Near-infrared Wavebands Research Articles

Piezo-photo coupling effect and extended optical absorption of piezoelectric-based hybrids for efficient bisphenol A degradation

The piezo-potential induced by stress or strain in piezoelectric compounds can produce an electric field, which has been demonstrated to be an effective technique for charge shifting or transfer in the domain of photocatalysis. In this study, a judicious combination of piezoelectricity and photocatalytic performance via ZIF-67N@BiFeO3@CdS composite is designed. After integrating, the intensity and scope of photo-absorption are increased. Owing to double polar electrical field in BiFeO3 and CdS, photo­generated carriers separation and transfer are efficient in Z-scheme and type-II pathway simultaneously. Extraordinary bisphenol A removal ability is achieved under visible-light and near-infrared waveband over the piezo-photocatalysis process. The related mechanism has been investigated in detail by experimental and theoretical insights. With the synergistic effect of enhanced light harvesting and piezophoto coupling behavior, this work gives an innovative vision in developing new-type piezoelectric photocatalysts.

Satellite determining dominant sources of particulate organic carbon across different eutrophic waters

Particulate organic carbon (POC) plays a vital role in carbon cycling in aquatic ecosystems. A knowledge of POC source dynamics is important for a comprehensive understanding of many biogeochmeical processes in inland and coastal waters. Yet, determining POC sources from remote sensing have not been fully explored. Using bio-optical datasets from 10 cruises in Taihu Lake, Poyang Lake, Daya Bay and the Pearl River Estuary, an optical classification scheme was developed to detect the dominant source of POC from remote sensing, taking into consideration the absorbing feature of phytoplankton pigment in the near-infrared waveband. Following the approach of POC source identification, the study waters were distinguished into two classes, the algae-based origin and detritus-dominance source. POC sources were thus mapped with 2016–2019 VIIRS imagery data, which exhibited significant temporal variability and spatial heterogeneity for the four study waters across different eutrophic states. It was observed that Poyang Lake was mostly terrigenous in all the study years and phytoplankton-related source was dominated in Daya Bay. Taihu Lake showed heterogeneous conditions varying with time and space, whereas most water areas was contributed by the terrestrial origin. Specially, the Pearl River Estuary presented a typical pattern of POC sources dynamics, with an exogenous source in the north-west waters, while endogenous in the south-east open areas. By implication, the methodology of POC source determination in the present study, will be conveniently applied to the common water color satellites and effectively identify the POC origins in time and space in future, which allows for a better understanding the carbon cycling and biogeochemical processes in inland and coastal waters with different eutrophication conditions.

Precision Chemical Weed Management Strategies: A Review and a Design of a New CNN-Based Modular Spot Sprayer

Site-specific weed control offers a great potential for herbicide savings in agricultural crops without causing yield losses and additional weed management costs in the following years. Therefore, precision weed management is an efficient tool to meet the EU targets for pesticide reduction. This review summarizes different commercial technologies and prototypes for precision patch spraying and spot spraying. All the presented technologies have in common that they consist of three essential parts. (1) Sensors and classifiers for weed/crop detection, (2) Decision algorithms to decide whether weed control is needed and to determine a suitable type and rate of herbicide. Usually, decision algorithms are installed on a controller and (3) a precise sprayer with boom section control or single nozzle control. One point that differs between some of the techniques is the way the decision algorithms classify. They are based on different approaches. Green vegetation can be differentiated from soil and crop residues based on spectral information in the visible and near-infrared wavebands (“Green on Brown”). Those sensors can be applied for real-time on/off control of single nozzles to control weeds before sowing after conservation tillage and in the inter-row area of crops. More sophisticated imaging algorithms are used to classify weeds in crops (“Green on Green”). This paper will focus on Convolutional Neural Networks (CNN) for plant species identification. Alternatively, the position of each crop can be recorded during sowing/planting and afterward herbicides can be targeted to single weeds or larger patches of weeds if the economic weed threshold is exceeded. With a standardized protocol of data communication between sensor, controller and sprayer, the user can combine different sensors with different sprayers. In this review, an ISOBUS communication protocol is presented for a spot sprayer. Precision chemical weed control can be realized with tractor-mounted sprayers and autonomous robots. Commercial systems for both classes will be introduced and their economic and environmental benefits and limitations will be highlighted. Farmers ask for robust systems with less need for maintenance and flexible application in different crops.

