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Molds do not appear only in the form of a particular phylogenetic or taxonomic grouping but also can be found in the form of Ascomycota, Zygomycota and Deuteromycota. The growth of the mold can be important in biodegradation and the production of numerous antibiotics, foods, enzymes and beverages. However, they can also be harmful to some other eatables foods, which cause diseases or food spoilage .
the organic matter on which they live and not through photosynthesis or self producing food. Molds produce hydrolytic enzymes from the dominant hyphal tips.
These enzymes breakdown compound biopolymers into simple like cellulose and starch into glucose, which can enter the hyphae. Mold in this way causes decomposition of organic matter and makes reprocessing of nutrients present in the ecosystem possible, enabling the recycling of nutrients throughout ecosystems. The development of microorganisms is restricted by hydrolytic enzymes and mycotoxins which are produced by molds.
Molds reproduce through tiny spores, which may be sexual or asexual; there are some that produce both kinds. They may consist of many or single nucleus. Molds breed on a dead organic substance; however, their presence is only evident to the unaided eye when mold colonies develop. Different types of molds will grow in different condition like temperature, humidity etc. Every mold has own growth temperature preference, for example some mold can grow at the temperature as low as 20°C,but some conditions do not encourage growth of molds, but can survive in a dormant state .
Figure 1.1: Growth Temperature Preferences of Moulds
All moulds have a preferred range of temperatures for growth. Figure 1.1 shows the moulds can be classified into 5 classes according to their growth temperature preferences, which are cold loving, cold tolerant, ambient loving, heat loving and high heat loving.
Common Types of Molds
Black Bread Mold
Black bread mold, scientific name is Rhizopus stolonifer, is a commonly circulated Mucoralean mold. The best temperature for black bread mold to grow quickly is between 15 and 30 degree Celsius. This is an asexual mode spore that is produced within sporangia, which break the spores when they grow up. Rhizopus stolonifer is a heterothallic species where sexual production occurs only when opposite mating kinds approaching to contact with it.
Black bread mold has an epidemic distribution. Normally they breed on soft fruits, such as peaches and strawberries and bread. A moist bread piece kept in a humid and enclosed container gathers bread mold for a couple of days. The mold breeds on bread and grow from spores, which float in the air. The mold spore grows by distributing branching threads after it drops onto the moist bread. Cell wall and cell membrane consists of many nuclei and cytoplasm that enclose the threads. The threads develop down into the bread and produce digestive enzymes that will change the bread into a liquid type. Growing bread mold soaks up the liquid. Finally, a new branching thread goes down into the bread and spreads the bread mold .
Figure 1.2: Black Bread Mold
Phytophthora Infestans is a kind of mold that will cause damage to tomatoes and potatoes through leaf. A new hypha breeds out of it and penetrates the leaf through a stoma after a mold spore drops on a leaf of a healthy potato plant in moist and warm conditions. Then small branches will breed out of the hypha and penetrate the walls of the leaf cells with the aids of enzymes. The hypha steals the nutrients from the cell filling and develops quickly, disperses throughout the tissues of the plant. This kind of mold can destroy and kill the entire potato plant. To prevent the growth of mold, prevent water clogging and keep the place dust free .
Figure 1.3: Phytophthora Infestans
Production of Volatile/ Odours
Microorganisms can produce a wide range of alcohols, ketones, aldehydes, esters, carboxylic acids, lactones, terpenes, sulphur and nitrogen compounds from breakdown of polymer compound. Among the substances produced are aliphatic alcohols, carbonyls, esters, lactones, aromatics and terpenoids. These compounds represent both primary and secondary metabolites, which microorganisms break the primary into secondary metabolites while retrieve energy for growing. The main metabolic pathways for secondary metabolite production are presented in Figure 1.4.
Figure 1.4: Pathways involved in the production of different secondary metabolites .
The volatiles which produced by the bacteria is from the breakdown of compound biopolymer, for example, carbohydrate and protein. The products from the breakdown of biopolymer basically are decarboxylation and deamination of amino acids. The vapours are basically methylamine, dimethylamine, trimethylamine, ammonia based and can also be sulphur based. The examples for the sulphur based are hydrogen sulphide, methyl mercaptan, dimethyl disulphide, derived from sulphur containing amino acids such as cysteine and methionine .
The bacterial volatiles or can be called off-odours can be used to indicate the degree of spoilage for foods. The index of freshness can use primary aliphatic alcohols to indicate  .
