Publications by authors named "Huichun Ye"

7 Publications

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Using continous wavelet analysis for monitoring wheat yellow rust in different infestation stages based on unmanned aerial vehicle hyperspectral images.

Appl Opt 2020 Sep;59(26):8003-8013

Yellow rust is the most extensive disease in wheat cultivation, seriously affecting crop quality and yield. This study proposes sensitive wavelet features (WFs) for wheat yellow rust monitoring based on unmanned aerial vehicle hyperspectral imagery of different infestation stages [26 days after inoculation (26 DAI) and 42 DAI]. Furthermore, we evaluated the monitoring ability of WFs and vegetation indices on wheat yellow rust through linear discriminant analysis and support vector machine (SVM) classification frameworks in different infestation stages, respectively. The results show that WFs-SVM have promising potential for wheat yellow rust monitoring in both the 26 DAI and 42 DAI stages.
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http://dx.doi.org/10.1364/AO.397844DOI Listing
September 2020

Identification of Head Blight in Winter Wheat Ears Using Continuous Wavelet Analysis.

Sensors (Basel) 2019 Dec 19;20(1). Epub 2019 Dec 19.

Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.

head blight in winter wheat ears produces the highly toxic mycotoxin deoxynivalenol (DON), which is a serious problem affecting human and animal health. Disease identification directly on ears is important for selective harvesting. This study aimed to investigate the spectroscopic identification of head blight by applying continuous wavelet analysis (CWA) to the reflectance spectra (350 to 2500 nm) of wheat ears. First, continuous wavelet transform was used on each of the reflectance spectra and a wavelet power scalogram as a function of wavelength location and the scale of decomposition was generated. The coefficient of determination between wavelet powers and the disease infestation ratio were calculated by using linear regression. The intersections of the top 5% regions ranking in descending order based on the values and the statistically significant (-value of -test < 0.001) wavelet regions were retained as the sensitive wavelet feature regions. The wavelet powers with the highest values of each sensitive region were retained as the initial wavelet features. A threshold was set for selecting the optimal wavelet features based on the coefficient of correlation obtained via the correlation analysis among the initial wavelet features. The results identified six wavelet features which include (471 nm, scale 4), (696 nm, scale 1), (841 nm, scale 4), (963 nm, scale 3), (1069 nm, scale 3), and (2272 nm, scale 4). A model for identifying head blight based on the six wavelet features was then established using Fisher linear discriminant analysis. The model performed well, providing an overall accuracy of 88.7% and a kappa coefficient of 0.775, suggesting that the spectral features obtained using CWA can potentially reflect the infestation of head blight in winter wheat ears.
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http://dx.doi.org/10.3390/s20010020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982701PMC
December 2019

Fabrication of high fill factor cylindrical microlens array with isolated thermal reflow.

Appl Opt 2018 Sep;57(25):7296-7302

We demonstrate a simple, controllable, and stable method for fabricating high fill factor cylindrical microlens array with a novel isolated thermal reflow process. In this method, microstripes with a very small gap were obtained via digital micromirror device-based lithography, then covered with polydimethylsiloxane (PDMS) solution. The prepared microstripes were isolated and were heated and reflowed to a cylindrical microlens array. During the reflow process, the semicross-linked PDMS can serve as a barrier to prevent the diameter change and the bonding of adjacent microlenses. By this special treatment, the fill factor of the cylindrical microlens array can be significantly improved. Moreover, the reflow time and temperature have very little effect on the microlens shape due to the surrounded semicross-linked PDMS. This will make our process stabler than traditional methods. The measured 3D profile is good and satisfactory, and excellent optical performance is demonstrated with the fabricated cylindrical microlens arrays. The proposed method may offer a viable route for fabrication of high fill factor microlens arrays in a very simple and stable way.
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http://dx.doi.org/10.1364/AO.57.007296DOI Listing
September 2018

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

Sensors (Basel) 2018 Jun 11;18(6). Epub 2018 Jun 11.

Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100094, China.

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast (), and glume blight () in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.
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http://dx.doi.org/10.3390/s18061901DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021985PMC
June 2018

Off-Nadir Hyperspectral Sensing for Estimation of Vertical Profile of Leaf Chlorophyll Content within Wheat Canopies.

Sensors (Basel) 2017 Nov 23;17(12). Epub 2017 Nov 23.

Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China.