Racetrack resonator based integrated phase shifters on silicon nitride platform

We demonstrate a compact, low power consumption phase shifter based racetrack resonator hybrid integrated with few-layer MoS2. The phase shifter is fabricated on a low-loss SiN platform. By using wet transfer method, the few-layer MoS2 is transferred to the SiN waveguide, and the ionic liquid is introduced to form a capacitor configuration. In the presence of electrostatic doping, the effective index of MoS2-SiN waveguide can be efficiently modulated by adjusting bias voltage. The phase tuning efficiency of our device is measured as 13.24 pm/V at 1530 nm, and the corresponding VπL is calculated as 0.41 V∙cm. The results indicate that the strong light-matter interaction between few-layer MoS2 and SiN photonic device in near-infrared waveband, which can be used for low-loss integrated optical links.

Vegetation Monitoring for Mountainous Regions Using a New Integrated Topographic Correction (ITC) of the SCS + C Correction and the Shadow-Eliminated Vegetation Index

The mountainous vegetation is important to regional sustainable development. However, the topographic effect is the main obstacle to the monitoring of mountainous vegetation using remote sensing. Aiming to retrieve the reflectance of frequently-used red–green–blue and near-infrared (NIR) wavebands of rugged mountains for vegetation mapping, we developed a new integrated topographic correction (ITC) using the SCS + C correction and the shadow-eliminated vegetation index. The ITC procedure consists of image processing, data training, and shadow correction and uses a random forest machine learning algorithm. Our study using the Landsat 8 Operational Land Imager (OLI) multi-spectral images in Fujian province, China, showed that the ITC achieved high performance in topographic correction of regional mountains and in transferability from the sunny area of a scene to the shadow area of three scenes. The ITC-corrected multi-spectral image with an NIR–red–green composite exhibited flat features with impressions of relief and topographic shadow removed. The linear regression of corrected waveband reflectance vs. the cosine of the solar incidence angle showed an inclination that nearly reached the horizontal, and the coefficient of determination decreased to 0.00~0.01. The absolute relative errors of the cast shadow and the self-shadow all dramatically decreased to the range of 0.30~6.37%. In addition, the achieved detection rate of regional vegetation coverage for the three cities of Fuzhou, Putian, and Xiamen using the ITC-corrected images was 0.92~6.14% higher than that using the surface reflectance images and showed a positive relationship with the regional topographic factors, e.g., the elevation and slope. The ITC-corrected multi-spectral images are beneficial for monitoring regional mountainous vegetation. Future improvements can focus on the use of the ITC in higher-resolution imaging.

3D single-pixel imaging at the near-infrared wave band.

Focal plane detector array technology in the infrared wave band is expensive or underdeveloped, and the detection efficiency is low, while single-pixel imaging (SPI) offers better performance, such as ultrafast time response and high quantum efficiency in wide wave bands. Therefore, SPI technology can be used for infrared imaging. In this work, a near-infrared raster scan SPI system is proposed. By means of a grating to modulate height information of objects, we can further achieve three-dimensional imaging in the framework of Fourier transform profilometry. The proposed approach is demonstrated with experiments at the wavelength of 1064 nm.

Near-infrared plasmonic sensing and digital metasurface via double Fano resonances.

