Piyush Kumar Jha

Kévin Vidot

Epameinondas Xanthakis

Xavier Falourd

Joran Fontaine

Vanessa Jury

Alain E Le-Bail
email: alain.lebail@oniris-nantes.fr

Kevin Vidot

Alain Le

Benchmarking of techniques used to assess the freeze damage in potatoes

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Freezing is a preservation technique that has been used for ages for increasing the shelf life of food products. Compared to other long-term preservation methods, freezing technique causes less deterioration to nutrients and sensory properties in fruits and vegetables [START_REF] Barbosa-Cánovas | Introduction to freezing. Freezing of fruits and vegetables: An agribusiness alternative for rural and semi-rural areas[END_REF]. However, it can cause some irreversible damages such as texture loss, colour change, etc. Three main phenomena may describe freeze damage; the primary mechanical effect caused by the transition of water into ice, the biochemical effect caused by cryo-concentration and the secondary mechanical effect eventually caused by ice contraction after freezing [START_REF] Reid | Overview of physical/chemical aspects of freezing[END_REF][START_REF] Shi | Thermal fracture in a biomaterial during rapid freezing[END_REF], 1998;[START_REF] Shi | Mechanical Property Changes during Freezing of a Biomaterial[END_REF].The extent of freeze damage caused to the food products on thawing is greatly linked to the size and location of the ice crystals, which in turn is related to the applied freezing rate [START_REF] Chevalier | Freezing and ice crystals formed in a cylindrical food model: Part II. Comparison between freezing at atmospheric pressure and pressure-shift freezing[END_REF]. Freeze damage can also be linked to the cryo-concentration effect; the aqueous solution present in the cells is exposed to a progressive concentration in solute caused by ice formation. The remaining aqueous phase which tends to become more and more concentrated can cause denaturation of the proteins and other organized biopolymers (i.e. cellulose based systems for fruits and vegetables), which in turn degrade their mechanical properties and by the way the overall texture of the tissue [START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF][START_REF] Lovelock | The denaturation of lipid-protein complexes as a cause of damage by freezing[END_REF][START_REF] Reid | Overview of physical/chemical aspects of freezing[END_REF]. The mechanisms of freeze damage associated with cryo-concentration effect have been thoroughly discussed in a review article from [START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF]. Rapid freezing (high freezing rate) favours the genesis of fine ice crystals distributed uniformly within the product, thus reducing the dislocation of water from intra to the extra cellular spaces, resulting in higher water holding capacity upon thawing. In addition, the time of exposure to the highly concentrated aqueous solution caused by cryoconcentration is being reduced during rapid freezing, resulting to a lesser extend of the biochemical degradations [START_REF] Delgado | Heat and mass transfer models for predicting freezing processes -a review[END_REF][START_REF] Fennema | An over-all view of low temperature food preservation[END_REF][START_REF] Orlowska | Controlled ice nucleation under high voltage DC electrostatic field conditions[END_REF][START_REF] Sadot | Numerical modelling of an innovative microwave assisted freezing process[END_REF][START_REF] Shi | Thermal Stresses From Large Volumetric Expansion During Freezing of Biomaterials[END_REF][START_REF] Singh | Food Engineering[END_REF]. The result is reduced cell destruction and better quality attributes.

However, two main disadvantages lie behind rapid freezing rates : (i) rapid freezing process requires a higher amount of energy, hence increases the consumed energy and the overall operating costs and (ii) the use of extremely high freezing rates such as cryogenic freezing, may lead to crack development in the samples and yield unexpectedly poor quality of the final product (secondary mechanical effect quoted above) [START_REF] Shi | Thermal fracture in a biomaterial during rapid freezing[END_REF], 1998;[START_REF] Shi | Mechanical Property Changes during Freezing of a Biomaterial[END_REF]. On the contrary, at a slow freezing rate, intracellular water move to the extracellular domains (from the inside of the cell) and thus can result in greater ice crystal size (in the extracellular spaces) and also in a higher cell dehydration [START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF][START_REF] Mazur | Freezing of living cells: mechanisms and implications[END_REF]. Besides, slow freezing rate will also result in a prolonged exposition of the tissue to the concentrated solution occurred from the cryo-concentration effect [START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF][START_REF] Mazur | The role of intracellular freezing in the death of cells cooled at supraoptimal rates[END_REF][START_REF] Mazur | Freezing of living cells: mechanisms and implications[END_REF]. In fact, the formation of larger ice crystals along with volume shrinkage and long-term exposure to high solute concentrations would cause a higher destruction of cellular structure (high risk of punctured cell membrane/cell wall, collapsed cell structure and cell separation) [START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF][START_REF] Chassagne-Berces | Freezing protocol effect on quality properties of fruit tissue according to the fruit , the variety and the stage of maturity[END_REF][START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF][START_REF] Mazur | Freezing of living cells: mechanisms and implications[END_REF]. As an outcome, the leakage of the fluid from the cell will be higher and a product having a water-soaked appearance and mushy texture will be obtained. The last important parameter that may be responsible for quality losses of frozen foods is the storage conditions; time-temperature parameters, as well as temperature fluctuations, are also responsible for the quality loss.

The assessment of the quality of a frozen food product is obtained via analytical methods used to quantify the freeze damage. Broadly, these methods can be categorized as global methods and focused methods. The global methods provide quality information at a macro/meso level.

In other terms, the quality information obtained using such methods is the average value from a whole sample or at least from a substantial piece of sample (several grams or several cm 3 ).

The global methods comprise of texture analysis, exudate loss measurement, solute diffusivity, impedancemetry, colour analysis, etc. While the focused methods provide quality information at a micro level (cell level or even at a lower scale such as ice crystal or water molecule scale). For instance, information about ice crystals size, cellular structure intactness, etc. can be obtained by using focused methods. Microstructures evaluation methods such as Scanning electron microscopy (SEM) (includes conventional SEM, environmental SEM (ESEM), and cryo-SEM), confocal laser scanning microscopy (CLSM), X-rays tomography, etc. fall under focused method. Low field nuclear magnetic resonance relaxometry (NMR) is at the same time a global and focused method as it embraces a sample of circa 1 cm 3 scale and provides info at the level of water molecules [START_REF] Jha | Assessment of freeze damage in fruits and vegetables[END_REF].

In the literature, numerous benchmarking studies are available related to freezing effects on the quality parameters of the fruits and vegetables. However, no studies are available in the literature that benchmarks the techniques used to assess the freeze damage in fruits and vegetables.

This work was framed under the following objectives i. To introduce new freeze damage assessment methods and check their efficiency in quantifying the freeze damage.

ii. To benchmark the freeze damage methods (both conventional and novel) used for assessing the freeze damage in plant-based products with the intention to facilitate the researchers and industries to choose the appropriate method to assess the freeze damage.

The ultimate objective of this study is to provide a decision table which will allow to categorize the analytical techniques based on sensitivity, efficiency, accuracy, cost of operation, and ease of operation.

Materials and methods

Product properties

Potatoes

Sample preparations

The sample size used to study the effect of conventional freezing processes on the quality parameters depended on the freeze damage assessment methods. For instance, to study the effect of freezing rates on freezing characteristics, texture, colour and drip loss, cuboids of potato (1.3 × 1.3 × 1 cm 3 -length × height × width; weight 1.95 ± 0.5 g) were used. The potatoes were cut in cuboid shape using a dicer (Ibili Manage, Inc. Spain). The potato samples used for NMR relaxometry and cryo-SEM analysis were cylindrical in shape (∅ = 8 mm and H = 10 mm). For confocal laser scanning microscopy (CLSM) analysis, cylindrical potato samples (∅ = 8 mm and H = 5 mm) were chosen. The samples were then immediately transferred into the freezer and were cooled from the ambient temperature to the desired temperature.

It is worth mentioning that during this study, one of our aims was to analyze the samples in its original state without causing any alterations to them, thus we had to vary sample size for potato according to the freeze damage assessment methods. For instance, NMR tube has an internal diameter of 1 cm and hence required sample having a diameter < 1 cm. Also, another requirement of NMR test is to have the NMR tube covered minimum up to 1 cm in height.

The cylindrical sample with a diameter of 8 mm and height of 1cm perfectly matched both the requirements. For cryo-SEM, sample size similar as NMR facilitated easy cutting of sample in the frozen state and allowed the selection of the analyzed sample from nearly the same location for each condition. For CLSM, small sample size helped the proper and fast staining of the sample and facilitated the selection of the analyzed sample from the same location of each matrix.

Freezing apparatus and freezing conditions

Freezing of potatoes (unblanched) was performed at -18 °C in a cold room, at -30 °C and 0.5 m/s air velocity in an industrial batch freezer (MATAL, France), and at -74 °C in an ultra-low temperature freezer (TSE240V, Thermo Scientific, Marietta, Georgia, USA). The three conditions will be referred to as slow freezing (SF), intermediate freezing (IF) and fast freezing (FF) in further sections of the manuscript. Once frozen, the samples were packed in the zip-lock and stored at -40 ± 2 °C (≈ for 2-3 days) until quality evaluation tests were performed. The time-temperature profile during the freezing tests was studied by inserting a K-type thermocouple at a geometric centre of the product. The (thermocouple) was calibrated against a reference platinum probe (Comptoir Lyon Allemand -Lyon-France). During measurements the temperature of the sample was recorded every 2 s with a data logger with an accuracy of ±0.1 °C. For comparison purposes, temperature profiles from the initial temperature 18 °C to -18 °C were considered. The characteristic freezing time and overall freezing time were determined using time-temperature data. The characteristic freezing time was the measure of local freezing rate and it was defined as the time during which the temperature at a particular point changed from the initial freezing point to a temperature at which 80% of the water (at that point) was converted into ice. The temperature range considered for the characteristic freezing time estimation was from -1 to -7 °C, similar temperature range was used by [START_REF] Li | Effect of power ultrasound on freezing rate during immersion freezing of potatoes[END_REF] for the determination of characteristic freezing time during ultrasound assisted freezing of potatoes. The overall freezing time was the time required to lower the temperature of the geometrical centre of the product from the ambient temperature (18 °C) in the present study) to a given temperature (-18 °C). Samples for quality analysis were frozen using the same procedure but without optical fibre inserted.

