Instant Insights: Decision Support Systems in Agriculture
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Instant Insights: Decision Support Systems in Agriculture
Koerner, Dr Oliver; Krishnaveni, Dr D.; Subrahmanyam, Dr D.; Padmavathi, Dr Ch.; Prasad, Dr M. S.; Katti, Dr G.; Sailaja, Dr B.; Gayatri, Dr S.; Voleti, Dr S. R.; Aitkenhead, Dr Matt
Burleigh Dodds Science Publishing Limited
09/2021
148
Mole
Inglês
9781801462112
15 a 20 dias
Descrição não disponível.
Chapter 1 - Developing decision support systems (DSS) for farm soil and crop management: Matt Aitkenhead, The James Hutton Institute, UK; 1 Introduction2 Spatial data and sensor requirements for DSS3 Models and software for DSS4 DSS user interface design, actuators and systems5 Decision support or decision-making?6 What reasons are there for low uptake of DSS?7 What will DSSs of the future look like?8 Summary9 Where to look for further information10 References
Chapter 2 - Decision-support systems for pest monitoring and management: B. Sailaja, Ch. Padmavathi, D. Krishnaveni, G. Katti, D. Subrahmanyam, M. S. Prasad, S. Gayatri and S. R. Voleti, ICAR-Indian Institute of Rice Research, India; 1 Introduction2 Pest identification3 Pest monitoring4 Pest forecasting5 Integrated pest management (IPM)6 Case studies7 Summary and future trends8 Where to look for further information9 References
Chapter 3 - Models, sensors and decision support systems in greenhouse cultivation: Oliver Koerner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; 1 Introduction2 Greenhouses as controllable units for decision making3 The decision-making process4 Growers' decision tools5 Models for decision support6 Case studies7 Future trends and conclusion8 Where to look for further information9 References
Chapter 4 - Modelling and decision support systems in precision agriculture: Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; 1 Introduction2 Key issues3 Human and social aspects4 Case studies with an emphasis on nitrogen management5 Research options for decision support systems to improve productivity in a precision agriculture framework6 Conclusion7 Future trends8 Where to look for further information9 References
Chapter 5 - Developing climate-based decision support systems from agricultural systems models: Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Senora de la Asuncion, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA; 1 Introduction2 Importance of a participatory approach in DSS development3 Examples of climate-based DSSs for crop and land management4 Examples of climate-based DSSs for pest and disease management5 Examples of climate-based DSSs for livestock (dairy) management6 Lessons learned on the development of climate-based DSSs7 Future trends and conclusion8 Where to look for further information9 References
Chapter 2 - Decision-support systems for pest monitoring and management: B. Sailaja, Ch. Padmavathi, D. Krishnaveni, G. Katti, D. Subrahmanyam, M. S. Prasad, S. Gayatri and S. R. Voleti, ICAR-Indian Institute of Rice Research, India; 1 Introduction2 Pest identification3 Pest monitoring4 Pest forecasting5 Integrated pest management (IPM)6 Case studies7 Summary and future trends8 Where to look for further information9 References
Chapter 3 - Models, sensors and decision support systems in greenhouse cultivation: Oliver Koerner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; 1 Introduction2 Greenhouses as controllable units for decision making3 The decision-making process4 Growers' decision tools5 Models for decision support6 Case studies7 Future trends and conclusion8 Where to look for further information9 References
Chapter 4 - Modelling and decision support systems in precision agriculture: Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; 1 Introduction2 Key issues3 Human and social aspects4 Case studies with an emphasis on nitrogen management5 Research options for decision support systems to improve productivity in a precision agriculture framework6 Conclusion7 Future trends8 Where to look for further information9 References
Chapter 5 - Developing climate-based decision support systems from agricultural systems models: Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Senora de la Asuncion, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA; 1 Introduction2 Importance of a participatory approach in DSS development3 Examples of climate-based DSSs for crop and land management4 Examples of climate-based DSSs for pest and disease management5 Examples of climate-based DSSs for livestock (dairy) management6 Lessons learned on the development of climate-based DSSs7 Future trends and conclusion8 Where to look for further information9 References
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precision agriculture;site-specific nutrient management;integrated soil fertility management;digital soil mapping;unmanned aerial vehicles (UAVs);expert systems;image-based diagnostics;crop pest DSS;forecasting models;Artificial Intelligence (AI);integrated pest management (IPM);climate control;crop quality;deterministic model;disease management;microclimate;plant stress detection;warning systems;Agricultural models;Nitrogen management;Climate forecasts;Participatory approach;Livestock management
