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During NIR 2019 conference, Gold Coast, Australia, a presentation upon a critical review of instrumentation and applications of handheld spectrometers was delivered during the plenary session held on Thursday morning, 19 September. Following the conference presentation, a vivid discussion flared up among the audience that equally involved academic scholars, industry representatives, as well as professionals who carry out every day in-the-field applications. Various aspects were raised connected with the emerged new generation of near-infrared instrumentation, with many individuals expressing their point-of-view on the merits and pitfalls of the miniaturized spectrometers. This vigorous dispute and exchange of impressions indicated that the community remains concerned about the applicability of such devices. That concern reflects the still relatively shallowly explored miniaturization versus performance factor, which can only be dismissed by focused feasibility studies with comparative analyses carried out on scientific-grade benchtop spectrometers. It is the aim of the present manuscript to summarize the discussed scientific content and to share the developed point-of-view with addition of our remarks.
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Original Article
Handheld near-infrared spectrometers:
Where are we heading?
Krzysztof B Be
c
1
, Justyna Grabska
1
, Heinz W Siesler
2
and
Christian W Huck
1
Abstract
During NIR 2019 conference, Gold Coast, Australia, a presentation upon a critical review of instrumentation and applications
of handheld spectrometers was delivered during the plenary session held on Thursday morning, 19 September. Following
the conference presentation, a vivid discussion flared up among the audience that equally involved academic scholars,
industry representatives, as well as professionals who carry out every day in-the-field applications. Various aspects were
raised connected with the emerged new generation of near-infrared instrumentation, with many individuals expressing
their point-of-view on the merits and pitfalls of the miniaturized spectrometers. This vigorous dispute and exchange of
impressions indicated that the community remains concerned about the applicability of such devices. That concern reflects
the still relatively shallowly explored miniaturization versus performance factor, which can only be dismissed by focused
feasibility studies with comparative analyses carried out on scientific-grade benchtop spectrometers. It is the aim of the
present manuscript to summarize the discussed scientific content and to share the developed point-of-view with addition of
our remarks.
Keywords
Handheld, portable, near-infrared instrumentation, application, evaluation, miniaturization versus performance
Introduction
It is commonly accepted to divide the fieldable spec-
trometers (i.e. deployable in-the-field, in contrast to
benchtop instrumentation, that is only applicable in a
laboratory setting) into transportable (e.g. deployable
on field while mounted in a car), portable in ‘suitcase’
format (>4 kg of total equipment weight) and hand-
held (<1 kg) ones.
1
These criteria suit the broadly
understood spectroscopy and spectrometry, including
e.g. elemental (atomic) techniques such as X-ray fluo-
rescence or laser-induced breakdown spectroscopy,
and even mass spectrometry (MS) or nuclear magnetic
resonance. When considering purely this sole factor,
NIR spectroscopy enjoys a fair advantage over several
other techniques in its compact technology. The most
recent years have brought ultra-miniaturized NIR
spectrometers to reality; such devices are either USB
powered or have own built-in battery, weigh less than
50 g and can be operated by an application installed on
a smartphone. The progress in miniaturization is
accompanied by software development aimed at ease
of use and suitability for operation by a non-expert
consumer community. Qualitative differences in the
level of sensor miniaturization achieved over the past
few decades in different fields of spectroscopy and
spectrometry are demonstrated in Figure 1.
While some other physicochemical methods of anal-
ysis reached similarly impressive levels of miniaturiza-
tion (e.g. fluorescence), NIR spectroscopy still offers
superior chemical specificity and applicability to a
broad range of sample types.
Searching for ‘portable near-infrared spectroscopy’
in ISI Web of Science database (https://apps.webof
knowledge.com) results in 239 publications since 2005
with increasing tendency (Figure 2(a)). The total
number of citations since 2005 is 2512 and from the
graph depicted in Figure 2(b) the highly increasing
number on a yearly basis can be deduced. From this
statistics, it is obvious that portable NIR spectroscopy
is an efficient and popular analytical chemistry tech-
nique. Current technological progress enables new
advance in miniaturization and there is no doubt that
1
Institute of Analytical Chemistry and Radiochemistry, CCB – Center for
Chemistry and Biomedicine, Innsbruck, Austria
2
Department of Physical Chemistry, University of Duisburg-Essen, Essen,
Germany
Corresponding author:
Christian W Huck, Institute of Analytical Chemistry and Radiochemistry,
CCB – Center for Chemistry and Biomedicine, Innrain 80/82, Innsbruck
6020, Austria.
Email: Christian.W.Huck@uibk.ac.at
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Figure 1. Various level of transportability of spectrometers. (a) Car-transportable GC–MS and long-path reflective FT-IR instrumentation,
(b) portable tunable diode-laser absorption spectroscopy (TDLAS) sensor mounted on a height-adjustable tripod, (c) Agilent 4300
Handheld FT-IR spectrometer and (d) miniaturized USB-powered NIR spectrometer Viavi MicroNIR Pro ES 1700. Source: Panel (a)
reproduced from Eckenrode
2
with permission under Elsevier Open Access license. Panel (b) reproduced from Zhang et al.
3
under CC-BY
4.0 license. Panel (c) reproduced from Hutengs et al.
4
under CC-BY 4.0 license.
Figure 2. Number of (a) publications and (b) citations of ‘portable near-infrared spectroscopy’ since 2005 according to Web of Knowledge
database.
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handheld NIR spectrometers belong to the next gener-
ation of analytical instrumentation. More and more
they are suitable to become a technology of choice
not only in industry but also in everyday life
applications.
There are several fields of application, which strong-
ly depend on maturing miniaturized spectroscopy as a
robust analytical tool – one of such fields is the agro-
food sector. European Commission stresses the prime
importance of food analysis for the public safety.
