Early Detection of Plant Physiological Responses to Different Levels of Water Stress Using Reflectance Spectroscopy
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Site
2.2. Field Data Collection
2.2.1. Plant Physiological Measurements
2.2.2. Hyperspectral Reflectance Measurements
2.3. Methods
2.3.1. Selection of Spectral Indices and Sensitive Bands
2.3.2. Multivariate Method
2.3.3. Sensitivity Analysis for Early Stress Detection
2.3.4. Statistical Analyses
3. Results
3.1. Vineyard Weather Condition and Physiological Responses of Grapevines to Induced Water Stress
3.2. Complete-Combination Indices Analysis of the Hyperspectral Reflectance Factor Data
3.3. The Relationship between the Grapevine Water Stress Response and Hyperspectral Reflectance Indices from the Literature
3.4. PLSR Analysis
3.5. Feasibility of Early Stress Detection
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Reflectance Index | Acronym | Equation | References |
---|---|---|---|
Leaf pigment | |||
Anthocyanin (Gitelson) | AntGitelson | AntGitelson = (1/R550 − 1/R700) × R780 | [48] |
Carotenoid Reflectance Index | CRI1 | CRI1 = 1/R510 − 1/R550 | [49] |
Carotenoid Reflectance Index | CRI2 | CRI2 = 1/R510 − 1/R700 | [49] |
Chlorophyll Index | CI | CI = (R750 − R705)/(R750 + R705) | [50] |
Optimized Soil-Adjusted Vegetation Index | OSAVI | OSAVI = (1 + 0.16) × (R800 − R670)/(R800 + R670 + 0.16) | [51] |
Red Green Index | RGI | RGI = R690/R550 | [52] |
Structure Intensive Pigment Index | SIPI | SIPI = (R800 − R450)/(R800 + R650) | [53] |
Transformed Chlorophyll Absorption in Reflectance Index | TCARI | TCARI = 3 × ((R700 − R670) − 0.2 × (R700 − R550) × (R700/R670)) | [54] |
TCARI/OSAVI | TCARI/OSAVI | [54] | |
Normalized Pigment Chlorophyll Index | NPCI | NPCI = (R680 − R430)/(R680 + R430) | [55] |
Greenness | |||
Enhanced Vegetation Index EVI | EVI | (2.5(R782 − R 675)/(R782 + 6 × R675 − 7.5 × R445 + 1)) | [56] |
Normalized Difference Vegetation Index | NDVI | NDVI = (R800 − R670)/(R800 + R670) | [57] |
Greenness Index | GI | GI = R554/R677 | [52] |
Green NDVI | GNDVI | GNDVI = (R750 − R540 + R570)/(R750 + R540 − R570) | [58] |
Red Edge Inflection Point | REIP | REIP = 700 + 40 × {[(R670 + R780)/2 − R700]/(R740 − R700)} | [59] |
Simple Ratio | SR | SR = R900/R680 | [57] |
Triangular Vegetation Index | TVI | TVI = 0.5 × (120 × (R750 − R550) − 200 × (R670 − R550)) | [60] |
Stress | |||
Fluorescence Ratio Index 1 | FRI1 | FRI1 = R690/R600 | [61] |
Fluorescence Ratio Indices 2 | FRI2 | FRI2 = R740/R800 | [61] |
Modified Red Edge Simple Ratio Index | mRESR | mRESR = (R750 − R445)/(R705 + R445) | [20] |
Normalized Phaeophytinization Index | NPQI | NPQI = (R415 − R435)/(R415 + R435) | [62] |
Photochemical Reflectance Index | PRI | PRI = (R531 − R570)/(R531 + R570) | [24] |
Plant Senescence Reflectance Index | PSRI | PSRI = (R680−R500)/R750 | [63] |
Red-Edge Vegetation Stress Index | RVSI | 0.5(R722 + R763) − R733 | [64] |
Simple Ratio Pigment Index | SRPI | SRPI = R430/R680 | [65] |
Water | |||
Water Index | WI | WI = R900/R970 | [66] |
