A Decision Support System for smallholder campesino maize-cattle production systems of the Toluca Valley in Central Mexico. Part II—Emulating the farming system

LivestockFuturesThis paper describes the functioning and validation of the Decision Support Systems described in the first part of the paper. The DSS ran three case studies with different farm sizes that represent the range of farmers found in the Valley. The DSS results were validated against survey data for the same cases. Traditional technologies for maize and milk production were reproduced by the DSS including land use and cattle feeding systems. The generic nature of the DSS was demonstrated as well as its capacity to deal with the system's socio-economic and biological aspects. The results suggest that the DSS was successful in reproducing the functioning of the farming system's main components. More importantly it simulated the complex interactions observed between the farmers and their crops and cattle. Finally, it is acknowledged that despite the size and complexity of the DSS, it only was able to emulate the functioning of the main components of the farming system

A Decision Support System for smallholder campesino maize-cattle production systems of the Toluca Valley in Central Mexico. Part I—Integrating biological and socio-economic models into a holistic system

The objective of this work was to develop a Decision-Support System (DSS) in order to support the decision making process by campesino farmers of Central Mexico. Two biological models, one socio-economic model and a survey database 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 cow model (dynamic hybrid model), 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 15,698 structural columns and 612 rows. The DSS successfully reproduced the functioning of the farming system's main components. More importantly, it simulated the complex interactions observed between the farmers and their crops and cattle, including traditional maize management practices

Molecular characterization and antimicrobial susceptibility of Staphylococcus aureus from small-scale dairy systems in the highlands of Central México

Staphylococcus aureus is involved in human and animal infections. Because of mastitis in dairy cows, milk can be contaminated by enterotoxin-producing strains, which constitutes a food poisoning risk. Animal handlers can be asymptomatic carriers, becoming an additional source of contamination. This research aims to improve our understanding of Staphylococcus aureus in small-scale dairy systems in central Mexico. Samples were taken in 12 dairy farms and included composite milk (from the four teats) and hand swabs from each farmer. Of 149 presumptive S. aureus isolates, 102 (84 from cows; 18 from farmers) were accurately identified by molecular methods. The genetic variability of 43 randomly selected isolates was determined by RAPD-PCR, and of these, 38 were genetically distinct (≤90% similarity). Of the 38 distinct isolates, 78.9% harboured at least one enterotoxin-encoding gene (staphylococcal enterotoxin a (sea)–sed, seg, and/or sei), whereas 100% carried icaA–icaD genes and 28% carried the bap gene. The latter three genes are all involved in biofilm formation. Susceptibility to antibiotics, bacteriocins, and bacteriophages, was also assayed; 36.8% of isolates were resistant to penicillin G. Only five isolates were resistant to bacteriocins nisin A and AS-48, and phiPLA-RODI was the most effective bacteriophage, infecting all of the isolates. These results support the need to adopt management strategies to improve hygiene and milking practices in order to enhance herd health and diminish the risk of food poisoning associated with the consumption of raw milk cheese. © 2014, INRA and Springer-Verlag France.This work was undertaken with funds from the Spanish Agency for International Development Cooperation (Agencia Española de Cooperación Internacional para el Desarrollo) through project AECID 11-CAP2-1526 and the Mexican National Council for Science and Technology (Consejo Nacional de Ciencia y Tecnología—CONACYT) grant 129449 CB-2009. CONACYT also provided the grant that enabled the postgraduate studies of Tania Berenice Salgado-Ruiz.Peer Reviewe

Dengue viruses cluster antigenically but not as discrete serotypes

The four genetically divergent dengue virus (DENV) types are traditionally classified as serotypes. Antigenic and genetic differences among the DENV types influence disease outcome, vaccine-induced protection, epidemic magnitude, and viral evolution.We scharacterized antigenic diversity in the DENV types by antigenic maps constructed from neutralizing antibody titers obtained from African green monkeys and after human vaccination and natural infections. Genetically, geographically, and temporally, diverse DENV isolates clustered loosely by type, but we found that many are as similar antigenically to a virus of a different type as to some viruses of the same type. Primary infection antisera did not neutralize all viruses of the same DENV type any better than other types did up to 2 years after infection and did not show improved neutralization to homologous type isolates. That the canonical DENV types are not antigenically homogeneous has implications for vaccination and research on the dynamics of immunity, disease, and the evolution of DENV