A look at engineering based approaches to developing harvest
A Look at Engineering Based Approaches to Developing Harvest, Processing and Controlled Environments for Essential Oil Production Murray Hunter Centre for Communication & Entrepreneurship University Malaysia Perlis AbstractAgriculture is a complex activity requiring complex processes upon uncertain variables. Thus developing propagation, production, harvesting, and post harvest equipment and processes cannot be built upon precise theorem. In most cases these processes need to be developed through observation, conceptualization, trial, error, insight, and emergent and heuristical thinking. This requires the utilization of various types of thinking processes and converging, discovery with trans-disciplinary knowledge. This paper examines agricultural engineeringdevelopment pathways with three examples the author has been involved within the essentialoil industry, 1. The development of automated tea tree harvesting through reengineering and adaptation, 2. The development of distillation processes through incremental emergent engineering and applying thermodynamic theories into practical situations, and 3. The development of controlled environment vetivert production through conceptual development and emergent innovation engineering.Introduction The ideal engineer is a composite ... He is not a scientist, he is not a mathematician, he is not a sociologist or a writer; but he may use the knowledge and techniques of any or all of these disciplines in solving engineering problems. (N. W. Dougherty, 1955)Over the time that humankind has existed upon the earth and society progressed fromhunter-gatherers to cultivators, we have encroached upon the Earth’s natural terrestrialecosystems with our agricultural systems. These human made eco-systems are notcompatible with the algorithms of nature and thus require our heavy intervention to maintaintheir efficiency, productivity, and sustainability. Our interventions to achieve short-termresults have created many long term consequences that were not foreseen – where wedegraded the soil, increased salinity, contaminated our waterways, lowered our water tables,as well as changing our micro-climates. In fact we do not really understand the trueinterrelationships between the variables influencing the results of our agricultural activities,as most often they are not direct cause and effect relationships (Lovelock 2005). Ourcontrived agro-eco-systems are really too complex for us to understand completely (see Paper presented to the National Conference on Agricultural and Food Mechanization 2012, 10-12 January at Pullman, Kuching, Sarawak
figure 1), and the way we really approach issues is through educated guesses based uponshort-term research results taking up limited correlating variables together with our personaland collective experiences. Infrastructure Government Regulation Positive Inputs Taxes & Conducive weather Water Negative Outputs subsidies Climate Or Sunshine Trade Floods, droughts, etc Nitrogen Runoffs, wastes, environment Agricultural inputs carbon Research Weather Fertilizers etc Rainfall Knowledge Wind Labour Sunshine UV radiation Temperature Some Humidity Resource inputs, Production Processes recycling fertilizers, herbicides, insecticides, machinery, back to Human research capabilities Farm size & layout system Habitisation Organisation & methods Knowledge Suitability of conditions Suppliers & contractors Pollution (air, land & water) Propagation Pollution Labour sources Attitudes and concerns Water resources Cultivation Positive Outputs (create hinterland where Products farm part of) Processing Physical Environment Customers Financing & Marketing Revenue flow various kinds of back to Soil capital Topography system Atmosphere Natural flora & Negative Inputs fauna habitat Business Urbanisation Adverse physical Environment Competition conditions Low prices Pests & diseases Markets Changing demand Pollution Finance patterns Heavy metals Trade environment An Agricultural Enterprise as a SystemFigure 1. The agricultural enterprise as an eco-system (Hunter 2009, P. 326).Due to eco-system and agricultural complexity, working within this environment requires anoverall environmental scale view as well as a discipline specific focused view. Our advancesin knowledge come from the ability to conceptualize and effectuate to develop new ideas andtheories that can be acted upon, in a similar way to how Einstein thought spatially and thenonly reverted to the discipline of mathematics to retrospectively support his imagination(Gardner 1993). Therefore in this way science becomes an art based on effectuation in not anun-similar way that Picasso would have created his masterpieces1. Art infersconceptualization, which infers creativity as the basis of our innovations. It is from theconcepts that an engineer then works backwards or emergently to solve a problem. Thus1 Effectuation can be best explained by imagining how a person cooks a meal after coming home fromwork. A person may look at what food ingredients are in the food pantry and refrigerator and then usethese ingredients to cook something that comes to mind. The process of effectuation is about thinkingof possibilities that may have potential and then evaluating and confirming the potential. Effectuationdoes not rely on preconception, which is something akin to a painter sitting in front of a blankpainting canvass thinking about what to paint. Effectuation is about creating something that willextend our ideas to fitting the solution.
