Identification and Fungicide Sensitivity of Fusarium spp. Associated with Root Rot of Scutellaria baicalensis in Shanxi Province, China.

Fusarium root rot is usually classified as an extremely destructive soilborne disease. From 2020 to 2021, Fusarium root rot was observed in production areas and seriously affected the yield and quality of Scutellaria baicalensis in Shanxi Province, China. Based on morphological characteristics and combined analysis of the internal transcribed spacer region of ribosomal DNA and translation elongation factor 1-alpha sequences, 68 Fusarium isolates obtained in this work were identified as F. oxysporum (52.94%), F. acuminatum (20.59%), F. solani (16.17%), F. proliferatum (5.88%), F. incarnatum (2.94%), and F. brachygibbosum (1.47%). In the pathogenicity tests, all Fusarium isolates could infect S. baicalensis roots, presenting different pathogenic ability. Among these isolates, F. oxysporum was found to have the highest virulence on S. baicalensis roots, followed by F. acuminatum, F. solani, F. proliferatum, F. brachygibbosum, and F. incarnatum. According to fungicide sensitivity tests, Fusarium isolates were more sensitive to fludioxonil and difenoconazole, followed by carbendazim, thiophanate-methyl, and hymexazol. In brief, this is the first report of Fusarium species (F. oxysporum, F. acuminatum, F. solani, F. proliferatum, F. incarnatum, and F. brachygibbosum) as causal agents of root rot of S. baicalensis in Shanxi Province, China. The fungicide sensitivity results will be helpful for formulating management strategies of S. baicalensis root rot.

Isolation, identification and transcriptome analysis of triadimefon-degrading strain Enterobacter hormaechei TY18.

Triadimefon, a type of triazole systemic fungicide, has been extensively used to control various fungal diseases. However, triadimefon could lead to severe environmental pollution, and even threatens human health. To eliminate triadimefon residues, a triadimefon-degrading bacterial strain TY18 was isolated from a long-term polluted site and was identified as Enterobacter hormaechei. Strain TY18 could grow well in a carbon salt medium with triadimefon as the sole nitrogen source, and could efficiently degrade triadimefon. Under triadimefon stress, a total of 430 differentially expressed genes (DEGs), including 197 up-regulated and 233 down-regulated DEGs, were identified in strain TY18 using transcriptome sequencing (RNA-Seq). Functional classification and enrichment analysis revealed that these DEGs were mainly related to amino acid transport and metabolism, carbohydrate transport and metabolism, small molecule and pyrimidine metabolism. Interestingly, the DEGs encoding monooxygenase and hydrolase activity acting on carbon-nitrogen were highly up-regulated, might be mainly responsible for the metabolism in triadimefon. Our findings in this work suggest that strain E. hormaechei TY18 could efficiently degrade triadimefon for the first time. They provide a great potential to manage triadimefon biodegradation in the environment successfully.

Fast Three-Dimensional Profilometry with Large Depth of Field.

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time-domain Gaussian fitting method is proposed in this paper. The concept of a time-domain Gaussian curve is firstly put forward, and the procedure of determining projector coordinates with a time-domain Gaussian curve is illustrated in detail. The neural network technique is applied to rapidly compute peak positions of time-domain Gaussian curves. Relying on the computing power of the neural network, the proposed method can reduce the computing time greatly. The binary defocusing technique can be combined with the neural network, and fast 3D profilometry with a large depth of field is achieved. Moreover, because the time-domain Gaussian curve is extracted from individual image pixel, it will not deform according to a complex surface, so the proposed method is also suitable for measuring a complex surface. It is demonstrated by the experiment results that our proposed method can extends the system DoF by five times, and both the data acquisition time and computing time can be reduced to less than 35 ms.

Modelling future land use land cover changes and their impacts on urban heat island intensity in Guangzhou, China.

