Going digital in agriculture: how radio and SMS can scale-up smallholder participation in legume-based sustainable agricultural intensification practices and technologies in Tanzania

Figures & data

Figure 1. Scheme illustrating the deep dive study.

Table 1. Farmers that learned something new as result of the campaign (%).

Topics of the campaign	Radio	SMS	Radio & SMS	Average across all channels
Planting	36	44	60	46
Seeds	49	56	69	58
Fertilizer and soil fertility	32	26	22	26
Pests and Diseases	36	37	51	40
Weeding	10	9	11	10
Harvesting	5	10	15	10
Storage	9	21	31	21

Table 2. Practices adopted by farmers as result of the campaign (%).

Topics of the campaign	Radio	SMS	Radio & SMS	Average across all channels
Planting	27	37	51	38
Seeds	34	41	45	40
Fertilizer & soil Fertility	25	18	19	20
Pests & diseases	34	31	40	34
Weeding	7	9	9	8
Harvesting	5	10	11	9
Storage	8	15	23	16

Figure 2. Relationship between communication channel, message complexity and reach (modified from Kansiime et al. 2017).

Table 3. Raw scores for different communication channels.

Communication channels	Awareness scores		Adoption scores
	Mean	Standard Deviation	Mean	Standard Deviation
Radio and SMS	0.79	0.91	0.67	1.04
Radio	0.48	0.96	0.42	1.08
SMS	0.49	0.91	0.43	0.99

Table 4. Tests of between subject effects on awareness of different farming practices.

Factors affecting awareness	Type III sum of squares	Df	Mean Square	F	p-value
Corrected Model	19.01	22	0.86	1.02	0.44
Intercept	0.476	1	0.48	0.56	0.45
Age	1.64	1	1.64	1.95	0.17
Cultivated land	0.01	1	0.01	0.01	0.92
Communication channels	4.77	2	2.38	2.82	0.06
Gender	0.02	1	0.01	0.02	0.90
Education	1.06	3	0.35	0.42	0.74
Error	171.52	203	0.85
Total	267.11	226
Corrected Total	190.53	225

Table 5. Pairwise comparisons of the effect of communication channels on awareness.

Communication channels (1)	Communication channels (2)	Mean Difference (1–2)	Std. Error	Sig.
Radio and SMS	Radio only	0.64	0.31	0.04
	SMS only	0.55	0.28	0.05
Radio only	Radio and SMS	−0.64	0.31	0.04
	SMS only	−0.09	0.27	0.73
SMS only	Radio and SMS	−0.55	0.28	0.05
	Radio only	0.09	0.27	0.73

Table 6. Tests of between subject effects on adoption of different farming practices.

Factors affecting awareness	Type III sum of squares	df	Mean Square	F	p-value
Corrected Model	26.45	22	1.20	1.153	0.30
Intercept	2.25	1	2.25	2.156	0.14
Age	0.37	1	0.37	0.354	0.55
Cultivated land	0.01	1	0.01	0.010	0.92
Communication channels	6.31	2	3.16	3.025	0.05
Gender	0.38	1	0.38	0.361	0.55
Education	2.64	3	0.88	0.845	0.47
Error	211.75	203	1.04
Total	295.69	226
Corrected Total	238.20	225

Table 7. Pairwise comparisons of the effect of communication channels on adoption.

Communication channels (1)	Communication channels (2)	Mean Difference (1–2)	Std. Error	Sig.
Radio and SMS	Radio only	0.78	0.34	0.02
	SMS only	0.67	0.31	0.03
Radio only	Radio and SMS	−0.78	0.34	0.02
	SMS only	−0.11	0.30	0.71
SMS only	Radio and SMS	−0.67	0.31	0.03
	Radio only	0.11	0.30	0.71

Table 8. Cost-effectiveness and effectiveness of cost for ‘SMS’, ‘radio’ and ‘radio and SMS’.

Media	Cost per farmer reached (USD)	% of farmers learning at least one practise	% of farmers adopting at least one practise	CE awareness ($ spent per farmer that has learned at least one new topic)	EC awareness (n. of farmers that learned at least one practise per $ spent)	CE adoption ($ spent per farmer that has adopted at least one practice)	EC adoption (n. of farmers that adopted at least one practise per $ spent)
SMS	1.85^a	90.4	84.3	2.0	0.49	2.2	0.46
Radio	0.36^b	89.8	74.6	0.4	2.50	0.5	2.07
Radio & SMS	2.21^c	96.9	86.2	2.3	0.44	2.6	0.39

Assumptions: ^aAs a benchmark for the cost related to the SMS, we considered the costs that were associated with the SMS campaign on maize for the UPTAKE project, where a total of 17 SMS were sent to 46,564 farmers. The average cost was derived by dividing the cost of the project (costs included cost to send the SMS and cost to produce the content) by the number of farmers reached.

^bThe average cost per farmer reached through radio was derived by dividing the total cost of the radio campaign (salaries, project set up costs, training of broadcasters, direct costs around equipment, and payment for radio airtime) by the number of farmers reached (Mitschke, 2017).

^cThe cost per farmer reached by radio and SMS is assumed to be given by the sum of the average cost per farmer reached by radio and the average cost per farmer reached by SMS.

Kansiime, M., Mulema, J., Karanja, D., Romney, D., & Day, R. (2017). Crop pests and disease management in Uganda: status andinvestment needs. Rome: PARM/IFAD.

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Mitschke V. 2017. Inducing the adoption of good agricultural practices by educating Tanzanian smallholder farmers – what works best and at what costs? [Master's thesis]. Wageningen University.

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