Designed methodology framework.
\r\n\t
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It is the reason why the next generation of process management leads to Process Performance Management or Corporate Performance Management. The phrase Corporate Performance Management (CPM) was coined by Gartner Group to describe the combination of process, methodologies, metrics and technologies to measure, monitor and manage the performance of the business. The oft-citied phrase: “ If I can not measure it, I cannot manage it” can be motivation of this chapter.
\n\t\t\tThis chapter deals with presentation way leads to establishment of efficiency system for process measurement and controlling in the manufacturing area. The process measurement can be defined as the application of the management cycle with a focus on organizational process. Muehlen present process management as the collection of planning, organizing and controlling activities for the goal-oriented management of the organization’s value chain regarding the factors quality, time, cost and customer satisfaction (Muehlen, 2004). The main goals of process management are the achievement of transparency with regard to process structure and process contribution.
\n\t\t\tThe description and practical application of process performance management system will be presented in case study. The case study also presents exploitation of data from an enterprises information system for decision–making is next point of this chapter.
\n\t\tThe process controlling has been discussed in the published books and papers in scientific journal (Shen, 2007) and (Aalst, 2007). A. Kronz presents principal tasks of process controlling in book (Scheer, 2006). He mentioned these points:
\n\t\t\tEvaluation, analysis and continues monitoring of business workflows (automatically or manually),
Map the process reality in a task-oriented manner according to the issue and task.
Result of process controlling is transparency of the process, in structural terms and for purpose of evaluation,
Results can also be used as the basepoint for process optimization.
Next author Michael zur Muehlen discusses in his book (Muhlen, 2004) of the workflow audit trail data with existing data warehouse structures and develops a reference architecture for process-oriented information system.
\n\t\t\tThe term of process controlling has been often discussed in relation to process management, because implementation of business process management is a way how to achieve of process performance management system establishment. The “Process Management and “Business Process” are contemporary terms used in the many companies. Many successful companies applied this management approach based on Hammer’s Business Process Reengineering Concept (Hammer, 1993). The authors develop the Hammer’s and Champy ideas in related works nowadays.
\n\t\t\tMany articles in journals and international conferences proceedings deal with BPM issue. High number of citations on business process management (BPM) seems to prove that BPM is a significant field of the recent research (Harmon, 2008). For example a Google.com search on „Business Process Management“ returns more than fourteen thousand pages where this phrase appears. The BPM issue is the subject of research focused on methodological or technological solution of BPM problems (Weske, 2007). The main problems are described by Wasana Bandara in article (Bandara, 2007), where fourteen global experts were interviewed for example. The problems examples show the lack of governance, lack of standards, lack of methodology, lack of tool support for process visualisation etc.
\n\t\t\tThe main principles of process measurement system are described by the authors and many authors discuss about phrase Corporate Performance Management. The phrase Corporate Performance Management (CPM) was coined by Gartner Group to describe the combination of process, methodologies, metrics and technologies to measure, monitor and manage the performance of the business. Prof A. W. Scheer discusses this issue and trends of CPM in his book (Scheer, 2006).
\n\t\t\tCPM is thus directed at continues monitoring of the effectiveness of the results of all company processes and the constant optimization thereof, i.e. its objective is a monitoring system that monitors the business performance of all pertinent business processes all the time, detects and reports weaknesses and problem situations, ideally even suggests optimization option and evaluates the success of improvement measures. Substantive recommendations for actions, including their chances of success, are needed so that the better decisions can be made more quickly. Process Performance Management may be regarded as the heart of CPM. (Scheer, 2006)
\n\t\t\tThe present trends in Corporate Performance Management are:
\n\t\t\tProcess mining for automated weak point analysis
Right time monitoring
Dynamic organizational analysis
These trends describe the purpose of application of process controlling in the manufacturing area. The application of process controlling based on process management principles for technological and diagnostics process control is one objective of our research. The main objectives of our research are design and verification of a control system based on business process management approach for control of process in the diagnostics and the electrical engineering and electronics manufacturing. In the following case study, I shall describe the practical demonstration of process controlling application.
\n\t\tDesigned methodology concept helps to implement the process performance measurement system based on process controlling. The concept has been developed into two steps:
\n\t\t\t\tAnalysis of processes and current needs of responsible managers, staffs, researchers and technicians. The designed questionnaires can be used in this step. We have obtained process attributes of key processes.
Study, selection and modification of suitable methods and tools for business process management and performance measurement.
The application of designed methodology is demonstrated on case study. Data collection for this case study was conducted these different techniques:
\n\t\t\t\tQuestionnaire – This method was used for process analyses and mapping of process attributes. The main problems were done via structured question to management and workers.
Participation/Observation – The researches were able to observe and processes in operation and validate recorded data.
Interview – This method enabled the collection information of management vision and requirements.
Methodology framework is presented by Table 1. As we can see the table presents key steps and activities in defined order. The methodology concept is based on business process and process performance management theory. It means application of Business Process
\n\t\t\t\tStep | \n\t\t\t\t\t\t\tActivities | \n\t\t\t\t\t\t\tOutput | \n\t\t\t\t\t\t
Business strategy definition | \n\t\t\t\t\t\t\tAnalysis of current situation Definition of mission, vision and strategic goals. | \n\t\t\t\t\t\t\tStrategy are defined | \n\t\t\t\t\t\t
Process design | \n\t\t\t\t\t\t\tImplementation of process modeling methodology Process models making Definition of main optimization criteria Process optimization | \n\t\t\t\t\t\t\tProcesses are designated. | \n\t\t\t\t\t\t
Process Controlling Implementation and Indicators Setup | \n\t\t\t\t\t\t\tDesign of process measurement and execution system Determination of periodicity of process measurement Implementation of tools for process measurement, execution and evaluation Design of system for correction proposal and improvement | \n\t\t\t\t\t\t\tSystem for process evaluation and execution of processes is implemented. \n\t\t\t\t\t\t\t\t Improvement system is defined. | \n\t\t\t\t\t\t
Designed methodology framework.
Management in first step. This step leads to:
\n\t\t\t\tprocess analysis and key process indicators setup
process description, modeling and optimization,
system of evaluation and process execution.
