**8. Conclusions**

The willingness to understand the main factors that rule the adoption of EEMs on CAS represents the driver that pushed toward the definition of the present framework. Aiming at providing a systemic view of the adoption, factors referring to the complexity, compatibility, and observability of the results coming from the adoption of EEMs were included in the model, encompassing, among others, the impacts on the operations and the other productive resources of an industrial firm, together with more traditional considerations regarding the operational and the economic and energetic factors. Results from the empirical application show how these features might prove critical in the path for the adoption, sometimes even capable of reversing the outcome, hence confirming the added knowledge brought by the framework. In this regard, future longitudinal research could explore the change of awareness in decision-makers when assessing EEMs in CAS and other sustainability practices within industrial operations. Moreover, the focus kept on the specific technology of CAS enabled to point out peculiar factors that might be lost approaching the problem through a more holistic perspective, e.g., difficulties in accessing CAS, which was a recurrent topic in the empirical investigations. Nonetheless, despite its non-negligible importance according to the interviewed decision-makers, the factor has never been approached by previous studies.

Using the framework, industrial decision-makers could tackle the perception of uncertainty they have concerning EEMs, beside finding valuable support to overcome the barriers related to risk, imperfect evaluation criteria, and lack of information, which might represent critical issues preventing a sound decision-making process. These barriersmight be particularly presentin SMEs, generally characterized by less trained or less skilled decision-makers, who may moreover face difficulties in the use of complex or overly detailed models. However, the structuring resulting from the synthesis process to which the framework was subjected made it possible to obtain a complete framework regarding the factors to be considered in the adoption of CAS EEMs, characterized at the same time by a high ease of use. Indeed, as pointed out by the empirical application, the evaluation of the user-friendliness and the effort required for the usage were overall positive, despite the fact that the greatest share of companies in the sample were SMEs. Policy makers, on the other hand, could take advantage of the framework to design tailored policies for enhancing the efficiency of CAS. Moreover, the assessment of the factors that rule the adoption of EEMs on CAS could lead to a deeper understanding of the specific barriers that affect the technology, which might move away with respect to the issue preventing the adoption of other technologies, assigned to different roles in a plant, e.g., electric motor systems. This deeper knowledge would, in turn, create solid foundations on which to lay the basis for the definition of drivers to overcome these barriers, improving the overall efficiency.

In conclusion, we would like to acknowledge some study limitations, starting from the narrowness of the application sample and its heterogeneity with respect to the industrial sectors. Besides, not all sectors are encompassed in the present study, e.g., textile or metal manufacturing are missing. Moreover, limiting the analysis to the technology of CAS did not enable to consider the entire set of impacts the adoption of an EEM has on the other productive resources or on the operations of a firm. Accordingly, future research could move towards this direction, furtherly extending the analysis to include a broader set of heterogeneous EEMs to better assess the impacts of their adoption. Additionally, further research could effectively develop approaches to measure such impacts more quantitatively, linking the impacts on production and operations performance. Furthermore, research could explore what synergies may be explored by integrating the developed framework into a broader set of tools to improve the sustainability performance of industrial enterprises, also connecting it with assessment tools, maturity models, etc.

**Author Contributions:** Conceptualization, D.A., A.T. and E.C.; methodology, E.C. and D.A.; validation, A.T., E.C. and D.A.; formal analysis, A.T., D.A. and E.C.; investigation, A.T., E.C. and D.A.; resources, A.T., D.A. and E.C.; data curation, D.A.; writing—original draft preparation, D.A., A.T. and E.C.; writing—review and editing, A.T., E.C. and D.A.; visualization, D.A.; supervision, A.T.; 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.

**Appendix A**

**Table A1.** *Cont.*

a The green background represents an excellent rating (4 on the Likert scale); the orange background represent a good rating (3 on the Likert scale); no mediocre or poor ratings are present.


*2.2.2 Electrophoresis and Western blotting*

Polyacrylamide gel electrophoresis (PAGE) is the separation of proteins based on mobility on a gel matrix, subjected to a charge differential between two sealed chambers, of a body fluid or tissue extract. This technique is frequently used to determine the distribution or banding pattern of protein groups in tissues under different conditions. Quantification of the intensity of the bands and their relative mobility by PAGE is carried out by densitometric analysis. Saliva is a convenient

**61**

*Oral Tissue Responses to Travel in Space DOI: http://dx.doi.org/10.5772/intechopen.86728*

peaks, but not the basic pattern.

**Figure 7.**

stability of the tissue or of sample preparation.

in the flight and in the habitat controls.

body fluid for measuring a variety of physiological conditions or responses on the basis of variations in protein content or distribution. For example, after testing more than 50 samples, PAGE separation of salivary proteins has shown that each individual pattern is unique. Namely, no superimposable patterns were found, therefore constituting essentially a salivary protein pattern fingerprint. Shown at the left in **Figure 7**, in duplicate, are the patterns of three (A, B, C) randomly selected individuals with the corresponding densitometric profiles at the right. **Figure 7** also shows how normal chewing changes the amplitude of several protein

*Electrophoresis and densitometry of saliva from three randomly selected individuals (A, B, and C) from a pool of approximately 50 test subjects. The left ordinate on the gel pattern image shows molecular based migration rates of a mixture of proteins of known size. At the right of the polyacrylamide gel electrophoresis (PAGE) banding patterns are the corresponding densitometric measurements. The top row (−) prior to, the bottom row (+) after, chewing. The asterisks show the migration distance of RII that can be identified by Western blotting.*

The PAGE protein banding patterns of the STS mission samples showed a decrease of some of the higher molecular weight bands while the faster moving smaller bands increased when these were compared to vivarium controls. The changes were not consistent between missions and may in part be due to lack of

Western blotting is a technique using antibodies generated to a specific protein for its identification among numerous others in the banding pattern. Proteins are transferred onto nitrocellulose membranes and stained with a washable dye to show the band distribution, then quantified by densitometry. The dye is removed and the membrane probed for reactivity with a specific antibody. These techniques were employed to test salivary gland extracts to measure protein patterns of flight animal

samples when compared with those of ground control animals (**Figure 8**).

The results show that the RII peaks in the STS-135 flight samples (**Figure 8**) were significantly smaller than the corresponding band amplitude in either vivarium or habitat controls, middle and bottom profiles, respectively. Western blotting experiments to determine the expression of α-amylase show a significant decrease

These results indicate that on the shorter, STS-135 flight the expression of RII was decreased, while in the longer Bion-M1 flight (**Figure 9**) an apparent stabilization or adjustment to the microgravity environment had occurred and the RII levels were not different, perhaps even increased from those of either of the controls. Both Bion-M1 and STS-135 flight and both control samples show a significant, but opposite change of a faster moving band that may represent a small protein or peptide. The findings regarding RII, generally thought to be a stress associated protein [35, 36] responding to the conditions of spaceflight [7], varied by methods of analysis but also between flights within a particular test measure from morphometric analyses of immunogold labeling experiments. Bion-M1 Western blotting results showed no difference between RII in Bion-M1 flight and vivarium control

**Figure 7.**

*Beyond LEO - Human Health Issues for Deep Space Exploration*

The expression of SMG secretory proteins was essentially unchanged in mice from the 13–15-day space shuttle flights. However, mice from the Bion-M1 flight showed significantly increased expression of an acinar cell protein, salivary androgen binding protein alpha (SABPα), a pheromone involved in mate selection [33], and the granular convoluted duct cell proteins epidermal growth factor (EGF) and nerve growth factor (NGF) (**Table 1**). PRP, present in acinar cell secretory granules of both sexes, and submandibular gland protein C (SMGC), present in terminal tubule cell secretory granules of female mice, were not significantly different from controls. In the SLG, PSP expression by demilune cells was significantly increased in mice from the space shuttle STS-131 flight, but not in mice from STS-135 [34]. The expression of both PKA-RII in demilune cells, and the acinar cell mucin Muc19,

*Quantitative TEM immunogold labeling of secretory proteins in SMG of female mice flown on STS-131 and*

*Quantitative TEM immunogold labeling of nuclear PKA-RII in PG of mice flown on STS-131 and STS-135, and the Bion-M1 biosatellite. Labeling results are shown as a percentage of the corresponding habitat control*

SABPα 114.6 ± 12.1 88.9 ± 26.3 221.9 ± 31.7\* PRP 111.1 ± 13.0 76.6 ± 9.0 134.4 ± 11.5 EGF 87.7 ± 12.4 36.3 ± 6.0 159.9 ± 4.6\* NGF 116.3 ± 23.3 89.9 ± 5.1 159.0 ± 10.6\* SMGC 83.0 ± 9.3 103.4 ± 5.3 —

*Labeling results are shown as a percentage of the corresponding habitat control mice ± SEM.*

**STS-131 STS-135 Bion-M1**

Polyacrylamide gel electrophoresis (PAGE) is the separation of proteins based on mobility on a gel matrix, subjected to a charge differential between two sealed chambers, of a body fluid or tissue extract. This technique is frequently used to determine the distribution or banding pattern of protein groups in tissues under different conditions. Quantification of the intensity of the bands and their relative mobility by PAGE is carried out by densitometric analysis. Saliva is a convenient

**60**

**Figure 6.**

*mice ± SEM.*

*\* p < 0.01.*

**Table 1.**

were increased, but not significantly.

*2.2.2 Electrophoresis and Western blotting*

*STS-135, and male mice flown on the Bion-M1 biosatellite.*

*Electrophoresis and densitometry of saliva from three randomly selected individuals (A, B, and C) from a pool of approximately 50 test subjects. The left ordinate on the gel pattern image shows molecular based migration rates of a mixture of proteins of known size. At the right of the polyacrylamide gel electrophoresis (PAGE) banding patterns are the corresponding densitometric measurements. The top row (−) prior to, the bottom row (+) after, chewing. The asterisks show the migration distance of RII that can be identified by Western blotting.*

body fluid for measuring a variety of physiological conditions or responses on the basis of variations in protein content or distribution. For example, after testing more than 50 samples, PAGE separation of salivary proteins has shown that each individual pattern is unique. Namely, no superimposable patterns were found, therefore constituting essentially a salivary protein pattern fingerprint. Shown at the left in **Figure 7**, in duplicate, are the patterns of three (A, B, C) randomly selected individuals with the corresponding densitometric profiles at the right. **Figure 7** also shows how normal chewing changes the amplitude of several protein peaks, but not the basic pattern.

The PAGE protein banding patterns of the STS mission samples showed a decrease of some of the higher molecular weight bands while the faster moving smaller bands increased when these were compared to vivarium controls. The changes were not consistent between missions and may in part be due to lack of stability of the tissue or of sample preparation.

Western blotting is a technique using antibodies generated to a specific protein for its identification among numerous others in the banding pattern. Proteins are transferred onto nitrocellulose membranes and stained with a washable dye to show the band distribution, then quantified by densitometry. The dye is removed and the membrane probed for reactivity with a specific antibody. These techniques were employed to test salivary gland extracts to measure protein patterns of flight animal samples when compared with those of ground control animals (**Figure 8**).

