Research Article
Volume 1 Issue 1 - 2014
Technomic Analysis of Biodiesel Production from Jatropha curcas: Shrub Cultivability, Consecutive-Competitive Reactions, Centrifugal Separation and Optimization
K R Sharma1,2*
1Department of Natural Sciences, San Jacinto College District North Campus, USA
2Department of Physics, Texas Southern University, USA
*Corresponding Author: K R Sharma, Department of Natural Sciences, San Jacinto College District North Campus, Houston, Texas; Department of Physics, Texas Southern University, Houston, Texas, USA.
Received: December 20, 2014; Published: December 31, 2014
Citation: K R Sharma. “Technomic Analysis of Biodiesel Production from Jatropha curcas: Shrub Cultivability, Consecutive-Competitive Reactions, Centrifugal Separation and Optimization”. EC Agriculture 1.1 (2014): 29-50.
Abstract
Advances in sequencing of genomes have leaded to the promise of genetically modified fuel crop such Jatropha curcas that is used to obtain Jatropha oil. The gene regulation via Ribosome inhibiting Protein in the shrub has been studied using transfection of clones of curcin genes found in Jatropha curcas in other plants. This can lead to better cultivability of the Shrub and higher yield of Jatropha oil. NGS, Next-Generation Sequencing machines available commercially are tabulated. The triglycerides in Jatropha oil can be transesterified using excess methanol in the presence of catalyst or excess methanol into biodiesel and glycerol. The glycerol can be sold as by-product. The kinetics of consecutive-competitive reactions during methanolysis of triglycerides with intermediates such as diglyceride, monoglyceride are modeled. The model solutions assuming irreversible simple first order kinetics were obtained using the method of Laplace transforms. Although biodiesel forms in each consecutive step under some conditions of reaction rate ratios ω and κ the yield of glycerol are seen to be higher than that of biodiesel. This can be called “cross-over” and can be seen in the illustrations shown as prototypical examples. The operating cost of separating biodiesel from glycerol using centrifuge can be obtained from computer simulations of layer formation during shear flow. For optimal total cost there exists a yield of biodiesel where the process can be operated at.
Keywords: Jatropha curcas; Biodiesel; Gentically modified crop; Gene regulation; Consecutive-competitive reactions; Centrifugal separation; Transesterification; Catalysis; Optimization; Oil well depletion; Energy sustainability
Abbreviations: FFA: The Free fatty acid; EPA: Environmental Protection Agency; FAME: Fatty Acid Methyl Ester
Introduction
At a consumption rate of 84.6 million barrels per day the 237 trillion liters of crude oil [1] reserves of the world can be expected to be depleted in another 74.5 years. The genominomics of Homo sapiens and other species is seeing a cost reduction steeper [2] than the Moore’s law for microprocessors according to the goal of NHGRI, National Human Genome Research Institute the cost per genome for humans is expected to decrease to less than $ 1000 by 2014 [3]. The cost of complete sequencing the genome of J. curcas in order to look for valuable mutations is down to $ 50 in 2014. According to agricultural biotechnology company, SGB, the cost of sequencing J. curcas five years ago was about $ 150,000. SGB spent $ 250,000 to create a master J. curcas genome. With advances in transfection and genetic modifications it is fully expected that genetically modified J. curcas will be used as a cash crop in order to provide feedstock for the burgeoning biodiesel industry. Jatropha oil is non-edible [4]. Being non-edible use of Jatropha oil as feedstock for biodiesel production is not a fuel for food swap. This will increase public confidence in fuel use. Jatropha comes from the Greek words ‘jatros’ that means doctor and ‘trophé’ that means nourishment.
The genetically modified crop portion of the biotechnology industry is about $ 173.2 billion dollars in 2011. This includes the seeds, maize, soybean grain and cotton markets. The market share of Monsanto in seeds is the largest in the industry. SBG is growing hybrid strains of the shrub that can be used in order to produce biodiesel and by-product glycerol in quantities that are comparable to petroleum when priced at $ 99 a barrel. This stain is called J2. SBG plans to grow the crop in 250,000 acres of J. curcas in Brazil, India and other countries worldwide. Dehgan [5] had studied the morphology of J. curcas 30 years ago. India consumes more diesel than gasoline every year, i.e., about 320 million barrels of diesel every year compared with 94 million barrels of gasoline every year. This is in part because of the Indian Railways caters people travelling year around. Mass production of biodiesel is round the corner. Fairless [6] discuss the million J. curcas seedlings planted on railway wastelands. J. curcas is a member of the Euphorbia family that first was discovered in Central America, it has been used as lamp oil and soap. Out of the 756 million acres of land discussed in the report [6] by Ministry of Rural Development of Government of India, 56.5% of the land is already under cultivation and the rest is non-arable wasteland. This wasteland is used for cultivation of J. curcas Shrub. The first commercial application of the J. curcas shrub was reported in Lisbon. It was used as lamp oil and for production of soap. It thrives in tropical and sub-tropical regions of the world such as Africa and Asia. Portuguese ships were used in order to import Jatropha oil [7]. J. curcas is a large shrub and can survive for 50 years. It can attain a height of 9.44 m as discussed in the review of biodiesel production from J. curcas by Addulla et al. [8] and others [9-11], it can grow with less water in semi-arid conditions and it can grow on soils with less nutrient contents. Leaves are even toxic and non-edible. Benefits of J. curcas plant parts, use of wastelands, treatment needed prior to animal feed use, medicinal applications are discussed elsewhere [8]. Jatropha oil contains about 25% protein, 47% fat and 5.5% moisture. It contains polyunsaturated linolenic acid and unsaturated linoleic acid in larger proportions. Seeds in Africa [12] were found to have 80% of linoleic acid and the seeds in India were found to have 81.9% linoleic acid (C18H32O2). Jatropha oil is extracted from the seeds using mechanical expelling of enzymatic methods [9]. The Free fatty acid (FFA) content of Jatropha oil is 14% which is higher than the 1% FFA content limit for use of base catalysts for conversion into biodiesel. This results in the formation of Soap.
Methods
Biodiesel production forecast
Biodiesel is a, Environmental Protection Agency (EPA) designated advanced biofuel. It is a mixture of fatty acid methyl ester (FAME). It is increasingly used as an alternate energy fuel source of choice. The world food production is high enough for a food and fuel portfolios in some advanced nations in the world. The feedstock for biodiesel production can be Sunflower oil, Jatropha oil, Coconut Oil, Coconut Biomass, Waste Vegetable Oil, Soybean Oil and Fats from animal husbandry. Catalytic transesterification of triglycerides into diglyceride and then into monoglyceride and then into glycerol and FAME takes place in a set of consecutive-competitive reactions. The catalyst can be alkali, acid or enzyme. It depends on the FFA, free fatty acid content in the feedstock.
Over the past decade the world production of biodiesel has gone up from 15,200 barrels per day in the year 2000 to 300,000 barrels per day in 2010. In terms of volume this is about 5 billion gallons in 2010. In the past two years, biodiesel production has exceeded targets. Production plants are present in nearly every state. 1000s of jobs are created. The sigmoidal growth of the biodiesel volume is seen from 2006. Biodiesel is designated by ASTM D6751 [13]. New laws and mandates on biodiesel came about in Brazil, China, United States and Argentina. Germany and Brazil are the world's leading biodiesel producers. Federal excise tax credits are provided for producers and distributors of agri-biodiesel at $ 1 for every gallon of biodiesel they blend with regular diesel.
Forecasts of global dynamics of biodiesel production [14] are available for 2015-2020 by feedstock used such as vegetable oil feedstocks, Jatropha oil , algae biodiesel and cellulose. The expected growth rate of biodiesel production in the world is about 6% between 2009-2018 according to Organization for Economic Cooperation and Development (OECD). By 2017 biodiesel production is expected at 25 billion liters. European biodiesel board estimated that the production of biodiesel in EU is about 9.6 million tons in 2010. By the year 2022, biofuel production is projected to consume a significant amount of total world production of sugar cane (28%), vegetable oils (15%) and coarse grains (12%).
In India, the former President of India, ABJ Abdul Kalam during his address to the nation on National Science Day, February 28th 2006 called for an increase in output of biodiesel from J. curcas crop from current levels of 2 tons per hectare to 4-6 tons per hectare [15]. The oil content of most Jatropha varieties ranges from 25-35%. Research in selection, intra-specific, inter-specific hybridization and mutation breeding is needed to develop varieties with more than 45% oil content so that a recovery of 35% under mechanical expelling. India has 60 million hectares of wasteland of which 30 million hectares are available for energy crops such as Jatropha. Cars that can run on biodiesel need be developed and encouraged. The Indian Railways runs passenger trains with diesel engine with 5% blend of biodiesel. 15 million J. curcas saplings are planted in Railways' land.
President B. Obama as a senator endorsed the budding biodiesel industry at a new biodiesel plant in Cairo, IL in 2006 [16]. The Renewable Energy group announced that it would build a 60 million gallon per year refinery and had raised $100 million in financing. Bunge Ltd., a major food processor and other venture capital firms were the contributors. About 76 biodiesel plants were in production in 2006, up from 22 in 2004. A biodiesel plant on an average costs up to $ 20 million to build and yields 30 million gallons per year of fuel. Biodiesel serves an important need of meeting the energy security of United States and the developing countries in the world.
Oil reserves are expected to be depleted by the year 2071 at the current levels of production. The crude oil reserves are estimated at 4.16 trillion liters worldwide [17]. Global consumption is 84.6 million barrels/day. Earth’s entire oil reserves, according to one estimates is 1.2 trillion barrels without oil sands and 3.74 trillion barrels with oil sands. At the present rate of consumption the oil reserves will be depleted in the next 38.8-122.2 years. Search is on for alternative oil finds. Per geological survey 3-4.5 billion barrels was found in Montana and North Dakota. If oil shale can be used as source of oil the reserves can last for 110 more years. Oil finds have been found in Russia, Columbia and Africa. According to the big rollover theory global oil production is already past its peak production [18]. M. K. Hubbert, Shell Oil Co., Houston, TX, studied the exhaustion of oil fields. Initial oil find, exploitation and exhaustion phases were identified. This followed the bell curve. He concluded that United States would peak in its oil production in 1970. The curve is called the Hubbert curve. The peak is also called the rollover. Lot of world oil experts feel that we are past the peak production. Every year, since 1970 we have found less oil and pumped less oil. Air pollution has been found as a result of continued and increased use of petroleum. Global warming has been concluded as a problem because of significant increase in concentration of CO2 in the earth’s atmosphere [19]. The principles of Sustainable Engineering were developed at the Sandestin Conference of 2003 [20]. This ought to set the direction of engineers who work on developing sustainable alternatives to current engineering practices. Energy is considered a primary component of sustainable engineering. Biodiesel is nontoxic. It has low emission profiles and is environmentally benign [21]. A century ago R. Diesel successfully used vegetable oil as fuel for his engine. Prior to WW II vegetable oils were blended with diesel fuels time and again.
