Coating of maize seeds with acephate for precision agriculture: Safety assessment in earthworms, bees, and soil microorganisms.

Acephate is commonly used as a seed treatment (ST) in precision agriculture, but its impact on pollinators, earthworms, and soil microorganisms remains unclear. This study aimed to compare the fate of acephate seed dressing (SD) and seed coating (SC) treatments and assess potential risks to bees, earthworms, and soil microorganisms. Additionally, a follow-up study on maize seeds treated with acephate in a greenhouse was conducted to evaluate the maize growth process and the dissipation dynamics of the insecticide. The results indicated that acephate SC led to greater uptake and translocation in maize plants, resulting in lower residue levels in the soil. However, high concentrations of acephate metabolites in the soil had a negative impact on the body weight of earthworms, whereas acephate itself did not. The potential risk to bees from exposure to acephate ST was determined to be low, but dose-dependent effects were observed. Furthermore, acephate ST had no significant effect on soil bacterial community diversity and abundance compared to a control. This study provides valuable insights into the uptake and translocation of acephate SD and SC, and indicates that SC is safer than SD in terms of adverse effects on bees and nontarget soil organisms.

Green analytical assay for the viability assessment of single maize seeds using double-threshold strategy for catalase activity and malondialdehyde content.

The development of nondestructive technology for the detection of seed viability is challenging. In this study, to establish a green and effective method for the viability assessment of single maize seeds, a two-stage seed viability detection method was proposed. The catalase (CAT) activity and malondialdehyde (MDA) content were selected as the most key biochemical components affecting maize seed viability, and regression prediction models were developed based on their hyperspectral information and a data fusion strategy. Qualitative discrimination models for seed viability evaluation were constructed based on the predicted response values of the selected key biochemical components. The results showed that the double components thresholds strategy achieved the highest discrimination accuracy (92.9%), providing a crucial approach for the rapid and environmentally friendly detection of seed viability.

A cost-saving, safe, and highly efficient natural mediator for laccase application on aflatoxin detoxification.

Laccase mediators possess advantage of oxidizing substrates with high redox potentials, such as aflatoxin B1 (AFB1). High costs of chemically synthesized mediators limit laccase industrial application. In this study, thin stillage extract (TSE), a byproduct of corn-based ethanol fermentation was investigated as the potential natural mediator of laccases. Ferulic acid, p-coumaric acid, and vanillic acid were identified as the predominant phenolic compounds of TSE. With the assistance of 0.05 mM TSE, AFB1 degradation activity of novel laccase Glac1 increased by 17 times. The promoting efficiency of TSE was similar to ferulic acid, but superior to vanillic acid and p-coumaric acid, with 1.2- and 1.3-fold increases, respectively. After Glac1-TSE treatment, two oxidation products were identified. Ames test showed AFB1 degradation products lost mutagenicity. Meanwhile, TSE also showed 1.3-3.0 times promoting effect on laccase degradation activity in cereal flours. Collectively, a safe and highly efficient natural mediator was obtained for aflatoxin detoxification.

Bioplastic derived from corn stover: Life cycle assessment and artificial intelligence-based analysis of uncertainty and variability.

Exploring feasible and renewable alternatives to reduce dependency on traditional fossil-based plastics is critical for sustainable development. These alternatives can be produced from biomass, which may have large uncertainties and variabilities in the feedstock composition and system parameters. This study develops a modeling framework that integrates cradle-to-grave life cycle assessment (LCA) with a rigorous process model and artificial intelligence (AI) models to conduct uncertainty and variability analyses, which are highly time-consuming to conduct using only the process model. This modeling framework examines polylactic acid (PLA) produced from corn stover in the U.S. An analysis of uncertainty and variability was conducted by performing a Monte Carlo simulation to show the detailed result distributions. Our Monte Carlo simulation results show that the mean life-cycle Global Warming Potential (GWP) of 1 kg PLA is 4.3 kgCO2eq (P5-P95 4.1-4.4) for composting PLA with natural gas combusted for the biorefinery, 3.7 kgCO2eq (P5-P95 3.4-3.9) for incinerating PLA for electricity with natural gas combusted for the biorefinery, and 1.9 kgCO2eq (P5-P95 1.6-2.1) for incinerating PLA for electricity with wood pellets combusted for the biorefinery. Tradeoffs for different environmental impact categories were identified. Based on feedstock composition variations, two AI models were trained: random forest and artificial neural networks. Both AI models demonstrated high prediction accuracy; however, the random forest performed slightly better.

Alternative crop residue management practices to mitigate the environmental and economic impacts of open burning of agricultural residues.

