Incidence and health risk assessment of hydrogen cyanide and multi-mycotoxins in Nigerian garri

Garri is a granular, starchy food prepared by the fermentation of mashed cassava. Hydrogen cyanide (HCN) and mycotoxins are contaminants in certain foods at different points along the food value chain. The incidence and contamination levels of HCN and multi-mycotoxins in garri from five agroecological zones of Nigeria were determined using a spectrophotometric method and ultra-high-performance liquid chromatography-tandem mass spectroscopy (UHPLC-MS/MS), respectively. The health risk associated with the consumption of contaminated garri was assessed. The health risk assessment model was used to calculate the dietary exposure of humans to the mycotoxins in garri. This was done by estimating the daily intake (EDI), the percentage tolerable daily intake (%TDI), the annual hepatocellular carcinoma (HCC) cases attributable to exposure to aflatoxins (AFs) in garri, as well as the HCC risk. The average intake of garri was estimated at 0.303 kg/day for a Nigerian adult. The incidence of HCN was 98.3% (0.056-2.463 mg/kg), and fermentation reduced the HCN level in garri more than other processing steps. The twenty-one mycotoxins identified and quantified were all within maximum levels, as applicable to those that are regulated by the EU. The %TDI for the other mycotoxins, with the exception of AFs, showed no alarming health risk with garri consumption. Annual HCC cases resulting from AF in garri were estimated at 10-60 cases for HBsAg + ve individuals and 4-23 cases for HBsAg - ve individuals based on 8.1% hepatitis B virus (HBV) incidence. Results further revealed no interdependence between HCN levels and mycotoxin content. This work suggests an unlikely chance of acute toxicity from HCN and major mycotoxins from a garri-based diet in Nigeria. Hence, it is recommended that concerned regulatory bodies maintain the existing permissible limits for HCN in Garri.

The Optimisation of Bitter Gourd-Grape Beverage Fermentation Using a Consolidated Response Surface Methodology (RSM) and Artificial Neural Network (ANN) Approach

The present study adopted a response surface methodology (RSM) approach validated by artificial neural network (ANN) models to optimise the production of a bitter gourd-grape beverage. Aset of statistically pre-designed experiments were conducted, and the RSM optimisation model fitted to the obtained data, yielding adequately fit models for the monitored control variables R2 values for alcohol (0.79), pH (0.89), and total soluble solids (TSS) (0.89). Further validation of the RSM model fit using ANN showed relatively high accuracies of 0.98, 0.88, and 0.82 for alcohol, pH, and TSS, respectively, suggesting satisfactory predictability and adequacy of the models. A clear effect of the optimised conditions, namely fermentation time at (72 h), fermentation temperature (32.50 and 45.11 °C), and starter culture concentration (3.00 v/v) on the total titratable acidity (TTA), was observed with an R2 value of (0.40) and RSM model fit using ANN overall accuracy of (0.56). However, higher TTA values were observed for samples fermented for 72 h at starter culture concentrations above 3 mL. The level of 35% bitter gourd juice was optimised in this study and was considered desirable because the goal was to make a low-alcohol beverage.

Application of a generative adversarial network for multi-featured fermentation data synthesis and artificial neural network (ANN) modeling of bitter gourd-grape beverage production

Artificial neural networks (ANNs) have in recent times found increasing application in predictive modelling of various food processing operations including fermentation, as they have the ability to learn nonlinear complex relationships in high dimensional datasets, which might otherwise be outside the scope of conventional regression models. Nonetheless, a major limiting factor of ANNs is that they require quite a large amount of training data for better performance. Obtaining such an amount of data from biological processes is usually difficult for many reasons. To resolve this problem, methods are proposed to inflate existing data by artificially synthesizing additional valid data samples. In this paper, we present a generative adversarial network (GAN) able to synthesize an infinite amount of realistic multi-dimensional regression data from limited experimental data (n = 20). Rigorous testing showed that the synthesized data (n = 200) significantly conserved the variances and distribution patterns of the real data. Further, the synthetic data was used to generalize a deep neural network. The model trained on the artificial data showed a lower loss (2.029 ± 0.124) and converged to a solution faster than its counterpart trained on real data (2.1614 ± 0.117).