During rapid urbanization in developing countries, changes in land use and land cover (LULC) can significantly alter urban land surface temperatures (LST), exacerbating the urban heat island (UHI) effect and degrading the outdoor environment. In this study, taking Guangzhou, China, as an example, we used Landsat series satellite data from 1992 to 2022, classified the LULC of the study area by the Support Vector Machine (SVM) method, estimated the LST of the area by the mono-window algorithm, and classified the LST of the study area into five UHI intensity classes based on the normalized values of the LST, and explored the influence of the LULC on the distribution of the UHI intensity. The CA-ANN (cellular automata-artificial neural network) model in QGIS software was employed to forecast the distribution of LULC and UHI intensity in Guangzhou for 2032. The findings reveal a strong correlation between UHI intensity and LULC, with water bodies and vegetation primarily exhibiting low and sub-low temperatures, while urban areas exhibit sub-high and high temperatures. The prediction results show that, according to the current development trend, compared with 1992, the water body and vegetation cover in 2032 will decrease by 46.97% and 34.24%, the building land will increase by 263.71%, and the sub-high and high temperature areas will increase by 127.76% and 375.92%. By analysing the spatial and temporal changes in LULC and its relationship with the distribution of UHI intensity during urbanization, this study assists government administrations and urban planners in devising sensible urban development strategies and implementing effective measures to plan LULC rationally. This approach aims to mitigate the impacts of the urban heat island and foster sustainable urbanization.

Mst1/2 Is Necessary for Satellite Cell Differentiation to Promote Muscle Regeneration.

The diminished ability for muscle to regenerate is associated with aging, diabetes, and cancers. Muscle regeneration depends on the activation and differentiation of satellite cells (SCs). Inactivation of Mst1/2 promotes cell proliferation by activating Yap, and that has been reported as a potential therapeutic target for improving many organ regeneration. However, the function of Mst1/2 in SCs fate decision and that effect on muscle regeneration remain unknown. By using inducible conditional knockout Mst1/2 in the SCs of mice and an inhibitor of Mst1/2, we found that inhibition of Mst1/2 in SCs significantly decrease Yap phosphorylation, thus causing Yap to accumulate in the nucleus and impairing SC differentiation; Mst1/2 were slightly elevated by irisin stimulation during SC differentiation; but inhibiting Mst1/2 in SCs significantly impaired irisin-induced muscle regeneration. These results indicate that Mst1/2 is necessary for SC differentiation and inhibiting Mst1/2 as a therapeutic target has potential risks for muscle regeneration.

Epstein-Barr virus infection with non-tumor-associated Anti-N-Methyl-D-Aspartate receptor encephalitis: a case report and review of literature.

To study a case of a middle-aged male with a non-tumor-associated Epstein-Barr virus (EBV) infection associated with Anti-N-methyl-D-aspartate receptor encephalitis (NMDARE), to explore the role of EBV in the pathogenesis of anti-NMDARE. The patient was diagnosed with "Anti-NMDARE, EBV infection" by using Cerebrospinal fluid (CSF) autoimmune encephalitis profile, and Metagenomics Next-Generation Sequencing (mNGS) pathogenic microbial assays, we discuss the relationship between EBV and NMDARE by reviewed literature. EBV infection may trigger and enhance anti-NMDARE, and the higher the titer of NMDAR antibody, the more severe the clinical presentation.

Detection of early bruises on apples using hyperspectral reflectance imaging coupled with optimal wavelengths selection and improved watershed segmentation algorithm.

BACKGROUND: Bruises caused by mechanical collision during the harvesting and storage and transportation period are difficult to detect using traditional machine vision technologies because there is no obvious difference in appearance between bruised and sound tissues. As a result of its fast and non-destructive characteristics, hyperspectral imaging technology is a potential tool for non-destructive detection of fruit surface defects. RESULTS: In the present study, visible near infrared hyperspectral reflectance images of healthy apples and bruised apples at 6, 12 and 24 h were obtained. To reduce hyperspectral data dimension, optimal wavelength selection algorithms including principal component analysis (PCA) and band ratio methods were utilized to select the effective wavelengths and enhance the contrast between bruised and sound tissues. Then pseudo-color image transformation technology combining with improved watershed segmentation algorithm (IWSA) were employed to recognize the bruise spots. The result obtained showed that band ratio images obtained better detection performance than that of PCA. The G component derived from pseudo-color image of λ 821 - λ 752 / λ 821 + λ 752 followed by IWSA obtained the best segmentation performance for bruise spots. Finally, a multispectral imaging system for the detection of bruised apple was developed to verify the effectiveness of the proposed two-band ratio algorithm, obtaining recognition rates of 93.3%, 92.2% and 92.5% for healthy, bruised and overall apples, respectively. CONCLUSION: The bruise detection algorithm proposed in the present study has potential to detect bruised apple in online practical applications and hyperspectral reflectance imaging offers a useful reference for the detection of surficial defects of fruit. © 2023 Society of Chemical Industry.

Nonradioactive direct telomerase activity detection using biotin-labeled primers.

