Distribution of the literature data evaluated, in terms of the variable studied, highlighting the sample of interest (healthy individuals) and its size in relation to the total amount obtained.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"983",leadTitle:null,fullTitle:"Pancreatitis - Treatment and Complications",title:"Pancreatitis",subtitle:"Treatment and Complications",reviewType:"peer-reviewed",abstract:"Pancreatitis may be acute or chronic. 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SNS has thoracolumbar distribution, and PNS has a craniosacral distribution, while ENS is the major part of the peripheral nervous system being found throughout the gastrointestinal tract, extending from the esophagus to the rectum, and is also present in the pancreas and in the gallbladder [1, 2, 3, 4].
\nANS has the responsibility to ensure that homeostasis be maintained in the face of disturbances produced by both the external and internal environment [5]. In the heart of rats, ANS begins its development on the embryonic 18.5 day until the twenty-first postnatal day (P21) [6].
\nSympathetic neurons are located in the paravertebral ganglia, have long axonal projections to the organs, and produce excitatory effects mediated by the noradrenergic transmitter norepinephrine (NE). Conversely, parasympathetic neurons are located in ganglia near or on the surface of organs, have shorter axonal projections, and produce inhibitory effects mediated by the cholinergic transmitter acetylcholine (ACh). The enteric nervous system provides the intrinsic innervation of the gut, controlling different aspects of the gut function, such as motility [4].
\nAlthough ANS can actually function autonomously, the central nervous system can contribute to a significant regulatory effect [3].
\nHeart rate variability (HRV) analysis is a practical, noninvasive, reproducible, and cost-effective resource that has been widely applied to study the autonomic behavior of the human organism, being particularly useful for the evaluation of sympathetic and parasympathetic components, although with regard to sympathetic behavior, there is still controversy about the mechanisms involved [7].
\nHigher vagally mediated heart rate variability is associated with better autonomic balance, better health outcomes, and flexible physiological responses. In contrast, lower HRV is associated with disease and all-cause mortality [8].
\nIn [9], some reference values for normality of HRV variables are suggested, although highlighting that “As no comprehensive investigations of all HRV indices in large normal populations have yet been performed, some of the normal values […] were obtained from studies involving small number of subjects.”
\nThe reference values for normality cited and recommended in the Task Force were taken from the work of Bigger et al. (1995). The authors were based on only 274 individuals considered healthy and restricted to be 40–69 years old [10].
\nThe aim of this chapter is restricted to the parasympathetic division of ANS. For the evaluation of this component, there is a well-established consensus that some variables, such as the root mean square of the successive RR interval differences (RMSSD), the percent of normal RR intervals that differed by more than 50 ms (PNN50) both in the time domain, and the absolute power of the high-frequency band component (HF ms2), in the frequency domain, specifically represent vagal modulation, presenting both diagnostic and prognostic properties [11, 12].
\nGenerally speaking, heart rate variability analysis has become the most used noninvasive tool to evaluate autonomic control mechanisms and to predict mortality risk in several clinical conditions, including coronary artery disease, heart failure, diabetes, and hypertension [13].
\nAccording to Goldberger et al. [14], there was some evidence that age influenced the responsiveness of the HRV parameters with changing parasympathetic effect. They studied 29 normal volunteers (15 women; mean age 39 ± 12 years) after β-adrenergic blockade with intravenous propranolol. Five-minute ECG recordings were made during graded infusions of phenylephrine and nitroprusside to achieve baroreflex-mediated increases and decreases in parasympathetic effect, respectively. There was some evidence that age influenced the responsiveness of the HRV parameters with changing parasympathetic effect, with significant association for RMSSD and PNN50.
\nDespite the significant amount of studies in the literature dealing with the HRV and autonomic regulation subject, there is a lack of studies with large series, addressing several variables in different age ranges, from birth to the elderly adult. So, we will evaluate the contribution of these three variables in the study of parasympathetic autonomic behavior throughout the life cycle based on the evaluation of a significant amount of data (835,902 in total) extracted from the literature regarding heart rate variability variables and admittedly related to the parasympathetic nervous system being 53,882 results from healthy individuals.
\nThe inclusion criterion was quite broad in view of the proposed objective, which was to establish reference values, based on the largest amount of information possible. Thus, by searching the available databases (PubMed, Google Scholar, Cochrane Library, ScienceDirect, Wiley Online Library, SciELO, LILACS, and Thesis Banks of Brazilian Universities, among others) and following the PRISMA 2009 flow diagram [15], articles evaluating the values of heart rate variability (Flow Diagram) were included, and after, those directly related to the parasympathetic component of ANS, in the time domains (RMSSD and PNN50) and in the frequency domain (HF ms2), in humans, regardless of age and gender and also regardless of the length of the time series, patient position, and analysis equipment, were selected but provided that the data were always collected from individuals specifically considered to be healthy. Based on this criterion, it is noteworthy that the individuals, who in the original work were cataloged as being from the general population, were not considered to be healthy because there are known comorbidities in this type of sample, and so, they were not included.
\nMean evolutionary behavior of RMSSS values for the different age groups studied. RMSSD (root mean square of the successive RR interval differences in ms; 1, healthy newborns subgroup; 2, children and adolescents (up to 20 years) subgroup; 3, young adults (20–40 years) subgroup; 4, middle-aged adults (40–70 years) subgroup.
Values with evident evidence of extreme outliers (three or more standard deviations below the first quartile or above the third quartile, from the set of values collected for a given variable) were excluded.
\n\nTable 1 informs the studied variable, its domain, and the amount of values collected in the literature.
\nDomain | \nVariable | \nTotal group | \nGeneral population + diseased | \nHealthy | \n
---|---|---|---|---|
Time | \nRMSSD ms | \n208,657 | \n183,155 | \n25,502 | \n
Time | \nPNN50 | \n49,400 | \n35,043 | \n14,357 | \n
Frequency | \nHF ms2 | \n159,894 | \n145,871 | \n14,023 | \n
Distribution of the literature data evaluated, in terms of the variable studied, highlighting the sample of interest (healthy individuals) and its size in relation to the total amount obtained.
RMSSD (root mean square of the successive RR intervals differences, in ms; PNN50 (percent of normal RR intervals that differed by more than 50 ms in %); HF (absolute power of the high-frequency band; 0.15–0.40 Hz, in ms2).
\nGroupings were made by age range to precisely characterize the evolutionary behavior of the parasympathetic system throughout the life cycle. The amounts of data evaluated for each group and their average ages and standard deviations are shown in Table 2.
\nAge range (years) | \nAge mean ± SD | \nRMSSD (ms) | \nPNN50 (%) | \nHF(ms2) | \n
---|---|---|---|---|
Newborns | \n[0 a 3 days] | \n234 | \n78 | \n272 | \n
Up to 20 | \n13.29 ± 4.64 | \n4,419 | \n2,790 | \n4,346 | \n
20–40 | \n25.21 ± 4.88 | \n8,459 | \n1,031 | \n5,721 | \n
40–70 | \n52.74 ± 7.56 | \n12,390 | \n10,468 | \n3,684 | \n
Totals | \n\n | 25,502 | \n14,357 | \n14,023 | \n
Mean and standard deviation of the analyzed age groups and respective amounts of data analyzed, by studied variable..
From all included studies, the mean and the standard deviation values of each variable of interest were extracted. The overall mean value was obtained by weighted average. The global standard deviation was obtained from the individual mean set of each study. As the collected values were the means and standard deviations, the existence of normality was assumed. The values from the different age groups were compared with the aid of the unpaired t-test assuming that the standard deviations of each group were not similar to each other (Welch correction). GraphPad InStat version 3.00 software was used to obtain P-values. A PDF file containing all the 335 references used to mounting the database can be solicited to the correspondent author. The large number of references would make it impossible to include them directly in the present text.
\n\nTable 3 summarizes the results obtained.
\nGroup | \nAge range | \nRMSSD | \nPNN50 | \nHF | \n
---|---|---|---|---|
\n | \n | Mean ± SD | \nMean ± SD | \nMean ± SD | \n
1 | \nNewborns | \n11.6 ± 0.9 | \n1.4 ± 3.7 | \n66.7 ± 85.5 | \n
2 | \nUp to 20 | \n52.0 ± 18.0 | \n25.7 ± 11.6 | \n1124.0 ± 710.8 | \n
3 | \n20–40 | \n53.1 ± 22.2 | \n19.9 ± 12.9 | \n2067.2 ± 1144.7 | \n
4 | \n40–70 | \n28.2 ± 11.8 | \n6.9 ± 0.3 | \n236.3 ± 248.5 | \n
Mean and standard deviation of the variables studied according to the different age groups.
RMSSD (root mean square of the successive RR intervals differences in ms; PNN50 (percent of normal RR intervals that differed by more than 50 ms), HF (absolute power of the high-frequency band; 0.15–0.40 Hz); SD, standard deviation.
\nThe statistical analysis (p-values, t-test unpaired, two-tailed, Welch correction) comparing the mean values for each variable along the age ranges is showed below.
