Pneumatic Conveying of Crystalline Sugar: the Impact on Donut-Shaped Cookie’s Physical and Sensory Properties

Abstract

In the cookie industry, sugar is generally handled by pneumatic conveying, which causes sucrose crystals to break, altering their granulometry. In order to understand how sugar with different granulometry and color impacts both physical and sensory characteristics of cookies, instrumental evaluations of texture (hardness and fracturability), color, quantitative descriptive sensory analysis, and affective tests were conducted. Sugar granulometry samples before pneumatic conveying (BPT 0.61 mm) were significantly higher (p<0.05) than samples after pneumatic conveying (APT 0.47 mm). BPT sugar showed less luminosity (L*) and a greater tendency to the yellow color (b*). The component analysis also allowed correlation of the data obtained through instrumental and sensorial analysis. A strong negative correlation (>0.8) between granulometry and hardness and between granulometry and color was noticed. When sugar granulometry decreased, the cookie hardness was increased (3.54 N), and the milk-flavored cookie coloring was darkened (L* 48.74 and 2.8 BCU). The affective sensory tests revealed that reducing sugar granulometry during pneumatic conveying did not interfere with the approval, preference, and cookie purchase intention. Using crystalline sugar submitted to pneumatic conveying in the production of milk-flavored cookies results in darker products with greater hardness and higher fracturability. However, these alterations do not affect consumers' acceptance of the cookies.

Keywords:
sucrose; hardness; particle size.

HIGHLIGHTS

• Pneumatic conveying affects the sugar particle size.

• Reducing the sugar particle size increases the hardness of the donut-shaped cookies.

• Reducing the particle size results in darker sugar and cookies.

• Changing the sugar grain size does not affect the acceptability of the cookies.

INTRODUCTION

The cookie is composed of a continuous glassy sugar pattern containing incorporated non-gelatinized starch granules and undeveloped gluten net and fat [¹]. It is a multicomponent system in which the molecular interaction between sugar and other compounds can be affected by the characteristics of the process and the ingredients used. Sugar is one of the pillars of the bakery industry, and sucrose transport in industrial processing lines can promote alterations related to size, shape, humidity, and vitreous transition properties [², ³].

Many authors reported sugar interference, specifically on the rheological behavior of the dough and the sensorial and quality cookie characteristics, such as sweetness, flavor, dimension, expansion, color, hardness, superficial finishing, and general appearance of the product [³, ⁴, ⁵, ⁶]. The main technological alterations observed during cookie fabrication include a lack of dimension pattern, texture, and superficial appearance of the products [⁷]. However, although previous studies have been dedicated to understanding the role of sugar in cookie properties, little has been observed regarding the effect of sucrose transport in the processing plant on the characteristics of cookies that receive its addition.

In general, ingredients can usually be transported hydraulically, mechanically, or pneumatically [⁸] in food industry. The movement of sugar in the processing plant generally occurs through pneumatic conveying [³]. This transport can be dense phased or dilute phased and operate under positive pressure, negative pressure, or a combination of both [⁹]. Pneumatic conveying has the advantage of being a closed system, reducing the possibility of product contamination [¹⁰]. However, during pneumatic conveying, collisions occur between sugar particles and the pipe wall or between itself, causing breakage and size reduction [¹¹]. Consequently, an increased proportion of fine particles related to alterations in water absorption capacity, starch retrogradation, and dough hardness are observed [³, ¹²]. Other than the sucrose particle size effect on the physical characteristics of the cookie that receives its addition, the sensorial perception of sugar crystals during consumption of bakery products has been associated with important qualities such as crunchiness and noise intensity [¹³], sweet flavor [¹⁴] and aromatic compounds profile [¹⁵].

Considering that none of the studies evaluated the sucrose transport effect in the cookie properties, this research aimed to do the pneumatic conveying of sugar and evaluate the impact of its addition on cookies' physical and sensorial characteristics. As did the cookie formulation, sugar pneumatic conveying by different suppliers occurred on an industrial scale. Formulated products with sugar before and after the pneumatic conveying were analyzed by researchers for its hardness, fracturability, color, sensorial characteristics description, and also its sensorial acceptance, preference and purchase intention.

MATERIAL AND METHODS

Ingredients and pneumatic conveying equipment

The following commercial ingredients were used to prepare the cookies: fat, emulsifier, flavoring, acidulants, yeast, salt and water, flour, sugar, and starch. Owing to the industrial nature of the process and confidentiality constraints, the exact proportions of the ingredients cannot be disclosed. Nevertheless, the formulation is consistent with standard industrial formulations commonly employed for this type of cookie in Brazil. The crystalline sugar (sucrose) used was from the 2012/2013 harvest, commercially classified as type 2 sugar [¹⁶], and was acquired from three different producers in the state of São Paulo, Brazil (Suppliers A, B, and C). Sugar samples were used before pneumatic conveying (BPT) and after they were submitted to pneumatic conveying (APT).

