Agriculture, and so the cultivation of wheat as well, is increasingly affected by the effects of climate change, with repercussions on vegetative growth, phenology, as well as yields. This is worsen by a greater uncertainty related to the variability of the climate, which is complicating the decisions to be taken by sector operators (Iizumi et al. 2018). In this context, farmers are experiencing increasing difficulties to comply on the one hand with the qualitative and quantitative standards, as required by the agro-food chain, or by the industrial sector, and on the other to preserve the environment and, last but not least, their own revenue. In recent years, thanks to the development of new technologies, the proliferation of internet-related services, the increased and greater availability of computational capacity, as well as the spread of smartphones and tablets, decision support systems are spreading in agriculture. However, if on the one hand they are often having high complexity and reliability, such systems require large amounts of information, being highly time and energy consuming for the farmer, who often does not complete the process. For these reasons we have created an extremely simple system, which requires very little, known information from the farmer, but is able to provide useful, reliable and effective information for the user. The system integrates a mechanistic crop growth simulation model (SSM-Wheat, Soltani et al. 2013), weather generators (LARS-WG, Semenov & Barrow 1997), algorithms for NDVI calculation and nitrogen withdrawal.

A simple yet reliable system to support fertilisation decision making at farm level / Ferrise, R.; Trombi, G.; Costafreda Aumedes, S.; Padovan, G.; Pasqui, M.; Di Giuseppe, E.; Moretto J.; Morari, F.. - STAMPA. - (2020), pp. 404-405. (Intervento presentato al convegno Crop modelling for Agriculture and Food Security under Global Change tenutosi a Le Corum, Montpellier, France nel February 3-5, 2020).

A simple yet reliable system to support fertilisation decision making at farm level

Ferrise, R.;Trombi, G.;Costafreda Aumedes, S.;Padovan, G.;
2020

Abstract

Agriculture, and so the cultivation of wheat as well, is increasingly affected by the effects of climate change, with repercussions on vegetative growth, phenology, as well as yields. This is worsen by a greater uncertainty related to the variability of the climate, which is complicating the decisions to be taken by sector operators (Iizumi et al. 2018). In this context, farmers are experiencing increasing difficulties to comply on the one hand with the qualitative and quantitative standards, as required by the agro-food chain, or by the industrial sector, and on the other to preserve the environment and, last but not least, their own revenue. In recent years, thanks to the development of new technologies, the proliferation of internet-related services, the increased and greater availability of computational capacity, as well as the spread of smartphones and tablets, decision support systems are spreading in agriculture. However, if on the one hand they are often having high complexity and reliability, such systems require large amounts of information, being highly time and energy consuming for the farmer, who often does not complete the process. For these reasons we have created an extremely simple system, which requires very little, known information from the farmer, but is able to provide useful, reliable and effective information for the user. The system integrates a mechanistic crop growth simulation model (SSM-Wheat, Soltani et al. 2013), weather generators (LARS-WG, Semenov & Barrow 1997), algorithms for NDVI calculation and nitrogen withdrawal.
2020
Book of Abstracts Second International Crop Modelling Symposium
Crop modelling for Agriculture and Food Security under Global Change
Le Corum, Montpellier, France
February 3-5, 2020
Ferrise, R.; Trombi, G.; Costafreda Aumedes, S.; Padovan, G.; Pasqui, M.; Di Giuseppe, E.; Moretto J.; Morari, F.
File in questo prodotto:
File Dimensione Formato  
Ferriseetal2020iCROPM2020-Book-of-Abstracts-404-405.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: DRM non definito
Dimensione 432.7 kB
Formato Adobe PDF
432.7 kB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1249183
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact