HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging

Bergsträsser, Sergej; Fanourakis, Dimitrios; Schmittgen, Simone; Cendrero-Mateo, Maria Pilar; Jansen, Marcus; Scharr, Hanno; Rascher, Uwe

doi:10.1186/s13007-015-0043-0

Plant Methods

Table 2 Vegetation indices performance based on a logarithmic regression model

From: HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging

Index	Rank	Source	COR	R ²	F	P	Index	Rank	Source	COR	R ²	F	P
ANCB	8	*ρ +* τ	0.80	0.64	66.94	0.00	PSNDb	7	τ	0.80	0.64	67.86	0.00
	13	τ	0.77	0.60	56.98	0.00		20	*ρ + τ*	0.75	0.56	48.48	0.00
	26	ρ	0.71	0.50	37.60	0.00		43	ρ	0.55	0.30	16.15	0.00
BGI2	9	ρ	0.80	0.63	65.65	0.00	PSRI	53	τ	0.37	0.14	6.02	0.02
	27	τ	−0.69	0.48	34.56	0.00		54	ρ + τ	0.35	0.12	5.41	0.03
	48	ρ + τ	0.46	0.22	10.41	0.00		61	ρ	0.15	0.02	0.82	0.37
Chlg	38	ρ + τ	0.60	0.36	21.10	0.00	PSSRa	23	τ	0.74	0.55	45.88	0.00
	41	ρ	0.56	0.31	17.32	0.00		49	ρ + τ	0.45	0.20	9.49	0.00
	57	τ	0.25	0.06	2.58	0.12		65	ρ	0.08	0.01	0.23	0.64
Chlre	15	τ	0.77	0.59	54.90	0.00	PSSRb	12	τ	0.78	0.61	58.42	0.00
	22	*ρ + τ*	0.75	0.56	47.42	0.00		21	*ρ + τ*	0.75	0.56	48.36	0.00
	33	ρ	0.63	0.40	25.60	0.00		51	ρ	0.41	0.17	7.64	0.01
EVI	1	*ρ + τ*	0.85	0.72	99.16	0.00	SR1	10	τ	0.80	0.63	65.28	0.00
	34	τ	0.62	0.38	23.21	0.00		17	*ρ + τ*	0.76	0.58	53.06	0.00
	44	ρ	0.54	0.29	15.88	0.00		31	ρ	0.66	0.44	30.07	0.00
MCARI	36	ρ	−0.61	0.37	22.07	0.00	SIPI	24	τ	0.72	0.52	41.39	0.00
	46	τ	0.51	0.26	13.02	0.00		52	ρ + τ	0.38	0.14	6.38	0.02
	47	ρ + τ	−0.49	0.24	12.24	0.00		66	ρ	−0.03	0.00	0.03	0.86
mND	3	τ	0.83	0.69	85.43	0.00	SR2	18	τ	0.76	0.58	51.62	0.00
	4	*ρ + τ*	0.82	0.67	76.13	0.00		45	ρ + τ	0.53	0.29	15.16	0.00
	28	ρ	0.69	0.47	34.36	0.00		63	ρ	0.10	0.01	0.42	0.52
mSR	14	τ	0.77	0.60	56.46	0.00	TCARI	37	ρ	−0.60	0.36	21.16	0.00
	40	ρ + τ	−0.57	0.32	18.27	0.00		42	ρ + τ	−0.56	0.31	17.09	0.00
	56	ρ	−0.29	0.08	3.46	0.07		64	τ	0.09	0.01	0.32	0.57
ND	2	τ	0.84	0.70	90.52	0.00	TCARI/OSAVI	30	ρ	−0.67	0.44	30.36	0.00
	6	*ρ + τ*	0.80	0.65	69.52	0.00		32	ρ + τ	−0.66	0.43	29.11	0.00
	29	ρ	0.69	0.47	34.36	0.00		59	τ	−0.21	0.04	1.71	0.20
NDVI	16	τ	0.77	0.59	54.01	0.00	TVI	50	ρ + τ	0.43	0.19	8.68	0.01
	35	ρ + τ	0.62	0.38	23.20	0.00		55	τ	0.29	0.09	3.57	0.07
	58	ρ	0.23	0.05	2.16	0.15		62	ρ	0.14	0.02	0.81	0.37
PSNDa	19	τ	0.76	0.57	50.71	0.00	VOG	5	τ	0.82	0.66	75.39	0.00
	39	ρ + τ	0.57	0.33	18.40	0.00		11	*ρ + τ*	0.78	0.61	60.69	0.00
	60	ρ	0.18	0.03	1.22	0.28		25	ρ	0.71	0.50	37.91	0.00

Determination (R²) and correlation (COR) coefficients, as well as significance level of the relation between the 22 vegetation indices (abbreviations in Table 1) and destructively-measured chlorophyll content. Vegetation indices were calculated based on reflectance (ρ), transmittance (τ) or combination of ρ with τ (i.e., ρ + +τ) source images. Indices were ranked based on the R² value (all three source images were included in the ranking). The entire leaf surface was averaged (n = 40). All four species (maize, rapeseed, barley and tomato) were plotted together (examples are shown in Additional file 1: Figure S1). Plants were grown under control or deficient nitrogen levels. Bold text indicates R² values greater or equal to 0.5.

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ISSN: 1746-4811

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