The study of crop phenotypic response to different environmental stress represents a crucial challenge for predicting the impact of climate change on current agriculture. In this context, current researches are focusing on the development of phenotyping platform for monitoring crop behavior under stress conditions. However, the high cost and power consumption of these technologies limits the use of this system in many contexts. Thus, this work aims to show a first step implementation of a simplified and low-cost phenotyping platform for crop monitoring.

A simplified approach of Phenotyping Platform for crop monitoring / Claudio Leolini, Luisa Leolini, Sergi Costafreda-Aumedes, Lorenzo Brilli, Marco Bindi, Giovanni Argenti, Marco Moriondo. - ELETTRONICO. - (2018), pp. 31-32. (Intervento presentato al convegno L'agronomia nelle nuove Agriculturae, biologica, conservativa, digitale e di precisione).

A simplified approach of Phenotyping Platform for crop monitoring

Luisa Leolini;Sergi Costafreda-Aumedes;Lorenzo Brilli;Marco Bindi;Giovanni Argenti;Marco Moriondo
2018

Abstract

The study of crop phenotypic response to different environmental stress represents a crucial challenge for predicting the impact of climate change on current agriculture. In this context, current researches are focusing on the development of phenotyping platform for monitoring crop behavior under stress conditions. However, the high cost and power consumption of these technologies limits the use of this system in many contexts. Thus, this work aims to show a first step implementation of a simplified and low-cost phenotyping platform for crop monitoring.
2018
Proceedings of the XLVII Conference of the Italian Society for Agronomy
L'agronomia nelle nuove Agriculturae, biologica, conservativa, digitale e di precisione
Claudio Leolini, Luisa Leolini, Sergi Costafreda-Aumedes, Lorenzo Brilli, Marco Bindi, Giovanni Argenti, Marco Moriondo
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1135573
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