Each experiment was performed at a minimum of individual triplicates.

Thawing protocol

The frozen potato samples were thawed at room temperature (20 ± 1 °C) for 2 h in a zip-lock bag ("static air thawing" method) before performing colour, drip loss, texture and solute diffusion measurements. For NMR analysis the samples were thawed at 4 °C for 4 h in the NMR tube.

Colour analysis

The colour of the potatoes was measured using a portable and handheld chroma meter CR-400 (Konica Minolta, Inc. Japan). Using this equipment, the L * , a * , b * values for samples from each condition were obtained with high accuracy. The maximum value for L * is 100 (represents a perfectly white surface or a perfectly reflecting diffuser) and its minimum value is 0 (represents perfectly black surface). The positive and negative a * corresponds to red and green colour. Similarly, positive and negative b * represents yellow and blue colour, respectively. A single value for the colour difference was achieved by calculating the overall colour difference (∆E) value; it takes into account the differences between L * , a * , b * of the specimen (e.g. frozen-thawed sample) and reference (fresh sample), and it was calculated by using Eq. ( 1) (Anon, 2018). The frozen samples were thawed before the colour measurements.

At least eight measurements were recorded for each freezing protocol.

ΔE = ΔL * + Δa * + Δb * (1)

Drip loss measurement

The drip loss required great care in terms of manipulation. The mass differences that are being determined are usually small and it can be advantageous to use paper tissue to collect all the drip released by a sample. This requires the weight of the bag containing the sample, the initial mass of the tissue paper and all the final masses. There is also a risk of moisture condensation on the sample during frozen storage (if unpacked) or during the thawing process or even sample handling after thawing if their temperature is lower than the dew point temperature. The drip loss unit is very often given as g drip per g of sample. In most existing studies, drip losses are expressed as free drip; this means that drip the collected from the sample due to gravity forces and possible capillary interactions with the tissue paper. In some studies, the samples are compressed under selected stress [START_REF] Jahncke | Frozen storage of unwashed cod (Gadus morhua) frame mince with and without kidney tissue[END_REF] or after centrifugation for selected g values under given times [START_REF] Penny | Use of a centrifuging method to measure the drip of pork Longissimus dorsi slices before and after freezing and thawing[END_REF]. In our study, the drip loss was determined based on the weight difference between frozen sample (W1), and thawed sample (W2). The drip loss (%) was calculated using Eq. (2). At least 9

samples were analyzed for each freezing condition.

Drip Loss % = W -W W × 100

(2)

Texture analysis

Texture analysis of food is often carried out using the TPA protocol (Texture Profile Analysis) proposed by Bourne [START_REF] Bourne | Texture Profile of Ripening Pears[END_REF]. Quite often, simple compression tests are used for frozen food aiming at determining the Young's Modulus (small deformation, typically 10% strain) and eventually the failure strain or stress. In our study, the frozen potato samples were thawed and compressed in a texture analyser (AMETEK, Lloyd Instruments, France) equipped with a 1000 N load cell and operating at a test speed of 50 mm/min beyond failure point which was marked by a significant drop in the force reading (Figure 1). The compression test was performed using a 50 mm compression plate. A similar procedure was used by [START_REF] Khan | Compressive Stiffness and Fracture Properties of Apple and Potato Parenchyma[END_REF][START_REF] Cano | Vegetables[END_REF] for determining the failure stress, Young's Modulus, and failure strain of potato. Based on our preliminary trials and the results from [START_REF] Khan | Compressive Stiffness and Fracture Properties of Apple and Potato Parenchyma[END_REF] and [START_REF] Alvarez | Influence of deformation rate and degree of compression on textural parameters of potato and apple tissues in texture profile analysis[END_REF], compression of the sample to 50% strain was found more than sufficient to cause the failure of our sample (Figure 1). The maximum force exerted during the compression test was recorded as the firmness/hardness (N) of the samples (Figure 1). Moreover, the stress vs. strain curves during compression tests were examined and Young's modulus (E) (the slope of the loading curve at the point of its highest gradient) was also acquired [START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF]. All measurements were performed at 21 ± 2ºC.

At least 12 samples were analyzed for each freezing condition.

Laser-puff firmness tester

A touchless laser-puff firmness tester which was designed and constructed in our lab (GEPEA lab, ONIRIS) was used for non-destructive measuring of the texture of fresh and frozenthawed potatoes (Figure 2). The firmness tester consists of the following components: a mean to generate impulsive jet of air; a nozzle (having a diameter of 0.004 m) to direct the air onto the surface of the specimen under investigation; a deformation measurement unit containing a laser source to generate coherent source of light directed on the surface of the object impacted by the air jet, a detector of the light which is reflected from the specimen surface, and an analyzer to estimate the amount of deformation sustained by the product surface; a control panel to change the pressure value and an appropriate software (developed in our lab) to execute the test. Based on the preliminary trials, for measuring the firmness of frozen-thawed potatoes, the air nozzle was located at 10 mm from the food surface and an air pressure of 5 × 10 5 Pa and air jet exposure time of 100 ms were found most appropriate. The estimated pressure exerted onto the food surface was in the range of 3.32 × 10 5 Pa assuming a surface of 1.256 × 10 -5 m² impacted by the air jet. Prussia, Astleford, Hewlett, & Hung (1994) used impact pressure of 3.10 × 10 5 Pa (45 psia) in order to determine the firmness of potato.

Similar to the authors, [START_REF] Hung | Peach Sorting Performance of Anondestructive Laser Air-Puff Firmness Detector[END_REF] who used the same exposure time to determine the firmness of peaches.

The sample was placed on the sample platform below the air delivery nozzle and the position of sample was adjusted using a positioner in order to ensure (i) the air jet and the laser hits the same point on the sample and (ii) the distance between end of the nozzle and the sample surface is same for all trials. Subsequently, by using the software air jet was directed on the sample and the deformation was measured. The software yielded deformation results in volts (Figure 3). The maximum deformation can be referred to as the difference between the highest initial value and lowest value recorded by the deformation unit during the test. The conversion of volts to mm (millimeter) based unit was made by multiplying with a conversion factor (in the present case, volt value was multiplied by 2 to obtain final value in mm). The final deformation value was an average of sixteen measurements.

Microstructure examination

Cryo-SEM analysis

Cryo-SEM analysis is a very specific technique which requires very careful and proper sample preparation. A thin specimen of slab shape was cut from a given location of the frozen food using a sharp scalpel. In our case, the central section of the frozen potato samples was selected for collecting the sample. Also, in the case of structured tissue, given shape must be provided to the sample to identify a given orientation; for example, in the case of a muscle, the longer section of sample is usually longitudinal to the fibers in order to be able to do cut view either parallel or perpendicular to the fibers. In the case of a vegetal tissue has no major orientation so special care was taken mainly for the location, shape and size of the sample. It was fixed into the groove notched in a copper sample holder (10 mm diam. 10 mm height) using an OCT (optimal cutting temperature) compound (Tissue-Tek, Sakura, Finetek, USA).

An important technical issue lies in preventing any thawing of sample when the sample is contacted onto the sample order. To overcome this difficulty, the following protocol was used. All manipulations were done in a cold box filled with CO2 sticks (-78.5 °C) in order to condition the sample which was kept in this ambiance. The sample holder was refreshed down to around 0 °C by contacting a CO2 stick. Then a small amount of OCT was installed in the groove of the sample holder. Then, at the same time, the sample holder was contacted onto a CO2 stick meanwhile the frozen sample was contacted to the OCT located in the groove.

Within less than a few seconds, the sample was fixed onto the sample holder thanks to the freezing of the OCT. The very high thermal diffusivity of the copper material (sample holder) compared to the frozen sample ensures that the sample will not undergo any thawing when the sample is contacted to the sample holder. The sample was left for 2 min in a box filled with dry CO2 to harden the OCT compound. After that, the sample was loaded onto a precooled copper specimen stub (in liquid N2) and was quickly transferred in the cryo-preparation chamber of the cryo-SEM (LS10, ZEISS EVO, Germany) maintained under vacuum at -80 °C, where it was cryo-fractured using a precooled sharp knife mounted inside the chamber.

The fractured sample was etched in the preparation chamber for about 5 to 10 min to expose the subsurface information in order to allow a partial sublimation of the ice crystals. The etching time required adjustment depending on the size of the sample, the pressure level and the type of tissue. The sample was finally coated with a thin conducting layer of gold (5 nm) in the cryo-preparation chamber and then was transferred to the cold stage in the cryo-SEM (maintained at -80 °C) where microstructural observation was performed. The fractured surfaces of potatoes were examined with an accelerating voltage of 11 kV. An illustration of the sample preparation steps is presented in Figure 4. It is worth mentioning that all the samples prepared for cryo-SEM analysis after the different freezing conditions acquired from the same potato.

