Novel vegan and sugar-substituted chocolates. Part I: physical-chemical characterization

Novel vegan and sugar-substituted chocolates. 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Part I: physical-chemical characterization Federica Torregrossa, Luciano Cinquanta, Onofrio Corona, Donatella Albanese, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3185753/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The confectionery industry is increasingly adopting new solutions and possible formulations to expand the ranges of chocolate products that support food styles linked to either cultural or health choices. The chemical-physical characteristics of chocolates (dark and milk) produced with traditional formulations or intended for vegan or demanding less simple sugars consumers (with a 10% reduction in calorific value), were analysed. The effects of the substitution of milk with coconut copra, almond and isolated soy proteins, and the replacement of sucrose with coconut sugars, stevia and erythritol, have been accounted for by analysing texture, rheology and water activity, differential scanning calorimetry (DSC) and fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry. The plant-based sample showed lower values for hardness and adhesiveness in the texture analysis, and a larger peak in the melting behaviour at the DSC. Moreover, the substitution of milk powder caused more than a halving of the yield stress and a similar decrease in apparent and Casson viscosity. The crystallisation of cocoa butter in the substituted-sugar sample involved the β V form, the most desirable crystal form in high-quality chocolate. Results by FFC NMR relaxometry allowed identification of differently sized aggregates whose chemical nature is discussed. FFC NMR relaxometry data confirm those by rheological and DSC investigations. vegan chocolate low-sucrose chocolate DSC rheology NMR relaxometry Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sweets farms are looking for new chocolate formulations that can meet dietary styles associated to either cultural choices or intolerances, and pathologies. Increasingly consumers demand less simple sugars in food, including diabetics who must limit or avoid the consumption of mono- and disaccharides. Stevia, as well as erythritol, is a viable alternative for replacing sugars in chocolate, thus making this product more appetible for diabetics [ 1 , 2 ]. Less used is, instead, coconut sugar, a natural sweetener obtained by evaporation of the sap of Cocos nucifera [ 3 ]. Moreover, lactose intolerant or even vegan subjects are unable to consume milk-based chocolates due to the presence of powdered cow milk which is added during chocolate production. As a general remark, addition of milk allows production of sweeter chocolate with more malleability and thermolability than dark chocolate [ 4 , 5 ]. Noticeably, attention must be paid in obtaining chocolate products that must have sensory characteristics like milk- and sugar-containing systems. Chocolate structure is directly related to the size of the tiny particles and crystals deriving from the components of the cocoa butter used during chocolate preparation. The crystalline arrangement of the β form crystals (V) in the cocoa butter allows a melting point between 33 and 34°C [ 6 ]. Chocolate flow properties are important for assessing its structure. Moreover, the taste of chocolate in the mouth is directly influenced by viscosity. Therefore, chocolate bad taste can be perceived when wrong flow/viscosity characteristics are achieved [ 7 , 8 ]. In addition, final chocolate texture, appearance and flavour can be considered as key attributes for consumer choice and acceptability [ 9 – 11 ]. All the aforementioned keys are related to the phase transitions of polymorphic forms in fat systems by their melting points which, in turn, are monitored by differential scanning calorimeter (DSC) [ 12 ]. Chocolate characteristics can be associated also with the molecular dynamics of the complex mixtures making this food product that can be explored by low field NMR relaxometry. This is a fast, reproducible, accurate and non-invasive technique, which can be applied to expand knowledge of chocolate stabilisation characteristics [ 13 , 14 ]. The aim of this study was to evaluate the main chemical-physical properties of novel plant-based and substituted-sugar chocolates. Two different chocolates have been prepared. In milk-less products milk powder was replaced with dried coconut copra, roasted almonds, and isolated soy proteins. In the case of substituted-sugar dark chocolate, sucrose was replaced with stevia, erythritol and coconut sugar. Comparison with traditional products (milk- and sucrose-containing chocolates) was carried out by analysing water activity, fatty acids content, texture, melting point by differential scanning calorimetry (DSC), rheology and fast field cycling NMR relaxometry. Materials and Methods Sampling The chocolate samples were made in an artisan confectionery laboratory (Cappello, Palermo, Italy) using, for both the control and the experimental samples, a refiner with counter-rotating porphyry rollers for mixing (Ing. Polin EC. S.p.A., Verona, Italy) and obtaining the paste of cocoa, and a bench robot set at 60°C for 4 hours of conching. The chocolate obtained was manually tempered on marble and molded into circular shapes in silicone molds with a weight of 7-8g, 4.5 mm of thickness and 35 mm of diameter for each shape obtained. Flow chart of production process is reported in Fig. 1 . Sample coding is as follows: MiC: Mi lk-containing C hocolate VeC : milk-less Ve gan C hocolate DaC : sucrose-containing Da rk C hocolate SuSC: Su bstituted -S ugar C hocolate Raw materials The cocoa mass was purchased from Valhrona (France): respectively Manjari Pur Madagascar 100%, for milk chocolate, and Araguani Pur Venezuela 100% for dark chocolate. The cocoa butter was purchased from ICAM Professional SPA, (Lecco, Italy). Dehydrated coconut (Pearls of Samarkand, Sri Lanka), powdered isolated soy proteins (Natural Soy Isolate, ProLabs, Eros, EuroSup), pure stevia powder (UOP Durante, Italy), and crystal coconut sugar (Monte Nativo, Sri Lanka), were purchased on online marketplace. Almonds were purchased by Musumeci company, (Bronte, CT, Italy). Natural Bourbon vanilla powdered by Vanilla Gourmet (Pescara, Italy); soy lecithin by Nutrition&Santè (Lecinova, Italy); erythritol by Chimpex (Caivano, NA, Italy). The percentage composition of the ingredients in the different samples is shown in Table 1 . The formulation of the SuSC sample results in a 10% reduction in calorific value: about 424.58 kCal 100 g − 1 , compared to 472.67 kCal 100 g − 1 in DaC sample. Table 1 Formulations of milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC). Ingredient % MiC VeC DaC SuSC Cocoa Mass 41 44.6 75 77 Sucrose 34.5 37 24 / Milk Powder 23.5 / / / Almond / 7.5 / / Coconut Copra / 5 / / Isolated soy proteins / 5 / / Erithritol / / / 9.6 Stevia / / / 0.1 Coconut Sugar / / / 12.1 Soy lechitin 0.5 0.5 0.5 0.5 Water activity and dry matter The analysis of the water activity was carried out with the HygroPalm-23 instrument (Rotronic, Basserdorf, Germany) following the ISO 21807:2004 method. The samples were all analysed in triplicate. Dry matter was analysed by using official analytical method (AOAC 930.15, 1990). Texture analysis Texture analysis was performed by using a TaXT2 texture analyser (Stable Microsystem) equipped with a cylindrical probe (P35) with which the chewing test with double compression was simulated. The parameters used for the test were as follows: pre-test speed 2 mm s − 1 ; test speed 2 mm s − 1 ; post-test speed 5 mm s − 1 ; distance 50%; load cell 25 kg. The test was conducted at 18 ± 0.5°C. Differential Scanning Calorimetry The melting profiles of chocolate samples were determined using Differential Scanning Calorimetry (Q Series DSC, TA Instruments, New Castle, Delaware, USA). 5–10 mg of chocolate samples were loaded in an aluminium pan and nitrogen was used as transport inert gas at a flow rate of 50 ml min − 1 . An empty pan was used as a reference, while indium was used for instrument calibration. Samples were initially equilibrated at 20°C and then heated to 60°C at 5°C min − 1 rate. Thermograms were analysed by TA Universal Analysis software (TA Instruments, New Castle, Delaware, USA) defining the melting peak temperature (Tm) and the melting enthalpy (ΔHm). Rheological analysis The rheological properties of chocolate were studied using a Haake Mars III rheometer (Thermo Scientific) equipped with Couette geometry (with coaxial cylinders) with an outer cylinder diameter of 43 mm, the inner one of 41 mm, and a gap of 3 mm. Chocolate flow parameters were determined by following the official method viscosity (ICA, 2000) of cocoa and chocolate products (Analytical method 46. CAOBISCO, Brussels). Chocolate was placed in a closed glass container. It was heated in a benchtop oven at 52°C for at least 1 hour before evaluating the flow properties at 40°C. The test was programmed in 4 steps: 1) pre-shear at a fixed shear rate ( \(\dot{\gamma }\) ) of 5 s − 1 for 5 min; 2) ascending ramp with ( \(\dot{\gamma }\) ) from 2 to 50 s − 1 in 3 min, 3) fixed shear rate at ( \(\dot{\gamma }\) ) = 50 s − 1 for 1 min; 4) descending ramp with ( \(\dot{\gamma }\) ) from 50 to 2 s − 1 in 3 min. The data recorded in the upward flow curve section were then interpolated using Casson's model: $$\sqrt{\tau }=\sqrt{{\tau }_{0}}+\sqrt{{\eta }_{c }\dot{\gamma }}$$ 1 where τ 0 is the Casson yield stress, i.e., the stress required for the fluid to start flowing, and η c is the Casson viscosity indicating the force required to maintain chocolate flow during the test. Thixotropy was measured by the hysteresis area formed by the difference between the upward and downward curves. The larger the hysteresis area, the longer the time needed for the fluid to recover its structure. Fast Field Cycling (FFC) NMR relaxometry Details about the technique have been already reported elsewhere [ 15 ]. Here, only a brief report on the used experimental conditions is reported. All the experiments were conducted on a Stelar Smartracer Fast-Field-Cycling Relaxometer (Stelar s.r.l., Mede, PV–Italy) set at a constant temperature of 25°C. The proton spins were polarized at a polarization field (B POL ) corresponding to a proton Larmor frequency (n L ) of 10 MHz for a period (T POL ) of about five times the T 1 estimated at this frequency. After each B POL , the magnetic field intensity (indicated as B RLX ) was systematically changed in the proton Larmor frequency n L comprised in the range 0.01–10 MHz. The period τ, during which B RLX was applied, has been varied on 32 logarithmic spaced time sets, each of them adjusted at every relaxation field to optimize the sampling of the decay/recovery curves. Free induction decays were recorded following a single 1 H 90° pulse applied at an acquisition field (B ACQ ) corresponding to n L of 7.2 MHz. A time domain of 100 µs sampled with 512 points was applied. Field-switching time was 3 ms, while spectrometer dead time was 15 µs. For all the experiments, a recycle delay of 2 s was used. A non-polarized FFC sequence was applied when the relaxation magnetic fields were in the range of the proton Larmor frequencies comprised between 20 and 10 MHz. A polarized FFC sequence was applied for B RLX values ranging between 3 and 0.01 MHz (Conte, 2021). All the decay/recovery curves acquired by applying the aforementioned experimental runs were exported to OriginPro 7.5 SR6 (Version 7.5885, OriginLab Corporation, Northampton, MA, USA) in order to apply the stretched exponential function (also known as Kohlraush–Williams–Watts function) reported in Eq. ( 2 ) [ 16 ]. $$I\left(\tau \right)={I}_{0}exp\left[-{\left(\frac{\tau }{{T}_{1}}\right)}^{k}\right]+{y}_{0}$$ 2 Here, I(τ) is the magnetization intensity at a given τ value; I 0 is the magnetization intensity at the asymptote of the decay/recovery curve; τ is the period of time during which B RLX is applied; T 1 is the longitudinal relaxation time; k is a parameter accounting for the relaxometry complexity of the samples. Eq. ( 1 ) accounts for the large sample heterogeneity resulting in a multiexponential behaviour of the decay/recovery curves. In particular, this equation can be considered as a superposition of exponential contributions, which describes the likely physical picture of some distributions in T 1 . Its application has the advantage that it is able to handle a wide range of relaxometry behaviors within only one single model. For this reason, any assumption about the number of exponentials to use for modelling the FFC NMR relaxometry data is not necessary [ 15 ]. The NMRD profiles (i.e., R 1 = 1/T 1 -vs-n L curves) were modelled according to the free-model analysis elsewhere reported [ 17 ], to obtain the distribution of correlation times from which information about the dynamic domains in chocolates were obtained. Results and Discussion Water activity and dry matter The MiC and VeC samples showed higher values of water activity than the other two samples (Table 2 ). This can be related to the presence of milk powder in (MiC) and coconut sugar in (VeC), a highly hygroscopic saccharide containing inulin [ 18 , 19 ], whose solubility, wettability and dispersibility have already been studied [ 20 ]. Table 2 Water activity and dry matter in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC). Samples Aw (mean ± st.dv) Dry Matter (%) MiC 0.445 ± 0.014 a 98.44 ± 0.8 a VeC 0.439 ± 0.008 a 98.36 ± 0.7 a DaC 0.375 ± 0.002 b 98.38 ± 0.7 a SuSC 0.378 ± 0.009 b 96.99 ± 0.9 a Different letters mean significant differences (p < 0.05). Differential Scanning Calorimetry The main quality parameters of chocolate, which are good mouth meltability, snapping properties, and glossiness, depend on the crystallization form of cocoa butter (CB) used as fat phase. Differential scanning calorimetry (DSC) is widely used for the evaluation of fat polymorphism and crystal network organization in chocolate (Fig. 1 ). The onset peak corresponds to the temperature at which a specific crystalline form begins to melt, the maximum peak corresponding to the temperature at which the melting curve reaches its peak maximum, the end of melting and the enthalpy related to the whole melting peak (Table 3 ). DaC and SuSC samples show a single peak, and in the case of SuSC a sharp one, with a maximum peak in contrast to MiC and VeC, for which it possible noting the presence of a double melting transition (inset of Fig. 1 ). The melting temperature of the cocoa butter for the polymorphic forms are I (17.3°C), II (23.3°C), III (25.5°C), IV (27.5°C), V β (33.8°C) and VI (36.3°C) [ 6 ]. The maximum peak temperature detected for the chocolate samples shows that the crystallisation of cocoa butter in the SuSC sample is the β V form, the most desirable crystal form in high-quality chocolate. The double melting transition in Mic and VeC sample could be caused by the triglyceride’s composition of milk and coconut copra fat that according with other authors [ 21 ], affect crystallization behaviour of CB. Differences between melting peaks as well as the enthalpy values of DaC and SuSC samples can be due to the different sugar composition. Sugars and their particle sizes also affect the CB crystallization because they represent nuclei which provide the “seed” around which fat crystals grow [ 22 ]. The melting enthalpy in DaC chocolate was significantly higher than those of MiC, VeC and SuSC (p < 0.05) indicating a higher extent of fat crystallization in systems probability due to the simultaneous presence of high amount of CB (75%) and homogeneous sugar phase in systems [ 23 ]. Table 3 Melting properties by Differential Scanning Calorimetry (DSC) in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC). Sample T onset (°C) T peak 1 (°C) T peak 2 (°C) T end (°C) T index (°C) ΔH m [J/g] MiC 25.3±0.2 a 31.47±0.41 a 31.67±0.42 a 34.6±0.1 a 9.33 39.7±8.66 a VeC 25.3±0.4 a 30.97±0.10 a 31.31±0.11 a 34.6±0.5 a 9.32 35.4±11.24 a DaC 25.2±0.3 a 31.64±0.09 b / 35.7±0.9 a 10.45 54.9±8.66 b SuSC 32.0 ± 0.1 b 32.47 ± 0.41 b / 35.8 ± 0.2 a 3.82 33.1 ± 0.02 a Different letters mean significant differences (p < 0.05). Texture Analysis Hardness of chocolate is a good parameter that points out proper control of temperature and stability of the fat crystal network formed during tempering process [ 24 , 25 ]. All treatments (VeC and SuSC) showed hardness values lower compared to the control samples (MiC and DaC) (Table 4 ). These data confirmed that samples with lower melting points tend to have a softer structure at the same temperature [ 26 ], i.e. , when subjected to the stress of texture analysis, showing a lower resistance to probe penetration. DSC results also showed a lower Tpeak for VeC sample, related to the lower point of fusion. VeC sample also had the lowest value of adhesiveness. Hardness value was highest in DaC, because of the absence of any other substances that can affect the structure of the chocolate. SuSC had the lower hardness value than (DaC) sample, owing to the presence of coconut sugar, highly hygroscopic sweetener containing a significant amount of inulin (about 5 g 100g − 1 ) [ 19 ]. Data confirmed that sucrose replacement with high ratios of sugar substitutes provide low hardness values respect to the controls [ 27 ]. Table 4 Texture parameters in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC). Samples height (mm) hardness (g) adhesiveness (g s) MiC 5.18 ± 0.30 12534 ± 530 -0.82 ± 0.76 VeC 4.50 ± 0.36 7836 ± 303 -17.9 ± 8.84 DaC 5.43 ± 0.40 21760 ± 323 -2.22 ± 1.36 SuSC 4.47 ± 0.48 9688 ± 1521 -0.35 ± 0.36 Rheology It is well known that chocolate does not usually have Newtonian behaviour, which was also confirmed for the samples analysed, all of which exhibited the characteristics of Casson's plastic fluid. Chocolate rheology is usually quantified using parameters like yield stress (τ 0 ) and apparent (plastic) viscosity (measured at shear rate 5 s − 1 ). Yield stress is a material property and is the stress corresponding to the yield point at which the material begins to deform plastically [ 7 ]. Results of flow curves data fitting to the Casson equation and the measurement of the hysteresis area (thixotropy) are shown in Table 5 . For all the samples, the shear rate applied resulted in a non-linear response in terms of shear stress (Fig. 2 ) indicating that chocolate aggregates aligned to the flow as the shear rate increase thus opposing less resistance, which is the reason why chocolate samples showed shear thinning behaviour. As for τ 0 values, the new formulations showed an opposite trend. In fact, in vegan chocolate, the substitution of milk powder caused more than a halving of the yield stress and a similar decrease in apparent and Casson viscosity. These data, consistent with the texture value showed a variation in the rheological properties of