Centrifugal separation is used to separate the glycerine and biodiesel layers by gravity differences. More degree of separation can be achieved by increased torque of the rotor [22]. A trade-off is seen between utility cost for rotor speed and purity level. Optimal operation of rotor can be derived at for maximum revenue.
At end of the second stage [23] with 99.2-99.6% conversion the mixture is passed through a vacuum distillation tower in order to separate the unreacted methanol, recover the sodium methylate catalyst and recycle the unreacted oil. B &P Process patented a process [24] to make biodiesel with less equipment, more yield and at a higher purity. They use a higher temperature than the boiling point of methanol and increased pressure of the reactor in order to keep the methanol from boiling. The centrifugal separator was made with perforated concentric cylinders. The separation process was effected in a counter-current manner. This makes the throughput higher and use less floor space. The glycerine passes through the rims and the biodiesel separates out through the axial region of the separator. The reaction is between the triglycerides present in the oil and methanol.
There are different methods to make biodiesel. One is by Transesterification using catalyst, enzyme or catalyst free and others are by Pyrolysis, Physical blending and Emulsion processes. The catalyst used can be alkali, acid or enzyme. When the FFA is greater than 1% the acid catalyst would be better [25]. Alkaline catalyst is used in commercial plants. Alkaline catalysts are preferred when the FFA in the feedstock is less than 0.5 wt %. Process is sensitive to water and FFA. Saponification of ester may occur in presence of water. Pyrolysis methods have been found to result in more biogasoline compared with biodiesel [26,27].
Next-generation sequencing
Some of the NGS machines available for purchase or approved are shown in Table 1 [3]. The size of the device ranges from a small hand held device to bread-loaf size to desktop to bench top to a set of 10 consoles that can fill a room. The cost per genome or per read length can be calculated. The capital cost of the equipment can be amortized and added to the reagents cost, labour, supplies and overhead costs. Different concepts are used during the measurement of the sequence distribution. The electrical current change due to the polarity of the base pairs as DNA is passed through nanopore is one concept used. Another concept uses the change in electrical current as ions are released when the DNA reacts. The capital equipment cost can run to the order of multi million dollars. It can also be in the $ 1000 range depending on the read expectations. Sequencing by synthesis methods is used usually. Although a surrogate Xpandomer is formed by encoding the ssDNA and as the Xpandomer passes through the nanopore it gets read. Run time is on the decrease across the board. Sample input sizes are to the tune of a few nanograms. Shot gun sequencing is used. Accuracy is improved. he variety of eukaryotes and prokaryotes that can be sequences are several ranging from bacteria to mammals. Some methods use lasers and optical devices and others use non-optical methods. The sequence information can be used in different applications. Disease specific cartridges are developed by one vendor. It can be used for personalized medicine or developing drugs for spreading pandemics such as the recent Ebola virus scare. Electronic circuitry is synergized with biochip in some cases. Nano trenches allow for efficient diffusion for probe target hybridization using fluorescent tags.
Name of Company Device Name Size of the Device Features of the Device Cost
Illumina, San Diego, CA HiSeq X Ten System 10 Consoles of Ultra-high Throughput Sequencers Can sequence 18,000 human genomes per year; can generate 1.8 trillion base pair data; run time less than 3 days $ 10 million
  NextSeq 500 Benchtop 3 billion base pairs can be sequenced in a day Per genome price less than $ 1000
$ 250,000
hotlink www.illumina.com
Thermo Fisher Scientific Sanger Sequencer   Read lengths of several hundred base pairs. $ 50-$250
  ClaSeek and MuSeek Kits   5ng – 1 µg sample input for ClaSeek kit and 100 ng of gDNA, cDNA for MuSeek kits. 120min amplification time for ClaSeek and 80min total time for MuSeek Kits. Build DNA library $ 1,120
  IonPGMTM Hi-QTM Sequencing Kit   200-400 base pair sequencing. Measures ions released as DNA reacts  
hotlink www.thermofisher.com
Roche GS Junior and GS FLX System desktop (55 lb weight) Read length of 1000 base pairs, high accuracy and high throughput; Shot gun reads. Size of genome spectrum from bacteria to mammals; Compare sequence reads for SNPs; pyrosequencing Goal- Ultra low cost
  Stratos Genomics’ SBX Method   Single Molecule Detection. Single drop biochemical reaction to encode the sequence of DNA into a surrogate called Xpandomer. Xpandomer passed through nanopore and base pairs are read.  
hotlink www.roche.com
Pacific Biosciences RS II System 300 lbbenchtop Uses lasers to sequence DNA; Average Read length is ~ 8500 base pairs; Single Molecule real time sequencing; DNA reactions are tracked in real time across 150,000 nanotrenches. Flourescent tags. Published a human reference genome. $ 700,000
hotlink www.pacificbiosciences.com
Oxford Nanopore MinIon Handheld, disposable A linear ssDNA is passed through a nanopore and the change in electrical current is used to deduce the base pairs. $ 900
hotlink www.nanoporetech.com
QuantuMDx, New Castle, United Kingdom Q-POCTM Handheld, Chip Based 15 minute bedside diagnoses; Disease Specific Catridges; Nanowire Biosensors (under development); Infectious Diseases; Tumor Profiling $ 5 - $ 20
hotlink www.quantumdx.com
GenapSys
Redwood City, CA
GENIUS – Gene Electronic Nano-Integrated Ultra-Sensitive Technology Bread-Loaf Sized Measures electric signal from DNA as it is copied. Code deduced from electrical signal Costs a few thousand dollars; $ 50 genome and point-of-care diagnostic use
hotlink http://genapsys.com
Table 1: Next generation sequencers commercially available.
