Advancements, limitations and challenges in hyperspectral imaging for comprehensive assessment of wheat quality: An up-to-date review.

The potential of hyperspectral imaging technology (HIT) for the determination of physicochemical and nutritional components, evaluation of fungal/mycotoxins contamination, wheat varieties classification, identification of non-mildew-damaged wheat kernels, as well as detection of flour adulteration is comprehensively illustrated and reviewed. The latest findings (2018-2023) of HIT in wheat quality evaluation through internal and external attributes are compared and summarized in detail. The limitations and challenges of HIT to improve assessment accuracy are clearly described. Additionally, various practical recommendations and strategies for the potential application of HIT are highlighted. The future trends and prospects of HIT in evaluating wheat quality are also mentioned. In conclusion, HIT stands as a cutting-edge technology with immense potential for revolutionizing wheat quality evaluation. As advancements in HIT continue, it will play a pivotal role in shaping the future of wheat quality assessment and contributing to a more sustainable and efficient food supply chain.

Fast quantitative analysis and chemical visualization of amylopectin and amylose in sweet potatoes via merging 1D spectra and 2D image.

The quantitative analysis and spatial chemical visualization of amylopectin and amylose in different varieties of sweet potatoes were studied by merging spectral and image information. Three-dimensional (3D) hyperspectral images carrying 1D spectra and 2D images of hundreds of the samples (amylopectin, n = 644; amylose, n = 665) in near-infrared (NIR) range of 950-1650 nm (426 wavelengths) were acquired. The NIR spectra were mined to correlate with the values of the two indexes using a linear algorithm, generating a best performance with correlation coefficients and root mean square error of prediction (rP and RMSEP) of 0.983 and 0.847 g/100 mg for amylopectin, and 0.975 and 0.500 g/100 mg for amylose, respectively. Then, 14 % of the wavelengths (60 for amylopectin, 61 for amylopectin) were selected to simplify the prediction with rP and RMSEP of 0.970 and 1.103 g/100 mg for amylopectin, and 0.952 and 0.684 g/100 mg for amylose, respectively, comparable to those of full-wavelength models. By transferring the simplified model to original images, the color chemical maps were created and the differences of the two indexes in spatial distribution were visualized. The integration of NIR spectra and 2D image could be used for the more comprehensive evaluation of amylopectin and amylose concentrations in sweet potatoes.

Prediction of Anthocyanidins Content in Purple Chinese Cabbage Based on Visible/Near Infrared Spectroscopy.

Purple Chinese cabbage (PCC) has become a new breeding trend due to its attractive color and high nutritional quality since it contains abundant anthocyanidins. With the aim of rapid evaluation of PCC anthocyanidins contents and screening of breeding materials, a fast quantitative detection method for anthocyanidins in PCC was established using Near Infrared Spectroscopy (NIR). The PCC samples were scanned by NIR, and the spectral data combined with the chemometric results of anthocyanidins contents obtained by high-performance liquid chromatography were processed to establish the prediction models. The content of cyanidin varied from 93.5 mg/kg to 12,802.4 mg/kg in PCC, while the other anthocyanidins were much lower. The developed NIR prediction models on the basis of partial least square regression with the preprocessing of no-scattering mode and the first-order derivative showed the best prediction performance: for cyanidin, the external correlation coefficient (RSQ) and standard error of cross-validation (SECV) of the calibration set were 0.965 and 693.004, respectively; for total anthocyanidins, the RSQ and SECV of the calibration set were 0.966 and 685.994, respectively. The established models were effective, and this NIR method, with the advantages of timesaving and convenience, could be applied in purple vegetable breeding practice.

Towards rapidly quantifying and visualizing starch content of sweet potato [Ipomoea batatas (L.) Lam] based on NIR spectral and image data fusion.