Seasonal Diversity and Occurrence of Filamentous Fungi in Smallholder Dairy Cattle Feeds and Feedstuffs in South Africa

This study investigated 65 (35 in summer and 30 in winter) smallholder dairy cattle feeds from Free State and Limpopo provinces in South Africa from 2018 to 2019 for fungal contamination and assessed the impacts of seasonal variation on fungal contamination levels, isolation frequency, and diversity. Samples were examined for fungal contamination using macro- and microscopic approaches, and their identities were confirmed by molecular means. A total of 217 fungal isolates from 14 genera, including Aspergillus, Fusarium, and Penicillium, were recovered from feeds from both seasons. The most prevalent fungal species recovered were A. fumigatus and P. crustosum. Mycological analyses showed that 97% of samples were contaminated with one or more fungal isolates, with the summer fungal mean level (6.1 × 103 to 3.0 × 106 CFU/g) higher than that of feeds sampled during winter (mean level: 1.1 × 103 to 4.1 × 105 CFU/g). Independent sample t-test revealed that the isolation frequencies of the genera Aspergillus and Fusarium were significantly (p ≤ 0.05) higher in summer than winter, while Penicillium prevalence in both seasons was not statistically (p > 0.05) different. Furthermore, the Shannon−Weiner diversity index (H′) revealed a higher fungal diversity in summer (H′ = 2.8) than in winter (H′ = 2.1). This study on fungal contamination could be used for future fungal control and mycotoxin risk management in South Africa.

Variability in metabolites produced by Talaromyces pinophilus SPJ22 cultured on different substrates

Background

Several metabolites released by fungal species are an essential source of biologically active natural substances. Gas chromatography high resolution time-of-flight mass spectrometry (GC-HRTOF-MS) is one of the techniques used in profiling the metabolites produced by microorganisms, including Talaromyces pinophilus. However, there is limited information regarding differential substrates’ impacts on this fungal strain’s metabolite profiling. This study examined the metabolite profile of T. pinophilus strain SPJ22 cultured on three different media, including solid czapek yeast extract agar (CYA), malt extract agar (MEA) and potato dextrose agar (PDA) using GC-HRTOF-MS. The mycelia including the media were plugged and dissolved in 5 different organic solvents with varying polarities viz.: acetonitrile, dichloromethane, hexane, 80% methanol and water, and extracts analysed on GC-HRTOF-MS.

Results

The study revealed the presence of different classes of metabolites, such as fatty acids (2.13%), amides (4.26%), alkanes (34.04%), furan (2.13%), ketones (4.26%), alcohols (14.89%), aromatic compounds (6.38%), and other miscellaneous compounds (17.02%). Significant metabolites such as acetic acid, 9-octadecenamide, undecanoic acid methyl ester, hydrazine, hexadecane, nonadecane, eicosane, and other compounds reported in this study have been widely documented to have plant growth promoting, antimicrobial, anti-inflammatory, antioxidant, and biofuel properties. Furthermore, T. pinophilus grown on PDA and MEA produced more than twice as many compounds as that grown on CYA.

Conclusion

Thus, our result showed that the production of essential metabolites from T. pinophilus is substrate dependent, with many of these metabolites known to have beneficial characteristics, and as such, this organism can be utilised as a sustainable and natural source for these useful organic molecules.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40694-022-00145-8.

