Radiations maximum at the first two sidebands and FNBW for the fundamental patterns of different values of SLL.
\r\n\tMain emphasis should be on its applications. In every field MOFs can be used due to its greater stability and high surface area, but the focus should be on applications.
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"57847",title:"Quality Management in Spice Paprika Production: From Cultivation to End Product",doi:"10.5772/intechopen.71227",slug:"quality-management-in-spice-paprika-production-from-cultivation-to-end-product",body:'\nSpice paprika, including bell pepper and chilli, is the second largest spice commodity worldwide (after black pepper) both in terms of its production volume and trade value [1]: the overall paprika/chilli production of the EU ranged between 48.8 and 108.0 thousand metric tons per year between 2002 and 2011, while 77.8–116.7 thousand metric tons per year was imported from non-EU countries during the same period. Spice paprika is a market leading commodity in certain countries such as Hungary. The latter is regarded as a spice paprika leader and the second largest per capita consumer in Europe, beside Spain [2].
\nDue to its agricultural origin, spice paprika is often naturally contaminated with various pathogenic or non-pathogenic bacteria (due to either poor growth, harvest/process sanitation or improper conditions during storage). Owing to its cultivation technologies and its volume in spice consumption, environmental and food safety of spice paprika cultivation and production expressed concern and can be assured by proper quality management along the entire technology chain from field to packaged end product. It is important to note, that deliberate contamination (e.g., food adulteration, intended malignant acts or even sabotage) may also cause safety risks.
\nSpice paprika is a condiment that consists of dried and ground paprika or chilli, a family of the species Capsicum annuum, that originate in Central Mexico. The name “paprika” is Hungarian and stems from the Greek “peperi” and in the Latin “piper”, both referring to pepper. The paprika varieties used to make spice paprika made their way to Hungary after Christopher Columbus brought them to Europe. From Spain, paprika cultivation spread to the South of France and to England. The industrialised production of the spice paprika started towards the end of the seventeenth century and grew to become highly developed by the mid-eighteenth century. It was during this period, when cultivation of the peppers in the Murcia region began. Paprika from Murcia would take on its own distinct character. In the years since the eighteenth century, the La Vera and Murcia regions have become the leading producers of Spanish paprika. The latter also arrived to Hungary as early as the sixteenth century. However, it remains unclear which route was opted. One hypothesis is that it was imported from Iberia as a substitute to spice pepper, when the Eastern trade paths were closed to the country being under Ottoman rule. Another theory is that it reached the country by the Southern Slavonic-Turkish mediation from the Balkan. Hungarians used paprika also as a medicine to prevent cholera and to treat typhus. Paprika varieties were afterwards cultivated there, and the climate of the regions of Kalocsa and Szeged proved ideal for growing. Central European paprika had a typically hot taste until the 1920s, when a Szeged breeder found a variety that produced a sweet tasting fruit, and then grafted it onto other plants. Both “hot” and “sweet” varieties of spice paprika have been cultivated in the Kalocsa and Szeged regions ever since, with practically closely similar cultivation and processing technologies, and similarly strict food safety requirements.
\nThe EU food safety regulations, established in the time period 2002–2004, whilst being updated several times since, are based on strict and harmonised food safety standards. The EU agency responsible to ensure food safety is the European Food Safety Authority (EFSA) established by Regulation 178/2002. Subsequent regulations cover the entire food chain from farm to fork, and enhance both prevention and follow-up. They include Regulations [European Commission (EC)] No 852/2004 and (EC) No 853/2004 (control food hygiene), and official controls to ensure compliance with feed and food, as well as animal health and welfare laws as outlined by Regulation (EC) 882/2004.
\nEffective enforcement of the legal regulations concerning food safety within the EU is assured, among others, by the Rapid Alert System for Food and Feed (RASFF) established in 1979. This is a public, reactive, hazard-based reporting system at EU community level, allowing rapid information exchange among EU member states on hazards related to distributed consumer products, including not only food contamination, but also food fraud [3]. Acting in concert with governmental or EU-specific level regulations and RASFF, expert advisory systems operating on market-based mechanisms and supported by the governments in member states also serve food product quality assurance in the overall food chain from crop cultivation, feed and food raw material production, to processing, storage, transport and trade.
\nSpices and herbs, in spite of their consumption in small quantities, are of special concern for environmental and food safety due to their use in dried form for seasoning, their long production and trade chains, and possibilities of their deliberate contamination. Spice paprika has been worldwide reported for chemical and microbiological contamination, as well as for fraud or food adulteration [4]. Different production stages within cultivation and production are subject to different contamination types. Cultivation is a common source of pesticide residues, and unfavourable harvest conditions may give rise to mycotoxins by pathogenic fungi. Spice paprika, as other spices, often becomes naturally contaminated with various bacteria (e.g., Salmonella spp., Bacillus cereus, Escherichia coli [5]) generating microbial hazard [6]. Storage and post-ripening prior to processing is attributed with microbial contamination and possible increases in mycotoxin content, and may significantly affect quality features. Technology steps (e.g., washing, separation and drying) may worsen microbial contamination or quality features, but normally do not lead to rises in mycotoxin levels. Nonetheless, decontamination technologies are a prerequisite for microbial safety. Upon effective decontamination, finishing steps in the processing technology (e.g., grinding, packaging and end product handling) do not affect the microbial status, but other, occasionally deliberate contamination due to mixing and food adulteration may occur at this stage. The implementation of proper quality control measures at each of the above steps, in conjunction with effective interaction between producers’ quality management practices and government activities are regarded as key factors in the provision of environmental and food safety of spice paprika production.
\nTo illustrate the need and the difficulties in provision of environmental and food safety of spice paprika production, quality assurance measures established along technologies are surveyed with main critical control points (CCPs) identified [7]. Thus, points of vulnerability and each step in the technology chain (cultivation and plant protection, storage and post-ripening, grinding, slicing and mixing and decontamination) are surveyed. If concerted performance of internal (manufacturer) and external (state) quality control measures act in synergy then these may guarantee good production practice and support product quality in spice paprika cultivation and processing.
\nThe leading risk factors and contamination cases, notified in the RASFF in the last 10 years (2007–2016), draw attention to the most important points of vulnerability in the supply chain and/or product flow, where entering contamination (hazard), according to the risk assessment concept, may cause medium or high risk and thus, requires the development of preventive and/or elimination processes. It is worth noting at this point that during the 10-year period mentioned above, 373 notifications in total were issued. These included the trade of spice paprika and chilli products, either between EU countries or between an EU country and a “third country” (exporting into the EU).
\nAforementioned notifications regarding spice paprika and chilli showed an almost steady distribution within those years, with an average of 37 notifications per annum in total, with the highest number of incidence occurrence in 2010 (70) and the lowest in 2014 (17). The priority list of the reasons of the notifications for spice paprika and chilli according to RASFF indicate the most important points of vulnerability during the entire production line, and draw attention to the accentuated necessity of quality control and management. Mycotoxins are the main risk sources (78%), but in some cases illegal dyes or other foreign compounds were detected (11%), and in further notifications pesticide residues (7%) and microbial infections (3%) were also reported (Figure 1).
\nThe number of notifications in RASSF between 2007 and 2016 regarding contamination of spice paprika.
As seen, the most important hazard of spice paprika and chilli products is mycotoxin contamination, where 225 and 62 events have been reported for aflatoxin and ochratoxin presence, respectively. Considering the number of incidents in temporal distribution, the highest number of aflatoxin contamination was reported in 2010 (52) and 2016 (37), while the lowest in 2009 (9) and 2014 (11). As for territorial distribution, the majority of cases occurred in products that originated from India (45%). Another 13 countries contributed more than 1% (more than 4 cases of incidents in the period studied) to the priority list. Another 28 EU and non-EU countries are responsible for the further 48 mycotoxin contamination events.
\nTo minimise the effects influencing quality, producers are obliged to operate quality management/assurance and food safety systems, for example, Hazard Analysis and Critical Control Points (HACCP), the documentation of which containing all steps of the technology, critical points, where human health risk could occur, self-control points, as well as solutions for possible problems. The authority is entitled to inspect and survey the documentation of self-control. For the latter to occur, own quality management systems are required to operate. These are similar among EU member states, yet may utilise different strategies in their approach. The implied reporting mechanisms (including data record systems) pertaining to biological and chemical contaminants are regulated by law.
\nIn the analysis of the production line of spice paprika or chilli products, typical contaminants and technological errors have to be considered, and accordingly, the optimal positions of the CCPs in the production line have to be identified. A model was implemented for a HACCP system for prevention and control of mycotoxins during the production of dried chilli [8], in which the most important critical control points (e.g., drying and sorting) were identified. Good Agricultural Practice, Good Manufacturing Practice, Good Safety Practice and HACCP were shown to be necessary for processing plants in order to assure proper quality management.
\nFor the grower side, there are several aspects that need to be taken into consideration. To control the quality of Hungarian ground spice paprika, the Government founded the Chemical Test and Spice Paprika Research Experimental Stations in Kalocsa (1917) and in Szeged (1921). The official selection of the commonly cultivated varieties began almost 80 years ago with the primal milestone: a non-pungent spice paprika cultivar was selected from the landrace populations by Ferenc Horváth. From the 1960s onwards, the selection and breeding continued in Kalocsa and Szeged at the reformed Research Stations, which were—and still are—supported by the Hungarian State.
\nDue to factors relating to the Hungarian soil and climate, the growers use only interior bred Capsicum annuum (L.) var. ‘Longum’ cultivars for spice paprika production. The breeding objectives are specified by the growers and the processing industry, according to the requirements of the consumers. Nowadays, a wide assortment of spice paprika varieties is available including the traditional varieties for the extensive growing technology and new hybrids for the most up-to-date paprika production under plastic tunnel.
\nThe successful open field spice paprika production is based on the selection of the growing area considering the soil type and the crucial facts of the microclimate. The sandy loam soil around Szeged region is applicable for direct sowing, as well as for transplanting spice paprika seedlings. Around the Kalocsa region, the soil contains more clay, which—depending on the humidity of the surface—could cause crust and therefore some difficulties at the germination stage. In order to prevent this from happening, the vegetation period is been extended by a few weeks, giving the chance to growers to grow transplants under plastic tunnels.
\nBased on performed research, it is worth mentioning at this point that in any given 10-year period, 2 or 3 years may limit the vegetation period by the probable latest frost at the end of April and the unpredictable chill point between the end of September and the first week of October. For the most profitable crop production, the growers prefer early (semi-determinate) and mid-early (indeterminate) cultivars for optimal yield (12–15 t/ha) at the harvest. Traditional open field direct sowing and transplanting cultivation technologies apply open pollinated semi-determinate (e.g., Kaldóm) or indeterminate sweet (e.g., Szegedi-80) and hot (e.g., Szegedi-178) varieties.
\nConsidering the disadvantageous impacts of the climate change in the Carpathian Basin and the increasing demand for both quantity and quality of the crop, the cultivation technology requires continuous development and breeding high genetic potential, virus-resistant varieties or hybrids. Applying the black plastic covered ridge cultivation with drip irrigation and soluble fertilisers, the open pollinated indeterminate (e.g., Kárminvörös) and hybrid (e.g., Jubileum F1, Szikra F1) varieties could reach 20–25 t/ha yield with high quality. It is worth noting at this point though, that this intensive technology bears a number of risk factors such as extreme weather conditions and the insect (e.g., Aphids) transmission of viruses (e.g., CMV, Potato Y). Both open field production has the risk of yield loss caused by the bacterial leaf spot (Xanthomonas campestris pv. vesicatoria), which could be simply solved with the plantation of bacteria resistant sweet (e.g., Kaldóm) or hot (e.g., Kalóz) varieties.
\nProfessional spice paprika production under non-heated plastic tunnel utilises the latest development of intensive growing technology with sweet (e.g., Bolero F1) and hot (e.g., Jubileum F1, Szikra F1) hybrids. The vegetation period is elongated from the middle of April to the end of November. The harvest period begins from the middle of July and ripened fruits could be harvested until the first serious frost. In case of continuous selective harvest, the average yield is up to 40 t/ha, approaching the genetic potential of the hybrid varieties. The fresh picked raw spice paprika material contains 150–180 American Spice Trade Association (ASTA) colour content with 16–18% dry matter content.
\nIn plant protection techniques, various agrochemicals, including numerous pesticide active ingredients and preparations have been registered for treatments in spice paprika cultivation. The choice of protection method is highly technology-dependent.
\nNumerous pesticide active ingredients have been authorised on spice paprika over the decades, having been banned or withdrawn ever since. Currently, 51 active ingredients are authorised for paprika cultivation. RASFF notifications were issued in relation to the residues of 30 active ingredients, the vast majority (23) were insecticides, and the others were fungicides (5) and soil disinfectants (2) [8, 9, 10].
\nThe effects of intensive cultivation conditions on the pesticide residue levels and the composition of bioactive substances were assessed [11]. In a cultivation modelling experiment, paprika plants were treated at three dosage levels of three recommended insecticides (pirimicarb, chlorpyrifos and cypermethrin) and a fungicide (penconazole). A small parcel experiment of intensively cultivated paprika was carried out, where the plants were treated 1–3 times with pesticide premixes at different dosages (three levels).The harvested and processed paprika was sampled and analysed for pesticide residues content and bioactive component amount. Residue levels of chlorpyrifos (0–1.747 μg/g dried paprika) detected in the differently treated paprika fruits negatively correlated the levels of capsanthin monoesters and β-carotene, as R2 was obtained 0.65 and 0.74, respectively. The content of carotenoids and tocopherols compared to the negative control samples decreased by 3.3–6.2 and 10.6–21.5%, respectively.
\nResearch conducted by the authors indicates that not only the pesticide active ingredients are subject to environmental concerns, but also the various additives used in their formulation to improve their physicochemical characteristics (stability, penetration and absorption). A recent outstanding example is the formulant polyethoxylated tallowamine used for the formulation of the herbicide active ingredient glyphosate, that has been found 2–3 orders of magnitude more toxic on given biochemical processes (e.g., cytotoxicity) or to non-target organisms [12, 13], and has recently been banned from the use in glyphosate-based herbicide preparations. Research carried out by the authors shows that glyphosate, as a total herbicide, is not used on paprika, except for pre-sowing or pre-emergence treatments. For neo-nicotinoid insecticides registered for use on paprika cultivation, however, it has been shown that the formulating agent modifies the toxicity of the formulated pesticide, many of them used in spice paprika, as compared to the corresponding active ingredients (glyphosate, isoproturon, fluroxypyr, pirimicarb, imidacloprid, acetamiprid, tebuconazole, epoxiconazole and prochloraz) [14], (clothianidin) [15]. As a result, authorisation of the formulating surfactants is expected to stricten [16].
\nThe profitable open field spice paprika growing technology is associated with plant protection by Integrated Pest Management (IPM), based on pest population dynamics forecast and the use of preventive and alternative solutions to decrease the environmental impact with chemical treatments. Among preventive solutions, plant rotation is essential, and the best fore crops for spice paprika are cereals. Avoiding the accumulation of pests (e.g., nematodes) and diseases (e.g., viruses, bacteria and fungi) after cultivation of paprika (or other Solanacea species) for 3 or 4 years, other crop cultivation is recommended. Utilisation of original, sealed and pelleted seed prevents the propagation of tobamo (TMV, PMMV) viruses both in direct sowing and transplanting technology. To avoid possible transmission of TMV by direct contact (e.g., planting), resistant hybrids are recommended by the breeders and seed trade companies. Plant nurseries are usually maintained in greenhouses or plastic tunnels, and it is crucial to keep them, free from any pests (e.g., aphids, thrips and nematodes).
\nAphids (e.g., Myzus persicae) are non-persistent vectors of the cucumber mosaic virus (CMV). Paprika infected by CMV produce at 20–30% lower yield. Preventing the infection of CMV by spraying mineral paraffin oil is recommended. It is the author’s view that this may raise environmental concerns. In case of serious aphid invasion, reasonable utilisation of pyrethroid insecticide (e.g., deltamethrin) is allowed until the withdrawal period prior to harvest.
\nThrips (e.g., Western flower thrips—Frankliniella occidentalis) cause their major damage by the nymph laying eggs in the plant tissue or the bud. The plant, the flowers and the small fruits are subsequently injured by feeding. Thrips are the major vectors of a serious plant disease, tomato spotted wilt virus (TSWV). The damage by thrips and TSWV in nurseries and under plastic tunnels threatens the economy of the entire production. Even though survival of the thrips is highly temperature-dependent, protection against them is difficult due to their special, hidden life-cycle. Indication of the presence of thrips in the plantation is simple with blue sticky traps, but efficient application of biological plant protection methods, for example, the thrips’ natural predators, like Orius genus and Amblyseius cucumeris requires special climatic conditions. Should other control techniques fail, a reasonable utilisation of certain mild insecticides (e.g., abamectin) is allowed within IPM.
\nTo avoid problems with nematodes (e.g., Meloidogyne incognita), plant nursery must always use nematode-free medium and plant trays for sowing. Utilisation of fresh medium also benefits to avoid the plant pathogenic fungi Rhizoctonia solani.
\nPreventing the damages of broad mite (Polyphagotarsonemus latus) in cultivation, plant nurseries must be treated with ventilated sulphur powder or spraying with an acaricide. After planting, at the end of May and the first decade of June, larvae of the turnip moth (Agrotic segetum) harm by cutting the seedlings. The hatch of the larvae is predictable with sex pheromone traps, and as such, a well-timed parathyroid treatment may optimise protection against young larvae. The cotton bollworm moth (Helicoverpa armigera) is the most harmful pest of spice paprika in open field plantation before harvest. The larvae feed on leaves, flowers and fruits, and finally hide into the fruit, consuming most of the seeds and leaving excrements. The damaged fruits are not only worthless, but potential sources of contamination. The swarming period of the imagoes is July to September. Protection is also based on light and sex pheromone traps, but the number of the possible treatments is limited by the harvest schedule.
\nAccording to the food market demands, the importance of biologically protected, high quality and healthy spice paprika is increasing, as in 10 years (2004–2014) the cultivation area increased from about 30 to 50 ha in Hungary. The up-to-date non-heated plastic tunnel is the optimal solution for intensive spice paprika growing with biological protection. Due to the control of the climate conditions via insect-proof ventilation and shading, plant protection can be solved with preventive insect traps, predators or parasitoids. The main pests in growing equipment are virus vector thrips and aphids. To keep aphids and cotton bollworm out, a simple solution is the utilisation of vector nets, and the use of protective clothing for the workers. If the moth imagoes are already in the equipment, a mix of Trichogramma species (T. pintoi, T. evanescens) appears to be efficient. The glasshouse whitefly (Trialeurodes vaporariorum) is current in greenhouses and plastic tunnels, and causes crop damage through both direct feeding and propagation of viruses. As a side effect of feeding, honeydew is excreted and in turn, a sooty mould covers the leaves and the fruits.
\nYellow sticky traps are suitable to indicate and to thicken the whitefly population in the growing equipment. Biological protection is applicable with the parasitoid wasp Encarsia formosa is supported with climate control. Powdery mildew (Leveillula taurica) fungi may cause heavy yield losses in growing equipment. To prevent the disease, climate control is crucial. Protecting the crop by spraying with sulphur and potassium bicarbonate is acceptable for biologically grown paprika.
\nAs mentioned before, the freshly picked raw spice paprika contains 16–18% dry matter. High quality ground paprika as raw material needs at least 4 weeks of after-ripening to decrease the rate of water content and increase the rate of dry matter and stable carotenoids. From the middle of July to mid-September, solar energy can be used for pre-drying in a hygienic equipment, like grids under a shaded and ventilated plastic tunnel.
\nPreparing the dried material for grinding, additional (max. 50°C) drying is needed until the dry matter content decrease to 6–8% or less. After gentle grinding, the final result is high quality paprika with excellent ASTA colour content, outstanding aroma compounds and bioactive components. There are three CCPs in the production line of spice paprika one occurs at the drying step, the second at the microbial decontamination stage and the third applies at mixing, if imported half-products are being used.
\nThe first of these CCPs, the drying step requires the highest foresight, because improper drying impairs the sensory and compositional properties of the product. Its temperature conditions have an apparent optimum: extensively high temperatures should not be applied to avoid formation of unpleasant aroma, pigment and flavour compounds, while drying at low temperature can lead to poor grinding characteristics.
\nQuality control laboratories at the processing plants carry-out the basic measurements (e.g., moisture, ash, sand, pigment content, microbiological status and colour determination by the protocol of the American Spice Trade Association (ASTA) at each marked points). To summarise the effects of processing, different steps were in-depth investigated regarding microbial contamination and concentration changes of the bioactive compounds.
\nDuring slicing, the microbial contamination of paprika increases, as the microbes present inside the berries emerge to the surface (Figure 2A). Drying greatly reduces microbial contamination, as most of the vegetative cells are killed. The numbers of mesophilic aerobic total bacteria and coliform counts dropped by 2–3 orders of magnitude, while Escherichia coli, Enterobacteriaceae and yeasts have almost entirely disappeared (Figure 2B).
\nThe effect of technology steps on the microbial status of the paprika half-product. A: slicing, B: drying, C: grinding.
Comparison of the dried half-product before and after grinding indicated complete eradication of coliforms, Escherichia coli and Enterobacteriaceae, while the mesophilic aerobic bacterial count and mould contamination increased by two orders of magnitude. This is due to the fact that the microbial load of paprika berries is not homogenous; a few heavily spoiled ones mixed with the healthy berries can contaminate the entire product (Figure 2C). The chemical composition, however, did not appear to undergo any significant change.
\nAnother CCP in the technology chain is at the microbial decontamination. To enhance food safety of spice paprika, a decontamination step needs to be carried out to secure the microbial purity of the product and to avoid contamination of food seasoned with it [17]. Various methods are in use and are incorporated into the processing technology (generally after the grinding step) or available for decontamination [18]. Their efficiency in reducing the microbial load in dried spices has been evaluated in literature [19]. Nonetheless, even though red sweet paprika is appreciated being an excellent source of essential nutrients and bioactive compounds, these assessments generally do not evaluate the effects the decontamination step may exert on the composition of the bioactive, aroma and colour components.
\nMicrobial decontamination is most often carried out by steam treatment or by irradiation by ionising radiation (e.g., gamma irradiation—the maximum allowed average radiation dose being 10 kGy) [20]. In spite of the high efficacy of microbial decontamination by irradiation, and even though legal regulations allow (and even advise) this technology in the EU for decontamination of dried herbs and spices, producers tend to choose steam treatment due to consumer aversion from the food radiation technology [21]. Consumer acceptance of irradiation remains poor despite numerous efforts of food industry experts and the EU legislation to dispel misconceptions regarding the use of isotope techniques and ionising radiation [22]. It has to be also mentioned, that sensory and anti-oxidative properties of the finished product may be slightly affected by the technology used [23]. Irradiation (at 1, 5 and 10 kGy doses) was proven highly effective in the treatment of ground dry spice paprika: the aerobic mesophilic total count (log) decreased from 6.84 to 5.08, 4.71 and 2.91 log cfu/g, respectively, while the mould count (log) from 3.78 to 3.54, 3.18 and 2.30, respectively. The numbers of coliforms (log) 3.71 and Enterobacteriaceae (log) 3.28 decreased under the detection limit after the treatments, even at the lowest dose, 1 kGy. Interestingly by irradiation, the dominant microflora of Bacilli (B. methylotrophicus, B. pumilus) gradually disappeared and species less sensitive to irradiation (Methylobacterium spp., Micrococcus spp. and Microbacterium spp.) came into consideration, meanwhile more bacteria of possible human relevance (Staphylococcus spp., Corynebacterium hansenii) were also isolated. While the microbial status improved by irradiation, the concentration of the bioactive components, such as carotenoids, tocopherols, vitamin C and the ASTA value decreased (p < 0.05).
\nStudies [24] conducted on different decontamination methods by comparing the effects on the microbial status and chemical composition, especially the bioactive compounds, colour and volatile components concluded that earlier methods, for example, irradiation and steaming effectively lowered the microbial decontamination rate, while only slightly affected the bioactive component content, however, decreased the levels of volatile aroma compounds. In contrast, alternative methods, for example, enhanced microwave treatment and radio-frequency heat treatment were less effective in the reduction of the microbial counts, and harmed the colour of the samples, but the bioactive chemical compositional parameters were not affected significantly. Even though the levels of carotenoids, tocopherols, vitamin C or other bioactive compounds and the ASTA values decreased, changing the composition rates of the volatile aroma substances, irradiation was considered to be of outstanding efficacy [25, 26].
\nA technology-dependent issue is, whether irradiation is carried out in bulk or in sealed packages of the finished product. Bioactive compounds are anticipated to decompose less in the latter case, although radiolysis products, involatile or volatile, may diffuse into the product from the packaging material [27]. Reduced amounts of carotenoids were reported at high irradiation dosages and long storage (e.g., 11.1 and 42.1% decrease in capsanthin levels upon irradiation at 10 kGy and a subsequent 10-month storage period, respectively) [28]. Approximately 40% reduction in anti-oxidant activity was seen upon a 20-week storage period, compared to 13% decrease in the control non-irradiated ground black pepper [29].
\nSteaming is a decontamination technique of spices of proven and high utility. Due to steam treatment (saturated dry steam, 108–125°C for 20–120 s) the mesophilic aerobic total bacterial count from 1.8 × 105 cfu/g to 6.0 × 102 cfu/g and moulds from 1.3 × 102 cfu/g to under the detection limit were reduced, while yeasts, coliforms, E. coli and Enterobacteriaceae could not be detected. According to the molecular identification, the dominant bacteria were spore forming rods, family Bacillaceae, namely B. methylotrophicus, B. pumilus, B. vallismortis and B. sonorensis before, while B. methylotrophicus, B. pumilus and B. amyloliquefaciens after treatment. The concentration of the main bioactive compounds, as capsanthin esters, total carotenoids, tocopherols, vitamin C and the ASTA value did not change significantly, however, the total tocopherol content decreased by 6%. The area percentage (%) of the volatile aroma compounds (e.g., acetic acid and pentanal) decreased, while in some cases (e.g., geranyl acetone, β-ionone and dihydroactinidiolide) a slight increase was detected.
\nSteam treatment was shown to cause a reduction of volatile oil content along with discoloration [30], and although high-temperature steaming is effective against contaminating microorganisms, it can decrease the volatile oil content, cause colour degradation and may increase the moisture content of dried paprika product, which then reduces shelf-life [31]. Furthermore, steaming is not suitable for spore inactivation. These results confirm that steaming provides a good possibility to reduce the microbial load, without drastically changing the content of bioactive compounds.
\nEven though well-described and evaluated industrial decontamination processes are available, alternative methods are also being developed and investigated for efficacy and effects. Microwave heating is advocated for effective reduction of the level of mesophilic bacteria. The method (98°C for 20 min) was indicated to reduce the total number of mesophilic bacteria 6.3*104-fold [32]. Microwave heating (30 s in dry and wet treatment) was found to allow the highest reduction of the bacterial level in chilli among different spices studied [33]. It is worth noting at this point that the method (100 s at various temperatures) did not result in a relevant reduction of the total counts of mesophilic aerobic bacteria even at 95°C, but affected the colour of the treated paprika lot unfavourably, giving it a darker, brownish character.
\nTo avoid the detrimental effect of the treatment method on the colour of spice paprika, a modified microwave treatment (including re-wetting of the sample, intensive mixing during the entire treatment and post-drying to the initial moisture level) was also evaluated by the authors. Mesophilic aerobic total bacterial counts were not significantly affected by the enhanced microwave treatment, however, mould populations and coliforms were reduced, if samples were kept at the given temperatures for at least 10 min. Significant changes were detected in carotenoids, and total tocopherol content decreased by 6.2% only at higher initial moisture content (30% and higher, 10 min, 95°C). Thus, enhanced microwave treatment allows a reduction of microbial contamination (principally for moulds and coliforms) without a decrease in the levels of bioactive compounds. The temperature did not significantly affect chemical composition, but had a significant effect on sample colour.
