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Q: NIR Spectroscopy for grading of fruits ( Answered 5 out of 5 stars,   1 Comment )
Question  
Subject: NIR Spectroscopy for grading of fruits
Category: Science > Technology
Asked by: qfruits-ga
List Price: $100.00
Posted: 05 Apr 2004 00:51 PDT
Expires: 05 May 2004 00:51 PDT
Question ID: 325300
Describe what is NIR Spectroscopy, and how does it work for
grading/sorting of fruits? What are its uses and applications in
grading/sorting for quality of fruits, eg. by sweetness, firmness,
etc? What are its advantages and disadvantages over current grading
technologies used in packinghouses. Is this technology currently being widely
adopted and in use commercially? What is the research and NIRS
technology adoptation and application trends in the next 5 or so
years? What companies (US and/or international) provide
grading/sorting machines or systems that
utilize this technology and at what price range?
Answer  
Subject: Re: NIR Spectroscopy for grading of fruits
Answered By: larre-ga on 06 Apr 2004 13:21 PDT
Rated:5 out of 5 stars
 
Thanks for asking.

My research has located the following information that is responsive
to your queries.

======================================================================
Describe what is NIR Spectroscopy, and how does it work for
grading/sorting of fruits?
======================================================================

"Near-infrared light spans the 800 nm - 2500 nm (12,500 - 4000 cm-1)
range and is energetic enough to excite overtones and combinations of
molecular vibrations to higher energy levels. NIR spectroscopy
is typically used for quantitative measurement of organic functional
groups, especially O-H, N-H, and C=O. Detection limits are typically
0.1%."

"When a light beam of NIR falls on a fruit, a little of the incident
radiation is reflected off the surface as regular reflectance. The
remaining radiation transmits through the surface, encounters small
interfaces in the cellular structure, and scatters in all directions.
Some of the radiation will be scattered back to the surface and leave
the fruit in the vicinity of the point of incidence. The remaining
scattered light diffuses deeper into the fruit and may eventually
reach the fruit some distance away from the point of incidence. As the
NIR light travels through the fruit, a certain amount is absorbed by
various constituents of the fruit. The absorption varies with the
constituents. The absorbed energy is transformed into other forms of
energy. Part of the absorbed radiation may be transformed into other
forms of radiation. Thus, the radiation that leaves the surface of the
fruit may consist of regular reflectance, body reflectance,
transmittance, and emissions. The characteristics of the radiation
that leaves the surface of the fruit depend on the properties of the
fruit and the incident radiation. Thus, determining transmittance and
absorption characteristics of fruit can provide information related
to the internal quality of fruit."

Due to copyright rules and restrictions, I can only quote an excerpt
of this paper. Please click on the URL below to read the entire
section on NIR Spectroscopy (Sections 3.1, 3.2, 3.3, pages 129-130 of
this .PDF document. To read the document you will need the free Adobe
Acrobat reader (http://www.adobe.com/products/acrobat/readstep2.html)

Proceedings of 99 International Conference on Agricultural Engineering
Nondestructive Technology for Fruits Grading, by Ji Baoping
China Agricultural University, Beijing, China
http://www.lib.ksu.edu/depts/issa/china/icae/part4/fe127.pdf


"Near infra-red is a small part of the spectrum of light (700 - 2500
nm).  At one end of this spectrum are the high energy waves such as
x-rays and ultraviolet, while at the other end of the spectrum are the
low energy waves such as infra-red, micro waves and radio waves.  Near
infra-red is a part of natural sunlight and is generated by several
light sources, such as tungsten halogen car driving lights.  Near
infra-red is between the visible and the infra-red.  We see in the
visible spectrum (obviously!).  The colour of an apple in the visible
spectrum gives us information on a variety of pigments and chemicals
in the fruit, but we can not ?see? things that do not absorb visible
light (e.g. a sugar solution).  However, it happens that water, sugar,
acids and a range of other organic substances absorb near infra-red in
proportion to their concentration."

