[Circular RNA-Encoded Proteins in Gastrointestinal Cancer:A Review].

Circular RNAs(CircRNAs)are a class of non-coding RNAs with a covalently closed-loop structure,high stability,and tissue specificity,with the production mechanisms different from linear RNAs.Recent studies have discovered that some CircRNAs can encode proteins via cap-independent translation mechanisms such as internal ribosome entry site,N6-methyladenosine,and rolling loop translation.The encoded proteins regulate homologous linear proteins or downstream signaling pathways via protein bait or other mechanisms,thereby exerting biological functions.Studies have shown that CircRNAs play a role in various diseases,especially in tumor progression,proliferation,invasion,and metastasis and immune regulation.Therefore,by elucidating the expression and roles of proteins encoded by CircRNAs in tumorigenesis and development,this paper is expected to provide new tumor markers and potential targets for tumor diagnosis and treatment.

Exosomal ACADM sensitizes gemcitabine-resistance through modulating fatty acid metabolism and ferroptosis in pancreatic cancer.

This study aimed to evaluate the potential of exosomes from cancer cells to predict chemoresistance in pancreatic cancer (PC) and explore the molecular mechanisms through RNA-sequencing and mass spectrometry. We sought to understand the connection between the exosomal Medium-chain acyl-CoA dehydrogenase (ACADM) level and the reaction to gemcitabine in vivo and in patients with PC. We employed loss-of-function, gain-of-function, metabolome mass spectrometry, and xenograft models to investigate the effect of exosomal ACADM in chemoresistance in PC. Our results showed that the molecules involved in lipid metabolism in exosomes vary between PC cells with different gemcitabine sensitivity. Exosomal ACADM (Exo-ACADM) was strongly correlated with gemcitabine sensitivity in vivo, which can be used as a predictor for postoperative gemcitabine chemosensitivity in pancreatic patients. Moreover, ACADM was found to regulate the gemcitabine response by affecting ferroptosis through Glutathione peroxidase 4 (GPX4) and mevalonate pathways. It was also observed that ACADM increased the consumption of unsaturated fatty acids and decreased intracellular lipid peroxides and reactive oxygen species (ROS) levels. In conclusion, this research suggests that Exo-ACADM may be a viable biomarker for predicting the responsiveness of patients to chemotherapy.

Deubiquitinase UCHL5 stabilizes ELK3 to potentiate cancer stemness and tumor progression in pancreatic adenocarcinoma (PAAD).

Aberrant ubiquitin-proteasome system (UPS) contributes to tumorigeneisis or drug resistance of Pancreatic Adenocarcinoma (PAAD). Previous studies have implicated the deubiquitinase UCHL5 was abnormally expressed in multiple malignancies. However, little was reported about the specific roles of UCHL5 in PAAD. We aimed to identify the biological roles of UCHL5 in PAAD and demonstrate its prognostic significance. Differential analysis revealed that UCHL5 expressed highly in tumors versus normal tissues, like TCGA-PAAD, GSE28735, GSE15471 and collected samples. Patients with high UCHL5 expressions had worse survival outcomes relative to those with low UCHL5 levels. Experimental assays showed that UCHL5 overexpression could significantly enhance cell proliferation, colony formation and self-renewal capacities. UCHL5 could also promote PAAD migration in vitro and in vivo. Mechanistically, UCHL5 could directly deubiquitinate and stabilize ELK3 proteins. UCHL5 relied on accumulated ELK3 proteins to drive cell growth, stem-like properties and migration abilities. In addition, enrichment analysis based on RNA-seq data implicated that ELK3 mainly correlated with Notch1 signaling and ELK3 could notably elevate ELK3 mRNA levels. UCHL5 could thus promote self-renewal abilities of PAAD and targeting ELK3 could inhibit the stemness features. In contrast, UCHL5 deficiency could suppress PAAD stemness features, and ectopic expression of ELK3 could rescue this effect. Last of all, we utilized the UCHL5 inhibitor, b-AP15, to treat PAAD cells and found that b-AP15 could inhibit the growth of PAAD cells in a dose-dependent manner. Collectively, our study uncovered the underlying mechanisms of UCHL5/ELK3/Notch1 axis in PAAD progression and stemness maintaince, shedding light on individualized treatment and risk stratification for PAAD patients.

