Burbano-Figueroa, Oscar: Yield, productivity and technical gaps that limit the cotton agricultural production system in the Colombian Caribbean. - Bonn, 2022. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5-65832
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5-65832,
author = {{Oscar Burbano-Figueroa}},
title = {Yield, productivity and technical gaps that limit the cotton agricultural production system in the Colombian Caribbean},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2022,
month = mar,

note = {This thesis contributes to understanding factors related to production situations in agricultural systems of the Colombian Caribbean using decision analysis. Decision analysis has numerous advantages when it is used for this purpose. It is a multidisciplinary framework which helps decision-makers or stakeholders evaluate competing alternative actions or interventions in order to choose the preferable option. Decision analysis is a bottom-up approach that collects knowledge developed by stakeholders (including farmers) and combines it with available field data and disciplinary expertise. This approach allows the inclusion of all variables that are essential for the contextual description of the problem, even if these variables are difficult to measure. Risks and uncertainties are also included in decision analysis reflecting better the reality of agricultural production situations. As a final remark, decision analysis is focused on active assessment of alternatives for improving system performance with the explicit intention to take action and assess consequences and not just studying how a system works.
The first part of this study describes the application of conceptual modeling on the understanding of the management of the cotton boll weevil (Anthonomus grandis grandis). To date, information on boll weevil (BW) management strategies in Colombia is only available in the forms of gray literature (technical reports) and informal knowledge held by crop advisors and farmers. The conceptual model developed in this study collected that information and integrated the informal local knowledge of crop advisors and farmers with disciplinary knowledge describing management strategies.
The second part of this study deepens in the understanding of the boll weevil management and applies decision analysis to assess pesticide-based strategies used at farm scale. Proactive and reactive management at farm-scale were represented as probabilistic production functions using budget partial analysis. This decision model layout was able to capture key properties of control strategies, while accounting for uncertainty about pest infestation pressure, control effectiveness and cotton yield and price. Simulation outcomes indicate that a proactive management for the BW is more efficient than a reactive approach given the current weevil infestation levels.
The fourth part of this study focuses on the assessment of economic prospects of irrigated horticultural systems. These production systems are an alternative to cotton crops for smallholders. Understanding these diversified systems require quantification of productivity and related risks for individual crops as well as an assessment of the benefits from diversification. A whole-farm decision analysis of this kind is an extension of Modern Portfolio Theory (MPT) that allows us to link the concepts of risks and returns for a multi-asset scenario (several crops or farm enterprises). Understanding this relationship is essential for identifying diversification strategies that farmers can validate and adjust to technical or economical limitations or individual preferences.
This study’s results show the versatility of decision analysis for its application to different typologies of decision-making problems in agriculture. It provides a conceptual modeling approach that incorporates planning horizons for the decision making problems. Conceptual models outlining strategic decision-making scenarios facilitates the process of quantitative modeling because it helps to define the decision making-problem to model while offering a model reference framework. This thesis provides layouts for two of those strategic-making scenarios that are not commonly represented in the literature of applications for decision analysis but are very common in agricultural settings: production under risk and whole-farm planning and operation. Production under risk was used for modeling pest management as a special production function describing losses. This framework has the potential to provide a unified protocol for assessing benefits in pest management, specially in those cases of integrated pest management. Whole farm-planning and operation was conceived as an extension of the Modern Portfolio Theory. This thesis provides a complete protocol of decision analysis describing its application in diversified systems.},

url = {https://hdl.handle.net/20.500.11811/9709}

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