Near infra-red spectroscopy and its applications in agriculture.
http://www.dpi.qld.gov.au/food/10576.html


Abstract Excerpt: NON-DESTRUCTIVE QUALITY MEASUREMENTS OF APPLES BY
MEANS OF NIR-SPECTROSCOPY

"For long-term storage of apples, the determination of the optimal
picking time of apples is very important. In Belgium, the optimal
picking time is predicted every year based upon different quality
tests. Because many of these tests are either subjective (for example
colour and taste) or time consuming to measure (for example soluble
solids and acid determination), there is a demand for an objective,
fast and non-destructive assessment of the quality of the apples. The
objective of this contribution was to evaluate the use of NIR
reflectance spectroscopy as a tool to measure quality attributes of
the apples such as soluble solid contents, acidity, starch index and
firmness in the context of optimal picking time determination."

Peirs, A., Lammertyn, J., Nicolaï, B. and De Baerdemaeker, J. 2000.
NON-DESTRUCTIVE QUALITY MEASUREMENTS OF APPLES BY MEANS OF
NIR-SPECTROSCOPY. Acta Hort. (ISHS) 517:435-440
http://www.actahort.org/books/517/517_55.htm

Also see: Near-infrared Spectroscopy in Food Analysis. This is a
Google-cached HTML version or a .pdf document that is no longer
available in that format. You may need to cut and paste this link into
your browser's location bar.

Near-infrared Spectroscopy in Food Analysis
http://66.102.7.104/search?q=cache:ZFjBj6ccCUwJ:www.deanet.it/Vetrina_editori/Wiley%2520Site/EAC/pdf/A1018-W.PDF+NIR+Spectroscopy+fruit+grading&hl=en&ie=UTF-8


======================================================================
What are its uses and applications in grading/sorting for quality of
fruits, eg. by sweetness, firmness, etc?
======================================================================

NIR Spectroscopy has been used for the following tasks and applications:

-- Determination of total soluble solids in fruit

-- Analysis of soluble solids in  pineapple and dry matter in mango.

-- Non-invasive assessment of pineapple fruit sweetness

-- Melon brix measurement (sweetness)

-- Non-destructive sweetness (Brix) grading of stonefruit

-- Prediction of harvest soluble solids content in Mandarin Oranges

-- Prediction of harvest acidity in Mandarin Oranges 

-- On-tree evaluation of harvesting quality of mango fruit 

-- Determination of moisture in whole dates

-- Fresh date sorting 

-- Maturity determination of pre-harvested fresh Dates

-- Determination of avocado maturity 

-- Lycpene content estimation in tomatoes

-- Determination of soluble solid contents, acidity, starch index and
   firmness in apples

-- Measurement of firmness and sugar content of sweet cherries

-- Early detection of fungi damage in citrus

-- Assessment of sugar content [Sucrose in a Water-Cellulose Matrix]

-- Detect the presence of microorganisms on fruit surfaces

-- Assessment of Melon Soluble Solids Content

-- Sugar Content Prediction in Cherries

-- Monitoring of Organic Acids and Sugars in Fresh and Processed
   Apple Juice

-- Quality Segregation of Kiwifruit According to Total Fruit Solids


Reference Links for Above List:

http://www.uckac.edu/postharv/PDF%20files/1999-3.pdf
http://www.actahort.org/books/517/
http://www.agri.gov.il/AGEN/AgenInfo.html
http://www.agri.gov.il/AGEN/Reports/AvocadoNIR.html
http://www.agri.gov.il/AGEN/Reports/Shmilovich005.html
http://chemistry.surfwax.com/files/Spectroscopy.html
http://ift.confex.com/ift/2001/techprogram/meeting_2001.htm
http://www.montpellier.cemagref.fr/teap/projets/caporal/publications/pubglove.htm
http://www.nraes.org/publications/nraes97.html
http://www.spie.org/web/meetings/programs/pe00/confs/4203.html
http://www.sun.ac.za/foodsci/publicat.htm
http://www.systemtechnologie.com/en/sortierung/sortec/index.php3


Examples and Correlations between Research and Industry
-------------------------------------------------------

"Applying NIR to the measurement of moving fruit on a packing/sorting
line poses particular challenges. Apples are typically sorted at line
speeds of 6 to 8 fruit per second and line speeds of 10 fruit per
second can be necessary for some applications.