18 June 2014 | Gs | Ai | Fs | Fm' | ΔF/Fm' | ETR | qP | NPQ |
FIR (n = 12) | 0.37 | 20.3 | 811 | 1221 | 0.33 | 145 | 0.64 | 5.19 |
INT (n = 12) | 0.31 | 19.7 | 800 | 1183 | 0.32 | 140 | 0.62 | 5.53 |
NIR (n = 8) | 0.39 | 20.1 | 784 | 1211 | 0.35 | 153 | 0.67 | 5.18 |
RMSE | 0.08 | 3.38 | 84 | 145 | 0.04 | 17 | 0.04 | 0.90 |
Significance level | ns. | ns. | ns. | ns. | ns. | ns. | ns. | ns. |
19 August 2014 | ||||||||
FIR (n = 12) | 0.17a | 21.1a | 827a | 1213a | 0.32a | 139a | 0.63 | 5.00a |
INT (n = 12) | 0.06b | 16.0b | 768b | 1067b | 0.28b | 121b | 0.59 | 5.89b |
NIR (n = 12) | 0.04b | 15.4b | 721b | 983b | 0.26b | 115b | 0.57 | 6.46b |
RMSE | 0.04 | 3.4 | 54 | 94 | 0.04 | 20 | 0.07 | 0.59 |
Significance level | *** | ** | *** | *** | * | * | ns | *** |
10 July 2015 | ||||||||
FIR (n = 24) | 0.30 | 7.88 | 694 | 962 | 0.27 | 117 | 0.57 | 1.88 |
INT (n = 24) | 0.33 | 7.35 | 711 | 1006 | 0.28 | 124 | 0.59 | 1.93 |
NIR (n = 24) | 0.33 | 9.45 | 694 | 967 | 0.27 | 117 | 0.57 | 1.87 |
RMSE | 0.08 | 3.85 | 83 | 180 | 0.07 | 32 | 0.10 | 0.2 |
Significance level | ns. | ns. | ns. | ns. | ns. | ns. | ns. | ns. |
21 September 2015 | ||||||||
FIR (n = 24) | 0.19 | 17.4 | 955 | 1359 | 0.29 | 128 | 0.56 | 2.10 |
INT (n = 24) | 0.18 | 17.0 | 1008 | 1408 | 0.29 | 125 | 0.54 | 2.12 |
NIR (n = 24) | 0.18 | 17.3 | 921 | 1369 | 0.32 | 140 | 0.61 | 2.13 |
RMSE | 0.03 | 3.8 | 172 | 219 | 0.07 | 32 | 0.11 | 0.21 |
Significance level | ns. | ns. | ns. | ns. | ns. | ns. | ns. | ns. |
Gs | Ai | Fs | Fm' | ΔF/Fm' | ETR | qP | NPQ | |
---|---|---|---|---|---|---|---|---|
18 June 2014 | ||||||||
Gs | 1.00 | |||||||
Ai | 0.75 ** | 1.00 | ||||||
Fs | 0.05 | 0.21 | 1.00 | |||||
Fm' | 0.27 | 0.37 ** | 0.85 ** | 1.00 | ||||
ΔF/Fm' | 0.39 * | 0.34 | 0.05 | 0.56 ** | 1.00 | |||
ETR | 0.39 * | 0.34 | 0.05 | 0.56 ** | 0.99 ** | 1.00 | ||
qP | 0.26 | 0.06 | −0.32 | 0.16 * | 0.85 ** | 0.85 ** | 1.00 | |
NPQ | −0.23 | −0.31 | −0.82** | −0.97 ** | −0.59 ** | −0.59 ** | −0.26 | 1.00 |
19 August 2014 | ||||||||
Gs | 1.00 | |||||||
Ai | 0.82 ** | 1.00 | ||||||
Fs | 0.47 ** | 0.29 | 1.00 | |||||
Fm' | 0.50 ** | 0.34 * | 0.82 ** | 1.00 | ||||
ΔF/Fm' | 0.26 | 0.22 | 0.15 | 0.68 ** | 1.00 | |||
ETR | 0.14 | 0.22 | 0.15 | 0.69 ** | 0.99 ** | 1.00 | ||
qP | 0.13 | 0.14 | −0.05 | 0.51 ** | 0.96 ** | 0.96 ** | 1.00 | |
NPQ | −0.50 | −0.31 | −0.81 ** | −0.99 ** | −0.69 ** | −0.69 ** | −0.53 ** | 1.00 |
10 July 2015 | ||||||||
Gs | 1.00 | |||||||
Ai | 0.31 ** | 1.00 | ||||||
Fs | −0.01 | −0.08 | 1.00 | |||||
Fm' | −0.10 | 0.00 | 0.87 ** | 1.00 | ||||
ΔF/Fm' | −0.18 | −0.10 | 0.40 ** | 0.84 * | 1.00 | |||
ETR | 0.19 | −0.10 | 0.48 ** | 0.84 ** | 0.99 ** | 1.00 | ||
qP | −0.22 | −0.14 | 0.24 * | 0.66 ** | 0.95 ** | 0.95 ** | 1.00 | |
NPQ | −0.12 | −0.04 | 0.74 ** | 0.96 ** | 0.91 ** | 0.91 ** | 0.75 ** | 1.00 |
21 September 2015 | ||||||||
Gs | 1.00 | |||||||
Ai | 0.76 ** | 1.00 | ||||||
Fs | 0.11 | −0.10 | 1.00 | |||||
Fm' | 0.29 * | 0.10 | 0.79 ** | 1.00 | ||||
ΔF/Fm' | 0.26 * | 0.31 ** | −0.39 ** | 0.25 * | 1.00 | |||
ETR | 0.26 * | 0.31 ** | −0.39 ** | 0.25 ** | 1.00 ** | 1.00 | ||
