**4. Results**

### **4.1. Demographics and socio-economic results**

Socio-demographic information, knowledge of AF on peanut and farming practices were collected during the survey. Age of the respondents ranged from 35 to 55 years old, and over 55 years old (Table 1). Peanut production is done mostly by men in Kandi (63.3%), Sa‐ valou (100%), and in Abomey-Bohicon (54.4%). A large number of peanut producers in Be‐ nin have not received any formal education, and have never heard of AF contamination of peanut.

Most respondents have no formal education. A large number is found in Kandi with 43.3% (13) literates. Over 9 respondents who received a formal education in Savalou, only 3.3% (1) continued to secondary school in Abomey-Bohicon, 36.7% (11) had primary education and only 6.7% (2) attended secondary school (Table 1).

the second group (46.7%); In Savalou, the majority (53.3%) is in group 1. More than half of

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The majority of the respondents own their land in Kandi (86.7%) and Savalou (60%), while

Income levels for most farmers in Kandi (33.3%) are less than \$350.14, and between \$700.28 and \$1,400.56. Half of the producers in Savalou an income level between to generate an in‐ come level to\$350.14 and \$700.28, while in Abomey, approximately 60.0% earn less than

**Aflatoxin Knowledge and Identification:** Very few respondents know about AF contami‐ nation of food. As Kaaya and Warren (2005) reported, a large number of producers, traders and even consumers are not aware of food contamination with AF. When respondents were asked about the criteria used to identify AF contaminated peanut, some of them reported that they could identify spoiled or contaminated crops by the color or the shape; common colors are black, brown, white dust and greenish. Respondents suspect also any nut that are

When asked if they had ever been sick from ingestion of AF contaminated peanut, most of the respondents' answers were negative. There is no report of diseases related to AF; how‐ ever, it was reported that important consumption of peanut could affect consumers' health (Table 2). About 27.78% (Kandi), 43.33% (Savalou) and 47.78% (Abomey) of respondents re‐ ported that they were affected by diseases such as malaria, diarrhea and coughing, due to a large and frequent consumption of peanut. This may show limited knowledge of the health

Of 90 farmers interviewed in Benin, about 95.6% dry peanut immediately after harvesting, and only 10% sort peanut before selling. However, the remaining farmers explained that not only it is time consuming to sort peanut but also, it reduces peanut quantity by 5 percent on average. Nevertheless, when peanut samples were tested for AF, results indicated that 91.5% of the samples tested were below the European standard (4 ppb), and only 8.5% were

During the survey, a number of respondents (78%) stated that they store their products for approximately 2 to 6 months or longer if market price is not favorable. In the northern re‐ gion (Kandi), this period can exceed 6 months (up to 12 months) because there is only one

**Aflatoxin level:** Distribution of AF levels for farmers samples are shown in Table 3. Based on European standards, we observe that a large number of the samples tested (91.5%) have a concentration level of less than 4 parts per billion (ppb). About 93.2% of the samples have a level less than the tolerance limit (15 ppb) set by the Food and Drug Administration (FDA). Based on WHO standards, the majority of the samples (96.6%) were safe for consumption, while 3.4% exceeded 20 ppb. In addition, most of the samples (98.3%) were less than the per‐

the respondents in Abomey (53.3%) have been farming for at least 30 years.

in Abomey a large percent (83.3%) rent land to produce peanut.

broken or attacked by insects to be contaminated by AF.

effects of consumption of AF contaminated peanut.

\$350.14.

above that limit.

growing season each year.

missible level in animal feed (100 ppb).


**Table 1.** Socio-demographics characteristics of peanut producers in Kandi, Savalou and Abomey-Bohicon.

Years of experience were divided into 3 groups: less than 15 years (group one), between 15 and 30 years (group two) and over 30 years (group three). In Kandi, most farmers belong to the second group (46.7%); In Savalou, the majority (53.3%) is in group 1. More than half of the respondents in Abomey (53.3%) have been farming for at least 30 years.

