Estimation of spikelet number per area by UAV-acquired vegetation index in rice (Oryza sativa L.)

Figures & data

Table 1. Dates of transplanting, heading, levels nitrogen (N) application rate, and levels of transplanting density in each year in each cultivar

		Date of transplant	Heading date	Levels of N^a	Levels of transplanting density^b
Ishikawa 65	2019	10 May	5–8 Aug.	3 (5.6–14.6)	2 (17.4 & 22.2)
		24 May	12–14 Aug.	2 (3.0 & 14.0)	2 (11.1 & 22.2)
	2020	10 May	11–15 Aug.	2 (5.6 & 14.6)	2 (17.4 & 22.2)
		24 May	18–20 Aug.	2 (3.0 & 14.0)	2 (11.1 & 22.2)
Koshihikari	2019	13 May	1–3 Aug.	4 (0.0–9.0)	1 (18.5)
	2020	28 April	31 Jul. – 2 Aug.	2 (3.5 & 5.0)	1 (18.5)
		10 May	6–8 Aug.	4 (0.0–9.0)	1 (18.5)

In parentheses: a, N application rate, g N m⁻². b, Planting density, hills m⁻².

Table 2. Vegetation indices (VIs), their equations and references

Vegetation Index	Equation	Reference
NDVI	(NIR – Red)/(NIR + Red)	Rouse et al., (1974)
GNDVI	(NIR – Green)/(NIR + Green)	Gitelson et al., (1996)
NDRE	(NIR – Red edge)/(NIR + Red edge)	Rodriguez et al., (2006)
SR	NIR/Red	Jordan, (1969)
CIgreen	(NIR – Green)/Green	Gitelson et al., (2003)
CIred edge	(NIR – Red edge)/Red edge	Gitelson et al., (2003)

NIR, Red, Green and Red edge represents the spectral reflectance of NIR, red, green and red edge band, respectively.

Figure 1. A schematic image of harvested area.

Harvested area is considered as a red rectangle with intermediate lines between the harvested hills (red circles) and the surrounding hills (green circles) with long and short sides (a). An example of a shape file representing harvest area (red rectangle) on an RGB ortho-image (b) and a VI (CI_green) map (c). For each harvested area, VI values were averaged over pixels within this shape file.

Table 3. Semimonthly daily mean temperature and cumulative solar radiation (MJ m⁻²) from the first half of May to the first half of August

	May		June		July		Aug
	1st half^a	2nd half^a	1st half^a	2nd half^a	1st half^a	2nd half^a	1st half^a
Daily mean temperature °C
2019	17.2	21.0	20.9	22.4	23.3	27.5	29.9
2020	18.0	18.8	23.0	22.8	22.7	24.9	28.2
Cumulative solar radiation MJ m^−2
2019	372.6	366.6	260.5	259.8	219.6	301.8	347.9
2020	291.9	287.2	290.8	274.0	133.7	239.4	274.0

a, ‘1st half’ denotes 1st to 15th day; ‘2nd half’ denotes 16th day to the end of month.

Figure 2. Relations between plant nitrogen content and vegetation indices (VIs). The closed circles denote Isihkawa 65 and the open Koshihikari. Lines correspond the best fit function. n = 108.

Figure 3. Relations between CIG15 and the number of spikelets in Ishikawa 65 and Koshihikari. The closed circles denote 2019 and the open 2020. ***Significant at 0.001 level (n = 54 in Ishikawa 65; n = 30 in Koshihikari).

Table 4. Cumulative solar radiation (MJ m⁻²) in the 15-day period before heading at each plot

		Date of transplanting	Cumulative solar radiation (MJ m^-^2)
Ishikawa 65	2019	10 May	328–349
		24 May	368–369
	2020	10 May	262–282
		24 May	269–275
Koshihikari	2019	13 May	273–294
	2020	28 April	209–223
		10 May	235–238

Table 5. Multiple regression analysis with the number of spikelets per unit area as a dependent variable and CIG15 and CSR15 as independent variables

F-value			R^2		Regression coefficient
			Intercept		CIG15		CSR15
Ishikawa 65	77.9	***	0.750	−4821	2614	***	43.71	***
Koshihikari	153.3	***	0.919	−8779	4697	***	39.62	**

Significant at **0.01 and ***0.001 level.

Figure 4. Relations between the number of spikelets measured and that estimated in Ishikawa 65 and Koshihikari. ***Significant at 0.001 level (n = 18 in Ishikawa 65; n = 10 in Koshihikari).

Rouse, J. W., Haas, R. H., Well, J. A., & Deering, D. W. (1974). Monitoring vegetation systems in the great plains with ERTS. Proceedings, Third Earth Resources Technology Satellite-1 Symposium (pp. 3010–3017). Greenbelt, NASA SP-351.

 Google Scholar

Gitelson, A. A., Kaufman, Y. J., & Merzlyak, M. N. (1996). Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 58(3), 289–298. https://doi.org/https://doi.org/10.1016/S0034-4257(96)00072-7

 Web of Science ®Google Scholar

Rodriguez, D., Fitzgerald, G. J., Belford, R., & Christensen, L. (2006). Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-biophysiological concepts. Australian Journal of Agricultural Research, 57(7), 781–789. https://doi.org/https://doi.org/10.1071/AR05361

 Google Scholar

Jordan, C. F. (1969). Derivation of leaf-area index from quality of light on forest floor. Ecology, 50(4), 663. https://doi.org/https://doi.org/10.2307/1936256

 Web of Science ®Google Scholar

Gitelson, A. A., Gritz, Y., & Merzlyak, M. N. (2003). Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology, 160(3), 271–282. https://doi.org/https://doi.org/10.1078/0176-1617-00887

 PubMed Web of Science ®Google Scholar