The information infrastructure can be applied for the methodology support. The information structure should be built on Service Oriented Architecture (SOA) which provides methods for systems development and integration where systems group functionality around business processes and package these as interoperable services. SOA also describes IT infrastructure which allows different applications to exchange data with one another as they participate in business processes. Service-orientation aims at a loose coupling of services with operating systems, programming languages and other technologies which underlie applications.
\n\t\t\tThe current management literature presents different methods for process performance management. Firstly, they are methods based on financial analysis of basic enterprise economic indicators (for example Economic Added Value measurement, DuPont analysis). Secondly, they are management methods used the financial and non financial indicators (typically represented by Balanced Scorecard method (BSC), EFQM model, Six Sigma, Value Based Management). The Balanced Scorecard method sophisticated presents how to define and implement the key process indicators and metrics for performance evaluation. Many companies have adopted Balanced Scorecard as a way of evaluating managerial performance.
\n\t\t\t\tThis methods supplements traditional financial measures with three additional perspectives: the customers, the internal business process and the learning and growth perspective. It is supposed to be a tool describing an organization’s overall performance across a number of measures on a regular basis.
\n\t\t\t\tThe basic idea is very straight forward. Kaplan and Norton began by arguing that "What you measure is what you get" and that "an organization\'s measurement system strongly affects the behaviour of managers and employees." They went on to say that "traditional financial accounting measures, like return-on-investment and earning-per-share, can give misleading signals for continuous improvement and innovation..." To counter the tendency to rely too heavily on financial accounting measures, Kaplan and Norton argued that senior executives should establish a scorecard that takes multiple measures into account. They proposed a Balanced Scorecard that considered four types of measures:
\n\t\t\t\tFinancial Measures: How Do We Look to Shareholders?
Internal Business Measures: What Must We Excel At?
Innovation and Learning Measures: Can We Continue to Improve and Create Value?
Customer Measures: How Do Customers See Us?
The BSC method gives a definition of strategy as hypothesis summary about causes and results. It can be declared as a sequence of “if – then”. The BSC, proposed by Kaplan and Norton, is the strategic management instrument:
\n\t\t\t\tto clarify and translate vision and strategy,
to communicate and link strategic objectives and measures,
to plan, set goals and align strategic initiatives,
to enhance strategic feedback and learning.
The case study is focused on printed circuit board production. This production is one part of our department and its customers are other universities departments and small companies from the Pilsen region. The objective was to establish the performance measurement system focused on process time measurement and real processes current status analysis. This case study also presents application of designed methodology.
\n\t\t\tDefinition of core problem and strategy of company was first task. The core problem of visualization was effectively solved by the Current Reality Tree (CRT). This chart shows causality of relevant undesirable effects of the analyzed situation. The practical example is shown in Fig. 1. The main problem is fall of profit related to production time, capacity and quality of process. On the other hand this situation might be described by a conflict diagram (Fig. 2). The diagram describes decision and optimizing problem of manufacturing - determination of optimum batch size.
\n\t\t\t\tThe conflict exists between increasing and decreasing of the batch size. The increasing of production run (D) makes to cost reduction (B) and decreasing (D) of the batch size makes to high quality of products (C). Both described situations have negative effect on the
\n\t\t\t\tCurrent problem of causality.
Conflict diagram of company.
production plan and profit. These problems and conflict were solved by designing methodology effectively. So cost reduction, quality improvement and time reduction were the main optimizing criteria according to methodology.
\n\t\t\t\tSecondly, the business strategy and main key process indicators were developed according to Balanced Scorecard. The Table 2 shows process indicators and the strategy is describes in ARIS model (Fig. 3). From this model we can make performance dynamic execution (it is part of last step methodology implementation).
\n\t\t\t\tARIS model of Balanced Scorecard business strategy.
Process indicators | \n\t\t\t\t\t\t\tStaffs Satisfaction | \n\t\t\t\t\t\t\tInternal Productivity | \n\t\t\t\t\t\t\tCustomer Satisfaction | \n\t\t\t\t\t\t\tTraining Course | \n\t\t\t\t\t\t\tFail- ures | \n\t\t\t\t\t\t\tROI | \n\t\t\t\t\t\t\tProcess Time | \n\t\t\t\t\t\t\tProcess Costs | \n\t\t\t\t\t\t
Unit | \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[number] | \n\t\t\t\t\t\t\t[number] | \n\t\t\t\t\t\t\t[-] | \n\t\t\t\t\t\t\t[min] | \n\t\t\t\t\t\t\t[EUR] | \n\t\t\t\t\t\t
Minimal Value | \n\t\t\t\t\t\t\t75 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t80 | \n\t\t\t\t\t\t\t1 | \n\t\t\t\t\t\t\t95 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t24 | \n\t\t\t\t\t\t\t40 | \n\t\t\t\t\t\t
Maximal Value | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t\t4 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t\t8 | \n\t\t\t\t\t\t\t72 | \n\t\t\t\t\t\t\t60 | \n\t\t\t\t\t\t
Tolerance | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t
Period | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t\tQ | \n\t\t\t\t\t\t
Planned Value | \n\t\t\t\t\t\t\t95 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t90 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t99 | \n\t\t\t\t\t\t\t5 | \n\t\t\t\t\t\t\t48 | \n\t\t\t\t\t\t\t50 | \n\t\t\t\t\t\t
Current Value | \n\t\t\t\t\t\t\t95 | \n\t\t\t\t\t\t\t1,5 | \n\t\t\t\t\t\t\t85 | \n\t\t\t\t\t\t\t2 | \n\t\t\t\t\t\t\t98 | \n\t\t\t\t\t\t\t5,3 | \n\t\t\t\t\t\t\t75 | \n\t\t\t\t\t\t\t75 | \n\t\t\t\t\t\t
Strategic indicators.
The process analysis and process modelling was the first important steps lead to process design. It contained following activities:
\n\t\t\t\tdefinition of the process model and attributes. It means determination of targets, key processes fragments, key performance indicators (KPI) and their dimensions,
processes fragment modelling (Fig. 5).
Core process model of PCB production.
The ARIS (Architecture of Integrated Information System) tools and process analyses were used in this part. The main problem was fall of profit related to production time, capacity and quality of the process. Due to this fact, the process controlling application based on CPM leads to this core problem minimization.
\n\t\t\t\tModel of process fragment.