Plasmonic sensing that enables the detection of minute events, when the incident light field interacts with the nanostructure interface, has been widely applied to optical and biological detection. Implementation of the controllable plasmonic double Fano resonances (DFRs) offers a flexible and efficient way for plasmonic sensing. However, plasmonic sensing and digital metasurface induced by tailorable plasmonic DFRs require further study. In this work, we numerically and theoretically investigate the near-infrared plasmonic DFRs for plasmonic sensing and digital metasurface in a hybrid metasurface with concentric ϕ-shaped-hole and circular-ring-aperture unit cells. We show that a plasmonic Fano resonance, resulting from the interaction between a narrow and a wide effective dipolar modes, can be realized in the ϕ-shaped hybrid metasurface. In particular, we demonstrate that the tailoring plasmonic DFRs with distinct mechanisms of actions can be accomplished in three different ϕ-shaped hybrid metasurfaces. Moreover, the resonance mode-broadening and mode-shifting plasmonic sensing can be fulfilled by modulating the polarization orientation and the related geometric parameters of the unit cells in the near-infrared waveband, respectively. In addition, the plasmonic switch with a high ON/OFF ratio can not only be achieved but also be exploited to establish a single-bit digital metasurface, even empower to implement two- and three-bit digital metasurface characterized by the plasmonic DFRs in the telecom L-band. Our results offer a new perspective toward realizing polarization-sensitive optical sensing, passive optical switches, and programmable metasurface devices, which also broaden the landscape of subwavelength nanostructures for biosensors and optical communications.

Development of an Optical System Based on Spectral Imaging Used for a Slug Control Robot

The state-of-the-art technique to control slug pests in agriculture is the spreading of slug pellets. This method has some downsides, because slug pellets also harm beneficials and often fail because their efficiency depends on the prevailing weather conditions. This study is part of a research project which is developing a pest control robot to monitor the field, detect slugs, and eliminate them. Robots represent a promising alternative to slug pellets. They work independent of weather conditions and can distinguish between pests and beneficials. As a prerequisite, a robot must be able to reliably identify slugs irrespective of the characteristics of the surrounding conditions. In this context, the utilization of computer vision and image analysis methods are challenging, because slugs look very similar to the soil, particularly in color images. Therefore, the goal of this study was to develop an optical filter-based system that distinguishes between slugs and soil. In this context, the spectral characteristics of both slugs and soil in the visible and visible near-infrared (VNIR) wavebands were measured. Conspicuous maxima followed by conspicuous local minima were found for the reflection spectra of slugs in the near infrared range from 850 nm to 990 nm]. Thus, this enabled differentiation between slugs and soils; soils showed a monotonic increase in the intensity of the relative reflection for this wavelength. The extrema determined in the reflection spectra of slugs were used to develop and set up a slug detector device consisting of a monochromatic camera, a filter changer and two narrow bandpass filters with nominal wavelengths of 925 nm and 975 nm. The developed optical system takes two photographs of the target area at night. By subtracting the pixel values of the images, the slugs are highlighted, and the soil is removed in the image due to the properties of the reflection spectra of soils and slugs. In the resulting image, the pixels of slugs were, on average, 12.4 times brighter than pixels of soil. This enabled the detection of slugs by a threshold method.

Near-infrared nonreciprocal thermal emitters induced by asymmetric embedded eigenstates

Engineering nonreciprocal thermal radiation is of great importance in both fundamental thermal science and practical energy applications, but the design of perfect nonreciprocal thermal emitters in the near-infrared region has not been reported due to considerably weak magneto-optical (MO) responses of natural materials. In this work, by taking advantage of high-Q asymmetric embedded eigenstates (EEs) and quasi-EEs, near-complete violation of Kirchhoff’s law has been achieved within the near-infrared waveband using epsilon-near-zero/MO dielectric/metal sandwich structures. The analytical dispersion relations of guided modes are firstly derived, perfectly predicting the asymmetric resonant peaks in absorption or emission spectra. We also establish explicit rules to build the connections between angular locations of EEs and the thickness of MO dielectric layer, which allows to flexibly tailor perfect nonreciprocal properties over a wide angular range. Besides, the influence of upper layer’s thickness, material loss and different substrates in asymmetric distributions of EEs has also been discussed. The unveiled mechanisms and tunability in engineering nonreciprocal thermal radiation might pave a new way for the next-generation energy devices to break the current limit of energy transfer and conversion efficiency.