Advances in infrared spectroscopy combined with artificial neural network for the authentication and traceability of food.

The authentication and traceability of food attract more attention due to the increasing consumer awareness regarding nutrition and health, being a new hotspot of food science. Infrared spectroscopy (IRS) combined with shallow neural network has been widely proven to be an effective food analysis technology. As an advanced deep learning technology, deep neural network has also been explored to analyze and solve food-related IRS problems in recent years. The present review begins with brief introductions to IRS and artificial neural network (ANN), including shallow neural network and deep neural network. More notably, it emphasizes the comprehensive overview of the advances of the technology combined IRS with ANN for the authentication and traceability of food, based on relevant literature from 2014 to early 2020. In detail, the types of IRS and ANN, modeling processes, experimental results, and model comparisons in related studies are described to set forth the usage and performance of the combined technology for food analysis. The combined technology shows excellent ability to authenticate food quality and safety, involving chemical components, freshness, microorganisms, damages, toxic substances, and adulteration. As well, it shows excellent performance in the traceability of food variety and origin. The advantages, current limitations, and future trends of the combined technology are further discussed to provide a thoughtful viewpoint on the challenges and expectations of online applications for the authentication and traceability of food.

M2 Macrophage-Derived Exosomes Promote Angiogenesis and Growth of Pancreatic Ductal Adenocarcinoma by Targeting E2F2.

Pancreatic ductal adenocarcinoma (PDAC), one of the most aggressive tumors all over the world, has a generally poor prognosis, and its progression is positively correlated with the density of blood vessels. Recently, tumor-associated macrophages (TAMs) were proven to be beneficial for angiogenesis, but their mechanism of action remains unclear. Our study indicated that M2 macrophages were positively correlated with the microvessel density (MVD) of PDAC tissues, and M2 macrophage-derived exosomes (MDEs) could promote the angiogenesis of mouse aortic endothelial cells (MAECs) in vitro. At the same time, the M2 MDEs could also promote the growth of subcutaneous tumors and increase the vascular density of mice. Moreover, we also found that miR-155-5p and miR-221-5p levels in the M2 MDEs were higher than those in M0 MDEs, and they could be transferred into MAECs, as demonstrated by RNA sequencing (RNA-seq) and qPCR analysis. Our data confirmed the interaction between TAMs and the angiogenesis of PDAC by exosomes. Additionally, targeting the exosomal miRNAs derived from TAMs might provide diagnostic and therapeutic strategies for PDAC.

Comparative study of oncologic efficacy of cephalomedial to lateral dissection versus medial to lateral dissection in laparoscopic total mesorectal excision for rectal cancer: An RCT study.

BACKGROUND AND OBJECTIVES: We compared the 3-year overall survival between cephalomedial-to-lateral approach proctectomy (CEMP) and medial-to-lateral approach proctectomy (MAP) in patients undergoing laparoscopic total mesorectal excision for rectal cancer. The advantages of CEMP and the clinical value of No. 253 lymph nodes resection have not been objectively analyzed in literature. METHODS: This was a prospective, two-arm, multicenter, single-blinded, randomized trial. The primary endpoint was 3-year overall survival, and secondary endpoints included safety, feasibility, oncological radicality (including number of No. 253 lymph nodes harvested), short-term outcome, 3-year disease-free survival, rate of postoperative complications, mortality, and rate of recurrence. RESULTS: From May 2016 to July 2020, 506 patients were enrolled-256 in the CEMP group and 250 in the MAP group. Comparison of overall survival and disease-free survival showed that there was treatment benefit in the CEMP group (28.22 ± 12.12 vs. 27.44 ± 13.06, p = 0.485; 27.24 ± 12.01 vs. 26.42 ± 12.81; p = 0.457). More No. 253 lymph nodes were harvested in the CEMP group, and cases with positive No. 253 lymph nodes had worse prognosis in stage III. Surgical safety was equal for both approaches. CONCLUSIONS: Dissection of No. 253 lymph nodes may be important to improve clinical prognosis, but further studies with larger samples are needed to confirm this finding.

Correction to: Circular RNA circNHSL1 promotes gastric cancer progression through the miR-1306-3p/SIX1/Vimentin axis.

After publication of the article [1], the authors reported errors of inter-duplication in Figure 3.

Circular RNA circCCDC9 acts as a miR-6792-3p sponge to suppress the progression of gastric cancer through regulating CAV1 expression.

