The Influence of the Presence of Borax and Nacl on Water

sensors

Letter The Inﬂuence of the Presence of Borax and NaCl on Water Absorption Pattern during Sturgeon Caviar (Acipenser transmontanus) Storage

Massimo Brambilla 1 , Marina Buccheri 2, Maurizio Grassi 2 , Annamaria Stellari 1, Mario Pazzaglia 3, Elio Romano 1 and Tiziana M. P. Cattaneo 2,* 1 Consiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria–CREA–Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Milano, 43–24047 Treviglio (Bergamo), Italy; [email protected] (M.B.); [email protected] (A.S.); [email protected] (E.R.) 2 Consiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria–CREA–Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via G. Venezian, 26–20133 Milano, Italy; [email protected] (M.B.); [email protected] (M.G.) 3 Agroittica Lombarda S.p.A., Via Kennedy, 25012 Calvisano Brescia, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-02-239-557-212

Received: 10 November 2020; Accepted: 10 December 2020; Published: 15 December 2020

Abstract: Sturgeon caviar quality relies not only on the perfect dosage of the ingredients but also on the long sturgeon breeding cycle (about 12–15 years) and the exact timing of the egg extraction. For the improvement and the promotion of Italian caviar, the development of an analytical system dedicated to fish products, and caviar, in particular, is fundamental. The use of near-infrared spectrometry (NIRS) technology is auspicious. The aquaphotomics approach proved to be an adequate analytical tool to highlight, in real-time, the differences in caviar quality stored with, or without, borax as a preservative. Seventy-five sturgeon caviar (Acipenser transmontanus) samples underwent spectral NIR characterization using a microNIR1700 in the 900–1700 nm range. Data processing was carried out according to the literature. Tenderometric and sensory analyses were also carried out in parallel. The results suggest that a process line under strict control and monitoring can result in high-quality caviar without any other preservative than salt. The challenge of producing caviar without any potentially-toxic preservatives could now be a reality. NIR spectroscopy and aquaphotomics can be, in the future, non-invasive methods to monitor the whole production chain.

Keywords: NIR spectroscopy; aquaphotomics; caviar quality; portable instrumentation; sustainability; qualitative determination; food chain monitoring

1. Introduction Sturgeon caviar (from now on, called caviar) is a food product whose preparation appears extremely simple, requiring sturgeon eggs and salt. However, its quality relies not only on the perfect dosage of the ingredients, but also on: (i) the long sturgeon breeding cycle (about 12–15 years), and (ii) the exact timing of the egg extraction. Various techniques establish how to process sturgeon roe to caviar, as [1] reported. These processing techniques significantly impact product composition and quality and, thereby, marketability [2–5]. The preparation processes differ mainly on the salt content (NaCl), ranging from 3.2% to almost 11.8% among the producers. The high salt content results in dehydration, which increases the concentration of lipids and proteins in a linear pattern. Nowadays, sturgeon breeding in Lombardy (Italy) is mainly oriented to caviar production and has attained global manufacturing leadership in this field. The Lombard caviar production exceeds 40 tons/year, 90% of which represents the export for a value of about 15,000,000 euros. The appearance