Monitoring the vertical profile of leaf chlorophyll (Chl) content within winter wheat canopies is of significant importance for revealing the real nutritional status of the crop. Information on the vertical profile of Chl content is not accessible to nadir-viewing remote or proximal sensing. Off-nadir or multi-angle sensing would provide effective means to detect leaf Chl content in different vertical layers. However, adequate information on the selection of sensitive spectral bands and spectral index formulas for vertical leaf Chl content estimation is not yet available. In this study, all possible two-band and three-band combinations over spectral bands in normalized difference vegetation index (NDVI)-, simple ratio (SR)- and chlorophyll index (CI)-like types of indices at different viewing angles were calculated and assessed for their capability of estimating leaf Chl for three vertical layers of wheat canopies. The vertical profiles of Chl showed top-down declining trends and the patterns of band combinations sensitive to leaf Chl content varied among different vertical layers. Results indicated that the combinations of green band (520 nm) with NIR bands were efficient in estimating upper leaf Chl content, whereas the red edge (695 nm) paired with NIR bands were dominant in quantifying leaf Chl in the lower layers. Correlations between published spectral indices and all NDVI-, SR- and CI-like types of indices and vertical distribution of Chl content showed that reflectance measured from 50°, 30° and 20° backscattering viewing angles were the most promising to obtain information on leaf Chl in the upper-, middle-, and bottom-layer, respectively. Three types of optimized spectral indices improved the accuracy for vertical leaf Chl content estimation. The optimized three-band CI-like index performed the best in the estimation of vertical distribution of leaf Chl content, with R² of 0.84-0.69, and RMSE of 5.37-5.56 µg/cm² from the top to the bottom layers, while the optimized SR-like index was recommended for the bottom Chl estimation due to its simple and universal form. We suggest that it is necessary to take into account the penetration characteristic of the light inside the canopy for different Chl absorption regions of the spectrum and the formula used to derive spectral index when estimating the vertical profile of leaf Chl content using off-nadir hyperspectral data.
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http://dx.doi.org/10.3390/s17122711DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751501PMC
November 2017

Spatial variability of available soil microelements in an ecological functional zone of Beijing.

Environ Monit Assess 2015 Feb 27;187(2):13. Epub 2015 Jan 27.

Department of Soil and Water Sciences, China Agricultural University, Beijing, 100193, China.

Understanding the spatial variability of soil microelements and its influencing factors is of importance for a number of applications such as scientifically formulated fertilizer and environmental protection. This study used descriptive statistics and geostatistics to investigate the spatial variability of available soil Fe, Mn, Cu, and Zn contents in agricultural topsoil (0-20 cm) in an ecological functional zone located at Yanqing County, Beijing, China. Kriging method was applied to map the spatial patterns of available soil Fe, Mn, Cu, and Zn contents. Results showed that the available soil Cu had a widest spatial correlation distance (e.g., 9.6 km), which for available soil Fe, Mn, and Zn were only 1.29, 2.58, and 0.99 km, respectively. The values of C 0/sill for available soil Fe and Zn were 0.12 and 0.11, respectively, demonstrating that the spatial heterogeneity was mainly due to structural factors. The available soil Mn and Cu had the larger values of C 0/sill (i.e., 0.50 and 0.44 for Mn and Cu, respectively), which showed a medium spatial correlation. Mapping of the spatial patterns of the four microelements showed that the decrease trend of available soil Fe and Mn were from northeast to southwest across the study area. The highest amount of available soil Cu was distributed in the middle of the study area surrounding urban region which presented as a "single island". The highest amount of available soil Zn was mainly distributed in the north and south of the study area. One-way analysis of variance for the influencing factors showed that the lithology of parental materials, soil organic matter, and pH were important factors affecting spatial variability of the available microelements. The topography only had a significant influence on the spatial variability of available soil Fe and Mn contents, parental materials, and the land use types had little influence on the spatial variability.
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http://dx.doi.org/10.1007/s10661-014-4230-7DOI Listing
February 2015

Heteroaggregation of microparticles with nanoparticles changes the chemical reversibility of the microparticles' attachment to planar surfaces.

J Colloid Interface Sci 2014 May 31;421:103-13. Epub 2014 Jan 31.

Department of Soil and Water Sciences, China Agricultural University, Beijing 100193, China. Electronic address:

This study theoretically investigated detachment of homoaggregates and heteroaggregates attached on the planar surfaces at primary minima during transients in solution chemistry. The homoaggregates were represented as small colloidal clusters with well-defined structures or as clusters generated by randomly packing spheres using Monte Carlo method. The heteroaggregates were modeled as microparticles coated with nanoparticles. Surface element integration technique was adopted to calculate Derjaguin-Landau-Verwey-Overbeek (DLVO) interaction energies for the homoaggregates and heteroaggregates at different ionic strengths. Results show that attached homoaggregates on the planar surface at primary minima are irreversible to reduction in solution ionic strength whether the primary spheres of the homoaggregates are nano- or micro-sized. Heteroaggregation of nanoparticles with a microparticle can cause DLVO interaction energy to decrease monotonically with separation distance at low ionic strengths (e.g., ⩽0.01M), indicating that the heteroaggregates experience repulsive forces at all separation distances. Therefore, attachment of the heteroaggregates at primary minima can be detached upon reduction in ionic strength. Additionally, we showed that the adhesive forces and torques that the aforementioned heteroaggregates experience can be significantly smaller than those experienced by the microspheres without attaching nanoparticles, thus, the heteroaggregates are readily detached via hydrodynamic drag. Results of study provide plausible explanation for the observations in the literature that attached/aggregated particles can be detached/redispersed from primary minima upon reduction in ionic strength, which challenges the common belief that attachment/aggregation of particles in primary minima is chemically irreversible.
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http://dx.doi.org/10.1016/j.jcis.2014.01.033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094237PMC
May 2014