\nGroup | \nRMSSD | \nPNN50 | \nHF | \n
---|---|---|---|
1 versus 2 | \nP < 0.0001 | \nP < 0.0001 | \nP < 0.0001 | \n
1 versus 3 | \nP < 0.0001 | \nP < 0.0001 | \nP < 0.0001 | \n
1 versus 4 | \nP < 0.0001 | \nP < 0.0001 | \nP < 0.0001 | \n
2 versus 3 | \nP = 0.0024 | \nP < 0.0001 | \nP < 0.0001 | \n
2 versus 4 | \nP < 0.0001 | \nP < 0.0001 | \nP < 0.0001 | \n
3 versus 4 | \nP < 0.0001 | \nP < 0.0001 | \nP < 0.0001 | \n
As can be observed, the P-values were extremely robust indicating significant extreme differences for all comparisons.
\nFigures were constructed showing the behavior of each variable along the progressive increase in chronological age, from the healthy newborn group (subgroup 1) to children and adolescents (subgroup 2) and young adults (subgroup 3), until reaching the middle-aged adults (subgroup 4).
\n\nIt is well known that the heart rate variability declines with age. Bonnemeier et al. (2003) [16] obtained 24 h recordings from 166 healthy volunteers (85 men and 81 women) aged 20–70 years. They found the most dramatic HRV parameter decrease between the second and third decades. Almeida-Santos et al. (2016) [17] obtained 24 h ECG recordings of 1743 subjects of 40–100 years of age. They found a linear decline in SDNN, SDANN, and SDNN index. Curiously, they described U-shaped pattern for RMSSD and pNN50 with aging, decreasing from 40 to 60 and then increasing after age 70.
\nThe present study adds new information about this evolutionary behavior. It was quite clear that parasympathetic autonomic development in healthy individuals is peculiar, being reduced at birth, presenting a progressive elevation up to about 20 years of age (for the three variables studied), and typically, after that initial elevation, two different patterns of behavior occur. The RMSSD variable arises a little more until around 40 years of age when it then begins to decline progressively (Figure 1), which we might call as a “‘negatively skewed tent’ behavior.” The PNN50 variable, once reaching its maximum levels around the age of 20, begins to decline progressively until the age of 70 (Figure 2), which would graphically be a “positively skewed tent” behavior. Finally, the HF variable rises from birth to about 40 years, when it begins to decline until 70 years of age being graphically a “negatively skewed tent” behavior (Figure 3).
\nMean evolutionary behavior of PNN50 values for the different age groups studied.PNN50% ((percent of normal R-R intervals that differed by more than 50 ms); 1, healthy newborns subgroup; 2, children and adolescents (up to 20 years) subgroup; 3, young adults (20–40 years) subgroup; 4, middle-aged adults (40–70 years) subgroup.
Mean evolutionary behavior of HF ms2 values for the different age groups studied. HF ms2 (absolute power of the high-frequency band; 0.15–0.40 Hz); 1, healthy newborns subgroup; 2, children and adolescents (up to 20 years) subgroup; 3: Young adults (20–40 years) subgroup; 4, middle-aged adults (40–70 years) subgroup.
We did not find significant studies on heart rate variability in healthy individuals over 70s, probably because above that age, the vast majority of the individuals already have some pathological impairment. Yes, it would exist for the general population, but that was not the focus at this moment. Therefore, a complete definition of HRV behavior in that older group, based on a significant sample like that used here for the other age groups, was not yet possible.
\nThe significant amount of data obtained, together with the extremely significant difference between the values in the different age groups, strongly indicates that this was not a casual finding but a true expression of parasympathetic autonomic behavior.
\nThis is a relevant finding as it sheds new light on the knowledge of normal values in different age groups, since the current gold standard is still established by the Task Force data, based on only 274 cases and exclusively on the age range of 40–69 years.
\nLike every other complex system, in accordance with Chaos Theory, ANS, at least in its parasympathetic component, exhibits a near-parabolic and nonsynchronous behavior for the main variables that evaluates it using heart rate variability, and this fact should be considered in the comparative analysis between healthy individuals and those with different grades of pathological impairment.
\nBased on the largest data set ever available for healthy individuals, the found values can be proposed as reference standards for future studies about heart rate variability.
\nThe authors would like to thank the Brazilian CNPq (National Council for Scientific and Technological Development) [Processes 308759/2015-0 and 308555/2018-0] and to FAPESP (São Paulo Research Foundation) [Process 2017/125297] for the financial support.
\nThe authors declare no conflict of interest.
Packaging industry stands at third position globally, next to food and petroleum industries contributing nearly 2% of Gross National Product in developed nations [1]. Approximately 51% of all packaging applications are dedicated to food sector [2]. Consumer inclination towards safe and healthy food have led to the development of state-of-the-art and unique approaches in food processing and packaging. One such development is the introduction of smart packaging technologies. Smart packaging although interchangeably used for intelligent packaging at times, refers to combination of active and intelligent packaging [3]. The Framework Regulation on Food Contact Materials (1935/2004) defines “
Active and intelligent packaging market was estimated at 17.50 billion US $ in 2019 and expected to reach at 25.16 billion US $ by 2025 witnessing a CAGR of 6.78%. Asia Pacific region was identified as the fastest growing market including China, Japan, India and South Korea and North America as the largest market with WestRock®, Honeywell®, BASF® and Amcor Ltd. as the major market players. Oxygen and moisture scavengers are the utmost commercialized forms of active packaging. Gas scavengers for food was the most marketed active packaging technique in USA during 2018–2019 [5]. During past ten years, the research interestedness in active and intelligent packaging has increased steadily as indicated by the trend of peer-reviewed publications in Figure 1 during 2010–2019. As per a survey conducted by O’Callaghan and Kerry (2016) [6] for applicability of smart packaging to cheese, the future is highly optimistic with consumers willing to pay more on receiving the information provided by these advanced technologies. However, to the best of our knowledge, not a single article has reviewed the application and future research directions of smart packaging technologies in cheese. Therefore, the present review offers insight to active and intelligent packaging systems for cheese and future research aspects.
Graph illustrating the number of publications on active packaging, intelligent packaging and cheese during the year 2010–2019 (
World cheese production has shown significant increase from 5.43 million tonnes in 1961, 14.58 million tonnes in 1995 to 22.65 million tonnes in 2015 [7]. About 3000 varieties of cheeses are produced throughout the world and the annual total cheese consumption during 2015–2028 is expected to grow at a CAGR of 1.4% [8]. EU 28 (European Union consisting of 28 countries) stood at first position in cheese export by exporting 841.8 thousand tonnes of cheese. The USA accounted for almost 20% of the world’s cheese production and exported 348.5 thousand tonnes of cheese contributing 13.8% of the total export share during 2018 while Japan and Russia were the top export destination [8]. Approximately 40% of world’s milk is converted to cheese with France, USA, Iceland, Finland and other developed nations being the major players in cheese production and consumption [7]. The total cheese production in USA was 5,908 million kg, with an import of 176 million kg [8]. Mozzarella is the highest produced cheese variety in USA and several other major cheese producing nations [9]. Additionally, the retail prices of cheese in almost all the countries had shown an upsurge during last ten years [8]. The detailed information about cheese production, consumption, import, export quantity of several countries and retail price of selected cheeses are presented in Table 1. The total whole cow milk cheese in India was 2250 tonnes in 2014 [7]. It is true that India is not a traditionally structured ‘cheese nation’ but it is gaining pace with increased domestic consumption and exports. India offers only 40 varieties of cheese of which about 60 per cent of the market is dominated by processed cheeses, 30 per cent by cheese spreads and the remaining 10 per cent by flavored and Mozzarella cheese [10].
Country | Production | Consumption | Imports | Exports | Retail Price | ||
---|---|---|---|---|---|---|---|
Cheese type | Currency | Price/kg | |||||
EU28 | 9376 | 9652 | 59 (H) | 842 (H) | |||
Germany | 2339 | 2002 | 32 | 130 | Gouda | EUR | 5.98 |
France | 1725 (A) | 1721 | — | 117 | Emmental | EUR | 8.43 |
Italy | 1101 (A) | 1320 | 10 | 100 | Mozzarella | EUR | 4.46 |
Netherlands | 880 (A) | 420 | — | 140 | Gouda | EUR | 10.98 |
Poland | 825 | 723 | — | 53 | Gouda | PLN | 20.69 |
Denmark | 452 | 166 | — | 73 | |||
United Kingdom | 426 | 795 | — | Cheddar | GBP | 7.28 | |
Ireland | 224 | 31 | — | 49 | NS | EUR | 9.60 |
Austria | 200 | 200 | — | — | |||
Spain | 179 (A) | 416 | — | — | NS | EUR | 8.60 |
Czech Republic | 135 | 201 | — | — | Edam | CZK | 144.73 |
Belgium | 109 | 164 | — | — | NS | EUR | 9.65 |
Lithuania | 102 | 58 | — | Tilsit | EUR | 7.34 | |
Finland | 87 | 142 | — | — | Edam | EUR | 9.08 |
Hungary | 84 | 129 | — | — | Trappist | HUF | 1700.00 |
Sweden | 82 | 201 | — | — | Herrgardsost | SEK | 90 |
Latvia | 47 | 39 | — | — | Hard cheese | EUR | 7.89 |
Estonia | 45 | 32 | — | — | Gouda | EUR | 8.24 |
Slovakia | 38 (A) | 74 | — | — | Edam | EUR | 6.55 |
Cyprus | 3 (A) | 22 | — | — | — | — | — |
Luxemburg | 3 | 16 | — | — | — | — | — |
Other EU | — | — | 17 | 179 | — | — | — |
North and Central America | |||||||
USA | 5908 | 5668 | 176 | 348 | Cheddar | USD | 11.87 |
Canada | 443 | 538 | 31 | — | NS | CAD | 14.70 |
Mexico | 419 | 539 | 123 | — | — | — | — |
El Salvador | — | — | 39 | — | — | — | — |
Nicaragua | — | — | — | 41 | — | — | — |
South America | |||||||
Brazil | 755 | 781 | — | — | Mozzarella | BRL | 30.49 |
Argentina | 579 | 574 | — | 49 | Quartirolo-type | ARS | 184.24 |
Chile | 101 (B) | 198 | — | — | Gouda | CLP | 6396.00 |
Colombia | 97 | 100 | — | — | — | — | — |
Uruguay | 45 | 33 | — | — | NS | UYU | 143.22 |
Other Europe | |||||||
Russia | 473 | 811 | 263 | — | NS | RUB | 412.60 |
Belarus | 332 | 128 | — | 210 | — | — | — |
Switzerland | 190 (A) | 186 | 62 | 68 | NS | CHF | 13.32 |
Ukraine | 168 | 198 | — | — | Russian (50% fat) | UAH | 172.00 |
Norway | 82 (C) | 101 | — | — | — | — | — |
Iceland | 11 | 9 | — | — | — | — | — |
Asia | |||||||
Turkey | 753 (D) | 714 | — | — | — | — | — |
Israel | 146 (A) | 160 | — | 51 | Edam | ILS | 41.30 |
India | 48 (E) | — | — | — | Mozzarella | INR | 380.00 |
Japan | 45 (F) | 321 | 297 | — | Processed | JPY | 1890.00 |
China | 41 (G) | 149 | 124 | — | — | — | — |
Kazakhstan | 28 | 47 | — | — | — | — | — |
Republic of Korea | 4 | 156 | 124 | — | NS | KRW | 16,225.0 |
Saudi Arabia | — | — | 172 | — | — | — | — |
Indonesia | — | — | 30 | — | — | — | — |
Philippines | — | — | 38 | — | — | — | — |
Oceania | |||||||
New Zealand | 385 (G) | 48 | 323 | Cheddar | NZD | 8.84 | |
Australia | 344 | 350 | 98 | 176 | Cheddar | AUD | 13.25 |
Africa | |||||||
Egypt | 395 | 482 | — | 61 | NS | EGP | 59.41 |
South Africa | 108 | 109 | — | — | NS | ZAR | 117.19 |
Zimbabwe | 3 | 9 | — | — | NS | USD | 4.00 |
Total selected countries | 21,277 | ||||||
Rest of world | — | — | 865 | 381 | — | — | — |
World | — | — | 2550 | 2550 | — | — | — |
Cheese production, consumption, imports, exports (in ‘000 tonnes) and retail price during 2018–2019.
(A) Cow’s milk cheese only; (B) Based on production of big dairies; (C) 2018: Cow’s milk cheese- 72,600 tonnes; (D) 2018: Cow’s milk cheese- 658,500 tonnes; (E) Refers to co-operative dairies only; (F) Natural cheese production; (G) Including processed cheese; (H) Excluding Intra-EU trade; NS- Not specified (
In order to simplify the cheese packaging requirements, its mandatory to classify them in several categories depending on their moisture content (hard, semi-hard, soft, very-soft), shapes (wheels or half-wheel cheese, cheese slabs also known as portioned cheese, sliced cheese, cheese squares, soft and creamy cheese, grated, diced and processed cheese) and preservation techniques (cheese preserved in brine, wax coated, modified atmosphere or vacuum packaged). The very hard, extra hard, hard to semi-hard category of cheese possess moisture content in the range of 36–52% and includes Edam, Gouda, Swiss, Parmesan, Cheshire and Romano [11]. Rindless types of cheese are ripened in their packaging material alike to cheeses having their surface covered with molds, bacteria or yeasts producing enzymes responsible for ripening [12]. The important factors for selecting packaging materials of very hard to hard varieties of cheese are ripening time, temperature, cheese surface area to volume ratio, gas production (if any), cheese product form (sliced, grated, portions) and permeability of packaging materials [13]. The packaging systems for rindless cheeses includes laminates of polyethylene terephthalate- low density polyethylene (PET-LDPE) (300/50 μm thickness), cover film of oriented (O)PET-LDPE (23/75 μm thickness), tubular bags of oriented polyamide (OPA)-LDPE (15/40 μm thickness) and trough film of PET-HMLDPE (high molecular weight LDPE) (200/25/25 μm thickness). Wax coatings (mineral, paraffin and microcrystalline wax) are used to prevent mold growth, moisture evaporation and high gas barrier properties [11]. Modified atmosphere packaging (MAP) with high barrier materials (PA/EVOH (ethylene vinyl alcohol), LLDPE/EVA (ethylene vinyl acetate)/Ionomers) is generally used for portioned or sliced hard cheese owing to their large surface area exposure to light and oxygen. Vacuum packaging is not preferred for cheese with eyes (Swiss, Gouda, Edam) as it rupture the eyes structure [14].
The semi-soft and soft varieties of cheese contain 52–80% moisture and can be further categorized broadly in three groups (i) ripened by bacteria e.g. Brick, Munster; (ii) ripened by surface mold e.g. Limburger, Brie, Camembert and (iii) internally mold ripened e.g. Gorgonzola, Roquefort, Stilton [15]. Packaging requirements of bacteria ripened cheeses is affected by presence of light, humidity, pH and gases. Internally mold ripened cheese should be packed in O2, CO2 and water permeable packages e.g. polystyrene, polyvinyl chloride or thermoformed packages etc., for optimum mold growth [3]. For externally ripened cheese, packaging should not take place until mold had grown to certain extent and packaging material with certain permeability to O2 and H2O are prerequisite to avoid growth of anaerobic proteolytic bacteria and moisture condensation inside cheese pack, respectively.
Fresh or unripened cheeses (e.g. cottage, quark, cream etc.) have moisture content greater than 80% and are exposed to lactic acid fermentation. Such cheeses have very high chances of dehydration or whey expulsion owing to their high-water activity. Some of the suitable packaging material for fresh cheeses are injection molded HDPE or PP packages with side slits for whey drainage, paraffin or PVDC (polyvinylidene chloride) coated paper and LDPE or PP laminated aluminum (Al) foil (7–20 μm) [14]. Processed cheese is hot filled into pouches, polymer coated or lacquered Al foils (12–15 μm). Processed cheese slices are packed in laminates of PET-HDPE, PET-PVDC and OPP-EVOH-LDPE and processed cheese spreads in tubes of LDPE/EVOH/PET or metal tubes, PP or PET-LDPE cups heat sealed with Al foil, tin plate or enameled Al cans and glass cups closed with Al foil plastic laminate or lidded with an easy opening tin plate [17]. A comprehensive list of permitted additives and their recommended usage level is presented in Table 2, which could be utilized for the development of legally permitted smart packaging materials. Also, a few commercially available smart packaging systems used for cheese are listed in Figure 2.
