**Moisture-Dependent Engineering Properties of Chia (***Salvia hispanica* **L.) Seeds**

Estefanía N. Guiotto, Vanesa Y. Ixtaina, Mabel C. Tomás and Susana M. Nolasco

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53173

## **1. Introduction**

*Salvia hispanica* L., whose common name is chia, is an annual herbaceous plant belonging to the *Lamiaceae* or *Labiatae* family. This botanical species, native to southern Mexico and north‐ ern Guatemala, was an important crop in pre-Columbian Mesoamerica in conjunction with corn, beans and amaranth. Chia seeds were valuated not only for food, but also for medi‐ cines and paints [1]. Its cultivation was banned by Spanish conquerors and replaced by exot‐ ic crops (wheat and barley) [2]. Nowadays, chia seeds are being reintroduced to western diets in order to improve human health.

These seeds have been investigated and recommended due to their oil content with the highest proportion of α-linolenic acid (omega-3) compared to other natural source known to date [3, 4], and also because of their high levels of protein, antioxidant, dietary fiber, vita‐ mins and minerals [5, 6]. Chia seeds from Argentina exhibited 30.0 - 38.6 g oil/100 g, with 60.7 - 67.8 g/100 g of α-linolenic acid [7, 8]. Figure 1 shows the chemical composition of chia seed [9].

Chia seed is traditionally consumed in Mexico, the southwestern U.S., and South America, but it is not widely known in Europe. However, in 2009, the European Union approved chia seeds as a novel food, allowing them to comprise up to 5% of a bread product's total matter [10]. Today, chia is mostly grown in Mexico, Bolivia, Argentina, Ecuador, Australia, and Guatemala, and it has been demonstrated that the species has great potential as a future crop plant [7, 11].

© 2013 N. Guiotto et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Engineering seed properties and their dependence on moisture content are necessary in the design of equipment for transporting, storage and/or processing. The knowledge of the mor‐ phology and size distribution of chia seeds is essential for the adequate design of the equip‐ ment for cleaning, grading and separation. Gravimetric properties are useful for the design of equipment related to aeration, drying, storage and transport. Bulk density determines the capacity of storage and transport systems while true density is useful for separation equip‐ ment; porosity of the mass of seeds determines the resistance to airflow during the aeration and drying of seeds. The frictional properties, such as the angle of repose and the static coef‐ ficient of friction, are important for the design of grain bins and other storage structures whose operation is influenced by the compressibility and flow behaviour of materials. Sev‐ eral researchers investigated the moisture dependence of engineering properties of seed or grain and reported different behaviour of these properties as a function moisture content.

Moisture-Dependent Engineering Properties of Chia (Salvia hispanica L.) Seeds

http://dx.doi.org/10.5772/53173

383

The aim of this work was to evaluate the engineering properties of dark chia seed as a func‐

Chia seeds (20 kg) were obtained from commercial sources in Salta, Argentina (25° S, 65.5° W). Seeds were packed in hermetic plastic vessels and stored at 5 ± 1°C until use. The seeds were manually cleaned to remove all foreign matter, such as stones, dirt, and broken seeds. In this way, a randomized sample of chia seeds (about 2 kg) was picked by a sample splitter (CPASA, Centro Proveedor Agropecuario, Buenos Aires, Argentina). The seeds were man‐

The dark chia seeds were further divided into seven lots and they were conditioned to ob‐ tain a moisture content range of 4.6 - 17.7% (d.b.).To obtained a less moisture content, a pre‐ determined quantity of seeds was dried down to the desired moisture content (convection air oven, 40 - 45°C). Higher moisture contents were reached indirectly through the satura‐ tion of the atmosphere in contact with the seeds. For this purpose, small, clean and dry ves‐

hermetically sealed for 36 - 240 h. These moisture levels were selected according to the con‐

The moisture content of the samples was determined by the ASAE standard method used

ditions usually applied in harvesting and most processing operations of grains [13].

of water, which was then

ually separated according to their white or dark pericarp surface.

sels containing the seeds were placed into a container with 100 cm3

for rapeseed [14], using a convection air oven at 130 ±1°C for 4 h.

tion of the moisture content and to compare their behavior with that of other grains.

**2. Materials and methods**

**2.2. Sample preparation**

**2.3. Moisture content**

**2.1. Seeds**

**Figure 1.** Chemical composition of chia seed (% d.b.)

*Salvia hispanica* fruit consist in four nutlets, similar to an indehiscent achene, which contains a single seed. These nutlets, are commercially named as seeds, and in the text, we will use this last term. The plant produces small white and dark seeds. Most of chia population that is commercially grown today contains a low percentage of white seeds. Their shapes are oval and in general, the white seeds are somewhat larger than the black ones. Ixtaina *et al.* [12], reported length, width and thickness value of 2.11, 1.32 and 0.81 mm for dark seeds and 2.15, 1.40 and 0.83 mm for white seeds, respectively. Chia seeds are shown in Figure 2.

