A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture
<p>Relative sensitivity and luminous in AS7341 integrated board. (<b>a</b>) Relative sensitivity of the AS7341. (<b>b</b>) Relative luminous intensity profile of the EAHC2835WD6 LED.</p> "> Figure 2
<p>Assembly and list of mechanical parts.</p> "> Figure 3
<p>Electronic connection diagram.</p> "> Figure 4
<p>Color checker and reflectivity curves [<a href="#B33-instruments-08-00024" class="html-bibr">33</a>]. In the figure, the distribution of the rows and columns corresponds to the original Color checker, and within each patch the reflectance curve is shown as a reference.</p> "> Figure 5
<p>Architecture of the proposed MLP.</p> "> Figure 6
<p>Experimental setup used to measure the reflectance with different colors using an OSA.</p> "> Figure 7
<p>Photograph of the constructed spectrometer. (<b>a</b>) View of the entire device. (<b>b</b>) Detailed view of the area where the samples were located. The numbers in the figure correspond to the identification in the <a href="#instruments-08-00024-f002" class="html-fig">Figure 2</a>.</p> "> Figure 8
<p>Comparison of the fits of multiple patches. MEA is the color checker reference reflectance. SEN is the raw reflectance, while ADJ is the best MLP setup-adjusted reflectance.</p> "> Figure 8 Cont.
<p>Comparison of the fits of multiple patches. MEA is the color checker reference reflectance. SEN is the raw reflectance, while ADJ is the best MLP setup-adjusted reflectance.</p> "> Figure 9
<p>Validation with a reference method based on the use of a Yokogawa AQ6373 optical spectrum analyzer. MEA is the OSA reference reflectance. SEN is the raw reflectance, while ADJ is the best MLP setup-adjusted reflectance.</p> "> Figure 10
<p>Measurements of transmittance and reflectance on a vegetable leaf.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Multispectral Sensor
2.2. Mechanical Design
2.3. Electronic Design
2.4. Color Checker
2.5. Machine Learning Algorithm
2.6. Measurement of Reflectance Using an Optical Spectrum Analyzer (OSA)
3. Results and Discussions
3.1. Assembly and Manufacturing
3.2. Model Selection and Training Error
3.3. Validation Error
4. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
LED | Light-emitting diode |
MLP | Multilayer perceptron |
MCU | Microcontroller unit |
VIS-NIR-SWIR | Visible–short-wave near-infrared |
LWC | Leaf water content |
SLA | Specific leaf area |
CHL | Chlorophyll content |
PLSR | Partial least-squares regression |
SVR | Support vector regression |
ML | Machine learning |
ANN | Artificial neural network |
IoT | Internet of things |
NIR | Near-infrared |
CMOS | Complementary metal-oxide semiconductor |
BW | Bandwidths |
ReLU | Rectified linear unit |
OSA | Optical spectrum analyzer |
PLA | Polylactic acid |
ASA | Acrylonitrile styrene acrylate |
UV | Ultraviolet |
MAE | Mean absolute error |
MEA | Reference reflectance |
SEN | Raw reflectance |
