Variable information.
\r\n\tThe book will aim to cover also the synthesis and optical properties of noble metal nanostructures, patterned surfaces, continuous or grated surfaces, and devices. This book intends to provide the reader with a comprehensive overview of the current state-of-the-art in plasmonic microscopy, surface-enhanced spectroscopic properties, such as Raman scattering or fluorescence, as well developments in techniques such as surface plasmon resonance and near-field scanning optical microscopy but also data transmission, plasmonic light modulators, and optoplasmonic networks.
",isbn:"978-1-80356-003-8",printIsbn:"978-1-80356-002-1",pdfIsbn:"978-1-80356-004-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,hash:"15d44e3a7898842276a9a9da9863a59d",bookSignature:"Dr. Patrick Steglich",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11147.jpg",keywords:"Biosensors, Surface Plasmon Resonance, Optoplasmonic Networks, Plasmonic Communication, Fabrication Methods, Device Simulation, Device Optimization, Surface Plasmon Resonance, Plasmonic Microscopy, Phonon-Plasmon Interaction, Physical Background, Mathematical Background",numberOfDownloads:14,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 19th 2021",dateEndSecondStepPublish:"February 25th 2022",dateEndThirdStepPublish:"April 26th 2022",dateEndFourthStepPublish:"July 15th 2022",dateEndFifthStepPublish:"September 13th 2022",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"A senior researcher in photonics at IHP - Leibniz Institute for Innovations in Microelectronics, book author, lecturer at Technical Unversity of Applied Sciences Wildau, and holder of three registered patents.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"223128",title:"Dr.",name:"Patrick",middleName:null,surname:"Steglich",slug:"patrick-steglich",fullName:"Patrick Steglich",profilePictureURL:"https://mts.intechopen.com/storage/users/223128/images/system/223128.jpeg",biography:"Patrick Steglich is a research associate at the IHP - Leibniz-Institut für innovative Mikroelektronik, Germany, and lecturer for photonics and optical technologies at the Technical University of Applied Sciences Wildau, Germany. He obtained a master's degree in Photonics from the Technical University of Applied Sciences Wildau in 2013. In 2017, he received his PhD in Industrial Engineering from the Università degli Studi di Roma 'Tor Vergata” for his work in the field of integrated photonics for communication and sensing. 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The achievement of the “Just-in-time”, JIT principle for all products delivered requires targeted managerial efforts for maintaining the continuity of the logistics processes [6, 7, 8, 9, 10], ensuring efficient human resource management [11, 12, 13], and optimal utilization of the warehousing potential [14, 15, 16, 17]. The identification, minimization, and elimination of deviations from set quality levels and the causes for failure of the system should be identified at the earliest possible stage in order to reduce the expenses for recovering the system to its normal operation. The level of quality has a positive impact on the implementation of the selected logistics strategy [18, 19, 20, 21], whereas the low level of quality is an indicator of the poor efficiency of the supply chain [22]. The main objective of the quality management processes is to ensure the effective performance of the logistics services. It has been concluded that when the quality management processes are operated as a system, they have a much more positive impact on the performance of the individual components of the system rather than the contrary. It has also been postulated that certain key areas of the logistics operations have a decisive impact on the efficiency of the logistics system, such as, for example, transportation and storage operations.
To analyze the costs for maintaining required quality levels, the components of those costs (Figure 1), need to be clarified:
Quality assurance-specific costs.
Improvement of the logistics system efficiency is a key factor for ensuring products that meet demand and the flawless management of the organization [23, 24, 25, 26, 27]. Logistics operators that organize the supply chain by setting targets and results based on a limited budget manage to achieve growth in their revenues and assets, and, at the same time, reduce their operational costs [28, 29]. Due to the constantly emerging risks in the operations in the real economy where the logistics operations take place, it is often necessary to respond to the specific situation for overcoming the bottlenecks without considering the strategic guidelines for business development [30]. This is why the systems that are very flexible and capable of changing together with the market and the changes in the external environment are the most rapidly developing ones. In essence, the purpose of logistics operations can be defined as the effective and timely movement of goods to the places where the customer needs them at a reasonable price [31]. However, there are often restrictive conditions for the fulfillment of those purposes, and the appropriate equipment for loading and moving the transport vehicles is not always available when they are needed. In addition, the capacity of each logistics warehouse is strictly confined and fixed. There is competition in the sector of logistics, too. Therefore, the business needs to focus on its main competence and outsource to external contractors those services, the operation of which causes unjustified losses of resources, in order to achieve effective management of the costs for quality improvement. Actually, the main purpose of cost optimization is to practically [32, 33] satisfy the customer’s requirements by reducing the time for making the delivery. The main impediment to achieving this purpose is caused by the limited possibility to transfer and receive information about the actual demand in real-time.
