Near-infrared Imaging System Research Articles

Enhancement of photoresponse for InGaAs infrared photodetectors using plasmonic WO3-x/CsyWO3-xnanocrystals.

Fast and accurate detection of light in the near-infrared (NIR) spectral range plays a crucial role in modern society, from alleviating speed and capacity bottlenecks in optical communications to enhancing the control and safety of autonomous vehicles through NIR imaging systems. Several technological platforms are currently under investigation to improve NIR photodetection, aiming to surpass the performance of established III-V semiconductor p-i-n (PIN) junction technology. These platforms include in situ-grown inorganic nanocrystals and nanowire arrays, as well as hybrid organic-inorganic materials such as graphene-perovskite heterostructures. However, challenges remain in nanocrystal and nanowire growth, large-area fabrication of high-quality 2D materials, and the fabrication of devices for practical applications. Here, we explore the potential for tailored semiconductor nanocrystals to enhance the responsivity of planar metal-semiconductor-metal (MSM) photodetectors. MSM technology offers ease of fabrication and fast response times compared to PIN detectors. We observe enhancement of the optical-to-electric conversion efficiency by up to a factor of ~2.5 through the application of plasmonically-active semiconductor nanorods and nanocrystals. We present a protocol for synthesizing and rapidly testing the performance of non-stoichiometric tungsten oxide (WO3-x) nanorods and cesium-doped tungsten oxide (CsyWO3-x) hexagonal nanoprisms prepared in colloidal suspensions and drop-cast onto photodetector surfaces. The results demonstrate the potential for a cost-effective and scalable method exploiting tailored nanocrystals to improve the performance of NIR optoelectronic devices.

Precision variety identification of shelled and in-shell pecans using hyperspectral imaging with machine learning

Pecans are essential nuts containing polyunsaturated fatty acids and dietary fiber which offer health benefits to humans. They are exported and sold in both in-shell and shelled forms. However, varietal identification poses a challenge to both producers and processors, which results in variety substitution for economic advantages. The aim of this study was to investigate the efficacy of visible near-infrared (VNIR) and near-infrared (NIR) hyperspectral imaging systems (HSI) to accurately identify pecan cultivars (Cape fear, Desirable, Stuart blend, and Sumner). The in-shell and shelled spectra were acquired using VNIR and NIR-HSI at wavelengths 400–1000 nm and 900–1700 nm, respectively. The spectra dimensionality was reduced using principal component analysis (PCA). Thereafter, the selected principal components (PCs) were used to build six machine learning classifiers (Decision Tree, Random Forest, Gradient Boosting, Partial Least Square Discriminant Analysis, Support Vector Machine, and Linear Discriminant Analysis (LDA)) for four-class classification. LDA with and without PCA achieved the highest accuracy for both pecan forms. For shelled pecans, the LDA without PCA achieved 90.59 % and increased to 91.67 % accuracy with PCA on the VNIR spectra, while the LDA without PCA achieved 93.36 % and increased to 93.52 % accuracy with PCA on the NIR spectra. For the in-shell pecans, LDA without PCA achieved 98.59 % and increased to 99.12 % accuracy with PCA on the VNIR spectra, while LDA with and without PCA achieved 98.26 % accuracy for the NIR spectra. Moreover, Successive Projection Algorithm was also implemented for wavelength selection and modeling with satisfactory results. Overall, higher accuracy was achieved in the in-shell pecan. This study revealed the usefulness of HSI systems in identifying pecan varieties.

Nutritional Quality Analysis and Classification Detection of Buckwheat in Different Harvest Periods.

