Field Crop 2024, Vol.7, No.1, 27-36 http://cropscipublisher.com/index.php/fc 31 domesticated varieties. The study of cassava genome from wild ancestors to cultivated varieties helps to understand the genetic improvement of cassava through domestication (Wang et al., 2014). By conducting in-depth research on this genetic connection, we can better understand the genetic characteristics of cassava and provide scientific basis for cassava breeding and improvement. Figure 3 Comparative genomic analysis of different cassava varieties (Wang et al., 2014) Note: a: Venn diagram showing the diversity of SNVs/InDels in the studied cassava genome; b: Chromosome in situ hybridization data, indicating the number and structure of chromosomes in KU50 varieties; c: The CirCOS plot shows the collinearity between the cassava genome region and the assumed homologous regions of the Ricinus communis and Arabidopsis thaliana genomes; d: The gene tree depicts the evolutionary differentiation of cassava from its wild ancestors to cultivated varieties, referencing comparisons with other species in the tung family based on chloroplast gene sequences 3 Breeding Strategies to Address Climate Change Selecting cassava varieties with strong stress resistance is one of the important breeding strategies to address climate change. By using traditional breeding methods, biotechnology methods, and molecular marker assisted selection, new cassava varieties with stronger stress resistance can be cultivated, contributing to ensuring global food security and energy supply. 3.1 Breeding cassava varieties with strong stress resistance The threat of climate change is increasing, especially drought and high temperatures, which can seriously affect crop yield, highlighting the importance of cassava resistance breeding. Improving non biological and biological stress resistance levels in breeding is a key response to these challenges (Snowdon et al., 2020; Cooper and Messina, 2022). The methods and strategies of resistance breeding include applying the "breeder equation" to predict selection responses during the breeding cycle, as well as integrating cross scale trait information from the genome to the ecosystem (Cooper and Messina, 2022). This method has been successfully applied to breeding crops such as temperate corn, and similar methods are also applicable to cassava.
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