The Basic or “Agronomic” System organizes all research data relationally and provides the functions and features for conducting agronomic, or plant research trials. This is the “core” of AGROBASE Generation II, and all the other optional modules may be licensed according to the requirements of the user’s research program.
Prevent unauthorized access to your data via a security and password system.
Assign users to a local area network for concurrent access to the “research groups” (relational data base system).
Develop your own import ‘profiles’ for fast and efficient import of data in similar files.
Import and export research data for different file types (Microsoft Excel®, ASCII text, Lotus® 1-2-3 files, FoxPro®, dBASE® and more)
Directly access and process external FoxPro® or dBASE® files, and text files.
Efficient import of experiments individually or as a group, multi-location trials, variety or treatment lists, or even just means from external analyses.
Direct and efficient export of data for experiments, trials, locations, years, and more, as Excel® spreadsheets and other file types.
Define data traits (numeric, float, date, character, logical) uniquely for your research program with your trait names.
Import or export lists of traits between research groups.
Define and then re-name globally as needed all traits, locations, and treatments for your research program.
View traits always in one or more pre-assigned order or grouping – your “master trait order” lists.
Define pick-lists for data entry for character or test traits – such as “round”, “oblong”, “red”, “violet”, etc.
Define your own measurement scales, such as average coefficients of infection (ACI) for disease reactions, and categorical scales.
Maintain data integrity by “locking” traits as read-only or hiding them from viewing.
Internationalize the interface – enter your own names or words in another language for buttons, tabs, checkboxes, and more.
Enter notes for each trait in each experiment – who took the data, conditions at the time, other observations, and even print as a report.
Access data immediately with a simple “point-and-click” in the research data explorer tree. No need to search for file names – just click on the experiment or trial’s icon.
View all data for any given treatment (hybrid, variety, etc.), or group of treatments, or all data at a given location or in a given year from the relational research data explorer with only a few mouse-clicks.
Instantly list all the plots, experiments, and nurseries that any treatment was planted in.
Enter and edit data in a spreadsheet-like format. Numerous tools to re-size and re-order fields, sort, query, view via a spilt-screen, and more.
Sort data by up to five sort levels.
Data validation via user-defined colors for out of bounds data for each trait, upon data entry or subsequent viewing.
Perform calculations with calculated traits that can be saved and used repeatedly throughout the system.
A master treatment management system lets you sort, group, create indexes, do reports, and much more for any or all of your treatments in your research program.
Store “static” traits (descriptors or attributes) of treatments, such as genetic origin, color, disease resistance or susceptibility, maturity group, or even the presence or absence of a QTL or a specific molecular marker for a given genotype.
Store static traits for locations, such as soil type, fertility, irrigation, plot size, etc.
Create selection indices or query data based on both dynamic and static traits, or correlate phenotypic data with molecular marker data.
Customize your research group by changing the system settings to reflect your field names and options for experimental designs, viewing data, etc.
Randomized complete block (RCBD) with and without repeating checks, square and rectangular lattice, lattice squares, split-plot, split-split-plot, strip plot, factorial with 2 to 4 factors, Latin square, Latin rectangle, group-balanced block, group-unbalanced block, non-replicated with repeated checks, and non-replicated grid layout with repeated checks experimental designs.
Maximum of 64,000 plots per experiment per location, depending upon the design.
Flexibility to swap treatments, remove blocks, substitute fillers for planting errors, and more, upon randomization.
Create and support perennial experiments by adding years to existing experiments and viewing data down years or across plots.
Sub-sampling with up to 999 sub-samples per experimental unit with calculations for mean, sum, variance, kurtosis, skewness, and more, also for un-equal sub-sampling.
Logically group treatments, checks, experiments, trials, and locations for efficient generation of trials and to reflect your research program.
Drag and drop of experiment names to develop hierarchies of grouped experiments on the research tree explorer.
Relationally link static treatment and location traits to each treatment in each experiment as desired.
Manage descriptive information for each experiment, trial, trait, treatment or location in the system.
Instantly view the status of your research program - the number of experiments, treatments, trials, variables, locations, and total data points currently present.
Generate a quick report or list for all or a group of experiments by design, location, year, or name of experiment.