5
In
2015, the European Union opened a challenge on
‘health, demographic chance and wellbeing’ to reward
solutions, intended for the general public, that allow to
analyse and secure food quality including allergen rec-
ognition. Thus, in 2017 at the CeBIT Exhibition in
Hannover, Germany, three companies were awarded
and shared 1 million e: 800,000 efor the winner,
Spectral Engines (Spectral Engines Oy, Helsinki,
Finland), and 100,000 e, each, for the two runners-
up, SCiO (Consumer Physics, Tel Aviv, Israel) and
Tellspec (Tellspec Inc., Toronto, Canada). These
three instruments have in common that they are (i)
cheap, (ii) portable, (iii) handheld, (iv) applicable to
fulfil the requested aim and (v) rely on internet-of-
things and cloud computing to enable communication
and to facilitate their use. At this point, it must be
noted that these companies are not the only ones at
the market, which will be discussed later.
It is a natural course to promote new technologies
capable of improving everyone’s life. Miniaturized
NIRS is one of the first methods of analytical chemis-
try that reached out to the level of ordinary consumers.
There is of course a great and unique potential in such
a trend. However, it becomes apparent that some
attempts to take shortcuts appeared. The community
gathered at the International NIR 2019 conference has
become well aware of the hazard resulting from rapidly
increasing use of NIR sensors in general public, which
we will outline at the end of this article. However, first
it is necessary to summarize the essentials of portable
NIR spectroscopy, the instrumental basis and the
applicability of the latest generation of handheld NIR
spectrometers. Only on such background, the major
point of the community’s concern can be expressed
comprehensively.
The principles of the technology leading to
miniaturized NIR spectroscopy
Best strategy for discussing the design of handheld
NIR spectrometers is to divide up the optical spectrum
by detector technology.
1
Detectors
In the silicon detector region, we have low cost 1D
and 2D array sensors, and therefore multichannel
techniques are dominating. Complementary metal–
oxide–semiconductor (CMOS) technology has been
gaining steadily on charge-coupled device, mainly
driven by developments in smartphones and cameras,
with CMOS requiring lower power consumption.
1
At
wavelengths longer than approximately 1050 nm,
indium–gallium–arsenide (InGaAs) detectors dominate
and have substituted both Germanium (Ge) and lead
salt detectors (lead sulphide (PbS) and lead selenide
(PbSe)), with lead salt single point detectors being
still available on the market. For miniaturized NIR
spectrometers, cost and power consumption are
major drivers. Therefore, single element detectors are
preferred showing the disadvantage of being noisier
than standard InGaAs (1700 nm cut-off) and require
cooling.
Wavelength selectors
Micro-electro-mechanical systems (MEMSs; if com-
bined with micro-optics then referred to as micro-
opto-electro-mechanical systems, i.e. optical MEMS
or MOEMS) enable constructing micro-scaled complex
mechanical devices directly in-silicon using various
techniques established in semiconductor industry for
chip manufacturing. MEMS-based spectrometers
have been proposed almost 20 years ago, including
Fourier transform (FT) spectrometers. In the case of
the latter, the key component is a resonantly driven
micro-mirror, suspended on two long springs, and
driven by interlocking comb-structured electrodes.
About a decade ago, it was expected that MEMS spec-
trometers would be rapidly commercialized, but this
fact did not become true.
1
A key issue in this context
is the size of the optics and the ability of an MEMS
comb actuator to drive the moving mirror. The com-
mercially successful handheld FT-IR spectrometer
from Thermo Fisher Scientific uses a voice-coil and
piston-bearing scheme, with a 1.2 cm diameter
moving mirror, which is essentially a scaled-down ver-
sion of conventional laboratory interferometers.
Compared to mid-IR, NIR sources are brighter and
detectors have a higher specific detectivity D*, so that
the issue of mirror size is mitigated in NIR instruments.
Between 2017 and 2020, NeoSpectra, the commercial
arm of Si-Ware Systems, has launched several MEMS
FT-NIR sensors/scanners that are based on the same
optical principle (the first and the latest product are
shown in Figure 3(e)).
A Hadamard spectrometer is a multiplex device that
observes more than one wavelength at a time using one
or two masks instead of slits. This spectrometer offers
both a Jacquinot and a multiplex advantage. In a single
mask design spectrometer, light passes from the source
through a sample and onto the entrance slit of a spec-
trograph; it is dispersed by a grating. Then, the encod-
ing mask selects 50% of the resolution elements and
passes that light onto a single element detector. A typ-
ical mask is an array of zeros and ones. The position of
the zeros and ones on the mask changes and the detec-
tor is read out for each of these positions. Typically,
Be
c et al. 3
the mask uses a cyclic S-matrix sequence, in which each
row is obtained by shifting the previous row one posi-
tion to the left. At the end of data collection, a simple
matrix transform recovers the spectrum from the col-
lected data. A handheld NIR spectrometer, using an
MEMS chip as the Hadamard encoding device, has
been commercially available since 2007 (Figure 3(a)).
The Hadamard mask is a programmable MEMS dif-
fraction grating, originally developed as key element in
a programmable correlation spectrometer for remote
detection and is included in a spectrometer for
NASA to determine water content on the surface of
the moon.
Almost 20 years ago, the use of a digital light pro-
jector as a Hadamard mask was described. Texas
Instruments’ DLP is probably the most common
MEMS device. Texas instruments offers two NIR
engines: DLP NIRscan and DLP NIRscan Nano, as
evaluation modules (EVMs) (Figure 3(c)). To achieve a
micro-scaled programmable Hadamard mask, the DLP
devices use MEMS-based digital micromirror device
(DMD), while Thermo Fischer design microPHAZIR
employs MEMS piano-like diffraction grating in its
implementation of the Hadamard principle.
Application of Hadamard transformation enables con-
structing compact cost-effective spectrometers with a
single-pixel photodetector operating at any wave-
length. An MEMS-driven moving mask is used to
encode the light intensity at its imaging slit, which is
then collected by a single-pixel detector. Afterwards,
the spectrum is obtained through an inverse
Hadamard transform.
