos AiresAlbaniaItanhem (BA)IlorinAcacias. Meta, ColombiaVerdelandia (MG)-Brasnica Fazenda OrienteCIATDarien. Valle, ColombiaEl Espinal. Tolima, ColombiaTerra Alta (PA)Kano[Computation]Puerto Caicedo. Putumayo, ColombiaFlorestal (MG) - UFV Campus FlorestalLUWEEROMatazulAkwa IbomLaje (BA)-RoqueEjuraVilla Garzon. Putumayo, ColombiaLuruacoHomboloQuilcace. Cauca, ColombiaTumacoCaribiaOvejasMomilLomeMukonoSabanagrandeBlamaSao Mateus (ES)KiggumbaNjuliMakokaZariaIbadanArmeroZomboAnlong Veng District, Oddar Meanchey provinceMutata. Antioquia, ColombiaAguazulValencia. Cordoba, ColombiaQuang NgaiAgustin CodazziMakeniKabalaNametilPalmiraBolivarKwaraKazilamuyagaTamalameque. Cesar, ColombiaBaranoa. Atlantico, ColombiaEsplanada (BA) - CachoeiraUkereweNhacoongoLaje (BA)-GaviaoMangabeira (BA)-IF BaianoGairoBuginyanyaMarukuMtwapa2Varzedo (BA)UmbeluziSao Francisco de Itabapoana (RJ)-Industria Dona ChicaPolonuevoBukembaRufunsaCampos Novos Paulista (SP)-Tereos SyralOgoniInharrimeBulingaUyoEmbuBarrancabermejaDarienCereteFumesuaSiayaCarimagua. Meta, ColombiaMacapa (AP)SabanalargaEl Overo. Valle, ColombiaCaldonoPallisaSabanalarga. Atlantico, ColombiaKhao Hinsorn Research Center, Kasetsart University, Chachoengsao provinceRatanak Mondul district, Battambang provinceMasakaEl Olivo. Cordoba, ColombiaApiayVitoria da Conquista (BA) - Fecularia ConquistaMvuaziKaberamaidoSulutiSan Vicente. Santander, ColombiaMontenegro. Quindio, ColombiaTouros (RN)-PrataBusiaunspecifiedMutataSanta CruzUniversity of HawaiiAkureOhawuCarepaLirakasuluApiay. Meta, ColombiaBugaPetrolina (PE)-UNIVASFPatiaMichikichiniItasyAgo-OwuPopayanDoncello. Caqueta, ColombiaDivoPajau. Brasil, BrazilQuilcaceFlorencia. Caqueta, ColombiaChiengiTangakonaOtobiMontenegroPuerto GaitanBarranquilla. Atlantico, ColombiaCorozalPinheiros (ES)MontanitaJeddoLao NgamSikhiu is a district (amphoe) in the western part of Nakhon Ratchasima provinceCienaga. Magdalena, ColombiaBela Vista de Goias (GO)TolúMarechal Candido Rondon (PR)-ATIMOPEl EspinalHoma BayArmeniaTESTKisesaAssin FosuBundaYopal. Casanare, ColombiabadagryObuduNaphokLa Dolores. Valle, ColombiaNamulonge-SendusuSenjehSampues. Sucre, ColombiaCajibioCoração de Maria (BA)GongoniLa HormigaRakaiPalmasecaChitedzeLoricaCruz das Almas (BA)-UFRB-CandealMargibiTracuateua (PA)TolúviejoPopayan. Cauca, ColombiaAcaciasTauramenaKipopoAgbarhoCIAT. Valle, ColombiaNgandajikaMkurangaOrito. Putumayo, ColombiaPuerto Asis. Putumayo, ColombiaCumaral. Meta, ColombiaRubiriziBuikweKalomoSan Martin. Meta, ColombiaMityanaOsunKiyakaPivijaySinceMontanita. Sucre, ColombiaConde (BA)-CanguritoNyankpalaVitoria da Conquista (BA)Prado (BA)MbuniHung YenLaje (BA) - Fazenda Sombra VerdeDeltaBoyce Thompson InstitutePitalitoKasinthukaPuerto AsisMorogoroMkondeziAbujaMonteria (UNICORDOBA). Cordoba, ColombiaWenchiSan VicenteCaracoli. Atlantico, ColombiaMokwaKebbiAlupeCapanema (PA)RubonaChatoCalotoUsiacuriSanta Cruz. Atlantico, ColombiaLa Hormiga. Putumayo, ColombiaMonteriaLaje (BA)-Rio de Areia 1Rio Frio. Magdalena, ColombiaTeresina (PI)OnneOrtegaIresiYopalFonsecaKabangweCaracoliEl Salado. Cordoba, ColombiaPuerto LopezLagoa D'Anta (RN)ManLagoa D'anta (RN)-LopesKWALEPuerto Gaitan. Meta, ColombiaConceicao dos Ouros (MG)Pojuca (BA)RiversMedia Luna. Magdalena, ColombiaFadaInaAremasain. Guajira, ColombiaBambiLukwakwaMalambo. Atlantico, ColombiaCornell BiotechChilimbaLoroSerereRio FrioDoncelloPalmar de VarelaMogovolasFumesua-KumasiSan Antonio de PalmitoSon LaMtwapaWarriNachingweaBulegeniVerdelandia (MG)-Brasnica Fazenda VilyamaZanzibarTapioca Development Institute (TDI), located in Huay Bong, Dan Khun Thot District, Nakhon RatchasimaPhu YenJamundi. Valle, ColombiaMalamboPureza (RN)Puerto Lopez. Meta, ColombiaFarakobaHanoiNgomaKasuluSevillaItamaraju (BA)Ban Khao Luk Chang, Ta Phraya Sistrict, Sa Kaeo provinceCienagaS. de Quilichao. Cauca, ColombiaEl MiraEdoGuanambi (BA)-IF BaianoCruz Das Almas (BA) - UFRB CAMABSerra dos Aimores (MG)-Cachoeira da MataMahondaLlanosVilla GarzonArmenia. Quindio, ColombiaMarataizes (ES)LiupoLaje (BA)-Rio de Areia 1MigoriWakisoCruz das Almas (BA)-UFRB-PP1GbarpoluEketPuerto CaicedoBarranca De Upia. Casanare, ColombiaLa Libertad. Meta, ColombiaLaberinto. Sucre, ColombiaCrossRiverMondomoLondrina (PR-Afapo)Teixeira de Freitas (BA)El Carmen. Bolivar, ColombiaMimoso do Sul (ES)CarimaguaTay NinhBayelsaValledupar. Cesar, ColombiaPonta Pora (MS)-Assentamento ItamaratiMogincualBuenaventuraBouakeItiuba (BA)San PabloKisesa-MaguEl SaladoDewoinBanteay Meanchey province Banteay MeancheyMulunguMsambweniNgabuCandelaria. Valle, ColombiaAlagoinhas (BA)-Boa UniaoNecocliCaloto. Cauca, ColombiaCabuyaro. Meta, ColombiaIkenneSan MartinSoeng Sang is a district in the southeastern part of Nakhon Ratchasima provinceInhambupe (BA)-BotelhoThateng district, Sekong provinceBuga. Valle, ColombiaCantaclaroS. de QuilichaoCorozal. Sucre, ColombiaNational Corn and Sorghum Research Center (Suwan Farm), Kasetsart University Nakhon Ratchasima provinceLuruaco. Atlantico, ColombiaLa Libertad. Meta, ColombiaIlesaPend. , ColombiaCerete. Cordoba, ColombiaVijes. Valle, ColombiaNaCRRI, Central UgandaLa UnionRokuprUnknownunknown2MbararaAugusto Correa (PA)MuhangaAzuaRwebitabadavieNiaouliJamundiChamkar Leu districtBarranquillaAtivemeNgettaGranada. Meta, ColombiaCampecheJosIBARAPAEl Carmen de BolivarChambeziMomil. Cordoba, ColombiaFrancisco PizarroSatiro Dias (BA)-Assentamento PapagaioPalmaseca. Valle, ColombiaLaje (BA)-Novo Horizonte 2ASan PedroCienaga De Oro. Cordoba, ColombiaMalam MadoriKumasiKamaConde (BA)-HumaitaRepelon. Atlantico, ColombiaNecocli. Antioquia, ColombiaCorpoica PalmiraBetuliaLaje (BA)-Rio de Areia 2MocubaNigerDanyiTororoKizimbaniFonseca. Guajira, ColombiaOshogboKaomaPitalito. Atlantico, ColombiaLaberintoAdetaSantaguedaKakamegaTchadNsukkaCabuyaroNamulongeKubwaIRRUADong NaiLa LibertadLaje (BA)-Fazenda Sao JorgekaseseBaranoaPalmar de Varela. Atlantico, ColombiaMatazul. Meta, ColombiaBwangaKisumuPescador. Cauca, ColombiaLaje (BA)-RogerioSahagun. Cordoba, ColombiaSabanalarga. Atlantico, ColombiaNgettaCarranzo. Cordoba, ColombiaMoralesSampuesChinuPouso Alegre (MG)Cajibio. Cauca, ColombiaLaje (BA)-Novo Horizonte 1YangambiNebbiPokuaseDaklakMorales. Cauca, ColombiaNyagatareMontanha (ES) - Fecularia ConquistaKibaaleBarranca De UpiaEl OveroArmero. Tolima, ColombiaCarepa. Antioquia, ColombiaSahagunLa Union. Sucre, ColombiaAlcobaca (BA)KilibaBetulia. Sucre, ColombiaAlbania. Sucre, ColombiaKaseseCIAT. Valle, ColombiaAbidjanPendembuMsabahaBarrancabermeja. Santander, ColombiaChinu. Cordoba, ColombiaUkiriguruOritolossaVijesLaje (BA)-Novo Horizonte 2BBolikham district, Bolikhamxay provinceCruz Das Almas (BA)-CNPMF-Area 2DamongoPatia. Cauca, ColombiaUmudikeRestrepo. Meta, ColombiaNeivaCostaRepelonSanto TomasChitalaEntre Rios (BA)ChochoLaje (BA) - CapelaQuissama (RJ)-PMQ HortoKadunaweBom Jesus da Lapa (BA) - IF BaianoEkitiPitalito. Atlantico, ColombiaOgutaNong Yai is a district in the province ChonburiCandelariaMolineros. Atlantico, ColombiaPescadorWenchi-BALa CumbreLaje (BA) - RailtonSanta Isabel do Para (PA)Santo Tomas. Atlantico, ColombiaMedia LunaEl OlivoTauramena. Casanare, ColombiaCumaralCaribia. Magdalena, ColombiaValleduparFloridaMondomo. Cauca, ColombiaMotiloniaAguazul. Casanare, ColombiaLaje (BA)-Novo RumoCienaga De OroStung Treng Province, Stung TrengPokuase-AccraEuclides da Cunha (BA)AKUMADANCruz Das Almas (BA) - UFRB - EstabuloAremasainLaje (BA)-Novo Horizonte 1AKibosKamuliLa DoloresAlagoinhas (BA)COLDStore, RACK1, Shelf2, Cruz Das Almas (BA) CNPMF - CitrusRuziziPlainIkot AfangaBengouPivijay. Magdalena, ColombiaKogiAruaAgenbodeValenciaNatagaimaCampos dos Goytacazes (RJ)-UENFILONGABundibugyoEgbemaKakonkoMubendeSanto Amaro (BA)BarrancasCachoeira de Minas (MG)Dourados (MS)-UFGDDOKOLOCruz Das Almas (BA) - CNPMF - Area 1 (Ladeira maracuja)Los PalmitosibadanGinebraMansaUbiaja
    No Locations Selected
    Trial Name:

    Location abbreviation will automatically be added as a prefix if multiple locations are selected.

