*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

± 3.0%, **Ij-BD** 67.3 ± 2.0%, and **Ij-BHac** 24.4 ±1.0%, and for leaf extracts, the corresponding percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indomethacin (**Indo**), which was employed as the reference drug, the inhibition percentage was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory activity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

shown the presence of terpenes such as phytol, the aliphatic nonacosane, and esterified aliphatic acids [35], whereas in a hexanic fraction obtained from the leaves of *I. semialata*, the main compounds isolated were triterpenes, such as lupeol, α-amyrin, oleanolic acid,

shown the presence of terpenes such as phytol, the aliphatic nonacosane, and esterified aliphatic acids [35], whereas in a hexanic fraction obtained from the leaves of *I. semialata*, the main compounds isolated were triterpenes, such as lupeol, α-amyrin, oleanolic acid, and friedelin [30]. In this report, the presence of esterified aliphatic acids was identified and, as in other species of the *Inga* genus, the presence of lupeol has been established. However, the following compounds: hentriacontane, α-tocopherol, lup-20 (29)-en-3-one

The results corresponding to the anti-inflammatory study of the organic extracts are presented in Figure 3. At the same dose of 1.0 mg/ear, all of the extracts showed anti-

tivity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

stitute of Standards and Technology (NIST) 1.7 Library.

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

The results corresponding to the anti-inflammatory study of the organic extracts are presented in Figure 3. At the same dose of 1.0 mg/ear, all of the extracts showed anti-

± 3.0%, **Ij-BD** 67.3 ± 2.0%, and **Ij-BHac** 24.4 ±1.0%, and for leaf extracts, the corresponding percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indomethacin (**Indo**), which was employed as the reference drug, the inhibition percentage was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory activity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

and 24-methylenecycloartan-3-one, are reported for the first time for this genus.

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

stitute of Standards and Technology (NIST) 1.7 Library.

32 29.19 518.7 (1.02)

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

*2.3. Anti-Inflammatory Activity of Organic Extracts from Inga jinicuil*

inflammatory activity. For the bark extracts, the percentages of inhibition were: **Ij-BH** 34.6 ± 3.0%, **Ij-BD** 67.3 ± 2.0%, and **Ij-BHac** 24.4 ±1.0%, and for leaf extracts, the corresponding percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indo-

and, as in other species of the *Inga* genus, the presence of lupeol has been established. However, the following compounds: hentriacontane, α-tocopherol, lup-20 (29)-en-3-one

from *Inga jinicuil*. However, similar studies have been documented for other species of the *Inga* genus; such is the case for *I. edulis*, where triterpene compounds including lupeol and stigmasterol, as well as aliphatic compounds, have been identified from extracts of the

stigmasterol, as well as aliphatic compounds, have been identified from extracts of the bark and leaves [33,34]. Likewise, extracts from the bark and leaves of *I. laurina* have

It is worth noting that this is the first report of a CG-MS analysis of hexanic extracts from *Inga jinicuil*. However, similar studies have been documented for other species of the *Inga* genus; such is the case for *I. edulis*, where triterpene compounds including lupeol and

It is worth noting that this is the first report of a CG-MS analysis of hexanic extracts from *Inga jinicuil*. However, similar studies have been documented for other species of the

*Inga* genus; such is the case for *I. edulis*, where triterpene compounds including lupeol and stigmasterol, as well as aliphatic compounds, have been identified from extracts of the bark and leaves [33,34]. Likewise, extracts from the bark and leaves of *I. laurina* have

tivity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indomethacin (**Indo**), which was employed as the reference drug, the inhibition percentage

was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory activity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indomethacin (**Indo**), which was employed as the reference drug, the inhibition percentage was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory ac-

methacin (**Indo**), which was employed as the reference drug, the inhibition percentage was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory activity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

percentages were: **Ij-LH** 34.9 ± 1.3%, **Ij-LD** 23.0 ± 1.0%, and **Ij-LHac** 49.6 ± 1.0%. For indomethacin (**Indo**), which was employed as the reference drug, the inhibition percentage was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory ac-

was 75.5 ± 2.2%. As can be seen, the two extracts with the greatest anti-inflammatory activity were **Ij-BD** followed by **Ij-LHac**, and the statistical comparison between the anti-

