This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: HyperBird, a cutting-edge imaging platform for observing microscopic traits in plants, can detect grape diseases—such as powdery and downy mildews, which cost vineyard owners billions in annual losses globally—days before physical symptoms become visible. The advancement could allow plant breeders to speed the development of disease-resistant grape varieties, cue growers to target fungicide use early in a disease's progression and provide vineyard workers with better, earlier information for crop management.
While regular cameras record three bands of wavelengths (red, blue and green) within the visible light spectrum, hyperspectral imaging records hundreds of narrow bands. With this hyperspectral power, the researchers created a high-throughput phenotyping microscope—meaning it can process hundreds of leaf samples within a few hours for observable traits related to disease resistance. This capability lets it detect changes inside a leaf before they are visible on the surface.
A trio of recently published papers outlines the arc of the technology's development. "It's harnessing the power of hyperspectral and high-throughput analysis in a much more accessible way for the scientist," said Katie Gold, assistant professor of grape pathology and Susan Eckert Lynch Faculty Fellow at Cornell AgriTech in the College of Agriculture and Life Sciences, one of three senior scientists on the papers and the HyperBird project. "We now have a physical system that allows us to translate complex questions and answer them with powerful tools in a way that's so much more accessible than ever before." "Hyperspectral information—beyond the visible range—can provide insights and deepen our understanding of many biological processes between leaf tissues and pathogens," said Yu Jiang, assistant professor and systems engineer in the School of Integrative Plant Science (SIPS), Horticulture Section, at Cornell AgriTech in CALS, who is also a senior scientist on the papers and the project.
The project also solved a major problem limiting hyperspectral imaging at microscopic scales, Jiang said. That issue concerns spatial resolution, which makes it possible to detect and distinguish a tiny spot on a leaf as a symptom of disease in relation to the surrounding pixels that represent healthy cells. "Imagine trying to find a Coke can in a photograph of a large room," Jiang said.
"If the image isn't detailed enough to separate the can from the background, the light reflected by the can gets mixed with light from everything around it. That makes its spectral signature—the distinctive pattern of light it reflects—harder to recognize." HyperBird is a hyperspectral extension of Blackbird, a prototype technology developed by Jiang and Lance Cadle-Davidson, Ph.D. '03, a research plant pathologist at the USDA's Agricultural Research Service (ARS), an adjunct associate professor in SIPS, and one of the senior project scientists and authors. In 2021, the team announced the release of Blackbird, designed to speed up the assessment of thousands of grape leaf samples for evidence of infection, which had been a bottleneck in Cadle-Davidson's lab's research to develop powdery mildew-resistant grape varieties.
Blackbird, a robotic high-throughput phenotyping camera that records in red, blue and green wavelengths, was a first step toward HyperBird's capabilities. While Blackbird provided the spatial resolution of an optical microscope, HyperBird supplies roughly 200 times more spectral resolution per pixel. This level of hyperspectral detail allows HyperBird to collect data in three dimensions per pixel.
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