The results show that the RII peaks in the STS-135 flight samples (**Figure 8**) were significantly smaller than the corresponding band amplitude in either vivarium or habitat controls, middle and bottom profiles, respectively. Western blotting experiments to determine the expression of α-amylase show a significant decrease in the flight and in the habitat controls.

These results indicate that on the shorter, STS-135 flight the expression of RII was decreased, while in the longer Bion-M1 flight (**Figure 9**) an apparent stabilization or adjustment to the microgravity environment had occurred and the RII levels were not different, perhaps even increased from those of either of the controls. Both Bion-M1 and STS-135 flight and both control samples show a significant, but opposite change of a faster moving band that may represent a small protein or peptide.

The findings regarding RII, generally thought to be a stress associated protein [35, 36] responding to the conditions of spaceflight [7], varied by methods of analysis but also between flights within a particular test measure from morphometric analyses of immunogold labeling experiments. Bion-M1 Western blotting results showed no difference between RII in Bion-M1 flight and vivarium control

#### **Figure 8.**

*Densitometric analysis of PAGE protein separation and anti-RII and anti-α-amylase reactivity in STS-135 mice. (A) PG protein samples from mice housed in, top panel, flight; middle panel, habitat; and bottom panel, vivarium type cages. The lighter curve represents the protein profile; the shaded area is the reactivity to anti-RII antibody. The ordinate axes are integrated density values of the proteins on the left-hand axis, and the integrated density values for RII and the reactivity of RII fragment (Rfr) on the right-hand axis. (B) PG α-amylase Western blotting. The ordinate shows integrated density, and the error bars show ±5% error. C1, vivarium control; C2, habitat control; F, flight. The values on the ordinate axis (ID) are integrated density in arbitrary units (with permission, from [13]).*

mice. Measuring RII, therefore, may be a sensitive test for stress reactions during spaceflight.

The variability may be due to the sensitivity of responses affecting RII synthesis. Previous studies point to a rapid and transient increase in the cases of brief acute stress, for example lift off of a spacecraft, followed by long-term, perhaps low level, prolonged time under stress, decrease. For example, a 60-day to a year tour resulting in a decrease of RII and leveling off at concentrations below normal. Eventual physiologic adjustment to flight conditions may start to bring RII production toward normal. An apparent increase also may result from a rough landing that might have occurred in the Bion-M1 flight and the acute response obliterating any reduction due to chronic long-term flight conditions.

Tissue extract samples showed a large faster moving component, presumably an RII fragment. The fragments did resemble the densitometric changes in the flight versus the control. These differences did not completely account for the change of flight values compared to the control. There may have been smaller fragments not visible on the Western blot that could account for the decreases in flight RII.

**63**

**2.3 Gene expression**

*Amy1, α-amylase; Bpifa2, PSP, Prpmp5, PRP; Prkar2a, RII.*

**Figure 10.**

**Figure 9.**

genes were downregulated.

Microarray analyses of the PG showed significant changes in the expression of numerous genes of flight mice compared to habitat ground control mice. In female mice flown on STS-135, the expression of 130 genes was significantly upregulated (log2 ratio ≥ 1), and 75 genes were downregulated (log2 ratio ≤ − 1), (**Figure 10**). In male mice flown on Bion-M1, the expression of 70 genes was upregulated, and 65

*Microarray analysis of secretory protein gene expression in PG of mice flown on STS-135 and the Bion-M1 biosatellite. Results are expressed as log2 of the ratio of expression in flight mice to that in habitat control mice.*

*Electrophoresis and Western blotting of flight (F) and control (C) PG extracts from mice of the Bion-M1 mission. (A) Protein banding patterns of the flight and control animals (F and C). The left lane (M) shows the relative mobilities of marker proteins of kilodalton (kD) size from 110 to 15 marked on the ordinate. Western blotting for RII is shown in the two right most lanes with two major bands, the first at an estimated 50 kDa size (RII), the second deemed to be a fragment between 14 and 20 kDa (Rfr). (B) densitometric profile of the control banding pattern which was not distinguishable from that of the flight (with permission, from [13]).*

*Oral Tissue Responses to Travel in Space DOI: http://dx.doi.org/10.5772/intechopen.86728* *Oral Tissue Responses to Travel in Space DOI: http://dx.doi.org/10.5772/intechopen.86728*

#### **Figure 9.**

*Beyond LEO - Human Health Issues for Deep Space Exploration*

mice. Measuring RII, therefore, may be a sensitive test for stress reactions during

*Densitometric analysis of PAGE protein separation and anti-RII and anti-α-amylase reactivity in STS-135 mice. (A) PG protein samples from mice housed in, top panel, flight; middle panel, habitat; and bottom panel, vivarium type cages. The lighter curve represents the protein profile; the shaded area is the reactivity to anti-RII antibody. The ordinate axes are integrated density values of the proteins on the left-hand axis, and the integrated density values for RII and the reactivity of RII fragment (Rfr) on the right-hand axis. (B) PG α-amylase Western blotting. The ordinate shows integrated density, and the error bars show ±5% error. C1, vivarium control; C2, habitat control; F, flight. The values on the ordinate axis (ID) are integrated density in*

reduction due to chronic long-term flight conditions.

The variability may be due to the sensitivity of responses affecting RII synthesis. Previous studies point to a rapid and transient increase in the cases of brief acute stress, for example lift off of a spacecraft, followed by long-term, perhaps low level, prolonged time under stress, decrease. For example, a 60-day to a year tour resulting in a decrease of RII and leveling off at concentrations below normal. Eventual physiologic adjustment to flight conditions may start to bring RII production toward normal. An apparent increase also may result from a rough landing that might have occurred in the Bion-M1 flight and the acute response obliterating any

Tissue extract samples showed a large faster moving component, presumably an RII fragment. The fragments did resemble the densitometric changes in the flight versus the control. These differences did not completely account for the change of flight values compared to the control. There may have been smaller fragments not visible on the Western blot that could account for the decreases in flight RII.

**62**

spaceflight.

*arbitrary units (with permission, from [13]).*

**Figure 8.**

*Electrophoresis and Western blotting of flight (F) and control (C) PG extracts from mice of the Bion-M1 mission. (A) Protein banding patterns of the flight and control animals (F and C). The left lane (M) shows the relative mobilities of marker proteins of kilodalton (kD) size from 110 to 15 marked on the ordinate. Western blotting for RII is shown in the two right most lanes with two major bands, the first at an estimated 50 kDa size (RII), the second deemed to be a fragment between 14 and 20 kDa (Rfr). (B) densitometric profile of the control banding pattern which was not distinguishable from that of the flight (with permission, from [13]).*

#### **Figure 10.**

*Microarray analysis of secretory protein gene expression in PG of mice flown on STS-135 and the Bion-M1 biosatellite. Results are expressed as log2 of the ratio of expression in flight mice to that in habitat control mice. Amy1, α-amylase; Bpifa2, PSP, Prpmp5, PRP; Prkar2a, RII.*

#### **2.3 Gene expression**

Microarray analyses of the PG showed significant changes in the expression of numerous genes of flight mice compared to habitat ground control mice. In female mice flown on STS-135, the expression of 130 genes was significantly upregulated (log2 ratio ≥ 1), and 75 genes were downregulated (log2 ratio ≤ − 1), (**Figure 10**). In male mice flown on Bion-M1, the expression of 70 genes was upregulated, and 65 genes were downregulated.

Interestingly, significant changes in gene expression occurred in the PG of habitat ground control mice compared to vivarium housed mice. In ground control female mice housed in the NASA Animal Enclosure Modules, the expression of 50 genes was significantly upregulated, and 33 genes were downregulated. For example, Western blotting of PG of STS-135 habitat control mice showed a decrease in the expression of α-amylase (**Figure 8B**). In ground control male mice housed in the Bion-M1 habitats, the expression of 42 genes was significantly upregulated, and 169 genes were downregulated. These results indicate that the effects of the habitats must be considered when assessing the overall effects of spaceflight on animal (as well as human) physiology.

Changes in the expression of secretory protein genes (**Figure 10**), for example, PKA-RII, largely paralleled the changes seen in protein expression as determined by immunogold labeling and Western blotting (e.g., PKA-RII expression in PG from STS-135 flight mice, **Figure 8B**).

There have been a few previous studies of salivary glands of rodents following spaceflight, and saliva collected from astronauts and cosmonauts before and after spaceflight. No changes in PG morphology were seen by light microscopy in mice flown for 12.5 days on Apollo 17 [37]. The SMG of rats flown for 18.5 days on Cosmos 936 and Cosmos 1129 showed a reduced glycoprotein content as determined by light microscopic histochemical staining [38, 39]. The saliva of 18 astronauts making up the primary and backup crews for Skylab missions of 28-, 59- and 84-days was analyzed preflight and postflight for flow rate, electrolytes, protein, immunoglobulin A (IgA) and lysozyme [40]. Changes were minimal except for an increase in IgA and a decrease in lysozyme concentrations. α-Amylase in cosmonaut saliva was decreased following an 18-day flight (uncited statement in [41]). The use of saliva for monitoring drug absorption was proposed, and saliva levels of acetaminophen were determined in 1 astronaut [42]. Analyses of saliva of cosmonauts during long-term spaceflight showed levels of cortisol below baseline [43], whereas salivary cortisol biorhythms and concentrations were preserved in astronauts onboard Spacelab [44] and cosmonauts on the International Space Station (ISS) [45]. Transient increases in saliva urea and phosphate concentrations, monitored in 2 astronauts during 6 months on the ISS, were consistent with serum concentrations reported in earlier studies [46]. Although studied in astronaut plasma, not saliva, in the NASA Twin Study, EGF and NGF levels were altered during a 340-day flight and after landing [47]. Our studies and those cited above indicate the feasibility of using saliva to monitor astronaut physiology and health.


