1 Application of NIRS to Olives, Olive Oil, and Cheese Products Emil W. Ciurczak Castelo-Branco, Portugal 28 May 2015
2 Why Near-Infrared? Used first by US Dept. Agriculture in 1960s for wheat, soy, corn, fruits; later cotton, milk, tobacco, etc. Can be used for as is plants and fruits a well as processed materials, such as cheese and milk Can be used in the field as well as laboratory Minimum sample preparation, no chemicals or dilutions Once calibrated, may be used by anyone in any situation Cost of equipment and training is quickly offset by major time savings
3 Determination of Chlorophyll in Olive Oil There are various grades of olive oil; extra virgin regular light Extra Virgin olive oil is considered the highest quality, the first pressing from freshly prepared olives. (It has a greenish-yellow tint and a distinctively fruity aroma because of the high levels of chlorophyll and other volatile materials extracted from the fruit. Regular olive oil is collected with the help of a warm water slurry to increase yield. (It is pale yellow in color, with a slight aroma, because it contains fewer volatile compounds) Light olive oil is very light in color and has no aroma because it has been processed under pressure to remove the chlorophyll and volatile compounds. (It is commonly used for frying because it does not affect the taste of fried foods and it is relatively inexpensive).
4 Non-destructive assessment of olive fruit ripening by a portable NIR A portable NIR was used for the determination of oil and moisture contents in intact olives. In this test, spectral data were recorded in the region from 1100 to 2300 nm at 1 nm intervals under two different experimental conditions: on-tree in the field in Trial 1 under laboratory room conditions in Trial 2. Calibration models were developed and evaluated using PLS regression separately for each trial set and for the combined group of samples.
5 Non-destructive assessment of olive fruit ripening by a portable NIR The combined model showed predictive statistics within the range of the individual models (R = 0.89 and RMSECV = 1.99 for oil content and R = 0.88 and RMSECV = 2.06 for moisture content), considered acceptable as an increase in the model robustness could be expected. These results encourage the use of portable NIR spectroscopy to monitor olive fruit ripening and to decide the optimal harvesting date on the basis of oil and moisture content. Although slightly better results were obtained under laboratory room conditions, the results obtained on-tree in the field were also accurate enough to determine the optimal harvest date of each cultivar.
6 Experimental Method In trial 1, NIR spectra of fruits on-tree were obtained, samples were then taken to laboratory. In trial 2, fruits were harvested, and brought to laboratory spectra collected. The average spectra of five fruits per date were used for later analyses in both trials. Spectra were acquired in absorbance with a portable spectrophotometer, between 1100 to 2300 nm at 1 nm intervals. Each spectrum is the average of 50 spectra acquired on the fruit equator with continuous measuring for a total scanning time of 5 sec. Spectra collection was controlled with a laptop computer (SNAP32 software)
7 Methodology After spectral collection, fruit samples were processed in the laboratory for analysis by reference methods. Fresh samples were weighed and then dried in an oven (105 C for 42h) to determine moisture content. The oil content of dried samples was recorded by NMR Minispec NMS100 (Bruker). Calibration models were developed separately for each trial set and for the combined group of samples. Full cross-validation (i.e. leaving-one-out) was used to determine the performance of the models and no outliers were removed in any step of the calibration process. Correlation between actual and predicted constituent values (r) and standard error of cross validation (RMSECV) were used to test the performance of calibrations (Shenk and Westerhaus, 1995).
8 Results and Discussion Reference data and Spectral Features Environmental conditions and ripening stages have provided wide ranges of variability for the characteristics evaluated (Table 1). For the combined group oil content ranged from 4.80 to % and moisture content from to %. In both trials 1 and 2 oil content increases at the beginning of the experiment and then stabilizes or even slightly decreases at the end of the ripening period (Figure 1). Moisture content showed the opposite trend decreasing during the ripening period; both oil and moisture content were highly correlated (R = 0.61, p < 0.001). Different patterns were observed in trials 1 and 2 probably due to the different climatic conditions of each experimental area.
9 The average raw spectra and coefficient of variation of olive fruit samples from T 1 and T 2 are shown in Figure 2: two water bands ~1460 nm & 1950 nm and oil around 1210 & 1730 nm. Calibration development for each trial set Calibration models were developed for moisture and oil contents for each trial independently and for the combined data set. The number of PLS factors, correlation coefficient and predictive error (RMSECV and RER) obtained for models are shown in Table 2. R values for oil content and moisture were slightly lower and RMSECV was higher for model 1, due to different conditions during data acquisition. On-tree fruit spectral data were used in model 1, while the spectral data of model 2 were obtained under constant laboratory room conditions.
