Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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He gained relevant professional experience in fields such as environmental science, chemistry, and waste management. Through all his academic and professional publications, he has fully practiced both qualitative and quantitative research methods. Additionally, he is the founder and CEO of ENQUAS Consulting, an investigation and consultancy office practicing in environmental, quality, and safety domains. Currently, he works as a full-time professor at the National School of Applied Sciences (ENSAH), Abdelmalek Essaadi University, Morocco. In his spare time, he acts as an editorial board member, reviewer, and proofreader for several reputed scientific journals.",institutionString:"Abdelmalek Essaâdi University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Abdelmalek Essaâdi University",institutionURL:null,country:{name:"Morocco"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1128",title:"Environmental Health",slug:"medicine-public-health-environmental-health"}],chapters:[{id:"68099",title:"Particulate Matter Exposure: Genomic Instability, Disease, and Cancer Risk",slug:"particulate-matter-exposure-genomic-instability-disease-and-cancer-risk",totalDownloads:916,totalCrossrefCites:0,authors:[{id:"291626",title:"Ph.D.",name:"Lyda",surname:"Espitia - Pérez",slug:"lyda-espitia-perez",fullName:"Lyda Espitia - Pérez"},{id:"296374",title:"BSc.",name:"Luisa",surname:"Jimenez - Vidal",slug:"luisa-jimenez-vidal",fullName:"Luisa Jimenez - Vidal"},{id:"296376",title:"MSc.",name:"Pedro Juan",surname:"Espitia - Pérez",slug:"pedro-juan-espitia-perez",fullName:"Pedro Juan Espitia - Pérez"}]},{id:"68542",title:"Pollution of Water Resources and Environmental Impacts in Urban Areas of Developing Countries: Case of the City of Les Cayes (Haiti)",slug:"pollution-of-water-resources-and-environmental-impacts-in-urban-areas-of-developing-countries-case-o",totalDownloads:1039,totalCrossrefCites:4,authors:[{id:"292961",title:"Dr.",name:"Ketty",surname:"Balthazard-Accou",slug:"ketty-balthazard-accou",fullName:"Ketty Balthazard-Accou"},{id:"293512",title:"Dr.",name:"Evens",surname:"Emmanuel",slug:"evens-emmanuel",fullName:"Evens Emmanuel"},{id:"293513",title:"Prof.",name:"Patrice",surname:"Agnamey",slug:"patrice-agnamey",fullName:"Patrice Agnamey"},{id:"293514",title:"Prof.",name:"Christian",surname:"Raccurt",slug:"christian-raccurt",fullName:"Christian Raccurt"}]},{id:"70169",title:"Rainwater Harvesting Infrastructure Management",slug:"rainwater-harvesting-infrastructure-management",totalDownloads:877,totalCrossrefCites:0,authors:[{id:"286307",title:"Dr.",name:"Mirzi",surname:"Betasolo",slug:"mirzi-betasolo",fullName:"Mirzi Betasolo"}]},{id:"66846",title:"Fluoride in Volcanic Areas: A Case Study in Medical Geology",slug:"fluoride-in-volcanic-areas-a-case-study-in-medical-geology",totalDownloads:879,totalCrossrefCites:1,authors:[{id:"189270",title:"Ph.D.",name:"Diana",surname:"Linhares",slug:"diana-linhares",fullName:"Diana Linhares"},{id:"189271",title:"Prof.",name:"Armindo",surname:"Rodrigues",slug:"armindo-rodrigues",fullName:"Armindo Rodrigues"},{id:"221729",title:"Dr.",name:"Patricia",surname:"Garcia",slug:"patricia-garcia",fullName:"Patricia Garcia"}]},{id:"68535",title:"Biophysical and Economic Factors of Climate Change Impact Chain in the Agriculture Sector of ECOWAS",slug:"biophysical-and-economic-factors-of-climate-change-impact-chain-in-the-agriculture-sector-of-ecowas",totalDownloads:664,totalCrossrefCites:1,authors:[{id:"280871",title:"Dr.",name:"Calvin",surname:"Atewamba",slug:"calvin-atewamba",fullName:"Calvin Atewamba"},{id:"280886",title:"Prof.",name:"Edward R",surname:"Rhodes",slug:"edward-r-rhodes",fullName:"Edward R Rhodes"}]},{id:"66922",title:"Mercury Cycling in the Gulf of Gdańsk (Southern Baltic Sea)",slug:"mercury-cycling-in-the-gulf-of-gda-sk-southern-baltic-sea-",totalDownloads:658,totalCrossrefCites:1,authors:[{id:"286374",title:"Dr.",name:"Dominika",surname:"Saniewska",slug:"dominika-saniewska",fullName:"Dominika Saniewska"}]},{id:"66661",title:"Metazoan Endoparasites as Biological Indicators of Baltic Cod Biology",slug:"metazoan-endoparasites-as-biological-indicators-of-baltic-cod-biology",totalDownloads:902,totalCrossrefCites:0,authors:[{id:"290007",title:"Prof.",name:"Kurt",surname:"Buchmann",slug:"kurt-buchmann",fullName:"Kurt Buchmann"}]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"247865",firstName:"Jasna",lastName:"Bozic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/247865/images/7225_n.jpg",email:"jasna.b@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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\n\t\t\t
1. Introduction
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1.1. Sources of biomass
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The two main sources of biomass for energy generation are purpose-grown energy crops and waste materials (Larkin et al., 2004). Energy crops, such as Miscanthus and short rotation woody crops (coppice), are cultivated mainly for energy purposes and are associated with the food vs. fuels debate, which is concerned with whether land should be used for fuel rather than food production. The use of residues from agriculture, such as barley, canola, oat and wheat straw, for energy generation circumvents the food vs. fuel dilemma and adds value to existing crops (Chico-Santamarta et al., 2009). In fact, these residues represent an abundant, inexpensive and readily available source of renewable lignocellulosic biomass (Liu et al., 2005).
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1.2. Current issues related to biomass utilization
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The main problem with agricultural straw is its relatively low density in its original or baled forms. The bulk density of loose and standard baled straw is approximately 40 kg/m3 and 100 kg/m3, respectively, compared with the bulk density of unprocessed wood residue, which is approximately 250 kg/m3 (Demirbaş, 2001; Tripathi et al., 1988). The relative low density of straw makes it more expensive to transport compared to wood and coal because a lower mass of straw can be transported per unit volume. Additionally, a larger storage area/volume is required for baled straw compared to wood chip. Densification into pellets increases the bulk density of biomass (McMullen et al., 2005; Obernberger and Thek,2004) and as a result, the net calorific content per unit volume is increased (Bhattacharya et al., 1989) and the storage, transport and handling of the material is easier and cheaper (Balatinecz, 1983; Bhattacharya et al., 1989; Kaliyan and Morey, 2006).
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The quality of fuel pellet is usually assessed based on its density and durability. High bulk density increases storage and transport capacity of pellets (Adapa et al., 2007; Mani et al., 2003). Since feeding of boilers and gasifiers generally is volume-dependent, variations in bulk density should be avoided (Larsson et al., 2008). A bulk density of 650 kg/m3 is stated as design value for wood pellet producers (Obernberger and Thek 2004). Low durability of pellets results in problems like disturbance within pellet feeding systems, dust emissions, and increased risk of fire and explosions during pellet handling and storage (Temmerman et al. 2006).
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Densification of straw and determining the optimal parameters involved is an art in itself. The entire process involves securing of baled straw from agricultural fields, size reduction (chopping and grinding), application of pre-treatment (chemical, physico-chemical, and biological), determining the physical and frictional properties of straw grinds, lignocellulosic characterization of straw, lab-scale and pilot-scale densification of grinds into pellets to determine the effect of various independent parameters on quality (density and durability), and energy analysis/ balance (Fig. 1). This chapter will only address the effect and need of lignocellulose characterization, pre-treatment and size reduction, and physical properties on densification of agricultural straw.
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Figure 1.
Processing steps involved in converting straw from field to pelletized product.
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2. Lignocellulosic biomass characterization
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2.1. Structure of lignocellulosic material
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Lignocellulosic material refers to plant biomass that is composed of cellulose, hemicellulose, and lignin (Fig. 2) (Lin and Tanaka, 2006). The major combustible component of non-food energy crops is cellulose, followed by lignin.
\n\t\t\t\t
\n\t\t\t\t\tCellulose: Cellulose is an organic polysaccharide consisting of a linear chain of several hundreds to over nine thousand β(1→4) linked D-glucose (C6H10O5)n units (Crawford, 1981; Updegraff, 1969). Cellulose, a fibrous, tough, water-insoluble substance, is found in the cell walls of plants, particularly in the stalks, stems, trunks and all the woody portions of the plant body (Nelson and Cox, 2005). Cellulose comprises 40-60% of the dry weight of plant material (the cellulose content of cotton is 90% and that of wood is 50%) (Encyclopædia Britannica, 2008; USDE, 2006).
\n\t\t\t\t
\n\t\t\t\t\tZandersons et al. (2004) and Shaw (2008) reported that binding of wood material during hot pressing / densification is mainly dependent on the transition of cellulose into the amorphous state. According to Hon (1989), due to the semi-crystalline structure, hydrogen bonded cellulose cannot be dissolved easily in conventional solvents, and it cannot be melted before it burns; hence, cellulose itself is not a suitable adhesive. This can be overcome by breaking the hydrogen bonds, thus making the cellulose molecule more flexible (Hon 1989). Cellulose requires a temperature of 320°C and pressure of 25 MPa to become amorphous in water (Deguchi et al., 2006).
\n\t\t\t\t
\n\t\t\t\t\tHemicellulose: Hemicellulose is made of several heteropolymers (matrix polysaccharides) present in almost all plant cell walls along with cellulose (Fig. 2). While cellulose is crystalline, strong, and resistant to hydrolysis; hemicellulose has a random, amorphous structure with less strength. Hemicellulose is a polysaccharide related to cellulose and comprises 20-40% of the biomass of most plants. In contrast to cellulose, hemicellulose is derived from several sugars in addition to glucose, including especially xylose but also mannose, galactose, rhamnose and arabinose (Shambe and Kennedy, 1985). Branching in hemicellulose produces an amorphous structure that is more easily hydrolyzed than cellulose (Shaw, 2008). Also, hemicellulose can be dissolved in strong alkali solutions. Hemicellulose provides structural integrity to the cell. Some researchers believe that natural bonding may occur due to the adhesive properties of degraded hemicellulose (Bhattacharya et al., 1989).
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\n\t\t\t\t\tLignin: Lignin is a complex chemical compound most commonly derived from wood and is an integral part of the cell walls of plants (Lebo et al., 2001; Zandersons et al., 2004). The compound has several unusual properties as a biopolymer, not the least its heterogeneity in lacking a defined primary structure. Lignin fills the spaces in the cell wall between cellulose and hemicellulose (Fig. 2). It is covalently linked to hemicellulose and thereby crosslinks different plant polysaccharides, conferring mechanical strength to the cell wall and consequently to the whole plant structure (Chabannes et al., 2001).
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Lignin acts as a binder for the cellulose fibres (Fig. 2). van Dam et al. (2004) have reported that lignin can be used as an intrinsic resin in binderless board production due to the fact that when lignin melts (temperatures above 140°C), it exhibits thermosetting properties. Lignin is the component that permits adhesion in the wood structure, and is a rigidifying and bulking agent (Anglès et al., 2001). Lehtikangas (2001) reported that water (8-15%) in pellets will reduce the softening temperature of lignin to 100-135°C by plasticizing the molecular chains. The adhesive properties of thermally softened lignin are thought to contribute considerably to the strength characteristics of briquettes made of lignocellulosic materials (Granada et al., 2002; Shaw, 2008).
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Figure 2.
Location and arrangement of cellulose microfibrils in plant cell walls (Murphy and McCarthy, 2005; Shaw, 2008).
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2.2. Rapid characterization of lignocellulosic materials
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The effect of various pre-processing and pre-treatment methods (Fig. 1) on the lignocellulosic matrix at the molecular level is not well understood. Applications of pre-processing methods such as size reduction or increasing porosity, and pre-treatment techniques such as steam explosion on agricultural biomass have demonstrated an improvement in pellet (compact) quality that can be attributed to the changes in the lignocellulosic components and distribution (Bagby, 1982; Focher et al., 1998). Therefore, it is critical to rapidly quantify the change in cellulose, hemicelluloses and lignin components of biomass due to application of pre-treatment methods.
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Infrared spectroscopy has the potential to produce qualitative and quantitative analytical data for samples with minimum or no sample preparation, and at high speed and throughput (Adapa et al., 2011b and 2009; Budevska, 2002; Luypaert et al., 2003; Smola and Urleb, 2000; Tucker et al., 2000). Traditionally, chemical analyses of the individual components (e.g., lignin) of lignocellulosics have been performed by acid hydrolysis followed by gravimetric determination of lignin (Kelley et al., 2004). These methods can provide highly precise data. However, these methods are laborious, time-consuming, and, consequently, expensive to perform and sample throughput is limited.
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2.3. Fourier transform infrared spectroscopy
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Fourier Transform Infrared Spectroscopy (FTIR) can be used to rapidly characterize and quantify cellulose-hemicellulose-lignin composition prior to and after application of various methods of pre-processing and pre-treatment of biomass (Adapa et al., 2009). The quantitative analysis of FTIR absorption spectrometry is based on the Bouguer-Beer-Lambert law (Sherman Hsu, 1997). According to this law, the intensities of absorption bands are linearly proportional to the concentration of each component in a homogenous mixture or solution.
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Regression equations to predict the lignocellulosic content of agricultural biomass can be developed using pure cellulose, hemicelluloses and lignin as reference samples, and subsequently mixing them in different proportions to determine the change in absorption intensity at characteristic peak height (Adapa et al., 2011b). An overview of the experimental procedure to characterize the lignocellulosic composition is provided in Figure 3.
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Pure cellulose has five distinct characteristic/ prominent peaks at wavenumbers of 1431, 1373, 1338, 1319 and 1203 cm-1. Similarly, hemicellulose (xylan) has prominent peaks at wavenumbers of 1606, 1461, 1251, 1213, 1166 and 1050 cm-1. The lignin spectrum has characteristic peaks at wavenumber of 1599, 1511, 1467, 1429, 1157 and 1054 cm-1. The intensity of absorption at characteristic peak heights of cellulose, hemicellulose and lignin were used to develop regression equations to predict lignocellulosic composition of any agricultural biomass (Table 1) (Adapa et al., 2011b).
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Figure 3.
Experimental procedure followed to characterize lignocellulosic composition of agricultural straw (Adapa et al., 2011b).
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\n\t\t\t\t\t\t\t\tEquation\n\t\t\t\t\t\t\t
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\n\t\t\t\t\t\t\t\t% Mean Absolute Deviation\n\t\t\t\t\t\t\t
Regression equations to predict the lignocellulosic composition of agricultural biomass (Adapa et al., 2011b).
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3. Pre-treatment of lignocellulosic biomass
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3.1. Need for pre-treatment
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Upon densification, many agricultural biomass materials, especially those from straw and stover, result in a poorly formed pellets or compacts that are more often dusty, difficult to handle and costly to manufacture. This is caused by lack of complete understanding on the natural binding characteristics of the components that make up biomass (Sokhansanj et al., 2005). The natural binding characteristics of lignocellulosic biomass can be enhanced by modifying the structure of cellulose-hemicellulose-lignin matrix by application of pre-processing and pre-treatment methods (Sokhansanj et al. 2005). It is postulated that by disrupting the lignocellulosic matrix of biomass materials via application of various chemical, physico-chemical (steam explosion, microwave, and radio frequency heating), and biological pre-treatment, the compression and compaction characteristics can be improved (Shaw 2008; Kashaninejad and Tabil, 2011). When high molecular amorphous polysaccharides are reduced to low molecular components, the polymer becomes more cohesive in the presence of moisture (Chen et al., 2004). The cellulose-hemicellulose-lignin matrix can be broken down to smaller amorphous molecules through acid or alkaline hydrolysis as well as through steam explosion (Ladisch, 1989; Vlasenko, 1997). Alkaline or acid solutions are often used for pre-treatment of biomass and the effect of pre-treatment depends on the lignin content of biomass. When biomass is treated with dilute alkaline solution, the internal surface area of the material is increased by swelling. Swelling causes a decrease in the degree of polymerization, separation of structural linkages between lignin and carbohydrates and disruption of the lignin structure (Fan et al., 1987). Increased moisture content resulting from chemical and enzymatic treatments is a problem, as the treated biomass has to be dried prior to densification. Steam explosion results in the hemicelluloses being hydrolyzed and water soluble, the cellulose is slightly depolymerized, the lignin melts and is depolymerized, which aid in binding particles together during densification. Zandersons et al. (2004) stated that activation of lignin and changes in the cellulosic structure during the steam explosion process facilitate the formation of new chemical bonds. Lam et al. (2008) reported that the quality (durability) of compacts produced from steam exploded sawdust was 20% higher than non-treated sawdust.
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3.2. Physico-chemical pre-treatments
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3.2.1. Steam explosion
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Steam explosion is one of the most applied pre-treatment processes owing to its low use of chemicals and limited energy consumption (Harmsen et al., 2010). During steam explosion pre-treatment process, the lignocellulosic biomass is heated with high pressure saturated steam having temperatures typically in the range of 180-230°C for 2-10 minutes. Subsequently, the substrate is quickly flashed to atmospheric pressure; as a result, the water inside the substrate vaporizes and expands rapidly, disintegrating the biomass (Grous et al., 1985; Kokta and Ahmed, 1998; Zimbardi et al., 1999). This causes great reduction in the particle size of the substrate (Fig. 4). The heart of the explosion pulping process is the reactor, which allows the use of high pressure during heating and cooking. The reactor can be of either the batch (Fig. 5) (Jin and Chen, 2006) or continuous type (Fig. 6) (Kokta and Ahmed, 1998; Adapa et al., 2010a).
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Figure 4.
Photographs showing the non-treated (30 mm hammer mill screen size) and steam exploded barley, canola, oat and wheat straw grinds.
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The extent of chemical and structural modifications from steam-explosion pre-treatment depends on residence time, temperature, particle size and moisture content (Sun and Cheng, 2002). However, the severity (Ro) of steam explosion is quantified as a function of retention time and reaction temperature (Equation 1) (Overend and Chornet, 1987; Viola et al. 2008).
Where T is the temperature in °C and t is the time in minutes.
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According to Zimbardi et al. (1999), the simplest way to carry out steam explosion is by batch procedure, hence widely reported in literature. However, the continuous reactors are of major interest for industrial applications. They have indicated that although the products obtained at the same treatment, severity in batch and continuous reactors are macroscopically different at first sight, there is still a lack of understanding to explain these differences. Consequently, they have developed experimental relationships between the two systems useful in making the data transfer straightforward (Equation 2).