Genetic modification and cultivability
DNA fragments are isolated, inserted into what are called vector molecules and introduced into bacteria or yeast cells whey are allowed to replicate. High throughput DNA sequence analysis has resulted in completion of several genomes of eukaryotes and prokaryotes.
Comparisons of sequences from among different organisms result in the realization of certain coding sequences and their functional metabolic products. DNA Microarrays are used to study metabolomics. Here global patterns and coordinated regulation of gene expression are investigated. Protein -protein interactions can be detected using two-hybrid analysis. Transgenic, cisgenic and subgenic are different methods of gene transfer. Transgenic method of gene transfer is when genes from other species are inserted into the plant. Cisgenic transfer is when the genes are transferred to the plant from the same species or closely related species. Subgenic transfer is gene modification by using gene editing tools such as CRISPR and TALENS.
The genetically modified crop portion of the biotechnology industry is about $ 173.2 billion dollars in 2011. This includes the seeds, maize, soybean grain and cotton markets. The market share of Monsanto in seeds is the largest in the industry.
Qin et al. [28] investigated the regulation expression of β-glucuronidase, GUS reporter gene in Nicotiana tabacum by curcin promoter. This was prepared from J. curcas L endosperm by cloning. A 0.6 kb fragment of a 5′ flanking region adjacent to the curcin gene of J. curcas endosperm was cloned. This fragment encodes a Type I, Ribosome-inactivating protein, RIP. The fragment of the curcin gene was used in order to drive the gene expression of GUS reporter gene found in Nicotiana tabacum . The promoter was found to be active in the endosperm tissue of dicotyledonous tobacco embryo. The activity was initiated at the embryonic stage during seed development.
Often times, in the field of plant genetic engineering the expression levels of target gene in certain tissues of the modified plant is specified. Promoter studies are used in design of bioreactors in order to manufacture proteins. Identification of molecular elements that can be used in order to control expression of external genes inside plants and promoter activity study are salient considerations. RIPS may be used to inactive ribosomes and serve as inhibitor of protein production. Curcin gene expression patterns can be used in scale-up of therapeutic drugs. Curcin genes have been cloned from seeds of J. curcas. Qin et al. [28] collected J. curcas seeds and germinated them in plastic pots containing nutrient soils. They were grown in the conservatory greenhouse for two months. Nicotiana tabacum plants were grown at 25°C under a 16 hour-8 hours of light and dark photoperiod regimes. For purposes of plant transformation Escherichia coli and Agrobacterium tumefaciens stains were also used.
The 5′ flanking sequence with Genbank accession #AF469003 was amplified using two primers. The forwordprimerP1F had the sequence 5′CCAAAGCTT-AATATTGGAATAGAAGACTTTG3′and the reverse primer P2R had the sequence 5′-CCAGGATCC-CAAATATCATTATACGAATACG3′. A HindIII site (AAGCTT) was added to the forward primer at the 5′ end and a BamHI site (GGATCC) was added to the reverse primer as shown in bold face. The amplified sequences were cloned into pMD18-T vector (TaKaRa) on both strands. The Curcin promoter was cut from pMD18-T vector with HindIII and Bam HI fragments. The recombinant plasmid pBI121-CPI formation is shown in Figure 1. The CaMV 35s promoter was replaced with the cloned HindIII-BamHI fragments. The plant expression vectors were transferred into cells of Agrobacterium tumefaciens by freeze-thaw treatment. The gDNA was extracted from tissues in the leaf. PCR analysis was carried out. The gDNA from Nicotiana tabacum was digested with HindIII and separated using agarose gel electrophoresis and transferred onto nylon membrane.GUS gene fragment was amplified using PCR from pPI121 using primers. DIG High Prime DNA Labelling and Detection Starter Kit II from Roche, Germany was used for hybridization and immunological detection. Fluorogenic reaction was carried out in 2 mM 4-methylumbelliferyl-n-L-glucuronide, MUG extraction buffer. Fluorescence was measured using spectrofluorometer with excitation beam at 365 nm and emission beam at 455 nm wavelengths. Different lengths of CPI were fused to the GUS reporter gene and transferred to tobacco plants. CPI promoter sequence was found to regulate expression of GUS gene in the endosperm seeds of Nicotiana tabacum . Regulatory motifs contained in the endosperm that might have played a role in GUS gene expression a search of the PLACE database was conducted. -377 to -179 bp in the genome was found to be the endosperm responsive region. It contained four AAAG, one GT-1 binding site one E box and one W boc TTGAC motifs. AAAG sequence has been found by prior investigators for gene expression in maize that is endosperm specific. These bind to the Dof protein. Dof proteins are DNA binding proteins that are found in plants and can increase transcription. One Dof protein isolated from maize, PBF is bound to Prolamin box. WRKYs are involved in the regulation of the development of seed and trichomes and defense against pathogen infection.