The results corresponding to the anti-inflammatory study of the organic extracts are presented in Figure 3. At the same dose of 1.0 mg/ear, all of the extracts showed antiinflammatory activity. For the bark extracts, the percentages of inhibition were: **Ij-BH** 34.6

The results corresponding to the anti-inflammatory study of the organic extracts are presented in Figure 3. At the same dose of 1.0 mg/ear, all of the extracts showed anti-

The results corresponding to the anti-inflammatory study of the organic extracts are

The results corresponding to the anti-inflammatory study of the organic extracts are

inflammatory activities of the extracts and the reference drug revealed significant differences (*p* < 0.05). No extract reached an effect equal to or greater than that of **Indo** (Indomethacin). However, the comparison using the Tukey test of the effect of the extracts and the reference drug showed that there were no significant differences (*p* < 0.05) between some of the extracts, such as **Ij-BH** compared to **Ij-LH** and **Ij-BHac** compared to **Ij-LD**.

Sample [1 mg/ear]

**Figure 3.** Percentage inhibition of inflammation (%) of **Ij-BH**, **Ij-BD**, **Ij-BHac**, **Ij-LH**, **Ij-LD**, and **Ij-LHac** extracts from *Inga jinicuil* and Indo (Indomethacin) in edema induced by TPA in mouse ear at 1.0 mg/ear. Values are presented as means ± standard error of the means (SEM). *n* = 5. ANOVA, with post-test Dunnet with *\* p* ≤ 0.05 in comparison with Indo and Tukey test, where different letters indicate significant differences among them. **Figure 3.** Percentage inhibition of inflammation (%) of **Ij-BH**, **Ij-BD**, **Ij-BHac**, **Ij-LH**, **Ij-LD**, and **Ij-LHac** extracts from *Inga jinicuil* and Indo (Indomethacin) in edema induced by TPA in mouse ear at 1.0 mg/ear. Values are presented as means ± standard error of the means (SEM). *n* = 5. ANOVA, with post-test Dunnet with \* *p* ≤ 0.05 in comparison with Indo and Tukey test, where different letters indicate significant differences among them.

### Even when species such as *I. laurina*, *I. edulis*, *I. marginata*, and *I. jinicuil* are employed *2.4. Antibacterial Activity of Inga jinicuil Organic Extracts*

to treat stomach and inflammatory disorders in traditional medicine, few studies have been conducted to confirm their attributed pharmacological properties. However, recent reports have shown the presence of flavonoids and other phenolic compounds in several of these species that may be associated with pharmacological effects [36]. The present study represents a preliminary approach in the assessment of the anti-inflammatory activity of *I. jinicuil*, with the bark extracts exerting a more consistent effect and **Ij-BD** showing the highest activity. It is noteworthy to mention that the chemical profile of this extract showed the presence of salicylates, terpenoids, and derivatives of epigallocatechin gallate, The antibacterial activity of bark and leaf *I. jinicuil* extracts were evaluated on clinically important micro-organisms. As showed in Table 4, the three extracts of bark (**Ij-BH**, **Ij-BD**, and **Ij-BHac**) exhibited excellent activity against *Pseudomona aeruginosa* (**Pa**) and methicillinresistant *Staphylococcus aureus* (**Sa1**), with MIC values of <3.12 and 50 µg/mL, respectively. Only **Ij-BH** showed activity against *Staphylococcus epidermidis* (**Se1**). Similarly, **Ij-LD** and **Ij-LHac** had good activity against *Pseudomona aeruginosa* (**Pa;** MIC < 3.12 µg/mL), methicillinresistant *Staphylococcus aureus* (**Sa1**; MIC = 50 µg/mL) and *Staphylococcus epidermidis* (**Se1**; MIC = 200 µg/mL).