6
Fabry–Perot interferometers are playing a dominant
role as a wavelength separation technique since about
Figure 3. Principles of wavelengths selectors built into different handheld NIR spectrometers: (a) MEMS Hadamard mask – microPHAZIR,
Thermo Fisher Scientific, Waltham, USA; (b) LVF –MicroNIR Pro ES 1700, VIAVI, Santa Rosa, USA; (c) MEMS DMD – implementation
of DLP NIRscan module, Texas Instruments, Dallas, USA; (d) MEMS Fabry–Perot interferometer – NIRONE Sensor S, Spectral Engines,
Helsinki, Finland; (e) MEMS Michelson interferometer – NeoSpectra, Si-Ware, Cairo, Egypt; (f) MEMS Michelson interferometer with
a large mirror – nanoFTIR NIR, SouthNest Technology, Hefei, China. ADC: analog-to-digital converter; InGaAs: indium–gallium–arsenide;
MEMS: micro-electro-mechanical system.
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25 years. A Fabry–Perot filter consists of two mirrors,
either plane or curved, facing each other and separated
by a distance d. There are two basic versions: an inter-
ferometer, where d is variable, and an etalon, where d is
fixed. The condition for constructive interference with a
Fabry–Perot interferometer is that the light forms a
standing wave between the two mirrors, in which case
the optical distance between the two mirrors must equal
an integral number of half wavelengths of the incident
light. A Fabry–Perot interferometer may be also imple-
mented through MEMS-technology, e.g. as it is used in
NIRONE Sensor S device. Thus, MEMS technology
enables to implement as a fully programmable optical
filter in the form of a micro-scale module.
Linear variable filters (LVFs) are optical bandpass
filters that have been wedged in one direction; the
thickness of the coating is not constant across the fil-
ters. The transmitted wavelength varies linearly across
the filter. A LVF can be thought of as a scanning
Fabry–Perot filter which scans the position across the
filter. The typical range is one octave. Ocean Optics
mid-infrared spectrometer has a nine-reflection ATR
interface and covers the wavenumber range 1818–
909 cm
1
at 75 cm
1
resolution, with a nominal S/N
ratio of 300:1. For NIR spectroscopy, the LVF tech-
nology is of interest for the following reasons: It is low
cost, very compact, rugged, satisfying spectral resolu-
tion for real applications, and low power consumption.
For example, VIAVI has a line of handheld and pro-
cess spectrometers based on LVF and InGaAs array
(Figure 3(b)).
In the silicon detector region, a number of filter tech-
nologies compete: LVFs and mosaic, patterned, and dis-
crete filters. Consumer Physics released a spectroscopic
product called SCiO, with dimensions of 67.7 mm
40.2 mm 18.8 mm and weight of 35 g. It consists of a
43 photodiode array, with optical filters over the indi-
vidual pixels. The device has only 12 resolution elements
resulting in a rather poor spectral resolution of ca. 28 nm
across its working spectral region of 740–1070nm
(13,514–9346 cm
1
). The absorption properties of numer-
ous samples in the visible/short-wave NIR should also be
considered as a limiting factor here. It becomes apparent
that this design accepted a number of compromises in
order to achieve its compact factor and low cost.
The instrumental development continues, and
almost every year new concepts and products are intro-
duced to the market of miniaturized NIRS. Some of
the engineering principles are being refined as well. As
a good example serves here the concept of Michelson
interferometer implemented in MEMS technology. The
difficulties with maintaining stable operation of the
MEMS elements and the optical throughput could
have been challenged recently. This technology was
introduced as the final products in NIRONE sensors
from Spectral Engines and nanoFTIR NIR spectrom-
eter from SouthNest Technology. The latter is one of
the most recent miniaturized NIR sensors; it imple-
ments an MEMS Michelson interferometer with a
large mirror (in relation to MEMS chip) in order to
improve the light output. This device operates over the
entire NIR wavelength region (12,500–3846 cm
1
;
800–2600 nm), which stands in contrast to most other
handheld spectrometers including the earlier MEMS-
based portable NIR sensors (Table 1). According to
the information provided by the vendor, in addition
to a very broad working spectral region, the sensor
offers higher (although still inferior to benchtops) spec-
tral resolution of 6 nm at 1600nm, high SNR and rapid
scanning, while being far more compact (143 mm
49 mm 28 mm dimensions and 220 g weight) than
early MEMS spectrometers. However, how these
Table 1. Spectral regions and spectral resolution in which the discussed handheld NIR spectrometers operate.
Spectrometer
Spectral resolution
Spectral resolution
(at wavelength)
a
(nm)(nm) (cm
1
)
microPHAZIR (Thermo Fisher Scientific) 1596–2396 6267–4173 11
MicroNIR Pro ES 1700 (VIAVI) 908–1676 11,013–5967 12.5 (at 1000)
25 (at 2000)
SCiO (Consumer Physics) 740–1070 13,514–9346 Unknown
b
NIRscan (Texas Instruments) 900–1700 11,111–5882 10
NIRONE Sensors (Spectral Engines) 1100–1350 9091–7407 12–16
1350–1650 7407–6061 13–17
1550–1950 6452–5128 15–21
1750–2150 5714–4651 16–22
2000–2450 5000–4082 18–28
c
NeoSpectra (Si-Ware Systems) 1350–2500 7407–4000 16 (at 1550)
nanoFTIR NIR (SouthNest Technology) 800–2600 12,500–3846 2.5 (at 1000)
6 (at 1600)
13 (at 2400)
NIR: near-infrared.
a
‘At wavelength’ parameter listed if available in the data-sheet provided by the vendor.
b
SCiO presents to the operator interpolated spectra with 1 nm data-spacing, but the real resolution is considerably lower.
c
Depending on the sensor implementation/factory configuration.
Be
c et al. 5
promising data-sheet entries translate into the
real-world analytical performance remains to be eval-
uated through peer-reviewed research.