BACKGROUND: As a novel type of noncoding RNAs, covalently closed circular RNAs (circRNAs) are ubiquitously expressed in eukaryotes. Emerging studies have related dysregulation of circRNAs to tumorigenesis. However, the biogenesis, regulation, function and mechanism of circRNAs in gastric cancer (GC) remain largely unclear. METHODS: The expression profile of circRNAs in 6 pairs of GC tissues and adjacent non-tumor tissues was analyzed by RNA-sequencing. Quantitative real-time PCR was used to determine the expression level of circCCDC9 in GC tissues and cell lines. Then, functional experiments in vitro and in vivo were employed to explore the effects of circCCDC9 on tumor growth and metastasis in GC. Mechanistically, dual luciferase reporter, fluorescence in situ hybridization (FISH), RNA immunoprecipitation (RIP) and RNA pull-down assays were performed to confirm that circCCDC9 directly sponged miR-6792-3p and alleviated suppression on target CAV1 expression. RESULTS: Evidently down-regulated expression of circCCDC9 was observed in both GC tissues and cell lines. Expression of circCCDC9 was negatively correlated with tumor size, lymph node invasion, advanced clinical stage and overall survival in GC patients. Functionally, overexpression of circCCDC9 significantly inhibited the proliferation, migration and invasion of GC cell lines in vitro and tumor growth and metastasis in vivo, whereas miR-6792-3p mimics counteracted these effects. Mechanistic analysis demonstrated that circCCDC9 acted as a "ceRNA" of miR-6792-3p to relieve the repressive effect of miR-6792-3p on its target CAV1, then suppressed the tumorigenesis of GC. CONCLUSIONS: CircCCDC9 functions as a tumor suppressor in inhibiting the progression of GC through miR-6792-3p/CAV1 axis, which has provided an exploitable biomarker and therapeutic target for patients with GC.

GINS complex subunit 4, a prognostic biomarker and reversely mediated by Krüppel-like factor 4, promotes the growth of colorectal cancer.

GINS complex subunit 4 (GINS4) is essential for DNA replication initiation and elongation in the G1 /S phase cell cycle in eukaryotes, however, its functional roles and molecular mechanisms remain unclear in many aspects. Our study was designed to investigate the clinical significance, biological function, and molecular mechanism of GINS4 in colorectal cancer (CRC). First, we confirmed that GINS4 expression was significantly overexpressed in CRC cells and tissues. The immunohistochemical results in tissue microarray from 106 CRC patients showed that a high level of GINS4 expression was positively correlated with advanced T stage, higher tumor TNM stage, and poor differentiation. The results from univariate and multivariate survival analysis models based on 106 CRC patients revealed that GINS4 might serve as an independent prognostic indicator for overall survival and disease-free survival of CRC patients. Moreover, downregulated GINS4 can inhibit growth and the cell cycle and accelerate cell apoptosis progression in vitro as well as inhibit tumorigenesis in vivo. Besides, our results also indicated that Krüppel-like factor 4 (KLF4) can negatively regulate GINS4 expression at the transcriptional level and the KLF/GINS4 pathway might play a vital role in the growth and prognosis of CRC.

Vision-Based Moving Obstacle Detection and Tracking in Paddy Field Using Improved Yolov3 and Deep SORT.

Using intelligent agricultural machines in paddy fields has received great attention. An obstacle avoidance system is required with the development of agricultural machines. In order to make the machines more intelligent, detecting and tracking obstacles, especially the moving obstacles in paddy fields, is the basis of obstacle avoidance. To achieve this goal, a red, green and blue (RGB) camera and a computer were used to build a machine vision system, mounted on a transplanter. A method that combined the improved You Only Look Once version 3 (Yolov3) and deep Simple Online and Realtime Tracking (deep SORT) was used to detect and track typical moving obstacles, and figure out the center point positions of the obstacles in paddy fields. The improved Yolov3 has 23 residual blocks and upsamples only once, and has new loss calculation functions. Results showed that the improved Yolov3 obtained mean intersection over union (mIoU) score of 0.779 and was 27.3% faster in processing speed than standard Yolov3 on a self-created test dataset of moving obstacles (human and water buffalo) in paddy fields. An acceptable performance for detecting and tracking could be obtained in a real paddy field test with an average processing speed of 5-7 frames per second (FPS), which satisfies actual work demands. In future research, the proposed system could support the intelligent agriculture machines more flexible in autonomous navigation.