    Trial Type:
    Year:
    Planting Date:
    Plot Width (m):
    Plot Length (m):
    Field Size (ha):
    Plants per Plot:

    Creates plant entries for each plot. Ignore if not adding plant entries.

    Inherits Management Factor(s) From Plots:
    Description:
    Stock Type Being Evaluated in Trial:
    Select a stock type accession cross family_name
    Design Type:
    Completely Randomized Complete Block Resolvable Row-Column Doubly-Resolvable Row-Column Augmented Row-Column Alpha Lattice Lattice Augmented Modified Augmented Design Nursery/Greenhouse Split Plot Strip Plot Partially Replicated Westcott
    Usage Help
    Use same randomization for all locations:
    First validate the form Continue to Next Step
  3. Design your trial layout

    Which accessions will be in the field?

    List of accessions to include (required):

    Which crosses will be in the field?

    List of crosses to include (required):

    Which family names will be in the field?

    List of family names to include (required):
    Name of Check 1:
    Name of Check 2:
    List of checks to include (required):
    List of checks to include (required):
    List of checks to include (required):
    List of checks to include. Checks list should be separate from accessions list. (optional):
    List of checks to include. Checks list should be accessions list. (optional):
    List of checks to include. Checks list should be accessions list. (optional):
    List of unreplicated accession (required):
    List of unreplicated cross (required):
    List of unreplicated family_name (required):
    List of replicated accession (required):
    List of replicated cross (required):
    List of replicated family_name (required):
    Need to create a list?    Manage Lists
    Number of rows in design:
    Number of columns in design :
    Number of times replicated accessions are replicated:
    Block sequence:
    Sub-block sequence:
    Default Number of Plants:

    Number of Plants:

    Number of Columns (required):

    Number of columns between two check columns (Optional):

    Number of replicates (required):
    Number of blocks (required):
    Number of field rows (Required):
    Number of Columns (Required):
    Number of Columns per Block (2 or 4):
    Number of Rows Per Block (Optional):
    Subplot 1 Treatment Name:
    Subplot 2 Treatment Name:
    Subplot 3 Treatment Name:
    Subplot 4 Treatment Name:
    Add Another Treatment:
    + Treatment
    Number of Plants Per Treatment (required):
    Show optional parameters:
    Column number per block:
    Number of field columns:
    Block size (required):
    Maximum block size (required):

    Which seedlots will you grow in the field?
    This is optional and can be decided later. If you do not know exactly which seedlot packets you will be planting at this time, you can add this information on the Trial Detail Page after the trial has been saved in the database.

    List of seedlots for selected accessions (optional):
    Number of seeds per plot (required if seedlot list given):
    Need a list of seedlots for the selected accessions?    Search Seedlots for Accessions

    Continue to Next Step
  4. Is your trial linked with other field trials, genotyping plates, or crossing experiments in the database? If you are unsure, you can skip this. This information can be added from the trial detail page after the trial is saved.


    Is this trial following-up a previous field trial?:
    No Yes
    Select the trial(s) which preceded this trial:

    If you go on to collect tissue samples for creating a 96 well plate for genotyping, when adding the genotyping plate (96 well plate layout) to the database you can use plot names or plant names or tissue sample names from this field trial. By doing so, we can create linkage between this field trial and the genotyping plate.

    Will this trial be genotyped?:
    No Yes

    If you go on to perform crosses on this field trial, each cross can be linked to specific female and male plots. When you upload these crosses we can then automatically link this field trial to the crossing experiment in the database.

    Will crosses be done on this trial?:
    No Yes

    Continue to Next Step
  5. Specify the number of rows and columns for the entire field

    By default field map display is set to serpentine and uses the block or rep number as row number.

    If you do not want to create field map along with this trial, set 'Plot layout format' to 'select plot layout format'.

    If you do not know exactly in which rows and columns you will end up planting the plots, do not provide this and go to the next step.

    If you will plant your plots in an irregular (non-rectangular) layout, do not provide this and go to the next step.

    You can upload the exact row and column information for your plots (in any layout shape) on the Trial Detail Page after you have created the trial in the database and actually planted the experiment.

    Field map display:
    (comes with design)
    Field map display:
    Number of rows (required):
    Plot layout format:
    select plot layout format Zigzag(unserpentine) Serpentine

    Continue to Next Step
  6. If you want to change the way in which plot names will be generated by the database

    It is recommended to allow the database to create the plot prefixes, so leave the prefix blank unless necessary.

    Custom plot naming/numbering:
     
    block based plot numbers (increment leading digit for every block)
      consecutive plot numbers throughout the blocks
    Plot prefix:
    Plot start number:
    1 101 1001
    Plot number increment:

    Continue to Next Step
  7. Review the generated trial layout. Make sure to click Submit at the bottom of this page if you approve of the trial!

    Check to confirm that your design looks good. If there are any problems you can redo the randomization step.


      

    • Even Block Numbers (e.g. 2,4,...)
    • Odd Block Numbers (e.g. 1,3,...)
    • Checks
    • Odd Rep Numbers (e.g. 1,3,...)
    • Even Rep Numbers (e.g. 2,4,...)
    No field map to display...

    Redo Randomization

    Trial Is Valid
    The following trial will be added


    Add Field Management Factor(s) to Design Confirm (Saves Trial In Database)

Complete! Your trial was saved in the database.

The trial was saved successfully

  • You may want to proceed to the trial detail page for the trial you just created.
  • You can print barcodes for the plots or plants or tissue samples in this trial.
  • You an add phenotypes for the plots or plants in this trial now.

The trial was saved to the database with no errors! Congrats Click Here

Complete! Your trial was saved in the database.

The trial was saved successfully

  • You may want to proceed to the trial detail page for the trial you just created.
  • You can print barcodes for the plots or plants or tissue samples in this trial.
  • You an add phenotypes for the plots or plants in this trial now.

The trial was saved to the database with no errors! Congrats Click Here

Close
×

Add Field Management Factor to Design

Add Field Management Factor Name:
Add Field Management Factor Description:
Field Management Factor Type:
Fertilizer Fungicide Irrigation Drought Herbicide Weeding Pruning Hormone treatment Light treatment
Field Management Factor Year:
Field Management Factor Date:
Applied To:
Plots Plants
Continue Close
×

Add Field Management Factor to Design

Apply Field Management Factors to Plants and Subplots and Tissue Samples (if available):       Continue Close
×

Partially Replicated Design Usage Help

Background:

Partially replicated designs have some treatments that are unreplicated and rely on replicated treatments to make the trial analysable. The design were described in Cullis et al. (2006). It is recommended that at least 20% of the experimental units are occupied by replicated treatments. The aim of these experiments is usually to select promising treatments from a set of replicated and unreplicated test treatments, with check and quality standard treatments providing the necessary replication overall to give a valid experiment. DiGGer (Coombes, 2002) was used to implement this design. DiGGer is a flexible tool for creating experimental designs that are efficient for specified blocking and correlation patterns. DiGGer package (http://www.austatgen.org/files/software/downloads) is an add-on for the statistical computing language and environment R (R Development Core Team, 2009).

Design Parameters:

The parameters will consider a sample partially replicated design trial with 200 unreplicated accessions, 119 accessions replicated 4 times, 26 rows in design, 26 columns in design, bock sequence of 13 by 2 (13, 2) i.e 2 blocks with each having 13 rows; sub-block sequence of block of 13 by 1 (13, 1) i.e 1 sub-block with each having 13 rows in each block.

List of Unreplicated Accession
  • You're expected to provide the list of unreplicated accessions in this selectbox. E.g. is a list of 200 accessions.
List of Replicated Accession
  • List of replicated accessions should be provided in this selectbox. E.g. is a list of 119 accessions.
Number of rows in design
  • Provide the number of rows you want to have in the design. E.g. 26 number of rows.
Number of Columns in Design
  • Provide the number of columns you want to have in the design. E.g. 26 number of columns.
Number of Times Replicated Accessions are Replicated
  • Provide the number of times you want the replicated accessions to be replicated. E.g. 4
Block Sequence
  • The block sequence should reflect the blocking structure of your design. E.g. (13, 2), meaning the design has 2 blocks and each block has 13 rows.
Sub-block Sequence
  • The sub-block sequence should reflect the sub-blocking structure of your design. E.g. (13, 1), meaning the design has 1 sub-block (column) and each sub-block has 13 rows.

NOTE:

  • The product of the number of rows and columns in the design should equal the total number of plots.
  • The sum of the unreplicated accessions and the replicated accessions (given the number of times it was replicated) should equal the total number of plots.

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Upload Genotypes

  1. Intro
  2. Data Type
  3. Genotyping Project
  4. Genotyping Protocol
  5. Genotype Info
  6. Confirm
  7. Complete
  1. This workflow will guide you through uploading genotypes into the database

    Select a genotyping project on the next screen. This project can represent a series of genotyping plates sent to a genotyping facilty.

    Ideally the sample names in your VCF file will match sample names in genotyping plates in the database; however, the sample names in your file can also match accession names in the database.

    Curently we support the VCF format, the Tassel HDF5 format, the Intertek CSV format, KASP data and SSR data for upload.

    If you are uploading many files that used the same genotyping protocol, you can do so, and the database will ensure that the marker information is consistent across the genotyping data (e.g. the same reference, alternate, position, etc.).



