Reflexive monitoring in action: setting up a monitoring system for learning effectiveness in agroecological farm innovation

Liberloo, Marion; Bijttebier, Jo; Lacour, Emilie; Stilmant, Didier; Marchand, Fleur

doi:10.1080/1389224x.2021.1984954

Cited by 3 publications

(4 citation statements)

References 33 publications

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“…Finally, a reasonable mathematical model was proposed based on mathematical modeling to estimate its emission. A powerful chicken house control software package [ 5 ] was designed to meet a variety of needs, consisting of a variety of control application modules, which can flexibly regulate the chicken house environment; a wireless sensor detection device for rabbit farm odor was developed [ 6 ], which can be used not only to monitor the breeding environment but also to analyze the health status of livestock and poultry-based on odor, health status, etc. To reduce the occurrence of diseases such as foot-and-mouth disease in rabbits, Bumanis et al [ 7 ] prevented the occurrence of diseases by installing wireless sensor networks in their poultry houses to analyze and compare the environmental parameters collected in real-time.…”

Section: Related Workmentioning

confidence: 99%

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model

Zhang

Qian

2022

Computational Intelligence and Neuroscience

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Currently, livestock and poultry farming is gradually developing towards modernization and scale, and closed livestock and poultry farms are widely used for poultry feeding management, but at the same time, the farming risks of large-scale farms are increasing. In this paper, based on the study of wireless sensor networks and biological neural network models, the environmental factors that mainly affect the growth of domestic rabbits are analyzed as an example, and the technology is used to design and implement an environmental monitoring system for modern farms. The design of the system is divided into three main parts: hardware design of each node, software design, and upper computer monitoring software design. The hardware part of the system uses coordinator nodes, router nodes, sensor nodes, and control nodes to form a wireless sensor network in the farm, carries out the hardware circuit design of each node, and based on the protocol stack, designs the software program of each node to realize the collection, transmission, and regulation of environmental information in the farm. In the upper computer part, the design and development of the upper computer monitoring software interface are used to complete the real-time display of environmental data, historical query, database storage, and curve drawing, and to design a remote client data query system based on the architecture to realize the query of environmental data of the farm by remote users and to carry out monitoring fault intelligent identification alarm. At the same time, the paper investigates the optimal deployment of wireless sensor network nodes and searches for the optimal location of sensor nodes through an improved biological neural network algorithm to maximize the network coverage and reduce the coverage of blind areas, and conducts simulation experiments with the coverage rate of a rabbit farm as the optimization target.

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Section: Related Workmentioning

confidence: 99%

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model

Zhang

Qian

2022

Computational Intelligence and Neuroscience

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“…Increasingly, governments and development agencies around the world that are adopting agroecology policies and programs need methods and tools to be able to monitor and evaluate the impact of their interventions, learn from successful or less successful examples, and inform new policies and programs (e.g. Liberloo et al, 2022;Lucantoni et al, 2022a;Tittonell, 2020). The ongoing international debate around models for sustainable agriculture intensification for food security and nutrition often demands 'proof' or 'hard evidence' on the potential of agroecologynot necessarily of other approachesto achieve such goals (e.g.…”

Section: Introductionmentioning

confidence: 99%

Lexical analysis improves the identification of contextual drivers and farm typologies in the assessment of transitions to agroecology through TAPE – A case study from rural Nicaragua

El Mujtar,

Zamor,

Salmerón

et al. 2023

Agricultural Systems

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“…Many teachers and researchers from all over the world are studying ecological education policies, such as Glackin and King [1], Payne [2], Reid [3], Rickinson and Mackenzie [4], Bylund [5], and many others. Mulder and Kupper [6] and Liberloo et al [7] considered the issues related to the ecologization of agrarian education. Grigoryeva [8], Liberloo et al [7], Koutsouris [9], Vic et al [10], Lambrechts et al [11], and MacGregor [12] have researched issues in creating a new agrarian education based on the concept of sustainable development.…”

Section: Introductionmentioning

confidence: 99%

“…Mulder and Kupper [6] and Liberloo et al [7] considered the issues related to the ecologization of agrarian education. Grigoryeva [8], Liberloo et al [7], Koutsouris [9], Vic et al [10], Lambrechts et al [11], and MacGregor [12] have researched issues in creating a new agrarian education based on the concept of sustainable development. Other issues that interfere with the development of ecological agriculture are the topics, for example, of papers by Vermunt [13] and Dorin [14].…”

Section: Introductionmentioning

confidence: 99%

The Chemical Training of Agrarian Specialists: From the Chemicalization of Agriculture to Green Technologies

et al. 2022

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The impact of agricultural production on the ecological condition of vast territories is of concern to the entire world community. Therefore, the concept of sustainable development should become the basis for the training of agricultural specialists. This article examines the transformation of the system of chemical training of agricultural students in Russia, taking into account the transition to the concept of sustainable development. The study of the history of the development of chemical training of agricultural specialists in Russia helped us to see the causes of the current crisis and highlights what should be preserved. The analysis of the modern needs of the agro-industrial complex made it possible to identify ways to modernize the system of teaching chemical disciplines in agricultural universities. As a result, the main trends of modernization of chemical training of future agricultural specialists in the context of the concept of sustainable development are identified. The chemical competencies of specialists of the agro-industrial sector working in the field of production, processing, and quality control of agricultural products are differentiated. The conditions of their formation are determined, and the effectiveness of the application of the principles of green chemistry for the formation of selected competencies is shown. The theoretical significance of the research is the development of the concept of ecological chemical education (green chemistry) for agricultural education. The practical significance of this work lies in the development of practical examples of the application of the principles of green chemistry in the educational process of an agrarian university. The originality of this research lies in determining the pedagogical conditions for the formation of chemical competencies of agricultural specialists in the context of orientation to the concept of sustainable development.

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Reflexive monitoring in action: setting up a monitoring system for learning effectiveness in agroecological farm innovation

Cited by 3 publications

References 33 publications

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model

Network Architecture for Intelligent Identification of Faults in Rabbit Farm Environment Monitoring Based on a Biological Neural Network Model

Lexical analysis improves the identification of contextual drivers and farm typologies in the assessment of transitions to agroecology through TAPE – A case study from rural Nicaragua

The Chemical Training of Agrarian Specialists: From the Chemicalization of Agriculture to Green Technologies

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