Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system

Table 1 Summary of published studies on the estimation of plant height and biomass of crops from RGB imagery acquired from unmanned aerial vehicles (UAVs)

Reference	Crop type	UAV	Sensors	Regression method	VIs/SfM	Canopy characteristic	Best accuracy
Bendig et al. [21]	Barley	MK-Oktokopter	Panasonic Lumix GX1 (RGB)	ER	–	Biomass	R² = 0.82
Bendig et al. [21]	Barley	MK-Oktokopter	Panasonic Lumix GX1 (RGB)	ER	–	PH	R² = 0.92
Watanabe et al. [27]	Sorghum	USM-S1	Powershot ELPH 110HS	GPM	–	PH	r = 0.84
Schirrmann et al. [28]	Wheat	Hexacopter (P-Y6)	Sony Nex 7	LR	–	Biomass	r = 0.68
Schirrmann et al. [28]	Wheat	Hexacopter (P-Y6)	Sony Nex 7	PCA	–	PH	r > 0.80
Iqbal et al. [22]	Poppy	Oktokopter	Canon 550D DSLR	LR	SfM	PH	R² = 0.71
Iqbal et al. [22]	Poppy	Oktokopter	Canon 550D DSLR	LR	SfM	Volume	R² = 0.71
Roth et al. [17]	Winter wheat	ARF Mikrokopter Okto XL	Canon EOS 100D	LR	None	Biomass	R² = 0.74
						PH	R² = 0.80–0.84
						CC	R² = 0.80–0.84
Bendig et al. [6]	Barley	MK-Oktokopter	Panasonic Lumix GX1 (RGB) + FieldSpec3	MLR	VIs + SfM	Biomass	R² = 0.84
Bendig et al. [6]	Barley	MK-Oktokopter	Panasonic Lumix GX1 (RGB) + FieldSpec3	MNLR	VIs + SfM	Biomass	R² = 0.84
Kim et al. [29]	Cabbage	DJI F550 Hexa-rotor	Powershot S110 RGB	MLR	–	PH	R² > 0.90
Li et al. [7]	Maize	Rotor-wing UAV	Sony A6000	MSLR	VIs + SfM	Biomass	R² = 0.78
Li et al. [7]	Maize	Rotor-wing UAV	Sony A6000	RF	VIs + SfM	PH	R² = 0.88
Holman et al. [30]	Wheat	DJI Wookong M	Sony Nex 7	–	SfM	PH	RMSE = 3.00 cm
Holman et al. [30]	Wheat	DJI Wookong M	Sony Nex 7	–	SfM	Growth rate	RMSE = 3.00 cm
Madec et al. [31]	Wheat	Hexacopter	Sony ILCE-6000	–	SfM	PH	RMSE = 3.50 cm

CC Canopy cover, ER exponent regression, GPM genomic prediction modeling, LR linear regression, MLR multiple linear regression, MNLR multiple non-linear regression, MSLR multiple stepwise linear regression, PCA principal components analysis, PH plant height, RF random forest, SfM structure from motion, VIs vegetation indices

ISSN: 1746-4811