Occurrence of aflatoxin B1: link between agricultural practices and estimation of risks to human health in peanut production systems across Adamawa, Centre and North regions of Cameroon

Occurrence of aflatoxin B1: link between agricultural practices and estimation of risks to human health in peanut production systems across Adamawa, Centre and North regions of Cameroon | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Occurrence of aflatoxin B1: link between agricultural practices and estimation of risks to human health in peanut production systems across Adamawa, Centre and North regions of Cameroon Pierre Germain Ntsoli, Marie Ampères Boat Bedine, Idriss Djoko Kouam, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6727619/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Dec, 2025 Read the published version in Food Safety and Risk → Version 1 posted 13 You are reading this latest preprint version Abstract Aflatoxin contamination in peanuts poses a significant health risk to consumers due to the carcinogenic nature of these toxins. In this study, the concentration of Aflatoxin B1 (AFB1) in peanut kernels and the associated risk of hepatocarcinoma risk were evaluated across different age groups within the Cameroonian population. This assessment was based on samples from distinct peanut production systems located in the Adamawa, Centre, and North regions of Cameroon. AFB1 concentrations in raw peanut samples (n = 90) were analyzed using an ELISA method. The results revealed varying frequencies of AFB1 contamination: 57.17% in low-resource peanut production systems (System 1), 47.36% in subsistence production systems integrating peanut, maize, and roots/tubers (System 2), 81.48% in semi-intensive integrated cotton-peanut production systems (System 3), and 100% in highly monetized peanut production systems (System 4). Correspondingly, the average AFB1 concentrations for these systems were 3.57, 4.14, 2.49, and 26.37 µg/kg, respectively. Notably, these AFB1 concentrations (especially those exceeding 2 µg/kg) were consistently linked to agronomic factors such as crop variety, previous field cultivation, fertilization practices, the application of phytosanitary products, and the type of storage bag employed. For all age categories, the mean exposure to AFB1 via peanut consumption was estimated to range between 1.40 and 150.02 ng/kg bw/day, resulting in a margin of exposure (MOE) of 1.40 to 5539.72. The average estimated cancer risk due to AFB1 exposure ranged from 0.06 to 6.89 cases/100,000 people/year. This study offers novel insights into the probabilistic risk assessment and potential health impact of AFB1 in peanuts from existing peanut production systems in Adamawa, Centre, and North, Cameroon. These findings can serve as a foundation for developing strategic mitigation measures tailored to different production systems, thereby promoting peanut production in alignment with global standards and contributing to the achievement of crucial food security objectives. Aflatoxin B1 Hepatocellular carcinoma Margin of exposure Peanut production systems Risk assessment Cameroon Figures Figure 1 Figure 2 1. Introduction The Sustainable Development Goals (SDGs), defined by all members of the United Nations for 2030, aim to achieve peace, prosperity, and improved food conditions (Tanumihardjo et al., 2020 ; Ortega-Beltran and Bandyopadhyay, 2021 ). They also seek to foster greater resilience in the face of insecurity and inequality, address low economic growth, combat deteriorating ecosystems, and mitigate climate change. Agriculture is strongly linked to most of the Sustainable Development Goals (Tanumihardjo et al., 2020 ). Among these goals, Ortega-Beltran & Bandyopadhyay ( 2021 ) specifically highlight that the main objective of agriculture-related targets is to produce safe and nutritious food, enhance incomes and livelihoods, and facilitate adaption to the challenges posed by climate change. Leguminous pod crops are vital crops for global agricultural production systems, especially in arid and semi-arid regions. Among these, peanuts are a staple food that plays an essential role in food security, particularly for people in tropical and subtropical areas. Beyond its place in production systems, its rotation with other food crops is crucial due to its ability to fix atmospheric nitrogen, which is vital to maintaining soil fertility. In addition to this capacity, peanuts are a highly recommended plant for the control of common wind erosion in arid and semi-arid zones. However, peanut are also a substrate favorable to fungal growth, especially for the toxigenic fungi Aspergillus flavus and Aspergillus parasiticus , which produce mycotoxins known as aflatoxins (B1, B2, G1, G2). Mycotoxins pose a significant danger to human and animal health. Currently, they represent the foremost food-related risk factor among food contaminants, surpassing pesticide residues, heavy metals, and food additives (Munkvold et al., 2019 ). Among all known mycotoxins, aflatoxins were the first to be discovered, owing of their involvement in the deaths of over 100,000 turkeys fed contaminated peanut feed. Aflatoxins, responsible for 5 to 28% of all cases of hepatocellular carcinoma (HCC) worldwide (Liu and Wu, 2010 ), are classified by the International Agency for Research on Cancer to be Group 1 carcinogens (IARC, 1996 ), with more than 80% of HCC cases occurring in low-incomes countries, where populations face a high-risk source of dietary exposure to aflatoxins, alongside chronic hepatitis B and hepatitis C viral infection (HBV and HCV) (Majeed et al., 2018 ). This context explains the fact that, liver cancer is ranked as the second and third most common cancer in men and women, respectively, and as the leading cause of death in men and the third leading cause of cancer death in African women (Ferlay et al., 2010 ). Cameroon is currently the 10th largest producer of peanuts in the world. Peanuts are cultivated across all agroecological zones using various technical models, which results in quality variations depending on the origin area and the predominant agricultural production system. Given the essential role of peanuts in the dietary habits of the Cameroonian population, and considering the risks of aflatoxin contamination primarily exacerbated by producers' lack of awareness about these toxins, coupled with poor associated pre- and post-harvest practices (Ntsoli et al., 2024 ), and climate change manifesting through erratic rainfall and subsequent droughts, it remains crucial to investigate the link between peanut-based production systems, the contamination levels of the peanut kernels produced within these systems, and the health risks for consuming populations. The application of probabilistic methods to estimating population exposure to mycotoxins constitute an ideal approach to assess exposure to these secondary metabolites, which are known to be carcinogenic by IARC ( 1996 ). To our knowledge, no study in Cameroon reported the link between the different peanut production systems, aflatoxin B1 contamination, and the associated human health risks. Thus, the present study aimed to investigate AFB1 contamination in peanuts, estimate dietary exposure to this toxin through peanut consumption, and assess the related human health risks for various age groups within the Cameroonian population dependent on this commodity, utilizing a probabilistic approach. 2. Materials and methods 2.1. Description of the study site and collection of samples A total of 90 peanut samples, each weighing between 0.5 and 1 kg and intended for human consumption, were collected from producers across four distinct peanut production systems in three regions of Cameroon (Adamawa, Centre, North). Sampling involved one sample per producer. These producers had previously been registered during a survey on knowledge and practices regarding mycotoxin and, specifically, aflatoxin contaminations, as detailed by Ntsoli et al. ( 2024 ). Sampling was conducted from January to March 2024, corresponding to five to six months post-harvest (i.e., during the post-storage period). The samples were transported in isothermal bags to the Animal Health Laboratory of the Faculty of Agronomy and Agricultural Sciences (FAAS) in Dschang and stored at 4°C pending toxicological analyses. A detailed description of the different peanut production systems and sample collection points is presented in Table 1 and Fig. 1 , respectively. Table 1 Description of Peanut Sample Collection Production Systems Production System 1 Production System 2 Production System 3 Production System 4 Geographic coordinates of collection points Latitude : 4º44 − 5º Longitude : 11º10–11º90 Latitude : 4º44 − 5º Longitude : 11º10–11º90 Latitude : 7º75 − 8º Longitude : 13º35 − 13º90 Latitude : 8º5–10º10 Longitude : 13º00–14º20 Regions Centre Centre North Adamawa Agro-ecological zones Forest area with bimodal rainfall Forest area with bimodal rainfall Guinean Savannah Zone Sudano-Sahelian savannah zone Production system description The traditional or subsistence peanut system is characterized by low resource levels and predominantly self-consumption. It operates on very small farms in Centre Cameroon, relying solely on family labor, with a strong prevalence of female involvement. A key characteristic of this system is the producers' complete lack of knowledge regarding mycotoxins in peanuts. The subsistence system integrating peanuts, maize, and tubers. This system is characterized by the alternating combination and/or rotation of peanuts, maize, and tubers, all of which play a direct role in food security and constitute the main staple foods of households. A notable feature of this system is the high proportion of female involvement among producers, who possess a slight awareness of kernel contamination by mycotoxins. The semi-intensive integrated cotton-peanut system, mainly in the North Cameroon region. In this system, cotton serves as the primary cash crop, cultivated under an intensive agricultural model. Peanuts, conversely, function as a rotational crop, aiming to generate additional income for the producer, restore soil fertility, and minimize the risks associated with cotton monoculture. The traditional monetized peanut system operates with a focus on the local market. Peanuts are the primary crop in this system, cultivated in pure stands on large farms, often in rotation with red millet or maize. Income generated per peanut season is substantial, largely attributed to the cultivation of extensive areas, improved stock management through the use of synthetic products, and the employment of mechanical threshers for shelling the pods. This system is characterized by a high proportion of male involvement, with most participants being household heads who possess no knowledge of mycotoxin contamination in kernels. Peanut storage capacity Weak Weak High High Number of samples collected 14 19 27 30 System 1 = low-resource peanut system; System 2 = subsistence system integrating peanuts, maize and tubers; System 3 = integrated cotton-peanut semi-intensive system; System 4 = highly monetized peanut system 2.2. Determination of aflatoxin B1 in peanut kernels and estimation of the risk of hepatocarcinoma 2.2.1. Assay of aflatoxin B1 in kernels AFB1 levels in the various samples were assessed using the quantitative immunochemical ELISA method ( Enzyme Linked Immune Sorbent Assay ). The AFB1 ELISA test kits (E-TO-E008 AFB1 ELISA KIT) used in this study were provided by Wuhan Elabscience® Biotechnology Co., Ltd. This method was selected for its simplicity, reliability, cost-effectiveness and speed (more than 100 samples can be analyzed in one day) with a detection limit of 0.01mg/kg (Daems et al., 2017 ). The principle of the ELISA method is based on the ability of a specific antibody to distinguish the three-dimensional structure of a specific aflatoxin. Its objective is to extract mycotoxins into a liquid phase for subsequent analysis. It is important to note that the particle size of the ground material influences the analytical result; a finer particle size yields better extraction efficiency (Beyene et al., 2019 ). The dosing protocol was applied according to the manufacturer's instructions. Briefly, 2 g of finely ground peanut powder from each sample were mixed with 50 mL of methanol (HPLC grade) and distilled water (70:30 v/v) and homogenized for 5 minutes. The mixture was then centrifuged at 4000 rpm for 10 minutes (Centrifuge Rotofix 32 A, Germany). The resulting supernatants were collected for AFB1 detection and transferred into conical microtubes (0.5 mL/microtube). Deionized water (0.5 mL) was added, and the solution was oscillated for 5 seconds. Subsequently, 50 µL of the prepared standards and samples (previously centrifuged and mixed with deionized water) were introduced into the microwells. This was followed by a series of reactions involving successive additions of conjugated HRP and antibody solution (step 1), buffer solution (five washes at 30-second intervals), substrate reaction A & B (step 2), and stop solution in each well. Incubation times of 30 and 15 min were applied to steps 1 & 2, respectively. The optical density was measured directly (within a maximum of 10 minutes after adding the stop solution) using a 450 nm ELISA plate reader (Chromatic Reader, USA) with standards of 0, 6, 12, 24 and 48 ppb. The concentration of AFB1 was calculated based on the standard curve equation (R 2 ≥ 0.98) obtained from the graph that combined the concentrations of the standards with their optical densities after reading on an ELISA plate reader. 