Paper presented at the International Symposium on Bananas and Plantains: Towards Sustainable Global Production and Improved Use, held October 10-14, 2011, Salvador (Bahia), Brazil. Includes references Bananas are often grown in mixed cropping systems. In Latin America, small growers cultivate bananas with minimal labor and purchased inputs in shaded coffee as a source of monthly income to supplement annual coffee sales. We deployed the framework of agroecological intensification in collaboration with six groups of small coffee growers in Costa Rica, Honduras, Nicaragua and Peru to assess the potential to improve the productivity of banana in mixed systems. After a formal diagnostic study of 30 smallholder coffee farms in each site carried out by scientists, farmer experimentation groups in the same sites did their own diagnostic sampling and identified priority areas for experimentation. Scientists and farmers developed prototypes for system improvement, and alternative management approaches of system components, labor and inputs. Across pilot zones, ‘Gros Michel’ was the most common cultivar, with banana mat density from 300 to 600 mats/ha with 950 to 1200 pseudostems/ha. Tree density varied from 150 to 550 trees/ha with available light ranging from 50 to 70%, and from 35 to 45% for banana and coffee. Farmer priorities across zones were similar: tree, banana and coffee resource partitioning; improved nutrition; coffee pruning; Fusarium wilt management; and marketing for better banana prices. Prototypes for testing addressed: light partitioning among trees, bananas and coffee; an input-output analysis of nutrients to increase the contribution of nitrogen from shade trees and reorient purchased nutrients; a shifting framework of Fusarium wilt management to address quarantine and cultivar substitution; and a marginal return analysis for step-wise intensification of the system, including banana.
Blazy, Jean-Marc, Ozier-Lafontaine, Harry, Doré, Thierry, Thomas, Alban, and Wery, Jacques
Agricultural systems, 2009 June, v. 101, no. 1-2, p. 30-41.
crop management systems, set of constraints, crop rotation, good agricultural practices, agroecosystems, crop management, agroecological zones, geographical variation, farming systems, innovation adoption, Musa, farm income, bananas, farms, cultivars, intercropping, pesticides, and conservation practices
Includes references Prototyping methods are useful for designing alternative crop management systems (CMS), but they are usually considered mainly at the field level and are poorly equipped to take into account farm diversity in terms of economic, social and natural constraints. This may limit the likelihood of adoption of alternative CMS. This paper proposes a two-step methodological framework that takes into account the diversity of farms in the prototyping of new CMS. The first step of the framework is to design a farm typology that is able to characterise the diversity of current CMS in terms of their technical nature, farming context, and performance. We define a farming context as a set of characteristics at the farm level that are likely to influence the structure and the biophysical and economic performances of CMS at the field level. The typology is designed from a statistical analysis of a set of descriptive variables collected for a sample of farms. The second step of the framework uses this farm typology in a specific work agenda with a panel of experts in order to design a set of alternative CMS prototypes. Prototypes, and the objectives they are meant to reach, are designed by analysing current CMS performances and by mobilising agro-ecological knowledge to identify technical ways to improve them. The typological characterisation of farm diversity then makes it possible to define a set of constraints (SOC) for each farm type. Once the prototypes are designed, the experts use a compatibility indicator (CI) ranging from zero to one to measure the level of compatibility between each prototype and the SOC of each farm type. We define a prototype as compatible with a farm type if the prototype is not likely to increase the constraints of a farm of that type (CI=1). Using this indicator in a process of iterative improvement of prototype design makes it possible to define a set of a priori compatible prototypes for each farm type. The aim of this paper is to present our methodological framework and its application for prototyping new banana crop management systems in Guadeloupe. The six-class typology we developed corresponded to a great diversity of CMS with contrasting performances and farming contexts. The method led to the prototyping of 16 innovative CMS, involving different modalities of intercropping, patterns of pesticide use, choices of hybrid cultivars, and rotations with cover or cash crops. Finally, we discuss the limits of our methodological framework and its utility for improving prototyping approaches.
Tixier, P., Malezieux, E., Dorel, M., Bockstaller, C., and Girardin, P.
European journal of agronomy, 2007 Feb., v. 26, issue 2, p. 71-81.
Rpest indicator, environmental factors, environmental impact, crop management, environmental indicators, cropping systems, simulation models, crop models, Musa, bananas, risk assessment, model validation, pesticides, leaching, and water pollution
Includes references Like many intensive monocultures, some features of banana-based cropping systems may be detrimental to the environment. Pesticide use is a major cause of surface water and groundwater pollution. The risk of water pollution due to pesticides is very high in the insular areas of the French West Indies (FWI). In order to assess these risks and help design more sustainable cropping systems, we propose using an indicator to assess the risk of pesticide pollution over time (Rpest). Rpest provides dynamic assessments through a linkage with a cropping system model that simulates environmental factors and agricultural practices. An expert validation check was conducted and demonstrated that Rpest can rank cropping systems by risk as well as experts. A sensitivity analysis highlighted that the indicator can take the properties of active ingredients and pedoclimatic data into account in assessments. Rpest helps to pinpoint high pollution risk periods. It can also be used to test alternatives and compare systems. This tool can be integrated into a model-based, global, prototyping methodology used for more sustainable cropping systems.