Ecotoxicity of glyphosate-based herbicide (GBH) to aquatic plants worldwide.
\r\n\tThe book will aim to cover also the synthesis and optical properties of noble metal nanostructures, patterned surfaces, continuous or grated surfaces, and devices. This book intends to provide the reader with a comprehensive overview of the current state-of-the-art in plasmonic microscopy, surface-enhanced spectroscopic properties, such as Raman scattering or fluorescence, as well developments in techniques such as surface plasmon resonance and near-field scanning optical microscopy but also data transmission, plasmonic light modulators, and optoplasmonic networks.
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He obtained a master's degree in Photonics from the Technical University of Applied Sciences Wildau in 2013. In 2017, he received his PhD in Industrial Engineering from the Università degli Studi di Roma 'Tor Vergata” for his work in the field of integrated photonics for communication and sensing. 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Every day, we are inundated with information about various leaders worldwide who have taken charge and solved yet another global problem in the right way. Solving any problem, unfortunately, can only restore the equilibrium that existed before the problem occurred. There is a lack of information on how crises arising from dynamic changes and emerging risks in the external environment can create favorable conditions for other leaders who see these as an opportunity to seek the path of innovation, develop their potential and transform into a more favorable outcome.
The positive effects of quality management have long been established in the scientific literature. If we compile a basic list of these effects, it would undoubtedly include cost reductions, better relationships with suppliers and customers, just-in-time deliveries, reduced waste, increased added value for customers, and better conditions for developing market potential. These benefits can also be applied to quality management in logistics.
Logistics is a key activity for any business idea. The challenges of market change require continuous improvement of supply chain performance and, in this process, quality improvement through risk analysis is important. Risk is always associated with uncertainty, therefore, to reach a new improved level of logistics services, processes must be managed and analyzed with appropriate methods. Quality management is based on conditional variables that are determined by the changing market conditions in a specific time span. Modern logistics firms are increasingly focused on improving supply chain performance, where improvement with quality management is the primary mechanism for achievement. This study seeks to identify the ways to achieve better business process performance in logistics services through the application of basic quality and risk management tools. There is no single correct approach or the best tool for quality management in logistics. It is necessary to find an approach that incorporates contingencies and the current market situation and to analyze and identify an effective service improvement strategy applicable to the changing circumstances. The research approach is to look for the synergistic effect of quality and risk management by applying appropriate tools for their integration based on the definition of the applicable conditional variables in the specific existing situation.
In late 2019, a new type of viral disease called coronavirus (COVID-19) was discovered in the provincial capital of Hubei [1, 2, 3] and within a few months, its spread spanned the globe. Many researchers support the view that urbanization and increasing population density are major catalysts for the spread of COVID-19 [3, 4, 5]. The outbreak of the COVID-19 pandemic has forced authorities worldwide to introduce restrictions and bans on the movement of people and goods throughout the supply chain. In response to these challenges, most countries have announced national travel and transport bans to certain regions [6]. The introduction of restrictions has become a huge challenge for all logistics stakeholders [2, 7], which include producers, municipal authorities, inspection bodies, medical practitioners, household purchasing decision-makers, managers deciding on the organization of order fulfillment in the supply chain, and many others [8, 9, 10]. The constraints and longer vehicle dwell times at border controls and entry and exit points in the country of delivery have necessitated an increase in shipping costs and prevented the necessary quantities of essential goods from being secured and stock reserves replenished. One of the conditions for quality management in logistics—those goods arrive on time—became an unenforceable condition for deliveries from locations where COVID-19 restrictions were imposed.
Quality management decisions in logistics activities during this period were driven by the importance of the role of logistics in supply management and the constraints introduced by government authorities. During a pandemic, stockpiling essentials and personal protective equipment for the population is a difficult challenge for the entire logistics chain [2, 11, 12, 13, 14]. The threat of the rapid spread of disease requires logistics organizations to respond quickly to ensure the seamless supply of personal protective equipment, disinfectants, medicines, medical supplies, essential foods, among others [2, 3, 4, 15, 16].
The constraints create risk-laden conditions managing the quality of logistics processes and making effective decisions related to capacity, choice, and use of means of transport, and compromise the performance of the supply chain processes [17, 18, 19, 20, 21].
The high population density in large population centers and living close to large retail chains have limited the ability to supply less accessible and remote areas with the same resources. A cost-effective method of redistribution through logistics was not implemented in the short term. The effort to limit the spread of the virus has created unaffordable conditions for the implementation of basic logistics activities and services. Household decision-makers reacted quickly to the changed conditions and stocked personal protective equipment and invested in commodities that had a limited shelf life, which required them to be discarded at a later stage. Fear of the shortage of goods anticipated due to the restrictions on the movement of vehicles created panic in the population [22, 23, 24] and, consequently, a glut of goods. This process triggered a new wave of shortages throughout the supply chain caused by the irregularity of consumption compared to the previous period and the depletion of goods due to overstocking [16, 25]. Households did not make purchase decisions based on their actual and expected consumption for future time periods.
The pandemic has forced households to increase their online purchases and reduce their visits to retail outlets [26, 27, 28], even for necessities and everyday purchases. Traditional order fulfillment approaches proved inadequate for the changed market conditions as consumers demanded that logistics service providers fulfill their orders within the day or within a few hours [29]. Some retail logistics chains have proved unprepared to provide their customers with full online real-time delivery traceability and prioritize task fulfillment by optimizing the solution of the same tasks on the fly. The introduction of various supply chain applications has allowed the most proactive in the industry to perform full supply chain traceability and help share information quickly with customers when deliveries are delayed.
The surge in essential goods has hampered all logistics operations in delivering on time [30, 31, 32] and resulted in an inability to meet planned and agreed quantities between the business partners managing them.
The COVID-19 pandemic forced rapid changes in logistics development and catalyzed the creation of new business models for query management. The path to adapt to the new normal requires the introduction of more automated processes and technologies to facilitate the processing of requests coming in via e-commerce [33]. There is a requirement to introduce a new, rethought supply chain business approach based on trust, value-added processes, and tolerance when contractual terms cannot be met because of restrictions. To achieve compliant logistics service performance is increasingly impossible without coordination between all stakeholders and real-time decision-making. Dynamic changes in the environment have become a major factor for quality process performance requiring a high degree of synchronization and collaboration [34, 35, 36, 37].
These developments have positively impacted inventory turnover but caused a boom in order fulfillment wherein quality control processes for performance management have been limited and, in some cases, even neglected. Reduced process controls have worsened the performance quality of set execution procedures. Quality management in logistics is concerned with delivering products on time, in the required quantity, and at the location specified by the customer. Due to the irregularity of deliveries resulting from the above reasons, warehouse space proved insufficient to cover the restocking of goods for increased consumption. The inadequacy of the existing infrastructure to conduct logistics operations, warehousing bottlenecks, and the breakdown of agreements between stakeholders on the supply and distribution of essential food and medical supplies are among the most debated topics in the literature [38, 39].
The increased frequency of emergency deliveries has necessitated the commitment of additional resources for the implementation of logistics processes, which are not always available during crisis situations and, therefore, has hampered the efficiency of processes and deteriorated the quality of their implementation. Accordingly, planned audits of the logistics quality management systems were not carried out and, in many cases, these were not carried out in their entirety and according to the planned measures. This created the conditions for impaired decision-making that ignored one of the basic data-driven principles of logistics quality management and caused confusion and delays in meeting agreed and contracted delivery quantities. Overstocking of products has also deteriorated the quality of value-added services, such as additional picking, repacking, and labeling. Overstocking of warehouse space has significantly impaired the implementation of replenishment policies as stock capacity is limited. The overloading of warehouse staff has delayed the decision-making about time schedules and workforce allocation.
Maintaining the quality of logistics services during a pandemic requires making the right and meaningful efforts to address the challenges posed by a dynamic changing environment. The application of a multidisciplinary approach and the coordination between all stakeholders actively involved in logistics processes have the potential to limit quality deterioration and other inconsistencies and are, perhaps, the only prerequisite for the success of these activities. Lack of coordination creates uncertainty in the fulfillment of customer requirements and implementation of planned quality management activities in logistics.
The risk of quality deterioration in logistics services increases manifold due to inefficient communication with customers in the event of delivery-related difficulties and reverse logistics of goods returned due to delays. Quality management in logistics has the potential to help ensure the proper distribution of essential goods during the period of retrenchment.
Some factors affecting supply chain management operations during a pandemic [40, 41, 42], have been the subject of many scientific publications and have been studied by several authors [43]. Quality assurance in logistics processes creates the prerequisites of a positive image for logistics brands to achieve a lasting trend of customer loyalty and competitive advantage [44, 45]. During the COVID-19 crisis, quality assurance was mainly related to the safety of supply and the reliability of supply chains.
