| Title: |
A LINEAR PROGRAMMING MODEL FOR BETTER DECISION MAKING IN THE GOAT SECTOR. |
| Authors: |
BATZIOS, Athanasios; THEODORIDIS, Alexandros; BOURNARIS, Thomas |
| Source: |
AGROFOR International Journal; 2024, Vol. 9 Issue 1, p52-60, 9p |
| Subject Terms: |
Goat farming; Livestock farms; Linear programming; Decision making; Economic statistics; Gross margins; Small farms; Sustainability; Farm size |
| Abstract: |
In this study a linear programming model was applied and the main structural and economic characteristics of the optimal organization of Greek goat farms were analyzed. The analysis was based on farm accounting data collected from 96 goat farms in northern Greece, through face-to-face interviews with farmers. The farm size in terms of does was used as a classification criterion and three farm size groups were formulated (small/medium/large size farms). Based on technical and economic data calculated for the surveyed farms and on specific indicators defined by livestock experts, a linear programming model was implemented for each of the three size groups of farms and the optimal plans under which farms maximize their gross margin were estimated. The optimal plans reveal the main structural characteristics of the farms and indicate the adjustments required to fully exploit the available technology. The results show that under the optimal plan all farms should increase the number of animals they rear. Small farms make full use of the available grazing land, while there is a small reduction in the use of grazing land in medium and large size farms. The farms under the optimal plans recommend to reduce production of feed on-farm and procure feed from the market, and produce cheese on-farm. The optimal structure indicates that goat farming should return to its traditional features and become a purely livestock farming activity operating under extensive production systems, making use of pastures of mountainous/disadvantaged areas, and avoiding excessive use of fodder. Under the production pattern, the farms will reduce production costs and improve their resilience and sustainability. [ABSTRACT FROM AUTHOR] |
| : |
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| Database: |
Complementary Index |