Name of the additive (&INS No.) | Recommended maximum levels | |||
---|---|---|---|---|
Unripened cheese | #Ripened cheese | Plain processed cheese/processed cheese, processed cheese spread | Note | |
Aspartame (951) | 1000 mg/kg | — | — | If used in combination with aspartame-acesulfame salt (INS 962), combined maximum use level, expressed as aspartame, should not exceed this level. |
Carotenoids | 100 mg/kg | — | 100 mg/kg | |
Chlorophylls and Chlorophyllin, copper complexes | 50 mg/kg | — | 100 mg/kg (Chlorophyll- INS No.-140) | |
Canthaxanthin (161 g) | 15 mg/kg | 15 mg/kg | — | For use in flavored products only |
Caramel III - ammonia caramel (150c) | 15000 mg/kg | — | — | |
Caramel IV-sulfite ammonia caramel (150d) | 50000 mg/kg | — | — | |
Indigotine (Indigo carmine) (132) | 200 mg/kg | — | — | For use in surface treatment only |
*Lauric arginate ethyl ester (243) | 200 mg/kg | — | — | Equivalent to 2 mg/dm2 surface application to a maximum depth of 5 mm, For use in surface treatment only |
Natamycin (Pimaricin) (235) | 40 mg/kg | 40 mg/kg | 40 mg/kg | |
Phosphates | 4400 mg/kg | — | 9000 mg/kg | As phosphorus |
Polysorbates | 80 mg/kg | — | — | On the creaming mixture basis |
Ponceau 4R (124) | 100 mg/kg | — | — | For use in surface treatment only |
Riboflavins | 300 mg/kg | 300 mg/kg | 300 mg/kg | |
*Sorbates | 2000 mg/kg | 3000 mg/kg | 3000 mg/kg | As sorbic acid, For Chhana and paneer only) |
Nisin (234) | 12.5 mg/kg | 12 mg/kg | 12.5 mg/kg | For Chhana and paneer only |
Propionic acid, sodium propionate, calcium propionate (singly or in combination, expressed as propionic acid) (280, 281, 282, 283) | 3000 mg/kg | 3000 mg/kg | — | |
Glucono delta lactone (575) | GMP | — | — | |
Sunset yellow FCF (110) | 100 mg/kg | — | 100 mg/kg | For use in surface treatment only |
Calcium chloride (509) | 200 mg/kg | 200 mg/kg | Except cream cheese | |
Beta-carotenes, vegetable (160a(ii)) | 600 mg/kg | 100 mg/kg | 1000 mg/kg | Except Coulommiers |
Carrageenan (407) | 5000 mg/kg | — | For cream cheese only | |
Alginate of sodium/potassium/ calcium (410, 402, 404) | 5000 mg/kg | — | — | For cream cheese only |
Propylene glycol alginate (405) | 5000 mg/kg | — | — | |
Paprika extract (160c) | GMP | GMP | — | |
Curcumin (100) | GMP | 100 mg/kg | 100 mg/kg | |
Annatto (160b (i) and (ii)) | GMP | $100 mg/kg @50 mg/kg | 50 mg/kg | $(Norbixin based) @(Bixin based) |
Lysozyme (1105) | — | GMP | — | |
Sodium salts of mono/di/poly phosphoric acid (339, 450 (i, ii, iii), 451 (i), 452 (i)) | — | 9000 mg/kg | — | Total salt content should not exceed 9000 mg/kg calculated as phosphorous/carbonates /citrate/ chloride |
Potassium salts of mono/di/poly phosphoric acid (340, 450 (iv, v), 451 (ii), 452 (ii)) | — | 9000 mg/kg | — | |
Allura red AC (129) | — | — | 100 mg/kg | |
Diacetyltartaric and fatty acid esters of glycerol (472e) | — | — | 10000 mg/kg | |
Hydroxybenzoates, para | — | — | 300 mg/kg | As para-hydroxybenzoic acid |
Iron oxides | — | — | 50 mg/kg | |
Sodium aluminum phosphates | — | — | 1600 mg/kg | For use in processed cheese only As aluminum |
Pimaricin (Natamicin) (235) | — | 2 mg/dm2 surface. | — | For surface/rind treatment only Not present in depth below 5 mm |
Additives permitted in different varieties of cheese as per FSSAI (Food Safety and Standards Authority of India).
Ingredients permitted in whey cheese includes Lauric arginate ethyl ester (INS No.-243) - 200 mg/kg and Sorbates (1000 mg/kg).&INS- International Numbering System for food additives.
$Indicates the amount of annatto if it is norbixin based.
@It indicates the amount of annatto if it is bixin based.
#Ripened cheese- Cheddar, Danbo, Edam, Gouda, Havarti, Tilisiter, Camembert, Brie, Saint Paulin, Samsoe, Emmentaler, Provolone, extra hard grating/sliced/cut/shredded cheese.
Commercially available active and intelligent packaging systems for cheese (A) biodegradable active antifungal film Antipack™ AF, Handary, Brussels, Belgium (B) antimicrobial films with natamycin, VGP SL®, Barcelona, Spain (C) edible plastic films developed from casein by Lactips, France (D) pull timer™, time temperature indicator for indicating temperature abuse developed by Macfarlane labels and insignia technologies, Scotland. (
“Active packaging” term was coined by food scientist Dr. Theodore Labuza [3], which includes oxygen absorbers, carbon dioxide absorbers/emitters, moisture absorbers, self-heating and self-cooling containers, antimicrobial packaging, ethanol emitters, flavor absorbers/releasers and microwave assisted containers [18]. The following section discusses different active packaging systems applicable to cheese and brief studies on active packaging materials for cheese and its products are also presented in Table 3.
Type of active packaging | Variety of cheese | Description |
---|---|---|
Cottage cheese [19] | Sachets of allyl isothiocyanate were effective against yeast and mold | |
Mozzarella cheese [13] | Lysozyme and ethylenediaminetetraacetic disodium salt (Na2-EDTA) inhibited the growth of coliform and | |
Kashar Cheese [20] | Zein and zein-wax coating with lysozyme, catechin and gallic acid. Lysozyme based film prevented the growth of | |
Mozzarella cheese [21] | Packages containing calcium lactate and lactic acid-based brine enhanced the shelf-life by 50% | |
Surface ripened cheese [22] | Polyethylene films coated with polyvinyldichloride and containing natamycin/nisin possessed inhibitory effect against | |
Zamorano sheep cheese [23] | Poly propylene and polyethylene terephthalate films with | |
Saloio cheese [24] | Whey protein isolate coating containing natamycin reduced water loss, color changes and microbial growth throughout the storage period of 60 days | |
Low fat cheese (5% fat in dry matter) [25] | Microbial oxygen absorber; Contains microorganisms which utilizes oxygen e.g. | |
High fat cheese (60% fat in dry matter) [25] | Microbial oxygen absorber containing | |
Cheddar cheese [26] | Microbial oxygen absorber containing | |
Delite 5% sliced cheese [26] | Microbial oxygen absorber containing | |
Saloio cheese [27] | ||
Camembert cheese [28] | 3-layered film with absorber/desorber film. 10% concentration of water absorbent, maintained attractive white appearance of cheese while 25% caused damage of the varnish layer due to swelling. | |
Cheese puffs [29] | Tricalcium phosphate-based UV light inhibitor could be incorporated directly into dry mix flavor powder of cheese puffs cooked in hot oil to prevent light induced rancidity and spoilage. |
Types of active packaging materials/systems explored for cheese and cheese-based products.
The presence of moisture not only affects the package appearance but also leads to poor texture and quality of cheese both microbiologically and chemically. Moisture control in the cheese package reduces the water activity thus preventing microbial growth and leaching of soluble nutrients [17]. Moisture scavengers include desiccants like silica gel, molecular sieves, natural clays like calcium oxide, calcium chloride and modified starch in the form of pads, sheets, sachets and blankets [4]. Moisture control in cheese packages could also be attained by incorporating humectant between different layers of packaging material, while keeping the inside layer water permeable. A two layered packaging material for moisture sensitive products like soft cheese was developed by [30] Marbler & Parmentier, (1999). The packaging material consisted of first functional layer (coated paper) for storing and releasing moisture and second layer (plastic laminate) for controlling gas permeability as a function of moisture content. These types of packaging material find their utility for cheese matured inside the package. Pantaleao, Pintado, & Pocas (2007) [27] successfully demonstrated humidity controller (Humidipak®) with Saloio cheese for shelf-life extension. A dual compartment vacuum packaging system (Tenderpac®) developed by SEALPAC® (Germany) for neatly collecting the drip loss from meat products, could be optimized for fresh unripened cheeses like mozzarella, quarg and cottage [31].
Oxygen scavengers market size was 1.80 billion USD in 2016 which is estimated to reach 2.41 billion USD in 2022 at a compound annual growth rate (CAGR) of 5.1%. North America (USA, Canada and Mexico) is the leading market while Asia Pacific region (China, India, Japan and South Korea) is the fastest growing market [5]. Oxygen is majorly responsible for cheese spoilage as its presence facilitates the growth of aerobic microorganisms, oxidation of cheese components, nutritional value decline, off-flavors generation, unacceptable color changes, shelf-life reduction and decrease in food safety [32]. Therefore, control of oxygen content inside cheese package is of prime importance. Modified atmosphere packaging (MAP), vacuum packaging and oxygen absorbers are the alternatives available to reduce or completely remove oxygen from the package [25]. However, MAP and vacuum packaging require costly equipment for packing cheese and still do not remove the oxygen completely (residual oxygen could be up to 1% in the headspace). Vacuum packaging can affect the appearance and structure of soft cheeses adversely and oxygen can also permeate through the packaging film during later stages of storage or distribution [33]. Oxygen scavengers provide the best alternative to remove the oxygen permeating through the packaging film and also to overcome the challenges of MAP and vacuum packaging [34].
