Evolutionary breeding for sustainable agriculture: Selection and multi-environmental evaluation of barley populations and lines

• Published in: Field crops research Vol. 204; pp. 76 - 88
• Main Authors: Raggi, Lorenzo, Ciancaleoni, Simona, Torricelli, Renzo, Terzi, Valeria, Ceccarelli, Salvatore, Negri, Valeria
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15-03-2017
• Subjects: Barley; Evolutionary breeding; GxE interaction; Sustainable agriculture; Yield stability; CCP; Barley; PPs; OA; EBP; Sustainable agriculture; GxE interaction; Yield stability; LI; Evolutionary breeding
• ISSN: 0378-4290; 1872-6852
• DOI: 10.1016/j.fcr.2017.01.011

•Evolutionary Breeding Program (EBP) successful in selecting materials for sustainable agriculture.•EBP materials (both populations and lines) out yielded some of the best controls under LI.•In low productive trials the EBP materials out yielded the recently developed lines, used as controls, on average.•The two EBP populations and four EBP lines showed the best combination of grain yield and both dynamic and static stability.•Breeding for OA and LI should be carried out under the same management system.
Varieties specifically bred for organic and low-input agriculture are presently lacking. A strategy to develop them is evolutionary breeding that relies on a combination of natural and artificial selection. This study investigated the ability of an evolutionary breeding program, carried out over 24 years, to select barley (Hordeum vulgare L.) heterogeneous populations and lines characterized by high grain yield and yield stability across different environments under organic and low-input conditions. A Composite Cross population (named AUT DBA) was initially developed by crossing Parental Populations highly productive under low-input conditions in Central Italy and diverse for several morpho-phenological traits. The AUT DBA was then multiplied for nine years under a low-input management system without any artificial selection.
Three cycles of artificial selection (from 2007/08 to 2009/10) were conducted by selecting within the AUT DBA plants characterized by high grain yield potential and a favourable combination of traits relevant for organic and low-input agriculture.
A new population (a lines mixture named mix48) was then developed by mixing the highest yielding and the most diverse lines; 13 lines were also selected. AUT DBA, mix48 and the 13 lines were evaluated for four successive years in multi-environmental trials carried out under different pedo-climatic conditions and management systems (organic and low-input) and using nine different lines, selected under high input conditions, as controls.
For each of the 24 entries (i.e. the two populations, the 13 selected lines and the nine controls) grain yield was recorded, and yield stability evaluated by using AMMI analysis, Shukla’s stability variance and Environmental variance. Average yield and yield stability indexes were calculated over all Environments and for low and high productive Environments, respectively. Finally, the effects on yield of climatic and soil characteristics were evaluated by using a reduced rank factorial regression analysis.
The grain yield of the AUT DBA and mix48 populations were significantly higher than four of the nine controls. On average, the two populations and the lines selected from them significantly out-yielded the recently developed lines in low-productive trials (P≤0.05), while no significant differences were detected in the high-productive trials. Across all the tested Environments, the populations showed a higher level of dynamic stability than the controls; six selected lines were also as stable as the populations. The two heterogeneous populations and four of the selected lines, showing the best combination of grain yield and both dynamic and static stability, could be recommended for use in Central Italy under organic and low-input management systems. The main conclusion of this work is that evolutionary breeding is indeed a low-cost and effective approach to develop both populations and lines for sustainable agriculture especially when carried out under low-input conditions.