Detecting Saliency in Infrared Images via Multiscale Local Sparse Representation and Local Contrast Measure

For infrared images, it is a formidable challenge to highlight salient regions completely and suppress the background noise effectively at the same time. To handle this problem, a novel saliency detection method based on multiscale local sparse representation and local contrast measure is proposed in this paper. The saliency detection problem is implemented in three stages. First, a multiscale local sparse representation based approach is designed for detecting saliency in infrared images. Using it, multiple saliency maps with various scales are obtained for an infrared image. These maps are then fused to generate a combined saliency map, which can highlight the salient region fully. Second, we adopt a local contrast measure based technique to process the infrared image. It divides the image into a number of image blocks. Then these blocks are utilized to calculate the local contrast to generate a local contrast measure based saliency map. In this map, the background noise can be suppressed effectually. Last, to make full use of the advantages of the above two saliency maps, we propose combining them together using an adaptive fusion scheme. Experimental results show that our method achieves better performance than several state-of-the-art algorithms for saliency detection in infrared images

Effects of Lactobacillus plantarum on the Fermentation Profile and Microbiological Composition of Wheat Fermented Silage Under the Freezing and Thawing Low Temperatures

The corruption and/or poor quality of silages caused by low temperature and freeze-thaw conditions makes it imperative to identify effective starters and low temperature silage fermentation technology that can assist the animal feed industry and improve livestock productivity. The effect of L. plantarum QZ227 on the wheat silage quality was evaluated under conditions at constant low temperatures followed by repeated freezing and thawing at low temperatures. QZ227 became the predominant strain in 10 days and underwent a more intensive lactic acid bacteria fermentation than CK. QZ227 accumulated more lactic acid, but lower pH and ammonia nitrogen in the fermentation. During the repeated freezing and thawing process, the accumulated lactic acid in the silage fermented by QZ227 remained relatively stable. Relative to CK, QZ227 reduced the abundance of fungal pathogens in silage at a constant 5°C, including Aspergillus, Sporidiobolaceae, Hypocreaceae, Pleosporales, Cutaneotrichosporon, Alternaria, and Cystobasidiomycetes. Under varying low temperature conditions from days 40 to days 60, QZ227 reduced the pathogenic abundance of fungi such as Pichia, Aspergillus, Agaricales, and Plectosphaerella. QZ227 also reduced the pathogenic abundance of Mucoromycota after the silage had been exposed to oxygen. In conclusion, QZ227 can be used as a silage additive in the fermentation process at both constant and variable low temperatures to ensure fast and vigorous fermentation because it promotes the rapid accumulation of lactic acid, and reduces pH values and aerobic corruption compared to the CK

Prevalence and clinical profile of metabolic syndrome in longevity: study from Guangxi Zhuang Autonomous Region, China

Abstract Background Metabolic syndrome (MetS) was a risk factor for cardiovascular diseases, yet the prevalence of MetS among nonagenarians and centenarians was rarely reported. Here we investigated the prevalence of MetS and its components among nonagenarians and centenarians in our Zhuang population from Bama, Guangxi Zhuang Autonomous Region, China. Method In Bama area, there registered 881 individuals who lived more than 90 years old in 269,800 local residents and our study involved 307 long-lived participants and 486 local younger (35–68 years) persons, as controls. MetS was defined according to the revised National Cholesterol Education Program’s Adult Treatment Panel III (NCEP ATPIII) criteria. Results The overall prevalence estimates of MetS among longevity group were 28.0% based on NCEP ATPIII criteria. The most common metabolic component was elevated blood pressure (61.1%), followed by raised fasting glucose (39.1%) and low high-density lipoprotein cholesterol (low HDL-C) (28.0%). The prevalence of MetS and abdominal obesity in women (33.6% and 22.1% respectively) was higher than that of men (19.8% and 3.7% respectively) (Prange < .001–0.019). Compared with controls, long-lived individuals were more likely to have two or more metabolic abnormalities (Prange < 0.001), and less likely to have zero or one metabolic abnormality (Prange < 0.001–0.020). Conclusion This study showed substantiality the prevalence and clinical profile of MetS in longevity population in Guangxi Zhuang Autonomous Region, China

A major QTL, which is co-located with cly1, and two minor QTLs are associated with glume opening angle in barley (Hordeum vulgare L.)