as well as derivatives of protocatechuic and coumaric acids, which may be associated with its biological effect [24,28,31]. In the case of the extracts from leaves, **Ij-LHac** showed the best inhibitory effect, and the analysis of its metabolic content revealed the presence of polyphenolic compounds, terpenoids, coumarins, vanillic acid derivatives, and flavonoid-The results obtained are interesting considering that in 2017 the WHO published a list of "priority pathogens" resistant to antibiotics, which include *Pseudomonas aeruginosa* (resistant to carbapenems) and *Staphylococcus aureus* (resistant to methicillin), emphasizing the urgent need for the search for new agents against these micro-organisms [5].

type compounds such as apigenin derivatives, all of which have reported anti-inflammatory effects [19,34,37]. Furthermore, previous reports regarding several of the metabolites present in both extracts have postulated an anti-inflammatory activity that proceeds via The antibacterial activity of bark and leaf extracts against *Pseudomona aeruginosa* (**Pa**) and methicillin-resistant *Staphylococcus aureus* (**Sa1**) can be attributed to the presence of several secondary metabolites: hentriacontane and α-tocopherol in **Ij-BH,** and polyphenols, flavonoids, and terpenoids in both **Ij-BD** and **Ij-BHac** [41]. Special attention may be paid to the presence of gallate and coumarin derivatives, since their antibacterial mechanism has been described at the cell membrane level by repressing the transport system of proteins and inhibiting the biofilm formation in clinical strains of **Sa1** [17,42,43]. Furthermore, coumarin derivatives are considered as potential antibacterial agents that act as inhibitors to several binding proteins of **Sa1** and potential competitive inhibitors of the DNA-gyrase [44,45]. It is worth noting that the chemical moiety responsible for the antibacterial activity of coumarins is the basic structure of benzopyrone, which resembles the structure of benzopyridone

present in antibacterial drugs derived from quinolone [44,45]. Therefore, the wide range of chemical structures found in these extracts may represent a potential source of molecular templates for new antibacterial drugs.

**Table 4.** Antibacterial activity (MIC µg/mL) of extracts from *Inga jinicuil*.

**Sa1**: methicillin-resistant *S. aureus*; **Sa2**: *S. aureus*; **Se1**: *S. epidermis*; **Se2**: *S. epidermis*; **Sh**: clinically isolated *S. haemolyticus*; **Ec1**: *E. coli* **Ec2**: *E. cloacae*; **Ef**: *E. fecalis*; **Kp**: *K. pneumoniae*; **Pa**: *P. aeruginosa*; **C1** and **C2**: controls of viability (\*: bacterial growth); **C+**: positive control (Gentamicine 100 µg/mL; –: not bacterial growth).

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

### *3.1. Plant Material and Extraction of Inga jinicuil*

Aerial parts of *Inga jinicuil* Schltdl & Cham. ex G. Don were collected in July 2019, in Libertad, Cunduacán, Tabasco, Mexico (10 m.a.s.l., latitude 18◦10053.06 N, longitude 93◦22028.13 W). A specimen was deposited at the Herbarium of the Academic Division of Biological Sciences of the Universidad Juárez Autónoma de Tabasco for its taxonomic identification (voucher number: 36576).

Plant material was dried at room temperature in the dark for 72 h, with drying and spraying in Pulvex MP300 milled (4–6 mm). The extracts were obtained by maceration with *n*-hexane, dichloromethane, and a 60:40 ethanol:water mixture 1:4; the maceration procedure was performed three times for each solvent in order to ensure an exhaustive extraction. These extracts were filtered, concentrated in a rotary evaporator (Heidolph G3, Schwabach, Germany), and then lyophilized (Heto Drywinner DW3) to give the bark (*n*-Hexane **Ij-BH**, Dichloromethane **Ij-BD**, Hydroalcoholic **Ij-BHac**) and leaf extracts (*n*-Hexane **Ij-LH**, Dichloromethane **Ij-LD**, Hydroalcoholic **Ij-LHac**).

