Low-temperature stress is considered as the major abiotic constraint limiting plant’s growth and the potential land cultivation. Crop adaptation to limiting temperature is thus an important breeding objective because it determines yield stability in environment-friendly cultivation practices. Conventional breeding methods had limited success in improving the cold tolerance of important crop plants because of the complexity of stress tolerance traits, low genetic variance, and lack of efficient selection criteria. The knowledge of physiology, of genetics, and of the DNA technology has improved substantially nowadays, and these advancements will allow the breeder to predict the breeding value of best genotypes by using physiology, genetics, and molecular information. The perspective for selecting more effectively cold-tolerant crops will involve efficient genotyping, reliable phenotyping and envirotyping, and adequate statistical models.
Frascaroli, E. (2018). Breeding Cold-Tolerant Crops. Switzerland : Springer Nature [10.1007/978-3-030-01415-5_9].
Breeding Cold-Tolerant Crops
Frascaroli, Elisabetta
2018
Abstract
Low-temperature stress is considered as the major abiotic constraint limiting plant’s growth and the potential land cultivation. Crop adaptation to limiting temperature is thus an important breeding objective because it determines yield stability in environment-friendly cultivation practices. Conventional breeding methods had limited success in improving the cold tolerance of important crop plants because of the complexity of stress tolerance traits, low genetic variance, and lack of efficient selection criteria. The knowledge of physiology, of genetics, and of the DNA technology has improved substantially nowadays, and these advancements will allow the breeder to predict the breeding value of best genotypes by using physiology, genetics, and molecular information. The perspective for selecting more effectively cold-tolerant crops will involve efficient genotyping, reliable phenotyping and envirotyping, and adequate statistical models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.