genetic base broadening
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2021 ◽  
Vol 12 ◽  
Author(s):  
Channappa Mahadevaiah ◽  
Chinnaswamy Appunu ◽  
Karen Aitken ◽  
Giriyapura Shivalingamurthy Suresha ◽  
Palanisamy Vignesh ◽  
...  

Sugarcane is a C4 and agro-industry-based crop with a high potential for biomass production. It serves as raw material for the production of sugar, ethanol, and electricity. Modern sugarcane varieties are derived from the interspecific and intergeneric hybridization between Saccharum officinarum, Saccharum spontaneum, and other wild relatives. Sugarcane breeding programmes are broadly categorized into germplasm collection and characterization, pre-breeding and genetic base-broadening, and varietal development programmes. The varietal identification through the classic breeding programme requires a minimum of 12–14 years. The precise phenotyping in sugarcane is extremely tedious due to the high propensity of lodging and suckering owing to the influence of environmental factors and crop management practices. This kind of phenotyping requires data from both plant crop and ratoon experiments conducted over locations and seasons. In this review, we explored the feasibility of genomic selection schemes for various breeding programmes in sugarcane. The genetic diversity analysis using genome-wide markers helps in the formation of core set germplasm representing the total genomic diversity present in the Saccharum gene bank. The genome-wide association studies and genomic prediction in the Saccharum gene bank are helpful to identify the complete genomic resources for cane yield, commercial cane sugar, tolerances to biotic and abiotic stresses, and other agronomic traits. The implementation of genomic selection in pre-breeding, genetic base-broadening programmes assist in precise introgression of specific genes and recurrent selection schemes enhance the higher frequency of favorable alleles in the population with a considerable reduction in breeding cycles and population size. The integration of environmental covariates and genomic prediction in multi-environment trials assists in the prediction of varietal performance for different agro-climatic zones. This review also directed its focus on enhancing the genetic gain over time, cost, and resource allocation at various stages of breeding programmes.


2016 ◽  
Vol 15 (6) ◽  
pp. 548-557 ◽  
Author(s):  
Francis Kwame Padi ◽  
Atta Ofori ◽  
Abraham Akpertey

AbstractIntroduction of clones from genetic groups that are underrepresented in the pedigree of commercial cacao varieties in West Africa represents an important aspect of cacao improvement strategy of broadening the genetic base to overcome current yield stagnation of the crop. The objective of the present study was to determine the combining abilities of more recently introduced cacao clones for yield and cropping efficiency in the early bearing years. Seven recently introduced clones were crossed as males to five clones commonly used in the seed gardens in Ghana using a North Carolina II design. The 35 F1 varieties and one commercial variety were evaluated in the field from June 2010 to March 2015 for four traits: increase in trunk cross-sectional area in the juvenile, and in the pod-bearing phases, bean yield and cropping efficiency. Though both GCA and SCA variances were significant for all traits, the ratios of GCA:SCA were much smaller than unity, indicating the importance of non-additive effects in the control of the traits. Among the set of clones therefore, prediction of F1 variety performance cannot be based on the GCA or per se (average) performance of the clones. Six varieties were more precocious, and eight had higher cropping efficiencies than the standard variety. Bean yields ranged from 0.74 to 1.05 t/ha/year in the fourth and fifth years after planting among the top six varieties. The study provides evidence of the large potential for productivity increase through the use of cacao clones beyond Pound's early introductions into West Africa.


PLoS ONE ◽  
2014 ◽  
Vol 9 (9) ◽  
pp. e107781 ◽  
Author(s):  
Mohar Singh ◽  
Ishwari Singh Bisht ◽  
Sandeep Kumar ◽  
Manoranjan Dutta ◽  
Kailash Chander Bansal ◽  
...  

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