BACKGROUND: Telomerase is a ribonucleoprotein enzyme responsible for maintenance of telomere length which expressed in more than 85% of cancer cells but undetectable in most normal tissue cells. Therefore, telomerase serves as a diagnostic marker of cancers. Two commonly used telomerase activity detection methods, the telomerase repeated amplification protocol (TRAP) and the direct telomerase assay (DTA), have disadvantages that mainly arise from reliance on PCR amplification or the use of an isotope. A safe, low-cost and reliable telomerase activity detection method is still lacking. METHOD: We modified DTA method using biotin-labeled primers (Biotin-DTA) and optimized the method by adjusting cell culture temperature and KCl concentration. The sensitivity of the method was confirmed to detect endogenous telomerase activity. The reliability was verified by detection of telomerase activity of published telomerase regulators. The stability was confirmed by comparing the method with TRAP method. RESULTS: Cells cultured in 32°C and KCl concentration at 200 mM or 250 mM resulted in robust Biotin-DTA signal. Endogenous telomerase activity can be detected, which suggested an similar sensitivity as DTA using radioactive isotope markers. Knockdown of telomerase assembly regulator PES1 and DKC1 efficiently reduced telomerase activity. Compared with TRAP method, Biotin-DTA assay offers greater signal stability over a range of analyte protein amounts. CONCLUSION: Biotin-labeled, PCR-free, and nonradioactive direct telomerase assay is a promising new method for the easy, low-cost, and quantitative detection of telomerase activity.

Early detection of myocardial involvement by T1 mapping of cardiac MRI in idiopathic inflammatory myopathy.

BACKGROUND: Polymyositis (PM) and dermatomyositis (DM) are common types of idiopathic inflammatory myopathy (IIM), wherein patients are prone to adverse cardiovascular events. PURPOSE: To explore the value of cardiac magnetic resonance imaging (MRI) for detecting cardiac involvement in PM/DM patients using a T1 mapping technique. STUDY TYPE: Prospective observational study. POPULATION: In all, 25 PM/DM patients free of cardiovascular symptoms and preserved ventricular systolic function and 25 healthy volunteers matched for age and sex served as controls. FIELD STRENGTH/SEQUENCE: Cardiac MRI at 3T, including steady-state free precession (SSFP) cine imaging, late gadolinium enhancement (LGE), and T1 mapping with modified Look-Locker inversion recovery (MOLLI). ASSESSMENT: Myocardial native T1 and extracellular volume (ECV) of the left ventricle as well as the correlations with disease activity were analyzed. STATISTICAL TESTS: Independent sample's t-test, Fisher's exact test, or chi-square test, Pearson's correlation (r) were applied. P ≤ 0.05 was considered significant. RESULTS: Left ventricular end-diastolic/end-systolic volume index (P = 0.643, P = 0.325, respectively), mass index (P = 0.719), and ejection fraction (P = 0.144) were not significantly different between PM/DM patients and controls. LGE was found in 19% of PM/DM patients and none of the control subjects. PM/DM patients showed significantly higher native T1 values (1263.7 ± 84.0 msec vs. 1200.6 ± 43.0 msec, P = 0.002) and expanded extracellular volume (ECV) (32.6 ± 3.7% vs. 26.7 ± 2.3%, P < 0.001) compared with control subjects. ECV values in PM/DM patients had a high proportion (60%) over the 95% percentile of normal controls. Meanwhile, there was a significant correlation between native T1 (r = 0.710, P = 0.0001) or ECV (r = 0.508, P = 0.01) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP). DATA CONCLUSION: T1 mapping of cardiac MRI is valuable to detect subclinical myocardial involvement in PM/DM patients, and both myocardial native T1 and ECV could serve as early imaging markers for myocardial impairment in PM/DM. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:415-422.

Plasma nesfatin-1 level is associated with severity of depression in Chinese depressive patients.

BACKGROUND: Nesfatin-1 plays a role in the regulation of emotional states like depression. The aim of this study was to investigate the plasma nesfatin-1levels in Chinese patients with depression and healthy subjects, and to determine the possible association between the plasma nesfatin-1 level and the severity of depression. METHODS: A total of 103 depressive patients and 32 healthy subjects were assessed. According to HAMD-17scores, 51, 18, and 34 patients were enrolled in the mild depression, moderate depression, and severe depression groups, respectively. Plasma nesfatin-1 levels were determined by the ELISA method. Differences between groups were compared and associations between plasma nesfatin-1 and other variables were analyzed. RESULTS: The plasma nesfatin-1 was significantly positively correlated with HAMD-17 score (r = 0.651). Compared with healthy controls (8.11 ± 3.31 ng/mL), the plasma nesfatin-1 level significantly increased in patients with mild depression (11.17 ± 3.58 ng/mL), with moderate depression (16.33 ± 8.78 ng/mL), and with severe depression (27.65 ± 8.26 ng/mL) respectively. Plasma nesfatin-1 level (Odds ratio [OR] = 1.269) was an independent indicator for severe depression by multivariate logistic regression analysis. CONCLUSION: The plasma nesfatin-1 level is positively correlated with the severity of depression. Plasma nesfatin-1 level may be a potential indicator for depression severity.

Association between sleep disorders and morning blood pressure in hypertensive patients.

Sleep disorders are known to increase the risk of hypertension, yet few studies have investigated the relation between sleep disorders and morning blood pressure (BP). This study aimed to determine, whether the morning BP is associated with sleep quality and sleep-disordered breathing. A total of 144 hypertensive patients were included in this cross-sectional study. Each subject underwent anthropometric measurements, biochemical testing, 24-h ambulatory BP monitoring, and polysomnography (PSG). Sleep quality and sleep-disordered breathing were determined by PSG parameters of sleep architecture and sleep respiratory. There were no significant differences between subjects with and without morning hypertension in the parameters of sleep architecture and sleep respiratory. In multiple regression analysis, morning BP was independently associated with night-time BP and morning BP surge, but not with the parameters of sleep architecture and sleep respiratory. Further analysis showed that both night-time BP and morning BP surge were independently associated with the sleep respiratory parameters. In conclusion, sleep-disordered breathing might indirectly affect the morning BP by elevated night-time BP, yet neither poor sleep quality nor sleep-disordered breathing was major determinants of elevated morning BP in hypertensive patients.

Diagnostic accuracy of magnetic resonance angiography for acute pulmonary embolism - a systematic review and meta-analysis.

BACKGROUND: The aim of this meta-analysis was to evaluate the diagnostic accuracy of magnetic resonance angiography (MRA) for acute pulmonary embolism (PE). METHODS: A systematic literature search was conducted that included studies from January 2000 to August 2015 using the electronic databases PubMed, Embase and Springer link. The summary receiver operating characteristic (SROC) curve, sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR) as well as the 95 % confidence intervals (CIs) were calculated to evaluate the diagnostic accuracy of MRA for acute PE. Meta-disc software version 1.4 was used to analyze the data. RESULTS: Five studies were included in this meta-analysis. The pooled sensitivity (86 %, 95 % CI: 81 % to 90 %) and specificity (99 %, 95 % CI: 98 % to 100 %) demonstrated that MRA diagnosis had limited sensitivity and high specificity in the detection of acute PE. The pooled estimate of PLR (41.64, 95 % CI: 17.97 to 96.48) and NLR (0.17, 95 % CI: 0.11 to 0.27) provided evidence for the low missed diagnosis and misdiagnosis rates of MRA for acute PE. The high diagnostic accuracy of MRA for acute PE was demonstrated by the overall DOR (456.51, 95 % CI: 178.38 - 1168.31) and SROC curves (AUC = 0.9902 ± 0.0061). CONCLUSIONS: MRA can be used for the diagnosis of acute PE. However, due to limited sensitivity, MRA cannot be used as a stand-alone test to exclude acute PE.

Measuring the Moisture Content in Maize Kernel Based on Hyperspctral Image of Embryo Region.

Maize is among the most important economic corps in China while moisture content is a critical parameterin the process of storage and breeding. To measure the moisture content in maize kernel, a near-infrared hyperspectral imaging system has been built to acquire reflectance images from maize kernel samples in the spectral region between 1 000 and 2 500 nm. Near-infrared hyperspectral information of full surface and embryo of maize kernel were firstly extracted based on band ratio coupled with a simple thresholding method and the spectra analysis between moisture content in maize kernel and embryo was performed. The characteristic bands were then selected with the help of Competitive Adaptive Reweighted Sampling (CARS), Genetic Algorithm (GA) and Successive Projection Algorithm (SPA). Finally, these selected variables were used as the inputs to build Partial Least Square (PLS) models for determining the moisture content of maize kernel. In this study, a significant relation, which the spectral reflectance decreases as moisture content increase, between moisture content and spectral of embryo in maize kernel was observed. For the investigated independent test samples, all the proposed regression models, namely CARS-PLS, GA-PLS and SPA-PLS, achieved a good performance by using the information of embryo region. The correlation coefficient (Rp) and Root Mean Squared Error of Prediction (RMSEP) and number of characteristic wavelength for the prediction set were 0.931 2, 0.315 3, 9 and 0.917 6, 0.336 9, 14 and 0.922 7, 0.336 6, 16 for CARS-PLS, GA-PLS and SPA-PLS models, respectively. And, compared with models obtained by full surface spectral information, less characteristic wavelengths is used for development of CARS-PLS, GA-PLS and SPA-PLS models, while similar results were obtained. Comprehensively analyzing to both model accuracy and model complexity, SPA-PLS model by using embryo region information achieved the best result. Wavelengths at 1 197，1 322 and 1 495 nm were applied to extracted the information of embryo region, and the bands at 1 322, 1 342, 1 367, 1 949, 2 070 and 2 496 nm were used to establish the SPA-PLS model. These results demonstrated that near-infrared hyperspectral information from embryo region is more effective for determination of moisture nondestructive in maize kernel.