Confocal laser scanning microscopy (CLSM)

The confocal laser scanning microscopy was also used for potatoes samples. Figure 5 provides a brief description of the protocol followed to prepare potatoes for the CLSM observations. The CLSM was performed using an Eclipse Ti inverted microscope (Nikon Ti A1, Japan). For each freezing condition, independent experiments were performed in triplicates.

It is worth noticing that the acridine orange (used for this study) is well known to be a metachromic dye, especially for staining DNA and RNA. Such dye is able to give fluorescence with emissions wavelength depended on its interaction with chemical functions, charge or geometry of a compound. The acridine orange was chosen here as a dye able to stain simultaneously the different cell layers of the fruits as it has been widely applied for fluorescent staining of plant tissue with a high fluorescence emission. The maximum emission wavelength of this dye is 500-530 nm and excitation occurs at about 488 nm.

NMR relaxometry

For all the freezing protocols, NMR tests were performed for samples in frozen state (at -20 °C) and frozen-thawed state (at 4 °C). Initially, the frozen samples were placed in the NMR tube (∅ = 10 mm) precooled to -20 °C. Then the tube was quickly placed in the spectrometer (maintained at -20 °C) and left for 10 min to ensure that the samples were at

-20 °C at the beginning of NMR test at a negative temperature. Upon completion of NMR tests in frozen condition, the same samples were thawed (at 4 °C for 4 h) and then NMR tests on frozen-thawed samples (at 4 °C) were carried out. In order to compare the damage caused by different freezing procedures, the NMR measurements of fresh samples were performed at 4 °C and were compared with results obtained for frozen-thawed samples obtained under various freezing protocols. The Minispec mq20 spectrometer (Bruker) at 0.47 T (20 MHz proton resonance frequency) equipped with a thermostated (± 0.1 °C) 1 H probe was used for NMR analysis. Triplicates were performed for each freezing condition of potato.

In the present study, " (transverse) relaxation time of protons and their respective population in the product were evaluated. The " distributions were determined using a Carr-Purcell-Meiboom-Gill (CPMG) sequence. For the NMR test at frozen and frozenthawed state, the 180° pulse separation was 0.04 and 0.1 ms, 2000 and 10000 even echoes were collected, and the 1024 and 256 scans were acquired with a recycle delay of 1 and 5 s resulting in a total acquisition time of about 20 and 40 min respectively.

An inverse Laplace transformation (ILT) was applied to convert the relaxation signal into a continuous distribution of " relaxation components. For this purpose, a numerical optimization method was used by including non-negativity constraints and L1 regularization and by applying a convex optimization solver primal-dual interior method for convex objectives (PDCO).

Statistical analysis

One-way ANOVA (analysis of variance) was used to determine any significant difference (in terms of freezing and quality characteristics) among the freezing conditions. Duncan's multiple range test was performed to determine differences between the means (p < 0.05).

Results and discussion

Effect of different freezing rates on temperature history

The representative temperature histories of potatoes frozen under the different freezing conditions are presented in Figure 6. The SF process yielded freezing curves having three showed only one stage (i.e. phase change state) in Figure 6. SF condition gave a degree of supercooling of 0.15 ± 0.07 °C, while no supercooling curve was observed for the other two freezing conditions. Similar freezing curves lacking obvious supercooling at higher freezing rates (at -80 °C and liquid nitrogen immersion freezing) were also obtained by Cao et al.

(2018) during freezing of blueberries. It was inferred by them that at a faster freezing rate the supercooled state might be unstable or lack persistence. The initial freezing point for SF and IF condition was recorded as -0.3 ± 0.14 and -0.73 ± 0.06 °C (Table 1). It seems that a slight depression in freezing point happened upon increasing the freezing rate. For FF condition, it was hard to detect the initial freezing point due to a rapid decline in the temperature during the freezing process. However, more replications could be helpful to be conducted prior to the confirmation of this outcome. Recently, [START_REF] Cao | Effects of freezing conditions on quality changes in blueberries[END_REF] also reported slight decrease (but not significant) in the initial freezing temperature of blueberries when the freezing rate was increased from 0.023 °C/s (at -20 °C) to 0.049 °C/s (at -40 °C) or 0.11°C/s (at -80 °C) or 0.76 °C/s (liquid nitrogen immersion freezing). The initial freezing point of blueberries at 0.023, 0.049, 0.11, and 0.76 °C/s rates were recorded as -2.67 ± 0.32 °C, -3.23 ± 0.12 °C, -3.53 ± 0.35 °C and -3.36 ± 0.60 °C respectively [START_REF] Cao | Effects of freezing conditions on quality changes in blueberries[END_REF].

Among other freezing parameters being studied, the characteristic freezing time was found to be the shortest for FF condition (8.52 ± 1.53 min), followed by IF and SF condition (17.18 ± 0.79 min and 29.12 ± 3.94 min respectively) (Table 1). The time spent in this zone is very crucial as it determines the quality of the final product. From the perspective of higher quality preservation, a shorter width of this zone is desired. Similar to characteristic freezing time, the overall freezing time and the overall freezing rate also exhibited a similar trend.

Texture analysis

Conventional method

The confined compression test was the conventional method used to determine the texture of potatoes. The hardness and Young's modulus values of fresh and thawed sample (from different freezing conditions) are shown in Table 2. The values of fresh samples were significantly different (p < 0.05) compared with those of the frozen-thawed samples. FF process caused less decay in hardness value (≈ 50%) than IF process (≈ 62%) or SF process (≈ 74%). However, significant differences in hardness values were observed only between SF and FF samples. Young's modulus values exhibit a similar tendency as hardness values in Table 2. [START_REF] Khan | Mechanical damage induced by controlled freezing in apple and potato[END_REF] reported that compressive stiffness of potato less degraded when freezing was performed at a higher freezing rate (10 °C/min) compared to slow freezing rate

(1 °C/min). According to [START_REF] Mazur | Freezing of living cells: mechanisms and implications[END_REF] They reported that rapid and cryogenic freezing condition had a higher hardness retention than the slow freezing condition.

Laser-Puff firmness tester

Laser-Puff firmness tester allows rapid and non-destructive texture analysis of the food products [START_REF] Hung | Peach Sorting Performance of Anondestructive Laser Air-Puff Firmness Detector[END_REF][START_REF] Mcglone | Kiwifruit and apricot firmness measurement by the non-contact laser air-puff method[END_REF]Prussia et al., 1994). An attempt was made to use this method, to the best of our knowledge for the first time, for measuring the texture of frozen-thawed fruits and vegetables. In this section, the results from laser-puff firmness analysis of potato will be presented and discussed. The deformation curves and deformation values obtained during laser-puff firmness test of fresh and frozen-thawed potatoes (under different freezing rates) are shown in Figure 7. The fresh samples had significantly (p < 0.05) lower deformation value than all frozen-thawed samples (Figure 7b).

As expected, SF samples suffered the highest deformation during the tests. The deformation occurred at IF samples was less than SF samples, but greater than the FF samples. However, the deformation values of IF samples were not significantly different (p > 0.05) from the values of SF and FF samples. The FF sample showed lower deformation than the other conditions, and those values were found to be significantly lower than SF, but not significantly different from IF values. The obtained results (in terms of deformation) are coherent with those obtained by the classical method (discussed above). In conclusion, this method could distinguish fresh and frozen-thawed samples, but had limited capability to differentiate the tested freezing conditions.

NMR relaxometry

NMR tests were performed for the samples in frozen (at -20 °C) and frozen-thawed states (at 4 °C) after being frozen under the different freezing conditions. Figure 8 shows the results from NMR relaxometry of potato in a frozen state (at -20 °C). The relaxation peaks, " * (including magnetic field inhomogeneities) and " of frozen samples provide information about the structure of the samples and about the unfrozen water at -20 °C (Figure 8). " # * is the relaxation peak of protons associated with the macromolecules. " $ * , " % , and " & are the relaxation peaks associated with the protons of unfrozen water [START_REF] Foucat | Short communication A subzero 1 H NMR relaxation investigation of water dynamics in tomato pericarp[END_REF][START_REF] Luyts | Low resolution 1H NMR assignment of proton populations in pound cake and its polymeric ingredients[END_REF]. Results showed that the " # * values (relaxation time and proton population) for all freezing conditions were similar, which indicated that the different freezing protocols didn't influence differently the systems at a macromolecular level (Figure 8a). Similarly, " $ * values were not significantly different among the different freezing conditions (Figure 8a). If we follow the hypothesis that the faster the freezing process is the less is the destruction it imparts, the values of relaxation peak components of non-freezable water ( " % and " & ) associated with the samples frozen quickly provide an evidence of better preservation of structures. Only samples that were frozen slowly (at -18 °C) showed different values for these relaxation peak components (Figure 8a Figure 9 represents the " peaks of fresh and frozen-thawed samples at 4 °C. With regard to fresh samples, the distribution of " relaxation peak has five components (" ' , " ( , " * , " + & " , ), whose values averages are in good agreement with the literature data [START_REF] Rutledge | Magnetic resonance imaging studies of the freeze-drying kinetics of potato[END_REF]. Based on these data, an allocation of different components of " have been proposed: " ' and " ( are the relaxation peaks associated with the water present in the cell walls and the vacuolar membrane. " * is the relaxation peak of water in starch grains. " + and " , are the relaxation peaks of water in the non-starch vacuoles, the nucleus and the cytoplasm [START_REF] Rutledge | Magnetic resonance imaging studies of the freeze-drying kinetics of potato[END_REF]. The measurement of the " components values (relaxation time and proton population) of the samples after thawing makes it possible to observe the influence of different freezing protocols on the mobility of the water compared with the fresh samples. It can be seen that the freezing-thawing process affects the resolution of the " distribution peaks (Figure 9). For instance, the " * and " + components which were distinctively visible in the fresh sample could no longer be differentiated in the frozen-thawed sample. Apart from this, " + and " , times of fresh potato decreased upon freezing-thawing.

Among the different freezing conditions used in this study, only FF (at -74 °C) preserved " components distributions with good resolution over the entire time range studied. Four " components were characterized for FF (against five for fresh samples), meanwhile, for IF and SF conditions, three and two " components could only be characterized. For all freezing conditions, the mobility of water associated with non-starch vacuoles, nuclei and cytoplasm (" + and " , ) decreased. This reflects a reorganization of the fluids following a partial rupture of the cellular structures [START_REF] Lahaye | Water mobility and microstructure evolution in the germinating medicago truncatula seed studied by NMR relaxometry. A revisited interpretation of multicomponent relaxation[END_REF] irrespective of the freezing speed. Compared to fresh sample, the decrease in " , time was lower for FF process (≈ 46%) and was followed by SF (≈ 53%) and IF (≈ 54%) process. However, no significant difference among freezing processes (in terms of " , time) was observed. " , component proton population data reveal that FF and IF samples had similar values (p > 0.05) as the fresh sample, while it significantly decreased (p < 0.05) in the case of SF samples. This decrease was followed by an increase in proton population of the consecutive peak in the " distribution curve for SF samples (Figure 9b), depicting the transfer of water between two compartments which might have probably happened due to the breakdown of vacuolar membrane. However, no such trend was observed for other freezing conditions (Figure 9c andd). The " component values (relaxation time and proton proportion) adjacent to the " , for SF samples was significantly different (p < 0.05) from those of FF and IF conditions. The " ' and " ( components of FF samples had similar relaxation times as the fresh samples, illustrating the overall better preservation of membranes and walls (despite a reorganization at the level of populations). IF also fairly maintained the " ( component values and they were found to be similar to the fresh sample. Due to poor resolution, it was difficult to extract " ' component value for IF samples. " ' and " ( component values for SF sample also could not be resolved due to the poor resolution of the peak. [START_REF] Cao | Effects of freezing conditions on quality changes in blueberries[END_REF] used " time of water proton to differentiate fresh blueberries from frozenthawed blueberries. They found that the freezing-thawing process caused a reduction in " time of vacuole, cell wall, cytoplasm and extracellular water compared to the fresh sample.

With respect to the proton population of different compartments, it was observed that freezing and thawing did not cause any alteration in the proton population of different compartments compared to a fresh samples. Moreover, they also used " relaxation peak data to distinguish different freezing conditions (i.e. freezing at -20, -40, -80 °C and freezing by immersing in liquid nitrogen). It was reported that among all freezing conditions, -80 °C freezing conditions better maintained " time of vacuole (p < 0.05) depicting better protection to the vacuole membrane. Unlike them, we did not observe any significant difference among the freezing trials with respect to the relaxation times of thawed samples frozen by different methods, however, we could observe a significant differences between FF, IF and SF conditions with respect to the proton population of " peaks. The proton population data (associated with " times) was used by [START_REF] Zhang | Changes in the vitamin C content of mango with water state and ice crystals under state/phase transitions during frozen storage[END_REF] to study the effect of state/phase transition on water mobility in frozen mango during 4-week storage.

Drip loss

Drip loss is one of the commonly and widely used methods to evaluate the freeze damage in frozen products (especially in meat, fish, fruits and vegetable matrices). This method estimates the freeze damage at a global level, or in other terms, provides an average value of freeze damage of a product. In this section the impact of the studied freezing conditions on the exudate loss from the product will be presented and discussed. Figure 10 shows the dependence of drip loss on freezing rate. The results reveal that drip loss decreased slightly when freezing rate was increased, however, significant difference was observed only between samples that were frozen under FF and SF conditions. IF samples were not significantly different (p > 0.05) compared to the samples of the other two freezing rates. The drip loss results exhibited similar trends to those of " , component proton population from NMR that showed that the application of -18 °C freezing protocol maintained less the intracellular water content. This result may be attributed to a better preservation of the intracellular water and to a lower damage of the pectocellulosic walls from the faster freezing rates. As a result, this method was able to detect the differences between the selected freezing rates. The water holding capacity of the frozen sample is linked to the size and location of ice crystals as well as the thawing rate (Van Buggenhout, Messagie, et al., 2006). The formation of large ice crystals in the cellular matrix can affect the water holding capacity of a cellular matrix in two ways: (i) large ice crystals genesis during freezing can damage the cell membrane due to mechanical effects, to cryo-concentration phenomena and shrinkage effects (particularly during slow freezing rates) which in turn, will promote loss of mass during thawing [START_REF] Bevilacqua | Histological measurements of ice in frozen beef[END_REF][START_REF] Delgado | Heat and mass transfer models for predicting freezing processes -a review[END_REF][START_REF] Sadot | Numerical modelling of an innovative microwave assisted freezing process[END_REF] and (ii) higher drip loss may occur due to the formation of bigger ice crystals which correspond to smaller specific surface area. This fact is associated with water re-absorption decrease during thawing [START_REF] Bevilacqua | Histological measurements of ice in frozen beef[END_REF][START_REF] Sadot | Numerical modelling of an innovative microwave assisted freezing process[END_REF]. [START_REF] Charoenrein | Effect of freezing rates and freeze-thaw cycles on the texture, microstructure and pectic substances of mango[END_REF] and [START_REF] Fuchigami | Programmed Freezing Affects Texture, Pectic Composition and Electron Microscopic Structures of Carrots[END_REF] observed decrease in exudate loss with increasing freezing rates in frozen mangoes and carrots.

Colour

Freezing-thawing process significantly (p < 0.05) affected the colour parameters (L * , a * , and b * values) of the unblanched potatoes Figure 11. The L * value (or lightness) and b * value (or yellowness) decreased, while the a * value (redness) increased for potatoes after freezingthawing (Figure 11a, b andc). These results are in agreement with the previously reported study on freezing-thawing of unblanched potatoes [START_REF] Koch | Pressure-shift freezing and its influence on texture, colour, microstructure and rehydration behaviour of potato cubes[END_REF]. The colour change during the freezing-thawing process of unblanched potato has been attributed to the browning reaction that generally happens due to enzymatic activity during thawing process [START_REF] Cano | Vegetables[END_REF][START_REF] Koch | Pressure-shift freezing and its influence on texture, colour, microstructure and rehydration behaviour of potato cubes[END_REF]. The freezing rates had little effect on the colour parameters of potatoes. Interestingly, it was found that FF process increased the redness value of potatoes significantly (p < 0.05) than compared to SF process. Chassagne-berces, Fonseca, et al.

(2010) reported that freezing at -80 °C increased the redness value of Golden Delicious apple compared to the one frozen at -20 °C. The redness value of IF samples was not significantly different compared with those frozen under FF and SF conditions. No significant differences for rest of the colour parameters (L * value, b * value and ∆E) were observed among the freezing protocols.

Microstructure analysis

Cryo-SEM analysis

Scanning electron microscopy permits to obtain very high-quality images of a food matrix microstructure. With respect to the frozen cellular matrices, micrographs acquired using SEM (especially the cryo-SEM) provide important details about ice and cell morphology (shape of the cell and the integrity of pectocellulosic walls). To the best of our knowledge, for the first time, cryo-SEM was used to compare the changes occurring to the microstructure of potato at different freezing rates. Figure 12 illustrates the SEM images of fresh and frozen potatoes.

The images of fresh and frozen potato were obtained using an environmental SEM (E-SEM) and cryo-SEM, respectively. It can be seen in the figure that the fresh potato has polyhedral shape cells with starch embedded in it. The microstructure morphology upon freezing depended highly on the freezing rate being applied. The SF process not only created bigger ice crystals in the cells but also caused the highest damage to the cellular structure. The cells were highly distorted (deformed cells with broken and irregular cell wall structure) under SF conditions. The IF process produced smaller ice crystals and maintained the cell wall integrity better than the SF conditions. However, some cells lost their polyhedral shape and turned almost into round shape when freezing was performed at IF conditions (cells pointed by the orange arrow in Figure 12e and Figure 12f). The FF process yielded smallest ice crystals compared to other freezing processes. Moreover, it can also be observed that the cellular structure (in terms of cell shape i.e. polyhedral shape and cell wall integrity) was maintained well. Similar to the authors, [START_REF] Bomben | Heat and mass transport in the freezing of apple tissue[END_REF], [START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF] and [START_REF] Chassagne-Berces | Freezing protocol effect on quality properties of fruit tissue according to the fruit , the variety and the stage of maturity[END_REF] cryo-SEM imaging could differentiate the apples frozen by different freezing conditions based on microstructure. Moreover, they also observed that slow freezing process (e.g. freezing at -20 °C or 0.4 K/min) altered the shape of the cell more than the fast freezing processes (e.g. freezing at -80 °C or 450 K/min or by liquid nitrogen immersion freezing). The calculations for ice crystals size were not made as it was difficult to locate the boundary of the ice crystals. Moreover, the ice crystals had a 3D structure and if the calculation were made, we could get only 2D information, this would have led to an inaccurate estimation of the size of the ice crystals. [START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF] quantified the size of ice crystals formed at different freezing protocols (at -20 °C, -80 °C and by immersion in liquid nitrogen) from the cryo-SEM images using gray level granulometry based on mathematical morphology. They reported that the size of ice crystals was between 10 and 30 μm after freezing at -20 °C and below 5 μm for faster freezing at -80 °C and by immersion in liquid nitrogen conditions. Since we were not able to quantify the size of ice crystals, a direct comparison with their results remained difficult.

CLSM analysis

CLSM images of fresh and frozen-thawed potatoes are presented in Figure 13. This method provides information about the status of the cell such as the shape of cells and integrity of the cell wall. Compared to the fresh sample, the cells were highly disorganised and distorted in SF samples. The altered shape of the cells and damaged cell wall structures in the slowly frozen sample can be observed in the CLSM images (Figure 13). The buckled and folded cell wall structure in SF samples indicated a major dehydration related damage that generally happens at lower freezing rates [START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF][START_REF] Gao | Mechanisms of Cryoinjury in Living Cells[END_REF][START_REF] Mazur | The role of intracellular freezing in the death of cells cooled at supraoptimal rates[END_REF][START_REF] Mazur | Freezing of living cells: mechanisms and implications[END_REF]. IF process affected the cell shape as cell walls were found slightly distorted, while IF seemed to have fairly preserved the integrity of the cellular structure and avoid cell wall rupture as observed by SF. Moreover, extracellular spaces that can be generated due to the freezing-thawing process were observed in IF samples (Figure 13c), while it was missing in FF samples (Figure 13d). It can be seen (Figure 13c and Figure 14c) that these gaps were adjacent to the shrunk cells, which clearly indicates the dislocation of water from the inner of the cell to the extracellular space. It was difficult to distinguish freezing-thawing induced gaps between the cells in SF sample as the structure was completely destroyed. FF condition helped to preserve the original shape and integrity of the cellular structure. The results from CLSM (in terms of cell morphology) were coherent with the results from cryo-SEM. [START_REF] Charoenrein | Effect of freezing rates and freeze-thaw cycles on the texture, microstructure and pectic substances of mango[END_REF] used CLSM to study the effect of freezing rates and freezethaw cycles on the cellular structure of mangoes. Using this method, they were able to observe the freezing-thawing related degradation of cellular structure. Moreover, based on CLSM images, they were able to discriminate the different freezing protocols (i.e. freezing at -80, -40 and -20 °C). For instance, CLSM micrographs depicted that cells observed after fast freezing (at -80 °C) and thawing suffered a minimal amount of degradation; the cells were still round and similar to cells from fresh tissues. The IF frozen (at -40 °C)-thawed sample showed a slightly flat cellular structure, while the slow frozen (at -20 °C)-thawed mangoes exhibited larger changes. The cells of the slowly frozen samples lacked uniformity and some intercellular spaces were also observed in slowly frozen tissues. [START_REF] Sirijariyawat | Texture improvement of fresh and frozen mangoes with pectin methylesterase and calcium infusion[END_REF] used CLSM to study the change in cellular morphology in mangoes upon freezing-thawing. They reported that freezing (at -50 °C) followed by storage (at -20 °C chest freezer for 14 days) and thawing (at 4 °C for 2 h and kept at 25 °C for 30 min prior to analysis) of mango samples transformed the well-defined circular to elliptical regular cells of fresh sample to irregular shaped cells with disintegrated cell wall.

Conclusions

In this study, potato samples were frozen under different freezing regimes and their quality were evaluated using different techniques. The slowly frozen (-18 °C) potatoes exhibited supercooling during freezing while no supercooling was noticed for other freezing conditions Intermediate freezing rate process led to relatively fine ice crystals compared to slow freezing process. Although IF process led to greater cell wall structure integrity, however, it was not able to preserve the cell shape. The fast freezing process not only promoted the formation of very fine ice crystals but also preserved the morphology of the cells. The NMR analytical parameters, texture and drip loss showed limitations to differentiate the different freezing protocols. . None of the freezing protocols preserved the colour parameters of the fresh potato.

Benchmarking of freeze damage assessment methods for vegetables on the basis of efficiency, accuracy, cost-of operation, and ease of operation

In this section, freeze damage assessment methods used during this study were evaluated based on various benchmarking parameters and a decision table (dedicated to benchmarking study) was proposed. Table 3 summarizes the results obtained within this study. Pros and cons related to the different methods considered in this study for assessing the freeze damage in potato were discussed.. These observations would provide useful information about the analytical techniques that can be used to estimate freeze damage efficiently.

The focused freeze damage assessment technologies like CLSM, and global freeze damage assessment techniques like texture analysis (also includes laser-puff texture analysis), low field NMR relaxometry, and colour analysis tests used in this study was found to be relevant methods to distinguish the fresh samples from frozen/thawed sample.

The acquired results suggest that cryo-SEM and CLSM are suitable for validating minor quality changes among the different freezing protocols. Meanwhile, the global methods such as texture, NMR, and drip loss can only reflect larger quality changes.

In order to compare freezing protocols, colour analysis was found to be an unsuitable parameter.

Efficiency and accuracy wise, cryo-SEM and CLSM can be termed as best methods to analyze the freezing injuries.

NMR, cryo-SEM and CLSM techniques are expensive techniques, whereas texture analysis, drip loss measurements, colour analysis are cost-effective technologies. The analyses time for NMR is long, while other methods take substantially less time.

From a global point of view, a debate could be opened on which is the most relevant technique to assess freeze damage. Two key parameters can be tackled, (i) the size of the field that is embraced by the technique and (ii) the representative size of the technique. For example, NMR will tackle a sample of ca 1 cm and will provide information at the level of a water molecule (2.75 Å). Cryo-SEM will look at field of ca 100 µm with information at nanometer scale, even though in this case the freeze damage is observed at the scale of an ice crystal (circa 10 µm). The ratio between the size of field and the representative size of technique could be considered as a kind of "freeze damage assessment index" (FDA Index) to assess the relevance of each technique. The higher the FDA index will be, the useful will be (a priori) the technique. From such point of view NMR looks like the best candidate, even though the interpretation and quantification of the freeze damage based on " and " values are not very well documented in the literature and still remain quite subjective. The major concerns relates to the size of the field. Observation of the freeze damage on a single cell can be very informative and detailed, but ca a hundred of cell should be analyzed to obtain an averaged information, which is out of reach for time reasons. Another aspect relies on the possibility to repeat the analysis and on the time needed for a single measurement. CLSM and Cryo-SEM bring informative images that can help to visualize the defaults and that can support observations done with other techniques at a broader field like NMR, texture, drip losses. The precision of the analytical method is one of the most important factors when choosing the methods for freeze damage assessment. A method that imparts minimum error to the measured result will help in better understanding of the impact of process conditions on the sample. Based on the error calculations made for the quantitative methods (Table 3), the drip loss measurement seemed to be more satisfactory , followed by colour analysis, hardness analysis, deformation analysis by the laserpuff tester, NMR analysis and Young's Modulus analysis. Overall, the error imparted by the analytical techniques were quite low in values.

The proper assessment of freeze damage remains a challenge and requires a mass of experimental work before drawing any conclusion. However, this comparative study is maybe the first one that proposes a benchmarking of so many different analytical techniques often considered to assess the freeze damage.

Captions for the Figures

Figure 1: Load-strain curve providing detail about the firmness of the potato during the compression tests. Figure 2: Laser-puff firmness testing prototype. Figure 3: A representative deformation curve obtained while performing the laser puff test. Conversion of volts to mm: 1 V = 2 mm. Figure 4: Illustration of sample preparation step prior to imaging in cryo-SEM. Figure 5: Protocol followed for CLSM imaging of unblanched potato. Figure 6: Representative freezing curves of potatoes under different freezing methods. Captions for Tables Table 1. Effects of different freezing protocols on the freezing properties of potatoes.

Table 2. Textural parameters measured for potatoes under different freezing conditions.

Table 3. Benchmarking study on freeze damage assessment methods.

  (Solanum tuberosum L. cv. Innovator) were the food matrix chosen for this benchmarking study. McCain Foods (Harnes, France) kindly supplied us potato batch having uniform size and maturity. Two batches of potato were used for this test. The first batch of potato was used for NMR tests. In order to reduce the variability, for each freezing condition, samples intended for NMR test were taken from the same potato. Potatoes from the second batch were used for time-temperature history study and freeze damage assessment tests. The average moisture content of both batches was 75.70 ± 1.40% (wet basis) (Note: the values of moisture content are presented here as mean ± standard deviation. Similarly, the values for other parameters in the entire manuscript are expressed as mean ± standard deviation).

  stages i.e. the supercooling, nucleation, and phase change. Meanwhile, intermediate freezing (IF) exhibited only two stages (i.e. nucleation and phase change stages) and fast freezing (FF)

  [START_REF] Chassagne-Berces | Freezing protocol effect on quality properties of fruit tissue according to the fruit , the variety and the stage of maturity[END_REF], lower dehydration associated with small ice crystals induced less breakage of cell walls, and hence, better texture preservation was achieved at higher freezing rates when compared to the slow freezing rate. The high freezing rates also decrease the collapse of cell walls and generate less intercellular spaces, and hence result in better texture preservation[START_REF] Chassagne-Berces | Changes in texture, cellular structure and cell wall composition in apple tissue as a result of freezing[END_REF]. Besides, Phinney, Frelka, Wickramasinghe, & Heldman (2017) reported that the extent of texture loss of potato depends on the freezing time. It was found that the hardness of thawed potato reached a maximum value when the freezing time decreased dramatically up to 1000 s. Further, increase in freezing time beyond 1000 s to around 5000 s did not cause any further texture loss in their case.Van Buggenhout et al. (2006) evaluated the effect of three different freezing conditions i.e. slow freezing (freezing time (ft) = 300 min), rapid freezing (ft = 40 min)) and cryogenic freezing (ft = 10 min)) on the hardness retention of thawed carrots.

  and b). It was observed that " % component values (relaxation time and proton population) for IF and FF conditions were not significantly different (p > 0.05) between each other, meanwhile, these values were significantly different (p < 0.05) with that obtained for SF condition. The lowest value of " % time observed for slow freezing (0.72 ms instead of around 0.80 ms for the other freezing conditions) can be explained by a greater destruction followed by a diffusion of "solutes" inducing a relative increase in viscosity[START_REF] Lahaye | Water mobility and microstructure evolution in the germinating medicago truncatula seed studied by NMR relaxometry. A revisited interpretation of multicomponent relaxation[END_REF]. The " & component relaxation times for all freezing conditions were not different from each other. But, the " & component proton population was significantly lower (p < 0.05) for SF compared to the other conditions. This seemed to indicate the loss of fluid from the respective water compartment due to greater damage occurred during SF process. No significant difference (p > 0.05) (with respect to " & component proton population) was observed among IF and FF samples.

  (i.e. -30 °C-intermediate freezing process and -74 °C-fast freezing process). The initial freezing point (initial freezing temperature) could be detected for slow freezing and intermediate freezing conditions, while it was hard to detect the initial freezing point for the fast freezing condition. The initial freezing point temperature data for slow freezing and intermediate freezing conditions revealed that a depression in freezing point occurred when freezing rate was increased. The slow freezing process resulted in coarser ice crystals and also caused the highest damage to the cellular structure. The cells were highly distorted (deformed cells with buckled and folded cell wall structure) when the slow freezing condition was used.

Figure 7 :

 7 (a) Deformation curve obtained for fresh and frozen-thawed samples (conversion of volts to mm: 1 V = 2 mm) and (b) deformation values (in mm) for fresh and frozen-thawed potatoes (under different freezing rates) acquired using laser-puff firmness tester. SF (slow freezing at -18 °C), IF (intermediate freezing at -30 °C) and FF (fast freezing at -74 °C).

Figure 8 :

 8 Figure 8: Distributions of relaxation peak components ((a) " * and (b) " ) at -20 °C of potato samples frozen by various freezing protocols: slow freezing at -18 °C (red lines), intermediate freezing at -30 °C (blue lines), and fast freezing at -74 °C (black lines). (The x-axis correspond to the relaxation times expressed in ms (milliseconds).

Figure 9 :

 9 Figure 9: " relaxation peak data of frozen-thawed potatoes at 4 °C: (a) fresh sample, (b) after freezing at -18 °C (c) after freezing at -30 °C and (d) after freezing at -74 °C.

Figure 10 :

 10 Figure 10: Effect of different freezing conditions on the drip loss of potato.

Figure 11 :

 11 Figure 11: Effect of freezing protocols on color parameters (a -L * value or Lightness, b -a * value or Redness, c -b * value or Yellowness and d -∆E) of potato. Mean values of 9 repetitions are represented with confidence interval. Figure 12: Microstructure of potato before and after freezing under the different freezing protocols. (a, b) environmental SEM images of the fresh cell showing the cellular structure and starch granules imbedded into it. Cryo-SEM after freezing at -18 °C-SF (c, d), at -30 °C-IF (e, f) and at -74 °C-FF (g, h), respectively. White colored arrows in images are pointing the cells containing ice crystals. Red arrow showing the area where the breakdown of cell structure happened. Orange arrows indicate the cells that might have transformed from polyhedral to almost round shape. Other abbreviations in the picture are A: air space; S: starch granule; W: cell wall structure.

Figure 13 :

 13 Figure 13: Microstructure evaluation using CLSM: (a) fresh potato, (b) frozen-thawed after freezing at -18 °C-SF, (c) at -30 °C-IF and (d) at -74 °C-FF. Other abbreviations in the picture are S: starch granule, W: cell wall, Sp is probably the gap created when of cell moved apart from each other as a consequence of freezing-thawing. The red arrows indicating the deformed, distorted and shrunk cells. Orange arrows indicating loss of regularity of the cell

Figure 14 :

 14 Figure 14: Microstructure evaluation using CLSM: (a) single cell of fresh potato, (b) single potato cell (imaged in frozen state) after freezing at -18 °C (SF), (c) frozen-thawed potato structure after frozen at -30 °C (IF) and (d) frozen-thawed potato structure after frozen at -74 °C(FF) (d). Sp is probably the gap between the cells created due to freezing-thawing process. Black arrow showing a part of broken cell wall. White arrow indicating discontinuity in the cell wall structure. Red arrow evince the deformed cell with irregular cell wall structure (orange arrows).

Acknowledgements:

This work received financial support from the French National Research Agency (ANR) and the Swedish Research Council FORMAS under the FREEZEWAVE project (SUSFOOD-ERANET, FR: ANR-14-SUSF-0001, SE: 2014-1925). We would like to thank Anthony Ogé (ONIRIS) for designing the laser-puff firmness tester. A special thanks to McCain food for supplying potatoes required for the experimentation. The authors would also like to thank Romain Mallet (Univ-Angers -SCIAM) for their assistance in cryo-SEM imaging respectively.


Tangi Aubert

Dr Fabien Grasset
email: grasset@univ-rennes1.fr

Stéphane Mornet

Etienne Duguet

Olivier Cador

Stéphane Cordier

Yann Molard

Valérie Demange

Michel Mortier

Dr Hajime Haneda
email: haneda.hajime@nims.go.jp

Functional Silica Nanoparticles Synthesized by Water-in-Oil Microemulsion Processes

Colloid-in-Water-in-Oil (C/W/O) microemulsion is a wellsuitable confined reacting medium for the synthesis of structured functional nanoparticles of controlled size and shape.

Introduction

Multi-functional silica nanoparticles (NPs) have tremendous potential applications as magnetic indicators and/or photon sources for a number of biotechnological and information technologies. Indeed, the chemistry of silica gained recently in interest in the design of new nanosized particles with functional architecture for applications in biotechnology and photonics [1,2].

Silica NPs are actually very promising candidates in the fields of bio-labelling, imaging, separation, diagnosis and therapy [3][4][5] and band-gap photonic materials when assembled in colloidal crystals [6,7]. These applications all require size-controlled, monodispersed, bright and/or magnetic NPs that can be specifically conjugated to biological macromolecules or arranged in higher ordered structures. Also the preparation of such functional NPs involves a very good understanding of the influence of the synthesis parameters in order to control the properties of the final product such as size, morphology, effects of the shell on the core particle, etc. Considering those demands, synthesis in microemulsions appeared as a promising route for the preparation of such complex silica NPs with a diameter below 100 nm [8]. Such a confined environment was involved during the last decade in our research activities to synthesize silica NPs with several types of nanostructures and properties [START_REF] Mornet | Ferrites: Proceedings of the 8 th International Conference on Ferrites (ICF8)[END_REF][START_REF] Grasset | [END_REF][11][12][13][14][15][16]. This contribution summarizes our own results on the synthesis through water-inoil (W/O) microemulsion and characterization of core-shell morphologies M@SiO 2 (M = γ-Fe 2 O 3 , ZnFe 2 O 4 , CeO 2 , Cs 2 Mo 6 Br 14 ) in the form of colloids or functional thin films. The different materials were studied by UV-Vis-NIR spectroscopy and dynamic light scattering (DLS) and characterized by X-ray diffraction data (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM) and magnetometer SQUID analysis.

Microemulsions for M@SiO 2 NPs synthesis

Microemulsions are thermodynamically stable dispersions of two immiscible fluids stabilized by the arrangement of surfactant molecules at the interface [17] : water-in-oil (W/O), oilin-water (O/W) and water-in-supercritical CO 2 (W/sc-CO 2 ). Three factors characterize a microemulsion: transparency (optical isotropy), droplet size (6 to 80 nm) and stability (thermodynamic) [START_REF] Kumar | Handbook of Microemulsion Science and Technology[END_REF]. This microreview focuses on w/o microemulsions for the preparation of inorganic nanoparticles, which consist of nanodroplets of pseudo-water phase dispersed in an oil phase and stabilized in spherical reverse micelles created by the surfactant molecules. Those water droplets can then be considered as nanoreactors and by controlling the molar ratio of the mixture oil/water/surfactant, it is possible to predetermine the size and shape of those droplets and, as a consequence, to tailor the size and shape of the final product [START_REF] Pileni | [END_REF]20]. Let us point out that microemulsion is a dynamic system because of the Brownian motion of the water droplets. When two droplets collide, they can fuse and interchange reactants [21,22] (scheme 1). This phenomenon is called intermicellar exchange and is strongly dependent on the elasticity of the surfactant film [START_REF] Kumar | Handbook of Microemulsion Science and Technology[END_REF]. Then classically the microemulsion exchange characteristic time τ ex is in the range ≈ 10 μs<τ ex <1 ms depending on the film flexibility i.e. the used surfactant [22]. Nevertheless, the exchange of particles (core nanoparticles and/or condensed nanoparticles) is generally inhibited, depending on the size of the particles, by the inversion of the film curvature [21,22]. Although no information was collected in the synthesis described here about the importance of these intermicellar exchange phenomena and the film flexibility, it is expected to act up on reactants exchange during the hydrolysis process [START_REF] Grasset | [END_REF].

Microemulsion was first used at the end of the 80's by several groups in order to control the synthesis of monodispersed SiO 2 nanoparticles [23][24][25]. The synthesis of silica requires an alkoxyde precursor, water and often a base for catalyzing the hydrolysis and condensation steps [13,[23][24][25][26].

The size of the monodispersed silica nanoparticles can be controlled from few ten nanometers to hundred nanometers. Moreover, since Chang et al. proposed to use microemulsion process to synthesize CdS@SiO 2 nanoparticles [8], a lot of studies have been published on the synthesis of functional silica nanoparticles with magnetic and/or optical properties [START_REF] Grasset | [END_REF]12,14,15,[27][28][29][30][31][32][33][34][35][36][37]. In the most common microemulsion processes, nanoparticles are obtained by simple mixing of two waterin-oil microemulsions, one containing a salt or a complex of metal (reactant #1) while the other contains a precipitating agent (reactant #2) [see scheme 2 from 38]. Nevertheless, a major drawback with this process remains the effect of the reactants and products on the microemulsion stability domain, particularly the metal concentration in the aqueous pseudo-phase used for precipitation reactions [START_REF] Kumar | Handbook of Microemulsion Science and Technology[END_REF]21,22].

That is why, to avoid this precipitation process, we have proposed an original method to design functional silica nanoparticles, using a colloid-in-water dispersion as the starting water pseudo-phase instead of the metal salt aqueous solution (see scheme 3) [START_REF] Mornet | Ferrites: Proceedings of the 8 th International Conference on Ferrites (ICF8)[END_REF][START_REF] Grasset | [END_REF][11][12][14][15][16]. This colloidal suspension allows the increase of the metal concentration without destabilizing the microemulsion, and avoids a subsequent calcination stage [39,40]. All the syntheses reported in this section were designed to prepare M@SiO 2 monodispersed nanoparticles by W/O microemulsions. Those syntheses are based on a sol-gel reaction in two steps confined into the water nanodroplets: (i) hydrolysis of an alkoxyde precursor, (ii) polycondensation of the hydrolyzed monomers.

Those reactions occur inside the pseudo-water phase droplets and at their interfaces with the oil phase. In more details, our W/O microemulsion process is based on three major reactants: an oil phase, a surfactant with a possible co-surfactant, and complex water phase (acid colloid, TEOS and ammonia). In all the synthesis described here, n-heptane was always chosen as the oil phase because of its low toxicity in comparison with other similar reactants like hexane. Many previous publications report studies on the influence of the surfactant depending on its alkyl chain length, head group size or ionic character. It is well assumed that the choice of the surfactant has a critical influence on the final shape and size of the product synthesized in the microemulsion [START_REF] Kumar | Handbook of Microemulsion Science and Technology[END_REF]22]. It is also recognized that using a co-surfactant leads to a higher fluidity of the interface film between the droplets and the oil phase, resulting in a higher rate of intermicellar exchange, but also in a higher curvature of the droplets, resulting in smaller final particles [41]. For most of the syntheses described here, the chosen non-ionic surfactant was Brij30® (Polyoxyethylene (4) lauryl ether), since it showed the best results in preliminary trials avoiding the use of any co-surfactant. By using Brij30® as the surfactant or co-surfactant, the temperature should be kept below 25°C in order to avoid any possible thermally induced phase inversion. The precursor was chosen to be tetraethylorthosilicate (TEOS) since it can be easily handled in the ambient air, contrary to other precursors like the air-sensitive tetramethoxysilicate (TMOS). As explained below, and contrary to the other published methods, in the present process, the hydrolysis of TEOS was firstly acid catalyzed thanks to the acidic water colloids whereas condensation was base catalyzed with final addition of ammonia. Ammonia has been chosen since it preferentially dissolves in the water phase and easily decomposes without any possible contaminant, contrary to other bases like sodium hydroxide which releases Na + ions that can be adsorbed at the surface of the synthesized particle and form sodium silicate.

The main interest of this proposed W/O microemulsion process is the preparation of multifunctional silica coated nanocrystals M@SiO 2 . Several types of M nanocrystal cores with interesting catalytic, magnetic or luminescence properties have been coated with silica, in order to get functional nanoparticles such as: ZnFe 2 O 4 @SiO 2 [START_REF] Grasset | [END_REF], CeO 2 @SiO 2 [12], Cs 2 [Mo 6 X 14 ]@SiO 2 (X = Cl, Br, and I) [14] and γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 [15]. Detailed description of synthesis process are given in cited corresponding papers. In all those cases, the major key-point is the stability of the starting acidic aqueous sols containing the core. Then they play the role of the aqueous phase in the heptane/surfactant/water mixture with a precisely controlled molar ratio defining the microemulsion. By choosing an appropriate concentration of the sol, it is possible to control the number of nanocrystals as core embedded in the silica nanoparticles. After their addition, organophilic TEOS molecules are more readily dissolved in heptane than in the aqueous droplets. While diffusing into the acidic aqueous droplets, TEOS is hydrolyzed:

Si-(OC 2 H 5 ) 4 + mH 2 O → Si-(OC 2 H 5 ) 4-m (OH) m + mC 2 H 5 OH
It is well-known that the number of nuclei will increase with rapid hydrolysis [26]. Thus, as for this microemulsion technique an acid catalysis is involved in the first step, a large number of nuclei are quickly generated resulting in a decrease of the final particle size. After completion of the hydrolysis process, aqueous ammonia solution is added to the mixture in order to base-catalyze the condensation of the hydrolyzed monomers inside the droplets by increasing the pH. The condensation induces the formation of Si-O-Si or Si-OH-Si bonds via olation, oxolation or alcoxolation. According to Finie et al. [26], after 30' in acidic condition, all the monomeric species of TMOS have been hydrolyzed and consequently have migrated into the droplets for condensation and formation of SiO 2 . Base catalysis of silica sol-gel reactions promotes condensation. Rapid condensation results in fast consumption of all precursors inside the micelles and in the formation of a dense silica structure. Moreover, a high dissolution rate ensures the production of spherical and dense particles by the ripening of potential aggregates formed during the collision of droplets containing nuclei. This leads to the production of a fairly homogeneous and monodisperse population of particles which are subsequently washed with n-heptane, ethanol and acetone in order to remove oil and surfactants. The particles are separated from the liquid phase by centrifugation and finally dried in a vacuum oven at 60°C or simply in the air at room temperature. The procedure for the CeO 2 @SiO 2 nanoparticules synthesis is summarized in figure 1 [12]. The scattering is due to the size of the CeO 2 core (diameter centered around 40 nm, see figure 2).

Characterization of the prepared NPs

Size and morphology

As previously explained, one of the most important issue in this microemulsion process is the stability of the colloid-in-water dispersion used as starting pseudo-water phase. Dynamic Light Scattering (DLS) technique is widely used to characterize the size of the performed nanocrystals as well as the size of the droplets in the microemulsion since this parameter is reliable to that of the final particles. The DLS technique measures the particle or droplet light diffusion due to Brownian motion and relates it to its hydrodynamic diameter by using the Stokes-Einstein equation. This technique gives useful informations about the hydrodynamic diameter and polydispersity of the nanocrystals dispersed in the droplets. An example is given in figure 2 showing two different CeO 2 dispersions with a hydrodynamic diameter of 7 nm and 40 nm respectively [12].

Microscopy techniques such as Scanning Electron Microscopy (SEM) or High resolution

Transmission Electron Microscopy (HRTEM) are also useful to get data about the shape and morphology of the prepared silica nanoparticles. The size of the monodispersed silica nanoparticles can range from few ten-nanometers to hundred nanometers with a good control as observed by SEM in figure 3a. HRTEM with HAADF-STEM mode (High-Angle Annular Darkfield-Scanning TEM) in particular is very powerful to determine the arrangement of the core particles within the silica shell. Figure 3b shows examples of ferrite nanocrystals and [Mo 6 Br 14 ] 2-clusters embedded in a silica particle [15].

Magnetic properties

For nanoparticles with interesting magnetic properties (γ-Fe 2 O 3 @SiO 2 [11] ; ZnFe 2 O 4 @SiO 2 [START_REF] Grasset | [END_REF]42] and γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 [15]), the evolution of magnetization versus temperature was studied in both DC (ZFCM (Zero Field Cooled Magnetization) and FCM (Field Cooled Magnetization)) and AC modes with a SQUID magnetometer. Through this study, we demonstrated clearly that the surface of SiO 2 induced systems with a minimum degree of aggregation and modified strongly the interactions between magnetic nanocrystals and most likely surface effects.

After the coating of each magnetic nanocrystals, significant changes in the magnetic behavior could be highlighted, particularly with regard to the blocking temperature [START_REF] Grasset | [END_REF]42].

As first example, a system consisting of aggregated or silica coated zinc ferrite nanocrystals was studied using DC and AC magnetization measurements [START_REF] Grasset | [END_REF]42]. The temperature dependence of the ZFCM and FCM curves of an aggregated or silica coated sample recorded under 10 Oe are presented in figure 4. The ZFCM increases with increasing temperature, passing through a broad maximum at Tmax = 32.5 K. On cooling, the FCM coincides with the ZFCM down to 30 K and then both curves significantly differ on cooling. As a result, the FCM also passes through a maximum at Tmax, but much less pronounced than in the ZFCM mode. One of the striking features of the silica coated nanocrystals is that the broad maximum on the FCM curve has disappeared compared to the uncoated ones. The FCM increases as the temperature is lowered and tends to saturate in the low-temperature limit as usual for superparamagnetic entities (figure 4).

For the aggregated nanocrystals, a superparamagnetic-super-spin-glass phase transition at Tg was identified and explained clearly these behaviors. The relaxation time diverges at Tg and the nonlinear susceptibility shows an abrupt increase. This critical behavior vanishes when the nanocrystals are not in close contact in case of silica coating particles or dispersed sols [START_REF] Grasset | [END_REF]42].