    Go to Next Step
  2. Select the type of genotyping data being uploaded

    Type of genotyping data:
    Select data type VCF Tassel HDF5 Intertek KASP (csv) SSR


    Go to Next Step
  3. Select the genotyping project or create a new one. A genotyping project is a specific genotyping event. You can have many genotyping projects under the same genotyping protocol to indicate that those genotyping events used the same markers.

    Select Genotyping Project Name Description Breeding program Year Location Genotyping Facility
    My project is not here. Create a new one.
    Genotyping Project Name:
    Should match Vendor Project if you have one
    Genotyping Facility:
    None Cornell IGD DArT Intertek IBRC Japan BGI
    Breeding Program:
    Year:
    Description:

    Go to Next Step
  4. Provide info about the genotyping protocol used. The genotyping protocol represents a specific instance of how genotypes were called for a set of markers in a genotyping platform. Many genotyping projects can use the same genotyping protocol.

    Select Protocol Name Header Description Number of Markers Protocol Description Reference Genome Species Sample Unit Create Date
    My protocol is not here. Create a new one.
    Genotyping Protocol Name:
    Genotyping Protocol Reference Genome:
    Species:
    Assay Type
    Select assay type GBS KASP SSR
    Description:
    Choose Sample Unit:
       Exported Tissue Sample Name: The sample names in your VCF are tissue_sample_names that already exist in genotyping plates (e.g. 96 well plates) or sampling trials in the database. The sample names in your VCF file can be the tissue_sample_name triple pipe joined to the accession_name (e.g. tissue_sample_name|||accession_name) or just simply the tissue_sample_name corresponding to the genotyping plate well or sampling trial sample. This is the recommended format.

       Accession: The sample names are of accession names

       Mixed Stocks: The sample names are a mix of accession names or plot names or sample names or other stock names. This is not recommended because it will lead to messy sample metadata.
    Location of Data Generation:
    Exported Tissue Sample Names Include Numbers Generated by Genotyping Facility (e.g. sample_name:IGD1001:09):
    The generated number is separated from the tissue sample name in the database by a ':' separating character.

    Go to Next Step
  5. Provide genotype information



    Type of Genotype Data:
    Ignore any possible warnings and upload genotypes?:
    No Yes

    File format information
    VCF format


    Select VCF File:

    File format information
    VCF format


    Select Tassel HDF5 (.h5) File:

    File format information
    Intertek format


    Select Intertek SNP Result Grid File:
    Select Intertek SNP Information File:

    File format information
    KASP data format


    Select KASP Marker Information File (csv):
    Select KASP Result File (csv):

    File format information
    SSR format


    Select SSR File:


    Check File Type Go to Next Step
  6. Finalize and submit your genotyping data

    Add these missing stocks as new accessions?:
    No (currently disabled for safety)
    Submit
  7. Complete! Your genotyping data was saved in the database.

    The genotyping data was saved successfully


Complete!
Complete!
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Upload VCF Template Information

This is for uploading VCF genotype data.
VCF is a tab separated format. If your VCF is very large (greater than 10GB), please consider converting it to an HDF5 (.h5) file using Tassel, and uploading the HDF5 formatted file instead.
Header:
The first row (header) must contain the following fields, followed by all genotyped sample names:
#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT Sample names...
Required fields:
  • #CHROM (chromosome: An identifier from the reference genome pointing to a contig in the assembly file (cf. the ##assembly line in the header). All entries for a specific CHROM should form a contiguous block within the VCF file. The colon symbol (:) must be absent from all chromosome names to avoid parsing errors when dealing with breakends. (String, no white-space permitted, Required))
  • POS (position: The reference position, with the 1st base having position 1. Positions are sorted numerically, in increasing order, within each reference sequence CHROM. It is permitted to have multiple records with the same POS. Telomeres are indicated by using positions 0 or N+1, where N is the length of the corresponding chromosome or contig. (Integer, Required) )
  • ID ( identifier: Semi-colon separated list of unique identifiers where available. If this is a dbSNP variant it is encouraged to use the rs number(s). No identifier should be present in more than one data record. If there is no identifier available, then the missing value should be used. (String, no white-space or semi-colons permitted) )
  • REF (reference base(s): Each base must be one of A,C,G,T,N (case insensitive). Multiple bases are permitted. The value in the POS field refers to the position of the first base in the String. For simple insertions and deletions in which either the REF or one of the ALT alleles would otherwise be null/empty, the REF and ALT Strings must include the base before the event (which must be reflected in the POS field), unless the event occurs at position 1 on the contig in which case it must include the base after the event; this padding base is not required (although it is permitted) for e.g. complex substitutions or other events where all alleles have at least one base represented in their Strings. If any of the ALT alleles is a symbolic allele then the padding base is required and POS denotes the coordinate of the base preceding the polymorphism. Tools processing VCF files are not required to preserve case in the allele Strings. (String, Required) )
  • ALT (alternate base(s): Comma separated list of alternate non-reference alleles. These alleles do not have to be called in any of the samples. Options are base Strings made up of the bases A,C,G,T,N,*, (case insensitive) or a breakend replacement string as described in the section on breakends. The '*' allele is reserved to indicate that the allele is missing due to a upstream deletion. If there are no alternative alleles, then the missing value should be used. Tools processing VCF files are not required to preserve case in the allele String, except for IDs, which are case sensitive. (String; no whitespace, commas, or angle-brackets are permitted in the ID String itself) )
  • QUAL (quality: Phred-scaled quality score for the assertion made in ALT. i.e. -10log10 prob(call in ALT is wrong). If ALT is '.' (no variant) then this is -10log10 prob(variant), and if ALT is not '.' this is -10log10 prob(no variant). If unknown, the missing value should be specified. (Numeric) )
  • FILTER (filter status: PASS if this position has passed all filters, i.e. a call is made at this position. Otherwise, if the site has not passed all filters, a semicolon-separated list of codes for filters that fail. e.g. "q10;s50" might indicate that at this site the quality is below 10 and the number of samples with data is below 50% of the total number of samples. "0" is reserved and should not be used as a filter String. If filters have not been applied, then this field should be set to the missing value. (String, no white-space or semi-colons permitted) )
  • INFO (additional information: (String, no white-space, semi-colons, or equals-signs permitted; commas are permitted only as delimiters for lists of values) INFO fields are encoded as a semicolon-separated series of short keys with optional values in the format: key=data[,data]. Arbitrary keys are permitted, although the following sub-fields are reserved (albeit optional):
    • AA : ancestral allele
    • AC : allele count in genotypes, for each ALT allele, in the same order as listed
    • AF : allele frequency for each ALT allele in the same order as listed: use this when estimated from primary data, not called genotypes
    • AN : total number of alleles in called genotypes
    • BQ : RMS base quality at this position
    • CIGAR : cigar string describing how to align an alternate allele to the reference allele
    • DB : dbSNP membership
    • DP : combined depth across samples, e.g. DP=154
    • END : end position of the variant described in this record (for use with symbolic alleles)
    • H2 : membership in hapmap2
    • H3 : membership in hapmap3
    • MQ : RMS mapping quality, e.g. MQ=52
    • MQ0 : Number of MAPQ == 0 reads covering this record
    • NS : Number of samples with data
    • SB : strand bias at this position
    • SOMATIC : indicates that the record is a somatic mutation, for cancer genomics
    • VALIDATED : validated by follow-up experiment
    • 1000G : membership in 1000 Genomes

    The exact format of each INFO sub-field should be specified in the meta-information (as described above). Example for an INFO field: DP=154;MQ=52;H2. Keys without corresponding values are allowed in order to indicate group membership (e.g. H2 indicates the SNP is found in HapMap 2). It is not necessary to list all the properties that a site does. )
  • FORMAT (A format field is given specifying the data types and order (colon-separated alphanumeric String). This is followed by one field per sample, with the colon-separated data in this field corresponding to the types specified in the format. The first sub-field must always be the genotype (GT) if it is present. There are no required sub-fields. As with the INFO field, there are several common, reserved keywords that are standards across the community:
    • GT : genotype, encoded as allele values separated by either of / or |. The allele values are 0 for the reference allele (what is in the REF field), 1 for the first allele listed in ALT, 2 for the second allele list in ALT and so on. For diploid calls examples could be 0/1, 1 | 0, or 1/2, etc. For haploid calls, e.g. on Y, male nonpseudoautosomal X, or mitochondrion, only one allele value should be given; a triploid call might look like 0/0/1. If a call cannot be made for a sample at a given locus, '.' should be specified for each missing allele in the GT field (for example './.' for a diploid genotype and '.' for haploid genotype). The meanings of the separators are as follows (see the PS field below for more details on incorporating phasing information into the genotypes):
      • / : genotype unphased
      • | : genotype phased
    • DP : read depth at this position for this sample (Integer)
    • FT : sample genotype filter indicating if this genotype was "called" (similar in concept to the FILTER field). Again, use PASS to indicate that all filters have been passed, a semi-colon separated list of codes for filters that fail, or '.' to indicate that filters have not been applied. These values should be described in the metainformation in the same way as FILTERs (String, no white-space or semi-colons permitted)
    • GL : genotype likelihoods comprised of comma separated floating point log10-scaled likelihoods for all possible genotypes given the set of alleles defined in the REF and ALT fields. In presence of the GT field the same ploidy is expected and the canonical order is used; without GT field, diploidy is assumed. If A is the allele in REF and B,C,... are the alleles as ordered in ALT, the ordering of genotypes for the likelihoods is given by: F(j/k) = (k*(k+1)/2)+j. In other words, for biallelic sites the ordering is: AA,AB,BB; for triallelic sites the ordering is: AA,AB,BB,AC,BC,CC, etc. For example: GT:GL 0/1:-323.03,-99.29,-802.53 (Floats)
    • GLE : genotype likelihoods of heterogeneous ploidy, used in presence of uncertain copy number. For example: GLE=0:-75.22,1:-223.42,0/0:-323.03,1/0:-99.29,1/1:-802.53 (String)
    • PL : the phred-scaled genotype likelihoods rounded to the closest integer (and otherwise defined precisely as the GL field) (Integers)
    • GP : the phred-scaled genotype posterior probabilities (and otherwise defined precisely as the GL field); intended to store imputed genotype probabilities (Floats)
    • GQ : conditional genotype quality, encoded as a phred quality -10log10 p(genotype call is wrong, conditioned on the site's being variant) (Integer)
    • HQ : haplotype qualities, two comma separated phred qualities (Integers)
    • PS : phase set. A phase set is defined as a set of phased genotypes to which this genotype belongs. Phased genotypes for an individual that are on the same chromosome and have the same PS value are in the same phased set. A phase set specifies multi-marker haplotypes for the phased genotypes in the set. All phased genotypes that do not contain a PS subfield are assumed to belong to the same phased set. If the genotype in the GT field is unphased, the corresponding PS field is ignored. The recommended convention is to use the position of the first variant in the set as the PS identifier (although this is not required). (Non-negative 32-bit Integer)
    • PQ : phasing quality, the phred-scaled probability that alleles are ordered incorrectly in a heterozygote (against all other members in the phase set). We note that we have not yet included the specific measure for precisely defining "phasing quality"; our intention for now is simply to reserve the PQ tag for future use as a measure of phasing quality. (Integer)
    • EC : comma separated list of expected alternate allele counts for each alternate allele in the same order as listed in the ALT field (typically used in association analyses) (Integers)
    • MQ : RMS mapping quality, similar to the version in the INFO field. (Integer)