10 Results and Discussion Reference data and spectral features The selection of different cultivars, environmental conditions, and ripening stages have provided wide ranges of variability for the characteristics evaluated (Table 1). In both trials 1 and 2 oil content increases at the beginning of the experiment and then stabilizes or even slightly decreases at the end of the ripening period (Figure 1). Moisture content showed the opposite trend decreasing during the ripening period. Oil and moisture content, were highly correlated (r= 0.61, p < 0.001). Different patterns were observed in trials 1 and 2, probably due to the different climatic conditions of each experimental area.
11 The average raw spectra and COV of samples from T 1 and T 2 are seen in Figure 2. Spectra are characterized by two water bands ~1460 nm and 1950 nm and oil ~1210 nm and 1730 nm. Calibration development for each trial set Calibration models were developed for moisture and oil contents for each trial independently and for the combined data set. The number of PLS factors, correlation coefficient and predictive error obtained for models are shown in Table 2. R values for oil content and moisture were slightly lower and RMSECV was higher for model 1 (probably due to different conditions during spectral data acquisition)
12 On-tree data were used in model 1; data for 2 obtained in the laboratory The NIR prediction of fruit moisture and oil content in intact olives has been previously reported. León et al. (2003, 2004) obtained calibration models accurate enough to predict oil content and moisture with r values of 0.94 and 0.93 Cayuela et al. (2009) obtained variable predictive ability based on the sample presentation reference laboratory method. The best results provided r values of 0.83 and 0.88 and RER values of 7.8 and 11.8 for oil content and moisture. Using a different portable instrument, Cayuela and Pérez- Camino (2010) obtained r values of 0.78 and 0.76 and RER values of 10.6 and 10.3 for oil content and moisture respectively.
13 The different cultivars evaluated in this work showed differences in lipid synthesis both in total amount of oil formed and the period of time, as well as the evolution of fruit moisture during ripening (Figures 3 and 4). The prediction values for oil content and moisture by cultivar and sampling date were closely correlated with reference
14 Figure 1. Change in moisture and oil content during the ripening period. Each point represents the mean value of 24 samples (Trial 1) and 16 samples (Trial 2); error bars indicate the SE
15 Figure 2: Avg. Spectra and CoV of Olive fruit samples Trial 1 = Black; Trial 2 = Grey
16 Tables 1 and 2
17 Figure 3: Reference values v. Predicted values
18 Figure 4
19 Comparison of NIR and lab for oil and moisture
20 Rapid, reliable analysis can contribute to process and quality improvements in numerous ways. For example, Assessment of raw olive acceptability. If the olives have been collected from the ground rather than fresh from the tree, they may be of poor quality with high acidity and hence lower value. Measurement of water and oil content. These parameters determine the price of the olives, with those having a greater oil content commanding a higher price. Process optimization. After extracting the oil, the remaining pulp or by-product (called alperujo) should have only minimal oil content, typically around 2% or less. If the oil exceeds this level, a problem with the process is indicated.
21 Methodology Olive samples were milled to a paste and placed in a glass petri dish before analysis. Spectra were collected between and 4000 cm -1 at 16 cm -1 resolution, with an accumulation time of 30 seconds per sample. The olive samples were also analyzed for oil and water content following the customer s established laboratory procedures. Some of the measured spectra are shown in Figure 1. Typically for NIR spectra, the absorption features are broad and overlapped, although several prominent features can be assigned either to water or to organic C H modes in the oil.
22 Figure 1: A number of olive samples CH = oil bands
23 Building the Software Model Using Principal Components 1. Define materials and acquire spectra of known references. 2. Optionally, configure algorithm parameters and spectral preprocessing such as baseline correction 3. Calibrate the method. The software automatically builds the models and determines the acceptance thresholds. 4. Review the classification results (for example, see Figure 2). Any issues with the data or performance of the method will be flagged by the troubleshooting engine, allowing corrective action to be taken. 5. The validated method is then deployed as a workflow within the dedicated Analyzer module, allowing routine use of the method.
