Effect of the adaptation of the power applied on the color of the dried product.
\r\n\tThis book intends to cover major mineral deficiency problems such as calcium, iron, magnesium, sodium, potassium and zinc. These minerals have very important task either on intracellular or extracellular level as well as regulatory functions in maintaining body homeostasis.
\r\n\r\n\t
\r\n\tBoth macrominerals and trace minerals (microminerals) are equally important, but trace minerals are needed in smaller amounts than major minerals. The measurements of these minerals quite differ. Mineral levels depend on their uptake, metabolism, consumption, absorption, lifestyle, medical drug therapies, physical activities etc.
\r\n\tAs a self-contained collection of scholarly papers, the book will target an audience of practicing researchers, academics, PhD students and other scientists. Since it will be published as an Open Access publication, it will allow unrestricted online access to chapters with no reading or subscription fees.
",isbn:"978-1-83881-085-6",printIsbn:"978-1-83881-081-8",pdfIsbn:"978-1-83881-086-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"8bc7bd085801296d26c5ea58a7154de3",bookSignature:"Dr. Gyula Mozsik and Dr. Gonzalo Díaz-Soto",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8935.jpg",keywords:"Calcium, Iron, Magnesium, Potassium, Sodium, Zinc, Diagnostic tools, Treatments, Food Fortification, Malnutrition, Metabolic Disorders, Lifestyle",numberOfDownloads:741,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 26th 2020",dateEndSecondStepPublish:"June 16th 2020",dateEndThirdStepPublish:"August 15th 2020",dateEndFourthStepPublish:"November 3rd 2020",dateEndFifthStepPublish:"January 2nd 2021",remainingDaysToSecondStep:"9 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Professor Emeritus of Medicine at Univesity of Pecs, Hungary, and recipient of Andre Roberts award from the International Union of Pharmacology in 2014. He published 360 peer-reviewed papers, 196 book chapters, 692 abstracts, 19 monographs, and edited 32 books.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"58390",title:"Dr.",name:"Gyula",middleName:null,surname:"Mozsik",slug:"gyula-mozsik",fullName:"Gyula Mozsik",profilePictureURL:"https://mts.intechopen.com/storage/users/58390/images/system/58390.jpg",biography:"Gyula Mózsik, MD,PhD, ScD(med) is a professor emeritus of medicine at First Department of Medicine, Univesity of Pécs, Hungary. He was head of the Department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition. His research fields are biochemical and molecular pharmacological studies in gastrointestinal tract, clinical pharmacological and clinical nutritional studies, clinical genetic studies, and innovative pharmacological and nutritional (dietetical) research in new drug production and food production. He published around 360 peer-reviewed papers, 196 book chapters, 692 abstracts, 19 monographs, 32 edited books. He organized 38 national and international (in Croatia ,France, Romania, Italy, U.S.A., Japan) congresses /Symposia. He received the Andre Robert’s award from the International Union of Pharmacology, Gastrointestinal Section (2014). 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MWs are characterized by the frequency (between 300 MHz and 300 GHz) and the wavelength (ranging from 1 m to 1 mm). According to the countries and regions, five frequencies (433, 896, 915, 2375, and 2450 MHz) are authorized for MW heating operations. The 2450 MHZ is the exclusive frequency for home appliances.
The interaction of a wave with the material depends on its own characteristics (frequencies, wavelength) and the nature of the material, particularly its absolute permittivity ε*, a complex number that determines how the material stores the electrical energy of the EF and its dissipation into heat. The readers can consult more specialized references for detailed information [1]. We can define rapidly here the real permittivity, or dielectric constant, of a material which denotes the capacity of the material to store electrical energy and the effective loss factor which expresses the ability of the material to absorb energy of the wave and dissipate it into the heat by dielectric relaxation and ionic conduction. If a material contains free charges (ions) and polar molecules (e.g., water molecule) when this material is subjected to an EF, the ions will move at an accelerated rate according to their charge, which will cause collisions between them and, by the result, a conversion of the kinetic energy into heat (ohmic heating). In the same way, the polar molecules of this material, which was initially randomly oriented, will be oriented according to the polarity of the field. If the EF is an alternative, these molecules will rotate to remain aligned on it. This dipolar rotation will generate frictions between the molecules which will lead to an internal generation of heat (dielectric heating).
When an EM wave is directed toward a material, a part of the wave is reflected on the surface, while the other part penetrates it to be absorbed. The absorption of the wave during its crossing results in a decrease of the amplitude of the internal EF and so of its power. For small or thin materials, the accurate calculation of the internal electric field is recommended by using the Maxwell equations. Lambert’s law (exponential EF decayed) may be used for larger objects.
The penetration depth is defined as the penetration distance in the material for which the 63% of incident power of the incident wave has been absorbed. This depth depends on the dielectric properties of the material as well as the wavelength. The penetration depth at 915 MHz is larger than the penetration depth at 2450 MHz at the same conditions. More power will be absorbed when the loss factor is high [1].
MW heating is inherently heterogeneous for several reasons:
For most cases, product size is very large compared to the penetration depth; thus, the energy of the EM wave will be completely absorbed before being able to reach the core or the bottom of the product. All the parts of the product not crossed by the EM wave will not undergo heating. Smaller products will heat faster than large ones, because MWs are able to penetrate the entire product. However, small products are also more sensitive to variations in EM fields that exist in the oven, particularly in a multimode cavity.
Dimensional resonance phenomena: sometimes, the wave is reflected against the lower edge of the product leading to interference phenomena. This results in producing cold spots (transmitted and reflected waves cancel each other) and/or hot spots (transmitted and reflected waves add up).
If the product is made of several components, the component with the highest dielectric constant tends to concentrate the energy, and its temperature will increase strongly compared to the other components which leads to selective overheating. The dependence of dielectric properties with the temperature often leads to increase the local temperature of the already hot points. As foods are generally low thermal conductivities, this phenomenon leads to local overheating (thermal runaway).
The shape of the product plays a major role in the heterogeneity of MW heating. The shape of the sample influences the penetration depth of the MWs and the location of the hot spots. In general, the presence of sharp edges and right angles leads to significant local overheating at these locations. Sundberg et al. [2, 3] found that the power density at the edge decreased with the increase of the opening angle; thus, oval or circular forms may in some cases reduce this problem. However, in these forms the MW power is concentrated in the center [4].
Drying is one of the most used methods for preserving food and preventing microbiological degradation. Food drying is also used for economic interests by lightening the product to minimize the transport costs (e.g., milk powder) or even for consumption aspects by creating new textures and/or products (e.g., prunes). This process aims to reduce the water activity (Aw) of the food product by removing some of its water. The amount of water to be removed to achieve the microbiological stability can be determined thanks to the sorption isotherm curve which shows the relationship between the water content and the water activity of a product. Generally, the water activity threshold from which there is no further development of pathogenic bacteria is 0.85–0.86 and 0.7 and 0.6 for yeasts and molds, respectively.
It is interesting to note that Aw does not only control the development of microorganisms, it also influences the rate of the chemical and biochemical reactions that take place within the food. The nonenzymatic browning (Maillard reaction) has a maximal activity for an Aw of 0.6–0.7, while the oxidation of lipids develops rather at very low and very high values of Aw. Thus, it is proper to adjust the final moisture of the product according to these considerations. The area generally targeted for good stability of the dried product is the range of Aw between 0.3 and 0.4. An important aspect must be emphasized here, namely, that drying has almost no lethal effect on the microorganisms present on the product due to insufficient product temperatures reached during drying. Proper packaging is therefore essential to avoid moisture recovery and keep the quality of the dehydrated product.
Industrial drying techniques are very varied depending on the nature of the product to dry (liquid, pasty, solid, or particulate) and of the desired final qualities. Most often, hot air (HA) convective drying is the main dehydration technique used in food industries. However, this method undergoes several problems such as poor end-product quality and low operation performance. Generally, in conventional drying method, two steps take place: a heat transfer from hot and dry surrounding medium to the product and then a mass (water and/or volatile compounds) transfer from the product to the surrounding atmosphere. In general, external heat and mass transfer can be easily controlled by a good monitoring of the drying air characteristics (velocity, temperature, relative humidity); thus, the internal transfer is the limiting step and the effective driving force for the drying operation. The drying rate decreases with time, and the removal of water becomes difficult. Therefore, conventional HA drying requires the application of severe conditions, particularly at the end of operation, which result in overheating and overdrying of the product surface. These reasons have greatly encouraged engineers to develop and propose new drying techniques such as MW drying. For example, MW drying was successfully applied to dry potatoes chips, pasta, and snacks [5]. Several studies of MW drying were resumed in the literature [6].
