# NINSAR Project: Defining Agroecological Routes Using Robots

Mohammad Naim, Davide Rizzo, Maryem Cherni, Marco Medici, Loïc Sauvée

► To cite this version:

Mohammad Naim, Davide Rizzo, Maryem Cherni, Marco Medici, Loïc Sauvée. NINSAR Project: Defining Agroecological Routes Using Robots. 2025, 10.5281/zenodo.17700793. [https://hal.science/hal-05380224v1](https://hal.science/hal-05380224v1)

HAL Id: hal-05380224

https://hal.science/hal-05380224v1

Submitted on 24 Nov 2025

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# NINSAR Project: Defining Agroecological Routes Using Robots

UniLaSalle
Institut Polytechnique

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Mohammad Naim* directed by Marco Medici & Loïc Sauvée

with the appreciated contribution of Davide Rizzo (2,4) & Maryem Cherni (3)

Research unit InTerACT (UP2018.CP102), UniLaSalle, Beauvais

InTerACT
UP 2018.C102 UniLaSalle

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## Introduction

There is an ongoing transition toward a new **human-centric** agricultural system centered on **Agroecology (AE)** as a foundation for **sustainable food production**. Autonomous machinery, and particularly robots, offer promising solutions, but they must advance in precision, adaptability, and productivity, since challenges aren't only in the technical capabilities of agricultural robots and automation but also in their **integration with agroecological principles, farmers' acceptance of these technologies, and their presentation in the market**.

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Under review!

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Ongoing!

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## Research questions

1. To what extent the modern agricultural revolution animates AE principles?

2. How can robots be integrated into agricultural operations/practices without compromising AE principles?

3. What factors influence the acceptance and adoption of agricultural robots by French Farmers?

4. What sustainable business models can be developed to support the implementation and scaling of agricultural robots?

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* A study that analyzes three key types of robotic operations in agriculture: **data collection, crop and soil management, and navigation and communication**.

* These operations are evaluated through four field agroecological principles: **biodiversity, synergy, recycling, and soil health**.

* Results demonstrate that **soil health and synergy** are the most animated principles in current robotic applications, while **recycling** is the least represented.

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* A study that **clusters 71 agricultural robots** based on variables including dimensions, energy source, price, and agricultural operations.

* **Five distinct categories** are identified: **Multifunctional, Heavy-Duty Tillers, Weeding & Monitoring, Field Weeders, and Large-Scale Harvesters**.

* Findings highlight the **specialization of robots** designed to address specific agricultural needs.

* It was shown that **robots with endothermic engines** are generally more expensive than **electric robots**.

* A review that examines the shift from **Agriculture 4.0** to **Agriculture 5.0**.

* It assesses this transition through the **13 agroecological principles defined by the HLPE (2019)**: recycling, input reduction, soil health, animal health, biodiversity, synergy, economic diversification, co-creation of knowledge, social values and diets, fairness, connectivity, land and natural resource governance, and participation.

* The study explores how technological innovation, automation, and data-driven systems can align with agroecological principles to enhance sustainability and resilience.

* Findings highlight the potential of **Agriculture 5.0** to promote a more equitable, human-centric, and ecologically balanced agricultural model.

* **Technology Acceptance Model 2 (TAM2)**, an extension of the Theory of Reasoned Action, was selected and adapted to investigate farmers' adoption of robotic technologies, focusing on factors such as perceived usefulness and ease of use.

* Findings revealed that French farmers' intention to adopt robots was strongly driven by **Perceived Usefulness**, with ease of use providing additional support.

* **Social influence**, particularly through **Subjective Norm** shaping Image, played a secondary but meaningful role, while **Job Relevance, Output Quality, and Result Demonstrability** significantly impacted Perceived Usefulness, highlighting the importance of demonstrating clear, tangible benefits.

* These results validated TAM2 in the context of agricultural robotics and suggested that adoption strategies should focus on communicating concrete performance gains, improving usability, and leveraging peer networks to foster positive perceptions.

* Considering factors and drivers identified in the previous tasks, research will involve **semi-structured interviews** with **agricultural robots' manufacturers** to gather detailed information on their value capture and creation.

* The interviews will be used to populate a **Business Model Canvas**, following **Osterwalder's 9-block framework**.

* The study will adopt **Eisenhardt's methodology** combined with **cross-case analysis** to systematically compare manufacturers.

* The resulting **Business Model Canvas** will cover all nine blocks: **Customer Segments, Value Propositions, Channels, Customer Relationships, Revenue Streams, Key Resources, Key Activities, Key Partnerships, and Cost Structure**.

## Funders & collaborators

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utc

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