**2.4 Statistical analysis**

164 From Preconception to Postpartum

Fetal blood was obtained by cordocentesis from the umbilical vein, a technique carried out without maternal premedication, and only under local anesthesia at the puncture site

Five hundred microlitres of umbilical venous blood were collected in a heparinised syringe for gasometric and acid-base analyses, pH, partial CO2 pressure (pCO2), bicarbonate

The concentrations of ketone bodies (aceto-acetate and beta-hydroxybutyrate), free fatty

Two hundred microlitres of umbilical venous blood were collected on sodium fluoride to measure glucose and lactate, and 200 µl were collected without anticoagulant to measure

The good quality of the sample was verified, in particular the absence of contamination by maternal blood or amniotic fluid (Forestier, 1988). An immediate check was made by determining the erythrocyte group iI, and then a Kleihauer test, red and white cell count

The serum hCG concentration of fetal blood was also measured, this test being proposed as a sensitive contamination marker due to the low hCG content of fetal serum, compared with

Fetal blood samples were stored in ice at +4°C and transported to the laboratory immediately. The blood pH and gas measurement and the deproteinisation of the whole blood with perchloric acid for the ketone bodies determination were carried out upon receipt of the samples; the deproteinisation supernatants were decanted and kept at -20°C. The blood was centrifuged at +4°C for the other analyses. The plasma glucose, lactate, cholesterol and hCG concentrations were determined immediately; the free fatty acid

The sample storage conditions were verified for the quantitative analysis carried out after

The gasometric and acid-base analyses (pH, pO2, pCO2, bicarbonate, SaO2) were carried out

The glucose and lactate concentrations were determined with the Ektachem 500 automated analyser (Kodak, New York, United States) by an enzymatic method using glucose oxidase (EC <IP_ADDRESS>) and lactate oxidase (EC <IP_ADDRESS>) and a measurement by reflectometry (reference

The total free fatty acid concentration was measured by a manual colorimetric enzymatic assay (Okabe et al., 1980), using an acyl-coenzyme A synthetase (EC <IP_ADDRESS>), an acylcoenzyme A oxidase (EC <IP_ADDRESS>) and a peroxidase (EC <IP_ADDRESS>) (Biomérieux, Marcy l'Etoile,

interval in adult blood: 3.6 – 5.8 mmol/l for glucose and 0.7 – 2.1 mmol/l for lactate).

that of the maternal blood and / or amniotic fluid (Dommergues et al., 1993).

contents were determined subsequently on the plasma kept at -20°C.

using the ABL 300 analyser (Radiometer, Copenhagen, Denmark).

concentration, partial oxygen pressure (pO2) and oxygen saturation (SaO2).

acids (FFA) and cholesterol were evaluated on the same sample.

and a leukocyte differential count were carried out.

**2.2 Sampling procedures**

(Daffos, 1983).

hCG.

freezing.

France).

**2.3 Analytical methods**

The comparative study between the results of the control group and the pathological group was carried out using the Student's t-test (unpaired series) and the Mann-Whitney U test (non-parametric test). The search for a possible relation between different constituents measured in the umbilical venous blood was carried out by calculating the linear correlation coefficient r and the Spearman coefficient rs. The significance of the correlations was evaluated with Fisher's exact test.

In the control group, an analysis by linear regression was used to study any changes in the parameters according to gestational age (expressed as weeks of amenorrhea).

A p value below 0.05 was considered to be statistically significant.


*3.1.1 Grazing resource*

The veld of the SEL is described as "*Aristida*-*Dactyloctenium*-*Eragrostis* other species grassveld". It has a carrying capacity of 0.084–0.14 tropical livestock units per hectare [6]. The grazing period ranges from November/December to April/ May. The veld remains nutritious and palatable for livestock across seasons. The herbaceous layer is dominated by *Aristida adscensionis* L., *Dactyloctenium giganteum* B.S. Fisher & Schweick., *Eragrostis viscosa* [Retz.] Trin., *Chloris virgata* Sw., and on deeper soils with more moisture, *Urochloa* spp., *Panicum* spp., *Cenchrus ciliaris* L., and *Digitaria* spp. [21]. On well-managed grazing systems, cattle exhibit annual live weight gains of 15 kg/ha. However, herbaceous species structure and composition are strongly influenced by seasonality of rainfall. For instance, the biomass disappears rapidly in drought years or when the start of the rainy season is delayed (**Figure 1**) [6]. Therefore, there is a need for supplementary feeding, especially during this period of scarcity of the grazing resource.

## *3.1.2 Crop residues*

In the SEL, poor-quality cereal crop residues (less than 4% crude protein) form the bulk of livestock supplementary feed in the dry season, which normally extends from May/June to October/November. The predominant crops are sorghum, millet, and maize. However, they are deficient in essential nutrients such as protein, phosphorus, calcium, and, to some extent, energy [22]. Such supplements have low feed intake resulting from low degradability and low digestibility. Therefore, they do not provide for optimum microbial growth in the rumen. As a result, animals raised on these low nutritive feeds exhibit poor condition and reduced reproductive performance [23]. Crop residues are managed in many ways

#### **Figure 1.**

*The grazing resource during dry seasons in the South East Lowveld of Zimbabwe.*

#### **Figure 2.**

*Maize stover forms part of the bulk of cereal stover supplements in the dry season.*

for livestock feeding. Cereal stovers are either grazed in situ or stored in stacks for supplementation during the dry season (**Figure 2**). During prolonged dry seasons, the first preference is for maintenance of productive animals such as lactating cows or the sick. Haulms from leguminous crops such as cowpea and groundnuts are also used in stall-feeding. Despite being of higher nutritive value than cereal stovers, they have limited availability as leguminous crops are not commonly cultivated at large scale. Recently, conservation agriculture has presented conflict of interest in utilisation of crop residues. Conservation agriculture is a farming method that utilises crop residues to retain moisture and enrich the soil [24]. Increased adoption of conservation agriculture creates limitations in the availability of crop residues for livestock feeding.

### *3.1.3 Browse trees*

Indigenous browse species are an important source of animal feed in livestockbased rural livelihoods of semi-arid areas (**Figure 3**) [25, 26]. The natural vegetation

**107**

**Table 1.**

*Adapted from Mudzengi et al. [36].*

*List of indigenous browse trees in the SEL.*

*Livestock Feeds and Feeding in Semi-Arid Areas of Southern Africa*

of the SEL is predominantly *Colophospermum mopane* [J.Kirk ex Benth.], J. Léonard woodlands found in association with *Kirkia acuminate* Oliv., *Dalbergia melanoxylon* Guill. & Perr, *Adansonia digitata* L., *Combretum* spp., *Acacia* spp., and *Commiphora*

[Harms] C.A.Sm. was discovered as a medicinal feed that helps livestock to survive drought [6]. Other browse species of the SEL are presented in **Table 1**. Most indigenous browse species remain abundant, evergreen, and relatively high in protein, metabolisable energy, vitamins, and minerals across seasons [27]. Unlike herbaceous species, browse species are less susceptible to climatic fluctuations, with crude protein (CP) levels of approximately 10% even in the dry season [28]. However, early and increased dependence on browse by livestock in semi-arid areas of the

spp. In addition, recently, a shrubby legume called *Neorautanenia brachypus*

**Scientific name Vernacular/English name** *Acacia albida* Shokoshoko/winter thorn *Acacia karroo* Muunga/sweet thorn

*Acacia xanthophloea* Kelenga/fever tree *Adansonia digitata* Mabuwu/baobab/muwu

*Aloe cameronii* Mhangani/aloe *Berchemia discolour* Munyii/bird plum *Boscia albitrunca* Shukutsu/shepherd's tree

*Brachystegia spiciformis* Musasa

*Julbernadia globiflora* Mutondo

*Neorautanenia brachypus* Zhombwe *Phragmites mauritianus* Shanga/reed grass

*Acacia tortilis* Sesani/umsasane/umbrella thorn

*Cassia abbreviata* Murumanyama/long-tail cassia *Cissus quadrangularis* Chiololo/chiololoti/muvengahonye *Colophospermum mopane* Mopane/xanatsi/turpentine tree *Combretum apiculatum* Chikukutsi/red bushwillow *Combretum imberbe* Mutsviri/mondo/monzo/leadwood *Dichrostachys cinerea* Mupangara/ndenge/sickle bush *Diospyros mespiliformis* Musuma/tithoma/jackalberry *Ficus sycomorus* Muonde/mikuwa/sycamore fig *Hippocratea crenata* Sengeti/valley paddle pod *Hyphaene petersiana* Makwangwala/Ilala/real fan palm

*Kigelia africana* Pfungu/mumvewa/sausage tree *Lonchocarpus capassa* Mupanda/umchitamuzi/rain tree *Mimusops zeyheri* Hlatsva/Chechete/red milkwood

*Salvadora persica* Dhungulu pokwe/mustard tree *Sclerocarya birrea* Mupfura/marula/mufura *Xanthocercis zambesiaca* Muhlaru/Musharo/Nyala berry

*DOI: http://dx.doi.org/10.5772/intechopen.90109*

*Livestock Feeds and Feeding in Semi-Arid Areas of Southern Africa DOI: http://dx.doi.org/10.5772/intechopen.90109*

*Livestock Health and Farming*

**Figure 1.**

**Figure 2.**

**106**

*3.1.3 Browse trees*

ity of crop residues for livestock feeding.

for livestock feeding. Cereal stovers are either grazed in situ or stored in stacks for supplementation during the dry season (**Figure 2**). During prolonged dry seasons, the first preference is for maintenance of productive animals such as lactating cows or the sick. Haulms from leguminous crops such as cowpea and groundnuts are also used in stall-feeding. Despite being of higher nutritive value than cereal stovers, they have limited availability as leguminous crops are not commonly cultivated at large scale. Recently, conservation agriculture has presented conflict of interest in utilisation of crop residues. Conservation agriculture is a farming method that utilises crop residues to retain moisture and enrich the soil [24]. Increased adoption of conservation agriculture creates limitations in the availabil-

*Maize stover forms part of the bulk of cereal stover supplements in the dry season.*

*The grazing resource during dry seasons in the South East Lowveld of Zimbabwe.*

Indigenous browse species are an important source of animal feed in livestockbased rural livelihoods of semi-arid areas (**Figure 3**) [25, 26]. The natural vegetation of the SEL is predominantly *Colophospermum mopane* [J.Kirk ex Benth.], J. Léonard woodlands found in association with *Kirkia acuminate* Oliv., *Dalbergia melanoxylon* Guill. & Perr, *Adansonia digitata* L., *Combretum* spp., *Acacia* spp., and *Commiphora* spp. In addition, recently, a shrubby legume called *Neorautanenia brachypus* [Harms] C.A.Sm. was discovered as a medicinal feed that helps livestock to survive drought [6]. Other browse species of the SEL are presented in **Table 1**. Most indigenous browse species remain abundant, evergreen, and relatively high in protein, metabolisable energy, vitamins, and minerals across seasons [27]. Unlike herbaceous species, browse species are less susceptible to climatic fluctuations, with crude protein (CP) levels of approximately 10% even in the dry season [28]. However, early and increased dependence on browse by livestock in semi-arid areas of the

#### **Table 1.**

*List of indigenous browse trees in the SEL.*

SEL during the dry season limits their availability in the rest of the season [29]. Fresh leaves of species such as *C. mopane*, for instance, are high in tannins and lignin [30, 31]. Additionally, indigenous browse species normally attract multiple uses at the livestock-wildlife interface with the more visible, more dominant, and more frequent browse species having more uses than less apparent plants [32]. They are used as sources of firewood, timber, fruits, edible roots, bark and leaves, and human and ethnoveterinary medicines [33–36]. Competitive use increases vulnerability to overutilisation, unsustainable harvesting, and mismanagement.


