A5032469272- Remote Sensing in Agriculture
- Spectroscopy and Chemometric Analyses
- Leaf Properties and Growth Measurement
- Smart Agriculture and AI
- Plant nutrient uptake and metabolism
- Soil Carbon and Nitrogen Dynamics
- Nematode management and characterization studies
- Plant Disease Resistance and Genetics
- Remote Sensing and Land Use
- Rice Cultivation and Yield Improvement
Purdue University West Lafayette
2020-2023
Western corn rootworm (WCR) is one of the most devastating species in North America because its ability to cause severe production loss and grain quality damage. To control loss, it important identify infection WCR at an early stage. Because root system earliest feeding source larvae stage, assessing direct damage crucial achieving detection. Most current methods still necessitate uprooting entire plant, which could permanent destruction a original root’s structural information. measure...
Hyperspectral imaging (HSI) is being widely applied in plant phenotyping platforms. Some new HSI devices such as LeafSpec was introduced recently which can provide a high signal-over-noise ratio along with higher spectral and spatial resolutions. However, most of the previous image processing algorithms only calculated averaged spectrum from leaf, but rarely include spatially distributed information on leaf level. Meanwhile, different nutrient stresses could result color patterns be used to...
As one of the largest supplied grain crops, corn plants often require a significant amount nitrogen fertilizer for optimal yield. However, excessive usage can lead to adverse environmental consequences, especially nearby hydrological network. To precisely manage application, accurate measurement crop deficiency is necessary. Hyperspectral imaging (HSI) techniques are widely applied in plant phenotyping effectively measure traits caused by biotic or abiotic stresses. While previous HSI...
Accurate assessment of corn nitrogen content level is beneficial for growers to make informed fertilizing decisions save costs and optimize yields. Hyperspectral imaging technology has been shown be capable profiling plant's physiological statuses in a rapid noninvasive way. However, the spatial variance hyperspectral signal across leaf rarely analyzed. In this study, leveraging feature extraction ability deep learning models, both spectral information collected with handheld imager,...
Abstract Background: Plant root phenotyping technologies play an important role in breeding, plant protection, and other science research projects. The customers urgently need that are low-cost, situ, non-destructive to the roots, suitable for natural soil environment. Many recently developed methods such as minirhizotron, X-CT, MRI scanners have their unique advantages observing but they also disadvantages cannot meet all critical requirements simultaneously. Results: study this paper...
Abstract The authors have withdrawn this preprint due to erroneous posting.