2.2.2. Estimation of exposure to AFB1 The estimated daily intake (EDI) was determined using the average aflatoxin levels derived from peanut samples, the daily amount of peanut consumed, and the average body weight. The EDI for the average aflatoxin B1 was premeditated using the following formula and expressed in µg/kg body weight/day (µg/kg bw/day) (Sifuentes dos Santos et al., 2013 ; EFSA Panel on Contaminants in the Food Chain et al., 2020 ). EDI = [daily intake (food) x average level of AFB1] / average body weight Daily consumption of peanuts in Cameroon according to Ingenbleek et al. ( 2017 ) is approximately 0.0364 kg/day (13.286 kg/year). The different age categories according to the EFSA ( Panel on Dietetic Products and Allergies ) (2009) and their corresponding estimated average weights in Cameroon used in this study are as follows: Infants – 3.2 (2.42–3.67) kg (Kaze et al., 2020 ), Toddlers 9.8 (7-12.6) kg, Children 27.68 (25.7–29.1) kg, Adolescents − 44.08 (31.6–55.6) kg (Wamba et al., 2013 ), Adults − 64,83 kg (Walpole et al., 2012 ). 2.2.3. Characterization of the margin of exposure to aflatoxin B1 The risk assessment of carcinogenic compounds, such as aflatoxins, was appropriately calculated based on the approach of the margin of exposure (MOE), which will be estimated by dividing the lower limit of the reference dose 10% (BMDL 10 ) for aflatoxin B1 by exposure to the toxin as recommended by EFSA Panel on Contaminants in the Food Chain et al. ( 2020 ), as expressed in the equation. MOE = Lower Limit of Reference Dose 10%/ EDI (Exposure) Hepatic carcinogenicity of aflatoxins is the critical consequence of the risk assessment. Therefore, the lower confidence limit of the reference dose for a 10% reference response (BMDL 10 ) for the frequency of hepatocellular carcinomas (HCC) in male rats was considered. The BMDL 10 for HCC related to AFB1 ingestion proposed by EFSA (2007) (0.17 µg/kg or 170 ng/kg body weight per day) was used in this study for the definition of MOE. A public health alarm is triggered when MOEs are less than 10,000 (JECFA, 2018 ). 2.2.4. Estimating the risk of liver cancer due to peanut consumption in Cameroon Ingestion of aflatoxins may be associated with the development of liver cancer (Shephard, 2008 ). Therefore, the liver cancer risk estimate for Cameroonian adult consumers will be calculated for aflatoxin B1. The aim is to estimate the population cancer risk per 100,000, which is the product of the EDI value and the mean hepatocellular carcinoma (HCC) potency from the individual hepatitis B surface antigen (HBsAg) potencies (HBsAg-positive and HBsAg-negative groups). The power values estimated by (JECFA, 2018 ) for AFB1, which corresponded to 0.3 cancers/year/100,000 population ng/kg bw/day (uncertainty range: 0.05–0.5) in HBsAg positive individuals and 0.01 cancers/year/100,000 population ng/kg bw/day (uncertainty range: 0.002–0.03) in HBsAg negative individuals (JECFA, 2018 ), will be adopted for this calculation. In addition, the average HBsAg + prevalence rate of 12.6% (adults-8.36%, 14.3%-adolescents, 0.55%-children) in Cameroon (Kenfack-Momo et al., 2022 ) was adopted and 87.4% (100 − 12.6%) was extrapolated to the HBsAg-negative groups. Therefore, the average potency for cancer in Cameroon will be estimated as follows according to the equation prescribed by Shephard ( 2008 ) and Adetunji et al. ( 2018 ): Average potency = [0.3 x HBsAg negative individuals in Cameroon] + [0.01 x HBsAg positive individuals / prevalence rate in Cameroon] Thus, the cancer risk (cancers per year per 100,000 population per ng of aflatoxin/kg bw/day) was estimated using the following formula in the equation: Cancer Risk = Exposure (EDI) × Average Potency 2.3. Data analysis Aflatoxin B1 levels were calculated by performing a regression analysis in Microsoft Excel (2019) using the AFB1 standards. The single-sample t-test was used to compare the means obtained with a reference value, a 95% confidence interval and a 5% probability threshold. A summary of the descriptive statistics (mean, median, standard deviation, standard error, skewness, Kurtosis, etc.) using the stats package of the R software version 4.3.2. Probabilistic risk assessment models were used: daily intake, exposure margin, average potency, and cancer risk. 3. Results 3.1. Occurrence of aflatoxin B1 in peanut kernels The number of peanut samples contaminated with AFB1 is presented by production systems in Tables 2 , 3 , and Fig. 2 . The occurrence levels of AFB1 range from 0 and 28.57 µg /kg in System 1, 0 and 30.66 µg /kg in System 2, 0 and 8.03 µg /kg in System 3, and 2.57 and 57.13 µg /kg in System 4. For System 1, the mean, standard error of the mean (SEM), and median AFB1 concentrations were 3.57, 2.02, and 0.96 µg/kg, respectively. Skewness and kurtosis values were 3.17 and 10.69, respectively, indicating a skewed and heavy-tailed AFB1 dataset for this production system (Table 2 ). The lower and upper bounds of the 95% confidence interval were − 0.8 and 7.95, respectively, and showed no significant differences at the 5% level, but significant differences at the 10% level (Table 3 ). Summary statistics for System 2 revealed mean, SEM, and median AFB1 concentrations of 4.14, 2.12, and 0.18 µg/kg, respectively. Skewness and kurtosis values were 2.55 and 5.50, respectively, indicating a skewed distribution with a moderate tail (Table 2 ). The lower and upper bounds of the 95% confidence interval were − 0.32 and 8.61, respectively, and showed no significant differences at the 5% level, but significant differences at the 10% level (Table 3 ). System 3 recorded mean, SEM, and median AFB1 concentrations of 2.49, 0.42, and 2.24 µg/kg, respectively. The dataset exhibited slight symmetry and a slight left tail, with skewness and kurtosis values of 0.756 and − 0.228, respectively (Table 2 ). Values of 1.62 and 3.37 were recorded as lower and upper bounds, respectively. Significant differences (P < 0.05) were observed (Table 3 ). For Production System 4, the mean, SEM, and median AFB1 concentrations were 26.37, 3.17, and 31.04 µg/kg, respectively (Table 2 ). This system's dataset was relatively symmetrical and light-tailed, with skewness and kurtosis values of 0.031 and − 1.523, respectively. The upper and lower bounds of 32.88 and 19.88 were recorded, respectively. Significant differences (p < 0.05) were observed (Table 3 ). Table 2 Summary of statistics of AFB1 concentration in raw peanut kernels obtained in four peanut production systems in Cameroon System 1 System 2 System 3 System 4 Total Number of samples 14 19 27 30 90 Average 3.57 4.14 2.49 26.37 10.97 Standard Error of Mean 2.02 2.12 0.42 3.17 1.65 Standard deviation 7.58 9.27 2.27 17.41 15.69 Asymmetry 3.17 2.55 075 0.03 1.45 Standard error of asymmetry 0.597 0.524 0.44 0.42 0.254 Kurtosis 10.69 5.493 -0.22 -1.52 0.71 Standard kurtosis Error 1.154 1.014 0.87 0.83 0.50 Interval 0-28.57 0-30.66 0-8.03 0-57.13 0-57.14 Q1 = first quartile 0 0 0.89 9.02 0.38 Q2 = median 0.96 0.18 2.24 31.04 3.20 Q3 = third quartile 3.20 3.36 3.81 40.37 11 The AFB1 contents presented in the table are expressed in µg /kg; System 1 = low-resource peanut system; System 2 = subsistence system integrating peanuts, maize, and tubers; System 3 = semi-intensive integrated cotton-peanut system; System 4 = highly monetized peanut system Table 3 Statistics of the AFB1 concentrations using one sample t-test of raw peanut samples from the four different peanut production systems 95% confidence interval t df Sigma (2-tailed) Mean difference Lower Bound Upper Bound System 1 1.765 13 0.10 3.60 -0.80 7.95 System 2 1.94 18 0.06 4.14 -0.32 8.61 System 3 5.843 26 0.00 2.50 1.62 3.37 System 4 8.298 29 0.00 26.37 19.88 32.88 Total 6.64 89 0.00 10.97 7.68 14.25 The AFB1 contents presented in the table are expressed in µg /kg; system 1 = peanut system with a low level of resources; system 2 = subsistence system integrating peanuts, maize, and tubers; system 3 = semi-intensive integrated cotton-peanut system; System 4 = Highly monetized peanut system To effectively assess the AFB1 concentrations in the peanut kernels collected from various peanut-based production systems, this study utilized regulatory limits and standards for AFB1 established by the European Food Safety Authority (EFSA), the China National Center for Food Safety Risk Assessment (CFSA), and FAO-WHO Codex Alimentarius . These limits are presented in Table 4 . Overall, the AFB1 levels recorded in samples from each production system demonstrated varying levels of compliance, depending on the specific regulatory thresholds used for quality control. Regarding the frequency and percentage of peanut samples contaminated with AFB1 and exceeding the permitted limits, System 1 recorded five samples (35.71%) above the EFSA standard and one sample (7.14%) above the CFSA and Codex Alimentarius regulations for oilseeds. For the same system, 8 (57.14%) of the samples collected tested positive at AFB1. For production system 2, five of the samples (26.31%) collected showed AFB1 levels exceeding the limit set by the EFSA, while two samples (10.52%) surpassed the limits set by the CFSA and Codex Alimentarius for oilseeds, with a total of 9 (47.36%) samples testing positive at AFB1. Production system 3 recorded twenty-two samples (81.48%) that tested positive for AFB. However, 14 samples (51.85%) showed levels above the EFSA standard allowed for AFB1, yet none exceeded the CFSA and Codex Alimentarius regulations for oilseeds. Finally, Production System 4 showed 30 positive samples (100%) for AFB1, with 30 (100%), 17 (56.66%) and 17 (56.66%) samples exceeding EFSA, CFSA, and Codex Alimentarius regulations for AFB1, respectively. Of the 90 samples analyzed for AFB1, 76.66% (69 samples) tested positive for AFB1, 60% (54 samples) exceeded EFSA limits; 44.44% (40 samples) were simultaneously above Codex Alimentarius and CFSA regulations. Table 4 Proportions of AFB1 concentrations of raw peanuts samples that exceeded EFSA, CFSA and Codex Alimentarius regulation System Number of samples Exceeding EFSA regulation Exceeding CFSA Regulation Exceeding Codex Alimentarius Regulation Proportion of samples positive at AFB1 System 1 14 5 (35.72%) 1 (7.14%) 1 (7.14%) 8 (57.14%) System 2 19 5 (26.32%) 2 (10.52%) 2 (10.52%) 9 (47.36%) System 3 27 14 (51.86%) 0 (0%) 0 (0%) 22 (81.48%) System 4 30 30 (100%) 17 (56.66%) 17 (56.66%) 30 (100%) Total 90 54 (60%) 20 (22.22%) 20 (22.22%) 69 (76.66%) Regulation for AFB1 content in peanut kernels: EFSA : 2 µg/kg, CFSA : 20 µg/kg, Codex alimentarius (Oilseed crops) : 15 µg/kg The contents of AFB1 presented in the table are in ug/kg; system 1 = peanut system with a low level of resources; system 2 = subsistence system integrating peanuts, maize, and tubers; system 3 = semi-intensive integrated cotton-peanut system; System 4 = Highly monetized peanut system 3.2. Agronomic factors associated with AFB1 contamination of samples above 2 µg/kg Table 5 indicates significant variations in the presence of AFB1 levels exceeding 2 µg/kg based on the peanut variety collected (p < 0.001), underscoring the critical influence of variety on contamination. The Manipintar variety is of particular concern, with 61.1% of its samples exhibiting AFB1 levels above 2 µg/kg, whereas the Peau-lisse and Siksa varieties generally show levels below this threshold. Conversely, the cropping system (monoculture vs. polyculture) did not significantly influence contamination at a threshold above 2 µg/kg AFB1 (p > 0.05). Crop precedents (particularly cassava, soybean, sweet potato, and yam) and fertilization practices also played a decisive role. A significant impact was observed for the absence of fertilizer use, with 86.1% of such samples having AFB1 levels above 2 µg/kg. The application of phytosanitary products helped to mitigate this contamination, as only 16.7% of samples from growers who utilized them had AFB1 levels exceeding 2 µg/kg. Finally, the type of drying and the type of storage bag demonstrated interesting, albeit less pronounced, trends. These findings collectively indicate that specific agronomic practices employed can influence both AFB1 contamination and content. These results highlight the necessity for careful management of cultivated varieties and agronomic practices to minimize AFB1 contamination. Tableau 5 Agronomic factors associated with AFB1 contamination of samples above 2 µg/kg Total N = 90 1 2 µg /kg N = 54 1 P-value 2 Variety 55–437 18 (20.0%) 8 (22.2%) 10 (18.5%) < 0.001*** Manipintar 38 (42.2%) 5 (13.9%) 33 (61.1%) Peau lisse 23 (25.6%) 14 (38.9%) 9 (16.7%) Siksa 11 (12.2%) 9 (25.0%) 2 (3.70%) Cropping system Monoculture 46 (51.1%) 15 (41.7%) 31 (57.4%) 0.14 Polyculture 44 (48.9%) 21 (58.3%) 23 (42.6%) Previous crop of the production site of the collected sample Peanut Yes 11 (12.2%) 5 (13.9%) 6 (11.1%) 0.7 No 79 (87.8%) 31 (86.1%) 48 (88.9%) Cotton Yes 12 (13.3%) 6 (16.7%) 6 (11.1%) 0.5 No 78 (86.7%) 30 (83.3%) 