UAV−Enabled Quantification of Grazing-Induced Changes in Uniformity of Green Cover on Semiarid and Mesic Grasslands

Coverage of living (green) vegetation influences rangeland processes and biodiversity but remains a challenge to quantify at small spatial grain. We describe a technique for rapid airborne (unmanned aerial vehicle) measurements of continuous spatial coverage of living vegetation at a resolution (spatial grain) of 8 cm ground sampling distance. We then applied this technique at the pasture (paddock) scale (tens of hectares) in two contrasting grassland ecosystems (semiarid shortgrass steppe in northeastern Colorado, United States and mesic grassland in central Texas, United States) to determine effects of locally relevant grazing treatments on spatial variability and dependence (pattern) in fractional coverage of green vegetation (fractional vegetation cover; FVC). Site-specific regression models developed using reflectance in visible and near-infrared wavebands explained 90% and 89% of variance in FVC for semiarid and mesic grassland, respectively. Mean FVC was similar among shortgrass steppe pastures differing in grazing treatment (light or heavy grazing by cattle, moderate cattle grazing with prairie dogs present). In contrast, FVC was lower with rotational compared with continuous, year-long grazing in the mesic grassland. Heavy grazing in shortgrass steppe and rotational grazing in mesic grassland increased the spatial uniformity in FVC by reducing spatial variability and increasing spatial dependence in FVC, the latter by increasing the similarity in FVC values among spatially separated patches. Unmanned aerial vehicle−enabled remote sensing provides for FVC at sufficiently small spatial grain to characterize spatial variation in FVC at the pasture scale. Results can be used to evaluate the effectiveness of management actions intended to alter spatial variation in FVC to achieve conservation or diversity objectives. Enhanced capacity to monitor FVC at small spatial grain promotes adaptive management of grasslands.

Remote Sensing for Palmer Amaranth (Amaranthus palmeri S. Wats.) Detection in Soybean (Glycine max (L.) Merr.)

Field studies were conducted in 2016 and 2017 to determine if multispectral imagery collected from an unmanned aerial vehicle (UAV) equipped with a five-band sensor could successfully identify Palmer amaranth (Amaranthus palmeri) infestations of various densities growing among soybeans (Glycine max [L.] Merr.). The multispectral sensor captures imagery from five wavebands: 475 (blue), 560 (green), 668 (red), 840 (near infrared [NIR]), and 717 nm (red-edge). Image analysis was performed to examine the spectral properties of discrete Palmer amaranth and soybean plants at various weed densities using these wavebands. Additionally, imagery was subjected to supervised classification to evaluate the usefulness of classification as a tool to differentiate the two species in a field setting. Date was a significant factor influencing the spectral reflectance values of the Palmer amaranth densities. The effects of altitude on reflectance were less clear and were dependent on band and density being evaluated. The near infrared (NIR) waveband offered the best resolution in separating Palmer amaranth densities. Spectral separability in the other wavebands was less defined, although low weed densities were consistently able to be discriminated from high densities. Palmer amaranth and soybean were found to be spectrally distinct regardless of imaging date, weed density, or waveband. Soybean exhibited overall lower reflectance intensity than Palmer amaranth across all wavebands. The reflectance of both species within blue, green, red, and red-edge wavebands declined as the season progressed, while reflectance in NIR increased. Near infrared and red-edge wavebands were shown to be the most useful for species discrimination and maintained their utility at most weed densities. Palmer amaranth weed densities were found to be spectrally distinct from one another in all wavebands, with greatest distinction when using the red, NIR and red-edge wavebands. Supervised classification in a two-class system was consistently able to discriminate between Palmer amaranth and soybean with at least 80% overall accuracy. The incorporation of a weed density component into these classifications introduced an error of 65% or greater into these classifications. Reducing the number of classes in a supervised classification system could improve the accuracy of discriminating between Palmer amaranth and soybean.

