Food and Energy Security (Jan 2023)
Approaches and determinants to sustainably improve crop production
Abstract
Abstract Plant scientists and farmers are facing major challenges in providing food and nutritional security for a growing population, while preserving natural resources and biodiversity. Moreover, this should be done while adapting agriculture to climate change and by reducing its carbon footprint. To address these challenges, there is an urgent need to breed crops that are more resilient to suboptimal environments. Huge progress has recently been made in understanding the physiological, genetic and molecular bases of plant nutrition and environmental responses, paving the way towards a more sustainable agriculture. In this review, we present an overview of these progresses and strategies that could be developed to increase plant nutrient use efficiency and tolerance to abiotic stresses. As illustrated by many examples, they already led to promising achievements and crop improvements. Here, we focus on nitrogen and phosphate uptake and use efficiency and on adaptation to drought, salinity and heat stress. These examples first show the necessity of deepening our physiological and molecular understanding of plant environmental responses. In particular, more attention should be paid to investigate stress combinations and stress recovery and acclimation that have been largely neglected to date. It will be necessary to extend these approaches from model plants to crops, to unravel the relevant molecular targets of biotechnological or genetic strategies directly in these species. Similarly, sustained efforts should be done for further exploring the genetic resources available in these species, as well as in wild species adapted to unfavourable environments. Finally, technological developments will be required to breed crops that are more resilient and efficient. This especially relates to the development of multiscale phenotyping under field conditions and a wide range of environments, and use of modelling and big data management to handle the huge amount of information provided by the new molecular, genetic and phenotyping techniques.
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