**2. Material and methods**

## **2.1. Market participant identification, data and sample collection**

We conducted surveys on AF contamination in peanut in three agro-ecological zones of Be‐ nin. Kandi (North), Savalou (South-east) and Abomey-Bohicon (South) were selected on the basis of their climatic conditions and levels of peanut production (Figure 2). A total of 30 farmers were selected in each of the three peanut producing regions of Benin during the pe‐ riod of May to July 2007. Peanut farmers were identified through the assistance of agricul‐ tural officers in the Ministry of Food and Agriculture (MoFA) and through the help of personnel from the University of Abomey-Calavi, Republic of Benin.

collected in the survey. Furthermore, a simulation of the risk of AF contamination on farm‐ ers' income from the production, storage and trading of peanut was done using the @RISK

Aflatoxin and Peanut Production Risk and Net Incomes

http://dx.doi.org/10.5772/51913

381

software.

**Figure 2.** Map of Benin showing research sites

During the visits to each farm household, farming practices related to grain storage and han‐ dling were observed and documented using information on the survey instrument. Ques‐ tionnaires were administrated to farmers by trained interviewers. Primary data collected included information on demographic and socioeconomic status, farming, post-harvest han‐ dling, storing and sorting practices, scheduled production activities, production level, household revenues and consumption frequency of peanut.

Peanut samples were collected at different post-harvest points and under different storage conditions. The levels of infestation of AF contaminated peanut under farmers' storage and marketing conditions were determined. It has been noted that AF levels vary along the mar‐ keting chain and the level of AF is more pronounced during storage and processing (Awuah et al., 2009).

Samples of 0.800 Kg (= 1.764 pounds) of peanut were taken in the fields and markets from each farmer. These samples were divided into two groups: sorted clean and rejected (bad) nuts. Bad nuts were the ones with discoloration and holes.

#### **2.2. Determination of aflatoxin (AF) level**

Assessment of AF levels was undertaken using the VICAM technique. VICAM is an AF test that produces numerical results using monoclonal antibody-based affinity chromatography. The test can isolate AF β1, β2, ğ1, and ğ2 from feeds, foods, grains, and nuts, and from dairy products.

This test involved observation of post-harvest and handling of peanut, collection of data on management issues related to grain storage and handling, collection of peanut samples, and testing them to detect AF levels. Each farmer's farm or business selected for the study was visited. The frequency of levels of AF found in peanut was used to estimate the probabilities of occurrence of AF.

#### **2.3. Statistical analysis**

Data collected during the survey were entered into an EXCEL spreadsheet and analyzed us‐ ing SAS software package version 9.1. These data were used to develop enterprise budgets for producing peanut. The costs of each business activity were estimated based on the data collected in the survey. Furthermore, a simulation of the risk of AF contamination on farm‐ ers' income from the production, storage and trading of peanut was done using the @RISK software.

**Figure 2.** Map of Benin showing research sites

**2. Material and methods**

380 Aflatoxins - Recent Advances and Future Prospects

et al., 2009).

products.

of occurrence of AF.

**2.3. Statistical analysis**

**2.1. Market participant identification, data and sample collection**

personnel from the University of Abomey-Calavi, Republic of Benin.

household revenues and consumption frequency of peanut.

nuts. Bad nuts were the ones with discoloration and holes.

**2.2. Determination of aflatoxin (AF) level**

We conducted surveys on AF contamination in peanut in three agro-ecological zones of Be‐ nin. Kandi (North), Savalou (South-east) and Abomey-Bohicon (South) were selected on the basis of their climatic conditions and levels of peanut production (Figure 2). A total of 30 farmers were selected in each of the three peanut producing regions of Benin during the pe‐ riod of May to July 2007. Peanut farmers were identified through the assistance of agricul‐ tural officers in the Ministry of Food and Agriculture (MoFA) and through the help of

During the visits to each farm household, farming practices related to grain storage and han‐ dling were observed and documented using information on the survey instrument. Ques‐ tionnaires were administrated to farmers by trained interviewers. Primary data collected included information on demographic and socioeconomic status, farming, post-harvest han‐ dling, storing and sorting practices, scheduled production activities, production level,

Peanut samples were collected at different post-harvest points and under different storage conditions. The levels of infestation of AF contaminated peanut under farmers' storage and marketing conditions were determined. It has been noted that AF levels vary along the mar‐ keting chain and the level of AF is more pronounced during storage and processing (Awuah

Samples of 0.800 Kg (= 1.764 pounds) of peanut were taken in the fields and markets from each farmer. These samples were divided into two groups: sorted clean and rejected (bad)

Assessment of AF levels was undertaken using the VICAM technique. VICAM is an AF test that produces numerical results using monoclonal antibody-based affinity chromatography. The test can isolate AF β1, β2, ğ1, and ğ2 from feeds, foods, grains, and nuts, and from dairy

This test involved observation of post-harvest and handling of peanut, collection of data on management issues related to grain storage and handling, collection of peanut samples, and testing them to detect AF levels. Each farmer's farm or business selected for the study was visited. The frequency of levels of AF found in peanut was used to estimate the probabilities

Data collected during the survey were entered into an EXCEL spreadsheet and analyzed us‐ ing SAS software package version 9.1. These data were used to develop enterprise budgets for producing peanut. The costs of each business activity were estimated based on the data