24 Quantitative Modeling of Oil and Water The oil and water content of the olives are key parameters for quality and both contribute to the NIR spectrum. The complex nature of NIR spectra sometimes makes it impossible to develop quantitative models based on the absorbance at a single wavelength. However, multivariate (Chemometric) methods such as partial least squares regression (PLS) still function in the presence of overlapping bands, and will allow models to be built. The olive spectra and properties determined by chemical analysis were loaded into software. One third of the data were designated as a validation set to verify the performance of the model. The spectra were pre-processed with first-derivative baseline correction.
25 Table 1: Properties of the olives for water and oil The calibration and validation results are summarized in Table 1 and Figure 3. The models use a modest number of latent variables and show good linearity and precision over the range of available samples. The standard errors of prediction (SEPs) were 1.5 % and 1.7 % for oil and water, respectively.
26 Experimental Results # PCs v. SEP Oil Water PLS Calibration PLS Validation
27 Analysis Scheme
28 What can be analyzed by NIR?
29 Techniques used for each assay
30 Results of Analyses Olive Leaves Soils Olive fruit (intact) Olive Paste
31 Instrument Specs Courtesy Unity Labs
32 Olive Oil Spectra
33 Calibrations for Fat and Moisture Fat N = number of samples RSQ = Correlation Coefficient (NIR vs. wet chem) Min = minimum reference value SECV = Cross Validation Error Moisture
34 Laboratory Measurements Courtesy Bruker Instruments
35 Spectra of EVOO, Soybean oil, EVOO adulterated w/50% soy, pure all natural OO
36 FT-NIR Analysis of Edible Oil Quality FT-NIR spectroscopy can help to: Identify the incoming oil Assess the quality of the oil Evaluate the frying capabilities Analysis: No sample preparation filling of 8mm disposable vials Temperature control at 50 C Measurement time: approx. 20 sec
37 Typical Performance for NIR Analysis to Check the Quality of Fresh Edible Oils Property Data Set Prediction Error Name Unit n Min Max RMSEP C16:0 Palmitic Acid % C18:0 Stearic Acid % C18:1 Oleic Acid % C18:2 Linoleic Acid % C18:3 Linolenic Acid %
38 Typical Performance for NIR Analysis to Check the Quality of Fresh Edible Oils Property Data Set Prediction Error Name Unit n Min Max RMSEP Gardner Color TFA Trans Fatty Acids % TFA low range % IV Iodine Value FFA Acidity %
39 FT-NIR Analysis of oils & fats in transflection Calibration development in progress Calibration from room temperature to 50 o C Lower but still sufficient accuracies Probably less possible components or parameters to be calibrated
40 Hand-Held Models are Available microphazir RX Handheld NIR Material Analyzer (a) and QualitySpec Trek ( nm) Hand-held Spectrometer (b) a b Courtesy Ahura [a] (Thermo) and ASDI [b]
41 Area NIR using Drones Whole fields or groves can be scanned
42 LandSat Images showing Productivity
43 And then there s dairy products
44 QC of Cheese by NIR Fat /- 0.3% Dry matter /- 0.5% Fat Dry Matter
49 Dry Matter and Fat in Cheese Dry Matter Fat Cheese Standards
50 Typical Instrument Spec Sheet
51 Conclusions Because of its versatility (many types of sample presentations), NIR is quite useful in food and agriculture With over 60 years of experience, there are many, many references for food applications available, either in a library or through instrument manufacturers Instruments range from sophisticated laboratory to rugged hand-held or instrument/vehicle mounted monitors The speed of analysis allows for may more samples to be (non-destructively) measured, assuring a good crosssample of a field or grove
/1 e Branch Pharmaceutical Keywords Near-infrared spectroscopy, lyophilized pharmaceuticals, water determination, Karl Fischer titration, loss on drying (LOD) Summary This Application Bulletin describes
Application Note 15: The use of a Near Infrared Transmission Analyser for Grape and Wine Quality Testing 1. Introduction 1.1 Background The use of spectroscopy in the wine industry is well established,
The Effects of Soil Moisture Content on Reflectance Spectra of Soils Using UV-VIS-NIR Spectroscopy I. Bogrekci, and W. S. Lee Agricultural and Biological Engineering Department University of Florida Gainesville,
INTERNATIONAL OLIVE COUNCIL COI/T.20/Doc. No 19/Rev. 3 February 2015 ENGLISH Original: ENGLISH Príncipe de Vergara, 154 28002 Madrid España Telef.: +34 915 903 638 Fax: +34 915 631 263 - e-mail: email@example.com
