Genetic progress in cowpea [Vigna unguiculata (L.) Walp.] stemming from breeding modernization efforts at the International Institute of Tropical Agriculture.
Patrick Obia OngomChristian FatokunAbou TogolaIbnou DiengStella SalvoBrian GarduniaSaba Baba MohammedOusmane BoukarPublished in: The plant genome (2024)
Genetic gain has been proposed as a quantifiable key performance indicator that can be used to monitor breeding programs' effectiveness. The cowpea breeding program at the International Institute of Tropical Agriculture (IITA) has developed and released improved varieties in 70 countries globally. To quantify the genetic changes to grain yield and related traits, we exploited IITA cowpea historical multi-environment trials (METs) advanced yield trial (AYT) data from 2010 to 2022. The genetic gain assessment targeted short duration (SD), medium duration (MD), and late duration (LD) breeding pipelines. A linear mixed model was used to calculate the best linear unbiased estimates (BLUE). Regressed BLUE of grain yield by year of genotype origin depicted realized genetic gain of 22.75 kg/ha/year (2.65%), 7.91 kg/ha/year (0.85%), and 22.82 kg/ha/year (2.51%) for SD, MD, and LD, respectively. No significant gain was realized in 100-seed weight (Hsdwt). We predicted, based on 2022 MET data, that recycling the best genotypes at AYT stage would result in grain yield gain of 37.28 kg/ha/year (SD), 28.00 kg/ha/year (MD), and 34.85 kg/ha/year (LD), and Hsdwt gain of 0.48 g/year (SD), 0.68 g/year (MD), and 0.55 g/year (LD). These results demonstrated a positive genetic gain trend for cowpea, indicating that a yield plateau has not yet been reached and that accelerated gain is expected with the recent integration of genomics in the breeding program. Advances in genomics include the development of the reference genome, genotyping platforms, quantitative trait loci mapping of key traits, and active implementation of molecular breeding.
Keyphrases
- genome wide
- dna methylation
- climate change
- copy number
- molecular dynamics
- quality improvement
- clinical trial
- systematic review
- randomized controlled trial
- healthcare
- single cell
- public health
- body mass index
- gene expression
- physical activity
- electronic health record
- high throughput
- machine learning
- study protocol
- cancer therapy
- phase ii
- artificial intelligence