During MW drying of strong moisture content product, EM energy is supplied directly to the volume of the product, which causes a rapid increase of the product temperature and an instantaneous vaporization of water inside the product [7]. This phenomenon causes an increase in the internal pressure and drives the water to liquid state toward the product surface [8]. This forced outflow of water increases the drying rate and so reduces the operation time (up to five times less than HA air drying for many products). Likewise, the increase in internal pressure prevents food shrinkage and case hardening during drying, which have a positive impact on the texture of the MW dried product. Indeed, it promotes a greater porosity and increases the rehydration ability [9].
The action of conservation provided by the drying to foodstuffs is mainly due to the decrease of Aw which thus makes it possible to limit the development of microorganisms. However, an additional action is observed in the case of MW drying. In fact, the rapid rise in temperature for water-rich products seems to produce a thermal shock effect on thermosensitive microorganisms. Laguerre et al. [10] have shown, in a comparative study of drying of onions either by HA or by MWs, a reduction of the total microbial count ten times greater for MW drying (about one to two log reductions). This is a significant advantage of MW drying compared to hot air drying.
Although the selectivity of EF may cause heating heterogeneity, this selectivity is rather an advantage in the case of MW drying. The level of energy absorption is controlled by the wet parts, resulting in positive selective heating of the inner layers of the product still having a relatively high moisture content without affecting the relatively dry outer layers, thereby facilitating the outflow of water to the surface.
However, even if the MW drying is faster than that of HA method, the MW drying efficiency is limited because of the rapid saturation of the surrounded air due to its low temperature. For this reason, MWs are usually associated with HA flow to improve water transfer at the surface of the product. Another difference between MW and HA drying is the surface temperature. During HA drying, the surface temperature does not exceed the controlled surrounding air temperature, which may be low (30–40°C) during thermosensitive product drying (e.g., aromatic plants), whereas excessive surface temperature may occur during MW drying, especially along the corner or edges, resulting in product carbonization and production of off-flavors especially during the final stages of operation [6].
In many works, a constant MW applied power is usually used throughout the drying period. This practice promotes the phenomena of thermal runaway (local overheating) at the end of drying. During MW drying performed at constant power, the applied specific power (power/product mass) increases exponentially as can be seen in Figure 1 for the drying of tomato as an example [11]. Thus, the product receives more and more energy over time while it needs less and less. Moreover, the thermal properties of the product (specific heat and thermal diffusivity) decrease at the same time as the moisture of the product; therefore, it becomes easier to heat the product while the heat accumulated in a zone can less easily diffuse to the whole product. All this, combined with the phenomenon of dimensional resonance, can lead to thermal runaway. This phenomenon can be observed in the case of drying onions [10, 12]. Figure 2 shows the evolution of hot spots up to charring on onion slices during MW drying. The fact that the black spots are very localized initially confirms the presence of dimensional resonance phenomena in this case.
Evolution of the specific power (W/g) as a function of time (min) for different initial specific power values during drying of tomatoes [11].
Evolution of hot spot during MW drying of onion slices [10].
To improve the quality of MW dried foods, the control of the applied power throughout the drying was studied in the literature. Li et al. [13] proposed the control of applied power according to the set product temperature, whereas Soysal et al. [14] adapted the applied power as a function of processing time. A very good quality product was obtained by Laguerre et al. [10, 15]. The authors controlled the power as a function of the product mass. This method was successfully tested for drying onions and tomatoes as presented in Table 1. A final product of fresh-like color, without any black spots, was obtained.
Effect of the adaptation of the power applied on the color of the dried product.
Despite its several advantages over the conventional methods, MW drying has some crucial problems as explained above. However, MW drying combined with other conventional heating methods enhances the drying efficiency as well as the dried product quality compared to MW drying alone. Applications of combined MW drying, principally, include MW-assisted hot air (HA) drying, MW vacuum drying, and MW freeze drying.
The application of MW energy (internal heating) associated with hot air flow (superficial heating) is a good method to overcome certain problems related to the use of these two methods separately. MW heating may be applied at the beginning of the drying process to heat the internal layers of the product rapidly. MW heating can be also applied at the second step of drying process, when the temperature profile is established, to force vapor out of the product which leads to create a porous structure. MW heating can also be applied at the end of drying process, where the mass transfer is reduced to improve the drying rate by removing the bound water [9]. For example, MW drying combined with HA drying at the last stage reduced the drying time by 64% as compared to convective air drying [16]. Saving drying time and improved quality were also reported, using this method, for other fruits such as blueberries [17], macadamia nuts [18], and green peas [19].
In order to reduce the boiling point of water and to prevent the oxidation reactions, MW heating can be associated with a vacuum to maintain the quality (color and flavor) of the dried products. This method was successfully used to dry apple slices [20], pumpkin [21], and cranberries [22]. This method is better than MW air drying in terms of energy consumption, drying time, and quality of the dried products [6].
Lyophilization, also known as freeze drying, is a low-temperature dehydration process, which involves freezing the product at the first step and then removing the ice by sublimation under low-pressure conditions. It is used for dehydration of very heat-sensitive materials particularly in food and pharmaceutical industries. This method preserves the structure and minimizes the loss of valuable compounds. However, this technology is limited by its high cost. In MW freeze drying, MW heating can be applied concurrently during the sublimation to supply the heat under vacuum conditions. MW heating can also be applied separately after a traditional lyophilization step. MW freeze drying offers many advantages due to its low processing temperature and lack of oxygen in the processing environment [23, 24]. However, as the MW energy does not interact with frozen water, thermal runaway might take place which may result in poor product quality [6].
Pasteurization and sterilization are widely used to extend the shelf life of most foods. The main goals of pasteurization are to destroy vegetative pathogenic microorganisms and to deactivate some enzymes in foods. Pasteurization temperatures and treatment time vary, primarily, depending on the nature, the pH of the product, and the target microorganism. In most pasteurization processes, the food is heated up to 60–85°C for a time varying from a few seconds to an hour. Pasteurization requires refrigerated storage conditions (3–4°C) for a storage life of 2–6 weeks. Sterilization, which can be seen as further pasteurization, destroys bacterial spores [25]. In solid or semisolid products, the heat transfer takes place mainly by conduction from the surface to the center often considered as the “cold” point. This leads to apply more severe conditions to reach the target temperature at the cold point, which results in an overcooking of the surface and a degradation of the quality of products. Optimizing thermal treatments (i.e., maximizing inactivation of bacteria while minimizing nutrient degradation) is therefore an important issue. However, this is not an easy task and it is always a technical and scientific challenge. Thanks to the direct and volumetric interaction between MWs and food, MW heating has the advantage of overcoming the limitation imposed by slow thermal diffusion of conventional heating.
Many studies demonstrated the effectiveness of using MW heating for pasteurization and sterilization of food [26, 27, 28]. Furthermore, different strains of microorganisms have been inactivated by MW heating, for example, Bacillus cereus, Campylobacter jejuni, Clostridium perfringens, Escherichia coli, Enterococcus faecalis, Listeria monocytogenes, Staphylococcus aureus, and Salmonella [29, 30].
The study of microbial destruction mechanisms during an MW heating has attracted a lot of interest [31, 32]. In particular, the possible existence of nonthermal (athermal) effects of microwaves is a subject of debate. Several theories have been proposed to explain how electromagnetic fields can inactivate microorganisms at sublethal temperature conditions. This effect would be due to the interaction between microwaves and certain cellular constituents. In contrast, many studies have refuted the lethal nonthermal effect of MWs. To distinguish between thermal and nonthermal effects, most studies are based on the experimental evaluation of conventional and MW inactivation under identical heating conditions.
Fujikawa et al. [33] showed no difference between inactivation treatments for E. coli (suspended in PB phosphate buffer) in a conventional water bath and in a MW oven. Welt et al. [34] have developed a device to evaluate the possible nonthermal effects of microwaves. They compared the inactivation of Clostridium sporogenes spores in a model medium (a phosphate buffer) under a same time-temperature condition for conventional and MW treatment. The results demonstrate the absence of a nonthermal effect.