engineering within this innovation paradigm loses its status as a discipline and gains its statusas the process of applying creative effectuation into solutions within the agricultural eco-environment.If the above argument string is accepted then it is not disciplinary knowledge that is soimportant but rather the ability through our cognitive processes to apply our knowledge toproblems and applications in order to solve them. The fraternity of engineers has largelyignored this but it is the application of and not the knowledge itself that brings solutions andinnovations. In solving agricultural problems particularly in the areas of mechanization andcontrolled environments, we don’t apply algorithms to problems as this doesn’t work wheneffectuation is needed. Heuristics are the key to guiding our emerging thinking and problemsolving. Any agricultural issue must be diagnosed through our thinking and applyingknowledge we have to the circumstances we observe, and every solution must be constructedfrom what knowledge we have and implemented through our emergent thinking.Heuristics is something belonging to logic, philosophy and psychology (Hutchinson 1971), athinking process something between the algorithmic and stochastic approaches (Polva 1945).Stafford Beer likened heuristics to a living organism, its DNA and existence developed alongan algorithmic blueprint, but sustaining survival in the environment through heuristics (Beer1981). Heuristics prescribe general rules for reaching goals, which we cannot reachalgorithmically, because we are not sure of the exact route to get there, as there are a numberof potential paths and these paths are at the point of beginning, unknown to us. Heuristics isthe way we actually live our lives, although we believe we are living life algorithmically withrules. We need heuristics to make decisions, although we are not aware of this. Whenheuristics are mentioned, we think of it’s contribution to artificial intelligence, but heuristicsis the reality of how an engineer develops new processes for products that the actual details ofthe production process, although in principal is known, is mysterious in finite detail to theengineer when starting out (Hunter 2006).Agricultural InnovationInnovation is a ”hot topic” in both the fields of agriculture and engineering, but too muchemphasis has been placed on amassing technology, rather than using amassed knowledge tocreate new knowledge through emergent thinking. This has important national consequencesas Dr. Asma Abdullah states that there “is also the tendency for Asian countries, includingMalaysia, to deal with the issue of values in development by importing many technologiesand systems wholesale from abroad without going through the process of mentaltransformation necessary to master them fully. Although Malaysia is going through rapidtransformation, our growth is one without development in the context of knowledgecontribution to science, engineering and technology. As long as we are consumers andoperators of sophisticated techniques, plants and technologies imported wholesale fromabroad, we are to a certain extent undergoing a technology-less form of industrialization.This transformation of values and attitudes is a key issue in the nation’s developmentagenda” (Asma 1995).
A lesson can be learned from some of the Japanese companies which have been able tosuccessfully compete on cost with their Chinese competitors. Japanese companies throughheuristics have been able to build their on plant and processing equipment at a third of thecost of the Chinese (Chen 2004), who purchased their equipment from third party vendors.The Japanese have realized that this is a source of competitive advantage and are able tocontinue to export from a much higher cost base because of substantial capital savings. Thisis a lesson for us in Malaysia aspiring to become a global player in both agriculture andmanufacturing industries in utilizing heuristical approaches in production process design.Through heuristic design we are able to increase our production process knowledge base, relyless on imported machineries and add both innovation and competitive advantage to thesector. This is an example to follow in other chemical plant development, which potentiallycan save firms large capital investments on new projects and acquire technology throughinternal deduction and experimentation.A heuristic approach to production process development in agriculture is an acquisition ofproprietary knowledge, which is exclusive to the firm. The effort to develop the process isbased on trial and error and thus is not easily duplicated quickly by other firms and can beconsidered a barrier to entry into that particular product/market, thus enabling the firm topractice monopoly differentiation for a period of time at a price premium to other firms. Thusthrough heuristic production process development the firm has developed a source ofcompetitive advantage. If the new production process can be developed without heuristics,then barriers to entry into the particular product/market would be low and the productcategory would be crowded with competitors, where the future of Malaysian agriculture isabout developing high value added crop diversity that can compete in uncontested marketspace, if possible.Advances in agricultural mechanization and devising of controlled environments is aboutimproving productivity, and developing new value added products. Historically our advancesmade in agricultural engineering and post harvest processing techniques has probably made alarger contribution to agriculture production than the “green revolution” in the 1940s and 50swhich enabled the controlled supply of nitrogen and other nutrients to crops – allowing ourmono-cropping model. For example, it was the invention and subsequent development of thecotton gin by Eli Whitney, saving hundreds of man-hours that allowed the rapid expansion ofthe cotton industry of the Southern American States and mass settlement (Schweikart &Pierson Doti 2010, P. 63).Diagnosing ProblemsComplex issues need two complementary ways of seeing. First we need to see the wholeenvironment the ‘what is” to get a contextual understanding of what a problem is. Thisrequires spatial thinking without being locked into specific disciplinary knowledge that willrestrict perspective. This is called field dependence where the environment is seenholistically, connections between categories of information can be seen, and information isprocessed in chunks (Witkin et. al. 1954).