48 (88.9%) Maize Yes 39 (43.3%) 17 (47.2%) 22 (40.7%) 0.5 No 51 (56.7%) 19 (52.8%) 32 (59.3%) Yam Yes 23 (25.6%) 4 (11.1%) 19 (35.2%) 0.010* No 67 (74.4%) 32 (88.9%) 35 (64.8%) Sweet potato Yes 26 (28.9%) 18 (50.0%) 8 (14.8%) < 0.001*** No 64 (71.1%) 18 (50.0%) 46 (85.2%) Soybean Yes 8 (8.89%) 0 (0%) 8 (14.8%) 0.020* No 82 (91.1%) 36 (100.0%) 46 (85.2%) Cassava Yes 15 (16.7%) 11 (30.6%) 4 (7.41%) 0.004** No 75 (83.3%) 25 (69.4%) 50 (92.6%) Type of fertilizer used None 57 (63.3%) 31 (86.1%) 26 (48.1%) < 0.001*** Mineral 29 (32.2%) 3 (8.33%) 26 (48.1%) Organic 1 (1.11%) 0 (0%) 1 (1.85%) Organic and mineral 3 (3.33%) 2 (5.56%) 1 (1.85%) Use of crop protection products during the field phase Yes 34 (37.8%) 6 (16.7%) 28 (51.9%) < 0.001*** No 56 (62.2%) 30 (83.3%) 26 (48.1%) Drying method Sun drying with dryer 7 (7.78%) 6 (16.7%) 1 (1.85%) 0.015* Sun drying without dryer 83 (92.2%) 30 (83.3%) 53 (98.1%) Precipitation during the drying phase Low 51 (56.7%) 24 (66.7%) 27 (50.0%) 0.12 Medium 39 (43.3%) 12 (33.3%) 27 (50.0%) High 0 (0%) 0 (0%) 0 (0%) Moisture content control Traditional (Sound of kernels) 90 (100.0%) 36 (100.0%) 54 (100.0%) Moisture meter - - - Type of storage bag Polypropylene bags 34 (37.8%) 10 (27.8%) 24 (44.4%) 0.056 Jute bag 34 (37.8%) 19 (52.8%) 15 (27.8%) Polyethylene bags 22 (24.4%) 7 (19.4%) 15 (27.8%) Use of chemical or natural substances for conservation Yes 12 (13.3%) 5 (13.9%) 7 (13.0%) > 0.9 No 78 (86.7%) 31 (86.1%) 47 (87.0%) 1 n (%) 2 *p < 0.05; **p < 0.01; ***p < 0.001 3.3 Assessment of the risk of exposure and hepatocarcinoma associated with the consumption of peanuts contaminated with AFB1 Table 6 presents the estimated risks of exposure and liver cancer for peanut-consuming populations, stratified by age group and the origin of the consumed peanut (peanut production system). For peanut samples from production system 1, the Estimated Daily Intakes (EDI) of AFB1 were 20.34, 13.28, 4.70, 2.95, and 2.00 ng/kg body weight/day for infants, toddlers, children, adolescents, and adults, respectively. The corresponding Margins of Exposure (MOE) were 9.54, 14.61, 41.28, 65.74, and 96.69, respectively. With a mean potency of 0.04594, the estimated cancer risks were 0.93, 0.61, 0.22, 0.13, and 0.09 cases/100,000 people/year, respectively. In production system 2, the EDI values were 23.35, 15.40, 5.45, 3.42, and 2.32 ng/kg body weight/day for infants, toddlers, children, adolescents, and adults, respectively. The MOE values for this system were 546.88, 837.41, 2365.25, 3766.33, and 5539.72. Maintaining the same average potency (0.04594), the corresponding cancer risks were 1.08, 0.71, 0.25, 0.16, and 0.11 cases/100,000 people/year for the same age categories. For System 3, the EDI values for infants, toddlers, children, adolescents, and adults were 14.18, 9.26, 3.28, 2.06, and 1.40 ng/kg body weight/day, respectively. The MOE values recorded were 14.73, 22.55, 63.69, 101.42, and 149.16, respectively. With the average potency remaining constant, the estimated cancer risks were 0.65, 0.43, 0.15, 0.09, and 0.06 cases/100,000 people/year, respectively. Finally, for Production System 4, the estimated daily intake values for infants, toddlers, children, adolescents, and adults were 1.58, 0.94, 0.35, 0.20, and 0.15 ng/kg bw/day, respectively. The MOE values recorded were 253.16, 425.53, 1142.85, 2000.00, and 2666.67, respectively. While the average potency was consistent with other regions, the cancer risks were 6.89, 4.50, 1.59, 1.00, and 0.68 cases/100,000 people/year, respectively (Table 6 ). Table 6 Risk evaluation for AFB1 via consumption of raw peanuts produced in the different production systems System Age range Average weight (Kg) Estimated daily intake (EDI) (ng/kg body weight/day) Margin of Exposure Cancer risk (Cases/100000 people/year) System 1 Infants 3.2 20.34 9.54 0.93 Toddler 9.8 13.28 14.61 0.61 Children 27.68 4.70 41.28 0.22 Adolescents 44.08 2.95 65.74 0.13 Adults 64.83 2.00 96.69 0.09 System 2 Infants 3.2 23.35 546.88 1.08 Toddler 9.8 15.40 837.41 0.71 Children 27.68 5.45 2365.25 0.25 Adolescents 44.08 3.42 3766.63 0.16 Adults 64.83 2.32 5539.72 0.11 System 3 Infants 3.2 14.18 14.73 0.65 Toddler 9.8 9.26 22.55 0.43 Children 27.68 3.28 63.69 0.15 Adolescents 44.08 2.06 101.42 0.09 Adults 64.83 1.40 149.16 0.06 System 4 Infants 3.2 150.02 2.48 6.89 Toddler 9.8 97.97 3.80 4.50 Children 27.68 34.68 10.75 1.59 Adolescents 44.08 21.78 17.12 1.00 Adults 64.83 14.81 25.18 0.68 1µg = 1000 ng; Average potency = 0.04594; system 1 = peanut system with a low level of resources; system 2 = subsistence system integrating peanuts, maize, and tubers; system 3 = semi-intensive integrated cotton-peanut system; System 4 = Highly monetized peanut system 4. Discussion 4.1. AFB1 content in peanuts kernels from different production systems Of the 90 peanut samples (intended for human consumption) collected from the four identified peanut-based production systems in Cameroon, 76.66% tested positive for AFB1. Our observations are almost similar to those of Abia et al. ( 2013 ), who obtained 97% of peanut samples contaminated with AFB1 in Cameroon. Also within Cameroon, Kana et al. ( 2013 ) reported that 100% of local peanut flour samples intended for animal feed were contaminated with aflatoxins. In a study simultaneously conducted in eastern Democratic Republic of Congo (DRC) (Central African sub-region) and Burundi (East Africa), Udomkun et al. ( 2018 ) reported that 100% of the peanut samples collected were contaminated with aflatoxins. In Nigeria, which borders Cameroon, 64% of peanut samples were reported positive for AFB1 (Ezekiel et al., 2021 ), while in North Africa, specifically Algeria, Ait Mimoune et al. ( 2018 ) recorded 57% of peanut samples contaminated with AFB1. Substantially similar results were reported on 55.43% of peanut samples from the Lusaka market in Zambia (Bumbangi et al., 2016 ). Examining global regulations for Aflatoxin B1, 60% of our samples showed AFB1 levels exceeding the maximum limit allowed by the EU (2 µg/kg). Contamination levels above EU regulations for aflatoxins were previously reported in 69.4% of peanut samples in the DRC (Udomkun et al., 2018 ). However, 22.22% of our samples had AFB1 levels above the Codex Alimentarius standard for oilseeds. This percentage is relatively lower than the 42% (491/1168) of peanut samples above the Codex Alimentarius , as reported by Jallow et al. ( 2021 ). Aflatoxin B1 concentrations across all samples for each production system ranged from 0 to 57.14 µg/kg, with an overall average of 10.94 µg/kg. For comparison, average AFB1 levels of 95.9 µg/kg were reported in Tanzania by Seetha et al. ( 2017 ), and to 29.3 µg/kg in the DRC (Udomkun et al., 2018 ). In Mali, Burkina Faso and Niger, mean aflatoxin levels of 115, 277, and 628 µg/kg were reported, respectively (Falade et al., 2022 ). In Ethiopia, aflatoxin levels ranging from 15 to 11 900 µg/kg have been reported by Chala et al. ( 2013 ); while in Pakistan Asghar et al. ( 2018 ) reported an average of 2.37 µg/kg of AFB1 in their peanut samples. Focusing specifically on production systems, the variable AFB1 values observed in samples from each system confirm that growers ' knowledge, perceptions, and agronomic practices within these systems contribute to either increasing or reducing kernel contamination by toxigenic Aspergillus flavus and parasiticus , and consequently, consumer exposure to aflatoxin B1. Our observations align with those of Akello et al. ( 2024 ) during a study conducted in Zambia as part of the evaluation of conservation agriculture practices implemented in several peanut-based production systems. This highlights the need to explain the observed differentials in kernel contamination by AFB1. Overall, all investigated peanut production systems recorded average AFB1 concentration exceeding 2 µg/kg (EU regulatory limit). The highly monetized traditional peanut system exhibited the most contaminated samples (26.37 µg/kg), significantly higher than the subsistence or low resources peanut system (3.57 µg/kg), the peanut system integrating maize and tubers (4.14 µg/kg), and the semi-intensive system integrating peanut and cotton (2.49 µg/kg). In Zambia, average total aflatoxin levels of 110, 99, and 87 ug/kg were reported by Akello et al. ( 2024 ) in peanut production basins involving the practice of agroforestry (peanut in association with Gliricidia sepium ), conventional tillage, and a lack of conservation agriculture techniques, respectively. For these two reported results, the variations can be justified by a set of agronomic practices applied in the different systems, which confirms the assertions of many studies conducted on the link between agronomic practices and mycotoxin contamination (Torres et al., 2014 ; Asare Bediako et al., 2019 ). Another explanation for these variations in AFB1 content can be justified by the varieties grown in each production system. Recently, during a survey of peanut-producing communities in Cameroon, Ntsoli et al. ( 2024 ) highlighted, for instance, that the Manipintar variety, which is widely used in the highly monetized traditional peanut system, has a very high level of susceptibility to mold contamination. Numerous studies consistently demonstrate differences in resistance levels to mycotoxicogenic fungal contamination and associated mycotoxins for many crops (Girdthai et al., 2010a , b ; Hamidou et al., 2014 ; Rose et al., 2016 , 2017 ; Waliyar et al., 2016 ). With this in mind, and based on our aforementioned results, it is evident to conclude that varietal resistance represents a primary approach in reducing aflatoxin contamination When combined with effective pre- and post-harvest methods, it significantly minimizes the risk of aflatoxin contamination (Pandey et al., 2019 ; Xu et al., 2022 ). 4.2. Risks of hepatocarcinoma from peanut consumption The risks of hepatocellular carcinoma associated with food consumption crucial predictors for assessing population exposure to food contaminants, particulary mycotoxins and, in our case, aflatoxin B1. This assessment is especially critical given the strategic importance of peanut (in terms food security, nutritional intake, and soil fertility management) within agrarian systems in arid and semi-arid tropics. The parameters of this hepatocellular carcinoma risk assessment varied according to the aflatoxin B1 concentrations recorded in peanut kernels (intended for human consumption) from each production system. Based on data concerning daily peanut consumption in Cameroon, and average weights by age category, estimated daily intakes ranged from 1.40 to 150.02 ng/kg body weight/day. However, our calculated daily doses considerably lower than those of another study conducted in Cameroon by Bouelet Ntsama et al. ( 2023 ), with found total daily intake (TDI) values ranging from 23 to 1000 ng/kg body weight/day for total aflatoxins in peanuts. Despite these differences, our estimated daily intakes (EDI) are well below 1000 ng/kg body weight/day, a level reported to cause adverse effects in consumer health and lead to diseases linked to the consumption of aflatoxin- contaminated food (Wu and Khlangwiset, 2010 ; Adetunji et al., 2018 ). Nonetheless, regular consumption of even slightly mycotoxin-contaminated foods does preclude bioaccumulation in human or animal biological tissues, which inherently carries risks associated with mycotoxin-related diseases. This phenomenon has been extensively demonstred in numerous published works (Escrivá et al., 2017 ; Castell et al., 2023 ). Therefore, the consumption of peanuts these different production systems could potentially lead to significant aflatoxin B1 exposure, posing harmful risks to Cameroonian consumers across various age groups (infants, toddlers, children, adolescents, and adults). Similar conclusions were drawn by Kortei et al. ( 2021 a) and Akello et al. ( 2024 ) during their respective research on peanuts in Ghana and Zambia. Similarly, the calculated margins of exposure (MOEs) ranged from 9.54 to 5539.72. These values represent a significant danger to peanut-dependent populations from these production systems, especially considering that a public health concern is typically raised when MOEs fall below 10,000 (JECFA, 2018 ; EFSA Panel on Contaminants in the Food Chain et al., 2020 ). Similar observations have been reported for the mycotoxin exposure from the consumption of various foodstuffs, with a MOE values not reaching 10,000 for aflatoxin-contaminated peanut consumption in Malaysia (Leong et al., 2011 ), Taiwan (Wang et al., 2018 ), Indonesia (Nugraha et al., 2018 ), China (Ding et al., 2012 ; Zhang et al., 2020 ; Qin et al., 2021 ), Nigeria (Adetunji et al., 2018 ; Ezekiel et al., 2021 ), Zambia (Akello et al., 2024 ; Musawa et al., 2024 ). Regarding the hepatocellular carcinoma risks associated with the consumption of peanuts from Cameroon's production systems, estimates ranging from 0.06 to 6.89 cancer cases/100,000 people/year are forecast. Our forecasts are in line with those of numerous other studies carried out. For instance, in China, between 0.003 and 0.17 cancer cases/100,000 people/year have been reported in their studies by Ding et al. ( 2012 ) in relation to the consumption of peanuts contaminated with AFB1. Wang et