There have been reported cases of aflatoxin outbreaks in Kenya which have led to severe poisoning in school children and adults fed on maize products, some of the products being donations by WHO food programmes for the school feeding programme [112, 113, 123]. These outbreaks of aflatoxin prevalence and aflatoxicosis have been blamed on the lack of regulations and control measures including lack of adherence to handling procedures such as drying period, maintaining required moisture levels, removal of damaged grains, lack of optimal ventilation and temperature during storage, prevention of insect damage which encourages moulding, failure by the national grain cereal companies to purchase the grains from farmers on time and failure to perform routine analysis of moisture and aflatoxin presence in the produce before milling [76]. It has been reported that the most critical interval of drying maize in Kenya is from when it starts drying up, down to approximately 20% moisture, and during this interval moulds occur more easily than any other period [26]. This period can be very long, ranging from 28 to 58 days, respectively, when traditional storage methods are adopted [26], during which, grains are subjected to extreme fluctuations in weather such as rainfall. In sub-Saharan Africa, weather is critical in addition to the prevalence of the S-strain of *Aspergillus flavus* which is more toxic as it produces more aflatoxins than any other strain of *A. flavus*. Nontoxic L-strain of *A. flavus* has been used to competitively exclude the producers through propagation during crop infection and thereby limit contamination in some countries such as the USA [76]. These highly competitive atoxigenic strains of *A. flavus* are applied to soil after which they spread to the crop, excluding the toxic strains [76]. There are about eight nontoxinproducing strains of *A. flavus*, which are capable of radically reducing aflatoxin in maize by 99% [76] and have been tried in Nigeria.

In Kenya, researchers at the Kenya Agricultural and Livestock Research Organization developed and manufactured a product called Aflasafe KE01 to fight aflatoxins in 2016 although this product has not yet trickled down significantly to the small-scale farmer. Aflasafe KE01 consists of four friendly strains of *A. flavus* which do not produce aflatoxins as active ingredient with sterilized sorghum and a binder making up 97% of the solid formulation which is applied preharvest by

**25**

allowed limit of AFM1.

*Aflatoxin B1: Chemistry, Environmental and Diet Sources and Potential Exposure in Human…*

broadcast during plant growth in the field (KALRO website, www.kalro.org). A single application is required in each cropping season to protect maize. The product has achieved between 80 and 99% reduction of aflatoxins in maize and groundnuts at harvest and in storage. Since soil is habitat for aflatoxin-producing fungi, contamination while the crop is still in the field or later during storage and processing is irreversible. Although Aflasafe KE01 reduces contamination in the field, it can only be effective if adopted alongside other safe standard procedures such as proper handling and storage of produce. However, the use of such techniques in Kenya has still not been felt nationally even though training of experts and building capability in Kenya for aflatoxin control have been very effective [76]. It has been recommended that contaminated maize and other grains such as millet be sold to ethanol producing factories since aflatoxins do not appear in the distilled alcohol [114], instead of using them to produce animal feed which makes the situation worse. Such developed country approaches for managing aflatoxin menace which include the use of food additives to make grain safe for farm animals by detoxifying the grain with anhydrous ammonia which reacts with aflatoxin molecules to destroy its toxicity have also not been adopted [76]. Such treatment, which must be done by trained personnel to avoid ammonia smell in the feed, can reduce aflatoxin by 95% [76]. No methods of analysis exist for detecting zero tolerance; therefore, tolerance levels should be based on a risk assessment approach rather than on analytical detection limits, the limits below which no detection is possible by analytical means [76]. This has not yet been achieved, and therefore a 'below detection limit' reported is just a product of instrument sensitivity and preparation losses but does not preclude trace level contamination and human exposure. So far more and more research have been concentrated on determining aflatoxin prevalence and levels in various foods, but research focus needs to shift towards effects and the use of biomarkers as well as

epidemiological studies to understand the health impacts in Kenya.

Human exposure from milk has been a major issue of concern [113, 115, 116]. This originates from feeding cows with contaminated feeds or encouraging unhygienic conditions during milking, handling and storage of milk. Dairy production is widely practised in Kenya, and it provides a source of income to farmers, animal feed industry workers and all other stakeholders within the value chain [116]. Dairy farming systems in Kenya have changed over the years from direct use of pastures and hay only to commercial type of animal feeding where cowshed feeding is achieved with grain-based concentrates and silage [103, 105]. This practice was adopted due to increased productivity and high demand for the product. Studies have shown that aflatoxin contamination occurs in commercial feeds in Kenya and that exposure of cattle to mycotoxins generally occurs through consumption of contaminated feeds [103, 105, 109, 117]. AFM1 is usually excreted after 12 h in milk and urine when animal feed contaminated with AFB1/AFB2 is administered to the animals [22]. Aflatoxin is highly toxic to livestock, and feed contamination has been linked to increased mortality in farm animals. When cows consume aflatoxin-contaminated feed, they biotransform approximately 3–6% of AFB1 and AFB2 in their liver by hepatic microsomal mixed-function oxidase enzyme system into hydroxylated metabolites AFM1 and AFM2 [118] which are secreted into milk. AFB1, AFM1 and AFM2 aflatoxins have been detected in cow milk in Kenya [105]. Although AFM1 is 1000 times less toxic compared to AFB1, the AFM1 levels are regulated, and milk containing above 0.5 ppb level of AFM1 is considered unfit for human consumption [117]. Many countries have therefore regulated levels of AFB1 in animal feed, and the EU maximum limit has been set to 5 ppb; and it is recommended that animals should consume less than 40 μg/day of AFB1 in order not to exceed the

*DOI: http://dx.doi.org/10.5772/intechopen.88773*

#### *Aflatoxin B1: Chemistry, Environmental and Diet Sources and Potential Exposure in Human… DOI: http://dx.doi.org/10.5772/intechopen.88773*

broadcast during plant growth in the field (KALRO website, www.kalro.org). A single application is required in each cropping season to protect maize. The product has achieved between 80 and 99% reduction of aflatoxins in maize and groundnuts at harvest and in storage. Since soil is habitat for aflatoxin-producing fungi, contamination while the crop is still in the field or later during storage and processing is irreversible. Although Aflasafe KE01 reduces contamination in the field, it can only be effective if adopted alongside other safe standard procedures such as proper handling and storage of produce. However, the use of such techniques in Kenya has still not been felt nationally even though training of experts and building capability in Kenya for aflatoxin control have been very effective [76]. It has been recommended that contaminated maize and other grains such as millet be sold to ethanol producing factories since aflatoxins do not appear in the distilled alcohol [114], instead of using them to produce animal feed which makes the situation worse. Such developed country approaches for managing aflatoxin menace which include the use of food additives to make grain safe for farm animals by detoxifying the grain with anhydrous ammonia which reacts with aflatoxin molecules to destroy its toxicity have also not been adopted [76]. Such treatment, which must be done by trained personnel to avoid ammonia smell in the feed, can reduce aflatoxin by 95% [76]. No methods of analysis exist for detecting zero tolerance; therefore, tolerance levels should be based on a risk assessment approach rather than on analytical detection limits, the limits below which no detection is possible by analytical means [76]. This has not yet been achieved, and therefore a 'below detection limit' reported is just a product of instrument sensitivity and preparation losses but does not preclude trace level contamination and human exposure. So far more and more research have been concentrated on determining aflatoxin prevalence and levels in various foods, but research focus needs to shift towards effects and the use of biomarkers as well as epidemiological studies to understand the health impacts in Kenya.

Human exposure from milk has been a major issue of concern [113, 115, 116]. This originates from feeding cows with contaminated feeds or encouraging unhygienic conditions during milking, handling and storage of milk. Dairy production is widely practised in Kenya, and it provides a source of income to farmers, animal feed industry workers and all other stakeholders within the value chain [116]. Dairy farming systems in Kenya have changed over the years from direct use of pastures and hay only to commercial type of animal feeding where cowshed feeding is achieved with grain-based concentrates and silage [103, 105]. This practice was adopted due to increased productivity and high demand for the product. Studies have shown that aflatoxin contamination occurs in commercial feeds in Kenya and that exposure of cattle to mycotoxins generally occurs through consumption of contaminated feeds [103, 105, 109, 117]. AFM1 is usually excreted after 12 h in milk and urine when animal feed contaminated with AFB1/AFB2 is administered to the animals [22]. Aflatoxin is highly toxic to livestock, and feed contamination has been linked to increased mortality in farm animals. When cows consume aflatoxin-contaminated feed, they biotransform approximately 3–6% of AFB1 and AFB2 in their liver by hepatic microsomal mixed-function oxidase enzyme system into hydroxylated metabolites AFM1 and AFM2 [118] which are secreted into milk. AFB1, AFM1 and AFM2 aflatoxins have been detected in cow milk in Kenya [105]. Although AFM1 is 1000 times less toxic compared to AFB1, the AFM1 levels are regulated, and milk containing above 0.5 ppb level of AFM1 is considered unfit for human consumption [117]. Many countries have therefore regulated levels of AFB1 in animal feed, and the EU maximum limit has been set to 5 ppb; and it is recommended that animals should consume less than 40 μg/day of AFB1 in order not to exceed the allowed limit of AFM1.

*Aflatoxin B1 Occurrence, Detection and Toxicological Effects*

potent, often causing disease even when ingested in minute quantities. They are accumulative, resistant to degradation and also heat resistant implying that ingestion of minute amounts still poses risks. The generation of aflatoxins in processed dagaa was explained by the fact that the samples were collected from the markets during the rainy season in July, when drying was incomplete; hence, the sun-dried dagaa were packed in plastic sacks when they were not completely dry resulting in the growth of moulds [59]. The samples which were dried on a rack with some aeration were found to have lower levels of aflatoxin [59]. In Kenya, aflatoxin contamination was reported to be less common in foods during dry seasons as the drying process is more efficient during that period [50]. Incomplete drying condition has been associated with production of aflatoxins in previous studies [85]. Studies done in Nigeria by Bukola et al. [111] on smoked-dried fishes sold in the markets revealed that aflatoxins B1 (AFB1) and G1 were present in the samples at concentrations between 1.5–8.1 and 1.8–4.5 μg/kg, respectively. These reported cases of aflatoxin contamination in staple foods such as maize flour and fish in Kenya indicate that a very large proportion of the population in Kenya is potentially exposed to sublethal concentrations of aflatoxins including AFB1 in their diet. Previous studies conducted in Uganda, Swaziland, Thailand and Kenya have shown positive correlations between levels of aflatoxin contamination in market food samples and cooked food samples with incidences of hepatocellular cancer and mortalities [25]. However, research on biomarkers to quantify aflatoxin exposure in individuals have still not yet

determined to link aflatoxin exposure with cancer risk in Kenya [4, 59].

maize by 99% [76] and have been tried in Nigeria.