Deliberate open burning of crop residues emits greenhouse gases and toxic pollutants into the atmosphere. This study investigates the environmental impacts (global warming potential, GWP) and economic impacts (net cash flow) of nine agricultural residue management schemes, including open burning, fertilizer production, and biochar production for corn residue, rice straw, and sugarcane leaves. The environmental assessment shows that, except the open burning schemes, fossil fuel consumption is the main contributor of the GWP impact. The fertilizer and biochar schemes reduce the GWP impact including black carbon by 1.88-1.96 and 2.46-3.22 times compared to open burning. The biochar schemes have the lowest GWP (- 1833.19 to - 1473.21 kg CO2-eq/ton). The economic assessment outcomes reveal that the biochar schemes have the highest net cash flow (222.72-889.31 US$2022/ton or 1258.15-13409.16 US$2022/ha). The expenditures of open burning are practically zero, while the biochar schemes are the most costly to operate. The most preferable agricultural residue management type is the biochar production, given the lowest GWP impact and the highest net cash flow. To discourage open burning, the government should tailor the government assistance programs to the needs of the farmers and make the financial assistance more accessible.

Array-optimized artificial olfactory sensor enabling cost-effective and non-destructive detection of mycotoxin-contaminated maize.

The MobileNetV3-based improved sine-cosine algorithm (ISCA-MobileNetV3) was combined with an artificial olfactory sensor (AOS) to address the redundancy in olfactory arrays, thereby achieving low-cost and high-precision detection of mycotoxin-contaminated maize. Specifically, volatile organic compounds of maize interacted with unoptimized AOS containing eight porphyrins and eight dye-attached nanocomposites to obtain the scent fingerprints for constructing the initial data set. The optimal decision model was MobileNetV3, with more than 98.5% classification accuracy, and its output training loss would be input into the optimizer ISCA. Remarkably, the number of olfactory arrays was reduced from 16 to 6 by ISCA-MobileNetV3 with about a 1% decrease in classification accuracy. Additionally, the developed system showed that each online evaluation was less than one second on average, demonstrating outstanding real-time performance for ensuring food safety. Therefore, AOS combined with ISCA-MobileNetV3 will encourage the development of an affordable and on-site platform for maize quality detection.

A global assessment of glyphosate and AMPA inputs into rivers: Over half of the pollutants are from corn and soybean production.

Glyphosate is widely used in agriculture for weed control; however, it may pollute water systems with its by-product, aminomethylphosphonic acid (AMPA). Therefore, a better understanding of the flows of glyphosate and AMPA from soils into rivers is required. We developed the spatially explicit MARINA-Pesticides model to estimate the annual inputs of glyphosate and AMPA into rivers, considering 10 crops in 10,226 sub-basins globally for 2020. Our model results show that, globally, 880 tonnes of glyphosate and 4,090 tonnes of AMPA entered rivers. This implies that 82 % of the river inputs were from AMPA, with glyphosate accounting for the remainder. Over half of AMPA and glyphosate in rivers globally originated from corn and soybean production; however, there were differences among sub-basins. Asian sub-basins accounted for over half of glyphosate in rivers globally, with the contribution from corn production being dominant. South American sub-basins accounted for approximately two-thirds of AMPA in rivers globally, originating largely from soybean production. Our findings constitute a reference for implementing and supporting effective control strategies to achieve Sustainable Development Goals 2 and 6 (food production and clean water, respectively) simultaneously in the future.

Assessment of textile effluent treatment by immobilized Trametes pubescens MB 89 for plant growth promotion.

Industrialization and the ever-increasing world population have diminished high-quality water resources for sustainable agriculture. It is imperative to effectively treat industrial effluent to render the treated water available for crop cultivation. This study aimed to assess the effectiveness of textile effluent treated with Trametes pubescens MB 89 in supporting maize cultivation. The fungal treatment reduced the amounts of Co, Pb and As in the textile effluent. The biological oxygen demand, total dissolved solids and total suspended solids were within the permissible limits in the treated effluent. The data indicated that the irrigation of maize with fungal-treated textile effluent improved the growth parameters of the plant including root, shoot length, leaf area and chlorophyll content. Moreover, better antioxidant activity, total phenol content and protein content in roots, stems and leaves of maize plants were obtained. Photosynthetic parameters (potential quantum yield, electron transport rate and fluorescence yield of non-photochemical losses other than heat) were also improved in the plants irrigated with treated effluent as compared to the control groups. In conclusion, the treatment of textile effluent with the immobilized T. pubescens presents a sustainable solution to minimize chemical pollution and effectively utilize water resources.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Promoting sustainable smallholder farming via multistakeholder collaboration.