The main problem about minimizing the costs for achieving the logistics purposes is related to the understanding about the management of the system itself as one that distributes the cargo (“push”) and one that requires distribution of the cargo where necessary and based on a customer’s order (“pull”) [34]. The first type of system is more appropriate in the case where no exact information about the need of goods is available. However, in this case, if demand is significantly higher than supply, distribution of scarce goods and priority servicing of selected customers is needed. The use of mathematical methods for planning routes, occupation of the warehousing facilities, and temporary hiring of workers can help to reduce costs. When accounting for the total operational overheads, the expenses for handling, storage, and transportation of the goods should be accounted for based on the main cost items. This can be done by identifying all the resources (including human resources), the packaging and repackaging operations performed, the processes, and the methods used for evaluation and control in order to ensure the overall performance of the process. In other words, the total costs for logistics are the sum of all costs incurred for the management and implementation of all processes and operations related to the logistics operations. Generally, the total costs can be divided into the following three groups:
costs associated with the operations,
costs related to with the management of the logistics system and,
costs associated with the application of possible logistics risks.
There is an interesting approach in the control of quality management costs, which was developed by Taguchi [35]. This method focuses on the causes for deviations from the quality and on establishing clearer criteria for defining the critical boundary that distinguishes between conforming and nonconforming services [36]. Taguchi’s contribution to quality management is related to the following principle that any variations and deviations in the function of quality are the results of random and nonrandom factors and losses are observed when the variation results in conditions where the product or service is on the exact boundary of the target conformity value [37]. This is the quadratic loss function since it is assumed that when the product or service is at its target value, the loss will be zero. According to Diallo, Khan, and Vail, the relationship between quality improvement by decreasing the variations and the costs can be analyzed by using Taguchi’s function. Many researchers have also applied Taguchi’s method in the field of logistics services [38, 39, 40, 41].
The contribution to the reduction of the total operational costs for prevention of nonconforming logistics services as compared to the increase in the costs for their management and their relationship to the costs for monitoring and control in logistics services has not been studied. A number of logistics organizations have not focused on this analysis and, as a result, perform restructuring or investments which do not yield the expected positive outcome. It is the author’s view that logistics service providers should draw their attention to investment in quality management related to the prevention of nonconformities. At the same time, logistics service providers should exercise more effort on the potential opportunities for the development of the actual logistics services and the service processes. This study offers a practical solution for management and analysis for measuring these qualitative changes.
The objective of the study is to analyze the contribution to total costs of the expenses for prevention related to quality management in logistics by focusing on the need to undertake priority preventive actions to ensure the provision of logistics services that meet the customer’s quality requirements. By using the applied methods, this study analyses the contribution to quality improvement of the costs attributed to the prevention and avoidance of nonconforming quality, for quality evaluation and control, and for covering the expenditures for nonconforming quality of the logistics services. The relationship between these groups of costs in quality management has been identified by means of structural modeling, which helps to establish the contribution of the costs to the achievement of sustainable quality of the logistics services.
The primary method for data analysis that has been used is Taguchi’s method, which defines quality from the perspective of cost minimization and the subsequent loss to society. Based on his definition about quality management, continuous, consistent, and targeted actions are required to achieve minimum variability of the logistics services offered. According to Taguchi, the efforts should focus on the following two aspects: defining the combination of factors that have the lowest impact on any deviation from quality, and adjusting those factors that are the cause for the deviation from the set target of the logistics services. Based on the results obtained from Taguchi’s loss function, the contribution of the different factors that could have an effect on the deviation from the customer’s expectations for high-quality logistics services can be quantified. This can be used for initiating improvements that could have a positive impact in terms of satisfying those expectations.
Taguchi’s method was applied in two stages:
A model generation stage, which allows the selection of those controllable levels of the factors that have the greatest contribution to the achievement of the logistics services quality level expected by the customers (studied dependence) and the respective significance levels.
Performing the actual analysis (Taguchi’s design) to identify the parameters of the analyzed factors that minimize the variation in the deviations. The calculation of the tolerances that contribute to the reduction of deviations from the expected quality level of the logistics services is performed using the software Microsoft Excel XLSTAT 2021® [42].
The proposed data to be evaluated have been taken from the annual financial statements of an operating logistics company in the food sector and have been subsequently divided into three main groups: for prevention and avoidance of nonconforming quality; for quality evaluation and control; for covering the costs for nonconforming quality of the logistics services. The information collected about the last two-year period has been summarized in tables in order to visually illustrate the potential impact and the actual improvement of the economic result. After the final data from the studied two-year period were collected (before and after the introduction of the changes in the cost structure), those data were summarized and presented in Table 1.
Short name | Nbr. Of categories | Period of time before implementation of the changes in the cost structure | Period of time after implementation of the changes in the cost structure |
---|---|---|---|
Prevention costs | 2 | 450 (in thousand euro) (450 k€) | 500 (in thousand euro) |
Evaluation and control costs | 2 | 200 (in thousand euro) | 250 (in thousand euro) |
Cost of nonconformities | 2 | 100 (in thousand euro) | 50 (in thousand euro) |
Variable information.