On the other hand, several studies demonstrated that the microwaves have a more important bactericidal effect [35, 36]. Sato et al. [37] found that the inactivation of E. coli K12 exposed to MW radiation was higher than that obtained in a water bath at the same temperature (45, 47, and 50°C).
Some authors support the thesis of improved bactericidal effect of microwaves. Kozempel et al. [38] developed an experimental device for detecting a possible nonthermal effect of microwaves on microorganisms at low temperature. The process combines instantaneous energy input to the food system by microwaves with rapid removal of thermal energy. The system used is a double-tube heat exchanger installed inside a continuous MW tunnel. The outer tube is microwaveable, while the inner tube is stainless steel and was used to cool the system instantly to keep the temperature at 45°C. The nonthermal effect of MW radiation has not been observed for yeast, Pediococcus sp., Escherichia coli, Listeria innocua, or Enterobacter aerogenes, in various liquids. However, the author has reported that MWs can improve or amplify the thermal effect in lethal conditions [38]. In the same context, Ramaswamy et al. [39] found that the inactivation of S. cerevisiae inoculated in apple juice treated with steam, hot water, or MW was not significantly different at sublethal temperature (<40°C). However, they found that MW radiations enhanced inactivation for same lethal temperature conditions (55–65°C).
Numerous studies on the interactions between MWs and certain cellular constituents, such as DNA, the cell membrane, enzymes, and proteins, have been carried out. Kakita et al. [40] studied the survival of bacteriophage PL-1, which is specific for Lactobacillus casei, under MW irradiation. More viral DNA fragmentation was found for MW heating over conventional heating. Shamis et al. [41] studied the effects of MW radiation on the membrane of the E. coli cell under sublethal temperature conditions (<40°C). Compared to conventional treatment, a different cellular morphology was observed (the cells are contracted and dehydrated). Nevertheless, this effect seems to be temporary; 10 min after the end of the exposure, the morphology of the cell seemed to return to the initial state of untreated controls. In this experiment, cell viability test revealed that the MW treatment was not bactericidal, since 88% of the cells were recovered. Similarly, Woo et al. [42] reported that MW radiation of Escherichia coli and Bacillus subtilis resulted in an increase in the amounts of nucleotides and protein released from cells. This leak was strongly correlated to MW power. The authors observed, by scanning electron microscopy, a significant damage on the surface of MW-treated E. coli cells; however, there was no significant change observed for B. subtilis cells. Likewise, Shin and Pyun [43] showed that MW treatment (at 50°C) causes irreversible damage to the membrane of Lactobacillus plantarum, associated with increase of the permeability. Also, observations by electron microscopy showed a change in cellular morphology on Candida albicans treated with MW [44].
To prove the existence of nonthermal effect of microwaves on microorganisms, exactly the same thermal history must be reproduced for MW and conventional treatments. Most of studies previously cited applied temperature measurement techniques inappropriate to MW heating, where the temperature was monitored at a single point of the sample. In addition, it is also important to eliminate the heating heterogeneity inherent in MW processing. Consequently, microorganisms are subjected to uneven heating as a result of the presence of cold and hot spots within the same sample. In summary, so far, the existence of nonthermal effect of MWs on microorganisms has not been proven; even if this effect exists, it has no significant consequence on the MW heating of foods.
In fact, it is difficult to compare the efficiency of MW over conventional heating process because of the inherent differences of heating principle between the two technologies [45].
In the case of conventional heating, a slow heat exchange occurs between the heating medium and the product. The heat diffusion inside the product depends on its physical properties (specific heat, thermal conductivity, porosity, etc.). However, it is well known that foods are bad thermal conductors, heat diffusion toward the cold spot is usually slow, and MW heating is generally faster than conventional heating. The heat is generated directly within the food. This direct volumetric heating significantly reduces the processing time resulting in greater retention of nutrients, sensitive vitamins, and aromatic constituents. Microwave-processed foods may also have better texture, taste, and appearance than products processed by conventional methods. For example, a two times faster MW pasteurization treatment of pickled asparagus at 915 MHz was published [46]. This advantage reduced significantly the thermal degradation of asparagus compared to a conventional treatment in a water bath. Similarly, an acceptable MW pasteurization of foie gras was reported with a time saving of 50% and better organoleptic qualities compared to a traditional method [47]. Moreover, MW pasteurization of packaged products is possible for different packaging materials (plastic, paper, and glass) [48, 49]. Furthermore, this technology can be combined with other technologies such as infrared heating for surface cooking, for example [50].
Despite the numerous advantages of MW decontamination technology, heating heterogeneity is a serious problem that leads to incomplete inactivation of microorganisms. Several studies have reported the survival of pathogens such as Salmonella spp. [51] and L. monocytogenes [52], in foods heated in MW ovens.
Goksoy et al. [53, 54] studied the effect of short-time MW exposures on Escherichia coli K12 and Campylobacter jejuni inoculated on chicken meat. A temperature variation of 20°C was measured between different parts of the sample. The auteurs reported that the samples subjected to MWs showed signs of partial cooking areas. There was no evidence that short-time exposure (up to 30 s) to MWs had any bactericidal effect on microorganisms. Apostolou et al. [55] confirmed these results. MW heating of chicken portions did not eliminate E. coli O157: H7. A significant variation of temperature (from 66.7 to 92°C) was also observed.
On the other hand, the heterogeneous heating causes a severe deterioration of food quality. Local overheating often results in irremediable changes of color where the temperature is highest [56]. These phenomena are mainly observed at the corners and the edges of the product due to wave reflection.
Another difficulty concerning MW decontamination is the problem of cold spot localization. During a typical thermal process, the cold point is well defined and located often at the center of the product. During MW pasteurization, one point temperature monitoring within the product is not sufficient to ensure food safety [57]. For example, Schnepf and Barbeau [58] studied the inactivation of inoculated Salmonella in poultry. Their results showed that measuring the internal temperature during MW treatment does not reflect the surface inactivation, where the temperature was lower. To locate the cold spot, the chemical marker method developed by Kim and Taub [59] was successfully used [60, 61, 62]. Combined with experimental investigations, numerical simulations are highly recommended to find the cold spot and to achieve an accurate study to develop a reliable MW decontamination process [57, 63, 64].
Before accepting MW technology as a reliable method for pasteurization and/or sterilization of food, it is important to ensure uniform heating during treatment. Several studies have been conducted to improve the quality and safety of MW-treated products, and various solutions have been proposed.
Fung and Cunningham [65] reported that MW heating in combination with conventional heating results in more uniform heating of food and better inactivation of bacteria. Datta et al. [66] found that MW heating in combination with infrared heating or air jets decreases the nonuniformity of temperature distribution. In the same field, Maktabi et al. [67] investigated the synergistic killing effect of laser, MW, and UV radiation on E. coli and on some other spoilage and pathogenic bacteria. It was found that the overall reduction in viable counts was significantly higher than the sum of the reduction values for the individual treatments. The order of the treatment processes had also a significant influence on microbial destruction. A successive process by laser, MW, and then UV was the most effective. Similarly, Lau and Tang [46] studied the heating uniformity and textural quality of pickled asparagus pasteurized by MW in comparison with the conventional hot-water pasteurization method. Two successive heating steps, first in water bath and then in 915 MHz MW oven, were successfully applied. Moreover, covering the top one-third of the product glass bottle with aluminum foil eliminated the overheating at the edges. MW pasteurization also reduced the cook value for pickled asparagus and reduced textural degradation.
On the other hand, the presence of an absorbent medium around the product can reduce the overheating of edges and corners. For example, some authors reported that immersion of the sample in hot water [48] or the use of a steam flow into the oven cavity [68] may be used to ensure a safer and better quality end product. Microwave-circulated water combination (MCWC) heating system demonstrated a relatively uniform heat distribution within packaged food products. Guan et al. [48] reported that microbial destruction by a pilot-scale MCWC heating system matched with designed degrees of sterilization (F0 value) for a conventional treatment.
Koskiniemi et al. [69] improved the heating uniformity of packaged acidified vegetables using a continuous 915 MHz MW system with a two-stage rotation device to rotate the products 180° during treatment. This method increased also the average temperature at the cold point to meet the industrial standard for in-pack pasteurization of acidified vegetables.