Optimization of Infrared Heating Conditions for Precooked Cowpea Production Using Response Surface Methodology

The infrared heating of preconditioned cowpea improves its utilization and potential application in food systems. This study investigated the effect of optimizing preconditioning and infrared heating parameters of temperature and time on cooking characteristics of precooked cowpeas using response surface methodology (RSM). The moisture level (32–57%), infrared heating temperature (114–185 °C), and time of processing the seeds (2–18 min) were optimized using a randomized central composite design to achieve optimal characteristics for bulk density and water absorption. A second-order polynomial regression model was fitted to the obtained data, and the fitted model was used to compute the multi-response optimum processing conditions, which were the moisture of 45%, the heating temperature of 185 °C, and time of 5 min. Precooked cowpea seeds from optimized conditions had a 19% increase in pectin solubility. The total phenolic and total flavonoid contents were significantly reduced through complexation of the seeds’ phenolic compounds with other macromolecules but nonetheless exhibited antioxidant properties capable of scavenging free radicals. There was also a significant reduction in phytate and oxalates by 24% and 42%, respectively, which was due to the heat causing the inactivation of these antinutrients. The obtained optimized conditions are adequate in the production of precooked cowpea seeds with improved quality.

Food safety, food security and genetically modified organisms in Africa: a current perspective

Moving forward from 2020, Africa faces an eminent challenge of food safety and security in the coming years. The World Food Programme (WFP) of the United Nations (UN) estimates that 20% of Africa's population of 1.2 billion people face the highest level of undernourishment in the world, likely to worsen due to COVID-19 pandemic that has brought the entire world to its knees. Factors such as insecurity and conflict, poverty, climate change and population growth have been identified as critical contributors to the food security challenges on the continent. Biotechnological research on Genetically Modified Organisms (GMOs) provides a range of opportunities (such as increased crop yields, resistance to pests and diseases, enhanced nutrient composition and food quality) in addressing the hunger, malnutrition and food security issues on the continent. However, the acceptance and adoption of GMOs on the continent has been remarkably slow, perhaps due to contrasting views about the benefits and safety concerns associated with them. With the reality of food insecurity and the booming population in Africa, there is an eminent need for a more pragmatic position to this debate. The present review presents an overview of the current situation of food safety and security and attempts to reconcile major viewpoints on GMOs research considering the current food safety and security crisis in the African continent.

Systematic Delineation of Media Polarity on COVID-19 Vaccines in Africa: Computational Linguistic Modeling Study

BACKGROUND

The global onset of COVID-19 has resulted in substantial public health and socioeconomic impacts. An immediate medical breakthrough is needed. However, parallel to the emergence of the COVID-19 pandemic is the proliferation of information regarding the pandemic, which, if uncontrolled, cannot only mislead the public but also hinder the concerted efforts of relevant stakeholders in mitigating the effect of this pandemic. It is known that media communications can affect public perception and attitude toward medical treatment, vaccination, or subject matter, particularly when the population has limited knowledge on the subject.

OBJECTIVE

This study attempts to systematically scrutinize media communications (Google News headlines or snippets and Twitter posts) to understand the prevailing sentiments regarding COVID-19 vaccines in Africa.

METHODS

A total of 637 Twitter posts and 569 Google News headlines or descriptions, retrieved between February 2 and May 5, 2020, were analyzed using three standard computational linguistics models (ie, TextBlob, Valence Aware Dictionary and Sentiment Reasoner, and Word2Vec combined with a bidirectional long short-term memory neural network).

RESULTS

Our findings revealed that, contrary to general perceptions, Google News headlines or snippets and Twitter posts within the stated period were generally passive or positive toward COVID-19 vaccines in Africa. It was possible to understand these patterns in light of increasingly sustained efforts by various media and health actors in ensuring the availability of factual information about the pandemic.

CONCLUSIONS

This type of analysis could contribute to understanding predominant polarities and associated potential attitudinal inclinations. Such knowledge could be critical in informing relevant public health and media engagement policies.

Metabolomic approaches for the determination of metabolites from pathogenic microorganisms: A review

Metabolomics is a high precision analytical approach to obtaining detailed information of varieties of metabolites produced in biological systems, including foods. This study reviews the use of metabolomic approaches such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GC-MS), matrix assisted laser desorption /ionization tandem time of flight mass spectrometry (MALDI-TOF-MS) and nuclear magnetic resonance (NMR) for investigating the presence of foodborne pathogens and their metabolites. Pathogenic fungi and their notable metabolites (mycotoxins) have been studied more extensively using metabolomics as compared to bacteria, necessitating further studies in this regard. Nevertheless, such identified fungal and bacteria metabolites could be used as biomarkers for a more rapid detection of these pathogens in food. Other important compounds detected through metabolomics could also be correlated to functionality of these pathogenic strains, determined by the composition of the foods in which they exist, thereby providing insights into their metabolism. Considering the prevalence of these food pathogens, metabolomics still has potentials in the determination of food-borne pathogenic microorganisms especially for the determination of pathogenic bacteria toxins and is expected to generate research interests for further studies and applications.