Overview The challenge to all baking companies in today s economy is to operate plants as efficiently as possible, with a focus on quality and keeping costs in check. With regulatory issues becoming more
Chemometric Analysis for Spectroscopy Bridging the Gap between the State and Measurement of a Chemical System by Dongsheng Bu, PhD, Principal Scientist, CAMO Software Inc. Chemometrics is the use of mathematical
FT-NIR SPECTROSCOPY application note Near-Infrared Spectroscopy in the Quality Control Laboratory of a Pharmaceutical Company An evaluation of a new technique for identification of raw materials and blinded
ANALYTICAL TOOL FOR RAPID ANALYSIS OF EDIBLE OIL MSc THESIS PROJECT CHEMICAL ENGINEERING AALBORG UNIVERSITY ESBJERG 1 Supervised by Lars Petersen Julius & Henrik Juhl. ANALYTICAL TOOL FOR RAPID ANALYSIS
Prediction of coffee cup quality based on near infrared spectra of green coffee beans: Implication for coffee value chain management Kassaye Tolessa 1, 2 and Pascal Boeckx 2 1 Jimma University 2 Isotope
Determining Acidity of Olive Oils I. Purpose/Objective: The purpose is to identify percent of oleic acids in different types of olive oils. Using a prepared sodium hydroxide solution with a known normality,
Application Note: 51594 FT-NIR for Online Analysis in Polyol Production Key Words Acid Number Ethylene Oxide FT-NIR Hydroxyl Value Polyester Polyols Abstract Hydroxyl value and other related parameters
Multivariate Chemometric and Statistic Software Role in Process Analytical Technology Camo Software Inc For IFPAC 2007 By Dongsheng Bu and Andrew Chu PAT Definition A system Understand the Process Design
NIR spectrometry Pavel Matějka NIR spectrometry molecular absorption/reflection spectrometry non-destructive method used in process analysis, QC/AC practical method that can replace more expensive, more
A White Paper from FOSS CHEMOMETRIC CORNER Qualification: Adulteration screening with NIR a case on skim milk powder Qualitative methods for adulteration screening are introduced and a case is presented:
Near Infrared Transmission Spectroscopy in the Food Industry Introduction: Near Infrared Spectroscopy is used in many industries including the pharmaceutical, petrochemical, agriculture, cosmetics, chemical
Spectrophotometric Analysis 2011 by L. Dickerson and H. Patterson Lab Type Greener Lab. Quantitative wet lab. Students work in pairs. Educational Objectives The student will determine the concentration
Spectroscopy II - Transmission, Absorption, Fluorescence, Beer s law and Scattering. Spectrophotometry and Fluorometry In this experiment you will use the Vernier SpectroVis Plus, a small, computer controlled
Olive_Oil_Spectrometry_v1c.docx Evaluating Olive Oil Quality through Absorbance and Fluorescence Spectrometry A spectrometric evaluation of olive oils. * 1.1 EXPERIMENTAL GOAL 1 OBJECTIVES In this experiment,
Physical Properties Analysis of Petroleum Products Using FT-NIR Darrell Kowalyk, A.Sc.T. CB Engineering LTD 515, 9945 50 Street Edmonton, AB, CA 1. Introduction Petroleum products have specifications based
QUANTITATIVE INFRARED SPECTROSCOPY Objective: The objectives of this experiment are: (1) to learn proper sample handling procedures for acquiring infrared spectra. (2) to determine the percentage composition
Caution Potassium permanganate solution is a skin irritant and may stain skin and clothing. Purpose To become familiar with using a spectrophotometer and gain an understanding of Beer s law and its relationship
Detection of trace contamination on metal surfaces using the handheld Agilent 4100 ExoScan FTIR Ensuring ultimate cleanliness for maximum adhesion Application Note Author John Seelenbinder Agilent Technologies,
MPA Multi Purpose Analyzer Innovation with Integrity FT-NIR Discover the Flexibility of FT-NIR Spectroscopy The MPA is the result of almost 40 years of experience in the engineering and production of FT-IR
Analytical Method Validation A. Es-haghi Ph.D. Dept. of Physico chemistry vaccine and serum research institute firstname.lastname@example.org http://www.rvsri.ir/ Introduction Test procedures for assessment of the
MEASURING PASTURE QUALITY IN THE FIELD: A CASE STUDY AT LIMESTONE DOWNS Ian Yule, Reddy Pullanagari and Pip McVeagh NZ Centre for Precision Agriculture, Massey University Private Bag 11 222, Palmerston
Near-Infrared Product Line from FOSS Cost-Effective, Efficient and Reliable FOSS: The Standard for Dedicated NIR Analysis FOSS is the world leading supplier of near-infrared (NIR) products and services.