NEAR-INFRARED SPECTROSCOPY PROGRESS REPORT
Rich Ozanich, Berkeley Instruments Inc.
http://postharvest.tfrec.wsu.edu/PC2001O.pdf


======================================================================
What are its advantages and disadvantages over current grading
technologies used in packinghouses?
======================================================================

"Advantages of using imaging technology for sensing are that it can be
fairly accurate, non-destructive, and yields consistent results. The
application of machine vision technology will improve industry?s
productivity, thereby reducing costs and making agricultural
operations and processing safer for farmers and processing-line
workers. It will also help to provide better quality and safe foods to
the consumers."

Technology Innovation and Sustainable Agriculture
http://www.lib.ksu.edu/depts/issa/china/icets2000/c/c1.pdf

Technology and Automation: Can it Decrease Costs/Improve Returns? 
http://postharvest.tfrec.wsu.edu/PC2002L.pdf

The Perishible Food Industry - Ripe for eCommerce
http://www.internetcapital.com/network/progress/pdf/agribuys-Ripe2.pdf

Cost Effective Real-Time Multi-Spectral Digital Video Imaging
http://www.hitech.com.sg/rl/multispectral/pdfs/CEMS_Overview.pdf


======================================================================
Is this technology currently being widely adopted and in use commercially?
======================================================================

Non-invasive Fruit Sampling

"In Michigan, a major apple-producing state, most packinghouses
currently employ digital imaging to sort fruit by size or to identify
externally defective apples that need to be culled."

Science News
http://www.sciencenews.org/articles/20020817/food.asp

Eleos Packhouses

"Although it appears that everything at Eleos is hi-tech, there are
also simple systems which give a great return on their investment. An
example of this is software development to continually monitor the
reject rates of individual people on the sorting tables. This system
contributed to one of the lowest sorting-table reject rates in the
industry for the 2002 season.

Future developments with research and technology are all focused on
maximising grower returns and improving shareholder returns. For this
there are three critical performance areas: one is to extract the
maximum number of Class 1 trays from each bin of fruit; the second is
inventory management with new technologies like NIR and in-line
firmness assessment being extremely useful in segregating fruit by
quality and supplying fruit at the optimum time; and the third is
looking at market requirements and planning for added value services
to niche markets..."

"For example, during the 2002 season Eleos automatically recorded the
dry matter content of more than 50 million fruit pieces that passed
over graders using Near Infra Red technology ? the industry norm being
a 30 fruit sample taken from each orchard maturity area."

Eleos Packhouses and Cookstores
http://www.eleos.co.nz/news.php

Zespri's
--------

"Zespri's "moving target" policy for setting Taste Zespri's DMI
underlines the reality that dry matter is as much a factor of seasonal
conditions as it is of orchard management practices. As such, Zespri's
policy of fixing each season's Taste Zespri DMI according to growing
conditions distances the programme from consumer quality demands.
Instead, Taste Zespri is a mechanism which rewards individual growers
for the quality of their fruit when compared with their neighbour's.
As such, Taste Zespri is a mechanism for redistributing returns,
rather than reflecting any additional value being paid for by the
consumer.

Another concern has been Zespri's fruit sampling regime whereby DMI is
determined by sampling 30 fruit from each maturity area. Our in-line
measuring of each fruit's dry matter content using Near Infra Red
(NIR) technology shows that maturity areas are not always homogeneous
for dry matter distribution. This underlies the fact that the industry
norm of only sampling 30 fruit to determine the DMI of a whole
maturity area creates such a degree of statistical error that fruit
grading and the subsequent premium payment system are of an arbitrary
nature."

http://www.eleos.co.nz/news.php


A remote acceptance probe and illumination configuration for spectral
assessment of internal attributes of intact fruit.