    If any of the fields is missing, it is replaced with the missing value. For example if the FORMAT is GT:GQ:DP:HQ then 0 | 0 : . : 23 : 23, 34 indicates that GQ is missing. Trailing fields can be dropped (with the exception of the GT field, which should always be present if specified in the FORMAT field). )
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Upload Intertek Template Information

This is for uploading Intertek genotype data.
Please use csv formatted files

For Intertek SNP Result Grid File:

The header must be:


SampleName.LabID All Marker Names In Separate Columns (e.g. marker name = S12_7926132)

The SampleName.LabID column should contain the sample name (exported_tissue_sample_name or accession_name) and it must exist in the database already

For Intertek SNP Information File:

The header must be:


IntertekSNPID CustomerSNPID Reference Alternate Chromosome Position Optional: additional marker info can be included. Please see below.
Optional columns: You can include additional marker infomation by selecting one or more column headers listed below. Please add the selected column(s) after "Position" column.
  • Quality
  • Filter
  • Info
  • Format
  • Sequence
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Upload Tassel HDF5 Template Information

This is for uploading Tassel HDF5 genotype data.
Please use HDF5 (.h5) formatted files that work with Tassel
Uploading an HDF5 file is important when the size of the VCF grows greater than 10GB
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Upload SSR Marker Info Template Information

SSR marker info may be uploaded in an Excel file (.xls or .xlsx)
Header:
The first row (header) must contain the following fields:
marker_name forward_primer reverse_primer annealing_temperature product_sizes sequence_motif sequence_source linkage_group
Required columns:
  • marker_name
  • forward_primer
  • reverse_primer
  • annealing_temperature
  • product_sizes
Optional columns (required in the header, but value may be left blank)
  • sequence_motif
  • sequence_source
  • linkage_group
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Upload SSR Marker Info Error

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Success

SSR marker info was saved successfully. You can now proceed with SSR genotyping data upload.

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Upload SSR Protocol (Marker Info)

SSR Protocol Name:
Species:
Description:

File format information
Spreadsheet format


Select an XLSX (or XLS) File:
Upload File Close
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Upload SSR Data Template Information

SSR data may be uploaded in an Excel file (.xls or .xlsx)
Example of SSR Data Spreadsheet:
sample_name s01 s01 s01 s02 s02 s02
139 170 194 203 229 290
sample_A 1 0 0 0 1 1
sample_B 0 0 0 1 0 0
sample_C 0 1 1 0 1 0
Column Info:
  • s01 and s02 are marker names.
  • 139, 170, 194 are product sizes generated by marker s01 and 203,229,290 are product sizes generated by marker s02.
  • sample_A, sample_B, sample_C are accession names.
  • "1" indicates the presence of PCR product.
  • "0" indicates the absence of PCR product.

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Upload KASP data Template Information

This is for uploading KASP genotype data.
Please use csv formatted files

For KASP Marker Information File:

The header must be:

MarkerName Xallele Yallele Chromosome Position Optional: additional marker info can be included. Please see below.
Note: For dosage calculation, Xallele is used as reference allele (0) and Yallele is used as alternative allele (1).
Optional columns: You can include additional marker information by selecting one or more column headers listed below. Please add the selected column(s) after "Position" column.
  • Quality
  • Filter
  • Info
  • Format
  • Sequence
  • FacilityMarkerName: if you are uploading genotyping data by using facility marker names, please include these names in the KASP marker information file using "FacilityMarkerName" header
For KASP Result File:
Note: If your genotyping facility assigned facility marker names and facility sample names for the genotyping data generated, you have an option to directly use these facility names for uploading. After uploaded into database, the genotyping data will be automatically linked to the original marker names and sample names.

If you are uploading genotyping data using your marker names and sample names, the header must be:

MarkerName SampleName SNPcall Xvalue Yvalue
Required columns:
  • MarkerName: Must exist in the marker information file. If you are uploading genotyping data using previously stored protocol, marker names must exist in the selected protocol.
  • SampleName: Must exist in the database as uniquenames.
  • SNPcall: Allele separated by ":" (for example A:G).
  • Xvalue: raw data of X.
  • Yvalue: raw data of Y.

If you are uploading genotyping data using facility marker names and facility sample names, the header must be:

FacilityMarkerName FacilitySampleName SNPcall Xvalue Yvalue
Required columns:
  • FacilityMarkerName: Must exist in the marker information file.
  • FacilitySampleName: Must exist in the database. You can create a link between each sample name and facility sample name by including facility sample name during uploading genotyping plates
  • SNPcall: Allele separated by ":" (for example A:G).
  • Xvalue: raw data of X.
  • Yvalue: raw data of Y.
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Add Genotyping Plate

  1. Intro
  2. Genotyping Project
  3. Basic Plate Info
  4. Well Info
  5. Trial Linkage
  6. Confirm
  1. This workflow will guide you through adding a genotyping plate in the database

    Genotyping plates represent 96 or 384 well plates.

    Each plate has a globally unique Plate ID.

    Each well in the plate has a globally unique tissue sample ID.

    The "contents" of each well can be either a tissue sample, plant name, plot name, or accession name. This "source" name must be in the database already. This is useful if you provide a field trial entity (such as a plot or plant or tissue sample name), so that phenotypes and genotypes can be directly compared.

    If you choose to submit your genotyping plate to a genotyping facility (Cornell IGD, Intertek, BGI, etc) we can generate the files they require for you. Please be aware of their requirements, such as blank well positions and concentrations.

    In addition to sample ID, you have an option to include facility identifier for each well.



    Go to Next Step
  2. Select a genotyping project

    Genotyping projects are for grouping genotyping plates and/or genotyping data together. Genotyping Project should match Vendor Project if you have one.

    If you need to create a genotyping project, click here

    Once you have a genotyping project, go to Next Step
  3. Provide info about your plate

    Genotyping Project Name:
    Genotyping Plate ID:
    -In Coordinate App this is called "Plate Name"
    -This is the globally unique name of the plate
    Plate Format:
    96 Well 384 Well
    Sample Type:
    DNA RNA Tissue
    Genotyping Plate's Description (optional):
    Include Identifiers Generated by Genotyping Facility
    (only for upload options):

    Go to Next Step
  4. Provide information about the wells in your plate


    Select One:
    Select a file format that you want to upload I am uploading a plate design I made in Excel I am uploading a Default Coordinate Android Application plate design I am uploading a Custom Coordinate Android Application plate design I need to design a completely new plate


    You want to upload an existing plate layout

    File format information
    Spreadsheet format


    Select Plate Layout XLSX File:

    You want to upload a Coordinate Android Application file.

    File format information
    Spreadsheet format


    Select Coordinate CSV File:

    You want to upload a Custom Android Application file.

    File format information
    Spreadsheet format


    Select Coordinate CSV File:

    You want to design a completely new plate.

    • Select a list for the source material going into each well. Your list should be a one to one pairing to each well e.g. if you want to fill 95 wells you should supply a list of 95 elements.
    • Note: From the most desirable to least desirable source observation unit you can choose: tissue samples, plants, plots, or accessions
    Source Observation Unit List:
    [loading...]


    Optional Blank Well: (Cornell IGD requires a specific well to be blank.)

    Optional Well Concentration (ng/ul): (If you used the same conc for all wells)

    Optional Well Volume (ul): (If you used the same vol for all wells)

    Optional Tissue: (If used the same tissue for all wells)
    Leaf Root Stem Seed Fruit Tuber

    Optional NCBI Taxonomy ID: (Official NCBI ID.)

    Optional Extraction: (If used the same extraction for all wells)

    Optional Person: (If same person prepared all wells.)

    Optional Date: (If plated on same date. YYYY/MM/DD)

    Optional Notes: (Additional notes for these wells.)

    Go to Next Step
  5. Is your genotyping plate linked with field trials in the database? This information can also be added from the genotyping plate detail page once the trial is saved in the database.

    If you provided us with information about where the tissue sample in each well originated (e.g. it came from a plot name or plant name or tissue sample name in a field trial), we will automatically create linkage between the field trial(s) and this genotyping plate.


    Continue to Next Step
  6. Finalize and submit your genotyping plate

    Automatic submission to the Genotyping Facility currently not working. You can submit it from the Genotyping Plate's detail page or download the information from the Genotyping Plate's detail page and submit it yourself after clicking Submit

    Submit

Complete! Your genotyping plate was saved in the database.

The genotyping plate was saved successfully

  • You may want to proceed to the genotyping plate detail page for the trial you just created.
  • You can print barcodes for the plate and tissue samples.

Complete! Your genotyping plate was saved in the database.

The genotyping plate was saved successfully

  • You may want to proceed to the genotyping plate detail page for the trial you just created.
  • You can print barcodes for the plate and tissue samples.

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Upload Template Information

This is for uploading a pre-existing genotyping plate layout.
File must be Excel file (.xls or .xlsx)
Header:
The first row (header) must contain the following:
date sample_id well_A01 row column source_observation_unit_name ncbi_taxonomy_id dna_person notes tissue_type extraction concentration volume is_blank
Optional column: In addition to sample ids, you can add facility identifiers in the last column with the header: "facility_identifier".

