Republish

We encourage you to republish this article online and in print, it’s free under our creative commons attribution license, but please follow some simple guidelines:
  1. You have to credit our authors.
  2. You have to credit SciDev.Net — where possible include our logo with a link back to the original article.
  3. You can simply run the first few lines of the article and then add: “Read the full article on SciDev.Net” containing a link back to the original article.
  4. If you want to also take images published in this story you will need to confirm with the original source if you're licensed to use them.
  5. The easiest way to get the article on your site is to embed the code below.
For more information view our media page and republishing guidelines.

The full article is available here as HTML.

Press Ctrl-C to copy

[NAIROBI] Scientists have shown that it is possible to speed up banana breeding through genomic prediction models, giving potential hope to banana breeders and smallholders in East Africa.
 
Banana, according to Moses Nyine, a research scientist at the International Institute of Tropical Agriculture, Uganda, and a co-author of the study, is an important staple crop for millions of people in Sub-Saharan Africa, especially those in East Africa.

“Breeders will increase the breeding efficiency by reducing the cost and time required to deliver high-yielding and disease-resistant varieties to farmers.”

Moses Nyine, The International Institute of Tropical Agriculture, Uganda

In a study published in The Plant Genome last month (2 March), researchers collected data on 15 key traits from 307 banana types that were grown in two fields in Uganda under low and high input field management conditions for two crop cycles from 2013 to 2016. The traits were grouped into five categories: plant stature, suckering behaviour, black leaf streak resistance, fruit bunch and fruit filling.
 
The DNA differences between the bananas were mapped. The researchers assessed the ability of six genomic prediction models to use cross-validation to identify the bananas with the best traits.
 
“The results demonstrate that genomic prediction is possible in banana breeding and the prediction accuracy can be improved by using models based on data from many different environments,” says Nyine.
 
Researchers found the accuracy of genomic prediction to be above 75 per cent.  

“Breeders will increase the breeding efficiency by reducing the cost and time required to deliver high-yielding and disease-resistant varieties to farmers,” adds Nyine, who is also a doctoral student at Palacký University in the Czech Republic. “Banana breeding is a lengthy and costly process, taking up to 20 years to deliver improved varieties to farmers”.
 
Smallholders, he explains, will be assured of food security and income despite the numerous pests, diseases and environmental stresses affecting banana in Africa.
 
Paul Kimani, a professor of plant breeding and genetics from Kenya’s University of Nairobi, tells SciDev.Net that the study demonstrates simultaneous selection of multiple traits of importance not only to farmers but also to other actors along the value chain.
 
But much more needs to be done to assess performance of the new varieties on the farm and in the market place, according to Kimani. He tells SciDev.Net, “One point that molecular breeders often overlook is that shortening time to develop a new variety is somewhat exaggerated. For instance, this study suggests that it will take about three to five years to develop hybrids using integrated genomic selection compared with 11-14 years for conventional breeding.
 
“But in reality the period is likely to be about eight to 13 years with genomic selection because the new hybrids still need multi-location and on-farm evaluation: an additional three to four years, and probably another year of sensory evaluation and [consumer] acceptability studies.”
 
This piece was produced by SciDev.Net’s Sub-Saharan Africa English desk.

References

Moses Nyine and others Genomic Prediction in a multiploid crop: Genotype by environment interaction and allele dosage effects on predictive ability in banana (The Plant Genome, 2 March 2018)

Related topics