Proportional coexistence of okanin chalcone glycoside and okanin flavanone glycoside in Bidens pilosa leaves and theoretical investigation on the antioxidant properties of their aglycones

Bidens pilosa plant has been shown to produce okanin flavanone glycoside and its chalcone derivative. In most other plants, due to chalcone isomerase enzyme, the flavanone tends to exist in higher proportions than their chalcone precursors. Herein we have utilized liquid chromatography-mass spectrometry approach and shown that within the leaves of Bidens pilosa plant the two okanin glycosides exist in unusual equal proportional distribution, which indicates that Bidens pilosa plant is an alternative rich source of these highly sought-after antioxidant molecules. The aglycone okanin chalcone (ONC) and okanin flavanone (ONF) have experimentally been shown to exhibit antioxidant activity. However, experimental findings have not conclusively determined which of the two compounds is a more potent antiradical than the other. Herein, the density functional theory (DFT) method is utilized to establish, from structural and thermodynamic energetic considerations, the preferred antioxidant molecule between the two aglycone okanins. A theoretical study on the antioxidant properties of ONC and ONF has been performed by considering their radical scavenging and metal cation (Mⁿ⁺, where M = Cu(II) or Fe (III)) chelation ability. The study has been performed using B3LYP/6-31 + G(d,p) method. In the case of the metal chelation mechanism, the LANL2DZ pseudo-potential was selected to describe the selected Mⁿ⁺ cations. The results of the study suggest that ONC is a better radical scavenger than ONF because of the extended electron delocalization on its neutral radical, which is due to the presence of conjugation within the ONC neutral radical after hydrogen atom abstraction. In the metal chelation mechanism, it is noted that the binding energies depend on the media, the nature of the ligand and the cation and the cation coordination site on the ligand. The charge and the spin density on Mⁿ⁺ decrease on coordination to the ligand. The ability of the ligands to reduce Mⁿ⁺ cations, coupled with the strong Mⁿ⁺ binding properties, has significant implication on the antioxidant ability of both okanins. However, since ONC⋅⋅⋅M⁺ⁿ interaction results in higher binding energy than ONF⋅⋅⋅M⁺ⁿ interaction, the implication is that ONC is a preferred free metal ion chelator than ONF.

The use of plant extracts and their phytochemicals for control of toxigenic fungi and mycotoxins

Mycotoxins present a great concern to food safety and security due to their adverse health and socio-economic impacts. The necessity to formulate novel strategies that can mitigate the economic and health effects associated with mycotoxin contamination of food and feed commodities without any impact on public health, quality and nutritional value of food and feed, economy and trade industry become imperative. Various strategies have been adopted to mitigate mycotoxin contamination but often fall short of the required efficacy. One of the promising approaches is the use of bioactive plant components/metabolites synergistically with mycotoxin-absorbing components in order to limit exposure to these toxins and associated negative health effects. In particular, is the fabrication of β-cyclodextrin-based nanosponges encapsulated with bioactive compounds of plant origin to inhibit toxigenic fungi and decontaminate mycotoxins in food and feed without leaving any health and environmental hazard to the consumers. The present paper reviews the use of botanicals extracts and their phytochemicals coupled with β-cyclodextrin-based nanosponge technology to inhibit toxigenic fungal invasion and detoxify mycotoxins.