**Figure 2.** Photographs of dark and white chia seeds (13x)

The knowledge of engineering properties constitutes important and essential data for the design of machines, storage structures, and processes. The value of this basic information is not only important to engineers but also to food scientists, processors, and other scientists who may exploit these properties and find new uses.

Engineering seed properties and their dependence on moisture content are necessary in the design of equipment for transporting, storage and/or processing. The knowledge of the mor‐ phology and size distribution of chia seeds is essential for the adequate design of the equip‐ ment for cleaning, grading and separation. Gravimetric properties are useful for the design of equipment related to aeration, drying, storage and transport. Bulk density determines the capacity of storage and transport systems while true density is useful for separation equip‐ ment; porosity of the mass of seeds determines the resistance to airflow during the aeration and drying of seeds. The frictional properties, such as the angle of repose and the static coef‐ ficient of friction, are important for the design of grain bins and other storage structures whose operation is influenced by the compressibility and flow behaviour of materials. Sev‐ eral researchers investigated the moisture dependence of engineering properties of seed or grain and reported different behaviour of these properties as a function moisture content.

The aim of this work was to evaluate the engineering properties of dark chia seed as a func‐ tion of the moisture content and to compare their behavior with that of other grains.

## **2. Materials and methods**

#### **2.1. Seeds**

**Figure 1.** Chemical composition of chia seed (% d.b.)

382 Food Industry

**Figure 2.** Photographs of dark and white chia seeds (13x)

who may exploit these properties and find new uses.

*Salvia hispanica* fruit consist in four nutlets, similar to an indehiscent achene, which contains a single seed. These nutlets, are commercially named as seeds, and in the text, we will use this last term. The plant produces small white and dark seeds. Most of chia population that is commercially grown today contains a low percentage of white seeds. Their shapes are oval and in general, the white seeds are somewhat larger than the black ones. Ixtaina *et al.* [12], reported length, width and thickness value of 2.11, 1.32 and 0.81 mm for dark seeds and 2.15, 1.40 and 0.83 mm for white seeds, respectively. Chia seeds are shown in Figure 2.

The knowledge of engineering properties constitutes important and essential data for the design of machines, storage structures, and processes. The value of this basic information is not only important to engineers but also to food scientists, processors, and other scientists

Chia seeds (20 kg) were obtained from commercial sources in Salta, Argentina (25° S, 65.5° W). Seeds were packed in hermetic plastic vessels and stored at 5 ± 1°C until use. The seeds were manually cleaned to remove all foreign matter, such as stones, dirt, and broken seeds. In this way, a randomized sample of chia seeds (about 2 kg) was picked by a sample splitter (CPASA, Centro Proveedor Agropecuario, Buenos Aires, Argentina). The seeds were man‐ ually separated according to their white or dark pericarp surface.

#### **2.2. Sample preparation**

The dark chia seeds were further divided into seven lots and they were conditioned to ob‐ tain a moisture content range of 4.6 - 17.7% (d.b.).To obtained a less moisture content, a pre‐ determined quantity of seeds was dried down to the desired moisture content (convection air oven, 40 - 45°C). Higher moisture contents were reached indirectly through the satura‐ tion of the atmosphere in contact with the seeds. For this purpose, small, clean and dry ves‐ sels containing the seeds were placed into a container with 100 cm3 of water, which was then hermetically sealed for 36 - 240 h. These moisture levels were selected according to the con‐ ditions usually applied in harvesting and most processing operations of grains [13].

#### **2.3. Moisture content**

The moisture content of the samples was determined by the ASAE standard method used for rapeseed [14], using a convection air oven at 130 ±1°C for 4 h.

#### **2.4. Engineering properties**

The engineering properties of seeds were assessed at all moisture levels, as described below.

In order to determine the average size of the seeds, a sample of 100 seeds was randomly se‐ lected. For each individual seed, the three principal dimensions, namely length (*L*), width (*W*) and thickness (*T*), were measured using a digital micrometer (least count 0.01 mm). The three principal dimensions were used to calculate the geometric mean diameter (*D*g) and surface area (*S*) of individual grains by assuming that the seeds were ellipsoid.

The geometric mean diameter (*Dg*) of chia seeds was calculated using the following relation‐ ship [15]:

$$D\_{\mathcal{g}} = \text{(LWT)}^{1/3} \tag{1}$$

<sup>3</sup> 10 *t*

where *m* is the unit mass of the seed (g) determined in samples used to calculate the true

The equivalent diameter (*De*) and sphericity (*ϕ*), defined as the ratio between the surface area of the sphere having the same volume as that of the seed and the surface area of the

1 3 <sup>6</sup>

100

æ ö = ´ ç ÷ è ø (6)

Moisture-Dependent Engineering Properties of Chia (Salvia hispanica L.) Seeds

æ ö <sup>=</sup> ç ÷ è ø

*De L*

**Seed Moisture Content (%d.b.)\* Reference** Cumin 7.0 - 22.0 Singh and Goswami, 1996. [13] Sunflower 4.0 - 20.0 Gupta and Das, 1997. [15] Fenugreek 8.9 - 20.1 Altuntaş et *al*., 2005. [16] Safflower 3.7 - 15.6 Baümler et *al*., 2006. [17] Sunflower 2.0 – 18.8 de Figueiredo et al., 2006 [18] Sunflower 2.9 – 20.1 de Figueiredo et al., 2006 [18]

(4)

385

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(5)

*<sup>m</sup> <sup>V</sup>* r

seed, were calculated using equation 5 and equation 6 respectively [18]:

*e <sup>V</sup> <sup>D</sup>* p

f

Quinoa 4.6 - 25.8 Vilche et *al*., 2003. [22] Soybean 8.7 - 25.0 Deshpande et *al*., 1993. [23] Amaranth 7.7 - 43.9 Abalone et *al*., 2004. [24] Chia 4.6 - 17.7 Guiotto et *al*., 2011 [25] Cotton 8.3 - 13.8 Özarslan, 2002. [26]

Rapeseed 4.7 - 24.0 Çalişir et *al.*, 2005. [28]

\* Moisture content range considered in each study

**Table 1.** References studying the engineering properties of several seeds

Flaxseed 6.1 - 16.2 Coşkuner and Karababa, 2007 [27]

The static coefficient of friction was measured using two structural materials, namely galvanized iron and aluminum. These materials are commonly used for transport, storage,

density.

æ ö <sup>=</sup> ç ÷ ç ÷ è ø

The specific surface area (*S*) of chia seeds was calculated it according to equation 2 [16]:

$$S = \pi D\_{\chi}^{2} \tag{2}$$

To determine the mass of a thousand seeds (*W*1000), a set of 100 randomly selected seeds was weighed with an analytical balance (0.0001 g accuracy) and then extrapolated to 1000 seeds. This process was replicated 30 times [13].

The bulk density (*ρb*), considered as the ratio of the mass sample of the seeds to its total vol‐ ume, was determinate using a weight per hectoliter tester [16] (equipment of 90 cm3 of total volume). The true density (*ρ<sup>t</sup>* ) defined as the ratio of the mass of the sample to its true vol‐ ume, was determined using an electronic balance reading 0.001 g and a pycnometer (50±0.1 cm3 capacity, liquid displacement method)[17]. The toluene (C7H8; *ρ* = 0.867 g cm-3) was used as a solvent to prevent water absorption in the seeds during the experiment [16]. Both meas‐ urements were performed in triplicate.

The porosity value (ε) defined as the fraction of space in the bulk seed which is not occupied by the seed [18], was determined from bulk and true densities using the relationship given by [19] and [20] as follows:

$$
\varepsilon = \left(\frac{\left(\rho\_t - \rho\_b\right)}{\rho\_t}\right) \times 100 \tag{3}
$$

The seed volume (*V*) was determined from the following relationship [21]

Moisture-Dependent Engineering Properties of Chia (Salvia hispanica L.) Seeds http://dx.doi.org/10.5772/53173 385

$$V = \left(\frac{m}{\rho\_t}\right) 10^3\tag{4}$$

where *m* is the unit mass of the seed (g) determined in samples used to calculate the true density.

**2.4. Engineering properties**

This process was replicated 30 times [13].

urements were performed in triplicate.

volume). The true density (*ρ<sup>t</sup>*

by [19] and [20] as follows:

cm3

ship [15]:

384 Food Industry

The engineering properties of seeds were assessed at all moisture levels, as described below.

In order to determine the average size of the seeds, a sample of 100 seeds was randomly se‐ lected. For each individual seed, the three principal dimensions, namely length (*L*), width (*W*) and thickness (*T*), were measured using a digital micrometer (least count 0.01 mm). The three principal dimensions were used to calculate the geometric mean diameter (*D*g) and

The geometric mean diameter (*Dg*) of chia seeds was calculated using the following relation‐

The specific surface area (*S*) of chia seeds was calculated it according to equation 2 [16]:

2 *<sup>g</sup> S D* = p

To determine the mass of a thousand seeds (*W*1000), a set of 100 randomly selected seeds was weighed with an analytical balance (0.0001 g accuracy) and then extrapolated to 1000 seeds.

