**1. Introduction**

The IoT and WSNs are becoming viable solutions that are widely utilized in real-time data collection and monitoring applications, which include automated irrigation, target monitoring, observing clinical records, tracking landslides and predictions for forest fire and disaster management. A WSN consists of numerous effective sensor nodes (SNs) that monitor climatic disasters found in harsh or remote areas. Furthermore, the SNs examine the atmospheric factors such as pressure, temperature, humidity, sound and moisture content representing intense symptoms. After an SN completes its sensing operation, the

**Citation:** Nagaraju, R.; C, V.; J, K.; G, M.; Goyal, S.B.; Verma, C.; Safirescu, C.O.; Mihaltan, T.C. Secure Routing-Based Energy Optimization for IoT Application with Heterogeneous Wireless Sensor Networks. *Energies* **2022**, *15*, 4777. https://doi.org/ 10.3390/en15134777

Academic Editor: Jose A. Afonso

Received: 29 May 2022 Accepted: 27 June 2022 Published: 29 June 2022

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

**Copyright:** © 2022 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/).

information is gathered and transmitted to the base station (BS). The sensor and data communication units of SNs consume more energy and once the entire energy is exhausted, it expires or is unable to process [1]. Hence, a node that is considered dead is unsuitable for either replacing with or recharging using an alternate power source. Hence, balancing the power utilization of a SN is more essential. To overcome these challenges, several developers have used clustering approaches [2], which can scale up the network lifetime and provide remarkable efficiency. Furthermore, it is supportive in maintaining power as numerous reliable clusters are formed. These clusters, based on the techniques used, can either be considered temporary or permanent. Moreover, clustering distributes the nodes that are placed jointly, which is accomplished based on similarity metrics such as the distance from the base station (BS), radius of transmission and density of the cluster. After the clusters are formed, a node from the cluster is chosen as the cluster head (CH) whose responsibility is to organize the data gathered from cluster members (CM) and transmit those data to the BS. When a single node cluster is considered, it mandatorily communicates with the sink rather than the BS, which finally results in a reduction in power utilization. In WSNs, the serious threats, along with the technical challenges, which arise due to the nature of resource constraints and its limited availability [3], have to be focused on to ensure revision and distribution. With WSNs in an open area, the sensors are more vulnerable to the unfriendly environment that arises due to humidity, increased temperature, pressure, snow, rain, dust and so on. These affect the functions of the wireless sensor network, and hence a demand arises to introduce robust and flexible SNs. Moreover, general and future challenges are constrained to the limited resources, the limited ability of communication, fault tolerance, stability, mobility, bandwidth, precision, reliability, availability, heterogeneity, accountability, uncontrollable setup and denial of service (DoS). Above all, some specific challenges have turned the attention of the researchers towards the utilization of power, network duration, throughput, security and routing protocols. In WSNs, during communication, energy consumption is a highly prominent issue that seeks attention. Energy efficiency has a greater impact on the entire performance of the network and acts as a significant function in the lifespan of a WSN [4]. The metrics that are essential while routing and estimating the cost function (CF) in a WSN are total energy, energy consumed and residual energy. Energy is one of the most significant aspects of the efficient working of wireless sensor networks. The longevity of the network is totally dependent upon the optimum use of the available energy; therefore, optimization is much needed for the efficient utilization of energy. Routing protocol, considered as an important factor, has to be selected carefully to route the data packets safely to the destination with less overhead because of the resource constraints of SNs, namely, their limited power and shorter range for communication. Numerous efforts have been made to bring out the best solutions for WSNs, yet extraordinary works are required [5]. The benefits of the IoT are as follows. An urban IoT has many facilities that may bring a number of benefits such as the management and optimization of traditional public services, including transport and parking facilities, lighting, the surveillance and maintenance of public areas, preservation of cultural heritage, garbage collection, public health care, i.e., hospitals, and schools. Therefore, the availability of different types of data that will store in the cloud or be collected by a data warehouse in the urban IoT should increase the transparency and promote the actions of the local government or municipality towards the citizens, which can increase the awareness of people about the status of their city and their life style. Therefore, the application of the IoT paradigm to the smart city is attractive and expansive for local government and administrations; however, it take times to adopt IoT technology in a wide manner.

This research is organized as follows: A detailed review of the literature related to this research is described in Section 2. The design, algorithms and functionality of the proposed protocol are elaborated on in Section 3. The simulation results of the proposed protocol are presented in Section 4, which is followed by the conclusion in Section 5.

#### **2. Related Works**

Mostly, in large scale networks such as the IoT and SNs with restricted constraints, the demanding factor is energy conservation. Generally, in networks based on clusters [6], the controlling entity is CH, whose significant role is to gather data and transmit them. Furthermore, in large scale WSNs integrated with the IoT, the crucial part is to route data securely as they involve constrained resources. Several existing approaches do not provide reliable and secure data routing in the network as they lack protection schema against threats [7]. A low-energy adaptive clustering hierarchy (LEACH) protocol consists of multi-stages [8]. The LEACH protocol's performance was improved by applying a multi-hop basis for transmitting information [9]. The design elucidated the unstable consumption of energy as the clusters were randomly created. Moreover, the multi-hop paths created were not optimized, which resulted in route breaks. In a chain–chain-based routing protocol (CCBRP) [10], the principles of LEACH as well as Power-Efficient Gathering in Sensor Information Systems (PEGASIS) were integrated, which resulted in scalable energy conservation in SNs while forwarding data. This hybrid CCBRP protocol, which was executed in two stages, reflected the drawback of a higher energy consumption in the nodes and the production of high latency. Subsequently, as the scalability is restricted, CCBRP was not suitable for larger networks. Kumar et al., proposed a data collection as well as a load balancing scheme that was designed to save energy. The network performance was improved in this scheme as the aggregating data were sequenced by data forwarding [11]. A vigorous authentication protocol for energy efficiency was developed for an industrial IoT-based WSN, which provided scalable data security. In this method, mutual authentication was followed between nodes, but the energy was consumed gratuitously, thereby compromising the network lifetime [12]. Likewise, the Shamir secret sharing method comprised two phases, namely, share generation as well as reconstruction. The generated secret was distributed among nodes and the secret key was reconstructed by the usage of any nodes of the subset. The data transmission using this method consumed additional energy leading to routing overheads [13]. If the flow entry exists, the forwarding is performed according to the flow table, and if not, the packet-in message is sent to the subset. After receiving the packet-in message, the subset will make a decision. An improved three-layer hybrid clustering method (ETL-HCM) analysed and limited the control traffic specifically while selecting CH. This method achieved an 18% improvement in the lifetime of the network as well as half of the nodes being alive compared with the hybrid hierarchical clustering approach (HHCA). However, this method was not suitable for selecting the grid head (GH) [14]. To beat hateful attacks such as Sybil, wormholes and a black hole, a novel protocol was introduced by Haseeb et al. to ensure reliable routing and data transmission [15]. The functioning of a combined GIN with GEAR protocol resulted in being too complicated to achieve data security [16]. A voting-based hybrid ensemble classification method was introduced for predicting the availability of parking lots, wherein 96% of the accuracy and 89% of the availability rate was achieved [17]. An optimal network coding backpressure routing (NCBPR) method was developed for a large-scale IoT to divert the flow of data packets from highly congested nodes to low ones, thereby balancing the load and optimizing the battery power [18]. The nodes in the network were formed as clusters and the CHs were selected based on the battery power. Moreover, an efficient data aggregation model was involved to improve the network throughput, wherein the redundant data packets were eliminated. An efficient load balancing optimization algorithm for the employment of energy effectual routing as well as a load balancing protocol were used to enhance the network lifetime [19,20]. The authors in [21] explored the cluster-based backpressure routing algorithm for IoTs, which discusses the energy and congestion issues in IoT environment. A brief discussion is also presented related to the sustainable development through the Internet of Things in [22,23].

A novel framework was proposed to handle environmental monitoring using wireless sensors connected with the internet, wherein two distinctive SNs were involved. Moreover, clients observed the information using the web application on the internet from anywhere. When the information of the SN surpassed the specified range, a notification was sent to the

clients insisting on the environmental setup being altered accordingly [24–26]. Energy is a critical issue in WSNs and the IoT, specifically when deployed in smart city applications and this was discussed briefly in [27–30].

Research Objectives

#### **3. Proposed Methodology**

The proposed routing protocol with a storage capacity protocol has been discussed in three phases. The first phase implements data routing with the security of the sensor nodes for confidential data through the IoT, which has heterogeneous energy using a multipath link routing protocol (MLRP). The next phase is to incorporate the H-TEEN protocol, which has load balancing capacity for sensor nodes that helps in attaining the energy optimization of nodes. Then the transmission of data is carried out using the security and optimization of energy. Finally, the data are stored with improved capacity using the ubiquitous data storage protocol (U-DSP). The architecture is given in Figure 1.

**Figure 1.** Proposed architecture.

#### *3.1. Multipath Link Routing Protocol (MLRP)*

MLRP comprises five various stages, namely, detecting neighbors, constructing topology, distributing pairwise keys, forming a cluster and transmitting data. Every process is described in detail below.