Abstract:

"Near infrared spectroscopy can be employed in the non-invasive
assessment of intact fruit for eating quality attributes such as
soluble solid content (SSC). Rapid sorting is dependent on a suitable
non-contact geometry of fruit, light source and detector assembly,
optimized for a given fruit commodity. An optical system was designed
with reference to distribution of SSC and light penetration into
rockmelon fruit. SSC of mesocarp tissue was not significantly
different over the greater part of the proximal-distal axis of the
fruit, particularly in the vicinity of the fruit equator. There was
also no consistent variation in SSC of mesocarp tissue with respect to
radial position of sampling. Mesocarp SSC was higher (~3% w/v) closer
to the seed cavity. The optical sampling system was therefore designed
to assess an equatorial position on the fruit. Light penetrating a
rockmelon fruit was empirically assessed to be diffuse at a depth of
<15 mm from the fruit surface. Signal decreased in an exponential
proportionality with depth into the fruit, but was still detectable at
depths in excess of the seed cavity of rockmelons. A partial
transmittance optical design was employed, with a collimated light
source interrupted by a central light stop, and a detector viewing the
shadowed region of the sample. This system did not physically contact
the sample."

Spectral Assessment of Intact Fruit
http://www.iop.org/EJ/abstract/-featured=jnl/0957-0233/11/12/304


======================================================================
What is the research and NIRS technology adoptation and application
trends in the next 5 or so years?
======================================================================

Abstract - Machine Vision

"In this presentation, current applications of machine vision in
agriculture are reviewed. The current status of research and
development of multispectral and hyperspectral imaging systems for
modern food engineering are discussed. An example of applications of
hyperspectral imaging technology for detection of defects and
contamination on apple surfaces of 4 different cultivars is given.
Future trends of technology applications are discussed."

Abstract
University of Kansas Library
U.S. Department of Agriculture
http://www.lib.ksu.edu/depts/issa/china/icets2000/c/c1.pdf


"Many applications using machine vision technology have been developed
in agricultural sectors such as land-based and aerial-based remote
sensing for natural resources assessments, precision farming,
postharvest product quality and safety detection, classification and
sorting, and process automation. This is because machine vision
systems not only mimic human eyes in recognizing size, shapes, color,
and texture of objects, but also provide numerical attributes of the
objects or scene being imaged. Besides seeing objects in the visible
color region, the machine vision system is also able to see these
objects in invisible light such as ultraviolet, near-infrared, and
infrared. The information received from objects in the invisible light
region can be very useful in determining preharvest plant maturity,
disease, or stress states. It is very useful in determining plant and
vegetable variety, maturity, ripeness, and quality. It is also useful
in detecting postharvest quality and safety such as defects,
composition, and functional properties, diseases and contamination of
plants, grains and nuts, vegetables and fruits, and animal products.

Introduction
USDA Agricultural Research Service
http://www.lib.ksu.edu/depts/issa/china/icets2000/c/c1.pdf


"Future Trends - Machine vision technology has the potential to become
very important to the agricultural industry. The uses of the machine
vision technology for land-based and aerial-based remote sensing for
natural resources assessments, precision farming, postharvest product
quality and safety detection, classification and sorting, and process
automation will become routine in the near future."

Future Trends
FUTURE TRENDS OF MACHINE VISION TECHNOLOGY FOR AGRICULTURAL 
APPLICATIONS, By Yud-Ren Chen
http://www.lib.ksu.edu/depts/issa/china/icets2000/c/c1.pdf


"Pilot testing of integrated systems offering these [non-invasive
physical] sampling capabilities may begin in a couple years, [Renfu]
Lu says. He envisions packinghouses eventually incorporating them for
the evaluation of every piece moving along the line. With the
appropriate calibration, he predicts, the technology should extend
such remote evaluation of similar sensory characteristics to cherries,
peaches, pears, and even oranges.

