This document analyzes aflatoxin levels and the fungi causing aflatoxins in rain-fed groundnuts from communal and small-holder farmers in Mashonaland Central, Zimbabwe. Samples were collected from three areas - Mt Darwin, Rushinga, and Chiweshe - and analyzed for aflatoxin concentration using ELISA and for fungal load by examining fungal growth. Results showed Mt Darwin had the highest aflatoxin and fungal levels while Rushinga and Chiweshe had lower levels, possibly due to education programs. Aflatoxin concentrations exceeded EU limits. The study assessed the presence of Aspergillus flavus, A. niger and other fungi to better understand a
Post Harvest Management Technologies for Reducing Aflatoxin Contamination in ...Francois Stepman
Dr. Loveness K. Nyanga
Senior Lecturer and Researcher, University of Zimbabwe
PhD, Wageningen University, The Netherlands
MSC and BSc, University of Zimbabwe
Management of Aflatoxin in Africa: working group on aflatoxin, Brussels 25/01/2016
Postharvest management technologies for reducing aflatoxin contamination in m...Francois Stepman
Loveness K. Nyanga (University of Zimbabwe/Action contre la faim)
Roundtable of aflatoxin experts on
“Building a multi-stakeholder approach to mitigate aflatoxin contamination of food and feed”
Brussels, Monday 25th January 2016
ICRISAT Research Program West and Central Africa 2016 Highlights- Aflatoxin c...ICRISAT
Awareness of aflatoxin contamination is being raised in northern regions of Ghana to combat the adverse economic, health and nutritional consequences, especially among rural communities.
Post Harvest Management Technologies for Reducing Aflatoxin Contamination in ...Francois Stepman
Dr. Loveness K. Nyanga
Senior Lecturer and Researcher, University of Zimbabwe
PhD, Wageningen University, The Netherlands
MSC and BSc, University of Zimbabwe
Management of Aflatoxin in Africa: working group on aflatoxin, Brussels 25/01/2016
Postharvest management technologies for reducing aflatoxin contamination in m...Francois Stepman
Loveness K. Nyanga (University of Zimbabwe/Action contre la faim)
Roundtable of aflatoxin experts on
“Building a multi-stakeholder approach to mitigate aflatoxin contamination of food and feed”
Brussels, Monday 25th January 2016
ICRISAT Research Program West and Central Africa 2016 Highlights- Aflatoxin c...ICRISAT
Awareness of aflatoxin contamination is being raised in northern regions of Ghana to combat the adverse economic, health and nutritional consequences, especially among rural communities.
An integrated approach to assessing and improving milk safety and nutrition i...ILRI
Presentation by G. Msalya, E. Joseph, F. Shija, L.R. Kurwijila, D. Grace, K Roesel, B Haesler, F Ogutu, A Fetsch, G Misinzo and H Nonga at the First African Regional Conference of the International Association on Ecology and Health (Africa 2013 Ecohealth), Grand-Bassam, Côte d'Ivoire, 1-5 October 2013.
Abstract— Coccidiosis swine causes high economic loss, and its prophylaxis is usually performed by the use of chemical drugs. However, these chemical drugs are not allowed in agroecological, organic or biological dynamic systems of production. Additionally, there are concerns about pharmacological resistance and contamination by the presence of chemical residues in the environment and at the food of animal origin. The objective of this study was to evaluate the weight gain and the prevalence of coccidia in piglets submitted to the following treatments: alcoholic extract of propolis 30% (AEP), chemical treatment toltrazuril (CTT), negative control with grain alcohol (NCA) and negative control without treatment (NCT). By means of the individual weights and the number of coccidia at the faeces, it was monitored 216 piglets from commercial farms. Under the conditions of this study none therapeutic intervention provided benefits for weight gain and prevalence of coccidia. Thus, by making it possible the minimization of chemical drug use, these results allow us to suggest the laboratory periodic monitoring as a prophylactic control method for swine coccidiosis.
Foodborne hazards in the scientific literature: Results of a systematic liter...ILRI
Presentation by Silvia Alonso, Michael Ocaido, Maud Carron, Kristina Roesel and Delia Grace at the Regional Conference on Zoonotic Diseases in Eastern Africa, Naivasha, Kenya, 9–12 March 2015.
The study probed into the statistical analysis of the effect of organic and inorganic fertilizer on the yield of sorghum; which was carried out at Abubakar Tafawa Balewa University (ATBU) School Farm, Bauchi State. The study relied on secondary data from ATBU school farm structured using a single variety of sorghum at three level of organic (0, 1 and 2t/kg) and four level of inorganic (0, 15, 30, 45kgN/ha) fertilizer. Cow dung and NPK were sources of fertilizer used in the secondary data. SPSS version 20 software was employed to analyze the data obtained. Each variable considered was subjected to univariate analysis of variance (ANOVA) and comparison of the means by employing Duncan Multiple Range Test (DMRT). The result indicated that the effect of fertilization on yield and weight of sorghum were significant at p=0.001. Application of 45kgN/ha of NPK gave the highest yield of 3.6t/ha among sole application of NPK, while 1t/ha of cow dung recorded the highest yield (2.37t/ha) among sole application of cow dung. It was observed that a combination of 2t/ha of cow dung + 45kg/ha of NPK significantly (P=0.001) gave the highest yield of 4.4t/ha of sorghum. However, it was not significantly better than sole application of 45kg/ha of NPK and a combine application of 2t/ha of cow dung + 30kg/ha of NPK. Similarly, 2t/ha of cow dung + 45kg/ha of NPK significantly gave the highest weight of 418kg/ha of sorghum.
The relationship between trace mineral concentrations of amniotic fluid with ...Ali Olfati
Ali Olfati1*, Gholamali Moghaddam1, Nasroallah Moradi Kor2, Behzad Baradaran3
1Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
2Young Researchers and Elite Club, Kerman Branch, Islamic Azad University, Kerman, Iran
3Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Serological evidence of brucellosis in goatsSameer Sankhe
This ppt is related to the serological evidence of brucellosis in goats. Brucellosis is an important zoonotic disease of public health and veterinary sector
Over recent years several factors have led to an escalation of feed ingredient prices especially fishmeal. As a consequence, alternative commodities have been used, mainly plant protein sources. However, as a result of this trend, aquaculture feeds have a higher risk of being contaminated with mycotoxins.
Abstract
Pathogen-tested sweetpotato planting material is shown to provide a significant boost in yield and quality in the sweetpotato seed systems and value chains. In the absence of pathogen-tested planting material, negative selection has been shown to be effective in some cultivars and locations as well. Protective net tunnels allow decentralised vine multipliers to maintain and multiply limited quantities of clean planting material. Commercial demand for sweetpotato planting material is likely to be sustained if seed producers are able to provide evidence of the superiority of their product to their customers. The objective of this study was to evaluate the effects of net tunnel source and of pathogen-tested planting material on yield and health status (sweetpotato virus disease [SPVD] and weevil incidence) of crop. Studies were conducted in 2015, at locations in Ghana that varied with regard to SPVD and weevil pressure. Four varieties were used with pathogen-tested planting materials—‘Apomuden’, ‘Dadanyuie’, ‘Bohye’, and ‘Ligri’—and multiplied in net tunnels. ‘Apparently’ healthy (field-derived, negatively selected) material of the same varieties were also multiplied in adjacent field plots at one location in northern Ghana. For ‘Apomuden’, the apparently healthy planting material was multiplied in both net tunnel and open field at the same location. The trials were conducted at three sites in northern Ghana: Nyankpala, Navrongo, and Wa. At each site, 8 treatment combinations (4 varieties and 2 sources of planting material) were arranged in a trial design with three replicates. The 4 x 5.1 m plots were planted to 17 vine cuttings per row, spacing 0.30 m within rows and 1 m between rows, and no additional irrigation. Weeding, reshaping, and vine lifting were done at all locations. NPK (15:15:15) was applied at Navrongo and Wa, 4 weeks after planting, as recommended, due to natural poor soil fertility. Data were analysed using Genstat (12th edition). There were highly significant differences among varieties and trial sites for plant establishment, foliage yield, root yield, weevil damage, and SPVD rating; but source of planting material was not found to be significant. For SPVD, net tunnel source is better than open field (p<0.01).><0.04). The results indicate that apparently healthy planting material was as effective as pathogen-tested planting material. Net tunnels may have a distinct advantage for maintaining and multiplying planting material to produce healthy sweetpotato crops.
Putri E. Abidin
Though Maize and Sorghum are known as susceptible to Aflatoxin contamination, but Rice is no-way different, more particularly when the crop is grown in coastal ecosystem and flood prone areas.
Taking NIR beyond feedstuffs - analysis to enhance pork production profitabilityMilling and Grain magazine
Swine production has been facing substantial economic challenges in recent years, due to poor crop yields and increased competition for raw materials from the biofuel industry. As a consequence, feed prices have been variable and more industrial by-products have become available. At the same time, we have experienced increasing sustainability demands on animal production, for example to reduce nutrient release in effluent, while producing more and cheaper food for an increasing world population. All this has driven the swine industry to implement more professional, accurate and precise practises.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
An integrated approach to assessing and improving milk safety and nutrition i...ILRI
Presentation by G. Msalya, E. Joseph, F. Shija, L.R. Kurwijila, D. Grace, K Roesel, B Haesler, F Ogutu, A Fetsch, G Misinzo and H Nonga at the First African Regional Conference of the International Association on Ecology and Health (Africa 2013 Ecohealth), Grand-Bassam, Côte d'Ivoire, 1-5 October 2013.
Abstract— Coccidiosis swine causes high economic loss, and its prophylaxis is usually performed by the use of chemical drugs. However, these chemical drugs are not allowed in agroecological, organic or biological dynamic systems of production. Additionally, there are concerns about pharmacological resistance and contamination by the presence of chemical residues in the environment and at the food of animal origin. The objective of this study was to evaluate the weight gain and the prevalence of coccidia in piglets submitted to the following treatments: alcoholic extract of propolis 30% (AEP), chemical treatment toltrazuril (CTT), negative control with grain alcohol (NCA) and negative control without treatment (NCT). By means of the individual weights and the number of coccidia at the faeces, it was monitored 216 piglets from commercial farms. Under the conditions of this study none therapeutic intervention provided benefits for weight gain and prevalence of coccidia. Thus, by making it possible the minimization of chemical drug use, these results allow us to suggest the laboratory periodic monitoring as a prophylactic control method for swine coccidiosis.
Foodborne hazards in the scientific literature: Results of a systematic liter...ILRI
Presentation by Silvia Alonso, Michael Ocaido, Maud Carron, Kristina Roesel and Delia Grace at the Regional Conference on Zoonotic Diseases in Eastern Africa, Naivasha, Kenya, 9–12 March 2015.