Therefore, to build the resilience of logistics processes in the face of dynamic environmental changes and emerging supply security risks and threats, organizations need to more clearly and accurately analyze the factors that help establish and ensure logistics service quality and customer satisfaction.
The study identifies the key factors that help to make the right logistics decisions for quality management in times of risk and dynamic changes in the environment. During a crisis from the external environment, the results show that quality management is introduced after the fact and is mainly related to corrective rather than preventive actions. This calls for a more in-depth investigation and concrete solutions for quality management through risk management in logistics, which is the main objective of the analyses in the different chapters of this study.
Replace the entirety of this text with the introduction to your chapter. The introduction section should provide a context for your manuscript and should be numbered as the first heading. When preparing the introduction, please bear in mind that some readers will not be experts in your field of research.
Considering the rapid changes in market conditions worldwide and as a result of the measures taken to physically distance and restrict access to ports due to the COVID-19 pandemic, there is no active physical communication between the user and the logistics service provider. Well-known quality assessment methods in most cases provide for such a communication and survey of user expectations. Some of the variables studied in these methods assess the logistics environment and evaluate the customers’ direct communication at the physical level of the employees performing the services (e.g. uniform and appearance).
This chapter presents some of the main and most popular methods, their key parameters, advantages, and disadvantages in their application for discussion. The most applicable models that have the potential to be used for quality assessment, in particular for the assessment of logistics services, are studied.
The study of the different service quality management models aims to assess their suitability and adequacy or need for improvement. Different standards and good practices for quality management have been practically identified, which, of course, also have different objectives. This makes their application difficult because often no clear distinction is made between a specification (which sets out requirements) and codes of good practice (recommending a course of action) in their use.
Customers have been found to rate the quality of service whether it is good or poor [46, 47, 48, 49, 50, 51]. Scholars opine that service quality is determined by the differences between expectations and perception of the service received [52, 53, 54]. It is undisputed that service quality is essential. What happens when the quality of logistics services is higher than expected and how to prevent the negative impact of various risk factors that could compromise high quality? Some researchers believe that customer satisfaction with the quality of certain services will determine the failure or success of a company [44, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64]. The main problem with measuring the quality of any service is related to its inherent characteristics: intangibility [65, 66], heterogeneity, and indivisibility. Accordingly, quality cannot be measured before the service is provided to the customer, unlike goods whose quality can be measured at any time [67]. Researchers agree that measuring the level of service quality is difficult but they have conflicting views on how logistics organizations overcome this difficulty in practice, regardless of what assessment methodology is used. Some researchers have segmented the market based on different types of logistics services [68, 69], some have studied the level of logistics services by different economic sectors [70], and others have studied the level of quality by geographical market segmentation, such as Vietnam [48], India [71], and Serbia [72].
Quality management activities are related to compliance with many standardization documents—various technical specifications, manuals, process management codes, and guidelines by various international organizations [73]. An important difference between standards and other documents is the level of consensus required for their approval. Standards and technical specifications contain requirements to which processes or services must conform (normative requirements), whereas other types of documents contain only recommendations. The main problem associated with quality assessment in the service area is the contradiction between the customers’ and service providers’ perceptions of quality service. Customers want to receive services of the highest quality according to their perceptions of excellent quality and service providers are looking for solutions that match their requirements and expectations.
Logistics firms have long viewed logistics not just as an area for cost improvement, but as a key source of competitive advantage within the firm’s overall marketing efforts. The quality performance of all these processes requires the integration of different activities and compliance control for pre-set criteria.
Researchers note that there are some basic and critically important indicators for the perception of consistent logistics service quality: timeliness [69, 74, 75, 76, 77], availability [78], and order compliance.
Although many researchers support the view that logistics services complement the marketing efforts of sales organizations, there is a lack of well-founded evidence on the meaning of logistics service quality and its essential attributes for customer evaluation. Little research has been done to identify the differences in quality assessment attributes for different market segments and, consequently, how these attributes change under the impact of risks from the external environment. There is also insufficient research on the impact of dynamic environmental changes on quality management models and concepts in logistics in particular. The different attributes for assessing the quality of logistics services differ for each market segment and they are radically different for services that customers request over the Internet and through direct contact. This suggests that firms need to adapt their logistics services to changes in the external environment and customer orientation primarily toward Internet commerce during the pandemic.
Adding unobservable attributes that are essential to customers’ perceived value of logistics services to the traditionally measured set of operational attributes to evaluate services.
Quality management involves the management of processes in a unified system. Logistics processes require efforts to be focused on the delivery of material flows by managing the selection and supplier performance improvement to just-in-time delivery of goods and customer service.
When measuring and analyzing quality in logistics, the first step is to determine the appropriate attributes for their corresponding level. Delivery time is the most used metric. There is no need for evidence confirming delivery delays as the most frequent cause of deterioration in the expected level of quality and customer dissatisfaction. Timeliness of delivery is cited by many researchers as the most important indicator for measuring quality [79, 80, 81, 82, 83, 84]. Among the most important quality indicators in logistics, the following have been mentioned by various sources: the quantity of orders fulfilled (matching the requested items), the quantity of orders processed per unit time, timely and complete product delivery information given to customers, personal contact with staff, the accuracy of fulfilled orders, the status of products received in orders, and prompt and timely response to order discrepancies. The impact of the logistics firm’s corporate image, the ability to handle non-standard logistics services, and the ability to technically execute the service are examined as additional indicators to assess quality.
These metrics have priorities differing by industry, such as when logistics is part of the functional departments of manufacturing companies the metrics are related to on-time delivery, error-free delivery, and lead time. In transport logistics, the quality assessment attributes are mainly: reliability of delivery, assurance of performance, payment options, and transfer of insurance and other risks. An interesting indicator that has become increasingly important in recent years is the possibility of reverse logistics and buyback.
Logistics service quality indicators are associated with several possible attributes:
Indicators related to export and import procedures. Nordås and Grosso have an interesting study on the impact of lengthy export and import procedures on logistics processes and the creation of strict trade barriers [97]
Indicators related to lead time:
Process performance indicators:
Quality of feedback and personal contact with employees in the logistics company [80, 111]
Conditions in the customer request related to minimum quantity or promotional offer [78]
Accuracy of the prepared request in accordance with the customer’s preferences [112]
The use, acceptance, and exchange of information with customers [78, 113, 114, 115]
The procedures for the preparation of requests [116]
Increase the number of requests sent by customers [117, 118]
Quality of requests related to promotional items and value of the total requested quantity [74, 119]
Speed and authority in handling discrepancies in the preparation of requests [111]
Customer satisfaction [54, 67, 120, 121, 122, 123]. Customer satisfaction depends on many factors related to the perceived quality of services provided, the emotional state of customers, social interaction, customer experience, and other specific subjective factors. Several researchers support the view that customer satisfaction with service quality is not an objective assessment of the actual situation but an emotional factor. Customer satisfaction is primarily associated with the evaluation of process outcomes and can be viewed as a positive evaluation of the service by the customer (Figure 1).
Key indicators for measuring logistics service quality.
The literature describes many quality assessment methods that can be used to help service providers understand whether they are partially or fully meeting client requirements. The differences in methods are based on different criteria for assessing the mismatch between clients’ expectations of the service and their perception of the service consumed. It is generalizable about all methods that to conduct them, information from the customers’ service evaluation needs to be analyzed, which means that customers are actively involved in the process. How can prospective customers who have not yet received the service evaluate it? These surveys, therefore, involve customers who have already received services. The whole market is relevant for the logistics organization, specifically, why did the other customers in logistics choose the competitor’s company? Another question that arises is how the opinion of those who do not use logistics companies but build their own logistics departments within production sites can be investigated.
The Grönroos model surveys a sample of business managers who are users of an existing and used service to test its perceived quality [46, 124]. Grönroos’ study supports the view that quality indicators are interrelated and there is a causal relationship between them. Quality assessment under this model compares the customer’s expected and perceived quality of service to measure user satisfaction. Grönroos identifies three components of service quality, namely: technical quality; functional quality; and image quality [124] (Figure 2).
Components of the Grönroos model (adapted [
The main criticism of Grönroos model is that this model does not assign different weighting factors to the overall evaluation of the service delivered, but only emphasizes the importance of functional quality. This critical flaw prevents the result of the measurement by the model to be an objective evaluation with practical application, but only stating the factors are interrelated. Several researchers have studied the method [125] and others have explored its practical application [126, 127]. Some researchers have criticized the method, empirically proving that there is no causal relationship between technical quality, image, and perceived quality and the relationships between these three aspects of quality are not significant [128]. To date, the paper describing the method has been cited 12,219 times in other scientific publications according to the Google Science website.