Detection of neighbors and construction of topology: It is considered that every node holds an ID{IDx}, certificate {CERTx}, public key {Kbs} and unique shared key {Kxbs}. To identify the neighbors, node broadcasts and receives NBR DET packet containing its ID as well as its CERT as in Equation (1).

$$\text{tax} \rightarrow \text{ } \ast : \text{NBR\\_DET} | ID\_{\text{x}} | \text{CERT}\_{\text{x}} \text{ } \tag{1}$$

The node receiving the NBR\_DET packet initially authenticates the ID of the node by verifying CERTx. When authenticated, the ID is added to the neighbor list by the receiver, or else the packet is dropped such that the unauthenticated node does not participate in this process of detecting neighbors. Once broadcasting is complete, neighbor information is forwarded to BS as in Equations (2) and (3).

$$\text{tax} \rightarrow BS: NBR\\_INFO|ID\_\mathbf{x}|\text{CERT}\_\mathbf{x}|E(k\_{\text{xbs}}, NBR\_\mathbf{x})|\tag{2}$$

$$\text{MAC}(\mathbf{k}\_{\text{xbs}\prime} \text{NBR\\_INFO} | ID\_{\text{x}} | \text{CERT}\_{\text{x}} | E(\mathbf{k}\_{\text{xbs}\prime} \text{NBR}\_{\text{x}})) \tag{3}$$

An intermediate node that is receiving the NBR\_INFO packet performs few functions such as:

Hence, a table is maintained by every node termed as a receiver packet table. Thus, the network traffic is reduced and node energy is saved to some extent. Once the NBR INFO packet is reached at BS, BS verifies MAC for authenticity and integrity; then neighbor information is authenticated using Kxbs between SN and BS. MAC, obtained from the data and by encrypting Kxbs, is used such that the intruder cannot either alter or spoof neighbor information.

#### *3.2. Distribution of Pairwise Key*

Once the information about the neighbor is obtained from the network nodes, BS analyzes the exact network topology and generates the neighbor matrix. Then the DFS algorithm is applied by which multiple paths are identified from BS to each source node. Beforehand, for each neighbor pair, BS generates the secret key, a random number, termed as pairwise key with the help of the hash function given by Equations (4)–(6).

$$k\_{xy} = h(secret, ID\_{\text{x}}, ID\_{\text{y}}) \tag{4}$$

BS unicasts this key to the corresponding node as

$$BS \rightarrow \propto : \text{PAIR\\_KEF} \mid \text{seq}\_{\text{no}} \mid ID\_{\text{bs}} \mid \text{CERT}\_{\text{bs}} \mid ID\_{\text{x}} \mid ID\_{\text{y}} \mid \text{E} \left(k\_{\text{xbs}}, k\_{\text{xy}} \left| \text{E} \left(k\_{\text{ybs}}, k\_{\text{xy}}\right)\right|\right) \tag{5}$$

$$\left| \left( \text{MAC}(\text{k\_{xbs}}, \text{PAIR}\_{\text{KEF}} |\_{\text{seq}} |\_{\text{ID}} | \text{CERT}\_{\text{bs}} |\_{\text{ID}} |\_{\text{D}} |\text{ID}\_{\text{y}} |\_{\text{E}} |\text{E}(\text{K}\_{\text{xbs}}, \text{Kxy}) \right| \left| \text{E} \left( \text{K}\_{\text{ybs}}, \text{K}\_{\text{xy}} \right) \right) \right| \tag{6}$$

The packet holds its type, sequence number, the ID of BS, neighbor and destination, certificate of BS, pairwise key and MAC of entire data. Every intermediate node that receives the packet performs the following operations:

$$\left| \mathbf{x} \rightarrow \mathbf{y} : \mathbf{C} \mathbf{H} \text{ALLIENGE} \left| ID\_{\mathbf{y}} \right| \mathbf{E} \left( \mathbf{K}\_{\mathbf{y} \boldsymbol{\theta} \boldsymbol{\nu}} \mathbf{K}\_{\mathbf{x} \boldsymbol{\theta}} \right) \middle| \mathbf{E} (\mathbf{K}\_{\mathbf{x} \boldsymbol{\nu}} \boldsymbol{ID}\_{\mathbf{x}} \left| none \right) \tag{7}$$

The packet at node y is decrypted using unique shared key *Kyb* and the pairwise key is generated followed by decrypting the next packet using the generated pairwise key then forwards the packet to x, which is given by Equation (8).

$$y \rightarrow \mathbf{x} : \text{CHALLENGE\\_REP} \left| ID\_\mathbf{x} \right| E(\mathbf{k}\_{\mathbf{xy}}, ID\_\mathbf{y} \left| none\\_\mathbf{1}) \tag{8}$$

Both the neighboring nodes verify one another by swapping the challenge packet as well as reducing overhead of resending pairwise key to y from BS. In end, each pair of nodes holds a pairwise key. When the CHALLENGE\_REP packet is not received at node x in the expected form, node x reports about the fake node to BS.

### *3.3. Cluster Formation*

BS initiates cluster formation and cluster head (CH) is selected based on residual energy. It is assumed that the energy level of the node does not change after the cluster is formed. In total, 5–8% of the cluster nodes are selected as CH with the criteria given below: (1) Two cluster heads should not be neighbors; (2) every CH has not less than 7–10% nodes as a neighbor. Then BS unicasts CH INT to CH along the route from CH to BS as illustrated in Figure 2. By considering that the node is next hop in route, the format of the packet CH INT is given by Equation (9).

Every node that receives the packet performs the following: (1) ID of the next hop is checked, if identical to its own, routing path (PATH) is decrypted and next hop from PATH is identified or else packet is dropped. (2) The sequence number is checked in the receiver packet table, then store packet type and sequence number if the sequence number did not exist in the table, and the changes needed are made, or else it is stopped. (3) Preceding hop is assigned its ID, while the subsequent one with the ID is found in PATH. (4) Routing table is stored in memory along with the previous one, as well as next hop, such that it helps in transmitting the data to BS. (5) PATH, as well as the sequence path for the subsequent hop, are encrypted with a pairwise key and the updated packet is forwarded. While CH is receiving the CH INT packet, decryption of PATH takes place and the data are verified by the MAC; then acknowledgement (ACK) is sent to BS via the same path.

When ACK is not received by BS within certain time from CH, the path is recomputed and the CH INT packet is sent again. A few criteria are involved in determining the routing path including the path having residual energy and power consumed. A path is selected with more residual energy and small hops count. To form a cluster, a CH ADV packet is sent by CHs to publicize their will.

ID and CERT are present in CH and the ADV packet, such that the receiving node ensures authentication. Nodes receiving several CH and ADV select CH based on two factors: (1) checking if the pairwise key is present in the ID advertised and (2) signal strength of advertisement forwarded. Once CH is selected, the will of the nodes is forwarded by CH JOIN packet with ID as well as MAC with pairwise key and a nonce. Once entire CH JOIN is received, information of the cluster members is sent to the BS by CH, and the TDMA schedule is created based on the total nodes in the cluster and unicast to every member. The packet has the following format by Equations (10)–(12).

$$\text{CH} \rightarrow \ast : \text{CH}\_{\text{-}} \text{ADV} | \text{ID}\_{\text{ch}} | \text{C} \text{ERT}\_{\text{ch}} \tag{10}$$

$$\text{x} \rightarrow \text{CH} : \text{CH} \\_\text{JOIN} | \text{ID}\_\text{x} | \text{MAC} \{ \text{K}\_\text{xch} \text{\\_} \text{CH} \\_\text{JOIN} | \text{ID}\_\text{x} | \text{none}\_\text{x} \tag{11}$$

$$\text{CH} \rightarrow \text{x}: \text{CH}\_{\text{x}} \text{SHED}|\text{ID}\_{\text{x}}|\text{E}(\text{k}\_{\text{xch}}, \text{t}\_{\text{x}}) \text{MAC}\left(\text{CH}\_{\text{SHED}|\text{ID}\_{\text{x}}|\text{E}(\text{K}\_{\text{xch}}, \text{t}\_{\text{x}}) \text{accne}\_{\text{x}} + 1\right) \tag{12}$$

#### *3.4. Data Transmission*

The data transmission phase comprises three subphases;

These subphases are observed with the form as given in Equations (13) and (14).

$$\infty \to \mathbb{C}H : \text{DATA} | \text{ID}\_{\text{x}} | \text{E} (\text{K}\_{\text{xch}} d\_{\text{x}}) \tag{13}$$

$$\text{MAC}(\text{K}\_{\text{xch}}, \text{DATA} | \text{ID}\_{\text{x}} | \text{E}(\text{K}\_{\text{xch}}, d\_{\text{x}})) \tag{14}$$

Once the data are received, they are aggregated by CH and then forwarded to BS by Equation (15).

$$\text{CH}\rightarrow\text{BS}:\text{AGGR\\_DATA}|\text{ID}\_{\text{ch}}|\text{ID}\_{\text{j}}|\text{E}\left(\mathbf{K}\_{\text{jcb}},\text{seq}\_{\text{t}\text{b}}\right)\Big|\text{E}(\mathbf{K}\_{\text{cdbs}},\mathbf{d}\_{\text{ch}})\Big|\text{MAC}(\mathbf{K}\_{\text{cdbs}},\text{AGGR\\_DATA}|\text{seq}\_{\text{t}\text{b}}|\text{E}(\mathbf{K}\_{\text{cdbs}},\mathbf{d}\_{\text{ch}})\Big)\tag{15}$$

AGGR\_DATA specifies the type of the packet, IDch and IDj denote the previous and next hop in the path, respectively; the packet reply is verified with the encrypted sequence number when AGGR\_DATA packet is received by any node with identical sequence number, then packet is dropped. Dch represents encrypted data for BS and MAC, which supports maintenance of the packet integrity and authentication. The following operations are performed by the node receiving this packet: (1) ID of the next hop is checked; when similar to its ID, the sequence number is decrypted. (2) The packet sequence number is verified in the receiver packet table, if not found, packet type and the sequence number is entered or else left out. (3) The entry of the subsequent hop is modified with the ID of the subsequent hop nodes and that of the preceding hops with its ID. (4) The sequence number is encrypted using the pairwise key of subsequent hop as well as then forwarded again. In this manner, data reach the BS through the route specified and BS uses an exclusively shared key (Kchbs), which evaluates the data efficiency.

