Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (∼2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible nea...
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of...
Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant...
International audienceThe prediction of carbon uptake by forests across fertility gradients requires...
Photosynthesis is currently measured using time-laborious and/or destructive methods which slows res...
Spectroscopy is becoming an increasingly powerful tool to alleviate the challenges of traditional me...
High-throughput and large-scale data are part of a new era of plant remote sensing science. Quantifi...
Photosynthetic efficiency of higher plants dynamically adapts to changing light intensity and is gre...
The spectral reflectance signature of living organisms pro-vides information that closely reflects t...
The possibility of predicting plant leaf chemical properties using hyperspectral images was studied....
The possibility of predicting plant leaf chemical properties using hyperspectral images was studied....
Wheat is an important cereal crop contributing to global food security. Growing human population req...
Remote sensing and spectral reflectance measurements of plants has long been used to assess the grow...
Hyperspectral imaging linked to subsequent neural networks based analysis has proven its suitability...
Numerous studies have investigated reflectance-based estimations of physico-chemical leaf traits suc...
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of...
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of...
Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant...
International audienceThe prediction of carbon uptake by forests across fertility gradients requires...
Photosynthesis is currently measured using time-laborious and/or destructive methods which slows res...
Spectroscopy is becoming an increasingly powerful tool to alleviate the challenges of traditional me...
High-throughput and large-scale data are part of a new era of plant remote sensing science. Quantifi...
Photosynthetic efficiency of higher plants dynamically adapts to changing light intensity and is gre...
The spectral reflectance signature of living organisms pro-vides information that closely reflects t...
The possibility of predicting plant leaf chemical properties using hyperspectral images was studied....
The possibility of predicting plant leaf chemical properties using hyperspectral images was studied....
Wheat is an important cereal crop contributing to global food security. Growing human population req...
Remote sensing and spectral reflectance measurements of plants has long been used to assess the grow...
Hyperspectral imaging linked to subsequent neural networks based analysis has proven its suitability...
Numerous studies have investigated reflectance-based estimations of physico-chemical leaf traits suc...
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of...
Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of...
Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant...
International audienceThe prediction of carbon uptake by forests across fertility gradients requires...