Circular RNA circNHSL1 promotes gastric cancer progression through the miR-1306-3p/SIX1/vimentin axis.

BACKGROUND: Mounting evidences indicate that circular RNAs (circRNAs) play vital roles in the development and progression of various cancers. However, the detail functions and underlying mechanisms of circRNAs in gastric cancer remain largely unknown. METHODS: The expression profile of metastasis-related circRNAs was screened by RNA-seq analysis. qRT-PCR was used to determine the level and prognostic values of circNHSL1 in gastric cancer tissues. In vitro cell wound healing and transwell (migration and invasion) and in vivo tumorigenesis and metastasis assays were performed to evaluate the functions of circNHSL1. Luciferase reporter, RNA immunoprecipitation (RIP) and rescued assays were employed to confirm the interactions between circNHSL1, miR-1306-3p and SIX1. It's widely accepted that as a mesenchymal marker, Vimentin promotes invasion and metastasis in various cancers. Luciferase reporter assay was used to determine the regulation of SIX1 on Vimentin. In addition, In situ hybridization (ISH) was performed to detect the level and prognostic values of miR-1306-3p. RESULTS: We found that the level of circNHSL1 was significantly up-regulated in gastric cancer, and positively correlated with clinicopathological features and poor prognosis of patients with gastric cancer. Functionally, circNHSL1 promoted cell mobility and invasion, as well as in vivo tumorgenesis and metastasis. Mechanistically, circNHSL1 acted as a miR-1306-3p sponge to relieve the repressive effect of miR-1306-3p on its target SIX1. Moreover, SIX1 enhanced Vimentin expression in the transcriptional level through directly binding to the promoter domain of Vimentin, thereby promoting cell migration and invasion. In addition, miR-1306-3p was down-regulated and negatively correlated with pathological features and poor prognosis in gastric cancer. CONCLUSIONS: CircNHSL1 promotes gastric cancer progression through miR-1306-3p/SIX1/Vimentin axis, and may serve as a novel diagnostic marker and target for treatment of gastric cancer patients.

PODXL, negatively regulated by KLF4, promotes the EMT and metastasis and serves as a novel prognostic indicator of gastric cancer.

BACKGROUND: Podocalyxin-like 1 (PODXL) was reported to be closely associated with the development of various cancers, yet its functional roles and molecular mechanisms remain vague. The aim of our study was to investigate the clinical significance, biological function and molecular mechanism of PODXL in gastric cancer (GC). METHODS: The level of PODXL in GC tissues was detected applying GC tissues microarray, fresh GC tissues and public database (Oncomine). The invasion, metastasis and tumorigenesis role of PODXL were performed in vitro and in vivo. The correlations between KLF4 and PODXL was determined in GC tissues microarray and fresh GC tissues, and the molecular regulatory mechanism between KLF4 and PODXL was explored in vitro. RESULTS: The high level of PODXL was detected in GC tissues with advanced T stage, lymph node metastasis, Union for International Cancer Control stage and poor differentiation. And Cox proportional hazards model revealed that PODXL can serve as an independent prognostic indicator for disease-free survival and overall survival of GC patients. Moreover, downregulation of PODXL could inhibit EMT and reduce invasion and metastasis in vitro as well as tumorigenesis in vivo. Additionally, our findings showed that PODXL may be a significant downstream target of KLF4. CONCLUSIONS: KLF4/PODXL signaling pathway assumes an irreplaceable role in tumorigenesis, invasion and metastasis of human GC and PODXL serves as an independent prognostic indicator for GC patients.

miR-301a plays a pivotal role in hypoxia-induced gemcitabine resistance in pancreatic cancer.

Hypoxia is a hallmark of pancreatic cancer (PC) and is associated with gemcitabine resistance. However, the mechanisms underlying hypoxia-induced gemcitabine resistance in PC remain greatly unknown. Our previous work showed that miR-301a, a hypoxia-sensitive miRNA, is involved in PC metastasis under hypoxia via regulation of its target gene P63. Here, we showed that miR-301a was upregulated in a NF-κB independent manner and promoted gemcitabine resistance under hypoxic conditions in vitro. In addition, TAp63, a member of the P63 family, reversed hypoxia-induced gemcitabine resistance by promoting degradation of HIF-1α. Furthermore, we proved that TAp63 was a functional downstream target of miR-301a and mediated the biological properties of miR-301a in PC. Taken together, these findings indicate that miR-301a exerts as a critical regulator involved in hypoxia-induced gemcitabine resistance in PC and may have potentials to be a therapeutic target for PC patients.

Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder.

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000-550 cm-1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

Application of Deep Learning in Food: A Review.

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food science and engineering. To our knowledge, this review is the first in the food domain. In this paper, we provided a brief introduction of deep learning and detailedly described the structure of some popular architectures of deep neural networks and the approaches for training a model. We surveyed dozens of articles that used deep learning as the data analysis tool to solve the problems and challenges in food domain, including food recognition, calories estimation, quality detection of fruits, vegetables, meat and aquatic products, food supply chain, and food contamination. The specific problems, the datasets, the preprocessing methods, the networks and frameworks used, the performance achieved, and the comparison with other popular solutions of each research were investigated. We also analyzed the potential of deep learning to be used as an advanced data mining tool in food sensory and consume researches. The result of our survey indicates that deep learning outperforms other methods such as manual feature extractors, conventional machine learning algorithms, and deep learning as a promising tool in food quality and safety inspection. The encouraging results in classification and regression problems achieved by deep learning will attract more research efforts to apply deep learning into the field of food in the future.

Krüppel-Like Factor 4 Inhibits Pancreatic Cancer Epithelial-to-Mesenchymal Transition and Metastasis by Down-Regulating Caveolin-1 Expression.

BACKGROUND/AIMS: Krüppel-like factor 4 (KLF4), a member of the KLF family of zinc finger transcription factors, has been identified as a tumor suppressor gene in a variety of tumors. However, the molecular mechanisms by which KLF4 inhibits epithelial-to-mesenchymal transition (EMT) and metastasis in pancreatic cancer remain unclear. METHODS: KLF4 expression in pancreatic cancer was analyzed using public datasets (Oncomine and The Cancer Genome Atlas). The expression of KLF4, caveolin-1 (Cav-1), E-cadherin, and vimentin, and their correlations with clinicopathological characteristics were evaluated by immunohistochemistry in pancreatic cancer tissues. The biological functions and underlying mechanisms of KLF4 expression on EMT and metastasis were also investigated in vitro and in vivo. RESULTS: Public datasets showed that KLF4 expression was significantly decreased in pancreatic cancer and correlated with the depth of invasion and disease stage. The expression of KLF4, Cav-1, E-cadherin, and vimentin protein in pancreatic cancer tissues was closely associated with pathological grade, disease stage, and metastasis. KLF4 expression was also positively correlated with E-cadherin expression and negatively correlated with vimentin expression, whereas Cav-1 expression was negatively associated with E-cadherin expression and positively correlated with vimentin expression. Knockdown of KLF4 expression promoted EMT and facilitated pancreatic cancer cell growth and metastasis in vitro and in vivo. In addition, immunohistochemistry (IHC) results indicated that KLF4 expression was negatively correlated with Cav-1 expression. Furthermore, down-regulating KLF4 expression increased Cav-1 and vimentin expression and decreased E-cadherin expression. Mechanistically, KLF4 could transcriptionally inhibit Cav-1 expression by binding directly to the promoter domain of Cav-1. CONCLUSIONS: KLF4 inhibits pancreatic cancer EMT and metastasis by down-regulating Cav-1 expression, suggesting that the KLF4/Cav-1 signaling pathway may be a novel diagnostic and therapeutic target.

Fast Detection of Striped Stem-Borer (Chilo suppressalis Walker) Infested Rice Seedling Based on Visible/Near-Infrared Hyperspectral Imaging System.