Figure 1: Recombinant Plasmid Formation [28] – CPI Replaces CaMV 35s Promoter in Plasmid pBI121.
Zhang et al. [29] applied next-generation Illumina Next-Generation Sequencing technology in order to study global gene expression patterns in leaves and roots and leaves of J. curcas, 2 hours, 2 days and 7 days after the onset of salt stress. They found that 1504 genes were up regulated, 1115 genes were down-regulated in leaves and roots under salt stress condition. Gene ontology studies reveal that number of metabolic processes that occur in the plant are affected by salt stress. The genes were found to regulate ABA and ethylene signaling, osmotic regulation, the reactive oxygen species scavenging system and the cell structure in the leaves and roots. Salt stress was found to interfere with plant growth and production. The molecular mechanisms for the salt response in leaves and roots were attempted to be studied. The morphological adaptations of plant in response to abiotic stress may be linked to gene expression. Productivity of crops are hampered by salinity of the soil. Ionic and osmotic stresses emanate from saline environment. Transcriptome studies on plants exposed to salt stress have been undertaken for maize, cotton, flowering plants. J. curcas is a perennial shrub and belongs to the species of Euphorbiaceae. It has high potential for biodiesel production. It is oil rich, drought-tolerant shrub. It is yet to be domesticated. Large scale plantation of J. curcas would need conversion of this species into a genuine crop. Next-generation sequencing studies of J. curcas may lead to attainment of these goals.
It is a diploid with a haploid genome size estimated at 416 Mbp. Sato et al. [30] completed the sequencing of whole genome of J. curcas. They used a combination of Sanger method and Next-Generation Sequencing method. They found 285,858,490 bp. The non-redundant sequences comprised of 120,586 contigs and 29,831 singlets. They accounted for 95% of the gene-containing regions with the average Guanine + Cytosine contents of about 34.3%. 40,929 complete and partial structures of protein encoding genes have been inferred. Sequence comparison studies reveal that 4% or 1529 putative protein-encoding genes are specific to the Euphorbiaceae species. More microsynteny was found between J. curcas and genome of castor bean and less microsynteny was found with soybean and Arabidopsis thaliana. Pyrosequencing was used to characterize cDNAs extracted from tissues of the shrub. 21,225 Unigene data was obtained [31]. Genetic diversity was characterized by polymorphism analysis using microsatellite markers. Biofuel production is expected to increase from the understanding achieved from these studies. Breeding of the fuel crop was accelerated by genomic selection.
Silva-Junior [32] found a set of SNPs for J. curcas using Illumina sequencing. Two Illumina GAIIx single end lanes were sequenced by using standard protocols. Raw reads were processed and aligned on mapped reference genome. Allele frequency was estimated by using Genotyper. A Bayesian genotype likelihood model was used in order to provide a posterior probability of occurrence of segregating variant allele at each locus. Illumina Golden Gate Genotyping Technology assays were designed using SNPs and in silico estimated minor allele frequency greater than 0.1. At least 60 bases were available on each SNP flank with no additional SNPs following. They report a unigene length of 39.7 Mbp and ~56% of the transcribed portion of the genome. They sampled 28,110 unigenes.
There was low seed yield found with J. curcas L as result of unreliable flowering. Flowering Locus T FT like genes are important flowering regulators in higher plants such as in Arabidopsis thaliana [3]. In order to better understand the genetic control of flowering in J. curcas an FT homolog, JcFT was isolated and characterized by Li et al. [33]. They found sequence analysis and phylogenetic relationship with the FT genes of Litchi chinensis, Populus nigra and other perennial plants. JcFT may encode a florigen that may act as a key regulator in flowering pathway.
There are three critical areas in the continuous process for manufacture of biodiesel:
  1. Feedstock Preparation
  2. Consecutive-Competitive Reactions
  3. Separation of Biodiesel and Glycerol
The total cost of the process may be optimized with respect to capital cost and operating cost. The AW, annual worth [34] analysis of a biodiesel manufacturing plant for different feedstocks in Taiwan was discussed [35]. With by-product sales credit for glycerol the process may be profitable depending on the raw material cost and market price of gasoline. The cost of raw materials is a critical factor in the profitability of biodiesel production. Twelve reports were reviewed [36,37] on economic feasibility of biodiesel production using different feed stocks and scales of operation. Significant factors that contribute to the bottom line of the biodiesel production were identified [38-40]. These include the cost of raw materials, plant size, credit received for glycerine as by-product sales. When waste cooking oil was used the material costs went down. Restaurant greases cost less than food-grade canola and soybean oils. The first factory that produced biodiesel at 300 tons per year from waste cooking oil was started in Chiayi county of Taiwan in October of 2004.
