scholarly journals Portable near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field

2021 ◽  
Vol 11 (7) ◽  
pp. 3209
Author(s):  
Karla R. Borba ◽  
Didem P. Aykas ◽  
Maria I. Milani ◽  
Luiz A. Colnago ◽  
Marcos D. Ferreira ◽  
...  
Keyword(s):  
Citric Acid ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Attributes ◽  
Internal Quality ◽  
Control Analysis ◽  
Tomato Quality ◽  
Wide Range ◽  
Different Types ◽  
Fresh Tomato

Portable spectrometers are promising tools that can be an alternative way, for various purposes, of analyzing food quality, such as monitoring in a few seconds the internal quality during fruit ripening in the field. A portable/handheld (palm-sized) near-infrared (NIR) spectrometer (Neospectra, Si-ware) with spectral range of 1295–2611 nm, equipped with a micro-electro-mechanical system (MEMs), was used to develop prediction models to evaluate tomato quality attributes non-destructively. Soluble solid content (SSC), fructose, glucose, titratable acidity (TA), ascorbic, and citric acid contents of different types of fresh tomatoes were analyzed with standard methods, and those values were correlated to spectral data by partial least squares regression (PLSR). Fresh tomato samples were obtained in 2018 and 2019 crops in commercial production, and four fruit types were evaluated: Roma, round, grape, and cherry tomatoes. The large variation in tomato types and having the fruits from distinct years resulted in a wide range in quality parameters enabling robust PLSR models. Results showed accurate prediction and good correlation (Rpred) for SSC = 0.87, glucose = 0.83, fructose = 0.87, ascorbic acid = 0.81, and citric acid = 0.86. Our results support the assertion that a handheld NIR spectrometer has a high potential to simultaneously determine several quality attributes of different types of tomatoes in a practical and fast way.

scholarly journals Rapid Nondestructive Simultaneous Detection for Physicochemical Properties of Different Types of Sheep Meat Cut Using Portable Vis/NIR Reflectance Spectroscopy System

Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1975
Author(s):  
Yanlei Li ◽  
Xiaochun Zheng ◽  
Dequan Zhang ◽  
Xin Li ◽  
Fei Fang ◽  
...  
Keyword(s):  
Physicochemical Properties ◽  
Shear Force ◽  
Near Infrared ◽  
Prediction Models ◽  
Simultaneous Detection ◽  
Nir Spectroscopy ◽  
Cooking Loss ◽  
Coefficient Of Determination ◽  
Sheep Meat ◽  
Different Types

The visible and near-infrared spectroscopy (Vis/NIRS) models for sheep meat quality evaluation using only one type of meat cut are not suitable for other types. In this study, a novel portable Vis/NIRS system was used to simultaneously detect physicochemical properties (pH, color L*, a*, b*, cooking loss, and shear force) for different types of sheep meat cut, including silverside, back strap, oyster, fillet, thick flank, and tenderloin cuts. The results show that the predictive abilities for all parameters could be effectively improved by spectral preprocessing. The coefficient of determination (Rp2) and residual predictive deviation (RPD) of the optimal prediction models for pH, L*, a*, b*, cooking loss, and shear force were 0.79 and 3.50, 0.78 and 2.28, 0.68 and 2.46, 0.75 and 2.62, 0.77 and 2.19, and 0.83 and 2.81, respectively. The findings demonstrate that Vis/NIR spectroscopy is a useful tool for predicting the physicochemical properties of different types of meat cut.

scholarly journals Determination of tomato quality attributes using near infrared spectroscopy and reference analysis

2016 ◽  
Vol 103 (1) ◽  
pp. 443-448 ◽  
Author(s):  
Audrius Radzevičius ◽  
Jonas Viškelis ◽  
Rasa Karklelienė ◽  
Danguolė Juškevičienė ◽  
Pranas Viškelis
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Attributes ◽  
Reference Analysis ◽  
Tomato Quality

scholarly journals Evaluation of Carrot Quality Using Visible-Near Infrared Spectroscopy and Multivariate Analysis

2018 ◽  
Vol 7 (4) ◽  
pp. 80 ◽  
Author(s):  
Ahmed Rady ◽  
Shinta Sugiharto ◽  
Akinboe Adedeji
Keyword(s):  
Vitamin C ◽  
Least Squares ◽  
Partial Least Squares ◽  
Near Infrared ◽  
Prediction Models ◽  
Rapid Determination ◽  
Quality Attributes ◽  
Prediction Performance ◽  
Soluble Solids ◽  
Β Carotene