We decided use the ARIS Process Performance Manager (ARIS PPM) software tool for process controlling in this case, because this tool can be implemented to any information system and structure. The information technologies make the important support for business process management nowadays. Owing to the fact that we are using tools ARIS for process modeling and optimization of processes, we decided to use the software ARIS PPM.
\n\t\t\t\tWith ARIS Process Performance Manager, IDS Scheer company offers a software solution that is a purpose-built for controlling and analyzing business processes. As a part of this solution, a patented procedure is used to collect process relevant data from the operational IT systems available for reconstructs process automatically and calculates key performance indicators online and particularly for presenting the actual process measurement in the form of event-driven process chains (eEPC).
\n\t\t\t\tARIS PPM imports all business transactions to be reviewed into the repository from one or more source systems via application-specific adapters. To begin with, depending on the source system, the process-relevant runtime information about the activities performed is highly disparate in nature (e.g. log files, vouchers, records). These are imported one after the other in chronological order by ARIS PPM and compiled into a process. A graphical illustration – the “event-driven process chain” (EPC) - containing all the individual activities (functions) are then generated automatically for each operation (process instance) – see Figure 8. As a result, even a process that extends beyond the boundaries of a single system can be represented cohesively and uniformly.
\n\t\t\t\tThe ARIS Process Performance Manager tool has these important functions for Process Performance Management:
\n\t\t\t\tVisualizing Real Process Structure
Key Performance Indicators and Analyses
Process documents
Weak Point Analysis
Process Mining: Automated Weak Point Analysis
Management Views
Offline Reports
Key process indicator | \n\t\t\t\t\t\t\tType | \n\t\t\t\t\t\t\tCategory | \n\t\t\t\t\t\t\tDescription | \n\t\t\t\t\t\t
Interval of order processing | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tProcess duration from an order acceptance till issue of an invoice. | \n\t\t\t\t\t\t
Interval of acceptance of an order | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration: “Receipt of order”. | \n\t\t\t\t\t\t
Interval of PCB design | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration: “Design of PCB”. | \n\t\t\t\t\t\t
Interval of manufacturing preparation | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration: “Manufacturing data preparation”. | \n\t\t\t\t\t\t
Interval of PCB manufacturing | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration “Manufacturing of PCB. | \n\t\t\t\t\t\t
Interval of PCB expedition | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration: “PCB expedition”. | \n\t\t\t\t\t\t
Interval of invoice issue | \n\t\t\t\t\t\t\tProcess | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tSub process duration: “Issue invoice”. | \n\t\t\t\t\t\t
Activity process time | \n\t\t\t\t\t\t\tFunction | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tDifference between the end of current activity (process) and the end of previous activity. | \n\t\t\t\t\t\t
Processing time of an activity | \n\t\t\t\t\t\t\tFunction | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tDifference between the end of activity and the start of a particular activity. | \n\t\t\t\t\t\t
Idle time of activity | \n\t\t\t\t\t\t\tFunction | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tDifference between the start of an activity and the end of previous activity. | \n\t\t\t\t\t\t
Keeping the order term | \n\t\t\t\t\t\t\tFunction | \n\t\t\t\t\t\t\tTime | \n\t\t\t\t\t\t\tDifference between planned and real order completion date. | \n\t\t\t\t\t\t
Key process indicators definitions.
The basis for all processes controlling is a process-oriented key performance indicator system that links the process perspective to the essential controlling aspects for business. The key performance indicators must enable conclusions to be drawn regarding the effectiveness of the processes (e.g. customer satisfaction) and their efficiency (e.g. processing time, delivery reliability, process quality and costs). In addition, the process-oriented key performance indicator system is configured so that it would be possible to make statements about the actual course of the process.
\n\t\t\t\tPre-configured process key performance indicators are calculated and aggregated for each imported process stage. The ARIS PPM base system already includes a core set of key performance indicators, and these are set as default ones regardless to a connected source system. The key performance indicator types can be divided into 3 groups:
\n\t\t\t\ttime-related key performance indicators (e.g. throughput times, processing times, frequencies),
cost-related key performance indicators (e.g. process costs/rates on the basis of the performance standard) and
quality-related key performance indicators (e.g. number of processors, error rates, deadline reliability)
The process owner can use ARIS PPM to achieve the optimum balance in the ”Time-Quality-Cost” magic triangle by taking a number of key performance indicators from each of the three ranges with added weighting and thus to yield a new key performance indicator. These user-defined key performance indicators can be set in the front-end at any time during runtime. Besides the preset key performance indicators, other specific key performance indicators are configured in the ARIS PPM base system as a part of the adaptation to the customer individual environment.
\n\t\t\t\tThese are defined, for instance, by the process types to be reviewed. The key performance indicators in ARIS PPM are endowed with process-relevant decision variables - ”dimensions”. These dimensions are also imported from the source systems as features of the individual process instances. The user evaluates the efficiency of his business processes with reference to the interplay between key performance indicators and dimensions in the process analysis.
\n\t\t\t\tThe set of key performance indicators must be calculated and defined flexibly, and in such a way that it can be expanded to the need of changing requirements of the company specific processes. Besides calculating key performance indicators, it is also necessary to be able to visualize the structure of actual processes since, it is the only way to how obtain generalized explanations for their performance behaviour.
\n\t\t\t\tThe implementation of ARIS PPM tool has been formulated in project. The project main phases were:
\n\t\t\t\tImplementation for printed circuit board manufacturing.
Verification and validation of results from implementation for PCB manufacturing.
Implementation for diagnostic process control.
Verification results and examination implementation proposal.
The first two phases were realized in following steps:
\n\t\t\t\tConceptual and technical workshop
Determination of process instance, fragments, KPI and process attributes. The results of process mapping and analysis from previous part were used in this step. The Table 3 presents used KPI.
The SW tool implementation means installation, customizing and connectivity settings. The manufacture section does not use information system now and data must be recorded on operation record cards. Due to this fact, we had to prepare the special software for CSV files generation and rewrite the data into SW ARIS PPM database using PC. Validation of results and their definition is last step of implementation.
\n\t\t\tFirst experience of PPM implementation, based on CPM idea, has shown benefits of this solution in the manufacturing area for technological process control, in this case for printed circuit board manufacturing. The SW tool ARIS PPM helps us to make analysis and processes monitoring, particularly:
\n\t\t\t\treal process course,
processes time,
comparing of the real and planned key indicators value,
type and kind of order.
