**1. Introduction**

Transit-oriented development (TOD) is a strategy of urban development that maximizes the transit accessibility to urban areas within walking distance [1]. The main purpose of TOD is to increase transit user comfort and alleviate automobile use by creating an accessible public transportation environment within the city [2]. Moving towards a transit-oriented approach, personal mobility can be prevented and looking in the long-term, more sustainable cities can be built [3].

TOD is practiced in densely populated areas with high demand for transit system facilities such as subway and bus stations. When planning a new public transportation system, organizers must first contemplate the socio-economic characteristics of the area and plan transportation facilities accordingly to the population density, land use, commercial facilities, and residences in the area [4]. The travel demand for transit systems increases when stations are newly introduced into an urban area. Early TODs focused on increasing the connectivity between urban planning and public transit to address problems such as urban sprawl, tra ffic congestion, and environmental degradation [5]. The development of the TOD concept was aimed at urban planning with a focus on public transit within the city [6]. Historically, TOD has been recognized as an e fficient development strategy in terms of the transit environment and socio-economic characteristics [7]. Calthorpe [1] stated that research on public transit use via high-density, multi-purpose land-use patterns could help shape a culture toward becoming a transit-friendly environment. This concept considered the regional factors, such as population density, complex land use, trip purpose, trip frequency, trip demand, and mode [2]. Also, various studies established the TOD evaluation criteria to achieve a more e fficient and sustainable transit environment and solve complex urban problems. Most previous research stated that e fficient and sustainable transit must balance the social and economic aspects of the transportation environment [8–10]. It means that land use, population density, and residential environment should be closely examined in urban planning [9]. To maximize e fficiency at the economic level, transit capacity must be met and maintained to minimize the consumption of resources [11]. The e fficiency of TOD also has been explored in previous studies [12–18]. They established one or more indicator variables to quantify the e fficiency of TOD strategies. Renne and Wells [16] identified various useful TOD indicators from monitoring successive TODs. Galelo et al. [17] found that travel volume was one of the most representative indicators for evaluating TOD e fficiency. However, Yu et al. [18] suggested that a single indicator had a limitation to e ffectively measure the performance of TOD e fficiency and multi-indicators were required.

The massive data created by the Internet of Things (IoT) in cities now enables data scientists to analyze the objective functions of TOD. With its data-driven approaches, data envelopment analysis (DEA) has been widely used to measure the e ffectiveness of the operation or management of transportation systems [19]. DEA has a significant advantage compared to parametric models as it does not require weight parameters to measure e fficiency [20]. The merit of DEA is its simplicity in estimating e fficiency with multiple inputs and outputs [19]. DEA also has merit compared to the parametric model. The parametric model assumes a specific production function for the relationship between input and output [18]. However, DEA does not make assumptions about the production function and the given data are utilized to estimate the production relationship between input and output [21]. Therefore, it is possible to avoid the error of setting the type of distribution according to the arbitrary judgment of the analyst. It is possible for the network DEA model to be designed in the order of stages which is required for the evaluation process [22,23]. It is also used with the slacks-based measure (SBM) model for direct comparisons between the observations [24]. The early DEA models have the disadvantage that the ine fficiency cannot be directly compared between di fferent observations [25], but the SBM model allows direct comparison between di fferent observations by measuring e fficiency based on the slack ratio [26].

The evaluation of the e fficiency of the transit system has been performed in previous studies using DEA model [27–31]. With the introduction of automatic fare collection (AFC) system, the data-driven approach for the transit-related analysis has become possible [32]. Various kinds of data, i.e., smartcard data, socio-economic data, and geographical data, were combined to evaluate the e fficiency of TOD [33]. Transit e fficiency was defined through the relationship between multiple inputs and outputs [34]. Transit e fficiency refers to how well the transit system was introduced and managed with respect to the socio-economics, transit infrastructures, and transit trips of each station area [8]. Regarding the TOD concept, both transit design and e fficiency must be considered to determine transit e fficiency [16,17].

The purpose of this research is to evaluate transit e fficiency in Seoul using the network slacks-based measure (NSBM) DEA model. The smartcard data and socio-economic data were used to evaluate the transit e fficiency of 352 subway station areas in Seoul. The evaluation process is developed as a two-stage network with transit design and e fficiency stage. In the evaluation process, the two-stage NSBM DEA model was used to measure e fficiency. The two-stage network constructed with transit design stage and transit e fficiency stage. With the results gathered from each stage, the overall e fficiency was measured to evaluate the transit e fficiencies of the subway station areas. Each station evaluated were grouped by each Seoul administrative unit and ranked based on its TOD e fficiency.

### **2. Methodology for Evaluating Transit E** ffi**ciency**

### *2.1. Concept of Data Envelopment Analysis (DEA)*

DEA is a nonparametric method for estimating production frontiers. The DEA model identifies relative e fficiencies using a number of input and output variables [20,21]. The purpose of measuring efficiency using the DEA model is to determine the strategy of an enterprise, organization, or industry. The first DEA model was developed to evaluate the e fficiency and increase production for farm yield in the UK [25]. With respect to productivity, DEA has been applied to linear programming and has been used in various fields [35]. The relative e fficiencies of decision-making units (DMUs) were determined and their performances compared. The original model was known as the Charnes, Cooper & Rhodes (CCR) model, which was employed to achieve constant returns to scale (CRS). Since the CRS condition assumes that the unit of production is kept constant at the optimal scale, the input and output are scaled proportionally. The CCR model is the most important model as it shows the most abbreviated methodological features. The CCR model estimates a ratio that can reduce the input as much as possible while keeping the output constant, and vice-versa. For example, there are some considerations to estimate the e fficiency score with the input-oriented CCR model. The e fficiency score is estimated by summing the weights of the output variables. The summed weights of output variables are between 0.0 and 1.0 score. With the observed *J* stations (*j* = 1, ... , *J*), each station produces the *M* outputs using *N* inputs. The ratio of the input value versus output value is the e fficiency score θ and the objective function is to minimize the θ*i* which is the reduced ratio of the input variables of target station *i*. The input-oriented CCR model, therefore, measures the weights of input and output variables to minimize the θ*i*, and the e fficiency score is estimated by weights of variables. The maximum value of the e fficiency score is equal to or less than 1.0 value with the constraints, i.e., *y*, *x* > 0 and λ ≥ 0. The e fficient stations consist of the production frontier, and the ine fficient stations improve e fficiency in the near direction of the production frontier. In other words, the e fficient stations are the reference group that the ine fficient station benchmarks to improve its e fficiency. The mathematical expression of the input-oriented CCR model is as follows:

$$\boldsymbol{\Theta}^{\mathrm{i}^\*} = \mathrm{Min} \left\{ \boldsymbol{\Theta}^i - \varepsilon \left( \sum\_{m}^{M} \boldsymbol{s}\_m^- + \sum\_{n}^{N} \boldsymbol{s}\_n^+ \right) \right\} \tag{1}$$

subject to:

∗

$$\begin{aligned} \theta^i \mathbf{x}\_m^i &= \sum\_{j=1}^J \mathbf{x}\_m^j \lambda^j + \mathbf{s}\_m^- \\ y\_r^j &= \sum\_{j=1}^J y\_r^j \lambda^j - \mathbf{s}\_r^+ \\ \lambda^j &\ge 0, \; \mathbf{s}\_m^- \ge 0, \; \mathbf{s}\_r^+ \ge 0 \end{aligned}$$

where θ*i* is the e fficiency score of the target station area *i*, *j* (*j* = 1, ... , *J*) is the number of observed station areas, *yj n* is the output number of each variable *r* (*r* = 1, ... , *R*) of a station area *j*, *xj m* is the input variable *m* (*m* = 1, ... , *M*) of a station area *j*, *yj r* is the output variable *r* of a station area *j*, λ*j* is the intensity vector of station area *j*, *s*− *m* is the slack vector of the input variable *xm*, *s k*+ *o* is the slack vector of the output variable *yr*.

### *2.2. Network Slacks-Based Measure DEA*

The NSBM DEA is used to measure the e fficiency of the network that consists of two or more stages. In general, measuring the e fficiency with DEA model involves two stages, an input stage, and an output stage. However, network DEA has more than two stages that include intermediate processes [22,23]. These intermediate processes are linking activities that occur in stages of production or that occur internally in DMUs. In other words, the output results of the first stage can be applied to

the second stage as inputs for the final result [22]. If the network becomes complex, early DEA models had a limitation with only contain one stage while the network DEA solves this problem by having multiple stages [24]. Since the transit system also has a complex network, the network DEA is suitable for measuring transit efficiency.

The transit infrastructure relative to the socio-economic is important in terms of the transit design [36]. Transit efficiency is defined as the number of transit trips relative to the infrastructures [37]. In this research, the transit design and transit efficiency stages were designed to measure transit efficiency. The process of TOD proceeds with three factors, i.e., socio-economic, transit infrastructure, and transit trip [11]. First, the socio-economic factors are examined to find the area where the transit is needed. Second, the transit infrastructures are built to the area selected from the socio-economic factors. Finally, the transit trips are derived through the socio-economic and transit infrastructures. These three factors are grouped by two stages which are transit design stage and transit efficiency stage. Figure 1 shows the framework of the process used to evaluate transit efficiency. The first stage, the transit design stage was measured by comparing the transit infrastructures with socio-economic factors. For the second stage, the transit efficiency was estimated by comparing the transit trips with transit infrastructures. The overall efficiency score is obtained by the average sum or weighted multiplication of each stage output from the design and efficiency stage. The weight of each stage can be determined by the purpose of the research or the characteristics of the subject [38]. Regarding the TOD evaluation, a bunch of previous studies considered the transit-related factors at the same level [11–13]. Since the concept of TOD considers design and efficiency at the same level, the importance of both stages is considered equal. In this research, identical weights are given at both stages in this research, i.e., *w*1 : 0.5 and *w*2 : 0.5. In other words, the assumption is made that both the transit design and efficiency stages are equal contributors to the overall efficiency score. With this assumption, the comprehensive efficiency of the station area could be obtained with consideration of the transit design and efficiency.

**Figure 1.** Network framework for measuring transit efficiency.

The production possibility set of network DEA is denoted as *Pnetwork* and its mathematical expression is shown in Equations (2)–(7). The term *z*(*k*,*h*) is an intermediate measure for evaluating transit efficiency, and Equation (5) show their mathematical expressions. The *z*(*k*,*h*) is applied to *z*(1,2) in this study, since the network framework for measuring the TOD efficiency requires a connection link from the transit design stage to the transit efficiency stage. Equation (5) describes an intermediate measure such as the weights of outputs from the design stage and inputs for the efficiency stage. Equation (6) is used to determine the variable returns to scale (VRS) condition. In the absence of Equation (6), CRS is assumed:

$$P\_{network} = (\mathbf{x}^k, \mathbf{y}^k, \mathbf{z}^{(k,h)}) \tag{2}$$

$$\mathbf{x}^{k} \ge \sum\_{j=1}^{J} \mathbf{x}\_{j}^{k} \boldsymbol{\lambda}\_{j}^{k} \,\forall k \tag{3}$$

$$y^k \le \sum\_{j=1}^{J} y\_n^k \lambda\_{n\prime}^k \,\forall n, k \tag{4}$$

$$z^{(k,h)} = \begin{cases} \sum\_{j=1}^{l} z\_j^{(k,h)} \lambda\_{j'}^k \,\forall k, h \text{ (as outputs from } k\text{)}\\ \sum\_{j=1}^{l} z\_j^{(k,h)} \lambda\_{j'}^h \,\forall k, h \text{ (as inputs to } h\text{)} \end{cases} \tag{5}$$

$$\sum\_{j=1}^{J} \lambda\_j^k = 1,\ \forall k\tag{6}$$

$$
\lambda\_j^k \ge 0, \,\forall j, k \tag{7}
$$

where *Pnetwork* is the production possibility set, *k* (*k* = 1, 2) is the number of stages that *k* = 1 is the transit design stage and *k* = 2 is the transit efficiency stage, *j* (*j* = 1, ... , *J*) is the number of observed station areas, *xkmj* ∈ *Rmk* + is the input variable of station area *j* of stage *k*, *ykrj* ∈ *Rrk*+ is the output variable of station area *j* of stage *k*, (*k*, *h*) ∈ *L* is the connection link from transit design stage to transit efficiency stage, *z*(*k*,*h*) ∈ *R*(*k*,*h*) + is an intermediate measure from the transit design stage to transit efficiency stage, λ*k* is the intensity vector corresponding to stage *k*, *z*(*k*,*h*) *j* λ*kj* is the outputs from the transit design stage, and *z*(*k*,*h*) *j*λ*hj*is the inputs to the transit efficiency stage.

The SBM DEA is a widely used model for evaluating efficiency [23]. Network DEA with a slacks-based approach was first developed by Tone and Tsutsui [22], and this model is called NSBM DEA model. The NSBM DEA model evaluates efficiency using the input and output slack. The slack is the difference value amount from the desired value amount from the actual input and output variables [24]. The two slack values are estimated irrespective of the variable unit and are calculated as an efficiency measure using the average of the reduced inputs and the average of the increased outputs. Since input and output variables have different units, slack values are converted to ratio values by dividing the original observation values. NSBM DEA is performed by calculating the slack between observations and production changes. NSBM DEA is referred to as a SBM because it is calculated based on the slack between the observations and production changes. The most important feature of NSBM DEA is that the measure of efficiency does not change even when the units of the input or output variables change. This is because the input or output slack is calculated as a ratio and is thus independent of the unit. Compared to the early DEA models, SBM model has the advantage of allowing direct comparison between different DMUs [23]. Since the efficiency score of early DEA model is estimated by adding the slacks of variables with different units, the inefficiency cannot be directly compared between different DMUs [28]. The efficiency of SBM model is measured by adding the slack ratio. Since SBM model uses the slack ratio of each variable, the efficiency can be measured regardless of the units of the variables [24].

NSBM DEA has three variations, i.e., the non-, input-, and output-oriented models. These three models can be employed depending on the objective or the features of the variables. In this research, we used the output-oriented SBM, for which the output direction is improving efficiency. The output-oriented SBM measures efficiency by fixed inputs and maximizing outputs. Since the outputs of each stage of transit analysis are required by the given conditions, the use of the output-oriented SBM is reasonable for determining the transit design and efficiency scores. It is difficult to change land use or eliminate existing facilities. Therefore, it is necessary to derive efficiency rankings by maximizing the output variables of each stage. NSBM DEA is widely used for evaluating relative efficiencies because it measures the efficiencies of DMUs. Given the transit system features mentioned

above, the NSBM DEA model is suitable for evaluating transit efficiency. The mathematical expression for measuring transit efficiency is shown in Equation (8).

$$\theta\_i^\* = \min \frac{\sum\_{k=1}^K w^k \left[1 - \frac{1}{m\_k} \left(\sum\_{m=1}^{m\_k} s\_{mi}^{k-} / x\_{mi}^k\right)\right]}{\sum\_{k=1}^K w^k \left[1 + \frac{1}{r\_k} \left(\sum\_{r=1}^{r\_k} s\_{ri}^{k-} / y\_{ri}^k\right)\right]} \tag{8}$$

subject to:

$$\begin{aligned} \sum\_{k=1}^{K} w^k &= 1, \,\,\forall k\\ w^k &\ge 0, \,\,\forall k\\ \mathbf{x}\_{\text{mi}}^k &= \sum\_{j=1}^{I} \mathbf{x}\_{\text{mj}}^k \boldsymbol{\lambda}\_j^k + \mathbf{s}\_{\text{m}}^{k-}, \,\forall m, k\\ y\_{\text{ri}}^k &= \sum\_{j=1}^{I} y\_{rj}^k \boldsymbol{\lambda}\_j^k - \mathbf{s}\_r^{k+}, \,\,\forall r, k\\ \sum\_{j=1}^{I} \boldsymbol{\lambda}\_j^k &= 1, \,\,\forall k\\ \boldsymbol{\lambda}\_j^k &\ge 0, \,\,\forall j, k\\ s\_{\text{m}}^{k-} &\ge 0, \,\,\forall m, k\\ s\_{\text{f}}^{k+} &\ge 0, \,\,\forall r, k \end{aligned}$$

where θ∗*i* is the overall efficiency score of station area *i*, *k* (*k* = 1, 2) is the number of the stages that *k* = 1 is the transit design stage and *k* = 2 is the efficiency stage, *wk* is the relative weight of stage *k*, *xkmi* is the input variable *m* of station area *i* of stage *k*, *ykri* is the output variable *r* of the station area *i* of stage *k*, λ*k* is the intensity vector corresponding to the stage *k*, *sk*−*m* is the slack vector of the input variable *xm* of the stage *k*, and *sk*+*r* is the slack vector of the output variable *yr* of the stage *k*.


*Article* **Development and Characterization of Pectin Films with** *Salicornia ramosissima***: Biodegradation in Soil and Seawater**

**Daniela G. M. Pereira 1 , Jorge M. Vieira 2 , António A. Vicente 2 and Rui M. S. Cruz 1,3,\***

**Abstract:** Pectin films were developed by incorporating a halophyte plant *Salicornia ramosissima* (dry powder from stem parts) to modify the film's properties. The films' physicomechanical properties, Fourier-transform infrared spectroscopy (FTIR), and microstructure, as well as their biodegradation capacity in soil and seawater, were evaluated. The inclusion of *S. ramosissima* significantly increased the thickness (0.25 ± 0.01 mm; control 0.18 ± 0.01 mm), color parameters a\* (4.96 ± 0.30; control 3.29 ± 0.16) and b\* (28.62 ± 0.51; control 12.74 ± 0.75), water vapor permeability (1.62 × 10−9 ± 1.09 × 10−10 (g/m·s·Pa); control 1.24 × 10−9 ± 6.58 × 10−11 (g/m·s·Pa)), water solubility (50.50 ± 5.00%; control 11.56 ± 5.56%), and elongation at break (5.89 ± 0.29%; control 3.91 ± 0.62%). On the other hand, L\* (48.84 ± 1.60), tensile strength (0.13 ± 0.02 MPa), and Young's modulus (0.01 ± 0 MPa) presented lower values compared with the control (L\* 81.20 ± 1.60; 4.19 ± 0.82 MPa; 0.93 ± 0.12 MPa), while the moisture content varied between 30% and 45%, for the film with *S. ramosissima* and the control film, respectively. The addition of *S. ramosissima* led to opaque films with relatively heterogeneous microstructures. The films showed also good biodegradation capacity—after 21 days in soil (around 90%), and after 30 days in seawater (fully fragmented). These results show that pectin films with *S. ramosissima* may have great potential to be used in the future as an eco-friendly food packaging material.

**Keywords:** biobased materials; biodegradable; food packaging; pectin film; physicomechanical; *Salicornia ramosissima*; sustainability

### **1. Introduction**

Packaging plays a key role in containing and protecting food from external influences, such as microorganisms, oxygen, and odors, among others. However, plastic packaging has a negative environmental impact on land and sea, since it generates huge amounts of solid waste. The reduction of this waste can be achieved with the development of new biodegradable packaging systems [1]. In recent decades, a considerable number of packaging films have been developed using biopolymers, such as proteins, and polysaccharides. More recently, the combination of clays, nanostructures, and other innovative materials has been studied for novel packaging applications [2–9]. In addition to biopolymers, plant-derived bioactive compounds—such as essential oils, minerals, carotenoids, vitamins, and polyphenols, among others—have been used to modify the films' antioxidant, antimicrobial, and physicomechanical properties [10–15].

