ANALYSIS OF FACTORS INFLUENCING ADOPTION OF MAIZE PRODUCTION TECHNOLOGIES BY FARMERS IN NORTHERN NIGERIA.pptx

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1. ANALYSIS OF FACTORS INFLUENCING ADOPTION OF MAIZE PRODUCTION TECHNOLOGIES BY FARMERS IN NORTHERN NIGERIA: A REVIEW By GARBA ADO, MUHAMMAD GARBA AND ZAKARI Alfa DEPARTMENT OF AGRICULTURAL EXTENSION AND RURAL DEVELOPMENT, FACULTY OF AGRICULTURE AND AGRICULTURAL TECHNOLOGY, ABUBAKAR TAFAWA BALEWA UNIVERSITY, BAUCH JULY, 2024 1

2. 1.0 INTRODUCTION 1.1 Background of the Review Production of sufficient food for the populace is one of the major challenges facing developing countries of the world. It is estimated that over 800 million people of the world are malnourished ( Nwosu , 2020). This development is probably due to low productivity resulting from low rate of adoption of improved agricultural production technologies in most developing countries including Nigeria. 2

3. 1.1 Background of the Review Cont’d Maize ( Zea mays L.) is a staple food for large population groups around the world particularly in developing countries ( Lawal et al, 2013). Maize is a highly yielding crop easy to process, readily digested with cost advantage when compared to other cereals (IITA, 2017). Maize is major source of carbohydrate, protein, vitamins and minerals which provides major source of calories in Nigeria (Ado and Abdullahi , 2010). 3

4. 1.1 Background of the Review Cont’d Adoption is a decision to make full use of an innovation or new technology as the best opportunity available to the farmer.(Rogers, 1995) Adoption is the process by which farmers adopt and integrate new and advanced farming practices, tools and technologies into their farming operations ( Amaza et al , 2017). 4

5. 1.2 Statement of Problem Despite the place of maize as one of the leading food and industrial crops in Nigeria, it has not been produced in sufficient quantities for human and industrial needs of the country. This could be attributed to low productivity of the maize farmers as a result of low adoption of improved production technologies due to constraints to adoption such as poor extension services, limited fund, scarcity and high cost of inputs, diseases and pests attacks among others ( Abdullahi , 2023). 5

6. The broad objective of the review is to analyze factors influencing adoption of maize production technologies by farmers in Northern Nigeria; the specific objectives were to: Describe socio-economic characteristics of maize farmers in the study areas Identify types of maize technology adopted Examine socio-economic factors influencing adoption of maize production technologies in study areas Identify constraints associated the adoption of maize production technologies in the study areas 1.2 Objectives of the Review 6

7. Table 1: Socio Economic Characteristics of Respondents in Adamawa and Kaduna State Adamawa State Kaduna State Variables Freq. % Mean Freq. % Mean Age (years) 11-20 02 2.04 7 6.0 21-30 24 24.48 30 25.6 31-40 31 31.63 40years 27 23.1 40years 41-50 17 17.34 15 12.8 51-60 16 16.32 32 27.4 61 -70 8 8.16 6 5.1 Educational level Illiterates 15 15.31 46 30.7 Primary 16 16.33 73 48.7 Secondary 41 41.84 22 14.6 Tertiary 25 25.51 9 6.0 Others 1 1.02 Sex Male 65 66.32 95 81.2 Female 33 33.67 22 18.2 Total 98 100 117 100 7 Source: Umar, A.M. (2020) RESULTS Source: Issa et al . (2016)

8. Table 1: Socio Economic Characteristics of Respondents in Adamawa and Kaduna State Adamawa State Kaduna State Variables Freq. % Mean Freq. % Marital Status Single 21 21.42 22 18.8 Married 59 60.20 75 64.1 Divorced 3 3.06 9 7.7 Widowed 15 15.31 11 9.4 Household size 1-3 20 21.42 - - 4-6 24 24.48 - - 7-9 38 38.77 6 persons - - 10 -12 16 16.32 - - Total 98 100 117 100 Source: Umar, A.M. (2020) Source: Issa et al . (2016)

9. Table 2: Socio-economics Characteristics of respondents in Bauchi and Borno State Bauchi State Borno State Variables Frequency % Mean Frequency % Mean Age 20-30 68 56.8 23 21.90 31-40 32 26.6 42 40.00 41-50 8 6.6 31yrs 30 28.58 30yrs 51-60 7 5.8 10 9.52 61-70 5 4.2 Sex Male 109 90.8 78 74.29 Female 11 9.2 27 25.71 Marital Status Single 41 34.2 62 59.05 Married 69 57.5 24 22.86 Divorced 3 2.5 11 10.48 Widowed 7 5.8 08 7.61 Source: Babuga et al . (2020) Source: Kadafur et al . (2020) 9

10. Table 2: Socio-economics Characteristics of respondents in Bauchi and Borno State Continue….. Bauchi State Borno State Educational Level Frequency % Mean Frequency % Mean Non-formal education 11 9.2 26 24.74 Primary education 17 14.1 29 27.62 Secondary education 32 26.7 35 33.33 Tertiary education 60 50.0 15 14.29 Household size 1-5 39 32.5 - - 6-10 36 30.0 - - 11-15 29 24.2 9persons - - 16-20 15 12.5 - - 21-25 1 0.8 - - Farming Experience 1-5 20 16.7 34 32.3 6-10 42 35.0 13yrs 38 32.8 8yrs 11-15 26 21.7 33 28.4 16-20 32 26.7 Total 120 100 105 100 Source: Babuga et al . (2020) Source: Kadafur et al . (2020) 10

11. Table 3: Socio Economic Characteristics of Respondents in FCT-Abuja and Niger State 11 FCT-Abuja Niger State Variables Freq. % Mean Freq. % Mean Age 21-30 28 14.3 42 52.5 31-40 64 32.6 44 years 20 25.0 34 years 41-50 48 24.5 12 15.0 51-60 52 16.4 4 5.0 61-70 34 12.2 2 2.5 Sex Male 162 81.8 53 66.25 Female 36 18.2 27 33.75 Marital Status Single 26 13.4 20 25.0 Married 150 77.3 56 70.0 Divorced 6 3.1 1 1.25 Window 12 6.2 3 3.75 Source: Loyce et al. ( 2023) Source: Ubandoma et al. (2024)

12. Table 3: Socio Economic Characteristics of Respondents in FCT-Abuja and Niger State Continue… 12 FCT-Abuja Niger State Variables Freq. % Mean Freq. % Mean Household size 1-5 76 38.4 30 37.50 6-10 86 43.4 7 Persons 19 11.25 7 Persons 11-15 50 18.2 31 38.75 Educational level No formal education 10 5 6 7.50 Primary education 104 52 9 11.25 Secondary education 54 27 35 43.75 Post secondary education 32 16 30 37.50 Farm size Less than 1ha 20 10.1 NA NA 1-2.9 168 84.8 1.5 hectare NA NA 3 and above 10 5.1 NA NA Total 198 100 80 100 Source: Loyce et al. ( 2023) Source: Ubandoma et al. (2024)

13. Table 4: Level of Adoption of Improved Technologies in Maize Production in FCT-Abuja 13 Improved Technology Mean Adoption level Planting of improved varieties of maize 2.89 High Selection of disease-free planting materials 2.89 High Selection of an appropriate site for maize production 2.91 High Seed viability test before planting 1.73 Low Monoculture for optimum yield 2.33 High Use of appropriate weed control technologies 2.28 High Farm monitoring, uprooting and destruction of diseased plants 2.45 High Using tillage methods especially in erosion prone area 2.88 High Use recommended spacing and planting distance 1.75 Low Use of integrated pest management 2.89 High Use of appropriate or suitable irrigation techniques 1.42 Low Use of integrated weed management 2.95 High Timely harvesting 3.00 High Mean score less than 2 = low level of adoption; mean score of 2 and above = high level of adoption Source: Loyce et al . (2023)

14. Table 5: Level of Awareness of Improved Maize Production Technologies in Kaduna State 14 Technologies Aware Not aware Rank Appropriate land preparation 117(97.5) 3(2.5) 1 st Use of manure 107(89.2) 13(10.8) 2 nd Seed dressing 91(75.8) 29(24.2) 3 rd Appropriate planting techniques 82(68.3) 38(31.7) 4 th Appropriate harvesting 81(67.5) 39(32.5) 5 th Use of herbicides 79(62.5) 41(34.2) 6 th Use of fertilizer 75(62.5) 45(37.5) 7 th Use of improved seed 55(45.8) 65(54.2) 8 th Source: Issa et al . (2016) Percentages are in parentheses

15. Table 6: Level of Adoption of Improved Maize Production Technologies in Kaduna State 15 Technologies Highly used Moderately used Low used Not used Use of improved seed 19(15.0) 18(15.0) 13(10.8) 70(58.3) Appropriate land preparation 102(85.0) 7(5.8) 5(4.2) 6(5.0) Appropriate planting time 52(43.3) 14(11.7) 10(8.3) 44(36.7) Used of seed dressing 42(35.0) 32(26.7) 19(15.8) 27(22.5) Use of fertilizer 33(27.5) 26(21.7) 24(20.0) 37(30.8) Use of pesticide 48(40.0) 13(10.8) 12(10.0) 47(39.2) Use of manure 64(53.3) 17(14.3) 11(9.2) 29(24.2) Appropriate harvesting techniques 52(43.3) 16(13.3) 14(11.7) 38(31.7) Source: Issa et al . (2016) Percentages are in parentheses

16. Table 7: Socioeconomics factors influencing adoption of maize in Bauchi State Variables Coefficient Standard error t Sig . Level Constant 1.020 0.166 6.128*** 0.000 Age 0.182 0.049 3.688*** 0.000 Sex -0.095 0.100 -0.957 NS 0.341 Marital status -0.032 0.071 -0.448 * 0.655 Household size 0.314 0.055 -4.912*** 0.000 Educational level -0.270 0.067 4.659 *** 0.000 Farming experience 0.295 0.081 3.631*** 0.000 Farm size 0.233 0.120 1.933** 0.056 Annual income -0.183 0.089 -2.055 NS 0.42 Occupation -0.367 0.140 -2.614** 0.010 Pseudo likelihood 4.2628 Probability > F 44.47 R 2 = 0.0784 R 2 Adjusted= 0.767 *Significant at P< 0.1; **Significant at P < 0.05; ***Significant at P< 0.01; NS = Not Significant. Umar et al . (2022) 16

17. Table 8:Factors Influencing Adoption of Improved Maize Production Technologies in FCT-Abuja 17 Unstandardized Coefficients Model B Std. Error T-value P-value (Constant) 0.889 0.64 13.944 0.000 Age 0.000 0.001 0.184 0.855 Sex 0.035 0.033 1.047 0.297 Marital Status 0.005 0.016 0.322 0.748 Educational level 0.006 0.002 -2.439 0.016* Farming Experience -0.001 0.002 -0.550 0.584 Cooperative 0.032 0.017 1.900 0.060** Farm size 0.047 0.023 2.095 0.038* Household size -0.004 0.005 -0.820 0.414 Income 1.59E-007 0.000 0.475 0.636 Credit -0.005 0.018 -0.291 0.771 R2 = 0.441 f-statistic = 1.861 Note: *significant at 5% **significant at 10% Source: Loyce et al . (2023)

18. Table 9:Factors Influencing Adoption of Improved Maize Production Technologies in Kaduna State 18 Variables B Standard Error Beta T Sig Constant 99.393 11.925 8.335 0.000 Age -1.395 1.710 -110 -0.816 0.416 Sex -3.333 5.856 0.054 -0.569 0.570 Marital Status 1.762 2.837 0.065 0.621 0.536 Educational level 1.88 1.541 0.078 0.771 0.442 Farming Experience -0.078 1.170 -0.060 -0.457 0.648 Land acquisition 3.387 2.054 -0.155 -1.649 0.102 Farm size 0.620 1.230 0.255 2.696 0.008*** Pseudo r-square=0.19 Note: ***significant at 1% Source: Issa et al . (2016)