Cleistogamous and chasmogamous are two opposing phenomena for flowering in barley. Cleistogamy limits the rate of outcrossing, and increases the cost of producing hybrid barley seeds. Selecting chasmogamous lines with a large glume opening angle is essential for the utilization of barley heterosis. In the current study, 247 DH lines derived from a cross between Yangnongpi7 and Yang0187 were used to identify and validate QTLs associated with the glume opening angle in different environments using SSR markers. Three QTLs associated with barley glume opening angle were mapped on chromosomes 2H and 7H. The major QTL QGOA-2H-2 was mapped on chromosome 2H with the flanking markers of KDH and GBM1498, explaining 63.92% of the phenotypic variation. The marker KDH was developed from the gene Cly1, the candidate gene for QGOA-2H-2. This new marker can be used to identify barley chasmogamous lines with a large glume opening angle. The two minor QTLs were validated at all three locations across two seasons after removing DH lines carrying the candidate gene Cly1 of QGOA-2H-2

Simultaneous determination and risk assessment of highly toxic pesticides in the market-sold vegetables and fruits in China: A 4-year investigational study

This study investigated the levels of highly toxic pesticides (HTPs) in 6554 vegetable and fruit samples from 31 regions of China, along with the associated risk of dietary exposure for the population between 2014 and 2017. 18 HTPs were detected in 325 (4.96%) samples, and the levels of HTPs in 103 (1.57%) samples were found to be higher than the maximum residue limits (MRLs) of China. The rate of detection of HTPs in six types of vegetables and fruits, in a decreasing order, was found to be as follows: eggplant (8.84%) >grape (5.58%) >tomato (5.43%) >cucumber (5.43%) >pear (3.12%) >apple (2.30%). The level of contamination of HTPs was found to be higher in vegetables compared with fruits. The vegetable and fruit samples with the highest percentages of HTPs exceeding MRLs were found in eggplants from Guangxi (20%) and grapes from Inner Mongolia (12.5%), respectively. Both, the average target hazard quotient (THQ) of a single highly toxic pesticide (HTP) and the average hazard index (HI) of the mixture of HTPs for adults and children from vegetables and fruits from the 31 regions were found to be less than one. Omethoate, carbofuran, ethoprophos, triazophos, and phorate were identified as the major contributors to the average HI for vegetables, and carbofuran, ethoprophos, omethoate, phorate, and phosphamidon were identified as the primary contributors to the average HI for fruits. The results of this study revealed that HTPs in vegetables and fruits did not cause any significant chronic risk of dietary exposure. The detection of HTPs exceeding MRLs in some of the samples implied that appropriate management guidelines for HTPs should be implemented to protect the health of the consumers

Strong non-growing season N uptake by deciduous trees in a temperate forest: A N-15 isotopic experiment

Nitrogen (N) is a critical element for vegetation growth and subsequent carbon (C) and nutrient cycling in terrestrial ecosystems. Plant N uptake, the only pathway for plants to directly obtain N from soils, is a bottleneck process for ecosystem C and N cycling. Ecological theories predict that deciduous trees remain dormant and do not take up N during winters as no growth occurs during this season. In this study, we adopted a N-15 isotopic experiment to trace N processes throughout the non-growing season in a temperate forest in northern China. The N-15-labelled inorganic N (NH4+ and NO3-) and (CN)-C-13-N-15-labelled organic N (glycine and tyrosine; equivalent to 150 mg N-15/m(2)) were applied to soils at mid-fall, and the N-15 recovery in various components of dominant evergreen and deciduous species was analysed. We found that soil N transformation remained active in the winter and microbial N immobilization reached its peak in late winter. Surprisingly, deciduous species maintained a high N uptake that was comparable with the evergreen species throughout the non-growing season. Perennial herbs did not take up N until the next spring. All plant species acquired inorganic N and simple amino acids, while only the tree species utilized complex amino acids. Throughout the non-growing season, evergreen and deciduous trees showed higher uptake rates for NH4+ and glycine than NO3- and tyrosine, while deciduous shrubs and herbs showed a stronger preference for NO3- over other N forms. Synthesis. The finding that deciduous trees have strong N uptake in the non-growing season challenges the conventional viewpoint that deciduous trees remain dormant during non-growing seasons. This mechanism might supplement the algorithm in the model representation of N-limited temperate forest ecosystems