Once connections can be made, problems or possibilities (opportunities) can be seen as apotential to solve or develop. A change in thinking is required where much more focus andattention should be given to the details. Thus holistic transforms into analytical thinkingwhich breaks down the whole into simpler parts where information can be reorganized. Thisis called field interdependence where the individual items within the field, rather than thefield as a whole is considered (Vaidya and Chasky 1980). Field independency aids analysis,to look at things in isolation to rest of field, categorize stimuli where one can impose theirown structures upon the problem, in a detached and impersonal manner (Hunter 2011, P.219). One however must be mindful in the field independence mode that they don’t fall intothe rigidity of their discipline which may narrowly regulate their perceptions of the problem(Jonassen & Grabowski 1993).Focus enables researching specific issues that may lead to the solution of the specific problemor enable the conceptualization of a new system, process, or piece of equipment. Decisionswill have to be made between a number of research priorities due to the multiplicity offactors, varying degrees each factor influences. For example in the production of essentialoils, yield and quality, resource limits, time, available competencies and cost are all issuesthat have influencing variables. The variables that most influence oil quality and yield wouldbe in this case selected for investigation. Potential factors influencing yield and quality can bemapped out on the Ishikawa (fishbone) diagram approach as shown in Figure 2. Location Climate Genetic Material Humidity Collection Temperature Purchase Sunshine hours Topography UV radiation Plant physiology Seasons Slope & drainage Propagation Yield and Rainfall characteristics Chemical Constituents of the Humus Nutrients Method of extraction Essential Oil Extraction time Compactness Drainage & water holding qualities Pest & weed pH control Pre-harvest handling Mineral residuals Irrigation & preparation Plant densities Soil type Time & method of harvest Agronomic Harvest & Soil Practices Extraction Practices Figure 2: Factors Influencing Essential Oil Yield and Constituents on a Ishikawa (fishbone) Diagram (Hunter 2009, P. 319).It is from this position that the information extracted from the environment and re-organizedin an Ishikawa array that the following basic questions that can assist in prioritising researchand development can be asked. These include;
1. What are the specific technical goals and objectives? 2. What are the major technology, infrastructure and climatic constraints (boundaries)? 3. What are the areas where innovations will develop quick improvements? 4. What is the probability of successful outcomes?, and 5. How do we choose between successful outcomes?Modifying ‘off the shelf solutions’ and knowledge can solve many problems and should beconsidered first. An ‘off the shelf solution’ is a research result that has proved positive, butnot tested in the site specific project that is intended. This will save project time and reducecost. Importing ideas, practices and equipment may not always suit local conditions and willbe expensive. Similar crops within the region may have methods and equipment that may beeasily modified to lead to a more effective solution. Unexpected costs should also beidentified.Other factors may require capital intensive solutions, where cost competitive production is afactor in success and sustainability. For many agricultural activities the use of mechanisationhas been proved to be more efficient than manual labour, even in very low labour costcountries (Timmer 1973). However small scale decentralised mechanised production unitsmay not always necessarily lead to lower production costs and there are often someadvantages in flexibility, at early project stages (Austin 1981). The selection of appropriatefarming, harvesting and processing equipment will depend on the technology available, thepotential to adapt the equipment to the site and crop, and the finance available. Not muchequipment will be available ‘off the shelf’ and in most cases existing equipment will need tobe modified. Practical experience during trials is needed to understand exactly what changesare necessary. Good metal and machine fabricators need to be identified.The final part of this paper will briefly apply the above discussion to three different types ofprojects and outline the engineering and cognitive approaches taken. The engineering aspectswill not be explained in detail as the author’s interest is in the thinking processes.Project One: Automating the tea tree harvest processTea tree (Melaleuca alternifolia) was introduced to Malaysia by the author back in 1991where a trial plot was planted at MARDI Serdang. With initial promising signs a much largertrial was undertaken at Berseri, Perlis to take advantage of the unique dry season in that state.Trial results showed that oil yields were far in excess of what commercial yields were inAustralia at that time and the economics showed that the net return per Ha. Wasapproximately three times of what oil palm would provide (Hunter 1997). However at thattime harvesting and filling the distillation bins was a completely manual task. To be aninternationally competitive producer of tea tree oil, these tasks needed to be automated,especially with rapidly rising wages and shortages of labour.The Australian tea tree industry had developed many innovative ways of harvesting throughconverting multi-crop foliage harvesters into meeting the requirements of specialized tea treeharvesters. The German company CLASS developed a specialized tea tree harvester withinthe Jaguar series which was very efficient, bringing the harvesting operation down to a one-