This study aimed to achieve the rapid quantification and visualization of the starch content in sweet potato via near-infrared (NIR) spectral and image data fusion. The hyperspectral images of the sweet potato samples containing 900-1700 nm spectral information within every pixel were collected. The spectra were preprocessed, analyzed and the 18 informative wavelengths were finally extracted to relate to the measured starch content using the multiple linear regression (MLR) algorithm, producing a good quantitative prediction accuracy with a correlation coefficient of prediction (rP) of 0.970 and a root-mean-square error of prediction (RMSEP) of 0.874 g/100 g by an external validation using a set of dependent samples. The MLR model was further verified in terms of soundness and predictive validity via F-test and t-test, and then transferred to each pixel of the original two dimensional images with the help of a developed algorithm, generating color distribution maps to achieve the vivid visualization of the starch distribution. The study demonstrated that the fusion of the NIR spectral and image data provided a good strategy for the rapidly and nondestructively monitoring the starch content of sweet potato. This technique can be applied to industrial use in the future.

Simultaneous quantifying and visualizing moisture, ash and protein distribution in sweet potato [Ipomoea batatas (L.) Lam] by NIR hyperspectral imaging.

This study aimed to achieve the rapid evaluation of moisture, ash and protein of sweet potato simultaneously by near-infrared (NIR) hyperspectral imaging (900-1700 nm). Hyperspectral images of 300 samples for each parameter were acquired and the spectra within images were extracted, averaged and preprocessed to relate to the three measured parameters, using partial least squares (PLS) algorithm, respectively, resulting in good performances. Nine, eleven and eleven informative wavelengths were selected to accelerate the prediction of the three parameters, generating a correlation coefficient of prediction (r P) of 0.984, 0.905, 0.935 and root mean square error of prediction (RMSEP) of 0.907%, 0.138%, 0.0941% for moisture, ash and protein, respectively. By transferring the best optimized PLS models to generate color chemical maps, the distributions and variations of the three parameters were visualized. NIR hyperspectral imaging is promising and can be applied to simultaneously evaluate multiple quality parameters of sweet potato.

An overview of recent advances and applications of FT-IR spectroscopy for quality, authenticity, and adulteration detection in edible oils.

Authenticity and adulteration detection are primary concerns of various stakeholders, such as researchers, consumers, manufacturers, traders, and regulatory agencies. Traditional approaches for authenticity and adulteration detection in edible oils are time-consuming, complicated, laborious, and expensive; they require technical skills when interpreting the data. Over the last several years, much effort has been spent in academia and industry on developing vibrational spectroscopic techniques for quality, authenticity, and adulteration detection in edible oils. Among them, Fourier transforms infrared (FT-IR) spectroscopy has gained enormous attention as a green analytical technique for the rapid monitoring quality of edible oils at all stages of production and for detecting and quantifying adulteration and authenticity in edible oils. The technique has several benefits such as rapid, precise, inexpensive, and multi-analytical; hence, several parameters can be predicted simultaneously from the same spectrum. Associated with chemometrics, the technique has been successfully implemented for the rapid detection of adulteration and authenticity in edible oils. After presenting the fundamentals, the latest research outcomes in the last 10 years on quality, authenticity, and adulteration detection in edible oils using FT-IR spectroscopy will be highlighted and described in this review. Additionally, opportunities, challenges, and future trends of FT-IR spectroscopy will also be discussed.

Isolation, Structural, Functional, and Bioactive Properties of Cereal Arabinoxylan─A Critical Review.

Arabinoxylans (AXs) are widely distributed in various cereal grains, such as wheat, corn, rye, barley, rice, and oat. The AX molecule contains a linear (1,4)-ß-D-xylp backbone substituted by α-L-araf units and occasionally t-xylp and t-glcpA through α-(1,2) and/or α-(1,3) glycosidic linkages. Arabinoxylan shows diversified functional and bioactive properties, influenced by their molecular mass, branching degree, ferulic acid (FA) content, and the substitution position and chain length of the side chains. This Review summarizes the extraction methods for various cereal sources, compares their structural features and functional/bioactive properties, and highlights the established structure-function/bioactivity relationships, intending to explore the potential functions of AXs and their industrial applications.

