WATER STATUS EVALUATION OF MAIZE CULTIVARS USING AERIAL IMAGES

ANDRADE JUNIOR, ADERSON SOARES DE; BASTOS, EDSON ALVES; SOUSA, CARLOS ANTONIO FERREIRA DE; CASARI, RAPHAEL AUGUSTO DAS CHAGAS NOQUELI; RODRIGUES, BRAZ HENRIQUE NUNES

doi:10.1590/1983-21252021v34n219rc

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Agricultural Engineering • Rev. Caatinga 34 (2) • Apr-Jun 2021 • https://doi.org/10.1590/1983-21252021v34n219rc copy

WATER STATUS EVALUATION OF MAIZE CULTIVARS USING AERIAL IMAGES

AVALIAÇÃO DO ESTADO HÍDRICO DE CULTIVARES DE MILHO POR IMAGENS AÉREAS

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The objective of this study was to evaluate the water status of maize cultivars through thermal and vegetation indexes generated from multispectral aerial images obtained from an unmanned aerial vehicle (UAV), and correlate them with physiological indicators and soil water contents. The application of three water regimes based on the reference evapotranspiration (ETo) (30%, 90%, and 150% ETo) was evaluated for two maize cultivars (AG-1051 and BRS-Caatingueiro). An UAV was used to acquire thermal and multispectral images. The indexes evaluated were CWSI, CI-G, CI-RE, CIV, NDVI and OSAVI, which were correlated with gas exchange and soil moisture measures. The CWSI present correlation with physiological indicators (stomatal conductance, transpiration, and net CO₂ assimilation rate) that can be used to evaluate water status of maize plants. The multispectral vegetation indexes NDVI and OSAVI can replace the CWSI thermal index in water status evaluations for maize plants.

Keywords:
Zea mays L.; ARP; Remote sensing; RGB imagens

Indexes	Abbreviation	Equation	Reference
Chlorophyll index–green	CI-G	$= \frac{R_{n}}{R_{g}} - 1$	Escadafal (1994)ESCADAFAL, R. Soil spectral properties and their relationships with environmental parameters: examples from arid regions. In: HILL, J.; MÉGIER, J. (Eds.). Imaging Spectrometry-A Tool for Environmental Observations. Dordrecht: Kluwer Academic Publishers, 1994. v. 4, cap. 5, p. 71-87.
Chlorophyll index – Red Edge	CI-RE	$= \frac{R_{n}}{R_{RE}} - 1$	Gitelson et al. (2003)GITELSON, A. A. et al. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30: 1248-1252, 2003.
Chlorophyll vegetation index	CVI	$= \frac{R_{n} R_{r}}{R_{g}^{2}}$	Vincini, Frazzi and D’Alessio (2008)VINCINI, M.; FRAZZI, E.; D’ALESSIO, P. A broad -band leaf chlorophyll vegetation index at the canopy scale. Precision Agriculture, 9: 303–319, 2008.
Normalized Difference Vegetation Index	NDVI	$= \frac{R_{n} - R_{r}}{R_{n} + R_{r}}$	Gitelson et al. (2003)GITELSON, A. A. et al. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30: 1248-1252, 2003.
Optimized Soil Adjusted Vegetation Index	OSAVI	$= \frac{R_{n} - R_{r}}{R_{n} + R_{r} + 0, 16}$	Roundeaux, Steven and Baret (1996)RONDEAUX, G.; STEVEN, M.; BARET, F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55: 95-107, 1996.
Crop Water Stress Index	CWSI	$= \frac{T_{c} - T_{d}}{T_{w} - T_{d}}$	Idso et al. (1981)IDSO, S. B. et al. Normalizing the stress-degree-day parameter for environmental variability. Agricultural Meteorology, 24: 45-55, 1981.

Source of variation	Degrees of freedom	Mean canopy leaf temperature (Tc)		Crop water stress index (CWSI)
Water regimes (WR)	3	246.695	***	0.0121	*
Blocks	2	0.567		0.0012
Error a	1	0.429		0.0012
Cultivars (C)	2	25.309	***	0.0004	ns
WR × C	15	9.929	***	0.0041	°
Error b	9	0.573		0.0011
CV - WR (%)		1.933		7.902
CV - C (%)		2.234		7.382

Source of variation	Degrees of freedom	gs		E		A
Water regimes (WR)	3	0.076	***	26.703	***	515.660	***
Blocks	2	0.002	ns	0.465	ns	25.830	ns
Error a	1	0.001		0.208		11.900
Cultivars (C)	2	0.000	ns	0.109	ns	12.310	ns
WR × C	2	0.001	ns	0.835	ns	4.080	ns
Error b	9	0.001		0.438		13.120
Total	23
CV - WR (%)		13.756		5.591		11.208
CV - C (%)		14.024		8.120		11.772

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