Schematic diagram of the FJM-200 fluidized bed opposed jet mill. 1, Infeed; 2, collection; 3, classification section; 4, grinding section; 5, compressed air; 6, discharge opening (Jin and Chen, 2006).
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Figure 6.
The Andritz (ANDRITZ AG, Graz, Austria) continuous biomass steam explosion facility for manufacturing of Medium Density and High Density Fiberboards (MDF/HDF), Forintek pilot plant at the FPInnovations, Quebec City, Quebec (Adapa et al., 2010a).
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3.2.2. Microwave and radio frequency (RF) heating
\n\t\t\t\t\t
Dielectric heating is an alternative method to conventional heating. Unlike conduction/convection heating, which is based on superficial heat transfer, dielectric heating is based on volumetric and rapid heat transfer (de la Hoz et al., 2005). When lignocellulosic materials are placed in an electric field for dielectric heating pre-treatment, dipole molecules such as water or other dielectric materials, rotate vigorously to orient in the field. More polar components will absorb more energy, and thus, “hot spots” will be created in non-homogeneous materials. It is hypothesized that this unique heating feature results in an “explosion” effect in the particles and improves the disruption of the lignocellulosic structures. In addition, the non thermal effects of electromagnetic field accelerate the disintegration of the crystal structures (de la Hoz et al., 2005). Dielectric heating can be categorized as microwave or radio frequency depending on the wavelength used in the heating devices (Oberndorfer et al., 2000).
\n\t\t\t\t\t
Microwave is electromagnetic waves between 300 MHz (wavelength 1 m) and 300 GHz (wavelength 1 mm). This range of spectrum lies between infrared and radio frequency radiation. Microwave irradiation has been extensively used in many processes because of its high heating efficiency and easy operation. Microwave energy can penetrate into materials and heat them quickly and uniformly. Microwave irradiation is considered to create thermal and non thermal effects. It has been applied as an efficient pre-treatment technique to enhance the hydrolysis of biomass materials. Some studies have demonstrated that microwave irradiation can change the structure of lignocellulosic materials and degrade or reduce lignin content, reduce cellulose crystallinity, and increase porosity and surface area of the materials (Azuma, 1984; Zhu et al., 2006b; Kashaninejad and Tabil, 2011).
In order to increase the efficiency of microwave heating pre-treatment, some researchers have combined microwave treatment with alkaline treatment such as NaOH or Ca(OH)2. Some used alkaline solution during microwave heating treatment (Zhu et al., 2005; 2006a; 2006b; 2006c; Keshwani et al., 2007; Kashaninejad and Tabil, 2011) and some applied the alkaline solution before the lignocellulosic materials were subjected to microwave irradiation (Zhu et al., 2006a; Hu and Wen, 2008). Combination of microwave irradiation and alkali treatment improves the degradation of biomass by accelerating the reactions during the pre-treatment process compared with the conventional heating chemical pre-treatment process. Remarkable changes (Table 2) have been reported in the chemical composition of biomass samples after microwave-alkali pre-treatment, particularly in hemicellulose, lignin, and cellulose contents (Kashaninejad and Tabil, 2011). It has been reported that alkali treatment dissolves lignin and hemicellulose, and microwave irradiation facilitates dissolving these components in alkali solutions (Jackson, 1977; Kumar et al., 2009; Lesoing et al., 1980; Zhu et al., 2005). Biomass samples pretreated by microwave-alkali technique have lower lignin, hemicellulose, and cellulose than samples pretreated by microwave-distilled water or untreated samples. Moreover, degradation and depolymerisation of lignin to smaller phenolic components is another influence of microwave-alkali pre-treatment that could be considered as binder in densification process. The pellets made from microwave-chemical pre-treated biomass grinds have significantly higher density and tensile strength (Table 3) than the untreated or samples pre-treated by microwave alone (Kashaninejad and Tabil, 2011).
\n\t\t\t\t\t
Radio frequency (RF) can penetrate more deeply into the materials compared with microwave heating because the radio frequency wavelength is up to 360 times greater than microwave (Marra et al., 2007). This unique characteristic is an advantage to treat large amount of material and it is easier to scale up the process. While radio frequency as a heating method has been widely applied in food-processing industries, there is not much report on application of radio frequency heating for lignocellulosic materials pre-treatment. Hu et al. (2008) used radio frequency heating in the NaOH pre-treatment of switchgrass to enhance its enzymatic digestibility. Because of the unique features of radio frequency heating (i.e., volumetric heat transfer, deep heat penetration of the samples, etc.), switchgrass could be treated on a large scale, at high solids content, and with a uniform temperature profile. At 20% solids content, radio frequency-assisted alkali pre-treatment (at 0.1 g of NaOH/g of biomass loading and 90°C) resulted in a higher xylose yield than the conventional heating pre-treatment. The optimal particle size and alkali loading in the radio frequency pre-treatment were determined to be 0.25-0.50 mm and 0.25 g of NaOH/g of biomass, respectively.
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Treatment
\n\t\t\t\t\t\t\t\t
Wheat straw
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Barley straw
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Protein
\n\t\t\t\t\t\t\t\t
Lignin
\n\t\t\t\t\t\t\t\t
Ash
\n\t\t\t\t\t\t\t\t
Starch
\n\t\t\t\t\t\t\t\t
Cellulose
\n\t\t\t\t\t\t\t\t
Hemicellulose
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Protein
\n\t\t\t\t\t\t\t\t
Lignin
\n\t\t\t\t\t\t\t\t
Ash
\n\t\t\t\t\t\t\t\t
Starch
\n\t\t\t\t\t\t\t\t
Cellulose
\n\t\t\t\t\t\t\t\t
Hemicellulose
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Untreated
\n\t\t\t\t\t\t\t\t
1.99b
\n\t\t\t\t\t\t\t\t
8.33a
\n\t\t\t\t\t\t\t\t
6.33f
\n\t\t\t\t\t\t\t\t
1.11d
\n\t\t\t\t\t\t\t\t
44.99b
\n\t\t\t\t\t\t\t\t
27.96a
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
1.61d
\n\t\t\t\t\t\t\t\t
11.95a
\n\t\t\t\t\t\t\t\t
6.03d
\n\t\t\t\t\t\t\t\t
0.79c
\n\t\t\t\t\t\t\t\t
46.93a
\n\t\t\t\t\t\t\t\t
27.40a
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave-distilled water
\n\t\t\t\t\t\t\t\t
2.24a
\n\t\t\t\t\t\t\t\t
8.01c
\n\t\t\t\t\t\t\t\t
8.87e
\n\t\t\t\t\t\t\t\t
1.48b
\n\t\t\t\t\t\t\t\t
39.69d
\n\t\t\t\t\t\t\t\t
22.62b
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
2.01a
\n\t\t\t\t\t\t\t\t
8.85b
\n\t\t\t\t\t\t\t\t
6.28d
\n\t\t\t\t\t\t\t\t
1.08b
\n\t\t\t\t\t\t\t\t
45.25b
\n\t\t\t\t\t\t\t\t
27.21a
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave-NaOH (1%)
\n\t\t\t\t\t\t\t\t
1.41e
\n\t\t\t\t\t\t\t\t
7.82d
\n\t\t\t\t\t\t\t\t
17.32b
\n\t\t\t\t\t\t\t\t
1.89a
\n\t\t\t\t\t\t\t\t
35.82e
\n\t\t\t\t\t\t\t\t
12.32d
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
1.80b
\n\t\t\t\t\t\t\t\t
6.65e
\n\t\t\t\t\t\t\t\t
16.96b
\n\t\t\t\t\t\t\t\t
0.60e
\n\t\t\t\t\t\t\t\t
40.81c
\n\t\t\t\t\t\t\t\t
8.74c
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave-NaOH (2%)
\n\t\t\t\t\t\t\t\t
1.36f
\n\t\t\t\t\t\t\t\t
7.09f
\n\t\t\t\t\t\t\t\t
34.77a
\n\t\t\t\t\t\t\t\t
0.27f
\n\t\t\t\t\t\t\t\t
34.77f
\n\t\t\t\t\t\t\t\t
4.06f
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
1.62d
\n\t\t\t\t\t\t\t\t
4.52f
\n\t\t\t\t\t\t\t\t
41.43a
\n\t\t\t\t\t\t\t\t
0.54f
\n\t\t\t\t\t\t\t\t
35.22d
\n\t\t\t\t\t\t\t\t
5.46d
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave-Ca(OH)2 (1%)
\n\t\t\t\t\t\t\t\t
1.85c
\n\t\t\t\t\t\t\t\t
8.11b
\n\t\t\t\t\t\t\t\t
12.24d
\n\t\t\t\t\t\t\t\t
0.69e
\n\t\t\t\t\t\t\t\t
45.66a
\n\t\t\t\t\t\t\t\t
14.94c
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
1.81b
\n\t\t\t\t\t\t\t\t
7.27d
\n\t\t\t\t\t\t\t\t
13.21c
\n\t\t\t\t\t\t\t\t
0.72d
\n\t\t\t\t\t\t\t\t
41.01c
\n\t\t\t\t\t\t\t\t
15.00b
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave-Ca(OH)2 (2%)
\n\t\t\t\t\t\t\t\t
1.52d
\n\t\t\t\t\t\t\t\t
7.55e
\n\t\t\t\t\t\t\t\t
15.89c
\n\t\t\t\t\t\t\t\t
1.31c
\n\t\t\t\t\t\t\t\t
42.56c
\n\t\t\t\t\t\t\t\t
11.10e
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
1.68c
\n\t\t\t\t\t\t\t\t
8.16c
\n\t\t\t\t\t\t\t\t
16.73b
\n\t\t\t\t\t\t\t\t
1.19a
\n\t\t\t\t\t\t\t\t
41.24c
\n\t\t\t\t\t\t\t\t
8.97c
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\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Means with the same letters designation (a, b, c, d, and e) in a column are not significantly different at P = 0.05.
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Table 2.
Chemical composition (% dry basis) of untreated and microwave pretreated of wheat and barley straw at power 713 W.
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\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Treatment
\n\t\t\t\t\t\t\t\t
Wheat straw
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Barley straw
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Fracture load (N)
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Tensile strength (MPa)
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\n\t\t\t\t\t\t\t\t
Fracture load (N)
\n\t\t\t\t\t\t\t\t
Tensile strength (MPa)
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\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Untreated
\n\t\t\t\t\t\t\t\t
19.10±5.61
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0.81±0.24
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\n\t\t\t\t\t\t\t\t
16.25±5.30
\n\t\t\t\t\t\t\t\t
0.68±0.22
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\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave- distilled water
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35.00±11.93
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1.48±0.46
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
14.25±5.31
\n\t\t\t\t\t\t\t\t
0.61±0.21
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave- NaOH (1%)
\n\t\t\t\t\t\t\t\t
85.46±22.94
\n\t\t\t\t\t\t\t\t
3.99±0.82
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
57.13±12.12
\n\t\t\t\t\t\t\t\t
2.42±0.47
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave- NaOH (2%)
\n\t\t\t\t\t\t\t\t
88.00±15.86
\n\t\t\t\t\t\t\t\t
3.69±0.66
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
90.75±22.42
\n\t\t\t\t\t\t\t\t
3.59±0.98
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave- Ca(OH)2 (1%)
\n\t\t\t\t\t\t\t\t
67.05±19.82
\n\t\t\t\t\t\t\t\t
3.03±0.79
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
42.38±10.30
\n\t\t\t\t\t\t\t\t
1.83±0.49
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
Microwave- Ca(OH)2 (2%)
\n\t\t\t\t\t\t\t\t
78.25±25.07
\n\t\t\t\t\t\t\t\t
3.31±1.03
\n\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t
67.25±19.94
\n\t\t\t\t\t\t\t\t
2.88±0.91
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t
Table 3.
Effect of microwave-chemical pre-treatments on fracture load and tensile strength of wheat and barley straw pellets at power 713 W.
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3.2.3. Chemical pre-treatment
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Different chemicals such as acids, alkalis, oxidizing agents and ozone have been used for chemical pre-treatment of lignocellulosic materials. Depending on the type of chemical used, pre-treatment could have different effects on structural components. Alkaline pre-treatment, ozonolysis, peroxide and wet oxidation pre-treatments were reportedly more effective in lignin removal, whereas dilute acid pre-treatment was more efficient in hemicellulose solubilization (Galbe and Zacchi, 2002; Sánchez and Cardona, 2008; Tomas-Pejo et al., 2008).
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\n\t\t\t\t\t\tAcid Hydrolysis: Inorganic acids such as H2SO4 and HCl have been used for pre-treatment of lignocellulosic materials and have been used on a wide range of feedstocks ranging from hardwoods to grasses and agricultural residues. Acid hydrolysis can be classified as concentrated or dilute-acid hydrolysis based on the dose of acid used in the process. In the first case, the biomass is treated with high concentration of acids at ambient temperatures, which results in high conversion of lignocellulosic materials. Although concentrated acids are powerful agents for cellulose hydrolysis, they are toxic, corrosive, hazardous, and thus require reactors that are resistant to corrosion, making the pre-treatment process very expensive. In addition, the concentrated acid must be recovered after hydrolysis to make the process economically feasible (Galbe and Zacchi, 2002; Sun and Cheng, 2002).
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Dilute-acid hydrolysis has been successfully developed for pre-treatment of lignocellulosic materials. Sulfuric acid at concentrations usually below 4% (wt) has been of the most interest in such studies as it is inexpensive and effective. Dilute H2SO4 pre-treatment can achieve high reaction rates and significantly improve cellulose hydrolysis (Esteghlalian et al., 1997). High temperature is favorable to attain acceptable rates of cellulose conversion. Despite low acid concentration and short reaction time, the use of high temperatures in dilute-acid hydrolysis accelerates the rate of hemicellulose sugar decomposition and increases equipment corrosion (Galbe and Zacchi, 2002; Taherzadeh and Karimi, 2007).
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\n\t\t\t\t\t\tAlkali hydrolysis: Dilute alkali such as sodium, potassium, calcium, and ammonium hydroxides have been used for pre-treatment of lignocellulosic materials in alkali hydrolysis. The effectiveness of these agents depends on the lignin content of the materials. Temperature and pressure are lower in alkali pre-treatment compared with other pre-treatment methods (Mosier et al., 2005). Alkali pre-treatment can be conducted at ambient conditions, but process time is longer (hours or days instead of minutes or seconds). Compared with acid process, alkaline process causes less sugar degradation, and many of the caustic salts can be recovered and/or regenerated.
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Sodium hydroxide has been studied more than other agents (Soto et al., 1994; Fox et al., 1989; MacDonald et al., 1983). Treatment of lignocellulosic materials using dilute NaOH results in swelling, leading to an increase in internal surface area, a decrease in the degree of polymerization, a decrease in crystallinity, separation of structural linkages between lignin and carbohydrates, and disruption of the lignin structure. However, calcium hydroxide (lime) is the least expensive hydroxide and has been shown to be an effective pre-treatment agent. The process of lime pre-treatment involves slurrying the lime with water, spraying it onto the biomass material, and storing the material in a pile for a period of hours to weeks. The particle size of the biomass is typically 10 mm or less. Elevated temperatures reduce contact time.
\n\t\t\t\t\t
\n\t\t\t\t\t\tOxidizing agents: In this pre-treatment, an oxidizing compound such as hydrogen peroxide (H2O2) or peracetic acid (CH3CO3H) is used to treat lignocellulosic materials and sometimes is applied in combination of an alkaline solution (e.g. NaOH) to improve effectiveness. This pre-treatment is usually carried out under mild temperature. This pre-treatment is more effective to increase crop residue digestibility compared with NaOH pre-treatment alone. Gould (1984) delignified agricultural residues using 1% H2O2 at 25°C for 18–24 h. Under this condition, more than half of the lignin and most of hemicellulose were solubilized. The pre-treatment of cane bagasse with H2O2 greatly enhanced its susceptibility to further hydrolysis. About 50% of the lignin and most of the hemicellulose were solubilized by 2% H2O2 at 30°C within 8 h, and a 95% efficiency of glucose production from cellulose was achieved in the subsequent saccharification by cellulase at 45°C for 24 h (Azzam, 1989).
\n\t\t\t\t\t
\n\t\t\t\t\t\tOzonolysis: In this process, ozone is used to change the structure of lignocellulosic materials and has been used for different materials such as wheat straw (Ben-Ghedalia and Miron, 1981), bagasse, green hay, peanut, pine ( Neely, 1984), cotton straw (Ben-Ghedalia and Shefet, 1983) and poplar sawdust (Vidal and Molinier, 1988). Ozonolysis is carried out at room temperature and normal pressure. It can effectively remove the lignin without producing any toxic residues. In this process, hemicellulose is slightly affected, but no change in cellulose has been reported. The main restriction of this process is the large amount of ozone utilization that makes the process expensive (Sun and Cheng, 2002). Binder et al. (1980) reported 60% removal of the lignin from wheat straw using ozone pre-treatment. Enzymatic hydrolysis yield increased from 0% to 57% as the percentage of lignin decreased from 29% to 8% after ozonolysis pre-treatment of poplar sawdust (Vidal and Molinier, 1988). Garcia-Cubero et al. (2009) studied the ozonolysis pre-treatment of wheat straw in a fixed bed reactor at room conditions and concluded that enzymatic hydrolysis yield of up to 88.6% compared to 29% in non-ozonated sample.
\n\t\t\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
3.3. Biological pre-treatment
\n\t\t\t\t
Most pre-treatments require expensive instruments or equipment that require high energy requirements, depending on the process. In particular, physical and thermo-chemical processes require ample amount of energy to change the lignocellulosic structure of biomass. Biological pre-treatment using various types of rot fungi is a process that does not require high energy for lignin removal from a lignocellulosic biomass, despite extensive lignin degradation. Biological pre-treatments are safe, environmentally friendly and less energy intensive compared to other pre-treatment methods. However, the rate of hydrolysis reaction is very slow and needs a great improvement to be commercially applicable.
\n\t\t\t\t
Biological pre-treatment comprises of using microorganisms such as brown-, white-, and soft-rot fungi for selective degradation of lignin and hemicellulose among which white-rot fungi seems to be the most effective microorganism (Fan et al., 1987). Brown rots mainly attack cellulose, while white and soft rots attack both cellulose and lignin. Lignin degradation occurs through the action of lignin-degrading enzymes such as peroxidases and laccase (Okano et al., 2005). These enzymes are regulated by carbon and nitrogen sources. The suitable fungi for biological pre-treatment should have higher affinity for lignin and degrade it faster than carbohydrate components.
\n\t\t\t\t
\n\t\t\t\t\tHatakka et al. (1983) studied the pre-treatment of wheat straw by 19 white-rot fungi and found that 35% of the straw was converted to reducing sugars by Pleurotus ostreatus in 5 weeks. Similar conversion was obtained in the pre-treatment by Phanerochaete sordid (Ballesteros et al., 2006) and Pycnoporus cinnabarinus (Okano et al., 2005) in 4 weeks. Akin et al. (1995) also reported the delignification of bermudagrass by white-rot fungi. The biodegradation of bermudagrass stems was improved by 29-32%, after 6 weeks, using Ceriporiopsis subvermispora and by 63-77% using Cyathus stercoreus.