Fruit: Toward Visual Taste Tests
http://www.sciencenews.org/articles/20020817/food.asp

U.S Department of Agriculture
Research Project: Development of Nondestructive Sensing Technologies
2003 Annual Report 

1. What major problem or issue is being resolved and how are you resolving it?

Poor, inconsistent fruit quality is a top concern for the fruit
industry. Currently, apples are graded based on multiple quality
factors such as size, color, shape, maturity or firmness. Many modern
packing facilities can sort and pack fruit, based on color and size or
weight, into as many classes as needed. However, sorting fruit for
internal quality, especially firmness, sugar content, and acid, is
still a great technological challenge. Fresh fruit should be free from
surface blemishes, bruises, and internal defects. Sorting for defects
is still performed by human inspectors. This has become a major source
of labor costs for the fruit packer and also causes the fruit
variability problem because human inspectors are prone to error and
inconsistency due to fatigue and emotional factors. The research
project at East Lansing, Michigan is focused on developing new sensors
and sensing technologies to nondestructively assess postharvest
quality (firmness, sugar content, acid, etc.), and detect defects
(bruises and surface blemishes), of apples and cherries. Research is
being conducted to understand the interaction of light with fruit
tissue and its relationship with fruit firmness and other quality
attributes. Near-infrared spectroscopy (NIRS) and hyperspectral and/or
multispectral imaging techniques are being investigated for predicting
internal quality of apple and cherry fruit. Hyperspectral imaging is
also being investigated for detecting bruises and other defects of
apples and for detecting pits and pits fragments in cherries.

2. How serious is the problem? Why does it matter?

U.S. fruit industry is losing competitive advantages in both domestic
and international markets because of intense foreign competition,
higher labor costs and scarcer domestic labor resources, and
increasing consumer demand for better fruit. The health of the
industry depends on adoption of new and/or improved technologies to
maintain and enhance fruit quality, improve operation efficiency, and
reduce production costs. Nondestructive sensing of fruit internal
quality is key to assuring and maintaining the quality and
wholesomeness of individual fruit delivered to the consumer. This
research will lead to the development of new sensing technologies that
would allow individual fruit to be inspected for internal and external
quality before they are shipped to the market. This would help the
industry provide consistent, superior quality fruit for the consumer,
increase consumer satisfaction and confidence, and improve industry
competitiveness and profitability.

3. How does it relate to the National Program(s) and National Program
Component(s) to which it has been assigned?

This research relates to National Program 306 Quality and Utilization
of Agricultural Products (100%) within the program component Quality
Characterization, Preservation, and Enhancement, of which the mandate
is to develop efficient technologies and improved or new equipment to
maintain or enhance product quality during harvest, storage,
transport, and marketing and new technology for product grading to
provide rapid, accurate, and reproducible information on quality. This
research is intended to develop nondestructive sensing technologies
for assessing, maintaining, and insuring the postharvest quality of
tree fruits.

4. What were the most significant accomplishments this past year?

A. Single most significant accomplishment during FY 2003:
Nondestructive sensing of apples and other fruits for such important
quality attributes as firmness and sugar content will allow the fruit
industry to deliver superior, consistent fruit to the marketplace,
better meet consumer demands for fruit quality, and thus improve
industry competitiveness and profitability. Research was performed in
the USDA-ARS facilities at Michigan State University, East Lansing,
Michigan to develop a light-based sensing technique for assessing and
sorting apple fruit for firmness and sugar content. An improved
multispectral imaging system that acquires light scattering profiles
from apple fruit for selected wavelengths simultaneously was assembled
and tested with different apple varieties. The system gave good
predictions of apple fruit firmness and sugar content, which will lead
to the development of a prototype real-time sensing system for sorting
and grading apple fruit for internal quality.