Polysaccharides (e.g., chitosan, cellulose, starch, alginate, and pectin) have gained attention because of their good film-forming capacity [16,17]. Pectin is a heteropolysaccharide found in fruits and vegetables. It is used in food products as a stabilizing and gelling ingredient. These gelling characteristics, together with those of biocompatibility

**Citation:** Pereira, D.G.M.; Vieira, J.M.; Vicente, A.A.; Cruz, R.M.S. Development and Characterization of Pectin Films with *Salicornia ramosissima*: Biodegradation in Soil and Seawater. *Polymers* **2021**, *13*, 2632. https://doi.org/10.3390/polym13162632

Academic Editors: Swarup Roy and Jong-Whan Rhim

Received: 1 July 2021 Accepted: 4 August 2021 Published: 7 August 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

and biodegradability, make pectin an ideal biomaterial for several applications, as in the case of the pharmaceutical and food industries [18]. Several studies have reported the development of pectin films with the incorporation of different compounds. In the study reported by Makaremi et al. [18], pectin–alginate films incorporated with ascorbic and lactic acids were developed, and showed the potential to be used in food packaging. In another study, Chaiwarit et al. [19] developed a pectin film loaded with clindamycin hydrochloride to modify the film's properties and use it as a topical drug delivery system. Nogueira et al. [20] presented a review of several methods of incorporating plant-derived bioactive compounds, among others, into pectin films for application in food packaging. The incorporation of green coffee oil and γ-aminobutyric acid residues affected the color of the films. The same review presented pectin films with *Acca sellowiana* waste byproducts (feijoa peel flour) with increased thickness and different mechanical properties.

An interesting application in the development of pectin films could be the incorporation of *Salicornia ramosissima*, a halophyte plant very rich in sodium, magnesium, potassium, calcium, and manganese. Moreover, this plant also presents good antioxidant properties [21]. Recently, this plant started to be produced by hydroponic systems, and generates a considerable number of byproducts after the cutting process. Thus, the use of this plant as a natural additive could provide a pectin film with modified properties, with a potential preservation effect mainly due to the presence of salts, and could thus be a relevant outcome to obtain an effective biodegradable active packaging material, while also contributing to the valorization of a byproduct.

To our knowledge, no study is available in the literature reporting the use of *S. ramosissima* as an additive in biodegradable packaging films. Thus, the objectives of this study were to develop and characterize a pectin film incorporating a halophyte plant—*S. ramosissima*—as well as to evaluate its biodegradation capacity in soil and seawater.

### **2. Materials and Methods**

### *2.1. Materials*

Apple pectin (50–70% degree of esterification; MW = 60,000–130,000 g mol−1 ) was purchased from Sigma (Algés, Portugal). Glycerol and NaBr were purchased from JMGS (Odivelas, Portugal). *Salicornia ramosissima* dried powder (from cut stem parts; particle size < 63 µm; moisture content = 7%; lipids 0.9 g, carbohydrates 4.5 g, fiber 16 g, proteins 18 g, and salt 47 g per 100 g) was kindly supplied by RiaFresh (Faro, Portugal). The soil (Eco Grow) was purchased from AKI (Faro, Portugal).

### *2.2. Preparation of the Films*

Pectin films were developed based on the method reported by Mendes et al. [22], with some modifications. First, 0.5 g of apple pectin was added to 25 mL of water previously heated to 75 ◦C and stirred for 10 min. Next, the film-forming solution was homogenized (Ultra-Turrax T25, Janke & Kunkel, Staufen, Germany) at 20,500 rpm for 5 min, and then 1.5 mL of glycerol was added and mixed with magnetic stirring for 1 h at 40 ◦C.

The pectin films incorporating *S. ramosissima* were prepared by adding 0.75 g (2.7% *w*/*w*) of dried, fine *S. ramosissima* powder (based on preliminary tests to obtain a film with homogeneous appearance) to 25 mL of water previously heated to 75 ◦C and stirred for 10 min. After this period, the same methodology was followed as previously used for pectin films. Then, the film-forming solutions were degassed for 5 min and placed to dry in Petri dishes for 48 h at 25 ◦C. After drying, the films were cut and stored at 25 ◦C and 57% relative humidity (obtained using a saturated NaBr solution) before analysis.

### *2.3. Thickness and Water Vapor Permeability (WVP)*

Three thickness measurements were randomly taken for each testing sample at different points with a digital micrometer (No. 293-5, Mitutoyo, Kawasaki, Japan). Mean values were used to calculate the WVP. The WVP of pectin films was determined gravimetrically, using the ASTM E96-92 procedure, with some modifications [23]. The permeation cell

was filled with 50 mL of distilled water to generate a 100% RH (2337 Pa vapor pressure at 20 ◦C), and the film was sealed on the top of the cells. Then, the cells were weighed using an analytical balance (AE200, Mettler Toledo, Barcelona, Spain) and placed inside a desiccator containing silica (0% RH; 0 Pa water vapor pressure; the air circulation was kept constant by using a fan inside the desiccator). The tests were conducted in triplicate, and changes in weight of the cells were recorded at intervals of 2 h to record moisture loss over time until a steady state was reached. The WVP (g m−1 s −1 Pa−1 ) of the films tested was determined by the following equation:

$$\text{WVP} = (\text{WVTR} \times \text{X}) / \Delta \text{P} \tag{1}$$

where WVTR = water vapor transmission rate (g m−2 s −1 ) through the film, calculated from the slope of the curve divided by the film's area; X = the film's thickness (m); and ∆P = the partial vapor pressure difference (Pa) across the two sides of the film.

### *2.4. Color and Opacity*

Color measurements were performed using a colorimeter (Minolta CR 400, Tokyo, Japan) previously calibrated with a standard white tile (EU certified; L\* = 84.67, a\* = −0.55, and b\* = 0.68)), which recorded the spectrum of reflected light to determine the parameters L\*, a\*, and b\*. The opacity of the samples was calculated based on the method reported by Martins et al. [24], as the relationship between the opacity of each sample in a black standard (Yb) and the opacity of each sample in a white standard (Yw), as can be seen in the equation:

$$\text{Operity} \left( \% \right) = \text{Yb} / \text{Yw} \times 100 \tag{2}$$

Three measurements were taken from each sample, and three samples from each film were tested.

### *2.5. Solubility and Moisture Content*

The water solubility and moisture content of the films were determined according to the method reported by Casariego et al. [25]. The film solubility in water was determined as the percentage of soluble material after 24 h of immersion in water. A disk of the film (2-cm diameter) was dried in an oven at 105 ◦C until constant weight to obtain the initial dry matter of the films (this part of the method allowed determining the films' moisture content). Then, the sample was immersed into 50 mL of deionized water and gently shaken (20 ◦C, 24 h). At the end of the 24 h, the insolubilized films were filtered and dried in a drying oven (105 ◦C, 24 h) to determine the weight of the dried matter that was not solubilized in water. Three replicates were obtained for each sample. The water solubility (%) of the films was calculated as follows:

$$\text{Solubility (\%)} = (\text{Mi} - \text{Mf}) / \text{Mi} \times 100\tag{3}$$

where Mi is the initial mass and Mf is the final mass of the sample.

### *2.6. Texture Measurements*

Mechanical properties were evaluated in a texture analyzer (TA.TX Plus Texture Analyzer) with the software "Exponent version 6.1.16" (Stable Micro Systems, Godalming, Surrey, UK), according to the ASTM D 882 standard method [26].

A scalpel was used to cut the samples into 20-mm-wide, 100-mm-long strips, which were mounted between tensile grips. The initial grip separation and the crosshead speed were set at 80 mm and 1.0 mm/s, respectively. The tensile strength (force/initial crosssectional area) and the elongation at break were computed directly from the strength curves vs. elongation curves by using the "Exponent" software. Young's modulus (Equation (4)) was calculated as the slope of the initial linear portion of this curve. Six measurements were taken of each sample.

$$\mathbf{E} = \mathbf{o} \mathbf{/} \mathbf{\varepsilon} \tag{4}$$

where E represents Young's modulus, σ is the tensile stress (force per unit area), and ε is the axial strain (deformation).

### *2.7. FTIR*

ATR-FTIR was used to obtain information about the interactions between components in films. The FTIR spectra of the films were recorded with a PerkinElmer 16 PC (Boston, MA, USA), using attenuated total reflectance mode (ATR). Each spectrum resulted from 16 scans at 4-cm−1 resolution, for a spectral range of 400–4000 cm−1 . All of the readings were performed at room temperature (20 ◦C).

### *2.8. Scanning Electron Microscopy (SEM)*

The samples were characterized using a desktop scanning electron microscope. All results were acquired using the ProSuite software.

The samples were added to aluminum pin stubs with electrically conductive carbon adhesive tape (PELCO Tabs™). Samples were coated with 2 nm of Au (20 Angstrom) for improved conductivity. The aluminum pin stub was then placed inside a Phenom Standard Sample Holder (SH) and acquired with 10 kV.

### *2.9. Biodegradation Tests*

### 2.9.1. Seawater

The biodegradation test in seawater was based on the methodology used by Accinelli et al. [27], with some modifications. The films were cut (3 cm × 2 cm) and submerged in 300 mL of seawater (pH = 7.20). The samples were shaken at 150 rpm (Edmund Buhler-7400 Tubingen shaker) and 25 ◦C.

The films' appearance was photographed during the time of the experiment. This test was carried out in triplicate for each sample.

### 2.9.2. Soil

The biodegradation test in soil was based on the methodology used by Altaee et al. [28], with some adaptations. The films were cut (3 cm × 2 cm) and placed inside a perforated polyethylene net (5 cm × 4 cm; mesh opening 4 mm). The films were placed in soil (pH = 5.5–6.5; Humidity = 50–60%; Conductivity = 0.2–1.2 EC; Nitrogen = 80–150 mg L−1 ; Phosphorus = 80–150 mg L−1 ; Potassium = 80–150 mg L−1 ; Organic Matter = >70%) at a distance of 11 cm from the surface in a rectangular vase (71 cm × 26 cm × 25.5 cm), and with a distance of 5 cm between each film. The soil was watered with 500 mL of water every 7 days and maintained at 25 ◦C throughout the study. The films' appearance was photographed and the area of biodegradation was measured during the time of the experiment. This test was carried out in triplicate for each sample.