General relativistic MHD simulations of non-thermal flaring in Sagittarius A*

ABSTRACT Sgr A* exhibits regular variability in its multiwavelength emission, including daily X-ray flares and roughly continuous near-infrared (NIR) flickering. The origin of this variability is still ambiguous since both inverse Compton and synchrotron emission are possible radiative mechanisms. The underlying particle distributions are also not well constrained, particularly the non-thermal contribution. In this work, we employ the GPU-accelerated general relativistic magnetohydrodynamics code H-AMR to perform a study of flare flux distributions, including the effect of particle acceleration for the first time in high-resolution 3D simulations of Sgr A*. For the particle acceleration, we use the general relativistic ray-tracing code bhoss to perform the radiative transfer, assuming a hybrid thermal+non-thermal electron energy distribution. We extract ∼60 h light curves in the sub-millimetre, NIR and X-ray wavebands, and compare the power spectra and the cumulative flux distributions of the light curves to statistical descriptions for Sgr A* flares. Our results indicate that non-thermal populations of electrons arising from turbulence-driven reconnection in weakly magnetized accretion flows lead to moderate NIR and X-ray flares and reasonably describe the X-ray flux distribution while fulfilling multiwavelength flux constraints. These models exhibit high rms per cent amplitudes, $\gtrsim 150{{\ \rm per\ cent}}$ both in the NIR and the X-rays, with changes in the accretion rate driving the 230 GHz flux variability, in agreement with Sgr A* observations.

Simulation of stray radiation from optical window with temperature-dependent spectral properties.

Stray radiation analysis coupled with a temperature field is performed for a semitransparent window, focusing on the temperature-dependent optical properties. The transient temperature response of the optical window-based encapsulation structure is first investigated under an external transient high-heat flux loading. The spectral selectivity of the window to thermal radiation is involved. Subsequently, several typical cases for stray radiation are conducted, considering the inhomogeneous optical properties caused by the temperature heterogeneity. It is found that the stray radiation distribution is more chaotic compared to the results with optical properties independent of temperature. In addition, the stray radiation power has a large deviation (150%) if one neglects the temperature dependence. Meanwhile, the difference in wave band power decreases with the wavelength rising. Additionally, the stray radiation power generated by the window is far less in the visible wave band than that in the near-infrared wave band. The results reveal that the temperature dependence in optical properties of a semitransparent window should be seriously considered when calculating the stray radiation, especially in high-precision detection devices.

Polarization-insensitive graphene photodetectors enhanced by a broadband metamaterial absorber.

Graphene, combined with plasmonic nanostructures, shows great promise for achieving desirable photodetection properties and functionalities. Here, we theoretically proposed and experimentally demonstrated a graphene photodetector based on the metamaterial absorber in the visible and near-infrared wavebands. The experimental results show that the metamaterial-based graphene photodetector (MGPD) has achieved up to 3751% of photocurrent enhancement relative to an antennasless graphene device at zero external bias. Furthermore, the polarization-independent of photoresponse has resulted from the polarization-insensitive absorption of symmetric square-ring antennas. Moreover, the spectral-dependent photocurrent enhancement, originated from the enhanced light-trapping effect, was experimentally confirmed and understood by the simulated electric field profiles. The design contributes to the development of high-performance graphene photodetectors and optoelectronic devices.

Ultra-narrowband near-infrared tunable two-dimensional perfect absorber for refractive index sensing.

