A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

Probability bounds analysis for Python

Probability bounds analysis (PBA) is a collection of mathematical methods generalising interval analysis and probability theory. PBA can be utilised for uncertainty quantification for both aleatory and epistemic uncertainty across a wide range of scientific fields. PBA is most useful when information about variables is only partially known and can be used without requiring untenable assumptions to be made about parameter values, distribution shapes or dependence between variables. This paper introduces a PBA library for the Python programming language

A Gateway for Technology Adoption in Agriculture: a Design-Thinking Approach for a Compliance Decision Support System

Globally, consumers are becoming more conscious of unsustainable farming practices. The appetite for safely produced, compliant and pesticide free crops is increasing. In response to these demands, the Argentinian government has issued new regulation to govern the application of <em>good agricultural practices </em>affecting production, storage and selling activities. This legislation is an opportunity to incentivise farm owners to adopt technology for recording mandatory information which has previously proven difficult. This project aims to test whether compliance software is an effective gateway for shifting farmers decision-making to technology, and from intuition-based to evidence-based, improving agricultural productivity. Understanding and integrating technology into their existing practices a substantial challenge for many farms. Consequently, the authors prototype a decision support system (DSS) for greenhouse farmers in Argentina that can track traceability of batches of crop and their treatments to reduce compliance risk. Incorporating lessons learned from previous DSS projects, the authors utilise design-thinking strategies to include end-users in the development of the system. Through such a tool, the authors can trial innovative features to test receptiveness of farm owners to utilise information technology solutions for decision-making, and identify barriers to data collection and technology adoptio

A Collaborative Decision Support System Framework for Vertical Farming Business Developments

The emerging industry of vertical farming (VF) faces three key challenges: standardisation, environmental sustainability, and profitability. High failure rates are costly and can stem from premature business decisions about location choice, pricing strategy, system design, and other critical issues. Improving knowledge transfer and developing adaptable economic analysis for VF is necessary for profitable business models to satisfy investors and policy makers. A review of current horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. Data from the literature alongside lessons learned from industry practitioners are centralised in the proposed DSS, using imprecise data techniques to accommodate for partial information. The DSS evaluates business sustainability using financial risk assessment. This is necessary for complex/new sectors such as VF with scarce data.</jats:p

Design Thinking and Compliance as Drivers for Decision Support System Adoption in Agriculture

To respond to increasing demands for good agricultural practices (GAP) and food safety, governments globally are introducing stringent regulations to govern agricultural compliance that affect production, storage, and sales activities. New legislation in Argentina to enforce GAP is an opportunity to test compliance as an incentive to adopt technological solutions. This research aims to determine whether compliance software is an effective gateway to shift farmers' decision-making strategies from intuition-based to evidence-based, improving agricultural productivity through technology. Integrating technology can be a significant hurdle for farms but is also a steppingstone towards more reliable processes. To address this, the authors prototype a decision support system (DSS) for greenhouse farmers in La Plata, Argentina, to help farmers keep traceable records of their crops and treatments to reduce compliance risk. The project incorporates lessons learned from previous DSS projects and utilises design-thinking strategies to involve the end-user in the development.</p

Design thinking and compliance as drivers for decision support system adoption in agriculture

To respond to increasing demands for good agricultural practices (GAP) and food safety, governments globally are introducing stringent regulations to govern agricultural compliance that affect production, storage, and sales activities. New legislation in Argentina to enforce GAP is an opportunity to test compliance as an incentive to adopt technological solutions. This research aims to determine whether compliance software is an effective gateway to shift farmers’ decision-making strategies from intuition-based to evidence-based, improving agricultural productivity through technology. Integrating technology can be a significant hurdle for farms but is also a steppingstone towards more reliable processes. To address this, the authors prototype a decision support system (DSS) for greenhouse farmers in La Plata, Argentina, to help farmers keep traceable records of their crops and treatments to reduce compliance risk. The project incorporates lessons learned from previous DSS projects and utilises design-thinking strategies to involve the end-user in the development

Design Thinking and Compliance as Drivers for Decision Support System Adoption in Agriculture

To respond to increasing demands for good agricultural practices (GAP) and food safety, governments globally are introducing stringent regulations to govern agricultural compliance that affect production, storage, and sales activities. New legislation in Argentina to enforce GAP is an opportunity to test compliance as an incentive to adopt technological solutions. This research aims to determine whether compliance software is an effective gateway to shift farmers' decision-making strategies from intuition-based to evidence-based, improving agricultural productivity through technology. Integrating technology can be a significant hurdle for farms but is also a steppingstone towards more reliable processes. To address this, the authors prototype a decision support system (DSS) for greenhouse farmers in La Plata, Argentina, to help farmers keep traceable records of their crops and treatments to reduce compliance risk. The project incorporates lessons learned from previous DSS projects and utilises design-thinking strategies to involve the end-user in the development.</p