Characterization of cropping and storage systems
The study was conducted in five villages in central Tanzania: Njoro in the Manyara region (Kiteto district), and Chitego, Mlali, Moleti, and Laikala in the Dodoma region (Kongwa district). A baseline assessment was conducted in each village during which the primary data was gathered on the cropping systems and livestock production systems, while the secondary data on the agricultural sector, demography, and market information from each district was used to characterize existing farming systems. A total of 312 farmers were recruited in 2013 and the study conducted in 2014 and 2015. The farms were geo-referenced using a geographical positioning system. Rain gauges were installed in each village to monitor rainfall distribution. Typically, this region receives approximately 300 mm rainfall in unfavorable years and 500 mm in favorable years.
Collection of soil samples to investigate Aspergillus species diversity
To identify sources of AFB1 contamination in the field, 312 composite soil samples were collected from each farmer and assayed for Aspergillus spp. in May 2013. Each composite soil sample was generated by mixing soil sub-samples collected from 50 m2 in each farmers’ field. During sampling, each sample area was divided into quarters and samples collected along a diagonal in each quarter. Soil sampling was done along a gradient to capture spore and other fungal propagules dispersal by storm rain water. At each sample station, approximately 5 g of soil was collected from a depth of 2–10 cm. A total of 12 samples per field were subsequently bulked and quartered to generate a composite sample per farmer (Jaime-Gracia and Cotty 2006). These samples were secured in paper bags and stored at 5 °C until further processing.
Isolation and characterization of A. flavus
Two assays involving colony pre-screening to eliminate non-Aspergillus spp. followed by assays for AFB1 production to confirm aflatoxigenicity were conducted to characterize A. flavus isolates (Abbas et al. 2004). The soil samples were air-dried and ground into a fine powder using a pestle and mortar. Ten grams of each soil sample was divided into 3 g portions, generating 3 replicates per sample. Each replicate sample was added to modified Dichloran Rose Bengal Chloramphenicol medium (Sigma-Aldrich, St. Louis, MO, USA) in Petri dishes and incubated for 4–7 days at 25 °C (Horn et al. 1995). Aspergillus species were identified according to Klich and Pitt (1988), and their population densities quantified on soil dry weight basis.
Subsequently, A. flavus was purified from original culture plates and plated on coconut-agar medium to investigate aflatoxin production (Lin and Dianese 1976). Fresh coconut extract was prepared by grinding a 2:1 mixture of distilled water and fresh coconut-flesh in a blender; boiling to skim off the oil, and then filtering through cheesecloth to obtain the fresh filtrate for augmenting the agar (BD Biosciences, Franklin Lakes, NJ, USA). The culture plates were incubated for 4–7 days at 30 °C without light. After 5 days, samples were assayed for presence of AFB1 using UV light (Sudini et al. 2015) and AFB1 production confirmed by thin-layer chromatography (TLC) (Park et al. 1994; Abbas et al. 2004).
Collection of crop produce to study aflatoxin contamination
Representative samples of crop produce were collected at two different times. First, samples were collected from standing crops in fields just before harvest in May/June of 2013 and 2014. Samples were collected along a 50 m transect using an approach similar to that used for soil sample collection. At each sample station, 10–12 cobs/ears of each crop were collected. Depending on field size, samples were pooled and quartered to generate one composite sample of 1 kg, air-dried to a constant weight to reduce moisture, placed in paper bags, and stored at 5 °C until further analysis (Mahuku et al. 2010). Farmers who provided field crop samples also provided stored samples of their crop produce for the study. These stored samples were those from the same fields in which samples of freshly harvested crop produce had been collected previously and stored for at least 5 months, the typical storage duration in the study area. During sample collection, a representative sample was obtained by mixing 10 samples, each weighing approximately 10 g, collected from different parts of each storage bag to constitute 100 g of sample and was used to evaluate AFB1 contamination.