Transforming smallholder farms is critical to global food security and environmental sustainability. The science and technology backyard (STB) platform has proved to be a viable approach in China. However, STB has traditionally focused on empowering smallholder farmers by transferring knowledge, and wide-scale adoption of more sustainable practices and technologies remains a challenge. Here, we report on a long-term project focused on technology scale-up for smallholder farmers by expanding and upgrading the original STB platform (STB 2.0). We created a formalized and standardized process by which to engage and collaborate with farmers, including integrating their feedback via equal dialogues in the process of designing and promoting technologies. Based on 288 site-year of field trials in three regions in the North China Plain over 5 y, we find that technologies cocreated through this process were more easily accepted by farmers and increased their crop yields and nitrogen factor productivity by 7.2% and 28.1% in wheat production and by 11.4% and 27.0% in maize production, respectively. In promoting these technologies more broadly, we created a "one-stop" multistakeholder program involving local government agencies, enterprises, universities, and farmers. The program was shown to be much more effective than the traditional extension methods applied at the STB, yielding substantial environmental and economic benefits. Our study contributes an important case study for technology scale-up for smallholder agriculture. The STB 2.0 platform being explored emphasizes equal dialogue with farmers, multistakeholder collaboration, and long-term investment. These lessons may provide value for the global smallholder research and practitioners.

Insights from modelling sixteen years of climatic and fumonisin patterns in maize in South Africa.

Mycotoxin contamination of agricultural commodities is a global public health problem that has remained elusive to various mitigation approaches, particularly in developing countries. Climate change and its impact exacerbates South Africa's vulnerability to mycotoxin contamination, and significantly threatens its's food systems, public health, and agro-economic development. Herein we analyse sixteen years (2005/2006-2020/2021) of annual national meteorological data on South Africa which reveals both systematic and erratic variability in critical climatic factors known to influence mycotoxin contamination in crops. Within the same study period, data on fumonisin (FB) monitoring show clear climate-dependent trends. The strongest positive warming trend is observed between 2018/2019 and 2019/2020 (0.51 °C/year), and a strong positive correlation is likewise established between FB contamination and temperature (r ranging from 0.6 to 0.9). Four machine learning models, viz support vector machines, eXtreme gradient boosting, random forest, and orthogonal partial least squares, are generalized on the historical data with suitable performance (RMSE as low as 0.00). All the adopted models are able to predict future FB contamination patterns with reasonable precision (R2 ranging from 0.34 to 1.00). The most important model feature for predicting average FB contamination (YA) is the historical pattern of average FB contamination in maize within the region (ΣFBs_avg). The two most significant features in modelling maximum FB contamination (YM) are minimum temperature from the CMIP6 data (Pro_tempMIN) and observed precipitation from the CRU data (O_prep). Our study provides strong evidence of the impact of climate change on FB in South Africa and reiterates the significance of machine learning modelling in predicting mycotoxin contamination in light of changing climatic conditions, which could facilitate early warnings and the adoption of relevant mitigation measures that could help in mycotoxin risk management and control.

Proficiency testing for event-specific quantification of genetically modified maize MON87427: Performance assessment based on the metrologically traceable reference values as assigned values.

The Asia Pacific Metrology Program and the Accreditation Cooperation joint Proficiency Testing (PT) program for the quantification of genetically modified maize MON87427 was organized by the National Institute of Metrology, China, to enhance the measurement accuracy and metrological traceability in the region. Certified reference materials were employed as test samples; metrologically traceable certified reference values served as PT reference values (PTRVs) for evaluating the participants results. The consensus values obtained from the participants were higher than the assigned values, potentially due to the systematic effects of DNA extraction process. The participants' relatively poor overall performance by the ζ-score compared with z-score demonstrates their need to thoroughly investigate quantification bias to elevate the measurement capability of genetically modified (GM) content and deepen their understanding of uncertainty estimation. This program confirmed the importance of using metrologically traceable reference values instead of consensus values as PTRV for reliable performance assessment.

Environmental prospective of valorizing corn processing effluent to produce ferulic acid grafted chitosan polymer.