Pulsed MW heating technique was also successfully tested. In this method, pulsed application of energy—i.e., turning the magnetron power “on” and “off” intermittently—leads to thermal energy equalization via conduction from hot to cold region during the power-off periods. This results in more uniform temperature distribution within the sample than during continuous application of energy [70, 71]. Sato et al. [37] reported also an enhanced killing rate of Escherichia coli K12 by using pulsed waves compared to continuous treatment.
Computational fluid dynamics (CFD) is widely used as an established approach for understanding and then optimizing food processing based on the solution to partial differential equations of mass, momentum, and energy transport. MW heating is a multiphysics phenomenon that requires electromagnetic propagation equations (i.e., Maxwell’s equation) to be combined simultaneously with the heat transfer equation to predict the MW power absorption as well as the temperature distribution inside the product [72]. Modeling of MW heating is widely studied in the literature. Interested readers can consult specialized references for more details [73].
In order to design and optimize a reliable MW pasteurization and/or sterilization process, heating model needs to be coupled with kinetic models correlating microbial decontamination. The resulting global model has to mimic the spatial temperature distribution as well as the microbial inactivation at every point within the sample. Few coupled numerical studies of bacterial inactivation by MW heating are reported in the literature. Recently, Masood et al. [64] published an excellent review about emerging technologies modeling to ensure microbial safety of foods.
The classical concept of decimal reduction time and thermal resistance constant (D and z values) was also used to characterize the microbial inactivation by MW heating. Cañumir et al. [74] determined D-values at constant power levels and proposed a z-value in watt to represent the resistance of a target germ during MW heating. Laguerre et al. [75] proposed new specific power destruction parameters, Dp- and zp-values, to qualify MW heating. The decimal reduction time (Dp value) is the treatment time required to reduce microbial population by 90% at a constant applied specific power expressed in W/mL or in W/g. The zp value is the change of specific power necessary to cause a tenfold change in the Dp values of microorganism under specified conditions. This concept has been successfully tested for sterilization of infant food in a lab-scale MW pilot. The optimal condition for MW sterilization of infant food was also determined.
Because of the heterogeneity of MW heating, microbial inactivation kinetics need to be coupled with nonlinear heat transfer model to calculate the temporospatial survival of bacteria [63]. Mallikarjunan et al. [76] developed a mathematical model that includes mass heat transfer to microbial inactivation kinetics. The variation of the dielectric properties with respect to the temperature is taken into account in the simulation process. A good agreement with experimental data was obtained. Hamoud-Agha et al. [57, 63] used COMSOL Multiphysics to investigate the inactivation of E. coli K12 suspended in a gel medium, comparing MW processing with conventional thermal treatment in a water bath. The authors coupled the thermal nonlinear microbiological inactivation model of Geeraerd et al. [77] with heat transfer and Maxwell’s equations integrated into a finite element model under dynamic heating conditions. The results revealed uneven temperature distribution during MW heating which led to a lower inactivation efficiency than water bath treatment. Simulation results were in good agreement with experimental data. The modeling approach to estimate efficiency of microbial inactivation was reliable despite the thermal heterogeneity inherent in the MW treatment. Application of holding time at lethal temperatures (55 and 57°C) did not help to homogenize the temperature distribution within the sample [57, 63].
However, because of digital resources required and time consumption, the use of physical models as presented before could be delicate for real industrial applications in the food industry. On the other hand, another approach based on experimental designs (EDs) and response surface methodology (RSM) can be relatively easy, fast to implement, and quite useful [78]. Nevertheless, RSM has some limitations [8]: (1) it uses a priori models (quadratic model whatever the studied response); (2) the number of tests to be reset can increase very quickly with the number of factors in the plan; (3) the factors must be completely independent; and (4) uncontrolled factors cannot be taken into account.
Another method proposed by Lesty et al. [79], based on iconographic correlations (CORICO), makes it possible to circumvent these difficulties [8]. After analysis of the experimental plan data, CORICO proposes regression models whose regressors are logical interactions (AND, Exclusive OR, IF, etc.) between factors. In addition, CORICO tolerates linked factors and allows the consideration of uncontrolled factors. Furthermore, it needs few numbers of essays comparatively to classical EDs, (17 essays for a 9-factor CORICO designs against 533 for a 9-factor Doehlert design), which allows to minimize costs. This method has recently been used in the agri-food sector for the optimization of the drying process of different food products (tomato, microalgae, apple) [11, 80, 81] as well as for MW cooking processes (beef burgundy, fish) [82, 83].
Conventional heat treatments for food preservation are generally characterized by poor end-product quality. Furthermore, these methods are not optimized for solid foods because of slow heat transfer from the surface to the cold point, often at the center of the product. Enhanced organoleptic and nutritional food properties combined with food safety is the aim of modern food processing technologies. Microwave (MW) heating has the advantages to overcome the limitation of slow thermal diffusion imposed by conventional heating. This technology knows a growing industrial demand thanks to its flexible and rapid heating performance. MW heating is successfully used for food drying and decontamination. However, this process is still relatively poorly controlled because of complex interactions between foods and MWs. Furthermore, the heating heterogeneity is the major drawback of this technology. Several methods were, nevertheless, proposed in the literature to improve the heating homogeneity. In general, coupling MW heating with other heating methods largely improved the microbiological safety, the drying efficiency, and the quality of various food products. Physical modeling and simulation are important tools to understand and to optimize MW heating processes. The application of these models is limited in industrial scale; however, experimental design-based approaches could be promising methods. Even so, developing a reliable industrial MW heating process is still a challenge.
Land is shrinking but world population is increasing in a rapid phase, so, modern agricultural practice is struggling to meet the level of primary productivity required to feed approximately 10 billion people by 2050 [1]. From last few decades the adverse effects of climate change and higher CO2 concentrations, the consequence of expected impacts on the water-use efficiency of dryland as well as irrigated crop production, potential effects on biosecurity, production, and quality of product through increased the frequency of introduced various abiotic (heat, salinity and drought) and biotic stresses (pests and diseases). In addition, climate change is also expected to cause losses of biodiversity, mainly in more marginal environments. Drought alone is expected to reduce crop productivity in half of the global arable land and it’s estimated around 50% in the next five decades [2]. It has been predicted that, on average, global yields of major economic important crops will be reduced by the unfavorable climatic conditions in wheat (6.0%), rice (3.2%), maize (7.4%) and soybean (3.1%) for every degree celsius increase in global mean temperature [3].
Climate resilience is an ability of the plant/crop to survive and recover from the effects of climate change. Some important practices that may help to adapt the climate change are soil organic carbon build up or carbon sequestration, in-situ moisture conservation, residue incorporation instead of burning, water harvesting and recycling for supplemental irrigation, growing biotic and abiotic resistance/tolerant varieties, location specific agronomic and nutrient management and breeding for multiple traits of interest including quality.
Plant Breeding has always played a pivotal role in human history from revolutionizing agriculture to feed the ever-growing population. The key role of plant breeding in agriculture is to develop a genetically superior genotype/variety, which is suitable for a specific as well as general cultivation of particular environment towards higher production [4]. Realizing the importance of genomic resources to expedite the breeding programs, huge amount of genetic data related to genes and QTLs (Quantitative Trait Loci) are generated after the advent of molecular biology and biotechnology [5]. The progress in precise phenotyping and genotyping offers tremendous opportunities to develop crop varieties that are suit for better changing the climatic conditions, which ameliorate in boosting the plant breeding activities for developing climate resilient varieties/cultivars [6]. Hence, development of climate resilient varieties utilizing Smart breeding tools to ensures the food security in adverse climatic conditions.
The effect of climate on agriculture is related to variability’s in local climates rather than in global climate patterns. The changes in the rainfall patterns, temperature, CO2 level and greenhouse gases resulting in the frequency and severity of extreme events such as flooding, drought, hail, and hurricanes etc. are major hindrance in achieving the food security for ever increasing population [7].