In Kenya, researchers at the Kenya Agricultural and Livestock Research Organization developed and manufactured a product called Aflasafe KE01 to fight aflatoxins in 2016 although this product has not yet trickled down significantly to the small-scale farmer. Aflasafe KE01 consists of four friendly strains of *A. flavus* which do not produce aflatoxins as active ingredient with sterilized sorghum and a binder making up 97% of the solid formulation which is applied preharvest by

There have been reported cases of aflatoxin outbreaks in Kenya which have led to severe poisoning in school children and adults fed on maize products, some of the products being donations by WHO food programmes for the school feeding programme [112, 113, 123]. These outbreaks of aflatoxin prevalence and aflatoxicosis have been blamed on the lack of regulations and control measures including lack of adherence to handling procedures such as drying period, maintaining required moisture levels, removal of damaged grains, lack of optimal ventilation and temperature during storage, prevention of insect damage which encourages moulding, failure by the national grain cereal companies to purchase the grains from farmers on time and failure to perform routine analysis of moisture and aflatoxin presence in the produce before milling [76]. It has been reported that the most critical interval of drying maize in Kenya is from when it starts drying up, down to approximately 20% moisture, and during this interval moulds occur more easily than any other period [26]. This period can be very long, ranging from 28 to 58 days, respectively, when traditional storage methods are adopted [26], during which, grains are subjected to extreme fluctuations in weather such as rainfall. In sub-Saharan Africa, weather is critical in addition to the prevalence of the S-strain of *Aspergillus flavus* which is more toxic as it produces more aflatoxins than any other strain of *A. flavus*. Nontoxic L-strain of *A. flavus* has been used to competitively exclude the producers through propagation during crop infection and thereby limit contamination in some countries such as the USA [76]. These highly competitive atoxigenic strains of *A. flavus* are applied to soil after which they spread to the crop, excluding the toxic strains [76]. There are about eight nontoxinproducing strains of *A. flavus*, which are capable of radically reducing aflatoxin in

**24**

## **7. Aflatoxin B1 regulation in Kenya**

The World Health Organization, in collaboration with the Food and Agriculture Organization, is responsible for assessing the risks to humans caused by mycotoxins through contamination in food and for recommending adequate maximum levels in food and feed. Risk assessments of mycotoxins in food done by the Joint FAO/WHO Expert Committee on Food Additives are used by governments and by the Codex Alimentarius Commission (the intergovernmental standard-setting body for food) to establish maximum levels in food and provide other risk management advice to control or prevent contamination [11]. The outcome of such health risk assessments can either be a maximum tolerable intake (exposure) level or other guidance to indicate the level of health concern (such as the margin of exposure), including advice on risk management measures to prevent and control contamination and on analytical methods and monitoring and control activities [25]. These tolerable daily intakes are used by governments and international risk managers, such as the Codex Alimentarius Commission, to establish maximum levels for mycotoxins in food [11]. The maximum levels for mycotoxins in food are very low due to their severe toxicity. For example, the maximum levels for total aflatoxins set by the Codex in various nuts, grains, dried figs and milk are in the range of 0.5–10 μg/kg [24]. The WHO encourages national authorities to monitor and ensure that levels of mycotoxins in foodstuff on their market are as low as possible and comply with the both national and international maximum levels, conditions and legislation [25].

Different countries and authorities worldwide have rules and regulations governing aflatoxin B1 in foods which include the maximum permissible levels and recommended levels for certain foods. The Kenya Bureau of Standards (KEBS) has adopted the broad Codex standard limits of 5 ppb (for single metabolite) and 10 ppb for total aflatoxins in food but does not have lower limits for sensitive foods such as milk. The US Food and Drug Administration (FDA) had given an action level (maximum permissible) of total aflatoxin (B1) in combination with B2, G1 and G2 in foods as 20 μg/kg above in which the commodity is withdrawn from the markets [59], except milk which has a maximum level of 0.5 ppb. The Food Standards Agency has set a legal limit of total aflatoxins in foods as 10 μg/kg. Higher levels of 100–300 μg/kg are tolerable for some animal feeds. The EU has set maximum permitted levels for aflatoxin B1 in nuts, dried fruits, cereals and spices ranging from 2 to 12 μg/kg, while the maximum permitted level for aflatoxin B1 in infant foods is set at 0.1 μg/kg [119]. The maximum permitted levels for aflatoxin B1 in animal feeds set by the EU range from 5 to 50 μg/kg, and these levels are much lower than those set in the USA [120]. The Joint FAO/WHO Expert Committee on Food Additives has set the maximum permitted total aflatoxin level of AFB1 in combination with the other aflatoxins (B2, G1 and G2) at 15 μg/kg in raw peanuts and 10 μg/kg in processed peanut, while the tolerance level of aflatoxin B1 alone is 5 μg/kg for dairy cattle feed [121, 124, 125]. Results from previous studies have however shown that it is difficult if not impossible to eradicate AFB1 in cereals once produced [26]. For that matter, consumers are left vulnerable to exposure, yet burning of contaminated cereals, one of the most feasible ways of containing the menace, has caused problem of food insecurity in the past.

#### **8. Conclusions**

Aflatoxicosis cases are very common in Kenya, and the major cause is contaminated maize and maize flour. The total aflatoxin and AFB1 levels that have been obtained in maize grains and maize flour are indicating that commercial milling

**27**

**Author details**

Joseph Owuor Lalah1

**Acknowledgements**

Kenya, Nairobi, Kenya

\*, Solomon Omwoma2

3 Department of Chemistry, Maseno University, Maseno, Kenya

\*Address all correspondence to<EMAIL_ADDRESS>
provided the original work is properly cited.

1 Department of Chemical Science and Technology, The Technical University of

The authors wish to thank the National Research Fund (NRF), Nairobi, Kenya,

through a multidisciplinary TUK/MMUST/Maseno/PCPB research grant.

2 Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and Dora A.O. Orony3

*Aflatoxin B1: Chemistry, Environmental and Diet Sources and Potential Exposure in Human…*

and packaging of maize flour reduce the levels of aflatoxins considerably. However, a large population in the rural and urban areas which still rely on maize flour from open markets, through donation or by traditional posho milling, could be more exposed to aflatoxins as these sources increase and fail to reduce the levels, respectively. More research is needed to identify and determine aflatoxin levels in other produce such as beans, peanuts, groundnuts and their processed products. The current KEBS regulation and maximum allowable limits, in terms of total or single metabolite, are adequate for monitoring and controlling aflatoxicosis menace; however, for export produce and for long-term control of aflatoxicosis in the country, the maximum allowable limits need to be reviewed and lowered. With improvements in analytical techniques which are capable of giving lower detection limits, maximum allowable limits can be lowered to almost zero tolerance to reduce aflatoxicosis and hepatocarcinogenesis in human in Kenya. Although a lot of research in Kenya has gone into identification and determination of aflatoxin levels in various human foods and animal feeds and their detoxification mechanisms, it is still not possible to directly link AFB1 exposure to liver cancer as less epidemiological and biomarker studies have been done in Kenya to confirm such linkage.

*DOI: http://dx.doi.org/10.5772/intechopen.88773*

*Aflatoxin B1: Chemistry, Environmental and Diet Sources and Potential Exposure in Human… DOI: http://dx.doi.org/10.5772/intechopen.88773*

and packaging of maize flour reduce the levels of aflatoxins considerably. However, a large population in the rural and urban areas which still rely on maize flour from open markets, through donation or by traditional posho milling, could be more exposed to aflatoxins as these sources increase and fail to reduce the levels, respectively. More research is needed to identify and determine aflatoxin levels in other produce such as beans, peanuts, groundnuts and their processed products. The current KEBS regulation and maximum allowable limits, in terms of total or single metabolite, are adequate for monitoring and controlling aflatoxicosis menace; however, for export produce and for long-term control of aflatoxicosis in the country, the maximum allowable limits need to be reviewed and lowered. With improvements in analytical techniques which are capable of giving lower detection limits, maximum allowable limits can be lowered to almost zero tolerance to reduce aflatoxicosis and hepatocarcinogenesis in human in Kenya. Although a lot of research in Kenya has gone into identification and determination of aflatoxin levels in various human foods and animal feeds and their detoxification mechanisms, it is still not possible to directly link AFB1 exposure to liver cancer as less epidemiological and biomarker studies have been done in Kenya to confirm such linkage.


**Chapter 9**

*Mineralogy - Significance and Applications*

ε-Fe2O3 in post-annealing of Fe2O3/ SiO2 nanostructure: Synthesis, computational particle shape analysis

[64] Sakurai S, Tomita K, Hashimoto K, Yashiro H, Ohkoshi S. Preparation of the nanowire form of ε-Fe2O3 single crystal and a study of the formation process. Journal of Physical Chemistry

in micrographs and magnetic properties. Ceramics International.

C. 2008;**112**(5):20212-20216

[65] Sakurai S, Jin J, Hashimoto K, Okhoshi S. Reorientation phenomenon

in a magnetic phase of ε-Fe2O3 Nanocrystal. Journal of the Physical Society of Japan. 2005;**74**(7):1946-1949

[66] Gao H, Yang J. Nanoscale silicon dioxide prepared by sol-gel process. Modern Applied Science.

on Nanomaterials-Research & Application; Brno, Czech. 2017

[68] Tauxe L, Mullender TAT, Pick T. Potbellies, wasp-waists, and superparamagnetism in magnetic hysteresis. Journal of Geophysical Research: Solid Earth.

1996;**101**(B1):571-583

2009;**19**(2):6706-6712

[67] Nikolic VN, Tadic M, Mrakovic A, Spasojevic V. Unusual temperature dependence of coercivity in ε-Fe2O3 phase. In: 9th International Conference

[69] Guo XH, Deng YH, Gu D, Che RC, Zhao DY. Synthesis and microwave absorption of uniform hematite nanoparticles and their core-shell mesoporous silica nanocomposites. Journal of Materials Chemistry.

2010;**4**(9):152-156

2017;**43**(3):7497-7507

**124**


**5. Special populations**

Children and pregnant women are at the highest risk for severe malaria when traveling to endemic areas and increased vigilance should be taken when dealing with these populations. It should be recommend that travel to endemic areas with a risk of transmission be avoided by these populations if possible, however if patients insist, the provider should stress that the traveler or the parents of the traveler insure that both personnel protective measures and chemoprophylaxis are strictly adhered to.

### **5.1 Pregnancy**

Contracting malaria while pregnant puts the mother at an increased risk for adverse outcomes. Malaria infection during pregnancy has been associated with premature labor, abortion and stillbirth. The traveler should be counseled that the diagnosis of malaria in pregnancy may be difficult due to relatively low parasitemia at clinical presentation. A very high degree of suspicion should be taken when a pregnant women presents with fever in an endemic area, as missing the diagnosis could have grave consequences (McGready et al., 2004). Appropriate precautions should be followed including mosquito avoidance and control measures discussed previously as well as chemoprophylaxis when clinically indicated. Reviewing label-specific information and current CDC recommendations should be adhered to. There are no published data indicating elevated risks with the use of DEET in pregnant or lactating women, and current U.S. Environmental Protection Agency and CDC sources do not advise additional precautions for using FDA-approved insect repellants in this population (Koren et al., 2003; Zielinski-Gutierrez et al., 2012). Chemoprophylaxis in pregnancy is limited, as both doxycycline and primaquine are contraindicated, and atovoquone/proguanil is not currently recommended due to lack of safety data from clinical studies. Medications considered safe during pregnancy include chloroquine and mefloquine. While data in the past have only recommended mefloquine in the last half of pregnancy, current recommendations state that there is no evidence of adverse outcome if taken in any of the three trimesters of pregnancy when no other option is available (CDC, 2012).