Quantification of multi-mycotoxin in cereals (maize, maize porridge, sorghum and wheat) from Limpopo province of South Africa

Mycotoxins are secondary metabolites that are produced by filamentous mycotoxigenic fungi belonging to the Alternaria, Aspergillus, Fusarium and Penicillium genera amongst others. Multi-class mycotoxins were extracted from 55 cereal samples and analysed using liquid chromatography-tandem mass spectrometry. The adopted extraction method for maize, maize porridge, sorghum and wheat was comprehensively validated. This method was further tested to determine the natural occurrence of mycotoxins in foodstuffs. Twelve (12) out of 22 mycotoxins were detected in maize, maize porridge, sorghum and wheat, including α-zearalenol (α-ZEL) (89%), fumonisin B₃ (FB₃) (84%), fumonisin B₁ (FB₁) (80%), tenuazonic acid (TeA) (78%), ochratoxin B (42%), deoxynivalenol (DON) (12%), ochratoxin A (11%), 3-acetyldeoxynivalenol (7%), sterigmatocystin (STG) (6%), 15-acetyldeoxynivalenol (2%), cyclopiazonic acid (CPA) (2%) and aflatoxin B₂ (2%). The data revealed high incidence rate of α-ZEL (range: 6.5-70.5 µg kg^-1) in all matrices. Maize samples had high mycotoxin co-occurrence compared to other matrices. All recovered mycotoxins in food commodities were within the maximum regulatory limits, with the exception of fumonisins (FB₁ and FB₃) exceeded the South African and European Commission regulation, and the highest concentration was 2153 µg kg^-1 in maize. It is essential to monitor the level of emerging mycotoxins in food commodities from rural areas as trace amount of CPA (< limit of quantification), STG (range: 0.30-0.74 µg kg^-1) were detected and high concentration of TeA (292.7 µg kg^-1) was detected in sorghum. The occurrence of these mycotoxins further encourages frequent analyses, their co-occurrence in the samples poses a significant threat to public health and more emphasis should thus be placed on reducing the contamination levels of these toxins in staples.

Parallel validation of a green-solvent extraction method and quantitative estimation of multi-mycotoxins in staple cereals using LC-MS/MS

In this study, 15 different mycotoxins were estimated in three staple cereals from selected agro-ecological regions in Nigeria using a 'novel' green extraction method, pressurized hot water extraction (PHWE) in comparison to a conventional solvent extraction method. Discrimination of the results of PHWE and solvent extraction using principal component analysis (PCA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA) did not yield any differential clustering patterns. All maize samples (n = 16), 32% (n = 38) of sorghum and 35% (n = 37) of millet samples were positive for at least one of the 15 tested mycotoxins. Contamination levels for the cereals were higher in the warm humid rain forest region and gradually decreased towards the hot and arid region in the north of the country. The results demonstrate the applicability of PHWE as a possible alternative extraction method to conventional methods of extraction, which are solvent based.

Decontamination of T-2 Toxin in Maize by Modified Montmorillonite Clay

Montmorillonite clay has a wide range of applications, one of which includes the binding of mycotoxins in foods and feeds through adsorption. T-2 toxin, produced by some Fusarium, Myrothecium, and Stachybotrys species, causes dystrophy in the brain, heart, and kidney. Various formulations that include lemongrass essential oil-modified montmorillonite clay (LGEO-MMT), lemongrass powder (LGP), montmorillonite clay washed with 1 mM NaCl (Na-MMT), montmorillonite clay (MMT), and lemongrass powder mixed with montmorillonite clay (LGP-MMT) were applied to maize at concentrations of 8% and 12% and stored for a period of one month at 30 °C. Unmodified montmorillonite clay and LGP served as the negative controls alongside untreated maize. Fourier Transform Infrared (FTIR) spectra of the various treatments showed the major functional groups as Si-O and -OH. All treatment formulations were effective in the decontamination of T-2 toxin in maize. Accordingly, it was revealed that the inclusion of Na-MMT in maize at a concentration of 8% was most effective in decontaminating T-2 toxin by 66% in maize followed by LGP-MMT at 12% inclusion level recording a 56% decontamination of T-2 toxin in maize (p = 0.05). Montmorillonite clay can be effectively modified with plant extracts for the decontamination of T-2 toxin.