The study probed into the statistical analysis of the effect of organic and inorganic fertilizer on the yield of sorghum; which was carried out at Abubakar Tafawa Balewa University (ATBU) School Farm, Bauchi State. The study relied on secondary data from ATBU school farm structured using a single variety of sorghum at three level of organic (0, 1 and 2t/kg) and four level of inorganic (0, 15, 30, 45kgN/ha) fertilizer. Cow dung and NPK were sources of fertilizer used in the secondary data. SPSS version 20 software was employed to analyze the data obtained. Each variable considered was subjected to univariate analysis of variance (ANOVA) and comparison of the means by employing Duncan Multiple Range Test (DMRT). The result indicated that the effect of fertilization on yield and weight of sorghum were significant at p=0.001. Application of 45kgN/ha of NPK gave the highest yield of 3.6t/ha among sole application of NPK, while 1t/ha of cow dung recorded the highest yield (2.37t/ha) among sole application of cow dung. It was observed that a combination of 2t/ha of cow dung + 45kg/ha of NPK significantly (P=0.001) gave the highest yield of 4.4t/ha of sorghum. However, it was not significantly better than sole application of 45kg/ha of NPK and a combine application of 2t/ha of cow dung + 30kg/ha of NPK. Similarly, 2t/ha of cow dung + 45kg/ha of NPK significantly gave the highest weight of 418kg/ha of sorghum.
The relationship between trace mineral concentrations of amniotic fluid with ...Ali Olfati
Ali Olfati1*, Gholamali Moghaddam1, Nasroallah Moradi Kor2, Behzad Baradaran3
1Department of Animal Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran
2Young Researchers and Elite Club, Kerman Branch, Islamic Azad University, Kerman, Iran
3Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Serological evidence of brucellosis in goatsSameer Sankhe
This ppt is related to the serological evidence of brucellosis in goats. Brucellosis is an important zoonotic disease of public health and veterinary sector
Over recent years several factors have led to an escalation of feed ingredient prices especially fishmeal. As a consequence, alternative commodities have been used, mainly plant protein sources. However, as a result of this trend, aquaculture feeds have a higher risk of being contaminated with mycotoxins.
Abstract
Pathogen-tested sweetpotato planting material is shown to provide a significant boost in yield and quality in the sweetpotato seed systems and value chains. In the absence of pathogen-tested planting material, negative selection has been shown to be effective in some cultivars and locations as well. Protective net tunnels allow decentralised vine multipliers to maintain and multiply limited quantities of clean planting material. Commercial demand for sweetpotato planting material is likely to be sustained if seed producers are able to provide evidence of the superiority of their product to their customers. The objective of this study was to evaluate the effects of net tunnel source and of pathogen-tested planting material on yield and health status (sweetpotato virus disease [SPVD] and weevil incidence) of crop. Studies were conducted in 2015, at locations in Ghana that varied with regard to SPVD and weevil pressure. Four varieties were used with pathogen-tested planting materials—‘Apomuden’, ‘Dadanyuie’, ‘Bohye’, and ‘Ligri’—and multiplied in net tunnels. ‘Apparently’ healthy (field-derived, negatively selected) material of the same varieties were also multiplied in adjacent field plots at one location in northern Ghana. For ‘Apomuden’, the apparently healthy planting material was multiplied in both net tunnel and open field at the same location. The trials were conducted at three sites in northern Ghana: Nyankpala, Navrongo, and Wa. At each site, 8 treatment combinations (4 varieties and 2 sources of planting material) were arranged in a trial design with three replicates. The 4 x 5.1 m plots were planted to 17 vine cuttings per row, spacing 0.30 m within rows and 1 m between rows, and no additional irrigation. Weeding, reshaping, and vine lifting were done at all locations. NPK (15:15:15) was applied at Navrongo and Wa, 4 weeks after planting, as recommended, due to natural poor soil fertility. Data were analysed using Genstat (12th edition). There were highly significant differences among varieties and trial sites for plant establishment, foliage yield, root yield, weevil damage, and SPVD rating; but source of planting material was not found to be significant. For SPVD, net tunnel source is better than open field (p<0.01).><0.04). The results indicate that apparently healthy planting material was as effective as pathogen-tested planting material. Net tunnels may have a distinct advantage for maintaining and multiplying planting material to produce healthy sweetpotato crops.
Putri E. Abidin
Though Maize and Sorghum are known as susceptible to Aflatoxin contamination, but Rice is no-way different, more particularly when the crop is grown in coastal ecosystem and flood prone areas.
Taking NIR beyond feedstuffs - analysis to enhance pork production profitabilityMilling and Grain magazine
Swine production has been facing substantial economic challenges in recent years, due to poor crop yields and increased competition for raw materials from the biofuel industry. As a consequence, feed prices have been variable and more industrial by-products have become available. At the same time, we have experienced increasing sustainability demands on animal production, for example to reduce nutrient release in effluent, while producing more and cheaper food for an increasing world population. All this has driven the swine industry to implement more professional, accurate and precise practises.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Lateral Ventricles.pdf very easy good diagrams comprehensive
Aspire Mtingwende BSc Research Paper
1. ANALYSIS OF AFLATOXIN LEVELS AND AFLATOXIN
CAUSING FUNGI ON RAIN-FED GROUNDNUTS IN
COMMUNAL AND SMALL HOLDER FARMERS IN
MASHONALAND CENTRAL, ZIMBABWE
By
ASPIRE MTINGWENDE
A dissertation submitted in partial fulfillment of the requirements for the BSc Honours Degree
in Biological Sciences
Department of Biological Sciences
Faculty of Science and Technology
Midlands State University
November 2014
2. Abstract
The study was carried out to determine the presence of aflatoxins and assess the fungal load in rain-fed
groundnuts from the Mashonaland Central province of Zimbabwe, which is the biggest Peanut farming
region in the country. Samples were collected from selected communal and small-holder farmers,
randomly in the three study areas Mt Darwin, Rushinga and Chiweshe between July and October 2013.
From these samples, the aflatoxin concentrations and fungal loads were determined. The aflatoxin content
of the peanuts was determined using the ELISA method, whilst the fungal load was determined through
the Blotter method, incubation and a final count of the nuts infested with Aspergillus. The aflatoxin
concentrations were then compared to the EU regulatory standard aflatoxin limit of 20ng/g in raw peanuts
for total aflatoxin load and 8ng/g for AFB1. Results showed that there was a statistically significant
difference between the three areas tested for aflatoxin concentration, showing a p-value of 0. However,
after checking for the statistical relationship within the study sites tested using a Multiple comparison post-
hoc test, it was found that the samples from site 3 in Chiweshe and those from site 1 in Rushinga did not
differ statistically, they both had a p-value of 0.733, at a 95% significance level. However, before data
analysis using One-way Anova was done to check for a statistical significance between the aflatoxin levels
in the study areas, the mean aflatoxin concentrations for each study area were calculated. It showed that Mt
Darwin was found to have the highest aflatoxin level of 35.56 ng/g, followed by Chiweshe with 6.532 ng/g
and Rushinga which had 5 ng/g. The AFB1 concentrations in these areas also ranged from 0 to 3 in
Chiweshe and Rushinga, respectively, whilst Mt Darwin gave an aflatoxin B1 concentration of 18 ng/g,
which is much higher than the EU regulatory limit of 8 ng/g. The A. flavus and A. niger presence in Mt
Darwin was also highest with figures of 30% and 22%, respectively. This was to be expected due to the
relatively high aflatoxin content from these areas. Chiweshe and Rushinga, however recorded much lower
A. flavus and A. niger levels on its groundnuts. Besides the Aspergillus, various other fungi were found in
the sampled nuts. Fusarium spp., notably F. oxysporum and F. moniliforme, showed a much higher
presence than any other fungi, inclusive of Aspergillus in all the study sites. This showed a probable high
mycotoxin concentration in the nuts. The high presence of Aspergillus spp., in the Mt Darwin area was
attributed to crop rotation and poor post-harvest management. However, the low levels in Rushinga and
Chiweshe could be attributed to surveillance programmes and farmer education on good groundnut
farming practice.
3. Acknowledgements
I attribute the work in this entire dissertation to Mrs Muhera, special thanks goes to her
mentorship and acumen in this project. The PPRI Institute at the Department of Research and
Specialist Services also played a huge role in the testing of the various samples that were done in
this dissertation.
Mr J Bare, my supervisor, was also an invaluable asset in the standardization of this project, his
direction and patience has been key.
III
4. Dedication
To my Mother and Father, who have been a pillar of hope in all my life, on a mission to make me
the person they aspire me to be. Much thanks also is given to my Sister and her husband, who
have been my keepers since the inception of my studies. The Lord is good.