\nNonetheless, in spite the corrected moisture content, all samples became browner and darker after the treatment, and as colour changes did not correlate with the observed levels in carotenoids and the ASTA value, it has been concluded that colour changes due to the treatment are likely to be related to plant carbohydrates and proteins.
\nOregano essential oil was attempted as a natural anti-microbial agent to reduce microbial count in paprika [34]. Although it was not found to be of adequate activity by itself to allow sufficient inactivation of microbial spores in paprika, when used in combination with high-pressure carbon dioxide, microbial inactivation largely increased (by 99.5%).
\nIn a number of food products, high hydrostatic pressures increase shelf-life and maintain nutritional and organoleptic properties better, the effect of high hydrostatic pressures and pasteurisation (in a water bath at 70°C for 10 min) was examined on the levels of given bioactive components and on the texture of spice paprika [35]. Pasteurisation treatment at high hydrostatic pressure (500 MPa) had less influence on the bioactive component content and on the texture, than at low pressure.
\nChemical treatment with ethylene oxide is also a worldwide available decontamination technology, but the potential use is limited by its toxicity. Due to its carcinogenic potential to humans, the use of ethylene oxide is forbidden to be used in food processing in the EU [36].
\nAs mentioned above, the last one among the three CCPs within the spice paprika processing technology is at the mixing step, where the imported half-products get into the manufacturing process. Determination of the origin or ensuring the authenticity of red paprika products is of high importance from both food safety and commercial aspects. To assess the composition of bioactive ingredients in spice paprika and to support the safety of the spice product chains, a wide range of compositional examinations were performed on spice paprika samples of several geographical origins.
\nA method of combining strontium isotope ratios with a multi-element pattern by means of inductively coupled plasma mass spectrometry (ICP-MS) was used to create a unique fingerprint of authentic Szegedi Fűszerpaprika and to categorise authentic and purchased paprika from different known, declared and unknown geographical origins, using principal component and canonical discriminant analysis [37]. Changes in element and strontium isotopic composition (87Sr/86Sr ratio) were examined throughout the production process. As such, the geographical origin of the spice paprika can be determined even after processing. Strontium isotope ratios are combined with multi-element pattern analysis in the “fingerprint” method, using ICP-MS, and another proper indicator of cultivation types (agrochemicals) and geographical origin (e.g., a distinction between Asia and Europe) is the δ15N value. A clear distinction between Japanese and foreign paprika products was achieved on the basis of their Cu and Rb content by ICP-MS [38]. Similarly, sweet, hot and hot/sweet paprika samples from Spain were assessed by their micro-elemental composition by ICP-MS followed by chemometric class-modelling techniques on variables selected by stepwise linear discriminant analysis [39, 40].
\nOrigin-protected Spanish spice paprika samples (Murcia and Extremadura) were analysed by colour characteristics to differentiate between geographical origins [41]. Co-ordinates in the CIELAB colour space and ASTA scale were measured from acetone extracts of paprika samples in UV-Vis spectral range. For origin discrimination multi-layer perceptrons, artificial neural networks models presented the best results for all types of paprika. According to another strategy [42], the entire absorbance range from 380 to 780 nm was used, and data was combined and reduced by means of principal component analysis. The anti-oxidant activity and the composition of polyphenolics and carbohydrates of spice paprika (Lakošnička and Lemeška) were investigated to attempt to verify the regional and botanical origin of Serbian autochthonous clones of red spice paprika using multi-variate statistical methods [43]. In addition, distinction was achieved to be made between Dutch bell peppers and those from other countries, using analytical strategies based on bulk δ18O elemental analysis of source and paprika fruit water, and on compound-specific, n-alkane, δ2H gas chromatography coupled to isotope ratio mass spectrometry analysis [44].
\nGas chromatography-olfactometry was also applied for the evaluation and identification of the odour-active compounds combined with the flavour dilution (FD) factors [45]. For the control of aflatoxin B1 and total aflatoxins in spice paprika powder, NIRS technique as an alternative method was applied using the Modified Partial Least Squares (MPLS) algorithm as a regression method [46]. Moreover, the contamination of mycotoxins (e.g., fumonisin B1, ochratoxin A and sterigmatocystin) and pesticide residues (e.g. metalaxyl fungicide) in spices were investigated by ultra-high performance liquid chromatography (UHPLC) coupled to a high resolution Orbitrap mass spectrometry (Orbitrap-HRMS) [47].
\nTo identify major differences in characteristics and chemical component composition of spice paprika by their origin, a set of samples (53 pieces) was investigated [48]. Samples from Spain and Peru showed outstandingly high total carotenoids content (in average 3709 and 3810 μg/g, respectively), and the ratio of capsanthin diesters to free capsanthins was found to be a good indicator of origin, supposedly due to differing climate conditions in the two countries. The calculated capsanthin diesters/free capsanthins ratio was found to be in average 4.0, 5.3, 8.1, 8.2, 17.1 and 22.0 in samples from Serbia, Hungary, Spain, Bulgaria, China and Peru, respectively. According to the results of NIR evaluation of spice paprika samples, there occurred some clustering among the samples according the country of origin.
\nThe geographical origin of spice paprika has also been successfully attempted to be characterised by their dominant microflora [49]. Although no substantial differences were found among the microbial loads of spice paprika samples from different countries (Brazil, Bulgaria, China, Hungary, India, Kenya, Peru, Serbia, Spain, Thailand and unknown origin) on the EU market, bacterial species in the dominant microflora, characteristic to climate, were identified. The presence of B. mycoides and B. licheniformis were found to be characteristic to Central Europe, B. mojavensis to Spain, B. safensis to tropical monsoon climate, B. amyloliquefaciens subsp. plantarum and B. amyloliquefaciens subsp. amyloliquefaciens to tropical climate, and no common species was identified for China.
\nIn addition to obligatory quality control and assurance measures by the producers and systematic analysis for compliance with food safety requirements at EU community level by RASFF, national authorities in EU member states also perform external control analyses to assure food safety (EC Regulation No 882/2004). At present, there are no microbiological criteria for dried spices in the European Community legislation, although, the Codex Code of Hygienic Practice specifies that dried spices should be free of pathogenic microorganisms at levels that may represent a health hazard. The European Spice Association (ESA) and the European Commission (EC) Recommendation 2004/24/EC specify that Salmonella spp. should be absent in 25 g of spice, E. coli must be under 102 cfu/g, and other bacteria requirements should be agreed between the buyer and the seller [50].
\nProper quality control measures at each of the above steps along with effective interaction between producers’ quality management practices and government activities are key factors in the provision of environmental and food safety of spice paprika production. To illustrate this, quality assurance measures established along spice paprika production technologies are surveyed with main CCPs identified. Concerted performance of internal (manufacturer) and external (state) quality control measures act in synergy to guarantee good production practice and to support product quality in spice paprika cultivation and processing.
\nThis work was supported by EU-project SPICED (Grant Agreement: 312631) with the financial support from the 7th Framework Programme of the European Union and by projects OTKA K109865 and K112978 by the Hungarian Scientific Research Fund. This publication reflects the views only of the authors, and the European Commission cannot be held responsible for any use which may be made of the information contained therein.
\nIn any wireless communication system, the antenna is an essential component to transmit or receive a message signal. In many applications such as satellite communication, point-to-point communication, military communication, surveillance, radar, sonar, aircraft, etc., the antenna gain and directivity should be sufficiently high so as to direct most of the antenna-radiated power along a particular direction by reducing the power level (side lobe power) at other directions. A single radiator may not meet such requirements due to its omnidirectional power pattern and high side lobe level (SLL) in the far-field region. Moreover, radiation of huge amount of transmitter power from a single antenna element needs high-power amplification in the feed network. The high-power amplifier is not easy to design and safe to handle. Therefore, a number of antenna elements are arranged along a line, called linear antenna array (LAA), or in a plane called planer antenna array (PAA). The use of multiple antenna elements in the transmission and reception systems simplifies the power amplifier design problem by reducing the power level per transmitting antenna elements of the arrays. Some other advantages of using antenna arrays are to improve signal fading resistance or deliberately exploit the signal fading; mitigate the interfering signal coming from other directions, adaptive beam forming, and null steering at both transmitter and receiver; and increase system capacity. Due to its high gain and narrow beamwidth, the large antenna arrays also find applications in weather forecast, astronomy, image processing, and biomedical imaging.
\nAlthough the antenna array with uniform excitation amplitude and equally spaced antenna elements is the simplest one for practical implementation and also can be used to synthesize different patterns, due to the high value of peak SLL, it is impractical to use in such applications. In conventional antenna array (CAA) system, the low side lobe pattern is obtained by tapering the static excitation amplitudes. The well-known analytical techniques to taper amplitude distributions in nonuniformly excited antenna arrays are Dolph-Chebyshev (DC) and Taylor series [1]. However, the high dynamic range ratio (DRR) and complex excitation of the antenna elements are the major drawbacks of such CAA synthesis method with nonuniform excitation, because the complex excitation is practically difficult to realize and designing the practical antenna with high DRR of static amplitude tapering provides various errors such as systematic errors and random errors.