The European Customer Satisfaction Index (EPSI) model, first introduced in 1999 as a method for modeling and predicting customer satisfaction, has been extensively studied by many researchers in the field of quality management [129, 130, 131, 132, 133, 134]. This method is based on the seven indices of the EPSI summary index. Sweden was the first country to introduce the index as the main method to measure customer satisfaction in different industries (SCSB). In 1994, the method was adapted to the American Customer Satisfaction Index (ACSI) [134, 135]. A few years later, after several publications and recommendations from the EOQ (European Organization for Quality) and EFQM (European Foundation for Quality Management), the EPSI was established as the main tool for measuring customer satisfaction in Europe [136, 137, 138]. When customer satisfaction is measured through surveys, several key issues arise, the main one being the collection and aggregation of survey data.
This issue is defined more clearly and determined by the structure and content of the satisfaction survey questionnaire and the method by which the sample size will be determined.
The Logistics Performance Index (LPI) is an indicator that measures the performance of retail supply chains or logistics performance and is produced by the World Bank every 2 years. Comparative data on the composite indicators of the index for the last 5 years are presented in Figure 3. The data defining the index was collected through a survey of international academic institutions, organizations, and individuals active in the global logistics market. Respondents assign scores by rating the result on a scale from 1 (worst) to 5 (best). Each of the indicators measured relates to an assessment of the overall level of skills and quality of logistics services and the scores are averaged across all respondents.
Logistics performance index. Source: Compiled from World Bank data (database: LPI), last updated: 10/29/2019, available at:
Trade and transport have been found to stimulate economic development and improve national competitiveness. The index allows these developments to be compared against the same reliable logistical criteria. The World Bank’s Logistics Performance Index (LPI) is this unique comparative tool. For example, the aggregated Logistics Efficiency Index (2018) ranks Bulgaria 52 out of 160 countries with an average score of 3.03. Some of the examined parameters by year, assessed on a 5-point rating scale, are presented in Figure 3.
The competence indicator of those engaged in logistics services at the national level throughout the reporting period has little variation in the scores awarded by the experts. The report, published after the survey, examined the direct correlation between deteriorating service quality indicators as a trade barrier and foreign direct investment in the sector [139].
The assessment of the logistics quality level must, of course, be evaluated by each market segment and, as a prerequisite, customer satisfaction must be surveyed. Negative assessments of quality are, in most cases, caused by risks that have not been sufficiently managed, for which a root cause analysis is necessary. Opportunities exist to assess user satisfaction and take prompt corrective action in cases with understated ratings. Quality is defined as “the degree to which a set of intrinsic characteristics of an object satisfy requirements” and a necessary condition for measuring quality is to define these requirements.
The requirements for logistics services originate from not only customers but also legislation applicable to the activity, stakeholders, and many others. The task is to ensure compliance with quality requirements and eliminate or minimize the impact of risks from logistics services or processes.
The need to integrate a multitude of activities requires quality management to focus on rapid change and flexibility in addressing the risks for the logistics organization to adapt to rapidly changing external circumstances.
In the last decade, the SERVQUAL model has been the most popular method for assessing service quality, which was first stated by Parasuraman, Zeithaml, and Berry in 1985 [67]. One of their articles, of only 14 pages, has nearly 6000 references to date [120] and the original article of 9 pages has nearly 37,000 references [67], while the improved methodology 3 years later has 40,000 [121].
The SERVQUAL model is a framework for service management [140] incorporating the core tasks of quality management with a focus on service quality. The main purpose of the SERVQUAL model is the comparison between perceptions and expectations that determine quality assessment and customer satisfaction.
The issue at hand is to measure customer expectations of logistics services given that the manifestation of these expectations is directly dependent on how customers interpret the environmental factors influencing the formation of expectations. The problems are exacerbated by the fact that some influencing factors may be within the control of the logistics firm, and therefore predictable, but other factors, such as psychological factors, are directly dependent on the customers themselves. Thus, logistics companies are challenged to ensure a clearer picture of their customers’ expectations, which can be the basis to chart a concrete path toward meeting it more fully. The SERVQUAL model may be applied to achieve this goal, which refers to the following three main postulates (Figure 4).
Main postulates of the SERVQUAL model source: [
The main analyses to be performed by logistics firms when applying the model are shown in Figure 5.
CAP analyses of the SERVQUAL model in logistics services source: Adapted [
The model used to conduct the main analyses and which can be used by logistics companies are shown in Figure 6.
SERVQUAL model processes in logistics services. Source: Adapted from Parasuraman, Zeithaml, Berry [
There are many different views on quality management in logistics. Perceptions of consistent quality in logistics services are quite different from the perspective of the activity manager and customer. Too often the quality criteria of the customer are quite different from those of those providing the logistics service. These reasons necessitate an exploration of different perspectives and appropriate means and methods to resolve the differences in these perceptions. Defining service quality is even more difficult than product quality. The main criteria for service quality are reliability and individual treatment by the organization providing them. To achieve compliance with these indicators, all employees must be involved in its management to conduct the activity, which meets the customer’s expectations. Unfortunately, there are fundamental differences between the ways that different departments of an organization perceive quality. The main reason for the emergence of non-conforming logistics processes is precisely this difference in perceptions of conforming quality as well as underestimation of its importance to the prosperity of the company.
The ways to solve these problems are related to effective communication and smoothing the differences between the different functional areas to achieve a service that meets the customer’s needs. The task becomes more complex when you add the impact of external and internal environmental changes on the matching quality criteria for a particular supply, service, or process by regulators and stakeholders.
Risk management in logistics and supply chains has been studied by many researchers. Their results confirm that mitigation opportunities depend on multiple interrelated factors and each of them can be the cause of drastic risk reduction if used wisely.
Most studies agree that adequate planning for the diversity of service offerings is the critical causal factor and can unlock a series of risk mitigation responses throughout the supply chain [141, 142, 143, 144]. The next most important cause is the flexibility of supply contracts [142, 145, 146, 147, 148].
These major risks can be managed if, based on the cause-effect relationships between different factors, work is done to reduce the overall impact of the risk. Risk management actions make it possible for the support function of logistics services to remain in the background and become a crucial factor for the market success of the business operation. According to Fuchs and Wohinz [149], it is also necessary to clarify that research does not often clearly distinguish between the concepts of supply chain-wide risks and logistics risks.
Risks are described as unplanned events in the scientific literature, which does not imply a lack of preparation to manage them. For supply chains, logistics risks are related to the main service objectives: the lack of appropriate and customer-required goods, in the required delivery time, in the specified location, in the required quality.
Quality management activities and their associated risks identify the likelihood of risks before they occur and may, accordingly, affect the conditional allocation of losses in advance. The costs of remediation can be summarized in three main groups:
Financial costs: once the non-conformity has been identified and action is taken to rectify it, the logistics organization must cover any damages to the customer. Studies find that the cost of correcting non-conformities is greater than what could have been spent on prevention in the planning process. The costs of recalling products and covering all reverse logistics activities are often excluded from the selling price of logistics services and are covered by the contingency and extraordinary costs line item.
Survival costs: in most cases, inconsistencies in processes entail, at least, legal consequences. Larger inconsistencies can be a challenge to business survival as restitution damages can drag a logistics organization into insolvency.
Reputation costs: inconsistencies in logistics operations and processes will, in most cases, result in customer backlash and a reduction in profit to cover losses from a reduction in planned sales.
Risk minimization and opportunity identification activities can be carried out in four phases:
Plan risk management actions by setting the risk management framework.
Implement actions to address risks in each logistics process.
Monitor and analyze performance management actions to minimize risks and uncover opportunities by monitoring and analyzing the strategic risk management framework.
Continuous improvement.
Logistics risks are generally associated with disruption of the planned material flow for any period [150, 151, 152]. Unexpected events or the reasons for their occurrence affect and hinder the supply of material flows of goods at an acceptable price.
Risk management in logistics is needed as an alternative to commercial insurance in cases where insurance coverage is limited or very costly. Preventive measures to manage risks are a form of insurance applied to assumed but unspecified events for which the probabilities and financial consequences are unknown. Various authors have studied the classification of the causes of supply chain risks in particular logistics, such as Essaber and Fuchs, whose work is one of the most generalized [149, 153, 154]. Based on these studies, four main causes of risk in logistics are outlined as shown in Figure 7.
Causes of risks in logistics services.
Operational risks are caused in the normal course of logistics operations and are often related to disruptions in the supply chain of the goods to be transported and stored [155, 156, 157, 158, 159]. This risk creates insurmountable conditions that make the delivery of the goods in the volume and assortment desired by the customer impossible.