### *2.10. Statistical Analyses*

The results were expressed as the mean and standard deviation of at least three replicates. The experimental data were analyzed with IBM SPSS (Statistical Product and Service Solutions) version 26. The analysis was performed with the *t*-test to detect significant differences between the two types of film for each parameter. The significance level used was 0.05.

### **3. Results and Discussion**

### *3.1. Physicomechanical Properties*

Table 1 shows the physical and mechanical parameters of the control and the supplemented pectin films. The thickness of the film with *S. ramosissima* significantly increased (*p* < 0.05). This increase can be explained due to a greater solid mass in the supplemented film.

film.

Table 1 shows the physical and mechanical parameters of the control and the supplemented pectin films. The thickness of the film with *S. ramosissima* significantly increased (*p* < 0.05). This increase can be explained due to a greater solid mass in the supplemented

**Table 1.** Physico-mechanical parameters of the developed films. **Table 1.** Physico-mechanical parameters of the developed films. **Control Film Film with** *S. Ramosissima*

*Polymers* **2021**, *13*, x FOR PEER REVIEW 5 of 13

a, b Different superscript letters indicate significant differences (*p* < 0.05). a, b Different superscript letters indicate significant differences (*p* < 0.05).

According to Hosseini et al. [29], the increase in film thickness may be related to the increase in dry matter content. In terms of color, the control film was clear, colorless, and lighter, as expressed by the highest L\* parameter. On the other hand, the incorporation of *S. ramosissima* led to darker and brownish-green films, presenting lower values of the L\* parameter and an increase in the a\* and b\* parameters (Figure 1). These results, and the increase in the film's opacity, are associated with the existing pigments in the dried powder—mainly pheophytins—obtained after drying *S. ramosissima* [30]. In another study reported by Nisar et al. [31], pectin films enriched with thinned young apple polyphenols were produced, and the authors also reported a decrease in the L\* values and an increase in the a\* and b\* values. In another study by Sganzerla et al. [32], Brazilian pine seed starch and pectin films with the incorporation of *Acca sellowiana* extracts also showed lower L\* values, together with higher a\* and b\* parameters. According to Hosseini et al. [29], the increase in film thickness may be related to the increase in dry matter content. In terms of color, the control film was clear, colorless, and lighter, as expressed by the highest L\* parameter. On the other hand, the incorporation of *S. ramosissima* led to darker and brownish-green films, presenting lower values of the L\* parameter and an increase in the a\* and b\* parameters (Figure 1). These results, and the increase in the film′s opacity, are associated with the existing pigments in the dried powder—mainly pheophytins—obtained after drying *S. ramosissima* [30]. In another study reported by Nisar et al. [31], pectin films enriched with thinned young apple polyphenols were produced, and the authors also reported a decrease in the L\* values and an increase in the a\* and b\* values. In another study by Sganzerla et al. [32], Brazilian pine seed starch and pectin films with the incorporation of *Acca sellowiana* extracts also showed lower L\* values, together with higher a\* and b\* parameters.

**Figure 1.** Developed films: (**a**) control film; (**b**) film with *S. ramosissima*. **Figure 1.** Developed films: (**a**) control film; (**b**) film with *S. ramosissima*.

The film with *S. ramosissima* showed a slight increase in the WVP. This increase may be related to the presence of salts and, thus, to the greater availability of hydroxyl groups to bind to water molecules [33], as well as to the film′s capacity to absorb more water molecules due to its higher mass and porous structure [34]. In a study reported by Chen et al. [35], the WVP also presented the highest values in pectin-/tara gum-based edible The film with *S. ramosissima* showed a slight increase in the WVP. This increase may be related to the presence of salts and, thus, to the greater availability of hydroxyl groups to bind to water molecules [33], as well as to the film's capacity to absorb more water molecules due to its higher mass and porous structure [34]. In a study reported by Chen et al. [35], the WVP also presented the highest values in pectin-/tara gum-based edible films with ellagitannins from the unripe fruit of *Rubus chingii* Hu. On the other hand, Nisar et al. [31] showed that the WVP decreased with the addition of components rich in polyphenols. According to the authors, the mobility of pectin chains was negatively affected by the interaction with polyphenols, so that the diffusion or penetration of water molecules through membranes was reduced, with a decrease in hydrophilic groups. The film with *S. ramosissima* also presented a higher water solubility compared with the control film. Aside from any modification to the films' structure, the presence of salts such as

sodium, magnesium, or calcium—which are soluble in water [21]—also contributed to a higher solubility of the film in water. According to Nisar et al. [31], the higher values of solubility in water and the degree of swelling of the films can be attributed to the presence of hydrophilic groups; these authors reported a behavior of their system that is identical to the one reported in our study, with a significant increase (*p* < 0.05) in solubility after the addition of apple polyphenols.

The moisture content also showed significant differences (*p* < 0.05) between the control film and the film with *S. ramosissima*. This difference is related to the higher mass of dry matter present in the film with *S. ramosissima*, contributing to lower moisture content. According to Pereda et al. [36], the moisture content is related to the total void volume occupied by water molecules in the network microstructure of the film. Similar results were obtained by Yehuala and Emire [37], where the addition of *Aloe debrana* extract and papaya leaf extract affected the moisture content of gelatin films.

Regarding the films' mechanical properties, the control film presented a more resistant structure, showing a higher value of tensile strength, while the film with *S. ramosissima* was more brittle/fragile. On the other hand, the elongation at break was higher for the film with *S. ramosissima*. According to Shaw et al. [38], the decrease in film resistance (tensile strength) and the increase in stretching capacity (elongation at break) can be attributed to the reduction in the number of intermolecular crosslinks between pectin molecules within the films, thus contributing to a weaker material. Similar results to this study were obtained by Gouveia et al. [39], who reported that the addition of CHCl to the pectin films caused a decrease in traction resistance. The results of Meerasri and Sothornvit [40] also showed the same behavior, with a decrease in tensile strength and an increase in elongation at break with the addition of γ-aminobutyric acid and glycerol. Moreover, Kang et al. [41] reported similar results to the ones obtained in the film with *S. ramosissima*. Pectin–polyvinyl alcohol– glycerol films combined with gamma irradiation and CaCl2 immersion presented tensile strength values between 0.09 and 0.27 MPa, and elongation at break values between 1.02 and 3.45%.

### *3.2. Fourier-Transform Infrared Spectroscopy (FTIR)*

FTIR spectroscopy was performed to determine the intermolecular interactions within the film matrix. The FTIR spectra of the control film and the pectin film with *S. ramosissima* are shown in Figure 2. A broad peak ranging from 3700 to 3000 cm−1 corresponds to the stretching of O–H because of hydrogen bonding interactions in the galacturonic acid [42]. The peak at 2935 cm−1 is attributed to stretching of C–H bonds [43], while the bands at 1744 and 1612 cm−1 are attributed to the absorptions by esterified and free carboxyl groups of pectin, respectively [44,45]. Moreover, the bands at 1103 and 1026 cm−1 were assigned to C–O–C stretching vibrations of the polymer chain structure [46]. In general, the pectin film with *S. ramosissima* exhibited a similar pattern compared to the control film, but showed a weaker response. *S. ramosissima* dry powder is a complex mixture of diverse salts and cellulosic compounds, and its incorporation probably contributed to weakening the intermolecular forces between the chains of adjacent macromolecules [47]. This result is corroborated, as previously referred, by the lower tensile strength obtained for the film with *S. ramosissima*.

**Figure 2.** FTIR spectra: (**a**) control film; (**b**) film with *S. ramosissima*. **Figure 2.** FTIR spectra: (**a**) control film; (**b**) film with *S. ramosissima*. **Figure 2.** FTIR spectra: (**a**) control film; (**b**) film with *S. ramosissima*.

#### *3.3. Scanning Electron Microscopy (SEM) 3.3. Scanning Electron Microscopy (SEM) 3.3. Scanning Electron Microscopy (SEM)*

SEM micrographs of the films′ surface are presented in Figure 3. The pectin film presented a homogeneous, compact, and smooth surface, while the film with *S. ramosissima* presented a heterogeneous and rough surface. This result is related to the presence of salts (mainly sodium, magnesium, and potassium) from *S. ramosissima* powder that changed the structure of the pectin film. The possible presence of faults or microholes also contributed to the lower tensile strength values obtained, and facilitated the migration of water vapor, causing an increase in the WVP [48], as previously shown in Table 1. SEM micrographs of the films' surface are presented in Figure 3. The pectin film presented a homogeneous, compact, and smooth surface, while the film with *S. ramosissima* presented a heterogeneous and rough surface. This result is related to the presence of salts (mainly sodium, magnesium, and potassium) from *S. ramosissima* powder that changed the structure of the pectin film. The possible presence of faults or microholes also contributed to the lower tensile strength values obtained, and facilitated the migration of water vapor, causing an increase in the WVP [48], as previously shown in Table 1. SEM micrographs of the films′ surface are presented in Figure 3. The pectin film presented a homogeneous, compact, and smooth surface, while the film with *S. ramosissima* presented a heterogeneous and rough surface. This result is related to the presence of salts (mainly sodium, magnesium, and potassium) from *S. ramosissima* powder that changed the structure of the pectin film. The possible presence of faults or microholes also contributed to the lower tensile strength values obtained, and facilitated the migration of water vapor, causing an increase in the WVP [48], as previously shown in Table 1.

**Figure 3.** SEM micrographs: (**a**) control film; (**b**) film with *S. ramosissima* (scale bar = 100 µm). **Figure 3.** SEM micrographs: (**a**) control film; (**b**) film with *S. ramosissima* (scale bar = 100 µm). **Figure 3.** SEM micrographs: (**a**) control film; (**b**) film with *S. ramosissima* (scale bar = 100 µm).