#### **5.2 Children**

Children are at risk of malaria and the associated complications while traveling to endemic areas, and should have the same personal protective measures as adults. DEET has been shown to be safe and effective and is recommended for use by both the CDC and the American Academy of Pediatrics (AAP) for all children over 2 months of age at concentrations between 10-30% based on duration of protection required (Koren et al., 2003; AAP, 2009, 2011; CDC, 2012). Chemoprophylaxis for children is not as restricted as for pregnant women, with contraindications including doxycyline usage in children under 8 and primaquine usage in G6PD deficient patients. Atovaquone/proguanil is FDA approved for children greater than 11kg but recommended for off-label use by the CDC and AAP for children >5 kg. Mefloquine is only FDA approved for children > 5 kg and older than 6 months of age, but when necessary recommend off-label for children < 5kg and any age (AAP, 2009; CDC, 2012). Parents of very young infants should be counseled to avoid areas endemic for malaria given the risk of severe disease in this population. Adherence to personal protective measures and chemoprophylaxis if often poor in children, and thus it must be stressed to the traveling parent the importance of these precautions.


**Abstract**

Municipal solid waste (MSW) composition, natural transformation, dynamics and impacts on inland water bodies in Nigeria were examined, using dumpsites and landfills as the common markers. Nigeria is estimated to have over 178.5 million people and kg/capita/day of 0.26–1.02 MSW, projected to increase with the expansion of the economy which is in need of better articulated MSW management strategies. The enormous natural inland surface and groundwater resources are daily challenged directly and indirectly, through decline in physical, chemical and biological quality. Solid waste disposal along the waterways and leachates from natural activities on materials at dumpsites and landfills was strongly identified and recognized as the source of pollutant inputs. The immediate and projected public health consequences in changes in inland waters were provided for resident aquatic organisms, some of which serves as food for resident human populations that are largely dependent on these water bodies for their daily water requirements.

**Keywords:** Nigeria, inland water bodies, municipal solid wastes, water quality, public health


**3. Kinetic Considerations**

The use of ToF-SIMS has been able to add to the morphological model derived by NR meas‐ urements by examining both the vertical as well as the lateral distribution of PCBM and P3HT in BHJ films [35]. In 150 nm thick films spun coated from a 1:1 weight ratio of P3HT:PCBM chlorobenzene solutions, ToF-SIMS imaging showed that the lateral phase sep‐ aration (within the limit of the micron resolution of SIMS imaging) was similar before and after an annealing treatment at 140ºC for 30 min. However, depth profiling clearly shows a vertical phase separation of P3HT:PCBM on the pristine blend (before annealing), with a higher concentration of PCBM close to the PEDOT:PSS interface. On the other hand, after annealing, the cross-sectional images of PCBM and P3HT are both uniform along the verti‐ cal axis showing that the annealing treatment suppresses the vertical phase segregation. Us‐ ing low voltage, high resolution TEM, Beal *et al.* [36] revealed some details of the mechanism of PCBM domain migration associated with the vertical segregation within P3HT:PCBM so‐

Xue *et al.* [37] have used the variation of the post-annealing cooling rate to create a series of "snapshots" of the reorganization processes that occur upon annealing. P3HT:PCBM blend devices exhibit a complex vertical stratification of both crystallinity and blend composition. Using a combination of UV-vis spectroscopy, XRD, NEXAFS, AFM, and contact angle meas‐ urements, they showed that annealing resulted in the formation of three distinct vertical lay‐ ers. Diffusion of PCBM from the interfaces into the bulk of the film results in the formation of (a) a P3HT rich substrate interfacial (wetting) layer, (b) a homogeneous 'bulk'central lay‐ er, and (c) a P3HT-rich air interfacial (capping) layer. The orientation of the P3HT molecules was shown to vary from *c*-axis P3HT alignment in the wetting layer at the substrate inter‐ face to an *a*-axis aligned in the capping layer at the air interface and also in the bulk layer. The data showed that by slowing the post-annealing cooling rate devices with significantly enhanced efficiencies can be prepared. This improvement in device performance was corre‐ lated with the observed increased crystallinity and hence polymer alignment, and also phase segregation both at the interfaces and in the bulk film. In particular, they found that slow cooling resulted in an aligned interfacial active layer/substrate structure that is benefi‐

Theoretical descriptions indicate a segregation preference for a typical photovoltaic device is where the donor (P3HT) is concentrated close to the substrate, and the acceptor (PCBM) next to the top surface, onto which the cathode (for example Al) is deposited. This distribu‐ tion of components is expected to enhance the selectivity of the contacts towards one type of charge carrier and so reduce charge leakage. As discussed above, there are clearly contradic‐ tory results in the experimental literature concerning the exact nature of this vertical phase segregation. However, there is agreement that annealing leads to an increase of the PCBM concentration closer to the cathode [30, 33-35], and this has been pointed out as being one of the reasons for the improvement of device efficiencies that is usually observed upon anneal‐ ing treatments. The timing of the annealing process, i.e. before or after the deposition of a metal electrode, is also known to influence the results. Post-production thermal annealing can improve the evolution of well-ordered nanoscale morphology because of a limitation of

lar cells by giving direct confirmation of P3HT and PCBM crystallization.

cial for charge transport.

218 Optoelectronics - Advanced Materials and Devices

PCBM overgrowth, that is, due to the confinement effect.

As shown in Figure 2, Muller *et al.* [11] and Kim *et al.* [12] reported an eutectic composition (Ce) of Ce ≈ 35 – 40 wt% PCBM and Zhao *et al.* [13] a value of Ce≈ 60 wt% PCBM. However, whilst these authors were trying to extract the thermodynamic behavior of the blends, kinet‐ ic factors are clearly affecting the resulting observations. It is these types of discrepancies in observed phase behavior that highlights the difficulty in understanding the fundamental relationship between morphology and device performance. Although the morphology of the BHJ is ultimately determined by thermodynamic factors, the observed thin film morphology can be dominated by the kinetics of the film preparation methods and parameters used, including solvent evaporation/drying rates and by the kinetics of cooling after annealing. Herein lies some of the answer as to the reason for the contradictions in the observed phase behavior and morphology of these systems, since in putting together a device, the process‐ ing conditions between different groups often vary and also almost certainly do not allow the system to reach a global free energy minima and hence true a thermodynamic state. Changes to processing conditions are well known to make big variations in device performance, but there are also much subtler effects associated with the well-known irreproducibility in other‐ wise identical processing conditions, which are problematic for OPV development.

The effect of drying kinetics on the resultant P3HT:PCBM blend has a profound effect on the final device characteristics [38], where it was found that films dried slowly had better per‐ formance characteristics (higher external quantum efficiency, higher power conversion effi‐ ciency, higher fill factor, and lower series resistance) than the rapidly dried films. The charge carrier mobility of holes and electrons in P3HT:PCBM thick films was shown to have more balanced transport properties and non-dispersive dynamics for the slowly dried films, where as the rapidly dried film displayed dispersive dynamics and unbalanced transport. All these differences in performance were explained by the rate of solvent evaporation, as fast solvent loss quenches the phase separation process, and conversely the longer the blend is mobile and contains solvent the more the mixture will proceed to a more phase separated state. Campoy-Quiles *et al.* [29] have studied the morphology changes induced by slow dry‐ ing and vapour annealing and showed that the PCBM concentration profile changes as the spin-coating speed (and hence the rate of drying) is reduced. Slow drying has a qualitatively similar effect to thermal annealing, whereby the composition gradient becomes more pro‐ nounced and the surface-segregated PCBM concentration increases.

The time-dependent morphology evolution of blend films of P3HT and PCBM, was investi‐ gated by Jo *et al.* [39], using two different annealing treatments with different morphology evolution time scales, i.e. a high-temperature thermal annealing (150 ºC), and a room-tem‐ perature solvent annealing. Comparing the morphological changes of the blend films after the two annealing treatments, solvent annealing resulted in a more favorable BHJ morpholo‐ gy than thermal annealing. The poor BHJ morphology after thermal annealing under these experimental conditions was attributed to the relatively fast diffusion and aggregation of the PCBM molecules during P3HT crystallization, which interfered with the growth of the elon‐ gated fibrillar P3HT crystals and subsequent evolution of the well-ordered BHJ morpholo‐ gy. These results are however, seemingly contradictory to those of Parnell *et al.* [34], suggesting that there are other factors that are contributing to the observed behaviors.

Figure 6, was compared with the structural changes during crystallization of the ternary P3HT:PCBM:solvent system observed in real time by grazing incidence x-ray diffraction (GIXD). It was shown that PCBM only crystallizes at the final stage of drying although its

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221

**Figure 6.** a) Schematic of the experimental setup for simultaneous real time GIXD and laser reflectometry of doctorbladed thin films in a controlled drying environment. (b) Schematic of P3HT unit cell. (c) Ternary phase diagram of P3HT-PCBM-DCB; the star symbols denote phase transitions in the binary cases. From reference [43]. "Reprinted with

Sobkowicz *et al.* [44] have measured the time- and temperature dependent aggregation of P3HT in o-dichlorobenzene solutions using rheometry and small-angle neutron scattering (SANS). They tried to set a starting point for understanding important aspects of morpholo‐ gy development in drying BHJ films. They found that the presence of PCBM dramatically slows the aggregation of P3HT in solution. Concentration and temperature dependencies were identified, with the latter being the more sensitive parameter. Analysis of the SANS data showed a strong affinity between P3HT and DCB with an interaction parameter that becomes more negative with increasing concentration, and elevated temperature dissolution suggesting UCST behavior in this polymer−solvent system. Modest cooling of P3HT solu‐ tions even in "good" solvents such as DCB resulted in rapid aggregation, although the ag‐ gregated solutions do not completely phase separate, but rather form physical gels consisting of anisotropic structures. An increase in solution modulus of several orders of

permission from (ACS Nano 5 (2011) 8579). Copyright (2012) American Chemical Society."

solubility limit is reached a very early stage of solvent evoporation.

The reasons for the irreproducibility of the performance of P3HT:PCBM BHJ solar cells fab‐ ricated using nominally identical conditions has been investigated by de Villers *et al.* [40]. They showed that this irreproducibility is the result of the occurrence of vertical phase seg‐ regation of P3HT to the top surface, which is controlled by subtle factors in the kinetics of solvent evaporation during spin-coating. When this type of vertical phase separation occurs, electron extraction is hindered by the poor contact between the PCBM component of the BHJ and the cathode.

