Integrating speed breeding with artificial intelligence for developing smart varieties

Introduction Global climate changes have severely impacted agricultural productivity worldwide. The severe repercussions of climate change range from extreme temperatures (high and low), excess sunlight, and elevated CO2 altering rainfall’s geographical nature, making crops more prone to disease (Wang et al., 2018). Several researchers have well-advocated climate change has become a prime aspect that tremendously affects plant growth, development, and productivity by provoking biotic and abiotic stresses (Hasegawa et al., 2018). The conventional plant breeding approach has been the saviour for ensuring food and nutritional security worldwide. It does it by strengthening genetic diversity and unravelling novel genes (Ahmar et al., 2020). The gain in genetic diversity and identification of novel genes through classical breeding is a time-consuming process involving hybridization/inter-crossing of elite/wild cultivars with common landraces (Al-khayri et al., 2015). The new crop varieties developed through the classical breeding approach possess superior agronomic traits that help increase their yield potential and stress resilience. Speed breeding technology has emerged as a versatile suite for manipulating the growing environment of crop plants to accelerate their breeding generation by enhancing the rate of flowering and seed set under the influence of AI (Razzaq et al., 2021). In addition, speed breeding instigates rapid generation advancement via reducing breeding time and resources by accelerating essential cellular and metabolic processes (Ghosh et al., 2018).