### *3.5. Incorporation of H-TEEN*

In H-TEEN, after selecting the CHs, CHs forwards the following parameters:

#### *3.6. U-DSP*

In a storage system, businesses store data in the data server located remotely, and hence data authenticity is assured. When, occasionally, unauthorized users delete or modify data, the server is compromised and/or randomly leads to Byzantine failures. As this is the initial process for recovering the storage errors quickly, cloud storage systems introduce a flexible as well as effective distributed approach with explicit dynamic data support for distribution of files in a cloud server. The homomorphic token is computed with the help of a universal hash function and is integrated with verification of erasure-coded data. Moreover, servers that misbehave are also identified. At last, file retrieving and error recovering procedures based on erasure-correcting code are defined.

#### **4. Performance Analysis and Discussion**

The efficiency of the secure routing protocol with energy optimization and data storage was evaluated with several simulation experiments with randomly varying topology. NS-2 version 2.34 was the simulation tool used and considered a multi-hop network with 1000 m × 1000 m size located in a randomized grid with SNs from 50 to 200. The sink node was at the centre of the network. Traffic was CBR of 600 packets/sec and packet size was 316 bytes. The heterogeneity of the network was proven in the simulation by testing the environment with different sets of nodes. The simulation parameters are shown in Table 1.

**Table 1.** Simulation parameters.

The performance measures considered were throughput, end-to-end delay, energy efficiency, the lifetime of the network and data storage capacity.

End-to-end delay, an important metric, is considered to deal with real-time traffic and transmit data packets within the stipulated time. End-to-end delay is the difference in the time taken between the source node transmitting data and the sink receiving it. It is the sum of the delay in transmission, propagation, queuing and processing at every hop.

Table 2 shows a comparison of the end–end delay. Figure 3 depicts the end–end delay for the proposed MLRP-HTEEN-UDSP protocol and Figure 4 compares it with the other protocols such as LEACH, CCBRP and PEGASIS. It suggests that the proposed protocol performs better than other protocols. The delay is at a minimum since the hierarchical architecture of the CHs for all the times chooses the route that has fewer hops with good quality links.

**Table 2.** Comparison of end–end delay.

**Figure 3.** End-to-end delay of MLRP-HTEEN-UDSP.

**Figure 4.** Comparison of end-to-end delay.

Throughput is the total packets received by the sink within a specified duration. The comparison of throughput is shown in Table 3.

**Table 3.** Comparison of throughput.

Figure 5 depicts the throughput of MLRP-HTEEN-UDSP, while Figure 6 compares the throughput of the proposed protocol with other protocols. The selection of multiple paths and minimum delay balances the load and uses the wireless spectrum efficiently. Thus, it achieves a higher throughput than other protocols.

**Figure 5.** Throughput of MLRP-HTEEN-UDSP.

**Figure 6.** Comparison of throughput.

Table 4 shows a comparison of the energy efficiency. The average energy efficiency is represented in Figure 7 where we can realize that our proposed protocol MLRP-HTEEN-UDSP has less energy dissipation compared with other protocols (LEACH, CCBRP and PEGASIS) as shown in Figure 8 with various node numbers.

**Table 4.** Comparison of energy efficiency.

**Figure 7.** Energy efficiency of MLRP-HTEEN-UDSP.

**Figure 8.** Comparison of energy efficiency.

Table 5 shows the comparison of the network lifetime. Figure 9 presents the network lifetime for the proposed MLRP-HTEEN-UDSP and Figure 10 shows a comparison of the network lifetime between the proposed and existing techniques.

**Table 5.** Comparison of network Lifetime.

**Figure 9.** Network lifetime of MLRP-HTEEN-UDSP.

**Figure 10.** Comparison of network Lifetime.

Table 6 shows the comparison of data storage. Figure 11 shows the data storage for the proposed MLRP-HTEEN-UDSP and Figure 12 shows the comparison of the data storage between the proposed and existing techniques.

**Table 6.** Comparison of data storage.

**Figure 11.** Data storage of MLRP-HTEEN-UDSP.

**Figure 12.** Comparison of data storage.

Table 7 represents the overall parameter comparison of the proposed and existing techniques, and Figure 13 is the graphical representation of the overall comparison.

**Table 7.** Overall comparisons of MLRP-HTEEN-UDSP.

**Figure 13.** Overall comparison of MLRP-HTEEN-UDSP.

#### **5. Conclusions**

In this research, an energy optimization method with secure routing for IoT heterogeneous WSN applications is proposed. This secure as well as reliable routing protocol gathers data about neighbor nodes at BS, and generates the key and energy-efficient multipath for every node. CHs help in data aggregation and forward them to BS, which continuously monitors nodes for residual energy to choose some new paths and CHs. By using the complexity of multimedia processing and the aggregation process to the CHs side, as well as preventing path loops and path cycles for establishing routes, the integrated implementation of MLRP-HTEEN-UDSP produced a minimum end-to-end delay in suitable data packets and reduced the energy consumption at SNs. We also demonstrated a light-weight distributed key management method for supporting secure communication among nodes. The performance of MLRP-HTEEN-UDSP outperforms the existing ones such as LEACH, CCBRP and PEGASIS in all the performance metrics including end-to-end delay, throughput, energy efficiency, network lifetime and data storage capacity. Future work of the proposed protocol will be extended to the performance analysis in the green IoT environments with an increased network size.

**Author Contributions:** Conceptualization, Writing—original draft R.N.; Supervision, V.C. and S.B.G.; Writing-original draft and review & editing, K.J. and M.G.; Validation, C.V.; propose the new method or methodology, N.R and S.B.G.; Formal Analysis, Investigation C.O.S.; Resources, S.B.G. and C.O.S.; Software, T.C.M.; Writing—review & editing, T.C.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** National Research Development Projects to finance excellence (PFE)-14/2022-2024 granted by the Romanian Ministry of Research and Innovation, this paper was partially supported by UE-FISCDI Romania and MCI through projects AISTOR, FinSESco, CREATE, I-DELTA, DEFRAUDIFY, Hydro3D, FED4FIRE—SO-SHARED, AIPLAN—STORABLE, EREMI, NGI-UAV-AGRO and by European Union's Horizon 2020 research and innovation program under grant agreements No. 872172 (TESTBED2) and No. 777996 (SealedGRID).

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data will be shared for review based on the editorial reviewer's request.

**Acknowledgments:** The work of Chaman Verma was supported by the European Social Fund under the project "Talent Management in Autonomous Vehicle Control Technologies" (EFOP-3.6.3-VEKOP-16-2017-00001). The publication of C.O.S. was supported by funds from the National Research Development Projects to finance excellence (PFE)-14/2022-2024 granted by the Romanian Ministry of Research and Innovation.

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

### **References**


*Hydrogeology Site Characterisation*

The first part of this section presents the principles and applications of ground penetrating radar (GPR) as a promising technology to detect and delineate aquifers or non-metallic minerals. Due to the inherent heterogeneity and isotropic nature of the subsurface, the need to improve approaches for groundwater detection and delineation remains vital.

In the second part, a case study on the hydrogeology characterisation of the Andean mountain groundwater resources of Central Chile is presented. Field surveys, streamflow gauging, environmental tracers, and a hydrological model are utilized as complementary techniques to improve site understanding.

Methods for predicting the risk of groundwater contamination with pesticides and their dangerous aspects for human health are then developed. These methods comprise risk acceptance assessment and integral groundwater contamination hazard index (IGCHI) evaluation according to a special scale.


*Edited by Mustafa Yildiz and Yasin Ozgen*

Potato (*Solanum tuberosum* L.) is the fourth-largest food crop produced in the world with approximately 370 million tonnes. This product is a staple in many diets throughout the world and the underground swollen tubers of the plant are rich sources of proteins, carbohydrates, minerals (K, Mn, Mg, Fe, Cu and P), and vitamins (C, B1, B3, B6, K, folate, pantothenic acid). Improvement of new potato cultivars resistant to biotic and abiotic factors is extremely important, as these are the main reasons for decreased potato production. Seed tuber production and tuber storage under healthy conditions after harvest are two important issues in potato cultivation. As such, this book discusses the importance of the potato plant and examines ways to increase its production and develop new cultivars resistant to stress factors via conventional and biotechnological methods.

ISBN 978-1-83969-166-9

*Solanum tuberosum*

– A Promising Crop for Starvation Problem

Published in London, UK © 2021 IntechOpen © Emma Brewster / iStock


*Article* **Accounting for Slot Harmonics and Nonsinusoidal Unbalanced Voltage Supply in High-Speed Solid-Rotor Induction Motor Using Complex Multi-Harmonic Finite Element Analysis**

**Tomasz Garbiec \* and Mariusz Jagiela**

Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, ul. Proszkowska 76, 45-758 Opole, Poland<EMAIL_ADDRESS>
**\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** Solid rotor induction machines are still used in high-speed systems. A two-dimensional field-circuit model based on the finite element method and the complex magnetic vector potential has been shown as a very time-effective tool in the analysis of their steady states compared to timedomain models. This continuation work presents a validated computational algorithm that enables the inclusion of the nonsinusoidal and/or asymmetrical voltage supply in the multi-harmonic field-circuit model of these machines that was presented in the previous works by the authors. The extended model accounts for both spatial harmonics due to slotting and/or winding distribution and the time-harmonics due to voltage waveform. The applicability range of the model therefore increases to cases when the machine is supplied with a nonsinusoidal three-phase system of voltages with symmetry or asymmetry that can be decomposed into three symmetrical components. Its short execution time characteristic allows for much more insightful design studies of the contribution of voltage supply- and slotting-related harmonics to the overall efficiency of the machine than is possible with the time-consuming time-domain models. The proposed computational framework has never been presented in the literature. The model is verified positively by the comprehensive time-domain model. It is especially useful in design studies on solid rotor induction motors related to the optimisation of the efficiency of induction motor-based drive systems.