Trans Fats What is a trans fat? Trans fatty acids, or trans fats as they are known, are certain fats found in such foodstuffs as vegetable shortenings, margarines, crackers, candies baked goods and many
AUGUST 2006 PRIMEFACT 231 Testing olive oil quality: chemical and sensory methods Dr Rod Mailer Principal Research Scientist (Oils), Pulse/Oilseed Genetics and Improvement, Wagga Wagga Clarrie Beckingham
Food Sci. Technol. Res., 19 (3), 393 398, 2013 Technical paper Rapid Determination of Water and Oil Content in Instant Noodles by Fourier Transform Near-Infrared Reflectance Spectroscopy Ying-guo Lü, Jie
Objectives: Keywords: Equilibrium Constant, ph, indicator, spectroscopy Prepare all solutions needed for measurement of the equilibrium constant for bromothymol Make the required spectroscopic measurements
Applications of Near Infrared Spectroscopic Analysis in the Food Industry and Research Written by Rolf Nilsson for the Food Safety Centre, Tasmanian Institute of Agricultural Research, University of Tasmania,
Automated wavelength and intensity calibration routines significantly improve accuracy of recorded spectra Wavelength calibration Calibration of dispersive spectral instruments has long been problematic
Spectrophotometric Determination of pka for Phenol Red This experiment uses instrumentation to accomplish quantitative analysis. You will get far more experience in this during CH427 if you are a Chemistry
Tutorial 4. Prediction with Near Infrared (NIR) Data This tutorial 1 shows how a validation sample can be used to compare the performance of different models and methods. In particular, we utilize Cookies
Spectrophotometry and the Beer-Lambert Law: An Important Analytical Technique in Chemistry Jon H. Hardesty, PhD and Bassam Attili, PhD Collin College Department of Chemistry Introduction: In the last lab
Estimating the Return on Investment for Raw Materials Identification Testing of Pharmaceuticals using Handheld Raman Analysers Moving raw material ID testing out of the laboratory and into the warehouse
COLOR.01-1 COLOR, SOLUTIONS (Spectrophotometric) PRINCIPLE SCOPE When white light passes through a colored solution, certain bands of the spectrum are absorbed allowing the transmitted portion to impart
EUROPEAN UNION GOVERNMENT OF ROMANIA GOVERNMENT OF THE REPUBLIC OF SERBIA Structural Funds 2007-2013 SPECTROPHOTOMETRY. PRINCIPLE AND APPLICATIONS As.dr.ing. ADRIAN EUGEN CIOABLA WORKSHOP 05 06 September
NIRCal Software data sheet NIRCal is an optional software package for NIRFlex N-500 and NIRMaster, that allows the development of qualitative and quantitative calibrations. It offers numerous chemometric
Quantitative work in HPLC Dr. Shulamit Levin Medtechnica www.forumsci.co.il/hplc Dr. Shulamit Levin, Medtechnica 1 Quantitative work in HPLC Dr. Shulamit Levin Medtechnica Data Handling Analytical Chemistry
RAPID MARKER IDENTIFICATION AND CHARACTERISATION OF ESSENTIAL OILS USING A CHEMOMETRIC APROACH Cristiana C. Leandro 1, Peter Hancock 1, Christian Soulier 2, Françoise Aime 2 1 Waters Corporation, Manchester,
A White Paper from FOSS Rapid methods for fat analysis in the meat industry By: Kristina Nedenskov Jensen, Chemometrician, Team Chemometric Development, FOSS and Per Waaben Hansen, Senior Chemometrician,
OPTIQUAD Application list January 2016 Table of contents 1 OPTIQUAD-M 4050 W to measure Fat, Protein, Lactose, Total Solids,... 2 2 OPTIQUAD-WW 4050 W to measure COD in industrial waste water applications...
VISIBLE SPECTROSCOPY Visible spectroscopy is the study of the interaction of radiation from the visible part (λ = 380-720 nm) of the electromagnetic spectrum with a chemical species. Quantifying the interaction
Spectroscopy 24 (2010) 629 639 629 DOI 10.3233/SPE-2010-0485 IOS Press Non-invasive blood glucose measurement by near infrared spectroscopy: Machine drift, time drift and physiological effect Simon C.H.
