Plant breeding software

Germplasm: every accession, line and variety with its origin and attributes. Pedigrees: parent-offspring relationships across generations, which underpin genetic relationship matrices in analysis. Crossing: planning crosses, recording pollinations and tracking seed lots.

Trials: experimental designs, plot layouts, field books and trait observations across environments. Genotypes: marker data linked to each line. Analysis and selection: estimating breeding values, ranking lines and recording advancement decisions.

Breedbase is an open-source breeding database developed at the Boyce Thompson Institute and used by public breeding projects for crops including cassava, yam and banana. The Breeding Management System, from the Integrated Breeding Platform, provides pedigree, trial and analysis modules. Field Book is a free Android app for collecting phenotypes in the field that exports to these databases.

BrAPI, the Breeding API, is an open standard that lets these tools exchange data, so a programme can mix applications without manual file conversion. When evaluating any product, check BrAPI compatibility.

Genomic selection predicts a line's breeding value from DNA markers using a model trained on lines with both genotypes and field data. It shortens breeding cycles by allowing selection before full field testing. Breeding software supports this by keeping genotypes and phenotypes linked to the same identifiers; the statistics are then run in tools such as R or ASReml.

Breeding is a logistics operation as much as a scientific one. Each season, seed must be packed for hundreds or thousands of plots across many locations, labelled correctly and shipped on time. Breeding software links seed lots to germplasm records and trial designs so packing lists, barcode labels and planting maps can be generated directly from the plan. When seed is harvested, new lots are created and connected to their parent plots, preserving traceability. Errors here — a mislabelled packet or a swapped plot — can invalidate a season's data, so barcode scanning at every handling step is one of the most valuable features a programme can adopt.

Phenotyping — measuring traits such as height, flowering date, disease score and yield — is often the bottleneck. Tablet apps such as Field Book speed up manual scoring and reduce transcription errors. High-throughput approaches use drones, sensors and imaging to collect data across many plots, generating large datasets that breeding software must store with plot identifiers and timestamps. Whatever the method, define each trait precisely — method, scale and unit — so values remain comparable across years and teams.

The end purpose of breeding software is better selection decisions. Useful features include selection indices that combine several traits with economic weights, side-by-side comparison of candidate lines with checks, and records of why each line was advanced or dropped. Recording decisions creates institutional memory and allows programmes to evaluate, years later, whether their selection strategy delivered genetic gain.

Public programmes often choose open platforms for cost and data sharing. Commercial seed companies weigh vendor support, security and integration with their own laboratory and genomics pipelines. In both cases, confirm data export and API access before committing.

Germplasm: the genetic material — seeds, lines, accessions — a programme works with. Pedigree: the record of a line's ancestry. Phenotype: observed traits. Genotype: DNA marker data. Breeding value: an estimate of an individual's genetic merit as a parent. Genetic gain: the improvement in a trait per breeding cycle. Check variety: an established variety included in trials for comparison. Selection index: a weighted combination of traits used to rank candidates.

A typical season starts by selecting entries and designing trials, then generating seed packing lists, labels and field maps. During the season, field staff record observations on tablets that sync to the database. After harvest, yield and quality data are uploaded, analysed with mixed models, and breeding values are written back to each line. The breeding team reviews rankings, records advancement decisions, and plans next season's crosses from the selected parents. Each step reads from and writes to the same records, so nothing is retyped.

Because every record carries the same identifiers, the programme can later trace any released variety back through its trials, crosses and parents — the audit trail that regulators, partners and future breeders depend on.

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