By observing Table 1, it can be seen that the costs for improvements after the introduction of the changes are two times greater than the costs for prevention and control, whereas the costs for covering losses as a result of nonconforming logistics services have decreased by half as compared to the period before the implementation of the changes. The change in the cost structure based on the pre-defined three groups has allowed for the practical application of Taguchi’s principle that the nonconforming logistics service cannot be improved through the process of control or covering the losses from the nonconformity after the service has been provided. The application does not have the potential to create a conforming service, but just to identify the conforming and nonconforming services. Based on the data obtained, the experimental design was built and a questionnaire was generated.
The data collection for the study was performed via telephone and online meetings in focus groups by taking into account all the restrictions imposed in relation to the pandemic. All participants in the study are currently managers in organizations where the main scope of business is the provision of logistics services in the field of trade and delivery of food products to wholesalers.
The participants in the study were selected based on their management experience and, in particular, their experience in the field of logistics services quality management costs. The required criterion for participation was at least 10 years of experience. Initial informative telephone conversations about the study and its methods, including the observation of all requirements of the relevant legislation related to personal data protection, were performed with potential participants in the study. Only 5 out of a total number of 20 potential participants did not agree to participate. The participants who confirmed participation received a questionnaire. The main purpose of this questionnaire was to study the potential attitudes and evaluations of the participants regarding the need of change in the structure of quality management costs. The study was performed in two consecutive panels in online meetings with a discussion in focus groups held in-between. The evaluation of the participants’ opinion was performed based on a 100-point scale ranging from 1 to 100. The questionnaire of the study is presented in Table 2.
By using the 100-point scale (where 1 is the lowest value and 100 is the response with the highest value), please, evaluate which, in your opinion, would be the most suitable cost structure for logistics services quality management represented in 8 different categories. | |||||
---|---|---|---|---|---|
Observations | Prevention costs | Evaluation and control costs | Cost of nonconformities | Respondents’ answers in the two panels | |
Obs1 | 450 | 200 | 100 | ||
Obs2 | 450 | 200 | 50 | ||
Obs3 | 450 | 250 | 100 | ||
Obs4 | 450 | 250 | 50 | ||
Obs5 | 500 | 200 | 100 | ||
Obs6 | 500 | 200 | 50 | ||
Obs7 | 500 | 250 | 100 | ||
Obs8 | 500 | 250 | 50 |
Questionnaire of the study.
After the study, the participants’ responses were averaged and summarized for further analyses using Taguchi’s method.
The method used allows on one hand a comparison to be made, while on the other to quantify the difference between the target function (optimum ratio between the quality management costs) and its actual manifestation. The objective was to find a solution for minimizing deviations from the target function for logistics services in the food sector.
In the course of the study, Taguchi’s principles and methods for quality management were used to identify the optimum ratio between the quality management costs. The first principle that was applied is related to the statement that quality should be designed in the logistics service before offering that service on the market and, respectively, a strategy should be undertaken to increase the prevention costs (designing conforming quality) at the expense of the other costs.
Based on the experimental design, further calculations were made to find the contribution of the increased or decreased share of certain overheads to the achievement of a conforming service impacted to the lowest possible extent by the other factors. The data obtained from the two focus group sessions held were averaged and entered in Table 3.
Observations | |||||
---|---|---|---|---|---|
Obs1 | 450 | 200 | 100 | 75.000 | 76.000 |
Obs2 | 450 | 200 | 50 | 80.000 | 82.000 |
Obs3 | 450 | 250 | 100 | 78.000 | 80.000 |
Obs4 | 450 | 250 | 50 | 84.000 | 85.000 |
Obs5 | 500 | 200 | 100 | 85.000 | 84.000 |
Obs6 | 500 | 200 | 50 | 98.000 | 97.000 |
Obs7 | 500 | 250 | 100 | 88.000 | 96.000 |
Obs8 | 500 | 250 | 50 | 99.000 | 99.000 |
Experimental design (response 1 and 2).
Based on the results from Table 3, the experts have given a significantly lower number of points to the ratio of costs in the cases where there is an increase in the costs for operations associated with the rectification of problems, rather than preventive actions. It was concluded that this was the right approach; however, despite this, it is the author’s view that logistics organizations practically continue using their entire potential not for the development of the types of services offered on the market, but for the rectification of problems that have occurred in the course of providing those services. The reasons for that could be related to the fact that often when designing the actual services, the processes are dragged over time, which in turn, may lead to a delay. Therefore, this process often needs to be compensated by reducing the time limits under signed contracts and by adjusting all the details and parameters related to the negotiation of the logistics service. As a result, certain logistics operations are skipped, which are subsequently performed without actually specifying their parameters. This, on the other hand, creates more favorable conditions for customer claims and undertaking actions to increase the control in order to avoid such nonconformity in the future. The higher level of control leads to an increase in costs and does not guarantee that the services will be conforming if the conditions that lead to the presence of claims remain unchanged.
The analysis of controllable factors that create conditions for deviations in the logistics services has been studied with respect to the contribution of costs for the different operations to the total operational costs. These costs include both the costs for planning the logistics services and the costs related to the control of those services and compensations to customers related to claims and returns, replacement, or repeated implementation of the logistics operations. It is the author’s view that claims could be minimized by designing logistics services that are needed by the customer rather than services that the organization is capable to provide. A number of studies have come to the conclusion that the prevention of claims is more efficient than covering the costs once a claim has been filed and, respectively, could result in greater customer satisfaction [43, 44, 45, 46, 47].