ADJ | Adjusted reflectance |
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Hidden Layers | Metric | Neurons per Layer | |||
---|---|---|---|---|---|
8 | 16 | 32 | 64 | ||
1 | MAE | 0.1315 | 0.0929 | 0.0721 | 0.0645 |
Total P | 152 | 304 | 608 | 1216 | |
2 | MAE | 0.1203 | 0.0874 | 0.0562 | 0.0398 |
Total P | 216 | 560 | 1632 | 5312 | |
3 | MAE | 0.1469 | 0.0639 | 0.0581 | 0.0356 |
Total P | 280 | 816 | 2656 | 9408 | |
4 | MAE | 0.0862 | 0.0538 | 0.0521 | 0.0515 |
Total P | 344 | 1072 | 3680 | 13,504 |
Patch | 415 | 445 | 480 | 515 | 555 | 590 | 630 | 680 | 910 | MAE |
---|---|---|---|---|---|---|---|---|---|---|
P01 [SEN] | 0.1012 | 0.0118 | 0.2234 | 0.0368 | 0.1864 | 0.0130 | 0.0884 | 0.1934 | 1.0643 | 0.2132 |
P01 [ADJ] | 0.0279 | 0.0385 | 0.0290 | 0.0551 | 0.0401 | 0.0770 | 0.0589 | 0.0614 | 0.1156 | 0.0559 |
P02 [SEN] | 0.3808 | 0.1078 | 0.0103 | 0.1876 | 0.1047 | 0.0943 | 0.0738 | 0.7812 | 1.7260 | 0.3852 |
P02 [ADJ] | 0.0313 | 0.0029 | 0.0150 | 0.0357 | 0.0036 | 0.0210 | 0.0463 | 0.0104 | 0.0646 | 0.0257 |
P03 [SEN] | 0.6498 | 0.2385 | 0.0053 | 0.0768 | 0.1175 | 0.0029 | 0.1751 | 0.0848 | 0.4497 | 0.2000 |
P03 [ADJ] | 0.0403 | 0.0250 | 0.0161 | 0.0721 | 0.0065 | 0.0913 | 0.0531 | 0.0571 | 0.0225 | 0.0427 |
P03 [SEN] | 0.0429 | 0.0284 | 0.2440 | 0.0331 | 0.1150 | 0.0263 | 0.1560 | 0.0562 | 0.2717 | 0.1082 |
P04 [ADJ] | 0.0449 | 0.0554 | 0.0190 | 0.0431 | 0.0510 | 0.0801 | 0.0747 | 0.0808 | 0.0567 | 0.0562 |
P04 [SEN] | 0.9657 | 0.3412 | 0.0406 | 0.1565 | 0.0973 | 0.0891 | 0.0339 | 0.4455 | 1.8225 | 0.4436 |
P05 [ADJ] | 0.0342 | 0.0177 | 0.0080 | 0.0426 | 0.0296 | 0.0665 | 0.0592 | 0.0616 | 0.0724 | 0.0435 |
P05 [SEN] | 0.7042 | 0.2666 | 0.2109 | 0.3292 | 0.1404 | 0.1496 | 0.1012 | 0.1640 | 1.7104 | 0.4196 |
P06 [ADJ] | 0.0497 | 0.0378 | 0.0101 | 0.0236 | 0.0211 | 0.1040 | 0.0426 | 0.0310 | 0.0197 | 0.0377 |
P07 [SEN] | 0.0105 | 0.0773 | 0.2417 | 0.0857 | 0.2464 | 0.1702 | 0.1416 | 0.6489 | 1.5542 | 0.3529 |
P07 [ADJ] | 0.0050 | 0.0303 | 0.0031 | 0.0267 | 0.0228 | 0.0100 | 0.0364 | 0.0184 | 0.0912 | 0.0271 |
P08 [SEN] | 0.5888 | 0.1922 | 0.0655 | 0.0156 | 0.2270 | 0.0996 | 0.2344 | 0.1208 | 1.3312 | 0.3195 |
P08 [ADJ] | 0.0204 | 0.0534 | 0.0349 | 0.0416 | 0.0097 | 0.0933 | 0.0382 | 0.0942 | 0.0209 | 0.0452 |
P09 [SEN] | 0.2375 | 0.0238 | 0.2259 | 0.0750 | 0.2776 | 0.1239 | 0.0531 | 0.5936 | 1.0351 | 0.2939 |
P09 [ADJ] | 0.0256 | 0.0132 | 0.0354 | 0.0044 | 0.0226 | 0.0151 | 0.0561 | 0.0554 | 0.0406 | 0.0298 |
P10 [SEN] | 0.3255 | 0.0625 | 0.2291 | 0.0849 | 0.2573 | 0.0887 | 0.2812 | 0.0069 | 1.3823 | 0.3021 |
P10 [ADJ] | 0.0263 | 0.0351 | 0.0439 | 0.0497 | 0.0188 | 0.0606 | 0.0419 | 0.0087 | 0.0832 | 0.0409 |
P11 [SEN] | 0.0169 | 0.0674 | 0.2801 | 0.0546 | 0.0208 | 0.1054 | 0.1356 | 0.2398 | 1.3895 | 0.2567 |
P11 [ADJ] | 0.0119 | 0.0022 | 0.0069 | 0.0271 | 0.0058 | 0.0449 | 0.0694 | 0.0259 | 0.0369 | 0.0257 |
P12 [SEN] | 0.0000 | 0.1064 | 0.2430 | 0.1812 | 0.0394 | 0.2092 | 0.1318 | 0.7150 | 1.2315 | 0.3175 |