Application and in-depth evaluation of
performance characteristics of portable
NIR spectrometers
The contemporary benchtop spectrometers implement
a long-matured technology and over the past decades
those devices converged almost to a generic FT-NIR
design differing mostly by subtle nuances, at least from
the application point-of-view. In sharp contrast, vari-
ous technology concepts have been implemented into
portable NIR instrumentation in its vigorous develop-
ment over the last 10 years, as briefly outlined in the
‘The principles of the technology leading to miniatur-
ized NIR spectroscopy’ section. Through adoption of
innovative approaches and overcoming engineering
challenges, various handheld NIR sensors have been
brought into the market. However, the progressing
miniaturization unavoidably influenced the working
characteristics (e.g. sensitivity and S/N, spectral
region, spectral resolution) and the resulting analytical
performance of such spectrometers in relation to the
benchtop ones. Furthermore, the vendors often took
upon completely different engineering directions
when designing their portable instruments. Therefore,
several research groups recognized the need for per-
forming comprehensive research studies aimed at
establishing the applicability limits of handheld NIR
spectroscopy. As a good example, Hoffman et al.
7
explored the transferability of spectral sets, as well as
qualitative and quantitative calibrations that have been
developed thereof, between NIR spectroscopy in
benchtop and portable scenario. Miniaturized spec-
trometers demonstrate a particular potential for the
analysis of natural products outside laboratories. In
2017, for instance, Kirchler et al.
8
investigated the fea-
sibility of using portable NIRS to determine the con-
tent of the anti-oxidative active ingredients (rosmarinic
acid and closely related polyphenols) in medicinal
plants. They compared the working characteristics
and the final analytical performance of two handheld
spectrometers exemplifying distinctly different design
philosophies and levels of miniaturization. The study
was based on the comparison with a reference bench-
top NIR spectrometer (high-performance Bu
¨chi
Figure 4. Identification performance of different types of handheld NIR spectrometers for the recycling of polymer commodities. Top row:
3D score plots of the PCA calibration. Bottom row: fit of test samples () into calibration plots. PE: polyethylene; PET: polyethylene
terephthalate; PP: polypropylene; PS: polystyrene; PVC: polyvinyl chloride. Reproduced from Ref. 11.
6NIR news 0(0)
NIRFlex N-500) and supported by exhaustive
data-analytical tools, including hetero-correlated 2D
plots that highlighted the differences between the
NIR spectra measured on the three spectrometers.
Further exploration of the potential of miniaturized
NIR sensors in quantitative assessment of the antioxi-
dant capacity of natural-borne products was demon-
strated by Wiedemair and Huck.
9
In that case, the total
of three different miniaturized NIR devices was evalu-
ated towards their performance in assessing gluten-free
grains. Performance comparisons of different handheld
near-infrared spectrometers have been performed in
the demanding scenario of quantitative analysis of a
pharmaceutical formulation as well, e.g. by Yan and
Siesler.
10
However, the discussed problem is essential in var-
ious other fields of research and analysis. Yan and
Siesler
11
studied the identification performance of dif-
ferent types of handheld NIR spectrometers for the
recycling of polymer commodities, including polyeth-
ylene (PE), polypropylene, polyethylene terephthalate,
polyvinyl chloride (PVC) and polystyrene. Four differ-
ent handheld spectrometers based on different mono-
chromator principles were investigated: Si-Ware
systems, Spectral Engines NR 2.0 W; DLP NIRscan
Nano EVM, and Viavi MicroNIR Pro ES 1700. The
investigation clearly demonstrated that the spectra of
the most common polymer commodities provide suit-
able analytical measurement parameters for the correct
classification of unknown test samples. Upon perform-
ing principal component analysis (PCA), all polymer
classes could be sufficiently separated, excepting PE
and PVC measured by the Spectral Engines NR
2.0W spectrometer (Figure 4).
Wiedemair et al.
12,13
have tested the performance of
SCiO in comparison with Bu
¨chi NIRFLex N-500 for
the analysis of protein content in millet samples and
the fat content in cheese samples. As can be deduced
from Tables 2 and 3 they found that the analytical
performance of portable devices may considerably
vary between different scenarios. Although clearly infe-
rior in the former analytical problem (Table 2), in the
determination of fat content in cheese (Table 3), the
inexpensive SCiO sensor delivered the performance,
evaluated by statistical values, comparable to the
high-performing benchtop instrument. Several other
examples may be mentioned that clearly demonstrate
the interest that portable NIRS attracts for a variety of
applications, e.g. identification/authentication of tex-
tiles as a measure against counterfeit.
14
This gives pros-
pects for future evolution of applications of
miniaturized NIRS. However, the scientific and profes-
sional community understands that the performance
evaluation of miniaturized spectrometers in different
scenarios needs to remain a continuously explored
direction, as new devices keep appearing on the
market.
The conclusions from the community discussion
at NIR 2019 concerning portable NIRS
The continuous instrumental developments and appli-
cations observed over the last few years have launched
NIR spectroscopy into a new era of on-site and in-the-
field analysis. Generally, popularization of handheld
instruments brings a reasonable prospect for enabling
truly wide scale applications and high volume NIR
spectroscopic analyses in a wide spectrum of scenarios.
Seen through these lenses, a major transformation is
occurring that brings this tool closer to general public
in everyday use. Vendors have succeeded in consider-
ably reducing manufacturing costs of handheld NIR
Table 2. Performance of benchtop versus ultra-portable NIR spectrometer in millet analysis. Parameters of the established PLS-R models
for protein content (7–14% w/w in this sample set).
Spectrometer State of the grains PCs R
2
(CV) RMSECV (mg GAE/g) R
2
(TV) RMSEP (mg GAE/g)
NIRFlex N-500 Intact 4 0.953 0.365 0.940 0.467
Milled 6 0.985 0.223 0.920 0.479
SCiO Intact 5 0.876 0.601 0.814 0.806
Milled 5 0.8240 0.743 0.782 0.840
CV: cross-validated regressions; GAE: gallic acid equivalents; NIR: near-infrared; PC: principal component; PLS-R: Partial Least Squares Regression;
RMSECV: Root Mean Square Error of Cross Validation; RMSEP: Root Mean Square Error of Prediction; TV: test set-validated regressions.