IV
5. Contents
List of tables................................................................................................................................... vii
List of figures ................................................................................................................................ viii
List of Appendices .......................................................................................................................... ix
CHAPTER 1: INTRODUCTION ...................................................................................................10
1.1 Background of the study ...................................................................................................10
1.2 Justification .......................................................................................................................11
1.3 Objective ...............................................................................................................................13
1.3.1 Main Objective:..............................................................................................................13
1.4.2 Specific Objective:.........................................................................................................13
CHAPTER 2: Literature Review ....................................................................................................14
2.1 Fungal species causing aflatoxin.......................................................................................14
2.1.1 Aspergillus flavus...........................................................................................................14
2.1.2 Infection in Peanuts........................................................................................................15
2.2 Chemical composition of aflatoxins..................................................................................15
2.3 Significance of aflatoxins......................................................................................................16
2.3.1 Health effects .................................................................................................................16
2.3.2 Economic effects............................................................................................................19
2.4 Methods of detecting aflatoxins........................................................................................20
2.4.1 Electrochemical techniques............................................................................................20
2.4.2 Chromatography.............................................................................................................21
2.4.3 Fluorescence...................................................................................................................23
2.5 Methods of countering aflatoxin .......................................................................................25
CHAPTER 3: MATERIALS AND METHODS.............................................................................28
3.1 Study site...........................................................................................................................28
3.1.1 Sampling and collection.................................................................................................28
3.2 Analysis of fungal load .....................................................................................................29
3.3 Aflatoxin analysis..............................................................................................................30
CHAPTER 4: RESULTS...............................................................................................................32
CHAPTER 5: DISCUSSION..........................................................................................................38
CHAPTER 6: Conclusions and recommendations .........................................................................40
6.1 Conclusions.......................................................................................................................40
6.2 Recommendations.............................................................................................................40
CHAPTER 7: References................................................................................................................41
7. List of tables
Table Page
1: EU regulatory aflatoxin concentrations for tree nuts, peanuts, cereals and raw
milk…………………………………………………………………………………………….…22
2: Presence of A. flavus, A. niger and A. parasiticus in samples from Mt
Darwin……………………………………………………………………………………………34
3: Presence of A. flavus, A. niger and A. parasiticus in samples from
Rushinga………………………………………………………………………………………….35
4: Presence of A. flavus, A. niger and A. parasiticus in samples from
Chiweshe……………………………………………………………………………………….…35
5: Incidence of fungi in the Total Fungal Count………………………………………….……....36
6: Concentration of aflatoxin production by the toxigenic A. flavus and A. niger isolated from
peanuts in Mt Darwin……………………………………………………….……………….…....37
7: Concentration of aflatoxin production by the toxigenic A. flavus and A. niger isolated from
peanuts in Rushinga……………………………………………………….……………….……...38
8: Concentration of aflatoxin production by the toxigenic A. flavus and A. niger isolated from
peanuts in Chiweshe…………………………………………………….……………….……..…38
VII
8. List of figures
Figure Page
1: Value of shelled groundnut exports from African regions………………………19
2: An example of groundnut seeds infected with A. flavus………………………..30
3: incidence of Aspergillus flavus and Aspergillus niger in
Darwin, Rushinga and
Chiweshe………………………….…………………………………………….…..36
VIII
9. List of Appendices
Appendix
Page
1: One- way Anova Comparison of total aflatoxin content in groundnuts from all
three study areas between groups at a 95% confidence
interval……………………………………………………………………………………………..…43
2: Output from Multiple comparisons post-hoc test between all study sites at 95% confidence
interval………………………………………….………………………...……………………….….43
IX
11. 10
CHAPTER 1: INTRODUCTION
1.1 Background of the study
Groundnuts (Arachis hypogaea L) rank sixth among oilseed crops and thirteenth among the
food crops of the world in terms of importance (NRC, 2008). In addition to providing high
quality edible oil (48-50%), easily digestible protein (26-28%), nearly half of the 13 essential
vitamins and seven of the essential minerals necessary for normal human growth, they
produce high quality fodder for livestock. They thus play a significant role in the livelihoods
of marginal farmers through income and nutritional security. Groundnuts are grown on 26.4
million hectares of land worldwide with a total production of 36.1 million metric tonnes
(NRC, 2008). Developing countries account for 97% of the world‟s groundnut area and 94%
of the total production (AOAC, 1984). In Zimbabwe, groundnut is the most important grain
legume grown in terms of the total production and area under cultivation (DRSS, 2002). The
crop provides an important source of food and cash income for smallholder farmers and until
the mid-1990s was a key export crop. However, production and export of the crop has
steadily declined since the late 1980s as a result of declining area under production and
reduced yields (DRSS, 2002). Various reasons have been forwarded for this decline,
including climate variability, pest and diseases contamination, including mycotoxins, and
competition for export markets.
Mycotoxins are chemical substances naturally produced by fungi that contaminate crops
during production, harvest, storage and food processing. Although thousands of mycotoxins
exist, few pose significant risks with regards to food safety. In this regard, three genera of
mycotoxin producing fungi are dominant, these are Aspergillus, Fusarium and Penicillium
(Probst, Schulthess and Cotty, 2010). Aflatoxins, caused by Aspergillus spp., are reported to
be some of the most potent mycotoxins characterized by carcinogenic, mutagenic, teratogenic
and immunosuppressive properties (El-Nakib, Pestka and Chu, 1981). Aflatoxins can be
found on a wide range of crop species including groundnuts, maize, sorghum, cassava,
cottonseed, Brazil nuts, spices, dried coconut and figs (Probst et al., 2010). Those common in
cereals and legumes are produced by two species of Aspergillus; A. flavus and A. parasiticus.
The native habitat of Aspergillus is the soil, decaying vegetation, hay and grains undergoing
microbiological deterioration (El-Nakib et al., 1981)
12. 11
Four chemical „types‟ of aflatoxins are known, these are B1, B2, G1 and G2 named from the
fluorescence produced when exposed to ultraviolet radiation (B for blue and G for green).
Aflatoxin B2 and G2 are dihydroxylated derivatives of B1 and G1 while aflatoxins M1 and
M2 are hydroxylated derivatives of B1 and B2 found in milk of cows that have been fed
aflatoxin contaminated fodder (Anon, 1989).
The thin layer chromatography (TLC) systems developed in the 1960s and 1970s are still the
most commonly used methods for detection and estimation of aflatoxins in groundnut and
several other agricultural commodities. These methods are expensive and time consuming
and so efforts have been made to develop more rapid and less expensive methods for
aflatoxin analysis (El-Nakib et al., 1981). Several enzyme-linked immunoarbosorbent assay
(ELISA) procedures have been reported for the estimation of aflatoxin B, in groundnut and
groundnut products (El-Nakib et al., 1981). These assays have advantages over conventional
analytical procedures using TLC and high pressure liquid chromatography (HPLC) in terms
of speed, ease of sample preparation and use and are potentially cheaper for aflatoxin
analysis. The major application of ELISA procedures at present is analysis of aflatoxin B1in
such agricultural commodities as maize, groundnut and groundnut products (El-Nakib et al.,
1981).
1.2 Justification
Groundnuts are a popular source of food throughout the world, including Zimbabwe. In
Zimbabwe, groundnuts are consumed as peanut butter or crushed and used for the groundnut
oil or simply consumed as a confectionary snack roasted, salted or in sweets. They are boiled,
either in the shell or unshelled. Groundnuts are produced in the tropical and subtropical
regions of the world, on sandy soils. The production practices vary from highly sophisticated
commercial ventures in the western world to more traditional cropping practices in third
world countries. In Zimbabwe, groundnuts are grown in the summer rainfall regions under
irrigated or rain-fed condition. According to the research done in the past 10 years the
Zimbabwean population showed exposure to aflatoxins (DRSS, 2013). Measurements of
urinary aflatoxin levels in samples collected from across the country were done and 4.3% of
the samples analyzed were contaminated (DRSS, 2013). In the same year, 11% of
Zimbabwean human breast milk analyzed was reported to be positive for contamination of
13. 12
aflatoxins M1 and M2 (Wild and Payne, 1987). Siwela (1996), analyzed two hundred and
seventy seven samples consisting of groundnuts, peanut butter, beans, cowpeas, maize,
sorghum and millet and found that 16 % of the commodities had a total aflatoxin level greater
than the action limit of 20 µg/g. As peanut butter was found to have a higher incidence of
aflatoxin contamination a study to follow aflatoxin carryover during large scale peanut butter
production was carried out in 1997.
High aflatoxin levels in Zimbabwean peanuts are affecting its trade and economy, thus
costing millions of dollars‟ worth of exports in the international market (DRSS, 2013).
Besides this, the local consumers are being exposed to detrimental carcinogenic levels in their
peanuts and peanut related foodstuffs that could wreak havoc on their health in the form of
cancer, aflatoxicosis and other related maladies.
The Zimbabwean economy is also currently trying to revive itself from a decade long
economic recession. The amount of trade and development it is missing out on in the
agricultural sector due to aflatoxins is enormous (DRSS, 2013). Hence the need to quantify
and alleviate this problem before it gets bigger and causes irreversible harm on its groundnut
industry. At present there has been a report at the Department of Research and Specialist
Services, on the possibility of aflatoxin contamination from the Mashonaland Central
Province which appeared to have a higher level of Aflatoxin. There is need for an
investigation to be carried on those areas so as to confirm the prevalence of the aflatoxins and
remedial measures to be effected as soon as possible.
Aflatoxins are carcinogenic and produced by the Aspergillus flavus group of fungi. The
maximum aflatoxin level for groundnut acceptable in USA is 20 ppb (Probst et al., 2011).
The nature and extent of distribution of this problem needs to be documented as the basis for
future intervention programmes.
14. 13
1.3 Objective
1.3.1 Main Objective:
to analyze and quantify the aflatoxin levels in specific study sites in Mashonaland
Central and compare them to EU regulatory standards on aflatoxin content.
1.3.2 Specific Objective:
to measure the extent and type of Aspergillus spp. colonizing groundnuts from the
study sites in Mashonaland Central, and
to determine the aflatoxin concentration in the three study sites and compare them
with each other.
15. 14
CHAPTER 2: Literature Review
2.1 Fungal species causing aflatoxin
Aflatoxins are secreted by up to 36 fungal species. However, most of these species do not
produce them in concentrations high enough to cause significant problems in the immune
system. The Aspergillus spp. contains a number of species notably A. flavus, A. niger and A.
parasiticus. A. flavus is the main producer of aflatoxin in Sub-Saharan Africa (Probst et al.,
2010).
2.1.1 Aspergillus flavus
A. flavus one of the main causes of mycological diseases in agronomically important crops
such as peanuts and corn. Besides Aspergillus fumigates, A. flavus is the main cause of
Human Invasive Aspergillosis and has been reported as the causative in most infection cases
through an entomological vector (Heathcote and Hibbert, 1978). Occurring mostly as a
saprophytic fungus on dead or decomposing plant material, it can infect food products,
cereals and nuts.
The infectious abilities of A. flavus are quite interesting as it causes disease in plants, animals
and insects. Most fungi have evolved from opportunistic forms to more specialized
pathogens. This is due to the production of a range of host-specific/ selective toxins and
extra-cellular enzymes that provide the much needed genetic isolation for evolutionary
changes. This results in divergence from within the species, causing separate pathogenicity
types. However, the production of a variety of toxins, including aflatoxins by A. flavus, has
allowed it to routinely associate with plants, animals and insects at will, as these nutrient
sources become available temporarily, thus resulting in non-divergence of this pathogenic
species. According to Cotty and Mellon (2006), entomological infection by A. flavus used as
not more than a substrate, for the creation of a large enough inoculum, thus exponentially
increasing the insect‟s damage in the plant to be affected.
A. flavus consists of two major strains, the L-type and S-type. The S strain has been found to
produce much more aflatoxin than the L strain and the toxigenicity of a particular A. flavus
community can actually be determined by the percentage of strain S isolates found within the
soil (Yu, 2004). Besides the L and S strains, recent research by Probst (2011), has proven to
us that not all A. flavus strains produce aflatoxin and these non-toxigenic strains can actually
be used to competitively exclude the toxigenic strains in peanuts (Yu, 2004).
16. 15
First reported in field maize by Tabubenhaus (1920), about 75years ago, the contamination of
crops prior to harvest or during storage by A. flavus and A. parasiticus continues to be an
international problem. The genes of these two important aflatoxigenic species are very
homologous, with most researchers failing to differentiate between the two in their studies.
(Vesonder, 1991).
2.1.2 Infection in Peanuts
Due to their saprophytic nature, fungal colonies of Aspergillus flavus originate on the soil.
Here, they decompose the various dead organic materials found in the farm field, such as the
corn kernels, cobs, peanut shells and grass stems. Prior to sowing of the plants, the fungus
overwinters as either mycelium or sclerotia (Dorner and Cole, 2002). Both of these can
germinate either producing hyphae or conidia (asexual fungal spores). The conidia are
dispersible and can be distributed around the soil and air. They then find their way onto the
peanut shells, within the soil and onto the plant stem with the use of insects or wind
distribution mechanisms. Here, the conidia spread through the production of hyphae. As the
colony grows, a mycelium is formed. This is a network of hyphae that secretes extracellular
enzymes which break down food sources. These enzymes can be toxic to the plant (Yu,
2004).
Aspergillus flavus can thrive in hot dry conditions. Unlike most fungi it reaches optimum
growth at 25- 42°C. However it will grow at temperatures of between 12- 48°C. This makes
it perfect for post-harvest infection.
2.2 Chemical composition of aflatoxins
Chemically aflatoxins are a group of difuranocoumarins produced by certain strains of
Aspergillus flavus and Aspergillus parasiticus (Eaton and Groopman, 1994). Presently 18
different types of aflatoxins have been identified with aflatoxins, these are, B1, B2, GI, G2,
M1 and M2 (Vesonder, 1991). Aflatoxins have high melting points of 260°C with a thermal
degradation temperature of 269°C and hence very stable to heat, (Vesonder, 1991). However
they are destroyed by strong oxidising agents and alkalis and are decomposed on exposure to
air, ultra-violet and visible light (Heathcote and Hibbert, 1978). Aflatoxins are produced on a
variety of substrates at an optimum temperature of 30-35° C with a relative humidity of 80-
85%. Among the substrates rice, groundnut and maize have been shown to yield substantial
amounts of aflatoxin under laboratory conditions (Eaton and Groopman, 1994).
17. 16
2.3 Significance of aflatoxins
2.3.1 Health effects
According to the American Association for Cancer Research (1980), Aflatoxin B1 (AFB1) is
now recognized amongst the most potent chemical carcinogens known to man. This acute
toxicity, mutagenicity and carcinogenicity of aflatoxins are associated with the presence of
the 8, 9 double bond and the terminal cyclopen-tanone ring. In order of toxicity,
B1>G1>B2>G2, this in itself shows the potency of this cyclopen-tanone ring.
Human exposure to AFB1 occurs directly through consumption of contaminated foods (eg,
cereals, nuts, dried fruits and vegetables) and indirectly through consumption of animal
products (eg, meat, milk, poultry and eggs). The problem of human consumption of foods
contaminated by AFB1 is most serious in developing countries that lack proper processing
procedures, storage facilities and food-safety monitoring (Payne, 1998). In addition, many of
the rural populations in developing countries are dependent on stored grains for their daily
diet and for feeding domestic birds or animals. Such practices constitute significant health
risks through the propagation of hazardous levels of AFB1 in the daily diet, owing to
consumption of domestic birds and animals that have been fed contaminated grain. However,
Payne (1998), discovered that the aflatoxin levels in populations from developed countries
were nearly as high as that found in South East Asia and Africa. This was attributed to a high
level of exposure to Aflatoxin B1 their food sources.
The acute effects of aflatoxin have been documented by a number of scientists both in
humans and in animals (Dorner and Cole, 2002). Evidence has shown AFB1 to cause cancer
in the organs and liver of a broad array of species (Yu, 2004). According to Cotty (1997), due
to the epidemiological studies conducted in Africa (Probst, 2007) and Southeast Asia
(Vesonder, 1991), evidence has shown a strong correlation connecting the incidence of liver
cancer in humans and the levels of AFB1 contamination in their daily diet. An
epidemiological study conducted in Swaziland by Dorner (2004), showed that a country with
a food supply dependent on imported grains, showed an association between the incidence of
liver cancer and the estimated levels of AFB1 in the daily dietary intake.
The work done by Ito, Peterson, Wick low and Goto (2001), along with that done by Cotty
(1997), using specific assays developed and validated so as to measure aflatoxin-albumin
18. 17
adducts in serum proved that AFB1 plays a role in the pathoetiologic process of hepatic and
pulmonary carcinomas. The detoxification of xenobiotics within the body involves numerous
activation and conjugation reactions. Of the metabolic products created during phase I
activation reactions, the most biologically important is the highly reactive electrophile
AFB1–8,9-epoxide. Other cytotoxic effects of the epoxide include inhibition of liver protein
synthesis and other protein interactions (IARC, 2002).
Studies conducted by Pitt (2000), Novas and Cabral (2002) and Probst (2007) on children
with dietary-protein deficiency in Africa have shown that Kwashiorkor, which is common
amongst children with this condition, could be caused by the ingestion of aflatoxin. This
effect has been attributed to their tissue‟s inability to metabolize and excrete the toxin due to
a dietary-protein deficiency. The extent of damage and proliferation of AFB1 related acute
hepatocarcinogenicity and hepatotoxicity decreases after the ingestion of protein supplements
in the diet. This has been attributed to the altering and distribution of the AFB1 toxin, thus
reducing its carcinogenicity and toxicity (AACR, 1980). To further cement these studies
Moss (1998) prevented liver tumor development by administering a diet with 10.32% total
protein plus 2 ng/g AFB1. This prevented tumor development in the 300-day study period.
Besides exposure to AFB1 from within the diet, exposure can also occur occupationally. This
is mainly through the inhalation of the dust produced during the processing of various grain
and seed products (Wark, 2004). This can result in the increased probability of pulmonary
fibrosis development. Very high aflatoxin levels were found in particles sampled from the air
in aerosolized grain dust. These data demonstrate that farmers, farm workers and grain
millers may be exposed to potentially hazardous concentrations of AFB1, particularly during
bin cleaning, animal feeding and milling of grain in enclosed buildings (Wark, 2004).
In animals, the effects of aflatoxins can be differentiated depending on the dosage taken and
time over which it is ingested. Acute toxicity is whereby large doses of aflatoxin are ingested
over a very small period and this is common in livestock. Since the principal target organ
affected by aflatoxins is the liver, aflatoxins react negatively with the various cell proteins,
thus leading to the inhibition of lipid and carbohydrate metabolism along with the production
of proteins (Creppy, 2002). Accumulation of these lipids leads to infiltration into the
herpatocytes thus causing liver cell death or necrosis. Disarrangement of the blood clotting
19. 18
mechanism (Jaundice) and a decrease in essential protein production within the liver along
with severely reduced liver function are some of the effects of aflatoxin on the body. This is
coupled with edema of the lower extremities, vomiting and abdominal pain. These effects of
aflatoxin on the body are termed Aflatoxicosis (Creppy, 2002).
Chronic toxicity occurs due to a long term exposure of aflatoxins in moderate to low
concentrations. Some of the symptoms are a decrease in the growth rate of the subject, along
with immunosuppression and a low egg and milk count in livestock. Prolonged exposure to
aflatoxin B1 has shown carcinogenic results along with extensive liver damage and swelling
of the gall bladder. Reactivity of aflatoxin compounds with T-cells along with a decline in
Vitamin K activities and stunted macrophage activity within the body are some of the effects
of immunosuppression. This puts the immune system at risk to attack from secondary
infections such as viruses, bacteria and other fungi (Creppy, 2002).
According to Nelson, Orum, Jaime-Garcia and Nadeem (1998), exposure to aflatoxins during
pregnancy can result in a host of teratogenic effects to the baby, such as wrinkled skin,
enlarged eye socket and microphthalmic eyes. The heart of treated group showed reduction in
size with wide ventricular lumen and shallow inter ventricular groove. The characteristic fetal
histopathological findings were vaccuolation and distortion of hepatic cord pattern.
Vaccuolation of the renal tubular epithelium and occlution of the lumen with casts were also
characterized. Regarding, the skeletal anomalies there were incomplete ossification in some
of the skull bones, the laminae of the vertebral arches throughout the vertebral column
remained cartilaginous. The sternum was incompletely ossified. The 2nd phalanx, carpus,
extremities of metacarpi had no cartilaginous drafts. The central and distal tarsal rows as well
as extremities of metatarsi also remained cartilaginous (Nelson et al., 1998)
An important case of aflatoxin contamination occurred in 150 villages in Northwest India in
the fall of 1974. Contaminated corn was found to be the major cause of the outbreak. 397
people suffered from severe aflatoxicosis, and 108 individuals died. A second outbreak was
reported in Kenya in 1982, where aflatoxin intake was estimated at 38 ng/g body weight. In
developed countries, aflatoxin contamination rarely occurs at levels that cause notable
aflatoxicosis in humans. Studies on human toxicity from ingestion of aflatoxins, therefore,
have focused only on their carcinogenic effect (USFDA, 2013; Probst, 2007).
20. 19
2.3.2 Economic effects
Figure1: Economic effects of Groundnut trade with the EU
According to World Trade Organization (WTO) rules, countries can choose their own
Sanitary and Phyto-Sanitary Standards (SPS) to protect human, animal and plant health as
long as they are non-discriminatory and justifiable by science. This discretion has resulted in
regulations that can serve as a significant barrier to trade, as revealed by numerous disputes
within the WTO (Selim, Popendorf, Ibrahim, El-Sharkawy and El- Kashory, 1996). Aflatoxin
regulations have attracted notice for their potential role in restricting trade. For example, total
peanut meal imports by European Union (EU) countries fell from more than one million tons
in the mid-1970s to just 200,000–400,000 tons annually after 1982, the year mycotoxin
regulations were first tightened in the EU. In 2002, the EU further tightened standards,
leading to concern about the impact on exports from Africa. The loss arising from rejection is
not limited to the value of the product. It also includes transportation and other export costs,
which are incurred by the exporter. Costs may also be borne by importing agents, shipping
companies, and brokers. Even when exporters are able to meet new standards, compliance
often involves significant capital expenditures for product redesign, building administrative
systems and maintaining new quality control, testing, and certification procedures (Selim et
al., 1996).
21. 20
Table 1: EU regulatory aflatoxin concentrations for tree nuts, peanuts, cereals and raw milk.
Foodstuff Aflatoxin Sum of B1, B2, G1 M1
Concentration and G2
Tree nuts (Ready to eat) 8
(For further processing) 12
4
20
2
15
0.05
Peanuts (Ready to eat) 2
(For further processing) 8
Cereals (Ready to eat) 2 4
(For further processing) 5 10
Raw milk --
Otsuki (2001) noted that, the least developed countries, such as those in Africa, are still
largely dependent upon on raw food exports, such as groundnuts and other commodities
under this new standard. As Finger and Otsuki (2001) noted, the cost of compliance with
WTO obligations related to the SPS Agreement in the least developed countries can exceed
total government development budgets for all expenditures.