The shelf-life of cheese tarts increased to 48 days when packaged with an iron-oxide based oxygen scavenger as compared to 7 days for control samples [35]. An oxygen scavenging film containing a blend of ethylene, methyl acrylate and cyclohexene methyl acrylate copolymer as oxygen scavenger resin was developed to overcome the oxidative rancidity in cheeses, dried milk and meat products [36]. A study on the effectiveness of various packaging methods for Gouda cheese revealed that oxygen scavengers (ATCO FT 210) were as effective as vacuum packaging and MAP (40% CO2 and 60% N2) in prolonging its shelf-life [34]. Microbiological oxygen scavenging material consisting of
Cheeses like Cheddar, Swiss, Blue, Colby etc. are highly prone to lipid oxidation owing to their high fat content. Antioxidants are extensively used to prevent oxidation by scavenging free radical but due to augmented customer trend for additives free food products, incorporation into packaging material is the best option [40]. Antioxidants incorporation into packaging material not only prevents quality deterioration of the product but also stabilizes the polymer [41]. Synthetic antioxidants like butylated hydroxytoluene (BHT) and butylated hydroxy anisole (BHA) are conventionally used in cheese packing. As per Code of Federal Regulation (CFR 21/172.115), the maximum rate of BHT addition to cheese is 200 mg/kg of fat and specific migration limit of BHA is 30 mg/kg of food product as per EU 10/2011 regulations. Asadero cheese was vacuum packed in LDPE co-extruded film containing 8 and 14 mg/g of BHT. Cheese packed in LDPE film incorporated with 8 mg/g of BHT had oxidized flavor while film with 14 mg/g of BHT surpassed the legal limit of BHT addition [42]. Therefore, similar to natural counterparts of other additives the recent focus is on natural antioxidants. Pomegranate peel extract (PPE) incorporated into zein films for packaging of Himalayan Kalari cheese retarded the oxidation of fat and protein due to the presence of polyphenols in PPE [43]. Sliced cheese packed in red algae films incorporated with 1% grape fruit seed extract (GFSE) showed decreased peroxide and thiobarbituric acid value indicating the antioxidant capability of GFSE [44]. Gelatin-chitosan edible film with Boldo herb extract possessed antioxidant and antimicrobial activity and had preservative effect on sliced Prato cheese by preventing psychrotrophs [41]. Similarly, other natural antioxidants like green tea extract [45], catechins [46] and rosemary extract [40] had been explored for their antioxidant potential in cheese packaging but the major challenge with antioxidant incorporated films in cheese packaging is synchronization of antioxidant diffusion rate according to cheese requirement. Also, for natural antioxidant incorporation in continuous film production by extrusion, their stability or thermal degradation is the major concern [46].
Cheeses packed with higher CO2 may suffer from sensory related issues as its dissolution leads to formation of carbonic acid [14]. Taleggio cheese produced excessive 2.5 mmol kg-1 day-1 CO2 when stored in nitrogen flushed packages at 6°C causing quality degradation [47]. However, carbon dioxide production is essential in some cheeses to achieve desired texture, eye formation in Emmental and Swiss cheese, and inhibition of microorganisms but excessive production could lead to puffed pouches or package burst [48]. When cheeses are preserved and sold at ambient temperature or when desired shelf life is high, the adverse effects of higher CO2 concentration aggravates many folds [47]. In such circumstances, carbon dioxide absorbers could be used to remove the excess CO2 and create a balanced internal cheese package atmosphere [2]. The only noticeable progress in segment of CO2 absorbers for cheese is by Fellows (2009) [49], who developed a mechanism for CO2 release from mold ripened cheese (e.g. Camembert) package using one-way valve while disallowing other gases to infiltrate. Crump (2012) [50] developed a CO2 absorber pouch using polyethylene that contained 1.1 g of calcium hydroxide (200 mesh) and silica gel each in 2:1 mixture of water for shrink wrapped Swiss cheese (114 g) and reported that the product remained in good color with acceptable taste without any expansion due to CO2 release during storage at 5°C for 4 months. The gas composition and volume of modified atmosphere packed semi-hard cheese (Kadett®, Arla Foods) packages were optimized using mathematical modeling based on gas solubility coefficients, initial carbon dioxide content in cheese and packaging material, thus avoiding consumer rejection due to volume changes [48].
Light, and principally UV light, may cause or accelerate various undesirable reactions like lipid oxidation in cheese. Also, riboflavin, an efficient photosensitizer, present in cheeses at levels of 0.30–0.60 mg/100 g, quickly captivates energy owing to its conjugated double bond and generates either free radicals or reactive oxygen species (ROS). These free radicals and ROS are the major causes of lipid oxidation, off-flavors, color bleaching and nutrient losses especially vitamin A in cheeses [51]. Light stabilizers are divided into five major categories namely: light absorbers, light screeners, excited-state quenchers, peroxide decomposers and free radical scavengers based on their mode of action [52]. Kristoffersen, Stussi, & Gould (1964) [53] reported reduced flavor deterioration in consumer packs of cheddar cheese using Uvinul D 49® as a UV light screening material. Uvinul® S-Pack is a novel FDA approved UV absorber for PET packaging films, which prevented the UV degradation of vitamins and β-carotene, thus highlighting its potential of preventing light degradation changes in cheeses kept in refrigerated illuminated cabinet of supermarkets [54]. Recently, flavonoids had been reported to facilitate the dissipation of photon energy to heat thus deterring photodegradation [22]. Thus, flavonoids incorporated packaging material as natural active element for UV light absorption may be explored for cheese.
Antimicrobial packaging is the most researched forms of cheese active packaging. Antimicrobial agent at certain minimum concentration (known as minimum inhibitory concentration (MIC)) diminishes or impedes microbial growth [9]. Antimicrobial effect in cheeses is most commonly obtained by organic acids and its salt derivatives (sorbic acid, citric acid and their anhydrides), bacteriocins (nisin, lacticin and pediocin), fungicides (imazalil and natamycin), enzymes (lysozyme and lactoferrin), essential oils (basil leaf, thyme, oregano and cinnamon) and miscellaneous compounds like potassium metabisulphite, allyl isothiocyanate, EDTA (ethylenediaminetetraacetic acid) or a combination of these agents [22, 55, 56]. Antimicrobial agents which are sensitive to higher polymer processing temperature are usually applied as coatings. Gliadin based bioplastic films prepared by casting, and containing cinnamaldehyde as active ingredient inhibited fungal growth in cheese spreads [57]. Immobilization of antimicrobial agents like nisin on the surface of cheese packaging material is a convenient technique, however immobilization is appropriate for fluids because of direct contact between antimicrobial surface and entire liquid food [58]. Active polyethylene terephthalate film immobilized with silver nanoparticles extended the shelf-life of white fresh cheese up to 30 days [59]. Labels containing antimicrobial agents can also be used for enhancing cheese shelf life. Labels containing allyl isothiocyanate enhanced the shelf-life of Danish Danbo cheese to 28 weeks when used in combination with MAP as compared to 18 weeks with MAP alone [60].
Chitosan, a natural polysaccharide had been utilized for antimicrobial cheese packaging owing to its biodegradable, antimicrobial, filmogenic and metal complexation attributes [61]. Cellulose polymer based antimicrobial films incorporated with nisin and natamycin showed the potential for preservation of sliced Mozzarella cheese [62]. Electrospinning technique was utilized for incorporation of nisin (at the rate of 5 mg/mL) in polyethylene oxide nanofibers to inhibit
Flavor emitters are mainly used to impart flavor to any packed product or scalp/downgrade any undesirable flavor due to harsher processing conditions, thereby improving sensorial attributes and chances of modifying product formulation [66]. It may be used for masking off-flavors but food processors may unfairly market their expired, unsafe or low-quality foods without letting the consumers know. ScentSational Technologies® is global leader in developing food packages with controlled release of legally permitted flavor into headspace of a pack at varying intervals and provision for adjustment of flavor intensity [31]. Recently, they have also ventured into developing customized and patented injection molded scented and/or flavored parts of any pack. Kraft foods had developed a system for controlled and prolonged release of volatile flavor upon opening and reopening of the package [67]. Such type of packaging innovation could also be used for cheese products like chiplets, slices, processed cheese etc. which are usually contained in multi-use packages.
Color releasing multilayered film is the novel technique for incorporating permitted food grade colors (Table 2) such as annatto over cheese surface. Such films generally find their application when low intensity shade of color is desired or color is adversely affected during any processing step, storage or distribution. Mohan, Ravishankar, & Gopal, (2010) [4] suggested the migration of edible food permitted red color from the wrapper of surimi to provide it a more desirable and acceptable color. Similarly, α, β-citral migrated from the cellulose acetate films and improved the yellowness of Coalho cheese without affecting its texture during 25 days of storage [68].
Rindless cheeses are cooked or uncooked hard varieties of cheese that are ripened in plastic film which allows little or no gas or moisture movement e.g. Cheddar, Edam, Gouda and Swiss. Natural rind is the outer crust of cheese formed either during cheese making or storage under controlled humidity and temperature [3]. These rinds are highly susceptible to undesirable fungal growth and becomes slimy at times. Gerber, Koehler, Grass, & Stark (2012) [69] developed a three layered, self-cleaning and porous rind inoculated with
Microwave susceptors are the substances which absorb microwave energy and convert it into heat energy. It consists of Al foil layer deposited on paperboard or polyester film for uniform heating treatment [18]. Emmi®, a USA based cheese manufacturing firm, provides different variants of fondue recipes (melted Swiss cheese) in microwaveable containers which are ready-to-(h)eat, convenient and recyclable [70]. These types of microwave assisted heating packs could be used for melted cheese recipes. The major concern with microwave assisted heating cheese containers is duration of microwave heating. Some pop-up sound mechanism could be attached with package which blows up and makes a noise on complete even heating of the package content [3].