Table 3. Performance of benchtop versus ultra-portable NIR spectrometer in cheese analysis. Parameters of the established PLS-R models
for fat content (9–36% w/w in this sample set).
Spectrometer State of the grains PCs R
2
(CV) RMSECV (mg GAE/g) R
2
(TV) RMSEP (mg GAE/g)
NIRFlex N-500 Intact 2 0.9726 1.5711 0.9431 1.8964
Grated 2 0.9930 0.7845 0.9913 0.7676
SCiO Intact 2 0.9801 1.2466 0.9838 1.1874
Grated 2 0.9838 1.0527 0.9940 0.8194
CV: cross-validated regressions; GAE: gallic acid equivalents; NIR: near-infrared; PC: principal component; PLS-R: Partial Least Squares Regression;
RMSECV: Root Mean Square Error of Cross Validation; RMSEP: Root Mean Square Error of Prediction; TV: test set-validated regressions.
Be
c et al. 7
spectrometers and made great efforts to make these
instruments suitable for everyday life applications by
a non-expert user community. However, caution
should be applied with the instruments advertised by
direct-to-consumer-companies.
The major gathering of the global NIR community
in Gold Coast, Australia in 2019 reflected that aware-
ness. The primary concern expressed by the experts in
the field was the following: miniaturized equipment still
requires comprehensive validation studies performed in
well-equipped laboratories. The need for closer coop-
eration between the vendors and these laboratories
would be beneficial for the adoption of new
technology.
Opportune conditions of the contemporary market
promote overly optimistic and aggressive marketing
strategies, which may bring the opposite effect. At
some point, the customers are likely to attempt to use
NIR spectroscopy in unrealistic scenarios and fail
therein. The resulting crisis of public trust in this tech-
nology may severely harm sales, and thus future devel-
opment. Such scheme can, however, be avoided if a
close cooperation between the vendor companies and
research laboratories is maintained. This summarizes
the ‘take home message’ from the NIRS community,
as resulted from the discussion upon the current state
and future path of miniaturized spectrometers at NIR
2019 conference (Gold Coast, Australia).
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) disclosed receipt of the following financial sup-
port for the research, authorship, and/or publication of this
article: This work was funded by the Austrian Science Fund
(FWF): M2729-N28.
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... Furthermore, no detailed investigations of the application of miniaturized spectrometers for direct on-site analysis of microplastics in solid state environmental matrices were made. In the recent decade, handheld portable spectrometers have become increasingly popular in NIR spectroscopy [34][35][36][37][38][39][40]. The physical principles underlying this technique make miniaturized and ultra-miniaturized sensors more feasible in terms of robustness of operation and cost-effectiveness compared to competing spectroscopic methods. ...
... Benchtop NIR spectrometers converged to a fairly standard design based on the Fourier-transform (FT) principle, implemented through Michelson or polarization interferometer. In sharp contrast, in the realm of portable spectrometers, a number of distinct optical concepts proved to be competitive, with FT-NIR spectrometers being less straightforward for successful implementation [35,36]. Currently, various sensor technologies are competing on the market, ranging from M(O)EMS (Micro-(Opto)-Electro-Mechanical Systems) based Hadamard and FT spectrometers, sensors implementing Digital Mirror Device (DMD), Fabry-Pérot filter based instruments, simple solutions implementing optical bandpass filters, to devices combining Linear Variable Filter (LVF) with sophisticated multi-element array detectors [35,36]. ...
... In sharp contrast, in the realm of portable spectrometers, a number of distinct optical concepts proved to be competitive, with FT-NIR spectrometers being less straightforward for successful implementation [35,36]. Currently, various sensor technologies are competing on the market, ranging from M(O)EMS (Micro-(Opto)-Electro-Mechanical Systems) based Hadamard and FT spectrometers, sensors implementing Digital Mirror Device (DMD), Fabry-Pérot filter based instruments, simple solutions implementing optical bandpass filters, to devices combining Linear Variable Filter (LVF) with sophisticated multi-element array detectors [35,36]. The diversity of the implemented solutions introduces large variations in the key characteristics of the available handheld and miniaturized spectrometers. ...
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Contamination by microplastics, a global environmental concern, demands effective monitoring. While current methods focus on characterizing the smallest particles, their low throughput hinders practical assessment. Miniaturized near-infrared (NIR) spectroscopy offers high-throughput capabilities and rapid on-site analysis, potentially filling this gap. However, diverse sensor characteristics result in significant differences among handheld NIR spectrometers. This study characterizes the analytical performance of these instruments for identifying soil microplastics, comparing miniaturized devices MicroNIR 1700ES, NeoSpectra Scanner, microPHAZIR, nanoFTIR-NIR, NIR-S-G1, and SCiO sensor against a reference benchtop instrument, the NIRFlex N-500. Detection of common polymers, ABS, EVAC, HDPE, LDPE, PA6, PMMA, POM, PET, PS, PTFE, and SBR, at low concentrations (0.75% w/w) was possible without sample preparation. Sensor selection proved crucial; FT instruments N-500 and NeoSpectra Scanner provided the most accurate analysis, while other handheld instruments faced various challenges. Covariance analysis, Principal Component Analysis (PCA), and mid-level data fusion revealed that miniaturized NIR spectrometers can successfully screen microplastics on-site. However, the ability of each sensor to discriminate certain groups of polymers strongly depends on its spectral characteristics. This study demonstrates the importance of sensor selection in the development of portable NIR spectroscopy for environmental monitoring of microplastics.
... relatively broad overtone and combination band spectra) compared to IRspectroscopy, NIR was reported especially useful for drug identification because of the non-invasiveness of the measurement, reduced detrimental effects of fluorescence and colorants, and the small sized, relatively cheap, and rapid sensor technology. [21][22][23][24][25][26][27] In earlier studies, our group demonstrated the applicability of a portable NIR-sensor for the reliable detection of cocaine, heroin, MDMA, methamphetamine, amphetamine, ketamine, the methylmethcathinone (MMC) isomers 2-MMC, 3-MMC, 4-MMC, and several adulterants in casework samples. [23,[27][28][29] The NIR-sensor used in these studies operated in the informative 1350 -2560 nm wavelength range and samples were analyzed through the bottom of a (NIR transparent) glass vial or through a plastic bag packaging. ...