al. ( 2018 ) estimated between 0.0007 and 0.2713 cancers/100,000/year related to the consumption of aflatoxin-contaminated peanuts and peanut products. Qin et al. ( 2021 ) during a spatial assessment of aflatoxin exposure in China, reported estimates of 0.000 to 0.851 liver cancer cases/100,000/year. On the other hand, Akello et al. ( 2024 ) report risks between 0.334 and 27.308 cancer cases/100,000 people/year in peanut production systems in Zambia, depending on the season, the location of cultivation, and the different age groups. By broadening comparisons on other nuts, Samimi et al. ( 2024 ) on hazelnuts imported from eastern Azerbaijan, report liver cancer risks of 0.03 cases/100,000 people/year in adults, compared to 0.11 cases/100,000/year in children. Conclusion This study is the first report on the probabilistic assessment of the risk of exposure to aflatoxin B1 in peanuts-based production systems in Cameroon. The margins of dietary exposure to aflatoxin B1 from peanut consumption are alarming. In addition, there is a potential risk due to peanut consumption, associated with aflatoxin B1-induced cellular hepatocarcinoma. As such, aflatoxin B1 contamination in peanuts should be reduced to ensure food safety. This work highlights the need to establish risk management strategies and set (regulatory) guidelines for peanut cultivation (pre- and post-harvest) in the different production systems involved in peanut production to prevent contamination, followed by regular monitoring of heavily consumed foodstuffs, especially peanut. Additionally, in the future a cumulative risk assessment from exposure to multiple mycotoxins should be considered, particularly in the population infected with hepatitis B and C viruses, to estimate the total burden of mycotoxins on human health. Declarations Acknowledgment The authors would like to thank the members of the Crop Sciences Department for their scientific guidance. Thanks , are also due to the members of the Animal Health Laboratory of the Faculty of Agronomy and Agricultural Sciences of the University of Dschang, especially Pr Ngoula Ferdinand and Dr Nguedia Dongmo Arius for their collaboration. The authors also thank the agricultural engineers Etame Kossi Georges, Ngalle Tchatcho Freddy and Mambale Maakte Ombretta for acting as guides and facilitating access to producers. Authors' Contribution PGN conceived and performed the experiments, sample collection, aflatoxin analysis, data analysis and wrote the manuscript. MABB helped conceive the experiments and prepare the manuscript. IDK was responsible for aflatoxin analysis and prepare the manuscript. GAMM was responsible for aflatoxin analysis and prepare the manuscript. RWT helped conceive the experiments and prepare the manuscript. AY conceived the original study and supervised the work. All authors read and approved the final manuscript. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate No application. Consent for publication The authors declare consent for publication. Competing interests The authors declare no conflict of interest. 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Cite Share Download PDF Status: Published Journal Publication published 08 Dec, 2025 Read the published version in Food Safety and Risk → Version 1 posted Editorial decision: Revision requested 09 Jul, 2025 Reviews received at journal 08 Jul, 2025 Reviews received at journal 06 Jul, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 18 Jun, 2025 Reviewers agreed at journal 16 Jun, 2025 Reviewers agreed at journal 13 Jun, 2025 Reviewers agreed at journal 13 Jun, 2025 Reviewers invited by journal 13 Jun, 2025 Editor assigned by journal 27 May, 2025 Submission checks completed at journal 27 May, 2025 First submitted to journal 22 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6727619","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471752778,"identity":"e98b75c3-6686-4e73-aa2a-afa775af162e","order_by":0,"name":"Pierre Germain Ntsoli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIie3PMQrCMBSA4TwCdil0jVOvUHAQBz1Li7MughQUTSjEpeBab+ERDA90Kc4OLiI4F1wcREx1EB1iR8H8Q0ggH8kjxGb7xehrx1cFIWG5LaoQRghwlT0JZFUeexDqViFNh67Pcbyf+DMhsC07fc/hkMQG0kpq3UWen1iQK4492R3U0xWI3EACdBsgJLKARSWh0XIXOgduJN4ZxA2Zn2nSktOSgDATl+obyMhOE5D4nehZGsDXWF/qWVS63USLVAkjaXp4BD5Gz58lWFyGo2juJMr8sbcT1B6rCXwScjVettlstj/tDqJmVoL49pi+AAAAAElFTkSuQmCC","orcid":"","institution":"University of Dschang","correspondingAuthor":true,"prefix":"","firstName":"Pierre","middleName":"Germain","lastName":"Ntsoli","suffix":""},{"id":471752779,"identity":"63dac6ce-2c99-4e93-8e24-d87ddae3ebc7","order_by":1,"name":"Marie Ampères Boat Bedine","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"Ampères Boat","lastName":"Bedine","suffix":""},{"id":471752780,"identity":"94a55a42-dda9-4b92-802a-baf20ef14cbc","order_by":2,"name":"Idriss Djoko Kouam","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Idriss","middleName":"Djoko","lastName":"Kouam","suffix":""},{"id":471752784,"identity":"899f9edb-6b09-48e3-bd7a-38154333aa50","order_by":3,"name":"Grace Arielle Mpoam Miague","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Grace","middleName":"Arielle Mpoam","lastName":"Miague","suffix":""},{"id":471752785,"identity":"391ed63f-924f-479b-a8e0-7a5990879e7d","order_by":4,"name":"Roland Wilfried Titti","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Roland","middleName":"Wilfried","lastName":"Titti","suffix":""},{"id":471752787,"identity":"bb72019a-1ca7-4b36-a405-9160c38e15f9","order_by":5,"name":"Aoudou Yaouba","email":"","orcid":"","institution":"University of Dschang","correspondingAuthor":false,"prefix":"","firstName":"Aoudou","middleName":"","lastName":"Yaouba","suffix":""}],"badges":[],"createdAt":"2025-05-22 19:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6727619/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6727619/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40550-025-00127-9","type":"published","date":"2025-12-08T15:59:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84858136,"identity":"c9f7e9f6-3037-4b78-832d-d475c3daa62d","added_by":"auto","created_at":"2025-06-18 06:30:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":99828,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of sample collection points\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6727619/v1/7a7a58b446f65eedce915cab.png"},{"id":84857045,"identity":"c4c12af1-6b1f-40c2-a291-cea7348dce3c","added_by":"auto","created_at":"2025-06-18 06:22:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15026,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot of AFB1 content in peanut kernels by production systems\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6727619/v1/ef82e03b612017a05457c57e.png"},{"id":98245578,"identity":"664722a4-7775-4eda-a525-b32f16cb0a76","added_by":"auto","created_at":"2025-12-15 16:18:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1606073,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6727619/v1/7aedaf31-6a2b-4f75-9041-a5570ba20d68.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Occurrence of aflatoxin B1: link between agricultural practices and estimation of risks to human health in peanut production systems across Adamawa, Centre and North regions of Cameroon","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Sustainable Development Goals (SDGs), defined by all members of the United Nations for 2030, aim to achieve peace, prosperity, and improved food conditions (Tanumihardjo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ortega-Beltran and Bandyopadhyay, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). They also seek to foster greater resilience in the face of insecurity and inequality, address low economic growth, combat deteriorating ecosystems, and mitigate climate change. Agriculture is strongly linked to most of the Sustainable Development Goals (Tanumihardjo et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among these goals, Ortega-Beltran \u0026amp; Bandyopadhyay (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) specifically highlight that the main objective of agriculture-related targets is to produce safe and nutritious food, enhance incomes and livelihoods, and facilitate adaption to the challenges posed by climate change.\u003c/p\u003e \u003cp\u003eLeguminous pod crops are vital crops for global agricultural production systems, especially in arid and semi-arid regions. Among these, peanuts are a staple food that plays an essential role in food security, particularly for people in tropical and subtropical areas. Beyond its place in production systems, its rotation with other food crops is crucial due to its ability to fix atmospheric nitrogen, which is vital to maintaining soil fertility. In addition to this capacity, peanuts are a highly recommended plant for the control of common wind erosion in arid and semi-arid zones. However, peanut are also a substrate favorable to fungal growth, especially for the toxigenic fungi \u003cem\u003eAspergillus flavus\u003c/em\u003e and \u003cem\u003eAspergillus parasiticus\u003c/em\u003e, which produce mycotoxins known as aflatoxins (B1, B2, G1, G2).\u003c/p\u003e \u003cp\u003eMycotoxins pose a significant danger to human and animal health. Currently, they represent the foremost food-related risk factor among food contaminants, surpassing pesticide residues, heavy metals, and food additives (Munkvold et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among all known mycotoxins, aflatoxins were the first to be discovered, owing of their involvement in the deaths of over 100,000 turkeys fed contaminated peanut feed. Aflatoxins, responsible for 5 to 28% of all cases of hepatocellular carcinoma (HCC) worldwide (Liu and Wu, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), are classified by the International Agency for Research on Cancer to be Group 1 carcinogens (IARC, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), with more than 80% of HCC cases occurring in low-incomes countries, where populations face a high-risk source of dietary exposure to aflatoxins, alongside chronic hepatitis B and hepatitis C viral infection (HBV and HCV) (Majeed et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This context explains the fact that, liver cancer is ranked as the second and third most common cancer in men and women, respectively, and as the leading cause of death in men and the third leading cause of cancer death in African women (Ferlay et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCameroon is currently the 10th largest producer of peanuts in the world. Peanuts are cultivated across all agroecological zones using various technical models, which results in quality variations depending on the origin area and the predominant agricultural production system. Given the essential role of peanuts in the dietary habits of the Cameroonian population, and considering the risks of aflatoxin contamination primarily exacerbated by producers' lack of awareness about these toxins, coupled with poor associated pre- and post-harvest practices (Ntsoli et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and climate change manifesting through erratic rainfall and subsequent droughts, it remains crucial to investigate the link between peanut-based production systems, the contamination levels of the peanut kernels produced within these systems, and the health risks for consuming populations.\u003c/p\u003e \u003cp\u003eThe application of probabilistic methods to estimating population exposure to mycotoxins constitute an ideal approach to assess exposure to these secondary metabolites, which are known to be carcinogenic by IARC (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). To our knowledge, no study in Cameroon reported the link between the different peanut production systems, aflatoxin B1 contamination, and the associated human health risks. Thus, the present study aimed to investigate AFB1 contamination in peanuts, estimate dietary exposure to this toxin through peanut consumption, and assess the related human health risks for various age groups within the Cameroonian population dependent on this commodity, utilizing a probabilistic approach.