### *3.2. HPLC Analysis*

Chromatographic analysis was carried out in a Waters 2695 separation module system with a Waters 2695 photodiode matrix detector and Empower Pro software (Waters Corporation, Milford, MA, USA). Chemical separation was performed using a Supelcosil LC-F column (4.6 mm × 250 mm i.d., particle size 5 µm) (Sigma-Aldrich, Bellefonte, PA, USA). The mobile acid phase was performed using 0.5% triflouroacetic, aqueous solution (solvent A), and acetonitrile (solvent B) gradient: 0–1 min, 0% of B; 2–3 min, 5% of B; 4–20 min, 30% of B; 21–23 min, 50% of B; 24–25 min, 80% of B; 26–27 min, 100% of B; 28–30 min, 0% of B. The flow rate was 0.9 mL/min with a volume of 10 µL sample. Absorbance was measured at 270 nm [46]. A preliminary identification of the peaks resolved was performed by comparison with *t*R and UV-Vis characteristic bands of known standards and literature data.

### *3.3. GC-MS Analysis of Hexane Extracts*

The chemical composition of **Ij-BH** and **Ij -LH** was analyzed on Gas Chromatography-Mass Spectrometry (GC-MS) equipment, consisting of an Agilent 6890 plus gas chromatograph coupled to a simple quadrupole mass spectrometry detector, model 5972N (Agilent Technology, Santa Clara, CA, USA).

Volatile compounds were separated on an HP 5MS capillary column (25 m long, 0.2 mm i.d., with 0.3-µm film thickness). Oven temperature was set at 40 ◦C for 2 min, then programmed at 40–260 ◦C for 10 ◦C/min, and maintained for 20 min at 260 ◦C. Mass detector conditions were as follows: interphase temperature, 200 ◦C, and mass acquisition range, 20–550. Injector and detector temperatures were set at 250 and 280 ◦C, respectively. Splitless injection mode was carried out with 1 µL of each fraction (3 mg/mL solution). The carrier gas was helium at a flow rate of 1 mL/min. The identification of volatiles was performed, comparing their mass spectra with those of the National Institute of Standards and Technology (NIST) 1.7 Library and comparing these with data from the literature [47].

### *3.4. Pharmacological Activity*

### 3.4.1. Anti-Inflammatory Activity

Male ICR mice with a weight range of 25–30 g, from Envigo RMS, S.A. de C.V., were used throughout the experiments. These animals were maintained in the Bioterium of Centro de Investigación Biomédica Del Sur (CIBIS-IMSS) under a 12 h light-dark cycle and constant temperature (23–25 ◦C) with free access to food and water. The animals were treated under the Mexican federal regulations for care and use of laboratory animals, NOM-062-ZOO-1999 Guidelines [48], and international ethical guidelines for the care and use of experimental animals [49]; the number of animals (*n* = 5) and the intensity of the noxious stimuli utilized were the minimum necessary to demonstrate the consistent effects of the pharmacological treatments. The animal studies were approved by the Ethics Committee of the Mexican Social Security Institute (R-2020-1702-008).

Auricular inflammation was induced following the method previously described [50]. The dose evaluated for the extracts was 1.0 mg/ear. A control group received acetone as vehicle, and Indomethacin (Indo, Sigma-Aldrich, Toluca, Mexico) 1.0 mg/ear was utilized as an anti-inflammatory positive control. All treatments were dissolved in acetone and applied topically on both ears immediately after the solution of 12-*O*-tetradecanoylphorbol-13-acetate (TPA, Sigma-Aldrich, Toluca, México) as an inflammatory agent. Six hours after the administration of TPA, the animals were euthanized by cervical dislocation.

Circular sections 6 mm in diameter were taken from both the treated (t) and nontreated (nt) ears, which were weighed to determine the inflammation. The percentage of inhibition was obtained employing the expression below:

% Inhibition = [Dw control − Dw treated/Dw control] × [100]

where Dw = wt − wnt; wt is the weight of the section of the treated ear; and wnt the weight of untreated ear section.

### 3.4.2. Antibacterial Activity

The extracts were evaluated against bacterial strains ATCC: methicillin-resistant *Staphylococcus aureus* (**Sa1**; ATCC 43330, *Staphylococcus aureus* (**Sa2**; ATCC 29213), *Staphylococcus epidermis* (**Se1**; ATCC 12228)*, Staphylococcus epidermis* (**Se2**; ATCC 35984), *Enterococcus fecalis* (**Ef**; ATCC 29212), *Escherichia coli* (**Ec1**; ATCC 25922), *Enterobacter cloacae* (**Ec2**; ATCC 700323), *Klebsiella pneumoniae* (**Kp**; ATCC 700603), *Pseudomona aeruginosa* (**Pa**; ATCC 27853), and the clinically isolated *Staphylococcus haemolyticus* (**Sh**; 1038). The strains were reseeded in antibiotic agar No. 1 (Bioxon, Mexico) for 24 h at 37 ◦C. The strain of clinical isolate was provided from the General Hospital of Acapulco, State of Guerrero, Mexico, to the Bacteria Bank of the Autonomous University of Guerrero (UAGro).