B. Other significant accomplishment(s), if any: The hyperspectral
imaging system has been improved and refined for more efficient and
faster acquisition of light scattering images from apple fruit over
the spectral region between 500 nm and 1000 nm. New computer
algorithms were developed for extracting spectral and scattering
profiles from hyperspectral scattering images of apple fruit. Both
spectral and scattering profiles were analyzed for improving
predictions of fruit firmness and sugar content. Scattering profiles
for different wavelengths were analyzed and optimal ratio combinations
of scattering profiles were determined over the spectral region of 500
nm and 1000 nm for two apple varieties, Red Delicious and Golden
Delicious.

In addition, different light beam designs (i.e., size and incidence
angle) were studied to determine the optimal light beam configuration
for both multispectral and hyperspectral imaging systems. Optimal
neural network parameters (i.e., neurons and epochs) were determined
for predicting fruit firmness and sugar content from the scattering
images acquired from the multispectral and hyperspectral imaging
system.

C. Significant activities that support special target populations: none.

5. Describe the major accomplishments over the life of the project,
including their predicted or actual impact.

Near-infrared spectroscopy (NIRS) was used for measuring quality of
cherry fruit and good predictions of firmness and sugar content were
obtained. The research provided a prototype for developing a NIR
sensor for grading and inspecting cherries and other small fruits for
firmness and sugar content. One important finding from NIRS studies of
apple fruit is that light pathlength differences can be useful for
predicting fruit firmness. Based on this finding, a new hypothesis was
proposed that light absorption is related to the chemical properties
of apple fruit whereas light scattering is more closely associated
with the structural or textural properties. This lead to the
development of a novel optical technique of using hyperspectral and
multispectral imaging to measure light scattering and absorption for
predicting fruit firmness and sugar content. Research has demonstrated
that this approach is promising for predicting fruit firmness. A
multispectral imaging system and a hyperspectral imaging system were
assembled and tested and computer algorithms were developed and
optimized for analyzing light scattering images. Good predictions of
fruit firmness and sugar content were obtained from both systems.
Further research is under way to develop a prototype real-time sorting
system and a low-cost, portable sensing device for assessing and
grading apple fruit for firmness and sugar content.

Near-infrared hyperspectral imaging was also investigated for
detection of bruises on apples. Useful spectral regions and
appropriate spectral resolutions were identified. Computer algorithms
were developed to identify bruises of mixed ages and up to 94%
classification accuracy was obtained. This study provided critical
information on developing an imaging system for automated detection of
fruit surface defects including bruises.

In collaborating with Michigan State University agricultural
engineering researchers, a firmness tester based on measurement of
bioyield force has been developed and tested, which showed a good
correlation with the standard destructive firmness measurement tester.




ARS Project - Development of Non-Destructive Sensing Technologies

6. What do you expect to accomplish, year by year, over the next 3 years?

FY 2004:

1) A prototype multispectral imaging system will be assembled and
tested, with the integration of computer algorithms, for real time
detection of the internal quality and condition of apples.

2) A low-cost, portable multispectral imaging device will be assembled
and tested for measuring apple fruit firmness and sugar content.

3) The method and technique for determining the optical properties of
apple fruit in the visible and near-infrared region will be assessed
experimentally. A radiation transfer model will be considered for
describing light scattering and absorption in apple fruit.

4) Hyperspectral imaging will be evaluated as a means to detect pits
and pit fragments in cherries.

FY 2005:

1) Refining and testing of the multispectral imaging system will be
carried out. The system will be extensively tested with fruit samples
obtained from different geographical locations and different variety
sources. Upon successful evaluation of the system, partnership with
the industry will be pursued for commercial application of the
technology

2) Modification and testing of the portable multispectral imaging
device will be conducted with different varieties of apples.

3) A prototype imaging spectroscopy system will be assembled for
measurement of the optical properties of apples and prediction of
fruit firmness and sugar content. An appropriate mathematical model
and computer algorithms will be developed for determining the
absorption and scattering properties of apple fruit.