The results of process mining and analysis have been used for process models correction and KPI planning. In short, the responsible management obtains quick management and performance view (see Fig. 7, 8).
\n\t\t\t\tThe solution mentioned above doesn’t use sophisticated information system. In this phase the data about process has been collected in excel files. The records from the paper sheet in manufacture section had to be rewritten to ARIS PPM database. In consequence of this we had to realize software for data converting from excel database to ARIS PPM database (CSV data format was used for this converting operation). It is obvious that this way isn’t suitable for big data volume. From this reason, the suitable information system has to be implemented in the next project phase. The structure and components of used information system presents Fig. 9.
\n\t\t\t\tManagement view.
Visualization of a process instance generated in ARIS PPM.
Information system structure.
This chapter presents an example of process controlling application. Process controlling described in this paper, comprises the following components:
\n\t\t\tEvaluation of the efficiency of business processes based on key performance indicators
Transparent representation of procedures actually performed for cause analysis.
Deduction of optimization measures.
Continuous monitoring of success developments.
Organizational analysis.
The process controlling is very important tool for process improvement in manufacturing area. The real application in manufacturing area was described in the practical case study focus on the small printed circuit board production. The case study describes way how to analyze the processes and introduces software tools, which have been applied. The benefits and results are documented in the Figures 7-8 as well.
\n\t\t\tThis solution corresponds with the new trend in process management area. Companies that are able to align their business processes to the requirements of their environment and surroundings will not only gain a competitive advantage, but they will also be able to manipulate this alignment better and faster than their competitors. The prerequisites for this solution are the supply of decision-relevant information and an ability to transform this information quickly and effectively into sustained measures for targeted alignment of business processes.
\n\t\tThis research is supported by the research plan MSM4977751310 “Diagnostic of interactive processes in electrical engineering“.
\n\t\tChlorophyll and carotenoid are important pigments that have been used as intrinsic optical molecular probes to observe plant performance during different phases of development. Chlorophyll and carotenoid are biosynthesized in chloroplast and their metabolism is closely related with the chloroplast development. Chlorophyll biosynthesis begins with the formation of 5-aminolevulinic acid (ALA) from glutamate (Glu) via Glu-tRNA synthetase, Glu-tRNA reductase (GluTR) and Glu-1-semialdehyde aminotransferase (GSA-AT) [1]. Eight molecules of ALA are condensed, eventually forming the symmetric metal-free porphyrin, protoporphyrin IX (Proto IX), which is a common precursor of haem and chlorophyll. The biosynthesis of chlorophyll continues by insertion of Mg2+ into Proto IX and followed by several steps in the chlorophyll cycle to create protochlorophyllide.
\nFurther, reaction is one of the most interesting steps because this is the first step in chlorophyll biosynthesis that requires light: the NADPH:protochlorophyllide oxidoreductase converts protochlorophyllide into chlorophyllide. This reaction is then continued to produce chlorophyll (chl) a and b. So, when dark-grown etiolated seedlings are exposed to light, protochlorophyllide is immediately converted to chlorophyllide and then further to synthesis of chl. Once chl a and b are formed and properly incorporated into the thylakoid membranes and associated photosystems, chloroplast is fully functional to do photosynthesis [2].
\nPlant carotenoids are synthesized and accumulated exclusively in plastids, most importantly, chloroplast and chromoplast [3]. There are two types of plant carotenoid: carotene, which is cyclized and uncyclized hydrocarbons, and xanthophylls, which are oxygenated derivatives of carotenes. Carotenoid synthesis is initiated by the formation of C40 compound phytoene by the head-to-head condensation of two molecules of geranylgeranyl diphosphate (GGDP) by phytoene synthase and then to a series of 4 sequential desaturation reactions, by two separate enzymes to produce lycopene, which has 11 conjugated double bonds [4]. Lycopene is then cyclized to α-carotene or β-carotene, which is then further hydroxylated to produce colorful xanthophylls such as lutein, β-cryptoxanthin, zeaxanthin, antheraxanthin, violaxanthin and neoxanthin. The biosynthesis and accumulation of carotenoids in the dark-grown etiolated seedling are essential for the assembly of membrane structure and benefits the development of chloroplast when seedlings emerge into the light [5]. Understanding the relationship between structure and photophysical properties of these pigments can provide insights into a better study of how photosynthesis works at the molecular level in chloroplast.
\nThe photophysical properties and functions of chlorophyll and carotenoid reside in their chemical structure. Chlorophylls are defined as cyclic tetrapyrroles carrying a characteristic isocyclic five-membered ring that are functional in light-harvesting or in charge separation in photosynthesis [6]. The chemical structure with IUPAC numbering scheme of chl a is shown in Figure 1. It is a squarish planar molecule, about 10 Å on a side. An Mg atom in the center of the planar portion is coordinated to four nitrogen atoms. The five rings in chlorophylls are lettered A through E, and the substituent positions on the macrocycle are numbered clockwise, beginning in ring A. Chlorophyll has two molecular axes: y-axis is defined as passing through the N atoms of rings A and C and x-axis passing through the N atoms of rings B and D. The delocalized π electron system extends over most of the molecule, except for ring D, in which the C-17—C-18 double bond is reduced to a single bond. The tail is formed by condensation of four isoprene units and is then esterified to ring D. It is often called phytol tail, after the polyisoprenoid alcohol precursor that is attached during biosynthesis. Because of the reduced ring D, plant chlorophylls such as chl a and b are classified as chlorins rather than porphyrins. These types of pigments have (in organic solvents) absorption bands around the blue and red spectral regions (Figure 2a), which are called B (or Soret) and Q bands, respectively, and arise from π→π* transition of the four frontier orbitals [7, 8]. One band each pair is polarized along the x-axis (Bx, Qx) and other along y-axis (By, Qy). The strong absorption band at the maximum absorption wavelength (λmax) 660 nm is called Qy transition band, which corresponds to the electronic transition polarized along the y-axis. The Qx-band of chl a shows a weak band near 550 nm, while the two overlapping Soret (B) bands show at about 430 nm. The chemical structure of Chl b is identical to chl a except at the C-7 position, where a formyl group replaces the methyl group. This structural change results in a shift of the Qy maximum absorption to shorter wavelength. The fluorescence spectrum of chlorophylls peaks at slightly longer wavelengths than the absorption maximum. The fluorescence emission (Figure 2b) is polarized along the y molecular axis, as it is emitted from the Qy transition. Shift of the emission to the longer wavelength side of the main transition is known as Stokes shift. In light reaction, chlorophyll plays as key pigment in the collection of light energy in the light-harvesting complexes and to carry out reversible photochemical redox reaction (Krasnovsky reaction) in the reaction centers.