Operational risks can be caused by the malfunction or insufficiency of warehouse equipment and transport vehicles and also by external factors, such as incorrect choice of transport of the supplier of goods, excessive complexity in transport routes, failure of transport infrastructure, incorrect choice of transport packaging of supplies, failures, malfunctions, and accidents during the delivery of cargo [155, 156, 157, 158].
Financial risks have been studied in many aspects along with different ways to overcome them by researchers who consider several main causes, such as poor cash flow management, investments in inappropriate time periods under restrictive conditions, inflating costs for the use of investments, and falling out of interest rates that do not meet market conditions, poor management of liabilities [159]. Financial risks adversely affect the firm’s overall operations and financial stability. These risks are often related to inadequate management of cash flows between organizations, excessive investments to enter new market segments, mismanagement or lack of coordination between the repayment of liabilities and expected receivables, the movement of cash between subsidiaries and related companies, sudden changes in tariff rates and tax legislation in the country of the raw material supplier.
Stakeholder-related risks stem from a deteriorating collaboration between supply chain partners. Environmental risks in logistics have the potential to negatively impact the environment [160, 161]. Stakeholder risks arise from supply chain disruption resulting from unanticipated rapid changes in the political environment and regulations, such as changes in tax rates, bans imposed by decree, embargoes, government bans and seizures, litigation, hacking, theft, and many others [162, 163, 164, 165].
Risks associated with unexpected events arise primarily from risks posed by force majeure (e.g. natural disasters; international terrorist actions; economic crises; and port, terminal, and land border closures and strikes). The severity of the risk is calculated by the outcome of the adverse event, which often affects the financial stability of the company and its ability to deliver services, the timeliness of delivery of goods, and impairs the quality of performance of commitments made [166]. Another type of risk is the increasing degree of cooperation between supply chain partners which can make it difficult to take quick and adequate decisions due to the different interests and priorities of the partners involved. Risks that lead to a breakdown in performance can also be caused by the bankruptcy of a supplier, deterioration of quality control by the supplier, a series of planning errors, and overly complex automated decision-making systems for delivery routes. Another risk that is difficult to predict relates to the failure of supply chain partners to meet their commitments and/or agreed terms.
Although many researchers support the view that logistics services complement the marketing efforts of sales organizations, there is a lack of well-founded evidence on the meaning of logistics service quality and its essential attributes for customer evaluation. Adding unobservable attributes that are essential to customers’ perceived value of logistics services to the traditionally measured set of operational attributes to evaluate services. Quality management involves the management of processes in a unified system. Logistics processes require efforts to be focused on the delivery of material flows by managing the selection and supplier performance improvement to just-in-time delivery of goods and customer service.
An important condition for the measurement and analysis of quality in logistics is the determination of the appropriate attributes for its measurement and their respective weights in the complex assessment. A review of the more common attributes in the scientific literature is made, highlighting that delivery time is the most used metric and delivery delays are the most common cause of deteriorating customer satisfaction. A critical review of the main models for assessing logistics service quality is provided.
The main aspects of logistics risk management are discussed. It is found that risk reduction opportunities depend on multiple interrelated factors and each of them can be the cause of drastic risk reduction if used wisely. It focuses on the four stages that should be followed as a continuous process to minimize the negative impact of risks and identify opportunities for improvement.
Risk management in logistics and supply chains has been studied by many researchers. Their results confirm that mitigation opportunities depend on multiple interrelated factors and each of them can be the cause of drastic risk reduction if used wisely. These major risks can be managed if, based on the cause-effect relationships between different factors, work is done to reduce the overall impact of the risk.
The study focuses on the integration of quality and risk management in the supply chain to examine the theoretical and practical guidelines and address the main risks of non-compliance with the customer and legislative requirements that arise in a constantly changing external environment.
Herbicides are chemical compounds used mostly to control weed (i.e., uncultivated) plants in agriculture and forestry and also for algae control [1, 2]. Herbicide formulations are designed to affect mainly plants, affecting specific plant biochemical pathways. However, it is common that this kind of pesticides affects nontarget organisms such animals, including aquatic organisms [3, 4].
The most used herbicide worldwide is glyphosate-based herbicide (GBH), such as Roundup® from Monsanto, and its usage has been increased [5] mainly due to the development of transgenic glyphosate-resistant crops [6]. Glyphosate (N-(phosphonomethyl) glycine (CAS no. 1071-83-6)) is a weak organic acid with a molecular weight of 169.09 M and has a half-life of 7–142 days in water and 76–240 in soil [6, 7]. Glyphosate has high solubility in water (10,000–15,700 mg L−1 at 25°C), and it readily dissolves and disperses in an aquatic environment.
Glyphosate affects a specific plant biochemical pathway, inhibiting the action of the enzyme 3-enolpyruvylshikimic acid 5-phosphate synthase (EPSPS) that is necessary for biosynthesis of amino acids such as phenylalanine, tyrosine, and tryptophan [8] (Figure 1). Animals do not have this biochemical pathway, and hypothetically, they would be safe from glyphosate. However, the use of glyphosate requires that some other compounds as surfactants are added to the commercial formulation to increase adhesion to the leaf surface and absorbance by plants, trespassing the waxy cuticle [6]. There are a variety of surfactants, but the most common used on glyphosate-based formulations has been polyethoxylated amine (POEA). This surfactant is known to be more toxic to animals then glyphosate itself [6, 9].
Glyphosate action on the biochemical pathway of plants inhibiting 3-enolpyruvylshikimic acid 5-phosphate synthase (EPSPS) enzyme and production of essential amino acids as phenylalanine, tyrosine, and tryptophan, causing plant death.
As mentioned above, glyphosate
In terrestrial animals, glyphosate reaches these organisms through direct application and contaminated food consumption. However, application of GBH in an aquatic environment is not so common when compared to terrestrial environments. Despite this, GBH can reach the aquatic environment through many ways. It can be applied directly on water bodies for algae control, although the opposite effect can be found, with proliferation of some species of algae due to the increase of phosphorus levels [18]. GBH can also reach the aquatic environment through leaching, run-off, and contaminated food source [6].
As mentioned, glyphosate has high solubility in an aquatic environment. Some studies say that 50% of glyphosate in natural waters dissipates by water flow and decomposition in a few days to 2 weeks [19, 20, 21]. Despite that, glyphosate binds to soil particles and solid surfaces [22], which makes its dissipation difficult. The by-products of glyphosate decomposition are sarcosine and aminomethylphosphonic acid (AMPA). The first one is known to be nontoxic [23] and the second one less or equally toxic for aquatic organisms than glyphosate [24, 25]. This substance has also a great solubility and dissipates in water in 7–14 days. POEA in natural environments degrades by microbial decomposition in 14 weeks and its half-life is estimated in 21–42 days [24].
Considering that glyphosate
One of the first studies that evaluated the effects of glyphosate and GBH in aquatic environments was performed by Folmar et al. [26]. According to Thomson’s ISI WoS (Institute for Scientific Information, Web of Science) database, using keywords as “glyphosate,” and “aquatic environment,” since 1979 to the present day, 233 papers have been published that evaluated the toxicological effects of glyphosate in aquatic environments (Figure 2). These papers addressed the toxic effects of glyphosate on various types of organisms. The invertebrate group was the most studied, with 52 published articles (21.3%), followed by fish with 51 (20.9%), amphibians 40 (16.4%), plant 31 (12.7%), and aquatic environment 30 (12.3%). The other groups were present in 40 published articles (16.4%) (Figure 3). For the investigated period and database, there were no papers which have evaluated the toxicological effects of glyphosate in aquatic mammals and birds. This scarcity of studies demonstrates the lack of knowledge on the risk of exposure of these groups in aquatic environments contaminated by glyphosate.
Number of papers published per year. Black bars represent the number of papers published in each year. Grey bars represent the number of papers accumulated per year. (*) Papers published until August 2018.
Number of papers per organism group. Black bars represent the number of papers on toxicological effects of glyphosate published for each aquatic organism groups. Asterisk indicates lack of studies evaluating the toxicological effects of glyphosate in aquatic mammals and birds.