4) A hyperspectral imaging system and computer algorithms will be
developed and tested for detecting cherries with and without the pit
or pit fragments.

FY 2006:

1) Numerical models and computer algorithms will be developed to study
the absorption and scattering of light in apple fruit. The absorption
and scattering properties of apple fruit and their changes due to
fruit pre- and post-harvest factors/conditions will be evaluated.

2) A further version of low cost, portable device will be developed,
with the integration of computer program for orchard and laboratory
measurements.

3) A prototype cherry pit detecting system will be constructed and
tested for its capability for real-time detection of pits and pit
fragments in cherries.

Development of Non-destructive Sensing Technologies
http://www.ars.usda.gov/research/projects/projects.htm?ACCN_NO=404600&showpars=true&fy=2003

<--- Continued Below --->

Clarification of Answer by larre-ga on 06 Apr 2004 13:21 PDT
======================================================================
What companies (US and/or international) provide grading/sorting
machines or systems that utilize this technology and at what price
range?======================================================================

At present, in most packaging and production implementations, NIR
spectroscopy components are added to current equipment. The following
companies are representative of vendors selling NIR components or
systems. Pricing depends upon so many factors that vendors require
very extensive specifications in order to quote prices. A number of
implementations are one-of-a-kind, pricing highly dependent on the
scale of the project.


Sentronic - For optical chemical process analysers and OEM-sensors
Sentronic is a customer specific manufacturer. Process spectrometer
for the chemical surface and concentration analysis based on UV/VIS,
NIR and Raman diode array spectroscopy.
 
Sentronic
http://www.sentronic.net/


NIRSolutions® by Büchi - Offers comprehensive tools for NIR
Spectroscopy. "The Buchi on-line solution includes the spectrometer
N-419 and the NIRLine N-420 Process Control Module. Combined with
Buechi recommended components like multiplexer and probes, reliable
systems for the continuous measurement of process parameters can be
implemented. With the pertinent software the NIRLine PLC can be
configured according to customer requests. The PLC is connected easily
via one of its various interfaces to the Process Control System
(PCS)."

Buchi
http://www.nirsolutions.com/?pid=adw


GetSpec - Meeting point for modular optical spectroscopy. "Evaluation
Kit for NIR and MIR applications in process or research and
development Novel uncooled infrared detection systems for multi-gas
analysis and process control in the wavelength range of 1 - 40
microns."

GetSpec
http://www.getspec.com/


Axiom Analytical - "Sampling Hardware: The Company's immersion probes,
flow cells and multiplexed sampling systems operate with spectroscopic
analyzers from all manufacturers. They provide unmatched robustness
and spectroscopic performance for mid-infrared, near infrared,
UV-visible, and Raman analysis."

Axiom Analytical
http://www.goaxiom.com/


Vision System for Sorting and Grading - "Agricultural produce is
characterised by a large variation in quality attributes. Colour,
size, appearance, shape, ripeness, texture, existence of diseases and
defects, etc., determine how attractive a fresh product is for the
consumer. Many products are sorted before being sold. The main
objectives of sorting are to reject bad products and to divide batches
into more uniform quality groups. Doing so, sorting adds value to
products.

Many of the visual quality attributes can be measured objectively with
a camera system. If a colour camera is used as an image sensor for the
computer, visualisation can be compared with human eye inspection. The
main advantages of automation are savings of labour costs and
objective quality evaluation. Integration with a mechanical system
facilitates transportation of produce at high speed, full-sight
inspection and physical rejection of products."

Vision System for Sorting and Grading
http://www.agrotechnologyandfood.wur.nl/base/BaseFrames.asp?lan=en&TpcId=4


Foss - "Providing a fast and objective analysis of grapes, GrapeScan?
helps you make the right decisions about your raw material. It also
provides a fast and accurate basis for payment of deliveries."