Advances in the Metabolic Mechanism and Functional Characteristics of Equol

Equol is the most potent soy isoflavone metabolite and is produced by specific intestinal microorganisms of mammals. It has promising application possibilities for preventing chronic diseases such as cardiovascular disease, breast cancer, and prostate cancer due to its high antioxidant activity and hormone-like activity. Thus, it is of great significance to systematically study the efficient preparation method of equol and its functional activity. This paper elaborates on the metabolic mechanism of equol in humans; focuses on the biological characteristics, synthesis methods, and the currently isolated equol-producing bacteria; and looks forward to its future development and application direction, aiming to provide guidance for the application and promotion of equol in the field of food and health products

Applications of THz Spectral Imaging in the Detection of Agricultural Products

Agricultural products need to be inspected for quality and safety, and the issue of safety of agricultural products caused by quality is frequently investigated. Safety testing should be carried out before agricultural products are consumed. The existing technologies for inspecting agricultural products are time-consuming and require complex operation, and there is motivation to develop a rapid, safe, and non-destructive inspection technology. In recent years, with the continuous progress of THz technology, THz spectral imaging, with the advantages of its unique characteristics, such as low energies, superior spatial resolution, and high sensitivity to water, has been recognized as an efficient and feasible identification tool, which has been widely used for the qualitative and quantitative analyses of agricultural production. In this paper, the current main performance achievements of the use of THz images are presented. In addition, recent advances in the application of THz spectral imaging technology for inspection of agricultural products are reviewed, including internal component detection, seed classification, pesticide residues detection, and foreign body and packaging inspection. Furthermore, machine learning methods applied in THz spectral imaging are discussed. Finally, the existing problems of THz spectral imaging technology are analyzed, and future research directions for THz spectral imaging technology are proposed. Recent rapid development of THz spectral imaging has demonstrated the advantages of THz radiation and its potential application in agricultural products. The rapid development of THz spectroscopic imaging combined with deep learning can be expected to have great potential for widespread application in the fields of agriculture and food engineering

Applications of THz Spectral Imaging in the Detection of Agricultural Products

Agricultural products need to be inspected for quality and safety, and the issue of safety of agricultural products caused by quality is frequently investigated. Safety testing should be carried out before agricultural products are consumed. The existing technologies for inspecting agricultural products are time-consuming and require complex operation, and there is motivation to develop a rapid, safe, and non-destructive inspection technology. In recent years, with the continuous progress of THz technology, THz spectral imaging, with the advantages of its unique characteristics, such as low energies, superior spatial resolution, and high sensitivity to water, has been recognized as an efficient and feasible identification tool, which has been widely used for the qualitative and quantitative analyses of agricultural production. In this paper, the current main performance achievements of the use of THz images are presented. In addition, recent advances in the application of THz spectral imaging technology for inspection of agricultural products are reviewed, including internal component detection, seed classification, pesticide residues detection, and foreign body and packaging inspection. Furthermore, machine learning methods applied in THz spectral imaging are discussed. Finally, the existing problems of THz spectral imaging technology are analyzed, and future research directions for THz spectral imaging technology are proposed. Recent rapid development of THz spectral imaging has demonstrated the advantages of THz radiation and its potential application in agricultural products. The rapid development of THz spectroscopic imaging combined with deep learning can be expected to have great potential for widespread application in the fields of agriculture and food engineering