Impact of Bauchi State Agricultural Development Programme (BSADP) on the Livelihood of Maize Farmers in Western Agricultural Zone of Bauchi State, Nigeria: 2009

3.0 RESULTS AND DISCUSSION:

3.1 Socio-Economic Characteristics of Respondents

Table 1 revealed the socio-economic characteristics of the respondents; Respondents’ age showed that majority (63.9%) of the farmers in the study area were between 31-50years while 14.8% were below 31years and only 7.7% were above 60 years. The implication of this result is that majority of the farmers are in their active age and can contribute immensely to food production to ensure food security in the study area, the state and the nation at large. This corroborates the findings of Yohanna et al., (2014).Who reported 41years as the mean age of farmers. So: most of the arable crop farmers were in their prime age and are still active farmers that are capable of seeking information on farming. Majority (72.0%) of the respondents were males. This implies that men in the study area were more involved in maize production than the women. In accordance with the prevailing culture, men are to cater for the households needs and may be assisted by other members of the household. This result is in line with the findings of Babalola and Olayemi (2013), who in their study on Determinants of farmers’ preference for sustainable land management, in Ogun State, Nigeria; reported that most (92.0%) farmers are males, which may be attributed to religious and cultural factors. However women should be encouraged by extension agents to participate in agricultural production by the help of a trusted member within the family; where she cannot manage the activities herself. Women are also known to effectively handle some aspect of farming activities along the agricultural value chain. They can therefore be engage in areas like local processing of agricultural produce where they have comparative advantage over men.

Majority (82.2%) of respondents are married, followed by 11.5% who are single, then 5.1% that are widow and 1.3% who are divorcees. The high percentage of married individuals may be attributed to regional factors where religion, norms and culture encourage marriage among citizens. This result is in agreement with the findings of Babalola and Olayemi (2013), who in their study on Determinants of Farmers’ Preference for Sustainable Land Management, in Ogun State, Nigeria. He reported that most (93.8%) of the farmers in the study area are married. Similarly, Ofuaku (2011) found that, married farmers had responsibilities that most be reflected on their farming activities. If marriage is a sign of responsibility, this shows that most of the farmers in this study area are responsible people who are committed to struggle so as to take care of family responsibilities, and this make them increase their level of production.

The results also revealed that 28.80% of maize farmers had attended one form of tertiary education or the other. Next is secondary education with 29.7%, followed by primary education which constituded19.4% and then Qoranic education constituted 16.8%. The high percentage of maize farmers with tertiary education is peculiar to western zone that has high percentage of educated farmers as reported by BSADP in 2006. This finding corroborates Yohanna et al., (2014) who reported that, most farmers had one form of education or another and the preponderance of such educated farmers in the study can influence their information seeking behavior which should be used to boost agricultural production. Findings of this study revealed that 44.8% of the maize farmers have arable crop farming as their primary occupation, civil servant constituted 15.1%, followed by vegetable crop farming which constitute 14.5%, then agro-processing was 7.9%, commodity marketing 5.3%, tree crop, livestock constituted 3.3% each, poultry farming 5.3% and fish farming which is the least with 0.7%. Arable crop farming been the primary occupation of most farmers in the study is in consistence with Mark (2011), who reported that over 70% of Nigerian populations are rural dwellers where farming activities is the major occupation.

3.2. Major Source of Information from the Various Extension Agencies

Major sources of extension service here refer to the major place, person or organization from which the farmer gets his extension service. Results from Table 2 shows that majority (65.8%) of the maize farmers in the study area received their major extension service from BSADP, 8.6% received from their Local Government extension agencies, 7.9% received from NGOs. The least was 1.3% who received their major extension service from private organizations. Which agrees with Issa and Kagbu (2017) in their studies of institutional Factors Influencing Crop Farmers Adoption of Recommended Agrochemical Practices in Nigeria; who finds that majority (93.1%) of farmers gets their information on new technology from Agricutural Development Programme (ADP). Yohanna et al, (2014) in his study on the Sources of Information on Climate Change among Arable Crop Farmers, In Adamawa State, Nigeria also reported that close to half of the respondents (42.28%) did not get information from extension agents. The contrast may be due to the general studies on topic done by most researchers and the specific focus on extension agencies in this research. Other sources of information are considered good; depending only on the nature and aim of information. Results from Table 2 shows that majority of the maize farmers who constitutes 53.6% consider radio as the most appropriate, affordable and convenient means of communication; followed by 32.7%, who preferred EAs. The least is 1.3% who considers other means of communication as most appropriate. This concurred with Arbuckler Jr. (2017) in his study of Communication Preferred by Iowa Farmers, Iowa, USA; fine out that farmers still prefer traditional forms (extension visit, meetings, workshops, field trips and radio) of communication than the new media forms ( inter-net, face book, whatsApp, etc) . Generally the farmers prefer radio as most appropriate means of communication in this part of the world, but extension scientist/experts do consider the nature of massage (simple or complex) and the ultimate aim (just to create awareness or adopt a technology). Other means of communication are good but extension agent is the best considering it as an individual and or group method that is done by physical contact, which cannot be easily replaced; thus a need for attention and more studies by researchers. Family, friends, neighbors, farmers’ association etc cannot replace extension agents, as their massage/source may be questionable and may be distorted as it pass from one person to another; except otherwise been trained.