Striped stem-borer (SSB) infestation is one of the most serious sources of damage to rice growth. A rapid and non-destructive method of early SSB detection is essential for rice-growth protection. In this study, hyperspectral imaging combined with chemometrics was used to detect early SSB infestation in rice and identify the degree of infestation (DI). Visible/near-infrared hyperspectral images (in the spectral range of 380 nm to 1030 nm) were taken of the healthy rice plants and infested rice plants by SSB for 2, 4, 6, 8 and 10 days. A total of 17 characteristic wavelengths were selected from the spectral data extracted from the hyperspectral images by the successive projection algorithm (SPA). Principal component analysis (PCA) was applied to the hyperspectral images, and 16 textural features based on the gray-level co-occurrence matrix (GLCM) were extracted from the first two principal component (PC) images. A back-propagation neural network (BPNN) was used to establish infestation degree evaluation models based on full spectra, characteristic wavelengths, textural features and features fusion, respectively. BPNN models based on a fusion of characteristic wavelengths and textural features achieved the best performance, with classification accuracy of calibration and prediction sets over 95%. The accuracy of each infestation degree was satisfactory, and the accuracy of rice samples infested for 2 days was slightly low. In all, this study indicated the feasibility of hyperspectral imaging techniques to detect early SSB infestation and identify degrees of infestation.

Identification of Varieties of Dried Red Jujubes with Near-Infrared Hyperspectral Imaging.

In order to realize rapid identification of dried red jujubes, this paper proposes a method based on near-infrared hyperspectral imaging technology. The near-infrared hyperspectral images (1 000～1 600 nm) of 240 samples in total from 4 cultivars of dried red jujubes will be acquired. The samples are to be divided into the calibration set and the prediction set in the ratio of 2∶1. 7, 8, 10 effective wavelengths are to be selected by principal component analysis(PCA), x-loading weight(x-LW)and successive projection algorithm(SPA) respectively. The dimensionality of original hyperspectral images will be reduced with PCA, and texture features of the first principal component image are to be extracted with gray-level co-occurrence matrix(GLCM).The partial least squares-discriminant analysis(PLS-DA), back propagation neural network(BPNN)and least square support vector machine(LS-SVM) are to be applied to build identification models with the selected effective wavelengths, texture features and fusion of the former two features. The identification rates of the models based on fusion features will be higher than those of models based on the spectral features or texture features respectively. The BPNN models based on the fusion features will obtain the best results, whose identification rates of prediction set are to be 100%. The results in this paper indicate that the near-infrared hyperspectral imaging technology has great potential to identify the dried red jujubes rapidly.

[Study on Visual Identification of Corn Seeds Based on Hyperspectral Imaging Technology].

The seed purity is an important indicator of seed quality. The paper proposes a visual identification method of corn seed based on the near-infrared (874~1,734 nm) hyperspectral image technology. Hyperspectral image data of 4 cultivars of a total of 384 corn seed samples will be acquired. Then 288 of samples are to be selected randomly as the calibration set, and the remaining 96 samples will be used for the prediction set. After inspection of the near-infrared spectral curves, 7 effective wavelengths (EWs) are to be selected by successive projection algorithm (SPA). And then 7 EWs of the calibration set will be used as input to build a partial least squares (PLS) model. Good results are to be obtained with Rc = 0.917 7, RMSECV = 0.444 2; Rcv = 0.911 5, RMSECV = 0.459 9. And the total identification rate of the developed PLS model will be 78.5% for the calibration set and 70.8% for the prediction set. Finally, average spectral data of each corn seed in a hyperspectral image will be extracted by image process technology, and used as input of the developed SPA-PLS model. In the produced identification map, different colors are to be used to represent different predicted cultivars. 3 mixture samples of corn seeds will be identified, and help to achieve satisfied visual effects. The result indicates that, by means of the visual identification technology we could intuitively observe the distribution of corn seeds of different cultivars in mixture samples. The research provides help for the identification and screening of seeds in agricultural production.

[Study on Non-Detective Determination of ß-Carotene Content in Loquats with Raman Spectroscopy].

In china, researches on Raman spectroscopy in terms of foodstuff mainly focus on carbohydrates, fatty acids, proteins and vitamins. Conventional methods for determining the carotenoids content require the extraction of the samples as well as other cleanup steps. In this work, Raman spectroscopy is applied to get the measured value form loquats with different mature stage which are compared with the reference value get from High Performance Liquid Chromatography (HPLC)，in order to find new, fast, and nondestructive calibration methods for quantification of ß-carotene content in loquat fruits. Least Squares Support Vector Machine and Partial least squares data processing methods are used to analyze the Raman spectra while PLS model has a prediction quality with the correlation coefficient of 0.845; the root-mean-square error of 0.022 µg·g(-1) and LS-SVM model has a better prediction quality with the correlation coefficient of 0.910 with the root-mean-square error of 0.058 µg·g(-1).