#### *3.4. Biodegradation Properties 3.4. Biodegradation Properties 3.4. Biodegradation Properties*

#### 3.4.1. Seawater 3.4.1. Seawater 3.4.1. Seawater

During the biodegradation test in seawater, both films underwent several changes (Figure 4). After the first day, the samples kept their initial appearance, and after this period the seawater in which they were submerged began to show signs of clouding for the film with *S. ramosissima*, while for the control film this change was not so evident. This result can be explained by the transfer of salts and pigments from the film with *S. ramosissima* to the seawater. During the biodegradation test in seawater, both films underwent several changes (Figure 4). After the first day, the samples kept their initial appearance, and after this period the seawater in which they were submerged began to show signs of clouding for the film with *S. ramosissima*, while for the control film this change was not so evident. This result can be explained by the transfer of salts and pigments from the film with *S. ramosissima* to the seawater. During the biodegradation test in seawater, both films underwent several changes (Figure 4). After the first day, the samples kept their initial appearance, and after this period the seawater in which they were submerged began to show signs of clouding for the film with *S. ramosissima*, while for the control film this change was not so evident. This result can be explained by the transfer of salts and pigments from the film with *S. ramosissima* to the seawater.

**Figure 4.** Biodegradation test in seawater. **Figure 4.** Biodegradation test in seawater.

On the 8th day, it was possible to verify that both films began to fragment into small pieces. In this period, the clouding of the water for the control film was also noticeable, possibly caused by the release of pectin. On the 16th day, greater changes were observed in the films′ structure, as they began to dissolve considerably in the seawater. This can be explained by the swelling of the film, as both the swelling and the solubility of the film can directly affect the water resistance properties of the films, particularly if it occurs in a On the 8th day, it was possible to verify that both films began to fragment into small pieces. In this period, the clouding of the water for the control film was also noticeable, possibly caused by the release of pectin. On the 16th day, greater changes were observed in the films' structure, as they began to dissolve considerably in the seawater. This can be explained by the swelling of the film, as both the swelling and the solubility of the film can directly affect the water resistance properties of the films, particularly if it occurs in a humid environment [31].

humid environment [31]. On the 22nd day, the seawater began to lose signs of clouding, especially for the film with *S. ramosissima*. After 30 days, it was found that both films were quite fragmented, presenting a "flaky" appearance, and completely losing their initial rectangular shape and, consequently, most of their initial structure. The rate of biodegradation of the film is related to different factors, including the swelling, the movement/agitation of the seawater, the presence of microorganisms in the seawater, the ratio volume of seawater/film, and the existence of oxygenation [27,49]. Data obtained by Alvarez-Zeferino et al. [49] corroborate those of this study by verifying low levels of biodegradation in the first days of testing and presenting a high rate of loss of physical integrity. Furthermore, Nakayama et al. [50] performed experiments to test the biodegradation of aliphatic polyesters in seawater; the authors concluded that, aside from microorganisms, several factors—such as On the 22nd day, the seawater began to lose signs of clouding, especially for the film with *S. ramosissima*. After 30 days, it was found that both films were quite fragmented, presenting a "flaky" appearance, and completely losing their initial rectangular shape and, consequently, most of their initial structure. The rate of biodegradation of the film is related to different factors, including the swelling, the movement/agitation of the seawater, the presence of microorganisms in the seawater, the ratio volume of seawater/film, and the existence of oxygenation [27,49]. Data obtained by Alvarez-Zeferino et al. [49] corroborate those of this study by verifying low levels of biodegradation in the first days of testing and presenting a high rate of loss of physical integrity. Furthermore, Nakayama et al. [50] performed experiments to test the biodegradation of aliphatic polyesters in seawater; the authors concluded that, aside from microorganisms, several factors—such as physicochemical effects from the sunlight, waves, and inorganic salts, among others—contribute to faster biodegradation in seawater.

#### physicochemical effects from the sunlight, waves, and inorganic salts, among others— 3.4.2. Soil

bility in water.

contribute to faster biodegradation in seawater. 3.4.2. Soil After 24 h in soil, there were no changes in the films′ structure, although the films After 24 h in soil, there were no changes in the films' structure, although the films showed signs of having some water absorption (Figure 5). After two days, the control film remained identical compared with day 0; however, the film with *S. ramosissima* absorbed water from the soil, and began to show some changes in its structure. This result is related to

showed signs of having some water absorption (Figure 5). After two days, the control film

water from the soil, and began to show some changes in its structure. This result is related to the fact that the film with *S. ramosissima*, as previously noted, presented a higher solu-

the fact that the film with *S. ramosissima*, as previously noted, presented a higher solubility in water. *Polymers* **2021**, *13*, x FOR PEER REVIEW 9 of 13

**Figure 5.** Biodegradation test in soil. **Figure 5.** Biodegradation test in soil.

After 14 days, there was a loss of more than 50% of the structure in both films, and after 21 days this loss was ~90%—the value indicated by the European Standard EN 13432 [51] for packaging to be considered biodegradable by biological action in a period of 6 months. This degradation is related, on the one hand, to the action of microorganisms existing in the soil. According to Shah et al. [52], the microorganisms responsible for biodegradation are bacteria and fungi; *Acidovorax facilis*, *Aspergillus fumigatus*, *Comamonas* sp., *Pseudomonas lemoignei*, and *Variovorax paradoxus* are among those normally found in soil. Our results are in agreement with the study reported by Jaramillo et al. [53], in which cassava starch films presented signs of biodegradation after 6 days. After 12 days, there was a greater change in the decomposition of films. On the other hand, the particular characteristics of the soil—such as the availability of phosphorus, which contributes to a higher load of fungi—are also responsible for the biodegradation phenomenon [54]. After 14 days, there was a loss of more than 50% of the structure in both films, and after 21 days this loss was ~90%—the value indicated by the European Standard EN 13432 [51] for packaging to be considered biodegradable by biological action in a period of 6 months. This degradation is related, on the one hand, to the action of microorganisms existing in the soil. According to Shah et al. [52], the microorganisms responsible for biodegradation are bacteria and fungi; *Acidovorax facilis*, *Aspergillus fumigatus*, *Comamonas* sp., *Pseudomonas lemoignei*, and *Variovorax paradoxus* are among those normally found in soil. Our results are in agreement with the study reported by Jaramillo et al. [53], in which cassava starch films presented signs of biodegradation after 6 days. After 12 days, there was a greater change in the decomposition of films. On the other hand, the particular characteristics of the soil—such as the availability of phosphorus, which contributes to a higher load of fungi—are also responsible for the biodegradation phenomenon [54].

The degradation mechanism can first result from a variety of physical and biological forces—such as heating/cooling, freezing/thawing, or wetting/drying—causing mechanical damage, such as the cracking of the polymeric materials. In our study, the presence of water contributed to the initial breakdown of the films. Then, during degradation, depolymerization occurs when the extracellular enzymes from the microorganisms break down the polymer, yielding short chains or smaller molecules—e.g., oligomers, dimers, and The degradation mechanism can first result from a variety of physical and biological forces—such as heating/cooling, freezing/thawing, or wetting/drying—causing mechanical damage, such as the cracking of the polymeric materials. In our study, the presence of water contributed to the initial breakdown of the films.  These short-chain molecules are then converted to biodegradation end-products, such as CO2, H2O, and biomass [52,55].

In general, biodegradation in both soil and seawater was practically obtained in a short period, with an average degradation rate of 4.3% and 3.3% per day in soil and seawater, respectively. Conversely, plastic or even paper packaging degradation is a very slow process, and it can take several years for those materials to be fully degraded, depending on the type of plastic or paper and the used conditions [56]. According to Chamas et al. [57], low-density polyethylene (LDPE) bags are estimated to decompose by 50% after 4.6 and 3.4 years, in inland (buried) and marine environments, respectively. In a study reported by Olaosebikan et al. [58], by the 10th–12th week of exposure in soil, brown newspapers started to degrade, and only pieces of the papers were found remaining, while plastic bags had thinned off and become transparent.

### **4. Conclusions**

The inclusion of *S. ramosissima* led to the development of opaque films with improved elongation at break (more flexible), but with less tensile strength (less rigid)—the latter being one of the films' limitations. Although the films presented a homogeneous appearance, the SEM analysis revealed a heterogeneous and rough surface across the film matrix. These modifications, as verified by FTIR analysis, could be credited to the interaction between functional groups of pectin and *S. ramosissima*. Generally, the properties are promising, and the presence of salts in the films may also contribute to a preservation effect, although further characterization and improvements of the antimicrobial and antioxidant properties are necessary to achieve the desired features. Finally, the biodegradation results demonstrated that pectin films with *S. ramosissima* can also be utilized as an eco-friendly food packaging material.

**Author Contributions:** Conceptualization, R.M.S.C.; validation, A.A.V. and R.M.S.C.; formal analysis, D.G.M.P., J.M.V., and R.M.S.C.; investigation, D.G.M.P., J.M.V., A.A.V., and R.M.S.C.; resources, A.A.V. and R.M.S.C.; writing—original draft preparation, D.G.M.P. and J.M.V.; writing—review and editing, A.A.V. and R.M.S.C.; supervision, R.M.S.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**

*Article*


**7. References**

Ikuta, K.; Hasegawa, M. & Goto, H. (2007). Total System of Hyper Finger for Remote Minimally Invasive Surgery (The 9th Report) Proposal and Experimental Verification of Safety Operation Strategies, *Proceedings of the 16th Annual Meeting of The Japan Society of Computer Aided Surgery*, pp. 43-44

**Chapter 1**

**Chapter 11**

**EMG Decomposition and Artefact Removal**

Traditionally, in clinical electromyography (EMG), neurophysiologists assess the state of the muscle by studying basic units of an EMG signal, which are referred to as motor unit action potentials (MUAPs). Information regarding the morphology and rate of occurrence of MUAPs is often used for diagnosis of neuromuscular disorders. In addition, recent studies have shown that the analysis of the energy content of MUAPs is a possible way for discriminating among normal, neurogenic, and myopathic MUAPs [38], illustrating, thus, the clinical value of the

A common way of obtaining such information is by observing MUAP activities on an oscilloscope and listening to their audio characteristics over the speakers. When doing this, the researcher is implicitly performing a time and frequency analysis of MUAPs. However, the results of this analysis are dependent on the experience of the investigator and on his ability to extract relevant information from the visual and auditory analysis. Furthermore,

The drawbacks related to the procedure described above have motivated the use of computer-based techniques for extraction of MUAPs from EMG signals [3, 19, 22, 27, 29, 32, 40]. Such methods, also known as EMG decomposition techniques, aim at classifying MUAPs generated by a common source into the same group. The results of this classification may provide information regarding the orchestration of the neuromuscular system, and therefore of the state of the muscle. A similar problem, often referred to as spike sorting, is found in the study of neuronal activities [25]. In this case, neuronal action potentials from the same source

Originally, the investigation of MUAP activities belonged to needle electromyographic (NEMG) studies, mainly because surface electrodes may easily produce an integration of many potentials, which precludes accurate study of their individual form. However, some recent studies have shown that the use of surface electrodes may be successfully applied for

> ©2012 Andrade et al., licensee InTech. This is an open access chapter 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

©2012 Andrade et al., licensee InTech. This is a paper 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.