The pneumatic conveying (Figure 1) used to move and fractionate the sugar consisted of a positive pressure and diluted phase system, according to the classification suggested by Klinzing and coauthors (2010) and Mills (2004) [⁹, ¹⁷]. The system applied to this study comprised three air blowers operating in a 0.40 to 0.67 bar pressure range with a pressure limit of 0,80 bar. The airflow generated by blowers was 16.5 m³/min, the estimated average air speed was 22.0 m/s, and the transport flow speed was approximately 11.0 m/s. Sugar temperature during pneumatic conveying reached a 40°C average.

Figure 1
Pneumatic conveying diagram in the food industry. 1 - Air blowers; 2 - Air coolers (room temperature); 3 - Pressure gauge; 4 - Temperature meter; 5 - Sugar bag; 6 - Hopper (sugar input); 7 - Disintegrator; 8 - Filters; 9 - Turbo; 10 - Magnet; 11 - Product output after shift-sieve; 12 - Storage silo; 13 - Dehumidifier; 14 - Transference Silo; 15 - Weigh scale; 16 - Transfer deposit; 17 - Sugar Deposit; 18 - Mixer.

Cookie processing

Milk-flavored cookies were manufactured on an industrial scale. Three different sugar batches were used in two conditions: before pneumatic conveying (BPT) and after being submitted to pneumatic conveying (APT), totaling six different cookie productions. Fat, emulsifier, flavoring, acidulant, yeast, salt, and water were mixed, followed by flour, sugar, and starch addition. The dough was molded, baked, and packaged until it was analyzed.

Sugar characterization

Its granulometry and color characterized sugar samples before and after pneumatic conveying. The granulometry was determined according to the GS2/9-37 method, created by the International Commission for Uniform Methods of Sugar Analysis [¹⁸], in quintuplicate and calculated using the Rens method.

The color was determined with a Chroma Meter colorimeter CR400/410 (Konica Minolta, Japan) using the CIE system (L, a*, b*) under D65 illuminant in quintuplicate.

Cookie instrumental analysis

Determining cookies' hardness and fracturability/crunchiness was done using the Stable Micro Systems Texture Analyser TAXT2i, probe 3-Point bending Rig (HDP/3PB), HDP/90 platform, and the results were expressed in Newton (N) and represented the arithmetic mean of 5 breaking force determinations for samples from the same cookie production. Parameters used in tests were: pre-testing speed (1.0 mm.s-¹), testing speed (3.0 mm.s-¹), after testing speed (10.0 mm.s-¹) and distance (5 mm), with compression force measurements, according to the BIS4/3PB [¹⁹] study, available in the equipment software.

Cookie color was analyzed using a BC-10 (Konica Minolta, Japan) Baking Contrast Meter colorimeter model using the CIELAB (L, a*, b*) system. The equipment can also measure the color and light/dark characteristics through Baking Contrast Units (BCU). BCU is derived from the standard tristimulus colorimetry 'L' value. The range is 0 for the darkest and 5.25 for the lightest. Each alteration of 0.1 BCU is approximately equal to a discerning hue for the human eye. BCU value is related to the color of the crust of baked goods. Color determination was performed with five repetitions for each of the six cookie productions. Additionally, the color (∆E) difference was calculated between the cookies fabricated with BPT sugar and APT sugar [¹³, ²⁰].

Cookies sensorial analysis

The cookies were sensorially analyzed using the descriptive method of evaluating attributes and affective methods of acceptance, preference, and purchase intention after approval by the Ethics Committee for Research Involving Human Beings (CAAE: 43419515.5.0000.5547).

In order to evaluate the sensorial aspects of the cookies, 15g of each sample (six productions) was served in disposable plastic plates, encoded monadically with a three-digit algorithm, at room temperature and in individual cabins.

Descriptive attribute evaluation test

Eleven trained judges [²¹] carried out the descriptive analysis method for evaluating attributes; they were selected based on their ability to spot differences amongst samples (p<0.05), their ability to repeat the results and team agreement, according to Meilgaard and coauthors (2006), Lawless and Heymann (2010) and Dutcoski (2013) [²², ²³, ²⁴].

A team of judges, as listed in Table 1, defined their references for each sensorial descriptor of interest for the research.

Table 1
Sensory descriptors and intensity references used in attribute evaluation.

