Leveraging peer-to-peer farmer learning to facilitate better strategies in smallholder dairy husbandry
| Autor: | Zaipuna O. Yonah, Devotha Nyambo, Thomas Clemen, Fidalis D. N. Mujibi, Edith Talina Luhanga |
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| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
Yield (finance) Experimental and Cognitive Psychology 04 agricultural and veterinary sciences Animal husbandry Peer-to-peer computer.software_genre 01 natural sciences Behavioral Neuroscience Agricultural science 040103 agronomy & agriculture 0401 agriculture forestry and fisheries Business computer 0105 earth and related environmental sciences |
| Zdroj: | Adaptive Behavior. 30:51-62 |
| ISSN: | 1741-2633 1059-7123 |
| DOI: | 10.1177/1059712320971369 |
| Popis: | Peer-to-peer learning paradigm is seldom used in studying how farmers can increase yield. In this article, agent-based modelling has been applied to study the chances of dairy farmers increasing annual milk yield by learning better farming strategies from each other. Two sets of strategies were considered; in one set ( S), each farmer agent would possess a number of farming strategies based on their knowledge, and in a second set [Formula: see text], farmer agents would possess farming strategies that they have adopted from their peers. Regression models were used to determine litres of milk that could be produced whenever new strategies were applied. By using data from Ethiopia and Tanzania, 28 and 25 determinants for increase in milk yield were fitted for the two countries, respectively. There was a significant increase in average milk yield as the farmer agents interacted and updated their [Formula: see text]– from baseline data, average milk yield of 12.7 ± 4.89 and 13.62 ± 4.47 to simulated milk yield average of 17.57 ± 0.72 and 20.34 ± 1.16 for Tanzania and Ethiopia, respectively. The peer-to-peer learning approach details an inexpensive method manageable by the farmers themselves. Its implementation could range from physical farmer groups to online interactions. |
| Databáze: | OpenAIRE |
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