**Keywords:** induction motor; solid rotor; effective parameters; finite element method


Preface

Water resources are highly influenced by the hydrologic cycle and play a role in the agri‐ culture economic development. However, as it is shown by the intergovernmental panel on climate change report, the phenomenon of changing climate has set way to exacerbate an already serious situation of water supply for various users. In this context, the scientif‐ ic investigations on the issue of sustainable use of water are timely and important. Im‐ provement of water management involves the accurate estimation of consumptive uses. One of the techniques is the assessment of evapotranspiration, as a major component of the hydrologic cycle.

As is known, some of the meteorological parameters necessary to estimate evapotranspira‐ tion are frequently missing or hard to collect, and the maintenance of meteorological sta‐ tions is costly. Therefore, the study presented in the first chapter aimed to estimate evapotranspiration using a limited number of meteorological parameters. With the interna‐ tionally accepted Penman-Monteith method as the standard, the estimation formulas of ra‐ diation-based methods were compared with those of temperature-based methods in the hope of discovering a simple estimation formula to solve the issue of lacking or missing me‐ teorological data.

In order to anticipate the necessary action for water management, researchers from Europe and South America have developed a model to forecast evapotranspiration based on an arti‐ ficial neural network. The predicted output and final results are compared for two different input parameters of evapotranspiration calculated with scintillometry and micrometeorolo‐ gy data. The goal of the study is to find which input data can be reliable to obtain evapo‐ transpiration forecast performances. Moreover, the optimal number of predicted days to obtain a correct final performance and the optimal number of input days of data to obtain a correct prediction are tested.

Given the same limitations—time and resources—data required to model evapotranspira‐ tion are not always available for a study site. But, North American specialists consider that off-site data from meteorological networks may be a suitable substitute. In their study, sen‐ sitivity to mixtures of on-site and off-site data inputs of three widely used models for calcu‐ lating evapotranspiration for a ponderosa pine forest where evapotranspiration was measured previously by eddy covariance was investigated.

Northern latitudes have been identified as a region where global climate change will have earlier and stronger impacts than in other regions of the world. All these changes will poten‐ tially alter the exchange of surface energy, water, and carbon cycles in high latitude ecosys‐ tems and consequently the response at the regional level to the atmosphere system. Accordingly, an interesting study, based on current numerical model outputs and compari‐

sons with field experimental observations, allowed to identify new challenges in northern agroecosystems.

Moisture evaporation from porous media is studied by its importance in drying of foods and building materials and biological products such as biopesticides. An exciting foray into the current state of knowledge in the frame of physics of moisture evaporation process from porous media is the subject of the last chapter. Further, the authors aim to establish theoreti‐ cal support for designing biopesticides able to ensure efficient and effective fight against harmful insects in agricultural crops.

#### **Prof. Dr. Daniel Bucur,**

University of Applied Life Sciences and Environment in Iasi, Romania


**Attachment and Biofilm Formation by**  *Salmonella* **in Food Processing Environments**

Efstathios Giaouris1, Nikos Chorianopoulos2,

Panagiotis Skandamis3 and George-John Nychas3 *1Department of Food Science and Nutrition, University of the Aegean 2Veterinary Research Institute, National Agricultural Research Foundation (NAGREF) 3Department of Food Science and Technology, Agricultural University of Athens (AUA) Greece*


**Information Technology and E-Commerce Reflexes on Total and Agricultural Trade in Egypt**

Mahmoud M .Fawaz1 , Abdelbaky M. Elshaib2 , Roshdy Sh. El Adwy1

1 Department of Agricultural Economics, kafr elsheikh University, kafr elsheikh, Egypt

2 Department.of Agricultural Economics, Tanta University, Tanta, Egypt

#### **Abstract**

Nowadays, E-commerce has been developing quickly and it brings great impact on economy of all the countries. We insist that the E-commerce development in developing countries and economies in transition will have fine perspectives if the government, corporations and all the related people make great effort together. These papers address the issue of understanding the components of the information economy and E-commerce (profitability of .ese Experiment, this research aimed to identification, entity, characteristics and divisions and to figure out its profitability in Egypt. This research aimed also to pinpoint the measures necessary to incorporate the E-commerce between Egypt and the others commentating countries. We therefore propose a framework consisting of five components. First, concept and entity of E-commerce and its importance in marketing area, secondly, information and communication technology in developing and developed countries, third, the effect of internet on the Egyptian trade, forth, the effect of Internet on the Egypt Agric. Trade

**Keywords:** (Ec) Electronic commerce, (ICT) Information and Communication Technology, (ITU) international Telecommunication Union, (PIS) Primary Information sector, (SIS) Secondary Information Sector, (ET) Electronic Trade,(BtoB) Business to Business, and (BtoC) Business to consumer.

## **1. Introduction**

Nowadays, E-commerce has been developing quickly and it brings great impact on economy of all the countries, and play important role in foreign agriculture trade in both developed and developing countries. Research Problem The research problem confined to important question; that is how far profitability would Egypt gain from ET, although it regarded as an user rather than producer of information technology. In addition, nowadays, the assessment of ET amount encountered a practical difficulties; this attributable to the absence of local or international system or rules could control such trade.Furthermore, the formal statistical institutions could not monitor the precise or actual amount of ET and the scientific studies and literatures pertaining such trade regarded very few either at local or international scale. It can be said, that the agricultural marketing via ET in Egypt still limited although there are a continuous increase in number of agricultural ET sites in Egypt. Consensus. This research aimed to: Determination of the direct positive impacts of ET on the national income, by supporting and boosting the external trade. Assessment of the effect of transportation means of technology (Internet) on the Egyptian Agric.

© 2012 Fawaz 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 cited.

Trade. Assessment of Relationship between information technology and GDP in Egypt. This research relied on qualitative and quantitative indications to display the economic impacts of ET and to address the gab between Egypt and the other countries.. The study comprised the data gathered between 1994 and 2009; that would be divided into 2 terms, the first between 1994 and 1998 (the period before establishment of internet handling). The second term was from 1999 to 2009 (period after launching of internet dealing in Egypt) in the aim of determination the impact of information revolution (internet dealing) on the agricultural marketing.

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(ICT) play a key role transforming of economic structures. The preceded studies confirmed that the economical impacts of (ICT) occurred on macro. And micro- economics levels. On the macroeconomics level, the studies mentioned that the rapid progress in (ICT) will lead to increase in international Trade cause minimization cost, advertising information exchange exhibitions, information availability in real time, more accessibility to the international market. And on microeconomic level, the studies confirmed that the (ICT) will help small business to access to international market, optimizing the resource allocation and reducing transaction cost. Examining the e-commerce important question is what impact (ICT) and Internet have on the productivity growth. It reduces transaction costs, allocates recourses better, increases economies of scale, improves the competitiveness of business in general, increase efficiency generates important

(IT) encompasses every thing that allows us to electronically gather, generate, store, analyze, distribute or otherwise use information.  It also includes more traditional telecommunication Technologies shushes cell phones or fax machines anything related to the electronic of information. Table (2) represents the Electronic commerce by type Business to Business and Business to consumer by region during the period 2005-2009, data showed that the global of (B to B) to increases with growth Percentage reached by 257.9% annually. The average of (B to B) reached 609.25Millar dollars. While (B to C) the average 60.5Millar dollars and growth Percentage reaches by 169.1%

E- commerce 2000 2003 2006 2009 Average Growth% B To B 43<PHONE_NUMBER> 609.25 257.9 B to C 8 33 76 125 60.5 169.1 Total 51<PHONE_NUMBER> 669.75 245.2

When compares between developing and developed countries Shown that the Digital divide

% B to B/total 84 88 92 91 88.75

**Table 2.** Electronic commerce by type (BtoB) from 1998 to 2009 (Millar dollars)

**2.2. Technology gap between developing and developed countries**

a. Internet: developing countries 34% while developed countries 66%.

b. Computer: developing countries (27%) while developed countries (73%). c. Mobile Phone: developing countries 46% while developed countries (54%).

Source: world internet usage and population statistics

*2.1.2. Information and Communication Technology (ICT)*

changes in the management and production processes of business.

*2.1.3. Distribution of Market Information Technology (IT)*

annually. And the average B to B/ Total 88.75%.

Source: Computed from the data cited from world Resource

(technology gab) in 2009:

Turkey, September 10-12, 2012

401 ISALS

#### **2. Information and Communication Technology in developing and developed countries**

#### **2.1. Internet activity worldwide**

The equation (1) describes that there is a significant increase of the internet host count from 1981- 2009 according to the world wide internet domain survey. By added the factor of time to the previous equation, the results of analysis statistics was as the following:

$$\begin{aligned} \text{Log } \mathbf{y}\_i &= 0.465 + 5.789 \log \mathbf{x}\_i \\ \text{(0.562)} & \quad \text{(17.912)} \\ \text{R}^2 &= 0.925 & \quad \text{F=320.844''} \end{aligned} \tag{1}$$

Where:Y t = Internet host count according to the world internet domain survey,X t = time (1, 2, 3…)

#### *2.1.1. Internet usage statistics by world Region*

Table (1) illustrates the internet usage by region during period 2000-2009, the highest growth percentage of internet usage was achieved by middle East which recorded 267 Percent, while Latin America and Caribbean occupied the second rank with 211% Africa, Asia, Europe, North America, and Australia occupied the rest ranks of growth with percents 198,165,152,105,114, respectively.

**Table 1.** Average internet usage statistics by world Region, 2000-2009

Source: world internet usage and population statistics

#### *2.1.2. Information and Communication Technology (ICT)*

(ICT) play a key role transforming of economic structures. The preceded studies confirmed that the economical impacts of (ICT) occurred on macro. And micro- economics levels. On the macroeconomics level, the studies mentioned that the rapid progress in (ICT) will lead to increase in international Trade cause minimization cost, advertising information exchange exhibitions, information availability in real time, more accessibility to the international market. And on microeconomic level, the studies confirmed that the (ICT) will help small business to access to international market, optimizing the resource allocation and reducing transaction cost. Examining the e-commerce important question is what impact (ICT) and Internet have on the productivity growth. It reduces transaction costs, allocates recourses better, increases economies of scale, improves the competitiveness of business in general, increase efficiency generates important changes in the management and production processes of business.