Required fields:
  • date (should be YYYY-MM-DD)
  • sample_id (the unique identifier for the sample in the well)
  • well_A01 (the position of the sample in the plate e.q. A10)
  • row (the row position of the sample in the plate e.g. A)
  • column (the column position of the sample in the plate e.g. 10)
  • source_observation_unit_name (must exist in the database. the identifier of the origin material. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name. For blank wells, you can write BLANK here and place a 1 in the is_blank column also.)
  • tissue_type (must be either leaf, root, stem, seed, fruit or tuber)
Optional fields:
  • ncbi_taxonomy_id (NCBI taxonomy identifier)
  • dna_person (the name of the person who prepared the well)
  • notes (any additional notes on the well)
  • extraction (free-text for the extraction method e.g. CTAB)
  • concentration (concentration in ng/ul)
  • volume (volume in ul)
  • is_blank (indicates if well is blank. write 1 if blank, otherwise leave empty.)
  • facility_identifier (if you would like to include facility identifiers in your genotyping plate layout, you can add facility identifiers in the last column with the header "facility_identifier")
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Upload Template Information

This is for uploading a Default Coordinate Android Application exported plate layout.
File must be a CSV file (.csv)
(Excel format not supported)

Header:
The first row (header) must contain the following:
date plate_id plate_name sample_id well_A01 well_01A tissue_id dna_person notes tissue_type extraction
Optional column: In addition to sample ids, you can add facility identifiers in the last column with the header: "facility_identifier".

Required fields:
  • date (should be YYYY-MM-DD)
  • plate_id (an identifier for a grouping of plates. called "Genotyping Project Name" in genotyping plate submission form. e.g. NextGenCassava)
  • plate_name (the unique name for the individual plate. called "Plate ID" in genotyping plate submission form. e.g. 18DNA00001)
  • sample_id (the unique identifier for the sample in the well. e.g. 18DNA00001_A01)
  • well_A01 (the position of the sample in the plate in this format A01)
  • well_01A (the position of the sample in the plate in this format 01A)
  • tissue_id (the identifier of the origin material. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name. this can also say 'BLANK' to indicate a blank well.)
  • dna_person (the name of the person who plated the individual sample. can be any name.)
  • tissue_type (must be either leaf, root, or stem)
Optional fields:
  • notes (any additional notes on the well)
  • extraction (free-text for the extraction method e.g. CTAB)
  • facility_identifier (if you would like to include facility identifiers in your genotyping plate layout, you can add facility identifiers in the last column with the header "facility_identifier")
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Upload Template Information

This is for uploading a Custom Coordinate Android Application exported plate layout.
File must be a CSV file (.csv)
(Excel format not supported)

Header:

Note that tissue type will be set to 'leaf' if you use this upload type, since tissue type is not provided in the upload and tissue type is required for DaRT.

The first row (header) must contain the following:
Value Column Row Identification Person Date
Optional column: In addition to sample ids, you can add facility identifiers in the last column with the header: "Facility Identifier".

Required fields:
  • Value (the identifier of the origin material. e.g. 2018MyPlant0001. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name. This can also say 'exclude' to indicate a BLANK)
  • Column (the column position of the sample e.g. 10)
  • Row (the row position of the sample e.g. A)
  • Identification (free text)
  • Person (the name of the person who plated the individual sample. can be any name.)
  • Date (should be YYYY-MM-DD)
Optional field:
  • Facility Identifier (if you would like to include facility identifiers in your genotyping plate layout, you can add facility identifiers in the last column with the header "Facility Identifier")
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Upload Seedlot Inventory

  1. Intro
  2. File format
  3. Upload inventory
  4. Fix missing seedlots problem
  5. Try submitting inventory again
  1. What is a seedlot inventory?

    • Seedlots represent physical seed in packets.
    • This seed can be from crosses or for named accessions.
    • Seedlots can have a specific location, box, weight(g), and count.
    • Seedlots can belong to breeding programs and organizations.
    • Seedlots can be used in trials (e.g. they were planted in a plot) and they can be harvested from a plot or plant (e.g. a cross was performed and seeds were collected.)
    • A seedlot inventory consists of giving a location and current weight(g) to your seedlots. The seedlot name is the unique identifier for each seedlot and so should be encoded in a barcode on each seedlot packet.
    • You can use the "Inventory" Android Application to scan seedlot barcodes and record weight. If you prefer you can create your own CSV file and upload that, if you do not want to use the Inventory Application. For info about the format of the file to upload, go to the next tab.
    • It is also possible to manually enter a transaction by going to the seedlot detail page and clicking "Add New Transaction".


    Go to Next Step
  2. Make sure you are collecting seedlot inventory in the following format

    The "Seed Inventory" Android Application will export this same exact format by default.



    Info about file format

    Once you think your file matches, go to Next Step
  3. Select your file and upload seedlot inventory

    Upload File (.csv):


    Submit
  4. Fixing the missing seedlot(s) problem

    • Seedlots must exist in the database prior to updating or adding inventory. The reason for this is that the inventory does not give information about the content (a named accession or a cross name) and this information is required for a seedlot to exist in the database. We also want to be careful about adding new seedlots into the database because we do not want data to be incorrectly linked to duplicates.
    • When adding seedlots into the database, you can upload an Excel file or you can add seedlots one at a time.

      • Upload Excel file

      • Add One Seedlot

    Once all your seedlots are in the database Click Here

    Seedlot Inventory Upload Error Messages

  5. Submit your inventory again. You should have corrected all errors by now, but if not please take a look at the errors in the red box below. You can continue to modify your file and then click Upload until it works.

    Upload Seedlot Inventory

    There exist these problems in your file:

Finished! Your seedlot inventory is in the database

The seedlot inventory file was uploaded successfully

  • You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just updated.
  • You can print barcodes for the seedlots.

Finished! Your seedlot inventory is in the database

The seedlot inventory file was uploaded successfully

  • You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just updated.
  • You can print barcodes for the seedlots.

Close
×

Upload Template Information

Seedlots may be uploaded in a CSV file (.csv)
(Excel .xls and .xlsx format not supported)

Header:
The first row (header) should contain the following:
box_id seed_id inventory_date inventory_person weight_gram
Required fields:
  • box_id (the name of the box that the seedlot is in. also called box_name.)
  • seed_id (unique identifier for the seedlot. must exist in the database. also called seedlot_name)
  • inventory_date (a timestamp for when the seedlot was inventoried)
  • inventory_person (the name of the person doing the inventory. can be any name. also called operator_name)
  • weight_gram (the weight in grams of the seedlot)
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Upload Seedlots

  1. Intro
  2. What seedlots do you have?
  3. File format
  4. Upload seedlots
  5. Fix errors in file
  6. Try submitting seedlots again
  1. What are seedlots?

    • Seedlots represent physical seed in packets.
    • This seed can be from crosses or for named accessions.
    • Seedlots can have a specific location, box, weight_gram, and count.
    • Seedlots can belong to breeding programs and organizations.
    • Seedlots can be used in trials (e.g. they were planted in a plot) and they can be harvested from a plot or plant (e.g. a cross was performed and seeds were collected.)


    Go to Next Step
  2. Seedlots fall into two categories

    Select One:
    I have seed lots for named accessions I have seed lots harvested from crosses



    Go to Next Step
  3. Make sure your file matches the correct file format



    Information about file format for uploading seedlots of named accessions

    Information about file format for uploading seed lots harvested

    Once you think your file matches, go to Next Step
  4. Provide basic information about the seedlots and upload your file

    Breeding Program:
    Location of seedlot storage:
    Organization Name:
    Upload File:
    Upload File:
    Upload Seedlots

  5. Fix all errors in your file

    • Accessions must exist in the database prior to adding seedlots of them. The reason for this is that an accession can be exist in many seedlots and therefore exists as a separate entity in the database. We also want to be careful about adding new accessions into the database because we do not want incorrectly duplicated data.
    • When adding accessions into the database, you can use either a list of accessions or an Excel file.
    Add your accessions to the database

    Once all your accessions are in the database Click Here

    • Crosses must exist in the database before adding your seed lots. The reason for this is that a cross can produce many seed lots and so the cross must exists as a separate entity in the database. We also want to be careful about adding new crosses into the database because we do not want data to be incorrectly linked to duplicates.
    • When adding crosses into the database, you can upload an Excel file or you can add seedlots one at a time.

      • Upload Excel file

      • Add One Cross

    Once all your crosses are in the database Click Here

    Seedlot Upload Error Messages

  6. Submit your seedlots again. You should have corrected all errors by now, but if not please take a look at the errors in the red box below. You can continue to modify your file and then click Upload until it works.

    Upload Seedlots

    There exist these problems in your file:

Finished! Your seedlots are now in the database

The seedlot file was uploaded successfully

  • You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just created.
  • You can print barcodes for the seedlots.

The seedlots were saved to the database with no errors! Congrats Click Here

Finished! Your seedlots are now in the database

The seedlot file was uploaded successfully

  • You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just created.
  • You can print barcodes for the seedlots.

The seedlots were saved to the database with no errors! Congrats Click Here

Close
×

Upload Template Information For Named Accessions

Header:
The first row (header) should contain the following:
seedlot_name accession_name operator_name amount weight_gram description box_name quality source
Required fields:
  • seedlot_name (must be unique)
  • accession_name (must exist in the database. the accession_name is the unique identifier for the named genotype)
  • operator_name (the name of the person who oversaw the inventory process. can be any name.)
  • amount (number of seeds in seedlot. can be provided in conjunction with weight_gram. must provide a value for amount or weight_gram or both.)
    AND/OR
    weight_gram (weight in grams of seedlot. can be provided in conjunction with amount. must provide a value for amount or weight_gram or both.)
  • box_name (the box name that the seed is located in. can be any name.)
Optional fields:
  • description (information about why this seedlot is being added)
  • quality (status of the seedlot, for example "ok", "moldy", "insect damage" etc.
  • source (an alternate source, such as a plot, subplot, or plant identifier from which the seed was collected)

Seedlots may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

Close
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Upload Template Information For Harvested Seedlots

Header:
The first row (header) should contain the following:
seedlot_name cross_unique_id operator_name amount weight_gram description box_name quality
Required fields:
  • seedlot_name (must be unique)
  • cross_unique_id (must exist in the database. a cross_unique_id can represent a cross between accessions e.g. AxB, but a cross can also represent a cross between specific plots in the field if you have this information)
  • operator_name (the name of the person who oversaw the inventory process. can be any name.)
  • amount (number of seeds in seedlot. can be provided in conjunction with weight_gram. must provide a value for amount or weight_gram or both.)
    AND/OR
    weight_gram (weight in grams of seedlot. can be provided in conjunction with amount. must provide a value for amount or weight_gram or both.)
  • box_name (the box name that the seed is located in. can be any name.)
Optional fields:
  • description (information about why this seedlot is being added)
  • quality (brief description of quality, e.g., "ok", "moldy", "insect damage", etc)

Seedlots may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

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Create New Seedlot

Name:
Seedlot Description:
Breeding Program:
Location:
Box Name:
Quality issues:
Contents:
Accession name:

OR

Cross Unique ID:
Source:
Seedlot/Plot/Subplot/Plant name to be used as the source for the first transaction
Amount (number of seeds):
Weight (g):
Organization:
Timestamp:
Transaction Description:
OK
×

Add Accessions

  • Using Lists
  • Uploading a File
Choose a List of Accessions to Add:
Manage Lists
Use Fuzzy Search:

Note: Use the fuzzy search to match similar names to prevent uploading of duplicate accessions. Fuzzy searching is much slower than regular search.