2.4 Methods of detecting aflatoxins
Since the discovery of aflatoxins over 50 years ago, several methods have been developed for
their efficient analysis and detection in the various foodstuffs they are secreted in (El-Nakib,
Path and Chu, 1981). These technologies are dependent on a number of characteristics in the
nature of aflatoxins, such as their electrochemical and optical properties. On this topic, I will
focus on the main detection methods which are Electrochemical techniques (ELISA),
Chromatography, fluorescence, spectrometry and UV absorption.
2.4.1 Electrochemical techniques
This method is probably the most common method of measuring aflatoxin levels in peanuts
and other grains globally. Here, aflatoxins are measured using electrical current and a pair of
some electrical immunosensors. These immunosensors consist of a pair of electrodes
(measuring and reference). The measuring electrode is coated with specific antibodies which
22. 21
will retain interest aflatoxins in the sample, whereas the other electrode is commonly made of
a combination of Ag / AgCl (El-Nakib et al., 1981).
During aflatoxin determination, the sample to be measured is taken and processed to the
specified mass. It is then mixed with a known portion of conjugated aflatoxins and special
enzyme, before placement into a microfilter plate hole. A measuring electrode is then placed
inside this hole coated with antibodies, specific to the target aflatoxins that are to be
measured. The free, “target aflatoxins” then compete for spaces on the available antibody
spaces on the measuring electrode. After a certain sterilization period, the electrode is then
removed from the sample and washed in buffer solution, that removes all traces of the sample
(Pestka, Li, Harder and Chu, 1981)
This thus leaves the electrode coating intact with captured free aflatoxins, which are not part
of the conjugate. After cleaning procedure, the electrode is introduced in a substrate solution
that reacts with enzymes in aflatoxins conjugate, changing the electrical conductivity of the
substrate depending on the amount of labeled aflatoxins antibodies attached to the electrode.
Thus, the greater the effect seen on aflatoxins marked, the lower the concentration of free
aflatoxins in the sample and vice-versa (Petska, 1981)
This procedure is however a typical setup to the various immunoassay or electrochemical
detection methods in use at the moment, various methods can be set-up. Tan (2009),
developed electrodes that were coated with conjugate aflatoxins in contrast to the typical
method of coating with specific antibody. He then mixed the antibodies with the sample. This
setup results in some antibodies being captured by the free aflatoxins within the sample,
whilst others being captured by those attached to the electrode. Some methods have even
reported the use of simple electrodes (Tan, 2009), while others have made use of multiple
electrodes (Morgan, Kang and Chan, 2002; Groopmann and Kensler, 1999), where the latter
has shown to have advantages over the first in that it is more user friendly, it is possible to
carry out many experiments in parallel with different samples and it reduces the time required
for new procedures (Groopmann and Kensler, 1999).
2.4.2 Chromatography
Regarded as one of the most popular detection techniques, chromatography is a very
powerful aflatoxin determination tool. Various methods of chromatography can be used, such
23. 22
as Gas chromatography, Liquid chromatography, Thin layer chromatography and High
performance liquid chromatography. However, in aflatoxin detection the most quantitative
results in the research and routine analysis of aflatoxins have been found through the use of
Liquid chromatography (LC), Thin layer chromatography (TLC) and High Performance
Liquid Chromatography (HPLC). They are used along with fluorescence detection stages
(Trater, Hanchay and Scott, 1984).
Liquid chromatography offers optimum dynamic range, good sensivity, versatility in use and
soft ionization conditions. Usually coupled to fluorescence detection stage (FLD), UV
absorption and amperometric detection, LC can be a very powerful detection method (Trater
et al., 1984). LC coupled with fluorescence stage use the aflatoxins fluorescence properties to
quantify them. This increases the accuracy and precision for aflatoxin detection.
Thin layer chromatography (TLC) is another method of chromatography that can be used to
analyze the chemical composition of various agricultural products and plants. TLC has a
number of advantages, such as its high user friendliness, availability of many sensitive and
selective reagents for detection and confirmation without interference of the mobile phase,
ability to repeat detection and quantification and cost effectiveness analysis. This is because
many samples can be analyzed on a single plate with low solvent usage and the time that
TLC employs to analyze the sample is less than that of the LC method (Trater et al., 1987).
Seitz (1975), determined that, the data obtained whilst using the TLC method compared to
HPLC and enzyme-linked immunosorbent assay (ELISA) was found to agree among method
but TLC was least expensive.
High Performance Liquid Chromatography (HPLC) has proven to be one of the main
aflatoxin detection and quantification methods on the market today. It has been used jointly
with techniques such as UV absorption, fluorescence and mass spectrometry and
amperometric detectors so as to increase precision in aflatoxin detection amongst samples.
According to Pons (1999), based on the analysis of aflatoxins B1, B2, G1 and G2, detection
limits of up to 5 ng/g of all four aflatoxins could be obtained based on HPLC and
amperometric detection methods. This is very impressive. HPLC can be modified by the
addition of a number of other detection techniques that thus increase its efficiency. For
24. 23
example, Seitz (1975) developed a method that uses HPLC along with diode array detector
(DAD) and a second order iterative algorithm called parallel factor analysis (PARAFAC).
Such method is used for quantifying aflatoxins B1, B2, G1, and G2 in pistachio nuts, this
work also use a solid phase extraction stage as a clean-up procedure. Whitaker and Dickens
(1983) also devised a new method that uses HPLC along with fluorescence detection using
pyridinium hydro-bromide as a post-column derivatization agent to determine aflatoxin M1
in milk and cheese. The detection limits obtained were of 1 ng/kg for milk and 5 ng/g for
cheese that are 50-fold lower than the maximum residue level (MRL) for AFM1 in milk and
40-fold than MRL for AFM1 in cheese set by various European countries.
Various techniques use chromatography for aflatoxin analysis in food (principally in milk,
cheese, corn, peanuts and nuts). Usually done using a fluorescence detector, aflatoxin
detection takes advantage of the fluorescence properties of aflatoxins under a determined
wavelength. As a result, researchers have been focused on improving these fluorescence
properties to develop more sensitive methods than the commonly used so far. Currently
techniques such as pre-column derivatization and post- column derivatization are commonly
used to improve aflatoxins fluorescence properties. They also have a clean-up stage to obtain
a more pure sample, permitting a better quantification. Some of the common methods used in
the clean-up stage are immunoaffinity column and solid phase extraction (Trater et al., 1987).
2.4.3 Fluorescence
The detection of aflatoxin has been through the use of their various photo-physical properties
such as their absorption and emission spectra. At 360nm, aflatoxins show characteristic
absorption of UV light. At 425nm, the B toxins show a blue inflorescence, hence the name
“B-toxins”. The G-toxins fluoresce green-blue at 540nm. However, according to Thean,
Lorenz, Wilson, Rodgers and Gueldner (1980), AFG is fairly rare. The fluorescence emission
of the G toxin is more than 10 times greater than that for the B toxin. These characteristics
are the ones used for the detection of aflatoxins and the aflatoxigenic strains they are secreted
from (Garner, 1975).
The black light test is a method which correctly identifies negative AFs samples with
minimum expenditure of time and money. This may be the easiest aflatoxin identification
method basing on the illumination of the sample with a UV lamp. Ensuring that the detection
25. 24
occurs in a dim place for optimum contrast, fluorescence may be bright or dim, depending on
the amount of fluorescing agent present. However, fluorescence does not happen exclusively
when aflatoxins are present. There are other substances in food that fluoresce under long
wave UV radiation. Fungi as various Penicillum spp., Aspergillus repens and other species do
not produce aflatoxins, but may produce fluorescent harmless metabolites (Thean et al.,
1980). Then, it can be said that fluorescence is not a specific indication of the presence of
aflatoxins, although it may indicate that conditions have been favorable for growth of toxic
molds (B-100 Series Ultraviolet Lamps, UVP). Furthermore, fluorescence is not stable. It
disappears in 4 to 6 weeks of continuous exposure to visible or UV radiation although the
toxin remains. Therefore, fresh samples must be taken. Hence, the reliability of the method
depends on the size of the sample taken for analysis and how it is taken. A sample must be
large enough to be representative of the entire lot and must be taken from all parts of the lot
(B-100 Series Ultraviolet Lamps, UVP). The black light test is commonly applied on animal
feed. However, it is only a preliminary confirmatory test and it does not give a quantitative
indication. Thus, confirmatory and quantitative measurements are needed to be applied to
those samples that reacted positively to the black light test. Non-fluorescing samples need not
be subjected to this. A quantitative screening test which commonly follows the black light
test is small chromatographic column (mini-column) (B-100 Series Ultraviolet Lamps, UVP).
After the quantitative test a judgment can be made as to whether or not accept a lot (Thean et
al., 1980).
LIF is a fluorescence detection technique pioneered by Yeung, Novotny and Ishii (1985).
This screening method consists on a mobile phase which contains an eluted sample of
aflatoxins. Such mobile phase passes through a detection window in the LIF detector. Thus,
the whole fluorescence induced by the laser is collected by the detector (Garner, 1995).
However, LIF detection is a technique restricted to a limited number of laboratories because
the high cost of the lasers, and because most of the analyze molecules have to be labeled with
dyes that match the laser wavelength (Garner, 1995).
Various other techniques can be combined with LIF so as to produce a more accurate
detection. HPLC can be combined with LIF along with electrochemical detection techniques.
This happens because the sensitivity levels of those hybrid techniques are much better than
the ones observed with conventional fluorescence. Photomultipliers are a quick and easy way
26. 25
to detect aflatoxin samples in bulk industrial food processes. Since Fluorescence systems
have a wide sensitivity, they are a useful tool to measure AFM1 in milk, which legal limit is
very low (about 50 parts per trillion). These systems are suitable for preliminary screening at
the earlier stages of the industrial process and make it possible to discard contaminated milk
stocks before their inclusion in the production chain (Seitz, 1975). Then, PTMs are compact
and easy-to-handle sensors for the rapid detection of low concentrations of AFM1 in liquid
solutions without the need for pre-concentration of the sample. They can be used as quick
“threshold indications” and as an “early warning system”, so as to rapidly single out
risk/alarm situations (Seitz, 1975)
Besides the above discussed methods, various other methods are being utilized in aflatoxin
detection and quantification. Examples are, ion mobility spectrometry, Fourier transform-near
infrared spectrometry, biosensors, adsorptive tripping voltammetry, optical fiber,
electrochemical transduction and flow injection monitoring, amongst a host of other
modifications that can be done on the conventional detection and quantification methods.