Based on the data collected, Taguchi’s model has been created, where the ratio LS means (Signal-to-Noise ratios) has been calculated. It defines the ratio between the mean value of the share of each cost from the total costs and the standard deviation. The variability of the analyzed indicators considered significant by the experts for the provision of a conforming service, defined by their standard deviation from the average value, is presented in Figure 2.
Signal-to-noise ratios.
The results presented in Figure 2 show that prevention costs have been evaluated as the most significant factor with positive impact, followed by the positive impact of the costs for control. The influence of the increase in the costs for nonconforming logistics services has been assessed as negative. The multiple criteria used by the logistics operators for calculation of the services are related to the satisfaction with their expected quality and are hard to quantify. The studies performed so far show that investing in the design of services has a significantly more positive impact on the expected quality than investment in a higher level of control on the performance of those services (the prevention costs and the costs for control are equally increased by 50 units).
Taguchi’s approach thus requires seeking an appropriate solution for reducing the variations applied to the expected quality of the logistics operations and provides an opportunity to find results for lower deviation from the target function. The model these decisions can be based on, so that the variations in the logistics services are lower than expected, is presented in Table 4.
Source | ||||||
---|---|---|---|---|---|---|
Intercept | 39.184 | 0.136 | 287.649 | 38.805 | 39.562 | |
Prevention costs-450 | −1.317 | 0.136 | −9.666 | −1.695 | −0.939 | |
Prevention costs-500 | 0.000 | 0.000 | ||||
Evaluation and control costs-200 | −0.402 | 0.136 | −2.952 | −0.780 | −0.024 | |
Evaluation and control costs-250 | 0.000 | 0.000 | ||||
Cost of nonconformities-50 | 0.775 | 0.136 | 5.690 | 0.397 | 1.153 | |
Cost of nonconformities-100 | 0.000 | 0.000 |
Model parameters (standard deviations).
The studied factors are statistically significant (at 0.05), which allows an optimum ratio to be set between the studied costs so that the deviation from the target function is as low as possible. Table 4 equally shows the statistical significance of each type of costs and their contribution to the achievement of an optimum combination of those costs. According to the feedback provided by the questionnaires, the most important factor in quality management is cost prevention because the absolute value of this factor is the highest. It can be stated that the prevention costs and the costs for control on the processes in the specific case that was studied were increased by the same number of units; however, the prevention costs demonstrated a much higher effect on the target function.
These results are confirmed by the main effects graphs in Figure 3.
LS means (means prevention costs, control costs, cost of nonconformities).
Logistics organizations should invest in operations for the prevention of nonconformities in order to decrease the variability in the target function, even if the causes of the variations are not eliminated.
It has been practically demonstrated that the costs for eliminating the variation in the target function are very high. A more feasible and practical solution is to just change the structure of the costs or to control the factors that are more significant and have a greater impact on the target function. This can be achieved without increasing the total expenses or with a minimum increase resulting just from the redistribution of costs in the proper direction. Furthermore, the overheads that do not have a positive impact on the variations in the target function could be decreased and thus invested properly, in areas where their impact could be more favorable. This is what the application of Taguchi’s method on the structure of quality management costs in logistics allows the user to do – to calculate the contribution of the three cost groups in order to achieve an optimum effect in the target function.
During the study, the change in the structure of quality management costs was analyzed based on the significant factors for achieving customer satisfaction defined by the experts. Data from the expenses incurred by the logistics company operating in the food sector were analyzed, which were divided into three groups of costs and described in the methodology. The road to improvement was found to be associated with the following:
cost reduction for nonconforming services after delivery,
keeping a relatively stable level of the expenditures for control and,
to distribute the highest share of expenses for prevention by investing in the improvement of the processes for designing conforming logistics services.
Based on the analyses, it was concluded that even a change in the cost structure could contribute to a higher level of customer satisfaction with the studied logistics services in the food sector. Reducing the variation around the target function could not only contribute to higher customer satisfaction; moreover, it could reduce the overheads for nonconformities after delivery which are caused in particular by such a variation. Indeed, higher customer satisfaction could be achieved, if there is less variation with respect to the service wanted by the customer and delivered on time.
First, I would like to thank my children, without whose support I would not have been able to realize this idea.
I also thank all the logistics companies and logistics managers who participated in the survey and shared their experiences.
The author declares no conflict of interest.
Globally, the demand for feeds and forage has increased due to the increase in the livestock population [5]. Hydroponically sprouted cultivars are used as a dietary supplement for animals in South Africa, the United Kingdom, the United States of America, Australia, and other parts of the world due to their ease of germination and growth [6, 7]. Besides, various authors have reported different harvesting and growth cycles for a barley fodder mat, ranging from a 6-day harvest cycle to a 10-day harvest cycle, implying that hydroponically produced fodder has a short growth period [8, 9]. The quality and quantity of fodder produced by hydroponics are also of interest. Farmers in India, for example, discovered that feeding their dairy cattle hydroponically grown barley increased milk yield from 0.5 to 2.5 l/day. They discovered an improvement in animal health as well as the fat content of their cow’s milk in addition to the increased yield [10].