\nConversely, the ultralow SLL pattern in the far-field of the antenna array can be realized even in uniform amplitude antenna arrays by exploiting “time” as a fourth dimension [2, 3]. The introduction of the additional dimension “time,” into the antenna array system, results in time-modulated antenna array (TMAA). By using the fourth degree of freedom, “time” in antenna array system, various errors in realizing the low SLL pattern can be drastically reduced, and error tolerance levels become equivalent to those obtained in conventional antenna array system for the patterns of ordinary SLLs [4, 5]. Yet, the main disadvantage in TMAA is the generation of sideband signals which appeared due to the time modulation of the antenna signals by periodically commutating the antenna elements with the specified modulation frequency. Therefore, time modulation involves with the radiation or reception of electromagnetic energy at different harmonics of the modulation frequency that are termed as sidebands. In some applications where the antenna array is synthesized at center (operating) frequency, sideband signals are not useful. In such cases, sideband signals and associated power losses are suppressed to improve the radiation efficiency at the operating frequency of the antenna array [5, 6]. Presently, it is investigated that sideband signals are also effective in synthesizing multiple patterns and researchers are interested to exploit the same in some specific applications of the modern-day communication systems like harmonic beam forming [7], generation of multibeam radiation pattern [8], beam steering [9, 10], direction finding [11], wireless power transmission [12], etc. The interested readers may refer to Reference [13] for the state-of-the-art overview, applications, and present research trend on time-modulation theory and techniques.
\nThis chapter explains about the fundamental theory and techniques of different time-modulation strategies and such antenna array synthesis methods using optimization algorithms. The parameters involved with the use of optimization techniques and TMAA synthesis problem have also been presented.
\nLet us consider a linear antenna array of N number of mutually uncoupled isotropic radiators with inter-element spacing d0. The antenna elements are placed along the x-axis with the first element at the origin of the geometrical coordinate system as shown in Figure 1. In the XZ plane (one of the vertical principle plane), the array factor expression of CAAs can be obtained as in Eq. (1) [1]:
\nBasic antenna array of N element with inter-element spacing of d0.
where ω0 = 2πf0 = 2π/T0 is the angular frequency in rad/sec for the operating signal of frequency f0 in Hz; T0 is the time period of the operating signal; β = 2π/λ is the wave number with λ being the wavelength; p = 1, ……, N represents the element number of the antenna array; Ap and Фp\n
In order to control the antenna pattern by using the additional degree of freedom, namely, “time,” periodically the static excitation amplitudes of the antenna element are time-modulated. The commonly used and simplest way of doing that is to insert high-speed radio-frequency (RF) switches in the feed network, just prior to radiating sources as shown in Figure 2. Each array element is assumed to be connected to the RF switches with individually controlled switching circuits. The switches are periodically “on” and “off” according to a predetermined on-time sequence \n
Time-modulated linear antenna array (TMLAA) geometry.
Let us further assume that all the switches corresponding to the antenna elements in Figure 2 are on (short circuited) at the same instant of time, say at the beginning of each period “η*Tm” with “η” being the time period number 0, 1, 2,…, by using rectangular pulses of amplitude unity. Hence, the switches which are on for the whole time period Tm as shown in Figure 3(a) can be directly connected to the signal as time modulation is not required for such cases. On the other hand, the switches remained short circuited for their specific on-time duration and open circuited after their corresponding on-time duration (\n
The periodic pulse sequence of the TMLAA. (a) Unit pulse of periodicity TP. (b) On–off time duration of each antenna elements for one time-modulation period TP, and it is repeated at every TP time interval.
After the switching operation, the array factor expression of Eq. (1) can be written as in Eq. (3) [2]:
\nwhere \n
where \n
where \n
Putting Eq. (4) in Eq. (3), the array factor expression of Eq. (3) is obtained as
\nThus, Eq. (6) expresses that the signal is not only radiated at the operating frequency, ω0 for k = 0, but also the signals are radiated at different harmonics of the modulating frequency, kωm, with ω0 as the center frequency. The signal radiation at different harmonics is termed as sideband radiation (SBR). For such a TMLAA, the array factor expression at kth harmonic of the modulation frequency is readily obtained by combining Eqs. (5) and (6) as
\nTherefore, the array factor at the fundamental frequency, i.e., at operating frequency (for \n
From Eq. (8), it can be observed that τp’s\n
It can be observed from Eqs. (7)–(10) that, due to time modulation, the sideband signals inherently appeared around the center frequency spaced in multiples of the modulation frequency. In this section, the characteristics of harmonic signal radiated by an arbitrary time-modulated element are observed by varying the normalized switch-on time for its complete range from 0 to 1. Then by defining relative and normalized sideband power, the effects of reducing SLL on the first null beamwidth (FNBW) and maximum sideband power level are observed.
\nFrom Eq. (7), we can see that the array factor at different sidebands is the superposition of the harmonic signal radiated from the individual antenna element. Hence, sideband power pattern and total sideband power can be obtained from the harmonic characteristics of the time-modulated elements as expressed in Eq. (5). The normalized harmonic radiation of the individual time-modulated antenna element is given as [15]
\nwhere hpk is the normalized/relative harmonic radiation corresponding to the pth element. The variation of normalized harmonic power of the first three harmonics (k = 1, 2, and 3) with normalized switch-on time, τp, over its complete range (0, 1) is shown in Figure 4. As can be seen, at the lower value of τp, all hpkmax are almost the same, and for τp → 0, all hpkmax are exactly equal to 0 (zero) dB as it is expected from the Fourier series of unit impulse function. However, at the other extremes of τp, when τp → 1, all hpkmax → −∞, which is the predicted result as can be seen in Eqs. (5) to (10), with k = 1, 2, and 3. Again there is no radiation at hp2 for τp = 0.5 and at hp 3 for τp = 0.3 and 0.66 which can also be verified from Eq. (5) with k = 1, 2, and 3. Thus, Figure 4 indicates that the contribution of the harmonic component from a particular element to produce the sideband pattern depends on the on-time duration of the corresponding element. Therefore, the desired sideband power pattern can be synthesized in TMAAs by judiciously controlling the on-time sequence of the time-modulated antenna elements.
\nVariation of the first three harmonic powers from an antenna element with normalized switch-on time, τp.
Usually in TMAA, the radiation pattern is synthesized at center frequency by suppressing the sideband radiation level to sufficiently low value. Thus, the maximum of the power radiated at f0 is used to normalize the corresponding power pattern at center frequency. On the other hand, the sideband power is divided by the maximum power at f0 to measure the relative power level at different sidebands with respect to that of the radiation at center frequency. In this regard, the relative signal power radiated at different harmonics (k ≠ 0) is measured as in Eq. (12):
\nwhere “SBLk” represents the relative value of sideband level at kth harmonic (k = 1, 2, …), i.e., relative value of the array factor AFk in dB, and “max (AF0 (θ, t))” is the maximum value of the array factor at operating frequency ω0, i.e., the maximum radiation level at k = 0. Thus, with k = 0, Eq. (11) gives the normalized power pattern for the center frequency pattern, whereas, for the sideband radiations (with k ≠ 0), it is the relative power with respect to the maximum of the center frequency pattern.
\nIt is understood that in addition to the desired operating frequency (center frequency), TMAAs also radiate signals at the infinite number of different harmonics of the modulation frequency. When the desired power pattern is synthesized at the center frequency, the sideband power is wasted. In this section, the influences on the first null beamwidth (FNBW) and sideband radiation by reducing SLL of the center frequency pattern are observed. The SLL of the power pattern at f0 is reduced by using the conventional amplitude tapering technique, namely, Dolph-Chebyshev (DC) [1], and a heuristic search global optimization method, namely, genetic algorithm (GA) [16].
\nThe conventional antenna array synthesis technique such as Dolph-Chebyshev (DC) method [1] can be directly used to realize power pattern of the desired value of SLL at the center frequency. For a 30-element uniformly excited (UE) TMAA, the equivalent excitation coefficient of the DC pattern of desired SLL is made equal to the normalized on-time duration of the array elements. Following the DC method, the power pattern of different values of SLL is obtained at the center frequency.
\nIn order to reduce the SLL at the center frequency pattern using optimization technique, a cost function is required. A well-defined cost function of any optimization problem is important to obtain satisfactory performance. The cost function measures the distances between the desired and obtained values of the radiation parameters which are to be controlled. During the optimization process, the algorithms compare the obtained values of the radiation parameters with those of their respective desired values. Without considering sideband radiation and FNBW, the cost function to realize the patterns of desired SLLs at f0 is defined as
\nwhere SLLmax is the actual value of the SLL as obtained during each trial of the optimization process and SLLd is its desired value. Any heuristic search global optimization method can be employed to reduce the SLL of the power pattern at f0. Here, one of the useful stochastic search global optimization methods, namely, genetic algorithm (GA), is used to synthesize the power pattern of different values of SLL of the array under consideration [17].
\nIt can be seen from Eqs. (5)–(10) that the Fourier coefficients and hence amplitudes of the harmonic signals are decreasing gradually with increasing harmonic order. Thus, the radiation energy at the first few harmonics (called sidebands) is most significant. So, the influence on the maximum radiation at the first two harmonics of TMAA is observed by reducing the SLL of the center frequency pattern. Firstly, the SLL of the power pattern at f0 is reduced by using the Dolph-Chebyshev (DC) method [1]. Then a global optimization method is used to synthesize the same pattern as obtained via DC. In order to observe the effects of reducing SLL on SBL and FNBW, these values are noted for different power patterns. Table 1 shows the simulation results of the maximum sideband level (SBLmax) at the first and second harmonics for the fundamental pattern with different values of maximum SLL (SLLmax) ranging from −15 dB to −55 dB. The radiation pattern at f0 as obtained by GA and DC with SLL of −55 dB is shown in Figure 5. The first null beamwidth (FNBW) for different values of SLLmax of the main beam radiation pattern has been noted and is plotted in Figure 6. The maximum two harmonics are normalized with respect to the maximum value of the radiation at f0. For the different values of SLLs, the change in SBLmax at the first and second harmonics is shown Figure 7. Since, the Dolph-Chebyshev (DC) method gives the optimum pattern, i.e., the pattern with minimum FNBW for a specific value of SLL or vice versa. For the DC patterns of different SLLs, the corresponding FNBW, SBL1(max), and SBL2(max) are also given in Table 1. The plot SLL vs. FNBW is shown in Figure 6, and that for SLL vs. SBLmax is shown in Figure 7. Figure 6 depicts that for the DC method, FNBW is linearly increased when |SLLmax| is enhanced, whereas Figure 7 shows that SBL1max initially decreases from −3.35 dB and obtained its minimum value of −13.36 dB at −25 dB SLL pattern. Thereafter, it gradually increases and becomes almost steady at −12.5 dB after −30 dB SLL. From Figures 6 and 7, it can be seen that for the GA-based patterns of different SLLs, SBLmax and FNBW vary randomly as in the cost function, only SLL is considered without controlling FNBW and SBL.