P12 [ADJ] | 0.0238 | 0.0170 | 0.0311 | 0.0092 | 0.0269 | 0.0396 | 0.0538 | 0.0048 | 0.0462 | 0.0280 |
P13 [SEN] | 0.3315 | 0.0997 | 0.1245 | 0.1055 | 0.2678 | 0.1416 | 0.2724 | 0.1534 | 1.1325 | 0.2921 |
P13 [ADJ] | 0.0025 | 0.0553 | 0.0270 | 0.0426 | 0.0185 | 0.0575 | 0.0544 | 0.0562 | 0.1125 | 0.0474 |
P14 [SEN] | 0.0158 | 0.0537 | 0.2410 | 0.0965 | 0.0725 | 0.0297 | 0.2062 | 0.0123 | 1.4320 | 0.2400 |
P14 [ADJ] | 0.0307 | 0.0325 | 0.0007 | 0.0576 | 0.0269 | 0.0461 | 0.0894 | 0.1021 | 0.0494 | 0.0484 |
P15 [SEN] | 0.0098 | 0.0846 | 0.2627 | 0.0875 | 0.2666 | 0.1928 | 0.2773 | 0.8341 | 1.3656 | 0.3757 |
P15 [ADJ] | 0.0169 | 0.0103 | 0.0251 | 0.0116 | 0.0156 | 0.0189 | 0.0771 | 0.0095 | 0.0184 | 0.0226 |
P16 [SEN] | 0.0557 | 0.1246 | 0.3437 | 0.0742 | 0.0513 | 0.1108 | 0.0020 | 0.5942 | 1.3167 | 0.2970 |
P16 [ADJ] | 0.0057 | 0.0023 | 0.0045 | 0.0040 | 0.0098 | 0.0355 | 0.0323 | 0.0089 | 0.1889 | 0.0324 |
P17 [SEN] | 0.7284 | 0.2087 | 0.1461 | 0.0436 | 0.2874 | 0.1565 | 0.1141 | 0.8319 | 1.7266 | 0.4715 |
P17 [ADJ] | 0.0184 | 0.0290 | 0.0576 | 0.0576 | 0.0087 | 0.0505 | 0.0622 | 0.0544 | 0.0079 | 0.0385 |
P18 [SEN] | 0.4446 | 0.1416 | 0.0936 | 0.1539 | 0.1740 | 0.1279 | 0.2828 | 0.1200 | 0.7277 | 0.2518 |
P18 [ADJ] | 0.0471 | 0.0310 | 0.0173 | 0.0716 | 0.0111 | 0.1187 | 0.0802 | 0.1067 | 0.0570 | 0.0601 |
P19 [SEN] | 1.4357 | 0.5724 | 0.3193 | 0.2977 | 0.0149 | 0.1225 | 0.0530 | 0.7924 | 1.6289 | 0.5819 |
P19 [ADJ] | 0.0611 | 0.0254 | 0.0440 | 0.0154 | 0.0083 | 0.0174 | 0.0234 | 0.0012 | 0.2344 | 0.0478 |
P20 [SEN] | 1.1232 | 0.4129 | 0.1501 | 0.2183 | 0.0188 | 0.1730 | 0.0699 | 0.5621 | 0.9140 | 0.4047 |
P20 [ADJ] | 0.1143 | 0.0207 | 0.0133 | 0.0011 | 0.0197 | 0.0025 | 0.0375 | 0.0301 | 0.1775 | 0.0463 |
P21 [SEN] | 0.7640 | 0.2806 | 0.0368 | 0.1537 | 0.0237 | 0.1206 | 0.0007 | 0.3400 | 0.4858 | 0.2451 |
P21 [ADJ] | 0.0419 | 0.0096 | 0.0003 | 0.0010 | 0.0198 | 0.0264 | 0.0475 | 0.0143 | 0.0400 | 0.0223 |
P22 [SEN] | 0.4042 | 0.1519 | 0.0880 | 0.0614 | 0.0959 | 0.0415 | 0.0905 | 0.1240 | 0.1185 | 0.1307 |
P22 [ADJ] | 0.0077 | 0.0453 | 0.0262 | 0.0447 | 0.0356 | 0.0908 | 0.0660 | 0.0655 | 0.0887 | 0.0523 |
P23 [SEN] | 0.1137 | 0.0146 | 0.2116 | 0.0432 | 0.1964 | 0.0685 | 0.1903 | 0.0288 | 0.0338 | 0.1001 |
P23 [ADJ] | 0.0116 | 0.0417 | 0.0096 | 0.0541 | 0.0080 | 0.0639 | 0.0822 | 0.1089 | 0.1339 | 0.0571 |
P24 [SEN] | 0.0241 | 0.0847 | 0.2855 | 0.0995 | 0.2447 | 0.1177 | 0.2359 | 0.1029 | 0.1286 | 0.1471 |
P24 [ADJ] | 0.0042 | 0.0117 | 0.0029 | 0.0355 | 0.0096 | 0.0398 | 0.0370 | 0.0378 | 0.0165 | 0.0217 |
MAE [SEN] | 0.3948 | 0.1564 | 0.1801 | 0.1147 | 0.1477 | 0.1073 | 0.1417 | 0.3561 | 1.0825 | 0.2979 |
MAE [ADJ] | 0.0293 | 0.0268 | 0.0200 | 0.0345 | 0.0188 | 0.0530 | 0.0550 | 0.0461 | 0.0748 | 0.0398 |
Color | 415 | 445 | 480 | 515 | 555 | 590 | 630 | 680 | 910 | MAE |
---|---|---|---|---|---|---|---|---|---|---|