Adriano O. Andrade, Alcimar B. Soares, Slawomir J. Nasuto and Peter J. Kyberd

http://dx.doi.org/10.5772/50819

interpretation of MUAP information.

are classified into a common group.

this procedure is time-consuming and prone to error.

cited.

**1. Introduction**

Additional information is available at the end of the chapter


*3.4. Moving Mesh*

The adaptive lens working mechanism relies on the transfer of piezoelectric forces to the flexible membrane through the fluid forces. In COMSOL Multiphysics-R , the coupling of the piezoelectric effect and the fluid-structure interaction is not possible through a direct Multiphysics feature. Hence, the moving mesh physics module is used to couple the piezoelectric forces with the fluid forces and apply the resultant on the flexible membrane. The explicit coupling of piezoelectric and laminar flow physics is performed in a way such that the solid domain velocities Equations (8) and (9) generated by the deformation of the piezoelectric actuator are applied as the mesh velocities on the walls of the fluid chamber as shown in Figure 4c. The geometric domains with the free deformation mesh and with the fixed mesh are as shown in Figure 4a,b, respectively.

$$V\_I = solid \cdot u\_\text{\\_tR} \tag{8}$$

$$V\_z = \text{solid} \cdot \text{u\\_tZ} \tag{9}$$

Equations (8) and (9) equate the solid velocities *u*\_*tR* and *u*\_*tZ*, which are produced by the piezoelectric actuator in radial axis (R) and deformation axis (Z), to the corresponding mesh velocities *Vr* and *Vz*. The mesh velocities applied to the fluid chamber wall are implicitly considered to be the external forces in the Navier–Stokes Equation (5) of the fluid-structure interaction physics module Equation (4). In this way, the moving mesh module explicitly couples the piezoelectric actuator force to the fluid force.

**Figure 4.** The domains specified in the Moving Mesh module to be (**a**) free mesh and (**b**) fixed mesh. (**c**) The solid domain velocity applied on the walls of the fluid chamber.


**4. Conclusion**

more invasive samples such as lymph node aspirates [136]. Ferreira *et al*. (2012) used cPCR followed by kDNA-probe hybridization of blood samples, skin, marrow and conjunctival swabs. The use of swabs gave the best results for detection of infection in both symptomatic and asymptomatic dogs, showing to be a suitable sample for the molecular diagnosis of CVL. Furthermore, Di Muccio et al (2012) argue that the use of nested PCR from conjunctival swabs shown to be the least invasive procedure with the best performance for the diagnosis of CVL

Among other less invasive sample types investigated, Solano-Gallego et al (2007) evaluated urine samples with qPCR technique, but the results described showed positivity only in dogs with severe renal injury [160]. Naranjo et al. (2012) identified the presence of *Leishmania* sp. DNA in lacrimal glands of infected dogs using qPCR, with positive correlation between positivity and the presence of ocular lesions [161]. Recently, Belinchon-Lorenzo (2013), using qPCR, demonstrated the presence of *Leishmania* kDNA in the hair and keratinocytes of infected animals. According to the authors, the use of the non-invasive hair sample for the diagnosis of CVL would be advantageous because it is easy to collect, handle, transport, and store [135]. However, further studies should be conducted to determine the sensitivity of this method.

> Elleviti – Torino, Italy 26.80\* --- 63.00\* --- Scanelis - Toulouse, France --- --- 60.30\* ---

Toulouse, France --- --- --- 127.30\*

Laboratório Veterinário INNO – Braga, Portugal 20.60\* 54.40\* --- ---

Cornell University - Ithaca NY, USA 22.50 60.00 --- --- Hermes Pardini - Belo Horizonte MG, Brazil 17.20\* 60.20\* --- --- Análisis Biológicos– Chapecó SC, Brazil 9.40\* 42.15\* 72.25\* -- Laborlife - Rio de Janeiro RJ, Brazil 30.10\* 77.40\* --- ---

Centro de Investigación y Análisis Biológicos – Madrid, Spain 13.60\* 60.30\* 73.70\* ---

\*Prices in Euros (€) and Brazilian Real (R\$) converted in US dollars (U\$), quotation of November 14th of 2013. €1 = aprox.

**Table 3.** Cost of the main diagnostic test for CVL in different laboratories consulted in the second semester of 2013 in

**Tests Price Serology cPCR qPCR qPCR and**

28.00\* 41.20\* --- ---

19.20 --- --- ---

**Citology**

in asymptomatic animals [156].

258 Leishmaniasis - Trends in Epidemiology, Diagnosis and Treatment

**Laboratory – Country**

Laboratoire d'Anatomie Pathologique Vétérinaire du Sud-Ouest –

Instituto Nacional de Investigação Agrária e Veterinária, I.P. – Lisbõa, Portugal

Texas Veterinary Medical Diagnostic Laboratory – San Antonio TX, USA

U\$ 1.34 - €1 = aprox.R\$ 0.43

U\$

In summary, detailed clinical evaluation complemented with highly sensitive test allows proper identification of infected dogs in an endemic area. Evidence shows that the use of a rapid serological test associated with a molecular diagnostic test with high specificity, such as qPCR, is required for identification of all infected dogs, both asymptomatic and symptomatic. On the other hand, for sick dogs a correct diagnosis is necessary either to perform dog culling in countries where this measure is used as a control strategy of VL or to define treatment. In this case, a detailed clinical evaluation should be associated with biochemistry and hemato‐ logical tests to identify signs of renal and hepatic failure, in conjunction with a serological test to confirm animal clinical condition.


*2.2.1. Study site, sample size, and sampling technique*

Dida Hara PA in Yabello and Alona PA in Arero of CCAFS learning site were purposefully selected for the study. For questionnaire survey 200 herders were selected using simple random sampling technique. A total of four focus group discussions (FDG) having 12 participants in each session were organized. Eight indigenous astrologists, eight indigenous intestinal readers, four veterinarians, four botanists, and two astrologists were also interviewed.

#### *2.2.2. Sources and data collection methods*

In this research flexible and eclectic research approaches which combine participatory rural appraisal (PRA) (as a tool in overt observation, FGD), key informant interview and survey questionnaire were used to collect data from different stakeholders. Overt observation and diagnostic approach were used as a complementary approach to understand how technical skills of indicators sign interpretation. Data was also gathered through in-depth interviews and questionnaire. The quantitative method deals mainly with herders' socioeconomic preparations following the forecast and perceptions on the status of the Borana weather forecast. Metrological data was also collected at National Meteorological Agency.

#### *2.2.3. Data analysis technique*

For the qualitative data which was collected using observation, interview, and focus group discussions, thematic content analysis was applied. Paraphrasing, identification, and characterization of the recurring themes were carried out in the analytical procedure. The household survey was analyzed using simple descriptive technique, i.e., percentage. Drought assessment method which was developed by [21] was adopted to identify drought and normal years within the last 27 years.


*Article* **Cognitive Biases in Critical Decisions Facing SME Entrepreneurs: An External Accountants' Perspective**

### **Arno Nuijten 1,2,\*, Nick Benschop 1, Antoinette Rijsenbilt 1 and Kristinka Wilmink 1**

Received: 18 September 2020; Accepted: 1 November 2020; Published: 5 November 2020

**Abstract:** Decisions by small and medium enterprise (SME) entrepreneurs are plagued by a variety of cognitive biases. Extant literature has mainly focused on a limited number of important biases (e.g., overconfidence) in a handful of important entrepreneurial decisions (e.g., start-up, market entry or exit). However, putting the spotlight on a few important biases and entrepreneurial decisions could leave other important biases and decisions underexposed. SME accountants are in a unique position to shed a broader light on this issue. SME entrepreneurs often seek advice of their accountants when they struggle with decisions that involve uncertainty and business risks in the domains of strategy, regulatory compliance, human resources, IT, and succession. In this study, we explore 12 different biases and analyze whether their importance can change across these decision domains. Interviews were performed with 14 SME accountants who provide an independent third-party view on decision making by over 3000 entrepreneurs. Our findings suggest that the importance of most of these biases varies from one decision domain to the other. We also identified four approaches (warn, inform, intervene, and coach) that accountants can take when entrepreneurs may fall victim to biases. We discuss the implications for research and practice of SME entrepreneurs and their accountants.

**Keywords:** SME entrepreneurs; accountants; cognitive biases; decision making; debiasing


*Perspective Chapter: Functional Human Brain Connectome in Deep Brain Stimulation (DBS)… DOI: http://dx.doi.org/10.5772/intechopen.109855*

tool for brain sensing in PD patients with DBS implanted at STN, thereby facilitating DBS programming and medication titration. Increased beta activities were observed in the hypodopaminergic state when the patients suffer from bradykinesia and rigidity and could be suppressed by DBS and dopaminergic medications. On the other hand, increased gamma activities were seen in times of dyskinesia [65–69]. However, in patients with connectivity-based stimulation, will the electrophysiological data correlate with the connectivity profile? Accolla et al. described that beta oscillations were detected in the cerebral circuit projecting from the STN to the motor and premotor cortical areas in PD patients [70]. Besides, Hirschmann et al. reported that with the use of magnetoencephalography (MEG), local field potential (LFP) and electromyogram (EMG), elevated beta coherence was found between M1 and STN in PD patients, which could be suppressed with administration of levodopa [71]. These findings suggested a link between electrophysiology data and connectivity-based stimulation.

