Improved Yield Prediction of Ratoon Rice Using Unmanned Aerial Vehicle-Based Multi-Temporal Feature Method

doi:10.1016/j.rsci.2023.03.008

摘要/Abstract

. [J]. Rice Science, 2023, 30(3): 247-256.

图/表 5

Fig. 1. Yield differences of ratoon rice at different stubble height groups. The red star represents the mean value for each group.

Fig. 2. Determination coefficients of vegetation indices (VIs) (A and B) and texture feature (C and D) for yield prediction of ratoon rice yield at different stubble heights. PI, Panicle initiation; HD, Heading; EF, Early filling; LF, Late filling; All represents all stubble height; SH0, SH15, SH30 and SH45 represent stubble heights of 0, 15, 30 and 45 cm, respectively.RECI, Red-edge chlorophyll index; WDRVI, Wide dynamic range vegetation index; R_ENT, Red_entropy; RE_SEC, Red-edge_second moment.

Table 1. Validation of ratoon rice yield models based on different feature sets.

Stage	Feature	No. of features	R²	RMSE	RRMSE
Panicle initiation	VIs	2	0.611	0.459	0.115
	Tex	2	0.576	0.472	0.118
	VIs + API	3	0.685	0.417	0.104
	Tex + API	3	0.564	0.477	0.119
	VIs & Tex	4	0.700	0.412	0.103
	VIs & Tex + API	5	0.732	0.406	0.101
Heading	VIs	2	0.618	0.334	0.083
	Tex	1	0.603	0.341	0.085
	VIs + API	3	0.654	0.317	0.079
	Tex + API	3	0.587	0.349	0.087
	VIs & Tex	3	0.690	0.302	0.075
	VIs & Tex + API	4	0.705	0.295	0.073
Early filling	VIs	2	0.491	0.480	0.118
	Tex	2	0.582	0.432	0.107
	VIs + API	3	0.478	0.486	0.120
	Tex + API	3	0.599	0.424	0.105
	VIs & Tex	4	0.606	0.420	0.104
	VIs & Tex + API	5	0.611	0.417	0.103
Late filling	VIs	1	0.006	0.776	0.190
	Tex	1	0.365	0.551	0.134
	VIs + API	2	0.257	0.597	0.146
	Tex + API	2	0.422	0.523	0.128
	VIs & Tex	2	0.244	0.606	0.148
	VIs & Tex + API	3	0.502	0.499	0.122
Multi-temporal	VIs	2	0.780	0.296	0.072
	Tex	3	0.702	0.345	0.084
	VIs + API	3	0.768	0.304	0.074
	Tex + API	4	0.730	0.334	0.081
	VIs & Tex	5	0.795	0.298	0.072
	VIs & Tex + API	6	0.794	0.300	0.073

Fig. 3. Validated scatter plot of measured and predicted yields of ratoon rice. A-D, Optimal prediction results for growth period at panicle initiation (A), heading (B), early filling (C) and late filling (D). E and F, Yield prediction results for the best multi-phase model without (E) and with API (F).VIs, Vegetation indices; Tex, Texture; API, Agronomic practice information; R2, Coefficient of determination; RMSE, Root mean square error; RRMSE, Relative root mean square error.

Fig. 4. Ratoon rice yield prediction map based on multi-temporal model (A), actual measured yield (B) and yield error between prediction and actual measured yields (C).

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