qP | 0.18 | 0.29 * | −0.65 ** | −0.06 * | 0.93 ** | 0.93 ** | 1.00 | |
NPQ | 0.31 ** | 0.20 | 0.37 ** | 0.82 ** | 0.63 ** | 0.63 ** | 0.31 ** | 1.00 |
Spectral Indices | Gs | Ai | Fs | Fm' | NPQ |
---|---|---|---|---|---|
R2 (RMSEcal) | R2 (RMSEcal) | R2 (RMSEcal) | R2 (RMSEcal) | R2 (RMSEcal) | |
NDSI(603,558) | 0.720 (0.063) | - | - | - | - |
NDSI(728,525) | 0.711 (0.066) | - | - | - | - |
NDSI(830,525) | 0.703 (0.068) | - | - | - | - |
NDSI(1000,525) | 0.694 (0.068) | - | - | - | - |
NDSI(715,620) | 0.715 (0.066) | - | - | - | - |
NDSI(818,620) | 0.707 (0.067) | - | - | - | - |
NDSI(1000,620) | 0.709 (0.067) | - | - | - | - |
NDSI(726,630) | 0.714 (0.068) | - | - | - | - |
NDSI(778,635) | 0.707 (0.069) | - | - | - | - |
NDSI(1000,635) | 0.707 (0.070) | - | - | - | - |
NDSI(705,535) | - | 0.256 (5.268) | - | - | - |
- | |||||
NDSI(704,540) | - | - | 0.275 (140.281) | - | - |
NDSI(704,540) | - | - | - | 0.284 (208.748) | - |
NDSI(685,415) | - | - | - | - | 0.681 (0.992) |
Gs | NPQ | |
---|---|---|
R2 (RMSEcal) | R2 (RMSEcal) | |
Leaf Pigment | ||
AntGitelson | 0.567 (0.100) *** | 0.269 (1.509) *** |
CRI1 | 0.663 (0.087) *** | 0.332 (1.441) *** |
CRI2 | 0.648 (0.090) *** | 0.207 (1.571) *** |
CI | 0.648 (0.090) *** | 0.529 (1.211) *** |
OSAVI | 0.662 (0.088) *** | 0.485 (1.261) *** |
RGI | 0.592 (0.097) *** | 0.364 (1.407) *** |
SIPI | 0.632 (0.092) *** | 0.376 (1.394) *** |
TCARI | 0.537 (0.103) *** | 0.368 (1.403) *** |
TCARI/OSAVI | 0.587 (0.098) *** | 0.433 (1.327) *** |
NPCI | 0.518 (0.106) *** | 0.544 (1.191) *** |
Greenness | ||
EVI | 0.156 (0.140) ** | 0.038 (1.731) ** |
NDVI | 0.662 (0.088) *** | 0.529 (1.211) *** |
GI | 0.277 (0.130) *** | 0.057 (1.714)** |
GNDVI | 0.218 (0.135) *** | 0.045 (1.724)** |
REIP | 0.540 (0.104) *** | 0.456 (1.301) *** |
SR | 0.680 (0.086) *** | 0.531 (1.196) *** |
TVI | 0.257 (0.131) *** | 0.086 (1.687) *** |
Stress | ||
FRI1 | - | 0.046(1.723)** |
FRI2 | 0.314 (0.126) *** | 0.356 (1.416) *** |
mRESR | 0.656 (0.089) *** | 0.383 (1.386) *** |
NPQI | 0.222 (0.134) *** | 0.094 (1.680) *** |
PRI | 0.022 (0.151) | 0.043 (1.725) ** |
PSRI | 0.278 (0.130) *** | - |
RVSI | 0.263 (0.131) | - |
SRPI | 0.530 (0.105) *** | 0.450 (1.309) *** |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Maimaitiyiming, M.; Ghulam, A.; Bozzolo, A.; Wilkins, J.L.; Kwasniewski, M.T. Early Detection of Plant Physiological Responses to Different Levels of Water Stress Using Reflectance Spectroscopy. Remote Sens. 2017, 9, 745. https://doi.org/10.3390/rs9070745
Maimaitiyiming M, Ghulam A, Bozzolo A, Wilkins JL, Kwasniewski MT. Early Detection of Plant Physiological Responses to Different Levels of Water Stress Using Reflectance Spectroscopy. Remote Sensing. 2017; 9(7):745. https://doi.org/10.3390/rs9070745
Chicago/Turabian StyleMaimaitiyiming, Matthew, Abduwasit Ghulam, Arianna Bozzolo, Joseph L. Wilkins, and Misha T. Kwasniewski. 2017. "Early Detection of Plant Physiological Responses to Different Levels of Water Stress Using Reflectance Spectroscopy" Remote Sensing 9, no. 7: 745. https://doi.org/10.3390/rs9070745