vegan chocolate compared to traditional one. The differences between dark and sugar-substituted chocolate showed an inverse trend in τ 0 values, which increased significantly (almost 70%) with sugar substitution, while the increase in viscosity was smaller (about 9%). This last was consistent with other results [ 28 ], in which dark sweetened with isomalt presented higher Casson viscosity than that of the sucrose containing chocolate, confirming that the chocolate formulations comprising high levels of sugar substitutes had higher apparent and Casson viscosity, and yield stress than the those of the control [ 29 ]. Thixotropy is a function of time-dependent fluid and can be evaluated through apparent viscosity or shear stress decreasing with the time of shear at constant rate. Thixotropy is calculated from the area of loop or a specific point on the ramp curves of shear stress or apparent viscosity at a specific shear rate [ 30 ]. Values reported in Table 5 were calculated as the area of loop formed between the upward and downward flow curves and as can be observed all samples showed thixotropic behaviour. Considering the thixotropic data [ 31 ], it appears that the VeC and SuSC samples have a more complex structure than the related reference chocolates (MiC and DaC). Table 5 Rheological properties in milk chocolate (MiC); vegan chocolate (VeC); dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC) Samples η app (Pa s) shear rate 5/s τ 0 (Pa) η c (Pa s) Thixotropy (Pa/s) MiC 23.8 6.55 ± 0.03 1.02 ± 0.002 335.3 VeC 11.5 2.87 ± 0.02 0.56 ± 0.001 524.8 DaC 13.2 3.82 ± 0.04 0.50 ± 0.002 106.6 SuSC 17.6 6.45 ± 0.03 0.54 ± 0.001 445.5 Fast Field Cycling (FFC) NMR relaxometry In Fig. 3 , Nuclear Magnetic Resonance Dispersion (NMRD) profiles, reporting the longitudinal relaxation rate as a function of the Larmor frequency of the applied electromagnetic field, is shown. VeC sample (the vegan chocolate) with fat replacers of milk powder, shows the lowest relaxation rate as compared to the other samples. This is justified by the different molecular motion affecting the fluctuation of the local electromagnetic field. A faster molecular motion is related to longer relaxation times T 1 and slower relaxation rate values [ 32 ]. In this case, it is possible to suggest that the different fat composition that characterizes VeC sample, affects the interaction of molecules of cocoa butter that serve for the crystallization process. This is because of the interaction between cocoa butter and milk powder replacers’ fats generating aggregates with higher molecular mobility as compared to the other chocolate samples. Nothing else can be qualitatively deduced by the visual inspection of Fig. 3 . For this reason, the model described elsewhere [ 17 ] has been applied. The inverse transformation of the function related to the relaxometry NMRD showed a time domain graph where different correlation times, each referred to the dynamic components of the chocolate matrixes, are reported (Fig. 4 ). The longest correlation times can be associated to larger aggregates moving slowly. Conversely, as correlation time values decrease, molecular dynamics increases because of the reduction of the molecular aggregates. Therefore, starting from the left-hand side of Fig. 4 , it is possible to state that the first proton population (at around 0.016 ms for MiC, VeC, and SuSC, respectively, while at 0.031 ms for DaC) is due to the presence of substances with higher proton mobility and faster correlation time. According to the preparation procedure of the different chocolates, the band at the shortest t C value can be associated to the presence of lactose and sucrose, that is two small-sized disaccharides. Moreover, the second correlation time at around 0.12 ms is conceivably due to proteins. In particular, in MiC, a net peak related to proteins is visible. This is explained by considering that this type of chocolate contains the largest content of proteins due to the use of cow milk, whereas the other products are made by cow milk surrogate proteins which enable a lower and broader band centered at 0.12 ms. Finally, the correlation time at the longest values (2.2 ms for MiC, 3.1 ms for VeC, 1.4, and 1.6 ms for DaC and SuSC, respectively) is related to non-polar substances such as the lipid fraction. The correlation time for this component is the longest in all the graphs, thereby corresponding to a high interaction of this component in the matrix. In fact, the cocoa butter is the main component of the continuous phase and responsible of the crystalline state of chocolate. MiC showed a high and large peak because of presence of both cocoa butter and milk powder fats. Both are mainly composed by saturated fatty acids that make them solid with the lowest proton mobility. According to the molecular mobility within the chocolate, the first peak of VeC sample (the one with milk powder replacers) is related to sucrose with lowest correlation time. A shorter and less net peak is related to the presence of isolated soybean proteins that were added in the mixture to replace the amount of milk powder proteins. Then, the range of signals related to lipids present in the VeC mixture was more variegated, with short and jagged population of peaks, and it was not possible to distinguish each peak related to a single component. But it was possible to identify solid fat components (related to cocoa butter and all the saturated fatty acids of coconut copra) with higher correlation times, while liquid fat components (oils, mainly unsaturated and polyunsaturated fatty acids from almond and coconut) have lower correlation times compared to solid fats, because of the slightly higher mobility of their protons compared to the solid fat components [ 14 ]. This different composition of the fat content in the sample is possibly the main reason of the interference of the different lipids in the crystallization process of cocoa butter. Results of NMR analysis are comparable with DSC results, where MiC and VeC sample showed a lower Tpeak of melting (compared to the dark chocolate samples) and a wider peak during the transition phase of chocolates. Sucrose is present also in the third sample (DaC), but at a lower concentration (24% of sucrose). The corresponding band is slightly shifted to the right, compared to the first two samples. The explanation can be found in the Fig. 3 , where the DaC sample shows higher Longitudinal Relaxation Rate compared to SuSC dark chocolate sample. Higher relaxation rates and lower relaxation times are related to a deeper solid-solid or sugar-solid interaction in food [ 33 ]. That means that sucrose may be more embedded within the cocoa butter continuous phase compared to the other chocolate samples. The proton population related to proteins in this sample is related to the proteins of cocoa mass, generally bound within tannins complexes, but visible in DaC and SuSC. The last net peak in the DaC graph is referred to cocoa butter, the highest peak with the highest correlation time, because of the high level of aggregation that is responsible for the crystallinity of chocolate. Alternative sugars as sucrose replacers were used for the formulation of the fourth sample (SuSC). One of these was the coconut sugar (a low-absorbable sugar containing sucrose, and inulin, a β-D-fructose polymer [ 34 ], then, erythritol and stevia sweetener. Figure 4 reveals a sucrose band that is less intense than that present in the other samples. This is in line with the sucrose concentration (about 50%) in coconut sugar [ 35 ], so SuSC contains about 6.0% of the total amount of sucrose (Table 1 ). That is, about one third of the DaC sample, so it is visible as a very small peak in the band of molecules with faster molecular movement at the beginning of Fig. 4 in SuSC. The relaxation rate of the SuSC sample shown in Fig. 3 is lower than that of DaC, due to less interaction between the alternative sugars within the cocoa butter network. This is consistent with the sugar-solid interactions [ 33 ]. The cocoa mass protein was included in the last peak in both the DaC and SuSC samples (Fig. 4 ). Conclusions The substitution of milk powder with vegetable ingredients showed strong differences with milk chocolate. The mixture of coconut copra, almonds and soy protein isolate, added in place of milk powder, affected the texture, with lower hardness and adhesiveness values, and the melting behaviour at DSC, with a wider peak. Moreover, vegan chocolate had the lowest longitudinal relaxation rate obtained by NMR, the lowest apparent viscosity and Casson yield stress, and the highest thixotropy value among all samples. In dark chocolate, the texture was partially influenced by the presence of a hygroscopic ingredient (inulin in coconut sugar), which reduced the hardness values in the substituted-sugar sample. Substitution of sucrose with sweeteners, on the other hand, showed that the crystallisation of cocoa butter was closer to the best form (β V) in the novel sample, while no other changes were recorded by rheology and NMR relaxometry analysis. Declarations Ethical Approval “not applicable” Competing interests “ I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper”. Authors' contributions OC; FC; CL; PLM: Investigation, Formal analysis. 