RESUMO
The advent of modern tools in agricultural experiments, digital data collection, and high-throughput phenotyping have necessitated field plot labels that are both machine- and human-readable. Such labels are usually made with commercial software, which are often inaccessible to under-funded research programs in developing countries. The availability of free fit-for-purpose label design software to under-funded research programs in developing countries would address one of the main roadblocks to modernizing agricultural research. The goal was to develop a new open-source software with design features well-suited for field trials and other agricultural experiments. We report here qrlabelr, a new software for creating print-ready plot labels that builds on the foundation of an existing open-source program. The qrlabelr software offers more flexibility in the label design steps, guarantees true string fidelity after QR encoding, and provides faster label generation to users. The new software is available as an R package and offers customizable functions for generating plot labels. For non-R users or beginners in R programming, the package provides an interactive Shiny app version that can be launched from R locally or accessed online at https://bit.ly/3Sud4xy. The design philosophy of this new program emphasizes the adoption of best practices in plot label design to enhance reproducibility, tracking, and accurate data curation in agricultural research and development studies.
Assuntos
Agricultura , Software , Agricultura/métodos , Humanos , Interface Usuário-ComputadorRESUMO
Genetic diversity is fundamentally important in crop improvement and provides plants with the capacity to meet the demands of changing environments. This work was carried out to assess the diversity and the extent of genetic relatedness among a number of assembled cassava (Manihot esculenta Crantz) accessions. We conducted a microsatellite marker analysis of 89 cassava accessions collected from Ghanaian and exotic sources. These accessions were assayed using 35 simple sequence repeat (SSR) markers. A total of 167 alleles were detected from 35 polymorphic markers with an average of 4.77 alleles per locus. High allelic frequency was detected across the accessions, ranging from 0.32 to 0.99 with an average of 0.62 per marker. Observed heterozygosity ranged from 0.03 - 0.97 across the accessions. Polymorphism information content (PIC) ranged from 0.03 to 0.78 with a mean of 0.45, indicating high level of polymorphism across the accessions. Comparatively, higher number of alleles, gene diversity and observed heterozygosity were detected among the local accessions compared with the exotic accessions indicating rich genetic diversity among them. Population structure analysis based on STRUCTURE identified two subpopulations and a large number of admixtures. Cluster analysis based on the neighbour joining algorithim further separated the collection into seven sub-groupings irrespective of geographical origin. This indicates the possible sharing of common genomic regions occurring across the accessions. High allelic frequency differences and levels of heterozygosity were observed among the germplasm. These findings indicated significant genetic variability in the germplasm to warrant selection.
RESUMO
Multi-parent advanced generation inter-cross (MAGIC) populations are an emerging type of resource for dissecting the genetic structure of traits and improving breeding populations. We developed a MAGIC population for cowpea (Vigna unguiculata L. Walp.) from eight founder parents. These founders were genetically diverse and carried many abiotic and biotic stress resistance, seed quality and agronomic traits relevant to cowpea improvement in the United States and sub-Saharan Africa, where cowpea is vitally important in the human diet and local economies. The eight parents were inter-crossed using structured matings to ensure that the population would have balanced representation from each parent, followed by single-seed descent, resulting in 305 F8 recombinant inbred lines each carrying a mosaic of genome blocks contributed by all founders. This was confirmed by single nucleotide polymorphism genotyping with the Illumina Cowpea Consortium Array. These lines were on average 99.74% homozygous but also diverse in agronomic traits across environments. Quantitative trait loci (QTLs) were identified for several parental traits. Loci with major effects on photoperiod sensitivity and seed size were also verified by biparental genetic mapping. The recombination events were concentrated in telomeric regions. Due to its broad genetic base, this cowpea MAGIC population promises breakthroughs in genetic gain, QTL and gene discovery, enhancement of breeding populations and, for some lines, direct releases as new varieties.