19. Table 10: Socio-economic determinants on adoption of maize production technologies in Adamawa State Variables Coef Std . Z Constant 2.412 1.911 407 Age -140 058 -0.16* Education level -0.140 0.0412 1.08** Household size 466 275 0.90** Access to credit 0.1626 0.3415 -0.48** Farm size 1.840 321 000 Sex -164 1.026 874** Extension contact 231 1.112 8.35*** Farming exp. -054 810 -4.97** Nagelkerke R 2 =832 *Significant P< 0.1; **Significant P < 0.05; ***Significant P< 0.01. Source: Umar. (2020). 19

20. Table 11: Factors Influencing Adoption of Improved Maize Production Technologies in Borno State Variable Coefficient Std . Err . Z Constant 0.3562 0.0378 9.42 *** Age 0.7619 0.3137 2.43** Sex 1.8723 1.6125 1.16 NS Farm size (ha) 0.2319 0.0685 3.38*** Education Level 0.0460 0.0121 3.8*** Access to credit 0.6363 0.2751 2.31** Household size 0.2708 0.1088 2.49** Income Level ( N ) 0.3285 0.0410 8.0*** Extension contact 0.0360 0.0099 3.65*** DST 0.8972 0.4125 2.18** Distance to market 0.4131 0.1738 2.38** Utilization of maize 1.5692 0.5478 2.86*** Maturity 0.3342 0.0391 8.55*** Acronyms: DST; Distance to Source of Technology Note: ***=P≤0.01, ** = P≤0.05. = NS; Not Significant Kadafur et al . (2020) 20

21. Table 12: Factors that Influence the Adoption of Improved Maize Production Technologies in Niger State 21 Variables Coefficient Standard Error T-ratio Age 1.938 0.298 6.505* Sex -0.033 0.052 -0.632 NS Educational level 0.025 0.040 0.062 Farming experience -1.053 0.105 -3.451* Contact with extension agents -0.064 0.026 -3.132* Fertilizer -0.079 0.108 -0.732 Household size 0.882 0.207 4.260* Membership of cooperative 1.917 0.828 2.315** Log likelihood function= -45.38571 Degree of freedom=7 Note: **significant at 5% , *significant at 10% and NS=not significant Source: Ubandoma et al. (2024)

22. Table 13: Problems affecting the adoption of Improved maize Production in FCT-Abuja, Niger and Adamawa States 22 FCT-Abuja Niger State Adamawa State Variables Freq. % Freq. % Freq. % High cost of Inputs 62 31.3 12 15.0 17 17.3 Inadequate capital 14 7.1 5 6.3 18 18.4 High cost of labour 50 25.3 9 11.3 24 24.5 Bad weather 11 5.6 20 25.0 10 10.2 Unavailability of land 13 6.6 8 10.0 11 11.2 Poor soil fertility 10 5.1 15 18.8 13 13.3 Pests and diseases 38 19.2 11 13.8 5 5.1 Total 198 100 80 100 98 100 Source: Loyce et al. ( 2023) Umar. (2020) Ubandoma et al. (2024)

23. Table 14: Problems affecting the adoption of Improved maize Production Bauchi , Kaduna and Borno State 23 Bauchi State Kaduna State Borno State Variables Freq. % Freq. % Freq. % Inadequate extension service 32 26.7 30 25.6 45 42.9 Inadequate capital 14 11.7 24 20.5 11 10.5 High cost of labour 22 18.3 27 23.1 5 4.8 Lack of market for produce 11 9.2 5 4.3 6 5.7 Unavailability of land 13 10.8 6 5.1 10 9.5 Poor soil fertility 10 8.3 16 13.7 12 11.4 Lack of education 18 15.0 9 7.7 16 15.2 Total 120 100 117 100 105 100 Source: Babuga et al . (2020) Issa et al . (2016) Kadafur et al . (2020)

24. 5.2 Recommendations Cost of input should be subsidized, since high cost of input prevented farmers from adopting improved maize production Technologies. Efforts should be made to make credit accessible to farmers, since lack of capital was an obstacle to the adoption of maize production. Extension agents should intensify campaigns for promoting the adoption of improved maize production in the study areas. 24

25. 5.1 Conclusion It is concluded that five variables which are educational status, farm size, access to credit household size and farming experience were found to have significant influence on adoption of maize production technologies in all the States under the review. 25

26. Thank you for listening 26