File format information
Spreadsheet format

Upload File:
Email Alert:
Email:
Use Fuzzy Search:

Note: Use the fuzzy search to match similar names to prevent uploading of duplicate accessions. Fuzzy searching is much slower than regular search. Only a curator can disable the fuzzy search.
Append Synonyms:

When checked, add synonyms of existing accession entries to the synonyms already stored in the database. When not checked, remove any existing synonyms of existing accession entries and store only the synonyms in the upload file.

Accessions may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

Close Continue
×

Upload Accessions Template Information

Header:
The first row (header) should contain the following:
accession_name species_name population_name organization_name synonym description PUI accession number acquisition date biological status of accession code country of origin donor donor PUI donor institute genome_structure institute code institute name introgression_backcross_parent introgression_chromosome introgression_end_position_bp introgression_map_version introgression_parent introgression_start_position_bp location_code ncbi_taxonomy_id notes organization ploidy_level product_profile released_variety_name seed source state transgenic type of germplasm storage code variety variety_release_id year_of_cloning
Comma Separated Fields:
  • The following fields can take comma-separated values to indicate there are several values for the accession: organization_name, synonym , PUI, accession number, acquisition date, biological status of accession code, country of origin, donor, donor PUI, donor institute, genome_structure, institute code, institute name, introgression_backcross_parent, introgression_chromosome, introgression_end_position_bp, introgression_map_version, introgression_parent, introgression_start_position_bp, location_code, ncbi_taxonomy_id, notes, organization, ploidy_level, product_profile, released_variety_name, seed source, state, transgenic, type of germplasm storage code, variety, variety_release_id, year_of_cloning
Required Fields:
  • accession_name (must be unique)
  • species_name (must exist in the database)
Optional Fields:
  • description - a free text description of the stock.
  • population_name (a population is a grouping of accessions. If the population already exists in the database, the accession will be added to it; otherwise, a new population will be created). Multiple populations can be specified, using the pipe symbol (|) as the separator (for example, pop1|pop2|pop3)
  • organization_name (the name(s) of the organization(s) which use this accession e.g. NARO,IITA)
  • synonym (an accession can be known by many names including local popular names. a synonym name can be used instead of the accession_name throughout the database; because of this, synonyms must themselves be unique. e.g. accession_synonym1,accession_synonym001)
  • PUI (no definition available)
  • accession number (no definition available)
  • acquisition date (no definition available)
  • biological status of accession code (no definition available)
  • country of origin (no definition available)
  • donor (no definition available)
  • donor PUI (no definition available)
  • donor institute (no definition available)
  • genome_structure (no definition available)
  • institute code (no definition available)
  • institute name (no definition available)
  • introgression_backcross_parent (no definition available)
  • introgression_chromosome (no definition available)
  • introgression_end_position_bp (no definition available)
  • introgression_map_version (no definition available)
  • introgression_parent (no definition available)
  • introgression_start_position_bp (no definition available)
  • location_code (no definition available)
  • ncbi_taxonomy_id (no definition available)
  • notes (no definition available)
  • organization (no definition available)
  • ploidy_level (no definition available)
  • product_profile (no definition available)
  • released_variety_name (no definition available)
  • seed source (no definition available)
  • state (no definition available)
  • transgenic (no definition available)
  • type of germplasm storage code (no definition available)
  • variety (no definition available)
  • variety_release_id (no definition available)
  • year_of_cloning (no definition available)

Accessions may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

Optional columns may be left out, if not used in your data.

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Accessions to be Added

Species name for added accessions

Population name for added accessions (optional)

Organization name for added accessions (optional)

The following accessions are new and will be added to the database:

Close Add Accessions
×

Fuzzy Matches

Accessions were found with similar names.

Download Fuzzy Matches Make Changes and Continue
×

Found Accessions

The following accessions already exist in the database:

Continue
×

Accessions Saved

Close
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Upload Crosses

  1. Intro
  2. Crossing experiment
  3. Upload your crosses
  1. Introduction

    • Crosses can be of different types (biparental, self, open, backcross, sib, polycross, bulk, bulk_open, bulk_self, doubled_haploid, or dihaploid_induction)
      • cross type descriptions:
        • biparental: An individual plant pollinated by another individual plant.
        • self: A self pollinated individual plant.
        • open: An individual plant pollinated by a group of plants or open pollinated (pollen may be from a group with known or unknown members).
        • backcross: An individual plant pollinated by one of its parents. Cross Unique ID can be used as one of the parents.
        • sib: Mating between individuals that have at least one parent in common. Generally between two individuals within the same plot.
        • polycross: Mating between individual female parent from a population and the corresponding male population.
        • bulk: A group of plants (usually a related family) pollinated by an individual plant (between a female population and a male accession).
        • bulk_open: A group of plants (usually a related family) that are pollinated by another group of plants or open pollinated (between a female population and a male population or unknown male parent).
        • bulk_self: A group of plants (usually a related family) that are self pollinated (each individual selfed, not combined pollen).
        • doubled_haploid: Plants derived from doubling the chromosome number of haploid tissue.
        • dihaploid_induction: Plants derived from reducing the chromosome set from tetraploid to diploid.
    • An individual cross can be linked to a female plot or plant, as well as a male plot or plant.
    • A cross can have a number of properties associated to it, such as number of flowers, pollination date, etc.
    • A cross can produce seed, which goes into a seedlot.
    • A cross can ultimately produce progeny, which then become named accessions in the database.


    Go to Next Step
  2. Select a crossing experiment for your crosses

    If you are uploading an Intercross file and using auto-generated cross unique IDs, please use manage Intercross section

    Crossing experiments are for grouping crosses together. The grouping is most often done for crosses derived from the same field trial, the same year, or for crosses that have the same breeding objective.

    If you need to create a new crossing experiment, click here

    If you already have a crossing experiment, go to Next Step
    You are uploading crosses for crossing experiment:




    Go to Next Step
  3. Enter basic information about the crosses and upload your file


    Breeding Program:

    Crossing Experiment:
    Crossing Experiment:

    File format information
    Spreadsheet format


    Upload File:

    Crosses may be uploaded using any of the supported file types: MS Excel (.xls or .xlsx), comma-separated file (.csv), tab-delimited file (.txt or .tsv), or semicolon-separated file (.ssv).

    Upload File

Finished! Your crosses are now in the database

The crosses file was uploaded successfully

  • You may want to proceed to the cross detail page(s) for the cross(es) you just created.
  • You can print barcodes for the crosses.
  • You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

The crosses were saved to the database with no errors! Congrats Click Here

Finished! Your crosses are now in the database

The crosses file was uploaded successfully

  • You may want to proceed to the cross detail page(s) for the cross(es) you just created.
  • You can print barcodes for the crosses.
  • You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

The crosses were saved to the database with no errors! Congrats Click Here

Close
×

Upload Crosses File Error

Close
×

Template Information


Header:
To set up crosses in the database, please provide required information. The first row (header) must contain the following:
cross_unique_id cross_combination cross_type female_parent male_parent
Required columns:
  • cross_unique_id (must NOT exist in the database)
  • cross_combination (required in the header, but value for cross combination (e.g. female accession/male accession) may be left blank)
  • cross_type (must be one of the following: biparental, self, open, sib, polycross, backcross, bulk, bulk_open, bulk_self, doubled_haploid, dihaploid_induction)
    • biparental: An individual plant pollinated by another individual plant.
    • self: A self pollinated individual plant.
    • open: An individual plant pollinated by a group of plants or open pollinated (pollen may be from a group with known or unknown members).
    • backcross: An individual plant pollinated by one of its parents.
    • sib: Mating between individuals that have at least one parent in common. Generally between two individuals within the same plot.
    • polycross: Mating between individual female parent from a population and the corresponding male population.
    • bulk: A group of plants (usually a related family) pollinated by an individual plant (between a female population and a male accession).
    • bulk_open: A group of plants (usually a related family) that are pollinated by another group of plants or open pollinated (between a female population and a male population or unknown male parent).
    • bulk_self: A group of plants (usually a related family) that are self pollinated (each individual selfed, not combined pollen).
    • doubled_haploid: Plants derived from doubling the chromosome number of haploid tissue.
    • dihaploid_induction: Plants derived from reducing the chromosome set from 4 to 2.
  • female_parent: Female parent names must exist as uniquenames in the database, can be accession, plot, plant or population stock type.
  • male_parent: Required in the header, but value may be left blank for most cross types. Must be specified for biparental, sib, backcross, polycross and bulk cross types. When specified, male parent names must exist as uniquenames in the database, can be accession, plot, plant or population stock type.
Optional columns (additional parent info): You can add additional parent info after male_plant column by using one or more of these column headers.
  • objective
  • female_focus_trait
  • male_focus_trait
  • female_source_trial
  • male_source_trial
Additional cross information:
  • After cross unique ids are stored in the database, you can add field crossing data (e.g. pollination date, total number of flowers pollinated, total number of fruits set) or progenies to each cross unique id.
  • Field crossing data and progenies can be uploaded via links in crossing experiment detail page or can be added directly in each cross detail page.
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Add New Cross

  1. Intro
  2. Crossing Experiment
  3. Enter cross information
  4. Enter parentage information
  5. Additional cross info
  1. What is a cross?

    • The Cross Tool can track any pollinations in a breeding program.
    • Each cross has a globally unique cross id.
    • Supported cross types are: biparental, self, open, backcross, sib, polycross, bulk, bulk_self, bulk_open, doubled_haploid, or dihaploid_induction
    • For an open pollinated cross, the cross can be defined as between female accession A and male population P1 (populations in the database are defined strictly as groups of accessions). If the male parent is not known, it can be left blank.
    • For backcross cross type, cross unique id can be used as one of the parents.
    • An individual cross can be linked to the specific female plot or plant, as well as to the specific male plot or plant.
    • A cross can have other data associated to it, such as number of flowers, pollination date, etc.
    • Seed produced by a cross can be managed using a seedlot.
    • Progenies from a cross can become named accessions in the database.