3.3. Types of Technologies Received from Extension Organizations

Table 5 revealed that majority of maize farmers which constituted 79.0% had at least, a maize demonstration farm in there locality within the 7 years under study, while 21% had not. Majority of them had seen a maize demonstration farm, this is consistent with BSADP report of 1999-2006 where it reported that 75% of demonstration farm that was intended were conducted. It also shows types of technologies received by respondents to include: land preparation, plant spacing, planting dept, plant protection, harvesting and storage among others; with the response of saying yes, as: 82.6%, 89.7%, 75.8%, 87.2%, 69.7%, and 85.6% respectively. These agrees with BSADP annual reports of 2009 to 2012 on extension activities and types of packages been disseminated independently or in collaboration with such organizations like SG2000, IITA, etc.

3.4. Types of Technologies Adopted/ Level of Adoption among Respondents

Table 6 reveals that technologies on land preparation, plant spacing and planting dept’s were adopted by 85.8%, 78.7% and 64.5% of respondents respectively: land preparation has the highest level of adoption with 85.8%; followed by plant spacing 78.7% and then planting dept 64.5%. Technologies on land preparation were highly adopted; while plant protection, harvesting and storage were poorly adopted by 30.3%, 19.2% and 27.5% respectively. Adoption level was lowest in harvesting techniques. The result is in contrast with Ugwumba and Okechukwu (2015) in their study of Adoption of Improved Maize Production Technologies in Enugu State, Nigeria; that shows a general low adoption level of the technologies except for the seed; but agrees with Anyanwu 2018 in her study of: Constraints to Adoption and Utilization of Cassava Production Technologies among Farmers in Imo State, Nigeria; who shows that land preparation was one of the techniques that were adopted by farmers. The adoption may be attributed to increase in yield, low cost of production or reduction in drudgery. Land preparation is paramount in maize production in terms of moisture control (water logging or dryness of farm lands) and so farmers will gladly adopt the technology each as his case may be; as the effect on yield is obvious. Plant spacing (inter and intra row) determine plant population and ultimately yield this may be the reason for high adoption. The low adoption rate seen in storage and harvesting techniques may be attributed to the needs of the farmers as traditional methods are satisfactory and relatively cheaper compared to modern ones.

3.5. Impacts of Maize Technologies Adopted By Respondents over the Years.

Table 5 reveals an impact in residence ownership where 35% of respondents had either build or purchase a house after 2009 as against 18.5% before 2009; there was also improvement in farm machinery ownership where 26.1% of respondents had acquired maize crusher after 2009 as against 16.9% before 2009. Herbicide use witness positive impact as well 82% of the farmers now using herbicides as against 67.3% of the former. These are in agreement with Ragasa et al., (2016) in their studies of the Impact of Agricultural Extension Services in the Context of a Heavily Subsidized Input System shows that 79% of farmers attested to have seen impact as against 21% who did not; Lawal et al., (2009) in their studies – Impact of Agricultural Extension Practices on the Nigerian Poultry Farmers Standard of Living show a 50% increase in egg production compared to initial 20%, and 58.3% of poultry farmers’ had improvement in their housing conditions. Cowley et al., (2015) in their studies The Impact of Extension on Farm Level Outcome; report a 19% increase as well.