#### *2.1.3. Distribution of Market Information Technology (IT)*

(IT) encompasses every thing that allows us to electronically gather, generate, store, analyze, distribute or otherwise use information.  It also includes more traditional telecommunication Technologies shushes cell phones or fax machines anything related to the electronic of information. Table (2) represents the Electronic commerce by type Business to Business and Business to consumer by region during the period 2005-2009, data showed that the global of (B to B) to increases with growth Percentage reached by 257.9% annually. The average of (B to B) reached 609.25Millar dollars. While (B to C) the average 60.5Millar dollars and growth Percentage reaches by 169.1% annually. And the average B to B/ Total 88.75%.

**Table 2.** Electronic commerce by type (BtoB) from 1998 to 2009 (Millar dollars) Source: Computed from the data cited from world Resource

#### **2.2. Technology gap between developing and developed countries**

When compares between developing and developed countries Shown that the Digital divide (technology gab) in 2009:

d. Land line: developing countries (45%) while developed countries (55%). But population in developing countries 81% and 19% in developed countries.

#### **2.3. Egypt Internet usage**

Egypt Internet usage and population compared with the Rest of the Africa in 2009. The Egypt has 5 million users for the international information net. The Percent of internet user with represent as the indirect indicator fore – commerce in Egypt is about 21.3%. But this Percent in Rest of Africa 78.7%. The population in Egypt about 8.5% in Africa. Some studies mentioned that may be Egypt become the biggest African countries for the number of internet users even more than south Africa, which is the highest percent in Africa.

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net). The second period was after that, from (1999-2009) this dummy variable represented as Dt. Average Total exports before using Internet about 11438.4 (million LE) .(S.T DEV) about 1081.042

By added the factor of time to the previous equation, the results of analysis statistics was as the

Where: Et = Total export in Egypt during the period (1997-2009), Dt = Dummy variable equal (1)

It illustrates the total Imports in Egypt before and after using internet, the results of the statistical analysis that there is significant increase in the total imports during the period after the internet comparing to the period before. (Average) total imports in Egypt before using internet about 38955.4 million LE.(S.T DEV) about 10448.87 and after using internet about 113052.4 million LE.(S.T DEV) about 74178.37 The study used the dummy variable to measure the effect of information revolution in Egypt. By added the factor of time to the previous equation, the results

Where: It = Total imports in Egypt during the period (1999-2009), DT: Dummy variable equal (0)

**Agriculture Export**

**Agriculture Imports**

**Trade Balance**

 10171.2 27656.1 -17485 1262 7900 -6638 10464.5 27550.4 -17086 1115 7500 -6385 11757.5 32460.6 -20703 1740 7200 -5460 11703.8 39890.9 -28187 1641 10800 -9159- 12006.1 44217.9 -32212 1689 12700 -11011 13281.0 44885.7 -31605 1488 13400 -11912 10684.8 56026 -45341 1760 15900 -14140 **Average 11438.4 38955.4 -275170 1527.86 10771.429 -9243.57**

for the period from (1992-1998) and (1) for the period from (1999-2009)

**Total Import**

**3.2. The effect of transportation means of technology (internet) on the Egyptian**

and after using internet (47554.82 million LE) .(S.T DEV) about 31764.58

Et = 11438.414 + 36116.404 Dt

= 0.356 F = 8.842\*\*

after using internet, equal (0) before using internet.

(1.205) (2.974) \*\*

of analysis statistics was the following:

It = 38955.386 + 74096.992 DT

= 0.297 F = 6.749\*

(1.747) (2.598) \*

following:

**imports**

R2

R2

**Years Total**

**Export**

Turkey, September 10-12, 2012

403 ISALS

(2)

(3)

**Agriculture Trade balance**

Table (3) illustrates Internet users in Egypt during the period 1998-2008. the number of Internet users increased from about 36.4 (1000 persons) in 1998 to 1.355.0 (1000 persons) in year 2008. And the index number increased from 100% in year 1998 to 3722.527. % in years 2008.

**Table 3.** Number of Internet users in Egypt, 1998-2008.

Source: world internet usage and population statistics. 2009.

#### **3. The effect of transportation means of technology (internet) on the Egyptian trade**

#### **3.1. The effect of transportation means of technology (internet) on the Egyptian export**

It illustrates the table export in Egypt before and after using internet, the results of the statistical analysis that there is a significant increase in the table exports during the period after the internet comparing to the period before. The study used the dummy variable to measure the effect of information revolution in Egypt, the study divided the period (1992-2009). The first period was from (1992-1998) and represented the period before the revolution of information in Egypt (inter-

net). The second period was after that, from (1999-2009) this dummy variable represented as Dt. Average Total exports before using Internet about 11438.4 (million LE) .(S.T DEV) about 1081.042 and after using internet (47554.82 million LE) .(S.T DEV) about 31764.58

By added the factor of time to the previous equation, the results of analysis statistics was as the following:

$$\begin{aligned} \text{Et} &= 11438.414 + 36116.404 \,\text{Dt} \\ \text{(1.205)} &\qquad \text{(2.974)} \,\text{\*\*} \\ \text{R}^2 &= 0.356 \qquad \text{F} = 8.842^{\ast \ast} \end{aligned} \tag{2}$$

Where: Et = Total export in Egypt during the period (1997-2009), Dt = Dummy variable equal (1) after using internet, equal (0) before using internet.

#### **3.2. The effect of transportation means of technology (internet) on the Egyptian imports**

It illustrates the total Imports in Egypt before and after using internet, the results of the statistical analysis that there is significant increase in the total imports during the period after the internet comparing to the period before. (Average) total imports in Egypt before using internet about 38955.4 million LE.(S.T DEV) about 10448.87 and after using internet about 113052.4 million LE.(S.T DEV) about 74178.37 The study used the dummy variable to measure the effect of information revolution in Egypt. By added the factor of time to the previous equation, the results of analysis statistics was the following:

It = 38955.386 + 74096.992 DT

(3)

 (1.747) (2.598) \* R2 = 0.297 F = 6.749\*

Where: It = Total imports in Egypt during the period (1999-2009), DT: Dummy variable equal (0) for the period from (1992-1998) and (1) for the period from (1999-2009)

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Where:EAT: Agric. Export in Egypt, Dt: Dummy variable equal (0) for the Period from 1992-1998

**4.2. the effect of transport in means of technology (Internet) on the Egyptian Agric.**

The equation (6) illustrates the total Agric. Imports in Egypt before and after using internet, the results of the statistical analysis that there is non significant decrease in the Agric. Exports during the period after the internet comparing to the period before. Average Agric. imparts in Egypt 10771.429 Million (LE) .(S.T DEV)3382.166, and After using internet about 12366.55 Million (LE) .(S.T DEV)3591.836. The study used the dummy variable to measure the effect of information

Where: IAt= Agric. Imports in Egypt, Dt= Dummy variable equal (0) for the period from 1992-

Where:YTAT: Total Agricultural Trade,GDP: Gross domestic product, ICT: information communi-

The equation (8) describes that there is significant increase relationship between Total Agricultural Trade, GDP, Internet host in Egypt. Internet user in Egypt Population ,the results of analysis

**5. Relationship between information technology and GDP,ICT in Egypt**  The equation ( 7 ) describes that there is significant increase relationship between Total Agricultural Trade and both (GDP) Gross domestic product in Egypt,( ICT) information communication

revolution in Egypt, the results of analysis statistics was the following.

technology in Egypt, the results of analysis statistics was as the following:

YTAT = -2.634 + 0.326 GDP +0.029h1 +0.0739 h2+ 0.0234P

( -5.091)\*\* (4.932)\*\* (1.092) (3.947)\*\* (0.413)

EAt=1527.857+ 2112.514 Dt

and (1) for the Period from 1999-2009.

y= 10771.429 – 1595.117 Dt

= 0.052 F= 0.881

YTAT= 3.412 + 0.315 GDP +0.731 ICT (3.91)\*\* (6.151)\*\* (4.735)\*\*

= 0.723 F 126.3\*\*

=0.691 F=103.2\*\*

(8.108) (0.939)

1998 and (1) far the period from 1999-2009

**Imports**

R2

R2

cation technology.

R2

statistics was as the following:

 (3.402)\*\* (3.326)\*\* R-2=0.48 F=11.061\*\* Turkey, September 10-12, 2012

405 ISALS

(5)

(6)

(7)

(8)

**Table 4.** Total and Agricultural export and total and imports Agricultural imports Agricultural in Egypt Before and after using internet. (Million LE)

Source: www.Egypt.gov.eg

#### **3.3. Relationship between total export and internet in Egypt**

The equation (4) describes that there is significant increase relationship between total export in Egypt and internet user, the result of analysis statistics was as the following:

Et = 12426.84 + 471.334h1 (5.344)\*\*\* (7.467) \*\*\* R2 = 0.918 F = 55.75 (4)

Where: Et: Total export in Egypt., h1: Internet users in Egypt., T: Time (1, 2, 3 … 14)

#### **4. The effect of transport in means of technology (Internet) on the Egyptian Agric. trade**

#### **4.1. The effect of transport in means of technology (Internet) on the Egyptian Agric. Exports**

It illustrates the total Agric. Export in Egypt before and after using internet, the results of the statistical analysis that there is significant increase in the Agric. Exports during the period after the internet comparing to the period before. Average Agric. Exports in Egypt before using Internet about 1527.86 Million (LE) .(S.T DEV) about 251.79, and after using internet about 5289.545 Million (LE). .(S.T DEV) about 3056.783 The study used the dummy variable to measure the effect of information revolution in Egypt, the results of analysis statistics was the following:

Where:EAT: Agric. Export in Egypt, Dt: Dummy variable equal (0) for the Period from 1992-1998 and (1) for the Period from 1999-2009.