Wang *et al.* [41] have used in-situ ellipsometry and grazing incidence x-ray scattering (GI-XS) to study molecular self-organization in P3HT and PCBM blend films in real time, during the drying process as they are cast from solution. They have identified three stages in film drying: (I) rapid solvent-evaporation, (II) moderate solvent-evaporation and rapid crystalli‐ zation, and (III) slow solvent-evaporation and slow crystallization. They showed that the on‐ set of fast crystallization commences when the volume fraction of P3HT:PCBM in a wet film reaches a critical volume fraction of 50%. The observed crystallization growth-mechanism is consistent with a heterogeneous nucleation process in which defects or impurities act as nu‐ cleation sites.

The rate of evaporation is clearly affected by the boiling point and vapor pressure of the sol‐ vents used. The influence solvent boiling point on the morphology and photovoltaic per‐ formance of P3HT:PCBMBHJ films produced via spin-coating, has been studied by Ruderer *et al*. [42]. The four solvents considered were chloroform (CF), toluene, chlorobenzene (CB) and xylene. Solar cells made using these solvents had different photovoltaic performances. Using a wide range of experimental techniques it was shown that solubility-driven cluster formation of PCBM occurred in these systems. In films made using solvents with poor solu‐ bility of PCBM many more clusters were formed. As-spun films showed no P3HT crystallin‐ ity, independent of the solvent used. After annealing, P3HT crystals formed with edge-on configuration relative to the substrate as the main orientation, with crystal lattice constants that were also independent of the solvent used. However the crystal sizes increased with in‐ creasing boiling point (i.e. decreasing evaporation rates) of the solvents used, which was at‐ tributed to the increased drying time during spin-coating and residual solvent in the BHJ films. For toluene-, CB-, and xylene-made films, lateral nanostructures were found. In the vertical direction P3HT enrichment layers were detected for toluene- and CB-made films and PCBM enrichment layers for the films made using toluene and xylene. Nevertheless films made using toluene, CB, and xylene showed similar photovoltaic performance. Con‐ versely, films made using chloroform presented a layered structure with a disadvantageous material distribution, with the P3HT hole conductor at the top electrode and the PCBM elec‐ tron conductor at the electron-blocking layer, consequently producing efficiencies that were significantly lower.

Schmidt-Hansberg *et al.* [43] have investigated the dynamics and thermodynamics of molec‐ ular ordering, in P3HT/PCBM mixtures, during film drying from 1,2-dichlorobenzene (DCB). The pathway through the phase diagrams of P3HT and PCBM solutions, as shown in Figure 6, was compared with the structural changes during crystallization of the ternary P3HT:PCBM:solvent system observed in real time by grazing incidence x-ray diffraction (GIXD). It was shown that PCBM only crystallizes at the final stage of drying although its solubility limit is reached a very early stage of solvent evoporation.

gy. These results are however, seemingly contradictory to those of Parnell *et al.* [34], suggesting that there are other factors that are contributing to the observed behaviors.

The reasons for the irreproducibility of the performance of P3HT:PCBM BHJ solar cells fab‐ ricated using nominally identical conditions has been investigated by de Villers *et al.* [40]. They showed that this irreproducibility is the result of the occurrence of vertical phase seg‐ regation of P3HT to the top surface, which is controlled by subtle factors in the kinetics of solvent evaporation during spin-coating. When this type of vertical phase separation occurs, electron extraction is hindered by the poor contact between the PCBM component of the

Wang *et al.* [41] have used in-situ ellipsometry and grazing incidence x-ray scattering (GI-XS) to study molecular self-organization in P3HT and PCBM blend films in real time, during the drying process as they are cast from solution. They have identified three stages in film drying: (I) rapid solvent-evaporation, (II) moderate solvent-evaporation and rapid crystalli‐ zation, and (III) slow solvent-evaporation and slow crystallization. They showed that the on‐ set of fast crystallization commences when the volume fraction of P3HT:PCBM in a wet film reaches a critical volume fraction of 50%. The observed crystallization growth-mechanism is consistent with a heterogeneous nucleation process in which defects or impurities act as nu‐

The rate of evaporation is clearly affected by the boiling point and vapor pressure of the sol‐ vents used. The influence solvent boiling point on the morphology and photovoltaic per‐ formance of P3HT:PCBMBHJ films produced via spin-coating, has been studied by Ruderer *et al*. [42]. The four solvents considered were chloroform (CF), toluene, chlorobenzene (CB) and xylene. Solar cells made using these solvents had different photovoltaic performances. Using a wide range of experimental techniques it was shown that solubility-driven cluster formation of PCBM occurred in these systems. In films made using solvents with poor solu‐ bility of PCBM many more clusters were formed. As-spun films showed no P3HT crystallin‐ ity, independent of the solvent used. After annealing, P3HT crystals formed with edge-on configuration relative to the substrate as the main orientation, with crystal lattice constants that were also independent of the solvent used. However the crystal sizes increased with in‐ creasing boiling point (i.e. decreasing evaporation rates) of the solvents used, which was at‐ tributed to the increased drying time during spin-coating and residual solvent in the BHJ films. For toluene-, CB-, and xylene-made films, lateral nanostructures were found. In the vertical direction P3HT enrichment layers were detected for toluene- and CB-made films and PCBM enrichment layers for the films made using toluene and xylene. Nevertheless films made using toluene, CB, and xylene showed similar photovoltaic performance. Con‐ versely, films made using chloroform presented a layered structure with a disadvantageous material distribution, with the P3HT hole conductor at the top electrode and the PCBM elec‐ tron conductor at the electron-blocking layer, consequently producing efficiencies that were

Schmidt-Hansberg *et al.* [43] have investigated the dynamics and thermodynamics of molec‐ ular ordering, in P3HT/PCBM mixtures, during film drying from 1,2-dichlorobenzene (DCB). The pathway through the phase diagrams of P3HT and PCBM solutions, as shown in

BHJ and the cathode.

220 Optoelectronics - Advanced Materials and Devices

cleation sites.

significantly lower.

**Figure 6.** a) Schematic of the experimental setup for simultaneous real time GIXD and laser reflectometry of doctorbladed thin films in a controlled drying environment. (b) Schematic of P3HT unit cell. (c) Ternary phase diagram of P3HT-PCBM-DCB; the star symbols denote phase transitions in the binary cases. From reference [43]. "Reprinted with permission from (ACS Nano 5 (2011) 8579). Copyright (2012) American Chemical Society."

Sobkowicz *et al.* [44] have measured the time- and temperature dependent aggregation of P3HT in o-dichlorobenzene solutions using rheometry and small-angle neutron scattering (SANS). They tried to set a starting point for understanding important aspects of morpholo‐ gy development in drying BHJ films. They found that the presence of PCBM dramatically slows the aggregation of P3HT in solution. Concentration and temperature dependencies were identified, with the latter being the more sensitive parameter. Analysis of the SANS data showed a strong affinity between P3HT and DCB with an interaction parameter that becomes more negative with increasing concentration, and elevated temperature dissolution suggesting UCST behavior in this polymer−solvent system. Modest cooling of P3HT solu‐ tions even in "good" solvents such as DCB resulted in rapid aggregation, although the ag‐ gregated solutions do not completely phase separate, but rather form physical gels consisting of anisotropic structures. An increase in solution modulus of several orders of magnitude accompanies the aggregation and the pure polymer solution modulus becomes frequency-independent. Although the percent crystallinity in the aggregated solutions can‐ not be calculated directly from these results, it appears that the crystalline fraction is lower in the solutions with PCBM present. These results also lend insight into the film drying process and will ultimately lead to improved processing procedures in pursuit of an opti‐ mized morphology for bulk heterojunction devices.

DMTA – Dynamic Mechanical Thermal Analysis

GIXS – Grazing Incidence X-ray Scattering

ITO – Indium Tin Oxide

NR – Neutron Reflectivity

OPV – Organic Photo-Voltaic

P3HT – poly(3-hexylthiophene)

PCBM – phenyl-C61-butyric acid methyl ester

SANS – Small Angle Neutron Scattering

SIMS – Secondary Ion Mass Spectrometry

TEM – Transmission Electron Microscopy

UCST – Upper Critical Solubility Temperature

2011-2012—Strategic Project—LA 25—2011-2012).

ToF-SIMS – Time-of-Flight Secondary Ion Mass Spectrometry

SAXS – Small-Angle X-ray Scattering

UV-Vis – Ultra-Violet Visible

WAXS – Wide-Angle X-ray Scattering

XRD – X-ray diffraction

**Acknowledgements**

GISANS - Grazing Incidence Small-Angle Neutron Scattering

NEXAFS – Near-Edge X-ray Absorption Fine Structure

GIWAXS/GIXD – Grazing Incidence Wide-Angle X-ray Scattering/x-ray diffraction

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MDMO-PPV – poly(2-methoxy-5-(3',7'-dimethyloctyloxy)-1,4-phenylenevinylene)

MEH-PPV - poly [2-methoxy-5-(2-ethyl-hexyloxy)-1,4-phenylene-vinylene]

PEDOT:PSS – Poly(3,4-EthyleneDiOxyThiophene):Poly(StyreneSulfonate)

Gabriel Bernardo acknowledges financial support from the IPC's (Institute for Polymers and Composites) strategic project: "PEst-C/CTM/LA0025/2011" (Projecto Estratégico—LA 25—

The rate of cooling, after annealing, also has a dramatic influence on the final morphology of the film. A slower cooling rate leads to a greater extent of crystallization, when semi-crystal‐ line polymers or crystalline nano-particles are involved. Despite this fact, only recently have some authors drawn attention to this important factor [37].


*3.2. Possibilistic Estimation Fusion*

Whereas pooling fusion aims at discarding alternatives, estimation fusion assumes that none of the sources are completely wrong and attempts to find a fusion result that is compatible with all information items [4]. Nonetheless, more specific or precise outcomes are still preferable. Estimation fusion has received less attention in the scientific community compared with pooling fusion (The higher number of citations of Dubois's paper [4] compared to Yager's paper [65] reflect the higher attention). Therefore, the following discussion takes a deeper look into the algebraic properties of estimation fusion.