\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
4. Particle size reduction and physical properties
\n\t\t\t
The application of pre-processing operations such as particle size reduction/ grinding is critical in order to increase the surface area of lignocellulosic biomass prior to densification (Mani et al. 2003). Particle size reduction increases the total surface area, pore size of the material and the number of contact points for inter-particle bonding in the compaction process (Drzymala, 1993). Size reduction is an important energy intensive unit operation essential for bioenergy conversion process and densification to reduce transportation costs (Bitra et al., 2009; Soucek et al., 2003). Energy consumption of grinding biomass depends on initial particle size, moisture content, material properties, feed rate of the material and machine variables (Lopo, 2002). A comprehensive summary of literature review on size reduction of lignocellulosic biomass is provided in Table 4.
\n\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\tType of Choppers/ Grinders\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\tBiomass\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\tParameters Measured and Correlations\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\tObservations\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\tReference\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Non-Treated and Steam Exploded Barley, Canola, Oat and Wheat Straw
\n\t\t\t\t\t\t
Hammer mill screen size (from 1.6 to 30.0 mm) on Specific Energy Effect of geometric mean particle size on bulk density Effect of geometric mean particle size on particle density Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Negative exponential and power correlation between geometric mean particle size with both bulk and particle density Specific energy requirement is material dependent Negative power correlation between hammer mill screen size and specific energy Shapiro-Wilk Test for normality was performed
Effect of screen sizes (from 12.7 to 50.8 mm) on Specific Energy Effect of screen sizes on grinding rate Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Positive correlation between screen size and grinding rate Positive correlation between tub rotational speed and grinding rate Specific Energy is material dependent Negative power/ exponential correlation between screen size and specific energy
\n\t\t\t\t\t\t
Arthur et al., 1982
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Coastal Bermudagrass
\n\t\t\t\t\t\t
Effect of moisture content on Specific Energy Effect of feed rate on Specific Energy
\n\t\t\t\t\t\t
Positive correlation between moisture content and specific energy Positive correlation between feed rate and specific energy
\n\t\t\t\t\t\t
Balk, 1964
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Wheat Straw and Corn Stover
\n\t\t\t\t\t\t
Effect of operating speeds (from 2000 to 3600 rpm) on Specific Energy Effect of hammer angles (90° and 30° hammers) on Specific Energy Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Positive correlation between operating speed and specific energy Geometric mean particle diameter decreased with an increase in hammer mill speed Specific energy increased with a decrease in hammer angle
\n\t\t\t\t\t\t
Bitra et al., 2009
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Knife and Hammer Mills
\n\t\t\t\t\t\t
Hardwood Chips, Wheat Straw and Corn Stover
\n\t\t\t\t\t\t
Effect of screen size (from 1.6 to 12.7 mm) on specific energy
\n\t\t\t\t\t\t
Negative correlation between screen size and specific energy Specific Energy is material dependent
\n\t\t\t\t\t\t
Cadoche and López, 1989
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Red Winter Wheat Straw
\n\t\t\t\t\t\t
Effect of screen size (from 1.59 to 4.76 mm) on specific energy Effect of feed rate (from 1.5 to 2.5 kg/min) on specific energy
\n\t\t\t\t\t\t
Negative correlation was observed between screen size and specific energy Feed rate did not have significant effect on specific energy
\n\t\t\t\t\t\t
Fang et al., 1997
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Wheat Straw
\n\t\t\t\t\t\t
Effect of screen size (3.2 and 1.6 mm) on Specific Energy Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Negative correlation between specific energy and screen size
\n\t\t\t\t\t\t
Himmel et al., 1985
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Tub Grinders
\n\t\t\t\t\t\t
Round Bales of Corn Stover and Perennial Grasses
\n\t\t\t\t\t\t
Effect of screen size (from 19.1 to 127.0 mm) on Specific Energy Effect of screen size on throughput Effect of screen size on bulk and particle densities
\n\t\t\t\t\t\t
Negative correlation between screen size and bulk density Positive correlation between screen size and particle density Negative correlation between screen size and specific energy Positive correlation between screen size and throughput
\n\t\t\t\t\t\t
Kaliyan et al., 2010
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Barley Straw, Corn Stover and Switchgrass
\n\t\t\t\t\t\t
Effect of Screen Sizes (3.2, 1.6 and 0.8 mm) on Specific Energy Effect of Moisture Content (8% and 12% wb) on Specific Energy Correlation between bulk and particle densities and geometric mean diameter Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Negative linear correlation between specific energy and hammer mill screen size at 8% mc Quadratic correlation between specific energy and hammer mill screen size at 12% mc Polynomial relations for bulk and particle densities with geometric mean particle diameters
\n\t\t\t\t\t\t
Mani et al., 2004
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Oat Straw, Rattle Grass and Miscanthus
\n\t\t\t\t\t\t
Effect of Screen size (from 1.0 to 10.0 mm) on specific energy Effect of moisture content on specific energy
\n\t\t\t\t\t\t
Negative power correlation between screen size and specific energy Positive correlation between moisture content and specific energy; significantly higher specific energy is required at smaller screen sizes
\n\t\t\t\t\t\t
Soucek et al., 2003
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Hammer Mill
\n\t\t\t\t\t\t
Corn Stover
\n\t\t\t\t\t\t
Effect of hammer thickness (6.4 and 3.2 mm) on Specific Energy Effect of hammer thickness (6.4 and 3.2 mm) on Grinding Rate Effect of hammer tip speed (54 to 86 m/s) on Specific Energy
\n\t\t\t\t\t\t
Negative correlation between hammer thickness and Specific Energy Negative correlation between hammer thickness and Grinding Rate Positive correlation between hammer tip speed and Specific Energy
\n\t\t\t\t\t\t
Vigneault et al., 1992
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t
Knife Mill
\n\t\t\t\t\t\t
Switchgrass, Corn Stover, and Wheat Straw
\n\t\t\t\t\t\t
Effect of rotational speed (from 250 to 500 rpm) on specific energy Analysis on ground particle size distribution
\n\t\t\t\t\t\t
Positive correlation between rotational speed and specific energy Screen size has significant effect on particle size distribution
\n\t\t\t\t\t\t
Womac et al., 2007
\n\t\t\t\t\t
\n\t\t\t\t
Table 4.
A comprehensive summary of literature review on size reduction of lignocellulosic biomass.
\n\t\t\t
\n\t\t\t\t
4.1. Chopping
\n\t\t\t\t
Baled agricultural biomass from the field does not have good flowing characteristics and may not flow easily into grinders such as hammer mills and disc refiners. Therefore, biomass needs to be chopped with a chopper (rotary shear shredder)/ knife mill/ tub grinder to accommodate bulk flow and uniformity of feed rate. A chopper, knife cutter, or knife mill is often used for coarse size reduction (>50 mm) of stalk, straw, and grass feed stocks (Bitra et al., 2009). Knife mills reportedly worked successfully for shredding forages under various crop and machine conditions (Cadoche and López, 1989).
\n\t\t\t\t
\n\t\t\t\t\tBitra et al. (2009) reported that the total specific energy (including energy to operate the knife mill) for agricultural biomass chopping increases with knife mill speed. The total specific energy for knife mill and tub grinder has been observed to have negative correlation with screen size and mass feed rate (Arthur et al., 1982; Bitra et al., 2009; Himmel et al., 1985). However, grinding rate (throughput) increases with an increase in screen size (Arthur et al., 1982).
\n\t\t\t\t
For tub grinders, an increase in screen size results in an increase in geometric mean length of particles and throughput, but a decrease in bulk density of the particles and specific energy consumption (Kaliyan et al., 2010).
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
4.2. Hammer mill grinding
\n\t\t\t\t
Typically, hammer mills are used in forage processing industry as they are relatively inexpensive, easy to operate and produces wide range of particles (Lopo, 2002). Hammer mills have achieved merit because of their ability to finely grind a greater variety of materials than any other machines (Scholten et al., 1985). The performance of a hammer mill is measured in terms of energy consumption and geometric mean diameter and particle size distribution of the ground product (Adapa et al., 2011a; Mani et al., 2004).
\n\t\t\t\t
\n\t\t\t\t\tScreen Size: Hammer mill screen opening size was the most significant factor affecting mill performance (Fang et al., 1997) and also has significant effect on mean particle size (Pfost and Headley, 1971). The specific energy required to grind agricultural biomass significantly increases with a decrease in hammer mill screen size and shows a negative power correlation (Arthur et al., 1982; Soucek et al., 2003). Similarly, Adapa et al. (2011a) reported negative correlation between specific energy and particle size of biomass as affected by hammer mill screen sizes. However, two other studies reported a second-order polynomial relationship between the specific energy requirements for grinding biomass (Mani et al. 2004; Sitkei, 1986). Usually, the mean geometric particle size for any particular biomass decreases with a decrease in hammer mill screen size (Adapa et al., 2011a). It has been reported that wider particle size distribution is suitable for compaction (pelleting/ briquetting) process (Adapa et al., 2011a; Mani et al., 2004). During compaction, smaller (fine) particles rearrange and fill in the void space of larger (coarse) particles producing denser and durable compacts (Tabil, 1996).
\n\t\t\t\t
\n\t\t\t\t\tOperating Speed (Peripheral Velocity): The speed has a significant effect on mean particle size (Pfost and Headley, 1971). The total specific energy of hammer mill grinding has direct correlation to an increase in hammer tip speed (Bitra et al., 2009; Vigneault et al., 1992). High speed hammer mills with smaller diameter rotors are good for fine or hard-to-grind material. However, at high tip speeds, the material moves around the mill parallel to the screen surface making the openings only partially effective. At slower speeds, the material impinges on the screen at a greater angle causing greater amounts of coarser feed to pass through (Balk, 1964).
\n\t\t\t\t
\n\t\t\t\t\tHammer Angles and Thickness: The direct energy input for grinding also depends on hammer angles. In general, the specific energy for grinding decreases with an increase in hammer degrees (Bitra et al., 2009). In addition, the specific energy for grinding increases with an increase in hammer thickness (Vigneault et al., 1992).
\n\t\t\t\t
\n\t\t\t\t\tMaterial Moisture Content and Feed Rate: A positive correlation has been reported between moisture content and specific energy consumption for grinding of agricultural biomass (Balk, 1964; Mani et al., 2004; Soucek et al., 2003). Feeding rate also has significant effect on specific energy consumption during hammer mill grinding and has positive correlation (O’Dogherty, 1982).
\n\t\t\t\t
\n\t\t\t\t\tBulk and Particle Densities, and Geometric Mean Particle Size: Usually, the bulk and particle density of agricultural straw significantly increases with a decrease in hammer mill screen size (Adapa et al., 2011a). The geometric mean particle size of pre-treated straw is usually smaller than that of the non-treated straw. This could be due to the fact that application of pre-treatment disrupts/ disintegrates the lignocellulosic structure of the biomass (Sokhansanj et al., 2005) leading to lower shear strength (easier to grind the straw).
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
4.3. Physical and frictional properties of biomass
\n\t\t\t\t
\n\t\t\t\t\tBulk Density: The goal of densification is to increase the bulk density of agricultural straw to facilitate economic storage, transportation and handling of the material. In addition, densification results in an increase in the net calorific content per unit volume. The bulk density of agricultural biomass depends on the type of biomass, moisture content, grind size, and pre-treatment (Mani et al., 2006). Lower bulk densities, and concerns with uneven and low flowability of straw grinds are critical issues to sustainable production of pellets using pellet mills (Adapa et al., 2009; Larsson et al., 2008).
\n\t\t\t\t
Typically, the bulk density of ground straw increases with a decrease in hammer mill screen size. Also, pre-treatments usually results in a decrease in bulk density since the organized lignocellulosic structure of biomass is disturbed/ disintegrated. In addition, the bulk density and geometric mean particle size of material is correlated by either power or exponential relations (Adapa et al., 2010b; Mani et al., 2004).\n\t\t\t\t\tTable 5 shows a summary of average bulk density of various agricultural biomasses ground using a hammer mill.
\n\t\t\t\t
\n\t\t\t\t\tParticle Density: Particle size of the grinds will have direct effect on the final pellet density. Theoretically, the density of pellet can be as high as the particle density of the ground biomass. Similar to bulk density, particle density also depends on the type of biomass, moisture content, grind size, and pre-treatment (Adapa et al., 2010b). The particle density is observed to have negative correlation with hammer mill screen size. Application of pre-treatment increases the particle density since disturbance/ disintegration of lignocellulosic structure results in finer components (Adapa et al., 2010b). Table 5 shows a summary of average particle density of various agricultural biomasses ground using a hammer mill.
\n\t\t\t\t
\n\t\t\t\t\tGeometric Mean Particle Size and Distribution: It has been reported that wider particle size distribution is suitable for compaction (pelleting/briquetting) process (Mani et al., 2004a). During compaction, smaller (fine) particles rearrange and fill in the void space of larger (coarse) particles producing denser and durable compacts (Tabil, 1996). Therefore, ideally the grinds should be normally distributed, should have near zero skewness and lower peak than expected for the normal and wider distribution of data (negative Kurtosis values). In addition, a decrease in the biomass grind size has been observed to have a positive effect on pellet mill throughput (Adapa et al., 2004).
\n\t\t\t\t
\n\t\t\t\t\tFrictional Properties: Prior to densification, biomass grinds need to be efficiently stored, handled and transported. Physical and frictional properties of biomass have significant effect on design of new and modification of existing bins, hoppers and feeders (Fasina et al., 2006). The frictional behavior of biomass grinds in all engineering applications is described by two independent parameters: the coefficient of internal friction, and the coefficient of wall friction. The former determines the stress distribution within particles undergoing strain, and the latter describes the magnitude of the stresses between the particle and the walls of its container (Seville et al., 1997). The classic law of friction states that frictional force is directly proportional to the total force that acts normal to the shear surfaces (Chancellor, 1994; Chung and Verma, 1989; Larsson, 2010). Frictional force depends on the nature of the materials in contact but is independent of the area of contact or sliding velocity (Mohsenin, 1970). Material properties such as moisture content and particle size affect the frictional properties and densification performance of an individual feedstock (Larsson 2010; Shaw and Tabil, 2006). In addition, the determination of coefficient of friction is essential for the design of production and handling equipment and in storage structures (Adapa et al., 2010a; Puchalski and Brusewitz, 1996). A comprehensive summary of literature review on coefficient of internal friction and cohesion of agricultural biomass is provided in Table 6.
\n\t\t\t\t
Predominantly, a linear correlation exists between normal and shear stress for agricultural straw grinds (Adapa et al., 2010a; Chevanan et al., 2008; Richter, 1954) at any specific hammer mill screen size. An increase in hammer mill screen size significantly decreases the shear stress for ground straw at any specific normal stress (Adapa et al., 2010a).
\n\t\t\t\t
The correlation for coefficient of internal friction and cohesion with average geometric mean particle sizes for agricultural straw grinds is provided in Adapa et al. (2010a). These correlations can be used to predict the coefficient of internal friction (slope of the linear plot) and the cohesion (intercept of the linear plot) for various geometric mean particle sizes. In general, the coefficient of internal friction for ground agricultural straw decreases with an increase in average geometric mean particle diameter. The coefficient of cohesion for straw grinds increases with an increase in average geometric mean particle size (Adapa et al., 2010a).
\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Biomass
\n\t\t\t\t\t\t\t
Hammer Mill Screen Size (mm)
\n\t\t\t\t\t\t\t
Moisture Content (%, wb)
\n\t\t\t\t\t\t\t
Geometric Mean Particle Diameter (mm)
\n\t\t\t\t\t\t\t
Bulk Density (kg/m3)
\n\t\t\t\t\t\t\t
Particle Density (kg/m3)
\n\t\t\t\t\t\t\t
Reference
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Barley
\n\t\t\t\t\t\t\t
6.4
\n\t\t\t\t\t\t\t
8.9
\n\t\t\t\t\t\t\t
0.88
\n\t\t\t\t\t\t\t
96
\n\t\t\t\t\t\t\t
1046
\n\t\t\t\t\t\t\t
Adapa et al., 2011a
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
3.2
\n\t\t\t\t\t\t\t
5.3
\n\t\t\t\t\t\t\t
0.46
\n\t\t\t\t\t\t\t
149
\n\t\t\t\t\t\t\t
1089
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
1.6
\n\t\t\t\t\t\t\t
7.8
\n\t\t\t\t\t\t\t
0.46
\n\t\t\t\t\t\t\t
155
\n\t\t\t\t\t\t\t
1149
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Canola
\n\t\t\t\t\t\t\t
6.4
\n\t\t\t\t\t\t\t
12.6
\n\t\t\t\t\t\t\t
0.89
\n\t\t\t\t\t\t\t
144
\n\t\t\t\t\t\t\t
1019
\n\t\t\t\t\t\t\t
Adapa et al., 2011a
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
3.2
\n\t\t\t\t\t\t\t
9.2
\n\t\t\t\t\t\t\t
0.52
\n\t\t\t\t\t\t\t
190
\n\t\t\t\t\t\t\t
1192
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
1.6
\n\t\t\t\t\t\t\t
8.3
\n\t\t\t\t\t\t\t
0.37
\n\t\t\t\t\t\t\t
203
\n\t\t\t\t\t\t\t
1309
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Corn Stover
\n\t\t\t\t\t\t\t
3.2
\n\t\t\t\t\t\t\t
6.22
\n\t\t\t\t\t\t\t
0.41
\n\t\t\t\t\t\t\t
131
\n\t\t\t\t\t\t\t
1170
\n\t\t\t\t\t\t\t
Mani et al., 2004
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
1.6
\n\t\t\t\t\t\t\t
6.22
\n\t\t\t\t\t\t\t
0.26
\n\t\t\t\t\t\t\t
156
\n\t\t\t\t\t\t\t
1330
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
0.8
\n\t\t\t\t\t\t\t
6.22
\n\t\t\t\t\t\t\t
0.19
\n\t\t\t\t\t\t\t
158
\n\t\t\t\t\t\t\t
1340
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Oat
\n\t\t\t\t\t\t\t
6.4
\n\t\t\t\t\t\t\t
10.9
\n\t\t\t\t\t\t\t
0.94
\n\t\t\t\t\t\t\t
111
\n\t\t\t\t\t\t\t
873
\n\t\t\t\t\t\t\t
Adapa et al., 2011a
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
3.2
\n\t\t\t\t\t\t\t
9.4
\n\t\t\t\t\t\t\t
0.57
\n\t\t\t\t\t\t\t
156
\n\t\t\t\t\t\t\t
1093
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
1.6
\n\t\t\t\t\t\t\t
7.7
\n\t\t\t\t\t\t\t
0.40
\n\t\t\t\t\t\t\t
196
\n\t\t\t\t\t\t\t
1240
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Wheat
\n\t\t\t\t\t\t\t
6.4
\n\t\t\t\t\t\t\t
9.5
\n\t\t\t\t\t\t\t
0.99
\n\t\t\t\t\t\t\t
107
\n\t\t\t\t\t\t\t
1078
\n\t\t\t\t\t\t\t
Adapa et al., 2011a
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
3.2
\n\t\t\t\t\t\t\t
9.5
\n\t\t\t\t\t\t\t
0.72
\n\t\t\t\t\t\t\t
141
\n\t\t\t\t\t\t\t
1225
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
1.6
\n\t\t\t\t\t\t\t
8.6
\n\t\t\t\t\t\t\t
0.45
\n\t\t\t\t\t\t\t
154
\n\t\t\t\t\t\t\t
1269
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 5.