#### **4.2. the effect of transport in means of technology (Internet) on the Egyptian Agric. Imports**

The equation (6) illustrates the total Agric. Imports in Egypt before and after using internet, the results of the statistical analysis that there is non significant decrease in the Agric. Exports during the period after the internet comparing to the period before. Average Agric. imparts in Egypt 10771.429 Million (LE) .(S.T DEV)3382.166, and After using internet about 12366.55 Million (LE) .(S.T DEV)3591.836. The study used the dummy variable to measure the effect of information revolution in Egypt, the results of analysis statistics was the following.

$$\begin{aligned} \text{y} &= 10771.429 - 1595.117 \,\text{Dt} \\\\ \text{R}^2 &= 0.052 & \text{F} &= 0.881 \end{aligned} \tag{6}$$

Where: IAt= Agric. Imports in Egypt, Dt= Dummy variable equal (0) for the period from 1992- 1998 and (1) far the period from 1999-2009

## **5. Relationship between information technology and GDP,ICT in Egypt**

The equation ( 7 ) describes that there is significant increase relationship between Total Agricultural Trade and both (GDP) Gross domestic product in Egypt,( ICT) information communication technology in Egypt, the results of analysis statistics was as the following:

$$\mathbf{Y}\_{\text{TAT}} = \mathbf{3.412} + \mathbf{0.315 GDP} + \mathbf{0.731} \text{ ICT}$$

$$(\mathbf{3.91})^{\*\*} \quad (6.151)^{\*\*} \text{ (4.735)\*}$$

$$\mathbf{R}^2 = \mathbf{0.723} \qquad \text{ F 126.3\*}$$

Where:YTAT: Total Agricultural Trade,GDP: Gross domestic product, ICT: information communication technology.

The equation (8) describes that there is significant increase relationship between Total Agricultural Trade, GDP, Internet host in Egypt. Internet user in Egypt Population ,the results of analysis statistics was as the following:

$$\mathbf{Y}\_{\text{TOT}} = \text{-2.634} + 0.326 \,\text{GDP} + 0.029 \eta \,\text{l} \,\text{+} 0.0739 \,\text{ }\eta \,\text{2+} 0.0234 \,\text{P}$$

$$\text{(-5.091)} \\ \text{\* (4.932)} \\ \text{\* (1.092)} \\ \quad \text{(3.947)} \\ \quad \text{(0.413)}$$
 $\text{R} \triangleq 0.691 \qquad \text{F} \equiv 103.2 \,\text{\textdegree} $

Where:YTAT: Total Agricultural Trade .GDP: Agric growth domestic product in Egypt.h1: Internet user in Egypt. h2: Internet host in Egypt and P=Population describes that there is significant increase relationship between Total Agricultural Trade, GDP, Internet user in Egypt and Internet host in Egypt. Population The equation describes that there is significant increase relationship between Total Agricultural Trade, gross domestic product GDP and internet user, n2: Internet host, Population in Egypt.:

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**Effect of Heat on Egg White Proteins**

\*Corresponding author, Tel.: +213<PHONE_NUMBER>; fax: +213 30 40 62 71

, Lyes Aissat, Khodir Madani

Thermal treatments applied to the egg white cause undesirable modifications of their physicochemical and functional properties. The goal of this study was to acquire some knowledge on the effect of heat on some physico-chemical properties of the albumen while applying different scales (temperature / time). The results show: a sigmoïdale evolution with negative slope of the transmittance, an irreversible loss of solubility. Native-Page of protein's albumen shows the apparition of several bands what denotes diversity of proteins in egg white. The comparison of these profiles dealt to different temperatures /20 min with those unprocessed, shows apparition of new bands and different relative mobility due to the formation of aggregates. Coagulation

Man has used bird eggs as food since prehistoric times [1, 2]. This reserve of proteins, lipids, vitamins and minerals is remarkable for varieties of nutrients it contains and their high nutritional value, due to a perfect balance of its constituents. Egg is always recognized as a food of high nutritional quality for humans [3, 4, 5, 6, 7]. Beyond their nutritional value, their primary function, namely the formation of a new individual, suggests that they contain many compounds essential to life, and therefore they constitute a major potential source of biological active molecules which interest the pharmaceutical, cosmetic and food [8, 9, 10].The food industry currently uses largely hen egg (especially egg white) as an ingredient, despite competition from increasingly strong dairy products. The origin of this interest is many functional properties of this latter (foaming and gelling properties in particular) [11].Egg white protein's are rich in essential amino acids, and possess excellent nutritional value, thus they have long been considered as reference proteins [12, 13, 14]. Nevertheless, the white gotten from breaking eggs is sensitive to contaminations of the environment [15, 16].To fight against these infections and protect the consumer, the heat treatment of food egg is often required to ensure microbial safety or to obtain desirable organoleptic attributes [17].The egg white is a hydrated medium, viscous, rich on protein, heat treatment would cause a distortion of its components, the non-enzymatic browning and coagulation of proteins [18, 19]. Polypeptide chains are unfolded and can form a gel or aggregates by the association of these molecules [20]. This aggregation leads to significant changes in the physico-chemical and functional properties of egg proteins [20, 21, 22, 23, 24].It is therefore very

Faculty of Nature and Life Sciences, 3BS Laboratory A. Mira University, Bejaia, Algeria

and/or precipitation of these proteins have been observed around 74°C/20 min.

**Keywords:** Proteins, egg white, heat denaturation.

Zoubida Akkouche\*

Email<EMAIL_ADDRESS>
**Abstract**

**1. Introduction**

© 2012 Akkouche 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 cited.

Turkey, September 10-12, 2012

407 ISALS

## **6. Conclusion**

The result of study shown that, there is a significant impact for information technology also E-Commerce applied on foreign trade sector generally, in addition to total trade balance export, import was also positive impact on Agriculture import, export Egyptian Agriculture trade balance. Through the study of the information economy and E-commerce, we can make conclusion as followings:

#### **7. References**

## **Effect of Heat on Egg White Proteins**

Zoubida Akkouche\* , Lyes Aissat, Khodir Madani

Faculty of Nature and Life Sciences, 3BS Laboratory A. Mira University, Bejaia, Algeria \*Corresponding author, Tel.: +213<PHONE_NUMBER>; fax: +213 30 40 62 71 Email<EMAIL_ADDRESS>
#### **Abstract**

Thermal treatments applied to the egg white cause undesirable modifications of their physicochemical and functional properties. The goal of this study was to acquire some knowledge on the effect of heat on some physico-chemical properties of the albumen while applying different scales (temperature / time). The results show: a sigmoïdale evolution with negative slope of the transmittance, an irreversible loss of solubility. Native-Page of protein's albumen shows the apparition of several bands what denotes diversity of proteins in egg white. The comparison of these profiles dealt to different temperatures /20 min with those unprocessed, shows apparition of new bands and different relative mobility due to the formation of aggregates. Coagulation and/or precipitation of these proteins have been observed around 74°C/20 min.

**Keywords:** Proteins, egg white, heat denaturation.

## **1. Introduction**

Man has used bird eggs as food since prehistoric times [1, 2]. This reserve of proteins, lipids, vitamins and minerals is remarkable for varieties of nutrients it contains and their high nutritional value, due to a perfect balance of its constituents. Egg is always recognized as a food of high nutritional quality for humans [3, 4, 5, 6, 7]. Beyond their nutritional value, their primary function, namely the formation of a new individual, suggests that they contain many compounds essential to life, and therefore they constitute a major potential source of biological active molecules which interest the pharmaceutical, cosmetic and food [8, 9, 10].The food industry currently uses largely hen egg (especially egg white) as an ingredient, despite competition from increasingly strong dairy products. The origin of this interest is many functional properties of this latter (foaming and gelling properties in particular) [11].Egg white protein's are rich in essential amino acids, and possess excellent nutritional value, thus they have long been considered as reference proteins [12, 13, 14]. Nevertheless, the white gotten from breaking eggs is sensitive to contaminations of the environment [15, 16].To fight against these infections and protect the consumer, the heat treatment of food egg is often required to ensure microbial safety or to obtain desirable organoleptic attributes [17].The egg white is a hydrated medium, viscous, rich on protein, heat treatment would cause a distortion of its components, the non-enzymatic browning and coagulation of proteins [18, 19]. Polypeptide chains are unfolded and can form a gel or aggregates by the association of these molecules [20]. This aggregation leads to significant changes in the physico-chemical and functional properties of egg proteins [20, 21, 22, 23, 24].It is therefore very

© 2012 Akkouche 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 cited.

important that manufacturers in the industry provide an egg product that combines functionality and safety [25].To limit the damaging effects of heat treatment, some researches propose the addition of additives to increase protein stability to heat. Plant's extracts rich in polyphenols as caffeic acid, helps to increase the thermal stability of milk proteins to the heat [26]. Chemical structure of these substances makes them a highly developed ability to bind to all sorts of molecules, primarily proteins [27].

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**2.4. Polyacrylamide gel electrophoresis under native conditions (NATIVE-PAGE)**

and charge of each protein [30].

**3. Results and Discussion**

heat treatment at 650 nm.

**3.1. Turbidity**

The equipment used is the mini-plate vertical electrophoresis on polyacrylamide gel described by Laemmli (1970) [29]. The protein electrophoresis under non denaturing conditions is done to separate proteins of egg white as a result of an electric field on a separating gel with 7.5% of acrylamide and a staking gel with 5% of acrylamide. The rate of separation depends on the mass

Turbidity is inversely proportional to the transmittance. Figures 1 show a negative slope sigmoidal evolution of protein denaturation of albumen to increasing temperatures ranging from 56 ° C to 89 ° C during 3 min, 10 min and 20 min respectively, it has been measured immediately after

**Fig 1.** Effect of heat time on egg white turbidity, measures done immediately after heat.

could be considered as the phase of denaturation of proteins.

a factor of 2, what drives to the formation of small size aggregates.

the stage of denaturation and the one of aggregation.