Estimation fusion is based on Zadeh's extension principle, which allows mapping functions to be used on fuzzy sets [66]. Let *Y*, *Z* be a frame of discernments and F : *Y* → *Z*. Let *A* be a fuzzy set defined on *Y* and *B* a fuzzy set defined on *Z*, and then F maps the fuzzy membership function *μA*(*y*) with *y* ∈ *Y* to *μB*(*z*) with *z* ∈ *Z* by *μB*(*z*) = *μA* F−1(*z*) = *μA*(*y*) with *z* = F(*y*). If F results in multiple outputs for the same *y*, then

$$\mu\_B(z) := \max\_{y \in Y \colon \mathcal{F}(y) = z} \mu\_A(y).$$

In multi-source estimation fusion, the input possibility distributions are first pooled by a fusion function—here referred to in this context as G. The result is then mapped by the multi-parameter function F(*x*1, *x*2,..., *xn*) with *xi* ∈ *Xi*, *i* ∈ {1, ..., *n*} onto a new frame of discernment *X*, i.e.,

$$\pi^{(\text{fu})}(\mathbf{x}) = \max\_{\substack{\mathbf{x}\_i \in \mathcal{X}\_i \colon \mathcal{F}(\mathbf{x}\_1, \dots, \mathbf{x}\_n) = \mathbf{x}}} \left( \mathbf{G}(\pi\_i(\mathbf{x}\_i)) \right), \tag{11}$$

for which the notation

$$\pi^{(\text{fu})}(\mathbf{x}) = \left\{ \frac{\mathbb{G}(\pi\_1(\mathbf{x}\_1), \pi\_2(\mathbf{x}\_2), \dots, \pi\_n(\mathbf{x}\_n))}{\mathbb{F}(\mathbf{x}\_1, \mathbf{x}\_2, \dots, \mathbf{x}\_n)} \right\}.\tag{12}$$

is used in the following. The fusion rule in (11) takes the maximum of G*i*(*πi*(*xi*)) for every *n*-tuple (*x*1 ∈ *X*1,..., *xn* ∈ *Xn*), which satisfies F(*x*1,..., *xn*) = *x*.

Yager [65] proposed an estimation fusion rule in which G is the minimum operator and F is defined to be an averaging operator.

**Definition 3** (Averaging Operator)**.** *An operator that satisfies the three properties of commutativity, monotonicity, and idempotency, is referred to as a* mean *or* averaging operator *[4]. Such an averaging operator* avg(·) *lies between* min(·) *and* max(·)*, i.e.,* min(·) ≤ avg(·) ≤ max(·)*.*

Yager's estimation fusion rule [65] is then:

$$\pi^{(\text{fu})}(\mathbf{x}) = \left\{ \frac{\min\_{i \in \{1, \dots, n\}} (\pi\_i(\mathbf{x}\_i))}{\text{F}(\mathbf{x}\_1, \mathbf{x}\_2, \dots, \mathbf{x}\_n)} \right\}. \tag{13}$$

The application of the minimum operator results in maximal specific possibility distributions, which are placed on an averaged frame of discernment. The disadvantages of estimation fusion are that (i) it requires a frame of discernment for which it is sensible to apply averaging operators on and that (ii) estimation fusion may lead to fusion results that have been deemed impossible by all sources, i.e., the results do not satisfy the zero preservation principle [4]. Regarding the first disadvantage, it is often assumed that *X* ⊆ R [65], which is also assumed for the remainder of this section.

If G is also an averaging operator, then a noteworthy interaction between estimation fusion and the frame of discernment takes place, which is relevant for practical implementations.

**Proposition 1.** *If* G *is an averaging operator other than the minimum operator and X* ⊆ R*, then fusion with (13) is influenced by the borders of X. More formally,* min*π*(fu)(*x*)>0 *x is dependent on* min*x*∈*X x and* max*π*(fu)(*x*)>0 *x on* max*x*∈*X x.*

**Proof.** Let *x*a = min *x*∈*X x* and *x*b = max *x*∈*X x*, i.e., *X* = [*x*a, *x*b]. Let *x* = min*i* min *xi*∈*Xi*:*πi*(*xi*)>0 *xi*, i.e., *x* is the smallest element in *X* for which at least one *πi* > 0. Furthermore, let *i* = arg min *i* min *xi*∈*Xi*:*πi*(*xi*)>0 *xi*. If G = min, then, for at least one permutation of the *n*-tuple

(*x*a, *x*a, ... , *x* , ... , *x*a, *x*a): G ⎛ ⎝*π*1(*x*a),..., *πi* (*x* ) % &' ( >0 ,..., *πn*(*x*a) ⎞ ⎠ > 0. This *n*-tuple defines the minimum boundary of *π*(fu) , i.e., min *π*(fu)(*x*)>0 *x* = F - *x*a,..., *x* ,..., *x*a . The same holds for the maximum boundary of *π*(fu) only that *x* = max*i* max *xi*∈*Xi*:*πi*(*xi*)>0 *xi*, *i* = arg max *i* max *xi*∈*Xi*:*πi*(*xi*)>0 *xi*, and max *π*(fu)(*x*)>0 *x* = F - *x*b,..., *x* ,..., *x*b .

An example of the effects of Proposition 1 is illustrated in Figure 2.

**Figure 2.** An example of the interaction between estimation fusion (12) and *X* as discussed in Proposition 1. A frame of discernment *X* = [0, 10] and three possibility distributions are given. Each possibility distribution claims complete knowledge; *π*1(*x* = 3) = 1, *π*2(*x* = 5) = 1, and *π*3(*x* = 7) = 1. The plots show fusion results (dashed red) in which F is the arithmetic mean and G is (**a**) the minimum, (**b**) the maximum, and (**c**) the arithmetic mean operator.

**Corollary 1.** *If X is also unbounded and* F *is an averaging operator other than the minimum or maximum operator, then (13) results in an unbounded π*(fu)*. If X is half-bounded, then π*(fu) *is also half-bounded.*

**Proof.** From Proposition 1 it follows directly that, if F = max, then lim *x*a→−∞ min *π*(fu)(*x*)>0 *x* = F(*x*a,..., *x* ,..., *x*a) = − ∞. If F = min, then lim*x*b→∞ max *π*(fu)(*x*)>0 *x* = F - *x*b,..., *x* ,..., *x*b = ∞.

Consequently, if G is an averaging operator other than the minimum operator, then it is reasonable to apply estimation fusion only on bounded *X*. Otherwise, (12) and (13) lead to fusion results spanning to infinity—even for very precise input possibility distributions.


**3. Data analysis**

#### **3.1 LC/LU accuracy assessment**

Before assessing the PRCs for the study area, the LC/LU image was tested for its accuracy. The accuracy assessment test consisted of collecting 600 referenced points using a stratified random method that randomly assigns points in each class. A 2016 Digital Globe basemap in ArcMap 10.5 of a higher spatial resolution (0.62 m) was utilized to visually interpret the land cover for each reference point. The output table consisted of a confusion matrix that displays the error of omission, the error of commission per class, and overall accuracy ranging from 0 to 1. Another test for accuracy of the LC/LU classification image included calculating the Cohen's kappa (K) coefficient [22].

## **3.2 PRC**

Potential runoff coefficient (PRC) values were derived to represent ratio of the rainfall that would convert to surface runoff per pixel. The PRC for the IRL area was determined by combining the soil texture, LC/LU, and the slope data. The PRC is calculated from a linear relationship between the runoff coefficients and slope, which is shown in Eq. (1) [23].

$$\mathbf{C} = \mathbf{C}\_0 + (\mathbf{1} - \mathbf{C}\_0) \frac{\mathbf{S}}{\mathbf{s} + \mathbf{s}\_0} \tag{1}$$

**125**

*A GIS-Based Approach for Determining Potential Runoff Coefficient and Runoff Depth…*

 is the PRC, S (%) is the slope of the land surface, *C*0 is the PRC for the near zero slope in reference to the first row of every land use class in PRC values for different land use, slope, and soil texture published in [23] which is sourced from published material [24–28]. *so*represents the slope constant for different land use and soil textures that were empirically derived over a collection of studies. Following reclassification, classes for both parameters were assigned arbitrary weighted values and the soil and LC/LU values for the data were multiplied in the ArcMap 10.5 "Raster Calculator" tool. The arbitrary values were assigned to the classes to conveniently identify each combination of LC/LU and soil texture per pixel from the products. The products of the combinations helped derive the *C*0and *s*0 per pixel in the image. The products for the variables were also used to calculate the PRC (Eq. (1)) using the

The total precipitation values were collected for eleven years (2006–2016), and imported into ArcMap 10.5 to be interpolated. The precipitation values (in.) for each of the years were interpolated using the Kriging method with a spherical semivariogram model. The method assumes that the values are more related when in close proximity, and the spatial autocorrelation decreases with distance. After the precipitation was interpolated for each year, the data were multiplied (cell-bycell) by the PRC raster of the corresponding year using the raster calculator tool provided in ArcMap 10.5 toolboxes. The output of the images provided the runoff depth (centimeters) for each year, and the average runoff depth for the eleven-year period (2006–2016) was calculated per pixel (10 m). The outputs of this image can delineate potential sources of runoff for inland waterbodies that may be connected

Concentrations of chlorophyll *a* in the IRL during the 2011 super algal bloom

were compared to runoff depth of surrounding areas. Kamerosky et al. [29] estimated and mapped the Chi *a* concentrations using the Medium Resolution Imaging Spectrometer (MERIS) platform aboard the European Space Agency (ESA) Environmental Satellite (ENVISAT) and calculated Normalized Difference

In order to meet proper data conditions for linear regression analysis in ArcMap 10.5, the raster images were sampled into vector data as a point feature class. Land development intensity (LDI) data was collected from the Florida Department of Environmental Protection (FDEP) Geospatial Open Data Site (http://geodata.dep.state.fl.us/). The LDI serves as a human disturbance gradient that incorporates land use and energy used per unit area [31]. It is used in watershed modeling to delineate human-dominated areas, and to scale the human induced impacts on physiological, biological, and chemical processes. A total of 600 points were randomly placed within the Halifax River and IRL watershed via "Create Random Points" tool. Points that were placed over large waterbodies were deleted, leaving 528 sample points left for the analysis. Values from the LDI and runoff

To adequately assess the relationship between urbanized areas of intense impervious coverage and surface runoff, an ordinary least squares (OLS) regression analysis and geographically weighted regression (GWR) was performed in ArcGIS 10.5. These regression analyses use bandwidth methods to find the

to the lagoon through a network of drainage systems.

**3.4 Linear regression between LDI and runoff depth**

Chlorophyll Index (NDCI) [29, 30].

depth were extracted to the points.

*DOI: http://dx.doi.org/10.5772/intechopen.87163*

Raster Calculator Tool.

**3.3 Runoff depth**

*A GIS-Based Approach for Determining Potential Runoff Coefficient and Runoff Depth… DOI: http://dx.doi.org/10.5772/intechopen.87163*

 is the PRC, S (%) is the slope of the land surface, *C*0 is the PRC for the near zero slope in reference to the first row of every land use class in PRC values for different land use, slope, and soil texture published in [23] which is sourced from published material [24–28]. *so*represents the slope constant for different land use and soil textures that were empirically derived over a collection of studies. Following reclassification, classes for both parameters were assigned arbitrary weighted values and the soil and LC/LU values for the data were multiplied in the ArcMap 10.5 "Raster Calculator" tool. The arbitrary values were assigned to the classes to conveniently identify each combination of LC/LU and soil texture per pixel from the products. The products of the combinations helped derive the *C*0and *s*0 per pixel in the image. The products for the variables were also used to calculate the PRC (Eq. (1)) using the Raster Calculator Tool.