Decoding Sorghum Root System Architecture for Resource Use Efficiency and Climate Resilience Under Multifactorial Stress Conditions.

Abstract

Climate-induced challenges, such as drought and nutrient depletion, are increasingly constraining global crop production, threatening food and nutritional security. Sorghum bicolor (L.), a climate-resilient cereal, demonstrates strong adaptive potential under resource-limited conditions due to its robust root system architecture (RSA). While above-ground improvements have received significant attention, the role of RSA in enhancing resource-use efficiency (RUE), particularly water use efficiency (WUE) and nitrogen use efficiency (NUE), remains underexploited in breeding programs. This review explores the physiological and molecular roles of sorghum RSA traits (e.g., root depth, density, branching pattern, and root angle) in improving RUE under abiotic stress. It highlights advances in multi-omics approaches, including transcriptomics, proteomics, and genome-wide association studies (GWAS), which provide insights into the genetic regulation of root development. High-throughput phenotyping platforms, including 2D, 3D, and emerging 4D imaging techniques, are evaluated for their effectiveness in capturing dynamic root traits and informing selection strategies. Sorghum's RSA offers a functional model for developing climate-resilient cultivars with improved WUE and NUE. The integration of modern phenotyping techniques with molecular insights and multi-omics strategies will expedite the identification of critical genetic and physiological determinants of RSA characteristics. This synthesis underscores the potential of RSA-targeted breeding strategies to enhance crop productivity and sustainability in water-and nutrient -constrained environments, aiding sustainable intensification and global food security in the face of climate change challenges.

Plant phenotyping relevance

ソルガム根系形態の表現型計測を扱うレビューであり、2D・3D・4D画像による高スループット表現型解析手法を評価しているため、方法レビューとして中心的です。

Code and data availability

The supplied blocks are from a review article on sorghum root system architecture. No public phenotype datasets, root images, sensor/3D inputs, author analysis code, trained models, or supplements containing such assets are mentioned; all cited studies are prior work, and no data or code availability statements appear.

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