An ultra-narrow-bandwidth near-infrared perfect plasmonic absorber with a periodic structure composed of metal-insulator-metal configuration is numerically designed and analyzed for a refractive index sensor. A perfect absorptivity of 99.99% and a rather narrow bandwidth of 2 nm are observed in the near-infrared wave band when the light is vertically incident in the structure. The ultra-high absorption and ultra-narrow bandwidth are explained as local surface plasmon resonance stimulated in the structure. The absorber is put into use as a plasmonic refractive index sensor with wavelength sensitivity as high as 1500 nm/RIU and figure of merit as high as 750, which significantly surpass those of many plasmonic sensors proposed in the past few decades. The designed absorber is tunable by changing geometry parameters. Because of the excellent sensing properties mentioned above, the proposed structure can be widely applied in fields such as photodetectors, biosensors, and chemical molecule detection.

Mid-Infrared Compressive Hyperspectral Imaging

Hyperspectral imaging (HSI) has been widely investigated within the context of computational imaging due to the high dimensional challenges for direct imaging. However, existing computational HSI approaches are mostly designed for the visible to near-infrared waveband, whereas less attention has been paid to the mid-infrared spectral range. In this paper, we report a novel mid-infrared compressive HSI system to extend the application domain of mid-infrared digital micromirror device (MIR-DMD). In our system, a modified MIR-DMD is combined with an off-the-shelf infrared spectroradiometer to capture the spatial modulated and compressed measurements at different spectral channels. Following this, a dual-stage image reconstruction method is developed to recover infrared hyperspectral images from these measurements. In addition, a measurement without any coding is used as the side information to aid the reconstruction to enhance the reconstruction quality of the infrared hyperspectral images. A proof-of-concept setup is built to capture the mid-infrared hyperspectral data of 64 pixels × 48 pixels × 100 spectral channels ranging from 3 to 5 μm, with the acquisition time within one minute. To the best of our knowledge, this is the first mid-infrared compressive hyperspectral imaging approach that could offer a less expensive alternative to conventional mid-infrared hyperspectral imaging systems.

Relating Hyperspectral Vegetation Indices with Soil Salinity at Different Depths for the Diagnosis of Winter Wheat Salt Stress

Abundant shallow underground brackish water resources could help in alleviating the shortage of fresh water resources and the crisis concerning agricultural water resources in the North China Plain. Improper brackish water irrigation will increase soil salinity and decrease the final yield due to salt stress affecting the crops. Therefore, it is urgent to develop a practical and low-cost method to monitor the soil salinity of brackish irrigation systems. Remotely sensed spectral vegetation indices (SVIs) of crops are promising proxies for indicating the salinity of the surface soil layer. However, there is still a challenge concerning quantitatively correlating SVIs with the salinity of deeper soil layers, in which crop roots are mainly distributed. In this study, a field experiment was conducted to investigate the relationship between SVIs and salinity measurements at four soil depths within six winter wheat plots irrigated using three salinity levels at the Yucheng Comprehensive Experimental Station of the Chinese Academy of Sciences during 2017–2019. The hyperspectral reflectance was measured during the grain-filling stage of winter wheat, since it is more sensitive to soil salinity during this period. The SVIs derived from the observed hyperspectral data of winter wheat were compared with the salinity at four soil depths. The results showed that the optimized SVIs, involving soil salt-sensitive blue, red-edge, and near-infrared wavebands, performed better when retrieving the soil salinity (R2 ≥ 0.58, root mean square error (RMSE) ≤ 0.62 g/L), especially at the 30-cm depth (R2 = 0.81, RMSE = 0.36 g/L). For practical applications, linear or quadratic models based on the screened SVIs in the form of normalized differential vegetation indices (NDVIs) could be used to retrieve soil salinity (R2 ≥ 0.63, RMSE ≤ 0.62 g/L) at all soil depths and then diagnose salt stress in winter wheat. This could provide a practical technique for evaluating regional brackish water irrigation systems.