Pesticide control agents are generally used with secondary packaging systems to prevent insects, or for fungicidal control, during import and export of food products over distant horizons. Packaging material with pesticide control could also be used to prevent detrimental effects of pests and insects for cheeses like Cheddar, Parmesan etc. which require longer ripening period. The major concerns with these types of pesticide control agents containing packaging is their permissible limit and regulatory issues for use with cheeses. Natamycin is a GRAS status (as per FDA) fungicide which is produced during fermentation by
Intelligent packaging has not been researched extensively for cheese as reflected by very few publications in Figure 1. A few intelligent packaging systems investigated for cheese are presented in this section. However, large size of cheese market including import and export offers attractive opportunities. A list of different suppliers of commercially available smart packaging materials along with their head office, website and contact point are detailed in Table 4.
Type of smart packaging | Company (Head Office) | Brand name | Website | Distributor/Contact point in Asia |
---|---|---|---|---|
Clariant® Chemicals (Switzerland) | OXY-GUARD™, O-Buster® | www.clariant.com | Clariant Chemical, Vadodara | |
Mitsubishi Gas Chemical (Japan) | Ageless | www.mgc.co.jp | Information & Advanced Materials Company, Oxygen Absorbers Division, Japan | |
Toppan Printing (Japan) | Freshilizer | www.toppan.com | Max Speciality Films Limited, Punjab, India | |
Multisorb Filtration Group® (New York, USA) | StabilOx®, Freshmax | www.multisorb.com | — | |
Southcorp Packaging (Acquired by Visy®) (Australia) | Zero2 | www.visy.com.au | No facility in India. Available in Thailand. | |
AGM Containers (USA) | ActiSorb®O | Clariant India, Maharashtra India | ||
Avery Dennison (California, USA) | TT Sensor™ | www.averydennison.com | Bangalore, Karnataka | |
IntroTech (Netherlands) | Monitor Mark® | www.introtech.eu | — | |
Vitsab® (Limhamn, Sweden) | CheckPoint® | www.vitsab.com | — | |
TempTime® Corporation (USA) | Fresh-Check® | www.temptimecorp.com | Lisaline Lifescience Technologies Pvt. Ltd., Thane, India | |
Life Materials Technology Limited (Hong Kong) | Agion® | www.life-materials.com | — | |
Addmaster Limited (UK) | Biomaster® | www.addmaster.co.uk | Jebsen & Jessen, Indonesia (Contact point in Asia) | |
VGP (Barcelona, Spain) | Natamycin | — | ||
Evert-Fresh Corporation (USA) | Evert-Fresh | www.evertfresh.com | — | |
Sekisui Jushi (Japan) | Neupalon | www.sjc-strapping.com | — | |
Peakfresh Products Ltd. (Australia) | Peakfresh | www.peakfresh.com | — | |
Sealed Air® Corporation (USA) | Dri-Loc® | www.sealedair.com | — | |
SEALPAC® (Germany) | Tenderpac® | www.sealpacinternational.com | Synerchem Sdn. Bhd., Selangor, Malaysia (Contact point in Asia) | |
Freshpoint Lab (Australia) | O2 Sense | www.freshpoint.com | — | |
Timestrip Ltd. | Timestrip | — | — | |
Mitsubishi Gas Chemical (Japan) | Ageless Eye | www.mgc.co.jp | Information & Advanced Materials Company, Oxygen Absorbers Division, Japan | |
Insignia Technologies Ltd. (Scotland) | Novas | www.insigniatechnologies.com | — | |
Temptrip LLC (USA) | Temptrip | www.temptrip.com | — | |
Mondi Plc (Austria) | Intelligent Box | www.mondigroup.com | — | |
COX Technologies (USA) | Fresh Tag | www.cox-tec.com | — | |
Timestrip (UK) | Timestrip® | www.timestrip.com | — | |
Ripesense Ltd. (New Zealand) | ripeSense® | www.ripesense.co.nz | — | |
Sirane Food Packaging Limited (UK) | Sira-Crisp™ | www.sirane.com | Sirane East, Vostok, Russia | |
VacPac Inc. (USA) | SmartPouch | www.vacpacinc.com | — |
Suppliers and Asian contact point of commercially available smart packaging systems.
Source: compiled from internet using website of the companies.
Gas indicators or package integrity or leak indicators generally indicate the presence or absence of any gas (majorly oxygen) on the basis of certain chemical or enzymatic reactions. Cheeses are packed under modified atmospheres usually devoid of oxygen to enhance their shelf life. However, the gas composition of cheese package may change relying on the microbial growth inside the package, barrier properties of the packaging material, efficiency of packaging system, or physical damage, if any, that causes leakage [72]. So, knowing the level of oxygen is important to ensure cheese quality and safety in the entire supply chain and throughout its shelf-life. Redox dye-based oxygen indicators have been reported to indicate the package integrity and status of MAP in food non-destructively [73]. A schematic illustration of Mozzarella cheese package equipped with an oxygen indicator and oxygen scavenger with dye-based oxygen sensor is presented in Figures 3 and 4, respectively.
A schematic illustration of intelligent packaging system using an oxygen indicator applied to mozzarella cheese package (
A schematic illustration of smart (active + intelligent) packaging system for mozzarella cheese package with oxygen indicator (shown in pink color) and oxygen scavenger (O-buster® oxygen scavenger) (
A single use fluorescent-based oxygen sensor prepared using platinum octaethylporphyrin-ketone (PtOEPK), a phosphorescent oxygen-sensitive dye, sensed oxygen concentration changes in MAP cheddar cheese over a period of 4 months. The sensor was reported to possess sensitivity in the range between 0.02% and 100% oxygen. Correlation between oxygen concentration and microbial growth presented an opportunity for assessment of cheese quality using colorimetric oxygen sensor [74]. Similarly, dye based ultraviolet light activated oxygen sensor was successfully developed and characterized for its oxygen sensitivity, oxygen dependent color change and mechanical properties by Deshwal et al. (2018) [75]. The developed indicator was integrated with MAP Mozzarella cheese as an integrity/oxygen indicator, which could be helpful for stakeholders in the entire supply chain [15]. Hempel, Gillanders, Papkovsky, & Kerry, (2012) [76] successfully exploited optical oxygen sensors for detecting integrity (ingress of oxygen) of vacuum packaged cheddar cheese samples during its storage.
Freshness indicators, mostly colorimetric in nature, determine the safety, quality or freshness of product based on microbial growth or chemical change. They trigger a visual indication mechanism by detecting the metabolites of microbial or chemical change [77]. Possibilities of freshness detection of packaged milk, cream and cottage cheese using polymer-based labels was proposed by Chen & Zall (1987) [78]. Major approach for characterizing the deterioration of any cheese is by identifying the volatile organic compounds liberated during its storage (or ripening) using solid phase microextraction-gas chromatography/mass spectroscopy (SPME-GC–MS). Octane, hexanal and 2-pentyl-furan were the indicators for light exposure as obtained during the volatile profile of processed cheese [79]. Fourier Transform Infrared Spectroscopy (FTIR) and near infrared spectroscopy (NIR) have also been used to rapidly identify the chemical groups involved in the Crescenza cheese spoilage for possible development of freshness indicator [80]. Most recently, a biodegradable chitosan film containing pomegranate peels/Melissa officinalis essential oil demonstrated not only antimicrobial potential but also anthocyanins functionality as a spoilage indicator changing its color from blue to red due to pH change of cream cheese during spoilage [77]. A diverse blue cheese classification or identification indicator based on chromogenic array pattern of several pH dyes differentiated five cheeses i.e. Roquefort, Blue Stilton, blue cheese with leaves, blue cheese spread and Cheddar with 100% accuracy [81]. Such type of indicators can be used as freshness indicators of blue cheese where the changes in pH and color could be correlated with cheese spoilage. An attempt for the development of red cabbage extract-based pH indicator for monitoring Ricotta cheese spoilage was reported by Bento, Pereira, Chaves, & Stefani, (2015) [82]. Biogenic amines like histamine, tyramine, tryptamine and phenylethylamine are produced in cheese during ripening. Several reports of histamine poisoning in the past for Gouda, Swiss, Cheddar, Cheshire etc. cheeses indicate the potential of biogenic amines as freshness or spoilage indicators for cheese [83]. Freshness indicators for poultry, fish and seafood are commercially available, but a very few “biological use by date” or “chemical best before date” indicators for dairy products had been reported to the best of our knowledge indicating research possibilities in this area.
Cheese ripening indicator could be defined as the use of any technique/process/sensor for spotting metabolites (majorly volatiles) or chemical breakdown by-products of glycolysis, proteolysis and lipolysis to quantify the maturity or age of any cheese variety. The earliest attempt in cheese segment included the use of amido black dye for detecting the age of Cheddar and lactose-hydrolyzed cheddar cheese. Dye binding values were correlated with the free amino acid content [84]. Electric nose (or e-nose) had been used for headspace fingerprinting of packaged ripened cheese (Crescenza) volatiles and the data obtained was found to be helpful for its shelf-life measurement [85]. Tavaria, Ferreira, & Malcata, (2004) [86] quantified major ripening descriptors like free fatty acids, acetic, isobutyric and isovaleric acid concentration during 180 days ripening period of Serra da Estrela cheese. These volatile fatty acids furnished information about the optimal consumption time of cheese which could also be successfully used as ripening indicator. Industrially successful models based on infrared reflectance spectra, attributed to the changes in absorbance patterns of alcohol and amide groups have been used to predict the ripening stages and sensory characteristics of Cheddar [87] and Camembert cheese [88] with a minute error of one day.