Most respondents have no formal education. A large number is found in Kandi with 43.3% (13) literates. Over 9 respondents who received a formal education in Savalou, only 3.3% (1) continued to secondary school in Abomey-Bohicon, 36.7% (11) had primary education and

Under 35 8 26.7 14 46.7 8 26.7 36-55 20 66.7 9 30.0 38 43.3 over 55 2 6.7 7 23.3 8 26.7

Female 11 36.7 0 0 5 45.6 Male 19 63.3 30 100 25 54.4

No formal education 17 56.7 23 76.7 19 63.3 Primary school 13 43.3 7 23.3 11 36.7 Secondary school 5 16.7 1 3.3 2 6.7

0-15 9 30.0 16 53.3 7 23.3 16-30 14 46.7 6 20.0 7 23.3 Over 30 7 23.3 8 26.7 16 53.3

Owner 26 86.7 18 60.0 5 16.7 Renter 4 13.3 5 16.7 25 83.3

\$0-\$350.14 10 33.3 13 43.3 18 60.0 \$350.14 - \$700.28 3 10.0 15 50.0 9 30.0 \$700.28 - \$1,400.56 10 33.3 2 6.7 2 6.7 Over \$1,400.56 7 23.3 0 0.0 1 3.3

**Table 1.** Socio-demographics characteristics of peanut producers in Kandi, Savalou and Abomey-Bohicon.

Years of experience were divided into 3 groups: less than 15 years (group one), between 15 and 30 years (group two) and over 30 years (group three). In Kandi, most farmers belong to

**Kandi Savalou Abomey-Bohicon**

Number % Number % Number %

only 6.7% (2) attended secondary school (Table 1).

384 Aflatoxins - Recent Advances and Future Prospects

Age groups

Gender

Education

Years of experience

Land tenure

Income levels (month)

The majority of the respondents own their land in Kandi (86.7%) and Savalou (60%), while in Abomey a large percent (83.3%) rent land to produce peanut.

Income levels for most farmers in Kandi (33.3%) are less than \$350.14, and between \$700.28 and \$1,400.56. Half of the producers in Savalou an income level between to generate an in‐ come level to\$350.14 and \$700.28, while in Abomey, approximately 60.0% earn less than \$350.14.

**Aflatoxin Knowledge and Identification:** Very few respondents know about AF contami‐ nation of food. As Kaaya and Warren (2005) reported, a large number of producers, traders and even consumers are not aware of food contamination with AF. When respondents were asked about the criteria used to identify AF contaminated peanut, some of them reported that they could identify spoiled or contaminated crops by the color or the shape; common colors are black, brown, white dust and greenish. Respondents suspect also any nut that are broken or attacked by insects to be contaminated by AF.

When asked if they had ever been sick from ingestion of AF contaminated peanut, most of the respondents' answers were negative. There is no report of diseases related to AF; how‐ ever, it was reported that important consumption of peanut could affect consumers' health (Table 2). About 27.78% (Kandi), 43.33% (Savalou) and 47.78% (Abomey) of respondents re‐ ported that they were affected by diseases such as malaria, diarrhea and coughing, due to a large and frequent consumption of peanut. This may show limited knowledge of the health effects of consumption of AF contaminated peanut.

Of 90 farmers interviewed in Benin, about 95.6% dry peanut immediately after harvesting, and only 10% sort peanut before selling. However, the remaining farmers explained that not only it is time consuming to sort peanut but also, it reduces peanut quantity by 5 percent on average. Nevertheless, when peanut samples were tested for AF, results indicated that 91.5% of the samples tested were below the European standard (4 ppb), and only 8.5% were above that limit.

During the survey, a number of respondents (78%) stated that they store their products for approximately 2 to 6 months or longer if market price is not favorable. In the northern re‐ gion (Kandi), this period can exceed 6 months (up to 12 months) because there is only one growing season each year.

**Aflatoxin level:** Distribution of AF levels for farmers samples are shown in Table 3. Based on European standards, we observe that a large number of the samples tested (91.5%) have a concentration level of less than 4 parts per billion (ppb). About 93.2% of the samples have a level less than the tolerance limit (15 ppb) set by the Food and Drug Administration (FDA). Based on WHO standards, the majority of the samples (96.6%) were safe for consumption, while 3.4% exceeded 20 ppb. In addition, most of the samples (98.3%) were less than the per‐ missible level in animal feed (100 ppb).


regions with warm and humid climates (Dohlman, 2003; Farombi, 2006). The present study demonstrates that farmers in the most humid area (Abomey-Bohicon) generate lower net re‐

August) -Abomey (Plant in March and Harvest in July)

Yield (Kg) 4,500 4,455 3,600 3,564 2,400 2,376

Revenue (\$) 1,890.75 1,871.85 1,512.60 1,497.48 1,008.39 998.31

Labor costs (\$) 174.69 184.14 174.69 184.14 174.69 184.14

Total variable costs (\$) 259.29 268.74 213.93 223.38 200.85 210.30

Income above variable costs (\$) 1,631.46 1,603.11 1,298.70 1,274.10 807.57 788.04