Glyphosate in the aquatic environment causes the death of the macrophyte community, which serves as a microhabitat for zooplanktonic, phytoplanktonic, and periphytic communities, and this leads to top-down control of planktonic organisms, affecting refuge and feeding to fish [27], triggering a chain effect. Studies have evaluated the effects of glyphosate on aquatic lentils (
Species | Group | Chemical | Glyphosate concentration (μg L−1) | Effect | Reference |
---|---|---|---|---|---|
Catenulaceae | Roundup® | 8456 | Increases mortality | [36] | |
Nostocaceae | Gly. (acid) | 0.1–8.8 mM | Increases growth | [28] | |
Phormidiaceae | Gly. (acid) | 0.005–0.048 mM | Increases growth | [2] | |
Chlorellaceae | Gly. (acid) | 293,000 | Chlorophyll fluorescence/decreases PP | [35] | |
Naviculaceae | Roundup® | 1000–10,000 | Increases mortality | [30] | |
Hydrocharitaceae | DCMU Gly. (acid) | 11,600 | Decreases chlorophyll fluorescence | [31] | |
Roundup® | [30] | ||||
Lemnaceae | Roundup® | 2800 | Increases growth | [2] | |
Gly. (acid) Roundup® | 46,900 | Increases growth | [29] | ||
Leptolyngbyaceae | Gly. (acid) | 0.003–0.02 mM | Increases growth | [2] | |
Onagraceae | Gly. (acid) | 4000 and 108,000 | Bioaccumulation | [2] | |
Microcystaceae | Gly. (acid) | 3–37 | Increases growth and toxin production | [28] | |
[18] | |||||
Gly. (acid) | 15,000 | Increases growth and toxin production | [2] | ||
Haloragaceae | Gly. (acid) Roundup® | 840 | Decreases root | [30] | |
Gly. (n.c.) | 220 | Chlorophyll fluorescence | [33] | ||
Haloragaceae | Rodeo® | 1000 | Increases growth | [34] | |
Nostocaceae | Gly. (acid) | >50 mM | Increases growth | [2] | |
Chlorophyceae | Gly. (acid) | 200,000 | Chlorophyll fluorescence/decreases primary productivity (PP) | [2] | |
Nostocaceae | Gly. (acid) | 0.005–0.02 mM | Increases growth | [2] |
Ecotoxicity of glyphosate-based herbicide (GBH) to aquatic plants worldwide.
Dörr [18] studied the effect of glyphosate on the growth and production of secondary metabolites by toxigenic strains of the cyanobacteria
The effects of herbicides on nontarget aquatic plants are emerging as a major conservation issue in aquatic biodiversity [29].
Another important community in aquatic ecosystems that is also affected by the use of glyphosate is the periphyton. In terms of primary production, the periphyton has a photosynthetic contribution 77% higher than that of phytoplankton [30]. Among the most common and potentially toxic outcrossing cyanobacteria,
The exposure to GBH reduced 78% of the primary productivity of phytoplankton when used at low concentrations (0.125 mg L−1) [33] and at high concentrations (3.8 mg L−1) [34], causing a disturbance in the trophic levels. In freshwater systems, glyphosate at high levels stimulated eutrophication by increasing total phosphorus and favoring the growth of cyanobacteria on the periphyton, which altered the typology of the study ecosystem that was a mesocosm [32].
Species-based differences in sensitivity to GBH exposure may lead to decreased richness and abundance of ecosystem species [34]. Even though herbicides are thought to kill terrestrial plants, it can have an even more devastating effect in water, due to the imbalance that causes mortality of algae and aquatic plants. This causes an increase in decomposing organic matter in the water, which will reduce the concentrations of dissolved oxygen in the system and increase the stress of aquatic communities [35]. Thus, algae and aquatic plants are considered as nontarget organisms that are sensitive to the effects of glyphosate, and the damage to the balance of the aquatic environment is of concern. The damage of glyphosate on the aquatic plant community ranges from the death of the plant itself to the reduction of environmental heterogeneity promoted by the local plants. Consequently, this leads to the death of other aquatic species, causing an imbalance in the ecosystem.
One of the pioneer studies of the effects of GBH on invertebrate organisms was carried out by Tsui and Chu [9] that studied the effects of this chemical on
Species | Chemical | Exposure time (h) | LC50 (μg L−1) | Reference |
---|---|---|---|---|
Roundup® | 48 | 1770 (1330–2340) | [38] | |
Roundup® | 96 | 4304 (2121–7902) | [44] | |
Roundup® | 96 | 2842 (2524–3190) | [44] | |
Roundup® | 48 | 5390 (4810–6050) | [38] | |
Eskoba®, Panzer Gold®, Roundup Ultramax®, Sulfosato Touchdown® | 48 | 250–16,770 | [45] | |
Roundup®, POEAE, Glyphosate acid | 96 | 18,000 (9400–32,000) | [46] | |
Rodeo®, X-77 Spreader®, ChemTrol® | 48 | 1,216,000 (996,000–1,566,000) | [47] | |
Eskoba®, Panzer Gold®, Roundup Ultramax®, Sulfosato Touchdown® | 48 | 2670–15,430 | [45] | |
Roundup®, POEAE, Glyphosate acid | 48 | 3000 (2600–3400) | [46] | |
Eskoba®, Sulfosato Touchdown® | 48 | 1620–31,410 | [48] | |
Rodeo®, X-77 Spreader®, ChemTrol® | 48 | 218,000 (150,000–287,000) | [47] | |
Roundup® | 96 | 657 (472–914) | [44] | |
Roundup®, POEAE, Glyphosate acid | 48 | 62,000 (40,000–98,000) | [46] | |
Roundup®, POEAE, Glyphosate acid | 96 | 43,000 (28,000–66,000) | [46] | |
Roundup® | 96 | 340,000 | [49] | |
Rodeo®, X-77 Spreader®, ChemTrol® | 96 | 720,000 (399,000–1,076,000) | [47] | |
Roundup® | 96 | 8199 (6690–9580) | [50] | |
Rodeo®, X-77 Spreader®, ChemTrol® | 96 | 1,177,000 (941,000–1,415,000) | [47] | |
Eskoba®, Sulfosato Touchdown® | 48 | 1220–1,282,000 | [48] | |
Roundup® | 1440 | 2200 | [51] | |
Roundup® | 96 | 12,240 (9454–22,360 | [44] | |
Roundup® | 24 | 18.3 ± 12.9 | [52] |
Ecotoxicity of glyphosate-based herbicide (GBH) to aquatic invertebrates, exposure time, LC50 value (lower-upper values), and reference.
Specifically about microinvertebrates (<35 μm), these organisms persist within resting eggs (or egg banks) in lake sediments [36]. They represent a major source of regenerative potential in lake ecosystems near agricultural areas, and play a key role in influencing the active population and community dynamics, seasonal succession, biogeographic patterns, and the evolution of populations [36, 37]. Despite the widely accepted importance of resting egg banks in the ecology of aquatic micro-invertebrates’ communities, recently, experimental studies have demonstrated that the extensive and inappropriate use of commercial GBH, associated with agricultural activities, may impair the hatching of resting eggs in the sediment of lakes [38, 39]. Gutierrez and collaborators [38] indicated that the GBHs (Sulfosato Touchdown®) affect the hatching dynamics of micro-invertebrates, and selectively alter the species richness and abundance of community hatched from lake sediment. Portinho and associates [39] extended these findings and indicated that commercial herbicides as Roundup® (a.i. glyphosate) separate or in combination with 2,4-dichlorophenoxyacetic acid (2,4-D) have the potential to suppress emergences of micro-invertebrates from resting egg banks from lake sediments.
The environmental implication of this scenario suggests that changes in micro-invertebrates’ structure and composition induced by herbicides will occur, causing not only negative impacts on the process of recolonization from resting egg banks but also shifts in community composition. Recent attempts to develop guidelines for protecting aquatic organisms have focused on emergence from resting egg banks within the context of an ecological community [40], with potential implications for studies related to environmental risk to, and integrity assessment of, aquatic ecosystems.
Fish species are particularly vulnerable to GBH and their susceptibility depends on the commercial formulation, fish species, fish developmental stages, and exposure conditions, such as concentrations, exposure time, and route of exposure. Furthermore, gender-specific response of fish to GBH has been indicated in guppy
In general, the surfactant and the commercial formulation showed higher toxicity to fish when compared to active ingredient (glyphosate pure) and their metabolite (AMPA). The 50% lethal concentration (i.e., LC50) of GBHs for fish has high variability, ranging from 1000 to 9750 μg L−1 [6, 41]. Chandrasekera and Weeratunga [42] found a LC50 of 976 μg L−1 for 48 h of exposure in fries of
Glyphosate and formulation compounds can be taken by fish via gills and digestive tract through ingestion of contaminated food or water [6, 45]. Once inside the organisms, glyphosate is absorbed and distributed to the whole body through blood circuit, reaching several tissues. GBHs can affect fishes in different ways, affecting many organs and as well molecular levels. In liver, vacuolization process was reported in hepatocytes and nuclear pyknoses; in kidney, studies report Bowman capsule dilatation and accumulation of hyaline drops in tubular cells; and in gills, glyphosate causes hyperplasia, lamellar fusion and aneurism [46, 47, 48, 49, 50]. Besides that, Langiano and Martinez [49] showed activation of the stress axis, with increased blood glucose levels. Souza-Filho and collaborators [44] also showed genotoxic effects in fish cells. Concerning to enzymes, Sandrini and collaborators [17] showed that glyphosate impairs acetylcholinesterase activity in synapses, preventing detaching of acetylcholine from receptors, impairing electric transmission by neurons. This can impair muscle contraction and information transmittance. GBH in sub-lethal levels can also impair fish feeding behavior as shown by Giaquinto and collaborators [51]. Also, a recent
OMIC technologies, such as proteomics, transcriptomics, and metabolomics, have been applied to investigate the molecular mechanisms and toxicity of GBHs on fish. For example, proteomics-based methods (two-dimensional gel electrophoresis associated with mass spectrometry and bioinformatics) were used to complement the knowledge about the ecotoxicity of GBH on
The herpetofauna is composed of reptiles and amphibians, and due to the low mobility, physiological requirements, and habitat specificity, this group has become ideal models for environmental conservation studies [55]. Amphibians are sensitive to exposure to contaminants and are considered good bioindicators in monitoring water quality [56]. Characteristics such as permeable skin, reproduction, and larval stages dependent on the aquatic environment make anuran amphibians highly vulnerable to pesticide contamination [57]. Evidence suggests that anuran species decline is related to the intensive use of pesticides [58, 59, 60].