2.5 Methods of countering aflatoxin
Due to the enormous economic significance this topic has, especially to the developing
countries, Aflatoxin control is currently a significant agenda on the FAO (Food Aid
Organization) research list. According to Otsuki (2001), currently, contamination of peanuts
by Aflatoxin is mostly being curbed by contemporary improvements on a variety of
traditional methods such as post-harvest drying, control of storage conditions, standardized
shelling, de-hulling and sorting. Early harvest of groundnuts from the fields and control of
insects along with adherence to regionally adjusted planting dates has also been found to
reduce the aflatoxin load within peanut farming regions in most developed countries.
However, regardless of generally good storage conditions, formation of aflatoxins frequently
occurs prior to harvest, during maturation of the crop and and/or whilst awaiting harvest. This
can result in some very significant losses, in fact, much more than those incurred during
storage.
The Biological Control Method, of the numerous approaches confronted to try and manage
aflatoxin contamination, has shown great promise in truly annihilating our aflatoxin issues.
Various organisms, have been researched on so as to ascertain their ability in controlling
27. 26
aflatoxin contamination, these include bacteria, yeasts and non-toxigenic fungal strains of A.
flavus and A. parasiticus.
According to Palumbo, Baker and Mahoney (2006), fungal growth and aflatoxin production
have shown to be inhibited by a number of bacterial species such as Lactobacilli spp.,
Several bacterial species, such as Bacillus subtilis, Lactobacilli spp., Pseudomonas spp.,
Ralstonia spp. and Burkholderia spp., have shown the ability to inhibit fungal growth and
production of aflatoxins by Aspergillus spp. in laboratory experiments. Palumbo (2006)
reported that a number of Bacillus, Pseudomonas, Ralstonia and Burkholderia strains isolated
from California almond samples could completely inhibit A. flavus growth. Several strains of
B. subtilis and P. solanacearum isolated from the non-rhizophere of maize soil were also able
to inhibit aflatoxin accumulation (Nesci, Bluma and Etcheverry, 2005). Termed strain no. 27,
a soil bacterium has recently been found to produce aflatoxin production inhibitors.
According to Abnet (2007), this strain was classified as a species of the genus
Stenotrophomonas, and was discovered to be intimately related to Stenotrophomonas
rhizophila. Two diketopiperazines were identified after isolation from the bacterial culture
filtrate as main active components. These diketopiperazines actively inhibited the production
of aflatoxin in Aspergillus parasiticus and Aspergillus flavus without affecting the growth of
the fungi, within a liquid media at several hundred µM (Abnet, 2007), Co-culture of strain no.
27 with aflatoxigenic fungi in liquid medium effectively suppressed aflatoxin production of
the fungus without affecting fungal growth. Their results showed that strain no. 27 could be a
practically effective bio-control agent for aflatoxin control.
Only one bacterium, Flavobacterium aurantiacum B-184, was able to irreversibly remove
aflatoxin from solutions (Lillehoj, 1967). In however, most cases, although these strains were
highly effective against aflatoxin production and fungal growth under laboratory conditions,
they do not give good efficacies in fields because it is difficult to bring the bacterial cells to
the Aspergillus infection sites on commodities under field conditions (Dorner, 2004). The
quest to contain our aflatoxin load has led to the study of various research approaches, so as
to reduce and, ultimately, eliminate aflatoxin contamination. Biological control using the
non-toxigenic isolates of the same fungus is probably the most promising, particularly for the
short-term. In field plot experiments, application of various non-aflatoxigenic isolates of A.
flavus and A. parasiticus to soil has effectively reduced aflatoxin concentrations in peanuts.
28. 27
The applied strains occupy the same niche as the naturally-occurring toxigenic strains and
competitively exclude them when crops are susceptible to infection. Various formulations
have been used to apply the non-toxigenic strains to soil, but the most effective methods have
been to combine the desired strain with a carrier/substrate, such as a small grain. This was
done either by minimally growing the desired strain on sterilized grain or by coating the
surface of the grain with conidia of the strain. After application to the field and uptake of
moisture, the fungus completely colonizes the grain, and abundant sporulation provides
inoculum levels sufficient to achieve a competitive advantage for the non-toxigenic strain. In
several years of field studies, particularly with peanuts and cotton, significant reductions in
aflatoxin contamination in the range of 70-90% have been achieved consistently, particularly
with peanut and cotton.
Yeasts have also been tried and tested as biological control agents against aflatoxin
production. It was noted that overall total mould counts of Aspergillus niger and Aspergillus
ochraceus reduced after being dipped in a dip treatment with a yeast suspension of
Saccharomyces cerevisae, post-harvest (Velmourougane, 2011). A similar reduction in
aflatoxin presecnce was observed in peanuts infected with A. parasiticus after dipping in a
suspension of Streptomyces (Zucchi, 2008).
Contemporary research into biocontrol of aflatoxin contamination has shown some
interesting recent new research line has demonstrated promising results to control aflatoxin
contamination (Sakuda, 1996). Streptomyces has proven to be the actinomycete of choice in
the manipulation of yeast as a biocontrol with compounds such as aflastatin A and B,
Blasticidin A and dioctatin A inhibiting the production of aflatoxin without preventing fungal
growth (Sakuda, 1999). Level of interference of these yeast secretions with fungal
proliferation is also critical, it is important that these compounds produced have minimal
interference since further treatments can be done on the aflatoxin causing fungi thus giving
extra protection from infections that may occur later. Since these compounds have not
interfered in the fungal development, the treated fungus may confer an extra protection by
niche competition against further infections (Sakuda, 1999).
29. 28
CHAPTER 3: MATERIALS AND METHODS
3.1 Study site
The study was conducted in three areas, Mt Darwin, Rushinga and Chiweshe, within the
Mashonaland Central province of Zimbabwe. According to DRSS (2011), Mashonaland
Central is one of the biggest peanut farming areas in the country. Mt Darwin, (Latitude
16°48‟ S, Longtitude 31°30‟ E), is one of the areas with the lowest rainfall patterns, with an
average of 760mm and an average temperature of 21°C, following a typically tropical pattern
with most of the rainfall occurring in the dry-wet season (October – April). It has an elevation
of 953m above sea level and red soils were typical in the areas sampled, with high clay
content. Rushinga (Latitude 16°40‟0 S, Longtitude 32°15‟0), with an elevation of 720mm
was the exception with soils that were loamy. The average rainfall patterns in this area were
much higher than those in Mt Darwin with 1740mm annually. The annual temperature is
15.7°C and the climate is regarded warm and temperate. Rainfall is consistent throughout the
year, with July being the driest month with an average of 49mm. Chiweshe (17°5‟32 S and
31°5‟8 E), with an elevation of 1245m above sea level. It has an average annual temperature
of 18°C. The soils in this area are clay-enriched and high in lixisols. It is also highly saturated
with bases. The climate in this area can be reffered to as humid sub-tropical.
3.1.1 Sampling and collection
In each area, farmers were chosen at random from the total registered peanut farmers, with
the DRSS, within the area. These farmers were an average of 10km apart and in each study
area, there were three study sites. From each site, 500g of groundnuts from each farmer were
collected. Therefore, in total, there were 9 samples of 500g each from three study areas, Mt
Darwin, Rushinga and Chiweshe.
The collected groundnuts were rain-fed, raw and cracked, having undergone harvest an
average of 2-3 weeks earlier. They were kept in khaki paper bags, in a well ventilated
cupboard for an average of a week, during which sampling was done on them. From each
sample, some of the peanuts were randomly selected from within the bag for the aflatoxin
analysis, whilst some were selected for a count of the infected nuts.
30. 29
3.2 Analysis of fungal load
The blotter method was used for isolation. Thus, per farmer, all the seeds were disinfected
with sodium hypochlorite (1%) for a period of a minute. All the seeds were then washed three
times with sterilised water. After drying for 5 minutes on a laminar flow, they were then
plated on sterilised filter paper with relatively high moisture content within sterilized Petri
dishes. Each dish was plated with five seeds in circular placement and each plate was
replicated 10 times for each treatment. Therefore each sample site had 50 seeds that were
observed for the presence of Aspergillus. The dishes were then incubated at a temperature of
25°C for 5 days.
After incubation, the prevalence of A. flavus, A. niger and A. parasiticus, along with the
various other fungal species developing in the plate was observed using a stereo-microscope.
Here, each nut was placed on blotter paper under the stereo-microscope and the mycelia
growing on the nut were observed intensively for differences in morphology. Once
determined, the various different colonies were collected and plated before observation on a
compound microscope. Observation under compound light microscope was done to analyze
the fungi for morphological characteristics that determine its species. The hyphae of each
colony were observed using a compound light microscope. Identification of the fungi was
based on growth habit characters, the morphological characters of mycelia and conidia
observed under a compound microscope. Literature by Maren and Johan (1988) and Singh,
Jenz, Thron and Mathur (1991) were used for the identification of the various species.
31. 30
Image 1 Image 2
Figure 2: an example of Peanut seeds infected with Aspergillus flavus, whilst image 2
shows healthy seeds.
Therefore, the number of seeds infected with the Aspergillus species was then counted and
recorded before the percent incidence was calculated with the following formular;
Percentage incidence = Number of infected seeds x100
Total seeds sampled
3.3 Aflatoxin analysis
The samples were analysed as batches, consistent with their origin and then ground into
powder form using a pestle and motar. Approximately 5g of the ground sample was then
weighed and put into a jar and sealed.
100ml of 70% methanol was then mixed with the 5g sample and shaken for 5 minutes using
an orbital platform shaker. After shaking, the mixture was centrifuged for 10 minutes at 4000
rpm. The supernatant was filtered off and 1ml of supernatant was mixed with 1ml of distilled
or deionised water. 50µL of the diluted supernatant was then used per well in each test.
A Max-Signal Total Aflatoxin ELISA Testing Kit was used during this testing procedure.
32. 31
50µL of pure aflatoxin B1 standard was added into different wells in duplicate. The sample
was then added in duplicate into different sampling wells at a volume of 50µL per sample.
100µL of antibody 1 were then mixed in these wells by gentle rocking the plate for 1minute.
The plate was then incubated for 30 minutes at a temperature of 24°C in an incubator. After
incubation, the plate was then washed with 250 µL, 1l wash solution three times. After the
final wash, the plate was then inverted and tapped dry on paper towels. The next step
involved the addition of 150µL of 1X Antibody 2 solution, then incubated for 30 minutes at
room temperature (20-25°C), whilst avoiding direct sunlight.