According to Intergovernmental Panel on Climate Change (IPCC), global temperature may be rise from 1.7 to 4.8°C during the twenty-first century and precipitation pattern will also be altered [8]. In recent times, it has been reported that the Yangtze river basin in China has become hotter and it is expected that the temperature will increase up to 2°C by 2050 relative to 1950 [9], and also reduce the rice (41%) and maize (50%) production by the end of the 21st century. This shift in climate will affect the environment, including the soil ecology and thus has the potential to threaten food security through its adverse effects on soil properties and processes [10]. Additionally, the direct and indirect effects of climatic change would lead to alter the nutrient and their bioavailability in soils (Figure 1). The effect of climate changes on biotic and abiotic stresses have already reduced the global agricultural production from 1 to 5% during the past three decades [11].
Adverse effects of climate change on agriculture and food production.
Some important practices that assist to adapt the climate changes for crop production including (i) Building resilience in soil (tillage management, avoid bare soil, fertilizer application after mandatory soil testing, increase soil carbon through organic manure, green manuring, crop rotation or intercropping with legume sequester carbon and biochar), (ii) Adapted cultivars and cropping systems (crop diversification, shallow-deep root and legume-cereal cropping system, improved early/short duration cultivars for tolerant against drought, heat and submergence capturing optimum yields despite climatic stresses), (iii) Rainwater harvesting and recycling (inter-row water harvesting, inter-plot water harvesting, in farm ponds and reservoirs and recycling), (iv) Farm machinery (chisel and para plow to opening the furrows which conserves rain water, laser leveler helps in increasing nutrient as well as water use efficiency), (v) Crop contingency plans (livestock and fishery interventions), (vi) Weather based agro advisories (automatic weather stations establishment at experimental farms and mini-weather observatories records for real time weather parameters such as rainfall, temperature and wind speed, which customized through agro advisories and improve weather literacy among the farmers).
Plant breeding procedures have been constantly evolving to meet the increasing food demand. The art of plant breeding has been practiced in various forms since the start of human civilization. In conventional plant breeding, development of a new cultivar take around 10–14 years and may even exceed this period based on the plant habit, reproductive cycle and complexity of traits involved. The rapid climate change necessitates the development of varieties in a shorter period to tackle with the unpredictable weather parameters. The concept of Smart breeding is an integration of conventional breeding strategies with advanced molecular, genomic and phenomic tools to efficiently and effectively breed the resilient crop cultivars with enhanced yield potential. New breeding approaches such as rapid generation advancement, doubled haploid (DH), marker assisted back crossing (MABC), marker assisted recurrent selection (MARS), genomic selection (GS) etc. have been used to help shorten the breeding cycle along with efficient screening for specific biotic and abiotic stresses. Biotechnology-based breeding technologies (marker-assisted breeding and genetic modifications) will be essential to assist and accelerate genetic gain, but their application requires additional investment in the understanding, genetic characterization and phenotyping for complex adaptive traits to be exploited for climate resilient breeding.
Climate change leading to severe weather fluctuations would also lead to evolution of plant diseases and pests, exposing crops to higher biotic pressure in addition to abiotic stresses. To make crop adaptation feasible in the era of changing climate, there is indispensible need to breed the crop plants with diverse genetic backgrounds. In order to feed the mushrooming population, there is urgent need to use crop wild relatives for developing broader spectrum varieties to tackle various biotic and abiotic stresses. During the era of domestication, selection preferences lead to modern crops with narrow genetic background, resulting in limitation of environmental adaptation and breeding capacity using modern germplasm [12]. Wild relatives and ancestral species relatively possess broader adaptation to environment and climates ultimately higher potential in crop improvement.
Prebreeding activity is a bridge for linking the desirable traits of CWR to the modern cultivar development by providing breeders with wild genetic diversity in a more immediately usable form [13, 14]. Pre-breeding is an opportunity to introgression of desirable genes, from wild species (primary, secondary and tertiary gene pools) into elite breeding lines/cultivars/genotypes, to overcome the linkage drag (Figure 2). Almost all cultivated crop species were originally domesticated from wild plants by humans, due to domestication inherently reduced the genetic variation [15]. The genetic potential of wild relatives has been reported in different crops like rice, wheat, maize, potato, tomato, cotton, tobacco, sugarcane, chickpea and pigeonpea [16, 17, 18, 19, 20, 21].Genomics strategies have been widely utilized in staple crops for transferring major genes (i.e. disease resistance) from wild germplasm to elite cultivars [22]. It is well documented that application of molecular mapping and sequencing to could be useful to unlock the genetic potential of CWR [23]. So, crop wild relatives (CWRs) are good reservoir of untapped genetic diversity, which may not exist in the cultivated gene pool that can be used to improve the numerous trait of interest including resistance/tolerance against diseases, insect-pests, drought, salinity, cold, heat and good agronomic adaption with quality improvement.
Untapped genetic resources/ CWRs towards the germplasm enhancement.
Wild species are used mainly for the introgression of disease and insect resistance into crops although drought, cold, heat and salinity tolerance have also been addressed in some staple crops. This is because most pathogens have faster adaptation to climate rendering cultivars vulnerable to novel deadly diseases [24]. The use of interspecific or intergeneric hybridization for disease resistance introgression is conventional one. Another potential technique to enhance genetic diversity and facilitate crop vigor with adaptation to different environmental niches is creating the polyploidy crops mimicking natural evolution through hybridization [25]. Enriched genes for biotic and abiotic stress resistance of CWR can be studied using comparative pool sequencing of genome assemblies, elucidating the potential genomic segments responsible for adaptation to different ecological niches. These have been explored in wild relatives of many crops including chickpea, barley and maize [26, 27, 28, 29].
To address the diversity within species, pan-genomics based on entire gene repository of a species can reveal the genetic variations such as structure variants (SVs) and single nucleotide polymorphism (SNPs) abundantly found in plants. One such example under SVs is presence/absence variants (PAVs) of Elicitin response (ELR) gene between wild and cultivated potato leads to resistance/susceptibility response to late blight disease [30]. Larger pan-genomes including both wild relatives and cultivars can acquire glut 0f dispensable genes resulting in phenotypic variations; thereby easing out with characterization of the trait associated genomic variants [31]. To tackle the deadly rust diseases in wheat in the context of changing climate, several pan-genomic R genes have been successfully identified and cloned from wild diploid wheat Aegilops tauschii [32].
Considering the risks of introducing foreign alleles into cultivars, other potential technique for developing climate-friendly crops is de novo domestication [33]. As most staple crops are grown majorly in the regions other than where they were originally domesticated with different climatic regimes. Nevertheless, their wild relatives and landraces exhibit better adaptation to local climate in the native regions. In the scenario of climatic change, there is chance to leverage this opportunity to use those underutilized or orphan crops e.g. rise in Sinapis alba (white mustard) acreage replacing the B. napus in Europe for biofuel production [34]. A pipeline strategy has been proposed for domestication of wild germplasm in some orphan crops such as quinoa [35]. In addition to direct planting of non-domesticated crop plants, relatively advance methodology of CRISPR/Cas9 boosts the wild germplasm domestication by editing of domesticated genes e.g. editing in wild tomatoes (Solanum pimpinellifolium) and ground cherry (Physalis pruinosa) mainly focused on flower improvement, plant architecture improvement, fruit size, fruit number and nutritional content [36, 37, 38]. It is evident from such a few successful introgressions of domesticated genes that use of wild germplasm in regular plant breeding is quite promising in countering the effects of climate change on agriculture and hence, food security.
The actual potential of the CWR in plant breeding largely remains underexploited due to linkage drag and frequent breeding barriers with the crops. Introgressiomics approach allows mass scale development of plant material and populations with introgression lines from CWR into the genetic background of crops [39]. This pre-emptive breeding technique could be focused or unfocused depending upon the objective. Besides genetic analysis of traits present in CWR, MAS driven generation of chromosome substitution lines (CSL), introgression lines (IL) or MAGIC populations allow the development of genetically characterized elite material. Genomic tools like high throughput molecular markers facilitate the characterization and development of Introgressiomics populations, which can be easily incorporated into major breeding programs for coping with the accelerating environmental challenges.
After the introgression into domesticated background from CWR, populations such as backcross populations (BC), recombinant inbred lines (RILs), doubled haploids (DH), near isogenic lines (NILs), multiparent advance generation intercross (MAGIC) populations as well as nested association mapping (NAM) populations are developed to study the introgressed gene(s). After mapping their locations on to the genome and it genotypic validation with molecular markers, they are further deployed using Marker assisted selection (MAS). Systematic screening of the huge number of progenies with MAS enhances the efficiency of breeding program (van de Weil 2010). Desirable recombinants can be developed at early generations using larger populations e.g. using marker-assisted backcrossing (MABC), an important QTL was introduced into a new lowland rice background in just 2 rounds of backcrossing [40].
