Desempeño biofísico y económico de sistemas de cultivos extensivos: una aproximación basada en modelos de simulación y algoritmos genéticos

En este trabajo se presenta un framework basado en modelos de simulación de cultivos y algoritmos genéticos para encontrar las combinaciones de variables de manejo (i.e. fertilización, secuencias y estructura de cultivos, y aplicación de fitosanitarios) que optimicen el desempeño biofísico y económico de sistemas de agrícolas extensivos. Además, se proponen valores umbral hipotéticos para las variable biofísicas y económicas a partir del cual se podría generar el colapso del sistema. Se generó una herramienta de diagnóstico que permite medir la distancia entre el desempeño de prácticas reales modales para Pergamino y los óptimos obtenidos mediante la optimización del algoritmo genético. Finalmente, se discuten las limitaciones de este tipo de aproximación y las implicancias para el diseño de sistemas de cultivos extensivos sustentables.Sociedad Argentina de Informática e Investigación Operativ

Decision Support Systems for Weed Management

Editors: Guillermo R. Chantre, José L. González-Andújar.Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate 'concepts and practice' providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas

Historical trends of the ecotoxicological pesticide risk from the main grain crops in Rolling Pampa (Argentina).

We showed the results of the first long-term analysis (1987-2019) of pesticide (herbicides, fungicides and insecticides) impact in the Rolling Pampa, one of the main agricultural areas of Argentina. Using a clear and meaningful tool, based not only on acute toxicity but also on scaling up the results to total sown area, we identified time trends for both pesticide impact and the ecoefficiency of modal pesticide profiles. By the end of the time series, soybean showed a pesticide impact four times greater than maize crop in the studied area. However, the time trend in the subperiod (2012-2019) showed a sustainable pattern of pesticide use in soybean crop, with an improvement in its ecoefficiency. Oppositely, maize showed a relatively constant ecoefficiency value during most of the time series, suggesting a possible path towards an unsustainable cropping system. Findings from this study suggest that some efforts have to be made to improve the pest management decisions towards a more efficient pesticide profiles in maize crop and to keep improving the ecotoxicity pesticide profile in soybean crops because of its large sown area in the studied area

Incorporação de indicadores de sustentabilidade na priorização de áreas para restauração florestal na bacia do rio Corumbataí, SP Incorporating sustainability indicators on site selection for forest restoration in the Corumbataí river basin

Na bacia do rio Corumbataí, a vegetação natural ocupa menos de 3% de sua área total, e a ausência dessa vegetação florestal tem levado ao aumento dos processos erosivos e ao desequilíbrio do regime hídrico de seus rios, causando diversos problemas no abastecimento de água de várias cidades, como Piracicaba e Rio Claro. Desse modo, existe a necessidade de um reflorestamento criterioso em áreas dessa bacia. No entanto, devido à limitação de recursos, é necessário que sejam realizados estudos de seleção de áreas prioritárias para que, com os recursos disponíveis, o ganho ambiental das áreas restauradas seja máximo. O objetivo deste trabalho foi desenvolver um método de priorização de áreas para restauração florestal baseado no uso de indicadores de sustentabilidade em microbacias. Cinco indicadores foram utilizados: porcentagem de mata nativa na APP; descontinuidade da vegetação nativa na bacia; diversidade da paisagem; variação média do uso da terra; e suscetibilidade à erosão. A seleção das microbacias para restauração das áreas de APP foi realizada por meio da ponderação linear dos indicadores e ordenamento das microbacias. Simulação inicial foi realizada para a seleção de 1.000 ha para restauração, e os resultados indicaram que os indicadores representam diferentes aspectos de sustentabilidade das microbacias. O método foi considerado útil na seleção de microbacias em condições extremas, diferenciando aquelas que necessitam de ações de conservação daquelas que necessitam de ações de restauração.<br>In the Corumbataí river basin, State of São Paulo, forest remnants occupy less than 3% of the original total area, and the absence of this natural vegetation has been increasing erosion and disturbing hydrological regime of its streams, causing many problems on water supply in urban areas like Piracicaba and Rio Claro. This situation shows the need of a well planned reforestation in areas of this watershed. However, since the funds are limited, it is necessary a site selection study to use available fund on reforestation projects considering the maximum environmental gain. This study aims to develop a site selection method for reforestation based on sustainable indicators of catchments. Five indicators were considered: native forest proportion in the Permanent Preservation Areas (APP); native forest discontinuity in the basin; mean variation of land-use; Shannon landscape diversity index; and mean erosion susceptibility. Catchment areas were selected using linear weighting of indicators and ranking of catchments. An initial simulation was made to select the best 1.000 ha for reforestation and the results showed that the indicators were able to capture distinct aspects of catchment sustainability. The method was considered useful for selecting catchments at extreme conditions, differentiating those that need conservation actions from those that need restoration actions