Extraction, characterization and antioxidant activity of polysaccharide from Pouteria campechiana seed.

In this study, the seed polysaccharides (PCSP) was ultrasonic-assisted extracted from Pouteria campechiana and optimized by response surface method (RSM). After separation and purification by DEAE-52 cellulose column and Sephadex G-75 glucan gel column, the pure polysaccharide component of PCSPa-1 was obtained, and its structure and antioxidant activity were analyzed. The results showed that the optimal parameters of PCSP with maximum yields (15.94%) were ultrasonic temperature of 79 °C, ultrasonic time of 69 min, and liquid to material ratio of 41 mL/g. The molecular weight of PCSPa-1 was 67900 Da. PCSPa-1 consisted of glucose and mannose with a molar ratio of 86.65:4.62, and the glycosidic bond mainly included →4)-α-d-Glc(1→ and →6)-α-d-Glc(1→. Scanning electron microscopy showed that PCSPa-1 was a strip structure with a smooth surface. In addition, PCSPa-1 had strong scavenging capacity to 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2'-azino-bis- (3-ethylbenzthiaz oline-6-sulphonic acid) (ABTS), hydroxyl radical, and superoxide radical. Polysaccharides of Pouteria campechiana seeds could be exploited as a natural antioxidant.

Physicochemical Properties and Protein Denaturation of Pork Longissimus Dorsi Muscle Subjected to Six Microwave-Based Thawing Methods.

Physicochemical changes and protein denaturation were evaluated for pork longissimus dorsi muscle subjected to different thawing methods. Fresh pork longissimus dorsi muscle served as a control. Microwave (MT), microwave combined with ultrasonic (MUT), microwave combined with 35 °C water immersion (MIT), microwave combined with 4 °C refrigeration (MRT), microwave combined with air convection (MAT), and microwave combined with running water (MWT) were applied. All microwave-based methods excepted for MT avoided localized overheating. The changes in the water holding capacity (WHC), color, TBARS, and protein solubility were lowest with MAT. Differential scanning calorimetry (DSC) and dynamic rheological property measurements indicated, that the MAT samples changed only slightly and presented with complete peaks and high G' values compared with the other treatments. Thus, MAT may reduce protein denaturation associated with meat thawing. The results of this study indicated that MAT effectively shortens thawing time, preserves meat quality and uniformity, and could benefit the meat industry and those who consume its products.

A high-density genetic map and QTL mapping of leaf traits and glucosinolates in Barbarea vulgaris.

BACKGROUND: Barbarea vulgaris is a wild cruciferous plant and include two distinct types: the G- and P-types named after their glabrous and pubescent leaves, respectively. The types differ significantly in resistance to a range of insects and diseases as well as glucosinolates and other chemical defenses. A high-density linkage map was needed for further progress to be made in the molecular research of this plant. RESULTS: We performed restriction site-associated DNA sequencing (RAD-Seq) on an F2 population generated from G- and P-type B. vulgaris. A total of 1545 SNP markers were mapped and ordered in eight linkage groups, which represents the highest density linkage map to date for the crucifer tribe Cardamineae. A total of 722 previously published genome contigs (50.2 Mb, 30% of the total length) can be anchored to this high density genetic map, an improvement compared to a previously published map (431 anchored contigs, 38.7 Mb, 23% of the assembly genome). Most of these (572 contigs, 31.2 Mb) were newly anchored to the map, representing a significant improvement. On the basis of the present high-density genetic map, 37 QTL were detected for eleven traits, each QTL explaining 2.9-71.3% of the phenotype variation. QTL of glucosinolates, leaf size and color traits were in most cases overlapping, possibly implying a functional connection. CONCLUSIONS: This high-density linkage map and the QTL obtained in this study will be useful for further understanding of the genetic of the B. vulgaris and molecular basis of these traits, many of which are shared in the related crop watercress.

Structural changes evaluation with Raman spectroscopy in meat batters prepared by different processes.