For the trials, cultures with 24 h of incubation (37 ◦C) were used and about 3–4 colonies were taken of each strain and diluted in Müeller–Hinton broth (MHb; Bioxon, Toluca, Mexico). The inoculums were adjusted using the 0.5 MacFarland scale (1.5 × 108 UFC/mL). Subsequently, dilution with distilled water was performed to obtain 1 × 104 UFC/mL.

The MIC of extracts was determined by the microtiter broth dilution method [51]. Briefly, the samples (50 mg/mL) were dissolved in a DMSO–water mixture (20:80), and the tested concentrations were 3.37, 6.75, 12.5, 25, 50, 100, and 200 µg/mL. The samples were added to sterile microplates of 96 wells, along with 200 µL of MHb and 2 µL of inoculum (1 × 104 UFC/mL). The viability controls used were: MHb + DMSO + inoculum and MHb+ inoculum; Gentamicin (**C +** , 100 µg/mL; Sigma Aldrich, Mexico) was employed as the reference antibiotic. The plates were incubated at 37 ◦C for 24 h, and after incubation the MIC was determined by adding 30 µL of a solution (0.05%) of 3-(4,5-dimethylthiazol-2-yl)- 2,5, diphenyl tetrazolium bromide (MTT, Sigma-Aldrich, Hong Kong, China) in every well, of which purple development was observed if there was viability of bacteria and colorless if there was no feasibility. All assays were performed in triplicate.

### *3.5. Statistical Analysis*

For the analysis of the anti-inflammatory activity, the data were expressed as the mean ± standard error of the mean (SEM), and statistical significance was determined using an analysis of variance (ANOVA) with a confidence level of 95% (\* *p* ≤ 0.05), followed by the one-tailed Dunnet test compared to Indo and the Tukey test. All analyses was performed using IBM SPSS statistics ver. 23.0 statistical program (GraphPad Software, IBM, San Diego, CA, USA).

### **4. Conclusions**

This report presents the biological activity of organic extracts obtained from the bark and leaves of *I. jinicuil*. The anti-inflammatory activity tests showed moderate to good effects, with the dichloromethane extract from bark showing the highest activity, followed by the hexanic extract from leaves. Based on the findings of anti-inflammatory activity, it is possible to propose the exploration of the potential antinociceptive effect of the tested extracts, using an appropriate pharmacological model. Likewise, it was found that the three extracts from the bark of this plant have excellent antibacterial activity (primarily against methicillin-resistant *Staphylococcus aureus* and *Pseudomonas aeruginosa* strains) and this leads us to consider the possibility of extending antibacterial activity tests to a greater number of microbiological strains of clinical interest. On the other hand, it should be mentioned that, to our knowledge, this is the first approach to the phytochemical profiling of bark and leaves of *I. jinicuil*, which is consistent with the chemotaxonomic profiles reported for other species of *Inga* and suggest the presence of polyphenolic compounds, flavonoids, triterpenes, and lipid prenols, as well as aliphatic and esterified aliphatic lipids; these natural products may be responsible for both bioactivities assessed in this work. These results allow predicting a wide potential for future studies aimed at the isolation and structural characterization of compounds that might serve as molecular templates with specific biological activities. Finally, it is important to highlight that these results systematically contribute to the use in traditional Mexican medicine of a highly important sociocultural and nutritional species such as *Inga jinicuil* Schltdl & Cham. ex G. Don.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/plants11060794/s1, Figure S1: UV-spectra of the main compounds of (Ij-BD) *I. jinicuil*; Figure S2: UV-spectra of the main compounds of (Ij-BHac) *I. jinicuil*; Figure S3: UV-spectra of the main compounds of (Ij-LD) *I. jinicuil*; Figure S4: UV-spectra of the main compounds of (Ij-LHac) *I. jinicuil*.

**Author Contributions:** Conceptualization, M.G.-C., C.E.L.-G. and A.G.-R.; methodology, A.J.G.-G., R.L.-R. and P.Á.-F.; validation, M.H.-R. and M.D.P.-G.; formal analysis, A.Z.; investigation, A.G.-R. and A.B.; resources, A.J.G.-G., R.L.-R. and M.R.F.; data curation, E.J.M.-S. and M.R.F.; writing—original draft preparation, A.J.G.-G., R.L.-R. and E.A.B.-G.; writing—review and editing, A.G.-R., C.E.L.-G. and A.B.; visualization, M.H.-R. and P.Á.-F.; supervision, M.D.P.-G.; project administration, M.G.-C., A.G.-R. and C.E.L.-G.; funding acquisition, A.G.-R., M.G.-C. and A.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by PRODEP, grant number UJAT-EXB-242.

**Institutional Review Board Statement:** The animal studies were approved by the Ethics Committee of the Mexican Social Security Institute (R-2020-1702-008).

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data is contained within the article and Supplementary Material.

**Acknowledgments:** The authors wish to thank Arturo Pérez, Jonathan Orduño, and Ixchel Palacios (CIBIS-IMSS), and Dora Elena Aguilar Dominguez and Wilbert Pérez Fuentes (DACB-UJAT) for technical and analytical assistance; al Consejo Nacional de Ciencia y Tecnologia (CONACYT) por la beca otorgada con No. de CVU: 703106; R.L.-R. (478597) was supported by CONACYT postdoctoral fellowship (866998).

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

### **References**


**6. Conclusions**

In this article, the authors highlighted the importance of vehicle motion control at handling limits and automated drifting as one of the critical developments of fully autonomous vehicles of the future, aiming at improved road safety. Vehicle automated drifting capabilities were demonstrated during different operating conditions with a systematic controller development process, as outlined below. The handling of changing road conditions and vehicle model nonlinearities is among the key advantages of the proposed adaptive MPC control framework. In Section 2, a nonlinear dynamic vehicle model and a nonlinear tire model were introduced for control-oriented purposes, and the parameter identification was carried out. In Sections 3 and 4, the control scheme and the updating strategy were explained in detail.

In Section 5.1, the weight matrices were determined using a single equilibrium for testing. It was shown that a linear MPC is capable of driving the nonlinear system into the desired drifting equilibrium, keeping it there with the appropriate tuning.

Linear MPC is a simpler control methodology compared to nonlinear MPC, but it performs poorly if the change in vehicle dynamic behavior is far from the design point due to nonlinearities or when it faces parameter variations (road surface changes). According to the proposed idea, these drawbacks can be eliminated by updating the discrete model of the vehicle, reformulating the MPC in an adaptive way, and utilizing measured or estimated model parameter values. This allows using the same MPC structure by updating it instead of using a more different linear MPC and a decision controller for drifting in multiple equilibria as a gain scheduling.

Another advantage of this method in vehicle motion control is directly handling changes in the road surface. A slight or abrupt variation in friction is a common occurrence in real-life driving scenarios. This paper showed that the controller could handle not only various transitions between multiple equilibria but also a simultaneous change in the road grip.

A reasonable next step of the work is to extend the proposed framework with trajectory-planning and -tracking capabilities and possibly online road surface estimation to demonstrate advantages in critical road safety scenarios.

**Author Contributions:** Conceptualization, Á.B., Sz.Cz., Á.D. and Zs.Sz.; methodology, Á.B., Sz.Cz., Á.D. and Zs.Sz.; software, Á.B., Sz.Cz., Á.D. and Zs.Sz.; validation, Á.B., Sz.Cz., Á.D. and Zs.Sz.; formal analysis, Á.B., Sz.Cz., Á.D. and Zs.Sz.; investigation, Á.B., Sz.Cz., Á.D. and Zs.Sz.; resources, Á.B., Sz.Cz., Á.D. and Zs.Sz.; data curation, Á.B., Sz.Cz., Á.D. and Zs.Sz.; writing—original draft preparation, Á.B., Sz.Cz., Á.D. and Zs.Sz.; writing—review and editing, Á.B., Sz.Cz., Á.D. and Zs.Sz.; visualization, Á.B., Sz.Cz., Á.D. and Zs.Sz.; supervision, Á.B., Sz.Cz., Á.D. and Zs.Sz.; project administration, Á.B., Sz.Cz., Á.D. and Zs.Sz.; funding acquisition, Á.B., Sz.Cz., Á.D. and Zs.Sz. All authors have read and agreed to the published version of the manuscript.