Synthesis of polyurethane-imids and application in surface plasmon polaritons waveguide

The crosslinkable electro-optic (EO) polymers polyurethane-imides (PUI) were designed and synthesized with monomers azo chromophore, phenyl diisocyanate and aromatic dianhydrides. Molecular structure characteristics for the polymers were evidenced by nuclear magnetic resonance (1HNMR) and fourier transform infrared (FTIR) spectroscopy. PUI as cladding, the strip long-range surface plasmon polaritons (LRSPPs) waveguides were designed and fabricated. The LRSPPs waveguiding along 18-nm-thin and 8-µm-wide gold stripes buried in EO PUI polymers were characterized at the light wavelength of 1310 nm and 1550 nm. The results indicated that the PUI can be used as preparation surface plasmon polaritons EO polymer optical waveguide materials, due to the merits of crosslinkable property, thermal stability, good film-forming ability, high processability and low optical waveguide propagation loss in near-infrared wave band.

A novel method for the definition of central wavelength and spectral bandwidth

Spectral calibration is an essential step in the calibration process of multispectral camera for Mars exploration. The precision of spectral calibration has a direct impact on the accuracy of Mars multispectral data inversion. The most common method for determining the central wavelength and spectral bandwidth of a multispectral camera is to fit the spectral response using a Gaussian function. The peak value fitted by Gauss is defined as the central wavelength of the camera, and the full width of the spectral band at half maximum is defined as the spectral bandwidth. But the spectral response of the Mars exploration multispectral camera in the near-infrared waveband deviates from the Gaussian distribution. In this case, the relative output deviation and the relative radiation error are large when data inversion is performed using the central wavelength and the spectral bandwidth determined by Gaussian fitting. In this paper, the spectral response of a multispectral camera is taken as a weight function, and a generalized weighted method is proposed to redefine the central wavelength and spectral bandwidth of the multispectral camera. The central wavelength is defined as the weighted average of wavelengths against the spectral response weighted factor, while the spectral bandwidth is defined as the generalized w bandwidth when the area within the bandwidth is w% of the total area. The simulation results showed that the relative output deviation was reduced by an average of 0.1% and a maximum of 1.3%, while the relative radiation error by an average of 0.14% and by a maximum of 1.83%, when compared with the Gaussian definition. The experiment results of the Mars exploration multispectral camera showed that there was an average reduction of 0.06% in relative output deviation and 0.05% in relative radiation error. The generalized weighted method provides another way for the definition of central wavelength and spectral bandwidth, and improvs the precision of Mars multispectral data inversion.

A Novel Genetic Algorithm-Based Optimization Framework for the Improvement of Near-Infrared Quantitative Calibration Models.

The global fishmeal production is used for animal feed, and protein is the main component that provides nutrition to animals. In order to monitor and control the nutrition supply to animal husbandry, near-infrared (NIR) technology was utilized for rapid detection of protein contents in fishmeal samples. The aim of the NIR quantitative calibration is to enhance the model prediction ability, where the study of chemometric algorithms is inevitably on demand. In this work, a novel optimization framework of GSMW-LPC-GA was constructed for NIR calibration. In the framework, some informative NIR wavebands were selected by grid search moving window (GSMW) strategy, and then the variables/wavelengths in the waveband were transformed to latent principal components (LPCs) as the inputs for genetic algorithm (GA) optimization. GA operates in iterations as implementation for the secondary optimization of NIR wavebands. In steps of the variable's population evolution, the parametric scaling mode was investigated for the optimal determination of the crossover probability and the mutation operator. With the GSMW-LPC-GA framework, the NIR prediction effect on fishmeal protein was experimentally better than the effect by simply adopting the moving window calibration model. The results demonstrate that the proposed framework is suitable for NIR quantitative determination of fishmeal protein. GA was eventually regarded as an implementable method providing an efficient strategy for improving the performance of NIR calibration models. The framework is expected to provide an efficient strategy for analyzing some unknown changes and influence of various fertilizers.