The decline of amphibian populations is related to the increase of environmental pollutants, the influence of climate change, habitat fragmentation, exposure to ultraviolet radiation, and human-induced environmental changes [61, 62]. Contamination of water bodies next to agricultural areas generally increases during the rainy season, that is, widely used to breed by most species of amphibians, and many species use temporary ponds and small streams adjacent to agricultural areas as part of their life cycle, harming the reproductive period and larval development [57, 58, 63]. During the rainy season, the agrochemical present in the soil are susceptible to be transported down the soil profiles and/or surfaces/underground water bodies and consequently affect the amphibian population [58] and other environmental (a) biotic elements [6, 64].
Herbicides may delay or inhibit the metamorphosis of amphibians directly impacting their reproduction [57]. According to Walker and collaborators [65], the main routes of herbicide absorption in anuran amphibians are through contaminated food ingestion and skin absorption of pollutants dissolved or suspended in water. After absorption, the substance is transported to different compartments of the body through blood. The effect of herbicides on tadpoles is less known when compared to adult amphibians, since the larvae of the anurans are less visible, and unlike adults, they do not have vocalization. Tadpoles of various species have not yet been described, which makes it even more difficult to study these organisms in depth [66].
The reduction in larval survival due to exposure to glyphosate was observed by Simioni and collaborators [67], Figueiredo and Rodrigues [68], and Costa and collaborators [69] in larvae of
Species | Chemical | Exposure time (h) | LC50 mg a.i./L | Reference |
---|---|---|---|---|
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [80] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 48 | 2.9–11.6 | [31] | |
Roundup® | 96 | 0.28 | [85] | |
Roundup® | 48 | 2.9–11.6 | [31] | |
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 48 | 2.9–11.6 | [31] | |
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 384 | 0.55–2.52 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 48 | 2.9–11.6 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 96 | 0.8–2.0 | [31] | |
Roundup® | 48 | 2.42 | [83] | |
Roundup® | 48 | 1.74 | [82] |
Ecotoxicity of glyphosate-based herbicide (GBH) to herpetofauna, exposure time, and LC50 value.
Reptiles are extremely sensitive to herbicide formulations and may exhibit changes in their behavior after exposure of these xenobiotics [74]. This group is fairly uniform and exposure to GBHs may affect its energy storage process [75, 76]. Schaumburg and collaborators [77] found that exposure to sublethal concentrations of glyphosate during the embryonic phase of
Currently in the Neotropical region, about 40 studies relate the indiscriminate use of herbicides based on glyphosate with the risk to biodiversity of herpetofauna. Schiesari and collaborators [80] reported that some species of amphibians, including tadpoles and adults and some reptiles are sensitive to exposure to formulations based on glyphosate. Exposure to sublethal concentrations of glyphosate is sufficient to cause irreversible damage to the DNA of amphibians and reptiles, so the use of GBH should be controlled in arable areas avoiding the decline of species that make up the herpetofauna group.
Glyphosate when used in recommended rates is considered not bioaccumulative and of low toxicity in birds [81]. However, the present acquaintance is not enough to make affirmation about low toxicity risk and low exposure of birds to herbicide considering the possible complex process behind the movement and accumulation of glyphosate, additives, and waste in the environment. Moreover, even the few available studies [82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96] have found direct and indirect effects of glyphosate on bird species (Figure 4). Among those, only five studies along years 1994 and 2017 on Google Scholar database have analyzed effects on aquatic bird species. Direct effects have been analyzed on male ducks (
Ecotoxicity of glyphosate-based herbicide (GBH) to aquatic birds. Direct (continuous arrows) and indirect (dashed arrows) effects of GBH on birds.
Indirect effects have been found in wetlands where the glyphosate is used to control the increase of
The direct effect of glyphosate on aquatic plants and macroalgae [87] can also affect aquatic birds once they make up the varied and plentiful diet of many of those birds. Changes in physiological, histological, and behavioral levels and lethal cases have been documented in fishes due to use of glyphosate [87, 88]. In this way, piscivorous birds can also be suffering indirect effects. In fact, all aquatic birds’ food chain can be affected by glyphosate once effects on invertebrates [81, 87, 88], amphibians [89], and reptiles [90] have already been confirmed.
Birds are very similar in their physiology and anatomy. Then, studies that have tested direct and indirect effects of glyphosate on nonaquatic birds can be also considered here. In Japanese quails (
Therefore, the controlled and scaled use of glyphosate in large areas is necessary to contribute to conservation of environmental heterogeneity and biological diversity avoiding the plausible effects on bird communities [83, 84, 85, 94]. To know what plants are important to bird diet and to promote techniques that do not eliminate all of those plants from the place are important activities before glyphosate application [91]. More studies that aim to analyze the bird contamination by herbicides are also necessary [97]. Long-term studies that encourage collaborative work between ecologist, toxicologist, and chemist are more pertinent [98].
For the best of our knowledge, GBH or glyphosate only was not tested in aquatic mammals. Searching on Web of Science website for the terms “Glyphosate AND mammal AND aquatic,” there is no study reported to date. Despite that, mammals in general are considered less sensible to GBH damages than other groups due to reduced contact with the environment of mammals when compared to other groups as fishes, amphibians, or aquatic invertebrates [99]. The main way that GBH or the active ingredient glyphosate reaches mammals’ bodies is through the digestive tract. However, it seems to be poorly absorbed and is excreted essentially nonmetabolized [100]. Essentially, mammals that were tested were rats, mice, and dogs [101], tested through injection or ingestion. Some studies report glyphosate in humans in medical case studies. Reported direct effects of GBH on mammals are described as a “wide range of clinical manifestations” such as skin and throat irritation, hypotension, or death [102] and include heart arrhythmias and atrioventricular block, cardiac electrophysiological changes and conduction blocks [103], pregnancy problems [104], disrupt transcriptional expression of the steroidogenic acute regulatory protein in testicle [105] and aromatase activity, alter mRNA levels, and interact with enzymes [106]. Indirect effects on mammals can be due to reduction of vegetation and animals that are a source of food such as invertebrates [101] and fishes. Although these mentioned studies were conducted in nonaquatic mammals, it is expected that aquatic mammals have similar or even more accentuated effect, since they have intense contact with water, and if it is contaminated, the exposure will be higher.
Despite the fact that GBHs were developed to control weeds, acting specifically in a restrict plan biochemical pathway, several studies demonstrated that there are many side effects on nontarget organisms in all great groups as reported extensively here. Looking to control these side effects, governments for many countries around the world established limits for usage and concentrations in water bodies. The USA, for example, allows 700 μg L−1 in water bodies, while Canada allows 280 μg L−1 in drink water. The Brazilian law is a little more restrictive, allowing 65 μg L−1 in water bodies class 2 that is used for crop and recreation of first degree (direct contact) [107]. However, we could check here that these maximum concentrations allowed are not safe for biodiversity conservation. Considering the Brazilian law, the more restrictive in American countries, populations of yellowtail tetra fish (
However, even with all those regulations, it is not being obeyed, since there is a large range of glyphosate and its metabolite (e.g., AMPA) concentrations in hydroresources [6, 64]. Therefore, another way of action for environment safety is preserving marginal forests of rivers, surveillance, and environment education. Another sustainable way to achieve this goal is changing the crop production matrix from large scale, that is, conventional-based production model to a smaller integrative-/organic-based production system, with controlled or restrictive usage of pesticides and other agrochemicals.
We are thankful to FAPEG (#201710267001261) for financial support.
The authors declare that there is no conflict of interest.
.