Climate change is affecting agriculture and natural water resources all over the world, which has an impact on the sustainability of food and water resources [11]. Because water and agriculture are inextricably linked and vital to most societies’ economies and security, hydroponic cultivation ensures year-round production while consuming less water [9, 12], as opposed to run-to-waste systems in field production [13]. It was reported earlier that hydroponic production used only about 2% of the water required for field production of the same crop [14] thus, the introduction of hydroponic systems for fodder production can help overcome the challenges encountered in conventional production.
Previous research has shown that soaking barley seed before sowing increases the rate of germination, softens the seed coat, and breaks seed dormancy, though the number of hours recommended for soaking barley seed ranged from 3 to 28 h [15, 16, 17, 18]. Similarly, the importance of using clean seeds for cultivation and seed sterilization during the soaking procedure cannot be overstated [9, 19]. Soaking seeds in a solution of 20% (bleach) for 30 min was recommended to prevent the formation of any fungal contamination [20, 21]. However, [22] using Mercuric chloride to prevent the proliferation of fungal contaminants while [23] tested both the effects of sodium hypochlorite (NaOCl) and Mercuric chloride (HgCl2) on a range of pathogens and proposed that surface sterilization of the seed is important to remove unwanted fungal growth.
Although earlier studies showed a wide range of water types, including both mist and flood irrigation [14, 24, 25], there is a scarcity of data on the amount and frequency of water/irrigation used in a hydroponic chamber to germinate barley seed. This was necessary to address the challenges of nutrient imbalance in hydroponic systems, soil quality and productivity, and soil-based ecosystem services [26, 27, 28] affecting barley biomass production. In this study, an 8-day harvest cycle was used in conjunction with post-germination irrigation frequency to determine the most effective method to break seed dormancy, cause germination, and grow into a seedling mat and see the impacts of these treatments on the nitrogen value, protein content, fresh weight, and dry weight of the seedling forage mat post-harvest compared to the original untreated seeds. Because soil-based farming is facing serious challenges in South Africa and other developing countries, fodder crop producers can use the study’s findings to obtain critical information that will aid in the optimization of inputs and the efficient utilization of resources in hydroponic fodder production.
Viable seeds of
The experiment was carried out in the plant tissue culture laboratory at the Cape Peninsula University of Technology’s Bellville Campus. A 230 cm × 450 cm growing room was used to control light and temperature and determine the best growing conditions. Shelving units measuring 200 cm in height, 127 cm in length, and 40 cm in depth were installed in the growing room. The shelving unit had six shelves that were 37 cm apart and measured 120 cm × 40 cm. Two fluorescent light bulbs were installed on each shelf. For drainage, a corrugated fiberglass sheet was cut to the size of the shelf below and positioned at a 55-degree angle. The front, bottom end was fitted with a D-shaped gutter. This was used to collect the runoff from the fiberglass sheets. The run-off was then directed back to a sump via the gutter, resulting in an ebb and flow closed watering system. After cleaning and soaking the seeds, they were placed in perforated aluminum containers measuring 10 cm × 20 cm. The perforations were evenly spaced across the tray’s bottom surface, with approximately 2 cm between each perforation. There was no need for a medium because the seeds germinated and formed a root mat that held the seedlings in place. The seed trays were then placed on the fiberglass sheeting, and each tray was fitted with an irrigation tube. Irrigation water was delivered to the seeds in their respective trays using a pump (HJ 1542 submersible), which delivered 622.5 mL/min to each tray for 2 min, for a total of 1245 mL. The pump was linked to a timer (MajorTech model MTD7), which controlled the amount of water delivered to each tray [29, 30]. Before the treated seeds were placed in the growing system, the entire setup, including the sump, Perspex shelves, and seed containers, was thoroughly cleaned and disinfected. The sump was filled with deionized water containing a 20% sodium hypochlorite solution, and the system was flushed to disinfect all surfaces [13].
The temperature of the room was kept at 23°C, as it was found that a temperature range of 20–30°C did not have a significant impact on growth [25, 31]. Two Samsung Smart InverterTM air conditioners were used to regulate the temperature. Fresh air was brought into the growing chamber through heap filters from outside the building. Lighting was provided with fluorescent tubes [32, 33]. The fluorescent bulbs used were Osram (L36/640) cool white fluorescent tubes with a light output of 5.96 kilo lux. The ExTech—Heavy Duty Digital Light Meter, model number HD 400, was used to measure the intensity of the light. A Panasonic TB178K timer control unit was used to set the lighting system to provide a photoperiod of 16 h day/8 h night [34, 35].