... Fourier Transform Infrared Spectroscopy (FTIR) is widely used as a characterization tool in pharmacology and materials science. Extended InGaAs p-i-n detectors with a 2.6 µm wavelength cutoff are popular in Near-Infrared (NIR) instruments [1][2][3][4] used in the medical, food and dairy industry. The FTIR instrument works by Fourier transforming the detected optical signal to obtain the infrared spectrum. ...
Conference Paper
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The extended 2.6 µm InGaAs p-i-n detector discussed, can be operated under reverse bias with guaranteed linear behavior at higher operating voltages. We demonstrate improved detection of CO 2 gas and Low-Density Polyethylene using this detector.
... These tools offer rapid on-site prediction of forage quality, enabling nutritional management by detecting variations in forage nutritive values, including dry matter (DM) [2][3][4][5], Crude Protein (CP) [2][3][4][5][6][7][8][9][10], and fiber contents and properties, such as actual Neutral Detergent Fiber (aNDF) [2,[6][7][8][9][10], Neutral Detergent Fiber Digestibility (NDFD) [4,7,8], Acid Detergent Fiber (ADF) [2][3][4][6][7][8][9][10], Acid Detergent Lignin (ADL) [2,4,7,8], and in vitro Total Digestibility (IVTD) [4,[6][7][8]10]. By facilitating daily adjustments to animal diets based on accurate, real-time forage analysis, handheld NIR devices can significantly enhance the efficiency of feed utilization, reduce environmental impact, and improve the overall profitability and sustainability of dairy farming operations [3,11,12]. ...
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This study investigates the efficacy of handheld Near-Infrared Spectroscopy (NIRS) devices for in-field estimation of forage quality using undried samples. The objective is to assess the precision and accuracy of multiple handheld NIRS instruments—NeoSpectra, TrinamiX, and AgroCares—when evaluating key forage quality metrics such as Crude Protein (CP), Neutral Detergent Fiber (aNDF), Acid Detergent Fiber (ADF), Acid Detergent Lignin (ADL), in vitro Total Digestibility (IVTD)and Neutral Detergent Fiber Digestibility (NDFD). Samples were collected from silage bunkers across 111 farms in New York State and scanned using different methods (static, moving, and turntable). The results demonstrate that dynamic scanning patterns (moving and turntable) enhance the predictive accuracy of the models compared to static scans. Fiber constituents (ADF, aNDF) and Crude Protein (CP) show higher robustness and minimal impact from water interference, maintaining similar R2 values as dried samples. Conversely, IVTD, NDFD, and ADL are adversely affected by water content, resulting in lower R2 values. This study underscores the importance of understanding the water effects on undried forage, as water‘s high absorption bands at 1400 and 1900 nm introduce significant spectral interference. Further investigation into the PLSR loading factors is necessary to mitigate these effects. The findings suggest that, while handheld NIRS devices hold promise for rapid, on-site forage quality assessment, careful consideration of scanning methodology is crucial for accurate prediction models. This research contributes valuable insights for optimizing the use of portable NIRS technology in forage analysis, enhancing feed utilization efficiency, and supporting sustainable dairy farming practices.
... They rely on different and new solutions due to the engineering difficulties of miniaturisation aspects. Such diverse technologies cause non-uniform performance and require more device-specific optimizations [5,15,16]. ...
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Near-infrared (NIR) spectroscopy is a well-established analytical technique that has been used in many applications over the years. Due to the advancements in the semiconductor industry, NIR instruments have evolved from benchtop instruments to miniaturised portable devices. The miniaturised NIR instruments have gained more interest in recent years because of the fast and robust measurements they provide with almost no sample pretreatments. However, due to the very different configurations and characteristics of these instruments, they need a dedicated optimization of the measurement conditions, which is crucial for obtaining reliable results. To comprehensively grasp the capabilities and potentials offered by these sensors, it is imperative to examine errors that can affect the raw data, which is a facet frequently overlooked. In this study, measurement error covariance and correlation matrices were calculated and then visually inspected to gain insight into the error structures associated with the devices, and to find the optimal preprocessing technique that may result in the improvement of the models built. This strategy was applied to the classification of sweet and bitter almonds, which were measured with the three portable low-cost NIR devices (SCiO, FlameNIR+ and NeoSpectra Micro Development Kit) after removing the shelled, since their classification is of utmost importance for the almond industry. The results showed that bitter almonds can be classified from sweet almonds using any of the instruments after selecting the optimal preprocessing, obtained through inspection of covariance and correlation matrices. Measurements obtained with FlameNIR + device provided the best classification models with an accuracy of 98 %. The chosen strategy provides new insight into the performance characterization of the fast-growing miniaturised NIR instruments.
... Using NIRS for this purpose requires the development of calibration equations for each new material of interest, which involves extensive sample collection to capture the wide range of forage properties that exist. Therefore, calibration model development is needed for hand-held NIR spectrometers in the agriculture sector (Beć et al., 2020;. ...
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Technological advancements have made hand‐held near infrared (NIR) spectrometers more affordable and more accurate, creating interest in on‐farm application for forage management. The objective of this study was to evaluate the ability of a hand‐held NIR spectrometer to predict grass percentage within fresh alfalfa (Medicago sativa L.):grass mixtures. Forage samples were collected at a range of maturities and varieties during the 2021 and 2022 growing seasons from multiple locations in New York. Fresh forage samples were chopped, and pure species were combined into known proportions on a dry matter basis, resulting in 534 samples. Analysis was carried out on NIR spectra collected from a hand‐held NeoSpectra spectrometer using stationary and sliding scanning techniques. Development of calibration models was completed using partial least squares regression with cross validation. The best performing calibration model using absorbance was from the sliding scanning technique with preprocessing consisting of mean‐centering (R2 = 0.89, root mean square error of prediction [RMSEP] = 13.7%, and ratio of prediction to deviation = 2.53). A total of 84% of the samples were correctly classified when the grass component was lower than 40%. For samples with the grass component above 40%, a total of 94% of the samples were correctly classified. Correct sample classification is critical considering that the extension recommendation in New York is to reseed alfalfa fields when the grass component exceeds 40% of the sward on a botanical composition basis. This research demonstrates that NIR technology has potential to provide the agricultural industry with rapid, non‐destructive, and affordable information to allow farmers and consultants to predict grass proportion within alfalfa:grass fresh forage mixtures in real time.