[Research on Cardiac Structure and Function in the Overweight and Obese population and Influence Factors].

In this study we performed Tissue Doppler Imaging (TDI), two-dimensional speckle tracking imaging (2D- STI) and three-dimensional speckle tracking imaging (3D-STI) on enrolled healthy, overweight and obese groups (34 subjects in each group), respectively, to analyze cardiac structure and its function. Compared with healthy group, global longitudinal strain (GLS), global circumferential strain (GCS), global area strain(GAS) and global radial strain (GRS) decreased progressively (P < 0.05). The ratio of early diastolic mitral inflow velocity to global early diastolic strain rate of left ventricle (E/e'sr) (r = 0.466, P < 0.001), GLS (r = 0.502, P < 0. 001), GCS (r = 0.426, P < 0.001), GAS (r = 0.535, P < 0.001) and GRS (r = -0.554, P < 0.001) were correlated with body mass index (BMI). E/e'sr (r = 0.37, P = 0.003), GLS (r = 0.455, P < 0.001), GCS (r = 0.282, P = 0.02), GAS (r = 0.412, P < 0.001) and GRS (r = -0.471, P < 0.001) were correlated with free fatty acid (FFA). Stepwise multiple linear regression revealed that BMI was independently correlated with E/e'sr, GLS, GCS, GAS and GRS. Waist to hip ratio (WHR) was independently correlated with GLS, GCS, GAS and GRS. FFA was independently correlated with E/e'sr (P < 0.05). The study showed that cardiac structure changed and impaired left ventricular global systolic and diastolic function in overweight and obes population. Moreover, BMI, WHR and FFA may be independent influence factors of cardiac function in overweight and obese population.

[Near-infrared spectra combining with CARS and SPA algorithms to screen the variables and samples for quantitatively determining the soluble solids content in strawberry].

In using spectroscopy to quantitatively or qualitatively analyze the quality of fruit, how to obtain a simple and effective correction model is very critical for the application and maintenance of the developed model. Strawberry as the research object, this research mainly focused on selecting the key variables and characteristic samples for quantitatively determining the soluble solids content. Competitive adaptive reweighted sampling (CARS) algorithm was firstly proposed to select the spectra variables. Then, Samples of correction set were selected by successive projections algorithm (SPA), and 98 characteristic samples were obtained. Next, based on the selected variables and characteristic samples, the second variable selection was performed by using SPA method. 25 key variables were obtained. In order to verify the performance of the proposed CARS algorithm, variable selection algorithms including Monte Carlo-uninformative variable elimination (MC-UVE) and SPA were used as the comparison algorithms. Results showed that CARS algorithm could eliminate uninformative variables and remove the collinearity information at the same time. Similarly, in order to assess the performance of the proposed SPA algorithm for selecting the characteristic samples, SPA algorithm was compared with classical Kennard-Stone algorithm Results showed that SPA algorithm could be used for selection of the characteristic samples in the calibration set. Finally, PLS and MLR model for quantitatively predicting the SSC (soluble solids content) in the strawberry were proposed based on the variables/samples subset (25/98), respectively. Results show that models built by using the 0.59% and 65.33% information of original variables and samples could obtain better performance than using the ones obtained by using all information of the original variables and samples. MLR model was the best with R(pre)2 = 0.9097, RMSEP=0.3484 and RPD = 3.3278.

[Near-infrared hyperspectral imaging combined with CARS algorithm to quantitatively determine soluble solids content in "Ya" pear].

