Authors
| Filter results2 paper(s) found. |
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1. Airborne Spectral Detection of Leaf Chlorophyll Concentration in Wild BlueberriesLeaf chlorophyll concentration (LCC) detection is crucial for monitoring crop physiological status, assessing the overall health of crops, and estimating their photosynthetic potential. Fast, non-destructive, and spatially extensive monitoring of LCC in crops is critical for accurately diagnosing and assessing crop health in large commercial fields. Advancements in hyperspectral remote sensing offer non-destructive and spatially extensive alternatives for monitoring plant parameters such as LCC.... K. Barai, C. Ewanik, V. Dhiman, Y. Zhang, U.R. Hodeghatta |
2. Predicting Water Potentials of Wild Blueberries During Drought Treatment Using Hyperspectral Sensor and Machine LearningDetecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using... Y. Zhang, U.R. Hodeghatta, V. Dhiman, K. Barai, T. Trang |