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The chapter will therefore begin with a brief description of the major Raman bands of carbon allotropes. In the following chapter a concise comparison between single walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), fullerenes and graphene is exposed. The characteristic features in Raman spectra of carbon allotropes, namely the intense signals D and G are investigated. In particular, the chapter will outline the Raman spectrum of graphene and different types of graphene oxide. The last part of the chapter is devoted to graphene nanocomposites.",book:{id:"6257",slug:"raman-spectroscopy",title:"Raman Spectroscopy",fullTitle:"Raman Spectroscopy"},signatures:"Elena Iuliana Bîru and Horia Iovu",authors:[{id:"215841",title:"Prof.",name:"Horia",middleName:null,surname:"Iovu",slug:"horia-iovu",fullName:"Horia Iovu"},{id:"215842",title:"Mrs.",name:"Iuliana",middleName:null,surname:"Biru",slug:"iuliana-biru",fullName:"Iuliana Biru"}]},{id:"58475",doi:"10.5772/intechopen.72933",title:"Raman Spectroscopy for In Vivo Medical Diagnosis",slug:"raman-spectroscopy-for-in-vivo-medical-diagnosis",totalDownloads:1669,totalCrossrefCites:11,totalDimensionsCites:17,abstract:"Raman spectroscopy is a noninvasive optical technique that can be used as an aid in diagnosing certain diseases and as an alternative to more invasive diagnostic techniques such as the biopsy. Due to these characteristics, Raman spectroscopy is also known as an optical biopsy technique. The success of Raman spectroscopy in biomedical applications is based on the fact that the molecular composition of healthy tissue is different from diseased tissue; also, several disease biomarkers can be identified in Raman spectra, which can be used to diagnose or monitor the progress of certain medical conditions. This chapter outlines an overview of the use of Raman spectroscopy for in vivo medical diagnostics and demonstrates the potential of this technique to address biomedical issues related to human health.",book:{id:"6257",slug:"raman-spectroscopy",title:"Raman Spectroscopy",fullTitle:"Raman Spectroscopy"},signatures:"Miguel Ghebré Ramírez-Elías and Francisco Javier González",authors:[{id:"214020",title:"Dr.",name:"Miguel",middleName:null,surname:"Ramirez-Elias",slug:"miguel-ramirez-elias",fullName:"Miguel Ramirez-Elias"},{id:"215413",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"González",slug:"francisco-javier-gonzalez",fullName:"Francisco Javier González"}]},{id:"58926",doi:"10.5772/intechopen.72864",title:"Raman spectroscopy in Zinc Ferrites Nanoparticles",slug:"raman-spectroscopy-in-zinc-ferrites-nanoparticles",totalDownloads:1811,totalCrossrefCites:9,totalDimensionsCites:17,abstract:"ZnFe2O4 ferrite nanoparticles are arousing a great interest in the biomedical field, thanks to their superparamagnetic behavior at room temperature. Functional properties depend on composition, size, nanoparticle architecture and, in turn, on the synthesis methods. Bulk ZnFe2O4 has the normal spinel structure (all Zn2+ ions in tetrahedral and all Fe3+ ions in octahedral positions), but at the nanometric size inversion takes place with a cationic mixing on divalent and trivalent sites. The sensitivity of the Raman probe to cation disorder favored the appearance of several works on a rich variety of nanosized zinc ferrites. An overview on these results is reported and discussed at variance with synthesis methods, grain dimensions, and dopants. We add to this landscape our results from new nanosized powder samples made by microwave-assisted combustion, with different dopants (Ca, Sr on Zn site and Al, Gd on Fe site). A detailed analysis of A1g, Eg, 3F2g Raman modes has been performed and Raman band parameters have been derived from best-fitting procedures and carefully compared to literature data. The vibrational results are discussed taking into account the characterization from X-ray powder diffraction raction, SEM-EDS probe, EPR spectroscopy and, of course, the magnetic responses.",book:{id:"6257",slug:"raman-spectroscopy",title:"Raman Spectroscopy",fullTitle:"Raman Spectroscopy"},signatures:"Pietro Galinetto, Benedetta Albini, Marcella Bini and Maria Cristina\nMozzati",authors:[{id:"215617",title:"Prof.",name:"Pietro",middleName:null,surname:"Galinetto",slug:"pietro-galinetto",fullName:"Pietro Galinetto"},{id:"215967",title:"Ms.",name:"Benedetta",middleName:null,surname:"Albini",slug:"benedetta-albini",fullName:"Benedetta Albini"},{id:"215968",title:"Prof.",name:"Marcella",middleName:null,surname:"Bini",slug:"marcella-bini",fullName:"Marcella Bini"},{id:"215969",title:"Dr.",name:"Maria Cristina",middleName:null,surname:"Mozzati",slug:"maria-cristina-mozzati",fullName:"Maria Cristina Mozzati"}]},{id:"56284",doi:"10.5772/intechopen.69891",title:"Factorial Design and Machine Learning Strategies: Impacts on Pharmaceutical Analysis",slug:"factorial-design-and-machine-learning-strategies-impacts-on-pharmaceutical-analysis",totalDownloads:1883,totalCrossrefCites:8,totalDimensionsCites:16,abstract:"Pharmaceutical analysis is going through an expeditious progress as the perception of ‘multivariate data analysis’ (MVA) becomes gradually more assimilated. Pharmaceutical analysis comprises a range of processes that covers both chemical and physical assessment of drugs and their formulations employing different analytical techniques. With the revolution in instrumental analysis and the huge amount of information produced, there must be an up-to-date data processing tool. The role of chemometrics then comes up. Multivariate analysis (MVA) has the capability of effectively drawing a complete picture of the investigated process. Moreover, MVA reproduces the arithmetic influence of variables and their interactions through a smaller number of trials, keeping both efforts and capitals. Spectrophotometry is among the most extensively used techniques in pharmaceutical analysis either direct (single component) or derivative (multicomponent). In addition to these recognized benefits, using chemometrics in conjunction with spectrophotometry affects three vital characteristics: accuracy, precision and robustness. The impact of hyphenation of spectrophotometric analytical techniques to chemometrics (experimental design and support vector machines) on analytical laboratory will be revealed. A theoretical background on the different factorial designs and their relevance is provided. Readers will be able to use this chapter as a guide to select the appropriate design for a problem.",book:{id:"5857",slug:"spectroscopic-analyses-developments-and-applications",title:"Spectroscopic Analyses",fullTitle:"Spectroscopic Analyses - Developments and Applications"},signatures:"Marwa S. Elazazy",authors:[{id:"198210",title:"Dr.",name:"Marwa",middleName:"S.",surname:"El-Azazy",slug:"marwa-el-azazy",fullName:"Marwa El-Azazy"}]},{id:"56996",doi:"10.5772/intechopen.70655",title:"Application of Mass Spectroscopy in Pharmaceutical and Biomedical Analysis",slug:"application-of-mass-spectroscopy-in-pharmaceutical-and-biomedical-analysis",totalDownloads:4468,totalCrossrefCites:4,totalDimensionsCites:11,abstract:"Mass spectrometry (MS) is a powerful analytical tool with many applications in pharmaceutical and biomedical field. The increase in sensitivity and resolution of the instrument has opened new dimensions in analysis of pharmaceuticals and complex metabolites of biological systems. Compared with other techniques, mass spectroscopy is only the technique for molecular weight determination, through which we can predict the molecular formula. It is based on the conversion of the sample into ionized state, with or without fragmentation which are then identified by their mass-to-charge ratios (m/e). Mass spectroscopy provides rich elemental information, which is an important asset to interpret complex mixture components. Thus, it is an important tool for structure elucidation of unknown compounds. Mass spectroscopy also helps in quantitative elemental analysis, that is, the intensity of a mass spectra signal is directly proportional to the percentage of corresponding element. It is also a noninvasive tool that permits in vivo studies in humans. Recent research has looked into the possible applications of mass spectrometers in biomedical field. It is also used as a sensitive detector for chromatographic techniques like LC–MS, GC–MS and LC/MS/MS. These recent hyphenated technological developments of the technique have significantly improved its applicability in pharmaceutical and biomedical analyses.",book:{id:"5857",slug:"spectroscopic-analyses-developments-and-applications",title:"Spectroscopic Analyses",fullTitle:"Spectroscopic Analyses - Developments and Applications"},signatures:"Uttam Singh Baghel, Atamjit Singh, Deeksha Singh and Manish\nSinha",authors:[{id:"204152",title:"Dr.",name:"Uttam",middleName:"Singh",surname:"Baghel",slug:"uttam-baghel",fullName:"Uttam Baghel"},{id:"204438",title:"Mrs.",name:"Deeksha",middleName:null,surname:"Singh",slug:"deeksha-singh",fullName:"Deeksha Singh"},{id:"204439",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh"},{id:"207608",title:"Dr.",name:"Manish",middleName:null,surname:"Sinha",slug:"manish-sinha",fullName:"Manish