    Go to Next Step
  2. Select a crossing experiment

    Crossing experiments are for grouping crosses together. The grouping is most often done for crosses derived from the same field trial, the same year, or for crosses that have the same breeding objective.

    If you need to create a crossing experiment, click here

    Once you have a crossing experiment, go to Next Step
  3. Enter basic information about the cross

    Cross type information
    Descriptions of cross types

    Breeding Program:


    Crossing Experiment:


    Cross Unique ID:


    Cross Combination (optional):


    Cross Type:
    Select a cross type biparental self open pollinated backcross sib bulk bulk selfed bulk and open pollinated doubled haploid dihaploid induction polycross reciprocal multicross


    Go to Next Step
  4. Enter basic information about the cross

    Female Parent:


    Male Parent:


    Selfed Parent:


    Female Parent:


    Male Population: (optional)


    Female Population:


    Male Parent:


    Selfed Population:


    Female Population:


    Male Population: (optional)


    Doubled Haploid Parent:


    Dihaploid induction Parent:


    Accessions to use in Polycross:


    Accessions to use in Reciprocal cross:


    Multicross Female Parents:


    Multicross Male Parents:


    Optional: If you choose to record exact cross parents, you can do so.

    Field Trial:
    Search Plots/Plants


    Female Plot/Plant:
    Enter trial name first


    Male Plot/Plant:
    Enter trial name first


    Optional: If you choose to record exact cross female parent, you can do so.

    Field Trial:
    Search Plots/Plants


    Female Plot/Plant:
    Enter trial name first



    Go to Next Step
  5. If you would like to add auto-generated progeny names for this cross, you can add it here

    Optional:

    Add New Accessions for Progeny:
    Number of progeny:
    Use Prefix and/or Suffix:
    Prefix:
    Suffix:

    Submit Cross

Finished! Your cross is now in the database

The cross was added successfully

  • You may want to proceed to the cross detail page for the cross you just created.
  • You can print barcodes for the cross.
  • You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Finished! Your cross is now in the database

The cross was added successfully

  • You may want to proceed to the cross detail page for the cross you just created.
  • You can print barcodes for the cross.
  • You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Close
×

Template Information

Individual Crosses:

biparental: An individual plant pollinated by another individual plant.

self: A self pollinated individual plant.

open pollinated: An individual plant pollinated by a group of plants or open pollinated (pollen may be from a group with known or unknown members).

backcross: An individual plant pollinated by one of its parents.

sib: Mating between individuals that have at least one parent in common. Generally between two individuals within the same plot.

bulk: A group of plants (usually a related family) pollinated by an individual plant.

bulk selfed: A group of plants (usually a related family) that are self pollinated (each individual selfed, not combined pollen).

bulk and open pollinated: A group of plants (usually a related family) that are pollinated by another group of plants or open pollinated (pollen may be from a group with known or unknown members).

doubled haploid: Plants derived from doubling the chromosome number of haploid tissue.

dihaploid induction: Plants derived from a chromosome reduction from tetraploid to diploid


Group of Crosses:

polycross: Creates a group of open pollinated crosses. Each accession in the selected list becomes the female parent in an open cross, and all the members of the list grouped together form the male parent.

reciprocal: Creates a group of biparental crosses. Starting with a list of accessions, all possible biparental cross combinations are made between them.

multicross: Creates a group of biparental crosses. Starting with a list of maternal accessions and a list of paternal accessions, direct crosses are made in order.

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Success

The cross or crosses were saved successfully.

Close
×

Add New Crossing Experiment

  1. Intro
  2. Add a crossing experiment
  1. What are crossing experiments?

    Crossing experiments group crosses. The grouping can reflect crosses done in the same field trial, crosses in a breeding program in a given year, or crosses that have the same breeding objective. This grouping can be used to encapsulate all the crosses done in a crossing block field trial that you have saved in the database (e.g. in Manage Trials your crossing block will appear as a field trial with plots)

    Go to Next Step
  2. Enter basic information about the crossing experiment


    Crossing Experiment Name:


    Breeding Program:
    Select Breeding Program 5CPBTICARICHCIATCIP-genebankCNRACornellCSIR-CRIEmbrapaIDIAFIITAINERA_IITA_DRCISABUITCKALROKUNaCRRINRCRIRayongSLARITARIUACUHUNILA-IndonesiaZARI


    Location of crossing experiment:
    Select Location RestrepoIgbariamRayongGranadaSanto Tomas. Atlantico, ColombiaFlorenciabwangaNaliendeleKokrokoChokweCalabarJaguaripe (BA) - Fazenda EsperançaCorozal. Sucre, ColombiaAgborSuakokoKibahaIshiaguBarahonaNjalaSotoubouaBuenos AiresAlbaniaItanhem (BA)IlorinAcacias. Meta, ColombiaVerdelandia (MG)-Brasnica Fazenda OrienteCIATDarien. Valle, ColombiaEl Espinal. Tolima, ColombiaTerra Alta (PA)Kano[Computation]Puerto Caicedo. Putumayo, ColombiaFlorestal (MG) - UFV Campus FlorestalLUWEEROMatazulAkwa IbomLaje (BA)-RoqueEjuraVilla Garzon. Putumayo, ColombiaLuruacoHomboloQuilcace. Cauca, ColombiaTumacoCaribiaOvejasMomilLomeMukonoSabanagrandeBlamaSao Mateus (ES)KiggumbaNjuliMakokaZariaIbadanArmeroZomboAnlong Veng District, Oddar Meanchey provinceMutata. Antioquia, ColombiaAguazulValencia. Cordoba, ColombiaQuang NgaiAgustin CodazziMakeniKabalaNametilPalmiraBolivarKwaraKazilamuyagaTamalameque. Cesar, ColombiaBaranoa. Atlantico, ColombiaEsplanada (BA) - CachoeiraUkereweNhacoongoLaje (BA)-GaviaoMangabeira (BA)-IF BaianoGairoBuginyanyaMarukuMtwapa2Varzedo (BA)UmbeluziSao Francisco de Itabapoana (RJ)-Industria Dona ChicaPolonuevoBukembaRufunsaCampos Novos Paulista (SP)-Tereos SyralOgoniInharrimeBulingaUyoEmbuBarrancabermejaDarienCereteFumesuaSiayaCarimagua. Meta, ColombiaMacapa (AP)SabanalargaEl Overo. Valle, ColombiaCaldonoPallisaSabanalarga. Atlantico, ColombiaKhao Hinsorn Research Center, Kasetsart University, Chachoengsao provinceRatanak Mondul district, Battambang provinceMasakaEl Olivo. Cordoba, ColombiaApiayVitoria da Conquista (BA) - Fecularia ConquistaMvuaziKaberamaidoSulutiSan Vicente. Santander, ColombiaMontenegro. Quindio, ColombiaTouros (RN)-PrataBusiaunspecifiedMutataSanta CruzUniversity of HawaiiAkureOhawuCarepaLirakasuluApiay. Meta, ColombiaBugaPetrolina (PE)-UNIVASFPatiaMichikichiniItasyAgo-OwuPopayanDoncello. Caqueta, ColombiaDivoPajau. Brasil, BrazilQuilcaceFlorencia. Caqueta, ColombiaChiengiTangakonaOtobiMontenegroPuerto GaitanBarranquilla. Atlantico, ColombiaCorozalPinheiros (ES)MontanitaJeddoLao NgamSikhiu is a district (amphoe) in the western part of Nakhon Ratchasima provinceCienaga. Magdalena, ColombiaBela Vista de Goias (GO)TolúMarechal Candido Rondon (PR)-ATIMOPEl EspinalHoma BayArmeniaTESTKisesaAssin FosuBundaYopal. Casanare, ColombiabadagryObuduNaphokLa Dolores. Valle, ColombiaNamulonge-SendusuSenjehSampues. Sucre, ColombiaCajibioCoração de Maria (BA)GongoniLa HormigaRakaiPalmasecaChitedzeLoricaCruz das Almas (BA)-UFRB-CandealMargibiTracuateua (PA)TolúviejoPopayan. Cauca, ColombiaAcaciasTauramenaKipopoAgbarhoCIAT. Valle, ColombiaNgandajikaMkurangaOrito. Putumayo, ColombiaPuerto Asis. Putumayo, ColombiaCumaral. Meta, ColombiaRubiriziBuikweKalomoSan Martin. Meta, ColombiaMityanaOsunKiyakaPivijaySinceMontanita. Sucre, ColombiaConde (BA)-CanguritoNyankpalaVitoria da Conquista (BA)Prado (BA)MbuniHung YenLaje (BA) - Fazenda Sombra VerdeDeltaBoyce Thompson InstitutePitalitoKasinthukaPuerto AsisMorogoroMkondeziAbujaMonteria (UNICORDOBA). Cordoba, ColombiaWenchiSan VicenteCaracoli. Atlantico, ColombiaMokwaKebbiAlupeCapanema (PA)RubonaChatoCalotoUsiacuriSanta Cruz. Atlantico, ColombiaLa Hormiga. Putumayo, ColombiaMonteriaLaje (BA)-Rio de Areia 1Rio Frio. Magdalena, ColombiaTeresina (PI)OnneOrtegaIresiYopalFonsecaKabangweCaracoliEl Salado. Cordoba, ColombiaPuerto LopezLagoa D'Anta (RN)ManLagoa D'anta (RN)-LopesKWALEPuerto Gaitan. Meta, ColombiaConceicao dos Ouros (MG)Pojuca (BA)RiversMedia Luna. Magdalena, ColombiaFadaInaAremasain. Guajira, ColombiaBambiLukwakwaMalambo. Atlantico, ColombiaCornell BiotechChilimbaLoroSerereRio FrioDoncelloPalmar de VarelaMogovolasFumesua-KumasiSan Antonio de PalmitoSon LaMtwapaWarriNachingweaBulegeniVerdelandia (MG)-Brasnica Fazenda VilyamaZanzibarTapioca Development Institute (TDI), located in Huay Bong, Dan Khun Thot District, Nakhon RatchasimaPhu YenJamundi. Valle, ColombiaMalamboPureza (RN)Puerto Lopez. Meta, ColombiaFarakobaHanoiNgomaKasuluSevillaItamaraju (BA)Ban Khao Luk Chang, Ta Phraya Sistrict, Sa Kaeo provinceCienagaS. de Quilichao. Cauca, ColombiaEl MiraEdoGuanambi (BA)-IF BaianoCruz Das Almas (BA) - UFRB CAMABSerra dos Aimores (MG)-Cachoeira da MataMahondaLlanosVilla GarzonArmenia. Quindio, ColombiaMarataizes (ES)LiupoLaje (BA)-Rio de Areia 1MigoriWakisoCruz das Almas (BA)-UFRB-PP1GbarpoluEketPuerto CaicedoBarranca De Upia. Casanare, ColombiaLa Libertad. Meta, ColombiaLaberinto. Sucre, ColombiaCrossRiverMondomoLondrina (PR-Afapo)Teixeira de Freitas (BA)El Carmen. Bolivar, ColombiaMimoso do Sul (ES)CarimaguaTay NinhBayelsaValledupar. Cesar, ColombiaPonta Pora (MS)-Assentamento ItamaratiMogincualBuenaventuraBouakeItiuba (BA)San PabloKisesa-MaguEl SaladoDewoinBanteay Meanchey province Banteay MeancheyMulunguMsambweniNgabuCandelaria. Valle, ColombiaAlagoinhas (BA)-Boa UniaoNecocliCaloto. Cauca, ColombiaCabuyaro. Meta, ColombiaIkenneSan MartinSoeng Sang is a district in the southeastern part of Nakhon Ratchasima provinceInhambupe (BA)-BotelhoThateng district, Sekong provinceBuga. Valle, ColombiaCantaclaroS. de QuilichaoCorozal. Sucre, ColombiaNational Corn and Sorghum Research Center (Suwan Farm), Kasetsart University Nakhon Ratchasima provinceLuruaco. Atlantico, ColombiaLa Libertad. Meta, ColombiaIlesaPend. , ColombiaCerete. Cordoba, ColombiaVijes. Valle, ColombiaNaCRRI, Central UgandaLa UnionRokuprUnknownunknown2MbararaAugusto Correa (PA)MuhangaAzuaRwebitabadavieNiaouliJamundiChamkar Leu districtBarranquillaAtivemeNgettaGranada. Meta, ColombiaCampecheJosIBARAPAEl Carmen de BolivarChambeziMomil. Cordoba, ColombiaFrancisco PizarroSatiro Dias (BA)-Assentamento PapagaioPalmaseca. Valle, ColombiaLaje (BA)-Novo Horizonte 2ASan PedroCienaga De Oro. Cordoba, ColombiaMalam MadoriKumasiKamaConde (BA)-HumaitaRepelon. Atlantico, ColombiaNecocli. Antioquia, ColombiaCorpoica PalmiraBetuliaLaje (BA)-Rio de Areia 2MocubaNigerDanyiTororoKizimbaniFonseca. Guajira, ColombiaOshogboKaomaPitalito. Atlantico, ColombiaLaberintoAdetaSantaguedaKakamegaTchadNsukkaCabuyaroNamulongeKubwaIRRUADong NaiLa LibertadLaje (BA)-Fazenda Sao JorgekaseseBaranoaPalmar de Varela. Atlantico, ColombiaMatazul. Meta, ColombiaBwangaKisumuPescador. Cauca, ColombiaLaje (BA)-RogerioSahagun. Cordoba, ColombiaSabanalarga. Atlantico, ColombiaNgettaCarranzo. Cordoba, ColombiaMoralesSampuesChinuPouso Alegre (MG)Cajibio. Cauca, ColombiaLaje (BA)-Novo Horizonte 1YangambiNebbiPokuaseDaklakMorales. Cauca, ColombiaNyagatareMontanha (ES) - Fecularia ConquistaKibaaleBarranca De UpiaEl OveroArmero. Tolima, ColombiaCarepa. Antioquia, ColombiaSahagunLa Union. Sucre, ColombiaAlcobaca (BA)KilibaBetulia. Sucre, ColombiaAlbania. Sucre, ColombiaKaseseCIAT. Valle, ColombiaAbidjanPendembuMsabahaBarrancabermeja. Santander, ColombiaChinu. Cordoba, ColombiaUkiriguruOritolossaVijesLaje (BA)-Novo Horizonte 2BBolikham district, Bolikhamxay provinceCruz Das Almas (BA)-CNPMF-Area 2DamongoPatia. Cauca, ColombiaUmudikeRestrepo. Meta, ColombiaNeivaCostaRepelonSanto TomasChitalaEntre Rios (BA)ChochoLaje (BA) - CapelaQuissama (RJ)-PMQ HortoKadunaweBom Jesus da Lapa (BA) - IF BaianoEkitiPitalito. Atlantico, ColombiaOgutaNong Yai is a district in the province ChonburiCandelariaMolineros. Atlantico, ColombiaPescadorWenchi-BALa CumbreLaje (BA) - RailtonSanta Isabel do Para (PA)Santo Tomas. Atlantico, ColombiaMedia LunaEl OlivoTauramena. Casanare, ColombiaCumaralCaribia. Magdalena, ColombiaValleduparFloridaMondomo. Cauca, ColombiaMotiloniaAguazul. Casanare, ColombiaLaje (BA)-Novo RumoCienaga De OroStung Treng Province, Stung TrengPokuase-AccraEuclides da Cunha (BA)AKUMADANCruz Das Almas (BA) - UFRB - EstabuloAremasainLaje (BA)-Novo Horizonte 1AKibosKamuliLa DoloresAlagoinhas (BA)COLDStore, RACK1, Shelf2, Cruz Das Almas (BA) CNPMF - CitrusRuziziPlainIkot AfangaBengouPivijay. Magdalena, ColombiaKogiAruaAgenbodeValenciaNatagaimaCampos dos Goytacazes (RJ)-UENFILONGABundibugyoEgbemaKakonkoMubendeSanto Amaro (BA)BarrancasCachoeira de Minas (MG)Dourados (MS)-UFGDDOKOLOCruz Das Almas (BA) - CNPMF - Area 1 (Ladeira maracuja)Los PalmitosibadanGinebraMansaUbiaja