Common fungal, moulds are able to produce volatiles which can change the quality of foods and beverages, although it is in a very small amount, for example dimethyldisulphide, geosmin and 2-methylisoborneol. These compounds are produced in large quantities in species specific combinations of different genera such as Penicillium, Aspergillus and Fusarium .
The fungi have a tendency to attack foods which contained high carbohydrate compound. The fungi break the carbohydrate compound into smaller part, which is glucose. Fungi continue to split the glucose by producing alcohols and esters, such as ethanol and ethyl acetate, which can be smelled by human. Some secondary metabolites which produced by the fungi are responsible for the decomposed smell .
The different stages and duration of the fungal growth can affect the production of volatile. As a result, fungal volatile can be used to show the growth of moulds on the foods and also the spoilage of the foods .
An electronic nose is a device that detects the specific components of an odour or flavour and then analyses its chemical composition to recognize it. The expression “electronic sensing” refers to the capability of reproducing human senses using sensor arrays and pattern recognition systems .
Electronic Nose, this term is first published in the literature by Julian Gardner from Warwick University in 1988. The term is used for a device made up of sensors combined with pattern recognition system which is able to perform recognition of simple or complex odours. Krishna Persaud and George Dodd were the first to reveal sensor array for discrimination between odours. Electronic noses have been in the market since 1990s but have typically been large in size and expensive. Making the devices smaller, less expensive, and more sensitive is the aim for the current undergoing research on the electronic noses .
Electronic noses were initially used for quality control applications in the food, beverage and cosmetics industries. The applications for electronic noses has been widen currently, which include detection of odours specific to diseases for medical diagnosis, detection of pollutants for environmental protection, detection of gas leaks for the safety of the employees .
Working Principle of Electronic Nose
Electronic nose was developed in order to mimic human olfaction, such as ordour or flavor. Electronic nose consists of a mechanism for chemical detection, such as an array of electronic sensors, and a mechanism for pattern recognition, such as a neural network, in order to generate signal pattern that are used for characterizing odours.
An odour is composed of molecules. Different molecules from different types of ordour have a specific size and shape. Each of these molecules has a correspondingly sized and shaped receptor in the human nose. When a specific receptor receives a molecule, receptor sends a signal to the brain to process. Then, the brain identifies the smell linked to the particular molecule. The development of the electronic noses is based on the biological model as to work in similar manner, but for electronic nose, sensors is used to perform the role of human receptors, and transmitting the signal to a program for processing, instead to the brain.
In general, electronic nose can be divided into three major parts, which are sample delivery system (neural system), detection system (sensory system) and computing system (electronic system) .
Figure 1.5: Electronic Nose Concept.
Application of Electronic Noses
Electronic noses have been used in various applications for wide range of areas. As electronic noses are developed to detect gases around the environment, it can be used in environmental application. By the nature of their trainability to a broad range of compounds, electronic noses are a good choice for air quality monitoring in an environment where the possible contaminants are known. For example, AromaScan A32S e-nose was employed to classify the source of odour emission lagoon, ambient air, confinement building exhaust fan or downwind ambient air. It also been used for differentiate different types of fungi that commonly lower indoor air quality in office buildings and industrial plants. Detection of hazardous contamination in the industrial plant can be implemented by electronic nose. Toxic gases such as insecticides, acetic acid, volatile organic compound (VOC), hydrogen sulphide, carbon monoxide, ethylene oxide, sulphur dioxide, ammonia etc. can be detected by electronic nose to avoid accident .
Second application of the electronic noses is applied in medical diagnostic and health monitoring applications. Many diseases and intoxications are accompanied by characteristic odours, and their detection can provide diagnostic clues, lead the laboratory evaluation, and involve the choice of immediate therapy. Estimating the time of death of corpses can also be applied with electronic nose. Their applications in medicine not only produce a more rapid treatment towards the infection but also reduce the misuse of antibiotics and mishandling of hazardous medicine .
The third application is entitled recognition of natural product. Electronic nose is used as an analytical tool to detect solvent, and the discrimination of spirits, to beverage and grain quality. For example, Cyranose 320 is employed to identify the different species of trees for the pulp and paper industries. Moreover, it is used to differential essential oil bearing plants. Wood chip sorting is also a field which has been applied with electronic nose. Review of recent literature on electronic-nose applications in natural products is shown in Table 1.1.
Table 1.1: Examples of applications of electronic noses to foodstuffs and beverages .
Toasting level of oak wood barrels
Headspace sample taken from above hot barrel immediately after toasting.
