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DOI	10.1016/j.compag.2021.106399
	Linear mixed model analysis of NDVI-based canopy coverage, extracted from sequential UAV multispectral imagery of an open field tomato irrigation experiment
	Garcia-Garcia, Delvis; la Rosa, Ximena Reynafarje; Bedoya, Diego Grados; Schrevens, Eddie
通讯作者	Garcia-Garcia, D (corresponding author), Univ Cent Marta Abreu Villas, Fac Ingn Elect, Dept Control Automat, Santa Clara, Cuba.
来源期刊	COMPUTERS AND ELECTRONICS IN AGRICULTURE
ISSN	0168-1699
EISSN	1872-7107
出版年	2021
卷号	189
英文摘要	This study presents the use of a linear mixed model to accurately estimate the dynamics of canopy cover (CC) during an irrigation experiment on a tomato crop, performed in the Peruvian coastal desert. Initially, the normalized difference vegetation index (NDVI)-based CC was computed using multispectral sensors over consecutive weekly UAV flights, during the growing season of the crop. The drone high-resolution sequential imagery, combined with image segmentation on plant level, results in repeated measures growth curves of the coverage per plant. To analyze these repeated measures data per plant, cubic polynomials without intercept showed the best goodness-of-fit of the CC dynamics per plant. As a consequence, this polynomial was incorporated in a linear mixed model (LMM) as a random coefficient model to fit the plant-specific time evolution of CC as deviations from the mean time effects per irrigation treatment. The mixed model approach is capable to estimate the coverage curves per plant with high accuracy and a very limited number of model parameters. The results and statistical analysis demonstrate the potential benefits of the linear mixed model for incorporating plant-specific random components in addition to classical fixed effects models. Thus, the proposed linear mixed canopy model is a very efficient way to model plant-specific growth curves together with the treatment and design structure of the experiment.
英文关键词	Canopy cover Irrigation Linear mixed model Multispectral imagery NDVI UAV
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000696799900002
WOS关键词	VEGETATION INDEXES ; NITROGEN ; BIOMASS ; WHEAT ; YIELD ; LIDAR
WOS类目	Agriculture, Multidisciplinary ; Computer Science, Interdisciplinary Applications
WOS研究方向	Agriculture ; Computer Science
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/362899
作者单位	[Garcia-Garcia, Delvis] Univ Cent Marta Abreu Villas, Fac Ingn Elect, Dept Control Automat, Santa Clara, Cuba; [Garcia-Garcia, Delvis; la Rosa, Ximena Reynafarje; Schrevens, Eddie] Katholieke Univ Leuven, Fac Biosci Engn, Dept Biosyst, Leuven, Belgium; [Bedoya, Diego Grados] Aarhus Univ, Dept Agroecol, Tjele, Denmark
推荐引用方式 GB/T 7714	Garcia-Garcia, Delvis,la Rosa, Ximena Reynafarje,Bedoya, Diego Grados,et al. Linear mixed model analysis of NDVI-based canopy coverage, extracted from sequential UAV multispectral imagery of an open field tomato irrigation experiment[J],2021,189.
APA	Garcia-Garcia, Delvis,la Rosa, Ximena Reynafarje,Bedoya, Diego Grados,&Schrevens, Eddie.(2021).Linear mixed model analysis of NDVI-based canopy coverage, extracted from sequential UAV multispectral imagery of an open field tomato irrigation experiment.COMPUTERS AND ELECTRONICS IN AGRICULTURE,189.
MLA	Garcia-Garcia, Delvis,et al."Linear mixed model analysis of NDVI-based canopy coverage, extracted from sequential UAV multispectral imagery of an open field tomato irrigation experiment".COMPUTERS AND ELECTRONICS IN AGRICULTURE 189(2021).