There were 25 treatments, each with 10 repetitions. Each treatment included a pre-soaking period followed by a post-soaking irrigation period (Table 1). Each repetition began with 100 g of viable seeds placed in a sterile plastic container containing 500 mL of distilled water containing a 20% solution of sodium hypochlorite (bleach) at room temperature [8, 14]. It was decided to test a range of seed soaking times, namely: 1, 3, 8, 16 and 24 h, which was compared against the control of 16 h. After the allotted soaking time, the seeds were washed in running, deionized water and placed in their respective growing trays without being exposed to darkness. Each tray was 10 cm × 20 cm in size. This ensured that the washed seeds had a depth of 1 cm. After that, the containers were placed in the hydroponic system to germinate (Figures 1 and 2). The seeds were allowed to germinate and grow into a forage mat for 8 days at 23°C under a photoperiod of 16-h day/8-h darkness.
Treatment code | Description | Treatment code | Description | Treatment code | Description | Treatment code | Description | Treatment code | Description |
---|---|---|---|---|---|---|---|---|---|
T1 | 1 h soak–2 h irrigation | T6 | 3 h soak–2 h irrigation | T11 | 8 h soak–2 h irrigation | T17 | 16 h soak–2 h irrigation | T21 | 24 h soak–2 h irrigation |
T2 | 1 h soak–4 h irrigation | T7 | 3 h soak–4 h irrigation | T12 | 8 h soak–4 h irrigation | T18 | 16 h soak–4 h irrigation | T22 | 24 h soak–4 h irrigation |
T3 | 1 h soak–8 h irrigation | T8 | 3 h soak–8 h irrigation | T13 | 8 h soak–8 h irrigation | T19 | 16 h soak–8 h irrigation | T23 | 24 h soak–8 h irrigation |
T4 | 1 h soak–10 h irrigation | T9 | 3 h soak–10 h irrigation | T14 | 8 h soak–10 h irrigation | T19 | 16 h soak–10 h irrigation | T24 | 24 h soak–10 h irrigation |
T5 | 1 h soak–12 h irrigation | T10 | 3 h soak–12 h irrigation | T15 | 8 h soak–12 h irrigation | T20 | 16 h soak–12 h irrigation | T25 | 24 h soak–12 h irrigation |
Treatments of
Photograph showing the hydroponic setup and irrigation supplied to each tray.
Photograph of barley seedlings at harvest (photo by R.A. Smith).
Drip irrigation tubes were used to flood each seed tray with 1245 mL of water, with the excess running off through drainage holes in the seed container. The runoff was collected and channeled back into the sump of the hydroponic system for reuse. When necessary, the sump was refilled with distilled water mixed with a 20% bleach solution to ensure disinfection. The five previously mentioned treatments were subjected to five different irrigation intervals, each with 10 repetitions. Flood irrigation was used to fill each seed tray with water every 2; 4; 8; 10; and 12 h, with the control being a 2 hourly water interval [24, 36].
Before removing the seedlings from their trays at the end of the 8-day growing cycle, a grid of 2 cm × 2 cm blocks was placed over the surface of the container, dividing the space into 50 blocks. This was used to determine the average leaf height per block by measuring the height of each leaf in the respective 2 cm × 2 cm block. The average leaf height of the sample plants for each block was then measured to determine the container’s overall average leaf height. The longest leaf in each tray was also measured and recorded. Thereafter the seedling mat was removed from its tray and the depth of the root mat was recorded to determine whether the initial 1 cm of soaked seed had expanded over the 8-day growing period.
For nutrient analysis, the trays were removed from the experiment and all excess remaining surface water was allowed to drain away after the allotted growth period of 8 days. The seedlings in their respective trays (Figures 1 and 2) were then weighed using a Kern KB 360-3 N scale that measures up to 0.01 g to determine their fresh weight. The weight of the seedling mat was calculated by subtracting the weight of the container from this measurement. Once the fresh weight of the plant material was determined, the seedling mat was removed from its tray and placed in brown paper bags before being dried in an oven (Labtech LDO-150F) at 60–70°C for 36–48 h. The plant material was weighed again after it had completely dried to determine its dry weight. Using a Culatti Typ MFC CZ13 mill, the dried plant material was ground and sieved after being weighed. Following that, samples of dried plant material were sent to the Agrifood Technology Station for protein and nitrogen analysis [37].
Data collected were analyzed using a two-way analysis of variance (ANOVA). The analysis was performed using Minitab 19.2.0/October 2, 2019, a stable release developed at the Pennsylvania State University, USA by Minitab LLC. Where F-value was found to be significant (P ≤ 0.05), Tukey honest significant difference (HSD) was used to compare the interaction between soaking time and irrigation interval at P ≤ 0.05 level of significance [38].
When comparing all soak treatments in conjunction with all irrigation intervals on average leaf length, Treatment 20 with 16-h soaking time and 12-h irrigation duration produced the longest leaf of 14.33 0.9 cm, while Treatment 9 produced the shortest leaf (6.23 0.40 cm) when compared to the control treatment. Both the independent and combined effects of soaking time and irrigation interval on leaf length were significant at P ≤ 0.05 (Figure 3). Additionally, the root mat expansion was most significant in Treatment 12 (8 h soak–4 h irrigation) and less significant in Treatment 25 (24 h soak–12 h irrigation) at a 95% confidence limit (Figure 4).