\nChemical structure of Chl a (a), Chl b (b), lycopene (c), β-carotene (d), zeaxanthin (e) and lutein (f) with IUPAC numbering system.
(a) UV–Vis absorption of Chl a (black) and Chl b (red) in MeOH, (b) fluorescence emission spectra of Chl a (red) and Chl b (black) in MeOH, (c) β-carotene (red), zeaxanthin (black) and lutein (blue) in EtOH, (d) lutein in several organic solvents; MeOH (black), acetone (pink), diethyl ether (purple), hexane (light blue), EtOH (blue).
Structure of carotenoid is characterized by a linear chain of conjugated π-electron double bonds (Figure 1). In oxygenic organisms, carotenoid usually contains ring structures at each end, and most carotenoids contain oxygen atoms, usually as part of hydroxyl or epoxide groups. The primary molecular factor that gives rise to their strong absorption bands in the visible spectral region is the number of π-electron conjugated double bonds, N. The position of the absorption maxima is affected by the length of the chromophore, the position of the end double bond in the chain or ring and the taking out of conjugation of one double bond in the ring or eliminating it through epoxidation. Progressive movement to longer wavelengths (bathochromic shift) is illustrated by the absorption spectra of the acyclic carotenoid of increasing chromophore length. Carotenoids show different optical characteristics in various solvents, depending on the polarizability of the solvent [9, 10]; however, generally they have a typical three-peaked absorption spectrum with well-defined maxima and minima (fine structure) (Figure 2a). A ring closure as in β-carotene produces a less-defined fine structure. The introduction of a carbonyl group in conjugation with the polyene system produces a bathochromic shift and the loss of fine structure [4]. The influence of other substituents such as OH is negligible, for example, β-carotene, cryptoxanthin and zeaxanthin all have very identical absorption spectrums. Owing to the double bonds in the molecule, all carotenoids exhibit cis-trans isomerization (stereomutation). A cis double bond implies a configuration with the highest-priority group on the same side, whereas in the trans configuration they are on opposite sides. The absorption spectrum of a cis isomer presents a subsidiary peak in the near-ultraviolet, the cis peak; generally, it is located 143 nm from the longest wavelength maximum. For example, cis peak will appear at 330 nm if the longest wavelength maximum is 473 nm. In photosynthetic systems, carotenoid has essential functions. First, carotenoid is an accessory pigment in the collection of light energy in the spectral region which chl does not absorb and in transferring energy to a chl pigment [11, 12]. Second, carotenoid functions in a process called photoprotection by quenching triplet state of chl before it reacts with oxygen to form singlet oxygen species (ROS) [13, 14]. Third, carotenoid regulates energy transfer in the light-harvesting antenna through a process called xanthophyll cycle, to avoid over-excitation of the photosynthetic system by safely dissipating excess energy [15, 16].
\nIn the chloroplast interior, there are four main constituents in plant thylakoids, that is, photosystem II (PSII), cytochrome b6f, photosystem I (PSI) and the ATP synthesis. Chlorophylls and carotenoids are embedded in PS II and PSI, large pigment-protein clusters, the structures of which are perfectly adopted to ensure that almost every absorbed photon can be utilized to drive photochemistry. Both PSII and PSI consist of two moieties, that is, core complex or the reaction center that is responsible for charge separation and light-harvesting antenna complexes that surround the core complex and have functions to increase the capture of light energy and energy transfer to the reaction center in the core complex.
\nOne can detect chlorophyll and carotenoid bound in PSII and PSI in chloroplast by measuring their absorption and fluorescence spectra. Figure 3a (solid red line) shows the absorption spectrum of diluted chloroplast that is indicated by red shift of Chl a, Chl b and carotenoid’s bands because these molecules are bound as pigment-protein complexes in chloroplast. The Soret band of chl a in the complexes was detected at 438 nm while in the MeOH it was found at 432 nm (Figure 2a black line). The fluorescence emission spectra (Figure 3b) indicate a strong emission band of PSII complexes with maximum wavelength at (λmax) about 682 nm and weak emission band of PSI complexes with λmax at about 730 nm. It is shown here that Chl a acts as the main contributor to the excitation band at 434 nm and it shows that excitation at 434 nm (Soret band) produces stronger emission intensity, while the excitation at 475 and 512 nm, correspond to Chl b Soret band and carotenoid, respectively, produces weaker emission intensity. If we monitor the emission at 682 nm and measure the excitation spectrum, it shows that the PSII emission at 682 nm is the result of contribution from Chl a, Chl b and carotenoids (Figure 3a solid black lines) with bands at λmax about 414, 434, 475 nm, respectively.
\n(a) Overlaid of UV–Vis absorption (red) and fluorescence excitation (black) (λem = 682 nm) spectra of chloroplast and (b) emission spectra of chloroplast with excitation at 434 (black), 475 (red) and 512 (blue) nm. Measurements were conducted at ambient temperature. The isolation of chloroplast was carried out as follows: 20 g of suji leaves (Pleomele angustifolia) were washed with running water and cut. The leaves were then homogenized in 200 mL ice-cold isolation buffer (300 mM sorbitol, 50 mM HEPES-KOH pH 7.5, 2 mM EDTA, 80% acetone, 0.1% BSA) for 10 min in a cold environment, followed by filtration using cloth. Centrifugation was conducted in 2 steps, to discard cell debris at 200 g, 4°C, 20 min and to harvest chloroplast pellet at 3000 g, 4°C, 20 min. Final chloroplast pellet was collected and subjected to spectrum UV–VIS (Shimadzu UV-1700)and fluorescence measurement (Jasco FP-8500).