The bulk density (*ρb*), considered as the ratio of the mass sample of the seeds to its total vol‐

ume, was determined using an electronic balance reading 0.001 g and a pycnometer (50±0.1

The porosity value (ε) defined as the fraction of space in the bulk seed which is not occupied by the seed [18], was determined from bulk and true densities using the relationship given

> ( ) <sup>100</sup> *t b t*

r r

The seed volume (*V*) was determined from the following relationship [21]

r

æ ö - = ´ ç ÷ ç ÷ è ø

e

 capacity, liquid displacement method)[17]. The toluene (C7H8; *ρ* = 0.867 g cm-3) was used as a solvent to prevent water absorption in the seeds during the experiment [16]. Both meas‐

ume, was determinate using a weight per hectoliter tester [16] (equipment of 90 cm3

1/3 ( ) *D LWT <sup>g</sup>* <sup>=</sup> (1)

) defined as the ratio of the mass of the sample to its true vol‐

(2)

of total

(3)

surface area (*S*) of individual grains by assuming that the seeds were ellipsoid.

The equivalent diameter (*De*) and sphericity (*ϕ*), defined as the ratio between the surface area of the sphere having the same volume as that of the seed and the surface area of the seed, were calculated using equation 5 and equation 6 respectively [18]:

$$D\_e = \left(\frac{6V}{\pi}\right)^{1/3} \tag{5}$$

$$
\phi = \left(\frac{D\_e}{L}\right) \times 100\tag{6}
$$


\* Moisture content range considered in each study

**Table 1.** References studying the engineering properties of several seeds

The static coefficient of friction was measured using two structural materials, namely galvanized iron and aluminum. These materials are commonly used for transport, storage, and handling operations of grains, pulses, and seed and for building storage and drying bins. A PVC cylinder (50 mm diameter, 50 mm high, open at both ends) was placed on an adjustable tilting table, faced with the test surface, and filled with the sample. The structural surface with the cylinder resting on it was tilted gradually with a screw device until the cyl‐ inder just started to slide down [22]. The angle (α) was read on a graduated scale and the friction coefficient was calculated using the following relationship:

$$
\mu = \tan \alpha \tag{7}
$$

erally indicative of its pattern of behavior in air streams, especially with respect to the ease of separating extraneous materials from the particle during cleaning by pneumatic means [26]. Significant differences (*p* < 0.05) were found between different moisture contents for

erties, *Dg* and *S,* increased linearly 8.14% and 16.9%, respectively, in function of increasing

that observed for amaranth, flaxseed, quinoa and soybean. Similar behavior of *S* was report‐ ed for fenugreek and soybean seeds. The increase of *S* may be due to seed dilatation during

> 0.97, *p* < 0.005) (Table 2 and Figure 4). This *Dg* trend was similar to

Moisture-Dependent Engineering Properties of Chia (Salvia hispanica L.) Seeds

). Both prop‐

387

http://dx.doi.org/10.5772/53173

geometric diameter (*Dg,* mean 1.28 mm) and for specific area (*S*, mean 5.20 mm2

**Seed [Reference] Regression equation R2** Amaranth [24] 1.071 + 0.00385 x 0.99 Chia [25] 1.2075 + 0.0057 0.97 Flaxseed [27] 1.941 + 0.011 x 0.97 Quinoa [22] 1.359 + 0.009819 x 0.99 Soybean [23] 4.882 + 0.0253 x 0.99

**Table 2.** Regression equation as a function of moisture content (x, %d.b.) with their respective coefficient of

**Figure 4.** Effect of moisture content (x, % d.b.) on specific area (*S*). Date correspond to the adjusted function reported

moisture sorption, resulting in contact area enhancement.

determination (R2) for geometric diameter (*Dg, mm*).

by (a) [23]; (b) [16] and (c) [25]

moisture content (R2

where µ is the static coefficient of friction, and α is the angle of tilt (degrees). The static coef‐ ficient of friction was replicated reading ten times for each moisture content.

Different authors evaluated the engineering properties of several seeds as a function of seed moisture content (Table 1). These data were considered to compare the behavior of different grain properties with regard to moisture content.

### **3. Results and discussion**

moisture sorption, resulting in contact area enhancement.

handling machinery.

diameter (*Dg, mm*).