Effect of soaking time and irrigation interval on average leaf length of
Effect of soaking time and irrigation interval on root mat expansion of
The highest nitrogen yield was obtained from seeds that had been soaked for 1 h and irrigated for 12 h (Treatment 5), while the lowest yield was obtained from Treatment 17 (Figure 5). Similarly, the protein content of the samples follows the same pattern, with the highest and lowest nitrogen yields recorded in Treatments 5 and 17, respectively (Figure 6). Furthermore, the freshly harvested
Effect of soaking time and irrigation interval on the nitrogen content of
Effect of soaking time and irrigation interval on the protein content of
Effect of soaking time and irrigation interval on fresh weight of
Effect of soaking time and irrigation interval on the dry weight of
Furthermore, the two-way ANOVA revealed that soaking time and irrigation interval had no independent effect on nitrogen and protein yield of
Findings from this study suggest that the seeds of
Treatment 12 (8-h soak with 4 hourly irrigation) had the highest mean root expansion (3.07 cm) after the 8-day growing cycle, which was significantly different from the control. Treatment 2 followed with a mean of 3.03 cm (1-h soak with a 4-hourly irrigation interval; Figure 5), which was less significant than Treatment 12 due to a marginal difference of 0.04 cm, which is significant. Treatment 2 would thus allow the cultivator to reduce soaking time again to achieve similar results, with both treatments having the greatest effect with an irrigation frequency of 4 h, though other researchers have reported that transient exposure of
Furthermore, the highest nitrogen and protein concentrations were obtained in Treatment 5 with a 1-h soaking treatment and a 12-h irrigation interval (Figures 6 and 7). These results did not agree with the controls of 16 h of soaking and 2 hourly irrigation intervals. This indicated that the seed requires a shorter soaking treatment (1 h) as well as a longer (12 h) irrigation interval to achieve the highest level of nutrients in the seedling at harvest time. However, as discovered during the growth experiment, a 12-h irrigation interval is not beneficial to seedling growth. It was interesting to note that the next highest statistical mean belonged to treatment 1 (1-h soak with a 2-h irrigation interval), which was only marginally less than the highest mean achieved in treatment 5, which also had a 1-h soak time but a 12-h irrigation interval. This was consistent with the control and resulted in seedlings that were stronger and healthier. The shorter soaking time benefits the grower by reducing the time spent pre-soaking the seed, but it does not help with water conservation because it is irrigated every 2 h. However, as the salinity of the hydroponic medium changes, this may change. However, this might change as the salinity of the hydroponic medium changes [43, 44]. Only crude nitrogen and protein were tested in this experiment, and further research into trace element levels would be required to determine the seedlings’ full nutrient spectrum post-harvest. Other studies found that shortening the growing period from 8 to 4 days resulted in higher nutrient levels, which could be investigated further.
Furthermore, all of the highest dry weight means were obtained using a 10-h irrigation interval. The most significant results were obtained with soaking treatments lasting 1 and 3 h, as shown in Treatments 4 and 9, respectively. Although less significant, Treatment 14 with an 8-h soaking time was only 0.24 g lighter than treatments 4 and 9. This indicated that the seed pre-soaking time before germination could be reduced to 1 h. Under a 10 hourly irrigation interval, all three treatments (Treatments 4, 9, and 13) produced the highest dry weight. The highest fresh weight recorded came from that of Treatment 12, with a soaking time of 8 h and an irrigation interval of 4 h. It can be deduced that the seedlings benefitted from longer pre-soaking treatment. They still required moderate watering as the irrigation interval was every 4 h. Neither of the treatments agreed with the controls for soaking nor irrigation. The second highest mean value was achieved with Treatment 2 with a 1-h soak and 4 hourly irrigations. This proved that the pre-soaking time could be reduced without it affecting the total weight of the seedling post-harvest, however, the water consumption required to enable growth remained relatively high. Therefore, the disparity recorded in the weight of fresh samples compared to dry samples agrees with the results of the previous study as reported by Emam [20]. An investigation into the use of a nutrient solution to the irrigation water would be required to establish if this would improve overall fresh weight, post-harvest and if the introduction of a nutrient solution would allow the irrigation interval to be decreased thereby saving water.
This study reveals that a 1-h pre-soaked treatment, under 4 or 12 hourly irrigation intervals (T2 and T5) was the best treatment for cultivating barley hydroponically to achieve better yield for optimal fresh fodder production. For dry fodder weight, the highest yields were obtained with irrigation intervals of 10–12 h. Even though other growth parameters investigated such as length and root map expansion deviated from this trend, shorter soaking time at increased irrigation frequencies, proved to be beneficial to the farmer in terms of weight, nutrient yield, and height of
The authors wish to acknowledge the financial assistance received from the Cape Peninsula University of Technology through the University Research Fund.
Authors declare no conflict of interest.
All data associated with this research are available on reasonable request from the corresponding author.
