In recent decades,genetic advances in yield improvement in the major cereal crops,including wheat,has stagnated or proceeded at a slower rate than is required to meet future global food demand,particularly in the face...In recent decades,genetic advances in yield improvement in the major cereal crops,including wheat,has stagnated or proceeded at a slower rate than is required to meet future global food demand,particularly in the face of climate change.To reverse this situation,and in view of the future climate scenario,there is a need to increase the genetic diversity of wheat to increase its productivity,quality,stability,and adaptation to local agro-environments.The abundant genetic resources and literature are a basis for wheat improvement.However,many species,such as wild relatives,landraces,and old cultivars have not been studied beyond their agronomic characteristics,highlighting the lack of understanding of the physiological and metabolic processes(and their integration) associated with higher productivity and resilience in limiting environments.Retrospective studies using wheat ancestors and modern cultivars may identify novel traits that have not previously been considered,or have been underestimated,during domestication and breeding,but that may contribute to future food security.This review describes existing wheat genetic diversity and changes that occurred during domestication and breeding,and considers whether mining natural variation among wheat ancestors offers an opportunity to enhance wheat agronomic performance,spike architecture,canopy-and organ-level photosynthetic capacity,and responses to abiotic stress,as well as to develop new wheat hybrids.展开更多
High-throughput crop phenotyping,particularly under field conditions,is nowadays perceived as a key factor limiting crop genetic advance.Phenotyping not only facilitates conventional breeding,but it is necessary to fu...High-throughput crop phenotyping,particularly under field conditions,is nowadays perceived as a key factor limiting crop genetic advance.Phenotyping not only facilitates conventional breeding,but it is necessary to fully exploit the capabilities of molecular breeding,and it can be exploited to predict breeding targets for the years ahead at the regional level through more advanced simulation models and decision support systems.In terms of phenotyping,it is necessary to determined which selection traits are relevant in each situation,and which phenotyping tools/methods are available to assess such traits.Remote sensing methodologies are currently the most popular approaches,even when lab-based analyses are still relevant in many circumstances.On top of that,data processing and automation,together with machine learning/deep learning are contributing to the wide range of applications for phenotyping.This review addresses spectral and red-green-blue sensing as the most popular remote sensing approaches,alongside stable isotope composition as an example of a lab-based tool,and root phenotyping,which represents one of the frontiers for field phenotyping.Further,we consider the two most promising forms of aerial platforms(unmanned aerial vehicle and satellites)and some of the emerging data-processing techniques.The review includes three Boxes that examine specific case studies.展开更多
基金the support of Funda??o para a Ciência e a Tecnologia (FCT, Portugal), through the GREEN-IT–Bioresources for Sustainability R&D Unit (UIDB/04551/2020, UIDP/04551/2020)the LS4FUTURE Associated Laboratory (LA/P/0087/2020)+1 种基金funded by FCT through the Program ‘Concurso de Estímulo ao Emprego Científico Institucional’ (CEECINST/00102/2018/CP1567/CT0039)the support from ICREA Acadèmia, Generalitat de Catalunya, and the project PID2019-106650RB-C21 from the Ministerio de Ciencia e Innovación, Spain。
文摘In recent decades,genetic advances in yield improvement in the major cereal crops,including wheat,has stagnated or proceeded at a slower rate than is required to meet future global food demand,particularly in the face of climate change.To reverse this situation,and in view of the future climate scenario,there is a need to increase the genetic diversity of wheat to increase its productivity,quality,stability,and adaptation to local agro-environments.The abundant genetic resources and literature are a basis for wheat improvement.However,many species,such as wild relatives,landraces,and old cultivars have not been studied beyond their agronomic characteristics,highlighting the lack of understanding of the physiological and metabolic processes(and their integration) associated with higher productivity and resilience in limiting environments.Retrospective studies using wheat ancestors and modern cultivars may identify novel traits that have not previously been considered,or have been underestimated,during domestication and breeding,but that may contribute to future food security.This review describes existing wheat genetic diversity and changes that occurred during domestication and breeding,and considers whether mining natural variation among wheat ancestors offers an opportunity to enhance wheat agronomic performance,spike architecture,canopy-and organ-level photosynthetic capacity,and responses to abiotic stress,as well as to develop new wheat hybrids.
基金the support of the Spanish project PID2019-106650RB-C21 from the Ministerio de Ciencia e Innovación,Spainsupport from the InstitucióCatalana de Recerca i Estudis Avan?ats(ICREA)Academia,Generalitat de Catalunya,Spain。
文摘High-throughput crop phenotyping,particularly under field conditions,is nowadays perceived as a key factor limiting crop genetic advance.Phenotyping not only facilitates conventional breeding,but it is necessary to fully exploit the capabilities of molecular breeding,and it can be exploited to predict breeding targets for the years ahead at the regional level through more advanced simulation models and decision support systems.In terms of phenotyping,it is necessary to determined which selection traits are relevant in each situation,and which phenotyping tools/methods are available to assess such traits.Remote sensing methodologies are currently the most popular approaches,even when lab-based analyses are still relevant in many circumstances.On top of that,data processing and automation,together with machine learning/deep learning are contributing to the wide range of applications for phenotyping.This review addresses spectral and red-green-blue sensing as the most popular remote sensing approaches,alongside stable isotope composition as an example of a lab-based tool,and root phenotyping,which represents one of the frontiers for field phenotyping.Further,we consider the two most promising forms of aerial platforms(unmanned aerial vehicle and satellites)and some of the emerging data-processing techniques.The review includes three Boxes that examine specific case studies.