Generate labels and reports to design virtually any type of label (also vertical), report, or field book. Save as a PDF® file, MS-Word® document or other file type.
Generate bar codes for Code 3 of 9, Interleaved 2 of 5, and Code 128 bar codes.
Print most or all of your field books or labels at one time from your logical grouping of experiments.
Visually create field planting plans by “drag and drop” from the research explorer tree in Cartesian or serpentine order, with different types of planters, for any spatial arrangement of experiments.
Generate sowing order lists and harvest order number for serpentine, Cartesian, moving spiral, shrinking spiral, double shrinking spiral, and front-to-back harvesting orders.
Manage field plans for even hundreds of experiments for many sites and locations from past years via selection lists, grouping, and hiding from view or access.
Develop experiment “traits” for experiment management practices, such as fungicide and herbicide application dates and rates, sowing date, irrigation, previous crop, etc. Develop specific experiment management reports, or even protocol reports.
The following are available for the Basic System, see the Advanced Statistics Module for further data analyses with more statistical routines.
Analyze balanced and orthogonal designs using linear models with main effects, interactions and nesting. Missing plot solutions for some designs.
Analyze square or rectangular lattices, with or without repetition of the basic design.
Analyze lattice squares.
Perform hundreds or more of ANOVAs all at once with a few keystrokes – such as 30 traits for 20 locations for the same multi-location trial (600 ANOVAs).
Automate data analysis for single ANOVAs for experiments, trials, experiment groups – or all your data for an entire year – via the ‘multiple single ANOVAs’ interface.
Analyze data by trait groups.
Analyze non-replicated or strip trials via moving means linear, quadratic, or row x column adjustment algorithms.
Means separation with LSD and Duncan’s Multiple Range Test.
Save analyses output as PDF®, MS-Word®, or HTML files, or send to your printer.
Means and summary statistics are automatically stored upon analysis for multiple or single factors such as for entries in yield trials. Immediately accessible by clicking on the means icon beneath the experiment or trial icon on the explorer tree.
Export means and even summary statistics to Excel®, dBASE®, or other formats.
Generate reports with means, ranks, and more for an individual experiment or a multi-location experiment. You can also include static traits for the treatments for more comprehensive reports.
Trait means can be displayed as percent of a check, percent of trial mean. percent of any variety or even sub-set of varieties or checks, or by rank.
Select or group varieties for the next cycle of testing by creating selection indices as part of the stored means.
Analysis of covariance.
Multiple regression.
Correlation.
View descriptive statistics, frequencies, and histograms.
Perform student's univariate t-test, and non-parametric statistics including Friedman's test for 2-way classification and Spearman's rank correlation.
Dynamic and direct link to GenStat® for additional and advanced statistical analyses, such as mixed model or REML analyses. Means stored for some designs in Generation II, using special GenStat library routines.
The Basic System offers many tools to expedite the transfer of data between Generation II and external file systems such as spreadsheets and database files.
The features below add to those capabilities by directly writing to, and reading from, selected personal data assistants (PDAs) to Generation II, making data transfer seamless and efficient.
Requires hand-held PCs or Palmtops® currently running under Palm OS 3.5® or better, with HotSync® Version 3.01 or higher, and about 5mb free main memory. Examples: Tungsten E® or Zire 31®.
In addition, supports the Pocket PC® 2003 and Pocket PC® 2003 SE under Windows Mobile 5® and WinCE.Net®. We recommend that you test Generation II with your PDA to ensure acceptable performance in data transfer. The Pocket PC implementation requires about 5MB of memory to install and the ActiveSync® 3.5 or higher.
A maximum of 20,000 plots and up to 18 traits, for at most 360,000 data points, may be processed per upload or download at one time for the Palm OS® version. The Pocket PC® version is limited to 1500 plots at a time, and 27,000 data-points.
For perennial experiments, any year, but only one year at a time can be uploaded.
Sub-sample data may be uploaded and downloaded as well for experiments and nurseries.
You can select a multi-location trial or any group of experiments so that your upload will include experiments across many locations.
For even more flexibility, you can access a planting plan for a site and upload some or all of the experiments in that site or location.
Nurseries may also be uploaded or downloaded.
Data integrity is maintained via a data point colour scheme upon downloading, to prevent incorrect overwriting of current data and verify downloading of new data.