Chapter
Near-Infrared (NIR) spectroscopy is a fast and non-destructive analytical technique widely used in food analysis. The latest advancements in miniaturization technology have led to the development of portable NIR spectrometers, which offer several advantages over traditional benchtop instruments, including ease of use, affordability, and flexibility in variety of analytical scenarios. This chapter provides an overview of the current state-of-the-art in portable NIR miniaturized food analytical systems, covering the design, performance, and applications of these systems. The fourth industrial revolution aims to deliver practical progress of new technologies, integrating improved autonomous miniaturized electronic devices and advancements in big data analytics. In the context of analytical systems, this progress provides tools to potentially revolutionize the way in which NIR spectroscopy can be used in food analytics, with more flexible and reliable analytical framework translating into enhanced manufacturing efficiency, reduced costs, and generally improved food product quality. This chapter highlights the key challenges and opportunities in using miniaturized NIR spectrometers in this field of application, including the intricacies related to these technologically diverse instruments as well as robust approaches to chemometric data modeling, which are decisive for ensuring reliable application of the portable analytical systems in food sector. These critical aspects are discussed in the context of case studies performed in the last few years, which represent diverse aspects of food analysis, including quality control, authenticity, safety, and traceability. The review concludes with a discussion on the future prospects of these systems and the emerging trends in the field. Overall, this chapter aims to provide insights into the current state-of-the-art in portable NIR miniaturized food analytical systems and to offer a comprehensive reference for researchers and practitioners working in this field.
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We present field deployment results of a portable optical absorption spectrometer for localization and quantification of fugitive methane (CH4) emissions. Our near-infrared sensor targets the 2ν3 R(4) CH4 transition at 6057.1 cm−1 (1651 nm) via line-scanned tunable diode-laser absorption spectroscopy (TDLAS), with Allan deviation analysis yielding a normalized 2.0 ppmv∙Hz−1/2 sensitivity (4.5 × 10−6 Hz−1/2 noise-equivalent absorption) over 5 cm open-path length. Controlled CH4 leak experiments are performed at the METEC CSU engineering facility, where concurrent deployment of our TDLAS and a customized volatile organic compound (VOC) sensor demonstrates good linear correlation (R2 = 0.74) over high-flow (>60 SCFH) CH4 releases spanning 4.4 h. In conjunction with simultaneous wind velocity measurements, the leak angle-of-arrival (AOA) is ascertained via correlation of CH4 concentration and wind angle, demonstrating the efficacy of single-sensor line-of-sight (LOS) determination of leak sources. Source magnitude estimation based on a Gaussian plume model is demonstrated, with good correspondence (R2 = 0.74) between calculated and measured release rates.
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The performance of a newly developed pocket-sized near-infrared (NIR) spectrometer was investigated by analysing 46 cheese samples for their water and fat content, and comparing results with a benchtop NIR device. Additionally, the automated data analysis of the pocket-sized spectrometer and its cloud-based data analysis software, designed for laypeople, was put to the test by comparing performances to a highly sophisticated multivariate data analysis software. All developed partial least squares regression (PLS-R) models yield a coefficient of determination (R2) of over 0.9, indicating high correlation between spectra and reference data for both spectrometers and all data analysis routes taken. In general, the analysis of grated cheese yields better results than whole pieces of cheese. Additionally, the ratios of performance to deviation (RPDs) and standard errors of prediction (SEPs) suggest that the performance of the pocket-sized spectrometer is comparable to the benchtop device. Small improvements are observable, when using sophisticated data analysis software, instead of automated tools.
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Full-text available
Mid-infrared (MIR) spectroscopy has received widespread interest as a method to complement traditional soil analysis. Recently available portable MIR spectrometers additionally offer potential for on-site applications, given sufficient spectral data quality. We therefore tested the performance of the Agilent 4300 Handheld FTIR (DRIFT spectra) in comparison to a Bruker Tensor 27 bench-top instrument in terms of (i) spectral quality and measurement noise quantified by wavelet analysis; (ii) accuracy of partial least squares (PLS) calibrations for soil organic carbon (SOC), total nitrogen (N), pH, clay and sand content with a repeated cross-validation analysis; and (iii) key spectral regions for these soil properties identified with a Monte Carlo spectral variable selection approach. Measurements and multivariate calibrations with the handheld device were as good as or slightly better than Bruker equipped with a DRIFT accessory, but not as accurate as with directional hemispherical reflectance (DHR) data collected with an integrating sphere. Variations in noise did not markedly affect the accuracy of multivariate PLS calibrations. Identified key spectral regions for PLS calibrations provided a good match between Agilent and Bruker DHR data, especially for SOC and N. Our findings suggest that portable FTIR instruments are a viable alternative for MIR measurements in the laboratory and offer great potential for on-site applications.
Article
A set of 42 millet (panicum miliaceum L.) samples was investigated for its protein content using standard Kjeldahl analysis and near-infrared spectroscopy. The performance of three handheld spectrometers was compared to a benchtop instrument. The used spectrometers operate in different regions of the NIR, which gives interesting insights into the applicability of each region. Additionally, semi-automated, consumer-oriented multivariate data analysis was compared to sophisticated data evaluation. The performance of the near-infrared instruments was compared using important statistical parameters of the established cross- and test set validated partial least squares regression (PLS-R) models. Milled and intact samples were analysed, in order to further evaluate the importance of homogeneity. The results showed that the benchtop spectrometer is capable of accurately analysing protein content of millet grains, with root mean square error (RMSEP) values for milled and intact grains of approximately 0.5%. Two PLS-R models of handheld instruments also yielded good results for milled grains with RMSEP values of about 0.6%. The semi-automated multivariate data analysis showed some drawbacks compared to standard data processing software. For intact grains, however, similar results could be achieved.