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Description of the study site and collection of samples\u003c/h2\u003e \u003cp\u003eA total of 90 peanut samples, each weighing between 0.5 and 1 kg and intended for human consumption, were collected from producers across four distinct peanut production systems in three regions of Cameroon (Adamawa, Centre, North). Sampling involved one sample per producer. These producers had previously been registered during a survey on knowledge and practices regarding mycotoxin and, specifically, aflatoxin contaminations, as detailed by Ntsoli et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Sampling was conducted from January to March 2024, corresponding to five to six months post-harvest (i.e., during the post-storage period). The samples were transported in isothermal bags to the Animal Health Laboratory of the Faculty of Agronomy and Agricultural Sciences (FAAS) in Dschang and stored at 4\u0026deg;C pending toxicological analyses. A detailed description of the different peanut production systems and sample collection points is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of Peanut Sample Collection Production Systems\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProduction System 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProduction System 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProduction System 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProduction System 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeographic coordinates of\u003c/p\u003e \u003cp\u003ecollection points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLatitude : 4\u0026ordm;44\u0026thinsp;\u0026minus;\u0026thinsp;5\u0026ordm;\u003c/p\u003e \u003cp\u003eLongitude : 11\u0026ordm;10\u0026ndash;11\u0026ordm;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLatitude : 4\u0026ordm;44\u0026thinsp;\u0026minus;\u0026thinsp;5\u0026ordm;\u003c/p\u003e \u003cp\u003eLongitude : 11\u0026ordm;10\u0026ndash;11\u0026ordm;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitude : 7\u0026ordm;75\u0026thinsp;\u0026minus;\u0026thinsp;8\u0026ordm;\u003c/p\u003e \u003cp\u003eLongitude : 13\u0026ordm;35\u0026thinsp;\u0026minus;\u0026thinsp;13\u0026ordm;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLatitude : 8\u0026ordm;5\u0026ndash;10\u0026ordm;10\u003c/p\u003e \u003cp\u003eLongitude : 13\u0026ordm;00\u0026ndash;14\u0026ordm;20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentre\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdamawa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgro-ecological zones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForest area with bimodal rainfall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eForest area with bimodal rainfall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGuinean Savannah Zone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSudano-Sahelian savannah zone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProduction system description\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe traditional or subsistence peanut system is characterized by low resource levels and predominantly self-consumption. It operates on very small farms in Centre Cameroon, relying solely on family labor, with a strong prevalence of female involvement. A key characteristic of this system is the producers' complete lack of knowledge regarding mycotoxins in peanuts.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe subsistence system integrating peanuts, maize, and tubers. This system is characterized by the alternating combination and/or rotation of peanuts, maize, and tubers, all of which play a direct role in food security and constitute the main staple foods of households. A notable feature of this system is the high proportion of female involvement among producers, who possess a slight awareness of kernel contamination by mycotoxins.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe semi-intensive integrated cotton-peanut system, mainly in the North Cameroon region. In this system, cotton serves as the primary cash crop, cultivated under an intensive agricultural model. Peanuts, conversely, function as a rotational crop, aiming to generate additional income for the producer, restore soil fertility, and minimize the risks associated with cotton monoculture.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe traditional monetized peanut system operates with a focus on the local market. Peanuts are the primary crop in this system, cultivated in pure stands on large farms, often in rotation with red millet or maize. Income generated per peanut season is substantial, largely attributed to the cultivation of extensive areas, improved stock management through the use of synthetic products, and the employment of mechanical threshers for shelling the pods. This system is characterized by a high proportion of male involvement, with most participants being household heads who possess no knowledge of mycotoxin contamination in kernels.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeanut storage capacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of samples collected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSystem 1\u0026thinsp;=\u0026thinsp;low-resource peanut system; System 2\u0026thinsp;=\u0026thinsp;subsistence system integrating peanuts, maize and tubers; System 3\u0026thinsp;=\u0026thinsp;integrated cotton-peanut semi-intensive system; System 4\u0026thinsp;=\u0026thinsp;highly monetized peanut system\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Determination of aflatoxin B1 in peanut kernels and estimation of the risk of hepatocarcinoma\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Assay of aflatoxin B1 in kernels\u003c/h2\u003e \u003cp\u003eAFB1 levels in the various samples were assessed using the quantitative immunochemical ELISA method (\u003cem\u003eEnzyme Linked Immune Sorbent Assay\u003c/em\u003e). The AFB1 ELISA test kits (E-TO-E008 AFB1 ELISA KIT) used in this study were provided by Wuhan Elabscience\u0026reg; Biotechnology Co., Ltd. This method was selected for its simplicity, reliability, cost-effectiveness and speed (more than 100 samples can be analyzed in one day) with a detection limit of 0.01mg/kg (Daems et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The principle of the ELISA method is based on the ability of a specific antibody to distinguish the three-dimensional structure of a specific aflatoxin. Its objective is to extract mycotoxins into a liquid phase for subsequent analysis. It is important to note that the particle size of the ground material influences the analytical result; a finer particle size yields better extraction efficiency (Beyene et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe dosing protocol was applied according to the manufacturer's instructions. Briefly, 2 g of finely ground peanut powder from each sample were mixed with 50 mL of methanol (HPLC grade) and distilled water (70:30 v/v) and homogenized for 5 minutes. The mixture was then centrifuged at 4000 rpm for 10 minutes (Centrifuge Rotofix 32 A, Germany). The resulting supernatants were collected for AFB1 detection and transferred into conical microtubes (0.5 mL/microtube). Deionized water (0.5 mL) was added, and the solution was oscillated for 5 seconds. Subsequently, 50 \u0026micro;L of the prepared standards and samples (previously centrifuged and mixed with deionized water) were introduced into the microwells. This was followed by a series of reactions involving successive additions of conjugated HRP and antibody solution (step 1), buffer solution (five washes at 30-second intervals), substrate reaction A \u0026amp; B (step 2), and stop solution in each well. Incubation times of 30 and 15 min were applied to steps 1 \u0026amp; 2, respectively. The optical density was measured directly (within a maximum of 10 minutes after adding the stop solution) using a 450 nm ELISA plate reader (Chromatic Reader, USA) with standards of 0, 6, 12, 24 and 48 ppb. The concentration of AFB1 was calculated based on the standard curve equation (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.98) obtained from the graph that combined the concentrations of the standards with their optical densities after reading on an ELISA plate reader.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Estimation of exposure to AFB1\u003c/h2\u003e \u003cp\u003eThe estimated daily intake (EDI) was determined using the average aflatoxin levels derived from peanut samples, the daily amount of peanut consumed, and the average body weight. The EDI for the average aflatoxin B1 was premeditated using the following formula and expressed in \u0026micro;g/kg body weight/day (\u0026micro;g/kg bw/day) (Sifuentes dos Santos et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; EFSA Panel on Contaminants in the Food Chain et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEDI\u003c/b\u003e = [daily intake (food) x average level of AFB1] / average body weight\u003c/p\u003e \u003cp\u003eDaily consumption of peanuts in Cameroon according to Ingenbleek et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) is approximately 0.0364 kg/day (13.286 kg/year). The different age categories according to the EFSA (\u003cem\u003ePanel on Dietetic Products and Allergies\u003c/em\u003e) (2009) and their corresponding estimated average weights in Cameroon used in this study are as follows: Infants \u0026ndash; 3.2 (2.42\u0026ndash;3.67) kg (Kaze et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Toddlers 9.8 (7-12.6) kg, Children 27.68 (25.7\u0026ndash;29.1) kg, Adolescents \u0026minus;\u0026thinsp;44.08 (31.6\u0026ndash;55.6) kg (Wamba et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Adults \u0026minus;\u0026thinsp;64,83 kg (Walpole et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Characterization of the margin of exposure to aflatoxin B1\u003c/h2\u003e \u003cp\u003eThe risk assessment of carcinogenic compounds, such as aflatoxins, was appropriately calculated based on the approach of the margin of exposure (MOE), which will be estimated by dividing the lower limit of the reference dose 10% (BMDL\u003csub\u003e10\u003c/sub\u003e) for aflatoxin B1 by exposure to the toxin as recommended by EFSA Panel on Contaminants in the Food Chain et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as expressed in the equation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMOE\u003c/b\u003e\u0026thinsp;=\u0026thinsp;Lower Limit of Reference Dose 10%/ EDI (Exposure)\u003c/p\u003e \u003cp\u003eHepatic carcinogenicity of aflatoxins is the critical consequence of the risk assessment. Therefore, the lower confidence limit of the reference dose for a 10% reference response (BMDL\u003csub\u003e10\u003c/sub\u003e) for the frequency of hepatocellular carcinomas (HCC) in male rats was considered. The BMDL\u003csub\u003e10\u003c/sub\u003e for HCC related to AFB1 ingestion proposed by EFSA (2007) (0.17 \u0026micro;g/kg or 170 ng/kg body weight per day) was used in this study for the definition of MOE. A public health alarm is triggered when MOEs are less than 10,000 (JECFA, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Estimating the risk of liver cancer due to peanut consumption in Cameroon\u003c/h2\u003e \u003cp\u003eIngestion of aflatoxins may be associated with the development of liver cancer (Shephard, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Therefore, the liver cancer risk estimate for Cameroonian adult consumers will be calculated for aflatoxin B1. The aim is to estimate the population cancer risk per 100,000, which is the product of the EDI value and the mean hepatocellular carcinoma (HCC) potency from the individual hepatitis B surface antigen (HBsAg) potencies (HBsAg-positive and HBsAg-negative groups). The power values estimated by (JECFA, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) for AFB1, which corresponded to 0.3 cancers/year/100,000 population ng/kg bw/day (uncertainty range: 0.05\u0026ndash;0.5) in HBsAg positive individuals and 0.01 cancers/year/100,000 population ng/kg bw/day (uncertainty range: 0.002\u0026ndash;0.03) in HBsAg negative individuals (JECFA, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), will be adopted for this calculation.\u003c/p\u003e \u003cp\u003eIn addition, the average HBsAg\u0026thinsp;+\u0026thinsp;prevalence rate of 12.6% (adults-8.36%, 14.3%-adolescents, 0.55%-children) in Cameroon (Kenfack-Momo et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) was adopted and 87.4% (100\u0026thinsp;\u0026minus;\u0026thinsp;12.6%) was extrapolated to the HBsAg-negative groups. Therefore, the average potency for cancer in Cameroon will be estimated as follows according to the equation prescribed by Shephard (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and Adetunji et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eAverage potency = [0.3 x HBsAg negative individuals in Cameroon] + [0.01 x HBsAg positive individuals / prevalence rate in Cameroon]\u003c/p\u003e \u003cp\u003eThus, the cancer risk (cancers per year per 100,000 population per ng of aflatoxin/kg bw/day) was estimated using the following formula in the equation:\u003c/p\u003e \u003cp\u003eCancer Risk\u0026thinsp;=\u0026thinsp;Exposure (EDI) \u0026times; Average Potency\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data analysis\u003c/h2\u003e \u003cp\u003eAflatoxin B1 levels were calculated by performing a regression analysis in Microsoft Excel (2019) using the AFB1 standards. The single-sample t-test was used to compare the means obtained with a reference value, a 95% confidence interval and a 5% probability threshold. A summary of the descriptive statistics (mean, median, standard deviation, standard error, skewness, Kurtosis, etc.) using the stats package of the R software version 4.3.2. Probabilistic risk assessment models were used: daily intake, exposure margin, average potency, and cancer risk.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Occurrence of aflatoxin B1 in peanut kernels\u003c/h2\u003e \u003cp\u003eThe number of peanut samples contaminated with AFB1 is presented by production systems in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The occurrence levels of AFB1 range from 0 and 28.57 \u0026micro;g /kg in System 1, 0 and 30.66 \u0026micro;g /kg in System 2, 0 and 8.03 \u0026micro;g /kg in System 3, and 2.57 and 57.13 \u0026micro;g /kg in System 4.