Sensors 2020, 20, 7174; doi:10.3390/s20247174 www.mdpi.com/journal/sensors Sensors 2020, 20, 7174 2 of 7 on the international market of products from countries with high production capacities and lower costs could represent a new obstacle for Lombard businesses and livestock. Not being able to compete, in terms of price, it is necessary to continue investing in product quality and innovation. Given the high costs of the raw materials, the caviar industry must offer an end product with the following features: (i) stable quality; (ii) sensory attributes well characterized; and (iii) adequate documental support from reliable and low-cost methods of investigation. Salting is considered the more delicate phase in light of the high variability of the roe. Compared to the wild one, the farming environment reduces the eggs’ variability; however, the inclusion in the regional context of new species of sturgeon and new farming conditions makes it difficult to calibrate the correct salting mixture for each circumstance. Italian business experiences have shown that different production batches, subjected to the same dosage, could result in different salt contents of the final product. During the product’s maturation, variable loss of brine occurs at varying of the salt mixture. For the improvement and the promotion of Italian caviar, the development of an analytical system dedicated to fish products and caviar is fundamental, and the use of near-infrared spectrometry (NIRS) technology is auspicious, not only for the quality of the final product, but also as an innovative control tool along the production line [6,7]. The European Union and the national legislations still allow some boron compounds (i.e., E284: boric acid-E285: sodium tetraborate) as preserving agents in caviar; however, recently, the Codex Alimentarius and some national regulations have pushed towards a borax-free product. Although the EFSA (European Food Safety Authority), in its latest scientific opinion of 2013 [8], confirmed the limited use of borax for caviar preparation, the international market prefers a borax-free product. Many countries have already prohibited the use of borax. The realization of a product free of preservatives improves its safety and its end quality. Among the different NIR technologies and procedures, several papers have reported the use of aquaphotomics as an immediate indicator of biological systems changes through the study of water pattern modification in the 1300–1500 nm NIR region [9]. This work aims to study the effect of borax on caviar storage, to develop a borax-free product with suitable organoleptic characteristics throughout the shelf life. The aquaphotomics approach was chosen as an adequate analytical tool to identify borax as a preservative in caviar during the curing process. A rapid and objective method that allows the discrimination of the two treatments (salt+borax and borax-free) is a prerequisite to improve caviar’s quality and safety at the end of the production chain. Fast detection and measurement of the borax presence would be intrinsically part of an innovation process of total quality control.