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Cassava (Manihot esculenta), a major staple crop, is the main source of calories for 500 million people across the globe. No other continent depends on cassava to feed as many people as does Africa. Cassava is indispensable to food security in Africa. It is a widely preferred and consumed staple, as well as a hardy crop that can be stored in the ground as a fall-back source of food that can save lives in times of famine. Despite the importance of cassava for food security on the African continent, it has received relatively little research and development attention compared to other staples such as wheat, rice and maize. The key to unlocking the full potential of cassava lies largely in bringing cassava breeding into the 21st century. [More...]


Project Links
NextGen Cassava website
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Cassava Descriptors
HTPG project
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For all questions about Cassava (phenotyping, genotyping, population genetics) subscribe to the cassava-discussion@cassavabase.org mailing list!
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RIKEN Cassava Database
Cassavabiotech.org (CAS, Shanghai, China)
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GOBii project
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Please Note: Website Data Usage Policy

Cassavabase adheres to the Toronto Agreement on prepublication data release.

All data deposited on cassavabase adheres to the Toronto Agreement on prepublication data release. To foster transparent and accessible data sharing culture, in accordance with the Toronto Agreement, all data deposited on cassavabase will be made public immediately. Data producers can provide information on the data they deposit, including planned analyses and publication timeline information, to indicate their publication intentions. Data users are expected to respect scientific etiquette and allow data producers the first global analyses of their data set, and should be aware that pre-publication data may not have been subject to full quality control and peer review, so caution must be applied when utilizing these data. More information is available on the data usage policy page.
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News
NextGen Cassava Impact Report
The NextGen Cassava I\ mpact Report is here.
Cassavabase Errata
An issue with genotyping data has been fixed in the database. Certain genotyping protocols stored the dosage information with inverted ref and alt values. All protocols are now using consistent values. We recommend to re-download the data if you use it locally. [May 2, 2022]
Cassavabase Webinar
A Cassavabase Webinar will be given on Wednesday, March 23, at 8am EST, 12:00 GMT, 13:00 WAT/CET and 15:00 EAT. Zoom Link.
Product Profile Management
Manage product profiles on the site! Each breeding program can define product profiles on the respective breeding program manage page. [Nov 1, 2020]
Mixed Model tool
A tool for calculating mixed models is now available. [Nov 1, 2020]
K-Means Clustering
Run clustering on your trial genotype dataset from a trial detail page or the clustering page. [Oct 30, 2018]
See all news...
Community
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Events
BreedBase Workshop at PAG 32
BreedBase will host a workshop at PAG 32:
Venue: Palm 7
Time: Tuesday, Jan 14, 2025, 10:30 am - 12:40 pm

Breedbase Booth

Main Exhibition Hall, Booth 502 (look for Boyce Thompson Institute)
See all events...
Featured Publication

Featured Publication

Training Population Optimization for Prediction of Cassava Brown Streak Disease Resistance in West African Clones  Alfred Ozimati, Robert Kawuki, Williams Esuma, Ismail Siraj Kayondo, Marnin Wolfe, Roberto Lozano, Ismail Rabbi, Peter Kulakow and Jean-Luc Jannink
G3,October 2018, doi:10.1534/g3.118.200710
GWAS of resistance to Cassav Green Mite pest and related traits in cassava  Lydia Ezenwaka, Dunia Pino Del Carpio, Jean-Luc Jannink, Ismail Rabbi, Eric Danquah, Isaac Asante, Agyemang Danquah, Essie Blay, and Chiedozie Egesi
Crop Science,September 2018, doi: 10.2135/cropsci2018.01.0024
Cassava Trait Preferences of Men and Women Farmers in Nigeria: Implications for Breeding  Bela Teeken, Olamide Olaosebikan, Joyce Haleegoah, Elizabeth Oladejo, Tessy Madu, Abolore Bello, Elizabeth Parkes, Chiedozie Egesi, Peter Kulakow, Holger Kirscht, Hale Ann Tufan
Economic botany,July 2018, https://doi.org/10.1007/s12231-018-9421-7
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    NextGen Cassava

    NextGen Cassava Breeding project promises to substantially increase the rate of genetic improvement in cassava breeding and unlock the full potential of cassava, a staple crop central to food security and livelihoods across Africa.

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    Project Partners

    • College of Agriculture and Life Sciences, Cornell University, USA
    • National Crops Resources Research Institute (NaCRRI), Uganda
    • National Root Crops Research Institute (NRCRI), Nigeria
    • International Institute of Tropical Agriculture (IITA), Nigeria
    • Boyce Thompson Institute (BTI) for Plant Research, USA
    • US Department of Energy (DOE) Joint Genome Institute (JGI), USA
    • Makerere University, Uganda


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