Development, chemometric-assisted optimization and in-house validation of a modified pressurized hot water extraction methodology for multi-mycotoxins in maize

Effective management of mycotoxins rely on stringent regulation and routine surveillance of food/feed commodities via efficient analysis, hence the continuous need for improved methods. The present study developed, optimized and validated a modified pressurized hot water extraction (PHWE) method for the simultaneous extraction of multi-mycotoxins from maize and subsequent quantification on LC-MS/MS. The PHWE system was modified using ethanol (EtOH) as a cosolvent, while a numerical modelling approach, the central composite design (CCD), was adopted for the optimization of the extraction conditions. Using the optimized method, it was possible to effectively extract and quantify 15 different mycotoxins from maize in a single step with satisfactory linearities (0.986-0.999), recoveries (14-124%) and other associated method validation parameters. Further efficacious application of the method to real samples re-affirmed the prospects of PHWE as a suitable, cost-effective and greener alternative to traditional methods of mycotoxin extraction.

Review on microbial degradation of aflatoxins

Aflatoxin (AF) contamination presents one of the most insidious challenges to combat, in food safety. Its adulteration of agricultural commodities presents an important safety concern as evident in the incidences of its health implication and economic losses reported widely. Due to the overarching challenges presented by the contamination of AFs in foods and feeds, there is an urgent need to evolve cost-effective and competent strategies to combat this menace. In our review, we tried to appraise the cost-effective methods for decontamination of AFs. We identified the missing links in adopting microbial degradation as a palliative to decontamination of AFs and its commercialization in food and feed industries. Cogent areas of further research were also highlighted in the review paper.

The effect of temperature and methanol-water mixture on pressurized hot water extraction (PHWE) of anti-HIV analogoues from Bidens pilosa

Background

Pressurized hot water extraction (PHWE) technique has recently gain much attention for the extraction of biologically active compounds from plant tissues for analytical purposes, due to the limited use of organic solvents, its cost-effectiveness, ease-of-use and efficiency. An increase in temperature results in higher yields, however, issues with degradation of some metabolites (e.g. tartrate esters) when PHWE is conditioned at elevated temperatures has greatly limited its use. In this study, we considered possibilities of optimizing PHWE of some specific functional metabolites from Bidens pilosa using solvent compositions of 0, 20, 40 and 60 % methanol and a temperature profile of 50, 100 and 150 °C.

Results

The extracts obtained were analyzed using UPLC-qTOF-MS/MS and the results showed that both temperature and solvent composition were critical for efficient recovery of target metabolites, i.e., dicaffeoylquinic acid (diCQA) and chicoric acid (CA), which are known to possess anti-HIV properties. It was also possible to extract different isomers (possibly cis-geometrical isomers) of these molecules. Significantly differential (p ≤ 0.05) recovery patterns corresponding to the extraction conditions were observed as recovery increased with increase in methanol composition as well as temperature. The major compounds recovered in descending order were 3,5-diCQA with relative peak intensity of 204.23 ± 3.16 extracted at 50 °C and 60 % methanol; chicoric acid (141.00 ± 3.55) at 50 °C and 60 % methanol; 4,5-diCQA (108.05 ± 4.76) at 150 °C and 0 % methanol; 3,4-diCQA (53.04 ± 13.49) at 150 °C and 0 % methanol; chicoric acid isomer (40.01 ± 1.14) at 150 °C and 20 % methanol; and cis-3,5-diCQA (12.07 ± 5.54) at 100 °C and 60 % methanol. Fitting the central composite design response surface model to our data generated models that fit the data well with R² values ranging from 0.57 to 0.87. Accordingly, it was possible to observe on the response surface plots the effects of temperature and solvent composition on the recovery patterns of these metabolites as well as to establish the optimum extraction conditions. Furthermore, the pareto charts revealed that methanol composition had a stronger effect on extraction yield than temperature.

Conclusion

Using methanol as a co-solvent resulted in significantly higher (p ≤ 0.05) even at temperatures as low as 50 °C, thus undermining the limitation of thermal degradation at higher temperatures during PHWE.