HYBRID APPROACHES IN PLANT BREEDING: COMBINING GENOMICS, BIOTECHNOLOGY, AND TRADITIONAL KNOWLEDGE FOR GLOBAL FOOD SYSTEMS

Abstract

 This study explores an integrated approach in which genetics, biotechnology and traditional knowledge are combined to transform food production in the world through plant breeding approaches.  Genomic sequencing, QTL mapping, and CRISPR-based assays with participatory ethnographic methodologies assisted us in discovering what farmers desired and how they bred plants.  A randomized complete block study using field research across multiple seasons generated quantitative phenotypic data, which included yield, water-use efficiency, and indicators of stress tolerance.  Application of the traditional knowledge as covariate in genotype environment interaction models displayed a significant correlation between attributes as indicated by the farmer and the heritability estimates that were statistically determined.  State-of-the-art machine learning models, in particular XGBoost with SHAP-based interpretability, demonstrated high predictive capability and demonstrated interaction between genetic and cultural factors.  Multivariate analysis (PCA and clustering) showed that there were unique genetic variation patterns which could be grouped with the varietal types as defined by the farmers.  Cultural significance of specific qualities was also supported by thematic analysis of qualitative narratives and ensured that technological improvements did not become socially or ecologically detached.  The combined results suggest that hybrid plant breeding strategies can significantly enhance the resilience, productivity, and flexibility of agriculture toward climate change and that such strategies will also guarantee an engagement and acceptance of farmers.  This research presents a viable and replicable methodological approach that incorporates molecular science and traditional bodies of knowledge and therefore improving the world food security and sustainability.