\u003c/p\u003e \u003cp\u003eFor System 1, the mean, standard error of the mean (SEM), and median AFB1 concentrations were 3.57, 2.02, and 0.96 \u0026micro;g/kg, respectively. Skewness and kurtosis values were 3.17 and 10.69, respectively, indicating a skewed and heavy-tailed AFB1 dataset for this production system (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The lower and upper bounds of the 95% confidence interval were \u0026minus;\u0026thinsp;0.8 and 7.95, respectively, and showed no significant differences at the 5% level, but significant differences at the 10% level (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSummary statistics for System 2 revealed mean, SEM, and median AFB1 concentrations of 4.14, 2.12, and 0.18 \u0026micro;g/kg, respectively. Skewness and kurtosis values were 2.55 and 5.50, respectively, indicating a skewed distribution with a moderate tail (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The lower and upper bounds of the 95% confidence interval were \u0026minus;\u0026thinsp;0.32 and 8.61, respectively, and showed no significant differences at the 5% level, but significant differences at the 10% level (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSystem 3 recorded mean, SEM, and median AFB1 concentrations of 2.49, 0.42, and 2.24 \u0026micro;g/kg, respectively. The dataset exhibited slight symmetry and a slight left tail, with skewness and kurtosis values of 0.756 and \u0026minus;\u0026thinsp;0.228, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Values of 1.62 and 3.37 were recorded as lower and upper bounds, respectively. Significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor Production System 4, the mean, SEM, and median AFB1 concentrations were 26.37, 3.17, and 31.04 \u0026micro;g/kg, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This system's dataset was relatively symmetrical and light-tailed, with skewness and kurtosis values of 0.031 and \u0026minus;\u0026thinsp;1.523, respectively. The upper and lower bounds of 32.88 and 19.88 were recorded, respectively. Significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were observed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of statistics of AFB1 concentration in raw peanut kernels obtained in four peanut production systems in Cameroon\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSystem 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSystem 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSystem 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSystem 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard Error of Mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsymmetry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard error of asymmetry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStandard kurtosis Error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-28.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0-30.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0-8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0-57.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0-57.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u0026thinsp;=\u0026thinsp;first quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u0026thinsp;=\u0026thinsp;median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u0026thinsp;=\u0026thinsp;third quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe AFB1 contents presented in the table are expressed in \u0026micro;g /kg;\u003c/p\u003e \u003cp\u003eSystem 1\u0026thinsp;=\u0026thinsp;low-resource peanut system;\u003c/p\u003e \u003cp\u003eSystem 2\u0026thinsp;=\u0026thinsp;subsistence system integrating peanuts, maize, and tubers;\u003c/p\u003e \u003cp\u003eSystem 3\u0026thinsp;=\u0026thinsp;semi-intensive integrated cotton-peanut system;\u003c/p\u003e \u003cp\u003eSystem 4\u0026thinsp;=\u0026thinsp;highly monetized peanut system\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics of the AFB1 concentrations using one sample t-test of raw peanut samples from the four different peanut production systems\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95% confidence interval\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSigma\u003c/p\u003e \u003cp\u003e(2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe AFB1 contents presented in the table are expressed in \u0026micro;g /kg;\u003c/p\u003e \u003cp\u003esystem 1\u0026thinsp;=\u0026thinsp;peanut system with a low level of resources;\u003c/p\u003e \u003cp\u003esystem 2\u0026thinsp;=\u0026thinsp;subsistence system integrating peanuts, maize, and tubers;\u003c/p\u003e \u003cp\u003esystem 3\u0026thinsp;=\u0026thinsp;semi-intensive integrated cotton-peanut system;\u003c/p\u003e \u003cp\u003eSystem 4\u0026thinsp;=\u0026thinsp;Highly monetized peanut system\u003c/p\u003e \u003cp\u003eTo effectively assess the AFB1 concentrations in the peanut kernels collected from various peanut-based production systems, this study utilized regulatory limits and standards for AFB1 established by the European Food Safety Authority (EFSA), the China National Center for Food Safety Risk Assessment (CFSA), and FAO-WHO \u003cem\u003eCodex Alimentarius\u003c/em\u003e. These limits are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Overall, the AFB1 levels recorded in samples from each production system demonstrated varying levels of compliance, depending on the specific regulatory thresholds used for quality control.\u003c/p\u003e \u003cp\u003eRegarding the frequency and percentage of peanut samples contaminated with AFB1 and exceeding the permitted limits, System 1 recorded five samples (35.71%) above the EFSA standard and one sample (7.14%) above the CFSA and \u003cem\u003eCodex Alimentarius\u003c/em\u003e regulations for oilseeds. For the same system, 8 (57.14%) of the samples collected tested positive at AFB1. For production system 2, five of the samples (26.31%) collected showed AFB1 levels exceeding the limit set by the EFSA, while two samples (10.52%) surpassed the limits set by the CFSA and \u003cem\u003eCodex Alimentarius\u003c/em\u003e for oilseeds, with a total of 9 (47.36%) samples testing positive at AFB1. Production system 3 recorded twenty-two samples (81.48%) that tested positive for AFB. However, 14 samples (51.85%) showed levels above the EFSA standard allowed for AFB1, yet none exceeded the CFSA and \u003cem\u003eCodex Alimentarius\u003c/em\u003e regulations for oilseeds. Finally, Production System 4 showed 30 positive samples (100%) for AFB1, with 30 (100%), 17 (56.66%) and 17 (56.66%) samples exceeding EFSA, CFSA, and \u003cem\u003eCodex Alimentarius regulations\u003c/em\u003e for AFB1, respectively.\u003c/p\u003e \u003cp\u003eOf the 90 samples analyzed for AFB1, 76.66% (69 samples) tested positive for AFB1, 60% (54 samples) exceeded EFSA limits; 44.44% (40 samples) were simultaneously above \u003cem\u003eCodex Alimentarius\u003c/em\u003e and CFSA regulations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportions of AFB1 concentrations of raw peanuts samples that exceeded EFSA, CFSA and Codex \u003cem\u003eAlimentarius\u003c/em\u003e regulation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExceeding EFSA regulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExceeding CFSA Regulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExceeding Codex \u003cem\u003eAlimentarius Regulation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProportion of samples positive at AFB1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (35.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (7.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (7.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (57.14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (26.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (10.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (10.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (47.36%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (51.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (81.48%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (56.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (56.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (22.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (22.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (76.66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRegulation for AFB1 content in peanut kernels:\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eEFSA : 2 \u0026micro;g/kg, CFSA : 20 \u0026micro;g/kg, \u003cem\u003eCodex alimentarius\u003c/em\u003e (Oilseed crops) : 15 \u0026micro;g/kg\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe contents of AFB1 presented in the table are in ug/kg;\u003c/p\u003e \u003cp\u003esystem 1\u0026thinsp;=\u0026thinsp;peanut system with a low level of resources;\u003c/p\u003e \u003cp\u003esystem 2\u0026thinsp;=\u0026thinsp;subsistence system integrating peanuts, maize, and tubers;\u003c/p\u003e \u003cp\u003esystem 3\u0026thinsp;=\u0026thinsp;semi-intensive integrated cotton-peanut system;\u003c/p\u003e \u003cp\u003eSystem 4\u0026thinsp;=\u0026thinsp;Highly monetized peanut system\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Agronomic factors associated with AFB1 contamination of samples above 2 \u0026micro;g/kg\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;5 indicates significant variations in the presence of AFB1 levels exceeding 2 \u0026micro;g/kg based on the peanut variety collected (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), underscoring the critical influence of variety on contamination. The Manipintar variety is of particular concern, with 61.1% of its samples exhibiting AFB1 levels above 2 \u0026micro;g/kg, whereas the Peau-lisse and Siksa varieties generally show levels below this threshold. Conversely, the cropping system (monoculture vs. polyculture) did not significantly influence contamination at a threshold above 2 \u0026micro;g/kg AFB1 (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eCrop precedents (particularly cassava, soybean, sweet potato, and yam) and fertilization practices also played a decisive role. A significant impact was observed for the absence of fertilizer use, with 86.1% of such samples having AFB1 levels above 2 \u0026micro;g/kg. The application of phytosanitary products helped to mitigate this contamination, as only 16.7% of samples from growers who utilized them had AFB1 levels exceeding 2 \u0026micro;g/kg. Finally, the type of drying and the type of storage bag demonstrated interesting, albeit less pronounced, trends. These findings collectively indicate that specific agronomic practices employed can influence both AFB1 contamination and content. These results highlight the necessity for careful management of cultivated varieties and agronomic practices to minimize AFB1 contamination.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTableau 5\u003c/strong\u003e \u003cp\u003eAgronomic factors associated with AFB1 contamination of samples above 2 \u0026micro;g/kg\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;90\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 \u0026micro;g /kg\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;36\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 \u0026micro;g /kg\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;54\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eVariety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManipintar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (42.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeau lisse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiksa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (3.70%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCropping system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonoculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (51.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (57.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolyculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (42.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ePrevious crop of the production site of the collected sample\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePeanut\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (87.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCotton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMaize\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (47.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (59.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (35.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35 (64.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSweet potato\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (28.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (71.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 (85.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSoybean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (8.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.020*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (91.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 (85.