\nThe patterns at f0 by DC | \nThe patterns at f0 by GA | \n||||||
---|---|---|---|---|---|---|---|
SLLmax (dB) | \nFNBW (deg) | \nSBL1(max) (dB) | \nSBL2(max) dB) | \nSLLmax (dB) | \nFNBW (deg) | \nSBL1(max) (dB) | \nSBL2(max) (dB) | \n
−15 | \n7.2 | \n−3.35 | \n−8.30 | \n−15.06 | \n8.4 | \n−10.01 | \n−17.91 | \n
−20 | \n8.4 | \n−7.2 | \n−17.83 | \n−20.03 | \n9.6 | \n−9.95 | \n−17.06 | \n
−25 | \n9.8 | \n−13.36 | \n−20.25 | \n−25.78 | \n10.4 | \n−8.51 | \n−14.27 | \n
−30 | \n11.2 | \n−12.28 | \n−19.31 | \n−30.28 | \n12.0 | \n−9.98 | \n−14.75 | \n
−35 | \n12.4 | \n−12.42 | \n−17.45 | \n−35.66 | \n17.2 | \n−12.19 | \n−17.39 | \n
−40 | \n13.8 | \n−12.42 | \n−17.45 | \n−40.04 | \n19.0 | \n−6.058 | \n−13.13 | \n
−45 | \n15.2 | \n−12.59 | \n−17.40 | \n−43.76 | \n20.2 | \n−10.12 | \n−14.572 | \n
−50 | \n16.6 | \n−12.58 | \n−17.40 | \n−50.52 | \n22.4 | \n−7.301 | \n−12.7870 | \n
−55 | \n18.0 | \n−12.55 | \n−17.37 | \n55.6 | \n23.6 | \n−7.3 | \n−12.9 | \n
Radiations maximum at the first two sidebands and FNBW for the fundamental patterns of different values of SLL.
GA- and Dolph-Chebyshev-based pattern of SLL of −55.6 dB at f0.
FNBW for different values of SLLs of the GA and Dolph-Chebyshev patterns at f0.
The plot of SBR1(max) and SBR2(max) for the different values of SLLs of the patterns at f0.
Different time-modulation strategies have been reported for synthesizing antenna arrays. These can be classified as (1) variable aperture size (VAS); (2) pulse shifting; (3) binary optimized time sequence (BOTS); (4) subsectional optimized time steps (SOTS); (5) variable aperture size (VAS) with quantized on-time (VAS-QOT) or quantized aperture size (QAS); and (6) nonuniform period modulation (NPM). From the array factor expression as given in Eq. (6), it can be observed that for TMAA, the array factor at different harmonic can be obtained if the Fourier coefficients of different time-modulated elements are known. Therefore, in the following sections, along with the brief description of different time-modulation approaches, the Fourier coefficients of time switching elements under the respective time-modulation scheme are presented.
\nThis is the first type of time-modulation strategy as reported in [2] where the aperture size of the antenna array is varied with time. The time-modulation principle as discussed in Section 2 falls under this category.
\nIn VAS time-modulation scheme, only the switch-“on” time duration is considered for deriving the array factor expression. However, when the RF switches are used to commutate the antenna elements in TMAAs, the radiation patterns at center frequency as well as at different harmonics depend not only on the switch-on time duration but also on the switch-“on” and switch-“off” time instants of the array elements [18, 19]. Thus along with the switch-on time durations as considered in VAS scheme, switch-on and switch-off time instants are also taken as another degree of freedom to control the power pattern in TMAA. For the pulse shifting strategy, periodic switching instants of the pth element over the modulation period are shown in Figure 8. In this case, both on-time instant \n
Switching instants defining pulse shifting strategy under two cases.
Hence, the normalized switch-on time duration, τp, is given as \n
Another possible situation may appear as shown in Figure 8(b) where \n
The complex Fourier coefficient for the pulse shifting strategy at kth harmonic due to the pth element under the two cases can be obtained, respectively, as [14].
\nBy taking into account the additional degree of freedom, namely, on-time instants of the antenna elements, improved array patterns can be observed. For example, more sideband reduction as compared to VAS approach is obtained when the same array pattern is synthesized at the center frequency [18, 19], and electronic beam steering [9] and harmonic beam patterns of different shapes [7, 8] can be realized without phase shifters.
\nIn binary optimized time sequence (BOTS), the switch-on time duration of an arbitrary pth element is divided into Q number of minimal time steps of equal length over a modulation time period Tm [20] as shown in Figure 9. The minimal time step, t0, is given by
\nSwitching function defining binary optimized time sequence (BOTS) strategy.
The periodic on–off sequence of the set of time steps corresponding to the pth element is represented by the switching function Up(t). If the on–off status of qth time step for the pth element is symbolized with a binary bit, \n
The complex Fourier coefficient of pth element at kth harmonic with the BOTS switching scheme can be obtained as [20]
\nwhere \n
In SOTS-based switching strategy, the time-modulation period (Tm) is divided into a number of subsections with variable lengths [21]. Let us assume that Tm is divided into Q number of time steps as shown in Figure 10 for the switching strategy of pth element of the array. For the qth time step, the on and off time instants of the switch are denoted by \n
The schematic of the periodic pulse sequence for SOTS switching strategy of the pth element of TMLAA.
The Fourier coefficient at the kth harmonics for the pth element can be written as
\nwhere \n
It can be observed that, if the number of subsections Q is 1, then SOTS is transformed into pulse shifting-based strategy. On the other scenario, if the on-time duration at each step, i.e., the separation between the on and off time instants, becomes multiples of \n
In Section 3, the different patterns of desired values of SLL at f0 are obtained by making the on-time sequence equal to the Dolph-Chebyshev coefficient of the corresponding patterns. Thus the appropriate set of on-time sequence is required to generate the desired pattern even in uniformly excited TMAAs.
\nIn this section, to generate different patterns in time-modulated antenna arrays (TMAAs) instead of considering continuous value of on-time duration [22], the modulation period is divided into a number of equal steps as in BOTS. However, in BOTS, multiple switching of on–off over the modulation period is considered. Such multiple changes of switching states over the modulation period need fast and complex switching circuit. Unlike BOTS, in this modulation scheme, the on–off states of the switches are assumed to change once over the complete modulation period like VAS. However, the on–off states of the switches are rounded off to the nearest quantization step to obtain quantized on-times (QOTs) of the corresponding elements as shown in Figure 11. In this time-modulation scheme, the time-modulation period, Tm, is quantized into “Q” number of discrete levels. At qth quantization level, the value of tq is given by q*(Tm/Q), where q = 1, 2… Q. The allowable on-time \n
The proposed time-modulation approach for the quantized on-time of the switches.
In all of the abovementioned switching strategies, all antenna elements are modulated with the same modulation frequency, ωm, and such time modulation is termed as uniform period modulation (UPM). Time-modulated antenna array (TMAA) based on UPM is commonly known as uniform TMAA (UTMAA). On the other hand, if the antenna elements of the array are time-modulated with different modulation frequencies as shown in Figure 12, it is defined as time modulation with nonuniform period modulation (NPM), and the corresponding array is defined as nonuniform TMAA (NTMAA) [23, 24]. Let us consider that the antenna elements are modulated with different modulation periods \n
Time-modulated array architecture with NPM switching strategy where f1 ≠ f2 ≠ … ≠ fN.
where \n
And finally, Fourier coefficient at the kth harmonics for the pth element is obtained as [24].
\nLet \n
where \n
The first summation indicates that the signals radiated at the center frequency \n
But in the case of NTMAA, the modulation frequencies are selected in such a way that f1 ≠ f2 ≠ … ≠ fN. So, due to different modulation frequencies of different antenna elements, the signals radiated from different harmonics appeared at different frequencies, and the term kfp in the second summation of [25] becomes different for different elements. That means the kth-order harmonics of different elements appear at different frequencies and the scenario is the same for all the other order harmonics. So, unlike UTMAA, the harmonic signals appeared at different frequencies and are distributed in space, which in turn decreases the resultant SBL [23]. Recently, some research works have reported the calculation of the sideband power of NTMAA [24, 25], and also the reduction of the sideband power losses using NTMAA is investigated [26].