Dark seeds represented 89% by mass of the samples studied. The initial moisture content was 10.0% and 10.9% d.b., for dark and white seeds, respectively. Averages of the three principal dimensions were *L* = 1.97 mm, *W* = 1.29 mm, and *T* = 0.84 mm for dark chia seeds. The statistical analysis (ANOVA) detected significant differences (*p* ≤ 0.05) between different moisture levels for each principal dimension. Figure 3, shows a linearly increasing tendency between the dimensions (*L*, *W*, and *T*) and moisture content (R2 > 0.95, *p* ≤ 0.005). Similar trends of increase have been reported in fenugreek [16], quinoa [22], soybean [23] and amar‐ anth [24] seeds. Knowledge of the seed axial dimensions is important, for instance, in deter‐ mining aperture sizes in the design of grain handling machinery. \* Moisture content range considered in each study Table 1. References studying the engineering properties of several seeds **4. Results and discussion**  Dark seeds represented 89% by mass of the samples studied. The initial moisture content was 10.0% and 10.9% d.b., for dark and white seeds, respectively. Averages of the three principal dimensions were *L* = 1.97 mm, *W* = 1.29 mm, and *T* = 0.84 mm for dark chia seeds. The statistical analysis (ANOVA) detected significant differences (*p* ≤ 0.05) between different moisture levels for each principal dimension. Figure 3, shows a linearly increasing tendency between the dimensions (*L*, *W*, and *T*) and moisture content (R2 > 0.95, *p* ≤ 0.005). Similar trends of increase have been reported in fenugreek [16], quinoa [22], soybean [23] and amaranth [24] seeds. Knowledge of the seed axial dimensions is important, for instance, in determining aperture sizes in the design of grain

Figure 3. Principal dimensions of dark chia seeds with different moisture content (1:4.6, 2:6.5, 3:8.7, 4:10.0, 5:12.5, 6:15.3, 7:17.7) **Figure 3.** Principal dimensions (a) length (*L*); (b) width (*W*); (c) thickness (*T*) of dark chia seeds with different moisture content (1) 4.6%, (2) 6.5%, (3) 8.7%, (4) 10.0%, (5) 12.5%, (6) 15.3%, (7) 17.7%).

The geometric mean of the axial dimensions is useful in estimating the projected area of a particle moving in the turbulent or nearturbulent region of an air stream. It is therefore generally indicative of its pattern of behavior in air streams, especially with respect The geometric mean of the axial dimensions is useful in estimating the projected area of a particle moving in the turbulent or near-turbulent region of an air stream. It is therefore gen‐

**Seed [Reference] Regression equation R2** Amaranth [24] 1.071 + 0.00385 x 0.99 Chia [25] 1.2075 + 0.0057 0.97 Flaxseed [27] 1.941 + 0.011 x 0.97 Quinoa [22] 1.359 + 0.009819 x 0.99 Soybean [23] 4.882 + 0.0253 x 0.99 Table 2. Regression equation as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for geometric

to the ease of separating extraneous materials from the particle during cleaning by pneumatic means [26]. Significant differences (*p* < 0.05) were found between different moisture contents for geometric diameter (*Dg,* mean 1.28 mm) and for specific area (*S*, mean 5.20 mm2). Both properties, *Dg* and *S,* increased linearly 8.14% and 16.9%, respectively, in function of increasing moisture content (R2 > 0.97, *p* < 0.005) (Table 2 and Figure 4). This *Dg* trend was similar to that observed for amaranth, flaxseed, quinoa and soybean. Similar behavior of *S* was reported for fenugreek and soybean seeds. The increase of *S* may be due to seed dilatation during erally indicative of its pattern of behavior in air streams, especially with respect to the ease of separating extraneous materials from the particle during cleaning by pneumatic means [26]. Significant differences (*p* < 0.05) were found between different moisture contents for geometric diameter (*Dg,* mean 1.28 mm) and for specific area (*S*, mean 5.20 mm2 ). Both prop‐ erties, *Dg* and *S,* increased linearly 8.14% and 16.9%, respectively, in function of increasing moisture content (R2 > 0.97, *p* < 0.005) (Table 2 and Figure 4). This *Dg* trend was similar to that observed for amaranth, flaxseed, quinoa and soybean. Similar behavior of *S* was report‐ ed for fenugreek and soybean seeds. The increase of *S* may be due to seed dilatation during moisture sorption, resulting in contact area enhancement.

and handling operations of grains, pulses, and seed and for building storage and drying bins. A PVC cylinder (50 mm diameter, 50 mm high, open at both ends) was placed on an adjustable tilting table, faced with the test surface, and filled with the sample. The structural surface with the cylinder resting on it was tilted gradually with a screw device until the cyl‐ inder just started to slide down [22]. The angle (α) was read on a graduated scale and the

> a

where µ is the static coefficient of friction, and α is the angle of tilt (degrees). The static coef‐

Different authors evaluated the engineering properties of several seeds as a function of seed moisture content (Table 1). These data were considered to compare the behavior of different