As such, connectomic DBS seems to be a reasonable and effective therapeutic option for advanced PD patients. Growing evidence has showed that depending on the symptoms, connectomic DBS can act on different circuits in the brain. In this way, the neuromodulation surgery can affect both motor and non-motor functions (**Table 2**) [23, 45, 61, 72–79].

**Table 2.**

*Clinical effects of connectomic DBS in PD.*


**Transcriptome Analysis of** *Sogatella furcifera* **(Homoptera: Delphacidae) in Response to Sulfoxaflor and Functional Verification of Resistance-Related P450 Genes**

**Xue-Gui Wang 1,\*,**†**, Yan-Wei Ruan 1,**†**, Chang-Wei Gong 1,**†**, Xin Xiang 1, Xiang Xu 2, Yu-Ming Zhang 1 and Li-Tao Shen 1**

Received: 18 August 2019; Accepted: 12 September 2019; Published: 15 September 2019

**Abstract:** The white-back planthopper (WBPH), *Sogatella furcifera*, is a major rice pest in China and in some other rice-growing countries of Asia. The extensive use of pesticides has resulted in severe resistance of *S. furcifera* to variety of chemical insecticides. Sulfoxaflor is a new diamide insecticide that acts on nicotinic acetylcholine receptors (nAChRs) in insects. The aim of this study was to explore the key genes related to the development of resistance to sulfoxaflor in *S. furcifera* and to verify their functions. Transcriptomes were compared between white-back planthoppers from a susceptible laboratory strain (Sus-Lab) and Sus-Lab screened with the sublethal LC25 dose of sulfoxaflor for six generations (SF-Sel). Two P450 genes (*CYP6FD1* and *CYP4FD2*) and three transcription factors (*NlE78sf*, *C2H2ZF1* and *C2H2ZF3*) with upregulated expression verified by qRT-PCR were detected in the Sus-Lab and SF-Sel strains. The functions of *CYP6FD1* and *CYP4FD2* were analyzed by RNA interference, and the relative normalized expressions of *CYP6FD1* and *CYP4FD2* in the SF-Sel population were lower than under dsGFP treatment after dsRNA injection. Moreover, the mortality rates of SF-Sel population treated with the LC50 concentration of sulfoxaflor after the injecting of dsRNA targeting *CYP6FD1* and *CYP4FD2* were significantly higher than in the dsGFP group from 72 h to 96 h (*p* < 0.05), and mortality in the *CYP6FD1* knockdown group was clearly higher than that of the *CYP4FD2* knockdown group. The interaction between the tertiary structures of *CYP6FD1* and *CYP4FD2* and sulfoxaflor was also predicted, and *CYP6FD1* showed a stronger metabolic ability to process sulfoxaflor. Therefore, overexpression of *CYP6FD1* and *CYP4FD2* may be one of the primary factors in the development of sulfoxaflor resistance in *S. furcifera*.

**Keywords:** *Sogatella furcifera*; sulfoxaflor; transcriptome; cytochrome P450 monooxygenase; RNA interference


**E**ff**ects of Dietary Chicory (***Chicorium intybus* **L.) and Probiotic Blend as Natural Feed Additives on Performance Traits, Blood Biochemistry, and Gut Microbiota of Broiler Chickens**

**Mohammadreza Khoobani 1, Seyyed-Hamed Hasheminezhad 1, Faramin Javandel 1, Mehran Nosrati 1, Alireza Seidavi 1,\*, Isam T. Kadim 2, Vito Laudadio 3 and Vincenzo Tufarelli 3,\***

Received: 28 November 2019; Accepted: 19 December 2019; Published: 20 December 2019

**Abstract:** The experiment was designed to determine the effect of different levels of chicory (*Chicorium intybus* L.) powder and a probiotic blend (PrimaLac®) on productive performance, blood biochemical parameters, and ileal microbiota in broiler chickens. A total of 225 one-day-old broilers (Ross 308) were used in a completely randomized design with five experimental diets as follows: 1—basal-diet without supplements (control-group); 2—basal-diet including probiotic blend; 3 basal-diet including 0.10% chicory; 4—basal-diet including 0.15% chicory; 5—basal-diet including 0.20% chicory. At 42 days of age, representative birds per replicate were randomly selected for blood samples and carcass measurements. Results showed that the body weight gain of broilers fed the probiotic blend or 0.10% chicory was significantly (*P* < 0.05) higher than those fed on the other treatments. The abdominal fat pad was significantly (*P* < 0.05) lower in birds fed diets including chicory compared with control or probiotic. Blood triglycerides and LDL levels were reduced (*P* < 0.05) and HDL increased (*P* < 0.05) when fed probiotic or chicory whereas no significant effect on the other serum parameters was found. Broiler ileal microflora from the control group had significantly (*P* < 0.05) higher count of *E. coli* and lower *Lactobacillus* than those from the other groups. From findings, it is possible to conclude that dietary chicory powder supported positively growth performance and improved gut microbiota in broiler chickens. However, more research is needed on this subject to better understand the mode of action of feed additives used.

**Keywords:** feed additive; growth promoter; medicinal plant; broiler

#### **1. Introduction**

Antibiotics are usually used in poultry for therapeutic, preventive, and nutritional purposes [1–3]. Using antibiotics for the growth promotion or prevention and treatment of infectious diseases can result in resistance among both resident bacterial pathogens and commensal organisms [4,5]. Therefore, there is increasing interest in using medicinal plants or probiotics and as natural alternatives to antibiotics for poultry production because they have the potential of inhibition against organisms improving animal performance [6–11].

Probiotics as live microorganisms can also improve the intestinal balance of the host livestock [12]. The mechanism of action of probiotics is mainly related to the competition for attachment sites of the intestinal mucosa, to prevent the pathogenic bacteria attachment by forming a physical obstacle [13], and also to stimulate epithelial and immune cells activities; therefore, supplementing diet with natural additives can improve poultry production.

Chicory (*Cicorium intybus* L.) is an important medicinally perennial herb plant of the *Asteraceae* family [14], containing valuable levels of fructooligosaccharides, inulin, coumarins, flavonoids, and many vitamins [15,16]. Chicory was used as an anti-hepatotoxic, antiulcerogenic, anti-inflammatory, digestive, diuretic, depurative, alexiteric, and tonic agent [17]. In particular, inulin is one of the beneficial components in chicory that can regulate appetite and lipid-to-glucose metabolism [18]. It has also been shown that chicory can promote the growth of useful microbes [19] and inhibit gut pathogenic bacteria growth [20]. Thus, chicory could be supplemented to poultry diets to manipulate the gut microflora composition and to enhance its integrity [20], improving also broiler performance and health status by modulating lipid metabolism with hypolipidemic effects [21–23].

Therefore, the aim of this study was to evaluate the effects of chicory powder and a commercial probiotic blend as natural feed additives on the productive performance, blood biochemical parameters, and ileal microflora of broiler chickens.

#### **2. Results and Discussion**

#### *2.1. Growth Performance*

Feed intake, body weight gain, and feed conversion ratio of broilers during the experimental period are summarized in Table 1, Table 2, and Table 3, respectively. No significant (*P* > 0.05) differences due to dietary treatment effects were observed on feed intake in the first and second growing periods, however, birds receiving diet supplemented with 0.10% chicory powder during the whole period of the experiment (1–42 days) had a higher (*P* < 0.05) feed intake than those receiving the basal or basal-diet supplemented with probiotics or 0.15–0.20% chicory. Similar results were reported by Faramarzzadeh et al. [24], who supplemented the broiler diet with 4.5% chicory powder. Live body weight gain of chickens was significantly affected by supplementing 0.10% chicory powder or probiotic blend during all rearing periods (*P* < 0.05).

**Table 1.** Feed intake (g) in broilers fed experimental diets.

Means within each column with different superscript differ significantly at *P* < 0.05; DOA: days of age.

Means within each column with different superscript differ significantly at *P* < 0.05; DOA: days of age.

**Table 3.** Feed conversion ratio (g/g) in broilers fed experimental diets.

Means within each column with different superscript differ significantly at *P* < 0.05; DOA: days of age.

Overall, the current study revealed that birds receiving diet supplemented with a probiotic blend or different levels of chicory powder during the experimental period improved significantly (*P* < 0.05) their feed conversion ratio than the other treatments. In line with the current findings, it was found that chickens fed diet supplemented with chicory powder had significantly lower feed efficiency compared to the unsupplemented group [24]. Similarly, Cabuk et al. [25] observed significant improvement in feed conversion ratio in broilers fed diet supplemented with herbal plant mixture. Further, Liu et al. [26] also reported that adding a basal diet with chicory powder significantly improved the feed conversion ratio for the first 13 days of the feeding period, which agrees with the present study. Improvement in broiler growth performance fed diet supplemented with chicory powder can be attributed to the enhancements of length, number, and surface area of intestinal villi that are paralleled with an increased digestive and absorptive capacity of jejunum [27,28]. Moreover, broiler chickens at a younger age will get more benefits than older ages by adding chicory powder to diets due to villi growth stimulation [26].

#### *2.2. Carcass Traits*

The effects of treatments on the relative weight of broiler carcass and non-carcass components are reported in Table 4. Apart from abdominal fat, there were no significant differences in carcass traits among dietary treatments. In particular, the abdominal fat percentage was significantly (*P* < 0.05) lower in broilers fed diet supplemented with three different levels of chicory powder than control and probiotic blend groups.

**Table 4.** Carcass characteristics (%) in broilers fed different experimental diets.

Means within each column with different superscript differ significantly at *P* < 0.05.

Accordingly, Pournazari et al. [10] found no effect of probiotics on carcass characteristics of broiler chickens. Furthermore, Aminzade et al. [29], Norbakht [30], Ocak et al. [31], and Mansoub [32] reported similar findings. In contrast, Panda et al. [33] and Faramarzzadeh et al. [24] found significant improvement in dressing percentage by supplementing chicory powder (3.0%) to broiler diet. The current results are also in agreement with Yusrizal and Chen [21] who found that broiler chickens fed diets supplemented with chicory fructans (1%) were heavier compared to controls.  Moreover, a positive relationship was found between adding chicory supplementation and carcass characteristics in poultry species [35–37]. The effect of adding chicory powder or probiotic blend to broiler diet may be due to an overall improvement of the intestinal microenvironment and to a reduction of endogenous nitrogen loss, leading to lower abdominal fat deposition in broiler chickens [21,33].

