scholarly journals Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: progress and challenges

2021 ◽  
pp. 100209
Author(s):  
Marcin Grzybowski ◽  
Nuwan K. Wijewardane ◽  
Abbas Atefi ◽  
Yufeng Ge ◽  
James C. Schnable
2013 ◽  
Vol 39 (2) ◽  
pp. 309 ◽  
Author(s):  
Qiong WU ◽  
Bo QI ◽  
Tuan-Jie ZHAO ◽  
Xin-Feng YAO ◽  
Yan ZHU ◽  
...  

Author(s):  
Bruce Walsh ◽  
Michael Lynch

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.


Author(s):  
Bruce Walsh ◽  
Michael Lynch

One of the major unresolved issues in quantitative genetics is what accounts for the amount of standing genetic variation in traits. A wide range of models, all reviewed in this chapter, have been proposed, but none fit the data, either giving too much variation or too little apparent stabilizing selection.


2021 ◽  
Vol 42 (11) ◽  
pp. 4177-4198
Author(s):  
Renato Herrig Furlanetto ◽  
Marcos Rafael Nanni ◽  
Monica Sayuri Mizuno ◽  
Luís Guilherme Teixeira Crusiol ◽  
Camila Rocco da Silva

Author(s):  
Hammad A Khan ◽  
Yukiko Nakamura ◽  
Robert T Furbank ◽  
John R Evans

Abstract A growing number of leaf traits can be estimated from hyperspectral reflectance data. These include structural and compositional traits, such as leaf mass per area (LMA) and nitrogen and chlorophyll content, but also physiological traits such a Rubisco carboxylation activity, electron transport rate, and respiration rate. Since physiological traits vary with leaf temperature, how does this impact on predictions made from reflectance measurements? We investigated this with two wheat varieties, by repeatedly measuring each leaf through a sequence of temperatures imposed by varying the air temperature in a growth room. Leaf temperatures ranging from 20 °C to 35 °C did not alter the estimated Rubisco capacity normalized to 25 °C (Vcmax25), or chlorophyll or nitrogen contents per unit leaf area. Models estimating LMA and Vcmax25/N were both slightly influenced by leaf temperature: estimated LMA increased by 0.27% °C–1 and Vcmax25/N increased by 0.46% °C–1. A model estimating Rubisco activity closely followed variation associated with leaf temperature. Reflectance spectra change with leaf temperature and therefore contain a temperature signal.


2009 ◽  
Vol 36 (1) ◽  
pp. 37-56 ◽  
Author(s):  
Neus Martínez-Abadías ◽  
Carolina Paschetta ◽  
Soledad de Azevedo ◽  
Mireia Esparza ◽  
Rolando González-José

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