Genomic scans can also reveal candidate domestication and improvement loci as well as post-domestication introgression using CWR [41, 42] to be further harnessed in the scenario of climatic challenges. In case of CWR, high throughput sequencing offers a cheap and rapid way to deploy thousands to millions of markers for mapping purposes [43]. Reduced representation techniques as genotyping by sequencing (GBS) or even nimble exom capture have been exploited to this effect in several CWR species already [42, 44, 45]. These technologies offer rapid marker density as required for rapid fine mapping and can saturate mapping populations in terms of capturing all of the recombinants.
The availability of a reference genome sequence in CWR during recent times greatly boosts the use of high-throughput sequence data. Some large scale genomic sequencing and re-sequencing programs are well underway [27, 46] often with reduced representation methods. Whole genome shotgun sequencing (WGS) techniques can also be utilized to characterize CWR germplasm for climate resilience breeding in major staple crops. E.g. Rice having smaller genome size (430 mb) long with its wild relatives has been re-sequenced using WGS [47, 48, 49]. Already sequenced germplasm collections including Chickpea [50], Rice [48], Soybean [51] and Wheat [52] etc. will provide insights into these diverse gene pools to be exploited in combating various biotic and abiotic challenges during this era of climate change. More recently, a massive scale genomic study of almost 80000 accessions from CIMMYT and ICARDA unraveled unprecedented amount of genetic diversity in 29 wheat species comprising cultivated wheats, CWRs and landraces to be exploited in wheat improvement for range of climate related plant traits [53].
Potentially revolutionary technology in modern plant breeding like genome editing has enabled scientists to alter genome of any organism with unprecedented precision without involvement of any foreign DNA [54]. CWR and their sequence information may serve as a reference library for all kind of diversity. This information on allelic diversity and its phenotype is a vital requirement for many genome editing approaches. In fact, these approaches will allow the use of this information from more distantly related, cross-incompatible CWR and domesticated species to be further utilized in crop improvement [55, 56].
Considering the various direct and indirect impacts of climate change on food production and agriculture along with rapid deterioration of arable land and perplexity of rainfall patterns, all these factors triggering various abiotic stresses such as drought, heat stress and biotic stresses like pest and disease attacks, the sophisticated techniques laden biotechnology toolkit has potential to address these immense challenges of developing the stress tolerant food crop cultivars in this hour of need [57]. With population growing at rapid rate under threatening scenario of climate change, it is high time to shift resilience from conventional breeding along with fertilizers and pesticides to genomics-assisted crop improvement techniques in order to achieve more sustainable and efficient yield gains [58].
Recent advances in biotechnology tools have the potential to understand the function of genes/QTLs that govern the economic traits, and applying this information’s to Smart breeding programs, leading to crop improvement. The advent of molecular markers such as Restriction fragment length polymorphism (RFLP), Rapid Amplified Polymorphic DNA (RAPD), Simple Sequence repeat (SSR), Kompetitive allele specific PCR (KASP), Cleaved amplified polymorphic sequence (CAPS) and especially Single Nucleotide polymorphism (SNP) have revolutionerized the field of plant genetics and facilitated molecular crop breeding [59].
The ultimate goal of crop breeding to develop super-varieties by assembling multiple desirable traits, such as yield related, superior quality, tolerance/resistance against biotic and abiotic stress and good environmental adaption. It is very challenging, difficult and time consuming to combine all traits in single genotypes by traditional breeding, so some alternates need to be compiling all important traits, into single varieties, can be done through marker assisted selection (MAS), which have become an integral component of genotypes/germplasm improvement. The potential benefits of using molecular markers linked to the genes/QTLs of interest in breeding programmes, which have shifted from phenotype-based (traditional breeding) to a combination of phenotype and genotype-based selection, are of great importance to the Smart breeding programme [60].
Breeding programme combine, with MAS strategies have major advantages compared to traditional phenotype-dependent breeding in terms of convenience and efficiency for transferring the genes/QTLs of interest to the plant genome [61]. Selection can be done selectively with the genotypes of molecular markers linked to the target traits, selection in off-season nurseries (reduce breeding cycle), making the technique more cost effective to grow for more generations per year (speed breeding), reduction of required population size because many lines can be discarded in earlier breeding generations after MAS. The most effective and usefulness of MAS approaches, for traits of simple inheritance (qualitative traits controlled by one or a few genes) have been well proven in many important crops [62].
Basically, two major MAS strategies are usually applied in breeding programme, (i) backcrossing for favorable alleles into elite germplasm, i.e. marker-assisted-backcrossing (MABC) and (ii) stacking multiple genes of different sources into elite breeding lines, i.e. marker-assisted gene pyramiding (MAGP). The success of MAS has depends to search the important QTLs for complex traits (controlled by minor genes), which account for a large proportion of phenotypic variation (major QTLs). Successful applications of MABC and MAGP for improving yield or yield component traits by using well characterized major QTLs/genes in important crops [63]. Successful implementation of MAS breeding in broad range of crops including barley, beans, cassava, chickpea, cowpea, groundnut, maize, potato, rice, sorghum, and wheat [64]. Genetic markers associated with agronomic traits can be introgressed into elite crop genetic backgrounds via marker assisted breeding (MAB). It allows stacking of desirable traits into elite varieties to make them better adapted to climatic changes.
With plummeting cost and greater accessibility of high throughput genome sequencing technology, the breadth of genomic data is expanding rapidly. In order to capture diversity of specific gene families within a large group, DNA samples can preferentially be enriched before sequencing. This approach can be adopted to define genetic variation in disease resistance gene repositories in Solanaceae and Triticeae (RNA seq) [65] and gluten gene families I bread wheat (GlutEn Seq) [66].
Sanger sequencing to study plant genomes is unfeasible due to low throughput and high sequencing costs. In 2005, Roche released its revolutionary 454 pyrosequencing platform [67]. Subsequently, several sequencing platforms such as developed by Illumina, ABI, Life technologies, PacBio, Oxford Nanopore and Complete genomics were released commercially, changing the scenario of genome sequencing. Depending on chemistry, second generation sequencing (SGS) approaches are classified as ligation based approaches and synthesis based approaches [68]. To rectify the problems of assembling repetitive genomic regions, long read sequencing offers solution by producing reads spanning the repeat regions [69].
Rapid cost reduction in genome wide genotyping allows large scale assessment of crop species diversity to capture climate related traits. It leverages cheaper sequencing to identify up to millions of SNPs in plant population [70]. High SNP density approach like whole genome resequencing (WGR) & low SNP density approach like reduced representation sequencing (RRS) are majorly used approaches. However, high density genotyping assay “SNP chips” enable large scale genotyping using SNP specific oligonucleotide probes rather than direct sequencing.
The variants identified by genotyping by sequencing (GBS) can be used for conventional QTL analysis and modern approach like genome wide association studies (GWAS). GWAS exploits the past recombinations in a diverse association panels to identity genes lined to phenotypic traits [71]. SNP genotyping have been widely used in many crops including wheat [72] and Maize [73]. Extensive use of GWAS is resulting in our enhanced understanding of genetics of important climate specific traits viz. drought and heat tolerance. In light of reducing sequencing cost and expensive validation of candidate genes, use of WGR to further enhance resolution of mapping studies is likely to become routine task in future [70].
The availability of reference genome assembly rewards us with information about gene content, ability to associate the traits with specific genes with subsequent insights into related biophysical and biochemical roles of gene(s) in the expression of that particular trait [74]. Resequencing of diverse crop cultivars reveals the gene content variation and DNA sequence differences between allelic variants, while sequencing of expressed gene products provides information on where and when genes are functioning. Such information when integrated within breeding pipelines, offers promise to accelerate the development of climate smart crop varieties.
