4.5 Article Proceedings Paper

Current status and future scenarios of hemp breeding

期刊

EUPHYTICA
卷 140, 期 1-2, 页码 121-131

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SPRINGER
DOI: 10.1007/s10681-004-4760-0

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genetic advances; hemp germplasm; improved varieties; key genes; metabolic pathways; multi-use crop

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Hemp is a multi-use crop, able to provide fiber, cellulose, seeds and seed oil, cannabinoid, and biomass. Integrating many agroindustrial chains, Cannabis is considered a. crop model in which insights into specific metabolic pathways and biosynthetic processes are valuable for improvement. of the plant for all sets of industrial derivatives. In this review the hemp breeding status is elucidated and many aspects are focused: (i) recovering, maintenance and characterization of genetic resources; (ii) widening of germplasm and genetic. variability; (iii) marker-assisted selection and development of breeding programs; (iv) sexual differentiation; (v) monitoring of THC content. Modem hemp varieties for fiber and other specific end uses have been developed and new varieties are entering production. The scenario for the breeding advances in hemp relies on basic and applied research which provides insights to identify a strategy for the design of modified plants with enhanced performance. This is accounted by the dissection of traits into components and the modification of single steps of the related metabolic pathways. These advances are provided by genomic techniques and are able: (i) to identify key genes encoding enzymes and regulatory factors participating in cannabinoid, fiber and oil biosynthesis; (ii) to identify the mode of regulation of these genes; (iii) to characterize the function of the selected genes through higher, lower or specific expression incited by specific promoters. The identification of molecular markers for specific traits, gathered in a saturated linkage map, will have a remarkable impact on hemp breeding. The advances in basic and applied research make it possible to design methods for the identification of superior parents and cross combinations and the development of selection schemes that rely on less labour-intensive and time-consuming methods.

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