Moreover, the first observation of the memory effect in oxide nanocrystals is identical to what has been already discovered in canonical spin-glass, supporting the existence of a true thermodynamic transition in agglomerated zinc ferrite magnetic nanoparticles (figure 5).

As second example, it was demonstrated that the silica coating of single γ-Fe 2 O 3 nanocrystal induced a shift of the transition temperature of maghemite (γ-Fe 2 O 3 ) into hematite (α-Fe 2 O 3 ). Indeed, classically maghemite turns hematite at 450°C [START_REF]De la solution a` l'oxyde[END_REF] while after coating it remains stable until 1000°C [11]. The magnetic studies realized on non-coated and coated nanocrystals have shown (i) a shift to lower value of the blocking temperature as observed in the magnetic curve recorded as a function of temperature by cooling the sample in zero-field (ZFCM) revealing a significant decline of magnetic interactions between the nanocrystals after coating; ii) the preservation of inverse spinel structure with ferromagnetic behavior up to 1000°C (figure 6).

Moreover, we should notice that in addition to these magnetic characterizations, studies by X-ray diffraction showed that the silica shell acts as well as a diffusion barrier up to 1000°C.

In conclusion to this part, it has been clearly shown through several examples that the average magnetic behavior for magnetic nanocrystals depends on their environment and that the magnetic properties of these nanocrystals at low temperature are essentially governed by the interface particle-habitat.

Potential application of the prepared NPs

Superscratch-resistant glass [13]

Silica nanoparticles can also be used to prepare functional thin films. Tartivel et al. made thin films of pure silica particles on glass slides in order to get superscratch-resistant transparent glasses [13]. Thin films were obtained by dip-coating of a soda-lime silica (SLS) glass slide directly in the microemulsion. Then, the samples were heated for 15 min at 400°C in air, both to drive silica condensation and particle formation and to remove the organic phases. Indentation (Vickers) scratching experiments were conducted to estimate the resistance toward mechanical damage, with a load increasing from 0 to 2.5 N and a loading rate of 0.01 N.s -1 . The loading cycle typically leads to three different regimes as the load increases: the micro-ductile regime, the micro-cracking regime and the micro-abrasive regime. Figure 7 shows pictures of the resulting glass slides after application of this loading cycle for both coated and uncoated samples. It appeared that coated samples show a longer micro-ductile regime, with the micro-cracking and micro-abrasive regimes occurring at higher load compared to uncoated SLS slides. As a consequence, the coated samples did not show any sub-surface lateral crack and remain optically transparent, while the uncoated samples exhibit large cracks that scatter light.

CeO 2 @SiO 2 anti-UV nanoparticles [12]

CeO 2 @SiO 2 dispersible nanopowders and thin films were prepared with the same procedure as previously described. The CeO 2 nanocrystals display very promising UV-absorption properties.

However, three important issues must be previously solved: a refractive index equal to 2.50 at λ = refractive index of such nanoparticles is to coat them by a thin layer of a material displaying a much lower refractive index such as silica (n = 1.45) [46]. Another way is to replace a part of the CeO 2 network anionic O 2-ion by low-polarizability anions such as F - [START_REF] Sronek | [END_REF].

In our recent study, it was possible to prepare core-shell and monodispersed spherical silica nanoparticles with a core of CeO 2 by the technique of w/o microemulsion. The thickness of the silica shell could be controlled and ranges from 5 to 20 nm [12]. The use of concentrated colloidal solutions of CeO 2 allowed preparing CeO 2 @SiO 2 systems containing more than 25% (weight mass) of CeO 2 . Figure 8 shows UV-Vis absorption spectrum of those prepared CeO 2 @SiO 2 nanopowders, which confirms the absorption in the UV domain. These functional nanoparticles could be useful (i) for reinforcement of glassy surface materials (ii) during the chemical-mechanical planarization (CMP) process in semiconductor industry. Nanoparticles with simultaneous luminescent and magnetic properties should find interesting applications in nano-biotechnologies . Magnetic properties could make the particle suitable for bio-imaging techniques such as Magnetic Resonance Imaging (MRI) or hyperthermia therapy [72] and luminescence properties could allow an optical tracing of the particles [73]. Moreover silica coated particles are good candidates for such applications since silica is a particularly inert material, it could prevent the diffusion of toxic metal cations from the cores and its surface could be easily functionalized by further treatment in order to get a bio-compatible, targetable and dispersed material at neutral pH. Indeed, for imaging applications, the current probes (organic dyes or Quantum Dots) encounter several challenges, such as limited tissue penetration and potential toxicity. To address these needs, it is important to develop new low toxicity near-infraredemitters coupled with silica coating in order to improve tissue penetration depth and colloidal stability [14,15,37,[74][75][76]. Recently, we have demonstrated the preparation of stable colloidal acidic sols containing [Mo 6 Br 14 ] 2-1 nm size cluster units and their dispersion in silica to form luminescent Cs 2 Mo 6 Br 14 @SiO 2 nanoparticules [14]. Let us recall that [Mo 6 Br 14 ] 2-units are based on a rigid Mo 6 Br i 8 cluster core additionally bonded to six apical ligands (Br a ). They are obtained by solid state chemistry route and can be used as soluble building blocks either directly or after functionalization, for the synthesis of various hybrid architectures including dendrimers and extended molecular arrays [77][78][79]. Particularly interesting are their photoluminescent properties characterized by a large emission region in the red and near infrared window (580-900 nm) [80,81].

Such wavelengths are weakly absorbed by tissues and blood constituting the human body [76,81].

Bifunctionnal magnetic and luminescent γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 structured nanoparticles were recently obtained by a one pot synthesis by C/W/O microemulsion [15]. γ-Fe 2 O 3 magnetic nanocrystals are located in the core of the nanoparticle and [Mo 6 Br 14 ] 2-are homogeneously dispersed in the silica matrix.

Figure 9 shows the emission spectrum of the particles after an irradiation at λ exc = 546 nm producing an intense red luminescence corresponding to the emission of the [Mo 6 Br 14 ] 2-units. The insert in figure 9 shows nicely the effect of an applied magnetic field along the wall of a cell containing a dispersion of such nanoparticles in an aqueous ethanolic solution (pH=8) as a function of time. The magnetization of those particles was also checked in both ZFC and FC modes, and the magnetic behavior was found to be typical of moderately monodispersed superparamagnetic ferrite nanocrystals dispersed in silica matrix [15].

Conclusion and Perspectives

This work has demonstrated that the W/O microemulsion method is sufficiently robust and efficient to be complementary with other techniques such as the Stöber's method for the preparation of monodisperse functional silica particles with a diameter below 100 nm. This highly reproducible technique can be used to prepare successfully complex M@SiO 2 nanoparticles (ZnFe 2 O 4 @SiO 2 , γ-Fe 2 O 3 @SiO 2 , CeO 2 @SiO 2 , Cs 2 Mo 6 Br 14 @SiO 2 ) with a high control in shape and size in the nanometric range (< 60 nm). The advantage of this W/O microemulsion process as compared to the Stöber's method is well demonstrated in the preparation of monodispersed bi-functional nanoparticles with complex architecture like γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 nanoparticles. Moreover, this method should be very useful for the encapsulation of polymer particles or unstable particles in acidic media. Such particles present a real interest for a wide range of applications such as bionanotechnology, catalysis, mechanical reinforcement of substrates, etc... However, further improvements remain to be done like, for example, bio-imaging applications: the actual excitation wavelengths used to observe an efficient luminescence of the clusters are located in the absorption band of tissues and organs constituting the human body. One solution could be to combine those clusters with rare earth elements to form an up-conversion system and allow the excitation of the clusters at low-energy wavelengths which would not be absorbed by the human body (e.g. Near-IR range). Finally, the toxicity of such particles should also be thoroughly investigated.

4. 3 .

 3 γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 nanoparticles for bio-imaging[15]

Scheme and figure captions Scheme 1 .Fig. 1 .

 11 Scheme and figure captions

Fig. 2 .

 2 Fig. 2. Dynamic light scattering of two CeO 2 colloidal sols.

Fig. 3a .

 3a Fig. 3a. SEM images of monodispersed silica nanoparticules. 3b. HAADF-STEM image γ-of Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 nanoparticles.

Fig. 4 .

 4 Fig. 4. Temperature dependence of the ZFCM and FCM curves of an aggregated (right) or silica coated (left) sample recorded under 10 Oe .

Fig. 5 .

 5 Fig. 5. Observation of the memory effect in zinc ferrite nanocrystals.

Fig. 6 .

 6 Fig. 6. Field versus temperature curves of γ-Fe 2 O 3 @SiO 2 nanoparticles.

Fig. 7 :

 7 Fig. 7: Scratch test patterns for a 0-2.5 N loading frame for a) SLS glass (substrate) annealed 15 min at 350°C, and b) nanoparticles-based coating on the same substrate.

Fig. 8 :

 8 Fig.8: UV-Vis absorption spectrum for core-shell CeO 2 @SiO 2 nanoparticles; Insert : HRTEM image of core-shell CeO 2 @SiO 2 nanoparticles.

Fig. 9 :

 9 Fig. 9: Red emission of γ-Fe 2 O 3 -Cs 2 Mo 6 Br 14 @SiO 2 particles after an irradiation at λ exc = 546 nm. Insert : Optical microscope images using λexc = 405 nm of dispersed nanoparticles under a magnetic field (1.5 T) showing the growth of a nanoparticles layer along the wall of a cell as a function of time.