Can hyperspectral measurements be used to estimate lodging and carbon content in wheat canopy?
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Hyperspectral measurements can be used to estimate carbon content in wheat canopy . However, there is no specific mention of using hyperspectral measurements to estimate lodging in wheat canopy in the provided abstracts.
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| Papers (5) | Insight |
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38 Citations | The paper does not mention the estimation of lodging or carbon content in wheat canopy using hyperspectral measurements. |
23 Citations | The paper does not mention the estimation of lodging or carbon content in wheat canopy using hyperspectral measurements. |
Open access 01 Jan 2013 14 Citations | The paper does not mention anything about estimating lodging or carbon content in wheat canopy using hyperspectral measurements. |
| Yes, hyperspectral measurements can be used to estimate carbon content in wheat canopy, but the paper does not mention estimating lodging. | |
14 Citations | The paper does not mention the use of hyperspectral measurements for estimating lodging and carbon content in wheat canopy. |
Related Questions
How can lodging in wheat be assessed?4 answersLodging in wheat can be assessed using various methods. One approach is to use unmanned aerial vehicles (UAVs) to collect canopy images and ground lodging area information at different growth stages of wheat. Another method involves processing point cloud data extracted from UAV images to assess the degree of wheat lodging. Additionally, high-definition images of wheat canopy can be collected using quadrotor UAVs, and the Unet network can be used to extract lodging areas by introducing the Involution operator and Dense block module. Furthermore, the pyramid transposed convolution network (PTCNet) can be used to extract and detect wheat lodging areas from satellite images, combining multi-scale high-level features with low-level features. Lastly, a detection method based on binocular vision can be used to determine the location and area of wheat lodging by analyzing the angle relationship between the stem and vertical direction and calculating the three-dimensional coordinates of wheat.
Which spectral bands have shown the carbon content using spectral signatures in hyperspectral measurements?3 answersHyperspectral remote sensing has been used to detect spectral signatures of carbon content in various applications, including agriculture. In the study by Bakken et al., carbon ion emission lines were observed in the spectra of C II, C III, and C IV. Johnson and Merton investigated the isolation and modification of carbon spectra using helium, and identified new carbon lines in the visible and ultraviolet spectra. Arias et al. discussed the detection of radical emissions in a natural gas flame using spectral radiation measurements, including the excited CH∗ and C 2 ∗ radicals. These studies demonstrate the use of hyperspectral measurements to detect carbon content in various contexts, such as ion emission lines, spectral bands associated with carbon spectra, and radical emissions in flames.
How can spectral signatures be used to measure the carbon content of plants?5 answersSpectral signatures can be used to measure the carbon content of plants by analyzing the absorbance data and spectral properties of vegetation. The spectral signatures of plants vary based on factors such as species, varieties, age, environmental conditions, and chemical composition. By performing spectral measurements and applying techniques like Principal Component Analysis, it is possible to identify the specific plant species and determine the relevant wavelengths or wavebands for identification. Additionally, the analysis of plant spectral signatures can help in detecting crop state differences and stress situations, providing information about plant development, physiological processes, and growth conditions. These variations in spectral signatures can be used to discriminate between stressed and healthy vegetation and quantitatively describe the impact of stress on crop agronomical parameters and yield.
How can hyperspectral measurements be used to estimate Canopy Nitrogen Content in wheat?5 answersHyperspectral measurements can be used to estimate Canopy Nitrogen Content (CNC) in wheat by analyzing the spectral reflectance of the canopy. Different spectral indices have been identified as optimal indicators for CNC retrieval in wheat. These include the red-edge band indices such as narrowband and broadband CI red-edge, as well as NDVI-like and ND 705 indices. The correlation between spectral indices and CNC varies with different observation angles, with angles of -30° and -40° showing higher correlation coefficients. Linear mixed models and random forest classifiers have been used to predict CNC based on spectral indices and canopy structure indices obtained from RGB and depth images. Additionally, a non-destructive and high-throughput method has been developed to estimate CNC from leaf hyperspectral reflectance data, which showed promising results in predicting CNC, leaf nitrogen, and leaf mass per area. These studies demonstrate the potential of hyperspectral measurements for accurate and timely estimation of CNC in wheat.
How is spectral indices used to estimate Canopy Nitrogen Content in hyperspectral measurement?4 answersSpectral indices are used to estimate canopy nitrogen content in hyperspectral measurements by analyzing the relationship between spectral reflectance and nitrogen concentration. Several studies have explored the use of spectral indices for this purpose. Patel et al. assessed the efficacy of seven canopy nitrogen indices, including the canopy chlorophyll content index (CCCI), and found that these indices showed correlation with canopy nitrogen concentration at different growth stages and seasons, but the relationships varied significantly between stages. Reyes-Trujillo et al. developed estimation models using three spectral data transformations (average reflectance spectrum, multiple scatter correction and Savitzky-Golay filter reflectance spectrum, and calculated vegetation indices) to explain nitrogen variation over time in sugarcane crops. Frels et al. investigated the relationship between vegetation indices and nitrogen use traits in wheat genotypes, finding that certain indices, such as the Maccioni index, were significantly related to nitrogen uptake and utilization efficiency. Corti et al. used hyperspectral line scan imaging to estimate crop variables in spinach canopies under water and nitrogen stress, achieving accurate estimation of nitrogen concentration from single leaf spectra hyperspectral images. Singh et al. developed spectral models using reflectance ratios to accurately predict leaf nitrogen concentration and chlorophyll content in sweet sorghum crops.
What research we can perform on multispectral data of different wheat breeds?5 answersMultispectral data of different wheat breeds can be used for various research purposes. One area of research is the assessment of lodging severity in wheat fields using high-resolution UAV data. Another research area is the establishment of a hyperspectral library of foliar diseases in wheat induced by different fungal pathogens. Multispectral and multitemporal data can also be implemented in wheat crop assessment models for agricultural monitoring and yield prediction. Additionally, multispectral scanning with real-time analog data processing can be used for wheat field recognition, mapping, and acreage measurement. Hyperspectral sensing techniques can provide valuable information on the chemical and physical properties of wheat plants, aiding in the quantification of yield-limiting factors.