The MilkoScan FT2 Opportunity through innovation Dedicated Analytical Solutions Standardisation and sustainability Combining innovative technology with unrivalled experience in dairy analysis, the MilkoScan
Interactive PDF Version 1.0 Start Trust needs reliability quality needs ZEISS The real challenge is to offer a product with consistent quality using raw materials which are themselves subject to ongoing
NIRS DA1650 Oilseed Crush analyser Direct measurements of solid and liquid samples The NIRS DA1650 Oilseed Crush analyser helps oil crushers to gain vital process data on liquid and solid material with
Release: 1 RTE4029A Assess olive oil for style and quality RTE4029A Assess olive oil for style and quality Modification History Not applicable. Unit Descriptor Unit descriptor This unit of competency specifies
Measurement & Analytics Measurement made easy MB3600-PH Versatile FT-NIR analyzer for the life sciences and pharmaceutical industries Designed for QA/QC, research and development and at-line PAT applications
Analysis of Riboflavin in a Vitamin Pill by Fluorescence Spectroscopy** Objectives In this lab, you will use fluorescence spectroscopy to determine the mass and percentage of riboflavin in a vitamin pill.
野 49菜 茶 業 研 究 所 研 究 報 告 13 : 49 ~ 53 (2014) 49 Non-destructive Detection of Browning of the Inner Scales of Onions using Near-Infrared Spectroscopy Hidekazu Ito and Susumu Morimoto * (Accepted; October
EXPERIMENT 11 UV/VIS Spectroscopy and Spectrophotometry: Spectrophotometric Analysis of Potassium Permanganate Solutions. Outcomes After completing this experiment, the student should be able to: 1. Prepare
1 Name: Lab Instructor: PREPARATION FOR CHEMISTRY LAB: SPECTROSCOPY 1. Why do you think some solutions appear colorless? 2. Using the following data points, graph absorbance versus concentration (absorbance
Experiment 2 EFFECT F EXTRACTIN CNDITINS AND TITRIMETRIC ASSAY F ENZYME ACTIVITY Some enzymes are present in extracellular fluids, secretions and excretions; assay and purification of the enzyme may be
Types of Cooking Fats and s - Smoking Points of Fats and s Not all fats are the same. Following are some basics on the various types of fats to help you make sense of what is best for your own body. Saturated
CHEM 142 Experiment: Quantitative Analysis of Blue Dye in Commercial Drinks Using Visible Spectroscopy Introduction: Spectroscopy is a technique that uses the interaction of energy with a sample to perform
Original Article J. of Biosystems Eng. 37(6):398-403. (2012. 12) http://dx.doi.org/10.5307/jbe.2012.37.6.398 Journal of Biosystems Engineering eissn : 2234-1862 pissn : 1738-1266 Estimation of the Flavor
A 21 a - Whey Protein Nitrogen Index GEA Niro Method No. A 21 a Revised: November 2009 1. Principle The undenaturated Whey Protein Nitrogen Index (WPN) is a measure of the heat treatment applied to the
1 Lab 2 Biochemistry Learning Objectives The lab has the following learning objectives. Investigate the role of double bonding in fatty acids, through models. Developing a calibration curve for a Benedict
Measuring Protein Concentration through Absorption Spectrophotometry In this lab exercise you will learn how to homogenize a tissue to extract the protein, and then how to use a protein assay reagent to
Measurement & Analytics Measurement made easy MB3600 Versatile FT-NIR analyzer designed for your industry The most reliable FT-NIR specifically designed for QA/QC MB3600 FT-NIR spectrometer for your industry
PROTEIN STUDY I: Thermal Analysis of a Protein INTRODUCTION Most proteins are made from unique combination of 20 L-amino acids found in nature that define the protein sequence. Three of these essential
Radiometric Calibration of a Modified DSLR for NDVI Christian Taylor Carlson Center for Imaging Science, Rochester Institute of Technology ABSTRACT Silicon CCD detectors found in commercial DSLR cameras
EXPERIMENT: VISIBLE LIGHT SPECTROSCOPY In this experiment we will be investigating the color produced when light is absorbed by a transparent solution. The color a solution will appear to us can be predicted