Average bulk and particle densities of various agricultural biomasses ground using a hammer mill
Normal stress from 10 to 200 kPa Hammer mill screen sizes of 6.35 and 3.18 mm Moisture contents of 7, 11 and 15% (wb) Galvanized steel
\n\t\t\t\t\t\t\t
Coefficient of wall friction increased from 0.18 to 0.26 with an increase in moisture from 7 to 15% No clear trend observed for the adhesion coefficient
\n\t\t\t\t\t\t\t
Mani et al., 2004
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Peat hull, Switchgrass and Poultry Litter
\n\t\t\t\t\t\t\t
Consolidating stress from 1.5 to 12.0 kPa Screen sizes from 0.79 to 3.20 mm Ring shear test
\n\t\t\t\t\t\t\t
No effect of screen size on internal friction and cohesive properties
\n\t\t\t\t\t\t\t
Fasina et al., 2006
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Peat Moss, Wheat Straw, Oat Hulls and Flax Shives
\n\t\t\t\t\t\t\t
Normal stress from 10 to 400 kPa Geometric mean particles sizes of 0.74 (peat moss), 0.65 (wheat straw), 0.47 (oat hulls) and 0.64 (flax shives) mm Moisture content 9-10% (wb) Mild steel surface
\n\t\t\t\t\t\t\t
Coefficient of wall friction were 0.68 (peat moss), 0.45 (wheat straw), 0.39 (oat hulls), and 0.41 (flax shives) Adhesion coefficients were 0.2635 kPa (peat moss), 10.687 kPa (wheat straw), 4.719 kPa (oat hulls), and 16.203 kPa (flax shives)
\n\t\t\t\t\t\t\t
Shaw and Tabil, 2006
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Alfalfa, Barley Straw, Wheat Straw and Whole Green Barley
\n\t\t\t\t\t\t\t
Normal stress from 200 to 735 kPa Moisture content for alfalfa, barley straw from 12.0 to 45.7%, and for wheat straw at 10.0% and whole green barley at 51.0% (wb) Chop size from 10 to 90 mm Polished steel surface
\n\t\t\t\t\t\t\t
Coefficient if friction on steel surface for alfalfa and barley straw increased with moisture content and was from 0.15 to 0.26, and 0.14 and 0.27, respectively Coefficient of friction for wheat straw and whole green barley were 0.13 and 0.21, respectively No effect of chop size on coefficient of internal friction on barley straw
\n\t\t\t\t\t\t\t
Afzalinia and Roberge, 2007
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Switchgrass, Wheat straw, and Corn Stover
\n\t\t\t\t\t\t\t
Normal stresses from 1.23 to 4.92 kPa Chop size of 7.81 and 13.50 mm for switchgrass, 7.09 and 10.39 mm for wheat straw, 7.80 and 14.89 mm for corn stover
\n\t\t\t\t\t\t\t
No effect of chop size on friction coefficients Coefficient of internal friction varied from 0.765 to 1.586
\n\t\t\t\t\t\t\t
Chevanan et al., 2008
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Reed Canary Grass
\n\t\t\t\t\t\t\t
Normal stresses of 0.52-7.52 kPa (low) and 23-275 MPa (high) Moisture contents from 6.7 to 17.1% (wb) for low normal stress, and 8.9 to 27.2% for high normal stress Screen sizes of 4.0 mm Ring shear test \n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
High friction value of 0.6 was obtained at normal stress of 50 MPa and lower At low normal stresses, the coefficient of kinematic wall friction (ratio of shear stress and normal stress) was positively correlated with moisture content and negatively correlated to normal stress At high normal stresses, the coefficient of kinematic wall friction was negatively correlated to both moisture content and normal stress
\n\t\t\t\t\t\t\t
Larsson, 2010
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Non-Treated and Steam Exploded Barley, Canola, Oat and Wheat Straw
\n\t\t\t\t\t\t\t
Normal stress from 9.8 to 39.2 kPa Moisture content of 10% (wb) Screen size from 1.6 to 6.4 mm
\n\t\t\t\t\t\t\t
No effect of screen size on shear stress values Steam exploded straw had higher coefficient of internal friction than non-treated straw grinds Coefficient of friction for non-treated barley, canola, oat and wheat straw were in the range of 0.505 to 0.584, 0.661 to 0.665, 0.498 to 0.590, and 0.532 to 0.591, respectively. Coefficient of friction for steam exploded barley, canola, oat and wheat straw were in the range of 0.562 to 0.738, 0.708 to 0.841, 0.660 to 0.860, and 0.616 to 1.036, respectively
\n\t\t\t\t\t\t\t
Adapa et al., 2010a
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 6.
A comprehensive summary of literature review on coefficient of internal friction and cohesion of agricultural biomass
\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
5. Summary
\n\t\t\t
The current chapter has explored the effects of pre-treatment (chemical, physico-chemical, and biological) and pre-processing (size reduction) techniques on densification of agricultural straw resulting in high quality (density and durability) pellets. It has been determined that an increase in bulk density of biomass also increases the net calorific content per unit volume of pellets, and facilitates easy and economical storage, transport and handling of the biomass. Pre-treatment and pre-processing methods disintegrate the basic lignocellulosic structure of biomass, and change the relative composition of lignin, cellulose and hemicelluloses in the material. In addition, physical and frictional properties of agricultural straw are altered. The application of pre-treatments breaks the long-chain hydrogen bond in cellulose, making hemicelluloses amorphous, and loosening the lignin out of the lignocellulosic matrix, resulting in better quality (physically) pellets. During this process, the high molecular amorphous polysaccharides are reduced to low molecular components to become more cohesive in the presence of moisture during densification process. Particle size reduction increases the total surface area, pore size of the material and the number of contact points for inter-particle bonding in the compaction process.
\n\t\t\t
It has been shown that the Fourier Transform Infrared Spectroscopy (FTIR) can be used to rapidly characterize and quantify cellulose-hemicellulose-lignin composition prior to and after application of various pre-processing and pre-treatment methods. Regression equations were developed to predict the lignocellulosic content of agricultural biomass using pure cellulose, hemicelluloses and lignin as reference samples.
\n\t\t
\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/17491.pdf",chapterXML:"https://mts.intechopen.com/source/xml/17491.xml",downloadPdfUrl:"/chapter/pdf-download/17491",previewPdfUrl:"/chapter/pdf-preview/17491",totalDownloads:9092,totalViews:760,totalCrossrefCites:8,totalDimensionsCites:33,totalAltmetricsMentions:0,impactScore:12,impactScorePercentile:98,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"October 18th 2010",dateReviewed:"March 23rd 2011",datePrePublished:null,datePublished:"August 1st 2011",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/17491",risUrl:"/chapter/ris/17491",book:{id:"450",slug:"biofuel-s-engineering-process-technology"},signatures:"Lope Tabil, Phani Adapa and Mahdi Kashaninejad",authors:[{id:"27220",title:"MSc",name:"Phani",middleName:null,surname:"Adapa",fullName:"Phani Adapa",slug:"phani-adapa",email:"phani.adapa@usask.ca",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"31671",title:"Prof.",name:"Lope",middleName:"G.",surname:"G. Tabil",fullName:"Lope G. Tabil",slug:"lope-g.-tabil",email:"lope.tabil@usask.ca",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Saskatchewan",institutionURL:null,country:{name:"Canada"}}},{id:"31672",title:"Dr.",name:"Mahdi",middleName:null,surname:"Kashaninejad",fullName:"Mahdi Kashaninejad",slug:"mahdi-kashaninejad",email:"mahdi.kashaninejad@usask.ca",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1. Sources of biomass",level:"2"},{id:"sec_2_2",title:"1.2. Current issues related to biomass utilization",level:"2"},{id:"sec_4",title:"2. Lignocellulosic biomass characterization",level:"1"},{id:"sec_4_2",title:"2.1. Structure of lignocellulosic material",level:"2"},{id:"sec_5_2",title:"2.2. Rapid characterization of lignocellulosic materials",level:"2"},{id:"sec_6_2",title:"2.3. Fourier transform infrared spectroscopy",level:"2"},{id:"sec_8",title:"3. Pre-treatment of lignocellulosic biomass",level:"1"},{id:"sec_8_2",title:"3.1. Need for pre-treatment",level:"2"},{id:"sec_9_2",title:"3.2. Physico-chemical pre-treatments",level:"2"},{id:"sec_9_3",title:"3.2.1. Steam explosion",level:"3"},{id:"sec_10_3",title:"Table 2.",level:"3"},{id:"sec_11_3",title:"3.2.3. Chemical pre-treatment",level:"3"},{id:"sec_13_2",title:"3.3. Biological pre-treatment",level:"2"},{id:"sec_15",title:"4. Particle size reduction and physical properties",level:"1"},{id:"sec_15_2",title:"4.1. Chopping",level:"2"},{id:"sec_16_2",title:"4.2. Hammer mill grinding",level:"2"},{id:"sec_17_2",title:"4.3. Physical and frictional properties of biomass",level:"2"},{id:"sec_19",title:"5. Summary",level:"1"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\tAdapa, P.K., Tabil L.G. & Schoenau, G.J.2011aGrinding Performance and Physical Properties of Non-Treated and Steam Exploded Barley, Canola, Oat and Wheat Straw. Journal of Biomass and Bioenergy,doi:10.1016/j.biombioe.2010.10.00435,549\n\t\t\t\t\t561\n\t\t\t\t\n\t\t\t'},{id:"B2",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAdapa\n\t\t\t\t\t\t\tP. K.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tTabil\n\t\t\t\t\t\t\tL. G.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSchoenau\n\t\t\t\t\t\t\tG. J.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCanam\n\t\t\t\t\t\t\tT.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tDumonceaux\n\t\t\t\t\t\t\tT.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2011bQuantitative Analysis of Lignocellulosic Components of Non-Treated and Steam Exploded Barley, Canola, Oat and Wheat Straw using Fourier Transform Infrared Spectroscopy. 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K.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2004\n\t\t\t\t\tCarbon materials obtained from self-binding sugar cane bagasse and deciduous wood residues plastics\n\t\t\t\t\tBiomass and Bioenergy\n\t\t\t\t\t345\n\t\t\t\t\t360\n\t\t\t\t\n\t\t\t'},{id:"B131",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZimbardi\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tViola\n\t\t\t\t\t\t\tE.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tNanna\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLarocca\n\t\t\t\t\t\t\tE.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCardinale\n\t\t\t\t\t\t\tM.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBarisano\n\t\t\t\t\t\t\tD.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2007\n\t\t\t\t\tAcid impregnation and steam explosion of corn stover in batch processes\n\t\t\t\t\tIndustrial Crops and Products\n\t\t\t\t\t195\n\t\t\t\t\t206\n\t\t\t\t\n\t\t\t'},{id:"B132",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZimbardi\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tViggiano\n\t\t\t\t\t\t\tD.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tNanna\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tDemichele\n\t\t\t\t\t\t\tM.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCuna\n\t\t\t\t\t\t\tD.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCardinale\n\t\t\t\t\t\t\tG.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1999\n\t\t\t\t\tSteam Explosion of Straw in Batch and Continuous Systems\n\t\t\t\t\tApplied Biochemistry and Biotechnology\n\t\t\t\t\t117\n\t\t\t\t\t125\n\t\t\t\t\n\t\t\t'},{id:"B133",body:'\n\t\t\t\tZhu, S., Wu, Y., Yu, Z., Zhang, X., Li, H., & Gao, M.2006a\n\t\t\t\t\tBioresource Technology,\n\t\t\t\t\tThe effect of microwave irradiation on enzymatic hydrolysis of rice straw.,97,1964\n\t\t\t\t\t1968\n\t\t\t\t\n\t\t\t'},{id:"B134",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZhu\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWu\n\t\t\t\t\t\t\tY.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYu\n\t\t\t\t\t\t\tZ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tChen\n\t\t\t\t\t\t\tQ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWu\n\t\t\t\t\t\t\tG.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYu\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWang\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tJin\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2006b\n\t\t\t\t\tMicrowave-assisted alkali pre-treatment of wheat straw and its enzymatic hydrolysis\n\t\t\t\t\tBiosystems Engineering\n\t\t\t\t\t437\n\t\t\t\t\t442\n\t\t\t\t\n\t\t\t'},{id:"B135",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZhu\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWu\n\t\t\t\t\t\t\tY.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYu\n\t\t\t\t\t\t\tZ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZhang\n\t\t\t\t\t\t\tX.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWang\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYu\n\t\t\t\t\t\t\tF.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tJin\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2006c\n\t\t\t\t\tProduction of ethanol from microwave-assisted alkali pretreated wheat straw\n\t\t\t\t\tProcess Biochemistry\n\t\t\t\t\t869\n\t\t\t\t\t873\n\t\t\t\t\n\t\t\t'},{id:"B136",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZhu\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tWu\n\t\t\t\t\t\t\tY.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tYu\n\t\t\t\t\t\t\tZ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLiao\n\t\t\t\t\t\t\tJ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tZhang\n\t\t\t\t\t\t\tY.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2005Pre-treatment by microwave/alkali of rice straw and its enzymic hydrolysis. Process Biochemistry, 40, 3082\n\t\t\t\t\t3086\n\t\t\t\t\n\t\t\t'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Tabil Lope",address:null,affiliation:'
Department of Chemical and Biological Engineering, University of Saskatchewan, Canada
Department of Food Science & Technology, Gorgan University of AgriculturalSciences and Natural Resources Gorgan, Iran
'}],corrections:null},book:{id:"450",type:"book",title:"Biofuel's Engineering Process Technology",subtitle:null,fullTitle:"Biofuel's Engineering Process Technology",slug:"biofuel-s-engineering-process-technology",publishedDate:"August 1st 2011",bookSignature:"Marco Aurélio dos Santos Bernardes",coverURL:"https://cdn.intechopen.com/books/images_new/450.jpg",licenceType:"CC BY-NC-SA 3.0",editedByType:"Edited by",isbn:null,printIsbn:"978-953-307-480-1",pdfIsbn:"978-953-51-4468-7",reviewType:"peer-reviewed",numberOfWosCitations:255,isAvailableForWebshopOrdering:!0,editors:[{id:"6625",title:"Dr.",name:"Marco Aurelio",middleName:null,surname:"Dos Santos Bernardes",slug:"marco-aurelio-dos-santos-bernardes",fullName:"Marco Aurelio Dos Santos Bernardes"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"763"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},chapters:[{id:"17474",type:"chapter",title:"The Effect of Thermal Pretreatment Process on Bio-Fuel Conversion",slug:"the-effect-of-thermal-pretreatment-process-on-bio-fuel-conversion",totalDownloads:3214,totalCrossrefCites:1,signatures:"Aleksander Ryzhkov, Vadim Silin, Tatyana Bogatova, Aleksander Popov and Galina Usova",reviewType:"peer-reviewed",authors:[{id:"27414",title:"Dr.",name:"Vadim",middleName:null,surname:"Silin",fullName:"Vadim Silin",slug:"vadim-silin"},{id:"43073",title:"Mr.",name:"Aleksander",middleName:null,surname:"Popov",fullName:"Aleksander Popov",slug:"aleksander-popov"},{id:"43074",title:"Prof.",name:"Tatyana",middleName:null,surname:"Bogatova",fullName:"Tatyana Bogatova",slug:"tatyana-bogatova"},{id:"43075",title:"Ms.",name:"Galina",middleName:null,surname:"Usova",fullName:"Galina Usova",slug:"galina-usova"},{id:"43077",title:"Mr",name:"Alexander",middleName:null,surname:"Ryzhkov",fullName:"Alexander Ryzhkov",slug:"alexander-ryzhkov"}]},{id:"17475",type:"chapter",title:"The Challenge of Bioenergies: An Overview",slug:"the-challenge-of-bioenergies-an-overview",totalDownloads:2765,totalCrossrefCites:3,signatures:"Nicolas Carels",reviewType:"peer-reviewed",authors:[{id:"24968",title:"Dr.",name:"Nicolas",middleName:null,surname:"Carels",fullName:"Nicolas Carels",slug:"nicolas-carels"}]},{id:"17476",type:"chapter",title:"Biogas Upgrading by Pressure Swing Adsorption",slug:"biogas-upgrading-by-pressure-swing-adsorption",totalDownloads:9273,totalCrossrefCites:4,signatures:"Carlos A. Grande",reviewType:"peer-reviewed",authors:[{id:"31487",title:"Dr.",name:"Carlos",middleName:"Adolfo",surname:"Grande",fullName:"Carlos Grande",slug:"carlos-grande"}]},{id:"17477",type:"chapter",title:"Use of Rapeseed Straight Vegetable Oil as Fuel Produced in Small-Scale Exploitations",slug:"use-of-rapeseed-straight-vegetable-oil-as-fuel-produced-in-small-scale-exploitations",totalDownloads:2984,totalCrossrefCites:1,signatures:"Grau Baquero, Bernat Esteban, Jordi-Roger Riba, Rita Puig and Antoni Rius",reviewType:"peer-reviewed",authors:[{id:"30674",title:"Dr.",name:"Jordi-Roger",middleName:null,surname:"Riba",fullName:"Jordi-Roger Riba",slug:"jordi-roger-riba"},{id:"30684",title:"MSc.",name:"Bernat",middleName:null,surname:"Esteban",fullName:"Bernat Esteban",slug:"bernat-esteban"},{id:"30685",title:"Dr.",name:"Grau",middleName:null,surname:"Baquero",fullName:"Grau Baquero",slug:"grau-baquero"},{id:"30686",title:"Dr.",name:"Rita",middleName:null,surname:"Puig",fullName:"Rita Puig",slug:"rita-puig"},{id:"30687",title:"Dr.",name:"Antoni",middleName:null,surname:"Rius",fullName:"Antoni Rius",slug:"antoni-rius"}]},{id:"17478",type:"chapter",title:"Nanotech Biofuels and Fuel Additives",slug:"nanotech-biofuels-and-fuel-additives",totalDownloads:6935,totalCrossrefCites:1,signatures:"Sergio C. Trindade",reviewType:"peer-reviewed",authors:[{id:"26784",title:"Dr.",name:"Sergio",middleName:"C",surname:"Trindade",fullName:"Sergio Trindade",slug:"sergio-trindade"}]},{id:"17479",type:"chapter",title:"Bioresources for Third-Generation Biofuels",slug:"bioresources-for-third-generation-biofuels",totalDownloads:4431,totalCrossrefCites:2,signatures:"Rafael Picazo-Espinosa, Jesús González-López and Maximino Manzanera",reviewType:"peer-reviewed",authors:[{id:"27371",title:"Dr.",name:"Maximino",middleName:null,surname:"Manzanera",fullName:"Maximino Manzanera",slug:"maximino-manzanera"},{id:"34626",title:"Mr",name:"Rafael",middleName:null,surname:"Picazo-Espinosa",fullName:"Rafael Picazo-Espinosa",slug:"rafael-picazo-espinosa"},{id:"87059",title:"Prof.",name:"Jesús",middleName:null,surname:"González-López",fullName:"Jesús González-López",slug:"jesus-gonzalez-lopez"}]},{id:"17480",type:"chapter",title:"Overview of Corn-Based Fuel Ethanol Coproducts: Production and Use",slug:"overview-of-corn-based-fuel-ethanol-coproducts-production-and-use",totalDownloads:5118,totalCrossrefCites:1,signatures:"Kurt A. 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1. Introduction
Plants constitute vast and diverse niches for endophytic organisms, and there is not a single plant species devoid of them. The most up-to-date definition for endophytes defines them as the microorganisms isolated from surface-sterilized plant tissues, which do not cause any noticeable harm to their host plants [1, 2]. The most abundant and common microbes living as endophytes are bacteria and fungi [3]. Endophytic bacteria are present in any kind of plant, from ferns and bryophytes to mono and dicotyledonous species [4]. In nature, mainly the intercellular spaces of the plant host are colonized by the endophytic bacteria [1, 5, 6]. But, endophytes have been also found in intracellular spaces of grapevine, barley, tobacco, Arabidopsis, and pine [7], suggesting that legumes may also have intracellular endophytes.
