A decision support system for Campesino maize-cattle production systems of the Toluca Valley in Central Mexico

• Main Author: Castelán-Ortega, Octavio A.
• Published: University of Edinburgh 2000
• Subjects: 630
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.642671

The viability of the <i>campesino </i>maize-cattle production system of Central Mexico is under stress by the North American Free Trade Agreement policies. To survive <i>Campesino </i>farmers are developing alternative production systems and more efficient uses of their land. The objective of this work was "to develop a "Decision-Support System" (DSS) in order to support <i>Campesino</i> farmers in this process. Two biological models, one socio-economic model and a survey database on the target farming system form the DSS. The CERES-Maize model simulated the yield response of three local land-races of maize to different management systems. The second biological model, a dynamic 'hybrid model', which predicts potential intake, digestion and animal performance of individual dairy cows, was used to simulate alternative feeding systems. A multi-period mathematical programming model integrated the outputs of the previous models with the survey database. This model was used to find the optimal combination of resources and technologies that maximised farmers' income. This model consists of 15,884 structural columns and 602 rows. The DSS was successfully in reproducing the functioning of the main components of the farming system. More importantly it simulated the complex interactions observed between the farmers and their crops and cattle, including traditional maize management practices. The model simulated the resulting effects of these practices on the feeding systems for cattle and on the household's labour demand. The DSS selected on a monthly basis the forage type, concentrate type and supplementation level fed to all classes of cattle on the farm. Moreover, it was able to incorporate the seasonal effects on forage quality and availability.