Article
Until very recently, handheld spectrometers were the domain of major analytical and security instrument companies, with turnkey analyzers using spectroscopic techniques from X-ray fluorescence (XRF) for elemental analysis (metals), to Raman, mid-infrared, and near-infrared (NIR) for molecular analysis (mostly organics). However, the past few years have seen rapid changes in this landscape with the introduction of handheld laser-induced breakdown spectroscopy (LIBS), smartphone spectroscopy focusing on medical diagnostics for low-resource areas, commercial engines that a variety of companies can build up into products, hyphenated or dual technology instruments, low-cost visible-shortwave NIR instruments selling directly to the public, and, most recently, portable hyperspectral imaging instruments. Successful handheld instruments are designed to give answers to non-scientist operators; therefore, their developers have put extensive resources into reliable identification algorithms, spectroscopic libraries or databases, and qualitative and quantitative calibrations. As spectroscopic instruments become smaller and lower cost, “engines” have emerged, leading to the possibility of being incorporated in consumer devices and smart appliances, part of the Internet of Things (IOT). This review outlines the technologies used in portable spectroscopy, discusses their applications, both qualitative and quantitative, and how instrument developers and vendors have approached giving actionable answers to non-scientists. It outlines concerns on crowdsourced data, especially for heterogeneous samples, and finally looks towards the future in areas like IOT, emerging technologies for instruments, and portable hyphenated and hyperspectral instruments.
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Textiles are extremely important materials for everyday life with a broad range of applications and properties. Due to the large variations in quality on the one hand and the increasing quality awareness and price consciousness of customers on the other hand, the availability of a simple tool for a rapid test of the correct identity of the purchased textile article would be a significant progress in customer protection. Miniaturization of near infrared spectrometers has advanced to the point where handheld instruments could provide reliable and affordable means to serve this purpose. One objective of the present communication was to scrutinize the identification and discrimination performance for textile materials for four real-handheld (<200 g) near infrared spectrometers based on different monochromator principles. The second focus was to show that in the near future these handheld instruments can be used by a non-expert user community to protect themselves against fraud in textile purchase situations. For this purpose, diffuse reflection spectra of 72 textile samples of synthetic and natural origin were measured. While in simple situations, test samples can readily be authenticated by visual inspection of their near infrared spectra only, for a more comprehensive identification of unknown samples principal component analysis in combination with soft independent modeling of class analogies was applied. In the present work, this approach provided a suitable analytical tool for the correct assignment of the investigated different types of textile materials. Moreover, the evaluation of the mean Euclidian distances in the principal component analysis score plots derived from the near infrared spectra of the textile classes under investigation allowed to compare the identification performance and discrimination capability of the different handheld instruments.
Article
Notwithstanding the first developments of miniaturized vibrational spectrometers more than a decade ago, only recently real handheld near-infrared (NIR) spectrometers (<200 g) became commercially available at significantly reduced costs compared to other portable systems. While on the one hand this development was driven by the consumer request for every-day-life applications by non-experts, on the manufacturer side it was supported by the availability and potential of new technologies such as micro-electromechanical systems (MEMS). In the present communication calibration spectra of a solid pharmaceutical formulation consisting of two excipients and three active ingredients, acetylsalicylic acid (ASA), ascorbic acid (ASC) and caffeine (CAF), have been measured with four handheld NIR spectrometers based on different monochromator principles and have subsequently been used to develop partial least squares (PLS) models for the quantitative determination of the active ingredients. Taking into account the instrumental and spectral peculiarities of the four instruments and the three analytes, respectively, the detailed analysis of the calibration parameters and the prediction accuracy for a test sample set then allowed to compare the performance of the different spectrometers for the analytical problem under investigation.
Article
The performance of three portable NIR spectrometers was compared by analysing the total antioxidant capacity (TAC) of different species of gluten-free grains. TAC is often used to evaluate the quality of foods and was determined using Folin-Ciocalteu measurements and used as reference data for establishing PLS-R models with NIR data. NIRS enables fast and non-invasive measurements. The microPhazir RX and the MicroNIR 2200 are broadly used in chemical and pharmaceutical industries, whereas SCiO is a pocket-sized, consumer-oriented spectrometer. The devices work in different regions of the NIR spectrum and their performances was compared using statistical parameters. 77 samples were measured and analysed using the software The Unscrambler X, as well as SCiO-Lab. All models established were cross- and test set validated. The multivariate data processing using The Unscrambler X yielded similar results as SCiO-Lab. The best model was established for non-milled samples measured with the MicroNIR 2200 and analysed using The Unscrambler X.
Article
For sustainable utilization of raw materials and environmental protection, the recycling of the most common polymers—polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polyvinyl chloride (PVC), and polystyrene (PS)—is an extremely important issue. In the present communication, the discrimination performance of the above polymer commodities based on their near-infrared (NIR) spectra measured with four real handheld (<200 g) spectrometers based on different monochromator principles were investigated. From a total of 43 polymer samples, the diffuse reflection spectra were measured with the handheld instruments. After the original spectra were pretreated by second derivative and standard normal variate (SNV), principal component analysis (PCA) was applied and unknown samples were tested by soft independent modeling of class analogies (SIMCA). The results show that the five polymer commodities cluster in the score plots of their first three principal components (PCs) and, furthermore, samples in calibration and test sets can be correctly identified by SICMA. Thus, it was concluded that on the basis of the NIR spectra measured with the handheld spectrometers the SIMCA analysis provides a suitable analytical tool for the correct assignment of the type of polymer. Because the mean distance between clusters in the score plot reflects the discrimination capability for each polymer pair the variation of this parameter for the spectra measured with the different handheld spectrometers was used to rank the identification performance of the five polymer commodities.