2021
DOI: 10.3390/foods10020216
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The Influence of Weather on the Occurrence of Aflatoxin B1 in Harvested Maize from Kenya and Tanzania

Abstract: A study was conducted using maize samples collected from different agroecological zones of Kenya (n = 471) and Tanzania (n = 100) during the 2013 maize harvest season to estimate a relationship between aflatoxin B1 concentration and occurrence with weather conditions during the growing season. The toxins were analysed by the ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method. Aflatoxin B1 incidence ranged between 0–100% of samples in different regions with an average valu… Show more

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Cited by 18 publications
(7 citation statements)
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“…Therefore, the weather in the three study sites of Kisumu, Makueni, and Kilifi had a high percentage of maximum relative humidity and temperatures which according to Muga et al (2019) influence the growth of fungi and aggravates aflatoxin contamination of maize. Likewise, in Temba et al (2021), low rainfall combined with high temperatures increase the chances of aflatoxin contamination in maize which proves the case in the study sites. Equally, in Keller et al (2022), the evolving climatic conditions in sub -Saharan Africa, Kenya included, are conducive for aflatoxin production.…”
Section: Discussionsupporting
confidence: 70%
“…Therefore, the weather in the three study sites of Kisumu, Makueni, and Kilifi had a high percentage of maximum relative humidity and temperatures which according to Muga et al (2019) influence the growth of fungi and aggravates aflatoxin contamination of maize. Likewise, in Temba et al (2021), low rainfall combined with high temperatures increase the chances of aflatoxin contamination in maize which proves the case in the study sites. Equally, in Keller et al (2022), the evolving climatic conditions in sub -Saharan Africa, Kenya included, are conducive for aflatoxin production.…”
Section: Discussionsupporting
confidence: 70%
“…Hence, DON and OTA did not constitute any mycotoxic risk in the food samples studied. [45][46][47] Safe levels of DON in all samples and unsafe levels of OTA in some (but not all) samples of Tom Bran in Nigeria have been reported. 18 The relative observable difference in these findings may be due to the season of sample collection and storage duration of product from which samples were drawn.…”
Section: Resultsmentioning
confidence: 99%
“…The logistic regression model resulted in the best F1 score with the highest %accuracy, %sensitivity, and %specificity ( Table 5 ) followed by RF and SVM. A previous study demonstrated that the RF model achieved high specificity (>80%) and sensitivity (76.2%) for AFB 1 detection in maize samples [ 32 ]. However, this preliminary study demonstrated the choice of spectral preprocessing procedures and machine learning algorithms to identify AFB 1 contamination.…”
Section: Discussionmentioning
confidence: 99%