Descriptor/Attribute	Definition	Reference
Milk flavor	The intensity of the milk flavor is found in cookies.	Imperceptible: Cookies without milk flavor. Extremely intense: Cookies manufactured with more than 50% of flavor applied in the formulation.
Color	Characteristic color of baked cookies. Varies from white to dark brown.	Imperceptible: Wheat flour used in the product. Extremely intense: Caramel-flavored ice cream syrup.
Hardness	Force is required for the product to break between the molars.	Soft: Marshmallow. Extremely hard: Hard candy (glazed).
Texture	Force is required for the product to disintegrate.	Little: Corn cake. A lot: Peanut brittle.

A nine-centimeter non-structured scale anchored in two extreme spots evaluated the intensity of attributes during testing in each sample. The test was conducted with two repetitions [²⁵].

Affective tests

Affective acceptance, preference, and purchasing intention tests were conducted with 100 judges [²²]. Flavor, color, texture, and global impression were the attributes related to acceptance, using a 9-point hedonic scale. A 5-point scale measured the purchasing intention test. Based on the results of the affective tests, it was possible to construct the internal preference map [²⁴].

Statistical analysis

Variance analysis (ANOVA) and Tukey's test with a 5% significance level were applied to the data that met the normality assumption. Non-parametric tests were utilized for datasets that did not exhibit symmetry.

The correlation between the cookies' instrumental and sensory analysis data and the consumer preference map was determined using main component analysis (PCA). All data was processed with the Statistic software (7.0 version), Minitab (14 version), or XLstat (2014 version).

RESULTS

Sugar alterations through pneumatic conveying

Samples from different sugar suppliers had a 23.3% granulometry reduction average, going from 0.61 mm to 0.47 mm, and did not differ between themselves (p>0.05) after pneumatic conveying [³]. It was noted that luminosity increase (L*) and yellow coloring reduction (b*) APT, indicating that the smaller the sucrose crystal is, the clearer the sugar is (Table 2).

Table 2
Color of sugar samples - transport and supplier factors1

Factor	Color 3
	L	a*	b*
Transport2
ATP	86.89 b	0.03a	9.38a
DTP	93.29 a	0.01a	5.49b
Supplier
A	90.71a	-0.02 a	7.19 a
B	89.63a	0.03b	7.27 a
C	90.56 a	0.12 c	7.83 a

• ¹
  Medians (n=5). Equal letters in the same column do not differ significantly according to the Kruskal Wallis test (p<0.05).
• ²
  ATP: sugar before pneumatic transport; DTP: sugar after pneumatic transport.
• ³
  L: luminosity; a^*: chromatic interval between red-green; b^*: Chromatic interval between yellow-blue.

Texture and donut-shaped cookies color

Texture instrumental analysis presented that the granulometry level of the sugar used in the test influenced cookies' hardness and fracturability values (Table 3). Cookies made with BPT sugar had a 2.33N hardness average, and the ones made with APT sugar had a 3.53N hardness average (p<0.05). These data values are smaller than those found in literature, which described the hardness varying between 20.5N to 16.1N in cookies with 31.2 to 17.6% sugar in dough making, respectively [⁴]. Different products making, processes and other ingredients can also affect cookies' hardness.

Table 3
Hardness and fracturability in cookies made with ATP and DTP sugar.

Hardness (N) - Transport x supplier interaction1
Transport2	Supplier
	A	B	C
ATP	2.36 ± 0.07 aB	2.51 ± 0.27 aB	2.12 ± 0.48 aB
DTP	3.68 ± 0.09 bA	3.19 ± 0.12 bA	3.47 ± 0.29 bA
Fracturability (mm) - Transport factor
ATP	0.08 ± 0.03a
DTP	0.11 ± 0.02b

• ¹
  Mean ± standard deviation (n=5). Equal lowercase letters in the row indicate statistically equal means by Tukey's test at the 5% significance level. Equal uppercase letters in the column indicate statistically equal means by Tukey's test at the 5% significance level.
• ²
  ATP: sugar before pneumatic transport; DTP: sugar after pneumatic transport.

Sugar with smaller granules diameters (APT) caused the cookies to have greater hardness and higher fracturability (p<0.05), an 47.9% and 37.5% increase average, respectively. Sugar with bigger granules (BPT) caused the cookies to have lesser hardness and fracturability (p<0.05). This behavior is widely reported in the literature [²⁸, ²⁹, ³⁰], where smaller sucrose particles are associated with increased cookie hardness due to their greater surface area and faster incorporation into the dough matrix. In contrast, coarser sugar particles tend to dissolve more slowly, remaining partially crystalline during baking and creating discontinuities in the structure, which contribute to a more tender and less compact texture. During baking, cookies undergo multiple transformations, including the formation of a porous structure, moisture loss, and browning reactions, while expansion progressively stops as gases are released and water evaporates [³¹].

BPT sugar from different suppliers presented similar (p>0.05) luminosity (55.81) and BCU (3.24) values (Table 4). The cookies' luminosity values found in this study are smaller when compared to those reported by Gallagher and coauthors (2003) [³⁵], Ryan and Brewer (2006) [³⁶], and Laguna and coauthors (2012) [¹³]. Sugar origin was only influenced by the* color gap (p<0.05), and the cookie fabricated with supplier C sugar showed less tendency to red coloring (Table 5).

Table 4
Color of cookies (Brightness and BCU) - Transport x supplier interaction1

Transport2	L			BCU 3
	Supplier			Supplier
	A	B	C	A	B	C
ATP	56.48± 0.83aA	55.77±1.68aA	55.18±1.73aA	3.28±0.05aA	3.22±0.11aA	3.21±0.11aA
DTP	49.04±0.99bcB	46.98±0.97bB	50.21±1.91bB	2.81± 0.06bcB	2.68±0.07bB	2.90±0.12bB

• ¹
  Mean ± standard deviation (n=5). Equal lowercase letters in the same row and equal uppercase letters in the same column indicate statistically equal means by Tukey's test at the 5% significance level.
• ²
  ATP: sugar before pneumatic transport; DTP: sugar after pneumatic transport; L: luminosity.
• ³
  BCU: Baking Contrast Units.

Table 5
Color of cookies - transportation and supplier factors1

Factor	Color 3
Transport 2	a*	b*
ATP	18.06 ± 0.44b	31.46 ± 0.69b
DTP	18.30 ± 0.42a	34.47 ± 0.77a
Supplier	a*
A	18.39 ± 0.24a
B	18.43 ± 0.28a
C	17.71 ± 0.35b

• ¹
  Mean ± standard deviation (n=5). Lowercase letters in the same column indicate statistically equal means by Tukey's test at the 5% significance level.
• ²
  ATP: sugar before pneumatic transport; DTP: sugar after pneumatic transport; a^*: chromatic range between red-green; b^*: chromatic range between yellow-blue.

Cookies fabricated with BPT sugar had higher luminosity (L*), less intense yellow (b*) and red color (a*), and a more intense crust color (BCU) compared to cookies fabricated with APT sugar (Tables 4 and 5). These data indicate that the sugar pneumatic conveying contributed to a 12.6% luminosity reduction average (L*), producing darker cookies and a greater tendency to the yellow color.

Sensory descriptive donut-shaped cookies attribute evaluation

Color, flavor, fracturability and hardness attributes were sensorial-described in samples (Figure 2 and Table 6). Hardness values varied between 4.75 to 5.03 and are consistent with those reported by Molina and coauthors (2021) [²⁷], who evaluated hardness and granulation on cookies made with different granulometry and amounts of sucrose. The authors observed through a sensory panel and an 11-point scale that the hardness varied from 4.4 to 5.6 and increased as the sucrose: flour ratio increased, not resulting in sensorial differences on cookies made with granule or powder-shaped sucrose.

Table 6
Analysis of sensory attributes (transport and supplier factors1).

Factor	Attributes
	Milk flavor	Color	Hardness	Fracturability
Supplier
A	7.60 ± 0.51a	5.53 ± 1.40a	5.03 ± 1.15a	4.04 ± 0.59b
B	7.73 ± 0.42a	5.56 ± 1.43a	5.02 ± 0.95 a,b	4.35 ± 0.50 a
C	7.74 ± 0.48a	5.58 ± 1.50a	4.75 ± 1.09b	4.35 ± 0.56a
Transport2
ATP	7.73 ± 0.45a	4.25 ± 0.6b	4.03 ± 0.55b	4.04 ± 0.53b
DTP	7.66 ± 0.49a	6.88 ± 0.53a	5.85 ± 0.56a	4.45 ± 0.54a

• ¹
  Mean ± standard deviation. Lowercase letters in the same column indicate statistically equal means by Tukey's test at the 5% significance level.
• ²
  ATP: sugar before pneumatic transport; DTP: sugar after pneumatic transport.

Figure 2
Descriptive sensory profile of color, flavor, fracturability and hardness attributes of biscuit dough made with sugar before (BPT) and after pneumatic conveying (APT).

The data was shown (Figure 2) using the product's attribute average values. The center of the figure represents the attribute scale starting point, in which intensity rises from the center to the periphery. Each attribute average is marked in its corresponding axis. Results suggest that cookies made with BPT sugar differ in a sensorial aspect from cookies made with APT sugar, especially in color and hardness attributes. It was possible to quantify the sensorial differences related to cookies fabricated with different granulometry (BPT and APT) and origins (Suppliers A, B, and C).

Variance analysis applied to the data collected in the sensorial test indicates isolated data variation (p<0.05) related to two respective factors: transport and supplier. Considering the supplier factor, there was only a fracturability significant value difference (p<0.05); cookie made with Supplier A sugar had a smaller value (p<0.05) and differed from cookies made with Suppliers B and C sugar, which did not differ between itself. However, considering the transport factor, flavor was the only non-different attribute between cookies made with BPT and APT sugar (Table 6). Hardness, fracturability, and color values pointed out by the judges were significantly (p<0.05) higher than cookies made with APT sugar, which matches the instrumental analysis results. Results showed that cookie differences caused by sugar granulometry influence could be sensory noticeable by trained judges, matching instrumentally measured results.

Acceptance, preference, and purchase intention of donut-shaped cookies

Sensorial acceptance of taste, color, texture, and global impression attributes presented variance between suppliers, but sugar-conveying conditions (BPT and APT) did not influence consumer acceptance. Sugar from Supplier B resulted in fewer accepted cookies regarding texture aspect (p<0.05) (Table 7) when compared to samples from cookies made with Suppliers A and B sugar. Even so, sugar granulometry is unrelated to this fact because the granulometry values did not differ between suppliers under the same conveying conditions. The rest of the evaluated attributes had no difference (p>0.05).

Table 7
Acceptance of cookies - supplier factor1

Supplier	Sensory attributes
	Taste	Color	Texture	Overall Impression
A	7.51 ± 1.2a	7.59 ± 1.2a	7.43 ± 1.2a	7.47 ± 1.2a
B	7.31 ± 1.3a	7.27 ± 1.3b	7.07 ± 1.4b	7.29 ± 1.2a
C	7.51 ± 1.2a	7.37 ± 1.4a,b	7.41 ± 1.2a	7.51 ± 1.2a

• ¹
  Mean ± standard deviation (n = 100). Lowercase letters in the same column indicate statistically equal means by Tukey's test at the 5% significance level.

The principal components and an internal preference map (Figure 3) were analyzed using the consumer's preference data. Data derived from attributes evaluated in the acceptance phase were included in the preference map. Based on this, sensorial characteristics were related to consumer preferences. The first main component explained that 80.64% of the variance occurred between samples. Main components 1 and 2 explained together 92.76% of the variance between samples, which indicates that the variance between samples was almost totally explained by these two components.

Figure 3
Descriptive sensory profile of color, flavor, fracturability and hardness attributes of biscuit dough made with sugar before (BPT) and after pneumatic conveying (APT).

The portrayal (Figure 3) suggests that consumers formed two distinct preference-groups. Cookies made with Suppliers A (BPT and APT) and C (BPT) sugar were remarked for their higher color, global impression, texture, and flavor attribute values (Preference 1). Otherwise, cookies made with Supplier B (BPT and APT) and C (APT) sugar were positioned on the left axis, and the sample descendant from Supplier B (APT) presented lower values related to the attributes evaluated. The map analysis shows that even with noticeable differences between samples under instrumental analysis, the consumer's preference is not affected by it.

Cookies exhibited a 73.6% to 80.6% purchase intention, which indicates that consumers would acquire every sample. The highest purchase intention value was observed in cookies made with Supplier A APT sugar (80.6%), whose intention was similar to the one obtained in Supplier C BPT sugar (80.0%). The results suggest that the sugar granule size used in cookie making did not influence the consumers' purchase intention.

DISCUSSION

The results indicate that collisions and interactions during pneumatic conveying cause sucrose particle breakage and make the product clearer, affecting its quality, according to other studies reports [¹⁷]. Smaller sucrose crystals show better uniformity and well-formed edges, reflecting more light [²⁶].

Although the primary focus of the study is on the physical and technological aspects of the cookies, other implications can be observed as a result of changes in granulometry. Changing the size of sugar particles affects texture, color, and macromolecular interactions in the dough cookie. These include changes in the gelatinization of starch, the formation of the gluten network and water retention [²⁷], and changes in the final microstructure of the product, which ultimately culminate in changes in texture during baking. In addition, other biochemical reactions can be altered, such as non-enzymatic browning reactions (like the Maillard reaction and caramelization) and the formation of aromatic compounds in the final product, which also impact sensory changes in the product evaluated. From a structural point of view, the presence of larger sugar crystals in the dough can create microvoids if dissolution is not complete. This contributes to a reduction in mechanical strength and, consequently, lower hardness.

Sugar with less granulometry (APT) presented a faster dissolution rate caused by the superficial area/volume ratio [²⁶, ²⁷] and greater availability to interact with doughs other ingredients [²], contributing to greater hardness and fracturability values. Sugars, other than acting as a sweetness agent, also act as an anti-plasticizer when dissolved in water and modify the dough's thermic/viscoelastic behavior during the cooking phase [²⁷]. In addition to formulation differences, sugar particle size plays a key role in determining cookie hardness due to its influence on dissolution kinetics and dough structure. Finer sugar particles dissolve more rapidly during mixing, leading to a higher concentration of solubilized sucrose in the aqueous phase of the dough. This increases the competition for water with proteins and starch, limiting gluten development and starch swelling, which ultimately contributes to a denser and harder baked structure.

These study's results are consistent with the ones reported by [²⁸], which formulated cookies with ultrathin particles (until 500 um) or thin particles (over 500 um) and demonstrated that less granulometry sucrose could delay or stop starch and gluten proteins thermic transitions, affecting the cookies texture properties. For this reason, this research reaffirms literature findings that the amount of sugar that gets in solution depends on sugar particle size [²⁹], influencing its interaction with other ingredients, cookie expansion, and, accordingly, its texture [³⁰].

In a similar study [²⁸], sugar fractions with particle sizes >180 µm, between 150-180 µm, and <150 µm were evaluated. The authors reported that formulations containing the finest fractions (<150 µm) exhibited the greatest hardness, reaching values of approximately 6.51 N. These findings indicate that the particle size of sugar and flour plays a significant role in determining dough rheology and the final quality of cookies. Specifically, reducing sugar particle size increases cookie hardness, whereas decreasing flour particle size has the opposite effect, in addition to promoting darker products. Furthermore, formulations with particle sizes below 150 µm showed superior sensory performance. Comparing these findings with the present results, a similar trend is observed, where the reduction in sugar particle size leads to increased hardness values. However, the lower hardness values obtained in this study suggest that factors such as dough composition, moisture content, and processing conditions may modulate the intensity of this effect. This reinforces that sugar particle size interacts with multiple variables in determining final texture.

The magnitude and direction of the effect observed in the present study are in agreement with previous findings, which consistently report an increase in hardness as sugar particle size decreases. However, the absolute hardness values reported here are lower than those found in other studies, which may be attributed to differences in formulation, sugar concentration, and processing conditions. This highlights that, although the trend is consistent, the extent of the effect is system-dependent.

Other studies have also demonstrated that ingredients with different particle size distributions significantly affect the quality of bakery products. The main reported changes include variations in hardness, chewiness, and specific volume [³², ³³, ³⁴]. Taken together, these studies support the hypothesis that particle size distribution is a critical parameter in bakery product design, as it governs ingredient functionality at both microscopic and macroscopic levels. In particular, sugar particle size influences not only mechanical properties such as hardness and fracturability, but also dough rheology, heat transfer, and structural setting during baking.

The control of sugar granulometry during pneumatic conveying is a fundamental aspect of food engineering, as it directly influences processed products' quality and final properties. Pneumatic conveying, widely used in the food industry because it is a closed and efficient system, can cause sugar crystals to fragment due to the impact between particles and with the walls of the pipes, resulting in changes in particle size and shape [⁹]. These changes affect not only the processability of the ingredient, such as its fluidity and dissolving capacity [²], but also impact the sensory and technological properties of the final products, such as texture, color, and expansion of the cookies [⁴]. Similarly, the finding that reducing sugar granulometry during pneumatic conveying results in more complex and darker cookies can guide engineers to adjust conveying parameters (such as pressure, air velocity and exposure time) to preserve desired ingredient and final product characteristics. In addition, these results can be extrapolated to developing processing technologies that minimize unwanted changes in other sensitive ingredients, promoting greater quality control and standardization in automated production lines [¹⁷]. This understanding of the impact of pneumatic sugar transport on cookie characteristics can bring new knowledge to the food industry. This can help optimize processes, provide greater standardization and food quality, and enable the development of more efficient processing technologies adapted to the specific needs of each product [¹⁷]. Therefore, the results of this study reinforce the importance of controlling sugar granulometry as a technological parameter, as even subtle reductions in particle size can significantly alter the mechanical properties of cookies. This relationship between particle size and hardness should be considered in industrial applications aiming to standardize texture and optimize product quality.

Regarding color, the cookies' crust darkening may be related to higher sugar dissolution in the dough, which participates in darkening reactions during baking. Changes in cookie surface color are produced by non-enzymatic darkening reactions and sugar caramelization during cooking [³⁷]. According to Laguna and coauthors (2012) [¹³], the gold-brown color results from sugar reducers and amino acids interaction beyond the Maillard reaction, which forms brown polymers or melanoidin.

Total color difference (∆E) was calculated based on each gap variation, starting from conveying conditions' average values (BPT and APT) or considering the color difference between cookies fabricated with BPT and APT sugar. ∆E found value was 7.68, higher than the one reported by Clerici, Oliveira, and Nabeshima (2013) [²⁰], who found a 2.79 ∆E value. Laguna and coauthors (2012) [¹³] reported that values higher than 3.0 ∆E indicated color differences noticeable to the human eye. Therefore, it is possible to say that there was a perceptible color variation between BPT and APT sugar.

