Conventional and Modern Breeding Strategies for Cassava Improvement: A Review of Controlled Hybridization to Genomic Selection

Abstract

Cassava ( Manihot esculenta Crantz) is a vital tropical root crop that underpins food security, livelihoods, and industrial development for over 800 million people globally, particularly in sub-Saharan Africa. Its resilience to drought and adaptability to marginal environments make it a strategic crop under climate change. However, cassava improvement remains constrained by biological and genetic complexities, including high heterozygosity, clonal propagation, long breeding cycles, and strong genotype × environment (G×E) interactions. Conventional breeding approaches, such as controlled hybridization and phenotypic selection, have historically contributed to yield improvement and disease resistance but are limited by low selection accuracy for polygenic traits and slow genetic gain. Recent advances in molecular genetics and genomics have transformed cassava breeding through the adoption of marker-assisted selection (MAS), genomic selection (GS), and genome-wide association studies (GWAS). These approaches enable the identification of quantitative trait loci (QTLs), prediction of breeding values, and dissection of complex trait architecture, thereby enhancing selection efficiency and accelerating breeding cycles. Statistical tools such as genomic best linear unbiased prediction (G-BLUP), additive main effects and multiplicative interaction (AMMI), and genotype plus genotype-by-environment interaction (GGE) biplot analysis have further improved genotype evaluation and stability analysis across diverse environments. Recent studies demonstrate that genomic selection can reduce cassava breeding cycles from approximately five years to two years while increasing genetic gain. Emerging technologies, including genome editing, high-throughput phenotyping, and artificial intelligence, offer additional opportunities for precision breeding. This review critically synthesizes conventional and modern cassava breeding strategies, highlighting their strengths, limitations, and integration into efficient breeding pipelines. The paper emphasizes the need for data-driven, multi-disciplinary approaches to develop climate-resilient, high-yielding, and quality cassava varieties for sustainable agricultural systems.