Dark seeds represented 89% by mass of the samples studied. The initial moisture content was 10.0% and 10.9% d.b., for dark and white seeds, respectively. Averages of the three principal dimensions were *L* = 1.97 mm, *W* = 1.29 mm, and *T* = 0.84 mm for dark chia seeds. The statistical analysis (ANOVA) detected significant differences (*p* ≤ 0.05) between different moisture levels for each principal dimension. Figure 3, shows a linearly increasing tendency between the dimensions (*L*, *W*, and *T*) and moisture content (R2 > 0.95, *p* ≤ 0.005). Similar trends of increase have been reported in fenugreek [16], quinoa [22], soybean [23] and amar‐ anth [24] seeds. Knowledge of the seed axial dimensions is important, for instance, in deter‐

Dark seeds represented 89% by mass of the samples studied. The initial moisture content was 10.0% and 10.9% d.b., for dark and white seeds, respectively. Averages of the three principal dimensions were *L* = 1.97 mm, *W* = 1.29 mm, and *T* = 0.84 mm for dark chia seeds. The statistical analysis (ANOVA) detected significant differences (*p* ≤ 0.05) between different moisture levels for each principal dimension. Figure 3, shows a linearly increasing tendency between the dimensions (*L*, *W*, and *T*) and moisture content (R2 > 0.95, *p* ≤ 0.005). Similar trends of increase have been reported in fenugreek [16], quinoa [22], soybean [23] and amaranth [24] seeds. Knowledge of the seed axial dimensions is important, for instance, in determining aperture sizes in the design of grain

Figure 3. Principal dimensions of dark chia seeds with different moisture content (1:4.6, 2:6.5, 3:8.7, 4:10.0, 5:12.5, 6:15.3, 7:17.7)

The geometric mean of the axial dimensions is useful in estimating the projected area of a particle moving in the turbulent or nearturbulent region of an air stream. It is therefore generally indicative of its pattern of behavior in air streams, especially with respect to the ease of separating extraneous materials from the particle during cleaning by pneumatic means [26]. Significant differences (*p* < 0.05) were found between different moisture contents for geometric diameter (*Dg,* mean 1.28 mm) and for specific area (*S*, mean 5.20 mm2). Both properties, *Dg* and *S,* increased linearly 8.14% and 16.9%, respectively, in function of increasing moisture content (R2 > 0.97, *p* < 0.005) (Table 2 and Figure 4). This *Dg* trend was similar to that observed for amaranth, flaxseed, quinoa and soybean. Similar behavior of *S* was reported for fenugreek and soybean seeds. The increase of *S* may be due to seed dilatation during

Moisture content (%d.b.) 1234567

(a) (b) (c)

**Figure 3.** Principal dimensions (a) length (*L*); (b) width (*W*); (c) thickness (*T*) of dark chia seeds with different moisture

The geometric mean of the axial dimensions is useful in estimating the projected area of a particle moving in the turbulent or near-turbulent region of an air stream. It is therefore gen‐

**Seed [Reference] Regression equation R2** Amaranth [24] 1.071 + 0.00385 x 0.99 Chia [25] 1.2075 + 0.0057 0.97 Flaxseed [27] 1.941 + 0.011 x 0.97 Quinoa [22] 1.359 + 0.009819 x 0.99 Soybean [23] 4.882 + 0.0253 x 0.99 Table 2. Regression equation as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for geometric

= tan (7)

Thickness (mm) 0,5 0,6 0,7 0,8 0,9 1,0

> Moisture content (%d.b.) 1234567

friction coefficient was calculated using the following relationship:

mining aperture sizes in the design of grain handling machinery.

Width (mm)

content (1) 4.6%, (2) 6.5%, (3) 8.7%, (4) 10.0%, (5) 12.5%, (6) 15.3%, (7) 17.7%).

0,6 0,8 1,0 1,2 1,4 1,6

grain properties with regard to moisture content.

Table 1. References studying the engineering properties of several seeds

moisture sorption, resulting in contact area enhancement.

Moisture content (%d.b.) 1234567

**3. Results and discussion**

**4. Results and discussion** 

handling machinery.

Large (mm)

386 Food Industry

1,0 1,2 1,4 1,6 1,8 2,0 2,2 2,4

diameter (*Dg, mm*).

\* Moisture content range considered in each study

m

ficient of friction was replicated reading ten times for each moisture content.


**Table 2.** Regression equation as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for geometric diameter (*Dg, mm*).

**Figure 4.** Effect of moisture content (x, % d.b.) on specific area (*S*). Date correspond to the adjusted function reported by (a) [23]; (b) [16] and (c) [25]

Bulk density, true density, and porosity (the ratio of inter granular space to the total space occupied by the grain) can be useful in sizing grain hoppers and storage facilities; they can affect the rate of heat and mass transfer of moisture during aeration and drying processes. The theories used to predict the structural loads for storage structures have bulk density as basic parameter. Bulk density and porosity are major considerations in designing near-ambi‐ ent drying and aeration systems, as these properties affect the resistance to airflow of the stored mass. Grain bed with low porosity will have greater resistance to water vapor scape during the drying process, which may lead to higher power to drive the aeration fans.

Chia seed bulk density decreased from 0.713 to 0.644 g cm-3 as a function of the increase of moisture content. Table 4 shows the relationship of bulk density with moisture content re‐ ported by different authors for several seeds. Regarding bulk density, chia seeds presented a behavior similar (non-linear) to those of cumin and safflower seeds. The negative linear rela‐ tionship of bulk density with moisture content was observed by other authors for amaranth, flaxseed, fenugreek, quinoa, rapeseed, sunflower and soybean (Table 4). The decrease in bulk density of seed with increase in moisture content indicates that the increase in volumet‐

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http://dx.doi.org/10.5772/53173

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**Seed [Reference] Regression equation R2** Amaranth [24] 869 – 3.50 x 0.87 Chia [25] 697.7+ 5.0 x – 0.4 x2 0.99 Cumin [13] 407 + 15.67 x – 0.70 x2 0.97 Flaxseed [27] 822.43 – 15.308 x 0.99 Fenugreek [16] 726.76 – 27.675 x 0.98 Quinoa [22] 771.5 – 3.94 x 0.98 Rapeseed [28] 616.74 – 1.4518 x 0.93 Safflower [17] 452.2 – 0.12 x2 0.96 Sunflower [15] 472.4 – 1.69 x 0.88 Sunflower\* [18] 446.35 – 201 x 0.87 Sunflower\*\* [18] 528,75 – 2.24 x 0.80 Soybean [23] 748.9 – 1.6626 x 0.99

\* black-hull oilseed, \*\*striped-hull oilseed

**Table 4.** Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of

These discrepancies observed for as much true density as for bulk density could be due to cell structure and the volume and mass increase characteristics of the seeds as moisture con‐

The average porosity observed for all dark samples was 35.3%, with significant differences *(p* ≤ 0.05) among moisture contents. The polynomial relationship between the porosity (ε, %) and moisture content (x, % d.b.) for chia seeds can be represented by ε = 40.0745 – 1.0991 x +

crease in porosity with increase in moisture content for amaranth, cumin, flaxseed, fenu‐ greek, quinoa, rapeseed, safflower, sunflower seeds, and trend linear decrease in porosity

= 0.9701, *p* < 0.0010) [25]. Nevertheless, different authors reported linear in‐

ric expansion is greater than weight.

determination (R2) for bulk density (ρ*b*, kg m-3).

tent increases [29].

) (R2

for soybean (Table 5).

0.0049 x2

True density average of dark chia seeds with different moisture content was 1.069 g cm-3. Statistical analysis showed significant differences (*p* ≤ 0.05) between different moisture lev‐ els. The true density of seed was found to increase linearly at a decreasing in moisture con‐ tent from 4.6 to 17.7% d.b. The relationship between true density (*ρ<sup>t</sup>* , g cm-3) and the moisture content (x, % d.b.) of the seed can be represented for *ρ<sup>t</sup>* = 1.1457 - 0.008x (R2 = 0.9912*, p* < 0.0001) [25]. This trend can be attributed to minor volumetric product contraction during drying with respect to the decrease of seed mass due to water loss. The negative linear rela‐ tionship of true density with moisture content was also observed by other authors for fenu‐ greek and soybean, but it was different for cumin, flaxseed, quinoa and sunflower seeds, which increased linearly. However, a non-linear decreasing relationship of true density with moisture content was reported for amaranth and safflower seed (Table 3).


**Table 3.** Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for true density (ρ*t*, kg m-3).

Chia seed bulk density decreased from 0.713 to 0.644 g cm-3 as a function of the increase of moisture content. Table 4 shows the relationship of bulk density with moisture content re‐ ported by different authors for several seeds. Regarding bulk density, chia seeds presented a behavior similar (non-linear) to those of cumin and safflower seeds. The negative linear rela‐ tionship of bulk density with moisture content was observed by other authors for amaranth, flaxseed, fenugreek, quinoa, rapeseed, sunflower and soybean (Table 4). The decrease in bulk density of seed with increase in moisture content indicates that the increase in volumet‐ ric expansion is greater than weight.