According to results obtained through instrumental analysis, cookies made with sugar submitted to pneumatic conveying tend to show darker coloring, higher hardness and fracturability.

The granulometric reduction of sugar during pneumatic conveying, although expected due to friction and impact between particles and metal surfaces, generates direct consequences on the behavior of the ingredient during thermal processing and, by extension, on the structure and texture of the final product. The results suggest that smaller particles favor greater dissolution of the sugar in the dough, intensifying Maillard reactions and caramelization and modifying the dough's macromolecular matrix, altering its mechanical resistance.

In addition, this study advances state of the art by linking, in an unprecedented way, the industrial process of pneumatic transportation to measurable changes in the quality of the final product, both in instrumental and sensory parameters.

The use of principal component analysis made it possible to demonstrate the strong correlation between sensory and instrumental attributes and show that the physical changes caused by the pneumatic transportation of sugar do not negatively impact consumer acceptance. Based on the results obtained, further studies could be carried out varying the pneumatic conveying conditions, such as pressure, airspeed, and the time the sugar is exposed to the system, to minimize the excessive reduction in crystal granulometry. Maintaining an intermediate granulometry can balance the operational efficiency of conveying and preserving the desired characteristics of the sugar, avoiding an excessive increase in hardness and darkening of the cookies. This technological optimization of the process can be strategic in modulating the characteristics of the sugar and the final product. In addition, implementing real-time monitoring systems for sugar granulometry during transport would enable automatic adjustments to the process parameters, ensuring greater final product standardization and quality.

Still, considering data obtained through affective and sensory analysis, it is suggested that the cookie industry can accept granulometry differences caused by the sugar's origin or by the use of pneumatic conveying technology since they do not compromise acceptance, purchase intention, or consumer preference.

Instrumental and sensory data correlation

The descriptive sensory attribute evaluation and instrumental analysis results were graphically exhibited (Figure 4) by a multivariate principal component analysis (MCA), making it possible to measure and evaluate a correlation between the values obtained. It was pointed to two distinct regions for the results, suggesting a similarity between the values under the same sugar-conveying conditions.

Figure 4
Principal component analysis for sensory attributes and instrumental measurements - BPT and APT sugar conveying.

Principal components 1 and 2 explained together 78.36% of the variation between samples. Paula and Conti-Silva (2014) [³⁸] explained a 74.4% data variance for two components in a snack texture instrumental and sensory correlation study using MCA. The first principal component explained that 53.72% of variance occurred between samples. The main sensorial descriptors related to this component were color, hardness, and fracturability, and color (BCU), hardness, fracturability, and granulometry instrumental results. It was noticed a contrast between hardness (instrumental and sensory), fracturability (instrumental) and color (sensorial) vectors with color (BCU) and granulometry vectors. Variance in the second main component (24.64%) was associated with flavor evaluated only under sensory matter, and, in this case, the association with this component was negative. Regarding vectors proximity (Figure 4), it is noticeable a positive linear correlation between hardness (instrumental and sensory), fracturability (instrumental and sensory) and between color and hardness (sensory). These variants presented a negative correlation with granulometry e and color (BCU).

Arifin and coauthors (2010) [³⁹] applied main component analysis to analyze data descendant from Quantitative Descriptive Analysis (QDA) and consumer’s acceptance test. Authors noticed high negative correlation between global “cookies” acceptance with hardness and fracturability, indicating that when these two factors increased, acceptance decreased. However, this fact was not observed in this research. Blonska, Marzec and Blaszczyk (2014) [⁴⁰] described the texture of cookies with different inulin and fat contents through main components that explained 83.8% of the data’s variance. It was observed strong positive correlations (higher than 0.8) between hardness, sound and crunchiness sensory evaluated with mechanical properties instrumentally measured. Correlation values obtained are similar to the ones found in this study.

The correlation between sensorial attributes with trained judges and the instrumental parameters (Table 8) demonstrates significant and positive correlation between instrumental and sensory hardness, between instrumental hardness and sensory fracturability, and between instrumental hardness and sensory color. As a result, it is affirmable that as instrumental measured hardness increases, it also occurs an increased perception of intensity in the hardness, fracturability and color sensory attributes.

Table 8
Pearson correlation matrix (n-1) for the sensory attributes (trained judges) and instrumental parameters evaluated in the cookies.