Wheat samples were made artificially moldy in the laboratory.
Freshness of soybean curd
10 s baseline, 50 s sample, 40 8C s ample extraction.
Barley grain quality
10 MOSFET, six MOS, one CO2 monitor
10 samples with normal odor and 30 with off odor. 3.33 g samples of each class were heated to 50.8C. Baseline and purge with zero air.
Samples allowed equilibrating for 30 min. A charcoal filter was used and the samples were’bubbled’.
Static headspace sampling of roughly 30 samples of three roasted coffees.
Fruit ripeness monitoring
Peaches, pears and apples placed into a plastic box. 150 mL headspace was pulled out with a gas tight syringe after 1 hr equilibrating. Sensors were allowed to stabilize for 10 min. They were purged with synthetic dry air.
Thickness shear mode quartz resonators coated with pyrrolic macrocycle
Slices of peaches and nectarines in sealed glass bottles and allowed to equilibrate for 10 min at 30.8C.
Process Monitoring is the fourth application can be found for electronic noses. The sensor of Taguchi (TGS) or FIS type which is commercially available has been used for process monitoring application. The electronic nose was used to observe the aroma of cell cultures to gain insight into cell and process state changes as well as to identify process faults. Besides that, it is used to check the composition of the bioreactor headspace gas, at the same time to track physiological state changes. Listing of process monitoring applications presented in the literature is shown in Table 1.2 .
Figure 1.6: Schematics on the integration of an electronic nose into a biological process .
Schematic for the integration of electronic nose is portrayed in Figure 1.6 and it shows the process of monitoring and detecting the gas. Before reaching the gas sensors, the reference gas, which can be the same as the process gas, is humidified. The sampling interface protects for liquid way in and compensates for flow variations.
Table 1.2: Example of process monitoring applications for BM, bioprocess monitoring and FM, food process monitoring .
BM – estimation of preculture quality
MOSFET, MOS, IR,CP
Preculture quality and state estimation for a rec. E. coli strain.
BM – estimation of cell growth
MOSFET, MOS, IR
ANN models established in E. coli batch; CHO perfusion; S. cerevisiae batch processes.
BM – detection of infection
MOSFET, MOS, IR, CP
Identification of Micrococcus sp. Infection in 500 L CHO process. Identification of B. cereus, P. aeruginosa in 2 L CHO process. Shake flask tests with E. coli.
BM – observation of metabolic burden
MOSFET, MOS, IR
Visualization of cell stress caused by strong over expression of rec. protein in E. coli.
BM – estimation of product concentration
MOSFET, MOS, IR
ANN model for rFVIII estimation in long-term perfusion CHO process.
FM – aroma quality of cured ham
Identification of off-flavor in Serrano type dry cured hams.
FM – quality control of drying process in ham production
Control of drying process of Iberian hams in chambers.
FM – quality control of sugar beet
Ion mobility spectrometry, MOS
Identification of spoiled sugar beet.
FM – sorting of fresh fruit juices
Identification of grape juices with off-flavor.
FM – off-flavors in cow’s milk
MOSFET, MOS, IR
Identification of feed off-flavor in cow’s milk.
The fifth application is the most promising and the most traveled road towards industrial application to electronic nose, which is food and beverage quality assurance. The development of artificial olfaction machines that are easy to use, portable, and provide a simplified sampling method, appears growing tremendously. It could be achievable for the practical utilization of a primary source of information to determine food and beverage quality. For example, LibraNose is used to detect the spoilage of the fish though the measure of the amount of amine, such as trimethylamine.
The electronic noses have been developed for classification of variety of foods and beverages, such as coffee, fishes, cheese, wines and peppers. Checking quality of raw meat by detecting the meat taint and off-flavours has been developed, such as using boar taint to determine the quality of raw boar meat. Electronic noses have been applied in dairy products, olive oil industry, fruits and vegetables industry plus farm. It has been used to measure the ripeness of the fruits, grain quality and mite infestation of wheat. However few studies have examined discrimination between spoilage bacteria, yeasts and fungi growing on foodstuffs. List of some applications of electronic noses and electronic tongue applications to food and beverage quality are listed in Table 1.3 .
Table 1.3: Example of applications of electronic noses to food and beverage quality .