Chapter 1 - Developing decision support systems (DSS) for farm soil and crop management: Matt Aitkenhead, The James Hutton Institute, UK; 1 Introduction2 Spatial data and sensor requirements for DSS3 Models and software for DSS4 DSS user interface design, actuators and systems5 Decision support or decision-making?6 What reasons are there for low uptake of DSS?7 What will DSSs of the future look like?8 Summary9 Where to look for further information10 References
Chapter 2 - Decision-support systems for pest monitoring and management: B. Sailaja, Ch. Padmavathi, D. Krishnaveni, G. Katti, D. Subrahmanyam, M. S. Prasad, S. Gayatri and S. R. Voleti, ICAR-Indian Institute of Rice Research, India; 1 Introduction2 Pest identification3 Pest monitoring4 Pest forecasting5 Integrated pest management (IPM)6 Case studies7 Summary and future trends8 Where to look for further information9 References
Chapter 3 - Models, sensors and decision support systems in greenhouse cultivation: Oliver Koerner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; 1 Introduction2 Greenhouses as controllable units for decision making3 The decision-making process4 Growers' decision tools5 Models for decision support6 Case studies7 Future trends and conclusion8 Where to look for further information9 References
Chapter 4 - Modelling and decision support systems in precision agriculture: Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; 1 Introduction2 Key issues3 Human and social aspects4 Case studies with an emphasis on nitrogen management5 Research options for decision support systems to improve productivity in a precision agriculture framework6 Conclusion7 Future trends8 Where to look for further information9 References
Chapter 5 - Developing climate-based decision support systems from agricultural systems models: Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Senora de la Asuncion, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA; 1 Introduction2 Importance of a participatory approach in DSS development3 Examples of climate-based DSSs for crop and land management4 Examples of climate-based DSSs for pest and disease management5 Examples of climate-based DSSs for livestock (dairy) management6 Lessons learned on the development of climate-based DSSs7 Future trends and conclusion8 Where to look for further information9 References
Chapter 2 - Decision-support systems for pest monitoring and management: B. Sailaja, Ch. Padmavathi, D. Krishnaveni, G. Katti, D. Subrahmanyam, M. S. Prasad, S. Gayatri and S. R. Voleti, ICAR-Indian Institute of Rice Research, India; 1 Introduction2 Pest identification3 Pest monitoring4 Pest forecasting5 Integrated pest management (IPM)6 Case studies7 Summary and future trends8 Where to look for further information9 References
Chapter 3 - Models, sensors and decision support systems in greenhouse cultivation: Oliver Koerner, Leibniz Institute of Vegetable and Ornamental Crops (IGZ), Germany; 1 Introduction2 Greenhouses as controllable units for decision making3 The decision-making process4 Growers' decision tools5 Models for decision support6 Case studies7 Future trends and conclusion8 Where to look for further information9 References
Chapter 4 - Modelling and decision support systems in precision agriculture: Nicolas Tremblay, Agriculture and Agri-Food Canada, Canada; 1 Introduction2 Key issues3 Human and social aspects4 Case studies with an emphasis on nitrogen management5 Research options for decision support systems to improve productivity in a precision agriculture framework6 Conclusion7 Future trends8 Where to look for further information9 References
Chapter 5 - Developing climate-based decision support systems from agricultural systems models: Clyde W. Fraisse, University of Florida-Gainesville, USA; Norman E. Breuer, Catholic University Nuestra Senora de la Asuncion, Paraguay; and Victor Cabrera, University of Wisconsin-Madison, USA; 1 Introduction2 Importance of a participatory approach in DSS development3 Examples of climate-based DSSs for crop and land management4 Examples of climate-based DSSs for pest and disease management5 Examples of climate-based DSSs for livestock (dairy) management6 Lessons learned on the development of climate-based DSSs7 Future trends and conclusion8 Where to look for further information9 References
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
precision agriculture;site-specific nutrient management;integrated soil fertility management;digital soil mapping;unmanned aerial vehicles (UAVs);expert systems;image-based diagnostics;crop pest DSS;forecasting models;Artificial Intelligence (AI);integrated pest management (IPM);climate control;crop quality;deterministic model;disease management;microclimate;plant stress detection;warning systems;Agricultural models;Nitrogen management;Climate forecasts;Participatory approach;Livestock management