\nIn Section 3.3, it is observed that, though the conventional amplitude tapering methods such as Dolph-Chebyshev and Taylor series can be used to obtain the power pattern of the desired SLL with minimum beamwidth at the operating frequency of time-modulated antenna arrays, these methods are not useful to control the undesired power radiated at different sidebands. Similarly, it is also observed that application of the stochastic computational technique, such as GA, for suppressing side lobe level of the center frequency pattern without taking into account the sideband radiation, cannot reduce sideband signal power. Also, the beamwidth of such patterns is unpredictable. The power pattern with low SLL and suppressed sideband is preferred for the different communication systems.
\nTherefore, the parameters to be considered to synthesize pencil beam pattern in TMAAs as shown in Figure 5 are SLL, FNBW, and SBL. However for the shaped beam pattern such as flattop and cosec squared, in addition to these three parameters, ripple level in the desired shaped region is another parameter to be taken into account. Further, it can be observed that while SLL is reduced, FNBW is increased and SBL is significantly large. In this regard, SLL, SBL, and FNBW for pencil beam pattern and SLL, SBL, FNBW, and ripple level for synthesizing shaped beam patterns are the conflicting parameters.
\nIn Eq. (13), the cost function is defined to synthesize the power pattern with a single objective that is to achieve the desired value of SLL in the synthesized power pattern. Conversely, the synthesized pencil beam patterns at the operating frequency should have reduced SLL along with sufficiently suppressed SBL and narrow beamwidth. Thus, TMAA synthesis problems are multi-objective optimization problems where the multiple objectives are low SLL and narrow beamwidth (BW) of the main beam at operating frequency and low value of maximum sideband level (SBLmax) for synthesizing pencil beam pattern while one more objective is low ripple level for synthesizing shaped beam patterns.
\nTMAA synthesis problem is non-convex and nonlinear in nature. A number of numerical techniques as already mentioned—Dolph-Chebyshev and Taylor series [1]—are available to synthesize pencil beam power pattern in conventional antenna arrays (CAAs). Also, some analytical methods are reported to generate shaped beam patterns and phase-only controlled multiple power patterns in CAAs [27, 28, 29]. Durr et al. described a modified Woodward-Lawson technique to design phase-differentiated multiple pattern antenna arrays with prefixed amplitude distributions [27]. The analytical technique reported in [28] is used to determine the nonlinear phase distribution of linear arrays. A method based on projection approach [29] is proposed to synthesize reconfigurable array antennas of a cosecant2 beam and a flattop beam (FTB) by using a common amplitude with phase-only control of analog phase shifters. Though these numerical and analytical techniques can also be applied to determine the nonlinear distributions of dynamic excitation coefficient and phase to synthesize power pattern at operating frequency of TMAAs, such methods have no control on sideband power level. Therefore, the powerful global stochastic optimization tools such as genetic algorithm (GA) [30], differential evolution (DE) [4, 5, 31, 32], particle swarm optimization (PSO) [7], simulated annealing (SA) [6, 33], and artificial bee colony (ABC) [22, 34] are essentially required to solve such multi-objective TMAA synthesis problems.
\nMost of the TMAA synthesis problems are solved by applying single-objective optimization method where all the objectives are added with different weighting factors to form a single cost function and the cost function is minimized by employing heuristic evolutionary algorithms. The different stochastic optimization techniques are used with the objective to synthesize desired patterns at the operating frequency by reducing SLL and SBL. One of the commonly used techniques to define the cost function of such conflicting multi-objective TMAA synthesis problem is as expressed in Eq. (26):
\nwhere \n
In Eq. (26), all the objectives are added with different weighting factors to form a single cost function. In such techniques, it is tedious and difficult to select proper weighting factor for the optimal solution. Improper set of weighting factors strongly effect on achieving the final values of the desired synthesizing parameters and hence on the performance of the optimization algorithm. Generally, some selected best results are presented without mentioning such difficulties. However, these values of the weighting factors are obtained by trial and error method [4]. Though multi-objective evolutionary algorithm (MOEA) [35, 36] can be used to solve such problems, the researchers are not comfortable with it as it has been used rarely as compared to single-objective optimization approaches.
\nIt is already discussed that time-modulated antenna array synthesis problems are non-convex as well as nonlinear. Therefore, stochastic, global computational techniques are required to solve such problems. In this regard, different population-based global searching techniques such as DE, SA, GA, PSO, ABC, and multi-objective evolutionary algorithm (MOEA) have been applied successfully to synthesize the desired pattern at the center frequency by suppressing sideband radiation to satisfactorily low levels. However, here the working principle of ABC and its implementation have been presented, and a novel approach to synthesize TMAA is discussed.
\nIn Section 4.5, the quantized aperture size (QAS) time modulation or variable aperture size with quantize on-time duration has been explained. In this section first to realize such time-modulation approach, a time modulator, namely, quantized time modulator (QTM), is presented. Then it is shown that though the quantized on-time duration has been used, however, by selecting a suitable number of quantization levels, the effect of quantization errors on the synthesized patterns can be reduced. In order to select the best possible set of quantized on-time values, the potentiality of artificial bee colony algorithm (ABC) has been exploited as the global searching algorithm. Thus, for the desired patterns, ABC finds the optimum set of unknown parameter values from the discrete search space of QOT. The synthesized results as obtained by using this quantized on-time are compared with that achieved by using continuous search space of on-time [6, 33]. Finally, considering the discrete search space of QOT, a low side lobe level (SLL) flattop pattern with low dynamic range ratio (DRR) is synthesized by utilizing a fully digitally controlled QTM. The major advantage of this approach is that by implementing the “time modulator” either as a discrete component on a printed circuit board or in an integrated circuit (IC), it can generate different patterns in the TMAA system.
\nFor appropriate switching operation at pth element, a current pulse with a pulse width of \n
The proposed quantized time modulator (QTM).
The wave form of the input and output pulses of different pulse widths that can be obtained at the outputs Oq\n\n∀\nq\n∈\n\n1\n…\nQ\n\n\n in Figure 13.
One of the most important features in TMAAs is to reconfigure different antenna patterns just by changing the on-time sequence across each element. Such a feature can easily be obtained in the proposed QTM employing PWS. The PWS consists of N number of (Q × 1) multiplexers and their outputs that are used to modulate antenna element using the quantized values of \n
Karaboga [37] introduced the artificial bee colony (ABC) algorithm to simulate intelligent food foraging behavior of the honeybee swarm. The ABC algorithm shows excellent performance for optimizing multivariable functions as compared to other similar algorithms like genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). ABC is a robust search and optimization algorithm with relatively fewer control parameters [38]. Although GA is extensively used due to its efficiency to solve the optimization problems with binary/discrete variables, it requires high computational time as well as high memory consumption to store unnecessary binary data during the conversion of a real number to binary and vice versa. The decoding method as applied in ABC algorithm requires one-line MATLAB code which directly quantizes continuous values of the variables by rounding off them. The food foraging behavior of real bees and the implementation of the algorithm have been briefly discussed in the following section.
\nThe constituents of the food foraging systems are the unemployed bees (UBs) and the employed bees (EBs) in a beehive and food sources (FSs) in their surroundings. Initially, all the bees are unemployed, and after they find a rich food source, they become employed. UBs are categorized into scout bees (SBs) and onlooker bees (OBs). The food foraging process is initiated when the SBs start to explore the rich food source randomly from any location by moving toward any direction of the search space. When SBs find a rich food source, it becomes an EB and returns to the hive to attract other bees by performing a special dance known as the waggle dance. Depending on the quality of the food source, the EBs recruit some bees to extract nectar from the source. The EBs abandon the current food source when the nectar of the source is finished and becomes scout bees (SBs). However, in the dancing area, OBs examine the quality and quantity of the food sources with the information provided by the EBs, and after examinations EBs select a food source. Thus during the food foraging process, exploration is carried out by SBs, and exploitation is carried out by EBs and OBs. Due to the presence of both exploration and exploitation, ABC becomes a robust search and optimization algorithm. It is to be noted that the objective of the bees in ABC is to find out the location of the best possible food sources within the search space. Hence, the possible locations of the food sources are the possible solutions to this process. But in other swarm intelligence algorithms, e.g., particle swarm optimization (PSO), the locations of the individual agents are the possible solution within the search space. It is assumed that the number of employed bees (NE) and number of onlooker bees are equal in the colony and also these are equal to the number food sources (FN).
\nIn the following steps, the real bee colony behavior into the problem space is implemented:
Specifying objective: The objective is to synthesize far-field patterns at f0 by simultaneously minimizing SLL, SBLmax, and first null beamwidth (FNBW) or ripple (R).
Parameters to be optimized: Depending on the requirement in an array synthesis problem, suitable independent parameters are chosen as the optimization parameter vector χ. The number of parameters in χ represents the dimension (D) of the specific optimization problem.
Defining the cost function: According to the design parameters discussed above and multiple objectives of the synthesis problem, the cost function is defined as
where δh with h = 0, 1, and 2 are the instantaneous values of different parameters of the desired patterns, while δhd is the desired values of the specific parameters. For all examples as considered in Section 8, δ0 is the maximum SLL (SLLmax) of the pattern at f0 and δ1 is the value of SBLmax among the first five sidebands. But, for the first two examples, δ2 represents FNBW, and, for the third case, it is the ripple level of the flattop pattern for which the positions of δhd and δh are interchanged in the Heaviside step function \n
Initialization: The possible solution, χi, where i = 1, 2… FN, of an arbitrary number of food sources is generated randomly within the search space. With FN possible locations, each with D dimension is expressed in terms of a [FN × D] matrix.
Evaluating the quality of the food source: For all the possible solutions, the values of ψ and the corresponding fitness values, μi, are evaluated.