After incubation, 100ml of TMB substrate was then added and the reaction was timed for
exactly a minute whilst the microtiter plate was covered. Finally, after incubating for 15
minutes at room temperature, we added 100µL of Stop buffer was then added to stop the
enzymatic reaction. Using a microwell reader, the plate was subsequently analysed. The
optical density reading for each microwell was then recorded, using an ELISA reader at
405nm. The aflatoxin content was then determined and stated in the results.
3.3 Data analysis
The data was analysed using One-way Anova, this was used to compare the total aflatoxin
content from the three study areas. Here, the area means were analysed to find a statistical
difference. The variation between means was also analysed using a Multiple comparison
post-hoc test to determine the statistical differences between the study sites. Data analysis
was done using the IBM SPSS statistical package.
33. 32
CHAPTER 4: RESULTS
The number of nuts infected with A. flavus and A. niger in each plate incubated are shown in
tables 2 to 4.
Table 2: Presence of A. flavus, A. niger and A. parasiticus in samples from Mt Darwin.
Plate A. flavus A. niger A. parasiticus
1 2 1 0
2 1 0 0
3 3 0 0
4 1 3 0
5 1 0 0
6 1 1 0
7 0 2 0
8 0 3 0
9 4 0 0
10 0 0 0
The results from Mt Darwin showed the presence of Aspergillus spp. in 13 out of 50 seeds
plated. A. niger showed a much lower prevalence in 10 seeds. A. parasiticus was not found in
any of the nuts observed.
34. 33
Table 3: Presence of A. flavus, A. niger and A. parasiticus in samples from Rushinga.
Nuts infected
Plate A. flavus A. niger A. parasiticus
1 0 0 0
2 0 1 0
3 0 0 0
4 0 0 0
5 0 0 0
6 1 0 0
7 0 1 0
8 0 3 0
9 3 0 0
10 0 0 0
35. 34
Table 3: Presence of A. flavus, A. niger and A. parasiticus in samples from Rushinga.
Nuts infected
Plate A. flavus A. niger A. parasiticus
1 0 0 0
2 0 1 0
3 0 0 0
4 0 0 0
5 0 0 0
6 1 0 0
7 0 1 0
8 0 3 0
9 3 0 0
10 0 0 0
From the results of the total fungal count, A. flavus had the highest prevalence in Mt Darwin,
this was also the case for A. niger and A. parasiticus. The Fusarium spp. had the highest
prevalence in all plated samples in all the sample sites, with F. oxysporum showing a total of
45 nuts and F. moniliforme having 25 nuts in all the sampled sites. S. sclerotiorum also
showed a significant presence in all the sampled sites.
From the results got, the percentage incidence of Aspergillus niger and Aspergillus flavus
were determined using the equation below and put in graph;
Percentage incidence= Number of infected seeds x100
Total seeds sampled
36. 35
Table 5: Incidence of total fungi in the Total Fungal Count.
Fungal species Mt Darwin Rushinga Chiweshe
A. flavus 15 4 5
A. parasiticus 0 0 0
A. niger 11 2 2
F. oxysporum 23 18 7
F. moniliforme 15 5 8
S. sclerotiorum 10 2 10
From the results of the total fungal count, A. flavus had the highest prevalence in Mt Darwin,
this was also the case for A. niger and A. parasiticus. The Fusarium spp. had the highest
prevalence in all plated samples in all the sample sites, with F. oxysporum showing a total of
45 nuts and F. moniliforme having 25 nuts in all the sampled sites. S. slerotiorum also
showed a significant presence in all the sampled sites.
4.2 : Aflatoxin analysis
The results of the aflatoxin analysis on each batch of nuts were then documented in Tables 5
to 8.
Table 6: Concentration of aflatoxin production by toxigenic A. flavus and A. niger
isolated from peanuts in Mt Darwin.
Aflatoxin( µ/kg)
AFB1 AFB2 AFG1 AFG2 Total
Sample 1 18.00 7.53 3.90 6.13 35.56
Sample 2 21.90 6.72 4.50 6.00 39.12
Sample 3 13.34 3.33 2.56 8.76 27.99
37. 36
Table 7: Concentration of aflatoxin production by toxigenic A. flavus and A. niger
isolated from peanuts in Rushinga.
Aflatoxin( µ/kg)
AFB1 AFB2 AFG1 AFG2 Total
Sample 1 2 0 0 3.423 5.435
Sample 2 1.453 0.931 1.221 0 3.587
Sample 3 3.121 0 0.021 2.224 5.455
A Post- Hoc multiple comparison test done within the 3 groups tested showed that sample 1
from Rushinga and sample 3 from Chiweshe did not differ statistically, both had p-values in
the test were 0.733 at 95% significance level. This showed there was a statistical relationship
between the peanut samples from these areas.
Table 8: Concentration of aflatoxin production by toxigenic A. flavus and A. niger
isolated from peanuts in Chiweshe.
Aflatoxin( µ/kg)
AFB1 AFB2 AFG1 AFG2 Total
Sample 1 2 0 0 3.423 5.435
Sample 2 1.453 0.931 1.221 0 3.587
Sample 3 3.121 0 0.021 2.224 5.455
The results from the aflatoxin analysis showed that Mt Darwin had the highest rates of
aflatoxin contamination in its peanuts with Aflatoxin B1 showing a mean precedence of
17.75ng/g in the sampled nuts. This was followed by Rushinga which had a mean aflatoxin
presence of 2.19ng/g and lastly Chiweshe with a mean AFB1 precedence of 1.92ng/g. Mt
Darwin also had the highest contamination of AFB1, AFG1 and AFG2, thus giving a mean
total load of 34.22ng/g. Chiweshe and Rushinga had much lower mean loads of 6,96ng/g and
4.83ng/g respectively in the samples done.
38. 37
The results from the aflatoxin analysis showed that Mt Darwin had the highest rates of
aflatoxin contamination in its peanuts, with Aflatoxin B1 showing a mean precedence of
17.75 ng/g in the sampled nuts. This was followed by Rushinga, which had a mean Aflatoxin
B1 precedence of 2.19 ng/g and lastly Chiweshe with a mean AFB1 precedence of 1.92 ng/g.
Mt Darwin also had the highest contamination of AFB2, AFG1 and AFG2, thus giving a mean
total aflatoxin load of 34.22 ng/g. Chiweshe and Rushinga had much lower mean loads of
6.96ng/g and 4.83ng/g respectively in the samples done. One- way Anova on the results got
showed that from all the study sites analysed, the results showed no statistical relationship.
The One–way anova test between groups gave a p-value of 0, at 95% significance level. This
showed no interaction in the mean values between groups, statistically.
39. 38
CHAPTER 5: DISCUSSION
Compared with the aflatoxin levels detected by Nyathi, Robens and Richard (1987), whereby
the M1 aflatoxin concentration in the breast milk from this area was above 20µl/L, the
aflatoxin concentrations determined in this study from Rushinga and Chiweshe have
decreased relatively to a point where they could not cause significant Aflatoxin M1
development within the body. Also comparing to the study done by Siwela, Reed and Kasali
(1996), on the peanuts and peanut butter from this area, in which the aflatoxin level was
greater than the international action limit of 20µl/L, the aflatoxin concentrations determined
were much lower. However, the aflatoxin concentrations from Mt Darwin were higher than
the international limit in all three samples collected.
Mt Darwin showed the highest prevalence of Aspergillus flavus and Aspergillus niger of all
the three study sites analysed. This could have been attributed to the low rainfall and drought
conditions that were experienced in the area in the 2012 - 2013 agricultural season. The stark
reduction in rain most probably reduced the kernel moisture within the peanuts, pre- harvest.
Thus creating a conducive environment for the development of fungal colonies within the
nuts. Besides just the development of the Aspergillus species, Mt Darwin had the highest
prevalence of agricultural parasitic fungi such as Fusarium spp. Here, F. moniliforme was
present in 20 out of the 50 nuts plated, 40% prevalence and F. oxysporum showing a 30%
presence in the nuts sampled from this area. Fusarium is a species that infects crops
drastically in conditions of low rainfall and drought (Probst, 2011). It produces various
mycotoxins into the medium it is growing in such as Fumunosins, tricothecenes and fusarins
(Probst, 2011). These toxins are quite potent and can cause a myriad of maladies on the
immune system, with the main one being Mycotoxicosis (Probst, 2011). Sclerotinia
sclerotiorum also showed an unusually high prevalence in these groundnuts in 22% of the
nuts sampled. Since this fungus attacks mostly beans, its high prevalence was attributed to
crop rotation. Some of the farmers had farmed beans in the same plots they farmed the
peanuts sampled, the previous season.
The aflatoxin concentration of the peanuts from Mt Darwin gave a total of 35.56 ng/g. This
40. 39
level of aflatoxin was exceedingly high, considering that the EU international action limit for
total aflatoxins in peanuts is marked at 20 ng/g. The AFB1 concentration for Mt Darwin was
also exceedingly high with a value of 18 ng/g. This means the peanuts coming from the
sampled farmers in the area were a health hazard and according to EU regulations, are unfit
for trade. The second most toxic aflatoxin G1 had a concentration of 3.90 ng/g, this means the
total potency of the peanuts is much lower, had it been that both AFB1 and AFG1 had high
levels, the potency would be much higher and probably cause noticeable harm to the body.
The samples taken from Rushinga showed an extremely low prevalence of A. flavus and A.
niger. This could be attributed to good rainfall in the area, thus resulting in increased kernel
moisture and a much stronger kernel not easily susceptible to damage. This makes fungal
infection to the nut more difficult (Novas and Cabral, 2002). These low Aspergillus spp.
levels correlated with the extremely low aflatoxin concentrations, which recorded a total of
5ng/g, with AFB1 showing 2 ng/g and AFG2 showing 3 ng/g. This makes the peanuts from
Rushinga very healthy, in terms of potency to Aflatoxins. However, the same cannot be said
for the safety of these peanuts in terms of mycotoxins in general, since a Fusarium presence
of 46% was noted. This high presence of Fusarium could result in an equally high
concentration of mycotoxins. The low aflatoxin level found in Rushinga and Chiweshe could
be attributed to good post-harvest procedures such as early harvest and storage in optimal
conditions taught to the farmers in surveillance programmes co-ordinated by the Ministry of
Agriculture.
The same can be said for Chiweshe, which had a very low total aflatoxin level of 6.532 ng/g.
This was to be expected with the low fungal load in its peanuts of 14% Aspergillus, 24%
Fusarium and 10% Sclerotinia. This level of Sclerotinia was the same as that found in Mt
Darwin, giving us reason to believe that crop rotation was the factor in this high prevalence
also. Fusarium was also relatively high due to previous maize farming in the plots used for
the peanuts. Here, the cobs are the ones infected, but the fungus spreads to the soil after
harvest when the entire plant is ploughed in for decomposition. Aspergillus parasiticus
showed absolutely no presence in all of the samples analysed. This could have been due to
competitive disclusion by A. flavus and A. niger, along with the other fungi in a habitat well
suited to them.