The current high-resolution structural models of antenna complexes have been obtained only for LHCII (2.72 Å) and recently for CP29 (2.8 Å) from PSII of spinach [17, 18]. Here we focus more on the LHCII structure. LHCII shows trimeric structure. Each monomeric contains three transmembrane α-helices, a, b and c (Figure 4a). One monomeric subunit contains eight chlorophyll (Chl) a pigments, six Chl b, two luteins (Lut), neoxanthin and one additional xanthophyll [17, 19]. The 14 chlorophylls are non-covalently attached in the protein cavity. Four carotenoid binding sites per monomer have also been characterized, but in this case the type of carotenoid bound can vary. Typically, two lutein molecules are in groves on both sides of helices a and b and have been likened to a cross-brace. A third carotenoid, 9-cis neoxanthin, is located in the Chl b-rich region near helix c. The fourth carotenoid is located at monomer-monomer interfaces in the trimer. It has been suggested that this site accommodates carotenoids that can participate in the xanthophyll cycle. It depends on the external stress level of the plant; the fourth carotenoid is either violaxanthin (no or low stress) or zeaxanthin (high stress) [20]. In this structure, the carotenoids are in van der Waals contact with the chlorophylls [9]. This is essential as carotenoids in LHCII act as accessory light-harvesting pigments and photoprotectors. The accessory light-harvesting function represents singlet-singlet energy transfer from the carotenoid to the chlorophylls. Since the singlet excited state lifetime of the carotenoid is quite short, approximately 200 fs, the carotenoid must be in close distance to a chlorophyll molecule if the energy transfer is to be efficient. Photoprotection function represents the quenching of triplet excited state of chlorophylls and so preventing the formation of singlet oxygen. This triplet-triplet exchange reaction also requires the carotenoid to be in close contact with the chlorophylls. Regarding CP29, it binds 3 carotenoids and 13 chlorophyll molecules [18]. The position of some chlorophyll binding sites in CP29 differs from LHCII.
\n(a) A view looking down on the top of trimeric complex of LHCII structure from spinach. Each monomer is colored magenta, yellow and pale green. The three-transmembrane helices (a, b and c) present in a monomer are labeled and are easily visible. Chl a molecules are in red, Chl b colored green and carotenoids colored orange. (b) Side-view of LHCII structure shows chlorophyll and carotenoid molecules are packed densely and close to each other (within van der Waals contact), enabling the crucial photo-protective role of these molecules to function by quenching triplet chlorophyll excited states. (c) Structure of PSII from Thermosynechococcus elongatus [28], a side-view representation of the overall dimer perpendicular normal with the pseudo-twofold symmetry axis. (e) PSII core reaction center is shown; component co-factors of the electron transport chain viewed along the membrane plane. The two branches are related by the pseudo-twofold symmetry axis. The respective pairs of pigments on the branches are labeled to indicate whether the Mg2_ is coordinated by D1, D2. (d) Structure of PSI from Synechococcus elongatus [29]; overview of the complete trimer looking along the membrane normal from the stromal side with each polypeptide of the trimer colored differently and chlorophyll molecules given in green. The two main proteins that comprise a monomer are PsaA (yellow) and PsaB (magenta). The electron transport chains are in the center of each monomer. (f) PSI core reaction center component co-factors of the electron transport chain are viewed along the membrane plane. The two branches are related by the pseudo-twofold symmetry axis. The representative pair of chlorophyll molecules on the branches are labeled A or B indicating whether the Mg2+ is coordinated by PsaA or PsaB. The iron–sulfur center of Fx involves residues from both PsaA and PsaB, while FA and FB are located in an extrinsic subunit called PsaC.
The current high-resolution crystal structure of PS II and PSI core complexes is limited to that from cyanobacteria and from pea, respectively [21, 22]. The core of PSII is a multi-subunit complex. Most of the chromophores involve light harvesting as well as electron transfer reaction and are bound to four main subunits, that is, D1, D2, CP43 and CP47. When the core of PSII and PSI reaction center structures is compared, the arrangement of the pigments and other electron transfer co-factors is also very similar (Figure 4c and d). Here, first we look at the PSII core reaction center. The core of reaction center of PSII is made from two major polypeptides called D1 and D2; each contains five membrane-spanning α-helices. These two helices clasp each other like two cupped hands holding on to each other. The redox cofactors are arranged into two arms that lie on either side of the point where the two groups of helices interact. This arrangement of the helices and the cofactors introduces a pseudo two-fold symmetry axes that runs through the center of reaction center normal to the plane of the membrane. In Figure 4e, it is seen that the electron transport pathway in PSII begins with a pair of chlorophyll molecules called P680 (PD1 and PD2). Then each arm contains, in order, one monomeric chlorophyll molecule, one pheophytin (a chlorophyll derivative) and one plastoquinone molecule. Here, only the D1 arm is active in electron transport. Upon excitation P680 becomes oxidized and one electron is injected out and passes down the active branch to the quinone QA. P680 is re-reduced by electron transfer from a special tyrosine residue called Z (Tyrz). A second turnover of P680 delivers a second electron to the plastoquinone and the secondary quinone QB is now reduced to QBH2. The hole on Tyrz is filled by electron transfer from the manganese cluster, the oxygen evolving complex. Every four turnovers of P680 stores four positive charges in the manganese cluster that are then used to oxidize water and evolve oxygen. While in CP43 and CP47, there are a total of 49 Chl a molecules that are bound and that function as internal antenna and allow excitation energy transfer from the peripheral antenna system to the reaction center.
\nUnlike PSII, in PS I, the same single polypeptides contain both antenna complexes (Lhca) and the reaction center core. The 3.3 Å resolution crystal structure of PSI from pea showed that plant PSI binds at least 173 Chl a and b molecules [22]. At this resolution of the crystal structure, it is not possible to identify the Chl species, but biochemical analysis of purified PSI indicated that it has a Chl a/b ratio in a range of 8.2–9.7 [23, 24]. A large number of Chl a and b molecules are bound to the Lhca protein, only about 100 Chl a are bound in the core complex, and the rest of Chl a and b are between these moieties. The latter represent the so-called “linker” chlorophylls which are located between Lhca monomers and “gap” chlorophylls (between Lhca and PSI core). The linker chlorophyll molecules probably play an important role in excitation energy transfer between Lhca antennas and from Lhca to the PSI core [20, 25, 26]. Based on biochemical analysis, PSI was reported to bind approximately 33/34 carotenoids, that is, about 12 carotenoid molecules are bound to Lhca, at the interface between Lhca and the core complex, and about 22 β-carotene are bound to the core [20, 23, 26]. Based on these biochemical analysis, it can be estimated that PSI-LHCII supercomplex contains about 215 chlorophyll and 45/46 carotenoid molecules.