Areas of application
Fermentation of sausages Processed chicken meat Packaged beef meat Ground meat Boar taint Alpaca and llama meat quality
Aroma detection in brewery Flavor detection
Trout freshness Freshness of cod Cod-fillet storage time Freshness of capelin
Fruit and vegetables
Aroma of pears Quality of tomatoes Maul Bacterial infection in potatoes Quality of strawberries Ripeness detection Apple ripeness Apple picking time Quality of apples and citruses Banana ripeness
Defects and rancidity of olive oil Classification of vegetable oils Classification of olive oil
Mite infestation Microbial quality Odor classification
Toasting of barrels Vintage years Vineyards of production Vinegar
Cheese ripening Off flavors in milk Cheddar cheese aroma Aroma of UHT milk Milk freshness
Electronic nose is also very important in the application of automotive and aerospace. Utilization of electronic nose in the automotive industry is primarily theoretical today, but such device still can be applied in several areas. These comprise of monitoring the exhaust for combustion efficiency, monitoring the cabin air for passenger safety, and monitoring the engine compartment for safety purposes such as leaking oil or other fluids. Automobile manufacturers have started to discuss the possibility of using an electronic nose to monitor the gas from exhaust for the presence of compounds which indicate the sign of unfinished combustion and send feedback to the engine to adjust the engine settings to improve combustion efficiency.
Besides automobile industry, electronic nose has been proposed for many applications in aerospace, some of the applications can be practical within the today’s technology but many of them still require more development to be succeeded. In the area of space exploration, electronic nose has been proposed for planetary atmospheric studies. This application modified base on the addition of an electronic nose to a rover to implement research on the atmosphere as the rover is moving and to study the changes in atmosphere over days, months or seasons when the rover is stationary. Perhaps the most important of using electronic nose in aerospace field is monitoring air quality in human habitats. The ability to observe the recycled breathing air in a closed chamber is important to NASA as it is needed to ensure clean air for the crew to survive in an enclosed environment such as the Space Shuttle and the International Space Station (ISS) .
Figure 1.7: The JPL electronic nose used in the flight experiment on STS-95 .
For the sixth application, electronic nose is investigated to detect explosive material, which is useful for detection of explosives field. Currently land mine is detected by dogs and it would take thousands of years to clear all the mass created during the war. With the development of electronic nose, it would save lot more human lives in shorter time. The Defense Advanced Research Projects Agency (DARPA) program currently is developing electronic nose to detect explosive mines by their chemical signatures. The Nomadics’ Fido (Fluorescence Impersonating Dog Olfaction) device is the current on progress project to assist human to clear the land mine. The device uses fluorescent polymer beads from MIT to detect trace amounts of TNT emanating from landmines and this device shows great promise for future deployment in demining applications which can save a lot of lives. The fluorescent quenching mechanism is show in Figure 1.8 .
Figure 1.8: Fluorescence quenching mechanism in polymer chemosensor films .
Final application can be applied by electronic nose is cosmetic and fragrances. Although the use of electronic nose in this field is more limited than any other field, but with using this technology, optimization and analytical tasks can be solved. HP 4440 Chemical Sensor and capillary GC/FID are reported successfully in classifying and differentiating odours. Alpha MOS Fox4000 electronic nose is used to demonstrate the ability of carrying out sensory analyses by accurately classifying “good” and “bad” batches of samples .
Figure 1.9: Alpha MOS Fox4000 electronic nose.
Gases are the key aspect in many industrial or domestic activities nowadays. In the last decade, gas sensors can be found in numerous fields for specific applications since demand for gas detection and monitoring has emerged particularly as the awareness of the need to protect the environment has grown. There are two generally important groups can be found in gas sensors industry, which are the detection of single gases (as NOx, NH3, O3, CO, CH4,H2, SO2, etc.) and the discrimination of odours or generally the monitoring of changes in the ambient.
Single gas sensors can be applied for fire detectors, leakage detectors, controllers of ventilation in cars and planes, alarm devices warning the overcoming of threshold concentration values of hazardous gases in the work places. The detection of volatile organic compounds (VOCs) or smells generated from food or household products has also become increasingly important and vital in food industry and enclosed place air quality. Besides that, electronic noses are designed to analyse such complex environmental mixtures and recent years are developed tremendously to cater the industry needs. Examples of application for gas sensors are shown in Table 1.4 .
Table 1.4: Example of applications for gas sensors .