The food industry requires new production models that include more environmentally friendly waste management practices, considering that the environmental loads of solid waste and wastewater associated with this sector cause damage to the receiving ecosystems. The approach considered in this study focuses on the design and environmental assessment of an enzymatic process for the valorization of ferulic acid present in the effluent of a corn tortilla plant. The ferulic acid can be immobilized on chitosan so that the ferulic acid grafted chitosan can be used as a bioactive film with enhanced antioxidant properties with potential applications in the biotechnology sector. Its real projection approach requires the evaluation of its environmental and economic performance, trying to identify its benefits and potential in the value chain, using the Techno-Economic Analysis (TEA) as a phase for the conceptual design of the process and the Life Cycle Assessment (LCA) methodology for the environmental evaluation. It should be noted that the TEA indicators are promising, since the values of the financial indicators obtained are representative of the economic profitability, which makes the ferulic acid valorization a viable process. In terms of the environmental impact of the process, the buffer dose and the chitosan production process are identified as the main critical points. This double benefit in environmental and economic terms shows that the valorization of ferulic acid for chitosan functionalization is a promising alternative to improve the sustainability performance of corn processing.

Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India.

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards.

Host Range Characterization of Phytophthora sansomeana Across Corn, Soybean, Wheat, Winter Cereal Rye, Dry Bean, and Oats and an In Vitro Assessment of Seed Treatment Sensitivity.

Formally described in 2009, Phytophthora sansomeana is a pathogen of increasing interest in native, agricultural, and horticulturally important plant species. The objective of this study was to elucidate the symptomatic and asymptomatic host range of P. sansomeana on six agricultural crop species commonly used in field crop rotations in Michigan. In addition, sensitivity to oomicides commonly used in seed treatments, including oxathiapiprolin, mefenoxam, ethaboxam, and pyraclostrobin, was performed to aid in disease management recommendations. Plant biomass, quantity of P. sansomeana DNA in roots, and reisolations were used to assess pathogenicity and virulence of 18 isolates of P. sansomeana on each plant species using an inoculated seedling growth chamber assay. Isolates displayed varying levels of virulence to the hosts tested. Reisolations were completed for each plant species tested, and varying quantities of P. sansomeana DNA were found within all plant species root samples. Corn, wheat, soybean, dry bean, and winter cereal rye plants were symptomatic hosts with significant reduction observed in the total plant biomass. No significant reduction in total plant biomass was observed in oats, and oat roots harbored the least amount of P. sansomeana DNA. No P. sansomeana isolates were insensitive to the oomicide compounds tested with mean absolute inhibition (EC50) values of fungicide required for 50% growth inhibition values of 7.8 × 10-2 µg/ml for mefenoxam, 1.13 × 10-1 µg/ml for ethaboxam, 2.6 × 10-2 µg/ml for oxathiapiprolin, and 3.04 × 10-1 µg/ml for pyraclostrobin. These results suggest that common crop rotations in Michigan may not be a viable option to reduce soilborne inoculum accumulation and oomicide seed treatments could be considered for early-season management of P. sansomeana.

Cortical parenchyma wall width regulates root metabolic cost and maize performance under suboptimal water availability.

We describe how increased root cortical parenchyma wall width (CPW) can improve tolerance to drought stress in maize by reducing the metabolic costs of soil exploration. Significant variation (1.0-5.0 µm) for CPW was observed in maize germplasm. The functional-structural model RootSlice predicts that increasing CPW from 2 µm to 4 µm is associated with a ~15% reduction in root cortical cytoplasmic volume, respiration rate, and nitrogen content. Analysis of genotypes with contrasting CPW grown with and without water stress in the field confirms that increased CPW is correlated with an ~32-42% decrease in root respiration. Under water stress in the field, increased CPW is correlated with 125% increased stomatal conductance, 325% increased leaf CO2 assimilation rate, 73-78% increased shoot biomass, and 92-108% increased yield. CPW was correlated with leaf mesophyll midrib parenchyma wall width, indicating pleiotropy. Genome-wide association study analysis identified candidate genes underlying CPW. OpenSimRoot modeling predicts that a reduction in root respiration due to increased CPW would also benefit maize growth under suboptimal nitrogen, which requires empirical testing. We propose CPW as a new phene that has utility under edaphic stress meriting further investigation.

Projecting the Contribution of Provitamin A Maize Biofortification and Other Nutrition Interventions to the Nutritional Adequacy and Cost of Diets in Rural Zimbabwe.