The endophytic bacterial communities make significant contributions to growth promotion and plant health in mutualistic (even symbiotic) relationships. The plant host protects the bacteria from the environment, while the endophytic community provides several benefits to the host. The benefits for the plant may include nutrient assimilation (such as nitrogen, phosphorus, or iron), growth stimulation, defense against pathogens, and/or protection against environmental stresses [8, 9]. Some of these effects might be altered when the plant is under stress [10].
The use of these natural symbionts/mutualists offers an opportunity to maximize legume crop productivity while reducing the environmental impacts of agriculture. For decades, most of the studies (and agricultural applications) have been about the effects of individual strains of bacteria, but recently with the bloom in bioinformatics and sequencing technology development, the knowledge about the plant microbiota has burst, and the potential to use and manipulate complex bacterial communities has started to be the target of a large research community.
2. Plant endophytic microbiome
In natural environments, the intracellular spaces of legumes are inhabited by numerous microorganisms, such as virus, fungi, nematodes, and bacteria. Here we focus on bacterial endophytes that benefit the plant in some way. Those bacteria colonize the host by several mechanisms, such as natural opening or injures and proliferate within the host. There is a huge taxonomic and functional diversity of endophytic bacteria, adapted to the microenvironments that the plant host provides. That diversity will be shaped by the microbial community members, the plant host, and the environmental conditions.
2.1 Colonization and distribution within the host plant
Colonization mechanisms vary with the type of interaction between the host and the bacteria and the life cycle of the microbe. Overall, most of the endophytic bacteria enter the plant through the roots. Since the microbial diversity decreases from the root to the leaves, it has been proposed that most of the microbes colonize the plant through the roots and proliferate to aboveground tissues [11] (Figure 1). Endophytic bacteria are usually “recruited” by plant host root exudates, such as organic acids, amino acids, and proteins [12, 13]. Once the bacteria are close to the root surface, they enter through lateral root emergence areas or other openings, caused by wounds or mechanical injuries. In the early stages, most of the endophytes are first observed in root hairs and subsequently in the root cortex [14]. However, endophytes can also colonize the leaves through the stomata, injuries in the epidermis, or introduced by vectors. In leaves, bacterial endophytes have been observed in the intercellular spaces of mesophyll, substomatal areas, and xylem tissues [15, 16].
Figure 1.
Diversity gradient of bacterial endophytic microbiota and growth promotion mechanisms to legumes. Legumes are surrounded and interact with bacteria in the soil and air (epiphytic bacteria in the rhizosphere and phyllosphere) and in the inter- and intra-cellular spaces (endosphere). Those bacteria can be saprophytic, pathogenic, or beneficial for the plant. The beneficial bacteria can promote plant growth by direct and indirect mechanisms. Direct mechanisms include phytohormone, volatiles, and other compounds production and facilitation of nutrient assimilation. Indirect mechanisms include pathogen and abiotic stress protection. ISR, induced systemic resistance.
In addition, the habit of the microbe conditions its colonization strategy. For example, obligate endophytes, which depend on the plant metabolic activity for their survival, are usually transmitted to the seed (vertical transmission) and spread inside the plant or through the action of a vector. On the contrary, most of the facultative endophytes, which have a free life in the soil and colonize the plant during some stage of their life cycle, colonize the plant through occasional wounds [17].
The colonization process itself alters host plant physiology (in a process called “niche construction” from the microbe’s point of view) by defense alterations or direct shift of the host metabolism [18]. Those microenvironment changes can affect the local microbiome structure and functions, by altering relationships among bacterial species and within the host. Furthermore, under particular conditions, part of the response of the plant will stimulate or recruit specific endophytes, which may contribute to survival or tolerance of that condition [19, 20]. It was proved in tomato cultivars that the transplant of the rhizosphere from a resistant to a susceptible cultivar suppressed Ralstonia solanacearum disease symptoms. They found a highly abundant flavobacterial genome in the resistant cultivar rhizosphere, and the isolated flavobacteria suppressed disease symptoms in the susceptible cultivar in pots [21]. In legumes, it was reported that Fusarium-resistant common bean cultivars showed a higher abundance of Pseudomonadaceae, Bacillaceae, Solibacteraceae, and Cytophagaceae families [22], but no further inquiries have been reported.
Another aspect affecting the colonization process of the endophytic bacteria is the host defenses. Endophytes live in the same environment as many plant pathogens and share close similarities with them. Microbe- or pathogen-associated molecular patterns (MAMPs/PAMPs) are conserved and necessary for microbial survival, but plants have evolved multiple receptors to recognize them and induce the plant immune system. Then, the colonization of endophytic bacteria triggers plant defenses, and the process needs to be avoided or blocked by the beneficial endophytes to be able to colonize and proliferate within the host [2, 23, 24]. It is not well understood yet how the beneficial bacteria overcome the defenses, but a few mechanisms have been unraveled, including the blockage of MAMPs and defense signaling [25]. The beneficial bacteria Bacillus subtilis avoid a strong defensive response in the host by blocking the detection of their own flagellin by the secretion of the flagellin-binding peptide subtilomycin [25, 26]. Another mechanism is the secretion of bacterial antioxidant enzymes, such as superoxide dismutases and glutathione-S-transferases to detoxify the reactive oxygen species that signals the plant defense [27]. An alternative mechanism is the suppression of salicylic acid (SA)-mediated defense signaling. Sinorhizobium fredii HH103 with defective type III secretion system (T3SS) is unable to suppress SA-dependent defenses and subsequently fails to promote nodulation on the host [28], indicating that the suppression of the SA-dependent defense is critical for endophyte colonization. Some of those mechanisms have not been reported in legumes, but if those bacteria are colonizing legumes, similar mechanisms might be in action.
The establishment of the endophytic bacterial community in the legume host is a complex and dynamic process that has been studied mostly in fragments and simplified systems (usually one bacterial strain in one host under one or a few conditions), and it must be further understood to take the best advantages of their potential benefits for legume agriculture.
2.2 Endophytic bacterial diversity
There is an enormous diversity of bacterial endophytes in legumes, considering that the rhizobia are also endophytes. The interaction of rhizobia and legumes has been studied for more than a century [29]. Since then, many rhizobial endophytic bacteria were isolated from different legumes, particularly root and nodule tissue. These bacteria can establish a symbiotic interaction, induce the formation of new organs in roots and stems called nodules, and fix atmospheric nitrogen. In addition, the so-called “new rhizobia” (or noncanonical rhizobial genera) of Alfa- and Beta-Proteobacteria has been reported in the last decades. They can form nodules and fix nitrogen and mainly belong to Microvirga spp. and Burkholderia spp., respectively [30]. Other non-nitrogen-fixer endophytes are present in nodules and sometimes improve nodule formation [31, 32, 33]. For instance, Hoque et al. [34] isolated rhizobia and non-rhizobia endophytes from two wild Acacia species from Australia, and nodules were produced by species of the genera Rhizobium, Ensifer, Mesorhizobium, Burkholderia, Phyllobacterium, and Devosia, much more than expected. In addition, rhizobial species were isolated from other plant tissues apart from nodules [3].
Overall, from a large number of bacterial genera present in legumes, the most frequent ones (excluding rhizobia) are Agrobacterium, Bacillus, Enterobacter, and Pseudomonas, followed by Acinetobacter, Arthrobacter, Curtobacterium, Devosia, Dyella, Herbaspirillum, Klebsiella Micromonospora, Microbacterium, Mycobacterium, Ochrobactrum, Paenibacillus, Pantoea, Rhodopseudomonas, Serratia, Staphylococcus, and Sphingomonas ([3, 9, 21], and reference therein) (Tables 1 and 2).
Rhizobium phaseoli, Bacillus tequilensis, B. altitidinus, B. tequilensis, B. siamensis, B. subtilis, Pantoea dispersa, Paenibacillus illinoisensis, Kosakonia oryzendophytica, Rhizobium mayense, P. dispersa
IAA; ACC-DA; P, Zn, and Si solubilization, siderophore
Culture-dependent studies of the endophytic bacterial microbiota in legume crops.
ACC, 1-aminocyclopropane-1-carboxylate; ACC-DA, ACC deaminase activity; IAA, indole-acetic acid; BNF, biological nitrogen fixation; Develop., developmental stages; MG, meta-genomics; MT, meta-transcriptomics; N.D. not determined; N.S., not significant; Morph & Bioch., morphological and biochemical characterization, Treat, treatment or factor affecting microbiome.
2.3 Factors affecting diversity
The composition, diversity, and abundance of the endophytic microbiome are influenced by the soil microbial pool; the plant host identity and status (genotype, development, and physiology); agricultural practices; and climate and environmental conditions (such as temperature, water supply, and nutrients) [8, 16, 71]. Comparisons among plant species (canola, wheat, pea, and lentil) in different locations and soil types pointed to the genotype influence as the highest effect determining endophyte diversity ([72] in Table 1). However, when considering close Medicago genotypes (intraspecies comparison), the host genotype effect was not significant (1% of contribution to the total variance), but both soil and plant genotypes were significant for the root microbiota diversity [53]. In the case of the leaf microbiome, the soil reduces its relative importance, since some bacteria colonize it from underground organs, but others enter through stomata or vectors [46]. Broadly, the soil limits the available microbial pool, while the host genotype is a relevant barrier for colonization. Agricultural practices could directly affect the microbiome by chemical applications or through changes in the host physiology. The effects of biotic and abiotic factors shaping the endophytic bacteria communities in plants were reviewed by Papik et al. [73]. In addition, the actual diversity could be masked by the method used to describe it (such as culture-dependent or -independent, see Section 2.4) [16].
2.4 How to study microbiome diversity
Natural communities of endophytic bacteria are conventionally studied using culture-dependent and -independent methods [74]. Culture-dependent methods imply the extraction of the microbes and their growth in synthetic media. Those strategies allow to isolate the microbe and further study them in vitro and in manipulative experiments, but they strongly underestimate the number of bacteria (and the diversity of the community), as cultivable bacteria usually represent only 0.001–1% of the actual bacteria in a sample [16, 75]. Recently, Hartman et al. [52] isolated 200 bacteria strains that represent ~20% of the most abundant genera in Trifolium roots, which was one-quarter of the ~3500 detected OTUs in a manageable effort to increase the cultivated endophytic bacteria from a legume (Table 1).
On the other side, culture-independent methods mostly rely on the extraction of bacterial genetic material from plant tissues. The genomic DNA can then be analyzed using a range of molecular fingerprinting techniques such as Amplified rDNA Restriction Analysis, Gradient Gel Electrophoresis, and Terminal Restriction Fragment Length Polymorphism (RFLP) [16]. In recent years, DNA fingerprinting techniques have been set aside by more advanced molecular techniques. Those new methods involve DNA extraction from the entire bacterial population to sequence a specific phylogenetic marker, such as the 16S rRNA gene, or the whole genome [76]. In addition, using RNA instead of DNA, it is possible to detect active functional diversity, which provides information about the transcriptionally active functions, as well as the massive analysis of proteins (peptides) or metabolites (by high throughput analysis of “omics”). The latter two do not provide taxonomic information but a functional one.
The sequence-based methods allow a deeper analysis of the endophytic diversity than traditional fingerprinting, although some of the species with low abundance might be still missed. To minimize those losses, it is important to sequence with high depth and carry out rarefaction analysis (to check that the OTU versus the diversity or richness reaches the plateau). Other technical considerations for sequencing analysis are discussed in detail by Lucaciu et al. [77].
The bacterial diversity of the microbiome can be described taxonomically and functionally by different approaches. The most traditional strategy is the taxonomic description of the diversity, which identifies the species present in the microbiome and quantifies their abundance by genome or specific gene sequencing. From that data, researchers have started to uncover what is known as the “core microbiome” [78], which is defined as the group of species present in one plant across different genotypes, environments, developmental stages, etc. Depending on the scale of the analysis, a higher or lower number of species are shared among them. For instance, if dicot and monocot species are compared, the number of shared species will be lower than if two cultivars of the same species are compared in the same environment. A core endophytic microbiome of roots of red clover (Trifolium pratense) includes 70% of Rhizobia, and it was dominated by the genera Pantoea, Sphingomonas, Novosphingobium, and Pelomonas [52] (Table 1). Glycine spp. nodules showed a majority of Ensifer genera, followed by Enterobacter, Stenotrophomonas, and Chryseobacterium (>0.5%), and some nonrhizobial bacteria only in soybean (Glycine max), including Enterobacter cloacae (3.62%), Stenotrophomonas sp. CanR-75 (2.79%), and Stenotrophomonas maltophilia (2.41%) [40] (Table 1). Overall, little is known about the core endophytic microbiome in legumes, although some core rhizospheric microbiomes have been described (e.g., [79]).
In addition to the core microbiome, the “keystone” species have been described [80]. Keystones are highly connected species that largely change the structure and function of the microbiome when removed. They may be predicted by co-occurrence networks (by correlation analysis) and are defined as those whose abundance highly correlates with most of the other species [81]. Those correlations can be positive or negative (i.e., two species are always together or the presence of one excludes the other), and the interaction between each other may be indirect (for instance, mediated by a change in the host) [82]. It has been predicted that when the keystone species is missing, the abundance and proportion of the community change, and occasionally, one species may extremely proliferate over the others. Knowing which are the keystone species for one host is critical to effectively design any agricultural management strategy to protect a healthy microbial community and improve the fitness of the crop.
A second strategy to characterize the microbiome is the functional description, based on the metabolic functions present in the microorganisms. According to the previous model (with a core microbiome and keystone species), the communities in the microbiome are built to occupy functional niches [81]. This means that one species might be (at least partially) replaced by another one, which provides the same function to the community and/or the host. Those key functions of a particular species are given by a set of genes that allow the microbe to effectively interact and benefit the rest of the microbial community and the plant host under specific conditions. These functional traits can be screened and studied by any “omic” analysis and then grouped by the presence of specific metabolic functions (see [83, 85] in Table 1). For instance, the most important genes differentially detected in the rhizosphere of pea (Pisum sativum) under different tillage and fertilization treatments were genes coding ABC transporters and secretion systems, transcription factors, peptidases, methane metabolism, quorum sensing, and bacterial motility proteins [85]. To understand which services the microbial community provides and may favor the host plant, the functional analysis may be more useful than a taxonomic-only approach. However, both are necessary and provide valuable information about the microbiomes.
3. Benefits of endophytic microbiota to the host plant
Once within the plant, endophytes might provide several benefits. We grouped them into three different kinds: direct growth promotion, protection against pathogens, and protection against abiotic stress (Figure 1).
Direct promotion occurs when endophytes stimulate shoot and/or root growth by increasing the availability of limiting nutrients or producing compounds that directly stimulate growth. On the other hand, indirect promotion occurs when the endophytes can protect the plant against diseases, pests, or environmental stress, indirectly improving the host performance [86]. The molecular mechanisms and pathways are not exclusive for each direct or indirect growth promotion effect. A single endophytic bacterial strain may have more than one of these plant-growth-promoting traits (e.g. [37, 41, 48, [49, 55] in Table 1, and [56, 57, 63, 65, 66, 68] in Table 2).
3.1 Increase of nutrient availability
The main mineral nutrients required for plant growth are nitrogen, phosphorus, and iron. There are numerous plant-growth-promoting microorganisms able to increase their availability, and some mechanisms have been determined.
3.1.1 Biological nitrogen fixation (BNF)
Nitrogen is crucial for plant growth and health. Approximately 30–50% of the N in crop fields results from BNF by soil microorganisms. The ability to fix atmospheric nitrogen (N2) is present in various bacterial species that are either free-living or endophytically associated with plant roots. BNF is the most and long-term studied plant-growth-promoting effect of soil microorganisms in legumes [87, 88]. Other plant growth promoter bacteria genera, different from rhizobia, are also able to enhance the acquisition of N by legumes. Anzuay et al. [89] and Taurian et al. [90] observed that endophytic bacteria belonging to Serratia, Acinetobacter, Bacillus, and Enterococcus enhanced peanut (Arachis hypogaea) N content. Dey et al. [91] reported that the increase in the number of nodules in plants inoculated with growth promoter bacteria could be attributed to the enhancement of root growth and root length. This enhancement provides more sites for nodulation by rhizobial strains in the soil. Furthermore, since BFN is a highly demanding ATP process, phosphorus is a critical nutrient for legumes.
