The Senescence (Stay-Green)—An Important Trait to Exploit Crop Residuals for Bioenergy

Energies

Susana Martínez¹  Arun Kumar²  Bernardo Ordás³  EduardoD. Munaiz⁴  Marlon Caicedo⁵ 

[1] Co.KGaA, Grimsehlstr. 31, 37574 Einbeck, Germany;3edata, I+D. Centro de Iniciativas Empresariales, Fundación CEL. O Palomar s/n, 27004 Lugo, Spain;Instituto Nacional de Investigaciones Agropecuarias (INIAP), Quito 170315, Ecuador;;KWS SAAT SE &School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana 141004, India;

关键词: stay-green;    senescence;    bioenergy;    breeding;    high-throughput phenotyping;    quantitative genetics;    genetics;    chlorophyll;    maize and rice;   

DOI  :  10.3390/en13040790

来源: DOAJ

【 摘 要 】

In this review, we present a comprehensive revisit of past research and advances developed on the stay-green (SG) paradigm. The study aims to provide an application-focused review of the SG phenotypes as crop residuals for bioenergy. Little is known about the SG trait as a germplasm enhancer resource for energy storage as a system for alternative energy. Initially described as a single locus recessive trait, SG was shortly after reported as a quantitative trait governed by complex physiological and metabolic networks including chlorophyll efficiency, nitrogen contents, nutrient remobilization and source-sink balance. Together with the fact that phenotyping efforts have improved rapidly in the last decade, new approaches based on sensing technologies have had an impact in SG identification. Since SG is linked to delayed senescence, we present a review of the term senescence applied to crop residuals and bioenergy. Firstly, we discuss the idiosyncrasy of senescence. Secondly, we present biological processes that determine the fate of senescence. Thirdly, we present the genetics underlying SG for crop-trait improvement in different crops. Further, this review explores the potential uses of senescence for bioenergy crops. Finally, we discuss how high-throughput phenotyping methods assist new technologies such as genomic selection in a cost-efficient manner.

【 授权许可】

Unknown