The shelf-life of any food commodity as mentioned on the package in terms of “biological use by date” or “chemical best before date” is subject to its temperature exposure history owing to temperature dependence of microbial growth, enzyme activity and chemical reactions. Time temperature indicators (TTIs) convey information about the temperature exposure of the food commodity over a period of time [89]. TTIs mainly finds their applications in temperature sensitive food products that are stored or distributed in chilled conditions like milk, cheese, ice-cream, yoghurt, meat, fish etc. Shellhammer & Singh (1991) [90] used enzyme-based full history TTI (I-POINT®) on cottage cheese to correlate temperature variation with cheese quality parameters and reported that the TTIs response was significantly affected by pH, titratable acidity and standard plate count of cheese samples. However, attempts of TTI usage in cheese are few and include shelf-life evaluation of Taleggio cheese [91] and Caprino type cheese [92] using TTIs. Potential of diacetylenic monomers as active ingredient in TTIs based on polymerization reaction for monitoring cheese maturity had also been suggested [93]. A study on evolution of proteolytic activity products in Azeitao cheese with fluctuating temperature revealed prominent presence of two free amino acids (valine and leucine) and two biogenic amines (tyramine and putrescine), which may serve as temperature change indicators for the development of microbial TTI for ripened cheese [94].
Cheese traceability at batch level is maintained using self-adhesive casein labels, written records, and in advanced cases information is stored in a local database. However, such systems are inefficient considering food safety, counterfeiting risks, voluminous cheese production, warehouse optimization and cost involved in production [95]. So, application of RFID tags at ‘farm to fork’ levels of cheese industry could provide reliable solutions as it stores more information and assess at longer distances [12]. Regattieri, Gamberi, & Manzini (2007) [96] developed a RFID based traceability systems for hard cheese (Parmigiano Reggiano) which detects the history of the product over entire supply chain. Every minute information starting from feed input, production details to detailed pedigree of a cheese piece is available, thus even facilitating consumers to authorize cheese origin and prevent cheese imitation. The final cost of such RFID tags on customer was calculated to be 0.5%. Similarly, improved traceability of long-ripened cheeses (Bra Tenero, Bra Duro, Raschera and Toma Piemontese) with automatic movement recording during production, handling in ripening room and warehouse, delivery, packing and selling was achieved using tags operating at low (125 kHz), high (13.56 MHz) and ultra-high (865 MHz) frequency [12]. RFID tags with an ability to store data related to 200 variables of cheese production not only improved the quality and yield control of the production plant but also possessed robustness against different temperature, humidity, acid and frictional forces [97]. Papetti et al. (2012) [98] designed a web based “infotracing system” for Italian cheese (
Physical shock indicators are of prime importance for status quo of any fragile product during its rough handling or carriage. Cheeses are often exported across the globe with highest probability of mishandling by personnel during any step of distribution channels or improper selection of transportation channel. Physical shock indicators could be developed using diffusion mechanism, where a fluid leaks and collects irreversibly in another impermeable package, thus indicating the force or pressure to which package content had been exposed. To the best of our knowledge and literature mining no physical shock indicator for cheese and food packaging had been reported. Convex-concave type of metallic structure could also be used to identify the forces to which any cheese packages are exposed over long distances.
Packaging could also be used for facilitating the reduction of cholesterol and lactose in cheeses using cholesterol reductase and lactase enzymes. Cholesterol reductase enzyme converts cholesterol to undigested form (coprosterol), reducing its absorption in intestine. An innovative ethylene-vinyl alcohol copolymer (EVOH) plastic encompassing 30% beta-cyclodextrins reduced the cholesterol concentration by 23% in UHT milk [100]. Such type of active plastic films could be incorporated with β-galactosidase enzyme (lactase) and explored for the development of lactose free whey cheeses due to increased incidences of lactose intolerance across the globe [101].
Citric acid, ferrous salt/ascorbic acid, cellulose triacetate and activated carbon/clays/zeolites are most commonly used off-odor absorbers finding their use in fish, cereals, fruits and poultry products [3]. Off-flavor and odor scavengers prevent cross contamination of pungent odor and aids in improving the overall acceptance of cheeses. However, it is imperative that the constituents scavenged should not be spoilage indicators or essential for flavor development. Some ketones, aldehydes and esters are associated with fruity flavor of cheeses which may be undesirable for some customers [102]. Aldehyde and ester scavengers in cheese packaging can be helpful in improving its sensorial quality. The identified volatile compounds from the headspace of cheese packages revealed the possibilities for development of absorption system and stabilization of sensory qualities of semi-soft ripened cheese [103].
The earliest documented and patented step to achieve the tack ability of a multilayered polyester film over cheese surface was the electrical discharge or flame treatment of the inner surface [104]. Such films were temporarily adherent and easily peel able while opening cheese package. Presently, these anti-stick films can find their vast application for packaging individual slices of processed cheese or Mozzarella cheese spheres thus, reducing sticking losses.
Carbon dioxide and ethanol not only inhibit bacteria, yeasts, molds but also reduces oxidation and could be used individually or in combination for cheese packaging systems to inhibit microbial growth and pack shrinkage [105]. Cheese is most commonly packed with higher CO2 concentration using MAP technique but CO2 dissolves in the product leading to package collapse [6]. Package collapse could be overcome by inserting CO2 emitters in standard MAP cheese trays with perforated false bottom. The controlled release of ethanol in cheese packs could be obtained by encapsulating in a carrier material [65]. Ethicap®, a commercialized ethanol emitter absorbed in silica pads and embedded in sachets made from ethylene vinyl acetate copolymer prevented the growth of molds and yeast, thereby enhancing the shelf-life of soft cheeses [106]. However, objectionable off-flavors involved with higher concentration of CO2 and ethanol are concerning and supplementary flavor mixtures may be required.
An innovative single use package having the ability to absorb oxygen, carbon dioxide and water vapor, comprising of calcium hydroxide which emits water due to CO2 absorption, thus activating transition metal (iron oxide) based oxygen scavenger has been developed. Such containers would be suitable for hard cheeses like Taleggio, which emits large amount of CO2 during ripening and require slight oxygen for maintaining the growth of live cultures [107].
Self-cooling packaging technique is based on an endothermic chemical reaction involving the dissolution of ammonium chloride or ammonium nitrate in water and heat pump technology using water as the heat transmission medium. Such type of packaging systems may remunerate the cold chain conditions, especially where supply channel is inefficient [3]. Initially, thermal sensitive cheese varieties may be shipped using secondary or tertiary thermal management system. Greenbox Thermal Management Systems™ utilizes organic phase change nanomaterial labeled as PureTemp®, to provide specifically designed distribution carriage systems with an ability to maintain temperature precisely for longer durations of supply [108]. It consists of a reusable, recyclable and completely biodegradable boxes in box arrangement with exterior layer of corrugated plastic. Such type of self-cooling containers may be really helpful for exporting cheeses over longer distances without any thermal abuse and quality deterioration.
Emmental and Gouda cheese possess typical and desired regular round holes (eyes) owing to the production of large amount of carbon dioxide during lactate metabolism [109]. Dye based CO2 indicators based on color intensity that is correlated with amount of CO2 released could be used to monitor advances in ripening and signpost the accomplishment of optimal ripening. Recently, a novel consumable adhesive CO2 indicator strip consisting of phenol red dye and tetrabutylammonium hydroxide coated onto silica nanoparticles was developed by Wang, Yusufu, & Mills, (2019) [110]. The color response was dependent on temperature and thickness of polymer barrier films. Such type of indicators could be explored for the development of CO2 indicator or freshness indicator for modified atmosphere packaged cheese and cheese-based products.
Temperature sensitive networks based on chitosan-poly-(N-isopropylacrylamide) for controlled release were developed by Alvarez-Lorenzo et al. (2005) [111], which can be used in active cheese packaging materials for precise emission of any active component. Films changing their gas permeability in response to degree of temperature and exposure duration may be frequently used during storage and distribution of respiring cheeses like Camembert and Gouda. BreatheWay® membrane technology (Apio Inc., California), based on side chain crystallizable (SCC) polymers provides the solution for gas permeability control according to change in temperature. The change in polymer properties like chain length and side chains can be used for attaining required oxygen and carbon dioxide permeabilities in cheese packages [3].
With the focal point being shifted to consumer convenience, quality and safety, active and intelligent packaging tools may help customers with informed choice. As the world is witnessing increased consumption of cheese, these packaging tools have potential market growth. The expansion of smart packaging technologies in cheese industry remains at a nascent stage. Recent research publications on smart packaging of meat, fish, fruits and vegetables suggest innovative ideas which could be conceptualized for cheese in near future. Smart packaging tools need to be of low cost and multiple benefits. The partnership of active and intelligent packaging can be used to complement each other’s actions. Existing challenges could be overcome by multidisciplinary approaches for the development of smaller, more powerful and cost-effective smart packaging systems. Biotechnology, nanotechnology, food science, sensor technology and information technology could be combined for overcoming the shortcomings. Biosensor and hybrid devices for cheese packaging remains untouched in terms of its development and commercialization. It could be expected that with the continuous advances in intelligent packaging and growing modified atmosphere packaged dairy products market, the demand for such type of intelligent packaging systems is expected to rise.
