Aflatoxigenic potential of Aspergillus section Flavi isolated from maize seeds, in Burkina Faso

Samandoulougou

et al. 2021

JAMB

A total of four samples of rice intended for infant flour production in Ouagadougou were received at the Physico-chemistry laboratory of Food Technology Department (DTA) for quality control. The latter were also tested for Aspergillus section Flavi presence and analyzed for aflatoxins B1, B2, G1 and G2 content using high performance liquid chromatography (HPLC). Among the twenty (20) strains of mold isolated from these samples, three Aspergillus section Flavi were obtained and cultivated in “Aspergillus flavus and parasiticus Agar (AFPA)” to ascertain if they belong to Aspergillus flavus or Aspergillus parasiticus species. The qualitative ability of aflatoxin production was also performed by fluorescence emission under ultra violet light at 365 nm after four days of incubation at 30 °C on Coconut Agar Medium (CAM). Statistical analysis results showed that 75% of samples were contaminated with total aflatoxins (AFs) with contents ranging from 0.54 ± 0.06 to 2.40 ± 0.07 µg/Kg. Aflatoxin B1 (AFB1) and aflatoxin B2 (AFB2) were detected in two contaminated samples. AFB1 had the highest concentration as compared with other aflatoxins. A significant level of contamination (p< 0.0001) was observed in sample R441 compared to other sample types.

Section: Discussionmentioning

confidence: 99%

Occurrence of Aflatoxins in Rice Intended for Infant Flour Production in Ouagadougou, Burkina Faso

Samandoulougou

et al. 2021

JAMB

Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods

Ngum

Babalola

Ekwomadu

et al. 2022

Toxins

Africa is one of the regions with high mycotoxin contamination of foods and continues to record high incidences of liver cancers globally. The agricultural sector of most African countries depends largely on climate variables for crop production. Production of mycotoxins is climate-sensitive. Most stakeholders in the food production chain in Africa are not aware of the health and economic effects of consuming contaminated foods. The aim of this review is to evaluate the main factors and their degree of contribution to the high levels of mycotoxins in African foods. Thus, knowledge of the contributions of different factors responsible for high levels of these toxins will be a good starting point for the effective mitigation of mycotoxins in Africa. Google Scholar was used to conduct a systemic search. Six factors were found to be linked to high levels of mycotoxins in African foods, in varying degrees. Climate change remains the main driving factor in the production of mycotoxins. The other factors are partly man-made and can be manipulated to become a more profitable or less climate-sensitive response. Awareness of the existence of these mycotoxins and their economic as well as health consequences remains paramount. The degree of management of these factors regarding mycotoxins varies from one region of the world to another.

Aflatoxins in Maize: Can Their Occurrence Be Effectively Managed in Africa in the Face of Climate Change and Food Insecurity?

Nji

Babalola

Mwanza

2022

Toxins

The dangers of population-level mycotoxin exposure have been well documented. Climate-sensitive aflatoxins (AFs) are important food hazards. The continual effects of climate change are projected to impact primary agricultural systems, and consequently food security. This will be due to a reduction in yield with a negative influence on food safety. The African climate and subsistence farming techniques favour the growth of AF-producing fungal genera particularly in maize, which is a food staple commonly associated with mycotoxin contamination. Predictive models are useful tools in the management of mycotoxin risk. Mycotoxin climate risk predictive models have been successfully developed in Australia, the USA, and Europe, but are still in their infancy in Africa. This review aims to investigate whether AFs’ occurrence in African maize can be effectively mitigated in the face of increasing climate change and food insecurity using climate risk predictive studies. A systematic search is conducted using Google Scholar. The complexities associated with the development of these prediction models vary from statistical tools such as simple regression equations to complex systems such as artificial intelligence models. Africa’s inability to simulate a climate mycotoxin risk model in the past has been attributed to insufficient climate or AF contamination data. Recently, however, advancement in technologies including artificial intelligence modelling has bridged this gap, as climate risk scenarios can now be correctly predicted from missing and unbalanced data.