\nThe core complex of PSI is composed of smaller number of subunits (15 subunit) than PSII. The large PsaA and PsaB subunit, which contain 11 trans-membrane helices each, forms a hetero-dimer that binds ~80 Chl a and ~20 β-carotene as cofactors for light harvesting as well as 6 Chl a, 2 phylloquinones and a 4Fe-4S cluster as cofactors for electron transfer reaction, with the exception of terminal electron acceptors (Fe-S clusters FA and FB) which are bound to the PsaC subunit [25]. At closer look (Figure 4f), the redox co-factors in the core reaction center are arranged into two arms that are located on either side of the region where two groups of helices interact with each other. Two chlorophylls form P700 and then each arm contains two monomeric chlorophyll molecules (the second one being in the equivalent position to the pheophytin present in photosystem II) followed by one quinone molecule. When P700 is oxidized, both arms of the electron transport pathway are able to work as it was reported that the electron can pass either down the B-branch or the A-branch [27].
\nChlorophyll and carotenoid can be isolated as free pigments, detached from the pigment-protein complexes, by organic solvent extraction. Important aspects such as the choice of organic solvents, light exposure and working temperature should be considered while isolating pigments. Based on the structure, chlorophyll is characterized with polar macrocycle ring with non-polar hydrocarbon tail. The structural difference between Chl b and Chl a is by having an aldehyde group in place of the methyl group at the macrocycle side group. This change is effecting the polarity of Chl b to be more polar in comparison to Chl a. In the case of carotenoid, structural difference can be seen from the number of conjugated double bonds and the presence of oxygen atoms. Considering these characteristics, mixtures of miscible polar and semi/non-polar solvents are used commonly to extract plant pigments. The mixture of solvent has double functions, that is, penetrating tissues/matrixes and extracting pigments from their lipophilic surrounding. During extraction, exposure of light should be avoided to reduce photodamage of the pigments. Temperature is also important. It is recommended to conduct extraction at lower temperatures, for example, on ice or using liquid nitrogen, to minimize activity of enzyme (e.g. chlorophyllase) that will catalyze breakdown. Antioxidant agent can be also added during extraction to avoid any unwanted oxidation.
\nAfter successful isolation, liquid chromatography has been widely used as an effective technique to separate individual type of pigments and for further purification. In this technique, the pigment separation is based on the polarity which depends on the interaction of pigment with the stationary and mobile phases. Elution method either normal phase or reversed phase is chosen according to the type of pigment to be separated. In addition, the choice of liquid chromatographic methods, namely thin layer chromatography (TLC), column chromatography (CC) and high-pressure liquid chromatography (HPLC), is referred to the speed, resolution and quantity of sample [30]. Currently, ultra-fast liquid chromatography (UFLC), a recent development of HPLC, has been used as a standard for liquid chromatography to achieve high-resolution data with low time consumption [31]. Purification with non-chromatographic method has also been developed, that is, purification method using dioxane has been effective to separate chlorophyll from most of the carotenoids and some lipids [32].
\nVarious types of column absorbents used for chromatographic separation of plant pigments have been well reviewed [30]. Here, we used a silica C30 column attached to UFLC analytic to achieve well separation of carotenoids from Pleomele angustifolia leaf using elution gradient program with mixture of water, methanol and methyl tert-butyl ether to separate, at least, 7 dominant pigments within 25 min. (Figure 5). The detailed identification of pigments, based on the chromatographic, spectrophotometric and mass properties, is summarized in Table 1. Chlorophyll a and chlorophyll b, α- and β-carotenes and violaxanthin are found to be the main chlorophylls and carotenoids, respectively, while the presence of lutein and zeaxanthin in this chloroplast is in low amount.
\nUFLC chromatogram of pigment extract from chloroplast of Pleomele angustifolia detected at 430 nm. The UFLC separation condition was as follows: Pigment separation was performed using UFLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and methyl tert-butyl ether (MTBE) at the flow rate of 1 mL/min at 30°C.
Peak No | \ntR [min] | \nλmaxs [nm] | \nMolecular ion | \nFragment ions [m/z] | \nIdentification | \n|||
---|---|---|---|---|---|---|---|---|
HPLC eluent | \nHexane | \nEthanol | \nAcetone | \nspecies [m/z] | \n||||
1 | \n7.3 | \n412,436,464 | \n— | \n— | \n— | \n— | \n— | \nViolaxanthin | \n
2 | \n12.8 | \n470,601,650 | \n451,595,642 | \n465,601,649 | \n458,596,646 | \n907.7 [M]+ | \n881.7 [M – COH]+ 855.7 [M – COH – Mg]+ | \nChlorophyll b | \n
3 | \n13.4 | \n422,445,472 | \n422,444,473 | \n−,446,474 | \n−,448,476 | \n568.4 [M]+ | \n551.4 [M – OH]+ 476.4 [M – 92]+ 430.3 [M – 138]+ | \nLutein | \n
4 | \n15.3 | \n−,451,477 | \n425,449,478 | \n425,451, 478 | \n428,454,481 | \n568.6 [M]+ | \n476.4 [M – 92]+ | \nZeaxanthin | \n
5 | \n16.6 | \n431,618,664 | \n427,613,661 | \n430,616,664 | \n431,617,662 | \n893.5 [M]+ | \n871.5 [M – Mg]+ 615.2 [M – phytyl]+ | \nChlorophyll a | \n
6 | \n20.1 | \n421,446,473 | \n421,445,474 | \n421,446,476 | \n422,445,473 | \n536.6 [M]+ | \n445.4 [M + H – 92]+ | \nα-carotene | \n
7 | \n21.2 | \n–,452,478 | \n–,451,479 | \n–,453,480 | \n–,454,482 | \n536.6 [M]+ | \n444.5 [M – 92]+ | \nβ-carotene | \n
Chromatographic, spectrophotometric and mass properties of pigments separated from the chloroplast of Pleomele angustifolia.
