干旱区生态环境知识资源中心(Arid): Comparative Performance of Spectral Reflectance Indices and Multivariate Modeling for Assessing Agronomic Parameters in Advanced Spring Wheat Lines Under Two Contrasting Irrigation Regimes

Arid

DOI	10.3389/fpls.2019.01537
	Comparative Performance of Spectral Reflectance Indices and Multivariate Modeling for Assessing Agronomic Parameters in Advanced Spring Wheat Lines Under Two Contrasting Irrigation Regimes
	El-Hendawy, Salah E.1,2; Alotaibi, Majed 1; Al-Suhaibani, Nasser 1; Al-Gaadi, Khalid 3; Hassan, Wael 4,5; Dewir, Yaser Hassan 1,6; Emam, Mohammed Abd El-Gawad 2; Elsayed, Salah 7; Schmidhalter, Urs 8
通讯作者	El-Hendawy, Salah E.
来源期刊	FRONTIERS IN PLANT SCIENCE
ISSN	1664-462X
出版年	2019
卷号	10
英文摘要	The incorporation of nondestructive and cost-effective tools in genetic drought studies in combination with reliable indirect screening criteria that exhibit high heritability and genetic correlations will be critical for addressing the water deficit challenges of the agricultural sector under arid conditions and ensuring the success of genotype development. In this study, the proximal spectral reflectance data were exploited to assess three destructive agronomic parameters [dry weight (DW) and water content (WC) of the aboveground biomass and grain yield (GY)] in 30 recombinant F7 and F8 inbred lines (RILs) growing under full (FL) and limited (LM) irrigation regimes. The utility of different groups of spectral reflectance indices (SRIs) as an indirect assessment tool was tested based on heritability and genetic correlations. The performance of the SRIs and different models of partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) in estimating the destructive parameters was considered. Generally, all groups of SRIs, as well as different models of PLSR and SMLR, generated better estimations for destructive parameters under LM and combined FL+LM than under FL. Even though most of the SRIs exhibited a low association with destructive parameters under FL, they exhibited moderate to high genetic correlations and also had high heritability. The SRIs based on near-infrared (NIR)/visible (VIS) and NIR/NIR, especially those developed in this study, spectral band intervals extracted within VIS, red edge, and NIR spectral range, or individual effective wavelengths relevant to green, red, red edge, and middle NIR spectral region, were found to be more effective in estimating the destructive parameters under all conditions. Five models of SMLR and PLSR for each condition explained most of the variation in the three destructive parameters among genotypes. These models explained 42% to 46%, 19% to 30%, and 39% to 46% of the variation in DW, WC, and GY among genotypes under FL, 69% to 72%, 59% to 61%, and 77% to 81% under LM, and 71% to 75%, 61% to 71%, and 74% to 78% under FL+LM, respectively. Overall, these results confirmed that application of hyperspectral reflectance sensing in breeding programs is not only important for evaluating a sufficient number of genotypes in an expeditious and cost-effective manner but also could be exploited to develop indirect breeding traits that aid in accelerating the development of genotypes for application under adverse environmental conditions.
英文关键词	partial least squares regression phenomics phenotyping proximal sensing techniques recombinant inbred lines stepwise multiple linear regression wavelength band selection
类型	Article
语种	英语
国家	Saudi Arabia ; Egypt ; Germany
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:000502356100001
WOS关键词	HYPERSPECTRAL VEGETATION INDEXES ; GRAIN-YIELD ; CANOPY REFLECTANCE ; WINTER-WHEAT ; OPTICAL-PROPERTIES ; SEASON PREDICTION ; PROTEIN-CONTENT ; NITROGEN STATUS ; WATER STATUS ; BIOMASS
WOS类目	Plant Sciences
WOS研究方向	Plant Sciences
EI主题词	2019-11-28
来源机构	King Saud University
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/311010
作者单位	1.King Saud Univ, Dept Plant Prod, Coll Food & Agr Sci, Riyadh, Saudi Arabia; 2.Suez Canal Univ, Dept Agron, Fac Agr, Ismailia, Egypt; 3.King Saud Univ, Dept Agr Engn, Coll Food & Agr Sci, Precis Agr Res Chair, Riyadh, Saudi Arabia; 4.Suez Canal Univ, Dept Agr Bot, Fac Agr, Ismailia, Egypt; 5.Shaqra Univ, Dept Biol, Coll Sci & Humanities Quwayiah, Riyadh, Saudi Arabia; 6.Kafrelsheikh Univ, Dept Hort, Fac Agr, Kafr Al Sheikh, Egypt; 7.Univ Sadat City, Environm Studies & Res Inst, Evaluat Nat Resources Dept, Menoufia, Egypt; 8.Tech Univ Munich, Dept Plant Sci, Freising Weihenstephan, Germany
推荐引用方式 GB/T 7714	El-Hendawy, Salah E.,Alotaibi, Majed,Al-Suhaibani, Nasser,et al. Comparative Performance of Spectral Reflectance Indices and Multivariate Modeling for Assessing Agronomic Parameters in Advanced Spring Wheat Lines Under Two Contrasting Irrigation Regimes[J]. King Saud University,2019,10.
APA	El-Hendawy, Salah E..,Alotaibi, Majed.,Al-Suhaibani, Nasser.,Al-Gaadi, Khalid.,Hassan, Wael.,...&Schmidhalter, Urs.(2019).Comparative Performance of Spectral Reflectance Indices and Multivariate Modeling for Assessing Agronomic Parameters in Advanced Spring Wheat Lines Under Two Contrasting Irrigation Regimes.FRONTIERS IN PLANT SCIENCE,10.
MLA	El-Hendawy, Salah E.,et al."Comparative Performance of Spectral Reflectance Indices and Multivariate Modeling for Assessing Agronomic Parameters in Advanced Spring Wheat Lines Under Two Contrasting Irrigation Regimes".FRONTIERS IN PLANT SCIENCE 10(2019).