For buckwheat, the optimal harvest period is difficult to determine-too early or too late a harvest affects the nutritional quality of buckwheat. In this paper, physical and chemical tests are combined with a method using near-infrared spectroscopy nondestructive testing technology to study buckwheat harvest and determine the optimal harvest period. Physical and chemical tests to determine the growth cycle were performed at 83 days, 90 days, 93 days, 96 days, 99 days, and 102 days, in which the buckwheat grain starch, fat, protein, total flavonoid, and total phenol contents were assessed. Spectral images of buckwheat in six different harvest periods were collected using a near-infrared spectral imaging system. Four preprocessing methods (SNV, S-G, DWT, and the normaliz function) and three dimensionality reduction algorithms (IVSO, VCPA, VISSA) were used to process the raw buckwheat spectral data, and the full and eigen spectra were established as a random forest (RF). Random forest (RF) and Least Squares Support Vector Machine (LS-SVM) classification models were used to determine the full and eigen spectra, respectively, and the optimal model for the buckwheat single harvest period was determined and validated. Through physical and chemical tests, it was concluded that the 90-day harvest buckwheat grain protein, fat, and starch contents were the highest, and that the total flavonoid and total phenolic contents were also high. The SNV preprocessing method was the most effective, and the feature bands extracted using the IVSO algorithm were more representative. The IVSO-RF model was the best discriminative model for the classification of buckwheat in different harvest periods, with the correct rates of the training and prediction sets reaching 100% and 96.67%, respectively. When applying the IVSO-RF model to the buckwheat single harvest period to verify the classification, the correct rate of the training set for each harvest period reached 96%, and that of the prediction set reached 100%. Near-infrared spectroscopy combined with the IVSO-RF modeling method for buckwheat harvest period detection is a rapid, nondestructive classification method. When this was combined with physical and chemical analyses, it was determined that a growth cycle of 90 days is the best harvest period for buckwheat. The results of this study can not only improve the quality of buckwheat crops but also be applied to other crops to determine their optimal harvest period.

A system for high-speed NIR transmission imaging of drug delivery in tissue

The development and characterisation of new drug delivery techniques often requires visualising the location of delivered fluid in tissue samples. The opacity of tissue means that this can typically only be done with destructive post-processing techniques, or with the use of ionising radiation (eg. X-ray). In this work we present a novel approach to imaging fluid during delivery into port-mortem tissue samples using transmission imaging at near-infrared (NIR) wavelengths. The system makes use of wavelengths just above the visible range (765 nm), at which tissue is relatively transparent, and to which visible light cameras remain sensitive. Thus, this system utilised a low-cost high-speed (1000 fps) camera and optical components designed for use with visible light. We demonstrate that this NIR imaging system is capable of measuring the location of delivered fluid and an 18G needle in 12 mm thick samples of muscle and fat tissue at 1000 fps. Predictions of needle depth using the imaging system compared well to the known needle position in the tissue: the standard deviation of the depth measurements was approximately 0.7 mm in muscle and 1.2 mm in fat. NIR images captured during and after delivery compare favourably with observations made using 2D X-ray and by sectioning the tissue post-injection. This system can support studies of fluid dispersion and penetration into tissue by new drug delivery systems, thus assist the development of new drug delivery techniques.

Simultaneous detection for storage condition and storage time of yellow peach under different storage conditions using hyperspectral imaging with multi-target characteristic selection and multi-task model

The detection for storage condition and storage time can ensure quality and safety of yellow peaches, and optimize storage management. This study explored the feasibility of simultaneously detecting the storage condition and storage time of yellow peach under different storage conditions using hyperspectral imaging technology combined with multi-target characteristic selection and multi-task model. Firstly, a total of 1080 hyperspectral images of 120 yellow peach samples under different storage conditions and different storage time were acquired using visible near-infrared hyperspectral imaging system. Subsequently, Savitzky-Golay first derivative was used to preprocess the raw spectra to improve the signal-to-noise ratio of the spectra. Distinguished index modified competitive adaptive reweighted sampling (DI-CARS) was proposed to select characteristic wavelengths that simultaneously characterize information of storage condition and storage time. Wild horse optimizer optimized support vector machine (WHO-SVM) was proposed for the multi-task modeling analysis. The results showed that multi-target characteristic selection and multi-task model not only reduced 66.67 % in computational cost, but also improved the accuracy, and multi-task WHO-SVM model based on multi-target DI-CARS achieved the optimal result with the overall accuracy reached 98.06 % and the number of characteristic wavelengths being 99. In conclusion, hyperspectral imaging combined with multi-target DI-CARS and multi-task WHO-SVM is feasible to simultaneously detect storage condition and storage time of yellow peach under different storage conditions.

Peritoneal fluid indocyanine green test for diagnosis of gut leakage in anastomotic leakage rats and colorectal surgery patients.

