Skip to main content
ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #429094
Research Project: The Triticeae Toolbox (T3) - Breeding Process and Data Facilitation to Accelerate Genetic Gain and Discovery

Location: Plant, Soil and Nutrition Research

Title: The potential of phenomic selection for the joint Ethiopian malt barley breeding program

Author
item SETOTAW, TESFAHUN ALEMU - Cornell University
item WILDE, PETER - Kws Saat Ag
item BERNAL VASQUEZ, ANGELA MARIA - Kws Saat Ag
item GEBRETSADIK, REBEKA - Addis Ababa University
item LAKEW, BERHANE - Addis Ababa University
item SHIFERAW, TIGIST - Addis Ababa University
item DIFABACHEW, YOHANNES FEKADU - Justus-Liebig University
item Jannink, Jean Luc

Submitted to: The Plant Phenome Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/2/2024
Publication Date: 10/8/2024
Citation: Setotaw, T., Wilde, P., Bernal Vasquez, A., Gebretsadik, R., Lakew, B., Shiferaw, T., Difabachew, Y., Jannink, J. 2024. The potential of phenomic selection for the joint Ethiopian malt barley breeding program. The Plant Phenome Journal. 7:e70003. https://doi.org/10.1002/ppj2.70003.
DOI: https://doi.org/10.1002/ppj2.70003

Interpretive Summary: This study looks at a new, low-cost method called phenomic selection to help choose the best barley plants for farming. Instead of using DNA (like in genomic selection), it uses special light scans—called near-infrared (NIR) spectra—to gather information about the seeds. Scientists tested this method on barley grown in five locations in Ethiopia between 2018 and 2021. The results showed that this technique could accurately predict important traits like when the plant flowers and matures, how tall it gets, seed weight, and how much grain it produces. The predictions were reliable, even when tested on new sets of plants. This shows that phenomic selection could help plant breeders in countries with fewer resources pick better barley varieties without needing expensive tools or tests.

Technical Abstract: Phenomic selection is an alternative approach to genomic selection that uses near-infrared spectra information to predict the performance of genotypes. This research assessed the effectiveness of phenomic selection in barley (Hordeum vulgare L.) using data from 21 trials carried out at Bekoji, Kofele, Holetta, Debre Markos, and Debre Berhane in Ethiopia from 2018 to 2021. Fivefold cross-validation analysis showed robust predictability for traits, ranging from 0.5 to 0.8 for days to heading, days to maturity, plant height, 1000-kernel weight, and grain yield. Days to heading and days to maturity showed similar correlation patterns across the ranges of the wavelengths. Days to heading and 1000-kernel weight were positively and negatively correlated along the range of the wavelength above 1800 nm, respectively. Forward validation using an independent set of genotypes provided predictability above 0.3 for all traits. This result underscores the effectiveness of phenomic selection and its potential application in low-budget, small-scale breeding programs. The study affirmed the Ethiopian barley breeding program could implement phenomic selection as a routine selection tool without extra cost.