Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing
Abstract
:1. Introduction
2. Materials and Methods
- FRBλ = bidirectional reflectance factor (dimensionless)
- La,λ = spectral radiance of the target (W cm−2 sr−1 μm−1)
- Lr,λ = spectral radiance of the reference plate (W cm−2 sr−1 μm−1).
- Yi = measured values
- Y = predicted values
- n = sample size
3. Results and Discussion
3.1. Nutrient Content
3.2. Spectral Reflectance
3.3. Model Calibration
3.3.1. Single Band
3.3.2. Band Ratio
3.3.3. Partial Least Squares Regression (PLSR)
3.4. Model Validation
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Attribute | Value |
---|---|
Coarse sand (g.kg−1) | 523.00 |
Fine sand (g.kg−1) | 370.00 |
Silt (g.kg−1) | 52.00 |
Clay (g.kg−1) | 55.00 |
Bulk density (g.cm−3) | 1.46 |
Particle density (g.cm−3) | 2.68 |
pH (water) | 6.92 |
Calcium (mmolc.dm−3) | 16.00 |
Magnesium (mmolc.dm−3) | 13.00 |
Sodium (mmolc.dm−3) | 3.00 |
Potassium (mmolc.dm−3) | 1.00 |
H + Al (mmolc.dm−3) | 18.20 |
Organic carbon (g.kg−1) | 7.02 |
Total nitrogen (g.kg−1) | 0.68 |
Organic matter (g.kg−1) | 12.10 |
Available phosphorus (mg.dm−3) | 23.00 |
C:N ratio | 10:1 |
Nutrient | Wavelength (nm) | Equation | R2 |
---|---|---|---|
P | 684 | y = −89.297x + 8.158 | 0.62 |
K | 684 | y = −915.51x + 74.546 | 0.63 |
Ca | 720 | y = 208.12x − 41.659 | 0.67 |
Nutrient | Band Ratio (nm) | Equation | R2 |
---|---|---|---|
P | 826/750 | P = 34.63x − 32.35 | 0.66 |
K | 744/816 | K = −256.09x + 265.54 | 0.70 |
Ca | 720/844 | Ca = 89.675x − 33.934 | 0.63 |
Zn | 1252/1148 | Zn = 6818.2x − 6643 | 0.66 |
Phenological Stage | Nutrient | Band | n | Adjusted R2 |
---|---|---|---|---|
V4 | Ca | 413, 625, 1301, 1405, 1683, 1714, 1726, 1727, 1883, 1904 | 16 | 0.98 |
Zn | 634, 1364, 1981, 1994 | 16 | 0.73 | |
R6 | Zn | 923, 925, 944, 951, 1864, 1890 | 17 | 0.90 |
R9 | K | 630, 1405 | 17 | 0.43 |
Ca | 613, 631, 1350 | 17 | 0.59 | |
All (V4, R6, R9) | P | 504, 651, 685, 1649, 1715 | 50 | 0.77 |
K | 504, 651, 685, 1715, 1735 | 50 | 0.84 | |
Ca | 705, 1890, 2377 | 50 | 0.73 | |
Zn | 751, 1715, 2434 | 50 | 0.57 |
Phenological Stage | Nutrient | Equation |
---|---|---|
V4 | Ca | Ca = 41.380740 − 10.38684 λ1683 nm − 3.63733 λ1405 nm + 1.344476 λ413 nm + 4.155283 λ1883 nm − 9.864286 λ1726 nm − 7.38664·λ1714 nm − 7.014894 λ1031 nm + 5.896256 λ1904 nm − 10.20575 λ1727 nm + 2.19506·λ625 nm |
Zn | Zn = −607.617 − 10181.2 λ634 nm + 3809.383 λ1364 nm + 2204.323 λ1994 nm − 3493.65 λ1981 nm | |
R6 | Zn | Zn = −119.164400 + 70.25752 λ944 nm + 71.05573 λ951 nm + 71.56557 λ1890 nm + 88.90969 λ1864 nm + 68.28416 λ925 nm + 67.71706 λ923 nm |
R9 | K | K = −1.65418 − 80.7834 λ630 nm + 116.8171 λ1405 nm |
Ca | Ca = 106.346000 − 252.393 λ1350 nm + 3637.852 λ631 nm − 3048.85 λ613 nm | |
All the bands together (V4. R6. R9) | P | P = 6.162487 − 124.4690 λ685 nm + 181.6616 λ651 nm − 87.4141 λ504 nm + 299.9536 λ1715 nm − 293.5019 λ1649 nm |
K | K = 8.754299 − 427.4241 λ685 nm + 2012.5704 λ651 nm − 1940.1794 λ504 nm + 2668.3838 λ1715 nm − 2624.0833λ1735 nm | |
Ca | Ca = 16.96427 + 193.3209 λ705 nm − 670.447 λ2377 nm + 458.5386 λ1890 nm | |
Zn | Zn = −92.4856 + 1803.0171 λ1715 nm − 2073.2190 λ2434 nm − 519.7374 λ751 nm |
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Amaral, J.B.C.; Lopes, F.B.; Magalhães, A.C.M.d.; Kujawa, S.; Taniguchi, C.A.K.; Teixeira, A.d.S.; Lacerda, C.F.d.; Queiroz, T.R.G.; Andrade, E.M.d.; Araújo, I.C.d.S.; et al. Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing. Appl. Sci. 2022, 12, 458. https://doi.org/10.3390/app12010458
Amaral JBC, Lopes FB, Magalhães ACMd, Kujawa S, Taniguchi CAK, Teixeira AdS, Lacerda CFd, Queiroz TRG, Andrade EMd, Araújo ICdS, et al. Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing. Applied Sciences. 2022; 12(1):458. https://doi.org/10.3390/app12010458
Chicago/Turabian StyleAmaral, Julyanne Braga Cruz, Fernando Bezerra Lopes, Ana Caroline Messias de Magalhães, Sebastian Kujawa, Carlos Alberto Kenji Taniguchi, Adunias dos Santos Teixeira, Claudivan Feitosa de Lacerda, Thales Rafael Guimarães Queiroz, Eunice Maia de Andrade, Isabel Cristina da Silva Araújo, and et al. 2022. "Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing" Applied Sciences 12, no. 1: 458. https://doi.org/10.3390/app12010458
APA StyleAmaral, J. B. C., Lopes, F. B., Magalhães, A. C. M. d., Kujawa, S., Taniguchi, C. A. K., Teixeira, A. d. S., Lacerda, C. F. d., Queiroz, T. R. G., Andrade, E. M. d., Araújo, I. C. d. S., & Niedbała, G. (2022). Quantifying Nutrient Content in the Leaves of Cowpea Using Remote Sensing. Applied Sciences, 12(1), 458. https://doi.org/10.3390/app12010458