A Bayesian network to predict the probability of organic farms’ exit from the sector: A case study from Marche, Italy
The maintenance of organic farming production schemes is a theme receiving a growing interest now that there are signs of a slowing in organic farming uptake in Italy. The present study develops a model based on a Bayesian network (BN) that is aimed at investigating the factors that affect the exit...
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| Veröffentlicht in: | Computers and electronics in agriculture 2010-04, Vol.71 (1), p.22-31 |
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| creator | Gambelli, D. Bruschi, V. |
| description | The maintenance of organic farming production schemes is a theme receiving a growing interest now that there are signs of a slowing in organic farming uptake in Italy. The present study develops a model based on a Bayesian network (BN) that is aimed at investigating the factors that affect the exit of a farm from the organic sector and to simulate the probability of maintaining an organic scheme for different farm types. The model is based on a database of organic farms, which has been integrated with qualitative information. Farm-type simulation and sensitivity analysis of most of the relevant variables have been carried out. Main results show that arable farm types are those with a higher probability to stay in the organic sector, while farmers’ age, Province the farm is situated in and farm size are the factors mostly influencing probability scores. |
| doi_str_mv | 10.1016/j.compag.2009.11.004 |
| format | Article |
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The present study develops a model based on a Bayesian network (BN) that is aimed at investigating the factors that affect the exit of a farm from the organic sector and to simulate the probability of maintaining an organic scheme for different farm types. The model is based on a database of organic farms, which has been integrated with qualitative information. Farm-type simulation and sensitivity analysis of most of the relevant variables have been carried out. 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The present study develops a model based on a Bayesian network (BN) that is aimed at investigating the factors that affect the exit of a farm from the organic sector and to simulate the probability of maintaining an organic scheme for different farm types. The model is based on a database of organic farms, which has been integrated with qualitative information. Farm-type simulation and sensitivity analysis of most of the relevant variables have been carried out. Main results show that arable farm types are those with a higher probability to stay in the organic sector, while farmers’ age, Province the farm is situated in and farm size are the factors mostly influencing probability scores.</description><subject>Agricultural and farming systems</subject><subject>agriculture</subject><subject>Agronomy. 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| ispartof | Computers and electronics in agriculture, 2010-04, Vol.71 (1), p.22-31 |
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| language | eng |
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| subjects | Agricultural and farming systems agriculture Agronomy. Soil science and plant productions Bayesian analysis Bayesian networks Bayesian theory Biological and medical sciences case studies Computer simulation farm management farm size Farm-type simulations farmers Farming Farms Fundamental and applied biological sciences. Psychology General agroecology. Agricultural and farming systems. Agricultural development. Rural area planning. Landscaping General agronomy. Plant production Generalities. Agricultural and farming systems. Agricultural development geographical variation Mathematical analysis Mathematical models Networks Organic farms survival organic production organic sector prediction simulation models |
| title | A Bayesian network to predict the probability of organic farms’ exit from the sector: A case study from Marche, Italy |
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