Net returns (\$) 1,626.54 1,598.16 1,294.26 1,269.69 802.62 783.09

Break-even price (\$/kg) 0.06 0.06 0.06 0.06 0.08 0.09

NPV (6%) 5,714 5,614 4,536 4,450 2,811 2,743

PI (6%) 1,060.00 1,042.42 1,134.02 1,112.44 522.46 509.75

IRR 95.13 93.47 10.08 98.79 46.88 45.74

**Table 4.** Estimated annual costs and returns budget for a large size farm (3ha) in each region, assuming that there is

Table 5 summarizes the costs and returns generated by farmers after 6 months of storage. Following Hell et al. (2000) and Kaaya and Kyamuhangire (2006) reports, who indicated that duration of storage positively influences fungal growth and AF production in food crops, this paper hypothesized that peanut stored for more than 6 months have a negative effect on


no change in price when farmers sort peanut and using the following peanut production practices

Total fixed costs (\$) 4.92 4.92 4.41 4.41 4.92 4.92

Kandi Savalou Abomey

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Not sorted Sorted Not sorted Sorted Not sorted Sorted



turns (\$783.09).



**Table 2.** Producers report sickness related to aflatoxin in three regions of Benin, and their characteristics



**Table 3.** Distribution of aflatoxin level for farmers based on standards (%).

#### **4.2. Enterprise budget**

Enterprise budgets for each region studied are shown in table 4. AF contamination reduces farmers' net returns. Peanut production is more profitable in Kandi than in the other re‐ gions. Table 4 shows that net returns above total expenses are \$1,626.54, \$1,294.26, and \$802.62 in Kandi, Savalou and Abomey-Bohicon, repectively. Estimated costs and returns budgets for sorting are also reported in table 4. Results show that there is a decrease in reve‐ nue and returns when farmers decide to sort peanut to improve quality. In addition, there is a decrease in yield (5%) and an increase in labor cost due to sorting, which in turn reduce farmers revenue and net returns. Previous studies conducted on the relationship between AF contamination and environmental conditions showed that high levels of AF are found in regions with warm and humid climates (Dohlman, 2003; Farombi, 2006). The present study demonstrates that farmers in the most humid area (Abomey-Bohicon) generate lower net re‐ turns (\$783.09).

**Region (N = 90 per region) Yes No**

Kandi 25 27.8 65 72.2

Savalou 39 43.3 51 56.7

Abomey 43 47.8 47 52.2

Dry peanut after harvesting 86 95.6 4 4.4

Sort peanut 9 10.0 81 90.0

Consume bad\* grains 0 0.0 90 100.0

Give bad\* grains to your animal 10 10.0 80 90.0

**Table 2.** Producers report sickness related to aflatoxin in three regions of Benin, and their characteristics

Less than 91.5 93.2 96.6 98.3 Greater than 8.5 6.8 3.4 1.7

USA standards 15 ppb

Enterprise budgets for each region studied are shown in table 4. AF contamination reduces farmers' net returns. Peanut production is more profitable in Kandi than in the other re‐ gions. Table 4 shows that net returns above total expenses are \$1,626.54, \$1,294.26, and \$802.62 in Kandi, Savalou and Abomey-Bohicon, repectively. Estimated costs and returns budgets for sorting are also reported in table 4. Results show that there is a decrease in reve‐ nue and returns when farmers decide to sort peanut to improve quality. In addition, there is a decrease in yield (5%) and an increase in labor cost due to sorting, which in turn reduce farmers revenue and net returns. Previous studies conducted on the relationship between AF contamination and environmental conditions showed that high levels of AF are found in

WHO standards 20 ppb

Animal standards 100 ppb

Producers report sickness related to aflatoxin in three regions of Benin, 2007

386 Aflatoxins - Recent Advances and Future Prospects

Characteristics

\* Bad: discolored or contaminated


**4.2. Enterprise budget**

**Aflatoxin limit** European standards

4 ppb

**Table 3.** Distribution of aflatoxin level for farmers based on standards (%).


Number % Number %


**Table 4.** Estimated annual costs and returns budget for a large size farm (3ha) in each region, assuming that there is no change in price when farmers sort peanut and using the following peanut production practices

Table 5 summarizes the costs and returns generated by farmers after 6 months of storage. Following Hell et al. (2000) and Kaaya and Kyamuhangire (2006) reports, who indicated that duration of storage positively influences fungal growth and AF production in food crops, this paper hypothesized that peanut stored for more than 6 months have a negative effect on farmers net returns. Since consumers may perceive that peanut quality will deteriorate dur‐ ing storage, due to AF contamination, they might lower price. Results show that AF growth increases with the length of storage and lowers revenue from peanut production, due to lower peanut quality.

Storage time Change in price Price Quantity Revenue Net returns (months) % (\$/kg) (kg) (\$) (\$) 0-2 15 0.48319 4,455.00 2,152.62 1888.38 2-4 10 0.46219 4,410.45 2,038.45 1774.21 4-6 5 0.44118 4,366.35 1926.33 1662.09 6-8 -5 0.39916 4,322.68 1725.43 1461.19 8-10 -10 0.37815 4,279.46 1618.28 1354.04 10-12 -15 0.35714 4,236.66 1513.09 1248.85

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Table 6.1. Sensitivity analysis for peanut budget by changing price and the effect on revenue, and net returns

Table 6.3. Sensitivity analysis for peanut budget by changing price and the effect on revenue and net returns

**Table 6.** Sensitivity analysis for large farms (3 ha) gross margins, assuming that price varies through sorting and

Results are also confirmed further. Figure 3 presents the tornado graphs for net returns for farmers who sort peanut before marketing. Price is the most important variable in the re‐ gression analysis. Drying has also a positive impact on farmers' revenue and net returns,

Storage time Change in price Price Quantity Revenue Net returns (months) % (\$/kg) (kg) (\$) (\$) 0-2 15 0.48 3564.00 1722.10 1503.77 2-4 10 0.46 3528.36 1630.76 1412.43 4-6 5 0.44 3493.08 1541.07 1322.74 6-8 -5 0.40 3458.15 1380.35 1162.02 8-10 -10 0.38 3423.56 1294.63 1076.30 10-12 -15 0.36 3389.33 1210.47 992.14 Table 6.2. Sensitivity analysis for peanut budget by changing price and the effect on revenue and net returns (Savalou) Storage time Change in price Price Quantity Revenue Net returns (months) % (\$/kg) (kg) (\$) (\$) 0-2 15 0.48 2376.00 1148.06 942.42 2-4 10 0.46 2352.24 1087.17 881.53 4-6 5 0.44 2328.72 1027.38 821.73 6-8 -5 0.40 2305.43 920.23 714.59 8-10 -10 0.38 2282.38 863.08 657.44 10-12 -15 0.36 2259.55 806.98 601.34

(Kandi)

(Abomey)

storage.

The assumption in this table is that there is a decrease in price by five percent, due to peanut quality. After 6 months of storage, significant differences are observed in product quality and on farmers' income*.* Hence, net returns per hectare above all expenses are reduced.





**Table 5.** Storage impact in each agro-ecological region (large farms 3 ha).

#### **4.3. Risk analysis**

Table 6 displays the results for the risk analysis. As farmers sort their stored product, we assume that an increase in peanut price of 15, 10 and 5 percent is offered over the storage period. Assumptions are shown in table 6.1, table 6.2 and table 6.3. These tables report the simulated effects of change in price and storage duration on farmers' costs and returns. We observe a significant relationship between net returns and price, and also a negative rela‐ tionship between net returns and sorting when farmers sort their peanut. The longer peanut is stored, the smaller is the final quantity due to fungal and AF production; however, for each region, as price increases by 5%, 10%, and 15%, revenue and net returns also increase. Overall, to improve quality of stored peanut, farmers sort peanut which results in an in‐ crease in labor cost, a decrease in yield and higher net returns. This finding confirms that sorting causes economic losses to peanut producers who want to improve peanut quality. Drying has also a positive impact on farmers' revenue and net returns, which shows that farmers have to dry peanut efficiently before selling their products. Further, as storage peri‐ od exceeds 6 months, the enterprise becomes less profitable. It is, therefore, more profitable and less risky, to increase selling price to cover cost of sorting; however, it is more risky for farmers to sort peanut 6 months after harvesting than to sort at harvest.

#### Aflatoxin and Peanut Production Risk and Net Incomes http://dx.doi.org/10.5772/51913 389


farmers net returns. Since consumers may perceive that peanut quality will deteriorate dur‐ ing storage, due to AF contamination, they might lower price. Results show that AF growth increases with the length of storage and lowers revenue from peanut production, due to

The assumption in this table is that there is a decrease in price by five percent, due to peanut quality. After 6 months of storage, significant differences are observed in product quality and on farmers' income*.* Hence, net returns per hectare above all expenses are reduced.