Carrot has a relatively high content of Vitamin C and it is a major source of natural carotenoids. However, carrot has a short shelf-life and is better consumed fresh. A quick assessment of its quality attributes is important to preserving its freshness. The objective of this study was to apply Vis-NIR spectroscopy to noninvasively assess and predict the various quality attributes of carrot (cv. Nectar), namely color (L*a*b*), moisture content (MC), total soluble solids (TSS), firmness, Vitamin C, and β-carotene. Two spectroscopic sensors (400-1,000 nm and 900-1,700 nm) were utilized and samples included whole root and 25.4 mm thick sliced disc. The best prediction models using partial least squares regression yielded correlation coefficient, r, and ratio of performance to deviation or r(RPD) of 0.50(0.73), 0.84(0.88), 0.86(2.07), 0.69(0.66), 0.97(1.44), 0.90(1.49), 0.47(1.47), and 0.92(1.76) for color indices, L* a* b*, firmness, MC, TSS, Vitamin C, and β-carotene, respectively. However, using only the wavelengths selected by interval partial least squares, the r(RPD) values for the aforementioned attributes improved and are presented as follows: 0.92(1.97), 0.96(2.83), 0.98(5.85), 0.99(6.65), 0.98(3.91), 0.99(5.93), 0.98(4.16), and 0.98(4.43), respectively. Generally, Vis-NIR region had higher prediction performance than NIR region, and whole roots had similar prediction performance as sliced samples. This study shows that rapid determination of quality parameters of carrot is possible through non-destructive Vis-NIR sensing, which could be useful for quality tracking during carrot supply chain. Moreover, results of this study could be improved using a larger sample size. 

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Nondestructive Quality Evaluation of Tomatoes

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 544c-544
Author(s):  
A. Hakim ◽  
A. Purvis ◽  
E. Pehu ◽  
I. Voipio ◽  
E. Kaukovirta
Keyword(s):  
Quality Evaluation ◽  
Tomato Fruit ◽  
Quality Attributes ◽  
Internal Quality ◽  
Attractive Alternative ◽  
Fluorescence Techniques ◽  
Nondestructive Quality ◽  
Alternative Techniques ◽  
Evaluation Techniques

Both external and internal quality of fruits such as tomatoes can be evaluated by different methods, but all most all of the methods are destructive. For this reason, there is a need to reassess some of the alternative techniques. Nondestructive quality evaluation is an attractive alternative. The principles of different nondestructive quality evaluation techniques such as optical, physical, and fluorescence techniques applied to tomato fruit is explained. Successful application of these techniques that could be used for evaluation of different quality attributes are illustrated. The advantages of nondestructive quality evaluation techniques are that they are very fast, easy, labor- and time-intensive, and inexpensive. These techniques could also be useful to evaluate the quality of other vegetables.

Nanoparticles Functionalized with Venom-Derived Peptides and Toxins for Pharmaceutical Applications

2020 ◽  
Vol 21 (2) ◽  
pp. 97-109 ◽  
Author(s):  
Ana P. dos Santos ◽  
Tamara G. de Araújo ◽  
Gandhi Rádis-Baptista
Keyword(s):  
Oral Absorption ◽  
Current Data ◽  
Pharmacological Activities ◽  
Venom Peptides ◽  
Essential Components ◽  
Wide Range ◽  
Different Types ◽  
Direct Use ◽  
Animal Venoms ◽  
Pharmaceutical Biotechnology

Venom-derived peptides display diverse biological and pharmacological activities, making them useful in drug discovery platforms and for a wide range of applications in medicine and pharmaceutical biotechnology. Due to their target specificities, venom peptides have the potential to be developed into biopharmaceuticals to treat various health conditions such as diabetes mellitus, hypertension, and chronic pain. Despite the high potential for drug development, several limitations preclude the direct use of peptides as therapeutics and hamper the process of converting venom peptides into pharmaceuticals. These limitations include, for instance, chemical instability, poor oral absorption, short halflife, and off-target cytotoxicity. One strategy to overcome these disadvantages relies on the formulation of bioactive peptides with nanocarriers. A range of biocompatible materials are now available that can serve as nanocarriers and can improve the bioavailability of therapeutic and venom-derived peptides for clinical and diagnostic application. Examples of isolated venom peptides and crude animal venoms that have been encapsulated and formulated with different types of nanomaterials with promising results are increasingly reported. Based on the current data, a wealth of information can be collected regarding the utilization of nanocarriers to encapsulate venom peptides and render them bioavailable for pharmaceutical use. Overall, nanomaterials arise as essential components in the preparation of biopharmaceuticals that are based on biological and pharmacological active venom-derived peptides.