3.1.2 Phosphate solubilization and mineralization
Even in phosphorus-rich soils (such as phosphate-fertilized soils), most of this element is in insoluble forms, and only a small proportion (~0.1%) is available to plants [92]. The solubilization of phosphates in the rhizosphere is one of the most common modes of action of growth promoter microbes that enhance nutrient availability to plants [93]. Phosphate-mineralizing and phosphate-solubilizing bacteria (PMB/PSB) secrete phosphatases and organic acids to convert insoluble phosphates (organic and inorganic) into soluble monobasic and dibasic ions [93]. Among legume endophytes, there are several phosphate-solubilizing bacteria able to promote plant growth, and some studies demonstrated that plant growth promotion was directly correlated with the increase of P in the plant tissues [89]. Soybean and peanut endophytes solubilize mineral phosphate [90]. In addition, several studies described endophytic bacteria with phosphate-solubilizing/-mineralizing ability that increase legume growth [89, 90, 94, 95]. The inoculation of pea with phosphate-solubilizing Pseudomonas spp. isolated from this legume, enhanced the plant biomass [96]. Pantoea spp. isolated from root nodules of peanut showed a strong phosphate-solubilizing activity [97]. However, the inoculation of phosphate-solubilizing bacteria isolated from peanuts did not promote growth when they were inoculated in the rapeseed culture [98]. These results point to a specific plant-bacteria interaction that directly affects the ability to promote growth or the efficiency of the mechanism.
The main phosphate-solubilizing mechanism in Gram-negative bacteria involves the bacterial PQQ cofactor, described as essential in P nutrition and plant growth. Mutation in the pqqH gene from Pseudomonas fluorescens caused the loss of the phosphate-solubilizing phenotype and plant growth promotion ability on tomato plants [99]. In legumes, Ahmed and Shahab [100] observed that a non-producing-PQQ bacteria (which lost the phosphate solubilization ability) showed a decrease in the growth promotion of bean plants. On the contrary, Ludueña et al. [101] determined that in the non-producing PQQ strain Serratia sp. promoted the growth of peanut at a similar level to the wild type, indicating that PQQ is not essential for growth promotion.
3.1.3 Iron uptake
Iron is essential for all living organisms, and its bioavailability in the soil is limited. Siderophores are small molecular compounds, secreted by microbes, which chelate iron in the soil and generate soluble complexes that can be absorbed by plants [97]. Microbial siderophores’ secretion directly stimulates plant growth by increasing the availability of iron in the soil surrounding the roots [102]. Plants lacking soil bacteria suffered from iron deficiency [103]. Therefore, this mechanism helps plants to thrive in low-iron soils. The inoculation of black mung bean (Vigna radiata) with the siderophore-producing endophyte, Pseudomonas sp. GRP3, reduced iron deficiency and chlorotic symptoms and increased the content of chlorophyll a and b [104]. Furthermore, since diazotrophic organisms require Fe+2 and Mo+2 factors for the functioning and synthesis of nitrogenase, iron solubilization by microbes also improved nitrogen fixation in legumes [105]. Native peanut isolates produce siderophores together with other plant-growth-promoting traits, increasing peanut growth and performance [106].
3.2 Phytostimulators
Endophytic bacteria directly promote plant growth by the production of phytohormones, such as auxin or cytokinin, or by lowering the plant ethylene (ET) levels. By these mechanisms, bacterial endophytes can also accelerate seedling emergence and promote plant establishment under adverse conditions.
3.2.1 Phytohormone-like molecule production
The production of phytohormones-like compounds is considered an important trait of endophytes that positively affects the growth and development of many plants including legumes [8, 10, 107]. Thus, changes in plant growth frequently reflect alterations in phytohormone levels induced by endophytes [3]. But, even when production of these compounds by growth promoter microbes has been demonstrated, that effect cannot be unequivocally attributed to them.
The five main phytohormones produced by bacteria are auxins, cytokinin, gibberellins, ET, and abscisic acid (ABA). It has been postulated that genes encoding biosynthesis of the auxins, cytokinin, and gibberellins are often present in the metagenome of plant endophytic bacterial communities [108]; however, it has not been yet explored in legumes using any omics approach (ET and ABA are discussed in Section 3.4.3).
Among these growth regulators, auxins are the most studied. These compounds affect plant growth by inducing cell enlargement and division, root development, apical dominance, increase growth rate, photo- and geo-tropism [109]. The production of auxin-like compounds increases seed production and germination along with increased shoot growth and tillering. Within these compounds, indole-acetic acid (IAA) is the most frequent and indeed most studied phytohormone in growth promoter bacteria. IAA produced by endophytic bacteria is one of the most relevant and studied effector molecules in growth promotion, pathogen defense, and plant-microbe interactions [104]. For instance, rhizobia from soybean, pea, and faba bean nodules not only fix nitrogen and produce siderophores, but also auxins (see Refs. [54, 110] in Tables 1 and 2, and [61]). IAA can be synthesized directly by plant-associated microbes, and ~ 80% of the rhizosphere bacteria may produce IAA [69, 111]. For instance, it could be produced by Alcaligenes, Azospirillum, Pseudomonas, Pantoea, Rhizobium, and Enterobacter in the presence of L-tryptophan as a precursor, although there are other pathways and a variety of auxins, such as indole-3-butyric acid (IBA), indole-3-pyruvic acid (IPA), or tryptophol (TOL), which are also produced by growth promoter bacteria [112].
Cytokinins are another group of growth-stimulating phytohormones that are responsible for cell division, plant senescence, seed germination, flower and fruit development, and apical dormancy [113, 114]. Although cytokinins are produced by several growth promoter microbes, few studies have demonstrated their beneficial effects.
Gibberellins are involved in many developmental processes in plants, such as flowering regulation, seed germination, stem and leaf elongation [114], but also the promotion of nodule organogenesis and the negative regulation of the rhizobial infection and root system development [115].
Several bacteria produce and regulate the production of more than one phytohormone, such as the rhizobacteria Bacillus aryabhattai, which produces ABA, IAA, cytokinin, and gibberellic acids in vitro and promotes soybean growth [116]. Thus, inoculation with endophytic bacteria may benefit legumes via the production or suppression of some phytohormones.
3.2.2 Volatile compounds and other phytostimulators
Some growth promoters’ bacteria can regulate plant growth by releasing volatile compounds [86]. For instance, B. subtilis, Bacillus amyloliquefaciens, and E. cloacae promote plant growth in legumes by releasing volatiles, such as 2,3-butanediol and acetoin [117, 118], while the mutants of B. amyloliquefaciens IN937a and B. subtilis GB03, blocked in their biosynthesis, did not promote Arabidopsis growth [118]. Studies on growth promotion by Chryseobacterium rhizoplane in mung bean indicate that 2,3-butanediol is the molecule causing growth stimulation [119]. Growth promotion mechanisms of volatiles in plants were reviewed by Sharifi and Ryu [120].
Other nonvolatile molecules such as bacterial cell components or secreted compounds have been proposed to be plant growth stimulators. The endophyte Serratia proteamaculans was able to promote soybean growth by the production of a lipo-chitooligosaccharide [121]. And the PQQ peptide, previously mentioned to be associated with P solubilization, has also shown growth promotion [99], antifungal activity, and the ability to induce systemic resistance [86]. The role of PQQ in plant-microbe interaction has been reviewed by Carreño-Lopez et al. [122].
Lastly, endophytes can generate allelopathic effects inhibiting the growth of neighboring plants or protecting the host plant from allelopathic effects from adjacent plants [123]. For example, endophytic bacteria of red clover seem to be responsible for the negative allelopathic effects observed over maize, reducing seedling emergence and height [124]. Additionally, some weeds have negative allelopathic effects on legumes, mediated by their endophytic bacteria, which inhibit nodulation [125].
Overall, there is a body of evidence that suggests that enhancing or regulating phytohormone or other phytostimulators via endophytic microorganisms is a viable strategy to increased crop production in agriculture [108], and because of these attributes, endophytes have gained ground in the area of agricultural sustainability.
3.3 Protection against pathogens
Among the major factors restraining agriculture are crop diseases and pests, while one important driver of plant health is the structure and dynamics of the plant-associated microbial communities [126]. In recent years, a deeper understanding of the endophytic microbiome and its potential has been achieved to become a fundamental tool in phytosanitary management and reduce the damage of plant diseases.
Endophytes can decrease the harmful effects of pathogens by different mechanisms, including direct and indirect mechanisms [104]. Direct inhibition of pathogens is mainly mediated by the synthesis of inhibitory allelochemicals such as antibiotics, hydrogen cyanide, iron-chelating siderophores [127], secretion of lytic enzymes, or quorum quenching (QQ) by degrading pathogens autoinducer signals [128]. Indirect biocontrol mainly includes the induction of the plant systemic resistance that inhibits the proliferation of a broad spectrum of phytopathogens [129].
3.3.1 Antibiosis
Most endophytes have been reported to produce secondary metabolites, and some of them exhibit antibacterial and antifungal properties, which help to inhibit the growth of phytopathogenic microorganisms [44]. Many metabolites with antimicrobial properties synthesized by endophytes have been described so far, such as flavonoids, peptides, quinones, alkaloids, phenols, steroids, terpenoids, and polyketides. Antimicrobial properties of bacterial metabolites were recently reviewed [130]. Hansen et al. [131] studied the microbiome of alfalfa (Medicago sativa) nodules and identified two families of molecules produced by Brevibacillus brevis in planta, such as antibacterial thyrozidines, and a new set of gramicidin-like molecules, britacidins. They conclude that, in addition to nitrogen fixation, it is likely that legume root nodules are also a source of active antimicrobial production.
3.3.2 Lipopeptides
Lipopeptides are low-molecular-weight cyclic peptides attached to a hydrophobic fatty acid. These molecules are classified into three families: surfactin, iturin, and fengycin. Iturins and fengycins show strong antifungal activities while surfactins exhibit strong antibacterial activity. Antimicrobial lipopeptides can form toroidal-like pores on cell membranes leading to membrane permeation and/or disintegration and protect plants directly suppressing the growth of pathogens or inducing systemic resistance [132]. Recently, 263 different lipopeptides were synthesized by 11 microbial genera, with Bacillus being the most abundant [133].
The common bean root microbiome was used to search potential biocontrol agents of Fusarium sp., Macrophomina sp., and Alternaria sp. fungi, causal agents of root rot disease [65]. Biocontrol assays conducted under controlled conditions demonstrated that B. amyloliquefaciens, B. halotolerans, Bacillus velezensis, Agrobacterium fabrum, and Pseudomonas lini displayed the highest protective effect, and lipopeptide biosynthetic genes encoding surfactin, iturin, bacillomycin, and fengycin were present. These bacteria can produce at least one or more lipopeptides that may be involved in biocontrol activity.
3.3.3 Lytic enzymes
During plant colonization, endophytes produce numerous enzymes, which successively aid the hydrolysis of the plant cell wall. There are numerous types of enzymes such as chitinases, cellulases, hemicellulases, and 1,3-glucanases [70, 134]. These enzymes are also capable of degrading fungal (and oomycetal) cell walls hyphae, spores, and sporangia, thus contributing to the protection of the plant. The isolate Pseudomonas spp. EGN 1 was the most promising bioagent for the management of the stem rot (Sclerotium rolfsii) in groundnut, mediated by an important protease and cellulase production [57]. While, Brigido et al. [135] evaluated the diversity and functionality of the endophytic bacterial strains in the roots of native legumes from two different sites in Portugal, finding 15 isolates with a high cellulase production.
3.3.4 Hydrogen cyanide
A few bacterial species are known to produce and excrete hydrogen cyanide, a potent inhibitor of cytochrome c oxidase and several other metalloenzymes [136]. The host plant is unaffected by the bacteria or the hydrogen cyanide produced by it. For this reason, hydrogen-cyanide-producing bacteria have an application as biological control agent. Zaghloul et al. [137] isolated a total of 167 endophytic bacterial from roots, nodules, leaves, and stems of faba bean (Vicia faba), pea, fenugreek (Trigonella foenumgracum), lupine (Lupinus spp.), common bean (Phaseolus vulgaris), and rice (Oryza sativa) at flowering stage. About 82% of the isolates showed positive results of hydrogen cyanide production. In another recent investigation, ~20 endophytic bacteria isolated from roots and nodules of chickpea (Cicer arietinum) and pea showed HCN production [66].
3.3.5 Siderophores
As previously mentioned, siderophores chelate iron in the soil making it more available for plants. Furthermore, by tightly binding the iron, siderophores reduce its bioavailability for plant pathogens and facilitate the death of the phytopathogens [138]. Some of the siderophores are known to be produced by endophytes, such as hydroxymate, phenolate, and/or catecholate types, confer biocontrol activities [139]. Also, the role of siderophores as part of the protective effect of the induced systemic resistance has been described in many studies. The production of siderophores is very common among Pseudomonas, Frankia, Streptomyces sp. Several researchers described endophytic bacteria producing siderophores isolated from different legumes as peanut, faba bean, soybeans, chickpea, pea, and bean [65, 66]. Bahroun et al., [140] demonstrate that Rahnella aquatilis B16C, Pseudomonas yamanorum B12, and P. fluorescens B8P isolated from faba bean nodules suppressed Fusarium solani root rot in three faba bean cultivars in greenhouse. The three strains were able to produce siderophores and significantly reduced the disease severity. Zhao et al. [54] obtained 276 isolates from root nodules of soybean, six of which showed antagonistic to the pathogenic fungus Phytophthora sojae 01. The isolates were identified as Enterobacter, Acinetobacter, Pseudomonas, Ochrobactrum, and Bacillus genera. The high correlation of siderophores production and the fungal inhibition of nodule endophytic bacteria in that study supported the idea that the ferrous absorption by endophytic bacteria may be a viable inhibitory mechanism.
3.3.6 Quorum quenching
The regulation of gene expression in response to fluctuations in cell-population density is known as “quorum sensing.” Many important bacterial processes are regulated by it. Quorum sensing regulates gene expression depending on the accumulation of a signal molecule in the environment. The signal, called autoinducer, allows the bacteria to perceive the existing population density and jointly executed responses. Gram-negative bacteria use acyl-homoserine lactone (AHL) as an autoinducer, whereas Gram-positive bacteria utilize modified peptides [141]. The bacterial quorum sensing controls a wide variety of physiological processes such as virulence, extracellular polymeric substances (EPS) production, mobility, and biofilm formation among others, which are essential for the establishment of a pathogen in the host plant [142].
Often endophytic bacteria can disrupt quorum sensing. This ability to interfere with bacterial cell-to-cell communication was collectively called “quorum quenching” and can be crucial to prevent the plant colonization by pathogenic bacteria that use quorum sensing to coordinate virulence [143]. Several chemicals and enzymes have been identified that target the key components of bacterial quorum-sensing systems in the recent years (such as [33]). The mechanisms of quorum quenching may be the inhibition of the signal synthesis or detection, signal enzymatic degradation (by enzymes such as AHL acylase, AHL lactonase, and oxidoreductases), or synthesis of structural analogs of the signal [144]. Lopes et al. [145] reported antimicrobial activity against Pseudomonas syringae pv. tabaci or Hafnia alvei 071 in endophytic bacteria isolated from common bean. The isolates Microbacterium testaceum BAC1065, BAC1100, and BAC2153, Bacillus thuringiensis BAC3151, and Rhodococcus erythropolis BAC2162 exhibited a greater ability to inhibit the response of AHL reporter.
3.3.7 Insecticides
Some metabolites with insecticidal action have been described. The famous B. thuringiensis produces crystalline inclusion bodies consisting of delta-endotoxins (also referred to as Cry proteins) during sporulation. These proteins, which are formed by variable-molecular-weight polypeptides (27–140 kDa), are highly toxic for a broad range of pest insects [146]. P. fluorescens strains exhibited a protective effect against aphids and some herbivorous beetles and termites [147]. The bacterium Lysinibacillus sphaericus (former Bacillus sphaericus) produces sphaericolysin, which is toxic for Spodoptera litura [148].
3.3.8 Induction of systemic response
Induced systemic resistance (ISR) is a term used for the resistance stimulated by chemicals agents or signals (elicitors) produced by beneficial microorganisms [149], whereby the plant’s innate defenses are potentiated against subsequent biotic challenges. In this way, the endophytes enhance the plant defenses against many pathogens [129]. The plant hormones jasmonic acid (JA) and ET are responsible for the regulation of the group of interrelated signaling pathways required to activate ISR. The main routes by which microbes regulate ISR in plants include: (i) phytohormones, (ii) pathogen-associated molecular patterns (PAMPs)/microbe-associated molecular patterns (MAMPs), and (iii) several elicitors (volatile organic compounds, siderophores, phytases, miRNAs, among others) [150]. Bacterial endophyte-mediated ISR has a broad spectrum of effectiveness. It was demonstrated that Acinetobacter, Azospirillum, Rhizobium, Pseudomonas, and Bacillus are beneficial inducers of systemic resistance in both leguminous and nonleguminous plants [151]. Dey et al. [91] described an endophytic isolate Klebsiella pneumoniae HR1 from the root nodules of black mung bean (Vigna mungo) capable of reducing the occurrence of Macrophomina phaseolina, which is the causal agent of the root rot disease in Vigna. The lowest percentage of disease incidence (18.2%) was observed when K. pneumoniae was applied in dual mode (seed bacterization + soil drench application). The increased activities of peroxidase (PR9), chitinase (PR3), and β-1,3-glucanase (PR2) in leaves indicated that K. pneumoniae HR1 induces a systemic response.
Endophytic bacteria have diverse mechanisms that could contribute, even simultaneously, to protect the plant against the attack of different pathogens, having the potential to produce a more efficient pathogen control on the fields.
3.4 Abiotic stress tolerance
Under abiotic stress conditions (such as drought, salinity, flooding, heat, chilling, or heavy metals), several metabolic responses are shared among plant species. Most of the stresses cause photosynthesis inhibition, oxidative stress, and hormone imbalances ending in reductions of shoot growth and yield impairments [10, 97, 152, 153, 154]. In addition, some of the responses are interconnected, for instance, reactive oxygen species and hormones mutually affect each other at early and late phases of abiotic stress (reviewed by [155]).
Endophytic bacteria can protect the host plant against some of those deleterious effects, by at least two different ways (alone or combined): (i) activation of host stress response systems soon after exposure to stress (named induced systemic tolerance), and (ii) biosynthesis of chemicals, which will contribute to the stress tolerance in the host [9]. Here we focus on three mechanisms by which the bacteria can protect the plant host against abiotic stress: redox status, water balance, and hormone regulation.
3.4.1 Redox status regulation
Oxidative damage (caused by reactive oxygen and nitrogen species) is a common consequence of environmental stress, which may cause damage to lipids, proteins, and overall to any subcellular component [156]. Then, the activation of the enzymatic and nonenzymatic antioxidant system is critical to tolerate adverse conditions. Several endophytic bacteria mediate a higher induction of the antioxidant system under stress. For instance, under salinity, the inoculation of peanut with the halotolerant bacteria Brachybacterium saurashtrense JG-06, Brevibacterium casei JG-08, or Haererohalobacter JG-11 showed lower oxidative damage, ion leakage, and K/Na ratio and higher growth, IAA, and Ca [157], while the inoculation of B. subtilis (alone or combined with Mesorhizobium ciceri) of chickpea reduced hydrogen peroxide accumulation and improved plant growth [10]. Soybean plant inoculated with Curtobacterium sp. SAK1 induced polyphenol oxidase activity, associated with growth protection and hormonal changes [158], while inoculated with Pseudomonas simiae increased catalase and peroxidase, but not polyphenol oxidase gene expression under salinity [159]. Also, soybean inoculated with B. cereus, Pseudomonas otitidis, and Pseudomonas sp. showed a reduction of hydrogen peroxide and membrane oxidative damage caused by PEG-induced drought [160]. However, if these responses are generated by the plant or bacterial enzymes remains unknown.