Larger-scale separation of Chl a and b can be achieved by CC using Sepharose CL-6B as the stationary phase and a mixture of 2-propanol (IPA) and hexane as the mobile phase. Chl a could be eluted using 1.5% IPA in hexane and Chl b with 10% IPA in hexane [33]. To achieve a pure, free carotenoid, saponification step is sometimes necessary to eliminate contamination of lipids and chlorophylls. Moreover, carotenoid ester can be hydrolyzed to produce parent carotenoid by using this method [34]. CC is usually used for carotenoid isolation in high quantity of pigment extract. Generally, the purpose of CC is to separate mixtures into carotenoid fractions which are either having high purity to be processed to crystallization or low purity to be extensively separated with further chromatography, that is, HPLC [35].
\nSilica and alumina are frequently used as the absorbent in the CC with the normal phase elution to separate the distinct carotenoids; however, it is not easy to use this method to separate carotenoid isomers, that is, geometrical isomers, diastereoisomers, and so on. In this case HPLC/UFLC can be used to overcome the difficulty in the separation of carotenoids by CC. Turcsi et al. (2016) revealed that the polar carotenoids including optical isomers, and region and geometrical isomers as well as non-polar carotenes, could be well separated by HPLC on C18 and C30 columns, respectively [36]. High purity of isolated pigment can be achieved by HPLC and crystallization processes. UFLC analysis of the purified zeaxanthin shows that this carotenoid had a high purity of around 99.3% (Figure 2, left). All purified pigments have purity higher than 95% (Figure 6).
\nPurification of zeaxanthin: (a) chromatogram detected at 450 nm. Insert figure is UV–Vis spectrum measured by UFLC diode array detector in the eluent and (b) ESI-MS/MS spectrum identification. The conditions of UFLC and ESI-MS/MS analysis were as follows: UFLC analysis of the purified zeaxanthin was performed using UFLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and MTBE at the flow rate of 1 mL/min at 30°C. The purified zeaxanthin was directly analyzed to LCMS 8030 (Shimadzu) with an isocratic elution of 0.1% formic acid (FA) in water (10%) and 0.1% FA in methanol (90%) at the flow rate of 0.3 mL/min. MS analysis was operated under the following conditions: (1) heat block temperature = 400°C; (2) desolvation line temperature = 250°C; (3) nebulizing N2 gas flow = 3 L/min; (4) drying N2 gas flow = 15 L/min; (5) interface voltage = 4.5 kV; (6) interface current = 0.1 μA; (7) mass range 400–700 m/z; (8) ionization mode = positive and negative.
Chromatographic, spectrophotometric and mass properties of pigment are minimum requirements for pigment identification [35]. These properties for all purified pigments are shown in the Table 1. In Figure 7 (right), absorption spectra of the purified chlorophyll a and the purified β-carotene in acetone have the same maximum absorption wavelength (λmax) and other spectral properties, such as the fine structure and spectrum shape, compared to these pigments in the references [37, 38]. Absorption spectrum of chlorophyll a in acetone shows typical Soret (431 nm), Qx (617 nm) and Qy (662 nm) bands, while two well-defined peaks in the absorption spectrum of β-carotene are found at 454 and 482 nm. This pigment analysis based on the results of spectrophotometer UV–Vis could support the advance pigment analysis using HPLC/UFLC equipped with photodiode array detection and coupled with the mass spectrometry. The LCMS technique has provided a power tool for pigment identification [39, 40]. Tentative identification for zeaxanthin peak separated by HPLC/UFLC analysis with PDA revealed that zeaxanthin has similar retention time (tR), maximum absorption wavelength (λmax) and the shape of absorption spectrum (data not shown) compared to the isolated zeaxanthin from corn which is a well-known source of zeaxanthin [41]. In addition the mass analysis provides the precursor and fragment ions at the specific m/z and characteristic fragmentation pattern for pigment identification. Mass spectrum of Chl a indicated the molecular ion [M]+ detected at m/z 893.6 and a fragment ion [M-Mg]+ at m/z 871.6 related to the loss of magnesium as the central metal of chlorophyll (Figure 1). This mass spectrum of Chl a agrees with the result that was reported [42].
\nPurification of Chl: (a) chromatogram detected at 660 nm. Insert figure is UV–Vis spectrum measured by UFLC diode array detector in the eluent and (b) ESI-MS/MS spectrum. The condition of UFLC and ESI-MS/MS analysis was as follows: UFLC analysis of the purified chlorophyll a was performed using HPLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and MTBE at the flow rate of 1 mL/min at 30°C. The purified chlorophyll a was directly analyzed to LCMS 8030 (Shimadzu) with an isocratic elution of 0.1% formic acid (FA) in water (10%) and 0.1% FA in methanol (90%) at the flow rate of 0.3 mL/min. MS analysis was operated under the following conditions: (1) heat block temperature = 400°C; (2) desolvation line temperature = 250°C; (3) nebulizing N2 gas flow = 3 L/min; (4) drying N2 gas flow = 15 L/min; (5) interface voltage = 4.5 kV; (6) interface current = 0.1 μA; (7) mass range 400–1000 m/z; (8) ionization mode = positive and negative.
Chlorophyll and carotenoid are chloroplast pigments which are bound non-covalently to protein as pigment-protein complex and play a vital role in photosynthesis. Their functions include light harvesting, energy transfer, photochemical redox reaction, as well as photoprotection. The exact number and stoichiometry of these pigments in higher plants are varied, but their compositions include Chl a, Chl b, lutein, neoxanthin, violaxanthin, zeaxanthin and β-carotene. Liquid chromatography methods are well developed to separate and purify different types of pigments. Identification and characterization of pigments can be well observed by spectroscopy methods such as UV–Vis absorption, fluorescence and mass spectrometry.
\nTatas Hardo Panintingjati Brotosudarmo (THPB) acknowledges the competence research grant (No. 120/SP2H/LT/DRPM/IV/2017) from Kemenristekdikti for the financial support. We also acknowledge Chandra Ayu Siswanti who helped in preparation of chloroplast isolation, pigment isolation and UFLC separation works. We acknowledge Dr. Hendrik Octendy Lintang for supporting fluorescence measurements of photosystem II and I in chloroplast.
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