2. Materials and Methods Materials: Spectra from seventy-five caviar (Acipenser transmontanus) samples were collected from Agroittica Lombarda S.p.A. (Calvisano, Brescia, IT), an Italian caviar factory known at the international level. Spectra were collected at scheduled times: before treatment (“no salt” samples) and after treatment, with 3.5% NaCl or a mixture of 3.5% NaCl + 0.04% sodium tetraborate at the time 0 and after 90, 150, and 210 days of storage. On the same samples, the tenderometric analysis was carried out using a Texture Analyzer TA 32 XT PLUS II (Stable Micro Systems Ltd., Godalming, Surrey GU7 1YL, UK), modified to test individual eggs at the constant temperature of 0 ◦C. The values of egg consistency and the distance and time the instrument took from the beginning of the measurement to the instant of the egg breakage were measured on every single egg (30 eggs/sample). NIR measurements took place directly on caviar samples before the packaging in jars (50 g each, time 0), and afterwards, at the opening of the jars during storage. Visual inspection detected the potential presence of molds, and a panel of 20 expert panelists carried out the sensory analysis on the caviar samples at the end of the storage period at the factory headquarter. Spectroscopy and Chemometrics: A portable MicroNIR 1700 spectrometer (VIAVI Solutions Italia SRL, Monza, Italy) was used for the spectra collection in the range of 900 to 1700 nm (200 scans; 128 points; three replicates; reflectance mode, resolution: 6.0 nm; signal/noise ratio—S/N: 25,000). The spectral data, converted in absorbance, were preprocessed according to [10] to verify the suitability Sensors 2020, 20, x FOR PEER REVIEW 3 of 8 spectralSensors 2020 data,, 20, 7174converted in absorbance, were preprocessed according to [10] to verify the suitability3 of 7 of the holistic aquaphotomics approach in highlighting the differences arising between borax and no borax samples during the storage. Excel spreadsheet (Office 365, Microsoft Corporation, Redmond, WA,of the USA) holistic and aquaphotomics MINITAB 17.0 approach statistical in software highlighting (Minitab the diInc.,fferences State College, arising between PA, USA) borax were and used no forborax data samples processing. during Repeatability the storage. between Excel spreadsheet replicates was (Offi verified.ce 365,Microsoft Aquagrams Corporation, were built up Redmond, at time 0WA, and USA) during and storage MINITAB (at 90, 17.0 150, statistical and 210 software days after (Minitab the jar Inc., packaging), State College, both for PA, “borax” USA) were and used“no borax”for data sets processing. of samples. Repeatability Principal component between replicates analysis (PCA) was verified. was applied Aquagrams (95% of were confidence built up level) at time to the0 and whole during dataset, storage selecting (at 90, the 150, wavelength and 210 days region afters from the jar1300 packaging), to 1550 nm. both Outlier for “borax” detection and in “nothe multivariateborax” sets of space samples. was carried Principal out component using the Mahalanobis analysis (PCA) distance was applied criteria: (95% observations of confidence falling level) above to thethe critical whole distance dataset, selectingwere labeled the wavelengthas outliers and regions removed. from The 1300 principal to 1550 component nm. Outlier analysis detection allowed in the themultivariate extraction space of useful was carriedinformation out using from the the Mahalanobis dataset, the distanceexploration criteria: of its observations structure, and falling the global above correlationthe critical distanceof the variables. were labeled Subsequently, as outliers using and removed. the most Theuncorrelated principal componentfrequencies analysis(i.e., 1342, allowed 1374, andthe extraction1426 nm), ofthe useful dataset information underwent from linear the discrimi dataset,nant the explorationanalysis (LDA) of its [11], structure, one of andthe most the global used classificationcorrelation of procedures, the variables. to assess Subsequently, the discrimina usingtion the power most uncorrelated of the aquaphotomics frequencies approach (i.e., 1342, between 1374, boraxand 1426 and nm), no borax the dataset samples. underwent The dataset linear underwent discriminant splitting analysis into (LDA) two datasets: [11], one a of calibration the most used set, containingclassification 2/3 procedures, of the observations to assess the discriminationchosen randomly, power and of thea validation aquaphotomics set, approachmade up between of the remainingborax and 1/3. no borax samples. The dataset underwent splitting into two datasets: a calibration set, containing 2/3 of the observations chosen randomly, and a validation set, made up of the remaining 1/3. 3. Results and Discussion 3. Results and Discussion Some examples of the quality of the collected spectra of sturgeon caviar samples are shown in FigureSome 1. examples of the quality of the collected spectra of sturgeon caviar samples are shown in Figure1.

Figure 1. Example of caviar spectra. Each color represents a NIR acquisition (sample). Figure 1. Example of caviar spectra. Each color represents a NIR acquisition (sample). The ranges of the variability of the main constituents of the analyzed samples are reported in TableThe1. It ranges is essential of the to variability consider thatof the the main composition constituents can varyof the by analyzed individual samples constituent are reported by about in Tablefive percentage 1. It is essential points, to within consider the that same the species, composition except can for thevary ash by content. individual These constituent data were by already about fivepresented percentage during points, the 6th within Italian the Symposium same species, NIRItalia except 2014 for the [12 ],ash as content. preliminary These results. data were already presented during the 6th Italian Symposium NIRItalia 2014 [12], as preliminary results. Table 1. Concentration ranges of the main constituents of the matrix [12]. Table 1. Concentration ranges of the main constituents of the matrix [12]. Constituent (%) Min Max Average SD Moisture Constituent52.10 (%) min 58.53 max average 55.46 SD 1.43 Protein Moisture22.48 52.10 27.0658.53 55.46 24.75 1.43 1.38 Fat Protein13.64 22.48 18.46 27.06 24.75 16.41 1.38 1.32 Ash 1.31 4.20 3.47 0.71 Fat 13.64 18.46 16.41 1.32 Ash 1.31 4.20 3.47 0.71 The aquaphotomics approach was applied for the first time in the present work as a holistic approachThe aquaphotomics to point out whether approach borax’s was addition applied aforffects the the first caviar time storage in the present and the qualitywork as of a theholistic final approachproduct. Figureto point2 reports out whether the repeatability borax’s addition of measurements; affects the caviar the aquagrams storage and of the the samples quality beforeof the final and after salt (NaCl) addition are shown (three replicates each).