A comprehensive study was conducted to evaluate the structural changes of meat and protein of pork batters produced by chopping or beating process through the phase-contrast micrograph, laser light scattering analyzer, scanning electronic microscopy and Raman spectrometer. The results showed that the shattered myofibrilla fragments were shorter and particle-sizes were smaller in the raw batter produced by beating process than those in the chopping process. Compared with the raw and cooked batters produced by chopping process, modifications in amide I and amide III bands revealed a significant decrease of α-helix content and an increase of ß-sheet, ß-turn and random coils content in the beating process. The changes in secondary structure of protein in the batter produced by beating process was thermally stable. Moreover, more tyrosine residues were buried, and more gauche-gauche-trans disulfide bonds conformations and hydrophobic interactions were formed in the batter produced by beating process.

Evaluation of the Nutritional Quality of Chinese Kale (Brassica alboglabra Bailey) Using UHPLC-Quadrupole-Orbitrap MS/MS-Based Metabolomics.

Chinese kale (Brassica alboglabra Bailey) is a widely consumed vegetable which is rich in antioxidants and anticarcinogenic compounds. Herein, we used an untargeted ultra-high-performance liquid chromatography (UHPLC)-Quadrupole-Orbitrap MS/MS-based metabolomics strategy to study the nutrient profiles of Chinese kale. Seven Chinese kale cultivars and three different edible parts were evaluated, and amino acids, sugars, organic acids, glucosinolates and phenolic compounds were analysed simultaneously. We found that two cultivars, a purple-stem cultivar W1 and a yellow-flower cultivar Y1, had more health-promoting compounds than others. The multivariate statistical analysis results showed that gluconapin was the most important contributor for discriminating both cultivars and edible parts. The purple-stem cultivar W1 had higher levels of some phenolic acids and flavonoids than the green stem cultivars. Compared to stems and leaves, the inflorescences contained more amino acids, glucosinolates and most of the phenolic acids. Meanwhile, the stems had the least amounts of phenolic compounds among the organs tested. Metabolomics is a powerful approach for the comprehensive understanding of vegetable nutritional quality. The results provide the basis for future metabolomics-guided breeding and nutritional quality improvement.

[Expression and Clinical Significance of Numb and P53 Proteins in Epithelial Ovarian Carcinoma].

OBJECTIVES: To investigate the expression and clinical significance of Numb and P53 proteins in epithelial ovarian carcinoma. METHODS: We co-tested the expressions of Numb and P53 proteins in epithelial ovarian tissues by immunohistochemistry, including 20 cases of normal tissues, 29 cases of benign tumors, 35 cases of borderline ovarian tumors and 87 cases of epithelial ovarian carcinoma. Their clinical significance was analyzed. RESULTS: The positive expression rates of Numb protein in normal ovarian tissues, benign ovarian tumors, borderline ovarian tumors and epithelial ovarian carcinoma were 5%, 13.8%, 51.4% and 70.1%, respectively, and with the rising trend and significantly difference among four groups ( P<0.05). The expression of Numb protein had significant positive correlation with stage and lymph node metastasis ( P<0.05), while Numb expression had no correlation with age, pathological type or histological grade ( P>0.05). The positive expression rates of P53 protein in normal ovarian tissues, benign ovarian tumors, borderline ovarian tumors and epithelial ovarian carcinoma were 0%, 3.4%, 28.6% and 63.2%, respectively, which had a gradually rising trend with significantly difference among four groups ( P<0.05). The expression of P53 protein in borderline ovarian tumors was significantly higher than those in normal ovarian tissues and benign ovarian tumors ( P<0.05). The expression of P53 protein in epithelial ovarian carcinoma group was significantly higher than those in the rest three groups ( P<0.05). Statistical significance was found between the expression of P53 protein and histological type, differentiation, stage, lymph node metastasis ( P<0.05); But Numb expression had no correlation with age ( P>0.05). The expression of Numb protein was positive correlated with the expression of P53 protein in borderline ovarian tumors and epithelial ovarian carcinoma ( r=0.488, P<0.05; r=0.231, P<0.05). CONCLUSIONS: Co-testing Numb and P53 protein might be helpful for the diagnosis and evaluation of prognosis of epithelial ovarian carcinoma and two proteins might work together in the development process of epithelial ovarian carcinoma.