3.6. Impact Analysis of BSADP on the Livelihood of Respondents Using ‘T’ test

‘T’ test was used to measure the impact of BSADP on some variables as they affect the respondents. Table 6 shows that there was impact on the residence ownership of respondents at P< 0.05 level of significant, 2- tail test. The tested result of 0.025 shows a moderate significant which confirmed the impact seen in the descriptive statistics analysis. It also shows an impact on housing type at P<0.001 significant level. The tested result of 0.000 shows a very high significance there by confirming the descriptive statistic analysis. The result further reveals that impact was made on the transport means of respondents at P< 0.001 significant level; tested statistic of 0.000 means that the degree of significance is very high. It is similar it is similar to communication means in same Table 6 which also tested 0.000 with a very high degree of significance on the communication means of maize farmers at P<0.001 significant level. There was low significant impact on the ownership of farm machinery among farmers with 0.041 tested statistics at P<0.05 significant level of two tail test. This may be due to alternatives such as human labour which is abundant and relatively cheap compared to maintenance of machines. Tested statistics on water sources was 0.002 at P<0.01 significant level; this means there was high impact on water source. Herbicide use and knapsack ownership had shown to be birds of the same feathers that flies to the same direction with very high impact of 0.000 at P<0.001. This may be as a result of the need of timely operation in maize. Ownership of work bulls shows high impact of 0.003 when tested at P<0.01.

5.0. CONCLUSION AND RECOMMENDATIONS

Most of the maize farmers in the study area were male who were in their prime age of production and married. Majority of them has formal education with farming as their primary occupation. Respondents’ major source of information on maize technology among various extension delivery agencies in the study area is BSADP. BSADP had made Impact in the livelihood of maize farmers in western agricultural zone of Bauchi State: highest impacts were on house type, means of transport type, communication means type, herbicide use and ownership of knapsack at a significant level of P<0.001. It is recommended that, all encompassing agricultural packages that will include all members of the family be considered in design of packages by consultants. Extension providers should encourage farmers to keep records since most of them can read and write, this will not only help the farmers but extension system as a whole. BSADP through its EAs; should uphold its good work in the study area and build cordial relationship with the farmers. Government and other donor agencies should keep on supporting Bauchi State Agricultural Development Programme (BSADP).

Table 1: Socio-economic characteristics of respondents

Variable		Frequency	Percentage
Age range Below 21 21-30 31-40 41-50 51-60 Above 60. Total		11 12 51 48 21 12 155	7.1 7.7 32.9 31.0 13.5 7.7 100
Sex
Male Female Total	113 44 157			72.0 28.0 100
Marital status
Married Single Widow Divorce Total Education level Primary Secondary Tertiary Quranic None Total Occupation Civil servant Arable crop farming Vegetable crop farming Tree crop farming Live stock farming Fish farming Poultry farming Commodity marketing Agro processing Total	129 18 8 2 157 30 46 23 26 30 155 23 68 22 5 5 1 8 8 12 152			82.2 11.5 5.1 1.3 100 19.4 29.7 14.8 16.8 5.4 100 15.1 44.8 14.5 3.3 3.3 0.7 5.3 5.3 7.9 100
Source: Field survey, 2016

Table 2: Major source of information from the various extension agencies

Variables	Frequency	Percentage
Major sources of extension service University Research institute NGOs Private organizations Donor agencies Local Government agencies Federal Government agencies BSADP Total	9 8 12 2 5 13 3 100 152	5.9 5.3 7.9 1.3 3.3 8.6 2.0 65.8 100

Source: Field survey, 2016

Table 3: Distribution of respondents according to types of technologies received.

Variables

Frequency

Percentage

Presence of demonstration farm

Yes

Total

Types of technology received

Land preparation

Yes

Total

Plant spacing

Yes

Total

Planting dept

Yes

Total

Plant protection

Yes

Total

Harvesting

Yes

Total

Storage

Yes

Total

124

156

130

157

141

157

121

157

137

157

110

157

134

157

79.0

21.0

100

82.6

17.4

100

89.7

10.3

100

75.8

22.7

100

87.2

12.8

100

69.7

30.3

100

85.2

14.8

100

Source: Field survey, 2016

Table 4. Percentage distribution of respondents by technology adopted/level of adoption (n=157)

Technology	Percentage
Land preparation	85.8
Plant spacing	78.7
Planting dept	64.5
Plant protection	30.3
Harvesting	19.2
Storage	27.5