Foss
http://www.foss.dk/c/p/solutions/products/showprodfamily.asp?prodfamilypkid=85&languageId=1&stepselect=1




Additional Resources/References
----------------------------------------------------------------------

Review of Process and Non-invasive Near-Infrared and Infrared
Spectroscopy: 1993?1999
http://bsel.ist.utl.pt/2004/News/Review%20of%20Process%20and%20Non-invasive%20Near-Infrared%20and%20Infrared%20Spectroscopy-%201993-1999.pdf

Papers of Yang Tao
http://www.agnr.umd.edu/users/bioreng/papers.htm

site:www.s-a-s.org nir fruit
://www.google.com/search?q=site:www.s-a-s.org+nir+fruit

W. F. McClure, Publications
http://www.bae.ncsu.edu/people/faculty/mcclure/publicat.html

Davies Publications since 1997
http://wwwexternal.scri.sari.ac.uk/SCRI/upload/PubsHVDavies.pdf

Instrumentation and Sensors for the Food Industry
http://www.chipsbooks.com/instrum.htm



Search Strategy/Google Search Terms
======================================================================

nir system integrator
disadvantages "nir technology" "fruit packing" "fruit production"
advantages "nir technology" "fruit packing" "fruit production"
benefits "nir technology" "fruit packing" "fruit production"
NIR Spectroscopy fruit grading
NIR Spectroscopy fruit trends OR "future trends"
NIR spectroscopy applications
NIR spectroscopy research
NIR spectorscopy vendors
NIR sensors

I hope you find this information useful. If you have questions about
the links provided, please, feel free to ask for clarification.

Best regards,

---larre

Request for Answer Clarification by qfruits-ga on 06 Apr 2004 15:38 PDT
Hi,

Thank you for the thorough research. I'd like to clarify my question
regarding the price range. I understand that it depends on many
factor, but I was hoping for some sort of estimate, say what's the
lowest end (minimum) costs, and what's the high end (complete system)
costs, and maybe a mid-range, typical installation costs. Also, I am
talking about commercial machines for packinghouse volumes, not
machines for lab environment.

Thanks

Clarification of Answer by larre-ga on 06 Apr 2004 16:18 PDT
I realize that you are speaking of packing house and production
facility installations. At this time, these are components of larger
systems, installed by system integrators. Spectoscopy sensors are yet
not "built in" to normal processing equipment, except on a custom
basis. This machinery is purchased from a dealer or manufacturer, who
might outsource the NIR portion, or use a local engineering firm to
install that portion of the equipment. Packing houses for the most
part are simply buying add-on sensors and PCs for analysis then custom
engineering them to their own process. I have not been able to locate
a manufacturer of packing house equipment that has a standard model
combining sensors/processing station.

I will however, attempt to get price range. The companies I have
called so far would not even quote a price range without knowing the
specific application. I admit I am not knowledgeable enough to put
together a "typical setup" that could, in turn, generate a "typical
bid".

 I will query the marketing departments, in hope that they will have
educational information available.

---l

Clarification of Answer by larre-ga on 06 Apr 2004 17:08 PDT
My apologies. Thanks for challenging me. I've located a manufacturer
that offers an NIR spectroscopy sensor (PowerVision) in combination
with their sorting and grading machinery.

Aweta
http://www.aweta.nl/index.html

You'll need to select language, then from the left menu, select
FRUITS. From the drop down menu, you may review processing machinery
for various fruits. PowerVision is the option that adds NIR
Spectroscopy.

I will see if I can locate a local or regional distributor and obtain
pricing information for you.

---l
qfruits-ga rated this answer:5 out of 5 stars
Sorry for the late rating. Anyway, thanks a lot for your help. I'll
try to contact some of the vendors that you listed.

Comments  
Subject: Re: NIR Spectroscopy for grading of fruits
From: dion1234-ga on 18 Apr 2004 21:40 PDT
 
Taste Technologies Ltd is a New Zealand based company that provides
NIR equipment. The systems can be integrated to almost all sizers,
providing an on-line grading system. They currently supply customers
throughout the world. The website is:www.tastemark.com

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