Non-Destructive and rapid evaluation of staple foods quality by using spectroscopic techniques: A review.

Staple foods, including cereals, legumes, and root/tuber crops, dominate the daily diet of humans by providing valuable proteins, starch, oils, minerals, and vitamins. Quality evaluation of staple foods is primarily carried out on sensory (e.g. external defect, color), adulteration (e.g. species, origin), chemical (e.g. starch, proteins), mycotoxin (e.g. Fusarium toxin, aflatoxin), parasitic infection (e.g. weevil, beetle), and internal physiological (e.g. hollow heart, black heart) aspects. Conventional methods for the quality assessment of staple foods are always laborious, destructive, and time-consuming. Requirements for online monitoring of staple foods have been proposed to encourage the development of rapid, reagentless, and noninvasive techniques. Spectroscopic techniques, such as visible-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance spectroscopy, and spectral imaging, have been introduced as promising analytical tools and applied for the quality evaluation of staple foods. This review summarizes the recent applications and progress of such spectroscopic techniques in determining various qualities of staple foods. Besides, challenges and future trends of these spectroscopic techniques are also presented.

Nondestructive spectroscopic and imaging techniques for quality evaluation and assessment of fish and fish products.

Nowadays, people have increasingly realized the importance of acquiring high quality and nutritional values of fish and fish products in their daily diet. Quality evaluation and assessment are always expected and conducted by using rapid and nondestructive methods in order to satisfy both producers and consumers. During the past two decades, spectroscopic and imaging techniques have been developed to nondestructively estimate and measure quality attributes of fish and fish products. Among these noninvasive methods, visible/near-infrared (VIS/NIR) spectroscopy, computer/machine vision, and hyperspectral imaging have been regarded as powerful and effective analytical tools for fish quality analysis and control. VIS/NIR spectroscopy has been widely applied to determine intrinsic quality characteristics of fish samples, such as moisture, protein, fat, and salt. Computer/machine vision on the other hand mainly focuses on the estimation of external features like color, weight, size, and surface defects. Recently, by incorporating both spectroscopy and imaging techniques in one system, hyperspectral imaging cannot only measure the contents of different quality attributes simultaneously, but also obtain the spatial distribution of such attributes when the quality of fish samples are evaluated and measured. This paper systematically reviews the research advances of these three nondestructive optical techniques in the application of fish quality evaluation and determination and discuss future trends in the developments of nondestructive technologies for further quality characterization in fish and fish products.

Rapid and non-destructive determination of drip loss and pH distribution in farmed Atlantic salmon (Salmo salar) fillets using visible and near-infrared (Vis-NIR) hyperspectral imaging.

Drip loss and pH are important indices in quality assessment of salmon products. This work was carried out for rapid and non-destructive determination of drip loss and pH distribution in salmon fillets using near-infrared (Vis-NIR) hyperspectral imaging. Hyperspectral images were acquired for salmon fillet samples and their spectral signatures in the 400-1700nm range were extracted. Partial least square regression (PLSR) was used to correlate the spectra with reference drip loss and pH values. Important wavelengths were selected using the regression coefficients method to develop new PLSR models, leading to a correlation coefficient of cross-validation (rCV) of 0.834 with root-mean-square errors by cross-validation (RMSECV) of 0.067 for drip loss and a rCV of 0.877 with RMSECV of 0.046 for pH, respectively. Distribution maps of drip loss and pH were generated based on the new PLSR models using image processing algorithms. The results showed that Vis-NIR hyperspectral imaging technique combined with PLSR calibration analysis offers an effective quantitative capability for determining the spatial distribution of drip loss and pH in salmon fillets.