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In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. 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He was head of this department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition, and dietetics. His research fields are biochemical pharmacological examinations in the human gastrointestinal (GI) mucosa, mechanisms of retinoids, drugs, capsaicin-sensitive afferent nerves, and innovative pharmacological, pharmaceutical, and nutritional (dietary) research in humans. He has published about 360 peer-reviewed papers, 197 book chapters, 692 abstracts, 19 monographs, and has edited 37 books. He has given about 1120 regular and review lectures. He has organized thirty-eight national and international congresses and symposia. He is the founder of the International Conference on Ulcer Research (ICUR); International Union of Pharmacology, Gastrointestinal Section (IUPHAR-GI); Brain-Gut Society symposiums, and gastrointestinal cytoprotective symposiums. He received the Andre Robert Award from IUPHAR-GI in 2014. Fifteen of his students have been appointed as full professors in Egypt, Cuba, and Hungary.",institutionString:"University of Pécs",institution:{name:"University of Pecs",institutionURL:null,country:{name:"Hungary"}}}]},{type:"book",id:"8008",title:"Antioxidants",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/8008.jpg",slug:"antioxidants",publishedDate:"November 6th 2019",editedByType:"Edited by",bookSignature:"Emad Shalaby",hash:"76361b4061e830906267933c1c670027",volumeInSeries:5,fullTitle:"Antioxidants",editors:[{id:"63600",title:"Prof.",name:"Emad",middleName:null,surname:"Shalaby",slug:"emad-shalaby",fullName:"Emad Shalaby",profilePictureURL:"https://mts.intechopen.com/storage/users/63600/images/system/63600.png",biography:"Dr. Emad Shalaby is a professor of biochemistry on the Biochemistry Department Faculty of Agriculture, Cairo University. He\nreceived a short-term scholarship to carry out his post-doctoral\nstudies abroad, from Japan International Cooperation Agency\n(JICA), in coordination with the Egyptian government. Dr.\nShalaby speaks fluent English and his native Arabic. He has 77\ninternationally published research papers, has attended 15 international conferences, and has contributed to 18 international books and chapters.\nDr. Shalaby works as a reviewer on over one hundred international journals and is\non the editorial board of more than twenty-five international journals. He is a member of seven international specialized scientific societies, besides his local one, and\nhe has won seven prizes.",institutionString:"Cairo University",institution:{name:"Cairo University",institutionURL:null,country:{name:"Egypt"}}}]}]},openForSubmissionBooks:{paginationCount:2,paginationItems:[{id:"11603",title:"People Management - Highlighting Futures",coverURL:"https://cdn.intechopen.com/books/images_new/11603.jpg",hash:"982c56a5fb4684d966f8f5e76b2638f5",secondStepPassed:!0,currentStepOfPublishingProcess:3,submissionDeadline:"March 22nd 2022",isOpenForSubmission:!0,editors:[{id:"450553",title:"Dr.",name:"Diana",surname:"Dias",slug:"diana-dias",fullName:"Diana Dias"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null},{id:"11601",title:"Econometrics - Recent Advances and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/11601.jpg",hash:"bc8ab49e2cf436c217a49ca8c12a22eb",secondStepPassed:!0,currentStepOfPublishingProcess:3,submissionDeadline:"May 13th 2022",isOpenForSubmission:!0,editors:[{id:"452331",title:"Dr.",name:"Brian",surname:"Sloboda",slug:"brian-sloboda",fullName:"Brian Sloboda"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},onlineFirstChapters:{paginationCount:17,paginationItems:[{id:"81751",title:"NanoBioSensors: From Electrochemical Sensors Improvement to Theranostic Applications",doi:"10.5772/intechopen.102552",signatures:"Anielle C.A. 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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. 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:null},{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:"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:"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:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{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:null},{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. 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For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. This series is intended for doctors, engineers, and scientists involved in biomedical engineering or those wanting to start working in this field.",coverUrl:"https://cdn.intechopen.com/series/covers/7.jpg",latestPublicationDate:"May 7th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:3,numberOfPublishedChapters:96,numberOfPublishedBooks:12,editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:null,institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda",middleName:"R.",surname:"Gharieb",fullName:"Reda Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. Osma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDv7QAG/Profile_Picture_1626602531691",institutionString:null,institution:{name:"Universidad de Los Andes",institutionURL:null,country:{name:"Colombia"}}},{id:"69697",title:"Dr.",name:"Mani T.",middleName:null,surname:"Valarmathi",fullName:"Mani T. Valarmathi",profilePictureURL:"https://mts.intechopen.com/storage/users/69697/images/system/69697.jpg",institutionString:"Religen Inc. | A Life Science Company, United States of America",institution:null},{id:"205081",title:"Dr.",name:"Marco",middleName:"Vinícius",surname:"Chaud",fullName:"Marco Chaud",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSDGeQAO/Profile_Picture_1622624307737",institutionString:null,institution:{name:"Universidade de Sorocaba",institutionURL:null,country:{name:"Brazil"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/70771",hash:"",query:{},params:{id:"70771"},fullPath:"/profiles/70771",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()