#### *2.3. Blood Parameters*

Table 5 summarized the effect of experimental diets on biochemical serum parameters of broilers at 42 days of age. Apart from serum triglycerides, LDL and HDL, dietary treatments did not induce any significant effect. Blood serum of broiler chicken fed control diet had significantly (*P* < 0.05) higher triglycerides and HDL concentrations than those fed chicory powder, whereas LDL level was lower by feeding experimental supplemented diets. The current findings are in agreement with those of Faramarzzadeh et al. [24], Yusrizal and Chen [21], Safamehr et al. [34] and Agazadehh et al. [38] who found that adding chicory-based fructans to broiler diet decreased also the serum total cholesterol, in addition to triglycerides and LDL in broilers.

**Table 5.** Blood biochemical constitutes (mg/dl) in broilers fed experimental diets.

Means within each column with different superscript differ significantly at *P* < 0.05.

#### *2.4. Ileal Microflora*

Data showed that adding probiotic blend and chicory powder to broiler diet had an antibacterial effect against *E. coli* while increasing *Lactobacillus* bacteria count (Table 6). The three supplementation levels of chicory powder and probiotic blend showed pronounced inhibition against *E. coli*.

**Table 6.** Ileal microflora (log CFU/g) in broilers fed experimental diets.

Means within each column with different superscripts differ significantly at *P* < 0.05.

In a previous study, Farrukh et al. [39] stated that chicory powder was effective against pathogenic bacteria, which in agreement with the present study. Furthermore, the antibacterial activity of chicory, and other herbal plants, was reported to counteract the growth of harmful bacteria [17,29]. The current study confirmed that chicory can be used as a natural antibacterial feed supplement, which may be due to the presence of inulin, bitter sesquiterpene lactones, coumarins, and other compounds. It has been

also reported that herbs and plant extracts stimulate the growth of beneficial bacteria and minimize pathogenic bacteria activity in the poultry gut [40,41].

The antibacterial activity of chicory mainly depended on strains and it is dose-dependent. The present study also showed that the feed additives used contributed to reducing the growth of pathogenic bacteria such as *E. coli*, and increased the beneficial bacteria, such as lactobacilli, and similar conclusions were reported by Jain et al. [42], Ocak et al. [31], and Nobakht et al. [30]. In this respect, Lee et al. [43] reported that the presence of pathogenic bacteria population in the gut may cause the breakdown of amino acids, and thereby reduce their availability for absorption. Herbs, such as chicory, might have the ability to stimulate the production of secretions in the small intestinal mucosa, pancreas, and liver to enhance nutrients digestion and increase their availability at the intestinal brush border [34,44]. It has been also demonstrated that the main beneficial effect of probiotic blend or chicory is to induce changes in the intestinal microbiota by selective stimulation of health-promoting bacteria [45–47].

#### **3. Materials and Methods**

#### *3.1. Birds and Management*

All procedures used in this study were approved by the Animal Ethics Committee of the Islamic Azad University, Rasht Branch, Iran, in agreement with the Directive 2010/63/EU. A total of 225 one-day-old broiler chicks (Ross 308) with similar initial body weight were randomly divided into 15 experiment units of 15 birds, each with three replicates per treatment for a total of five experimental diets. The experiment was conducted at a commercial poultry farm (Khomam city, Guilan, Iran). The broilers were kept in floor pens (1.0 × 1.5 × 0.5 m) and treatment groups were equally distributed among pens. Temperature and relative humidity were maintained within the optimum range. The lighting program was 23 h light and 1 h darkness. Each pen was equipped with an individual feeder and a nipple drinker. Broilers in a pen were not able to consume feed assigned to the adjoining pen. All experiments were carried out from day 1 to day 42 of age. Birds were vaccinated against infectious bronchitis (1 and 18 days of age), Newcastle disease (1 and 18 days of age), avian influenza (1 day of age), and Gumboro disease (14 and 24 days of age).

#### *3.2. Feed Formulation*

A two-phase feeding program was used; a starter diet was used from 1–21 days and a finisher diet from 22–42 days. The ingredients and nutrient composition of diets are shown in Table 7. Feed and water were supplied ad libitum throughout the experimental period. Diets were formulated to meet or exceed the National Research Council (NRC) nutrient requirements for broiler chickens. Two types of natural feed supplements were used: a multi-strain probiotic (PrimaLac®, Star-Labs/Forage Research Inc. Clarksdale, USA) as a lyophilized mixture containing 1 × 108 CFU/g of *Lactobacillus casei*, *Lactobacillus acidophilus*, *Bifidobacterium thermophilum*, and *Enterococcus faecium* (the microbial blends and concentrations are proprietary); chicory powder purchased from a local producer (Rasht, Iran). The following dietary treatments were formulated: Treatment 1—basal-diet with no supplementation as control; Treatment 2—basal-diet supplemented with probiotic blend [following manufacturer's instructions level: 0.900 g/kg (0.09%) from 1–14 days, 0.454 g/kg (0.0454%) from 15–28 days, 0.225 g/kg (0.0225%) from 29–42 days]; Treatment 3—basal-diet supplemented with chicory powder at 0.10%; Treatment 4—basal-diet supplemented with chicory powder at 0.15%; Treatment 5—basal-diet supplemented with chicory powder 0.20%.

**Table 7.** Ingredients and chemical composition of the basal diet.

1 Supplied per kg of mixture: 3,600,000 IU vitamin A; 800,000 IU vitamin D3; 7200 IU vitamin E; 710 mg vitamin B1; 2640 mg vitamin B2; 1176 mg vitamin B6; 400 mg vitamin B9; 6 mg vitamin B12; 800 mg vitamin K3; 3920 mg pantothenate acid; 12,000 mg niacin; 40 mg biotin; 200,000 mg choline chloride. 2 Supplied per kg of mixture: 40,000 mg manganese; 20,000 mg iron; 33,900 mg zinc; 4000 mg copper; 400 mg iodine; 80 mg selenium.

#### *3.3. Growth and Carcass Measurements*

Mortality rate and growth performance, as feed intake, feed conversion ratio, and body weight gain, were recorded per pen at 21 and 42 days of age. After 12 h of fasting, five birds per treatment were randomly selected for carcass characteristics measurements at 42 days of age. Birds were sacrificed, plucked, and eviscerated, then the weight of the whole carcass, carcass components (drumsticks and breast), liver, gizzard, and abdominal fat were excised and individually weighed. Carcass traits components were calculated as a percentage of the preslaughter live body weight.

#### *3.4. Serum Biochemical Analysis*

At the end of the trial (42 days), ten broilers per group (30 birds/treatment) were selected for blood sampling. Blood samples were collected from the wing veins and centrifuged at 3000 *g* × 10 min to obtain serum. Samples were stored at −20 ◦C until analyzed for total protein, albumin, glucose, total cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and uric acid, using commercial laboratory kits (TeifAzmoon Pars Co, Tehran, Iran).

#### *3.5. Ileal Microflora*

For the ileal microbial count, at 42 days of age, 30 birds (two birds from each replicate) were randomly selected and killed by cervical dislocation. One gram of ileum content was sampled and transferred into sterile tubes containing 9 ml of sterile PBS and homogenized and serially diluted. A small sample (0.1 ml) from each dilution was inoculated on MRS agar (Man Rogosa Sharpe agar, Merck, 1.10660.500) was used to culture *Lactobacilli*, and Eosin Metilan-Blue (EMB, Merck, 1.01347.0500) was used for *E. coli,* then incubated under anaerobic conditions at 37 ◦C for 72 h. Bacterial units were counted by a colony counter and adjusted to 1 g sample. The bacteria counts were reported as log10 CFU/g of ileal digesta.

#### *3.6. Statistical Analysis*

The experiment was carried out in a complete randomized design with dietary feed additives as the main effects. The model assumptions of normality and homogeneity of variance were tested using Shapiro–Wilk's and Levene's tests, respectively. Data were subjected to analysis of variance (ANOVA) according to the General Linear Model (GLM) procedure of SAS/STAT (SAS software version 8, Institute Inc., Cary, NC, USA). The statistical model used was: Yijk = μ + Ti + Rij + Eijk, where: Yijk = response variables from each individual replication or pen; μ = the overall mean; Ti = the effect of dietary additive; Rij = the inter-experimental unit (replications) error term; Eijk = the intra-experimental unit error term. Means were compared for significant differences using the LSMEANS option of SAS/STAT (SAS software version 8, Institute Inc., Cary, NC, USA). Statistical significance was established at *P* < 0.05.

#### **4. Conclusions**

Chicory powder and probiotic blend as natural feed supplements in broiler diet supported positively the growth and feed efficiency of birds, without affecting most of the blood biochemical parameters. Moreover, it is important to underline that probiotics and chicory supplementation showed a significant effect in inhibiting the growth of potentially pathogenic *E. coli*, and in enhancing the growth of beneficial *Lactobacillus* gut bacteria. Thus, this study demonstrated that natural feed additives can be successfully used as an alternative to antibiotics as growth promoters for broiler chickens.

**Author Contributions:** Conceptualization, M.K., S.-H.H. and A.S.; methodology, F.J. and M.N.; validation, M.K., S.-H.H. and A.S.; formal analysis, M.K. and M.N.; investigation, M.K., S.-H.H. and A.S.; data curation, A.S., I.T.K. and V.T.; writing—review and editing, V.L., A.S. and V.T. All authors have read and agreed to the published version of the manuscript.

**Funding:** Financial support by Rasht Branch, Islamic Azad University, grant number <IP_ADDRESS>74 is gratefully acknowledged.

**Acknowledgments:** The authors would like to thank the support of technicians of the Institutions.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*