September 9, 2003 On-Line Monitoring and Process Analytical Technologies Purpose Process analytical technologies (PAT) are systems which provide continuous on-line monitoring of critical quality parameters
1 Ultraviolet-Visible (UV-Vis) Spectroscopy Background Information Instructions for the Operation of the Cary 300 Bio UV-Visible Spectrophotometer See the Thermo OMNIC Help reference on page 49. Ultraviolet-Visible
Practical Environmental Measurement Methods Trace Gas Exchange Measurements with Standard Infrared Analyzers Last change of document: February 23, 2007 Supervisor: Charles Robert Room no: S 4381 ph: 4352
Reduce Energy Consumption through Plate Design in Thermo-Mechanical Pulp (TMP) Arvind Singhal HICO Product Manager J&L Fiber Services ABSTRACT Empirical models were developed to quantify the effects of
Continuous Emissions Monitoring Stack Testing Process Monitoring Quality Control Engine Exhaust Gas Monitoring Workplace Air Quality Monitoring Combustion Research Emergency Rescue Services Advanced Solutions
FTIR Instrumentation Adopted from the FTIR lab instruction by H.-N. Hsieh, New Jersey Institute of Technology: http://www-ec.njit.edu/~hsieh/ene669/ftir.html 1. IR Instrumentation Two types of instrumentation
2nd/3rd Year Physical Chemistry Practical Course, Oxford University 2.02 DETERMINATION OF THE FORMULA OF A COMPLEX BY SPECTROPHOTOMETRY (4 points) Outline Spectrometry is widely used to monitor the progress
Milk and Dairy FT-NIR Analyzers for QC in the Lab and Production Innovation with Integrity FT-NIR FT-NIR Spectroscopy for the Analysis of Milk and Dairy Products Bruker Optics FT-NIR analyzers for quality
Experiment Colorimetry: Quantitative Analysis with Light John R. Amend, PhD, Montana State University and Dale A. Hammond, PhD, Brigham Young University Hawaii The purpose of this experiment is to... LEARNING
RICE QUALITY AND PROCESSING Comparison of Milling Characteristics of Hybrid and Pureline Rice Cultivars S.B. Lanning and T.J. Siebenmorgen ABSTRACT Milling characteristics of two long-grain pureline and
Analytical Test Method Validation Report Template 1. Purpose The purpose of this Validation Summary Report is to summarize the finding of the validation of test method Determination of, following Validation
Introduction to Fourier Transform Infrared Spectrometry What is FT-IR? I N T R O D U C T I O N FT-IR stands for Fourier Transform InfraRed, the preferred method of infrared spectroscopy. In infrared spectroscopy,
Ch 100: Fundamentals of Chemistry 1 CALCULATING THE SIZE OF AN ATOM Introduction: The atom is so very small that only highly sophisticated instruments are able to measure its dimensions. In this experiment
Particle in a Box : Absorption Spectrum of Conjugated Dyes Part A Recording the Spectra and Theoretical determination of λ max Theory Absorption bands in the visible region of the spectrum (350-700 nm)
MB3600-HP12 / Measurement & Analytics Laboratory FT-NIR Heavy Oils Analyzer Crude oil, fuel oil, heavy oil upgrader unit feeds Adapted for crude oil, fuel oil and heavy oil upgrader unit feed applications
International Journal of Science, Environment and Technology, Vol. 5, No 4, 2016, 1850 1860 ISSN 2278-3687 (O) 2277-663X (P) NON-DESTRUCTIVE QUALITY ASSESSMENT OF CITRUS FRUITS USING FT-NEAR-INFRARED SPECTROSCOPY
SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF THE pk a OF A WEAK ACID I. Introduction The UV - VIS spectrophotometer will be used to determine the pk a of two indicator solutions, methyl red and bromocresol
Chem 131A: Absorbance of Riboflavin Purpose: The purpose of this experiment is to: 1) Familiarize the student with the use of the HP 8452 diode array spectrophotometer, 2) examine the limitations of the
DATES AND LOCATIONS 13-14 April 2015 Princeton Marriott at Forrestal, 100 College Road East, Princeton NJ 08540, New Jersey 16-17 April 2015 Hotel Nikko San Francisco 222 Mason Street, San Francisco, CA
Flour Milling Process Analysis Get more out of your production with High Resolution in-line analysis ProFoss Dedicated Analytical Solutions Get a clearer picture of your flour milling production with High