3.4.2 Water use efficiency regulation
Under stress, plant tissues usually modulate osmotic and water retention, by stomata activity and/or accumulation of osmotically active compounds. The latter compounds, also known as compatible solutes, include sugars (e.g., sucrose, trehalose, etc.), organic acids (e.g., malate), inorganic ions (e.g., calcium), amino acids (e.g., glycine betaine, proline) [161]. An increase in drought tolerance was detected after the inoculation of Sphingomonas sp. LK11 (isolated from Tephrosia apollinea) in soybean, by the accumulation of sugars and amino acids (glycine, glutamate, and proline) [162], and after the inoculation with Rhizobium etli in common bean, by the overexpression of trehalose-6-phosphate synthase [163]. Trehalose is an osmotically active compound that accumulates both in plants and microbes under stress. In particular, the role of trehalose in the tripartite symbiosis between plants, rhizobia, and arbuscular mycorrhiza under abiotic stress has been recently reviewed [164].
The optimal regulation of water use efficiency is critical to improved crop production. On one side is essential to survive dehydration stress (such as drought, salinity, heat, and chilling), but a constitutively highly efficient water use may reduce yields, by reducing CO2 assimilation. The use of bacteria that contribute to transiently intensify stress-tolerance responses can help to improve productivity in marginal environments. In addition, if the endophytic bacteria enhance the osmocompatible compounds in response to the stress, it is possible to increase not only the tolerance to drought, but also the tolerance to chilling, heat, and salinity stress, which share a “dehydration” component. In the latter case, we expect a partial tolerance due to the ion toxicity, not related to the reduction in water potential.
3.4.3 Hormone regulation
As it was mentioned before, endophytic bacteria can regulate hormone synthesis and degradation and synthesize some of the plant hormone-like compounds by themselves. In addition, specific hormone regulation could also protect against abiotic stress increasing growth, yield, and survival.
Abscisic acid (ABA) is the main plant hormone related to water stress. It stimulates root growth and optimizes water uptake and nutrient acquisition, regulates shoot and root hydraulic conductivity, and upregulates the antioxidant system and compatible osmolytes synthesis [161]. The inoculation of Sphingomonas in soybean leaves induced ABA accumulation and reduced chlorophyll degradation and growth inhibition. However, under drought, ABA levels were lower in inoculated plants. So, in this case, the initial increase of ABA might have a role in acclimation to the stress induced by the bacteria inoculation [162]. In addition, ABA may interfere with SA-, JA-, and ET-mediated plant defenses [165], which may have undesired consequences under biotic stress.
Ethylene (ET) is usually considered a plant growth inhibitor, but at low levels, it can promote growth in several plant species. At moderate levels, ET inhibits both root and shoots elongation, while at high levels, enhances senescence and organ abscission [166]. The direct precursor of ET in the plant biosynthetic pathway, 1-aminocyclopropane-1-carboxylate (ACC), is exuded from plant roots together with other amino acids. The enzyme ACC deaminase cleaves ACC into ammonia and alfa-ketobutyrate. Plant growth promoter bacteria that express the enzyme ACC deaminase utilize their products (ammonia and ketobutyrate) as nitrogen and carbon sources, respectively. Bacterial ACC deaminase is not excreted from the bacterial cytoplasm [167]; hence, the decrease of plant ET levels relies on the ability of ACC deaminase expressing bacteria to take up ACC before it is oxidized by the plant’s ACC oxidase [167]. When those bacteria are present, ET production could be lowered, relieving stress-induced growth inhibition [168]. For instance, the inoculation of pea (P. vulgaris) plants with Aneurinibacillus aneurinilyticus and Paenibacillus sp., two strains with high ACC activity in vitro, increased salt and drought tolerance. The combined inoculation reduced plant ET content and increased root and shoot length and biomass, as well as chlorophyll content [169]. The inoculation of alfalfa plants with Bacillus megaterium NMp082, which can produce ACC deaminase activity and IAA in vitro, also enhanced their salt tolerance [170]. Lastly, a novel mechanism was proposed in which salt tolerance is mediated by the activation of ET signaling. The inoculation of alfalfa with the bacteria Enterobacter sp. SA187 (isolated from a desert plant) increases salt tolerance, and studies in Arabidopsis indicate that the bacteria activate the ET signaling pathway [171]. The different mechanisms by which microorganisms can interfere with ET signaling were reviewed by Ravanbakhsh et al. [167].
Auxins regulate many important physiological processes related to growth and development affecting photosynthesis and responses to stress [161]. Under stress, auxins stimulate root elongation and density, increasing the water and nutrient availability, although they may interfere with SA-dependent plant defenses.
The inoculation of chickpea with Serratia sp. in nutrient-deficient soil induced more IAA and higher yields [172], while the same plant inoculated with IAA-producing B. subtilis NUU4 in combination with M. ciceri IC53 stimulated root and shoot biomass and improved nodule formation under salt stress [173]. Soybean plants inoculated with B. aryabhattai strain SRB02, which produces IAA, GA, and ABA, showed higher drought tolerance through stomatal closure, and higher root and shoot rates under high temperatures [116], and the same host treated with Sphingomonas sp. LK11 and Serratia marcescens TP1 (which produced IAA in vitro) stimulated root and shoot growth with increased ABA and GA and reduction of JA [162]. Overall, abiotic stress protection mediated by plant hormones and crop salinity protection mediated by beneficial bacteria have been reviewed [10, 174, 175].
Some primary stresses share the responses among them, such as those that generate dehydration (water or temperature deficit) or oxidative stress (dehydration, hypoxia, ions). For example, the double inoculation of chickpea with M. ciceri IC53 and B. subtilis NUU4 reduced the infection rate of root rot caused by Fusarium solaniin salty soils [173], although the mechanism was not determined. Then, a bacteria strain, inducing a protective mechanism against oxidative stress, can protect the crop against a diversity of stress, which generates redox imbalances. Consequently, knowing the responses that each stress triggers in the plant may allow us to predict which bacteria or group of them could protect the plant against a combination of stresses.
4. Synthetic communities of plant-associated bacteria to a more sustainable agriculture
Natural microbial communities within the plants are complex systems, with unknown functions and interrelationships among the microbial species and with the host plant. Small consortia of bacteria, with a “designed” composition, called “synthetic communities,” reduce the complexity of those systems to be studied and used. The goal is to simplify the network while preserving the interactions and most of the functions, which may be lost in single plant-microbe interactions [175]. The use of synthetic communities allow us to ask questions about the performance and stability of the microbial community as well as to study conditions necessary to generate interaction patterns required to provide specific benefits. They are not only valuable as models but also as assays for biotechnological approaches [176].
4.1 How to study synthetic communities?
Manipulative experiments with synthetic bacterial communities can validate the predicted keystone species and, in general, help to find out specific effects of the resulting community under some pathogen infection or environmental condition. Those studies required in vitro experiments in gnotobiotic (germ-free) systems [11], where the plant is inoculated with a few or several microbial species, and the diversity is monitored across time. For instance, a gnotobiotic system was used to study the bacteria-colonizing alfalfa nodules [131]. The authors inoculate alfalfa with the four accessory bacterial members B. brevis Ag35, Paenibacillus sp. Ag47, Pseudomonas sp. Ag54, and Pantoea agglomerans Ag15, plus the nodulating strain Sinorhizobium meliloti RM1021. They observed that the addition of B. brevis neutralized the cooperation between Pseudomonas sp. Ag54 and Paenibacillus sp. Ag47, shifting the community from cooperative to competitive.
Another alternative, it is to use synthetic communities in a non-germ-free environment (more accessible and simpler to set up) to evaluate the protective or antagonist effect of a small group of species under a particular condition. Overall, only a few studies of the kind have been carried out in legumes until now. For instance, Lu et al. [177] described the diversity of nonrhizobial bacteria (32 genera) in legume nodules inoculated with Bradyrhizobium elkanii H255, Rhizobium multihospitium–like HT221, or Burkholderia pyrrocinia with or without the addition of N fertilization. The study suggested a vital role of that group of bacteria in N fixation in legumes.
The synthetic communities are a way to understand how microbial communities are built in the plants but also the base to a more complex (and likely more effective) phytostimulation effects, biological control of diseases, and protection against abiotic stress.
4.2 Can we manipulate the plant microbiome to improve the fitness or yield of legumes?
There are a variety of strategies to manipulate the microbiome of a plant host and could be classified according to the direct target: (i) the microbiome itself, (ii) the plant genome, or (iii) the holobiome (plant plus microbial community) (reviewed by [39, 178]).
The microbiome (i) can be modified by the exogenous inoculation of the microbe, increasing the abundance of a single strain or a few species together. The first case is the most traditionally used, and there are thousands of examples, such as the inoculation with rhizobia. In those cases, the single strain should be compatible with the host genotype and able to overcome the competence of the native microbiome and the environmental conditions. The second case is open to unexplored scenarios, such as an infinite possibility of a higher number of strains/species combinations. This strategy is just starting to be explored, such as with non-nodulating bacterial species present in the nodules (and sometimes in the rest of the plant) that promote nodulation. For instance, the inoculation of common bean (P. vulgaris L.) with Paenibacillus polymyxa and B. megaterium strains showed a synergistic effect with Rhizobium strains on the plant growth [179]. On the contrary, the inoculation of alfalfa with different strains of the mutualistic P. fluorescens, showed that the increase in the community richness led to a negative complementary effect causing the loss of the protective effect against pathogens [180]. These results highlight the importance to evaluate the effects of any agricultural treatment or management on the microbial community.
The inoculation with synthetic communities has the advantage (over the use of the native microbiome) to allow the design of a community, which includes distant species (which may provide complementary benefits), or similar species, which increase the efficiency of the community (by using a wider diversity of resources) [19]. However, with the number and diversity of species, it also increases the complexity to handle the system and to commercialize the inoculants.
The plant genome (ii) could be manipulated by traditional breeding, gene editing, or transgenesis, changing the ability of the host to interact with the microbes (such as changing the exudates or volatiles). Instead of only breeding for pathogen resistance or abiotic stress tolerance, this could be a complementary alternative to select crop legumes to be more responsive to the presence of beneficial microbes [181]. For instance, modern accessions of common bean showed a lower abundance of Bacteroidetes and higher of Actinobacteria and Proteobacteria than the wild accession [79], with a gain in the diversity of rhizospheric bacterial and a stronger effect of the bean genotype [182]. In addition, Mendes et al. [183] showed that common bean breeding for Fusarium oxysporum resistance altered the functionality of the rhizosphere, unintentionally increasing the host protection against other pathogens. We hypothesize that a similar effect is happening in the endosphere, although it has not been explored yet. Additionally, when using this approach, it is relevant to evaluate that host defenses against pathogens are still functional.
Lastly, the holobiome (iii) could be altered through specific agricultural practices such as crop rotation, mineral, and organic fertilization, tillage practices, etc., favoring a specific community composition or function. Several studies reported the effect of agricultural management on the rhizosphere of legumes and its effect on crop performance. A meta-study showed the effect of crop rotation, intercropping, or companion planting on the rhizospheric microbial richness and diversity [184]. Those agricultural practices did not always have positive effects in richness and diversity, and legume-cereal crop rotation (relevant to reduce N fertilization) showed inconsistent results on the microbiome. A recent study showed that pea-wheat rotations showed no effect in the diversity index, but they affected the specific co-occurrence networks for each crop [185] suggesting a more complex effect of crop rotation that needs to be further studied. Certain chickpea cultivars select a more beneficial microbiome for the subsequent wheat plants, and they were associated with the antagonist species Penicillium canescens [186]. Red clover and potato crops in rotation shared 73% of the bacterial endophytes, and 21% of those species promoted plant growth and yield in potato bioassays [187], while 74% of the shared species showed some degree of in vitro antibiosis against Rhizoctonia solani, a pathogen of both crops. We hypothesize that changing the rhizosphere will affect the endosphere too, by changing the available microbial pool, but that effect has not been explored at legume endophytic microbiomes.
4.3 Are there collateral impacts of using synthetic communities in agriculture?
Lastly, it is important to consider alive microbes will be released to the environment and into products used or consumed by humans and animals, so the potential risks need to be considered and tested [188]. There is no internationally agreed protocol to be complimented, but recently, Vilchez et al. [189] have proposed an Environmental and Human Safety Index (EHSI) protocol to determine the safety of the bacterial strains. The protocol evaluates microbial and animal sensitivity/pathogenicity and ecotoxicity in different model organisms, and it has been validated for many well-known bacteria. In addition, on the agronomical level, little information is available on the nontarget effects on microbial communities and the resulting impact on the soil function [32].
5. Final remarks and future directions
Agricultural legume crops are usually treated with synthetic chemicals to increase growth, control diseases, and mitigate environmental stress, which has high economic, environmental, and health costs. However, there is a myriad of endophytic bacteria that colonize the plant at least in part of its life cycle that could replace or complement those chemicals with great benefits for the plants. In addition, the huge bacterial diversity could be combined to provide several benefits at the same time. For that purpose, the use of synthetic communities is critical to study how the microbial community evolves within the plant as much as their beneficial effects.
The use of synthetic bacterial communities to improve and make more sustainable legume production is still in early stages of development, but it is a promising field. Using synthetic communities has the theoretical advantage of combining strain benefits and contributing to the survival of the bacteria on the field and inside the plant while producing a package of benefits for the legume. Although it is expected to have more difficulties at the time of commercial production.
On the other hand, changes in the agricultural management with some specific purpose could be a more affordable strategy for most of the small-scale producers in low-income countries, which are the ones in more need of sustainable and accessible technologies. Additionally, the use of soil-native microorganisms could have the advantage to reduce possible adverse consequences on the environment and health.
For the moment, the knowledge about endophytic bacteria in legumes, the possibility to “design” synthetic communities for a specific goal, and to manipulate the holobiome by agricultural practices is still incipient. However, the potential benefits for current agriculture to improve yields and sustainability have a great unexplored potential in the endophytic bacterial microbiome of legume crops.
Acknowledgments
This work was supported by FONCyT (PICT STARTUP 2018-0065, PICT 2018-01326) and INTA (I069, I127, I516). CC is a CONICET fellow. MIM and TT are Career Investigators of CONICET. MIM, LV, and MCG are Career Investigators of INTA.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Author contributions
LV and MM conceived and planned the overall idea of the review manuscript. All authors contributed to the article and approved the submitted version.