The recent explosion in genomic data is rapidly triggering a fundamental shift to genomic based breeding [75]. The ability to identify and genotype umpteen SNPs at ever reducing costs facilitated expansion of MAS in breeding to plethora of traits and across wider range of crops [76]. A major outcome of availability of high throughput genome wide markers is a move towards population based trait association and breeding i.e. NAM or MAGIC populations to ultimately enhance the trait mapping resolution by greatly increasing the number of recombinations in the population. After identification and validation of the candidate genes, there achieved the deeper understanding of biological mechanism underlying the trait, which can subsequently be improved through MAB or genetic alterations. Furthermore, precise understanding of the molecular basis of traits enables the engineering of novel alleles or mining of potentially desirable alleles from CWR, facilitating further enhancement of the trait.
Genome editing has enabled breeders to precisely add or delete any DNA sequence in the genome and has shown enormous potential to revolutionize the crop improvement in this very decade [70, 77]. Some approaches like transcription activator-like effector nucleases (TALENs) and zinc finger nucleases (ZFNs) have been in the game for more than 2 decades. However, type II clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) system from Streptococcus pyogenes [78] developed in last decade has been most versatile tool in breeder’s toolkit to introduce desirable or novel traits and accelerate development of climate smart crop varieties.
Usually, a custom-made guide RNA (gRNA) along with Cas9 nuclease is delivered into plant protoplast, where Cas9 produces double strand break (DSB) 3 bp upstream of the NGG motif (protospacer adjacent motif-PAM sequence) [78]. Cellular repair machinery through non-homologous end joining (NHEJ) can lead to frameshift mutation causing a knock-out. Otherwise, a donor DNA template can be provided for precise genetic knock-in through homologous recombination (HR). CRISPR/Cas9 was initially used to disrupt genes related to disease susceptibility in crops such as OsERF922 gene disruption in rice for blast resistance [79] and loss of function in susceptibility gene TaMLO for powdery mildew resistance in wheat [80]. Genome editing has also been used to tackle some abiotic stresses in staple crops like a promoter of a gene AGROS8 was replaced with a stronger one to impart drought tolerance in maize [81].
Due to changing climates, it may be quite beneficial for the farmers to have early maturing varieties, which enables plants to complete crucial developmental periods before the onset of a stress. It has been achieved by disrupting a flower repressing gene SP5G to develop early maturing tomato varieties [82]. For instance, developing climate rice to grow in diverse climates, generally desirable traits are cold, heat and drought tolerance at seedling and reproductive stages [83]. Secondary characters like root and flag leaf traits can be useful to generate cultivars with improved drought and heat tolerance [84]. Here, CRISPR tools could prove to be of great value for exploration of the candidate genes from CWR (O. officinalis, O. nivara and O. glaberrima) for abiotic stress resistance [85].
Genome editing has also huge potential to accelerate the domestication of novel crops form CWR or minor crops with valuable traits for coping with extreme climatic events. This would allow the editing of key genes for domestication in potential new crops for rapid enhancement of currently limited gene pools to maximize the use of germplasm adapted to climate change. Also, multiplexing of CRISPR systems for simultaneous editing of multiple genetic loci can boost the speed and efficiency manifolds. However, there are a number of shortcomings in this approach including off target effects [86], low efficiency of HR, restrictive PAM sequences and regulatory concerns, which paved the way for advent of more sophisticated technologies like DNA free genome editing, base editing and prime editing.
Conventional genome editing using recombinant DNA (rDNA) leads to random host genome integration and can generate undesirable genetic changes or DNA damage [87], along with concerns over genetically modified organism (GMO) regulations with introduction of foreign DNA [88]. DFGE takes care of such critical issues along with reduced risk of off-targets. Initially, it was successfully deployed in rice and tobacco with transfection of protoplast with CRISPR-Cas9 ribonucleoprotein (RNP) [89]. Also, a particle bombardment mediated DFGE approach has been developed in wheat and maize [90, 91].
It is evident that a single base change can cause variation in the elite traits [92], so there required an efficient technique to cause precise and efficient point mutations in plants. CRISPR-Cas9 driven base editing is new approach which accurately transform one DNA base to another without repair template [93]. E.g. Cytidine deaminases convert cytosine (C) to uracil (U), which is treated as thymine (T) in subsequent DNA repair and replication, thus creating C•G to T•A substitution. It has been utilized in wheat, maize and tomato [94] and can be quite useful for gene functional analysis and therefore can assist breeding for better stress adapted varieties.
Another latest milestone in this genome engineering era called prime editing allows introduction of all known 12 base to base conversions in addition to mutations such as insertions and deletions using prime editing guide RNA (pegRNA) [95]. This promising approach opening up numerous possibilities for effectively targeting and modifying desirable genome sequences to accelerate functional genomics and introduction of genes for adaptation to diverse climates can boost breeding for climate smart crop varieties in near future [96].
In this rejuvenated plant mutagenesis breeding era, genome editing can be used in functional genomics for the identification of candidate genes for climate related agronomic, physiological and phonological traits, which can be exploited for crop improvement in adaptation to changing climate. Despite having enormous potential and real world applications of genome editing technologies, the regulatory and ethical concerns may limit it, as happened in a few European countries. In the nutshell, genome editing in complementation with conventional plant breeding can be adopted to develop and deploy climate smart crop varieties in the farmers’ fields.
Advances in phenomics and genomics have generated unprecedented amount of new data, enabling breeders to continuously pushing the crop yields on positive side [97]. Despite success in techniques like genomic selection (GS) in cereals and legumes, lack of predictive accuracy for many complex traits (yield) have revealed their inability to adequately model all relevant factors inherent to such traits due to complexity of the interactions between genetic and environmental components of phenotypic variation [98]. Several mapping studies have shown that such complex traits are controlled by minor genes (polygenes) with small but cumulative effect, hence go undetected while analyzing them in smaller population size.
Relationship between genotype and phenotype is not always linear and small changes on one hierarchical level may have bigger impact on other levels. Many statistical models therefore fail to accurately delineate the non-linear relationships. Additionally, epistatic interactions are hard to detect while mapping genotype to phenotype with linear models due to low power and sheer computational demand [99]. With continuously falling cost of genome sequencing, advent of innovative genetic assays to explore missing heritability and genetic regulation, breeders have access to wide range of high-throughput sensors and imaging techniques for spectrum of traits and field conditions.
Omics technologies (genomics, transcriptomics, proteomics, metabolomics, phenomics, epigenomics and microbiomics) together with approaches to gather information about climate and field environment conditions have become routine in breeding programs now a days. However, ability to accurately predict & select best lines for the specific environment relies on our ability to model these immensely complex systems from web of genomic and phenomic data at hand e.g. multiomics big data. Integrating with phenomics and genomics, AI technologies by assisting with big data, can boost up the development of climate resilient crop varieties with enhanced yield potential and stability and improved tolerance to expected simultaneous environmental stresses (abiotic and biotic).
Accelerated plant breeding for climate resilience is critically dependent upon high resolution, high throughput, field level phenotyping that can effectively screen among better performing breeding lines within larger population across multiple environments [100]. With advent of novel sensors (unmanned air vehicle-UAV), high resolution imagery and new platforms for wide range of traits and conditions, phenomics has been elevating the collection of more phenotypic data over the past decade [101, 102]. High throughput phenotyping (HTP) allows the screening for plant architectural traits and early detection of desirable genotypes. It enables accurate, automated and repeatable measurements for agronomic traits (seedling vigor, flowering time, flower counts, biomass and grain yield, height and leaf erectness, canopy structure) as well as physiological traits (photosynthesis, disease and stress tolerance). HTP methods such as RGB imaging, 3-D scanning, thermal and hyper spectral sensing and fluorescence imaging have been successfully utilized to identify, quantify and monitor plant diseases [103].
By coupling GWAS with high throughput phenotyping facilities, phenomics can be adopted as novel tool for studying plant genetics and genomic characterization enhancing the crop breeding efficiency in era of climate change [104]. Recently, deep learning (DL) has been extensively used to analyze and interpret more phenomic big data, especially for advancing plant image analysis and environmental stress phenotyping [105].
Genomic selection as been extensively used breeding approach for climate resilience in agriculture in last decade, especially for complex polygenic traits. It involves prediction models developed by estimating the combined effect of all existing markers simultaneously on a desirable phenotype. Highly accurate prediction can result into enhanced levels of yields by shortening the breeding cycles. Omics layers (gene expression, metabolite concentration and epistatic signals) can be better predictors of phenotype than SNPs alone due to their molecular proximity to the phenotype. Many such omics layers that explain trait variation have not been made available to the statistical models lowering down its efficacy. Several approaches such as mixed effect linear models and Bayesian models to select only most important predictive SNPs are majorly used.