BACKGROUND: Evidence of the effectiveness of biofortified maize with higher provitamin A (PVA) to address vitamin A deficiency in rural Africa remains scant. OBJECTIVES: This study projects the impact of adopting PVA maize for a diversity of households in an area typical of rural Zimbabwe and models the cost and composition of diets adequate in vitamin A. METHODS: Household-level weighed food records were generated from 30 rural households during a week in April and November 2021. Weekly household intakes were calculated, as well as indicative costs of diets using data from market surveys. The impact of PVA maize adoption was modeled assuming all maize products contained observed vitamin A concentrations. The composition and cost of the least expensive indicative diets adequate in vitamin A were calculated using linear programming. RESULTS: Very few households would reach adequate intake of vitamin A with the consumption of PVA maize. However, from a current situation of 33%, 50%-70% of households were projected to reach ≥50% of their requirements (the target of PVA), even with the modest vitamin A concentrations achieved on-farm (mean of 28.3 µg RAE per 100 g). This proportion would increase if higher concentrations recorded on-station were achieved. The estimated daily costs of current diets (mean ± standard deviation) were USD 1.43 ± 0.59 in the wet season and USD 0.96 ± 0.40 in the dry season. By comparison, optimization models suggest that diets adequate in vitamin A could be achieved at daily costs of USD 0.97 and USD 0.79 in the wet and dry seasons, respectively. CONCLUSIONS: The adoption of PVA maize would bring a substantial improvement in vitamin A intake in rural Zimbabwe but should be combined with other interventions (e.g., diet diversification) to fully address vitamin A deficiency.

Human health risks of heavy metal(loid)s mediated through crop ingestion in a coal mining area in Eastern China.

The heavy metal(loid)s (HMs) in soils can be accumulated by crops grown, which is accompanied by crop ingestion into the human body and then causes harm to human health. Hence, the health risks posed by HMs in three crops for different populations were assessed using Health risk assessment (HRA) model coupled with Monte Carlo simulation. Results revealed that Zn had the highest concentration among three crops; while Ni was the main polluting element in maize and soybean, and As in rice. Non-carcinogenic risk for all populations through rice ingestion was at an "unacceptable" level, and teenagers suffered higher risk than adults and children. All populations through ingestion of three crops might suffer Carcinogenic risk, with the similar order of Total carcinogenic risk (TCR): TCRAdults > TCRTeenagers > TCRChildren. As and Ni were identified as priority control HMs in this study area due to their high contribution rates to health risks. According to the HRA results, the human health risk was associated with crop varieties, HM species, and age groups. Our findings suggest that only limiting the Maximum allowable intake rate is not sufficient to prevent health risks caused by crop HMs, thus more risk precautions are needed.

Economic analysis of banana peel and sweet potato vines in diets for rabbits.

This study aimed to evaluate the costs of using banana peel (BP) and sweet potato vine (SPV) in rabbit diets. BP and SPV were chosen to replace maize and alfalfa hay, because, in addition to the ingredients having similar nutritional characteristics, they are among the most expensive ingredients in rabbit diets. Data were obtained through a biological assay carried out in the Cuniculture Laboratory of the Universidade Federal de Santa Maria, Santa Maria, RS, Brazil. Fifty New Zealand white rabbits, weaned at 35 days of age, were fed during the growth phase (35 to 84 days) with increasing levels of BP and SPV, replacing maize and alfalfa hay (T0, T25, T50, T75 and T100% replacement). A diet containing 100% replacement (T100) had the lowest cost per kilogram, which was R$ 1.18/kg, while the controlled diet was 57% more expensive, costing R$ 2.08/kg. The total operating cost to produce a rabbit with control treatment was R$10.93/head and at T100, it was R$6.51/head. The animal income for a live rabbit was R$ 24.08 and R$ 23.95 in treatments T0 and T100, respectively. Regarding the gain margin per animal (GMA), in TO it was R$ 13.16 while in T100 it was R$ 17.44, therefore the GMA was 32.55% higher when using the T100 diet. In conclusion, it is more economical and feasible to feed rabbits with diets containing 100% BP and SPV, replacing maize and alfalfa hay.

Aflatoxins in maize flour produced in Mozambique and its risk assessment.

This study investigated the occurrence of aflatoxins (B1, B2, G1, and G2) in maize flour produced in Mozambique and to assess the associated carcinogenic risk. At different opportunities, 30 samples of maize flour were collected in five flour processing factories. These were determined by high-performance liquid chromatography (HPLC) with fluorescence detection. AFB1 concentrations ranged from 0.25 to 0.33 µg kg-1. The levels of total aflatoxins ranged from 0.55 to 1.05 µg kg-1, with a mean of 0.89 µg kg-1, for which maximum limits (MLs) are 10 and 4 µg kg-1 for Mozambique and the European Union, respectively. The calculated Margin of Exposure (MOE) for men and women was 243 and 231, respectively, so several folds below the risk cut-off level, indicating that consumption of such maize flour poses a potential risk of hepatocarcinoma related to aflatoxin exposure due to high intake of this food, a staple diet in most African countries.