Abstract
Key messageDespite phenotyping the training set under unfavorable conditions on smallholder farms in Madagascar, we were able to successfully apply genomic prediction to select donors among gene bank accessions.Poor soil fertility and low fertilizer application rates are main reasons for the large yield gap observed for rice produced in sub-Saharan Africa. Traditional varieties that are preserved in gene banks were shown to possess traits and alleles that would improve the performance of modern variety under such low-input conditions. How to accelerate the utilization of gene bank resources in crop improvement is an unresolved question and here our objective was to test whether genomic prediction could aid in the selection of promising donors. A subset of the 3,024 sequenced accessions from the IRRI rice gene bank was phenotyped for yield and agronomic traits for two years in unfertilized farmers’ fields in Madagascar, and based on these data, a genomic prediction model was developed. This model was applied to predict the performance of the entire set of 3024 accessions, and the top predicted performers were sent to Madagascar for confirmatory trials. The prediction accuracies ranged from 0.10 to 0.30 for grain yield, from 0.25 to 0.63 for straw biomass, to 0.71 for heading date. Two accessions have subsequently been utilized as donors in rice breeding programs in Madagascar. Despite having conducted phenotypic evaluations under challenging conditions on smallholder farms, our results are encouraging as the prediction accuracy realized in on-farm experiments was in the range of accuracies achieved in on-station studies. Thus, we could provide clear empirical evidence on the value of genomic selection in identifying suitable genetic resources for crop improvement, if genotypic data are available.
Highlights
The demand for rice in sub-Saharan Africa (SSA) is increasing steadily, outpacing local supply, and forcing many Africa countries to import increasing amounts of rice from Asia (USDA 2018)
For the selection from year 1 to year 2, the GBLUP model (Eq 4) was applied to each site (Anjiro and Behenjy) and for each trait (STW and total panicle dry weight (TPW)) independently, and predicted genotypic values (PGVs) and expected improvement" (EI) were calculated for all untested accessions to select top 20 accessions for each criterion-site-trait combination
The selection based on PGV and EI from year 2 to year 3 showed a large overlap, and in total 52 accessions were selected for TPW
Summary
The demand for rice in sub-Saharan Africa (SSA) is increasing steadily, outpacing local supply, and forcing many Africa countries to import increasing amounts of rice from Asia (USDA 2018). The national average yield remains below 3 t ha−1, whereas achievable on-farm yields can exceed 7 t ha−1 (Saito et al 2017) and are comparable to tropical regions elsewhere This large yield gap highlights that conventional on-station breeding approaches that seek to select breeding lines with high yield potential under “ideal” high-input conditions may not produce desired results. The prevalence of traditional rice varieties throughout Madagascar (Minten and Barrett 2008) is a further sign that plant breeding has not properly addressed the needs of the mostly resource-poor smallholder farmers It is indicative of specific adaptations to lower soil fertility being present in such traditional varieties, which were found to be more efficient in P acquisition (Mori et al 2016) and internal P utilization (Wissuwa et al 2015) or may even show a combination of both desirable traits (Rose et al 2015). A future breeding program targeting to close this yield gap may move the selection process from highly fertilized breeding stations to fields representing conditions a crop may experience in farmers’ fields and should attempt to utilize any adaptive traits of traditional varieties
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