Source: Field survey, 2016

Table 5a: Distribution of respondents according to living condition before and after 2009

Variables

Before 2009

Frequency Percentage

After 2009

Frequency Percentage

Residence ownership

Purchase/ build

Inherited

Rented

Family

Others

Total

House type

Mud thatched

Mud zinc

Cement bricks zinc

Others

Total

Type of major transport means

None

Bicycle

Motorcycle

Tricycle

Pick-up

Others

Total

Means of communication owned

Radio only

TV only

TV and Radio

None

Total

Water source

Well

Borehole

River/stream

Tap water

Total

Herbicide use

Yes

Total

29 18.5

79 50.3

20 12.7

25 15.9

4 2.5

157 100

21 13.4

92 58.6

43 27.6

1 0.6

157 100

20 12.8

34 21.8

94 59.6

2 1.3

6 3.8

1 0.6

157 100

108 68.9

1 0.6

46 29.2

2 1.3

157 100

76 47.7

55 35.5

21 13.5

2 3.2

157 100

106 67.3

51 32.7

157 100

55 35.0

63 40.1

12 7.6

19 12.1

8 5.1

157 100

6 3.8

89 56.7

60 38.2

2 1.3

157 100

13 8.3

19 12.2

89 59.4

17 10.9

18 11.5

1 0.6

157 100

68 43.1

3 2.0

84 53.6

2 1.3

157 100

70 44.2

44 28.2

22 14.2

21 13.5

157 100

128 82.0

29 18.0

157 100

Source: Field survey, 2016

Table 5b: Distribution of respondents according to living condition before and after 2009

Variables

Before 2009

Frequency Percentage

After 2009

Frequency Percentage

Farm machinery ownership

Tractor

Planter

Water pump

Maize crusher

Others

Total

Work bulls

None

Two

Four

Six

Eight

Ten

Total

12 6.8

18 10.2

51 32.2

29 16.9

56 33.9

157 100

75 47.1

55 35.5

22 14.2

4 2.6

1 0.6

0 0

157 100

22 14.1

13 8.9

48 30.4

42 26.1

32 20.0

135 100

59 37.8

56 35.8

32 20.9

3 2.0

2 1.4

3 2.0

157 100

Source: Field survey, 2016

Variables	Mean	‘T’	Df	Sig. (2- tail )
Residence ownership	0.19108	2.265	156	0.025*
House type	-0.21656	-4.671	156	0.000***
Transport means	-4.3226	-5.812	154	0.000***
Communication means	-0.50667	-6.074	149	0.000***
Farm machinery ownership	0.24545	2.071	109	0.041*
Major water source	-0.253225	-3.121	153	0.002**
Herbicide use	0.29530	7.209	148	0.000***
Knapsack ownership	0.14094	3.952	148	0.000***
Work bulls ownership	-0.26351	-2.975	147	0.003**

Source: Field survey, 2016

*= significant at P<0.05, **= significant at P<0.01, ***= significant at P<0.001

REFERENCES

Arbuckeler Jr. J.G (2017) Communication Preferred by Iowa Farmers. Iowa Farm and Rual Life Poll, ISU News: Iowa, USA.

Anyanwu, C. G. (2018). Constrains To Adoption and Utilization of Cassava Production Technologies Among Farmers in Imo State, Nigeria. Scientific Paper Series Management, Economics Engineering in Agriculture And Rural Development. 18 (1); 67 -72.

Bates M.J. (2012) Fundamental of Forms of Information.Journal of American Society for Information Science and Technology, 57 (8), 1033-1045.

BSADP 1999 - 2006. Bauchi State Agricultural Development Programme report: P. 7, 25 - 40.

BSADP 2009 - 2012. Bauchi State Agricultural Development Programme report: P. 30 - 50.

Cawley, A.P.,Heanue,K., O’Donoghue,C. and Sheehan,M. (2015) The Impact of Extension Services on Farm Level Outcome: An Instrumental Variable Approach. Paper presented at the 150^th EAAE Seminar. “The Spatial Dimension in Analyzing the Linkages Between Agriculture, Rural Development and the Environment”. Jointly organized between Scotland Rural College (SRUC) and Teagasc Scotland’s Rural College, Edinburgh, Scotland October 22-23, Pp. 1-18.

Issa, F.O. and Kagbu, J.H.(2017) Institutional Factors Influencing Crop Farmers Adoption of Recommended Agrochemical Practices in Nigeria. Journal of Agricultural Extension 21 (1): 1 – 6

Lawal,B.O.,Torimiro,D.O. and Makanjuola, B.A. (2009) Impact of Agricultural Extension Practices on the Nigerian poultry Farmers’ Standard of living: A perceptional Analysis. Journal of Tropical and Subtropical Agroecosystems 10 (3):465-473.

Mark, K. (2011) Farmingfuture:LessonfromKwara. Think Africa Press. www.thinkafricapress.com/nigeria/ farming- futurelessons-kwara .

Ofuaku. A. U (2011) Rural Farmers’ Perception of Climate Change in Central Agricultural Zone of Delta State of Nigeria. Indonesian Journal of Agricultural Science 12 (2): 63-69.

Olusegun, A.F.,Dare A and Begho T. (2014). Factors Influencing Adoption Decision of Maize Farmers In Nigeria. International Journal of Food And Agricultural Economics. 2 (3); 45-54.

Ragasa, C.,Mazunda,J.,Kadzamira,M. (2016) The Impact of Agricultural Extension Services In The Context of Heavy Subsidized Input System. International Food Policy Research Institute (IFPRI) Discussion paper Pp 1-30.

Ugwumba, C.O.A. and Okechukwu, E.O. (2015). Adoption of improved maize production technologies in enugu state Nigeria. International journal of agricultural innovations and research. 3 (1); 259 – 261.

Yohanna, I., Ndaghu, A. A and Barnabas, B.P. (2014). Sources of information on Climate Change Among Arable crop farmers in Adamawa State, Nigeria. Journal of Agriculture and Veterinary Science 7 (1) Pp 32 – 36.

Cite this Article: Chiroma, IA; Tarki, SK; Bako, BD; Shirama, L (2021). Impact of Bauchi State Agricultural Development Programme (BSADP) on the Livelihood of Maize Farmers in Western Agricultural Zone of Bauchi State, Nigeria: 2009 - 2015. Greener Journal of Agricultural Sciences 11(2): 80-89.

ARTICLE INFO	ABSTRACT
*Article No.:* 051121046 *Type: Research*	The study was conducted to study the impact of Bauchi State Agricultural Development Programme (BSADP) on the livelihood of Maize Farmers in Western Agricultural Zone of Bauchi State, Nigeria: 2009 – 2015.The objectives of the study were to: describe the socio-economic characteristics of respondents, determine type of technology received/adopted by respondents and examine the impact(s) of maize technology adopted by the respondents over the years. A multi-stage sampling technique was used to collect primary data with the aid of a structured questionnaire. Results obtained showed that 63.9% of respondents in the study area are in their prime stage of production and majority (79.1%) of the respondents had one form of western education. It also revealed that 65.8% of the respondents receive their major extension services from BSADP. Impact was made on farmers at various significant levels of 0.05, 0.01 and 0.000. Highest impacts were on house type, means of transport type, communication means type, herbicide use and ownership of knapsack at a significant level of P<0.001. The study concluded that BSADP had made Impact in the livelihood of maize farmers in western agricultural zone of Bauchi State. Extension providers should encourage farmers to keep records since most of them can read and write, this will not only help the farmers but extension system as a whole. BSADP through its EAs; should uphold its good work in the study area and build cordial relationship with the farmers. Government and donor agencies should keep on supporting Bauchi State Agricultural Development Programme (BSADP).
*Accepted:* 13/05/2021 *Published:* 29/06/2021
Corresponding Author CHIROMA, Ibrahim Audu* *E-mail:* buabudam@ gmail.com *Phone:* +2348066950067
*Keywords:* impact; BSADP; livelihood; maize farmers.

Sub-Zones	Blocks	Cells	Sub-Cells	Sample Size
Alkaleri	2	2Cells/Block=4	2SubCell/Cell=8	4farmers/Sub-Cell =32
Bauchi	2	2Cells/Block=4	2SubCell/Cell=8	4farmers/Sub-Cell =32
Dass	2	2Cells/Block=4	2SubCell/Cell=8	4farmers/Sub-Cell =32
Kirfi	2	2Cells/Block=4	2SubCell/Cell=8	4farmers/Sub-Cell =32
Toro	2	2Cells/Block=4	2SubCell/Cell=8	4farmers/Sub-Cell =32
TOTAL	10	20	32	160