Sinha"}]}],mostDownloadedChaptersLast30Days:[{id:"59012",title:"Graphene Nanocomposites Studied by Raman Spectroscopy",slug:"graphene-nanocomposites-studied-by-raman-spectroscopy",totalDownloads:2238,totalCrossrefCites:27,totalDimensionsCites:42,abstract:"The goal of this chapter is to provide a general introduction about graphene nanocomposites studied by Raman spectroscopy. The chapter will therefore begin with a brief description of the major Raman bands of carbon allotropes. In the following chapter a concise comparison between single walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), fullerenes and graphene is exposed. The characteristic features in Raman spectra of carbon allotropes, namely the intense signals D and G are investigated. In particular, the chapter will outline the Raman spectrum of graphene and different types of graphene oxide. The last part of the chapter is devoted to graphene nanocomposites.",book:{id:"6257",slug:"raman-spectroscopy",title:"Raman Spectroscopy",fullTitle:"Raman Spectroscopy"},signatures:"Elena Iuliana Bîru and Horia Iovu",authors:[{id:"215841",title:"Prof.",name:"Horia",middleName:null,surname:"Iovu",slug:"horia-iovu",fullName:"Horia Iovu"},{id:"215842",title:"Mrs.",name:"Iuliana",middleName:null,surname:"Biru",slug:"iuliana-biru",fullName:"Iuliana Biru"}]},{id:"56996",title:"Application of Mass Spectroscopy in Pharmaceutical and Biomedical Analysis",slug:"application-of-mass-spectroscopy-in-pharmaceutical-and-biomedical-analysis",totalDownloads:4468,totalCrossrefCites:4,totalDimensionsCites:11,abstract:"Mass spectrometry (MS) is a powerful analytical tool with many applications in pharmaceutical and biomedical field. The increase in sensitivity and resolution of the instrument has opened new dimensions in analysis of pharmaceuticals and complex metabolites of biological systems. Compared with other techniques, mass spectroscopy is only the technique for molecular weight determination, through which we can predict the molecular formula. It is based on the conversion of the sample into ionized state, with or without fragmentation which are then identified by their mass-to-charge ratios (m/e). Mass spectroscopy provides rich elemental information, which is an important asset to interpret complex mixture components. Thus, it is an important tool for structure elucidation of unknown compounds. Mass spectroscopy also helps in quantitative elemental analysis, that is, the intensity of a mass spectra signal is directly proportional to the percentage of corresponding element. It is also a noninvasive tool that permits in vivo studies in humans. Recent research has looked into the possible applications of mass spectrometers in biomedical field. It is also used as a sensitive detector for chromatographic techniques like LC–MS, GC–MS and LC/MS/MS. These recent hyphenated technological developments of the technique have significantly improved its applicability in pharmaceutical and biomedical analyses.",book:{id:"5857",slug:"spectroscopic-analyses-developments-and-applications",title:"Spectroscopic Analyses",fullTitle:"Spectroscopic Analyses - Developments and Applications"},signatures:"Uttam Singh Baghel, Atamjit Singh, Deeksha Singh and Manish\nSinha",authors:[{id:"204152",title:"Dr.",name:"Uttam",middleName:"Singh",surname:"Baghel",slug:"uttam-baghel",fullName:"Uttam Baghel"},{id:"204438",title:"Mrs.",name:"Deeksha",middleName:null,surname:"Singh",slug:"deeksha-singh",fullName:"Deeksha Singh"},{id:"204439",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh"},{id:"207608",title:"Dr.",name:"Manish",middleName:null,surname:"Sinha",slug:"manish-sinha",fullName:"Manish Sinha"}]},{id:"54928",title:"Metal Complexes of Pharmaceutical Substances",slug:"metal-complexes-of-pharmaceutical-substances",totalDownloads:3247,totalCrossrefCites:6,totalDimensionsCites:11,abstract:"Significant progresses have been made in the inorganic and organic chemistry up to the present concerning the synthesis, characterization, and application of the metal complexes of pharmaceutical substances. From the wide range of fields in which these coordination compounds find their application, many efforts were focused on the study of their importance in the biological processes. The coordination complexes of many pharmaceutical substances having different pharmacological effects e.g., pyrazinamide (PZA), nicotinamide (NAM), nicotinic acid (NIC), theophylline (TEO), captopril (CPL), tolbutamide (TBA), clonidine (CLN), guanfacine (GUAF), etc. with transition metals were synthesized and used in order to improve their pharmacological and pharmacotechnical properties and also for the drug analysis and control. Several techniques such as Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), X-ray spectroscopy, mass spectrometry, ultraviolet-visible (UV-Vis) spectrophotometry, electron paramagnetic resonance (EPR) spectroscopy, X-ray diffraction, elemental analysis, electrochemical methods, thermal methods, and scanning electron microscopy were used for the physicochemical characterization of the complex composition. A significant interest in the development of metal complex-based drugs with unique research and therapeutic and diagnostic opportunities is currently observed in the medicinal inorganic chemistry area.",book:{id:"5857",slug:"spectroscopic-analyses-developments-and-applications",title:"Spectroscopic Analyses",fullTitle:"Spectroscopic Analyses - Developments and Applications"},signatures:"Tünde Jurca, Eleonora Marian, Laura Graţiela Vicaş, Mariana\nEugenia Mureşan and Luminiţa Fritea",authors:[{id:"192598",title:"Dr.",name:"Fritea",middleName:null,surname:"Luminita",slug:"fritea-luminita",fullName:"Fritea Luminita"},{id:"192813",title:"Prof.",name:"Jurca",middleName:null,surname:"Tünde",slug:"jurca-tunde",fullName:"Jurca Tünde"},{id:"192814",title:"Dr.",name:"Marian",middleName:null,surname:"Eleonora",slug:"marian-eleonora",fullName:"Marian Eleonora"},{id:"192815",title:"Prof.",name:"Vicas",middleName:null,surname:"Laura Gratiela",slug:"vicas-laura-gratiela",fullName:"Vicas Laura Gratiela"},{id:"192816",title:"Prof.",name:"Muresan",middleName:null,surname:"Mariana Eugenia",slug:"muresan-mariana-eugenia",fullName:"Muresan Mariana Eugenia"}]},{id:"69058",title:"Hardware of MRI System",slug:"hardware-of-mri-system",totalDownloads:937,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Magnetic resonance imaging (MRI) is comprehensively applied in modern medical diagnosis and scientific research for its superb soft-tissue imaging quality and non-radiating characteristics. Main magnet, gradient assembly, and radio-frequency (RF) assembly are main hardware in an MRI system. The hardware performance has direct relationship with the ultimate system overall performance. The development of MRI system toward high magnetic field strength will acquire high signal-to-noise ratio (SNR) and resolution, and meanwhile the manufacture difficulty of main magnet, gradient assembly, and RF assembly will also be significantly elevated. This will make challenges on the design, materials, primitive device, and also the whole machine assembly. This chapter introduces the main hardware of the MRI system and corresponding functions and developments.",book:{id:"7313",slug:"nuclear-magnetic-resonance",title:"Nuclear Magnetic Resonance",fullTitle:"Nuclear Magnetic Resonance"},signatures:"Qiuliang Wang",authors:[{id:"302605",title:"Prof.",name:"Qiu-Liang",middleName:null,surname:"Wang",slug:"qiu-liang-wang",fullName:"Qiu-Liang Wang"}]},{id:"69423",title:"Atomic Spectroscopy",slug:"atomic-spectroscopy",totalDownloads:1384,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Atomic spectroscopy includes a number of analytical techniques used to determine the elemental composition of a sample (it can be gas, liquid, or solid) by observing its electromagnetic spectrum or its mass spectrum. Element concentrations of a millionth (ppm) or one billionth part (ppb) of the sample can be detected. There are different variations of atomic spectroscopy, emission, absorption, fluorescence, and mass spectroscopy. Determination of an appropriate technique requires a basic understanding of each technique since each has its individual strengths and limitations. This chapter is designed to provide a basic overview to the atomic spectroscopy techniques and how can you select the one that best suits our analytical problems.",book:{id:"7674",slug:"modern-spectroscopic-techniques-and-applications",title:"Modern Spectroscopic Techniques and Applications",fullTitle:"Modern Spectroscopic Techniques and Applications"},signatures:"Deniz Sahin",authors:[{id:"283971",title:"Associate Prof.",name:"Deniz",middleName:null,surname:"Şahin",slug:"deniz-sahin",fullName:"Deniz Şahin"}]}],onlineFirstChaptersFilter:{topicId:"502",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:8,numberOfPublishedChapters:86,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:96,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:283,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:138,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:128,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:9,numberOfPublishedChapters:100,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBo