Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types
Chlorophyll levels are a key indicator of plant nitrogen status, which plays a critical role in optimizing agricultural yields. This study evaluated the performance of three low-cost multi-spectral sensors, AS7262, AS7263, and AS7265x, for non-destructive chlorophyll measurement. Measurements were t...
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MDPI AG
2025-03-01
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| author | Prattana Lopin Pichapob Nawsang Srisangwan Laywisadkul Kyle V. Lopin |
| author_facet | Prattana Lopin Pichapob Nawsang Srisangwan Laywisadkul Kyle V. Lopin |
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| description | Chlorophyll levels are a key indicator of plant nitrogen status, which plays a critical role in optimizing agricultural yields. This study evaluated the performance of three low-cost multi-spectral sensors, AS7262, AS7263, and AS7265x, for non-destructive chlorophyll measurement. Measurements were taken from a diverse set of five leaf types, including smooth, uniform leaves (banana and mango), textured leaves (jasmine and sugarcane), and narrow leaves (rice). Partial least squares regression models were used to fit sensor spectra to chlorophyll levels, using nested cross-validation to ensure robust model evaluation. Sensor performance was assessed using <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> and mean absolute error (MAE) scores. The AS7265x demonstrated the best performance on smooth, uniform leaves with validation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores of 0.96–0.95. Its performance decreased for the other leaves, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores of 0.75–0.85. The AS7262 and AS7263 sensors, while slightly less accurate, achieved reasonable <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores ranging from 0.93 to 0.86 for smooth leaves, and from 0.85 to 0.73 for the other leaves. All sensors, particularly the AS7265x, show potential for non-destructive chlorophyll measurement in agricultural applications. Their low cost and reasonable accuracy make them suitable for agricultural applications such as monitoring plant nitrogen levels. |
| format | Article |
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| spelling | doaj-art-e9cde9b4283248b8a75a742b4e02eff12025-08-20T03:08:59ZengMDPI AGSensors1424-82202025-03-01257219810.3390/s25072198Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf TypesPrattana Lopin0Pichapob Nawsang1Srisangwan Laywisadkul2Kyle V. Lopin3Department of Biology, Faculty of Science, Naresuan University, Phitsanulok 65000, ThailandDepartment of Biology, Faculty of Science, Naresuan University, Phitsanulok 65000, ThailandDepartment of Biology, Faculty of Science, Naresuan University, Phitsanulok 65000, ThailandDepartment of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, ThailandChlorophyll levels are a key indicator of plant nitrogen status, which plays a critical role in optimizing agricultural yields. This study evaluated the performance of three low-cost multi-spectral sensors, AS7262, AS7263, and AS7265x, for non-destructive chlorophyll measurement. Measurements were taken from a diverse set of five leaf types, including smooth, uniform leaves (banana and mango), textured leaves (jasmine and sugarcane), and narrow leaves (rice). Partial least squares regression models were used to fit sensor spectra to chlorophyll levels, using nested cross-validation to ensure robust model evaluation. Sensor performance was assessed using <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> and mean absolute error (MAE) scores. The AS7265x demonstrated the best performance on smooth, uniform leaves with validation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores of 0.96–0.95. Its performance decreased for the other leaves, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores of 0.75–0.85. The AS7262 and AS7263 sensors, while slightly less accurate, achieved reasonable <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> scores ranging from 0.93 to 0.86 for smooth leaves, and from 0.85 to 0.73 for the other leaves. All sensors, particularly the AS7265x, show potential for non-destructive chlorophyll measurement in agricultural applications. Their low cost and reasonable accuracy make them suitable for agricultural applications such as monitoring plant nitrogen levels.https://www.mdpi.com/1424-8220/25/7/2198chlorophyll sensorslow-cost sensorsspectral sensorsspectral reflectancepartial least squares regressionnested cross-validation |
| spellingShingle | Prattana Lopin Pichapob Nawsang Srisangwan Laywisadkul Kyle V. Lopin Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types Sensors chlorophyll sensors low-cost sensors spectral sensors spectral reflectance partial least squares regression nested cross-validation |
| title | Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types |
| title_full | Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types |
| title_fullStr | Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types |
| title_full_unstemmed | Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types |
| title_short | Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types |
| title_sort | evaluation of low cost multi spectral sensors for measuring chlorophyll levels across diverse leaf types |
| topic | chlorophyll sensors low-cost sensors spectral sensors spectral reflectance partial least squares regression nested cross-validation |
| url | https://www.mdpi.com/1424-8220/25/7/2198 |
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