41. 40
CHAPTER 6: Conclusions and recommendations
6.1 Conclusions
The Aflatoxin levels from Mt Darwin were too high, according to EU regulations. Those
from Rushinga and Chiweshe were considerably low. However, there was no statistical
relationship between the aflatoxin concentrations in the sampled study areas. A high
prevalence was also found in the Fusarium spp. and Sclerotinia spp., meaning there was a
high probability that there were significant mycotoxin levels in the peanuts from these areas.
6.2 Recommendations
The use of fungicides by the farmers from Mt Darwin is advised. Biological controls could be
used also, to help reduce the fungal load in these peanuts without necessarily bringing harm
to the environment. Programmes on proper pre-harvest and post-harvest control such as those
conducted in Rushinga and Chiweshe should be done in Mt Darwin also. Proper crop rotation
in Mt Darwin and Rushinga should be taught to farmers, this could reduce the impact of fungi
on the groundnut crop. Local groundnut buyers such as those from the Reapers company
should test for aflatoxin when buying from the farmers, this in itself will enforce stringent
farming methods, resulting in healthier peanuts that can be exported internationally.
42. 41
CHAPTER 7: References
Anon. (1989). Mycotoxins Economic and Health Risks. Council of Agricultural Science and
Technology, Report No. 116. Pp91.
American Association for Cancer Research, An Evaluation of Chemicals and Industrial
processes associated with cancer in Humans: IARC monographs. (1980). Cancer Res. 40: 1-
12.
Abnet, C. C. (2007). Carcinogenic food contaminants. Cancer Invest. 25: 189-196.
Bruns, H. (2003). Controlling aflatoxin and Fumunosin. Journal of Toxicology: Toxin
Review. 22: 153-178.
Creppy, E. E. (2002). Update of Survey, regulation and toxic effects of Mycotoxin in Europe.
ToxicolLett. 127: 19-29.
Cotty, P. J. (1997). Aflatoxin producing potential of communities of Aspergillus in the US.
Mycol Res. 101: 698-704.
Dorner, J. W. (2008). Food additives and Contaminants. Toxicol Res. 25: 203.
Dorner, J. W. (2004). Biological control of Aflatoxin contamination in crops. J. Toxicol
Toxin Rev. 23: 425-450.
Dorner, J. W and Cole, R. J. (2002). Effect of application of Non-toxigenic strains of
Aspergillus flavus and Aspergillus parasiticus on subsequent aflatoxin contamination in
peanut storage. J Stored Prod Res. 38: 329-339.
Eaton, D. L and Groopman, J. D. (1994). The Toxicology of Aflatoxins. Academic Press. New
York. Pp 338-426.
El-Nakib, O., Path, J and Chu, F. S. (1981). Determination of Aflatoxin B1 in corn, wheat
and peanut butter by ELISA. Journal of the Association of Official Analytical Chemists. 64:
1077-2000.
43. 42
Finley, J. W., Robinson, S. F and Armstrong, D. J. (1992). Food Safety assessment by the
American Chemical Society. Academic Press. Washington DC. Pp 261-275.
Goldbatt, L. A. (1969). Aflatoxin. Academic Press, New York. Pp 1-40.
Groopmann, J. D and Thomas, W. (1999). Critical Reviews in Toxicology. 19: 113-124.
Garner, R. C. (1975). Aflatoxin separation by HPLC. Journal of Chromatography. 103: 173-
186.
Heathcotte, J. G and Hibbert, J. R. (1978). Aflatoxins: The Chemical and Biological Aspect.
Elsevier. New York. Pp 173-187.
Ito, Y., Petersen, S. W., Wicklow, D. T and Goto.T. (2001). Aspergillus pseudotamarii: A
new aflatoxin producing species in Aspergillus section Flavi. Mycological Research.105:
233-239.
International Agency for Research on Cancer.(2002). Traditional herbal medicines, some
mycotoxins, naphthalene and styrene. IARC Monograph on the Evaluation of Carcinogenic
risk of Chemicals to humans. 82.
Liener, E. B., Ciegler, A and Hall, H. H. J. (1967). Bacteriology. 93: 464-471.
Moss, M. O. (1998). Recent studies of Mycotoxins. Sympseroc Applied Microbiol. 27: 625-
754.
Morgan, M. A., Kang, A. S and Chan, H. W. (2002). Aflatoxin determination in peanut butter
by ELISA. J. Sci Food Agric. 37: 908-914.
Nyathi, F and Richard, J. L. (1987). Aflatoxins in Animal and Human health. Rev Environ
Contam Toxicol. No. 127: 69-94.
44. 43
Nesci, A. V., Burma, R. V and Etcheverry, M. G. (2005). European Journal of Plant
Pathology.115: 159.
Nelson, M. R., Orum, T. V., Jaime- Garcia, R and Nadeem, A. (1998). Applications of
geographic information systems in plant epidermiology. Plant Dis. 83: 308-319.
Novas, M. V and Cabral, D. (2002). Association of mycotoxin and sclerotia production in
Aspergillus flavus , Plant Dis. 86: 215-216.
Payne, G. A. (1998). Process of contamination by Aflatoxin producing fungi and their
impacts on crops. Mycotoxins in Agriculture and food safety. New York. 38-45.
Payne, G. A and Brown, M. P. (1998). Genetics and physiology of aflatoxin biosynthesis.
Annual Rev Phytopathology. 36: 329-362.
Probst, C., Schulthess, F and Cotty, P. J. (2010). Impact of A. flavus community structure on
the development of lethal levels of aflatoxins in Kenyan maize. Journal of Applied
Microbiology. 108: 600-610.
Probst, C., Bandhpadhyay, R., Price, L. E and Coty, P. J. (2011). Identification of atoxigenic
Aspergillus flavus isolates to reduce contamination in Kenyan maize. Plant Diseases. 95: 21-
218.
Pitt, G. H. (2000). Ecology and population Biology of aflatoxigenic fungi in soil. J. Toxicol
Toxin Rev. 22: 351-379.
Pestka, J. J., Li, Y., Harder, W. O. and Chu, F. S. (1981). Comparison of radioimmunoassay
and enzyme-linked immunosorbent assay for determining aflatoxin M, in milk. Journal of the
Association of Official Analytical Chemists. 64: 294-301
Pons, W. A. (1999). High pressure liquid chromatographic determination of aflatoxins in
corn. Journal of the Association of Official Analytical Chemists. 62:586-594.
Palumbo J. D., Baker J. L. and Mahoney, N. E. (2006). Microbiology Ecology. 52: 45.
45. 44
Richard, J. L. and G. A. Payne. (2003). Mycotoxins in plant, animal, and human systems.
Council for Agricultural Science and Technology. Task Force Report. 139: 23.
Sakuda, S. (1996). Aflastatin A, a novel inhibitor of aflatoxin production of Aspergillus
parasiticus, from Streptomyces. Journal of the American Chemical Society. 33: 7855-7856.
Scheidegger, K. A. and G. A. Payne. (2003). Unlocking the secrets behind secondary
metabolism: A review of Aspergillus flavus from pathogenicity to functional genomics.
Journal of Toxicology-Toxin Reviews. 22: 423-459.
Selim, M.I., Popendorf, W.J., Ibrahim, M.S., El-Sharkawy, S. and El- Kashory, S. (1996).
Aflatoxin B1 in common Egyptian foods. J AOAC Int. 79(5):1124-1129.
Seitz, L. M. (1975). Comparison of methods for aflotoxin analysis by high pressure liquid
chromatography. Journal of Chromatography. 104:81-89.
Siwela, J., Reed, J. D. and Kasali, O. B. (1996). Hazards to live stock of consuming Aflatoxin
contaminated meal in Africa ICRISAT proceedings of international workshop on Aflatoxin
contamination in ground nuts. International Journal of Environmental Research and Public
Health. 10: 3363-3383.
Taubenhaus, J. J. (1920). A study of the black and the yellow molds of ear corn. Texas
Agricultural Experimental Station Bulletin. 20: 270.
Tan, A. (2009). A membrane-based enzyme immunoassay test for AFB1. Int J Food
Microbiol. 5: 73-80.
Trater, E. J., Hanchay, J. P. and Scott, P. M. (1984). Improved liquid chromatographic
method for determination of aflatoxins in peanut butter and other commodities. Journal of the
Association of Official Analytical Chemists. 67:597-600.
Thean, J. E., Lorenz, D. R., Wilson, D. M., Rodgers, K. and Gueldner, R.G. (1980).
Extraction, cleanup, and quantitative determination of aflatoxins in corn. Journal of the
Association of Official Analytical Chemists. 63:631-633.
Velmouragne, E. (2011). Management of Aspergillus ochraceus and Ochratoxin-A
46. 45
contamination in coffee during on-farm processing through commercial yeast inoculation.
Biological Control. Elsevier. Orlando. Pg 215-221.
Wyllie, T. D. and Morchause, L. G. (1978). Mycotoxin Fungi, Mycotoxins, Mycotoxicoses-
An Encyclopedic Handbook. Clinial microbiology review. 12: 1147-1179.
Whitaker, T. B. and Dickens, J. W. (1983). Evaluation of a testing program for aflatoxin in
corn. Journal of the Association of Official Analytical Chemists. 66:1055-1058.
Zucchi, T. D., Moraes, L. A. and Melo, I. S. (2008). Streptomyces sp. ASBV-1 reduces
aflatoxin accumulation by Aspergillus parasiticus in peanut grains. Journal of Applied
Microbiology. 105: 2153-2160.
47. 46
CHAPTER 8: Appendices
i) One- way Anova Comparison of total aflatoxin content in groundnuts from all three study
areas between groups at a 95% confidence interval
Sum of Squares df Mean Square F Sig.
Between Groups 1611.794 2 805.897 70.524 .000
Within Groups 68.564 6 11.427
Total 1680.358 8
ii) Output from Multiple comparisons post-hoc test between all study sites at 95% confidence interval
(I) site (J) site Mean Difference
(I-J)
Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound
1.00
2.00 29.39333*
2.76011 .000 20.9246 37.8621
3.00 27.26333*
2.76011 .000 18.7946 35.7321
2.00
1.00 -29.39333*
2.76011 .000 -37.8621 -20.9246
3.00 -2.13000 2.76011 .733 -10.5988 6.3388
3.00
1.00 -27.26333*
2.76011 .000 -35.7321 -18.7946
2.00 2.13000 2.76011 .733 -6.3388 10.5988