• Stationary Phase 1: The transmittance is steady according to the temperature. This phase

• Downward Phase: Corresponds to a negative evolution of the transmittance according to temperature. It is about the transition phase between the stage of denaturation and the stage of aggregation. The slope of this part informs us on the speed of transition between

• Stationary Phase 2: This phase could correspond to the phase of aggregation of proteins. • Ascending Phase: All curves include a positive phase from 86°C. This reduction of trouble could be associated to the sedimentation of the aggregates formed or to the formation of the S-Ovalbumine of which the ray of Stock is weaker than the one of native protein of

This sigmoid with negative slope includes four distinct parts:

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The purpose of this study was to gain knowledge on the effect of heat on some properties of egg white proteins. This new knowledge will be useful in improving methods of pasteurization and sterilization to reduce the negative impact of heat on technological properties of egg white.

## **2. Materials and methods**

#### **2.1. Preparation of egg white**

After washing and cleaning of eggs bought in trade, they are carefully broken and the white and yolk separated, taking the precaution of removing chalazae. The pH of the albumen is measured immediately using a pH meter (Hanna Instruments, Microprocessor pH211 pH Meter); it is equal to 9.45 ± 0.02.

The volume of egg white is measured using a test-tube and then adjusted with the buffer solution Tris-HCl (20 mM pH 8.2) to obtain a dilution solution of 1:200.

A gentle stirring for 10 minutes is done on the samples, followed by filtration with a strip agase. Identical volumes were transferred into tubes. After heat treatment in a water bath thermostated (Memertt) under continuous agitation at temperatures of 56 ° C to 89 ° C with a step of 3 ° C for 3 min ,10 min and 20 min, the tubes were immediately immersed in an ice bath for 1 minute to stop the denaturation process [16,24].

#### **2.2. Measure of transmittance**

It consists in measuring the transmittance of the egg white processed relative to that of untreated; the latter is used to bring back the turbidity at 0 (which corresponds to a transmittance of 100%). This measure is performed at a wavelength of 650 nm [24], immediately after heat treatment and after 24 hours of storage at 4 ° C.

#### **2.3. Determination of protein solubility**

The treated samples were centrifuged at 20000 g for 20 min at 4 ° C [24]. The proteins of the supernatant were measured by the Bradford method [28]. Solubility S (%) of proteins is expressed relative to an untreated white using the following formula:

$$\text{S\%} = \frac{\text{Concentration of proteins in supernatural treated}}{\text{Concentration of proteins in supernatural untreated}}$$

The measurements are carried out immediately after the heat and after 24 hours of storage at 4 ° C.

#### **2.4. Polyacrylamide gel electrophoresis under native conditions (NATIVE-PAGE)**

The equipment used is the mini-plate vertical electrophoresis on polyacrylamide gel described by Laemmli (1970) [29]. The protein electrophoresis under non denaturing conditions is done to separate proteins of egg white as a result of an electric field on a separating gel with 7.5% of acrylamide and a staking gel with 5% of acrylamide. The rate of separation depends on the mass and charge of each protein [30].

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

#### **3.1. Turbidity**

Turbidity is inversely proportional to the transmittance. Figures 1 show a negative slope sigmoidal evolution of protein denaturation of albumen to increasing temperatures ranging from 56 ° C to 89 ° C during 3 min, 10 min and 20 min respectively, it has been measured immediately after heat treatment at 650 nm.

**Fig 1.** Effect of heat time on egg white turbidity, measures done immediately after heat.

This sigmoid with negative slope includes four distinct parts:

Statistical analysis reveals that the percentage of transmittance measured immediately and after 24 hours storage at 4 ° C of heat change over time was significant (P <0.05) and that the disorder is less important at 3 min than 10 min and 20 min respectively. So while extending heat, the trouble appears rapidly (lower temperature) ;for transmittance measured immediately after treatment, the trouble appears from 59°C at 20 min. whereas at 3 min and 10 min, it appears respectively at 68°C and 65°C.

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ity in the range of lower temperatures (56-71° C), could be due to denaturation and aggregation

Figures 3 and 4 show the electrophoretic patterns on polyacrylamide gel (7.5%) in native condi-

89°C.

On the first gel (figure 3), all samples are similar to the control; but ovotransferrin band intensity decreases from 59°C, which could be due to its gelation due to its heat-sensitivity. As the highest temperature here is 71°C, we can conclude that its effect on the structure of the egg white proteins is minimal-or at least it does not cause major changes in its structure; also denaturation protein phase cannot be observed on a Blue Native gel. In the second gel (figure 4),, high temperatures are clearly a major effect because the proteins all migrated to a higher position, suggesting an aggregation-resistant electrophoresis conditions. The comparison between the two gels suggests that under the chosen conditions, coagulation and /or precipitation begins to be observed around

Egg products are used as ingredients in many food sectors for their techno-unique feature. Stabilization treatments applied to egg white provide good control of hygiene but also induce an alteration of functional properties. Indeed, when egg white is subjected to heat, its globular proteins are prone to changes in structure and conformation. Depending on the extent of the temperature and duration of the treatment, these changes can range from denaturation at the gelation or coagulation. Our study shows effect of heat on some physico-chemical properties of egg white proteins such a sigmoidal evolution of transmittance and an irreversible loss of solubility. Analysis of electrophoretic profiles of native proteins heated at different temperatures, shows appearance of several bands, indicating diversity of proteins in egg white. The comparison of these profiles with those who did not undergo any heat shows appearance of new bands and different relative mobility due to the formation of protein aggregates. Coagulation and / or precipitation

of egg white proteins around 74°C/20 min were observed.

of egg white protein more sensitive to heat, such as ovotransferrin [16, 24, 31].

tions of egg white proteins after heat during 20 min.

**Fig 3.** Native-Page of albumen heated during 20 min. A: control (Oval, Ovot, Lys) 1mg/ml, B: unheated white, C: 56°C, D: 59°C, E: 62°C,

**3.3. Native - PAGE**

F: 65°C, G: 68°C, H: 71°C.

74°C.

**4. Conclusion**

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**Fig 4.** Native-Page of albumen heated during 20 min. A: 74°C, B: 77°C, C: 80°C, D: 83°C, E: 86°C, F:

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Student test indicates no significant differences between the transmittance measured immediately after heat and after 24 hours storage at 4 ° C treated samples. So the phenomenon of protein denaturation in albumen; is irreversible and interactions occurring between them are covalent (disulfide bridge) and non covalent, (hydrophobic and electrostatic interactions).Statistical analysis reveals that the evolution of transmittance as a function of temperature is significantly different (P <0.05). In fixing the time of heat treatment, the temperature is increasing turbidity increases. This could be explained by protein aggregation most resistant to heat such as ovalbumin, which represents 54% of proteins in egg white [16, 24]. At temperatures understood between 55°C and 65°C, transmittance decrease could be explained by denaturation and aggregation of the most sensitive proteins to heat as the ovotransferrin (13% of proteins in white) and at temperatures more elevated (≥74C°), the fall of the transmittance could be due to the denaturation and aggregation of the most heat-resistant proteins such as ovalbumin .

#### **3.2. Solubility**

According to figure 2, the heat applied to solutions of egg white lead to irreversible loss of solubility for the three times studied as a function of temperature.

**Fig 2.** Effect of heat time on egg white solubility, measures done immediately after heat.

After heat during 20 min at 89 °C , only (23.44 ± 0.21) % soluble proteins remained, while after 10 min and 3 min at 89 °C (28.64 ± 0.4)% and (32.43 ± 0.27)%, respectively remained soluble. The strong decrease in solubility at higher temperatures (74-89 °C) is probably due to denaturation and aggregation of heat-resistant proteins such as ovalbumin [31]. While the weak loss in solubility in the range of lower temperatures (56-71° C), could be due to denaturation and aggregation of egg white protein more sensitive to heat, such as ovotransferrin [16, 24, 31].

#### **3.3. Native - PAGE**

Figures 3 and 4 show the electrophoretic patterns on polyacrylamide gel (7.5%) in native conditions of egg white proteins after heat during 20 min.

**Fig 3.** Native-Page of albumen heated during 20 min. A: control (Oval, Ovot, Lys) 1mg/ml, B: unheated white, C: 56°C, D: 59°C, E: 62°C, F: 65°C, G: 68°C, H: 71°C.

**Fig 4.** Native-Page of albumen heated during 20 min. A: 74°C, B: 77°C, C: 80°C, D: 83°C, E: 86°C, F: 89°C.

On the first gel (figure 3), all samples are similar to the control; but ovotransferrin band intensity decreases from 59°C, which could be due to its gelation due to its heat-sensitivity. As the highest temperature here is 71°C, we can conclude that its effect on the structure of the egg white proteins is minimal-or at least it does not cause major changes in its structure; also denaturation protein phase cannot be observed on a Blue Native gel. In the second gel (figure 4),, high temperatures are clearly a major effect because the proteins all migrated to a higher position, suggesting an aggregation-resistant electrophoresis conditions. The comparison between the two gels suggests that under the chosen conditions, coagulation and /or precipitation begins to be observed around 74°C.

## **4. Conclusion**

Egg products are used as ingredients in many food sectors for their techno-unique feature. Stabilization treatments applied to egg white provide good control of hygiene but also induce an alteration of functional properties. Indeed, when egg white is subjected to heat, its globular proteins are prone to changes in structure and conformation. Depending on the extent of the temperature and duration of the treatment, these changes can range from denaturation at the gelation or coagulation. Our study shows effect of heat on some physico-chemical properties of egg white proteins such a sigmoidal evolution of transmittance and an irreversible loss of solubility. Analysis of electrophoretic profiles of native proteins heated at different temperatures, shows appearance of several bands, indicating diversity of proteins in egg white. The comparison of these profiles with those who did not undergo any heat shows appearance of new bands and different relative mobility due to the formation of protein aggregates. Coagulation and / or precipitation of egg white proteins around 74°C/20 min were observed.

