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In order to identify tea varieties quickly, efficiently, and nondestructively, an adaptive improved possibilistic c-means (AIPCM) clustering with the fuzzy Mahalanobis distance was proposed to classify the Fourier transform infrared reflectance (FTIR) spectra of tea samples. Three varieties of tea samples were scanned and FTIR spectra were acquired for 96 tea samples of different geographical origins using the FTIR- 7600 infrared spectrometer. Multiple scatter correction was employed to eliminate light scattering of FTIR spectral data. After that, principal component analysis and linear discriminant analysis were applied to reduce the dimensionality of FTIR spectra and extract the discriminant information, respectively. Then, the data were clustered by several fuzzy clustering algorithms. AIPCM had the highest clustering accuracy and its accuracy achieved up to 98.5%. The experimental results showed that FTIR spectroscopy coupled with AIPCM clustering was superior in classification of tea varieties. [ABSTRACT FROM AUTHOR]

Abstract The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vector machine regression (WT-LSSVR) is proposed to select the optimal wavelength and establish the detection model. The Vis-NIR hyperspectral images of 405 tomato leaf samples were obtained and the whole region of tomato leaf sample spectral data was collected and preprocessed. In addition, WT-LSSVR is used to select optimal wavelength and establish the detection model using db4 and db6 as wavelet basis function, respectively. Furthermore, the best prediction performances for detecting cadmium (Cd) content in tomato leaves was obtained by second derivative (2nd Der) pre-processing method, with R c 2 of 0.9437, RMSEC of 0.0988 mg/kg, R p 2 of 0.8937, RMSEP of 0.2331 mg/kg, R cv 2 of 0.9357, RMSECV of 0.1455 mg/kg, RPD of 3.081 and bias of 0.00863 using db6 (daubechies 6) as wavelet basis function with wavelet fourth layer decomposition. The results of this study indicated that WT-LSSVR can effectively select the optimal wavelength and Vis-NIR hyperspectral imaging has great potential for detecting heavy metal content in tomato leaves under different cadmium stresses. Graphical Abstract Unlabelled Image Highlights • WT-LSSVR is proposed to select the optimal wavelength and establish the detection model. • There is a correlation between the spectrum and cadmium content in tomato leaves. • Vis-NIR hyperspectral imaging has great potential for detecting heavy metal content. [ABSTRACT FROM AUTHOR]

Abstract In order to identify the moldy tea leaves in a fast and nondestructive way, a method involving wavelet coupled with k-nearest neighbor (WKNN) was proposed to select effective characteristic wavelengths in this paper. The hyperspectral imaging of 300 dried tea samples with 3 different mildew degrees (contrast check, mild moldy and severe moldy) were obtained using hyperspectral data acquisition device. Besides, food microbiological examination results showed that mold count and total numbers of colony increased with the increase of storage time, temperature and humidity. Roughness penalty smoothing (RPS) algorithm was used to preprocess the raw spectra. Afterwards, WKNN was applied to select the optimal wavelengths of spectral data by using db4, db6, sym5, sym7 as wavelet basis functions, respectively. In addition, five layers of wavelet decomposition were adopted based on different wavelet basis functions. Linear discriminant analysis (LDA) algorithm was used to build the classification models based on preprocessed spectra feature in characteristic wavelengths. The results showed that four optimal prediction models were optimal decomposition level in each wavelet basis function. In addition, the best performance model among all LDA models achieved an identification rate of 100% in the calibration set and 98.33% in the prediction set, in which db4 was used as wavelet basis function and the optimal wavelet decomposition level was 2. WKNN algorithm can effectively achieve the best wavelet decomposition layer and the best wavelengths. WKNN algorithm combined with NIR hyperspectral imaging technology can realize the effective wavelength extraction and classification of dried tea with different mildew degrees. Graphical abstract Unlabelled Image Highlights • Wavelet coupled with k-nearest neighbor (WKNN) was proposed. • Mold count and total numbers of colony with different sample sets were carried out. • Hyperspectra imaging of dried tea samples with 3 different mildew degrees were obtained. • WKNN feature extraction algorithm is feasible and effective for building models. [ABSTRACT FROM AUTHOR]

In this study, impact of crystal size on salt (NaCl) uptake and water activity (aw) of dry‐cured pork was investigated by hyperspectral imaging. Three grades of NaCl labeled fine flake, medium flake, and large flakes were used during the 3 day salting period. Spectra and spatial information were extracted from three subsurfaces labeled surface‐1, surface‐2, and surface‐3 for each sample and prediction models were established based on partial least squares regression, synergy interval partial least squares, and competitive adaptive reweighted sampling partial least squares. The overall results indicated that processing with NaCl of different crystal sizes influenced NaCl uptake and aw of pork samples. Distribution maps based on spatial analysis further revealed that crystal size impacted NaCl uptake to a large extent. Thus, in the drive to process meat with lower NaCl content, crystal morphology may be considered in further studies in dry‐cured meat processing. Practical applications: Meat preservation with salt (NaCl) is a widely applied traditional technique of safe‐guiding meat from microbial invasion because of its effectiveness and the ease of accessing the commodity. Yet, several studies have associated noncommunicable diseases, including hypertension, cardiovascular disease, and stroke to the high intake of NaCl. As a result, several strategies are being developed for reducing NaCl contents in processed foods in a bid to avert these health‐related concerns. Some of these strategies involved studying the dissolution characteristics of salt crystals in saliva, brining with high‐powered ultrasound, among others. Dry‐cured pork is a worldwide delicacy. Thus, for the purposes of understanding how crystal size influence total NaCl levels in dry‐cured pork, this investigation was carried out. The outcome of this study may be considered in the formulation of future research needs in the drive to achieving sodium reduction in salted meat while maintaining quality and salt intensity. [ABSTRACT FROM AUTHOR]