Revenue (\$) 1,796.22 1,440.60 957.98

Income above variable costs (\$) 1,536.90 1,226.27 757.14

Net returns (\$) 1,531.90 1,222.27 752.34

Table 6 displays the results for the risk analysis. As farmers sort their stored product, we assume that an increase in peanut price of 15, 10 and 5 percent is offered over the storage period. Assumptions are shown in table 6.1, table 6.2 and table 6.3. These tables report the simulated effects of change in price and storage duration on farmers' costs and returns. We observe a significant relationship between net returns and price, and also a negative rela‐ tionship between net returns and sorting when farmers sort their peanut. The longer peanut is stored, the smaller is the final quantity due to fungal and AF production; however, for each region, as price increases by 5%, 10%, and 15%, revenue and net returns also increase. Overall, to improve quality of stored peanut, farmers sort peanut which results in an in‐ crease in labor cost, a decrease in yield and higher net returns. This finding confirms that sorting causes economic losses to peanut producers who want to improve peanut quality. Drying has also a positive impact on farmers' revenue and net returns, which shows that farmers have to dry peanut efficiently before selling their products. Further, as storage peri‐ od exceeds 6 months, the enterprise becomes less profitable. It is, therefore, more profitable and less risky, to increase selling price to cover cost of sorting; however, it is more risky for


farmers to sort peanut 6 months after harvesting than to sort at harvest.

**Table 5.** Storage impact in each agro-ecological region (large farms 3 ha).


**4.3. Risk analysis**


Kandi Savalou Abomey

lower peanut quality.

388 Aflatoxins - Recent Advances and Future Prospects

Table 6.1. Sensitivity analysis for peanut budget by changing price and the effect on revenue, and net returns (Kandi)


Table 6.2. Sensitivity analysis for peanut budget by changing price and the effect on revenue and net returns (Savalou)


Table 6.3. Sensitivity analysis for peanut budget by changing price and the effect on revenue and net returns (Abomey)

**Table 6.** Sensitivity analysis for large farms (3 ha) gross margins, assuming that price varies through sorting and storage.

Results are also confirmed further. Figure 3 presents the tornado graphs for net returns for farmers who sort peanut before marketing. Price is the most important variable in the re‐ gression analysis. Drying has also a positive impact on farmers' revenue and net returns, which shows that farmers have to dry peanut efficiently before selling their products. How‐ ever, there is a negative relationship between sorting and net returns. It is evident that when farmers sort peanut, it negatively affects net returns. Similarly, coefficients for storage (-0.03) and other labor variables like harvesting (-0.001) have a negative influence on net returns for each region.

In addition, based on the assumptions used to develop the sensitivity analysis of the NPVs in Table 6, risk is incorporated in NPV at different price levels and at different storage times. Figure 4 shows that NPV for farmers who sort peanut and sell at the normal price is smaller than those who sell sorted peanut at a higher price (5%). It is, therefore, more profitable and less risky, to increase selling price to cover cost of sorting. Tornado graphs above show that there is a significant relationship between price and NPV. As price goes up due to sorting, the NPV also increases; for instance, with a probability of 80%, NPV is 15.24% smaller when farmers sort immediately at harvest (Figure 5). Sorting peanut stored for 6 months is more risky than when farmers sort at harvest;

**Figure 4.** Cumulative probability distribution of the net present value for sorted and non-sorted peanut at varying pri‐

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**Figure 5.** Cumulative probability distribution of the net present value for stored peanut at harvest and six months later.

ces according storage time (no change, 5% increase).

**Figure 3.** Tornado graphs of the net returns of peanut production in each region, assuming that peanut is sorted be‐ fore marketing.

which shows that farmers have to dry peanut efficiently before selling their products. How‐ ever, there is a negative relationship between sorting and net returns. It is evident that when farmers sort peanut, it negatively affects net returns. Similarly, coefficients for storage (-0.03) and other labor variables like harvesting (-0.001) have a negative influence on net returns for

In addition, based on the assumptions used to develop the sensitivity analysis of the NPVs in Table 6, risk is incorporated in NPV at different price levels and at different storage times. Figure 4 shows that NPV for farmers who sort peanut and sell at the normal price is smaller than those who sell sorted peanut at a higher price (5%). It is, therefore, more profitable and less risky, to increase selling price to cover cost of sorting. Tornado graphs above show that there is a significant relationship between price and NPV. As price goes up due to sorting, the NPV also increases; for instance, with a probability of 80%, NPV is 15.24% smaller when farmers sort immediately at harvest (Figure 5). Sorting peanut stored for 6 months is more

**Figure 3.** Tornado graphs of the net returns of peanut production in each region, assuming that peanut is sorted be‐

each region.

fore marketing.

risky than when farmers sort at harvest;

390 Aflatoxins - Recent Advances and Future Prospects

**Figure 4.** Cumulative probability distribution of the net present value for sorted and non-sorted peanut at varying pri‐ ces according storage time (no change, 5% increase).

**Figure 5.** Cumulative probability distribution of the net present value for stored peanut at harvest and six months later.
