This chapter focuses on the data needed for developing, testing, and applying crop and farm models. The chapter reviews the kinds of data available to crop and farm modellers. The chapter describes practices concerning storage, exchanging, and combining data from various sources, examining the socio-economic and ethical implications. The chapter looks at the role of companies in data flows and generating recommendations to farmers. The chapter presents examples of successful use of agricultural data, both for science and for agricultural practice. Finally, the chapter looks ahead to future research trends in this area
The authors present an overview of agricultural systems models. Beginning with why systems are mode...
In agricultural research targeted at food security, crop experiments in fields are a crucial source ...
This paper presents ideas for a new generation of agricultural system models that could meet the nee...
Agricultural modeling has long suffered from fragmentation in model implementation. Many models are ...
We review the current state of agricultural systems science, focusing in particular on the capabilit...
FarmDESIGN Model with the case study farms and their data for the paper "A model to examine farm hou...
Data from agronomy experiments are typically collected and stored in a number of mini-mally document...
This book addresses methodological issues of production ecology. A central issue is the combination ...
Crop modelling has the potential to contribute to global food and nutrition security. This paper bri...
Crop modelling has the potential to contribute to global food and nutrition security. This paper bri...
Information and Communication Technologies (ICT) are being used across the world to generate efficie...
The biomedical domain has shown that in silico analyses over vast data pools enhances the speed and ...
This paper presents ideas for a new generation of agricultural system models that could meet the nee...
The development of digital agriculture or smart farming highlights the importance of data and data e...
The agricultural machinery produces an increasing number of measurements during operations. The prim...
The authors present an overview of agricultural systems models. Beginning with why systems are mode...
In agricultural research targeted at food security, crop experiments in fields are a crucial source ...
This paper presents ideas for a new generation of agricultural system models that could meet the nee...
Agricultural modeling has long suffered from fragmentation in model implementation. Many models are ...
We review the current state of agricultural systems science, focusing in particular on the capabilit...
FarmDESIGN Model with the case study farms and their data for the paper "A model to examine farm hou...
Data from agronomy experiments are typically collected and stored in a number of mini-mally document...
This book addresses methodological issues of production ecology. A central issue is the combination ...
Crop modelling has the potential to contribute to global food and nutrition security. This paper bri...
Crop modelling has the potential to contribute to global food and nutrition security. This paper bri...
Information and Communication Technologies (ICT) are being used across the world to generate efficie...
The biomedical domain has shown that in silico analyses over vast data pools enhances the speed and ...
This paper presents ideas for a new generation of agricultural system models that could meet the nee...
The development of digital agriculture or smart farming highlights the importance of data and data e...
The agricultural machinery produces an increasing number of measurements during operations. The prim...
The authors present an overview of agricultural systems models. Beginning with why systems are mode...
In agricultural research targeted at food security, crop experiments in fields are a crucial source ...
This paper presents ideas for a new generation of agricultural system models that could meet the nee...