We are highly thankful to Director, ICAR-National Dairy Research Institute, Karnal for providing the required facilities to carry out the present work.
The authors declare no conflict of interest that might be perceived as affecting the neutrality of the article.
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Almost all the parts of this plant, that are, fruit, leaves, flower bud, trunk, and pseudo-stem, can be utilized. This chapter deals with the fiber extracted from the pseudo-stem of the banana plant. It discusses the production of banana pseudo-stem fiber, which includes plantation and harvesting; extraction of banana pseudo-stem fiber; retting; and degumming of the fiber. It also deals with the characteristics of the banana pseudo-stem fiber, such as morphological, physical and mechanical, durability, degradability, thermal, chemical, and antibacterial properties. 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Community- and research-based conservation mechanisms could be an appropriate approach for mitigating the problems pertinent to the loss of medicinal plants and their habitats and for documenting medicinal plants. Chromatography; electrophoretic, macroscopic, and microscopic techniques; and pharmaceutical practice are mainly used for quality control of herbal medicines.",book:{id:"8502",slug:"plant-science-structure-anatomy-and-physiology-in-plants-cultured-in-vivo-and-in-vitro",title:"Plant Science",fullTitle:"Plant Science - Structure, Anatomy and Physiology in Plants Cultured in Vivo and in Vitro"},signatures:"Admasu Moges and Yohannes Moges",authors:[{id:"249746",title:"Ph.D.",name:"Admasu",middleName:null,surname:"Moges",slug:"admasu-moges",fullName:"Admasu Moges"},{id:"297761",title:"MSc.",name:"Yohannes",middleName:null,surname:"Moges",slug:"yohannes-moges",fullName:"Yohannes Moges"}]},{id:"29764",title:"Underlying Causes of Paresthesia",slug:"underlying-causes-of-paresthesia",totalDownloads:193348,totalCrossrefCites:3,totalDimensionsCites:7,abstract:null,book:{id:"1069",slug:"paresthesia",title:"Paresthesia",fullTitle:"Paresthesia"},signatures:"Mahdi Sharif-Alhoseini, Vafa Rahimi-Movaghar and Alexander R. 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The enzymes of the glycolytic pathway presenting the greatest multiplicity were phosphofructokinase, fructose 1,6-bisphosphate aldolase, glyceraldehyde-3-phosphate dehydrogenase, and pyruvate kinase. The genes that encode citrate synthase and subunits of the succinate dehydrogenase complex are the ones that show the greatest multiplicity, while in the phosphoenolpyruvate-pyruvate-oxaloacetate node, only malic enzymes and pyruvate phosphate dikinase present two copies in some Streptomyces. The extra DNA from these multiple gene copies can be more than 50 kb, and the question arises whether all of these genes are transcribed and translated. As far as we know, there is few information about the transcription of these genes in any of this Streptomyces, nor if any of the activities that are encoded by a single gene could be limiting both for growth and for the formation of precursors of the antibiotics produced by these microorganisms. Therefore, it is important to study the transcription and translation of genes involved in carbon metabolism in antibiotic-producing Streptomyces growing on various sugars.",book:{id:"10893",title:"Actinobacteria",coverURL:"https://cdn.intechopen.com/books/images_new/10893.jpg"},signatures:"Toshiko Takahashi, Jonathan Alanís, Polonia Hernández and María Elena Flores"},{id:"82757",title:"Seed Dormancy: Induction, Maintenance and Seed Technology Approaches to Break Dormancy",slug:"seed-dormancy-induction-maintenance-and-seed-technology-approaches-to-break-dormancy",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.106153",abstract:"Dormancy is the major cause of erratic germination, patchy emergence and uneven seedling establishment in the field. These traits are exceedingly undesirable in crop production as future phases of growth and development are strongly linked to uniform seedling development at early growth phases. Variations in maturation time, and difficulty in managing abiotic and biotic stresses during pre- and postharvest are common consequences of uneven germination and seedling emergence. Minimizing this negative impact of dormancy in a seed lot is the major concern of all seed production companies. Generally, mature seeds show some considerable dormancy during which embryo growth is halted momentarily because one or more internal and external stimuli for growth resumption is/are absent. If the inhibition of seed germination is solely due to insufficient or complete absence of external signals, then the seed is in a state of quiescence. Otherwise, if linked to internal factors, then the seed is in a state of dormancy. Induction, maintenance, and release of dormancy are therefore related to Seed-dependent factors such as morphology, hormones, state of embryo maturity at seed dispersal and chemical inhibitors. This chapter focuses on species-dependent methods currently used to break dormancy, reduce germination time and improve emergence and seedling establishment.",book:{id:"11322",title:"Seed Biology Updates",coverURL:"https://cdn.intechopen.com/books/images_new/11322.jpg"},signatures:"Tabi Kingsley Mbi, Ntsomboh Godswill Ntsefong and Tatah Eugene Lenzemo"},{id:"79168",title:"Pulses: A Potential Source of Valuable Protein for Human Diet",slug:"pulses-a-potential-source-of-valuable-protein-for-human-diet",totalDownloads:2,totalDimensionsCites:0,doi:"10.5772/intechopen.99980",abstract:"Nutritional profile of pulses has significant importance in human diet with respect to protein and mineral quality and bioavailability. Protein energy malnutrition is widespread throughout the world especially among the developing countries. Pulses being rich in macronutrients such as protein from 20 to 26% and low in calories are most suitable for product development for target-oriented population. 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Additionally, this overview can give insight into the development of new product with balanced nutritional quality and high protein contents as a potential protein supply for malnourished population.",book:{id:"12236",title:"Legumes Research- Volume 2",coverURL:"https://cdn.intechopen.com/books/images_new/12236.jpg"},signatures:"Saima Parveen, Amina Jamil, Imran Pasha and Farah Ahmad"},{id:"83043",title:"Applications of CRISPR/Cas9 for Selective Sequencing and Clinical Diagnostics",slug:"applications-of-crispr-cas9-for-selective-sequencing-and-clinical-diagnostics",totalDownloads:3,totalDimensionsCites:0,doi:"10.5772/intechopen.106548",abstract:"In this chapter, we will discuss the applications of CRISPR/Cas9 in the context of clinical diagnostics. We will provide an overview of existing methods and their use cases in the diagnostic field. Special attention will be given to selective sequencing approaches using third-generation sequencing and PAM-site requirements. As target sequences in an AT-rich environment cannot easily be accessed by the commercially available SpCas9 due to rarity of NGG PAM-sites, new enzymes such as ScCas9 with PAM-site requirements of NNG will be highlighted. Original research on CRISPR/Cas9 systems to determine molecular glioma markers by enriching regions of interest will be discussed in the context of potential future applications in clinical diagnostics.",book:{id:"11804",title:"CRISPR Technology",coverURL:"https://cdn.intechopen.com/books/images_new/11804.jpg"},signatures:"Maximilian Evers, Björn Brändl, Franz-Josef Müller, Sönke Friedrichsen and Stephan Kolkenbrock"},{id:"83012",title:"Cotton Based Cellulose Nanocomposites: Synthesis and Application",slug:"cotton-based-cellulose-nanocomposites-synthesis-and-application",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106473",abstract:"Nanocellulose is a renewable natural biomaterial which has risen to prominence due to its biodegradability and physiochemical properties making it a promising candidate to replace non-biodegradable synthetic fibers. Due to its profound qualities, nanocellulose extracted from cotton fibers have tremendous application potential and have been intensively studied particularly in the generation of nanofillers and as reinforcement components in polymer matrixes. Deposition of inorganic nanoparticles on cotton fabric result in antimicrobial textiles with multifunctional use particularly in manufacture of PPE and as filtration devices against environmental pollutants and pathogens. This chapter compiles three main sections. The first section gives an overview of the extent of work done in the creation and application potential of cotton-based nanocomposites. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. 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He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}}]}},subseries:{item:{id:"4",type:"subseries",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11400,editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",slug:"yuping-ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",biography:"Dr. Yuping Ran, Professor, Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China. Completed the Course Medical Mycology, the Centraalbureau voor Schimmelcultures (CBS), Fungal Biodiversity Centre, Netherlands (2006). International Union of Microbiological Societies (IUMS) Fellow, and International Emerging Infectious Diseases (IEID) Fellow, Centers for Diseases Control and Prevention (CDC), Atlanta, USA. Diploma of Dermatological Scientist, Japanese Society for Investigative Dermatology. Ph.D. of Juntendo University, Japan. Bachelor’s and Master’s degree, Medicine, West China University of Medical Sciences. Chair of Sichuan Medical Association Dermatology Committee. General Secretary of The 19th Annual Meeting of Chinese Society of Dermatology and the Asia Pacific Society for Medical Mycology (2013). In charge of the Annual Medical Mycology Course over 20-years authorized by National Continue Medical Education Committee of China. Member of the board of directors of the Asia-Pacific Society for Medical Mycology (APSMM). Associate editor of Mycopathologia. Vice-chief of the editorial board of Chinses Journal of Mycology, China. 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