Determination of AFB1 from grains/kernels
The 100 g sub-samples were weighed ground into a fine powder, and two replicate samples of approximately 20 g of each sample were mixed with 100 mL of 70% methanol/distilled water (v/v) containing 0.5% potassium chloride. The mixture was transferred to a 250-mL conical flask, shaken at 300 rpm for 30 min (Gallenkamp Orbital Shaker, CAT # SCM 300 0101, Weiss Technik, Grand Rapids, MI, USA) and filtered through Whatman No. 41 filter paper (GE Healthcare, Little Chalfont, UK). The filtrate was assayed for AFB1 using an in-house indirect competitive enzyme-linked immunosorbent assay (ELISA) (F96 MaxiSorp, Thermo Fisher Scientific, Waltham, MA, USA) at a detection limit of 1 μg/kg and mean recovery of 92.5% (Reddy et al. 2001). The method was validated with naturally contaminated corn reference materials (4.2 and 23.0 μg/kg AFB1, product no. TR-A100, batch no A-C-268 and A-C 271; R-Biopharm AG, Darmstadt, Germany). This method has high reproducibility with mean percentage recovery of 92.5% of AFB1 (Reddy et al. 2001). Briefly, the samples were tested using a polyclonal antibody produced against AFB1-BSA. Alkaline phosphatase-conjugated anti-rabbit antibodies (Sigma-Aldrich) were used as the secondary antibodies, and para-nitrophenyl phosphate (Sigma-Aldrich) was used as a substrate. Colorimetric reaction was measured using an ELISA plate reader (Multiskan reader, Thermo Fisher Scientific) using a 405-nm filter. To further confirm the presence of AFB1 in selected samples, the filtrate was subjected to thin-layer chromatography using silica gel-coated 20 × 20 cm glass plates (Fluka Analytical, Sigma-Aldrich), developed in chloroform: acetone (93:7, v/v) under vapor saturated conditions, and detected directly under long-wave UV light based on fluorescence (Park et al. 1994; Abbas et al. 2004).
Tracking farmer learning and adoption of aflatoxin mitigation technologies
Following the collection of crop and soil samples, intervention activities for mitigation, awareness, and technology promotion were undertaken for 2 years (2013–2014). The mitigation technologies included (1) ventilated drying of groundnuts in the field (the Mandela cork method (ICRISAT 2012), (2) ventilated drying of other grains/kernels on polythene sheets to avoid exposure to soil, (3) hand-sorting of grain/kernels before processing into various food products, (4) minimization of wet shelling, during which pods were soaked for 5–10 min for softening and ease shelling by hand, and (5) ventilated storage of well-dried groundnuts and other kernels/grains in moisture-free, dry wooden pallets. This ventilated drying system allows air to flow through stacked haulms with pods, slowly drying the nuts and preventing the spread of the A. flavus. Focus group discussion, field demonstrations, and farmer learning sessions were organized through the learning-by-doing approach for technology promotion and knowledge dissemination. In June 2015, 188 of the 312 farmers involved in the study were tracked to assess the outcome of farmer learning and adoption of correct post-harvest management practices in grain/kernel handling compliance of AFB1 mitigation practices. Crop samples were obtained to assess the frequency of AFB1 contamination in stored samples to compare with the baseline.
Data analysis
Data from the baseline and farmer learning sessions were coded and subjected to statistical analysis using SPSS version 16 (SPSS, Inc., Chicago, IL, USA), R version 3.1.1 (R Development Core Team 2014), SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA 2013), and STATA version 14. AFB1 levels were tested to determine the statistical significance of differences between various samples using the two-sample t test by considering that samples showed independent assuming unequal variance (Cressie and Whitford 1986). Furthermore, multiple linear regression was performed to identify the effect of each factor associated with AFB1 contamination by controlling for other covariate variables (Dismuke and Lindrooth 2006), enabling differentiation between actual factors and spurious associations. Four dummy variables coded as 1 if the sample was (1) from geocarpic structures, i.e., from (“groundnut-bambara nut dummy”), (2) an oilseed crop, (3) a stored crop sample, and (4) taken after training of farmers, but otherwise coded as 0, were generated and included in the ordinary least squares regression with a sample size of 2485.