man operation and ability to harvest up to 10 Ha on a daily basis. However in today’s pricesthe cost of this harvester is in excess of RM4.7 Million.The Sabah Economic Development and Investment Authority (SEDIA) made the decision todevelop tea tree as a strategic crop for Sabah in 20082. There was not nearly the amount offunds available to purchase specialized harvesting equipment from Germany. A local solutionwas required. The decision was made to strip down and completely rebuild a corn harvester,modifying the front-end cutters, mulchers, and foliage carry shafts so it could handle theharvesting of tea tree and fill a bin attached to the end and carried by the harvester.As a previous solution to this problem has been achieved, it became a matter of reengineeringand adaptation utilizing locally available items and parts. This required studying the presentsolution and determining how this can be transformed into a local version. The critical issueshere were the cutters and flow of the trees into the mulchers after cutting. This was eventuallysolved through postulating how to this could be achieved (the conceptual world), trialling thisin the field (experimentation), observing the results (Evaluation), and re-postulating andmodifying the cutters, re-trialling, observing and re-postulating again. Thus the developmentprocess is part conceptualization and part real world experience in determining a finaloutcome.However the solution was not achieved through this single learning loop and the assumptionshad to be changed about the mode of cutting from a linear method along some rails to acircular method (complete re-evaluation). This was done and the postulate, trial, observe, re-postulate, and re-trial sequence continued until a positive solution occurred. Figure 3 belowrepresents this learning process.Thus the thinking processes in this first example relied on spatial skills. Conceptualization isa form of imagination and it is very important in being able to work backwards to determinewhat will be the kinetic processes and how these can be best governed. The key to developingthis harvester was prior knowledge about how the other harvester worked as a process whenharvesting tea trees, knowledge about the capabilities of what is available locally, and spatialimagination to be able to run this process within the mind. One is running the mind back fromthe solution and adapting local parts to this end in a mental picture. The only way todetermine whether the solution works is to try it and observe and try to imagine what couldcontrol the process better within the imagination.The locally fabricated harvester cost RM220,000 to build, trial modify and put it into service.2 This was undertaken by Institute of Development Studies (Sabah) before the formation of SEDIA.
Figure 3. The learning process (Hunter 2009, P. 219).Project Two: Scaling up Essential Oil Distillation ProcessesEssential oil distillation is a very well established process and although governed bynumerous laws of thermodynamics related to latent heat, gas laws, vapour laws, steam, andphyto-chemistry, it is a relatively practical process commonly used around the world by bothlarge and small agricultural based enterprises. The distillation process is primarily influencedby the nature of the plant material, characteristics of the volatile materials, and size and shapeof the distillation apparatus. These three factors vary the application of the various laws thatapply.Consequently scaling up is not a linear process. Steam, vapour pressure, and general volatileconstituent vapourization characteristics will change as size scales up. Thus as designs arescaled up, theoretical considerations are overridden by practical trial and error as theconverging influences of all relevant theories are too complex to calculate out and thusunexpected results occur. Thus scaling up distillation is an emergent development process.The process of postulation based on smaller distillation unit behaviour, observation,evaluation, and re-postulation is necessary. Postulation becomes a process of imagining theinteraction of the steam, chemical constituents, and biomass, as distillery dimensions areenlarged. Like the harvester, spatial intelligence is the paramount quality required. Aknowledge of the constituents and various laws relevant to the process are also required sothese can be mentally manipulated extrapolated from observation of the performance of the