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Sensorsproduct.product.2020 ,Figure20 Figure, 7174 2 2reports reports the the repeatabilityrepeatability of measurements; the the aquagrams aquagrams of of the the samples samples before before4 of 7 and after salt (NaCl) addition are shown (three replicates each). and after salt (NaCl) addition are shown (three replicates each).

FigureFigure 2. Aquagrams2. Aquagrams of of samples samples before before (red(red lines),lines), and after (blue (blue lines), lines), salt salt (NaCl) (NaCl) addition—three addition—three replicatesFigurereplicates 2. each.Aquagrams each. of samples before (red lines), and after (blue lines), salt (NaCl) addition—three replicates each. DiffDifferenceserences highlighted highlighted on on the the aquagrams aquagrams betweenbetween salted and no no salted salted samples samples are are due due to tosalt’s salt’s hydrationhydrationDifferences power, power, highlighted mainly mainly resulting resulting on the in aquagramsin an an increase increase between of of absorbance absorbance salted in and in the the no NIR saltedNIR range range samples from from 1400 are 1400 due to to 1500 to1500 salt’s nm. nm. Results suggested continuing the study of the influence of preservatives (NaCl, borax) by using Resultshydration suggested power, continuingmainly resulting the study in an of increase the influence of absorbance of preservatives in the NIR (NaCl, range borax) from by1400 using to 1500 the the aquaphotomics approach, due to the perfect fitting of absorbance curves among replicates aquaphotomicsnm. Results suggested approach, continuing due to the the perfect study fittingof the ofinfluence absorbance of preservatives curves among (NaCl, replicates borax) (Figure by using2). (Figure 2). the Figureaquaphotomics3 reports theapproach, aquagrams due of to the the borax perfect and fitting no borax of samples.absorbance curves among replicates Figure 3 reports the aquagrams of the borax and no borax samples. (Figure 2). Figure 3 reports the aquagrams of the borax and no borax samples.

Figure 3. Caviar aquagrams during ripening in borax (on the left) and no borax (on the right) samples. Figure 3. Caviar aquagrams during ripening in borax (on the left) and no borax (on the right) samples. The red lines (bright and dark) refer to acquisitions at 0 and 90 days; the green lines represent samples The red lines (bright and dark) refer to acquisitions at 0 and 90 days; the green lines represent samples at 150 days, and the blue lines the samples at 210 days from packaging. at 150 days, and the blue lines the samples at 210 days from packaging. Figure 3. Caviar aquagrams during ripening in borax (on the left) and no borax (on the right) samples. In Figure3, the aquagrams built up during caviar storage are reported. The absorbance of samples TheIn red Figure lines 3,(bright the aquagramsand dark) refer built to acquisitionsup during atca 0viar and storage90 days; arethe greenreported. lines representThe absorbance samples of containing salt (NaCl) or salt + borax showed similar profiles along the storage time in the spectral samplesat 150 containingdays, and the salt blue (NaCl) lines orthe salt samples + borax at 210 showed days from similar packaging. profiles along the storage time in the rangespectral from range 1340 tofrom 1512 1340 nm. to Significant1512 nm. Significant differences differences in absorbance in absorbance values were values only were noted only at noted 210 daysat of storage210In days Figure for of bothstorage 3, the sets foraquagrams of both samples, sets builtof suggesting samples, up during suggesting that ca theviar use thatstorage of the borax usearedoes ofreported. borax not introducedoes The not absorbance introduce significant of anomaliessamplessignificant containing that anomalies may resultsalt that (NaCl) in may quality orresult salt deterioration in + qualityborax showed deterioration during similar the during preservation profiles the preservationalong of caviar. the storage of caviar. time in the spectralApplyingApplying range from the the PCA 1340PCA to toto the1512 the whole wholenm. Significant datasetdataset pointedpointed differences out the in absorbancepossibility to values to discriminate discriminate were only between between noted at samples210samples days treated of treated storage with with saltfor salt both (NaCl) (NaCl) sets and and of those samples,those treated treat suggestinged withwith saltsalt that + borax,borax, the useas as shown shownof borax in in Figure Figuredoes 4.not4 . introduce significant anomalies that may result in quality deterioration during the preservation of caviar. Applying the PCA to the whole dataset pointed out the possibility to discriminate between samples treated with salt (NaCl) and those treated with salt + borax, as shown in Figure 4.

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Figure 4. Principal component analysis (PCA) applied to the whole caviar sample set in the aquagram range: NaCl salt (square), borax (circle), a = short time of storage; b = long time of storage; c = whole borax set.

Figure 4.FigureThePrincipal score 4. Principal plot, component constructed component analysis usinganalysis (PCA) PC1 (PCA) vs. applied appliedPC2 (98.9% to to the the whole of whole explained caviar caviarsample samplevariance), set in inshowed the the aquagram aquagram that, along range: NaClthe salt PC1range: (square), (83.1% NaCl boraxofsalt explained (square), (circle), borax variance a = short(circle),— time95% a = short of storage;confidence time of bstorage;= level),long b time no= long borax of time storage; and of storage; borax c = whole samplesc = whole borax were set. discriminatedborax set. with positive score values associated with the borax set. In comparison, the PC2 (15.8% Theof scoreexplained plot, variance) constructed seemed usingto split PC1the observatio vs. PC2ns (98.9%into two ofgroups, explained depending variance), on the length showed of that, The score plot, constructed using PC1 vs. PC2 (98.9% of explained variance), showed that, along along thestorage, PC1 (83.1%with lower of score explained values variance—95%associated with longer of conﬁdence conservation level), time. no borax and borax samples the PC1 (83.1% of explained variance—95% of confidence level), no borax and borax samples were were discriminatedFigure 5 shows with the positive primary score wavelengths values associatedresponsible for with PCA the results. borax set. In comparison, the PC2 discriminatedThe PCA withapplied positive to the score whole values dataset associated enabled with identifying the borax borax’s set. In presencecomparison, on the the 1PC2st principal (15.8% (15.8% of explained explained variance) variance) seemed seemed to split to the split observatio the observationsns into two groups, into twodepending groups, on the depending length of on the component. Based on the absorbance differences in the 1400–1430 nm wavelengths range, such a length ofstorage,result storage, is withascribable with lower lower to score the firstvalues score overtone valuesassociated bands associated with of the longer OH with conservationstretching longer vibration conservation time. of water time. molecules. This Figurefinding5Figure shows follows 5 shows the NaCl primary the andprimary borax’s wavelengths wavelengths different responsible responsiblehydration capacities,for for PCA PCA results. results.resulting from their chemical st structuresThe PCA that applied differ in to their the wholepotential dataset interactions enabled with identifying water molecules. borax’s presence on the 1 principal component. Based on the absorbance differences in the 1400–1430 nm wavelengths range, such a result is ascribable to the first overtone bands of the OH stretching vibration of water molecules. This 0.2 1452 finding follows NaCl and borax’s different hydration capacities, resulting1512 from their chemical 0.1 14601440 structures that differ in their potential interactions with water molecules.1488 0.0 1476 -0.1 1342 1426 -0.20.2 14521412 -0.3 1512 0.1 14601440 -0.4 1488 0.0 1476 -0.1-0.5 1342 1426

Second Component -0.2-0.6 1364 1412 -0.3-0.7 1374 -0.4-0.8 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 First Component Second Component -0.6 1364 -0.7 1374 -0.8 FigureFigure 5. 5.PCA PCA loading plot. plot. -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 First Component The PCAThe LDA applied carried to out the on whole the calibration dataset set enabled (43 observations) identifying resulted borax’s in the following presence linear on the 1st principaldiscrimination component. functions: Based on the absorbance differences in the 1400–1430 nm wavelengths range, Figure 5. PCA loading plot. such a result is ascribableBorax 15.71 to the first879.19 overtone ∙ “1342 nm” bands – 724.82 of the ∙ “1374 OH stretching nm” 991.4 vibration ∙ “1426 nm” of water (1) molecules. This findingThe follows LDA carried NaCl andout on borax’s the calibration different set hydration (43 observations) capacities, resulted resulting in the following from their linear chemical No Borax 2.51 205.9 ∙ “1342 nm” – 95.23 ∙ “1374 nm” 258.56 ∙ “1426 nm” structuresdiscrimination that differ functions: in their potential interactions with water molecules. (2) The LDAOverall, carriedBorax the classification 15.71 out on the 879.19 procedure calibration ∙ “1342 achieved nm” set – (43724.82 a good observations) ∙classification “1374 nm” rate resulted 991.4 (97.7%) ∙ “142 in (Table6 thenm” following2): the best(1) linear discriminationclassification functions: performance regarded the observations from no borax samples, while 1 out of 20 borax samples resultedNo Borax in the 2.51 wrong classification.205.9 ∙ “1342 nm” – 95.23 ∙ “1374 nm” 258.56 ∙ “1426 nm” (2)

BoraxOverall,= the classification15.71 + 879.19 procedure“1342 achieved nm” – a 724.82 good classification“1374 nm” rate+ (97.7%)991.4 “1426 (Table 2): nm” the best (1) − · · · classification performance regarded the observations from no borax samples, while 1 out of 20 borax samplesNo Boraxresulted= in the2.51 wrong+ 205.9classification.“1342 nm” – 95.23 “1374 nm” + 258.56 “1426 nm” (2) − · · · Overall, the classification procedure achieved a good classification rate (97.7%) (Table2): the best classification performance regarded the observations from no borax samples, while 1 out of 20 borax samples resulted in the wrong classification. Sensors 2020, 20, 7174 6 of 7

Table 2. Classiﬁcation matrix of the calibration set.

Sensors 2020, 20, x FOR PEER REVIEW Borax No Borax 6 of 8 Borax 19 0 No boraxTable 2. Classification matrix1 of the calibration 23 set. Total 20 23 Borax No borax Correctly classified 19 23 Borax 19 0 No borax 1 23 The application of the discriminantTotal equations (Equations20 23 (1) and (2)) to the validation set resulted in the classification matrix of TableCorrectly3: classified 19 23 The application of the discriminant equations (Equations (1) and (2)) to the validation set resulted in the classificationTable matrix 3. Classification of Table 3: matrix of the validation set.

Table 3. Classification matrixBorax of the validation No set. Borax Borax 10Borax No borax 0 No borax Borax 010 0 12 Total No borax 100 12 12 Correctly classiﬁedTotal 1010 12 12 Correctly classified 10 12 Such high classiﬁcation rates for both borax and no borax samples support the adequacy of the Such high classification rates for both borax and no borax samples support the adequacy of the aquaphotomicaquaphotomic approach approach in monitoring in monitoring the the caviar’s caviar’s ripening and and detecting detecting the presence the presence of borax. of borax. Figure6 showsFigure the 6 shows tenderometric the tenderometric data expresseddata expressed (from (from left left to to right) right) asas (i) (i) values values of ofthe the maximum maximum peak force; (ii) thepeak time force; required (ii) the time for required the egg for breaking; the egg breaki and (iii)ng; and the (iii) distance the distance the platethe plate traveled traveled to to break break the eggs. the eggs.

FigureFigure 6. Results 6. Results of of the the tenderometric analysis. analysis.

The analysisThe analysis of the twoof the groupstwo groups of samplesof samples (borax(borax and and no no borax) borax) did not did point not out point significant out significant differences for the consistency of the eggs (measured in terms of the maximum peak force the differences for the consistency of the eggs (measured in terms of the maximum peak force the instrument instrument applies to achieve eggs breakage). applies to achieveHowever, eggs time breakage). and distance values to achieve the egg breakage were lower in the borax samples, However,suggesting time a and lower distance elasticity valuesof the eggs to receiving achieve borax the eggin the breakage brining process were than lower those in treated the borax with samples, suggestingNaCl a lower only. elasticityThe difference of the in the eggs dehydration receiving capaci boraxty of in added the brining salts could process be one thanreason those for such treated with different elasticity, resulting from differences in water clusters’ formation. If confirmed, this finding NaCl only. The difference in the dehydration capacity of added salts could be one reason for such could affect both the shelf life duration and the end quality of the caviar. The panel test also pointed different elasticity,out such lower resulting elasticity from of the di eggs,fferences relating init with water lower clusters’ organoleptic formation. quality of borax If confirmed, samples (data this finding could affectnot both shown). the The shelf preliminary life duration results and obtained the endby texture quality analyzer of the and caviar. sensory The analysis panel suggests test also a pointed out such lowerlower quality elasticity of the ofcaviar the produc eggs,ed relating using sodium it with tetraborate lower as organoleptic a preservative, supporting quality of the borax need samples to have a rapid method to identify the sodium tetraborate presence in caviar batches. (data not shown). The preliminary results obtained by texture analyzer and sensory analysis suggests a lower quality4. Conclusions of the caviar produced using sodium tetraborate as a preservative, supporting the need to have a rapidThe method aquaphotomics to identify approach the sodiumwas shown tetraborate to be adequate presence in studying in caviar the storage batches. process of caviar. Based on the external perturbation induced by the two preservatives on the water response, 4. Conclusionsit was possible to distinguish between borax and no borax samples using a portable NIR instrument when a high S/N value is assured. The LDA applied to the validation set achieved high classification The aquaphotomicsrates for both borax approach and no borax was samples. shown Differe to bences adequate in chemical in studying structure between the storage the two process types of caviar. Based on theof salt external used allowed perturbation the detection induced of borax, by due the to its two different preservatives hydration power, on the even water if added response, in a it was possible tosmall distinguish percentage. between borax and no borax samples using a portable NIR instrument when a high S/N value is assured. The LDA applied to the validation set achieved high classification rates for both borax and no borax samples. Differences in chemical structure between the two types of salt used allowed the detection of borax, due to its different hydration power, even if added in a small percentage. NIR spectroscopy and aquaphotomics can be, in the future, used as non-invasive methods to discriminate between fish origin, as suggested by preliminary results reported in the technical report Sensors 2020, 20, 7174 7 of 7 of the project n. 201300004629, funded by Lombardy Region (data not published) and to potentially monitor the whole production chain.

Author Contributions: Conceptualization: T.M.C. and M.B. (Marina Buccheri); methodology: M.B. (Marina Buccheri); software: E.R.; validation: M.B. (Massimo Brambilla), A.S., and M.G.; formal analysis: A.S. and M.G.; investigation: M.B. (Marina Buccheri); resources: M.P.; data curation: M.B. (Massimo Brambilla); writing—original draft preparation: T.M.C.; writing—review and editing: M.B. (Marina Buccheri); visualization: T.M.C.; supervision: M.B. (Massimo Brambilla); project administration: M.P.; funding acquisition: M.P.All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Lombardy Region (Italy), Measure 124–PSR 2007–2013”. Project n. 201300004629. Acknowledgments: Authors thank Agroittica Lombarda S.p.A. [Calvisano (Brescia) Italy] for samples collection and technical support. The study was partially funded by Lombardy Region (Italy). Conﬂicts of Interest: The authors declare no conﬂict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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