Bulk density, true density, and porosity (the ratio of inter granular space to the total space occupied by the grain) can be useful in sizing grain hoppers and storage facilities; they can affect the rate of heat and mass transfer of moisture during aeration and drying processes. The theories used to predict the structural loads for storage structures have bulk density as basic parameter. Bulk density and porosity are major considerations in designing near-ambi‐ ent drying and aeration systems, as these properties affect the resistance to airflow of the stored mass. Grain bed with low porosity will have greater resistance to water vapor scape during the drying process, which may lead to higher power to drive the aeration fans.

True density average of dark chia seeds with different moisture content was 1.069 g cm-3. Statistical analysis showed significant differences (*p* ≤ 0.05) between different moisture lev‐ els. The true density of seed was found to increase linearly at a decreasing in moisture con‐

*p* < 0.0001) [25]. This trend can be attributed to minor volumetric product contraction during drying with respect to the decrease of seed mass due to water loss. The negative linear rela‐ tionship of true density with moisture content was also observed by other authors for fenu‐ greek and soybean, but it was different for cumin, flaxseed, quinoa and sunflower seeds, which increased linearly. However, a non-linear decreasing relationship of true density with

> **Seed [Reference] Regression equation R2** Cumin [13] 1010 + 6.05 x 0.98 Flaxseed [27] 826.92 + 28.91 x 0.99 Fenugreek [16] 1275.8 – 37.555 x 0.99 Quinoa [22] 853.19 + 13.16 x 0.98 Sunflower [15] 694.6 + 3.72 x 0.92 Sunflower\* [18] 706.12 + 4.06 x 0.94 Soybean [23] 1254.8 – 5.258 x 0.99

, g cm-3) and the

= 0.9912*,*

= 1.1457 - 0.008x (R2

0.99

0.99

tent from 4.6 to 17.7% d.b. The relationship between true density (*ρ<sup>t</sup>*

moisture content was reported for amaranth and safflower seed (Table 3).

Amaranth [24] (1411(100 + x))/

\* black-hull oilseed

determination (R2) for true density (ρ*t*, kg m-3).

Safflower [17] 0,7887+(0,000298 x)-

(100 + 1,25 x)

(0,0004551 x2)

**Table 3.** Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of

moisture content (x, % d.b.) of the seed can be represented for *ρ<sup>t</sup>*

388 Food Industry


**Table 4.** Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for bulk density (ρ*b*, kg m-3).

These discrepancies observed for as much true density as for bulk density could be due to cell structure and the volume and mass increase characteristics of the seeds as moisture con‐ tent increases [29].

The average porosity observed for all dark samples was 35.3%, with significant differences *(p* ≤ 0.05) among moisture contents. The polynomial relationship between the porosity (ε, %) and moisture content (x, % d.b.) for chia seeds can be represented by ε = 40.0745 – 1.0991 x + 0.0049 x2 ) (R2 = 0.9701, *p* < 0.0010) [25]. Nevertheless, different authors reported linear in‐ crease in porosity with increase in moisture content for amaranth, cumin, flaxseed, fenu‐ greek, quinoa, rapeseed, safflower, sunflower seeds, and trend linear decrease in porosity for soybean (Table 5).


Since porosity depends on bulk and true densities, the magnitude of its variation depends mainly on these properties. Therefore, the porosity of each type of seed or grain could re‐ spond differently with increasing moisture content. This fact could be attributed to the seeds' morphological characteristics; the relative changes in their length, width, and thick‐ ness; and the associated bulk and true densities. Taking into account the high level of poly‐ unsaturated fatty acids, chia seeds can be easily affected by temperature. For this reason, aeration is an important process to maintain a low uniform temperature and prevent the moisture migration. The resistance to airflow or pressure drop is affected by different fac‐ tors, such as the bulk density, porosity, and moisture content. Due to the low bulk density and size of chia seeds, the grain bed will have an important pressure drop, requiring a high

The variation of volume (*V*), equivalent diameter (*De*), thousand seed mass (*W1000*), and sphericity (*ϕ*) of chia seeds with moisture content (4.6 - 17.7 % d.b.) is shown in Figure 5.; the

revealed significant differences (*p* < 0.05) between seeds with different moisture content for *V, De* and *W1000*. Nevertheless, sphericity did not present significant differences (*p* > 0.05).

The sphericity varied between 65.8% and 67.6%, values higher than the data reported for sunflower and safflower seed, but lower than those of amaranth, quinoa, rapeseed and soy‐

> **Seed [Reference] Sphericity (%)** Amaranth [24] 82 # Fenugreek[16] 60.79 – 64.06 Quinoa [22] 77 – 80 Rapeseed [28] 93 – 92 Safflower [17] 58 – 62 Sunflower\* [18] 49 – 52 Sunflower\*\* [18] 47 – 50 Soybean [23] 80.6 – 81.6