smaller distillery. One will heuristically determine what laws are important and apply theircalculations through incremental effectuation to scaling up design3.Project Three: The Production of Vetiver by HydroponicsVetiver grass (Chrysopogon zizanoides) is primarily used for soil stabilization, erosioncontrol, and water treatment. The rhizomes also contain a volatile oil that has woody andearthy notes valuable for fine and natural perfumery. Traditionally vetiver is cultivateddirectly into the soil where the roots grow down some three to four metres in depth and theroots have to be dug up for distillation. The effort required to produce this oil is well reflectedin the market prices. Production in Malaysia must compete against low cost producingcountries like China, Haiti, Indonesia, and India.The cultivation of vetiver can also be undertaken hydroponically which would dramaticallylessen labour costs. This could be achieved through plating the grass through a nettingarrangement and then allowing the roots to dangle into a water bath which can be keepcirculating with specifically selected nutrients. It would take approximately twelve monthsfor the roots to grow to a length of around four feet when they could be trimmed back to sixinches and reinserted into the water bath for another round of growth.The conceptualization of this alternative vetiver process most probably came into mindthrough an insight based on connecting hydroponics with the problem of digging up roots fordistillation. Once again this engineering concept is not the result of using algorithms, butrather imaginative and effectuated thinking processes. The process would be made effectivethrough trial and error.ConclusionTechnical and social disciplines are undergoing convergence which can be seen in the waymany industries are merging together into one. Convergence is creeping into the research anddevelopment process where trans-disciplinary approaches are required to solve problems.Being an engineer is not good enough in isolation. In order to create, an engineer must haveknowledge across a number of disciplines so that knowledge can be synergized into somemeaningful expressions in the form of new applications and inventions. This would normallybe triggered by some deep insight that relates trans-disciplinary knowledge with some issuesfacing society that need to be solved, as is shown in figure 4 in the field of biotechnology.This creates new knowledge and new knowledge itself is a source of exponential growth ofopportunity.3 One can only really guess as which laws are taking over dominance in the process based on experience andknowledge about the characteristics of what is being distilled.
“Issues facing society to be solved” New Forms of Expression Other disciplines of Insight Expressed knowledge Application & Microbiology Our current Knowledge Invention Biology Trans-disciplinary synergy of Deep Insight knowledge Engineering Agriculture Physics Chemistry BiochemistryFigure 4. . Trans-disciplinary knowledge and the expression of new knowledge as applicationor invention (Hunter 2011, P. 176).This phenomenon can be seen at a national level if one looks at the number of residentpatents filed per million population in each country. Focusing on the Asia-Pacific region,Figure 5. shows the number of resident international patents applied for in the region during2010. International patent filings are more relevant than domestic patent filings as theinternational filings figures are a better indicator of the country’s international influence inthe global business arena. Countries like Japan, Republic of Korea, China and Australia arefar in front of the rest of the Asia-Pacific Region. In the Asian Grouping, India had 627international patent filings during 2010 and Singapore 402. Both countries have invested inR&D very heavily, with India expected to become an industrial giant in the near future andSingapore publically emulating the Korean research model in cluster development, in largeinvestments like the biotechnology Biopolis. Although aggregate filings are low in the rest ofthe Asian Region, Malaysia stands out with some relative success with its national policies onprojects like the Multimedia Super Corridor (MSC) in generating new patent filings. TheAsian region still has a long way to go, however issues like innovation, research anddevelopment, and commercialization are on top of the policy agendas at this time.
Australia 2139 Brunei 3 China 3910 Indonesia 6 India 627 Japan 26906 Dem. Rep. Korea 4 Republic Korea 5935 Malaysia 54 New Zealand 316 Philippines 15 Singapore 402 Thailand 12 Vietnam 9 0 5000 10000 15000 20000 25000 30000 Source: WIPO Statistics Number of International Patents Filed by ResidentsFigure 5. International Patents Filed by Residents in Asia-Pacific Region 2010Schumpeter (1954) argued that economic growth requires innovation – the generation ofhigher quality products at lower unit costs. The future of regions and nations depend on newideas and new products that energize those places and facilitate economic growth (Feldman& Florida 1994).Knowledge without application is useless in creating tangible benefits to society, buthopefully this paper has shed light that it is not knowledge in itself that is important rather theability to apply it. And the ability to apply it doesn’t rely upon formulae, theory or algorithm,but rather emergent thinking and the heuristics have developed. This is a neglected part ofengineering education and this is also the quality that makes a good engineer stand out fromthe rest of the pack.Only innovation will make an essential oil industry viable in Malaysia and truly competitiveinternationally. This depends upon our ability to conceptualize, imagine and sketch outconcepts in our mind rather than having capital and the most up to date equipment at ourdisposal.References:Asma, A., Going Glocal: Cultural Dimensions in Malaysian Management, Kuala Lumpur,Malaysian Institute of Management, 1995, P. 179.Austin, J. E., (1981), Agroindustrial Project Design Analysis, Baltimore, The John HopkinsUniversity Press, pp. 121-125.Beer, S., Brain of the Firm 2nd Ed., Chichester, John Wiley & Sons, 1981, pp. 52-53.
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