Application of indocyanine green (ICG) fluorescence has led to new developments in gastrointestinal surgery. However, little is known about the use of ICG for the diagnosis of postoperative gut leakage (GL). In addition, there is a lack of rapid and intuitive methods to definitively diagnose postoperative GL. To investigate the effect of ICG in the diagnosis of anastomotic leakage in a surgical rat GL model and evaluate its diagnostic value in colorectal surgery patients. Sixteen rats were divided into two groups: GL group (n = 8) and sham group (n = 8). Approximately 0.5 mL of ICG (2.5 mg/mL) was intravenously injected postoperatively. The peritoneal fluid was collected for the fluorescence test at 24 and 48 h. Six patients with rectal cancer who had undergone laparoscopic rectal cancer resection plus enterostomies were injected with 10 mL of ICG (2.5 mg/mL) on postoperative day 1. Their ostomy fluids were collected 24 h after ICG injection to identify the possibility of the ICG excreting from the peripheral veins to the enterostomy stoma. Participants who had undergone colectomy or rectal cancer resection were enrolled in the diagnostic test. The peritoneal fluids from drainage were collected 24 h after ICG injection. The ICG fluorescence test was conducted using OptoMedic endoscopy along with a near-infrared fluorescent imaging system. The peritoneal fluids from the GL group showed ICG-dependent green fluorescence in contrast to the sham group. Six samples of ostomy fluids showed green fluorescence, indicating the possibility of ICG excreting from the peripheral veins to the enterostomy stoma in patients. The peritoneal fluid ICG test exhibited a sensitivity of 100% and a specificity of 83.3% for the diagnosis of GL. The positive predictive value was 71.4%, while the negative predictive value was 100%. The likelihood ratios were 6.0 for a positive test result and 0 for a negative result. The postoperative ICG test in a drainage tube is a valuable and simple technique for the diagnosis of GL. Hence, it should be employed in clinical settings in patients with suspected GL.

Rare Earth Nanoprobes for Targeted Delineation of Triple Negative Breast Cancer and Enhancement of Radioimmunotherapy.

Radiotherapy demonstrates a synergistic effect with immunotherapy by inducing a transformation of "immune cold" tumors into "immune hot" tumors in triple negative breast cancer (TNBC). Nevertheless, the effectiveness of immunotherapy is constrained by low expression of tumor-exposed antigens, inadequate inflammation, and insufficient tumor infiltrating lymphocyte (TILs). To address this predicament, novel lutecium-based rare earth nanoparticles (RENPs) are synthesized with the aim of amplifying radiation effect and tumor immune response. The nanoprobe is characterized by neodymium-based down-conversion fluorescence, demonstrating robust photostability, biocompatibility, and targetability. The conjugation of RENPs with a CXCR4 targeted drug enables precise delineation of breast tumors using a near-infrared imaging system and improves radiation efficacy via lutetium-based radio-sensitizer invivo. Furthermore, the study shows a notable enhancement of immune response through the induction of immunogenic cell death and recruitment of TILs, resulting in the inhibition of tumor progression both invitro and invivo models following the administration of nanoparticles. Hence, the novel multifunctional nanoprobes incorporating various lanthanide elements offer the potential for imaging-guided tumor delineation, radio-sensitization, and immune activation post-radiation, thus presenting an efficient radio-immunotherapeutic approach for TNBC.

Near-infrared imaging of heat transfer behavior between gadolinium and fluid during magnetization/demagnetization process of magnetocaloric effect

This paper reports on the application of a near-infrared (NIR) imaging system for visualizing heat transfer dynamics from a bulk gadolinium (Gd) sample to the surrounding water during the magnetization/demagnetization process of the magnetocaloric effect (MCE). The suggested approach relied on the spectral variation in water absorption band at 1150 nm wavelength within the NIR spectrum. An experimental setup integrated a telecentric uniform-illumination system, a halogen lamp, and an NIR camera to enable real-time monitoring of a single magnetization and demagnetization cycle induced by an external magnetic field, which was generated by a permanent-magnet-based magnetic circuit. Two-dimensional absorbance images captured during this cycle clearly depicted the thermal energy generated by the MCE in water. Furthermore, an analysis of the thermal boundary layer and the quantification of heat transfer from Gd to water provided insights into the dynamics over time. These results indicated the potential of our NIR imaging techniques in optimizing thermal–fluid interactions within MCE systems, thereby improving the design and efficiency of magnetic refrigeration systems.