**Funding:** TKP2020 Institution Excellence Subprogram, Grant No. BME-IE-MIFM, Autonomous Systems National Laboratory Program Ministry of Innovation and Technology NRDI Office.

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The research reported in this paper and carried out at the Budapest University of Technology and Economics was supported by the National Research Development and Innovation Fund (TKP2020 Institution Excellence Subprogram, Grant No. BME-IE-MIFM) based on the charter of bolster issued by the National Research Development and Innovation Office under the auspices of the Ministry for Innovation and Technology. In addition, the research was supported by the Ministry of Innovation and Technology NRDI Office within the framework of the Autonomous Systems National Laboratory Program.

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


**4. Concluding Remarks**

Based on the method of generating classes of probability distributions presented by [12], we introduce a new class called Normal-*G*. It has the advantage of demanding no additional parameters besides the baseline ones. We demonstrate that the proposed class generates identifiable sub-models as long as the parent distribution is identifiable. The pdf of the class can be written as a linear combination of pdfs of exponentiated distributions; it allows us to easily derive the raw moments, the incomplete moments and the moment generating function.

We bring Monte Carlo simulation studies to attest the good performance of the MLEs of two distributions generated by the class and to illustrate its usefulness, applications to real datasets are made. The fitted models are compared to other competitive distributions regarding the Anderson-Darling and the Cramér-von Mises statistics, as well as commonly used information criteria as goodness-of-fit measures. The general results indicate that the Normal-*G* outperforms the other distributions in comparison. The new class is powerful and provides parsimonious models, which may hopefully interest practitioners of statistics, soil science, oceanography and other fields.

**Author Contributions:** All of the authors contributed relevantly to this research article.

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

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


Vegetation Index and Dynamics

*Edited by Eusebio Cano Carmona, Ana Cano Ortiz, Riocardo Quinto Canas and Carmelo Maria Musarella*

Published in London, United Kingdom

## *Supporting open minds since 2005*

#### Vegetation Index and Dynamics

http://dx.doi.org/10.5772/intechopen.87465

Edited by Eusebio Cano Carmona, Ana Cano Ortiz, Riocardo Quinto Canas and Carmelo Maria Musarella

#### Contributors

Jon Bryan Burley, Zhi Yue, Amjad ur Rahman, Esra Gürbüz, Semih Ekercin, Shujaul Mulk Khan, Engin Eroğlu, Tuba Gül Doğan, Madan Prasad Singh, Manohara Tattekere Nanjappa, Sukumar Raman, Suresh Hebbalalu Satyanatayana, Ayyappan Narayanan, Ganesan Rengaian, Sreejith Kalpuzha Ashtamoorthy, Elena Runova, Vera Savchenkova, Ekaterina Demina-Moskovskay, Anastasia Baranenkova, Algimantas Česnulevičius, Artūras Bautrėnas, Linas Bevainis, Donatas Ovodas, Claudionor Silva, Arthur Santos, Fernando Santil, Anna Brook, Maria Polinova, Sara del Río, Ángel Penas, Raquel Alonso-Redondo, Giovanni Breogán Ferreiro Lera, Aitor Álvarez-Santacoloma, Alejandro González-Pérez, Sam Paul Mathew, Raveendranpillai Prakashkumar, Sylvester Onoriode Obigba, Maria M. Borisova-Mubarakshina, Ilya A. Naydov, Daria V. Vetoshkina, Marina A. A. Kozuleva, Daria V. Vilyanen, Boris N. N Ivanov, Natalia N. Rudenko, Rahmouni Abdelkader, Brahimi Djamel, Brahimi Abdelghani, Mesli Lotfi, Samora M. Andrew, Siwa A. Kombo, Shabani A.O. Chamshama, Clara Inés Saldamando-Benjumea, Gloria Patricia Cañas-Gutiérrez, Jorge Muñoz, Rafael Arango Isaza, Eusebio Cano Carmona, Ricardo Quinto Canas, Ana Cano Ortiz, Carmelo María Musarella

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#### Vegetation Index and Dynamics

Edited by Eusebio Cano Carmona, Ana Cano Ortiz, Riocardo Quinto Canas and Carmelo Maria Musarella p. cm. Print ISBN 978-1-83969-385-4 Online ISBN 978-1-83969-386-1 eBook (PDF) ISBN 978-1-83969-387-8


**2. Mycotoxin**

Fungal toxins are secondary metabolites, which can cause some diseases in living things known as mycoses; meanwhile, dietary exposure to such metabolites produces the disease named mycotoxicoses. Mycotoxins are known as secondary metabolites, produced from microfungi and able to cause–effect human health as well as animals. Mycotoxins are commonly used as antibiotics and growth promotants because of their unique characteristics in pharmacological activity. Most of the mycotoxin are found as natural contaminant food, mainly in vegetable and feed. Nut, cereals, oilseeds, dried fruits, spices, and food from animal origins for example milk, egg, and meat are also may contain mycotoxin either outside or inside the product [10, 11]. A mycotoxin is believed no function in the life of a producer cell, unlike primary metabolites [12]. There are few types of mycotoxin such as aflatoxins (AFs), zearalenone (ZEA), deoxnivalenol (DON), ochratoxin (OTA) and T-2 toxin (trichothecene mycotoxin) which are a significant threat to the life and health of human and live stocks [13]. Mycotoxins are low molecular weight and thermalstable secondary metabolite of toxic molds that belong to genera *Aspergillus,*

**87**

**Figure 1.**

*Primary groups of mycotoxins in various food products.*

*Recent Biosensors Technologies for Detection of Mycotoxin in Food Products*

*Penicillium, Alternaria,* and *Fusarium*. These toxins are present in the mycelium and spore of the mold. Mycotoxin may become a biological weapon in bioterrorism

The established mycotoxins for agriculture and public health concerns including aflatoxins, ochratoxins, zearalenone, T-2 and HT-2 toxin, deoxynivalenol, fumonisins, citrinin, patulin, and ergot alkaloids shown in **Figure 1**. Aflatoxins B1 and M1 (AFT B1 & M1) [15] produced by *Aspergillus flavus* and *A. parasiticus* species grown on grains and cereals, spices, tree nuts. Aflatoxin B1(AFB1) is one of the most carcinogenic substances produced by fungi and results in inevitable contamination of food and feed at deficient concentrations. Four main types of aflatoxin naturally contaminate foods which are aflatoxin B1 (AFB1), G1 (AFG1) and their dihydroderivatives B2 (AFB2) and G2 (AFG2). Others without additional metabolites known as Aflatoxin M1 and Aflatoxin M2 [16]. AFT M1 being a 4-hydroxylated metabolite of AFT B1, is found in cow and sheep milk and milk products. Some studied had been identified there is 20 aflatoxins that belongs to a group called highly substituted difuranocoumarins. The International Agency for Research on Cancer (IARC) had been classified aflatoxin as very toxic compounds in group 1 due

Ochratoxin A (OTA) produced by *Aspergillus ochraceus, A. carbonarius,* and *Penicillium verrucosum* is one of the most abundant contaminants in grain and pork products, coffee, dried grapes, as well in wine and beer at humidity around 15–19%

*DOI: http://dx.doi.org/10.5772/intechopen.89022*

**3. Types of mycotoxin**

because of its acute and chronic toxicities [14].

to evidence that shows the carcinogenicity in human [17].

*Recent Biosensors Technologies for Detection of Mycotoxin in Food Products DOI: http://dx.doi.org/10.5772/intechopen.89022*

*Penicillium, Alternaria,* and *Fusarium*. These toxins are present in the mycelium and spore of the mold. Mycotoxin may become a biological weapon in bioterrorism because of its acute and chronic toxicities [14].