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Sugar Tech 24:841–856. https://doi.org/10.1007/s12355-021-01101-3 Saraiva A, Carrascosa C, Ramos F, Raheem D, Lopes M, Raposo (2023) Coconut sugar: chemical analysis and nutritional profile; health impacts; safety and quality control; food industry applications. Int J Environ Res Public Health 20(4). https://doi.org/10.3390/ijerph20043671 Kowsalya P, Kamalapreetha BAnbarasan R, Mahendran R (2022) Processing of coconut neera to produce sugar granules and study on its properties. Sugar Tech 25:603–609. https://doi.org/10.1007/s12355-022-01208-1 Afoakwa EO, Paterson A, Fowler M, Vieira J (2009) Fat bloom development and structure-appearance relationships during storage of under‐tempered dark chocolates. J Food Eng 91:571–581. https://doi.org/10.1016/j.jfoodeng.2008.10.01 Svanberg L, Ahrné L, Lorén N, Windhab E (2011) Effect of sugar,cocoa particles and lecithin on cocoa butter crystallization in seeded and non-seeded chocolate model system. J Food Eng 104:70–80. https://doi.org/10.1016/j.jfoodeng.2010.09.023 Afoakwa EO, Paterson A, Fowler M, Vieira (2009a) Influence of tempering and fat crystallization behaviours on microstructural and melting properties in dark chocolate systems. Food Res Int l 42:200–209. https://doi.org/10.1016/j.foodres.2008.10.007 Machálková L, Hřivna L, Nedomová Å, Jůzl M (2015) The effect of storage temperature on the quality and formation of blooming defects in chocolate confectionery. Potr 9:39–47. https://doi.org/10.5219/425 Grassia M, Messia M, Marconi E et al (2021) Microencapsulation of phenolic extracts from cocoa shells to enrich chocolate bars. Plant Foods Hum Nutr 76:449–457. https://doi.org/10.1007/s11130-021-00917-4 Taşoyan İC, Yolaçaner ET, Öztop MH (2023) Physical characterization of chocolates prepared with various soybean and milk powders. J Texture Stud 54:34–346. 10.1111/jtxs.12744 Lim PY, Wong KY, Thoo YY, Siow LF (2021) Effect of inulin, fructo-oligosaccharide, trehalose or maltodextrin (M10 and M30) on the physicochemical and sensory properties of dark compound chocolate. LWT-Food Sci Techol 149:111964. https://doi.org/10.1016/j.lwt.2021.111964 Nebesny E, Żyżelewicz D (2005) Effect of lecithin concentration on properties of sucrose-free chocolate masses sweetened with isomalt. Eur Food Res Technol 220:131–135. https://doi.org/10.1007/s00217-004-1009-z Abbasi S, Farzanmher AH (2009) Optimization of the formulation of prebiotic milk chocolate based on rheological properties. Food Technol Biotechnol 47:396–403. https://doi:10.1007/s13197-020-04536-w Mujumdar A, Beris AN, Metzner AB (2002) Transient phenomena in thixotropic systems. J Non-Newton Fluid Mech 102:157–178. https://doi.org/10.1016/S0377-0257(01)00176-8 Cheng D-H (1986) Yield stress: a time dependent property and how to measure it Rheol Acta. 25:542–554. http://dx.doi.org/10.1007/BF01774406 Piacenza E, Chillura Martino DF, Cinquanta L, Conte P, Lo Meo P (2022) Differentiation among dairy products by combination of fast field cycling NMR relaxometry data and chemometrics. Magn Reson Chem 60:369–385. https://doi.org/10.1002/mrc.5226 Pocan P, Grunin L, Oztop MH (2022) Effect of different syrup types on turkish delights (Lokum): a TD-NMR relaxometry. ACS Food Sci Technol 2:1819–1831. https://doi.org/10.1021/acsfoodscitech.2c00222 Du M, Cheng X, Qian L et al (2023) Extraction, physicochemical properties, functional activities and applications of inulin polysaccharide: a review. https://doi.org/10.1007/s11130-023-01066-6 . Plant Foods Hum Nutr Somawiharja (2018) Indigenous technology of tapping, collecting and processing of coconut ( Cocos Nucifera ) sap and its quality in Blitar Regency, East Java, Indonesia 1. Food Res 2., 398–403. https://doi.org/10.26656/fr.2017.2(4).075 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3185753","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":221022020,"identity":"e47f1b7f-6867-4431-b810-f4da2b39fc2a","order_by":0,"name":"Federica Torregrossa","email":"","orcid":"","institution":"Università di Palermo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Federica","middleName":"","lastName":"Torregrossa","suffix":""},{"id":221022021,"identity":"84c7ad4a-2a0b-45df-a638-19df3b7e15fe","order_by":1,"name":"Luciano Cinquanta","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYBACPiA+AGYxw4TYGxgYEoA0Gw4tbOhaJBh4DkC14NCDISzBIJGASw4qLJH88MDPHTYM/O28B2/z1Nyp45/5xuzBwx12DHzyDTi0pBkc7D2TxiBxmC/ZmufYMwmJ2znmBolnknE7TCKH4QBv22EGA2YeM2ketsMSDLdzzCQS25jxajn4F67l32EJ+ZtnQFrq8Wo5DLcFyJAwuMED0nIYtxaeZwaHZdvSeCQO8xhbzu07LLnxTFqZROKZ4zxsbAlYtfCzJz/++LbNRo6//4zhjTffDvPLHT+8TfLnjmo5+eYD2K2BAh4QIQHnMjZARAgCFC2jYBSMglEwCmAAAPgDT4/TDAlxAAAAAElFTkSuQmCC","orcid":"","institution":"Università di Palermo","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Luciano","middleName":"","lastName":"Cinquanta","suffix":""},{"id":221022023,"identity":"2d84fe94-d7af-4102-abbb-c82e094fa763","order_by":2,"name":"Onofrio Corona","email":"","orcid":"","institution":"Università di Palermo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Onofrio","middleName":"","lastName":"Corona","suffix":""},{"id":221022025,"identity":"3413b305-5fe5-4481-8f27-342d02282053","order_by":3,"name":"Donatella Albanese","email":"","orcid":"","institution":"University of Salerno","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Donatella","middleName":"","lastName":"Albanese","suffix":""},{"id":221022031,"identity":"3de248ee-4c5c-4cba-b0da-a911d7efccd5","order_by":4,"name":"Francesca Cuomo","email":"","orcid":"","institution":"University of Molise","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Cuomo","suffix":""},{"id":221022034,"identity":"045120ea-16d6-484a-baf6-a795d87baea5","order_by":5,"name":"Calogero Librici","email":"","orcid":"","institution":"Università di Palermo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Calogero","middleName":"","lastName":"Librici","suffix":""},{"id":221022037,"identity":"fa7e68fb-0996-4b68-9c39-cf968883fca0","order_by":6,"name":"Paolo Lo Meo","email":"","orcid":"","institution":"Università di Palermo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paolo","middleName":"Lo","lastName":"Meo","suffix":""},{"id":221022039,"identity":"451a0c66-b7d8-48c5-8661-22346100e0dd","order_by":7,"name":"Pellegrino Conte","email":"","orcid":"","institution":"Università di Palermo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pellegrino","middleName":"","lastName":"Conte","suffix":""}],"badges":[],"createdAt":"2023-07-19 15:59:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3185753/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3185753/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":40666177,"identity":"41d083a6-1fb4-4876-b8b4-a3b7046fdb3b","added_by":"auto","created_at":"2023-07-27 14:29:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31819,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential Scanning Calorimetry (DSC) plot of a) milk chocolate (MiC); b) vegan chocolate (VeC); c) dark chocolate (DaC) and d) sugar-substituted chocolate (SuSC).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3185753/v1/fce5e92337f36d8415acfe2a.png"},{"id":40664793,"identity":"8fd400cb-f75f-4879-b5e1-3de4bd453fad","added_by":"auto","created_at":"2023-07-27 14:21:55","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":297884,"visible":true,"origin":"","legend":"\u003cp\u003eLeft: flow curves of milk chocolate MiC (1) and vegan chocolate VeC (2). Right: flow curves of dark chocolate DaC (3) and SuSC dark chocolate (4).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3185753/v1/146b65a04ceb5fe77a680a52.jpeg"},{"id":40664794,"identity":"303580ad-8adb-47e7-bb1b-5879ee73dca8","added_by":"auto","created_at":"2023-07-27 14:21:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47121,"visible":true,"origin":"","legend":"\u003cp\u003eNMR Relaxometry evaluating Relaxation Rate for milk chocolate (MiC); vegan chocolate (VeC); dark chocolate control (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3185753/v1/91a4626befecd443cba75e3c.png"},{"id":40664792,"identity":"23d8dda8-719b-4695-9dc0-254a55e10d19","added_by":"auto","created_at":"2023-07-27 14:21:54","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":234718,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation times obtained by inverse transformation of data resulted by Relaxation Rate (Figure 3) for milk chocolate (MiC); vegan chocolate (VeC); dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3185753/v1/4a05c2e725ddd465e90664c1.jpeg"},{"id":40748290,"identity":"fda33231-1f43-4959-ba89-9d6e1c38c1b9","added_by":"auto","created_at":"2023-07-29 03:52:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":586653,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3185753/v1/42208140-f5d4-4d62-b97a-3baf8085692b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Novel vegan and sugar-substituted chocolates. Part I: physical-chemical characterization","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSweets farms are looking for new chocolate formulations that can meet dietary styles associated to either cultural choices or intolerances, and pathologies. Increasingly consumers demand less simple sugars in food, including diabetics who must limit or avoid the consumption of mono- and disaccharides. Stevia, as well as erythritol, is a viable alternative for replacing sugars in chocolate, thus making this product more appetible for diabetics [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Less used is, instead, coconut sugar, a natural sweetener obtained by evaporation of the sap of \u003cem\u003eCocos nucifera\u003c/em\u003e [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, lactose intolerant or even vegan