The present study proposed competitive adaptive reweighted sampling (CARS) algorithm to be used to select the key variables from near-infrared hyperspectral imaging data of "Ya" pear. The performance of the developed model was evaluated in terms of the coefficient of determination(r2), and the root mean square error of prediction (RMSEP) and the ratio (RPD) of standard deviation of the validation set to standard error of prediction were used to evaluate the performance of proposed model in the prediction process. The selected key variables were used to build the PLS model, called CARS-PLS model. Comparing results obtained from CARS-PLS model and results obtained from full spectra PLS, it was found that the better results (r(2)pre = 0. 908 2, RMSEP=0. 312 0 and RPD=3. 300 5) were obtained by CARS-PLS model based on only 15. 6% information of full spectra. Moreover, performance of CARS-PLS model was also compared with PLS models built by using variables got by Monte Carlo-uninformative variable elimination (MC-UVE) and genetic algorithms (GA) method. The result found that CARS variable selection algorithm not only can remove the uninformative variables in spectra, but also can reduce the collinear variables from informative variables. Therefore, this method can be used to select the key variables of near-infrared hyperspectral imaging data. This study showed that near-infrared hyperspectral imaging technology combined with CARS-PLS model can quantitatively predict the soluble solids content (SSC) in "Ya" pear. The results presented from this study can provide a reference for predicting other fruits quality by using the near-infrared hyperspectral imaging.

[Characteristic wavelengths selection of soluble solids content of pear based on NIR spectral and LS-SVM].

To improve the precision and robustness of the NIR model of the soluble solid content (SSC) on pear. The total number of 160 pears was for the calibration (n=120) and prediction (n=40). Different spectral pretreatment methods, including standard normal variate (SNV) and multiplicative scatter correction (MSC) were used before further analysis. A combination of genetic algorithm (GA) and successive projections algorithm (SPA) was proposed to select most effective wavelengths after uninformative variable elimination (UVE) from original spectra, SNV pretreated spectra and MSC pretreated spectra respectively. The selected variables were used as the inputs of least squares-support vector machine (LS-SVM) model to build models for de- termining the SSC of pear. The results indicated that LS-SVM model built using SNVE-UVE-GA-SPA on 30 characteristic wavelengths selected from full-spectrum which had 3112 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.956, 0.271 for SSC. The model is reliable and the predicted result is effective. The method can meet the requirement of quick measuring SSC of pear and might be important for the development of portable instruments and online monitoring.

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

[Principles and applications of hyperspectral imaging technique in quality and safety inspection of fruits and vegetables].

The quality and safety of fruits and vegetables are the most concerns of consumers. Chemical analytical methods are traditional inspection methods which are time-consuming and labor intensive destructive inspection techniques. With the rapid development of imaging technique and spectral technique, hyperspectral imaging technique has been widely used in the nondestructive inspection of quality and safety of fruits and vegetables. Hyperspectral imaging integrates the advantages of traditional imaging and spectroscopy. It can obtain both spatial and spectral information of inspected objects. Therefore, it can be used in either external quality inspection as traditional imaging system, or internal quality or safety inspection as spectroscopy. In recent years, many research papers about the nondestructive inspection of quality and safety of fruits and vegetables by using hyperspectral imaging have been published, and in order to introduce the principles of nondestructive inspection and track the latest research development of hyperspectral imaging in the nondestructive inspection of quality and safety of fruits and vegetables, this paper reviews the principles, developments and applications of hyperspectral imaging in the external quality, internal quality and safety inspection of fruits and vegetables. Additionally, the basic components, analytical methods, future trends and challenges are also reported or discussed in this paper.

[Detection of slight bruises on apples based on hyperspectral imaging and MNF transform].

Bruising is one of the major defects occurring on apple surface inevitably during postharvest handling and processing stage. To detect slight bruises on apples fast and efficiently, a novel bruises detection algorithm based on hyperspectral imaging and minimum noise fraction transform is proposed. First, the hyperspectral images in the visible and near-infrared (400 approximately 1 000 nm) ranges are acquired, and MNF transform based on full ranges could obtain better detection performance compared to PCA transform; Second, five wavebands (560, 660, 720, 820 and 960 nm) are selected as the effective wavebands based on the coefficient curve of I-RELIEF method conducted on spectra extracted from intact and bruise surface; Third, the bruises detection algorithm is developed based on the effective wavebands and MNF transform method. For the investigated 40 sound samples and 40 different time stage bruise samples, the results with a 97. 1% overall detection rate are got. The recognition results indicate that the proposed methods and the effective wavelengths selected in this paper are feasible and efficient. This research lays a foundation for the development of multispectral imaging system based on MNF transform for slight bruises detection on apples.