The total cost of production can be written as follows:
    (1)
The capital costs can increase with increase in reactor size needed to perform the reactions. The reactor size will be larger for larger reaction times or higher conversion targets. However the separation costs of separating biodiesel from glycerol, FAME mixture will be lesser at higher conversion from the reactors. When the conversion is lower the capital cost will decrease on account of the reactor size and the separation costs will increase on account of the load on the rotor of the centrifuge used. The variation of reactor size with conversion for a CSTR can be seen to be exponential for a given throughput. The variation of utility cost for a given throughput with conversion of Jatropha oil in the reactors can be expected to be non-linear and can be obtained from computer simulations. Eq. (1) can be expressed in terms of conversion of Jatropha oil. The resulting equation can be differentiated with respect to conversion and equated to zero and the extremam as can be obtained. The conversion corresponding to a minimum can be obtained by confirming that the second derivative of the objective function is negative at the extremam. This gives impetus to study the kinetics of the consecutive-competitive reactions in the reactors and the velocity profiles in the centrifuge during separation of the product and by-product.
Consecutive-Competitive reactions
It can be seen from the economic analysis the yield of biodiesel compared with other by-products such as glycerol can be a critical design criteria in making these plants more profitable. The reaction sequence for formation of FAME, fatty acid methyl ester from triglycerides found in palm oil and other feedstock involve the formation of diglycerides, monoglycerides and glycerol in sequence with FAME produced in each intermediate step [41]. The reaction scheme can be represented as shown in Figure 2 and the flow diagram for the biodiesel, glycerol factory from J. curcas cash crop is shown in Figure 3. The reactions are catalyzed. The catalyst type depends on the FFA content in the feedstock. The triglycerides species is represented with symbol A, diglycerides with R, monoglycerides with S and glycerol with T. The product FAME formed in each step is given by P and the methanol used is given as B.
Figure 2: Transeterification catalyzed reactions from triglycerides to glycerol and FAME.

Figure 3: Flow diagram for continuous production of biodiesel and gluycerol from J. curcas shrub fuel crop in semi-arid farms.
Om Tapanes et al. [42] studied the reaction pathways and reaction sequences during base catalyzed transesterification of triglycerides of fatty acids including linoleic acid and determined the most probable pathway and the rate determining step of the reactions using molecular orbital calculations. The scheme in Figure 2 may be applicable for the biodiesel production from Jatropha oil. The reactions in the reactor during biodiesel production may be modeled as scheme of multiple reactions of the consecutive-competitive/series-parallel type [43]. The methanol can be assumed to be in excess. Hence the reactions shown below can be assumed to obey the pseudo first order kinetics. The concentration of methanol can be lumped with the intrinsic second order reaction rate constant to give a pseudo first order lumped rate constant. The catalytic effect is also captured here.
The reactions in the reactor during biodiesel production may be modeled as scheme of multiple reactions of the consecutive-competitive/series-parallel type. The methanol can be assumed to be in excess. Hence the reactions shown below can be assumed to obey the pseudo first order kinetics. The concentration of methanol can be lumped with the intrinsic second order reaction rate constant to give a pseudo first order lumped rate constant. The catalytic effect is also captured here.
The reactions are modeled as follows:
    (2)
Where A- triglyceride, B- Methanol (CH3OH), R- 1,2 and 1,3 diglyceride, S- monoglyceride, P- FAME, T- Glycerol.
It may be assumed that once the product P is formed it does not participate in the reaction any further. The FAME is harvested from the kettle. As glycerol (T) can be sold for profit this scheme is of more interest. This reaction set is applicable for successive attacks of a compound by a reactive material. In this case the reactive material is methanol and the compound is triglyceride.
The kinetics of the reactions can be written as follows:
    (3)
The scheme of reactions can be modeled as shown in Eq. (2) as a consecutive-competitive type [43]. The reaction rate expressions in Eq. (3) can be written in dimensionless form as follows after making the following substitutions;
    (4)
In dimensionless form the rate expressions given in Eq. (3) can be seen to become;
    (5)
    (6)
    (7)
    (8)
The rate expression for the product, FAME can be obtained by adding the contributions from the methanolysis of triglyceride, diglyceride and monoglyceride steps and can be seen to be:
    (9)
In order to evaluate the selectivity of the FAME product P over the by-product, glycerol, T solution to Eqs. (5-8) were obtained by the method of Laplace transforms [44].
The solutions are as follows:
    (10)
    (11)
    (12)
    (13)
The product yield can be found by difference as:
    (14)
Model solutions given by Eqs. (10-14) were plotted in Microsoft Excel 2010 for Windows 7.0 on a Hewlett Packard Compaq Elite 8300 desktop computer with Intel Core i7 processor with 3.9 GHz speed. The results for the product distribution is shown in Figure 4 and Figure 5. The simulations were conducted for values of reaction rate constant ratios κ < 1 and ω < 1 and further for ω < κ.
Figure 4: Trigylceride (A), Diglyceride (R), Monoglyceride (S), Glycerol (T) and FAME (P) Product Ditribution in Progressive Methanolysis [45] at κ = 0.75 and ω = 0.4.

Figure 5: Trigylceride (A), Diglyceride (R), Monoglyceride (S), Glycerol (T) and FAME (P) Product Ditribution in Progressive Methanolysis at κ = 0.75 and ω = 0.35.
It can be seen from the Figures 4-7 that the conversion of species A, XA increases in a monotonic manner as predicted in Eq. (10). The monoglyceride and diglyceride yields go through a maximum. A change in curvature from convex to concave can be seen in the product yields of FAME and glycerol. There is a rate increase later in time in the formation of glycerol. The selectivity of FAME can be poor compared with that of glycerol formation as can be seen in Figure 5. FAME yield can be high as shown in Figures 4, 5. There can also be a “cross-over” from higher selectivity of FAME to lower selectivity of FAME compared with glycerol as can be seen in Figure 7. In such cases, CSTR can be used with residence times less than the cross-over point in order to obtain higher yield of FAME. The convexo-concave curvature in the product yields is consistent with experimental studies such as that reported by Jaya and Ethirajulu [46].