subjects are unable to consume milk-based chocolates due to the presence of powdered cow milk which is added during chocolate production. As a general remark, addition of milk allows production of sweeter chocolate with more malleability and thermolability than dark chocolate [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Noticeably, attention must be paid in obtaining chocolate products that must have sensory characteristics like milk- and sugar-containing systems. Chocolate structure is directly related to the size of the tiny particles and crystals deriving from the components of the cocoa butter used during chocolate preparation. The crystalline arrangement of the β form crystals (V) in the cocoa butter allows a melting point between 33 and 34\u0026deg;C [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Chocolate flow properties are important for assessing its structure. Moreover, the taste of chocolate in the mouth is directly influenced by viscosity. Therefore, chocolate bad taste can be perceived when wrong flow/viscosity characteristics are achieved [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, final chocolate texture, appearance and flavour can be considered as key attributes for consumer choice and acceptability [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. All the aforementioned keys are related to the phase transitions of polymorphic forms in fat systems by their melting points which, in turn, are monitored by differential scanning calorimeter (DSC) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Chocolate characteristics can be associated also with the molecular dynamics of the complex mixtures making this food product that can be explored by low field NMR relaxometry. This is a fast, reproducible, accurate and non-invasive technique, which can be applied to expand knowledge of chocolate stabilisation characteristics [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The aim of this study was to evaluate the main chemical-physical properties of novel plant-based and substituted-sugar chocolates. Two different chocolates have been prepared. In milk-less products milk powder was replaced with dried coconut copra, roasted almonds, and isolated soy proteins. In the case of substituted-sugar dark chocolate, sucrose was replaced with stevia, erythritol and coconut sugar. Comparison with traditional products (milk- and sucrose-containing chocolates) was carried out by analysing water activity, fatty acids content, texture, melting point by differential scanning calorimetry (DSC), rheology and fast field cycling NMR relaxometry.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSampling\u003c/h2\u003e \u003cp\u003eThe chocolate samples were made in an artisan confectionery laboratory (Cappello, Palermo, Italy) using, for both the control and the experimental samples, a refiner with counter-rotating porphyry rollers for mixing (Ing. Polin EC. S.p.A., Verona, Italy) and obtaining the paste of cocoa, and a bench robot set at 60\u0026deg;C for 4 hours of conching. The chocolate obtained was manually tempered on marble and molded into circular shapes in silicone molds with a weight of 7-8g, 4.5 mm of thickness and 35 mm of diameter for each shape obtained. Flow chart of production process is reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSample coding is as follows:\u003c/p\u003e \u003cp\u003e \u003cb\u003eMiC: Mi\u003c/b\u003elk-containing \u003cb\u003eC\u003c/b\u003ehocolate \u003cb\u003eVeC\u003c/b\u003e: milk-less \u003cb\u003eVe\u003c/b\u003egan \u003cb\u003eC\u003c/b\u003ehocolate\u003c/p\u003e \u003cp\u003e \u003cb\u003eDaC\u003c/b\u003e: sucrose-containing \u003cb\u003eDa\u003c/b\u003erk \u003cb\u003eC\u003c/b\u003ehocolate \u003cb\u003eSuSC: Su\u003c/b\u003ebstituted\u003cb\u003e-S\u003c/b\u003eugar \u003cb\u003eC\u003c/b\u003ehocolate\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRaw materials\u003c/h2\u003e \u003cp\u003eThe cocoa mass was purchased from Valhrona (France): respectively Manjari Pur Madagascar 100%, for milk chocolate, and Araguani Pur Venezuela 100% for dark chocolate. The cocoa butter was purchased from ICAM Professional SPA, (Lecco, Italy). Dehydrated coconut (Pearls of Samarkand, Sri Lanka), powdered isolated soy proteins (Natural Soy Isolate, ProLabs, Eros, EuroSup), pure stevia powder (UOP Durante, Italy), and crystal coconut sugar (Monte Nativo, Sri Lanka), were purchased on online marketplace. Almonds were purchased by Musumeci company, (Bronte, CT, Italy). Natural Bourbon vanilla powdered by Vanilla Gourmet (Pescara, Italy); soy lecithin by Nutrition\u0026amp;Sant\u0026egrave; (Lecinova, Italy); erythritol by Chimpex (Caivano, NA, Italy). The percentage composition of the ingredients in the different samples is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The formulation of the SuSC sample results in a 10% reduction in calorific value: about 424.58 kCal 100 g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, compared to 472.67 kCal 100 g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in DaC sample.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulations of milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIngredient %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVeC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDaC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSuSC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCocoa Mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSucrose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilk Powder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoconut Copra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsolated soy proteins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErithritol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStevia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoconut Sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy lechitin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eWater activity and dry matter\u003c/h2\u003e \u003cp\u003eThe analysis of the water activity was carried out with the HygroPalm-23 instrument (Rotronic, Basserdorf, Germany) following the ISO 21807:2004 method. The samples were all analysed in triplicate. Dry matter was analysed by using official analytical method (AOAC 930.15, 1990).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTexture analysis\u003c/h2\u003e \u003cp\u003eTexture analysis was performed by using a TaXT2 texture analyser (Stable Microsystem) equipped with a cylindrical probe (P35) with which the chewing test with double compression was simulated. The parameters used for the test were as follows: pre-test speed 2 mm s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; test speed 2 mm s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; post-test speed 5 mm s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; distance 50%; load cell 25 kg. The test was conducted at 18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eDifferential Scanning Calorimetry\u003c/h2\u003e \u003cp\u003eThe melting profiles of chocolate samples were determined using Differential Scanning Calorimetry (Q Series DSC, TA Instruments, New Castle, Delaware, USA). 5\u0026ndash;10 mg of chocolate samples were loaded in an aluminium pan and nitrogen was used as transport inert gas at a flow rate of 50 ml min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. An empty pan was used as a reference, while indium was used for instrument calibration. Samples were initially equilibrated at 20\u0026deg;C and then heated to 60\u0026deg;C at 5\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e rate. Thermograms were analysed by TA Universal Analysis software (TA Instruments, New Castle, Delaware, USA) defining the melting peak temperature (Tm) and the melting enthalpy (ΔHm).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eRheological analysis\u003c/h2\u003e \u003cp\u003eThe rheological properties of chocolate were studied using a Haake Mars III rheometer (Thermo Scientific) equipped with Couette geometry (with coaxial cylinders) with an outer cylinder diameter of 43 mm, the inner one of 41 mm, and a gap of 3 mm. Chocolate flow parameters were determined by following the official method viscosity (ICA, 2000) of cocoa and chocolate products (Analytical method 46. CAOBISCO, Brussels). Chocolate was placed in a closed glass container. It was heated in a benchtop oven at 52\u0026deg;C for at least 1 hour before evaluating the flow properties at 40\u0026deg;C. The test was programmed in 4 steps: 1) pre-shear at a fixed shear rate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\dot{\\gamma }\\)\u003c/span\u003e\u003c/span\u003e) of 5 s \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 5 min; 2) ascending ramp with (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\dot{\\gamma }\\)\u003c/span\u003e\u003c/span\u003e) from 2 to 50 s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in 3 min, 3) fixed shear rate at (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\dot{\\gamma }\\)\u003c/span\u003e\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;50 s \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for 1 min; 4) descending ramp with (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\dot{\\gamma }\\)\u003c/span\u003e\u003c/span\u003e ) from 50 to 2 s \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in 3 min. The data recorded in the upward flow curve section were then interpolated using Casson's model:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\sqrt{\\tau }=\\sqrt{{\\tau }_{0}}+\\sqrt{{\\eta }_{c }\\dot{\\gamma }}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere τ\u003csub\u003e0\u003c/sub\u003e is the Casson yield stress, i.e., the stress required for the fluid to start flowing, and η\u003csub\u003ec\u003c/sub\u003e is the Casson viscosity indicating the force required to maintain chocolate flow during the test. Thixotropy was measured by the hysteresis area formed by the difference between the upward and downward curves. The larger the hysteresis area, the longer the time needed for the fluid to recover its structure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eFast Field Cycling (FFC) NMR relaxometry\u003c/h2\u003e \u003cp\u003eDetails about the technique have been already reported elsewhere [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Here, only a brief report on the used experimental conditions is reported. All the experiments were conducted on a Stelar Smartracer Fast-Field-Cycling Relaxometer (Stelar s.r.l., Mede, PV\u0026ndash;Italy) set at a constant temperature of 25\u0026deg;C. The proton spins were polarized at a polarization field (B\u003csub\u003ePOL\u003c/sub\u003e) corresponding to a proton Larmor frequency (n\u003csub\u003eL\u003c/sub\u003e) of 10 MHz for a period (T\u003csub\u003ePOL\u003c/sub\u003e) of about five times the T\u003csub\u003e1\u003c/sub\u003e estimated at this frequency. After each B\u003csub\u003ePOL\u003c/sub\u003e, the magnetic field intensity (indicated as B\u003csub\u003eRLX\u003c/sub\u003e) was systematically changed in the proton Larmor frequency n\u003csub\u003eL\u003c/sub\u003e comprised in the range 0.01\u0026ndash;10 MHz. The period τ, during which B\u003csub\u003eRLX\u003c/sub\u003e was applied, has been varied on 32 logarithmic spaced time sets, each of them adjusted at every relaxation field to optimize the sampling of the decay/recovery curves. Free induction decays were recorded following a single \u003csup\u003e1\u003c/sup\u003eH 90\u0026deg; pulse applied at an acquisition field (B\u003csub\u003eACQ\u003c/sub\u003e) corresponding to n\u003csub\u003eL\u003c/sub\u003e of 7.2 MHz. A time domain of 100 \u0026micro;s sampled with 512 points was applied. Field-switching time was 3 ms, while spectrometer dead time was 15 \u0026micro;s. For all the experiments, a recycle delay of 2 s was used. A non-polarized FFC sequence was applied when the relaxation magnetic fields were in the range of the proton Larmor frequencies comprised between 20 and 10 MHz. A polarized FFC sequence was applied for B\u003csub\u003eRLX\u003c/sub\u003e values ranging between 3 and 0.01 MHz (Conte, 2021). All the decay/recovery curves acquired by applying the aforementioned experimental runs were exported to OriginPro 7.5 SR6 (Version 7.5885, OriginLab Corporation, Northampton, MA, USA) in order to apply the stretched exponential function (also known as Kohlraush\u0026ndash;Williams\u0026ndash;Watts function) reported in Eq.\u0026nbsp;(\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$I\\left(\\tau \\right)={I}_{0}exp\\left[-{\\left(\\frac{\\tau }{{T}_{1}}\\right)}^{k}\\right]+{y}_{0}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, I(τ) is the magnetization intensity at a given τ value; I\u003csub\u003e0\u003c/sub\u003e is the magnetization intensity at the asymptote of the decay/recovery curve; τ is the period of time during which B\u003csub\u003eRLX\u003c/sub\u003e is applied; T\u003csub\u003e1\u003c/sub\u003e is the longitudinal relaxation time; k is a parameter accounting for the relaxometry complexity of the samples. Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) accounts for the large sample heterogeneity resulting in a multiexponential behaviour of the decay/recovery curves. In particular, this equation can be considered as a superposition of exponential contributions, which describes the likely physical picture of some distributions in T\u003csub\u003e1\u003c/sub\u003e. Its application has the advantage that it is able to handle a wide range of relaxometry behaviors within only one single model. For this reason, any assumption about the number of exponentials to use for modelling the FFC NMR relaxometry data is not necessary [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The NMRD profiles (i.e., R\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1/T\u003csub\u003e1\u003c/sub\u003e-vs-n\u003csub\u003eL\u003c/sub\u003e curves) were modelled according to the free-model analysis elsewhere reported [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], to obtain the distribution of correlation times from which information about the dynamic domains in chocolates were obtained.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWater activity and dry matter\u003c/h2\u003e \u003cp\u003eThe MiC and VeC samples showed higher values of water activity than the other two samples (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This can be related to the presence of milk powder in (MiC) and coconut sugar in (VeC), a highly hygroscopic saccharide containing inulin [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], whose solubility, wettability and dispersibility have already been studied [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWater activity and dry matter in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAw (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;st.dv)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDry Matter (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.445\u0026thinsp;\u0026plusmn;\u0026thinsp;0.014\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.439\u0026thinsp;\u0026plusmn;\u0026thinsp;0.008\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.375\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.378\u0026thinsp;\u0026plusmn;\u0026thinsp;0.009\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eDifferent letters mean significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDifferential Scanning Calorimetry\u003c/h2\u003e \u003cp\u003eThe main quality parameters of chocolate, which are good mouth meltability, snapping properties, and glossiness, depend on the crystallization form of cocoa butter (CB) used as fat phase. Differential scanning calorimetry (DSC) is widely used for the evaluation of fat polymorphism and crystal network organization in chocolate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The onset peak corresponds to the temperature at which a specific crystalline form begins to melt, the maximum peak corresponding to the temperature at which the melting curve reaches its peak maximum, the end of melting and the enthalpy related to the whole melting peak (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). DaC and SuSC samples show a single peak, and in the case of SuSC a sharp one, with a maximum peak in contrast to MiC and VeC, for which it possible noting the presence of a double melting transition (inset of Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The melting temperature of the cocoa butter for the polymorphic forms are I (17.3\u0026deg;C), II (23.3\u0026deg;C), III (25.5\u0026deg;C), IV (27.5\u0026deg;C), V β (33.8\u0026deg;C) and VI (36.3\u0026deg;C) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The maximum peak temperature detected for the chocolate samples shows that the crystallisation of cocoa butter in the SuSC sample is the β V form, the most desirable crystal form in high-quality chocolate. The double melting transition in Mic and VeC sample could be caused by the triglyceride\u0026rsquo;s composition of milk and coconut copra fat that according with other authors [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], affect crystallization behaviour of CB. Differences between melting peaks as well as the enthalpy values of DaC and SuSC samples can be due to the different sugar composition. Sugars and their particle sizes also affect the CB crystallization because they represent nuclei which provide the \u0026ldquo;seed\u0026rdquo; around which fat crystals grow [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The melting enthalpy in DaC chocolate was significantly higher than those of MiC, VeC and SuSC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) indicating a higher extent of fat crystallization in systems probability due to the simultaneous presence of high amount of CB (75%) and homogeneous sugar phase in systems [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMelting properties by Differential Scanning Calorimetry (DSC) in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT\u003csub\u003eonset\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT\u003csub\u003epeak 1\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003csub\u003epeak 2\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u003csub\u003eend\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT\u003csub\u003eindex\u003c/sub\u003e (\u0026deg;C)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eΔH\u003csub\u003em\u003c/sub\u003e [J/g]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3\u0026plusmn;0.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.47\u0026plusmn;0.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.67\u0026plusmn;0.42\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.6\u0026plusmn;0.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.7\u0026plusmn;8.66\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVeC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.3\u0026plusmn;0.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.97\u0026plusmn;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.31\u0026plusmn;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.6\u0026plusmn;0.5\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.4\u0026plusmn;11.24\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDaC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.2\u0026plusmn;0.3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.64\u0026plusmn;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.7\u0026plusmn;0.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.9\u0026plusmn;8.66\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSuSC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eDifferent letters mean significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTexture Analysis\u003c/h2\u003e \u003cp\u003eHardness of chocolate is a good parameter that points out proper control of temperature and stability of the fat crystal network formed during tempering process [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. All treatments (VeC and SuSC) showed hardness values lower compared to the control samples (MiC and DaC) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These data confirmed that samples with lower melting points tend to have a softer structure at the same temperature [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], \u003cem\u003ei.e.\u003c/em\u003e, when subjected to the stress of texture analysis, showing a lower resistance to probe penetration. DSC results also showed a lower Tpeak for VeC sample, related to the lower point of fusion. VeC sample also had the lowest value of adhesiveness. Hardness value was highest in DaC, because of the absence of any other substances that can affect the structure of the chocolate. SuSC had the lower hardness value than (DaC) sample, owing to the presence of coconut sugar, highly hygroscopic sweetener containing a significant amount of inulin (about 5 g 100g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Data confirmed that sucrose replacement with high ratios of sugar substitutes provide low hardness values respect to the controls [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTexture parameters in milk chocolate (MiC), vegan chocolate (VeC), dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eheight (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehardness (g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eadhesiveness (g s)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12534\u0026thinsp;\u0026plusmn;\u0026thinsp;530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e-0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7836\u0026thinsp;\u0026plusmn;\u0026thinsp;303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e-17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21760\u0026thinsp;\u0026plusmn;\u0026thinsp;323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e-2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9688\u0026thinsp;\u0026plusmn;\u0026thinsp;1521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e-0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRheology\u003c/h2\u003e \u003cp\u003eIt is well known that chocolate does not usually have Newtonian behaviour, which was also confirmed for the samples analysed, all of which exhibited the characteristics of Casson's plastic fluid. Chocolate rheology is usually quantified using parameters like yield stress (τ\u003csub\u003e0\u003c/sub\u003e) and apparent (plastic) viscosity (measured at shear rate 5 s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Yield stress is a material property and is the stress corresponding to the yield point at which the material begins to deform plastically [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Results of flow curves data fitting to the Casson equation and the measurement of the hysteresis area (thixotropy) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. For all the samples, the shear rate applied resulted in a non-linear response in terms of shear stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicating that chocolate aggregates aligned to the flow as the shear rate increase thus opposing less resistance, which is the reason why chocolate samples showed shear thinning behaviour. As for τ\u003csub\u003e0\u003c/sub\u003e values, the new formulations showed an opposite trend. In fact, in vegan chocolate, the substitution of milk powder caused more than a halving of the yield stress and a similar decrease in apparent and Casson viscosity. These data, consistent with the texture value showed a variation in the rheological properties of vegan chocolate compared to traditional one. The differences between dark and sugar-substituted chocolate showed an inverse trend in τ\u003csub\u003e0\u003c/sub\u003e values, which increased significantly (almost 70%) with sugar substitution, while the increase in viscosity was smaller (about 9%). This last was consistent with other results [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], in which dark sweetened with isomalt presented higher Casson viscosity than that of the sucrose containing chocolate, confirming that the chocolate formulations comprising high levels of sugar substitutes had higher apparent and Casson viscosity, and yield stress than the those of the control [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Thixotropy is a function of time-dependent fluid and can be evaluated through apparent viscosity or shear stress decreasing with the time of shear at constant rate. Thixotropy is calculated from the area of loop or a specific point on the ramp curves of shear stress or apparent viscosity at a specific shear rate [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Values reported in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e were calculated as the area of loop formed between the upward and downward flow curves and as can be observed all samples showed thixotropic behaviour. Considering the thixotropic data [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], it appears that the VeC and SuSC samples have a more complex structure than the related reference chocolates (MiC and DaC).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRheological properties in milk chocolate (MiC); vegan chocolate (VeC); dark chocolate (DaC) and sugar-substituted dark chocolate (SuSC)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eη\u003csub\u003eapp\u003c/sub\u003e (Pa s)\u003c/p\u003e \u003cp\u003eshear rate 5/s\u003c/p\u003e\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e τ\u003csub\u003e0\u003c/sub\u003e (Pa)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eη\u003csub\u003ec\u003c/sub\u003e (Pa s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThixotropy (Pa/s)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e335.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVeC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e524.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e106.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e445.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFast Field Cycling (FFC) NMR relaxometry\u003c/h2\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Nuclear Magnetic Resonance Dispersion (NMRD) profiles, reporting the longitudinal relaxation rate as a function of the Larmor frequency of the applied electromagnetic field, is shown. VeC sample (the vegan chocolate) with fat replacers of milk powder, shows the lowest relaxation rate as compared to the other samples. This is justified by the different molecular motion affecting the fluctuation of the local electromagnetic field. A faster molecular motion is related to longer relaxation times T\u003csub\u003e1\u003c/sub\u003e and slower relaxation rate values [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In this case, it is possible to suggest that the different fat composition that characterizes VeC sample, affects the interaction of molecules of cocoa butter that serve for the crystallization process. This is because of the interaction between cocoa butter and milk powder replacers\u0026rsquo; fats generating aggregates with higher molecular mobility as compared to the other chocolate samples. Nothing else can be qualitatively deduced by the visual inspection of Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. For this reason, the model described elsewhere [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] has been applied. The inverse transformation of the function related to the relaxometry NMRD showed a time domain graph where different correlation times, each referred to the dynamic components of the chocolate matrixes, are reported (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The longest correlation times can be associated to larger aggregates moving slowly. Conversely, as correlation time values decrease, molecular dynamics increases because of the reduction of the molecular aggregates. Therefore, starting from the left-hand side of Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, it is possible to state that the first proton population (at around 0.016 ms for MiC, VeC, and SuSC, respectively, while at 0.031 ms for DaC) is due to the presence of substances with higher proton mobility and faster correlation time. According to the preparation procedure of the different chocolates, the band at the shortest t\u003csub\u003eC\u003c/sub\u003e value can be associated to the presence of lactose and sucrose, that is two small-sized disaccharides. Moreover, the second correlation time at around 0.12 ms is conceivably due to proteins. In particular, in MiC, a net peak related to proteins is visible. This is explained by considering that this type of chocolate contains the largest content of proteins due to the use of cow milk, whereas the other products are made by cow milk surrogate proteins which enable a lower and broader band centered at 0.12 ms. Finally, the correlation time at the longest values (2.2 ms for MiC, 3.1 ms for VeC, 1.4, and 1.6 ms for DaC and SuSC, respectively) is related to non-polar substances such as the lipid fraction. The correlation time for this component is the longest in all the graphs, thereby corresponding to a high interaction of this component in the matrix. In fact, the cocoa butter is the main component of the continuous phase and responsible of the crystalline state of chocolate. MiC showed a high and large peak because of presence of both cocoa butter and milk powder fats. Both are mainly composed by saturated fatty acids that make them solid with the lowest proton mobility. According to the molecular mobility within the chocolate, the first peak of VeC sample (the one with milk powder replacers) is related to sucrose with lowest correlation time. A shorter and less net peak is related to the presence of isolated soybean proteins that were added in the mixture to replace the amount of milk powder proteins. Then, the range of signals related to lipids present in the VeC mixture was more variegated, with short and jagged population of peaks, and it was not possible to distinguish each peak related to a single component. But it was possible to identify solid fat components (related to cocoa butter and all the saturated fatty acids of coconut copra) with higher correlation times, while liquid fat components (oils, mainly unsaturated and polyunsaturated fatty acids from almond and coconut) have lower correlation times compared to solid fats, because of the slightly higher mobility of their protons compared to the solid fat components [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This different composition of the fat content in the sample is possibly the main reason of the interference of the different lipids in the crystallization process of cocoa butter. Results of NMR analysis are comparable with DSC results, where MiC and VeC sample showed a lower Tpeak of melting (compared to the dark chocolate samples) and a wider peak during the transition phase of chocolates. Sucrose is present also in the third sample (DaC), but at a lower concentration (24% of sucrose). The corresponding band is slightly shifted to the right, compared to the first two samples. The explanation can be found in the Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, where the DaC sample shows higher Longitudinal Relaxation Rate compared to SuSC dark chocolate sample. Higher relaxation rates and lower relaxation times are related to a deeper solid-solid or sugar-solid interaction in food [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. That means that sucrose may be more embedded within the cocoa butter continuous phase compared to the other chocolate samples. The proton population related to proteins in this sample is related to the proteins of cocoa mass, generally bound within tannins complexes, but visible in DaC and SuSC. The last net peak in the DaC graph is referred to cocoa butter, the highest peak with the highest correlation time, because of the high level of aggregation that is responsible for the crystallinity of chocolate. Alternative sugars as sucrose replacers were used for the formulation of the fourth sample (SuSC). One of these was the coconut sugar (a low-absorbable sugar containing sucrose, and inulin, a β-D-fructose polymer [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], then, erythritol and stevia sweetener. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e reveals a sucrose band that is less intense than that present in the other samples. This is in line with the sucrose concentration (about 50%) in coconut sugar [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], so SuSC contains about 6.0% of the total amount of sucrose (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). That is, about one third of the DaC sample, so it is visible as a very small peak in the band of molecules with faster molecular movement at the beginning of Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e in SuSC. The relaxation rate of the SuSC sample shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e is lower than that of DaC, due to less interaction between the alternative sugars within the cocoa butter network. This is consistent with the sugar-solid interactions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The cocoa mass protein was included in the last peak in both the DaC and SuSC samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe substitution of milk powder with vegetable ingredients showed strong differences with milk chocolate. The mixture of coconut copra, almonds and soy protein isolate, added in place of milk powder, affected the texture, with lower hardness and adhesiveness values, and the melting behaviour at DSC, with a wider peak. Moreover, vegan chocolate had the lowest longitudinal relaxation rate obtained by NMR, the lowest apparent viscosity and Casson yield stress, and the highest thixotropy value among all samples. In dark chocolate, the texture was partially influenced by the presence of a hygroscopic ingredient (inulin in coconut sugar), which reduced the hardness values in the substituted-sugar sample. Substitution of sucrose with sweeteners, on the other hand, showed that the crystallisation of cocoa butter was closer to the best form (β V) in the novel sample, while no other changes were recorded by rheology and NMR relaxometry analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;not applicable\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;\u0026nbsp;I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOC; FC; CL; PLM: Investigation, Formal analysis. PC \u0026amp; PLM: Data curation, Supervision, Writing - review \u0026amp; editing. DA: Methodology, Investigation, Writing - review \u0026amp; editing. LC \u0026amp; FT Conceptualization, Methodology, Investigation, Validation; Review \u0026amp; editing, Supervision)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funds other than those of the relevant universities\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOon request to authors\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRodriguez Furl\u0026aacute;n LT, Baracco Y, Lecot J, Zaritzky N, Campderr\u0026oacute;s ME (2017) Effect of sweetener combination and storage temperature on physicochemical properties of sucrose free white chocolate. 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Food Res 2., 398\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.26656/fr.2017.2(4).075\u003c/span\u003e\u003cspan address=\"10.26656/fr.2017.2(4).075\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"vegan chocolate, low-sucrose chocolate, DSC, rheology, NMR relaxometry","lastPublishedDoi":"10.21203/rs.3.rs-3185753/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3185753/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe confectionery industry is increasingly adopting new solutions and possible formulations to expand the ranges of chocolate products that support food styles linked to either cultural or health choices. The chemical-physical characteristics of chocolates (dark and milk) produced with traditional formulations or intended for vegan or demanding less simple sugars consumers (with a 10% reduction in calorific value), were analysed. The effects of the substitution of milk with coconut copra, almond and isolated soy proteins, and the replacement of sucrose with coconut sugars, stevia and erythritol, have been accounted for by analysing texture, rheology and water activity, differential scanning calorimetry (DSC) and fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry. The plant-based sample showed lower values for hardness and adhesiveness in the texture analysis, and a larger peak in the melting behaviour at the DSC. Moreover, the substitution of milk powder caused more than a halving of the yield stress and a similar decrease in apparent and Casson viscosity. The crystallisation of cocoa butter in the substituted-sugar sample involved the β V form, the most desirable crystal form in high-quality chocolate. Results by FFC NMR relaxometry allowed identification of differently sized aggregates whose chemical nature is discussed. FFC NMR relaxometry data confirm those by rheological and DSC investigations.\u003c/p\u003e","manuscriptTitle":"Novel vegan and sugar-substituted chocolates. Part I: physical-chemical characterization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-27 14:21:50","doi":"10.21203/rs.3.rs-3185753/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fce0c39d-bc53-4f09-8ef0-f0d1f3613093","owner":[],"postedDate":"July 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-07-29T03:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-27 14:21:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3185753","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3185753","identity":"rs-3185753","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}