Post-harvest insect infestation and mycotoxin levels in maize markets in the Middle Belt of Ghana

Danso, J.K.; Osekre, E.A.; Opit, George P.; Manu, N.; Armstrong, Paul R.; Arthur, F. H.; Campbell, James F.; Mbata, George N.; McNeill, Samuel G.

doi:10.1016/j.jspr.2018.02.004

Cited by 30 publications

(15 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other studies revealed that the storage of harvests in inappropriate structures also favours the growth of insects and mould, especially when the humidity is high [1,28,29]. Indeed, the increase of humidity strongly coincides with the amplification of damages leading to the significative losses of the harvests weight [9,10, 30,31].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Determination of Merchantability of Maize (Zea mays L.) as Epis, Spathes and Grains Stocked in the Production Areas of Côte d'Ivoire

Bamba

Biego²,

Coulibaly

et al. 2020

JAERI

View full text Add to dashboard Cite

Aims: This study aims to determine merchantability of maize produced and stocked as grains, epis and spathes of maize in five departments of Côte d’Ivoire. Study Design: A total of 375 samples were collected at rate of 75 samples by department (Botro, Korhogo, Katiola, Agniblékro and Bondoukou). Then, the received samples were sent to the laboratory in order to analyse their merchantability. Place and Duration of Study: The collection of samples was carried out on grains, epis and spathes maize from February 2013 to January 2014. Then, the analyzes were carried out at the Biochemistry and Food Sciences Laboratory of the Félix Houphouët-boigny University. Methodology: The humidity was determined by drying until constant weight when the losses and damages of grains have been quantified by counting and weighing. Results: The results show that for maize grains, humidity levels vary from 8.59±0.11% to 14.18±0.52%. Concerning epis of maize, humidity levels are between 9.85±0.23% to 13.02±0.32%. For maize spathes, humidity levels fluctuate between 11.16±0.29% to 14.17±0.32%. The damages varies from 5.01±2.64% to 19.35±2.00% for maize grains, 9.05±5.27% to 21.29±7.17% for epis and 17.95±1.13% for spathes. As regards weigh losses, proportions of grains, epis and spathes are between 1.53±1.17% and 5.10±0.97%, 2.43±1.70% and 6.54±1.79% and 2.76±1.18% and 5.11±2.65%, respectively. Conclusion: A significant variability from one department to another can be noticed at level of maize quality regardless the type of maize. The merchantability of maize seems to be tied to post-harvest treatments (drying), type of storage (epis, grains and spathes) and structure of storage.

show abstract

Section: Discussionmentioning

confidence: 99%

“…[12] as well as Danso, et al [29] revealed that the multiplication of insects pests is due to the storage conditions (grouped or isolated storage). They have also observed a diversity at the level of the number and the specie of insects pests according to the sites of studies.…”

Section: Discussionmentioning

confidence: 99%

Determination of Merchantability of Maize (Zea mays L.) as Epis, Spathes and Grains Stocked in the Production Areas of Côte d'Ivoire

Bamba

Biego²,

Coulibaly

et al. 2020

JAERI

View full text Add to dashboard Cite

show abstract

“…Jute bags can easily absorb moisture because of high porosity which favors rapid growth and multiplication of molds. Purdue Improved Crop Storage (PICS) bags that rely on the principle of hermetic storage have been used to prevent A. flavus infestation and aflatoxin contamination during storage (Sudini et al, 2015;Danso et al, 2018Danso et al, , 2019Walker et al, 2018). Although aflatoxin contamination is more severe in the field during pre-harvest stage, contamination may increase during post-harvest if management practices such as transportation and storage are deficient.…”

Section: Factors Affecting Toxigenicity and Aflatoxin Contaminationmentioning

confidence: 99%

Functional Biology and Molecular Mechanisms of Host-Pathogen Interactions for Aflatoxin Contamination in Groundnut (Arachis hypogaea L.) and Maize (Zea mays L.)

et al. 2020

View full text Add to dashboard Cite

Aflatoxins are secondary metabolites produced by soilborne saprophytic fungus Aspergillus flavus and closely related species that infect several agricultural commodities including groundnut and maize. The consumption of contaminated commodities adversely affects the health of humans and livestock. Aflatoxin contamination also causes significant economic and financial losses to producers. Research efforts and significant progress have been made in the past three decades to understand the genetic behavior, molecular mechanisms, as well as the detailed biology of host-pathogen interactions. A range of omics approaches have facilitated better understanding of the resistance mechanisms and identified pathways involved during host-pathogen interactions. Most of such studies were however undertaken in groundnut and maize. Current efforts are geared toward harnessing knowledge on hostpathogen interactions and crop resistant factors that control aflatoxin contamination. This study provides a summary of the recent progress made in enhancing the understanding of the functional biology and molecular mechanisms associated with host-pathogen interactions during aflatoxin contamination in groundnut and maize.

show abstract

“…Therefore, delays in maize harvest after that stage means giving the fungus time to efficiently increase the contamination. Then, keep kernel moisture below 14% is mandatory in the postharvest stages, from drying to the whole storage period (Danso et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Predicting Mycotoxin Occurrence in Maize

2021

View full text Add to dashboard Cite

Meteorological conditions are the main driving variables for mycotoxin-producing fungi and the resulting contamination in maize grain, but the cropping system used can mitigate this weather impact considerably. Several researchers have investigated cropping operations’ role in mycotoxin contamination, but these findings were inconclusive, precluding their use in predictive modeling. In this study a machine learning (ML) approach was considered, which included weather-based mechanistic model predictions for AFLA-maize and FER-maize [predicting aflatoxin B1 (AFB1) and fumonisins (FBs), respectively], and cropping system factors as the input variables. The occurrence of AFB1 and FBs in maize fields was recorded, and their corresponding cropping system data collected, over the years 2005–2018 in northern Italy. Two deep neural network (DNN) models were trained to predict, at harvest, which maize fields were contaminated beyond the legal limit with AFB1 and FBs. Both models reached an accuracy >75% demonstrating the ML approach added value with respect to classical statistical approaches (i.e., simple or multiple linear regression models). The improved predictive performance compared with that obtained for AFLA-maize and FER-maize was clearly demonstrated. This coupled to the large data set used, comprising a 13-year time series, and the good results for the statistical scores applied, together confirmed the robustness of the models developed here.

show abstract

Post-harvest insect infestation and mycotoxin levels in maize markets in the Middle Belt of Ghana

Cited by 30 publications

References 10 publications

Determination of Merchantability of Maize (Zea mays L.) as Epis, Spathes and Grains Stocked in the Production Areas of Côte d'Ivoire

Determination of Merchantability of Maize (Zea mays L.) as Epis, Spathes and Grains Stocked in the Production Areas of Côte d'Ivoire

Functional Biology and Molecular Mechanisms of Host-Pathogen Interactions for Aflatoxin Contamination in Groundnut (Arachis hypogaea L.) and Maize (Zea mays L.)

Machine Learning for Predicting Mycotoxin Occurrence in Maize

Contact Info

Product

Resources

About