Figure 6: Trigylceride (A), Diglyceride (R), Monoglyceride (S), Glycerol (T) and FAME (P) Product Ditribution in Progressive Methanolysis at κ = 0.75 and ω = 0.6.

Figure 7: Trigylceride (A), Diglyceride (R), Monoglyceride (S), Glycerol (T) and FAME (P) Product Ditribution in Progressive Methanolysis at κ = 0.75 and ω = 0.25
Centrifugal separation of FAME and glycerol: torque requirements
The separation costs of FAME and glycerol may be a critical factor in the process design of biodiesel production. Computer simulations can be used in order to obtain the torque requirements of a rotor to affect centrifugal separation of liquids with different viscosity and density. A typical CINC centrifugal liquid-liquid separator can be obtained from commercially such as the CINC processing equipment, Inc. The CINC Liquid-Liquid Centrifugal Separator utilizes the force generated by rotating an object about a central axis. By spinning two fluids of different densities within a rotating container or rotor the heavier fluid is forced to the wall at the inside of the rotor while the lighter fluid is forced toward the center of the rotor. A cut-away view of such a centrifugal separator may be viewed at the internet webpage http:///www.cincmfg.com/How_our_Centrifuges_Work_s/108.htm
The theory for separation used currently in the industry is the Stokes settling of oil droplets. For high volume separation such as the biodiesel and glycerol mix from the reactor outflow, a centrifuge such as the one described in this study may be used. Here layers can be expected to form, with one layer that is biodiesel rich and another layer that is glycerol rich. The peripheral layer is glycerol rich and may be collected from a port at the outer centrifugal bowl as shown in Figure 8 and the biodiesel-rich layer may be collected from the inner rotor wall that is rotating. There is not much discussion in the literature for the theory of centrifugal separation of layered flow. The velocity profiles of the glycerol-rich layer and biodiesel-rich layer are derived from the equations of continuity and motion. The thickness of the interface of the biodiesel and glycerol is calculated from a component mass balance of the biodiesel in the inlet and outlet streams of the continuous centrifuge. Numerical simulations are run on a desktop computer for a given angular speed of rotor, ω (RPM) and density ratio of the fluids and viscosities of the fluids. A set of four simultaneous equations and simultaneous unknowns are solved for using the MINVERSE command [45] in Microsoft Excel for Windows 2007. These constants are used to obtain the power draw at the rotor from the torque required. A log-log plot is developed form the simulations for the power draw at the rotor that may be used in the design of such systems.
Figure 8: Cross-sectional view of centrifugal separator of oil and water.
Shear flow theory
Consider a centrifuge with a outer bowl radius of R (m) and an inner rotor radius of κ R (m). The inner rotor is allowed to rotate at an angular velocity of ω RPM. The feed has high concentration of biodiesel about 33% mass fraction biodiesel (xF). It is desired to achieve a separation efficiency of 97.9%. The outlet oil stream is from the inner rotor and the outlet water stream is from the periphery of the bowl. The density ratio of the oil and water is γ.Viscous flows are considered at steady state.
Consider a thin shell of fluid with thickness Δr and at a distance r from the center of the centrifuge as shown in Figure 8. It is assumed that the momentum transfer is predominantly in the radial direction. The tangential velocity assumes a profile that varies with the distance r from the center of the centrifuge. It is assumed that for high volume feeds two layers are formed, i.e., one rich in biodiesel and the second layer rich in glycerol. As the tangential force from the rotor is increased the species with the higher specific gravity will gain more momentum and move to the periphery of the centrifuge.
The species with the lower specific gravity will remain in the inner layer close to the rotor. The density of the glycerol was assumed to be “heavy” and was taken as 1260 kg.m-3 and the density of the biodiesel was taken as 860 [47] kg.m3. For such a pair, the peripheral layer would be glycerol-rich and the inner layer would be biodiesel-rich. Earlier discussions in the literature have been largely on droplet formation of oil and layer formation or “slick” formation is not discussed much. Let the radius of the outer centrifugal bowl that is held stationary be R (m) and that of the inner rotor be κ R (m). The inner rotor is allowed to rotate at an angular velocity of ω RPM (revolutions per minute).The water is collected by a port at the periphery of the bowl and the oil is collected through the port in the inner rotor. The feed is introduced from the top of the centrifuge.
The feed location has not been optimized in the study. The equation of continuity and motion for vθ and the equation of motion for shear stress, τ can be written from the Appendix in Bird, Stewart and Lightfoot [48] as follows;
    (15)
Integrating Eq. (15);
    (16)
The Newton’s law of viscosity for the shear rate is given by:
    (17)
For the oil rich inner layer (Figure 8) combining Eq. (16) and Eq. (17):
    (18)
Integrating Eq. (18) twice;
    (19)
Eq. (19) is valid for, κ R ≤r ≤ α R.
For the water rich peripheral layer (Figure 8), in a similar manner the tangential velocity of the fluid can be written as follows:
    (20)
Eq. (20) is valid for, α R ≤ r ≤ κ R.