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCassava\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (7.41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (69.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50 (92.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eType of fertilizer used\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (63.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMineral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrganic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1.85%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrganic and mineral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (5.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1.85%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse of crop protection products during the field phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (37.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (62.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDrying method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSun drying with dryer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (7.78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (1.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSun drying without dryer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (92.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (98.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePrecipitation during the drying phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMoisture content control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraditional (Sound of kernels)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMoisture meter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eType of storage bag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolypropylene bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (37.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJute bag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (37.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolyethylene bags\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse of chemical or natural substances for conservation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (13.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (87.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e\u0026nbsp;n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003e2 *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/br\u003e\u003cp\u003e \u003cb\u003e3.3 Assessment of the risk of exposure and hepatocarcinoma associated with the consumption of peanuts contaminated with AFB1\u003c/b\u003e \u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the estimated risks of exposure and liver cancer for peanut-consuming populations, stratified by age group and the origin of the consumed peanut (peanut production system).\u003c/p\u003e \u003cp\u003eFor peanut samples from production system 1, the Estimated Daily Intakes (EDI) of AFB1 were 20.34, 13.28, 4.70, 2.95, and 2.00 ng/kg body weight/day for infants, toddlers, children, adolescents, and adults, respectively. The corresponding Margins of Exposure (MOE) were 9.54, 14.61, 41.28, 65.74, and 96.69, respectively. With a mean potency of 0.04594, the estimated cancer risks were 0.93, 0.61, 0.22, 0.13, and 0.09 cases/100,000 people/year, respectively.\u003c/p\u003e \u003cp\u003eIn production system 2, the EDI values were 23.35, 15.40, 5.45, 3.42, and 2.32 ng/kg body weight/day for infants, toddlers, children, adolescents, and adults, respectively. The MOE values for this system were 546.88, 837.41, 2365.25, 3766.33, and 5539.72. Maintaining the same average potency (0.04594), the corresponding cancer risks were 1.08, 0.71, 0.25, 0.16, and 0.11 cases/100,000 people/year for the same age categories.\u003c/p\u003e \u003cp\u003eFor System 3, the EDI values for infants, toddlers, children, adolescents, and adults were 14.18, 9.26, 3.28, 2.06, and 1.40 ng/kg body weight/day, respectively. The MOE values recorded were 14.73, 22.55, 63.69, 101.42, and 149.16, respectively. With the average potency remaining constant, the estimated cancer risks were 0.65, 0.43, 0.15, 0.09, and 0.06 cases/100,000 people/year, respectively.\u003c/p\u003e \u003cp\u003eFinally, for Production System 4, the estimated daily intake values for infants, toddlers, children, adolescents, and adults were 1.58, 0.94, 0.35, 0.20, and 0.15 ng/kg bw/day, respectively. The MOE values recorded were 253.16, 425.53, 1142.85, 2000.00, and 2666.67, respectively. While the average potency was consistent with other regions, the cancer risks were 6.89, 4.50, 1.59, 1.00, and 0.68 cases/100,000 people/year, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk evaluation for AFB1 via consumption of raw peanuts produced in the different production systems\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge range\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage weight (Kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEstimated daily intake (EDI) (ng/kg body weight/day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMargin of Exposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCancer risk (Cases/100000 people/year)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSystem 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdolescents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSystem 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e546.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e837.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2365.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdolescents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3766.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5539.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSystem 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdolescents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSystem 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToddler\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdolescents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003cp\u003e1µg = 1000 ng; Average potency = 0.04594;\u003c/p\u003e\n\u003cp\u003esystem 1\u0026thinsp;=\u0026thinsp;peanut system with a low level of resources;\u003c/p\u003e \u003cp\u003esystem 2\u0026thinsp;=\u0026thinsp;subsistence system integrating peanuts, maize, and tubers;\u003c/p\u003e \u003cp\u003esystem 3\u0026thinsp;=\u0026thinsp;semi-intensive integrated cotton-peanut system;\u003c/p\u003e \u003cp\u003eSystem 4\u0026thinsp;=\u0026thinsp;Highly monetized peanut system\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1. AFB1 content in peanuts kernels from different production systems\u003c/h2\u003e \u003cp\u003eOf the 90 peanut samples (intended for human consumption) collected from the four identified peanut-based production systems in Cameroon, 76.66% tested positive for AFB1. Our observations are almost similar to those of Abia et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who obtained 97% of peanut samples contaminated with AFB1 in Cameroon. Also within Cameroon, Kana et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) reported that 100% of local peanut flour samples intended for animal feed were contaminated with aflatoxins. In a study simultaneously conducted in eastern Democratic Republic of Congo (DRC) (Central African sub-region) and Burundi (East Africa), Udomkun et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported that 100% of the peanut samples collected were contaminated with aflatoxins. In Nigeria, which borders Cameroon, 64% of peanut samples were reported positive for AFB1 (Ezekiel et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while in North Africa, specifically Algeria, Ait Mimoune et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) recorded 57% of peanut samples contaminated with AFB1. Substantially similar results were reported on 55.43% of peanut samples from the Lusaka market in Zambia (Bumbangi et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExamining global regulations for Aflatoxin B1, 60% of our samples showed AFB1 levels exceeding the maximum limit allowed by the EU (2 \u0026micro;g/kg). Contamination levels above EU regulations for aflatoxins were previously reported in 69.4% of peanut samples in the DRC (Udomkun et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, 22.22% of our samples had AFB1 levels above the \u003cem\u003eCodex Alimentarius\u003c/em\u003e standard for oilseeds. This percentage is relatively lower than the 42% (491/1168) of peanut samples above the \u003cem\u003eCodex Alimentarius\u003c/em\u003e, as reported by Jallow et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAflatoxin B1 concentrations across all samples for each production system ranged from 0 to 57.14 \u0026micro;g/kg, with an overall average of 10.94 \u0026micro;g/kg. For comparison, average AFB1 levels of 95.9 \u0026micro;g/kg were reported in Tanzania by Seetha et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and to 29.3 \u0026micro;g/kg in the DRC (Udomkun et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In Mali, Burkina Faso and Niger, mean aflatoxin levels of 115, 277, and 628 \u0026micro;g/kg were reported, respectively (Falade et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Ethiopia, aflatoxin levels ranging from 15 to 11 900 \u0026micro;g/kg have been reported by Chala et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); while in Pakistan Asghar et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported an average of 2.37 \u0026micro;g/kg of AFB1 in their peanut samples. Focusing specifically on production systems, the variable AFB1 values observed in samples from each system confirm that growers ' knowledge, perceptions, and agronomic practices within these systems contribute to either increasing or reducing kernel contamination by toxigenic \u003cem\u003eAspergillus flavus\u003c/em\u003e and \u003cem\u003eparasiticus\u003c/em\u003e, and consequently, consumer exposure to aflatoxin B1. Our observations align with those of Akello et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) during a study conducted in Zambia as part of the evaluation of conservation agriculture practices implemented in several peanut-based production systems. This highlights the need to explain the observed differentials in kernel contamination by AFB1.\u003c/p\u003e \u003cp\u003eOverall, all investigated peanut production systems recorded average AFB1 concentration exceeding 2 \u0026micro;g/kg (EU regulatory limit). The highly monetized traditional peanut system exhibited the most contaminated samples (26.37 \u0026micro;g/kg), significantly higher than the subsistence or low resources peanut system (3.57 \u0026micro;g/kg), the peanut system integrating maize and tubers (4.14 \u0026micro;g/kg), and the semi-intensive system integrating peanut and cotton (2.49 \u0026micro;g/kg). In Zambia, average total aflatoxin levels of 110, 99, and 87 ug/kg were reported by Akello et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in peanut production basins involving the practice of agroforestry (peanut in association with \u003cem\u003eGliricidia sepium\u003c/em\u003e), conventional tillage, and a lack of conservation agriculture techniques, respectively. For these two reported results, the variations can be justified by a set of agronomic practices applied in the different systems, which confirms the assertions of many studies conducted on the link between agronomic practices and mycotoxin contamination (Torres et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Asare Bediako et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Another explanation for these variations in AFB1 content can be justified by the varieties grown in each production system. Recently, during a survey of peanut-producing communities in Cameroon, Ntsoli et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) highlighted, for instance, that the Manipintar variety, which is widely used in the highly monetized traditional peanut system, has a very high level of susceptibility to mold contamination. Numerous studies consistently demonstrate differences in resistance levels to mycotoxicogenic fungal contamination and associated mycotoxins for many crops (Girdthai et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010a\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Hamidou et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rose et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Waliyar et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). With this in mind, and based on our aforementioned results, it is evident to conclude that varietal resistance represents a primary approach in reducing aflatoxin contamination When combined with effective pre- and post-harvest methods, it significantly minimizes the risk of aflatoxin contamination (Pandey et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Risks of hepatocarcinoma from peanut consumption\u003c/h2\u003e \u003cp\u003eThe risks of hepatocellular carcinoma associated with food consumption crucial predictors for assessing population exposure to food contaminants, particulary mycotoxins and, in our case, aflatoxin B1. This assessment is especially critical given the strategic importance of peanut (in