Rapid determination of residual pefloxacin in mutton based on hyperspectral imaging and data fusion

Non-destructive detection of veterinary drug residues in meat products is critical for ensuring food safety and human health. The feasibility of using visible near-infrared (Vis-NIR) and near-infrared (NIR) hyperspectral imaging (HSI) system combined with data fusion for the prediction of pefloxacin residues in mutton was investigated in this study. A partial least squares regression optimization model was developed by multivariate data processing methods. The results showed that the low-level fusion (LLF) produced better results with R2P = 0.907 and RMSEP = 0.462 as compared to individual data blocks. Furthermore, intermediate-level fusion (ILF) based on iterative retention of informative variables algorithm showed the best results with R2P = 0.940 and RMSEP = 0.375. Finally, the visualized distributions of Vis-NIR and NIR based on the optimal model combination were mapped. The results have demonstrated that a combination of HSI with data fusion may be applied to rapidly and non-destructively detect pefloxacin residues in mutton.

Perfusion outcomes with near-infrared indocyanine green imaging system in laparoscopic total mesorectal excision for mid-rectal or low-rectal cancer (POSTER): a study protocol

IntroductionAnastomotic leakage (AL) is defined as the failure of complete healing or disruption of the anastomosis subsequent to rectal cancer surgery, resulting in the extravasation of intestinal contents into the...

Phase 2 Clinical Trial of VGT-309 for Intraoperative Molecular Imaging During Pulmonary Resection

BackgroundAdvances in intraoperative molecular imaging (IMI) may improve surgical outcomes when resecting tumors in the lung. A single-center trial was conducted using VGT-309, a cathepsin-targeted near-infrared imaging agent that causes lung nodules to fluoresce during surgical resection. The end point of this phase 2 study was to evaluate the frequency that IMI with VGT-309 resulted in a clinically significant event (CSE): localization of pulmonary nodules, discovery of unsuspected additional cancers, or identification of positive margins. MethodsPatients undergoing surgical resection for known or suspected cancer in the lung received VGT-309 (0.32 mg/kg) preoperatively. During the surgical procedure, localization and resection of the nodules were performed using standard surgical techniques. Near-infrared imaging was then used to localize nodules, seek occult lesions, and assess resection margins. Efficacy was measured by the frequency of CSEs. ResultsOf the 40 patients who underwent pulmonary resection with VGT-309, 17 (42.5%) had at least 1 CSE. Near-infrared imaging identified lesions not found by standard surgical methods in 16 patients, additional cancers not found by preoperative imaging in 1 patient, and margins within 5 mm of the closest staple line in 2 patients. VGT-309 performance was tested across a broad range of tumor types and commercial near-infrared imaging systems. VGT-309 appeared safe, well-tolerated, with no infusion reactions, and no drug-related serious adverse events. ConclusionsThis phase 2 study demonstrated the utility of IMI with VGT-309 in localizing pulmonary nodules, recognizing synchronous lesions, and identifying positive margins. A multi-institutional study will further evaluate the efficacy of VGT-309.

Self-equilibrium segmentation of near-infrared images of dental microcracks

The issue of missing teeth caused by dental microcracks has become a central topic in dental clinical medicine. Near-infrared technology combined with advanced image segmentation algorithms has become one of the leading technical routes for dental clinical medicine diagnosis. In this study, the NIR image segmentation method of dental microcracks was studied in depth to further utilize the advantages of near-infrared imaging technology in the detection technology of dental microcracks. The main contributions and research contents of this paper include (1) we designed a near-infrared imaging system for dental imaging, which provides solid data support for the study of advanced segmentation algorithms; (2) we designed a self-equilibrium segmentation algorithm for occult fracture of teeth based on U-Net++. The core module of this algorithm includes a multi-resolution residual encoder and a self-equilibrium composite loss function. The multi-scale residual encoder significantly improves the feature extraction capability of U-Net++. The self-equilibrium combined loss function ensures the consistency of the model’s attention to positive and negative samples, which enhances the robustness of U-Net++. (3) We have demonstrated through extensive experiments that our algorithm performs better than other dental occultation segmentation methods. This study is valuable for improving the diagnostic accuracy of dental occult fractures and promptly detecting the potential danger of the dental.