Car ventilation control
Gasoline Vapour Detection
Toxic/flammable/explosive gas detectors
Food quality control
Packaging quality control (off-odours)
Indoor air quality
Solid State Gas Sensor
Solid state gas sensors, based on a range of principles and materials, are the best candidates to be developed as the commercial gas sensors for a wide range of applications in different industries. The great interest of industrial and scientific world on solid state gas sensors comes from their plentiful of advantages, for example, tiny sizes, high sensitivities in detecting very low concentrations (at level of ppm or even ppb), able to detect wide range of gaseous chemical compounds such as VOC, possibility of on-line operation and, due to possible bench production, low cost. On the other hand, the traditional analytical instruments such as mass spectrometer, NMR, and chromatography are costly, complex, and large in size. Moreover, most analysis requires sample preparation, so that on-line, real-time analysis is difficult to be implemented.
Solid-state chemical sensors although have been widely used, but they also suffer from limited measurement accuracy and problems of long-time stability. However, recent advances in nanotechnology will improve gas sensing in which will dramatically increase the performances of solid state gas sensors.
For optical processes which employ infra-red absorption of gases, chemical processes, which detect the gas by means of a selective chemical reaction with a reagent, mainly utilize solid-state chemical detection principles. On the contrary, solid state gas sensors use numerous of physical effects to realize the detection of gases. A characteristic of solid state gas sensors is the reversible interaction of the gas with the surface of a solid-state material. Besides that, based on the conductivity change of gas-sensing material, the detection of the reaction between gas and material can be performed by measuring the change of capacitance, work function, mass, optical characteristics or reaction energy released by the gas interaction.
Organic or inorganic materials are deposited in the form of thick or thin films and used as active layers in gas sensors. The measured reading is performed via electrodes, diode arrangements, transistors, surface wave components, thickness-mode transducers or optical arrangements. Although the basic principles behind solid state gas sensors are alike for all the devices in the market, a multitude of different technologies have been developed. Due to the wide range of sensors, a rich fabric of interdisciplinary science ranging from solid state physics, chemistry, electronics and biology leads the development modern gas-sensing devices. The improvement of solid state sensors is strongly depending on the development of technologies which mainly driven by other than sensor applications. A list of example of solid state gas sensors is reported in Table 1.5 .
Table 1.5: Types of solid state gas sensors with the corresponding physical change .
Types of devices
Semiconductor gas sensors
Field effect gas sensors:
diodes, transistors, capacitors
Work function electrical polarization)
Piezoelectric sensors :
Quartz crystal microbalances (QMB), surface acoustic wave (SAW), microcantilevers
(fiber optic or thin film)
SPR, reflection, interferometer, absorption, fluorescence, refractive index or optical path length
Catalytic gas sensors:
Seebeck effect, pellistors, semistors
Heat or temperature
Electrochemical gas sensors (potentiometric or amperometric)
Electromotive force or electrical current in a solid state electrochemical cell
A neural network is a parallel system capable of resolving paradigms that linear computing cannot. The term, neural network, has two distinct meanings. One is traditionally used to refer to biological neural networks and the other in modern usage refers to artificial neural networks.
An Artificial Neural Network is an information processing paradigm that is adopting the way of biological nervous systems to process information. The key element of this paradigm is the new structure of the information processing system, which is composed of a large number of highly interconnected processing elements, also called as neurons, working together to solve specific problems. In most cases an artificial neural network is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase .
Figure 1.10: Artificial neural network.
Architecture of Neural Networks
The most influential work on neural nets in the 60’s went under the heading of ‘perceptrons’ a term coined by Frank Rosenblatt. The network adapts as follows, change the weight by an amount proportional to the difference between the desired output and the actual output.
As an equation:
Î” Wi = Î· * (D-Y).Ii
where Î· is the learning rate, D is the desired output, and Y is the actual output .
Back-Propagated Delta Rule Networks (BP)
Back-Propagated Delta Rule Networks is a development from the simple Delta rule in which extra hidden layers (layers additional to the input and output layers, not connected externally) are added. The network topology is constrained to befeedforward, for example, loop-free – generally connections are allowed from the input layer to the first (and possibly only) hidden layer; from the first hidden layer to the second and so on; and from the last hidden layer to the output layer .
The hidden layer learns to recode or to provide a representation for the inputs. More than one hidden layer can be used. The architecture is more powerful than single-layer networks: it can be shown that any mapping can be learned, given two hidden layers (of units). The units are a little more complex than those in the original perceptron, as the input and output of the graph is considered as a function .
Figure 1.11: Hidden Layer of BP network .
The weight change rule is a development of the perceptron learning rule. Weights are changed by an amount proportional to the error at that unit times the output of the unit feeding into the weight [
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