The boundary conditions can be seen to be;
at the outer stationary wall,    (21)
Substituting Eq. (21) in Eq. (20);
    (22)
at the inner rotor wall,
    (23)
Substituting Eq. (23) in Eq. (20);
    (24)
at the interface of oil rich and water rich layer,
Interface is assumed to be without any accumulation of forces;
    (25)
The velocity across the interface of oil rich and water rich layer is assumed to be continuous;
    (26)
In this study Eqs. (22, 24-26) were used to solve for the integration constants, c1, c2, c3 and c4 using the MINVERSE function in Microsoft Excel for Windows 2007. The set of equations Eq. (22,24-26) that are needed to obtain the integration constants are given in the matrix form as follows;
    (27)
Eq. (27) is a set of four simultaneous equations and four unknowns.The vector of constants can be obtained as follows;
    (28)
The layer thickness ratio, α can be estimated as follows. A component balance on the oil in the feed stream, peripheral water stream and inner rotor oil stream would yield:
    (29)
or
    (30)
Let the residence time of the fluid in the continuous centrifuge be θ (hr). Then;
    (31)
and
    (32)
Dividing Eq. (2.80) by Eq. (2.81) and Equating with Eq. (16);
    (33)
Results and Discussion
Simulations were run on the desktop computer using Microsoft Excel for Windows, 2007. An example calculation that was done for oil and water separation may be used for illustration purposes here.
The calculations were performed for an rotor speed of 1000 RPM. The separation efficiency is about 97.9%. The values in bold face are obtained by using the MINVERSE command in Microsoft Excel for Windows 2007. The results are the inverse of the matrix as described in Eq. (28). Simulations were repeated for 29 different values of angular speeds of rotor. Each of the torque values were recorded in another column in the spreadsheet. The torque is calculated from the shear stress the rotor wall multiplied with the surface area of the rotor and the moment arm distance, κ R, and multiplied with the angular speed ω in RPM. The results of these simulations are shown in Figure 9 on a log-log plot. The relationship is found to be linear in the log-log plot. For the example run as shown in Table 2 the separation efficiency is about 37%.Inorder to achieve more separation more stages need be considered.
Figure 9: Power draw as a function of rotor speed for κ = 0.74.

Oil Water Separation by Centrifugation Feed Outlet(Oil) Outlet(Water)
      xoil 0.33 0.99 0.01    
μ w 0.001 Pa.S xw 0.67 0.01 0.99    
μ oil 1000 Pa.S vrotor 13.3877551        
κ 0.74   vper 27.6122449        
1-κ2 0.4524   Separation 0.979591837 0.326531 Ratio    
α 0.83386   Efficiency          
R 5 10000 Gallons V        
ρ oil 900 kg.m3 Ft H 0.522028 m    
ρ water 1000 kg.m3            
θres 1 hr            
v 41 m3.h-1            
γ 0.9   0 0 0.00002 1    
α 0.83386   3.6523E-05 1 0 0    
      1 0 -1 0    
      2.87636E-05 1 -28.7636 -1    
                 
                 
c1 34.76614   -0.034766137 0.034766137 1 -0.034766137   0
c2 999.9987   1.26976E-06 0.99999873 -3.7E-05 1.26976E-06   1000
c3 34.76614   -0.034766137 0.034766137 -2.7E-07 -0.034766137   0
c4 -0.0007   1.000000695 -6.9532E-07 5.4E-12 6.95323E-07   0
  RPM              
T ω α Torque          
199 1000 0.83386 42.32546536          
Table 2: Calculations for a given set of oil and water viscosities and ω = 10 RPM.
The set of simulations were repeated for a higher viscosity of oil, μoil (5000 Pa.s). The power draw at the rotor is also shown in Figure 9 in the log plot. The increase in power draw corresponding to an increase in viscosity of oil was not high.
Conclusion
Advances in microarray analysis, sequencing of genomes may lead to the improvement in cultivability of J. curcas shrub. The ribosome inhibiting protein action and regulation of gene expression studies from transfected clones of the curcin gene from the J. curcas and other studies may increase the yield of the Jatropha oil from the shrub. NGS, Next-Generation Sequencing machines that are rapidly becoming less expensive from different vendors are compared side by side and tabulated. The genominomics of sequencing J. curcas has changed rapidly in recent years and holds promise for higher quality shrubs. The pathway that is more probable during biodiesel formation from triglycerides in Jatropha oil obtained from quantum orbital calculations is of the consecutive-competitive type. The yield of biodiesel over glycerol can be higher for some reaction rate constant ratios and vice versa for some reaction rate constants. The results from model solutions are shown in Figures 3-7. The centrifugal separation of glycerol and biodiesel are simulated using Microsoft Excel Spreadsheet. For a given density ratio and viscosity ratio the power needed for the rotor as a function of RPM is obtained from the simulations and found to be log linear as shown in Figure 9. Plot was obtained for 29 different values of the agitator RPM and two liquids with different viscosities. The layer formation may become unstable at certain volume fractions of the feed. The velocity profiles for Couette flow in the centrifuge when layers are formed are obtained. The torque is calculated from the shear stress the rotor wall multiplied with the surface area of the rotor and the moment arm distance, κ R, and multiplied with the angular speed ω in RPM. The conversion of Jatropha oil in the reactors may be optimized for minimization of total cost of reactor and separator.
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