Bifunctional Tumor-Targeted Bioprobe for Phothotheranosis.

Background: Near-infrared (NIR) phototheranostics provide promising noninvasive imaging and treatment for head and neck squamous cell carcinoma (HNSCC), capitalizing on its adjacency to skin or mucosal surfaces. Activated by laser irradiation, targeted NIR fluorophores can selectively eradicate cancer cells, harnessing the power of synergistic photodynamic therapy and photothermal therapy. However, there is a paucity of NIR bioprobes showing tumor-specific targeting and effective phototheranosis without hurting surrounding healthy tissues. Methods: We engineered a tumor-specific bifunctional NIR bioprobe designed to precisely target HNSCC and induce phototheranosis using bioconjugation of a cyclic arginine-glycine-aspartic acid (cRGD) motif and zwitterionic polymethine NIR fluorophore. The cytotoxic effects of cRGD-ZW800-PEG were measured by assessing heat and reactive oxygen species (ROS) generation upon an 808-nm laser irradiation. We then determined the invivo efficacy of cRGD-ZW800-PEG in the FaDu xenograft mouse model of HNSCC, as well as its biodistribution and clearance, using a customized portable NIR imaging system. Results: Real-time NIR imaging revealed that intravenously administered cRGD-ZW800-PEG targeted tumors rapidly within 4 h postintravenous injection in tumor-bearing mice. Upon laser irradiation, cRGD-ZW800-PEG produced ROS and heat simultaneously and exhibited synergistic photothermal and photodynamic effects on the tumoral tissue without affecting the neighboring healthy tissues. Importantly, all unbound bioprobes were cleared through renal excretion. Conclusions: By harnessing phototheranosis in combination with tailored tumor selectivity, our targeted bioprobe ushers in a promising paradigm in cancer treatment. It promises safer and more efficacious therapeutic avenues against cancer, marking a substantial advancement in the field.

Right hemihepatectomy preserving the fluorescently visible paracaval portion of the caudate lobe.

The paracaval portion (PC) of the caudate lobe is a small area of the liver located in front of the inferior vena cava. Conventional right hemihepatectomy (RH) along the Rex-Cantlie line involves resection of not only the anterior and posterior sections but also the PC behind the middle hepatic vein (MHV). However, to preserve the future liver remnant volume as much as possible, PC-preserving RH may be beneficial in selected patients. We injected an indocyanine green (ICG) solution in the PC portal branch under intraoperative ultrasonography (IOUS) guidance and performed an RH preserving the fluorescently visible PC in a patient with liver metastasis. The patient was a 47-year-old male with a 24 ×10 cm metastatic hepatic tumor from sigmoid colon cancer. CT volumetry revealed that the left hemiliver excluding the caudate lobe was 55%, and the caudate lobe was 5.3%. Before hepatic transection, the ICG solution was injected into the PC portal branch under IOUS guidance. During hepatic transection, the PC was identified as a fluorescent area behind the MHV using a near-infrared imaging system. Thus, the anatomical right-side boundary of the caudate lobe was clearly found. Following RH, the PC was preserved as a fluorescently visible area. The patient had an uneventful recovery. RH preserving the fluorescently visible PC of the liver is a feasible procedure.

Agarose Gel Characterization for the Fabrication of Brain Tissue Phantoms for Infrared Multispectral Vision Systems.

Synthetic phantoms that recreate the characteristics of biological tissues are valuable tools for systematically studying and comprehending physiologies, pathologies, and biological processes related to tissues. The reproduction of mechanical and optical properties allows for the development and evaluation of novel systems and applications in areas such as imaging, optics, ultrasound, or dosimetry, among others. This paper proposes a methodology for manufacturing agarose-based phantoms that mimics the optical properties of healthy brain tissue within the wavelength infrared range of 800 to 820 nm. The fabrication of such phantoms enables the possibility of testing and experimentation in controlled and safe environments toward the design of new near-infrared multispectral imaging systems in neurosurgery. The results of an experimental optical characterization study indicate the validity and reliability of the proposed method for fabricating brain tissue phantoms in a cost-effective and straightforward fashion.