C01 [SEN] | 0.0610 | 0.0084 | 0.0698 | 0.0605 | 0.0579 | 0.0015 | 0.0461 | 0.2506 | 0.5129 | 0.1187 |
C01 [ADJ] | 0.0443 | 0.0062 | 0.0168 | 0.0093 | 0.0400 | 0.0193 | 0.0494 | 0.0084 | 0.0297 | 0.0248 |
C02 [SEN] | 0.0386 | 0.0210 | 0.0976 | 0.0704 | 0.0651 | 0.0066 | 0.0053 | 0.1931 | 0.4643 | 0.1069 |
C02 [ADJ] | 0.0043 | 0.0430 | 0.0008 | 0.0740 | 0.0079 | 0.0773 | 0.0232 | 0.0728 | 0.0281 | 0.0368 |
C03 [SEN] | 0.0022 | 0.0108 | 0.0864 | 0.0128 | 0.0430 | 0.0152 | 0.0230 | 0.2283 | 0.4864 | 0.1009 |
C03 [ADJ] | 0.0226 | 0.0041 | 0.0202 | 0.0002 | 0.0280 | 0.0624 | 0.0062 | 0.0008 | 0.0297 | 0.0193 |
C04 [SEN] | 0.1804 | 0.0722 | 0.0006 | 0.0054 | 0.0486 | 0.0056 | 0.0561 | 0.2513 | 0.5210 | 0.1268 |
C04 [ADJ] | 0.0447 | 0.0042 | 0.0589 | 0.0106 | 0.0303 | 0.0014 | 0.1478 | 0.0316 | 0.0305 | 0.0400 |
C05 [SEN] | 0.4016 | 0.1510 | 0.0793 | 0.0342 | 0.0219 | 0.0321 | 0.0118 | 0.1860 | 0.5104 | 0.1587 |
C05 [ADJ] | 0.1216 | 0.0437 | 0.0233 | 0.0605 | 0.0137 | 0.0207 | 0.0036 | 0.0792 | 0.0300 | 0.0440 |
C06 [SEN] | 0.1365 | 0.0200 | 0.0457 | 0.0268 | 0.0792 | 0.0604 | 0.0654 | 0.0024 | 0.4364 | 0.0970 |
C06 [ADJ] | 0.0119 | 0.0717 | 0.0308 | 0.0321 | 0.0207 | 0.0362 | 0.0151 | 0.0251 | 0.0247 | 0.0298 |
C07 [SEN] | 0.3073 | 0.0869 | 0.0080 | 0.0454 | 0.0432 | 0.0265 | 0.0418 | 0.0438 | 0.4413 | 0.1160 |
C07 [ADJ] | 0.1468 | 0.1245 | 0.1129 | 0.0800 | 0.1455 | 0.0035 | 0.0385 | 0.0684 | 0.0258 | 0.0829 |
C08 [SEN] | 0.0315 | 0.0702 | 0.1317 | 0.0139 | 0.0925 | 0.0664 | 0.0964 | 0.0536 | 0.5008 | 0.1174 |
C08 [ADJ] | 0.0531 | 0.0515 | 0.0791 | 0.0369 | 0.0658 | 0.0343 | 0.0075 | 0.0201 | 0.0279 | 0.0418 |
C09 [SEN] | 0.0045 | 0.0501 | 0.0204 | 0.0599 | 0.0164 | 0.0038 | 0.0347 | 0.0731 | 0.4641 | 0.0808 |
C09 [ADJ] | 0.0249 | 0.0494 | 0.0210 | 0.0250 | 0.0728 | 0.0224 | 0.0104 | 0.0353 | 0.0275 | 0.0321 |
MAE [SEN] | 0.1293 | 0.0545 | 0.0599 | 0.0366 | 0.0520 | 0.0242 | 0.0423 | 0.1425 | 0.4820 | 0.1137 |
MAE [ADJ] | 0.0527 | 0.0442 | 0.0404 | 0.0365 | 0.0472 | 0.0308 | 0.0335 | 0.0380 | 0.0282 | 0.0391 |
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Botero-Valencia, J.; Reyes-Vera, E.; Ospina-Rojas, E.; Prieto-Ortiz, F. A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture. Instruments 2024, 8, 24. https://doi.org/10.3390/instruments8010024
Botero-Valencia J, Reyes-Vera E, Ospina-Rojas E, Prieto-Ortiz F. A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture. Instruments. 2024; 8(1):24. https://doi.org/10.3390/instruments8010024
Chicago/Turabian StyleBotero-Valencia, Juan, Erick Reyes-Vera, Elizabeth Ospina-Rojas, and Flavio Prieto-Ortiz. 2024. "A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture" Instruments 8, no. 1: 24. https://doi.org/10.3390/instruments8010024
APA StyleBotero-Valencia, J., Reyes-Vera, E., Ospina-Rojas, E., & Prieto-Ortiz, F. (2024). A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture. Instruments, 8(1), 24. https://doi.org/10.3390/instruments8010024