#### **5. References**

[1] C.Allemeersch. The ovoproduits in France. Veterinary doctorate thesis. Veterinary National school Of Aflort.1983; 70:1-151.

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[19] C .Sanchez, S .Fremont .Consequences of the thermal treatments and formulation on the structure

[20] M-S .Appavou. Survey of the influence of the temperature and the pressure on the structure and the dynamics of the inhibitor of the bovine pancreatic trypsine. A survey by diffusion of neutrons. Thesis of doctorate. University of Paris XI Orsay. Specialty: Biophysical. 2005; 1-228. [21] H .Neurath, HB .Bull .Denaturation and hydration of proteins. From the Division of Agricultural

[22] D .Lorient. Biochemical Modifications of the constituent food. Techniques of engineer.2009; 3400:

[23] ISL .Navizet. Modelling and analysis of the mechanical properties of the proteins. Thesis of

[24] I .Van der Plancken , A .Van Loey, ME .Hendrickx .Effect of heat-treatment one the physicochemical properties of egg white proteins: A kinetic study. Newspaper of Food Engineering.

[25] V .Lechevalier. Ciaisaillement, creation of interfaces and thermal treatment. Thesis of physicochemistry Doctorate and quality of the byproducts. School of life-Agro-health doctorate. 2005. [26] M-M .Filion. Improvement of the thermal stability of milk by modulation of the potential of oxydoréduction. Faculty of the Sciences of agriculture and food. University Laval, Quebec. 2006.

[27] E .Hagerman, L G .Butler .Protein precipitation Method to Quantitative and Determination of

[28] MM .Bradford. A rapid and sensory method to the quantification of microgram quantities of

[29] UK .Laemmli. Cleavage of structural proteins during the assembly of the head of T4 bacteriophage.

[30] GM .Walker .The Protein Protocols Handbook (second edition). SD Polyacrylmide Frost Electrophoresis of proteins. University of Hertfordshire, Hatfield, UK. 2002: 1-1103.

[31] C .Desert, C .Guérin-Dubiard, F .Nau, G .Jan, F .Valley, J .Mallard. Comparison of Defers Electophoretic Separation of Hen Egg White Proteins., School National Superior Agronomic of

protein utilizing the principle of protein-dye biding. *Anal Bioch*. 1976; 72: 248-254.

tannins. Newspaper of Agriculture. *Food Chem*. 1978; 26(4): 809-812.

and the allergenic of the food proteins, Direct Science. 2003; 43:13-20.

Biochemistry, University Minnesota,St, Paul. 1936: 519-527.

doctorate. Paris University 6 Pierre & Marie Curie. 2004.

1-20.

2006; 75: 316-326.

*Nature*. 1970; 227(259): 680-685.

Rennes, *Food Chem*. 2001 ; 49 :4553-4561.

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International Conference on Applied Life Sciences (ICALS2012)

**Assessment of Environmental Quality of**

**Structure: Multivariate and Graphical**

Sapto Purnomo Putroand Riche Hariyati

Prof. Soedharto, SH, Tembalang Campus, Semarang, Indonesia

**Approaches**

ity and sediment over time.

farming.

**1. Introduction**

**Abstract**

**Coastal Fishpond Areas Using Macrobenthic**

Department of Biology, Faculty of Mathematic and Natural Sciences Diponegoro University, Jl.

Environmental degradation that results in decreased quantity of farmed fish production is an issue that often arises in rapid aquaculture industry. This study aims to develop the method of environmental quality assessment of aquaculture using macrobenthic structure to ensure the sustainability of its activity. The research was conducted at three fish farming sites along coastal of Sayung, Demak Regency, Central Java, i.e. milkfish ponds, shrimp ponds, and mixture pond. Determination of the environmental quality of the farms was done by analyzing data and environmental parameters and macrobenthic abundance and biomass using multivariate and the graphical methods. The results of Principle Component Analysis (PCA) projected from an aquatic environment parameters showed no signs of grouping based on three types of ponds, but there are signs of grouping by time sampling, indicating fluctuations in physico-chemical conditions of waters over time. Based on the macrobenthic abundance, study sites were dominated by gastropods (97%), the rest of bivalves (2%) and polychaetes (1%). Results from ordination analysis, ABC curves and k-dominance showed no signs of clustering by types of pond, but between sampling times. This implies that multivariate and graphical methods can sensitively detect any environmental change, particularly changes in macrobenthic community, water qual-

**Keywords:** environmental quality, multivariate, graphical method, macrobenthic structure, fish

Macrobenthic animals are invertebrate animals that are relatively small and retained on sieve size of 500 m m and stayed at the bottom habitat by digging a hole in the substrate or sediment, either have home tube (tubicolous) and do not have the tube [1]. The animal has an important role in the formation of sedimentary habitats. These organisms can stimulate and improve the process of mineralization of organic matter and improve the exchange of particles in the boundary layer between water and sediments [2]. They play an important role in the food chain through the transfer of organic carbon back to the pelagic ecosystem [3]. Through mechanisms such as

> © 2012 Putro and Hariyati; 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 cited.

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**7. Conclusions**

In this work, a data augmentation framework for Artificial Generation of common cause Variability in SMT industrial assembling lines was proposed. The aim of the AGV module is to allow for a prompt application of monitoring procedures in new products for which extensive historical data is not available, without incurring in prohibitive rates of false alarms. The AGV module is based on process knowledge and codifies the dominant modes of common cause variation due to known physical phenomena. The proposed approach can be even implemented in the absence of an historical dataset, as long as there is accumulated information from related processes. This particular aspect was also covered in our analysis in this paper.

The data generated by the AGV module proved to reproduce well the long term variability of real process data. The critical issue of high false alarm rates was solved. On the other hand, we also report that the monitoring statistics show limited detection capabilities. This happens because the PCA model accounts for inter-lot variation, while the process will typically operate in localized regions at a given time. Furthermore, the sensitivity of the PCA monitoring scheme is also a ffected by the very large number of variables under monitoring.

Future work should therefore consider the application of the AGV module to other case studies. Furthermore, novel monitoring approaches should be development in order to account for the presence

of different lots (improve the sensitivity of the *T*2-statistic) and reduce the impact of irrelevant residuals when the number of monitored variables is very large (improve the sensitivity of the *Q*-statistic).

**Author Contributions:** T.J.R. and M.S.R. developed the methodology and wrote the paper; P.D. and C.M. provided the data and process knowledge. All authors have read and agreed to the published version of the manuscript.

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

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


*3.2. Analysis of Subjective Workload Scores*

Once the variable associated with reaction time had been discarded, the approach was repeated while considering the workload values recorded by the participants. A combined representation of the exercise design profile and superimposed subjective workload values was created.

Figure 4 presents a combined representation of the designed taskload profile and superimposes the workload values assessed by each participant.

The rationale behind the plots is the same as in the case of reaction time. The only difference is that, in this case, the secondary axis presents the workload values on a scale of 1 to 5.

In addition to the series identifying each of the participants, an additional series of data points has been included in the graphs. The values indicated with an orange star correspond to the mean values of the six participants in each of the moments where the workload is evaluated. As can be seen, in general, the values evaluated by each of the participants are closer to the mean in the first evaluations of the exercises and in the final minutes. In the middle minutes of the exercise and in the intermediate minutes of the taskload cycles, the values assessed by the participants are more dispersed due to the different actions implemented by the participants, especially in the conflict resolution processes.

**Figure 4.** Combined representation of the designed taskload profile of the exercises together with subjective workload assessments for the six participants. The first row of graphs presents Exercise 1 on the left and Exercise 2 on the right. The second row presents the data from Exercise 3 on the left and Exercise 4 on the right.

Unlike what happened in the case of the reaction time variable, the workload values evolve throughout the exercise. The initial hypothesis in this case is that the highest subjective workload values are reached in minutes when the designed taskload is highest. However, in general, this relationship is not observed.

The fact that workload values evolve over the course of the exercise makes them a variable of interest in the study. After the combined graph analysis, the results obtained are as follows:

• The general tendency of the participants is to assess the highest workload values out of phase with the designed taskload. This is particularly clear in the graphs of Exercise 1 and Exercise 3. The reason for this is that events that have a higher value of taskload associated with them appear to have a longer duration than in the designed taskload profile. Therefore, participants must implement actions to deal with these events for longer periods of time. Depending on the actions selected by each participant, especially in conflict resolution processes, the taskloads of more complex events can influence the workload of ATCOs for longer periods of time.

All of the above leads to the conclusion that the designed taskload is not a good reference. This profile was unique for each of the exercises. However, the decision-making process of each ATCO and the conflict resolution strategies used are specific to each controller.

Therefore, in order to explain the workload values evaluated by each of them, it is necessary to compare these values with a specific taskload profile for each participant and each exercise.

Analysis of the graphs in Figure 4 leads to the conclusion that the actual taskload experienced by each controller was different from the designed taskload. Therefore, it is necessary to determine the actual events that took place in the simulation for each participant so that a taskload reference representative of what actually happened may be obtained.

To find out which events took place during the simulations and at what time, the radar screen recordings of each controller were examined. The steps in the methodology to obtain the actual profile were the following:

	- a. The first event is the change of flight level. Some participants, upon identifying that two aircraft were about to encounter a conflict, would anticipate the situation and change the flight level of one of the aircraft before being alerted by the conflict detection tool. This event was assigned a base score of 2 points.
	- b. The second event is the change of speed. As in the previous case, some participants detected in advance that an overtaking conflict was going to occur. In this case, some participants considered that the easiest way to resolve it was to change the speed of one of the aircraft involved. Since the taskload induced is similar to that of flight level changes, this event was also scored with a base value of 2 points.