Slim and robust eye tracker on eyeglass temples with NIR patterned mirrors.

Eye trackers play a crucial role in the development of future display systems, such as head-mounted displays and augmented reality glasses. However, ensuring robustness and accuracy in gaze estimation poses challenges, particularly with limited space available for the transmitter and receiver components within these devices. To address the issues, we propose what we believe is a novel eye tracker design mounted on foldable temples, which not only supports accurate gaze estimation but also provides slim form-factor and unobstructed vision. Our temple-mounted eye tracker utilizes a near-infrared imaging system and incorporates a patterned near-infrared mirror for calibration markers. We present wearable prototypes of the eye tracker and introduce a unique calibration and gaze extraction algorithm by considering the mirror's spatial reflectance distribution. The accuracy of gaze extraction is evaluated through tests involving multiple users with realistic scenarios. We conclude with an evaluation of the results and a comprehensive discussion on the applicability of the temple-mounted eye tracker.

Broadband Achromatic Metalens for Tunable Focused Vortex Beam Generation in the Near-Infrared Range.

Vortex beams accompanied with orbital angular momentum have attracted significant attention in research fields due to their formidable capabilities in various crucial applications. However, conventional devices for generating vortex beams still suffer from bulky sizes, high cost, and confined performances. Metalens, as an advanced platform to arbitrarily control the optical waves, has promising prospects to address the predicament for conventional devices. Although great progress has been demonstrated in the applications of vortex beams, they are still confronted with fixed functionality after fabrication that severely hinders their application range. In this work, the phase-change material of Ge2Sb2Te5 (GST) is employed to design the meta-atoms to realize tunable optical responses. Moreover, the focused vortex beam can be accomplished by superimposing a helical phase and hyperbolic phase, and the chromatic aberrations in near-infrared (NIR) range can be corrected by introducing an additional phase compensation. And the design strategy is validated by two different metalenses (BAMTF-1 and BAMTF-2). The numerical results indicate that the chromatic aberrations for two metalens can be corrected in 1.33-1.60 μm covering the telecom range. Moreover, the average focusing efficiency of BAMTF-1 is 51.4%, and that of BAMTF-2 is 39.9%, indicating the favorable performances of designed BAMTF. More importantly, their average focal lengths have a relative tuning range of 38.82% and 33.17% by altering the crystallization ratio of GST, respectively. This work may provide a significant scheme for on-chip and tunable devices for NIR imaging and communication systems.

336P Dual-mode near-infrared multispectral imaging system equipped with deep learning models improves the identification of cancer foci in breast cancer specimens

336P Dual-mode near-infrared multispectral imaging system equipped with deep learning models improves the identification of cancer foci in breast cancer specimens

Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology

Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians' abilities to detect and characterize caries in pediatric patients using this instrument. Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. The reliability of lesion characterization (ie, grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.

Hyperspectral imaging combined with deep learning for discrimination of Lingwu long jujube in terms of the time after bruising

The timely detection and classification of bruised Lingwu long jujube is crucial for reducing economic losses in the agricultural industry. Traditional machine learning methods had been effectively used for bruise time classification with limited samples while the challenges were presented when the amount of data expanded. Deep learning methods can offer a solution. The hyperspectral image of the jujube sample was obtained using near-infrared hyperspectral imaging system (900–1700 nm). The optimal input variables were obtained by comparing the performance of the partial least squares-discriminant analysis, artificial neural network, and one-dimensional convolutional neural network (1D-CNN) models based on the spectral data and the fusion data of spectral and textural features. The optimal variable was the fusion data that could improve the model performance (from 92.68% to 96.10%). The above-mentioned three classifiers were used to establish models based on fusion data for two different dataset sizes consisting of large datasets (LD) (820) and small datasets (SD) (200) to explore the influence of dataset size on model performance. As the sample size increased, the 1D-CNN had good robustness with a classification rate of 94.00% for SD and 96.10% for LD in the prediction sets for all samples. The classification rate of prediction sets for 0 h after bruising increased from 90.00% to 92.68%, and from 80.00% to 90.24% in the class of 24 h after bruising. The findings provided a new approach to building a large spectral library and developing an online classification and detection system, thereby providing new ideas for the development of grading systems for Lingwu long jujube.