\n',keywords:"sustainable agriculture, abiotic and biotic stresses protection, food security, endophytic bacteria, synthetic communities",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80641.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80641.xml",downloadPdfUrl:"/chapter/pdf-download/80641",previewPdfUrl:"/chapter/pdf-preview/80641",totalDownloads:53,totalViews:0,totalCrossrefCites:0,dateSubmitted:"September 19th 2021",dateReviewed:"January 7th 2022",datePrePublished:"March 31st 2022",datePublished:null,dateFinished:"February 27th 2022",readingETA:"0",abstract:"Plant-associated microbiomes confer fitness advantages to the plant host by growth promotion through different mechanisms including nutrient uptake, phytohormones production, resistance to pathogens, and stress tolerance. These effects of the potentially beneficial microbes have been used in a diversity of biotechnological approaches to improve crop performance applying individual bacterial cultures. However, healthy plants host a diversity of microorganisms (microbiota). Next-generation sequencing technologies have offered insights into the relative abundances of different phylogenetic groups in a community and the metabolic and physiological potential of its members. In the last decade, researchers have started to explore the possibilities to use temporal and functional combinations of those bacteria in the form of synthetic communities. In this chapter, we review the benefits of using endophytic bacteria in legumes, the available methodological approaches to study the effects of bacterial communities, and the most recent findings using synthetic communities to improve the performance of legume crops.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80641",risUrl:"/chapter/ris/80641",signatures:"Mariela I. Monteoliva, Lucio Valetti, Tania Taurian, Clara S. Crociara and María Carla Guzzo",book:{id:"10749",type:"book",title:"Legumes Research - Volume 1",subtitle:null,fullTitle:"Legumes Research - Volume 1",slug:null,publishedDate:null,bookSignature:"Dr. Jose Carlos Jimenez-Lopez and Dr. Alfonso Clemente",coverURL:"https://cdn.intechopen.com/books/images_new/10749.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83969-491-2",printIsbn:"978-1-83969-490-5",pdfIsbn:"978-1-83969-492-9",isAvailableForWebshopOrdering:!0,editors:[{id:"33993",title:"Dr.",name:"Jose Carlos",middleName:null,surname:"Jimenez-Lopez",slug:"jose-carlos-jimenez-lopez",fullName:"Jose Carlos Jimenez-Lopez"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Plant endophytic microbiome",level:"1"},{id:"sec_2_2",title:"2.1 Colonization and distribution within the host plant",level:"2"},{id:"sec_3_2",title:"2.2 Endophytic bacterial diversity",level:"2"},{id:"sec_4_2",title:"2.3 Factors affecting diversity",level:"2"},{id:"sec_5_2",title:"2.4 How to study microbiome diversity",level:"2"},{id:"sec_7",title:"3. Benefits of endophytic microbiota to the host plant",level:"1"},{id:"sec_7_2",title:"3.1 Increase of nutrient availability",level:"2"},{id:"sec_7_3",title:"3.1.1 Biological nitrogen fixation (BNF)",level:"3"},{id:"sec_8_3",title:"3.1.2 Phosphate solubilization and mineralization",level:"3"},{id:"sec_9_3",title:"3.1.3 Iron uptake",level:"3"},{id:"sec_11_2",title:"3.2 Phytostimulators",level:"2"},{id:"sec_11_3",title:"3.2.1 Phytohormone-like molecule production",level:"3"},{id:"sec_12_3",title:"3.2.2 Volatile compounds and other phytostimulators",level:"3"},{id:"sec_14_2",title:"3.3 Protection against pathogens",level:"2"},{id:"sec_14_3",title:"3.3.1 Antibiosis",level:"3"},{id:"sec_15_3",title:"3.3.2 Lipopeptides",level:"3"},{id:"sec_16_3",title:"3.3.3 Lytic enzymes",level:"3"},{id:"sec_17_3",title:"3.3.4 Hydrogen cyanide",level:"3"},{id:"sec_18_3",title:"3.3.5 Siderophores",level:"3"},{id:"sec_19_3",title:"3.3.6 Quorum quenching",level:"3"},{id:"sec_20_3",title:"3.3.7 Insecticides",level:"3"},{id:"sec_21_3",title:"3.3.8 Induction of systemic response",level:"3"},{id:"sec_23_2",title:"3.4 Abiotic stress tolerance",level:"2"},{id:"sec_23_3",title:"3.4.1 Redox status regulation",level:"3"},{id:"sec_24_3",title:"3.4.2 Water use efficiency regulation",level:"3"},{id:"sec_25_3",title:"3.4.3 Hormone regulation",level:"3"},{id:"sec_28",title:"4. Synthetic communities of plant-associated bacteria to a more sustainable agriculture",level:"1"},{id:"sec_28_2",title:"4.1 How to study synthetic communities?",level:"2"},{id:"sec_29_2",title:"4.2 Can we manipulate the plant microbiome to improve the fitness or yield of legumes?",level:"2"},{id:"sec_30_2",title:"4.3 Are there collateral impacts of using synthetic communities in agriculture?",level:"2"},{id:"sec_32",title:"5. Final remarks and future directions",level:"1"},{id:"sec_33",title:"Acknowledgments",level:"1"},{id:"sec_37",title:"Conflict of interest",level:"1"},{id:"sec_33",title:"Author contributions",level:"1"}],chapterReferences:[{id:"B1",body:'Hallmann J, Quadt-Hallmann A, Mahaffee WF, Kloepper JW. Bacterial endophytes in agricultural crops. Canadian Journal of Microbiology. 1997;43:895-914'},{id:"B2",body:'Santoyo G, Moreno-Hagelsieb G, del Carmen Orozco-Mosqueda M, Glick BR. Plant growth-promoting bacterial endophytes. 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Chickpea genotypes shape the soil microbiome and affect the establishment of the subsequent durum wheat crop in the semiarid North American Great Plains. Soil Biology and Biochemistry. 2013;63:129-141'},{id:"B188",body:'Sturz AV, Christie BR, Matheson BG. Associations of bacterial endophyte populations from red clover and potato crops with potential for beneficial allelopathy. Canadian Journal of Microbiology. 1998;44:162-167'},{id:"B189",body:'Zhang J, Cook J, Nearing JT, Zhang J, Raudonis R, Glick BR, et al. Harnessing the plant microbiome to promote the growth of agricultural crops. Microbiological Research. 2021;245:126690'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Mariela I. Monteoliva",address:"monteoliva.mariela@inta.gob.ar",affiliation:'
Plant Physiology and Genetic Resources Institute—Agricultural Studies Unit (IFRGV—UDEA), National Institute of Agricultural Technology—National Council of Scientific and Technical Research (INTA—CONICET), Argentina
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These Ag-n/TiO2 NT/Ti composite layers appear to be useful as platforms for precise surface analytical investigations of minute amounts of numerous types of organic molecules: pyridine (Py), mercaptobenzoic acid (MBA), 5-(4-dimethylaminobenzylidene) rhodamine (DBRh) and rhodamine (R6G); such investigations are known as surface enhanced Raman Spectroscopy (SERS). Geometrical factors related to the nanotubes and the silver deposit affect the SERS activity of the resulting composite layers. The results presented here show that, for a carefully controlled amount of Ag-n deposit located mainly on the tops of titania nanotubes, it is possible to obtain high-quality, reproducible SERS spectra for probe molecules at an enhancement factor of 105–106. This achievement makes it possible to detect organic molecules at concentrations as low as, e.g., 10−9 M for R6G molecules. SEM investigations suggest that the size of the nanotubes, and both the lateral and perpendicular distribution of Ag-n (on the tube tops and walls), are responsible for the SERS activity. These features of the Ag-n/TiO2 NT/Ti composite layer provide a variety of cavities and slits which function as suitable resonators for the adsorbed molecules.",signatures:"Marcin Pisarek, Jan Krajczewski, Marcin Hołdyński, Tomasz\nPłociński, Mirosław Krawczyk, Andrzej Kudelski and Maria Janik-\nCzachor",authors:[{id:"147864",title:"Dr.",name:"Marcin",surname:"Pisarek",fullName:"Marcin Pisarek",slug:"marcin-pisarek",email:"mpisarek@ichf.edu.pl"},{id:"211433",title:"MSc.",name:"Jan",surname:"Krajczewski",fullName:"Jan Krajczewski",slug:"jan-krajczewski",email:"jkrajczewski@chem.uw.edu.pl"},{id:"211436",title:"Dr.",name:"Marcin",surname:"Holdynski",fullName:"Marcin Holdynski",slug:"marcin-holdynski",email:"mholdynski@ichf.edu.pl"},{id:"211437",title:"Dr.",name:"Tomasz",surname:"Plocinski",fullName:"Tomasz Plocinski",slug:"tomasz-plocinski",email:"tplocinski@inmat.pw.edu.pl"},{id:"211439",title:"Dr.",name:"Miroslaw",surname:"Krawczyk",fullName:"Miroslaw Krawczyk",slug:"miroslaw-krawczyk",email:"mkrawczyk@ichf.edu.pl"},{id:"211440",title:"Prof.",name:"Andrzej",surname:"Kudelski",fullName:"Andrzej Kudelski",slug:"andrzej-kudelski",email:"akudel@ichf.edu.pl"},{id:"211441",title:"Prof.",name:"Maria",surname:"Janik-Czachor",fullName:"Maria Janik-Czachor",slug:"maria-janik-czachor",email:"mczachor@ichf.edu.pl"}],book:{id:"6257",title:"Raman Spectroscopy",slug:"raman-spectroscopy",productType:{id:"1",title:"Edited Volume"}}}],collaborators:[{id:"30304",title:"Prof.",name:"Tito",surname:"Trindade",slug:"tito-trindade",fullName:"Tito Trindade",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"58810",title:"Dr.",name:"Guangqiang",surname:"Liu",slug:"guangqiang-liu",fullName:"Guangqiang Liu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"58811",title:"Prof.",name:"Weiping",surname:"Cai",slug:"weiping-cai",fullName:"Weiping Cai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"147864",title:"Dr.",name:"Marcin",surname:"Pisarek",slug:"marcin-pisarek",fullName:"Marcin Pisarek",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"211433",title:"MSc.",name:"Jan",surname:"Krajczewski",slug:"jan-krajczewski",fullName:"Jan Krajczewski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"212234",title:"Dr.",name:"Sara",surname:"Fateixa",slug:"sara-fateixa",fullName:"Sara Fateixa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"214513",title:"Prof.",name:"Izabela",surname:"Rzeznicka",slug:"izabela-rzeznicka",fullName:"Izabela Rzeznicka",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shibaura Institute of Technology",institutionURL:null,country:{name:"Japan"}}},{id:"215426",title:"Prof.",name:"Hideyuki",surname:"Horino",slug:"hideyuki-horino",fullName:"Hideyuki Horino",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"215580",title:"Dr.",name:"Qian",surname:"Zhao",slug:"qian-zhao",fullName:"Qian Zhao",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"226020",title:"Prof.",name:"Helena",surname:"Nogueira",slug:"helena-nogueira",fullName:"Helena Nogueira",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null}]},generic:{page:{slug:"advertising-policy",title:"Advertising Policy",intro:"
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Exoplanet characteristics and their comparison to Solar System planets are provided as well as general detection methods and planned probes to gather additional data.",book:{id:"10210",slug:"solar-system-planets-and-exoplanets",title:"Solar System Planets and Exoplanets",fullTitle:"Solar System Planets and Exoplanets"},signatures:"Joseph Bevelacqua",authors:[{id:"115462",title:"Dr.",name:"Joseph",middleName:"John",surname:"Bevelacqua",slug:"joseph-bevelacqua",fullName:"Joseph Bevelacqua"}]},{id:"65725",title:"On the Deviation of the Lunar Center of Mass to the East: Two Possible Mechanisms Based on Evolution of the Orbit and Rounding Off the Shape of the Moon",slug:"on-the-deviation-of-the-lunar-center-of-mass-to-the-east-two-possible-mechanisms-based-on-evolution-",totalDownloads:984,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"It is known that the Moon’s center of mass (COM) does not coincide with the geometric center of figure (COF) and the line “COF/COM” is not directed to the center of the Earth, but deviates from it to the South-East. Here, we discuss two mechanisms to explain the deviation of the lunar COM to the East from the mean direction to Earth. The first mechanism considers the secular evolution of the Moon’s orbit, using the effect of the preferred orientation of the satellite with synchronous rotation to the second (empty) orbital focus. It is established that only the scenario with an increase in the orbital eccentricity e leads to the required displacement of the lunar COM to the East. It is important that high-precision calculations confirm an increase e in our era. In order to fully explain the shift of the lunar COM to the East, a second mechanism was developed that takes into account the influence of tidal changes in the shape of the Moon at its gradual removal from the Earth. The second mechanism predicts that the elongation of the lunar figure in the early era was significant. As a result, it was found that the Moon could have been formed in the annular zone at a distance of 3–4 radii of the modern Earth.",book:{id:"8444",slug:"lunar-science",title:"Lunar Science",fullTitle:"Lunar Science"},signatures:"Boris P. Kondratyev",authors:[{id:"277909",title:"Prof.",name:"Boris",middleName:"Petrovich",surname:"Kondratyev",slug:"boris-kondratyev",fullName:"Boris Kondratyev"}]},{id:"68357",title:"Solar System Exploration Augmented by In Situ Resource Utilization: System Analyses, Vehicles, and Moon Bases for Saturn Exploration",slug:"solar-system-exploration-augmented-by-in-situ-resource-utilization-system-analyses-vehicles-and-moon",totalDownloads:824,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Human and robotic missions to Saturn are presented and analyzed with a range of propulsion options. Historical studies of space exploration, planetary spacecraft and astronomy, in situ resource utilization (ISRU), and industrialization all point to the vastness of natural resources in the solar system. Advanced propulsion is benefitted from these resources in many ways. While advanced propulsion systems were proposed in these historical studies, further investigation of nuclear options using high-power nuclear electric and nuclear pulse propulsion as well as advanced chemical propulsion can significantly enhance these scenarios. Updated analyses based on these historical visions are presented. At Saturn, nuclear pulse propulsion with alternate propellant feed systems and Saturn moon exploration with chemical propulsion and nuclear electric propulsion options are discussed. Issues with using in situ resource utilization on Saturn’s moons are discussed. At Saturn, the best locations for exploration and the use of the moons as central locations for Saturn moon exploration are assessed. Environmental issues on Titan’s surface may present extreme challenges for some ISRU processes. In-space bases for moon-orbiting propellant processing and ground-based processing will be assessed.",book:{id:"7338",slug:"planetology-future-explorations",title:"Planetology",fullTitle:"Planetology - Future Explorations"},signatures:"Bryan Palaszewski",authors:[{id:"279275",title:"M.Sc.",name:"Bryan",middleName:null,surname:"Palaszewski",slug:"bryan-palaszewski",fullName:"Bryan Palaszewski"}]},{id:"65534",title:"Solar System Exploration Augmented by In Situ Resource Utilization: Lunar Base Issues",slug:"solar-system-exploration-augmented-by-in-situ-resource-utilization-lunar-base-issues",totalDownloads:1108,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Creating a presence and an industrial capability on the Moon is essential for the development of humankind. There are many historical study results that have identified and quantified the lunar resources and analyzed the methods of obtaining and employing those resources. The idea of finding, obtaining, and using these materials is called in situ resource utilization (ISRU). The ISRU research and development efforts have led to new ideas in rocket propulsion. 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Additionally, we overview some of the novel materials with outstanding properties, such as low weight, increased radiation resistance, and self-healing capabilities with a potential to reduce mission costs and improve prospects for extended human exploration of extraterrestrial bodies.",book:{id:"10955",title:"Lunar Science - Habitat and Humans",coverURL:"https://cdn.intechopen.com/books/images_new/10955.jpg"},signatures:"Natalia E. Koval, Bin Gu, Daniel Muñoz-Santiburcio and Fabiana Da Pieve"},{id:"80241",title:"The Evolution of the Moon’s Orbit Over 100 Million Years and Prospects for the Research in the Moon",slug:"the-evolution-of-the-moon-s-orbit-over-100-million-years-and-prospects-for-the-research-in-the-moon",totalDownloads:57,totalDimensionsCites:0,doi:"10.5772/intechopen.102392",abstract:"As a result of solving the problem of interaction of Solar-system bodies, data on the evolution of the Moon’s orbit were obtained. These data were used as the basis for the development of a mathematical model for the Moon representing its motion over an interval of 100 million years. A program of exploration of the Moon with the aim of creating a permanent base on it is outlined. Such a base is intended for exploring the Earth, the Sun, and outer space.",book:{id:"10955",title:"Lunar Science - Habitat and Humans",coverURL:"https://cdn.intechopen.com/books/images_new/10955.jpg"},signatures:"Joseph J. Smulsky"},{id:"80217",title:"Educational and Scientific Analog Space Missions",slug:"educational-and-scientific-analog-space-missions",totalDownloads:78,totalDimensionsCites:0,doi:"10.5772/intechopen.101392",abstract:"Analog space missions in Poland include international scientific, technological, and business projects designed and realized by a private research company Analog Astronaut Training Center Ltd. (AATC) devoted to the future Moon and Mars exploration. Growing experience in educational aspect of the training as well as continuous development of the habitat and its professional space science laboratory equipment correspond to increased interest of educational organizations, universities, and individual students. We serve unique practical platform for space engineering, space master, and even space doctoral theses. In addition to a wide range of training courses offered for future astronauts, for example, diving, skydiving, rocket workshops, and stratospheric missions, AATC provides a private laboratory to simulate the space environment. It carries out scientific experiments focused on biology and space medicine, as well as addressing several multidisciplinary issues related to the Moon and Mars exploration, including space mining. The main goal of each our analog simulation is to get publishable results, what means that our analog astronauts obtain not only certification of completion of the training but also ability to continue studies and to perform it individually. This chapter summarizes methodology used by us, didactic tools, and obtained results for both educational and scientific analog simulations.",book:{id:"10955",title:"Lunar Science - Habitat and Humans",coverURL:"https://cdn.intechopen.com/books/images_new/10955.jpg"},signatures:"Agata Maria Kołodziejczyk and M. Harasymczuk"},{id:"79544",title:"Regolith and Radiation: The Cosmic Battle",slug:"regolith-and-radiation-the-cosmic-battle",totalDownloads:113,totalDimensionsCites:0,doi:"10.5772/intechopen.101437",abstract:"This chapter discusses regolith utilization in habitat construction mainly from the point of view of radiation protection of humans on missions of long duration. It also considers other key properties such as structural robustness, thermal insulation, and micrometeoroid protection that all have to be considered in parallel when proposing regolith-based solutions. The biological hazards of radiation exposure on the Moon are presented and put in the context of lunar exploration-type missions and current astronaut career dose limits. These factors guide the research in radiation protection done with lunar regolith simulants, which are used in research and development activities on Earth due to the reduced accessibility of returned lunar samples. The ways in which regolith can be used in construction influence its protective properties. Areal density, which plays a key role in the radiation shielding capacity of a given material, can be optimized through different regolith processing techniques. At the same time, density will also affect other important properties of the construction, e.g. thermal insulation. A comprehensive picture of regolith utilization in habitat walls is drawn for the reader to understand the main aspects that are considered in habitat design and construction while maintaining the main focus on radiation protection.",book:{id:"10955",title:"Lunar Science - Habitat and Humans",coverURL:"https://cdn.intechopen.com/books/images_new/10955.jpg"},signatures:"Yulia Akisheva, Yves Gourinat, Nicolas Foray and Aidan Cowley"}],onlineFirstChaptersTotal:5},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"24",title:"Sustainable Development",doi:"10.5772/intechopen.100361",issn:null,scope:"
\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
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\r\n\t
\r\n
\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"June 28th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. In 2017, Usha was awarded the Marquis Who’s Who Lifetime Achiever Award.",institutionString:null,institution:{name:"RMIT University",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:11,paginationItems:[{id:"91",title:"Sustainable Economy and Fair Society",coverUrl:"https://cdn.intechopen.com/series_topics/covers/91.jpg",editor:{id:"181603",title:"Dr.",name:"Antonella",middleName:null,surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo",profilePictureURL:"https://mts.intechopen.com/storage/users/181603/images/system/181603.jpg",biography:"Antonella Petrillo is a Professor at the Department of Engineering of the University of Naples “Parthenope”, Italy. She received her Ph.D. in Mechanical Engineering from the University of Cassino. Her research interests include multi-criteria decision analysis, industrial plant, logistics, manufacturing and safety. She serves as an Associate Editor for the International Journal of the Analytic Hierarchy Process. She is a member of AHP Academy and a member of several editorial boards. 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Her focus is on quality, innovation, leadership, and personalised learning. She works primarily at the strategic and policy levels, both nationally and internationally, and with key international organisations. She is committed to promoting and improving OFDL in the context of SDG4 and the future of education. Ossiannilsson has more than 20 years of experience in her current field, but more than 40 years in the education sector. She works as a reviewer and expert for the European Commission and collaborates with the Joint Research Centre for Quality in Open Education. Ossiannilsson also collaborates with ITCILO and ICoBC (International Council on Badges and Credentials). She is a member of the ICDE Board of Directors and has previously served on the boards of EDEN and EUCEN. Ossiannilsson is a quality expert and reviewer for ICDE, EDEN and the EADTU. She chairs the ICDE OER Advocacy Committee and is a member of the ICDE Quality Network. 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\r\n\tThe demographic shifts are creating interesting challenges. People are living longer, resulting to an aging demographic. We have a large population of older workers and retirees who are living longer lives, combined with a declining birthrate in most parts of the world. Businesses of all types are looking at how technology is affecting their operations. Several questions arise, such as: How is technology changing what we do? How is it transforming us internally, how is it influencing our clients and our business strategy? It is about leveraging technology to improve efficiency, connect with customers more effectively, and drive innovation. The majority of innovative companies are technology-driven businesses. Realizing digital transformation is today’s top issue and will remain so for the next five years. Improving organizational agility, expanding portfolios of products and services, creating, and maintaining a culture of innovation, and developing next -generation leaders were also identified as top challenges in terms of both current and future issues.
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\r\n\tThe most sustained profitable growth occurs when a company expands its core business into an adjacent space. This has significant implications for management because innovation in business ecosystems differs from traditional, vertically integrated firms. Every organization in the ecosystem must be aware of the bigger picture. Innovation in ecosystems necessitates collaborative action to invent and appraise, efficient, cross-organizational knowledge flows, modular architectures, and good stewardship of legacy systems. It is built on multiple, interconnected platforms. Environmental factors have already had a significant impact in the West and will continue to have an impact globally. Businesses must take into account the environmental impact of their daily operations. The advantage of this market is that it is expected to grow more rapidly than the overall economy. Another significant challenge is preparing the next generation of leaders to elevate this to the number one priority within the next five years. There can be no culture of innovation unless there is diverse leadership or development of the next generation of leaders; and these diverse, next-generation leaders are the ones who will truly understand the digital strategies that will drive digital transformation.
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