Intelligent Techniques Analysis for Glycosylation Site Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Alhassan Alkuhlani ◽  
Walaa Gad ◽  
Mohamed Roushdy ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Cell Interaction ◽  
Glycosylation Site ◽  
Machine Learning Classification ◽  
Site Prediction ◽  
Glycosylation Sites ◽  
Wide Range ◽  
Feature Extraction And Selection ◽  
Computational Intelligent

Background: Glycosylation is one of the most common post-translation modifications (PTMs) in organism cells. It plays important roles in several biological processes including cell-cell interaction, protein folding, antigen’s recognition, and immune response. In addition, glycosylation is associated with many human diseases such as cancer, diabetes and coronaviruses. The experimental techniques for identifying glycosylation sites are time-consuming, extensive laboratory work, and expensive. Therefore, computational intelligence techniques are becoming very important for glycosylation site prediction. Objective: This paper is a theoretical discussion of the technical aspects of the biotechnological (e.g., using artificial intelligence and machine learning) to digital bioinformatics research and intelligent biocomputing. The computational intelligent techniques have shown efficient results for predicting N-linked, O-linked and C-linked glycosylation sites. In the last two decades, many studies have been conducted for glycosylation site prediction using these techniques. In this paper, we analyze and compare a wide range of intelligent techniques of these studies from multiple aspects. The current challenges and difficulties facing the software developers and knowledge engineers for predicting glycosylation sites are also included. Method: The comparison between these different studies is introduced including many criteria such as databases, feature extraction and selection, machine learning classification methods, evaluation measures and the performance results. Results and conclusions: Many challenges and problems are presented. Consequently, more efforts are needed to get more accurate prediction models for the three basic types of glycosylation sites.

Wetting of glass surface using natural surfactants

2020 ◽  
Vol 12 ◽  
Author(s):  
Nihar Ranjan Biswal
Keyword(s):  
Contact Angle ◽  
Glass Surface ◽  
Pure Water ◽  
Amyl Alcohol ◽  
Synthetic Surfactant ◽  
Wide Range ◽  
Different Types ◽  
Natural Surfactants ◽  
Triton X ◽  
Solid Liquid

Background: Surfactant adsorption at the interfaces (solid–liquid, liquid–air, or liquid–liquid) is receiving considerable attention from a long time due to its wide range of practical applications. Objective: Specifically wettability of solid surface by liquids is mainly measured by contact angle and has many practical importances where solid–liquid systems are used. Adsorption of surfactants plays an important role in the wetting process. The wetting behaviours of three plant-based natural surfactants (Reetha, Shikakai, and Acacia) on the glass surface are compared with one widely used nonionic synthetic surfactant (Triton X-100) and reported in this study. Methods: The dynamic contact angle study of three different types of plant surfactants (Reetha, Shikakai and Acacia) and one synthetic surfactant (Triton X 100) on the glass surface has been carried out. The effect of two different types of alcohols such as Methanol and amyl alcohol on wettability of shikakai, as it shows little higher value of contact angle on glass surface has been measured. Results: The contact angle measurements show that there is an increase in contact angle from 47° (pure water) to 67.72°, 65.57°, 68.84°, and 68.79° for Reetha, Acacia, Shikakai, and Triton X-100 respectively with the increase in surfactant concentration and remain constant at CMC. The change in contact angle of Shikakai-Amyl alcohol mixtures are slightly different than that of methanol-Shikakai mixture, mostly there is a gradual increase in contact angle with the increasing in alcohol concentration. Conclusion: There is no linear relationship between cos θ and inverse of surface tension. There was a linear increase in surface free energy results with increase in concentration as more surfactant molecules were adsorbing at the interface enhancing an increase in contact angle.

Impact of Environmental Degradation on Human Health

2016 ◽  
Vol 3 (1) ◽  
pp. 1 ◽  
Author(s):  
_______ Archana ◽  
Charu Datta ◽  
Pratibha Tiwari
Keyword(s):  
Environmental Degradation ◽  
Human Population ◽  
Environmental Problems ◽  
Population Increase ◽  
Human Beings ◽  
The People ◽  
Wide Range ◽  
Different Types ◽  
Economic Institute ◽  
Day By Day

Degradation of environment is one of the most serious challenges before the mankind in today’s world. Mankind has been facing a wide range of problem arising out of the degradation of environment. Not only the areas under human inhabitation, but the areas of the planet without human population have also been suffering from these problems. As the population increase day by day, the amenities are not improved simultaneously. With the advancement of science and technologies the needs of human beings has been changing rapidly. As a result different types of environmental problems have been rising. Environmental degradation is a wide- reaching problem and it is likely to influence the health of human population is great. It may be defined the deterioration of the environment through depletion of resources such as air, water, and soil. The destruction of ecosystem and extinction of wildlife. Environmental degradation has occurred due to the recent activities in the field of socio-economic, institute and technology. Poverty still remains a problem as the root of several environmental problems to create awareness among the people about the ill effect of environmental pollution. In the whole research it is clear that all factors of environmental degradation may be reduced through- Framing the new laws on environmental degradation, Environment friend policy, Controlling all the ways and means of noise, air, soil and water pollution, Through growing more and more trees and by adapting the proper sanitation policy.  

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