From the prospective of breeding, by accessing the rich set of omics and environmental data lying between plant genotype and its phenotype, superior and refined impact can be achieved on desirable phenotype. Next gen AI holds promise for GS as acquisition of large scale genomics and phenomics data in addition to molecular layers between them such as transcriptomics, proteomics and epigenomics will facilitate a period, where AI models can identify and explain the complex biological interactions [99].
Next gen AI will surely require knowledge and rationality of breeders as well as farmers to evaluate the efficacy of outcomes. In coming times, agriculture will rely on Next Gen AI methods for making decisions and recommendations from big data (highly heterogeneous and complex) that are representative of environment and system biology based understanding of the behavioral response of plants.
The current pace of yield increase in staple crops like wheat, rice and maize is insufficient to meet the future demand in the wake of climate change [106]. A major limiting factor in plant breeding is the longer generation times of the crops, typically allowing 1–2 generations in a year. Several ‘speeding breeding’ protocols, using extended photoperiods and controlled temperatures have enabled breeders to harvest up to 6 generations per year by reducing the generation time by more than half [107]. Such protocols have been reported in several important crops such as spring wheat (Triticum aestivum) [108], barley (Hordeum vulgare) [109], chickpea (Cicer arietinum), rice (Oryza sativa) [110] and canola (Brassica napus).
Speed breeding can potentially accelerate the discovery and use of allelic diversity in landraces as well as in CWR to be further used in developing climate resilient crop varieties. One such example is recent discovery of new sources of leaf rust resistance after screening of the Vavilov wheat collection using speed breeding along with gene specific molecular markers [111].
Interestingly, speed breeding can also be integrated with advanced technique like gene editing to precisely alter the plant genes for better coping with various biotic and abiotic stresses in threatening climatic changes. In traditional CRISPR gene editing, the sgRNA directs Cas9 enzymes to cut target sequence. ‘CRISPR-ready’ genotypes containing heterologous Cas9 gene can be created. For instance, a transformant harboring a Cas9 transgene can be used a donor to create a stock of elite inbred lines using speed marker-assisted backcrossing. Such an integrated system like ExpressEdit could circumvent the bottlenecks of in vitro manipulation of plant materials also making gene editing fast-tracking [1]. Integration of both the techniques without tissue culture/foreign DNA requires handful of technological breakthroughs with the desirable outcomes being allelic modification, these would bypass genetically modified organism (GMO) label. It has been widely reported that single or multiplex edits can be obtained [112] and could be implemented with some tissue culture free techniques like CRISPR-Cas9 ribonucleoprotein (RNP) complexes in wheat [91] and maize [90].
Genomic selection (GS) unlike MAS uses genome-wide DNA markers in order to predict the genetic gain of breeding individuals for complex traits such as yield [113]. The effect of large number of genetic variants for such a complex traits is captured through linkage disequilibrium (LD) with the genome-wide markers (SNPs), effects of which are determined in large training populations (lines in which marker genotype and trait are measured). Since speed breeding can substantially lowers down the generation periods, it can maximize the benefits by applying genomic selection at every generation to select parents for next generation. Modern genotyping techniques such as rAmpSeq may considerably reduce the genotyping cost for genomic selection [114]. When combined with speed breeding protocol, the approach for stacking of best haplotypes (ones with desirable resistance alleles/desirable edits) could be used rapidly to develop new cultivars [1] with improved performance across multiple traits like coping with adverse climatic variations or any pathogen/insect attack.
Re-domestication of crop plants for capturing the desirable alleles for climate resilience can be sped up by linking it with speed breeding. Re-creation of the polyploids such as groundnut (Arachis hypogea) and banana (Musa spp.) can be benefitted by such approach. Speed breeding could accelerate re-domestication at multiple selection steps after crossing of diploids followed by colchicine application [115]. Ultimately, it will provide access to novel plant traits for developing cultivars of these crops exhibiting disease resistance and stress adaptation. Also, Gene editing and targeted mutagenesis coupled with speed breeding could prove to be more efficient to create healthier foods by biofortification. For instance, the increased content of vitamin B9 in rice and antinutritional glucosinolates from Brassica seeds etc. [1].
Combining all these tools with speed breeding approach would provide rapid access to desirable alleles and novel variation present in CWR and would accelerate the breeding pipelines to develop more climate resilient varieties (Table 1).
Crop species | Target trait/Improved trait | Technology/ Technique used | Reference |
Rice | Submergence tolerance | MAB | [116] |
Rice | Grain number, dense erect panicles and larger grain size | CRISPR/Cas9 | [117] |
Rice | Maintenance of heterosis | CRISPR/Cas9 | [118, 119] |
Wheat | Heat tolerance | GWAS | [120] |
Wheat | Leaf rust, fusarium head blight and stripe rust resistance | Speed breeding | [121, 122, 123, 124] |
Wheat | Powdery mildew-resistant | CRISPR/Cas9 | [80] |
Finger millet | Salt tolerance | RNA sequencing | [125] |
Sorghum | Low and high nitrogen conditions | RNA sequencing | [126] |
Sugarcane | Drought and chilling resistance | CRISPR/Cas9 | [127] |
Maize | Kernel row number | RNA sequencing | [128] |
Maize | High amylopectin content | CRISPR/Cas9 | [129] |
Cotton | Salt and drought tolerance | GWAS | [130] |
Soybean | Salt and drought tolerance | CRISPR/Cas9 | [131, 132] |
Soybean | Salt tolerance | RNA sequencing | [133] |
Chickpea | Drought, salinity, cold and heavy metal stress resistance | RNA sequencing | [134] |
Lentil | Seedling drought stress resistance | RNA sequencing | [135] |
Tomato | High temperature stress responsiveness | GWAS | [136] |
Tomato | Powdery mildew-resistant | CRISPR/Cas9 | [137] |
Tomato | Longer internodes and lighter green leaves with smoother margins | TALEN | [138] |
Tomato | Short (hairy) roots with stunted meristematic, altered branching and increased yield | CRISPR/Cas9 | [139, 140] |
Tomato | Fruits never turn red, altered firmness | CRISPR/Cas9 | [141] |
Broccoli | Dwarf phenotype | CRISPR/Cas9 | [142] |
Watermelon | Albino phenotype | CRISPR/Cas9 | [143] |
Potato | Reduced steroidal glycoalkaloids in leaves and Undetectable level of reducing sugar in tubers | TALEN | [144, 145] |
Mushroom | Reduced browning | CRISPR/Cas9 | [146] |
Banana | Cold and salt resistance | CRISPR/Cas9 | [147] |
Coconut | Root wilt disease | CRISPR/Cas9 | [148] |
Papaya | Drought, heat and cold resistance | CRISPR/Cas9 | [149] |
Apple | Albino phenotype and Blight resistance | CRISPR/Cas9 | [150, 151] |
Utilization of smart breeding tools and techniques for crop improvement.
In the face of ongoing and projected climate change, including higher temperatures and more erratic climate events across extensive regions over the globe, breeding of crop plants with enhanced yield potential and improved resilience to such environments is crucial for global food security. Improved plant varieties that can withstand diseases and pests with efficient use of fewer resources, exhibiting stable yields amidst stressful climate in near future could only help to achieve the goal of climate resilient agriculture. In order to be able to make contribution in climatic resilience, research attention is indispensable for currently underutilized crop species. The concept of smart breeding largely depends upon generating large breeding populations, efficient high throughput phenotyping, big data management tools and downstream molecular techniques to tackle the vulnerability of crop plants to changing climate (Figure 3). The efficient preservation and conservation of plant genetic resources is also a pre requisite for climate smart breeding. Strategies for capturing the novel variation may include the state of the art tools such as gene editing to directly introduce novel alleles found in wild plants into domesticated crop varieties. Generating new crop cultivars with the capability to tolerate multiple stresses can be achieved with increasing information on their basal physiological and genetic mechanisms. The technological improvements in phenotypic and genotypic analysis, as well as the biotechnological and digital revolution could definitely pave the way for developing and deployment of climate smart varieties in coming times.
Compilation of state-of-the-art genomic, phenomic and computational tools comprising smart breeding approach for climatic resilience in agriculture.
The authors declare they have no conflict of interest.
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