Employed bees’ stage: The greedy nature of the employed bees (EBs) is incorporated, and the new sources (si) surrounding its neighborhood are generated as follows:
where j\n
Onlooker bees’ stage: The quality of the food source is represented by the fitness value, μi, of the cost function, and onlooker bees select the new source by means of the probability, \n
where μmax is the maximum fitness value among the current possible solutions. Like employed bees (EBs), the greedy selection is also applicable to onlooker bees(OBs).
Scout bees’ stage: In this stage, the abandonment of a food source by the employed bees is simulated. If the fitness value of the cost function is not improved during a specified number of steps called “limit = FN*D” [25], it is ignored, and the parameter, \n
\n
Remembering the best solution: The overall new best solution as mentioned in the steps “e–h” replaces the previous best, and the value is then stored.
Stopping criterion: Steps “(e)” to “(i)” are repeated until the cost function converges to the desired value or a predetermined value of maximizing the number of cycles (MNC).
The VAS-based synthesis problems that have been reported in [6, 33] are considered at first, and the QAS-based time-modulation approach is applied to realize the patterns. Here, the modulation period Tm is quantized in 10 equal discrete levels, i.e., Q = 10. Hence, the discrete search space for the optimization problem (τp) becomes {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1}.
\nExample 1: A 30-element UE TMLAA is placed along the x-axis with one element at the origin, and a uniform inter-element spacing of 0.7λ is considered. It is desirable in practice for such an array to feed with {Ap} = 1 and {\n
ABC optimized power pattern obtained by using the discrete value of τp of Table 2.
Element numbers (p) | \nτp | \n
---|---|
1 | \n1 | \n
2 | \n0.30 | \n
3 | \n0.10 | \n
4–22 | \n1 | \n
23 | \n0.90 | \n
24 | \n0.90 | \n
25 | \n0.10 | \n
26 | \n0.10 | \n
27 | \n0.10 | \n
28 | \n0.90 | \n
29 | \n0.10 | \n
Optimum discrete values of \n
Example 2: In the second example, the synthesis problem as discussed in [33] is considered. From the list of static and dynamic excitations of one-half of the linear arrays as presented in Table 3, Ref. [33], it was found that out of the five edge elements, only three are time-modulated to synthesize the sum pattern, whereas, for the difference pattern, time modulation is applied only on four center elements. In this work, to synthesize the sum and difference pattern, the proposed method is applied in the following way. For the UE TMLAA, the sum pattern is synthesized by taking the discrete τp values of five edge elements (in one-half of the array) as “χ.” In order to compare the ABC optimized results with those of SA, during optimization, the three lower values of τp are rounded off to their nearest quantization levels, whereas the higher two τp values are kept to 1 so that the ABC optimized pattern is obtained by time modulating the same number of (i.e., three) elements as observed in SA. However, to synthesize the difference pattern, perturbation of discrete τp values of four center elements are considered. In Eq. (27), the same values of δhd’s as used in Example 1 are set. Figures 16 and 17 show the ABC optimized sum and difference patterns, respectively. For optimizing the sum and difference pattern with NE = 30 and limit = 450, the ABC takes only 23 and 5 iterations, respectively (refer to Figure 18). The corresponding optimum discrete values of τp are shown in Table 3. It can be observed that the sum and difference pattern is obtained by time modulating the same number of elements as found in [33]. As compared to [33], SLLmax and SBLmax of the sum pattern are improved by 2.03 and 1.5 dB, respectively. In case of difference pattern, the SBLmax is reduced by 2.37 dB with only 0.37 dB rise in SLL. Also, for both the sum and difference patterns, the amount of sideband power is found to be 3.35% and 4.69% of the total power which are 4.30% and 5.45% in the respective patterns of [33]. The FNBW of ABC optimized sum pattern and difference pattern was found as 6.12 and 4.56°, respectively, which are quite comparable to 5.88 and 4.59° as for the patterns in [33].
\nElement numbers | \n1 & 30 | \n2 & 29 | \n3 & 28 | \n4 & 27 | \n5 & 26 | \n6–11 & 25–20 | \n12 & 19 | \n13 & 18 | \n14 & 17 | \n15 & 16 | \n|
---|---|---|---|---|---|---|---|---|---|---|---|
τp | \nSum pattern | \n1 | \n1 | \n0.2 | \n0.9 | \n0.1 | \n1 | \n1 | \n1 | \n1 | \n1 | \n
Difference pattern | \n1 | \n1 | \n1 | \n1 | \n1 | \n1 | \n0.1 | \n0.9 | \n0.3 | \n0.1 | \n
Optimum discrete values of τp of ABC optimized sum and difference pattern, as shown in Figures 12 and 13.
ABC optimized sum pattern as obtained by time modulating the same percentage (20%) of elements as in [33]. SLL and SBLmax of the pattern are obtained as −17.87 and −31.44 dB, respectively.
ABC optimized difference pattern as obtained by time modulating the same percentage (26.7%) of elements as in [33]. SLL and SBLmax of the pattern are obtained as −16.05 and −31.44 dB, respectively.
Convergence characteristics of ABC for the synthesized sum and difference patterns of Figures 5 and 6.
Figure 19 shows SBLs of the first 30 sidebands for the synthesized patterns as considered in Example 1 and Example 2. It can be observed that at the higher sidebands also, the SBLs are below SBLmax. Further observation shows that the no radiation is produced at 10th, 20th, and 30th sideband with quantized values of τp as at these harmonics the array factor expression becomes zero for all elements.
\nSideband levels of the first 30 sidebands for the different patterns in examples 1 and 2.
Example 3: In this example, it is shown that the same time modulator can also be used to synthesize a flattop pattern. Accordingly, a symmetrical TMLA with element number N = 20 and inter-element spacing d0 = 0.5λ is considered. Here, the objective is to synthesize a flattop pattern in the broadside direction with digitally controlled static excitation amplitudes and phases by using five digital attenuators and phase shifters. A flattop pattern with a beamwidth of 30°, maximum ripple level (Rmax) at the flat region of less than 1 dB, and transition width of 8° is selected as the target pattern. Although such pattern with more stringent design specification is reported in [6], analog attenuators and phase shifters are required. Due to symmetry, the dimension of the parameter vector χ = {Ap, \n
ABC optimized space pattern at f0 and the first 30 sidebands. At f0, the flattop pattern is obtained with SLL, SBLmax, and Rmax of −29.31, −29.9, and 1.22 dB, respectively.
Element numbers (p) | \nNormalized on-time, τp | \nDiscrete values of excitation | \n|
---|---|---|---|
Amplitude, Ap | \nPhase, \n | \n||
1 & 20 | \n0.65 | \n0.200 | \n−33.75 | \n
2 & 19 | \n0.95 | \n0.325 | \n−22.50 | \n
3 & 18 | \n0.95 | \n0.475 | \n0 | \n
4 & 17 | \n1 | \n0.525 | \n33.75 | \n
5 & 16 | \n1 | \n0.675 | \n67.50 | \n
6 & 15 | \n1 | \n0.975 | \n90 | \n
7 & 14 | \n1 | \n1 | \n112.50 | \n
8 & 13 | \n1 | \n0.800 | \n135 | \n
9 & 12 | \n1 | \n0.600 | \n−180 | \n
10 & 11 | \n1 | \n0.700 | \n−146.25 | \n
Optimum discrete values of Ap, \n
In the continuous search space of VAS time-modulation method [2, 3, 4, 5, 6], the on-time duration of array elements can be of any value between 0 and Tm. In [2], for each time-modulated elements, the current pulse required with pulse width over the range of (0.1Tm < \n
Introduction of the additional degree of freedom “time” provides flexibility in synthesizing antenna array patterns and overcomes the shortfalls of realizing the patterns through conventional array synthesis methods. Among the different time-modulation strategies, QAS can be realized through a simple digital circuit consisting of a pulse generator, simple tapped delay line with equal delay at each tap output, flip-flops, and multiplexers. This circuit can be implemented in either an integrated circuit (IC) form or in a printed circuit board and can be used as a discrete component to generate different patterns. However, as far as the nonuniform period modulation is concerned, the function of the quantized time modulator (QTM) circuit needs to be investigated, specifically to time modulate the elements with multiple frequencies which need accommodation of multiple PLLs in the circuit for the multiple frequencies. Regarding other time-modulation approaches, complexity in the switching circuit increases as per the sequence, VAS, pulse shifting, BOTS, SOTS, and NPM, respectively, while their performance in synthesizing low SLL power patterns with suppressed SBL follows the reverse order. Thus, for a time-modulation approach, the improved performance in terms of the capability of synthesizing low side lobe power patterns by suppressing harmonic signal level is obtained at the cost of complex switching mechanism. However, due to the advancement in the semiconductor technology, availability of high-speed semiconductor switches makes it possible to realize such complex switching mechanism by writing simple program code in complex programmable logic devices (CPLDs).
\nIn all the time-modulation approaches except NPM, for the desired power pattern, optimization algorithm is required to determine the proper set of on-time sequence. The construction of suitable cost function with multiple objectives such as narrow beamwidth; low values of SLL and SBL, etc.; and the selection of corresponding weighting factors plays an important role to achieve the best possible power patterns. This chapter gives a brief fundamental insight toward all this issues.
\nThis work is financially supported by the Ministry of Electronics and Information Technology (MeitY), Govt. of India, under Visvesvaraya Young Faculty Fellowship of Visvesvaraya Ph.D. scheme (Grant No. PhD-MLA-4(29)/2015-2016) and DST-SERB project ref. file number EEQ/2016/00836, dated January 17, 2017.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. 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