terms food security, nutritional intake, and soil fertility management) within agrarian systems in arid and semi-arid tropics. The parameters of this hepatocellular carcinoma risk assessment varied according to the aflatoxin B1 concentrations recorded in peanut kernels (intended for human consumption) from each production system. Based on data concerning daily peanut consumption in Cameroon, and average weights by age category, estimated daily intakes ranged from 1.40 to 150.02 ng/kg body weight/day. However, our calculated daily doses considerably lower than those of another study conducted in Cameroon by Bouelet Ntsama et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), with found total daily intake (TDI) values ranging from 23 to 1000 ng/kg body weight/day for total aflatoxins in peanuts. Despite these differences, our estimated daily intakes (EDI) are well below 1000 ng/kg body weight/day, a level reported to cause adverse effects in consumer health and lead to diseases linked to the consumption of aflatoxin- contaminated food (Wu and Khlangwiset, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Adetunji et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Nonetheless, regular consumption of even slightly mycotoxin-contaminated foods does preclude bioaccumulation in human or animal biological tissues, which inherently carries risks associated with mycotoxin-related diseases. This phenomenon has been extensively demonstred in numerous published works (Escriv\u0026aacute; et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Castell et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the consumption of peanuts these different production systems could potentially lead to significant aflatoxin B1 exposure, posing harmful risks to Cameroonian consumers across various age groups (infants, toddlers, children, adolescents, and adults). Similar conclusions were drawn by Kortei et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003ea) and Akello et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) during their respective research on peanuts in Ghana and Zambia.\u003c/p\u003e \u003cp\u003eSimilarly, the calculated margins of exposure (MOEs) ranged from 9.54 to 5539.72. These values represent a significant danger to peanut-dependent populations from these production systems, especially considering that a public health concern is typically raised when MOEs fall below 10,000 (JECFA, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; EFSA Panel on Contaminants in the Food Chain et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar observations have been reported for the mycotoxin exposure from the consumption of various foodstuffs, with a MOE values not reaching 10,000 for aflatoxin-contaminated peanut consumption in Malaysia (Leong et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Taiwan (Wang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Indonesia (Nugraha et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), China (Ding et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Qin et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Nigeria (Adetunji et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ezekiel et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Zambia (Akello et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Musawa et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding the hepatocellular carcinoma risks associated with the consumption of peanuts from Cameroon's production systems, estimates ranging from 0.06 to 6.89 cancer cases/100,000 people/year are forecast. Our forecasts are in line with those of numerous other studies carried out. For instance, in China, between 0.003 and 0.17 cancer cases/100,000 people/year have been reported in their studies by Ding et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) in relation to the consumption of peanuts contaminated with AFB1. Wang et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) estimated between 0.0007 and 0.2713 cancers/100,000/year related to the consumption of aflatoxin-contaminated peanuts and peanut products. Qin et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) during a spatial assessment of aflatoxin exposure in China, reported estimates of 0.000 to 0.851 liver cancer cases/100,000/year. On the other hand, Akello et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) report risks between 0.334 and 27.308 cancer cases/100,000 people/year in peanut production systems in Zambia, depending on the season, the location of cultivation, and the different age groups. By broadening comparisons on other nuts, Samimi et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on hazelnuts imported from eastern Azerbaijan, report liver cancer risks of 0.03 cases/100,000 people/year in adults, compared to 0.11 cases/100,000/year in children.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study is the first report on the probabilistic assessment of the risk of exposure to aflatoxin B1 in peanuts-based production systems in Cameroon. The margins of dietary exposure to aflatoxin B1 from peanut consumption are alarming. In addition, there is a potential risk due to peanut consumption, associated with aflatoxin B1-induced cellular hepatocarcinoma. As such, aflatoxin B1 contamination in peanuts should be reduced to ensure food safety. This work highlights the need to establish risk management strategies and set (regulatory) guidelines for peanut cultivation (pre- and post-harvest) in the different production systems involved in peanut production to prevent contamination, followed by regular monitoring of heavily consumed foodstuffs, especially peanut. Additionally, in the future a cumulative risk assessment from exposure to multiple mycotoxins should be considered, particularly in the population infected with hepatitis B and C viruses, to estimate the total burden of mycotoxins on human health.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the members of the Crop Sciences Department for their scientific guidance. Thanks\u003cstrong\u003e,\u003c/strong\u003e are also due to the members of the Animal Health Laboratory of the Faculty of Agronomy and Agricultural Sciences of the University of Dschang, especially Pr Ngoula Ferdinand and Dr Nguedia Dongmo Arius for their collaboration. The authors also thank the agricultural engineers Etame Kossi Georges, Ngalle Tchatcho Freddy and Mambale Maakte Ombretta for acting as guides and facilitating access to producers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePGN\u003c/strong\u003e conceived and performed the experiments, sample collection, aflatoxin analysis, data analysis and wrote the manuscript. \u003cstrong\u003eMABB\u003c/strong\u003e helped conceive the experiments and prepare the manuscript. \u003cstrong\u003eIDK\u003c/strong\u003e was responsible for aflatoxin analysis and prepare the manuscript.\u003cstrong\u003e\u0026nbsp;GAMM\u003c/strong\u003e was responsible for aflatoxin analysis and prepare the manuscript. \u003cstrong\u003eRWT\u003c/strong\u003e helped conceive the experiments and prepare the manuscript. \u003cstrong\u003eAY\u003c/strong\u003e conceived the original study and supervised the work. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo application.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare consent for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbia WA, Warth B, Sulyok M, Krska R, Tchana AN, Njobeh PB, Dutton MF, Moundipa PF (2013) Determination of multi-mycotoxin occurrence in cereals, nuts and their products in Cameroon by liquid chromatography tandem mass spectrometry (LC-MS/MS). 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World Mycotoxin J 15:171\u0026ndash;186\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang W, Liu Y, Liang B, Zhang Y, Zhong X, Luo X, Huang J, Wang Y, Cheng W, Chen K (2020) Probabilistic risk assessment of dietary exposure to aflatoxin B1 in Guangzhou, China. Sci Rep 10:7973\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-safety-and-risk","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Safety and Risk](https://www.springer.com/journal/40550)","snPcode":"40550","submissionUrl":"https://submission.nature.com/new-submission/40550/3","title":"Food Safety and Risk","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aflatoxin B1, Hepatocellular carcinoma, Margin of exposure, Peanut production systems, Risk assessment, Cameroon","lastPublishedDoi":"10.21203/rs.3.rs-6727619/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6727619/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAflatoxin contamination in peanuts poses a significant health risk to consumers due to the carcinogenic nature of these toxins. In this study, the concentration of Aflatoxin B1 (AFB1) in peanut kernels and the associated risk of hepatocarcinoma risk were evaluated across different age groups within the Cameroonian population. This assessment was based on samples from distinct peanut production systems located in the Adamawa, Centre, and North regions of Cameroon. AFB1 concentrations in raw peanut samples (n\u0026thinsp;=\u0026thinsp;90) were analyzed using an ELISA method. The results revealed varying frequencies of AFB1 contamination: 57.17% in low-resource peanut production systems (System 1), 47.36% in subsistence production systems integrating peanut, maize, and roots/tubers (System 2), 81.48% in semi-intensive integrated cotton-peanut production systems (System 3), and 100% in highly monetized peanut production systems (System 4). Correspondingly, the average AFB1 concentrations for these systems were 3.57, 4.14, 2.49, and 26.37 \u0026micro;g/kg, respectively. Notably, these AFB1 concentrations (especially those exceeding 2 \u0026micro;g/kg) were consistently linked to agronomic factors such as crop variety, previous field cultivation, fertilization practices, the application of phytosanitary products, and the type of storage bag employed. For all age categories, the mean exposure to AFB1 via peanut consumption was estimated to range between 1.40 and 150.02 ng/kg bw/day, resulting in a margin of exposure (MOE) of 1.40 to 5539.72. The average estimated cancer risk due to AFB1 exposure ranged from 0.06 to 6.89 cases/100,000 people/year. This study offers novel insights into the probabilistic risk assessment and potential health impact of AFB1 in peanuts from existing peanut production systems in Adamawa, Centre, and North, Cameroon. These findings can serve as a foundation for developing strategic mitigation measures tailored to different production systems, thereby promoting peanut production in alignment with global standards and contributing to the achievement of crucial food security objectives.\u003c/p\u003e","manuscriptTitle":"Occurrence of aflatoxin B1: link between agricultural practices and estimation of risks to human health in peanut production systems across Adamawa, Centre and North regions of Cameroon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 06:22:33","doi":"10.21203/rs.3.rs-6727619/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-09T10:22:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-08T07:42:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-06T21:25:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269558634637347459942843732990859033851","date":"2025-06-18T12:55:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82764025280813201985201683710212474465","date":"2025-06-18T12:19:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276337889534730684653105271171342933863","date":"2025-06-18T11:02:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"175083116887454419170027880826659430864","date":"2025-06-16T06:47:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257874879321515021569362427248982050661","date":"2025-06-13T21:49:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115778734958320543436901333942794401168","date":"2025-06-13T12:27:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-13T10:07:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-28T03:21:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-28T03:17:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Safety and Risk","date":"2025-05-22T19:45:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-safety-and-risk","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Safety and Risk](https://www.springer.com/journal/40550)","snPcode":"40550","submissionUrl":"https://submission.nature.com/new-submission/40550/3","title":"Food Safety and Risk","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aa212d7f-81db-4e32-915e-9bc77065fc95","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:15:12+00:00","versionOfRecord":{"articleIdentity":"rs-6727619","link":"https://doi.org/10.1186/s40550-025-00127-9","journal":{"identity":"food-safety-and-risk","isVorOnly":false,"title":"Food Safety and Risk"},"publishedOn":"2025-12-08 15:59:16","publishedOnDateReadable":"December 8th, 2025"},"versionCreatedAt":"2025-06-18 06:22:33","video":"","vorDoi":"10.1186/s40550-025-00127-9","vorDoiUrl":"https://doi.org/10.1186/s40550-025-00127-9","workflowStages":[]},"version":"v1","identity":"rs-6727619","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6727619","identity":"rs-6727619","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}