		Sensory attributes				Instrumental parameters
		Taste	Color	Hardness	Fracturability	Hardness (N)	Fracturability (mm)	BCU1	Granulometry (mm)
Sensory attributes	Taste	1	0,32	0,25	0,02	0,19	0,06	-0,44	-0,42
	Color	0,32	1	0,71	0,50	0,83	0,49	-0,84	-0,87
	Hardness	0,25	0,71	1	0,31	0,75	0,47	-0,84	-0,78
	Fracturability	0,02	0,50	0,31	1	0,44	0,32	-0,39	-0,44
Instrumental parameters	Hardness (N)	0,19	0,83	0,75	0,44	1	0,55	-0,75	-0,87
	Fracturability (mm)	0,06	0,49	0,47	0,32	0,55	1	-0,55	-0,54
	BCU1	-0,44	-0,84	-0,84	-0,39	-0,75	-0,55	1	0,83
	Granulometry (mm)	-0,42	-0,87	-0,78	-0,44	-0,87	-0,54	0,83	1

• ¹
  BCU: Baking Contrast Units - instrumental color measurement. Bold values indicate significant correlation at a 5.0% significance level.

Still, it was noticed that fracturability values measured in a sensorial and instrumental way showed positive correlation, but not significant. Alternatively, in the matter of cookies colors, matrix values presented significant and negative correlation between instrumental (BCU) and sensorial color, which was expected because of the parameters scale differences. The BCU scale varied between 0 (darker) and 5.25 (lighter) and the sensory scale varied between 0 (lighter) and 9.0 (darker).

Pearson's correlation matrix (Table 8) also showed strong negative correlation between granulometry and instrumental and sensorial hardness. The same behavior occurred in correlation to the color sensory evaluated. Regarding the BCU, it was noticed a strong positive correlation with granulometry. Due to this, when granulometry values decrease, the cookies hardness and color are increased, making it harder and darker.

However, it is important to emphasize that the experimental model used has inherent limitations. The analyses were conducted exclusively on milk-flavored cookies, using sugar from three suppliers in the same geographical region. Although these controls bring robustness to the experimental design, they limit the direct extrapolation of the results to other cookie formats, doughs with different compositions, or other bakery products. It is important to recognize that other types of cookies, formulations with different levels of fat, protein, or other sugars, and ingredients from different geographical origins may respond differently to variations in sugar granulometry. Therefore, future research could explore how these granulometry changes behave in other food systems with different moisture profiles and structures. Despite this, this work makes an integrated contribution to the advancement of knowledge in food engineering by demonstrating how the control of apparently simple industrial parameters, such as the pneumatic conveying of ingredients, can significantly impact the food industry.

CONCLUSION

Pneumatic conveying affected the crystalline sugar granulometry and color, decreasing the average granules diameter and luminosity. Sugar submitted to pneumatic conveying resulted in increased hardness, increased fracturability and darker cookies when compared to those made with sugar that was not pneumatically transported. These differences were evidenced through instrumental and sensory attributes evaluation.

A strong negative correlation between sugar granulometry and instrumental and sensory hardness of the cookies was observed. The same behavior occurred between granulometry and color correlation. Thus, when the granulometry of the sugar decreases, there is an increase in hardness and darkening on milk-flavored donut-shaped cookies.

The affective tests, overall, showed that sugar granulometry had no effect on consumer acceptance, preference and purchase intention. For this reason, the cookie industry can admit sugar and cookies differences caused by the use of pneumatic conveying technology.

• Funding:
  This research received no external funding.
• Institutional Review Board Statement: The study was approved by the Ethics Committee for Research Involving Human Beings (CAAE: 43419515.5.0000.5547) and was conducted in accordance with the ethical standards of the committee and the Declaration of Helsinki.
• Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Use of Generative Artificial Intelligence

The authors declare that large language models and other generative artificial intelligence (AI) or AI-assisted technologies cannot be credited as authors and have not been listed as authors of this paper.

The authors declare that generative artificial intelligence (AI) or AI-assisted tools were used under full human supervision. The tool(s) and version(s) used, and their purpose, are described here: ChatGPT (https://chatgpt.com/), was used under full human supervision for text proofreading. No confidential or sensitive data were uploaded to such tool(s), and all AI-assisted content was checked, corrected and approved by the authors, who take full responsibility for the integrity and originality of the manuscript.

Acknowledgments:

To the cookie and dough-making company for the opportunity to develop this research. To Granolab from Brazil, for its texture-meter and colorimeter machine availability, as well as the support professionals involved in the making of the texture and color analysis applied in this study.

Data Availability Statement:

Research data are available in the repository (please type the hyperlink). https://repositorio.utfpr.edu.br/jspui/handle/1/1395

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• Editor-in-Chief:
  Bill Jorge Costa

• Associate Editor:
  Bill Jorge Costa

Publication Dates

• Publication in this collection
  14 Sept 2026
• Date of issue
  2026

History

• Received
  23 May 2025
• Accepted
  26 May 2026